{"meta":{"query_hash":"481f82bad2ca","filters":{"topic":"Advanced Neuroimaging Techniques and Applications"},"cohort_total":2751,"direct_labels_cover":6,"predictions_cover":2751,"exported":2751,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/481f82bad2ca","api":"https://metacan.xera.ac/api/v1/cohort?topic=Advanced+Neuroimaging+Techniques+and+Applications"},"results":[{"id":"W108913140","doi":"10.1016/s0079-6123(01)34025-6","title":"Chapter 24 Visual pathways following cerebral hemispherectomy","year":2001,"lang":"en","type":"review","venue":"Progress in brain research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"China Scholarship Council","keywords":"Superior colliculus; Pretectal area; Superior Colliculi; Midbrain; Hemispherectomy; Neuroscience; Visual system; Commissure; Anatomy; Psychology; Cerebral cortex; Retina; Biology; Central nervous system; Epilepsy","score_opus":0.3964250188350444,"score_gpt":0.5568198452668143,"score_spread":0.1603948264317699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W108913140","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008989734,0.9899855,0.00009641775,0.000901784,0.00007144697,0.0030281132,0.0000115145895,0.00029884663,0.005516432],"genre_scores_gemma":[0.00027160766,0.98871785,0.0057756724,0.00008840275,0.0003099453,0.0026672983,0.00010899528,0.00018400956,0.0018761953],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962572,0.00024518964,0.000648127,0.0009704481,0.0008979188,0.0009811067],"domain_scores_gemma":[0.9980478,0.00061660697,0.00012492172,0.00083590124,0.00012228526,0.00025244924],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0013164653,0.00041627127,0.0013072634,0.0005886147,0.00017329043,0.00007960937,0.00051561213,0.00033507004,0.00018457191],"category_scores_gemma":[0.00032271442,0.00034819293,0.00048234453,0.0014874128,0.00031575203,0.00008270156,0.00047662435,0.0024068349,0.000109461216],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000124150065,0.00022048037,0.00076922553,0.003950281,0.000035736917,0.0005642045,0.00002240253,1.6476877e-8,0.000001521521,0.0013519201,0.0010593729,0.99201244],"study_design_scores_gemma":[0.00037646812,0.00014492628,0.000028331971,0.013005998,0.000052229978,0.00017723574,0.000014539715,0.000037236518,0.000012436407,0.00077819696,0.98508584,0.00028654392],"about_ca_topic_score_codex":0.000008109491,"about_ca_topic_score_gemma":0.0000023257433,"teacher_disagreement_score":0.99172586,"about_ca_system_score_codex":0.0002796566,"about_ca_system_score_gemma":0.00028761104,"threshold_uncertainty_score":0.999897},"labels":[],"label_agreement":null},{"id":"W1143664502","doi":"10.1016/j.bbr.2015.08.028","title":"Neuromarkers of the common angiotensinogen polymorphism in healthy older adults: A comprehensive assessment of white matter integrity and cognition","year":2015,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Allergy and Infectious Diseases; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health; National Center for Advancing Translational Sciences; DNA Genotek","keywords":"White matter; Cingulum (brain); Cognition; Uncinate fasciculus; Psychology; Superior longitudinal fasciculus; Diffusion MRI; Fractional anisotropy; Hyperintensity; Internal medicine; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.2334855925832703,"score_gpt":0.4665982097030035,"score_spread":0.23311261711973316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1143664502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96998805,0.00008841306,0.000058321264,0.028556302,0.0000152094635,0.0010408261,0.000036289162,0.000014590305,0.00020199828],"genre_scores_gemma":[0.9968252,0.00001734227,0.002149105,0.0008671243,0.000008181063,0.00004921785,0.000022282553,0.0000143266325,0.000047186535],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998604,0.00028474233,0.00027303633,0.0002136116,0.00041740164,0.00020723473],"domain_scores_gemma":[0.9988812,0.00018406204,0.000085456275,0.00033727507,0.00040399053,0.000107969805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004092481,0.00008503188,0.00021711543,0.00016044876,0.0000660813,0.0000054846496,0.000113894894,0.00005703512,0.000012441233],"category_scores_gemma":[0.00007095849,0.00006311028,0.00004526525,0.0003825895,0.00035751105,0.00004604006,0.00023409918,0.00066493737,7.105303e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028811465,0.00024093327,0.9886788,0.00006445426,0.0000041512744,0.000011642225,0.00029936928,4.080582e-7,0.005636952,0.00008916405,0.0036129318,0.0010730949],"study_design_scores_gemma":[0.0012620839,0.00031883866,0.9960882,0.0002900947,0.000012156175,0.000059176495,0.0004424144,0.00024942527,0.0009351519,0.00021525336,0.00007822491,0.000049000257],"about_ca_topic_score_codex":0.0010208995,"about_ca_topic_score_gemma":0.000041484738,"teacher_disagreement_score":0.027689178,"about_ca_system_score_codex":0.000062925414,"about_ca_system_score_gemma":0.00011922739,"threshold_uncertainty_score":0.2888859},"labels":[],"label_agreement":null},{"id":"W1161154887","doi":"10.1089/neu.2013.2866","title":"To Exclude or Not To Exclude: Further Examination of the Influence of White Matter Hyperintensities in Diffusion Tensor Imaging Research","year":2013,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Hyperintensity; Magnetic resonance imaging; Medicine; Psychology; Nuclear medicine; Radiology","score_opus":0.16270061074861494,"score_gpt":0.41914143939694887,"score_spread":0.25644082864833395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1161154887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97806585,0.0000057134243,0.00026015972,0.020853683,0.000028858327,0.0006159918,0.000002474176,0.000007929298,0.00015936414],"genre_scores_gemma":[0.9943581,0.000018178329,0.0028195798,0.0023123275,0.00004282641,0.000025415133,1.2225318e-7,0.000022355924,0.00040106775],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99859124,0.00009679793,0.0005113819,0.00014475301,0.000472882,0.00018292718],"domain_scores_gemma":[0.9983759,0.00014247223,0.00020324251,0.0003493101,0.0008394401,0.0000896286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036460158,0.000094807656,0.0002464456,0.00038608024,0.00005122158,0.000012495469,0.0002547514,0.000024449118,0.00006104993],"category_scores_gemma":[0.00036759002,0.00005898625,0.00006250359,0.00050381507,0.000097130716,0.00015073312,0.00018588887,0.00036365777,0.000009160547],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025843628,0.00017122288,0.10358873,0.00007564258,0.0000039515244,0.000024740746,0.0026816153,0.00041092356,0.8863397,0.000015774189,0.0012266871,0.005202561],"study_design_scores_gemma":[0.0003083835,0.00025996668,0.9692922,0.00046019023,0.000007593256,0.00021882243,0.00052475295,0.00011768572,0.028119536,0.00007649795,0.00056285807,0.00005147258],"about_ca_topic_score_codex":0.00003596971,"about_ca_topic_score_gemma":0.0000033638842,"teacher_disagreement_score":0.8657035,"about_ca_system_score_codex":0.000045281704,"about_ca_system_score_gemma":0.000034003348,"threshold_uncertainty_score":0.24053894},"labels":[],"label_agreement":null},{"id":"W12021418","doi":"10.1186/1532-429x-17-s1-p383","title":"In vivo free-breathing DTI &amp; IVIM of the whole human heart using a real-time slice-followed SE-EPI navigator-based sequence: a reproducibility study in healthy volunteers","year":2015,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Reproducibility; Medicine; Intravoxel incoherent motion; Angiology; In vivo; Breathing; Sequence (biology); Biomedical engineering; Nuclear medicine; Cardiology; Diffusion MRI; Anesthesia; Magnetic resonance imaging; Radiology; Biology; Chromatography","score_opus":0.11894399807139165,"score_gpt":0.3863276348346188,"score_spread":0.26738363676322713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W12021418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9880535,0.0087769795,0.00024210538,0.0014481393,0.00007704264,0.0012693189,0.00001013543,0.000025449035,0.00009731205],"genre_scores_gemma":[0.982853,0.00014878342,0.016421683,0.0002534548,0.00013185042,0.000036811016,7.688749e-7,0.000044271437,0.00010939727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99623936,0.0006025298,0.0011003773,0.00064798334,0.0010862421,0.00032350814],"domain_scores_gemma":[0.99605054,0.000072643226,0.00034044846,0.0029298658,0.00043626412,0.000170257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005604062,0.00022157392,0.0010216536,0.00020406106,0.00007760451,0.000017796336,0.00043397176,0.00008346176,0.000008349039],"category_scores_gemma":[0.0010831454,0.00017712741,0.0006205402,0.0009506054,0.0001845881,0.00015522377,0.00012397986,0.0006611227,0.0000010393795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034302452,0.005658128,0.64593655,0.0008683849,0.00046773988,0.0017494054,0.008731023,0.026208848,0.28917164,0.0000596652,0.0058112782,0.011907084],"study_design_scores_gemma":[0.036419827,0.006710333,0.6500617,0.0057474775,0.0016974403,0.0038186177,0.0016058871,0.007389508,0.012410881,0.0027053843,0.2701004,0.0013324873],"about_ca_topic_score_codex":0.0021445972,"about_ca_topic_score_gemma":0.00006111525,"teacher_disagreement_score":0.27676076,"about_ca_system_score_codex":0.0004460401,"about_ca_system_score_gemma":0.00056119286,"threshold_uncertainty_score":0.7223046},"labels":[],"label_agreement":null},{"id":"W123779339","doi":"10.1139/jpn.0842","title":"Microstructural thalamic changes in schizophrenia: a combined anatomic and diffusion weighted magnetic resonance imaging study","year":2008,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Thalamus; Magnetic resonance imaging; Schizophrenia (object-oriented programming); Diffusion MRI; Functional magnetic resonance imaging; Diffusion-Weighted Magnetic Resonance Imaging; Neuroscience; Medicine; Pathophysiology; Nuclear magnetic resonance; Psychology; Radiology; Psychiatry; Pathology; Physics","score_opus":0.020601816042030686,"score_gpt":0.29871461153270473,"score_spread":0.278112795490674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W123779339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99339265,0.0024807176,0.00005417819,0.0036253678,0.0001826093,0.00023573461,0.0000018887567,0.00001707047,0.000009777249],"genre_scores_gemma":[0.9944296,0.001507367,0.0033979858,0.000583131,0.00004581527,0.0000031890092,1.5107912e-7,0.00000859576,0.000024190591],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991853,0.00003294572,0.00024568703,0.00022873195,0.00015841374,0.00014890634],"domain_scores_gemma":[0.99956584,0.000022630267,0.00014437154,0.0001357461,0.00004289575,0.000088511224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010599921,0.000109351015,0.0002033477,0.00019286582,0.000164578,0.000016812079,0.000105758256,0.000017377548,0.0000016669763],"category_scores_gemma":[0.000029187488,0.00008513444,0.000020999747,0.0003868009,0.0002242008,0.00012686235,0.000058501973,0.00028431928,1.0073172e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002836143,0.00022520855,0.91782236,0.000011990013,3.9612002e-7,0.00013186784,0.00012503377,2.1819217e-7,0.07721486,0.00009355778,0.000056596353,0.004034289],"study_design_scores_gemma":[0.0024050374,0.00084419595,0.9900448,0.000085901374,0.000014250061,0.0041910186,0.0000769705,0.0007852911,0.00052814576,0.0007765563,0.000168676,0.00007918039],"about_ca_topic_score_codex":0.00000506988,"about_ca_topic_score_gemma":0.000009275671,"teacher_disagreement_score":0.07668672,"about_ca_system_score_codex":0.000010764666,"about_ca_system_score_gemma":0.00005561019,"threshold_uncertainty_score":0.34716818},"labels":[],"label_agreement":null},{"id":"W125137646","doi":"10.1007/978-3-642-23629-7_20","title":"Apparent Intravoxel Fibre Population Dispersion (FPD) Using Spherical Harmonics","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Population; Computer science; Autocorrelation; Spherical harmonics; Voxel; Orientation (vector space); Dispersion (optics); Anisotropy; Diffusion MRI; Kurtosis; Diffusion; Quaternion; SIGNAL (programming language); Artificial intelligence; Acoustics; Algorithm; Mathematics; Optics; Physics; Statistics; Geometry; Mathematical analysis","score_opus":0.09551955099753882,"score_gpt":0.34454474679262476,"score_spread":0.24902519579508592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W125137646","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25860775,0.000026643294,0.74077505,0.00025441297,0.000083826744,0.00016173287,4.9496805e-7,0.00007589989,0.00001415773],"genre_scores_gemma":[0.5648142,0.0000045896372,0.4348037,0.00032469153,0.000043380816,0.0000024028175,0.000001755407,0.000005020074,2.6934904e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904937,0.000010384991,0.00015419185,0.0003685181,0.00020115903,0.00021639609],"domain_scores_gemma":[0.999472,0.000028833087,0.000050375478,0.0003215524,0.000047500205,0.00007974575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100763,0.00010051133,0.00012417509,0.00008223214,0.00011244082,0.000021562879,0.00018903612,0.000038613674,0.000012757351],"category_scores_gemma":[0.00003849564,0.000083721,0.000029973184,0.0006517592,0.00015604179,0.00012990502,0.00013151861,0.00018577649,0.0000019175434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004891539,0.0002399594,0.100526996,0.00003607429,0.00000330864,0.000036739664,0.0010642157,0.00980685,0.049798246,0.00039595284,0.000015925052,0.8380268],"study_design_scores_gemma":[0.00024447808,0.00015618835,0.09416543,0.00012411334,0.000011936517,0.00012039935,0.0000014022257,0.8454543,0.047758248,0.011704282,0.0000720515,0.00018718957],"about_ca_topic_score_codex":0.000067163,"about_ca_topic_score_gemma":0.0000032862479,"teacher_disagreement_score":0.8378396,"about_ca_system_score_codex":0.00011112136,"about_ca_system_score_gemma":0.000045477856,"threshold_uncertainty_score":0.34140435},"labels":[],"label_agreement":null},{"id":"W131673369","doi":"10.1007/978-3-540-71512-2_8","title":"Insights into Brain Connectivity Using Quantitative MRI Measures of White Matter","year":2007,"lang":"en","type":"book-chapter","venue":"Understanding complex systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"White matter; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.4724008109973974,"score_gpt":0.4077308608957799,"score_spread":0.06466995010161747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W131673369","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003357227,0.00059361523,0.8002177,0.00040303395,0.00015340306,0.0011638075,0.000033362518,0.00017582321,0.19692354],"genre_scores_gemma":[0.95514405,0.00004573915,0.019667644,0.00038606118,0.00019892487,0.000015908041,0.00008219343,0.00019527254,0.024264205],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99796635,0.00004442038,0.0006870101,0.0005561549,0.00050224544,0.00024383893],"domain_scores_gemma":[0.998009,0.00035434004,0.0006543611,0.000624582,0.00023045042,0.00012725718],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025862138,0.00040860864,0.0009534105,0.0005613742,0.00030185422,0.000027443964,0.00015556042,0.0002454991,0.00007294053],"category_scores_gemma":[0.00003157579,0.00038929918,0.00020228841,0.00011640766,0.00035874502,0.000077240555,0.00011529172,0.00043108736,0.000012950092],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011652716,0.0000457762,0.00081201235,0.0008057008,0.0002177384,0.00004148957,0.0009498631,0.00015874153,0.0077027,0.9825331,0.006598494,0.00001785481],"study_design_scores_gemma":[0.0035934104,0.0013298097,0.00091489666,0.016319806,0.0012854841,0.00082152605,0.0040010884,0.031262815,0.0008585843,0.56864893,0.3678394,0.0031242876],"about_ca_topic_score_codex":0.00010450262,"about_ca_topic_score_gemma":0.000037384023,"teacher_disagreement_score":0.95480835,"about_ca_system_score_codex":0.0009281135,"about_ca_system_score_gemma":0.000089254376,"threshold_uncertainty_score":0.9998559},"labels":[],"label_agreement":null},{"id":"W136828434","doi":"10.1016/j.nic.2012.12.001","title":"Normal Myelination","year":2013,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; University of Toronto","funders":"","keywords":"Myelin; Medicine; Central nervous system; Neuroscience; Myelin basic protein; Oligodendrocyte; Peripheral; Peripheral nervous system; White matter; Nervous system; Magnetic resonance imaging; Anatomy; Pathology; Biology; Radiology; Internal medicine","score_opus":0.14336042343664893,"score_gpt":0.439233678035619,"score_spread":0.29587325459897007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W136828434","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004471696,0.9914004,0.0042366358,0.00031416374,0.00018478313,0.0017952787,0.00010748783,0.00041410167,0.0015024138],"genre_scores_gemma":[0.000029034538,0.9765196,0.021536022,0.0005993227,0.00019407002,0.00019838315,0.00040600754,0.00013682028,0.00038073858],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972674,0.00007900029,0.0012869949,0.0006816082,0.00033993917,0.00034500513],"domain_scores_gemma":[0.99673474,0.00040293712,0.001272854,0.0011270231,0.00027783532,0.0001846194],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008730451,0.00045715686,0.0018791906,0.00033466137,0.00007553737,0.0000202942,0.0003963917,0.00010557779,0.00004963295],"category_scores_gemma":[0.00032546057,0.00040689748,0.0007111181,0.0007714146,0.0002680785,0.00012489167,0.00019779163,0.0009769745,0.00018757065],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000034820612,0.00014581686,0.00037260202,0.0034913886,0.000030545434,0.00001396419,0.000004829544,0.0000019965591,4.297035e-7,0.000015732723,0.0017948012,0.9941244],"study_design_scores_gemma":[0.00014643809,0.00017038052,0.00034840917,0.0017832551,0.0007325385,0.00009966232,0.0000012272118,0.00017938834,7.8724156e-7,0.00003762325,0.99622846,0.00027186095],"about_ca_topic_score_codex":0.00001051521,"about_ca_topic_score_gemma":2.9082918e-7,"teacher_disagreement_score":0.99443364,"about_ca_system_score_codex":0.00004313441,"about_ca_system_score_gemma":0.00028066177,"threshold_uncertainty_score":0.9998383},"labels":[],"label_agreement":null},{"id":"W1427495351","doi":"10.1007/s00406-003-0414-9","title":"Influence of genetic loading, obstetric complications and premorbid adjustment on brain morphology in schizophrenia:","year":2003,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schizophrenia (object-oriented programming); Atrophy; Ventricle; Psychology; Frontal lobe; Corpus callosum; Brain morphometry; Cerebrospinal fluid; Audiology; Medicine; Physiology; Internal medicine; Psychiatry; Neuroscience; Magnetic resonance imaging","score_opus":0.05276867094052904,"score_gpt":0.366264441450614,"score_spread":0.3134957705100849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1427495351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99232477,0.00026647424,0.0015102954,0.0017222944,0.00005882457,0.0002401607,0.000008551004,0.000022408904,0.003846227],"genre_scores_gemma":[0.9686624,0.0010217013,0.028147021,0.0020979804,0.0000111407335,0.0000036696335,6.912533e-7,0.00001079599,0.000044611683],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99862856,0.00021928275,0.00049199036,0.00043810284,0.000089670386,0.00013238021],"domain_scores_gemma":[0.9987687,0.00055564917,0.00017122994,0.00037408678,0.000015510057,0.000114816816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014834214,0.00009771682,0.00019691978,0.00011613027,0.000048709786,0.000003720372,0.0001363488,0.000016377433,9.687462e-7],"category_scores_gemma":[0.00087572035,0.00008894479,0.000045185876,0.00027123332,0.0007864119,0.0000281675,0.00007574169,0.00023907935,0.0000014433241],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015935936,0.0016824254,0.8947433,0.00012295991,0.0000052487317,0.000023907094,0.00005199341,0.00045930612,0.043970216,0.0392211,0.00013128409,0.019428905],"study_design_scores_gemma":[0.0007637862,0.0006438747,0.99340457,0.00010538939,0.0000122130705,0.000088945635,0.000006205987,0.00022336704,0.00030403328,0.003703736,0.0006775711,0.00006628236],"about_ca_topic_score_codex":9.5195765e-7,"about_ca_topic_score_gemma":6.9551686e-7,"teacher_disagreement_score":0.0986613,"about_ca_system_score_codex":0.0000018152645,"about_ca_system_score_gemma":0.000046314537,"threshold_uncertainty_score":0.36270633},"labels":[],"label_agreement":null},{"id":"W1446022853","doi":"10.3233/jad-142079","title":"Diffusion Tensor Imaging Correlates of Cognitive-Motor Decline in Normal Aging and Increased Alzheimer's Disease Risk","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Cognitive decline; Disease; Cognition; Neuroscience; Psychology; Medicine; Dementia; Cognitive psychology; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.046967013432982166,"score_gpt":0.3415765063678017,"score_spread":0.29460949293481953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1446022853","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778804,0.018668152,0.0009517497,0.0018087034,0.00006479079,0.00044346924,0.00009809435,0.000038758837,0.00004584656],"genre_scores_gemma":[0.99608237,0.0006813678,0.0024962034,0.00052110857,0.00014055973,0.000014114816,0.000022135051,0.000037421094,0.000004728069],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983385,0.000097044984,0.00068321865,0.0002442686,0.00040225888,0.00023469071],"domain_scores_gemma":[0.99738294,0.00020436056,0.0006225644,0.00024051256,0.00043810558,0.0011115206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039429206,0.00021110335,0.000420543,0.00032489572,0.00006356309,0.000020620839,0.000119281925,0.000030001482,0.000017230537],"category_scores_gemma":[0.00083595724,0.00017663998,0.00016297326,0.00022666033,0.00019537694,0.00030027478,0.00013830229,0.00037619277,0.000002514884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021869603,0.00067917013,0.9853529,0.00002020335,0.00011988503,0.00047356595,0.00009294794,0.000019238272,0.00038844792,0.000025903499,0.00021674873,0.010424042],"study_design_scores_gemma":[0.00422361,0.00021667895,0.9829803,0.00075094023,0.0035774847,0.00009268858,0.00015475453,0.0058616768,0.00049085415,0.0012320202,0.000224268,0.00019473204],"about_ca_topic_score_codex":0.00005569634,"about_ca_topic_score_gemma":0.0000012746954,"teacher_disagreement_score":0.018201927,"about_ca_system_score_codex":0.000023036175,"about_ca_system_score_gemma":0.00026532728,"threshold_uncertainty_score":0.72031695},"labels":[],"label_agreement":null},{"id":"W1446429242","doi":"10.3233/pep-13039","title":"Diffusion-weighted magnetic resonance imaging and pediatric epilepsy","year":2015,"lang":"en","type":"article","venue":"Journal of Pediatric Epilepsy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Magnetic resonance imaging; Epilepsy; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion MRI; Pediatric epilepsy; Medicine; Nuclear magnetic resonance; Diffusion; Neuroscience; Functional magnetic resonance imaging; Psychology; Radiology; Physics","score_opus":0.03669287988482227,"score_gpt":0.3121617593605929,"score_spread":0.27546887947577064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1446429242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94022524,0.04849868,0.005852604,0.0035901451,0.0004004622,0.00040404752,0.000013545454,0.00012861112,0.0008866474],"genre_scores_gemma":[0.9251026,0.018212138,0.05049818,0.0008445305,0.0047279308,0.00001721268,0.0000049950727,0.00007201667,0.00052041723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980539,0.000056316112,0.00075716735,0.00028644924,0.0005194091,0.00032674192],"domain_scores_gemma":[0.99795884,0.00017533776,0.00051701814,0.0003449739,0.00046940835,0.0005344022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004603861,0.0002245389,0.00044947496,0.0004571454,0.000094903575,0.000033594893,0.00020311814,0.00007386917,0.0000392968],"category_scores_gemma":[0.00034587306,0.00018451904,0.00013345604,0.0007029506,0.00007157472,0.00022167529,0.00010886891,0.0005666364,0.00001663997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015676528,0.00023964004,0.9384384,0.000047176505,0.0000036268032,0.00029283838,0.00017332024,0.0000015077796,0.00015728395,0.00015986153,0.040817793,0.019511763],"study_design_scores_gemma":[0.008092349,0.0016985062,0.8713564,0.00008477112,0.0012558134,0.004663494,0.00033329902,0.0013818148,0.00016104295,0.011484965,0.09878581,0.0007017342],"about_ca_topic_score_codex":0.0000064895053,"about_ca_topic_score_gemma":2.8875445e-7,"teacher_disagreement_score":0.06708202,"about_ca_system_score_codex":0.00008025434,"about_ca_system_score_gemma":0.00022794578,"threshold_uncertainty_score":0.7524468},"labels":[],"label_agreement":null},{"id":"W1481624280","doi":"10.1002/nbm.3326","title":"Quantitative MRI in a non‐surgical model of cervical spinal cord injury","year":2015,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Sunnybrook Hospital; McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research; Lantheus Medical Imaging","keywords":"White matter; Medicine; Spinal cord; Magnetic resonance imaging; Diffusion MRI; Luxol fast blue stain; Hemosiderin; Histology; Spinal cord injury; Pathology; Myelin; Radiology; Central nervous system; Internal medicine","score_opus":0.16688352249975225,"score_gpt":0.4616736964257666,"score_spread":0.29479017392601436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481624280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9444259,0.00025078442,0.03476444,0.015351666,0.00005383402,0.00082908187,0.000028717976,0.00009743519,0.004198143],"genre_scores_gemma":[0.95416594,0.00011405323,0.045055777,0.00043634072,0.00004850794,0.000052190924,0.000019349012,0.000015948406,0.000091876835],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988264,0.000019679726,0.00042127795,0.00025924447,0.0002742625,0.00019916108],"domain_scores_gemma":[0.9993142,0.00003912628,0.00008162796,0.00027651916,0.00009904319,0.00018947477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028713286,0.00012174342,0.00038571705,0.00034807718,0.00000917531,0.0000015554131,0.00011222605,0.000077660035,0.00001421031],"category_scores_gemma":[0.00009376319,0.00009877921,0.000035440997,0.00073933264,0.00024833882,0.0000442589,0.00006104804,0.00028062414,0.000007086429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.07739259,0.013236252,0.25016785,0.002148685,0.00013591904,0.0022260824,0.003910922,0.0018979283,0.3457955,0.12237619,0.051017627,0.12969445],"study_design_scores_gemma":[0.0335587,0.04295489,0.10425655,0.004691479,0.00020382981,0.0005442612,0.0018096255,0.6860036,0.018010117,0.06720702,0.039445408,0.001314512],"about_ca_topic_score_codex":0.00008514705,"about_ca_topic_score_gemma":0.000007111893,"teacher_disagreement_score":0.6841057,"about_ca_system_score_codex":0.00009337749,"about_ca_system_score_gemma":0.000118471966,"threshold_uncertainty_score":0.40280992},"labels":[],"label_agreement":null},{"id":"W1482977697","doi":"10.1007/978-3-642-15705-9_67","title":"Inference of a HARDI Fiber Bundle Atlas Using a Two-Level Clustering Strategy","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Fiber bundle; Cluster analysis; Computer science; Tractography; Artificial intelligence; Bundle; Pattern recognition (psychology); Atlas (anatomy); Segmentation; Pairwise comparison; Diffusion MRI; Inference; Normalization (sociology); Fiber tract; Population; Spatial normalization; Voxel; Anatomy; Medicine; Magnetic resonance imaging","score_opus":0.10183918342541161,"score_gpt":0.3880531155902251,"score_spread":0.2862139321648135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1482977697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35878694,0.0000059437484,0.6407979,0.00014936813,0.000060899947,0.00012729892,0.0000016152349,0.00003746867,0.00003257168],"genre_scores_gemma":[0.56478393,9.0541835e-7,0.4350256,0.00013031963,0.000049052112,0.000003405571,4.7554892e-7,0.000004927893,0.0000013869497],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902666,0.000008176694,0.00018710061,0.00034437442,0.00020277839,0.0002309087],"domain_scores_gemma":[0.999189,0.00011532336,0.000073453375,0.00043762423,0.00011485569,0.000069696005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001676329,0.000106881285,0.00016847518,0.00014586153,0.000078728975,0.00003486827,0.00027850998,0.00003871558,0.000016165694],"category_scores_gemma":[0.00010059725,0.000092125614,0.0000316471,0.0006859441,0.00034838056,0.00013693946,0.00020514723,0.00033671028,0.0000023161135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012923948,0.00010606396,0.007138744,0.000041929274,0.0000027043784,0.000010314533,0.0002351968,0.07852054,0.6507849,0.0002572012,0.0000018548761,0.26288763],"study_design_scores_gemma":[0.00031063598,0.000118541866,0.0066828253,0.00011850971,0.0000070159604,0.0001379915,4.360725e-7,0.83312297,0.15322798,0.006064898,0.000072120136,0.0001361052],"about_ca_topic_score_codex":0.00009957936,"about_ca_topic_score_gemma":0.00005676138,"teacher_disagreement_score":0.75460243,"about_ca_system_score_codex":0.000028540971,"about_ca_system_score_gemma":0.00016667813,"threshold_uncertainty_score":0.37567735},"labels":[],"label_agreement":null},{"id":"W1483514369","doi":"10.1007/978-3-642-23629-7_8","title":"Sparse Multi-Shell Diffusion Imaging","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Mental Health","keywords":"Computer science; Spherical harmonics; Diffusion MRI; Shell (structure); Artificial intelligence; Representation (politics); Compressed sensing; Generalization; Pattern recognition (psychology); Artificial neural network; Computer vision; Algorithm; Magnetic resonance imaging; Physics; Mathematics; Materials science","score_opus":0.083009533607663,"score_gpt":0.33806608395518184,"score_spread":0.25505655034751884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1483514369","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07130011,0.00004138321,0.927565,0.0005441933,0.000110502995,0.0002024028,5.0151624e-7,0.00015821474,0.00007771894],"genre_scores_gemma":[0.55492735,0.0000066377497,0.44398415,0.0010355475,0.00003303268,0.00000564281,4.973436e-7,0.0000056448284,0.000001497053],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999032,0.0000087555445,0.00013379219,0.000412156,0.00016099236,0.00025229968],"domain_scores_gemma":[0.9993435,0.00003833532,0.000039615916,0.00043617986,0.0000578514,0.00008450965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013658797,0.00010320742,0.000114472336,0.00016133835,0.0001006478,0.000019720344,0.0002649886,0.000021305588,0.0000145456825],"category_scores_gemma":[0.00005280209,0.00008423792,0.00002845648,0.00060669094,0.00028490555,0.0001204832,0.00018905399,0.00019354663,0.000011147262],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019706864,0.00032013268,0.14658341,0.000020294146,0.0000013652746,0.00010386805,0.0014157682,0.00043346192,0.09403757,0.00025551734,0.000019923078,0.75678897],"study_design_scores_gemma":[0.00063739106,0.00009588164,0.12901469,0.00013820032,0.0000089802,0.00022477451,0.0000013515224,0.7083982,0.1494862,0.011354139,0.0003907977,0.0002493907],"about_ca_topic_score_codex":0.00003325515,"about_ca_topic_score_gemma":0.0000045867423,"teacher_disagreement_score":0.7565396,"about_ca_system_score_codex":0.000044385586,"about_ca_system_score_gemma":0.000044816396,"threshold_uncertainty_score":0.3435123},"labels":[],"label_agreement":null},{"id":"W1489388295","doi":"10.1007/978-3-642-33418-4_36","title":"Sparse DSI: Learning DSI Structure for Denoising and Fast Imaging","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Diffusion MRI; Noise reduction; Artificial intelligence; SIGNAL (programming language); Diffusion; Pattern recognition (psychology); Dictionary learning; Computer vision; Algorithm; Image (mathematics); Magnetic resonance imaging; Physics","score_opus":0.035530827183147325,"score_gpt":0.3374550121171708,"score_spread":0.3019241849340235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489388295","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20588809,0.0002091608,0.79254764,0.0009413595,0.000092824834,0.00022767551,0.0000011247287,0.000085278676,0.0000068494164],"genre_scores_gemma":[0.64510894,0.0000047880035,0.35402545,0.0006776322,0.00016577364,0.000005904548,0.0000016037136,0.000008878696,0.0000010015315],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990386,0.0000104829505,0.000121683304,0.00032537902,0.0001399832,0.0003639053],"domain_scores_gemma":[0.99943537,0.00013990734,0.00005101347,0.00021072333,0.000057835197,0.000105144216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019263555,0.00011473371,0.00014231695,0.00013550208,0.00022309732,0.000058895417,0.00013256024,0.000027510394,0.000002462929],"category_scores_gemma":[0.00012887381,0.00009785662,0.000021525966,0.000400102,0.00022563484,0.00023685076,0.00012807094,0.00024972096,5.087365e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013824854,0.000028306778,0.14321479,0.00004288954,0.0000020258663,0.0000040106297,0.0010196185,0.0046093226,0.087911725,0.00020133906,0.000013441697,0.7629387],"study_design_scores_gemma":[0.001177437,0.00017087109,0.06802886,0.00030603967,0.00003875438,0.00084851193,0.0000115271005,0.67955106,0.22534807,0.020656234,0.0033140196,0.0005485976],"about_ca_topic_score_codex":0.000004921712,"about_ca_topic_score_gemma":0.0000017038992,"teacher_disagreement_score":0.7623901,"about_ca_system_score_codex":0.00004735289,"about_ca_system_score_gemma":0.000033699587,"threshold_uncertainty_score":0.3990477},"labels":[],"label_agreement":null},{"id":"W1496266809","doi":"10.1007/978-3-642-15705-9_69","title":"Probabilistic Anatomical Connectivity Using Completion Fields","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Probabilistic logic; Computer science; Diffusion; Diffusion MRI; SIGNAL (programming language); Imaging phantom; Artificial intelligence; Field (mathematics); Algorithm; Probabilistic analysis of algorithms; Machine learning; Data mining; Magnetic resonance imaging; Mathematics; Physics","score_opus":0.05624690948395681,"score_gpt":0.3600744338762137,"score_spread":0.30382752439225685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496266809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47358412,0.0000018330859,0.5254782,0.00065121276,0.000088903966,0.00013497671,4.2408567e-7,0.00005256729,0.000007779341],"genre_scores_gemma":[0.7001778,3.8390365e-7,0.29916963,0.0005644112,0.00007880197,0.0000045426677,7.065911e-7,0.0000035867745,1.2921859e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992085,0.000009416462,0.00010905942,0.00033913658,0.00015271064,0.0001811609],"domain_scores_gemma":[0.99935055,0.00014249199,0.000032231485,0.0003373205,0.000073529634,0.00006389063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018634804,0.000076808006,0.00012030385,0.00009903667,0.00010682713,0.000029369168,0.00016195701,0.00004813439,0.000009583705],"category_scores_gemma":[0.00022557216,0.00006598467,0.00002280269,0.0005201133,0.00035697743,0.0000783573,0.00009418721,0.00038792694,0.0000012040202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004376922,0.00039522364,0.07461263,0.00006251633,0.000003796805,0.000046571415,0.0003874724,0.030505212,0.56123406,0.006337742,0.000016002676,0.326355],"study_design_scores_gemma":[0.00016807781,0.000055836274,0.022041144,0.000025564352,0.0000041137528,0.00016496496,1.0534116e-7,0.9144866,0.0267849,0.036104627,0.00007223005,0.000091834605],"about_ca_topic_score_codex":0.000021318137,"about_ca_topic_score_gemma":0.000022430111,"teacher_disagreement_score":0.8839814,"about_ca_system_score_codex":0.00004558697,"about_ca_system_score_gemma":0.00008567157,"threshold_uncertainty_score":0.2690777},"labels":[],"label_agreement":null},{"id":"W1496884366","doi":"10.3171/2012.1.peds11363","title":"Corticospinal tract mapping in children with ruptured arteriovenous malformations using functionally guided diffusion-tensor imaging","year":2012,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Diffusion MRI; Corticospinal tract; Fractional anisotropy; Tractography; White matter; Motor cortex; Radiology; Magnetic resonance imaging; Neuroscience; Psychology","score_opus":0.06553312276105167,"score_gpt":0.31434234697393987,"score_spread":0.2488092242128882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1496884366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97004163,0.00030878646,0.028291536,0.0008094992,0.00020082985,0.00025278304,0.000008927702,0.000043661577,0.00004236835],"genre_scores_gemma":[0.98240995,0.00021231422,0.015555534,0.001058906,0.0006922761,0.0000055309188,0.000007792069,0.0000376478,0.000020021796],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982745,0.000036259087,0.00078796915,0.0001371483,0.00041309968,0.00035099805],"domain_scores_gemma":[0.9985341,0.00009776044,0.0007189579,0.00020205839,0.00023493911,0.0002121875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002949775,0.00017625156,0.00034249265,0.00071266084,0.00012016686,0.000033464934,0.00008921022,0.000042278563,0.000014139004],"category_scores_gemma":[0.00016765246,0.00014465925,0.00014343322,0.0007780344,0.000041115167,0.0005425673,0.00003063238,0.0004913668,0.000002253275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041841427,0.0004842757,0.99335593,0.00001774876,0.000008458367,0.00007307987,0.00004953967,0.00026662627,0.0042474475,0.000012166019,0.00047552577,0.0009673575],"study_design_scores_gemma":[0.0006020529,0.00007738514,0.9836581,0.00005351319,0.00013400237,0.013311003,0.00002910478,0.000752287,0.000036420584,0.00004188173,0.0011636786,0.00014058457],"about_ca_topic_score_codex":0.0000039700753,"about_ca_topic_score_gemma":7.3082674e-8,"teacher_disagreement_score":0.013237923,"about_ca_system_score_codex":0.00010252097,"about_ca_system_score_gemma":0.00015763474,"threshold_uncertainty_score":0.5899033},"labels":[],"label_agreement":null},{"id":"W1497909821","doi":"10.1002/047134608x.w8258","title":"High Angular Resolution Diffusion Imaging (<scp>HARDI</scp>)","year":2015,"lang":"en","type":"other","venue":"Wiley Encyclopedia of Electrical and Electronics Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Tractography; Angular resolution (graph drawing); White matter; Diffusion; High resolution; Computer science; Geology; Neuroscience; Magnetic resonance imaging; Medicine; Remote sensing; Psychology; Physics; Radiology; Mathematics","score_opus":0.009248931267733814,"score_gpt":0.24429748537093068,"score_spread":0.23504855410319686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1497909821","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025839865,0.25078654,0.3095672,0.0011122614,0.0006125066,0.0034320655,0.00011974659,0.0052924287,0.40323737],"genre_scores_gemma":[0.16885751,0.31691244,0.18400928,0.00079246116,0.0045119138,0.00055407506,0.0008968789,0.003541213,0.3199242],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986894,0.000011125488,0.00024645915,0.00035815313,0.0002334128,0.0004614468],"domain_scores_gemma":[0.9993123,0.00005262233,0.00010671472,0.00028668647,0.000053802964,0.00018789724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009188472,0.00026133965,0.00040021408,0.00030452432,0.000031474625,0.000008561834,0.000099510326,0.00013719613,0.000009131808],"category_scores_gemma":[0.00016441081,0.0002523707,0.00006708693,0.0004698182,0.00003585854,0.000041625088,0.000055245997,0.00044265622,0.0000034547252],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047899142,0.00052322104,0.0016331987,0.0005709655,0.00019887736,0.00008622556,0.00012004273,0.0003085959,0.039350554,0.03716166,0.8362909,0.08370787],"study_design_scores_gemma":[0.0004395827,0.00017662493,0.0002145685,0.00018751243,0.00010986171,0.00009965416,0.0000021677533,0.008330091,0.0007176105,0.00088888605,0.9886966,0.00013683937],"about_ca_topic_score_codex":0.000038896575,"about_ca_topic_score_gemma":0.0000019372887,"teacher_disagreement_score":0.15240571,"about_ca_system_score_codex":0.00008913577,"about_ca_system_score_gemma":0.00008602299,"threshold_uncertainty_score":0.99999285},"labels":[],"label_agreement":null},{"id":"W1499087426","doi":"10.1007/978-3-540-39903-2_26","title":"Visualization of Neural DTI Vector Fields Using Line Integral Convolution","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Diffusion MRI; Voxel; Tractography; Tensor field; Fractional anisotropy; Visualization; Fiber bundle; Artificial intelligence; Vector field; Anisotropy; Line integral; Tensor (intrinsic definition); Computer science; Bundle; Computer vision; Convolution (computer science); Line (geometry); Physics; Mathematics; Mathematical analysis; Artificial neural network; Geometry; Optics; Integral equation; Materials science","score_opus":0.07878309860122387,"score_gpt":0.36631929826678017,"score_spread":0.2875361996655563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1499087426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001990981,0.0001388199,0.9965155,0.0003937552,0.00024666954,0.00033534598,0.0000039233573,0.000065544904,0.00030947334],"genre_scores_gemma":[0.78639257,0.000039506063,0.21175191,0.0014245914,0.00020456553,0.0000041308867,0.00001807474,0.00002964305,0.00013501372],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882454,0.000009625107,0.00029794205,0.0004250264,0.00026625642,0.00017659103],"domain_scores_gemma":[0.9991194,0.000067702924,0.00018233065,0.0003782881,0.00019847997,0.00005379973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012402669,0.00018651277,0.00028958608,0.00028093564,0.00006237354,0.00001720888,0.00018909691,0.00015082798,0.000015643061],"category_scores_gemma":[0.00006944404,0.00016721665,0.00006524184,0.00026448755,0.00035851396,0.00007797505,0.000087882734,0.00035184328,8.4370527e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021294536,0.0004103058,0.0033487312,0.00091820676,0.000057969373,0.00014506918,0.0012389836,0.17687885,0.074537896,0.11963679,0.00022587321,0.62238836],"study_design_scores_gemma":[0.00035402857,0.00040065084,0.00020333716,0.0007010678,0.000046388916,0.00016748166,1.6932341e-7,0.92542124,0.026822817,0.04456662,0.0009902617,0.000325966],"about_ca_topic_score_codex":0.000013519862,"about_ca_topic_score_gemma":0.000004924403,"teacher_disagreement_score":0.7847636,"about_ca_system_score_codex":0.000120230965,"about_ca_system_score_gemma":0.000115112016,"threshold_uncertainty_score":0.6818897},"labels":[],"label_agreement":null},{"id":"W1506092539","doi":"10.1002/mrm.25865","title":"Surface‐to‐volume ratio mapping of tumor microstructure using oscillating gradient diffusion weighted imaging","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Cancer Institute; National Institutes of Health; School of Medicine, New York University; National Institute of Biomedical Imaging and Bioengineering; York University; Center for Advanced Imaging Innovation and Research","keywords":"Thermal diffusivity; Ex vivo; Diffusion; In vivo; Nuclear magnetic resonance; Diffusion MRI; Effective diffusion coefficient; Chemistry; Range (aeronautics); Volume (thermodynamics); Materials science; Surface-area-to-volume ratio; Biophysics; Analytical Chemistry (journal); Biomedical engineering; Thermodynamics; Physics; Magnetic resonance imaging; Chromatography; Biology","score_opus":0.05642136463734083,"score_gpt":0.3310188081416106,"score_spread":0.2745974435042698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1506092539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97795415,0.0040267827,0.012161972,0.0042191558,0.00013280152,0.000886216,0.0000070173933,0.00009127795,0.0005206285],"genre_scores_gemma":[0.8784764,0.00007216443,0.11998641,0.0009668476,0.00014612851,0.000018190198,0.000012152587,0.000040207706,0.000281518],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981171,0.000046168672,0.0006394273,0.00043616202,0.00041334133,0.00034781583],"domain_scores_gemma":[0.998861,0.000056932295,0.00017949173,0.00047794016,0.00021065929,0.00021393447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034444235,0.00022271129,0.0005196084,0.00023701905,0.00006319869,0.000007523039,0.00015606666,0.000038731432,0.000049525333],"category_scores_gemma":[0.00033438724,0.00018151145,0.000039961946,0.00091664406,0.00021504804,0.000054889417,0.000109453,0.0002707974,0.000003108145],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015765082,0.000089769776,0.33210668,0.00014532483,0.0000026013902,0.00013947918,0.0020710353,0.00030574662,0.628945,0.0002014589,0.0025643948,0.033270866],"study_design_scores_gemma":[0.008973957,0.0012672385,0.47220704,0.0062518944,0.00012053469,0.0010569841,0.0025335855,0.34862703,0.013068277,0.0044332156,0.14059645,0.0008638095],"about_ca_topic_score_codex":0.00029899596,"about_ca_topic_score_gemma":0.000006147445,"teacher_disagreement_score":0.61587673,"about_ca_system_score_codex":0.00015206732,"about_ca_system_score_gemma":0.000080706755,"threshold_uncertainty_score":0.7401822},"labels":[],"label_agreement":null},{"id":"W150669400","doi":"10.1007/978-3-642-39094-4_67","title":"Reconstruction of HARDI Data Using a Split Bregman Optimization Approach","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion MRI; Noise (video); Artificial intelligence; SIGNAL (programming language); Noise reduction; Diffusion imaging; Algorithm; Signal reconstruction; Exploit; Signal-to-noise ratio (imaging); Pattern recognition (psychology); Computer vision; Signal processing; Image (mathematics); Magnetic resonance imaging","score_opus":0.11902295309021613,"score_gpt":0.3356993330657442,"score_spread":0.21667637997552805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W150669400","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001270311,0.00009051419,0.99662554,0.00016709138,0.00012494178,0.000558619,0.000015469359,0.00007376067,0.0022170385],"genre_scores_gemma":[0.009170524,0.00005369684,0.99021965,0.0001821233,0.00017264878,0.000004993248,0.000063320105,0.00002585022,0.000107206346],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847275,0.0000070200153,0.00031018347,0.0007539272,0.00028452437,0.00017160056],"domain_scores_gemma":[0.99819493,0.000046819547,0.0002444085,0.0012852385,0.00016942479,0.000059198494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018620481,0.00018951406,0.0003181316,0.000305886,0.00007642578,0.000037921956,0.00054668455,0.00012942396,0.000026675503],"category_scores_gemma":[0.000039859322,0.00017296968,0.00003959214,0.00023894299,0.0005066934,0.00024082113,0.00042309688,0.0003432936,0.0000014772658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010692261,0.000039875347,0.00011879855,0.00016465547,0.000012524625,0.0000047388166,0.00007129274,0.26553652,0.0013130432,0.0026513957,0.000030830695,0.7300456],"study_design_scores_gemma":[0.00012065066,0.00003749526,0.00002645786,0.00036422626,0.00002924574,0.00029159253,1.3179273e-7,0.99001217,0.0006229698,0.008065169,0.00027659358,0.00015329302],"about_ca_topic_score_codex":0.000019624145,"about_ca_topic_score_gemma":7.3393755e-7,"teacher_disagreement_score":0.7298923,"about_ca_system_score_codex":0.000095312455,"about_ca_system_score_gemma":0.00016666483,"threshold_uncertainty_score":0.7053499},"labels":[],"label_agreement":null},{"id":"W1508815940","doi":"10.1002/jmri.24256","title":"Correlation between fractional anisotropy and motor outcomes in one‐year‐old infants with periventricular brain injury","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Research Resources","keywords":"Fractional anisotropy; Diffusion MRI; Internal capsule; White matter; Medicine; Correlation; Treadmill; Physical medicine and rehabilitation; Physical therapy; Magnetic resonance imaging; Radiology","score_opus":0.02002616906693191,"score_gpt":0.3024408896021785,"score_spread":0.28241472053524663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508815940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9718142,0.0012221226,0.017807612,0.008654555,0.00002217813,0.0003944516,0.000005054761,0.000019286965,0.000060544036],"genre_scores_gemma":[0.9477428,0.0002084618,0.05104717,0.0005806144,0.00009454532,0.000019104942,0.000002127644,0.000019824753,0.00028531923],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990352,0.000027830372,0.00034964015,0.0001500606,0.0002809428,0.00015637097],"domain_scores_gemma":[0.99925846,0.00013596113,0.00022158482,0.00014112658,0.00015044803,0.00009239532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001376342,0.00010992052,0.00025801762,0.00018593205,0.000046905112,0.000034039305,0.000058896756,0.000027384545,0.000059463036],"category_scores_gemma":[0.00016557891,0.000087456574,0.000040874987,0.00015920229,0.00007685168,0.00025947645,0.000028513172,0.00032733608,0.0000038715025],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060853457,0.000058711445,0.9674507,0.0000084255225,0.0000040118225,0.000024004856,0.000032411583,0.000009221949,0.0023722446,0.000081827464,0.00030427653,0.029593311],"study_design_scores_gemma":[0.0011152223,0.00032315767,0.99269074,0.00019345677,0.000027738794,0.00015976958,0.000039953284,0.0011684372,0.00011281265,0.0009055824,0.003174246,0.00008888307],"about_ca_topic_score_codex":0.00002710104,"about_ca_topic_score_gemma":3.8544587e-7,"teacher_disagreement_score":0.03323956,"about_ca_system_score_codex":0.000049812366,"about_ca_system_score_gemma":0.0000425977,"threshold_uncertainty_score":0.35663757},"labels":[],"label_agreement":null},{"id":"W1513935208","doi":"10.3389/fnins.2015.00257","title":"Boosting brain connectome classification accuracy in Alzheimer's disease using higher-order singular value decomposition","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; National Center for Research Resources; F. Hoffmann-La Roche; Synarc; University of Southern California; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Bayer HealthCare; Meso Scale Diagnostics; National Science Foundation","keywords":"Neuroimaging; Connectome; Disease; Prodromal Stage; Alzheimer's disease; Human Connectome Project; Artificial intelligence; Singular value decomposition; Computer science; Alzheimer's Disease Neuroimaging Initiative; Logistic regression; Neuroscience; Diffusion MRI; Cognitive decline; Pattern recognition (psychology); Cognition; Medicine; Machine learning; Psychology; Cognitive impairment; Magnetic resonance imaging; Pathology; Dementia; Functional connectivity; Radiology","score_opus":0.15730349016295483,"score_gpt":0.41116882441069313,"score_spread":0.2538653342477383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1513935208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5954808,0.0005523716,0.39211604,0.009380457,0.00082476315,0.0010407569,0.000009532786,0.000249456,0.00034579492],"genre_scores_gemma":[0.90880805,0.000019881301,0.0888439,0.0021993576,0.000043244323,0.000033992877,0.000011715046,0.0000215089,0.00001835948],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857426,0.00007843378,0.00028677168,0.0005128058,0.000262329,0.00028540418],"domain_scores_gemma":[0.99917203,0.00006940576,0.00012504097,0.0003568903,0.00006764758,0.00020897224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027602585,0.00013404725,0.00018167924,0.000266573,0.00009062553,0.000038683425,0.00018691343,0.00003811983,0.000001116678],"category_scores_gemma":[0.0008671979,0.00014242672,0.000028950368,0.0010333468,0.00018769906,0.00035239107,0.00006412177,0.00022027167,0.0000011636777],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038333362,0.00095566607,0.70176077,0.000052159063,0.00000526297,0.00041633775,0.0003745427,0.012937385,0.25357774,0.007257218,0.0053175907,0.016961979],"study_design_scores_gemma":[0.0012070015,0.000100453,0.34158272,0.00020486444,0.000042556232,0.00004094091,0.00006583176,0.6385038,0.0020241484,0.008054968,0.007848582,0.000324161],"about_ca_topic_score_codex":0.000025486243,"about_ca_topic_score_gemma":5.030223e-7,"teacher_disagreement_score":0.62556636,"about_ca_system_score_codex":0.00016860485,"about_ca_system_score_gemma":0.00016579073,"threshold_uncertainty_score":0.58079934},"labels":[],"label_agreement":null},{"id":"W1520400319","doi":"10.1002/nbm.3104","title":"Effects of diffusion on high‐resolution quantitative <i>T</i><sub>2</sub> MRI","year":2014,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Nuclear magnetic resonance; Effective diffusion coefficient; White matter; Diffusion; Diffusion imaging; Spin echo; Diffusion MRI; Anisotropy; Physics; Resolution (logic); Isotropy; Chemistry; Magnetic resonance imaging; Optics; Medicine; Thermodynamics","score_opus":0.02169109480085831,"score_gpt":0.3219398308283474,"score_spread":0.3002487360274891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1520400319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9336182,0.00014279751,0.06046933,0.0042579863,0.00009705242,0.0007189146,0.00000538869,0.00013765311,0.00055269117],"genre_scores_gemma":[0.99116117,0.00034846022,0.007145216,0.0010941224,0.0000990078,0.000062645246,0.00004077588,0.00002265428,0.000025943209],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99893504,0.00004681963,0.00028964545,0.00028238175,0.0002583273,0.00018780383],"domain_scores_gemma":[0.99905294,0.00035025773,0.00012591678,0.00030463567,0.00006397183,0.00010225576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018754907,0.00014090321,0.00032681148,0.00030572605,0.000035973357,0.0000017700668,0.00007977384,0.0000720474,0.0000046981913],"category_scores_gemma":[0.0003332959,0.000110947185,0.000042920277,0.0005019006,0.00018327076,0.000031067266,0.000035932273,0.00019723154,0.000014327914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016899404,0.0003894328,0.00072797044,0.000203697,0.0000057590987,0.000010037145,0.000070256385,0.0000108559525,0.9758301,0.0088298,0.0016024137,0.012150707],"study_design_scores_gemma":[0.003935352,0.0029388717,0.087184,0.0013493974,0.00006878452,0.000015556896,0.000023123295,0.0031869416,0.8888544,0.005022871,0.007246309,0.00017442416],"about_ca_topic_score_codex":0.000033174678,"about_ca_topic_score_gemma":0.0000024729773,"teacher_disagreement_score":0.0869757,"about_ca_system_score_codex":0.000061150844,"about_ca_system_score_gemma":0.000019087069,"threshold_uncertainty_score":0.45242947},"labels":[],"label_agreement":null},{"id":"W1525443459","doi":"10.1002/hbm.22441","title":"Gray matter alterations in early aging: A diffusion magnetic resonance imaging study","year":2013,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Gray (unit); Neuroscience; Magnetic resonance imaging; Neuroimaging; Precuneus; Context (archaeology); Psychology; Hum; Brain aging; Anatomy; Functional magnetic resonance imaging; Biology; Medicine; Nuclear medicine; Cognition; Radiology","score_opus":0.04402403207313782,"score_gpt":0.3263843318786671,"score_spread":0.2823602998055293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525443459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9816332,0.00017033407,0.0045583504,0.009380003,0.000019403547,0.0015576809,0.0000012634594,0.00022022796,0.0024595533],"genre_scores_gemma":[0.99017656,0.0000030835952,0.0037093295,0.0030738215,0.00007253242,0.0005100329,0.000008821489,0.00003577917,0.002410032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987942,0.000050901705,0.00032246983,0.00039551052,0.0001539991,0.00028289648],"domain_scores_gemma":[0.999284,0.00005694225,0.000059930855,0.00047351312,0.00005312657,0.00007246473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012939691,0.00015522537,0.0001896598,0.0002462837,0.00024045176,0.00008087858,0.00012825082,0.000021593061,0.00026305573],"category_scores_gemma":[0.000027716162,0.00015268422,0.000042510746,0.00029340293,0.000056665707,0.00017511245,0.000096622156,0.00026453426,0.0001342738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028281179,0.0003093313,0.8984075,0.000020528787,0.0000016148937,0.00003066849,0.0020302967,0.0000016658396,0.08818134,0.0005192979,0.0067768637,0.0037180576],"study_design_scores_gemma":[0.00070912205,0.00006312666,0.9877558,0.00017373692,0.000006330996,0.000019238034,0.00035189255,0.00062610954,0.00003359009,0.003119821,0.006991188,0.00015004573],"about_ca_topic_score_codex":0.00029417747,"about_ca_topic_score_gemma":0.000019653568,"teacher_disagreement_score":0.08934829,"about_ca_system_score_codex":0.000052605836,"about_ca_system_score_gemma":0.000010280004,"threshold_uncertainty_score":0.6226282},"labels":[],"label_agreement":null},{"id":"W1525759131","doi":"10.1002/jmri.24604","title":"Fast computation of myelin maps from MRI T<sub>2</sub>relaxation data using multicore CPU and graphics card parallelization","year":2014,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Multi-core processor; Parallel computing; MATLAB; Computation; Graphics; CUDA; Graphics hardware; Computational science; Relaxation (psychology); Algorithm; Computer graphics (images)","score_opus":0.051499703464215535,"score_gpt":0.3265626779576491,"score_spread":0.27506297449343353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525759131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49241006,0.0035997212,0.5027641,0.00093591574,0.00005476805,0.0001753964,0.000022619673,0.00002046236,0.000016957292],"genre_scores_gemma":[0.8604095,0.0016219511,0.13755621,0.00018737197,0.00014790543,0.0000017065125,0.000050584415,0.000022950378,0.0000018546066],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870014,0.000065985005,0.0005735969,0.00023058128,0.00030060476,0.0001291199],"domain_scores_gemma":[0.99852675,0.00012300331,0.0006277496,0.0003243915,0.00032239652,0.00007570464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034099387,0.00012528752,0.00028979479,0.00015655402,0.00006968114,0.000027111477,0.00014359341,0.000037528993,0.0000014508528],"category_scores_gemma":[0.0002359649,0.0001181006,0.00004626919,0.00020025551,0.00011939481,0.00027589215,0.00007940802,0.00022348756,4.3299318e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014458063,0.00012066348,0.07884676,0.000103003855,0.000012735856,0.00001800771,0.00026516465,0.002153329,0.24179764,0.0002504551,0.0007558821,0.6755318],"study_design_scores_gemma":[0.0018569164,0.00017546026,0.20071384,0.0009230209,0.00023194672,0.00025821317,0.000094227864,0.77801365,0.009103458,0.0049141655,0.0035307372,0.00018434365],"about_ca_topic_score_codex":0.00002940518,"about_ca_topic_score_gemma":0.0000024277072,"teacher_disagreement_score":0.7758603,"about_ca_system_score_codex":0.000027842441,"about_ca_system_score_gemma":0.00004568238,"threshold_uncertainty_score":0.48160028},"labels":[],"label_agreement":null},{"id":"W1525872531","doi":"10.1111/j.1528-1167.2007.01105.x","title":"Evaluation of Subcortical White Matter and Deep White Matter Tracts in Malformations of Cortical Development","year":2007,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Pathology; Cortical dysplasia; Anatomy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06337090375870061,"score_gpt":0.3646028097670102,"score_spread":0.3012319060083096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1525872531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93510264,0.000033742035,0.05989658,0.001066761,0.000013664552,0.00042340628,0.0000022902673,0.000017309729,0.0034436071],"genre_scores_gemma":[0.9594374,0.0000073589854,0.040078957,0.00034536014,0.00001066946,0.000032824133,0.00001529194,0.00001113486,0.000061028742],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988289,0.00002911983,0.00051046227,0.00014354248,0.0003285214,0.00015944059],"domain_scores_gemma":[0.99942917,0.00005221193,0.000100779944,0.0001874318,0.00016133656,0.00006909398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006832126,0.00008256589,0.0001811792,0.00013806263,0.000024369487,0.0000033721803,0.0000409231,0.000050071194,0.00034453388],"category_scores_gemma":[0.000051282957,0.00007609106,0.000024833738,0.00016976826,0.00008081874,0.00007888965,0.00002759532,0.0001429716,0.000026290627],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003804244,0.00016737389,0.99298227,0.000049086237,0.0000069248895,0.0000021206185,0.0004146811,0.000018169798,0.001981766,0.00034876209,0.0002845458,0.0037062373],"study_design_scores_gemma":[0.0004991933,0.000033947428,0.9927381,0.00006292582,0.000062366795,0.000033004944,0.00006094532,0.0017515373,0.004017111,0.00038508495,0.0002898386,0.00006590006],"about_ca_topic_score_codex":0.000001955983,"about_ca_topic_score_gemma":0.0000072275243,"teacher_disagreement_score":0.024334734,"about_ca_system_score_codex":0.000049375652,"about_ca_system_score_gemma":0.000047451587,"threshold_uncertainty_score":0.37724042},"labels":[],"label_agreement":null},{"id":"W1530581289","doi":"10.1007/978-3-642-15705-9_74","title":"Fast and Accurate Reconstruction of HARDI Data Using Compressed Sensing","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Computer science; Compressed sensing; Diffusion MRI; Diffusion; Pattern recognition (psychology); Artificial intelligence; Data mining; Magnetic resonance imaging","score_opus":0.09438748449517516,"score_gpt":0.3712630114860339,"score_spread":0.27687552699085877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1530581289","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36085835,0.000007667305,0.6386575,0.0002625361,0.000098491786,0.000084072584,0.000002495143,0.000024799412,0.0000040642826],"genre_scores_gemma":[0.5267759,0.0000026258713,0.47309282,0.00008834679,0.00003644753,1.6016457e-7,0.0000012082346,0.000002462959,5.8248602e-8],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993309,0.000007518773,0.00012503636,0.0003188104,0.0001038953,0.000113883245],"domain_scores_gemma":[0.99921584,0.0000756845,0.00006474333,0.000537309,0.00006725109,0.00003918094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016350647,0.00006228762,0.00011578266,0.00009841343,0.00007704611,0.000027241334,0.00018084356,0.00002682092,0.0000012467971],"category_scores_gemma":[0.00008449955,0.000054283428,0.000008101563,0.00037220356,0.00043275536,0.0001865164,0.000243167,0.00020681995,1.3633907e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037236575,0.0000074641416,0.0029148373,0.000011193897,8.1754274e-7,0.0000022398394,0.000051227955,0.0016286881,0.47391742,0.000020045347,9.487535e-7,0.5214414],"study_design_scores_gemma":[0.00012408881,0.0000153329,0.0034768577,0.000063426676,0.0000052361856,0.00037661672,4.6717653e-7,0.88498294,0.10911477,0.0017592655,0.000029543993,0.000051469808],"about_ca_topic_score_codex":0.000026465681,"about_ca_topic_score_gemma":0.000009782703,"teacher_disagreement_score":0.88335425,"about_ca_system_score_codex":0.0000088440365,"about_ca_system_score_gemma":0.000053424425,"threshold_uncertainty_score":0.22136138},"labels":[],"label_agreement":null},{"id":"W1533378118","doi":"10.1007/978-3-642-15705-9_71","title":"Symmetric Positive-Definite Cartesian Tensor Orientation Distribution Functions (CT-ODF)","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cartesian coordinate system; Tensor (intrinsic definition); Cartesian tensor; Diffusion MRI; Orientation (vector space); Tensor field; Parametrization (atmospheric modeling); Computer science; Positive-definite matrix; Mathematical analysis; Mathematics; Pure mathematics; Geometry; Physics; Tensor density; Exact solutions in general relativity; Optics","score_opus":0.023883811653267608,"score_gpt":0.3153876280106692,"score_spread":0.29150381635740163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1533378118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20204023,0.000010228065,0.79517287,0.0020335063,0.00027656983,0.00025436658,0.000015665193,0.00013893795,0.00005766178],"genre_scores_gemma":[0.88239557,0.000003619495,0.11669134,0.0006808633,0.00013920262,0.000024352516,0.000052876476,0.000008218477,0.000003967988],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99886316,0.0000130181,0.00016575727,0.00045524063,0.00024626596,0.00025657468],"domain_scores_gemma":[0.999107,0.00015697267,0.000060025053,0.00040241185,0.00017100577,0.00010258852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017241188,0.000115920826,0.00012379067,0.00025220905,0.00024354486,0.000057586294,0.00016706913,0.000033149056,0.000008384558],"category_scores_gemma":[0.0002384048,0.00010156787,0.000038289254,0.0023587348,0.000286971,0.0001736861,0.000068250796,0.00040286672,0.000016039665],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028967883,0.00030626703,0.07578608,0.00002372474,0.0000059989616,0.00005590983,0.00024288763,0.0021795917,0.102158986,0.0065976577,0.00010992893,0.812504],"study_design_scores_gemma":[0.0011261948,0.0005386336,0.57360166,0.0001140963,0.00005700139,0.0010474741,0.0000036762783,0.28245866,0.11770021,0.019255351,0.0035296613,0.00056737167],"about_ca_topic_score_codex":0.000031455904,"about_ca_topic_score_gemma":0.0000139341055,"teacher_disagreement_score":0.8119366,"about_ca_system_score_codex":0.00008054668,"about_ca_system_score_gemma":0.000088990564,"threshold_uncertainty_score":0.41418177},"labels":[],"label_agreement":null},{"id":"W1536516995","doi":"10.1016/b978-0-444-53355-5.00014-2","title":"Real-time functional magnetic imaging—brain–computer interface and virtual reality","year":2011,"lang":"en","type":"review","venue":"Progress in brain research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec en Outaouais; Université du Québec à Montréal; Université du Québec à Trois-Rivières; Institut Philippe Pinel de Montréal","funders":"Solar Energy Technologies Office; Canadian Institutes of Health Research","keywords":"Virtual reality; Brain–computer interface; Interface (matter); Computer science; Human–computer interaction; Functional Brain Imaging; Computer graphics (images); Psychology; Neuroscience; Neuroimaging; Operating system; Electroencephalography","score_opus":0.25519859627306263,"score_gpt":0.5071566394127673,"score_spread":0.2519580431397047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536516995","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038673697,0.99014205,0.00092668046,0.0040689735,0.00005609351,0.0027378048,0.00004215188,0.00028514647,0.0017024498],"genre_scores_gemma":[0.000048406862,0.9863691,0.008542515,0.00011217444,0.00032235245,0.0013172704,0.00013455567,0.00012410476,0.0030295379],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.996413,0.0006057981,0.0006437483,0.0010963848,0.00053927995,0.00070181955],"domain_scores_gemma":[0.99728733,0.0011398706,0.00014093475,0.0009487259,0.00022886884,0.0002542805],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0019454521,0.00039599778,0.0010422389,0.00069392915,0.00014439288,0.00008117361,0.00040286337,0.00021826335,0.00022664323],"category_scores_gemma":[0.00025217296,0.00033518058,0.00016136542,0.00078213715,0.0011000165,0.00009372572,0.0008451625,0.0017240148,0.00010899803],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039697963,0.00019166998,0.00020803449,0.002786325,0.000017772205,0.00007030727,0.000045171993,5.7976756e-8,0.0000044564295,0.0016855295,0.027012575,0.9679384],"study_design_scores_gemma":[0.00035848503,0.00035647702,0.00088780414,0.00606158,0.000049186194,0.0003670598,0.00000657737,0.00032146682,0.0000031411575,0.0011382105,0.9901625,0.0002875096],"about_ca_topic_score_codex":0.000030667517,"about_ca_topic_score_gemma":0.0000014552559,"teacher_disagreement_score":0.9676509,"about_ca_system_score_codex":0.00021282153,"about_ca_system_score_gemma":0.0003083861,"threshold_uncertainty_score":0.99991},"labels":[],"label_agreement":null},{"id":"W1536611676","doi":"10.1002/hbm.22715","title":"Striatal shape abnormalities as novel neurodevelopmental endophenotypes in schizophrenia: A longitudinal study","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children; Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; National Human Genome Research Institute; University of Toronto; Government of Ontario; Weston Brain Institute; Alzheimer's Society; National Institute of Mental Health; Ontario Brain Institute; Michael J. Fox Foundation for Parkinson's Research","keywords":"Endophenotype; Psychology; Globus pallidus; Neuroscience; Schizophrenia (object-oriented programming); Basal ganglia; Cognition; Psychiatry; Central nervous system","score_opus":0.11409521056844762,"score_gpt":0.35374477765786844,"score_spread":0.2396495670894208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1536611676","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98968303,0.000010141229,0.0053894036,0.0008528319,0.00003361226,0.00070844614,0.00000424276,0.00026634333,0.0030519327],"genre_scores_gemma":[0.99108046,0.0000015370423,0.0075685796,0.0007322223,0.00013860187,0.00011800716,0.000024749566,0.000032880616,0.0003029298],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99866533,0.000040204366,0.00035102866,0.00043478125,0.00021910842,0.00028954187],"domain_scores_gemma":[0.9993536,0.00011610443,0.000086827386,0.00032853108,0.000034356563,0.00008057067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028980023,0.00019150123,0.00027687117,0.00023071935,0.00023589957,0.000040680363,0.00016292046,0.00003573328,0.00008419144],"category_scores_gemma":[0.0001509821,0.00019643095,0.00005133525,0.0002490832,0.00007199375,0.00012558869,0.00015040518,0.00032038853,0.000022979204],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040541042,0.0030629942,0.6527459,0.00028305882,0.00012450319,0.00016053236,0.005414891,0.00005303227,0.2020921,0.12076503,0.0018792228,0.013013314],"study_design_scores_gemma":[0.0027615102,0.00027176258,0.9895264,0.00011021157,0.00001504876,0.000070269525,0.0005956784,0.0002923514,0.00018535071,0.0026977032,0.0032402968,0.00023344325],"about_ca_topic_score_codex":0.000082814615,"about_ca_topic_score_gemma":0.00003290039,"teacher_disagreement_score":0.33678046,"about_ca_system_score_codex":0.00005796463,"about_ca_system_score_gemma":0.000037985163,"threshold_uncertainty_score":0.8010222},"labels":[],"label_agreement":null},{"id":"W1537667007","doi":"10.1097/00004647-200010000-00013","title":"Does Labeled α-Methyl-L-Tryptophan Image ONLY Blood–Brain Barrier Transport of Tryptophan?","year":2000,"lang":"en","type":"letter","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Tryptophan; Blood–brain barrier; Chemistry; Neuroscience; Biophysics; Biochemistry; Biology; Central nervous system; Amino acid","score_opus":0.015682009674359256,"score_gpt":0.286477622615402,"score_spread":0.27079561294104276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537667007","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3453166,0.01146069,0.0032429162,0.6289275,0.002287484,0.0030206959,0.0022888298,0.0004896952,0.002965547],"genre_scores_gemma":[0.029694678,0.009100526,0.38643724,0.516789,0.03364265,0.00015098517,0.0007861137,0.0011666691,0.022232141],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9943154,0.00023676392,0.002413551,0.0007501316,0.0014417793,0.00084237487],"domain_scores_gemma":[0.995581,0.0002455941,0.0017870966,0.0012371725,0.0007155803,0.00043357455],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00053496077,0.00094122166,0.0028950449,0.00083244004,0.00013342369,0.00004695408,0.0009316698,0.0007959191,0.001521548],"category_scores_gemma":[0.00017609297,0.00062438246,0.0016211199,0.0006579129,0.0003778731,0.0004248294,0.000062886465,0.004476045,0.000014066158],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010647281,0.002969476,0.0011518742,0.0019290091,0.004620456,0.008068724,0.000662075,0.000015501571,0.42930642,0.00039731103,0.52321947,0.026594948],"study_design_scores_gemma":[0.0064760977,0.00047132405,0.0016679906,0.00069124915,0.0068244897,0.0024647536,0.000017452967,0.000012053762,0.17080085,0.0028241624,0.80699617,0.00075342995],"about_ca_topic_score_codex":0.000025310315,"about_ca_topic_score_gemma":0.0000025994373,"teacher_disagreement_score":0.38319433,"about_ca_system_score_codex":0.00003278863,"about_ca_system_score_gemma":0.0006742948,"threshold_uncertainty_score":0.99962074},"labels":[],"label_agreement":null},{"id":"W1545733638","doi":"10.1111/j.1528-1167.2011.03149.x","title":"Diffusion tensor imaging in temporal lobe epilepsy","year":2011,"lang":"en","type":"review","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Temporal lobe; Diffusion MRI; White matter; Epilepsy; Neuroscience; Psychology; Neuroimaging; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.13661580210335458,"score_gpt":0.40329472578486264,"score_spread":0.26667892368150803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1545733638","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00001592145,0.990007,0.0018201891,0.00020392577,0.00011645977,0.0016967364,0.000034213215,0.00040347117,0.00570209],"genre_scores_gemma":[0.000099700184,0.9867408,0.010433821,0.00027971918,0.00021200108,0.00043649744,0.00023630877,0.00014436482,0.0014167682],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99782145,0.00007394126,0.00078890944,0.0007248724,0.00016342854,0.0004273957],"domain_scores_gemma":[0.9983786,0.00008106502,0.0003434109,0.0009815753,0.000047690017,0.00016769997],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001743804,0.00048684934,0.0015362293,0.00040030846,0.000067194545,0.000016852397,0.0002989762,0.00019307443,0.00020244956],"category_scores_gemma":[0.00007622094,0.00039254152,0.00043314524,0.00048824973,0.00010760631,0.00007714447,0.00017943821,0.0008554169,0.00025999403],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008722598,0.00019553039,0.0074602417,0.0025419835,0.000009458325,0.0001705711,0.00002103083,2.124801e-8,0.0000026944028,0.0012798439,0.004728156,0.9835817],"study_design_scores_gemma":[0.00025445296,0.000038934446,0.0017538944,0.009474771,0.0002407071,0.00035649145,0.0000048536394,0.000020678253,0.0000011664888,0.00060275476,0.9869089,0.00034236733],"about_ca_topic_score_codex":0.00005126704,"about_ca_topic_score_gemma":0.0000018840155,"teacher_disagreement_score":0.98323935,"about_ca_system_score_codex":0.00015987486,"about_ca_system_score_gemma":0.00014339347,"threshold_uncertainty_score":0.99985266},"labels":[],"label_agreement":null},{"id":"W1548276524","doi":"10.1007/978-3-540-85988-8_34","title":"Joint Segmentation of Thalamic Nuclei from a Population of Diffusion Tensor MR Images","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health","keywords":"Segmentation; Computer science; Artificial intelligence; Diffusion MRI; Population; Pattern recognition (psychology); Cluster analysis; Scale-space segmentation; Market segmentation; Image segmentation; Consistency (knowledge bases); Computer vision; Magnetic resonance imaging; Medicine","score_opus":0.042578165811634254,"score_gpt":0.31693476319321184,"score_spread":0.2743565973815776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548276524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5057341,0.000014969825,0.49387214,0.00021375927,0.000022029992,0.00011662358,0.0000025954726,0.000021078618,0.0000027361957],"genre_scores_gemma":[0.6850222,0.000018009998,0.31480783,0.000115973875,0.00002211366,0.0000031076668,0.000006494212,0.000003924025,4.1199635e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99923265,0.000011679538,0.00020918071,0.00023325307,0.00021723221,0.00009602404],"domain_scores_gemma":[0.99945885,0.00006261937,0.00012043624,0.00025596365,0.00007654029,0.000025571338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006774433,0.00006850846,0.00015372824,0.00013979146,0.000053180247,0.0000040743753,0.000107116226,0.000024477935,0.000004981356],"category_scores_gemma":[0.00005227846,0.000056272584,0.000029590488,0.00044236862,0.00020706233,0.000092836286,0.00006811811,0.000083950865,5.356082e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011209363,0.00008191932,0.15931436,0.000015793968,0.0000012556492,0.00000392053,0.00041515837,0.0019499441,0.7887014,0.000021990061,0.000004408663,0.049478598],"study_design_scores_gemma":[0.00021254773,0.000073394,0.54908437,0.00007719713,0.0000045046754,0.000018885568,7.0935005e-7,0.054955404,0.39196888,0.0035574634,0.0000015822518,0.000045034893],"about_ca_topic_score_codex":0.00016536671,"about_ca_topic_score_gemma":0.0000025654965,"teacher_disagreement_score":0.39673254,"about_ca_system_score_codex":0.000036988204,"about_ca_system_score_gemma":0.000026491703,"threshold_uncertainty_score":0.22947294},"labels":[],"label_agreement":null},{"id":"W1548601077","doi":"10.1002/hbm.22145","title":"A longitudinal study of the relationship between personality traits and the annual rate of volume changes in regional gray matter in healthy adults","year":2012,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Cancer Institute; National Institute of Mental Health; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Psychology; Openness to experience; Personality; Extraversion and introversion; Big Five personality traits; Agreeableness; Inferior parietal lobule; Neuroticism; Conscientiousness; Brain size; Lateralization of brain function; Developmental psychology; Cognition; Neuroscience; Magnetic resonance imaging; Social psychology; Medicine","score_opus":0.1885079530509189,"score_gpt":0.3825435778354087,"score_spread":0.1940356247844898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548601077","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9784796,0.000072445175,0.00012797266,0.02044351,0.0000045190227,0.0008047098,0.000008736234,0.000010439431,0.000048057253],"genre_scores_gemma":[0.9989724,0.0000018661758,0.00015367025,0.00068294274,0.000054341705,0.00007506286,0.0000034096217,0.000008174282,0.00004810048],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99912125,0.00021782167,0.0002593222,0.00014797329,0.00010849494,0.0001451564],"domain_scores_gemma":[0.99921554,0.00040759094,0.00015203342,0.00016174087,0.00003339852,0.000029718025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007961404,0.00007726284,0.00020735375,0.000092590584,0.000099158766,0.0000028780476,0.00008533196,0.000028096121,0.000006899964],"category_scores_gemma":[0.00011110099,0.00005141385,0.000028119417,0.00024624445,0.00018620255,0.00005611163,0.00005237136,0.00023681676,3.9791175e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096092794,0.00012232517,0.98701483,0.00007644024,0.000004490331,2.789507e-7,0.010307399,5.3163586e-7,0.00009127405,0.001994606,0.00022367736,0.00006807981],"study_design_scores_gemma":[0.0016929072,0.00008377032,0.99418205,0.00018924208,0.000010818712,0.0000047844114,0.0020126149,0.000007826359,0.0000021839744,0.0016022003,0.00016806093,0.000043532895],"about_ca_topic_score_codex":0.00030187346,"about_ca_topic_score_gemma":0.00033423674,"teacher_disagreement_score":0.020492822,"about_ca_system_score_codex":0.000023482136,"about_ca_system_score_gemma":0.000011167595,"threshold_uncertainty_score":0.20965959},"labels":[],"label_agreement":null},{"id":"W1548679134","doi":"10.1002/mrm.24987","title":"Oscillating gradient spin‐echo (OGSE) diffusion tensor imaging of the human brain","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Innovates; Fondation pour la Recherche Médicale","keywords":"Diffusion MRI; White matter; Nuclear magnetic resonance; Splenium; Corpus callosum; Fractional anisotropy; Spin echo; Human brain; Cingulum (brain); Physics; Nuclear medicine; Magnetic resonance imaging; Chemistry; Medicine; Anatomy; Neuroscience; Psychology; Radiology","score_opus":0.03501310678795453,"score_gpt":0.33755879262844846,"score_spread":0.3025456858404939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548679134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95432633,0.0023161883,0.00038377914,0.03604222,0.000073858646,0.0012556667,0.0000018204707,0.00008540407,0.0055147316],"genre_scores_gemma":[0.9915326,0.00015162634,0.0038055317,0.002459473,0.00011976116,0.00013271744,0.0000035321907,0.00002859252,0.0017661396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984472,0.00004610469,0.0005281166,0.00033403168,0.0003548963,0.00028965835],"domain_scores_gemma":[0.99886215,0.00012033718,0.00016040812,0.00067661726,0.00010126678,0.00007922434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023450413,0.00016711833,0.00034158825,0.00012233348,0.00010496734,0.0000057852603,0.0002308357,0.000037552694,0.0002658119],"category_scores_gemma":[0.00041850895,0.00010508087,0.000057386867,0.0004905732,0.00042056266,0.000044530418,0.00011968433,0.00031763848,0.0000060585294],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009471474,0.00011948003,0.6210673,0.0000906256,0.0000012805037,0.000013030942,0.000487008,0.000003712295,0.23558156,0.0012554091,0.009165733,0.1322054],"study_design_scores_gemma":[0.0011897594,0.00020873896,0.970261,0.0011138243,0.000017185595,0.00005170863,0.00021147632,0.002580584,0.0011490334,0.0044674366,0.018637642,0.00011162342],"about_ca_topic_score_codex":0.0005181432,"about_ca_topic_score_gemma":0.000011295413,"teacher_disagreement_score":0.3491937,"about_ca_system_score_codex":0.000055532404,"about_ca_system_score_gemma":0.000018735054,"threshold_uncertainty_score":0.42850736},"labels":[],"label_agreement":null},{"id":"W1555964684","doi":"10.1111/j.1753-4887.2010.00327.x","title":"A primer for brain imaging: a tool for evidence-based studies of nutrition?","year":2010,"lang":"en","type":"review","venue":"Nutrition Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institutes of Health; Canadian Institutes of Health Research; FrieslandCampina; Pfizer; European Commission; Royal Society; Danone; PepsiCo","keywords":"Magnetoencephalography; Brain function; Brain Structure and Function; Neuroimaging; Observational study; Brain activity and meditation; Neuroscience; Psychology; Human brain; Functional Brain Imaging; Functional magnetic resonance imaging; Randomized controlled trial; Magnetic resonance imaging; Brain aging; Electroencephalography; Medicine; Pathology; Cognition; Radiology","score_opus":0.4072667511973302,"score_gpt":0.5307548116773119,"score_spread":0.12348806047998168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555964684","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.1889856e-7,0.9371459,0.030295214,0.0056298664,0.00009236963,0.02634514,0.00035366754,0.00012555261,0.000012070071],"genre_scores_gemma":[1.7869935e-7,0.7387215,0.21150728,0.0008418901,0.0003835915,0.047888774,0.00042968584,0.000067021094,0.00016007373],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99735653,0.00011531199,0.001467708,0.0006267158,0.00016878666,0.00026496078],"domain_scores_gemma":[0.9958231,0.0015235215,0.0010651703,0.00085396477,0.000654091,0.00008014104],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00086615764,0.00044639062,0.0030392006,0.0002691709,0.00011313047,0.000016177097,0.00022554668,0.0001861729,0.0000144993455],"category_scores_gemma":[0.002735629,0.00034950918,0.0016500494,0.00039018437,0.00016768598,0.00011168713,0.00003252466,0.00034685744,0.000008379383],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026033083,0.00059928204,6.626181e-7,0.21921363,0.000028699327,6.766498e-7,0.0000028621712,4.0763344e-9,0.0001286331,0.0011388917,0.10590857,0.67295206],"study_design_scores_gemma":[0.00089027046,0.00020397299,2.0016033e-7,0.16280606,0.0014582142,0.000032947464,0.0000025990798,0.0000070532737,0.00014964447,0.0014186428,0.83278805,0.00024232276],"about_ca_topic_score_codex":5.3168725e-7,"about_ca_topic_score_gemma":2.934468e-7,"teacher_disagreement_score":0.7268795,"about_ca_system_score_codex":0.00010179597,"about_ca_system_score_gemma":0.00019086064,"threshold_uncertainty_score":0.9998957},"labels":[],"label_agreement":null},{"id":"W1557791310","doi":"10.1002/jmri.24424","title":"Symmetry of the fornix using diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; National Research Council Canada; National Research Council Institute for Biodiagnostics; University of Winnipeg; Alberta Innovates","funders":"Manitoba Health Research Council","keywords":"Tractography; Fornix; Diffusion MRI; Fractional anisotropy; Physics; Magnetic resonance imaging; Nuclear magnetic resonance; Symmetry (geometry); Medicine; Mathematics; Psychology; Radiology; Neuroscience; Geometry","score_opus":0.029181777633138926,"score_gpt":0.31313057351235196,"score_spread":0.283948795879213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1557791310","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9660914,0.0121271005,0.010708147,0.009244675,0.00018128956,0.00054498273,0.0000036212325,0.00003466295,0.001064134],"genre_scores_gemma":[0.9477194,0.00025318115,0.050749928,0.0008659603,0.00014404209,0.000006013807,2.3473731e-7,0.00003116665,0.00023007239],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986292,0.00003614686,0.0005859023,0.0001495722,0.00036947484,0.00022970997],"domain_scores_gemma":[0.99852,0.00008142959,0.0005154672,0.0003922021,0.00040516505,0.000085739804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019173982,0.00013654427,0.00029208302,0.00013581669,0.00010240676,0.000026985124,0.0002604633,0.000019907327,0.00007383066],"category_scores_gemma":[0.0002039367,0.00008878957,0.00019070375,0.00031303952,0.00018016949,0.00020856167,0.000113083704,0.0003502314,0.0000027006815],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030240186,0.00012501428,0.5031357,0.00005476746,0.0000037824261,0.000026633932,0.00007105748,0.0000117386035,0.20125245,0.0001647452,0.0027260014,0.29239792],"study_design_scores_gemma":[0.0014936671,0.000110754896,0.91609794,0.001426859,0.00015932812,0.0030819075,0.0002702923,0.026929025,0.013229278,0.0048488122,0.032141488,0.00021064816],"about_ca_topic_score_codex":0.000032025917,"about_ca_topic_score_gemma":1.4201679e-7,"teacher_disagreement_score":0.4129623,"about_ca_system_score_codex":0.000061030845,"about_ca_system_score_gemma":0.00007432167,"threshold_uncertainty_score":0.36207336},"labels":[],"label_agreement":null},{"id":"W1565146755","doi":"10.71781/32272","title":"Anatomo-functional magnetic resonance imaging of the spinal cord and its application to the characterization of spinal lesions in cats","year":2008,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Université de Montréal; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale","keywords":"Spinal cord; White matter; Spinal cord injury; Magnetic resonance imaging; Medicine; Central nervous system; Neuroscience; Diffusion MRI; Functional magnetic resonance imaging; Paralysis; Psychology; Radiology; Surgery","score_opus":0.05947184844213551,"score_gpt":0.37398807487980196,"score_spread":0.31451622643766647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565146755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99387467,0.00084294943,0.0005000129,0.0016078178,0.000057515335,0.0022744627,0.000065205495,0.0000029662226,0.0007744101],"genre_scores_gemma":[0.99686235,0.0002742415,0.0009763838,0.00009647557,0.00003664205,0.0002577308,0.00022581304,0.000019795843,0.0012505766],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99900997,0.000025105308,0.0003465199,0.000313515,0.00020055422,0.00010431535],"domain_scores_gemma":[0.9991533,0.000012884019,0.00027089997,0.00036250212,0.00016452055,0.00003585347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010460675,0.00013013187,0.00021642816,0.00009973774,0.000104058694,0.000010586979,0.00026205683,0.000053681753,0.000027945096],"category_scores_gemma":[0.000045228524,0.00009503236,0.00003757987,0.0004257808,0.000050055394,0.00006693747,0.00008123573,0.00020376424,0.000004978727],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001001537,0.00015298616,0.0041800593,0.00008158568,0.000003622176,0.0000025809188,0.00022807415,0.0000037944956,0.22803062,0.00040361148,0.00008061265,0.76583093],"study_design_scores_gemma":[0.00028905738,0.0001879281,0.935821,0.0007750907,0.00004623755,0.000044532313,0.00008793444,0.0003582552,0.043876763,0.00007129201,0.018333923,0.00010796484],"about_ca_topic_score_codex":0.000045106623,"about_ca_topic_score_gemma":0.00006338971,"teacher_disagreement_score":0.931641,"about_ca_system_score_codex":0.000032430482,"about_ca_system_score_gemma":0.00014246324,"threshold_uncertainty_score":0.3875307},"labels":[],"label_agreement":null},{"id":"W1565314341","doi":"10.1136/thoraxjnl-2011-201054b.92","title":"S92 Cognitive function &amp; cerebral white matter tract microstructure in COPD","year":2011,"lang":"en","type":"article","venue":"Thorax","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Medicine; Diffusion MRI; Cardiology; COPD; Grey matter; Internal medicine; Cognition; Working memory; Montreal Cognitive Assessment; Pathology; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.07821473167748443,"score_gpt":0.3400433047447701,"score_spread":0.2618285730672857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1565314341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9526661,0.000068914014,0.021791967,0.0010134607,0.00007344165,0.0005968834,0.00003625553,0.00021105225,0.023541903],"genre_scores_gemma":[0.98628575,0.0000058100272,0.009697592,0.0020066502,0.000054837885,0.000040102925,0.000060389055,0.000023558752,0.0018253127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99943346,0.000015709176,0.00013061083,0.00020692707,0.00006272678,0.0001505476],"domain_scores_gemma":[0.99966115,0.00001216045,0.00004595097,0.0001907424,0.000039530092,0.00005048852],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004172614,0.00010017393,0.00012919535,0.000067552864,0.000032880853,0.000006019395,0.000043507865,0.00005742051,0.0010053589],"category_scores_gemma":[0.000008528125,0.000088432666,0.000037062662,0.0001443989,0.000051294875,0.00006916906,0.000021313843,0.00023654639,0.00023740731],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038532162,0.00022633403,0.9695901,0.000044869215,0.00001218487,0.000021949038,0.0008412101,4.6800494e-7,0.012233181,0.00034338303,0.011225728,0.0050752433],"study_design_scores_gemma":[0.000475419,0.000056939807,0.9826292,0.00006575436,0.00005121666,0.000104248604,0.000065396714,0.00000656055,0.003431712,0.0030688404,0.009935517,0.00010919081],"about_ca_topic_score_codex":0.00001918616,"about_ca_topic_score_gemma":0.0000104304845,"teacher_disagreement_score":0.033619624,"about_ca_system_score_codex":0.000018822839,"about_ca_system_score_gemma":0.0000131470615,"threshold_uncertainty_score":0.99990785},"labels":[],"label_agreement":null},{"id":"W1576590016","doi":"10.1002/mrm.25093","title":"Comparison of sampling strategies and sparsifying transforms to improve compressed sensing diffusion spectrum imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Undersampling; Compressed sensing; Computer science; Sampling (signal processing); Algorithm; Artificial intelligence; Wavelet; Pattern recognition (psychology); Computer vision","score_opus":0.06568937023446123,"score_gpt":0.3810956298662001,"score_spread":0.31540625963173885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1576590016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7025083,0.0030891425,0.28419384,0.0077360617,0.000065847475,0.00076910545,0.0000021872554,0.00010051824,0.0015350523],"genre_scores_gemma":[0.95105267,0.00020808658,0.048176497,0.00040070456,0.00009095222,0.000012394156,0.000004701908,0.000023144936,0.00003086802],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986074,0.000024513343,0.00049855607,0.00036021514,0.00023622885,0.00027307885],"domain_scores_gemma":[0.99925804,0.00017231716,0.000091730435,0.0003241987,0.000044176235,0.00010950894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025042397,0.00017192494,0.00053935923,0.00018361649,0.000061837854,0.000013917252,0.00008755318,0.00003606883,0.000013866019],"category_scores_gemma":[0.00011214896,0.00014036773,0.000025291434,0.00028769445,0.00021138285,0.0000696348,0.000044562395,0.00025234188,7.117997e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001367538,0.000076681994,0.038942162,0.00023697222,0.0000014996634,0.000007458169,0.0013034145,0.000080026126,0.36578774,0.0015306533,0.00007480991,0.5918218],"study_design_scores_gemma":[0.006442719,0.0025904973,0.5944306,0.0054317825,0.00012523508,0.0001281737,0.00443085,0.28523642,0.04063219,0.01774832,0.042165082,0.00063807797],"about_ca_topic_score_codex":0.00019762246,"about_ca_topic_score_gemma":0.000025587688,"teacher_disagreement_score":0.5911837,"about_ca_system_score_codex":0.000026729087,"about_ca_system_score_gemma":0.000018467223,"threshold_uncertainty_score":0.572403},"labels":[],"label_agreement":null},{"id":"W1578806482","doi":"10.1002/syn.21765","title":"Quantitative imaging of neuroinflammation in human white matter: A positron emission tomography study with translocator protein 18 kDa radioligand, [<sup>18</sup>F]‐FEPPA","year":2014,"lang":"en","type":"article","venue":"Synapse","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Translocator protein; Positron emission tomography; Radioligand; White matter; Nuclear medicine; Fractional anisotropy; Diffusion MRI; Binding potential; Corpus callosum; Internal capsule; Magnetic resonance imaging; Nuclear magnetic resonance; Psychology; Chemistry; Neuroscience; Medicine; Pathology; Neuroinflammation; Internal medicine; Physics; Radiology; Receptor","score_opus":0.023151158286920333,"score_gpt":0.3166299127115478,"score_spread":0.29347875442462745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1578806482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98285484,0.000032668,0.013062786,0.0010826177,0.0000047779527,0.0021984193,0.000006770158,0.00013126472,0.0006258253],"genre_scores_gemma":[0.993116,0.000002536527,0.0063651237,0.0000741284,0.00002195965,0.0002719496,0.000024447456,0.0000451246,0.00007873519],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99858373,0.00012109365,0.00041413037,0.00041568835,0.00023039282,0.00023496465],"domain_scores_gemma":[0.99912894,0.000038368697,0.00017723125,0.0004747898,0.00008888474,0.000091786875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024295376,0.00021322722,0.00036078488,0.00032405896,0.00009323231,0.000016031088,0.00013398947,0.00003503622,0.000031901935],"category_scores_gemma":[0.000023728406,0.000177418,0.000068142086,0.0004733072,0.000110959496,0.00014863293,0.00002659592,0.00025284674,0.0000034466684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070226757,0.0008398538,0.527316,0.00025567002,0.000032235013,0.0000360519,0.001806935,0.00021972384,0.46708637,0.0005735247,0.00027017496,0.00086121063],"study_design_scores_gemma":[0.012416342,0.008688228,0.61922216,0.0026233532,0.00045144162,0.00023670694,0.0028114852,0.019853346,0.3283228,0.0035437548,0.0005843458,0.0012460328],"about_ca_topic_score_codex":0.00006255278,"about_ca_topic_score_gemma":0.0000089231025,"teacher_disagreement_score":0.13876356,"about_ca_system_score_codex":0.000029986015,"about_ca_system_score_gemma":0.000024504387,"threshold_uncertainty_score":0.7234896},"labels":[],"label_agreement":null},{"id":"W1581093187","doi":"10.1002/hbm.22620","title":"A DTI-based tractography study of effects on brain structure associated with prenatal alcohol exposure in newborns","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital","funders":"National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; South African Medical Research Council","keywords":"Tractography; Fractional anisotropy; Diffusion MRI; White matter; Neuroimaging; Prenatal alcohol exposure; Psychology; Neuroscience; Medicine; Pregnancy; Magnetic resonance imaging; Biology; Radiology","score_opus":0.04296533638788373,"score_gpt":0.3226505155792089,"score_spread":0.27968517919132513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581093187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931339,0.000007064433,0.0034182544,0.0015789914,0.000009645623,0.0014280338,0.0000071608056,0.00019287957,0.00022409421],"genre_scores_gemma":[0.99677694,1.3624116e-7,0.0012197,0.0017421275,0.000039402294,0.00010044667,0.00005006935,0.000039674065,0.00003152855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986999,0.0001491132,0.0002738417,0.00038360734,0.00026098161,0.00023252457],"domain_scores_gemma":[0.998584,0.0006394777,0.00018924053,0.00046717536,0.000052043066,0.00006809038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022457396,0.00020223632,0.0003613487,0.0003610121,0.00010368795,0.0000132422265,0.00013389313,0.00007556877,0.000007918808],"category_scores_gemma":[0.00031980933,0.00017257954,0.000060161885,0.00054548116,0.00005612436,0.000044805336,0.000021631678,0.00038689253,3.818394e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028032082,0.0030315442,0.5404529,0.00060301,0.00017062381,0.000108228225,0.0031369396,0.0007638436,0.4406271,0.0017679419,0.0017630024,0.0072945664],"study_design_scores_gemma":[0.0062096706,0.0027988192,0.9838511,0.0010876129,0.000037103033,0.000004430166,0.00019461112,0.00041735498,0.003948676,0.0007609807,0.00047059075,0.00021909972],"about_ca_topic_score_codex":0.000020340482,"about_ca_topic_score_gemma":0.000100619516,"teacher_disagreement_score":0.44339818,"about_ca_system_score_codex":0.000037750022,"about_ca_system_score_gemma":0.000019675015,"threshold_uncertainty_score":0.703759},"labels":[],"label_agreement":null},{"id":"W1583057043","doi":"10.1002/mrm.24325","title":"Oscillating and pulsed gradient diffusion magnetic resonance microscopy over an extended<i>b</i>‐value range: Implications for the characterization of tissue microstructure","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Institute of Biomedical Imaging and Bioengineering; University of Florida","keywords":"Spin echo; Diffusion; Nuclear magnetic resonance; Effective diffusion coefficient; Resolution (logic); Materials science; Analytical Chemistry (journal); Characterization (materials science); Chemistry; Magnetic resonance imaging; Physics; Nanotechnology; Computer science; Thermodynamics","score_opus":0.02941873910434306,"score_gpt":0.35205289786474825,"score_spread":0.3226341587604052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583057043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95065457,0.03423272,0.0055142767,0.0065728524,0.00011888009,0.0026727282,0.00007791709,0.00006570929,0.000090328926],"genre_scores_gemma":[0.977278,0.004996088,0.014897524,0.0013528395,0.00036310777,0.00050343026,0.00009042156,0.00005729924,0.00046127453],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99849087,0.00004892238,0.0005110305,0.0003888422,0.00018629458,0.00037405879],"domain_scores_gemma":[0.99873155,0.00022179609,0.000175683,0.00063734496,0.00010664726,0.0001270042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003389504,0.00022383366,0.00038313694,0.00011009225,0.00018441491,0.000010194518,0.00016979051,0.000089165536,0.000053572392],"category_scores_gemma":[0.00019906383,0.000154773,0.000033498673,0.00041199854,0.00039928046,0.000103962724,0.0000595505,0.00021010655,4.058395e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001109694,0.00009840023,0.07870598,0.000089379464,9.902465e-7,6.712125e-7,0.00061203697,7.495919e-7,0.6931001,0.0010622748,0.00018282303,0.22603561],"study_design_scores_gemma":[0.0015186656,0.00060737465,0.9024081,0.0002829337,0.00006125816,0.0000650071,0.000053181324,0.0012001363,0.0045864675,0.0008280138,0.088256106,0.00013275664],"about_ca_topic_score_codex":0.00007731942,"about_ca_topic_score_gemma":0.000010164782,"teacher_disagreement_score":0.8237021,"about_ca_system_score_codex":0.000042839376,"about_ca_system_score_gemma":0.000023475726,"threshold_uncertainty_score":0.631146},"labels":[],"label_agreement":null},{"id":"W1585992480","doi":"10.1007/978-3-642-04271-3_96","title":"A New Approach for Creating Customizable Cytoarchitectonic Probabilistic Maps without a Template","year":2009,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Institute of Biomedical Imaging and Bioengineering; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Computer science; Probabilistic logic; Pairwise comparison; Artificial intelligence; Pattern recognition (psychology); Computer vision; Image registration; Image (mathematics)","score_opus":0.04725669324274098,"score_gpt":0.3433014189683457,"score_spread":0.2960447257256047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1585992480","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004099724,0.000028969596,0.99272317,0.0017226003,0.00002715743,0.0010089395,0.0000013453816,0.00019636838,0.0001917487],"genre_scores_gemma":[0.4251944,0.0000013245473,0.5740163,0.00065425894,0.00008335066,0.000029575123,0.000003019676,0.000006737028,0.000011033272],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868137,0.000010601175,0.00018878015,0.00058294396,0.00017390947,0.00036237674],"domain_scores_gemma":[0.9991816,0.00012776244,0.000059984897,0.00045004528,0.00006316523,0.00011743562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025215294,0.00013885282,0.0002132319,0.00016154017,0.00016989416,0.00006169478,0.00029159838,0.00003832912,0.0000029774199],"category_scores_gemma":[0.00019591284,0.000113843926,0.000044887707,0.00082976004,0.00013393164,0.0000912605,0.000060456987,0.00021548037,0.000001845042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009163122,0.00014947109,0.0010378672,0.00008110003,0.0000031752313,0.000006369275,0.0005674155,0.10688086,0.017284207,0.001184125,0.00011140387,0.8726024],"study_design_scores_gemma":[0.0006939684,0.0002892213,0.00064380135,0.000116433745,0.000012702355,0.00016755516,4.005379e-7,0.935401,0.009524738,0.052686553,0.0002966768,0.00016693426],"about_ca_topic_score_codex":0.000014529755,"about_ca_topic_score_gemma":0.0000015036707,"teacher_disagreement_score":0.87243545,"about_ca_system_score_codex":0.0000972716,"about_ca_system_score_gemma":0.0002178705,"threshold_uncertainty_score":0.46424204},"labels":[],"label_agreement":null},{"id":"W1586285828","doi":"10.3233/jad-2012-121156","title":"MRI Signatures of Brain Macrostructural Atrophy and Microstructural Degradation in Frontotemporal Lobar Degeneration Subtypes","year":2012,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Northern California Institute for Research and Education; U.S. Department of Veterans Affairs","keywords":"Frontotemporal lobar degeneration; Atrophy; White matter; Fractional anisotropy; Frontotemporal dementia; Diffusion MRI; Magnetic resonance imaging; Semantic dementia; Pathology; Medicine; Psychology; Dementia; Neuroscience; Radiology; Disease","score_opus":0.0342027077982406,"score_gpt":0.3304098974408907,"score_spread":0.29620718964265014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586285828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98681146,0.010385275,0.000725069,0.0017782415,0.00008072833,0.00017979482,0.0000198206,0.0000097104485,0.000009929218],"genre_scores_gemma":[0.9814862,0.000081996586,0.017950956,0.00026727267,0.00016898316,0.0000022482488,0.000022297132,0.000012087764,0.000007950726],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992366,0.000033481585,0.00034697517,0.000091879534,0.00015752377,0.00013357803],"domain_scores_gemma":[0.9992928,0.000022793658,0.00027129357,0.00011661442,0.0001020478,0.00019443789],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010237613,0.0001028706,0.00020019086,0.00011408311,0.000032486318,0.00001096024,0.000050744256,0.000036877416,0.000013802918],"category_scores_gemma":[0.000049289225,0.00008101583,0.00007600397,0.000098392076,0.00007428303,0.00030624765,0.000020570373,0.00015929832,3.366551e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009945827,0.00015995094,0.6992023,0.000059195696,0.0000942558,0.000032412016,0.000244347,0.000098826415,0.2857727,0.0010905009,0.0025109402,0.009739943],"study_design_scores_gemma":[0.00088890485,0.000107961656,0.9565722,0.000058377565,0.00027225213,0.00009971412,0.000030862182,0.00022853252,0.040052846,0.0010572263,0.00052832643,0.00010279835],"about_ca_topic_score_codex":0.000011461594,"about_ca_topic_score_gemma":0.0000018223571,"teacher_disagreement_score":0.25736988,"about_ca_system_score_codex":0.00002186856,"about_ca_system_score_gemma":0.0000536427,"threshold_uncertainty_score":0.33037296},"labels":[],"label_agreement":null},{"id":"W1586359640","doi":"10.3171/2014.12.jns142690","title":"Letter to the Editor: Correlation of diffusion tensor imaging and intraoperative macrostimulation","year":2015,"lang":"en","type":"letter","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medtronic Europe; London Health Sciences Centre; Boston Scientific Corporation; Case Western Reserve University","keywords":"Medicine; Diffusion MRI; Intraoperative neurophysiological monitoring; Medical physics; Radiology; Magnetic resonance imaging; Surgery","score_opus":0.04195500756839228,"score_gpt":0.3228766359568912,"score_spread":0.28092162838849893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586359640","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017467042,0.00018294228,0.009372089,0.96974874,0.0026061377,0.00050119177,0.000030116018,0.000028170562,0.000063548],"genre_scores_gemma":[0.07931824,0.00020370916,0.0022482637,0.87765807,0.03983804,0.000016128519,0.000044413566,0.000097576376,0.0005755522],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.998513,0.00008809835,0.0006093073,0.0001808968,0.00046310772,0.0001455855],"domain_scores_gemma":[0.99803287,0.0003862173,0.0006846449,0.00026191582,0.0005605654,0.00007380498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029750922,0.00017634539,0.00041427294,0.00030436472,0.00006669376,0.000030558964,0.0000976518,0.00012126259,0.0000061032274],"category_scores_gemma":[0.00039709284,0.00011409875,0.00012093268,0.00020556181,0.00008273079,0.00012404035,0.000060615974,0.0013077834,0.0000023886153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007715271,0.000022073653,0.004491984,0.000032013788,0.000008699889,0.00012495984,0.00007296659,0.00009597828,0.004220725,0.0000012980507,0.98901016,0.0018419971],"study_design_scores_gemma":[0.00024845847,0.0001523397,0.007320344,0.0002741157,0.00010812195,0.00067266513,0.0000066354687,0.00094269187,0.00025162083,0.00009665853,0.9898248,0.00010155591],"about_ca_topic_score_codex":0.0000022889426,"about_ca_topic_score_gemma":8.393343e-8,"teacher_disagreement_score":0.09209068,"about_ca_system_score_codex":0.000048533573,"about_ca_system_score_gemma":0.00007210179,"threshold_uncertainty_score":0.5681741},"labels":[],"label_agreement":null},{"id":"W1588899353","doi":"10.1016/j.neuroimage.2015.06.040","title":"White matter atlas of the human spinal cord with estimation of partial volume effect","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"Atlas (anatomy); White matter; Segmentation; Brain atlas; Computer science; Voxel; Partial volume; Artificial intelligence; Magnetization transfer; Pattern recognition (psychology); Cartography; Anatomy; Magnetic resonance imaging; Medicine; Geography; Radiology","score_opus":0.051300732631459865,"score_gpt":0.35632173538735296,"score_spread":0.3050210027558931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588899353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98788595,0.000006458275,0.00803005,0.0015058541,0.00002620017,0.00047975397,0.000006771898,0.000055675726,0.00200331],"genre_scores_gemma":[0.99476224,4.9106814e-7,0.004458873,0.00020640151,0.000027721293,0.000026035066,0.000005587794,0.000020369867,0.00049226364],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99931175,0.00003819432,0.00017945922,0.00016365833,0.00020356035,0.00010335735],"domain_scores_gemma":[0.99925035,0.000013125521,0.00014810431,0.00046174193,0.0000754077,0.000051266314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007814011,0.00009380423,0.00017854561,0.00003346126,0.000034726887,0.0000052611113,0.000108406304,0.000021089243,0.000022702088],"category_scores_gemma":[0.00003115899,0.00005994374,0.00005021458,0.000157425,0.00016665393,0.000055106913,0.000050281666,0.00013703098,0.000013271966],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009979422,0.00025734678,0.9033203,0.00027262032,0.000015438496,0.000021277625,0.000070486945,0.00028855665,0.07543453,0.00043190338,0.014984798,0.003904797],"study_design_scores_gemma":[0.0011994576,0.0032166725,0.89578855,0.00016258788,0.00013151391,0.00012884464,0.000005415635,0.0019079202,0.09441055,0.00028790312,0.002651509,0.00010905942],"about_ca_topic_score_codex":0.000012148259,"about_ca_topic_score_gemma":4.6032184e-7,"teacher_disagreement_score":0.018976029,"about_ca_system_score_codex":0.000011732696,"about_ca_system_score_gemma":0.000023977624,"threshold_uncertainty_score":0.24444348},"labels":[],"label_agreement":null},{"id":"W1595872863","doi":"10.1002/mrm.25108","title":"Investigating the stability of mcDESPOT myelin water fraction values derived using a stochastic region contraction approach","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; Medical Research Council; Michael Smith Health Research BC","keywords":"Parameter space; Sensitivity (control systems); Contraction (grammar); Imaging phantom; Biological system; Range (aeronautics); Mathematics; Computer science; Mathematical optimization; Physics; Statistics; Materials science; Optics","score_opus":0.10386940134591494,"score_gpt":0.3451068070371636,"score_spread":0.24123740569124869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1595872863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78030646,0.00058776885,0.21500541,0.0029689802,0.000042198943,0.0007541842,5.789921e-7,0.00005839986,0.00027600638],"genre_scores_gemma":[0.9831183,0.000063884094,0.016037034,0.00046921766,0.00016879171,0.000087069435,0.000009126538,0.000020286941,0.00002626579],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851334,0.00015400388,0.0004974972,0.00032208074,0.00029103676,0.00022206454],"domain_scores_gemma":[0.99887747,0.0002875535,0.00016007411,0.0004868011,0.00012825175,0.000059849997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076834497,0.00014744712,0.0003584227,0.00009233728,0.00009623196,0.000004967097,0.00010591291,0.00006639684,0.000021707088],"category_scores_gemma":[0.0008918041,0.000087820736,0.000036610203,0.00025495503,0.00052755966,0.00006625987,0.000032299005,0.0003590294,9.485551e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028483281,0.00030675522,0.025918681,0.0003320942,0.000006883846,0.00000446128,0.0021980368,0.0010775479,0.8397908,0.0006891357,0.00019694897,0.12919378],"study_design_scores_gemma":[0.004542348,0.0015282955,0.27707288,0.0018627679,0.00026502015,0.00031822396,0.0018526131,0.63344574,0.05228141,0.022431416,0.0039843167,0.00041494897],"about_ca_topic_score_codex":0.0002354173,"about_ca_topic_score_gemma":0.0000036926492,"teacher_disagreement_score":0.78750944,"about_ca_system_score_codex":0.000076862314,"about_ca_system_score_gemma":0.000027219758,"threshold_uncertainty_score":0.35812256},"labels":[],"label_agreement":null},{"id":"W1596591320","doi":"10.1007/s10489-016-0833-8","title":"A multicomponent approach to nonrigid registration of diffusion tensor images","year":2016,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Diffusion MRI; Affine transformation; Computer science; Tensor (intrinsic definition); Distortion (music); Structure tensor; Diffusion; Mutual information; Computer vision; Artificial intelligence; Image registration; Orientation (vector space); Pattern recognition (psychology); Image (mathematics); Mathematics; Geometry; Magnetic resonance imaging; Physics; Radiology; Medicine","score_opus":0.08411722725463726,"score_gpt":0.3464097997324712,"score_spread":0.26229257247783394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1596591320","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04717914,0.000012705675,0.9380406,0.001263522,0.00001279423,0.0007582394,0.000007192551,0.00013278383,0.012593014],"genre_scores_gemma":[0.8520631,0.0000697701,0.14700882,0.00024041158,0.000029266774,0.00015803448,0.000004636413,0.000015247171,0.00041071666],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990664,0.0000060337125,0.00028660634,0.0003131903,0.00017869179,0.00014904275],"domain_scores_gemma":[0.99920034,0.00006410339,0.000097304895,0.00046583836,0.000079386045,0.00009300017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000083273786,0.000112095615,0.00017465584,0.00007141495,0.00003700357,0.000004759455,0.00013206962,0.000036693047,0.000016705331],"category_scores_gemma":[0.000052615487,0.00007334658,0.000043503896,0.00016583534,0.00007678175,0.000030755975,0.000056098288,0.00006710488,0.00004727527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078699304,0.00026072527,0.00028350987,0.000027434435,0.000004213902,7.3465867e-7,0.00005588006,0.000008740151,0.9057326,0.025650468,0.00049509713,0.06740192],"study_design_scores_gemma":[0.0001850824,0.000121237485,0.0049831728,0.00010221974,0.000022726617,0.00002292967,0.00006344861,0.00038520608,0.9820078,0.003625976,0.008327415,0.0001527859],"about_ca_topic_score_codex":0.000012199468,"about_ca_topic_score_gemma":2.3209493e-7,"teacher_disagreement_score":0.80488396,"about_ca_system_score_codex":0.00003343082,"about_ca_system_score_gemma":0.000015944892,"threshold_uncertainty_score":0.29909867},"labels":[],"label_agreement":null},{"id":"W1598901374","doi":"10.3389/fnagi.2015.00131","title":"Gray matter blood flow and volume are reduced in association with white matter hyperintensity lesion burden: a cross-sectional MRI study","year":2015,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Toronto Western Hospital; Heart and Stroke Foundation","funders":"University of Toronto; Canadian Stroke Network; Canadian Institutes of Health Research; Sunnybrook Research Institute; Heart and Stroke Foundation of Canada","keywords":"Hyperintensity; White matter; Magnetic resonance imaging; Fluid-attenuated inversion recovery; Lesion; Cerebral blood flow; Medicine; Cardiology; Voxel-based morphometry; Voxel; Grey matter; Putamen; Psychology; Internal medicine; Radiology; Pathology","score_opus":0.04051851309697691,"score_gpt":0.3136729019631118,"score_spread":0.2731543888661349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1598901374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866091,0.0000143004045,0.0094731,0.0029872882,0.00025596019,0.00048133786,0.0000049270134,0.00006969404,0.000104297884],"genre_scores_gemma":[0.9846898,0.0000063431694,0.0128121795,0.0011476319,0.000038579812,0.000052242198,0.0000022159643,0.000018359238,0.0012326505],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985628,0.000051336378,0.00021341858,0.0005703548,0.0003429206,0.000259129],"domain_scores_gemma":[0.99940544,0.000011451353,0.00012174851,0.0002647818,0.00009854448,0.00009800277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033413633,0.00013594203,0.00020858683,0.00020598351,0.00009509046,0.00007865385,0.00012247302,0.000040538118,0.0000034631598],"category_scores_gemma":[0.000087153334,0.00012267067,0.0000185921,0.00045999244,0.00011944218,0.0002252003,0.000087370085,0.00032175923,0.000004283703],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041353665,0.00014355307,0.99531025,0.00000993325,0.0000012254154,0.00004957589,0.00026707188,0.00038414053,0.0014851188,4.1497466e-7,0.0022774301,0.000029910922],"study_design_scores_gemma":[0.0009212341,0.00011791565,0.9919663,0.000043427943,0.000010532211,0.00010024929,0.00018467955,0.0059168893,0.00019788701,0.00006562072,0.00035306197,0.00012221311],"about_ca_topic_score_codex":0.000038940932,"about_ca_topic_score_gemma":0.0000056697263,"teacher_disagreement_score":0.0055327485,"about_ca_system_score_codex":0.00014949872,"about_ca_system_score_gemma":0.0000360133,"threshold_uncertainty_score":0.50023645},"labels":[],"label_agreement":null},{"id":"W1607963120","doi":"10.1007/978-3-540-85990-1_22","title":"Human Brain Myelination from Birth to 4.5 Years","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Internal capsule; Computer science; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.04755122668089339,"score_gpt":0.3491319561679287,"score_spread":0.3015807294870353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1607963120","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4136493,0.0000068352483,0.58305407,0.003044043,0.00003497736,0.00012153299,0.0000012113697,0.00007694003,0.000011104545],"genre_scores_gemma":[0.69549173,0.0000014487678,0.3004719,0.003917192,0.0000986289,0.000007701231,0.0000021260296,0.0000052567016,0.0000040353616],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99917024,0.000008316576,0.00011029797,0.00034713873,0.0002040918,0.00015991284],"domain_scores_gemma":[0.99946153,0.000062639505,0.000025321315,0.00032680706,0.000047834466,0.00007588876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009153061,0.00006865319,0.000095943564,0.00017201656,0.00011332528,0.000015878792,0.00020889351,0.000024318155,0.000008609483],"category_scores_gemma":[0.00007829368,0.000064727035,0.000018627696,0.00079713465,0.00014974427,0.00007234817,0.00010139694,0.00013452767,0.000012675001],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015633006,0.00019107648,0.038913112,0.000010253385,0.0000033148824,0.00015033342,0.002935835,0.015070381,0.32122943,0.0005579622,0.0006689275,0.62025374],"study_design_scores_gemma":[0.0006404214,0.0003391557,0.8285021,0.000111023306,0.0000041074304,0.00011270278,8.0368704e-7,0.06620014,0.06838274,0.031065952,0.004327571,0.0003132959],"about_ca_topic_score_codex":0.000046066307,"about_ca_topic_score_gemma":0.000009646919,"teacher_disagreement_score":0.789589,"about_ca_system_score_codex":0.000056233905,"about_ca_system_score_gemma":0.000047529604,"threshold_uncertainty_score":0.2639492},"labels":[],"label_agreement":null},{"id":"W1613048622","doi":"10.1177/1971400915598071","title":"Reversible restricted-diffusion lesion representing transient intramyelinic cytotoxic edema in a patient with traumatic brain injury","year":2015,"lang":"en","type":"article","venue":"The Neuroradiology Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital","funders":"","keywords":"White matter; Corpus callosum; Medicine; Diffusion MRI; Traumatic brain injury; Effective diffusion coefficient; Magnetic resonance imaging; Emergency department; Diffuse axonal injury; Lesion; Radiology; Pathology; Psychiatry","score_opus":0.11228367959974137,"score_gpt":0.3642983670378126,"score_spread":0.2520146874380712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1613048622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97396153,0.00010223828,0.004516566,0.020362042,0.00008971511,0.00056338066,0.0000016125549,0.000080636746,0.00032229102],"genre_scores_gemma":[0.9946993,0.00021192174,0.002907085,0.0019286108,0.000116682626,0.000028958735,0.0000035785342,0.000028560371,0.000075279124],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99835104,0.00034132582,0.00047887518,0.0002766471,0.00023761447,0.00031452134],"domain_scores_gemma":[0.998851,0.0002125059,0.00024586054,0.00041845426,0.00008767128,0.00018449705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046391028,0.00015691643,0.00030266933,0.00021439006,0.00016715663,0.000020270643,0.0002089019,0.00007138636,0.000007877775],"category_scores_gemma":[0.00035297323,0.00009647399,0.00006736636,0.00047512614,0.00015010004,0.00009679431,0.0000543338,0.00096183055,0.0000055694927],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00978919,0.0030522305,0.078378364,0.00020159465,0.00016524874,0.00743474,0.013490894,0.0048163347,0.6182299,0.001115636,0.15226848,0.11105736],"study_design_scores_gemma":[0.030456642,0.0352788,0.42644945,0.004099172,0.00093713927,0.29169515,0.0077251308,0.038623754,0.021007964,0.03508367,0.10617704,0.0024660723],"about_ca_topic_score_codex":0.000011272573,"about_ca_topic_score_gemma":0.0000030580206,"teacher_disagreement_score":0.597222,"about_ca_system_score_codex":0.000089504625,"about_ca_system_score_gemma":0.0001332094,"threshold_uncertainty_score":0.41787288},"labels":[],"label_agreement":null},{"id":"W1615815280","doi":"10.3171/2010.3.jns091832","title":"Tractography of the amygdala and hippocampus: anatomical study and application to selective amygdalohippocampectomy","year":2010,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fornix; Uncinate fasciculus; White matter; Tractography; Diffusion MRI; Neuroscience; Hippocampus; Amygdala; Anatomy; Corpus callosum; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Medicine; Psychology; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.018225487089576643,"score_gpt":0.31826215321891266,"score_spread":0.300036666129336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1615815280","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99659365,0.000029111632,0.00094131374,0.0017707647,0.00008277767,0.0005198497,0.0000028214636,0.000018207562,0.00004147057],"genre_scores_gemma":[0.99788415,0.000031549618,0.00147816,0.0004972767,0.00007152011,0.00001619793,1.8808336e-7,0.000016568607,0.0000043903933],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909323,0.000043417942,0.00037865192,0.00017171055,0.00020451218,0.00010846126],"domain_scores_gemma":[0.9989041,0.00021558344,0.00031143648,0.00025139668,0.00017678888,0.0001406962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026027433,0.000103992126,0.0002796635,0.00024526045,0.000066779336,0.000013460616,0.00009308677,0.00003949922,0.0000012927911],"category_scores_gemma":[0.00020614122,0.000070764756,0.00009133097,0.00053361437,0.000125541,0.00007315533,0.000049372833,0.00051088404,2.1801844e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016247887,0.00047353547,0.5522493,0.000018271718,0.000023532017,0.000011277362,0.00018528383,0.0000015978642,0.42539322,0.0001307035,0.00041335952,0.020937437],"study_design_scores_gemma":[0.00045064246,0.00041034745,0.98367876,0.000027476774,0.00008472046,0.0007157258,0.000072490635,0.00004817004,0.010199312,0.0022681798,0.0019715768,0.00007259798],"about_ca_topic_score_codex":0.0000030034107,"about_ca_topic_score_gemma":0.0000022431725,"teacher_disagreement_score":0.43142945,"about_ca_system_score_codex":0.0000068770196,"about_ca_system_score_gemma":0.000042270854,"threshold_uncertainty_score":0.28857028},"labels":[],"label_agreement":null},{"id":"W163465042","doi":"10.1007/978-3-642-40760-4_59","title":"A Cross-Sectional Piecewise Constant Model for Segmenting Highly Curved Fiber Tracts in Diffusion MR Images","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Alberta; Western Canada Research Grid; Compute Canada","keywords":"Piecewise; Segmentation; Constant (computer programming); Diffusion; Computer science; Diffusion MRI; Cross section (physics); Fiber; Artificial intelligence; Market segmentation; Image segmentation; Mathematics; Mathematical analysis; Physics; Materials science; Magnetic resonance imaging; Medicine","score_opus":0.05039745930564653,"score_gpt":0.34868536098693936,"score_spread":0.2982879016812928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W163465042","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37518027,0.000016521592,0.62348825,0.00070921547,0.00004263141,0.00048378838,0.0000037024874,0.000060578976,0.000015056834],"genre_scores_gemma":[0.635546,0.0000036778376,0.3637475,0.0005556618,0.00004103687,0.00008308412,0.0000034914574,0.0000074397335,0.000012065325],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868166,0.000009682137,0.0002589663,0.00049912883,0.0002215816,0.00032895873],"domain_scores_gemma":[0.99921495,0.0002190527,0.00007300264,0.00026992132,0.0001478824,0.000075218326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024583578,0.00012657087,0.0001555947,0.00018838602,0.0001465458,0.000112003225,0.00020694567,0.000049421567,0.000012853723],"category_scores_gemma":[0.00013449597,0.00010642119,0.000041625262,0.00048727106,0.0002749005,0.00028332922,0.00012229006,0.00021622043,0.0000040469054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060904997,0.00046303822,0.21082512,0.00009828851,0.0000041496714,0.000014621214,0.0005739042,0.18439142,0.38447252,0.0003315789,0.00007267971,0.21869178],"study_design_scores_gemma":[0.0005529091,0.000046957546,0.07368841,0.0000620824,0.0000018824472,0.000025731531,2.471171e-7,0.89273393,0.020295855,0.012451533,0.000028925433,0.00011155235],"about_ca_topic_score_codex":0.000029936054,"about_ca_topic_score_gemma":0.0000058469127,"teacher_disagreement_score":0.7083425,"about_ca_system_score_codex":0.000100837016,"about_ca_system_score_gemma":0.000101608464,"threshold_uncertainty_score":0.433973},"labels":[],"label_agreement":null},{"id":"W1706210574","doi":"10.1016/j.pscychresns.2015.06.017","title":"Investigation of white matter abnormalities in first episode psychosis patients with persistent negative symptoms","year":2015,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto; McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Fornix; Uncinate fasciculus; Cingulum (brain); White matter; Fractional anisotropy; Psychology; Psychosis; Fasciculus; Superior longitudinal fasciculus; Schizophrenia (object-oriented programming); Inferior longitudinal fasciculus; Anhedonia; Internal medicine; Medicine; Neuroscience; Psychiatry; Magnetic resonance imaging; Hippocampus; Radiology","score_opus":0.1073756453976198,"score_gpt":0.36467744201648505,"score_spread":0.25730179661886526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1706210574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97560817,0.0000792346,0.00028850127,0.020045659,0.00007761126,0.0009294596,0.000018122078,0.00007644823,0.002876798],"genre_scores_gemma":[0.98855793,0.00001633776,0.010205651,0.00073776644,0.00005293737,0.00017523178,0.000024800782,0.000048708254,0.00018063458],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99784905,0.00014348315,0.00036574295,0.00046255777,0.00073610595,0.000443039],"domain_scores_gemma":[0.9984574,0.00010253661,0.00012028211,0.000546785,0.0005284152,0.00024459208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040743224,0.00017595949,0.0002535847,0.000499687,0.00017089637,0.000028531895,0.00020587313,0.000036821544,0.00002485809],"category_scores_gemma":[0.00008578428,0.0001526854,0.000069032474,0.0009359465,0.00039962193,0.00028469742,0.00013659209,0.0005645848,0.000017811906],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020824854,0.00014459871,0.9940098,0.00012816097,0.000013380314,0.00000205177,0.0008117135,0.000049930906,0.000023170818,0.0001877465,0.0043302816,0.00009090612],"study_design_scores_gemma":[0.0019350302,0.0005496154,0.9921683,0.00045589785,0.000024684967,0.000018199793,0.0005037111,0.0006647289,0.00017135359,0.0025631578,0.00077953545,0.0001657608],"about_ca_topic_score_codex":0.00022319255,"about_ca_topic_score_gemma":0.00006111868,"teacher_disagreement_score":0.019307893,"about_ca_system_score_codex":0.000108783184,"about_ca_system_score_gemma":0.000089053414,"threshold_uncertainty_score":0.622633},"labels":[],"label_agreement":null},{"id":"W1726170819","doi":"","title":"Connectivity directionally-encoded color map: a streamline-based color mapping","year":2014,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Artificial intelligence; Computer science; Computer vision; Orientation (vector space); Color image; Set (abstract data type); Pattern recognition (psychology); Image (mathematics); Image processing; Mathematics; Physics","score_opus":0.03975453725186294,"score_gpt":0.2916540061378824,"score_spread":0.25189946888601944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1726170819","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1811385,0.000278403,0.75765765,0.040651385,0.00020684811,0.0017646769,0.00018666282,0.0014319684,0.01668388],"genre_scores_gemma":[0.7664503,0.00012639914,0.22562625,0.0007371039,0.000070013455,0.0006554733,0.0010474281,0.00009326778,0.005193773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9952766,0.001981362,0.00065010256,0.0011777366,0.00048836175,0.00042583823],"domain_scores_gemma":[0.99200904,0.0021960253,0.0006775448,0.0024520217,0.0023724479,0.00029290214],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0028488142,0.0004744999,0.0006965715,0.00029335465,0.00044779887,0.00017218998,0.0006948033,0.00036468683,0.00013072767],"category_scores_gemma":[0.0020251889,0.000506998,0.0003553429,0.00041949187,0.00034532772,0.00007480341,0.00076075963,0.0011140528,0.00004776671],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001031227,0.020225693,0.0694234,0.007670071,0.0015092801,0.00018498156,0.0076364055,0.006364332,0.23470107,0.38831034,0.06296067,0.19998251],"study_design_scores_gemma":[0.004024327,0.000007713581,0.022473536,0.008414497,0.0004440954,0.00009234778,0.00010117298,0.397421,0.25146317,0.019408347,0.2942782,0.0018715735],"about_ca_topic_score_codex":0.00043227937,"about_ca_topic_score_gemma":0.00030568877,"teacher_disagreement_score":0.5853118,"about_ca_system_score_codex":0.0002954898,"about_ca_system_score_gemma":0.00057275716,"threshold_uncertainty_score":0.99973816},"labels":[],"label_agreement":null},{"id":"W1743269311","doi":"10.1002/hbm.22830","title":"Rich club analysis in the Alzheimer's disease connectome reveals a relatively undisturbed structural core network","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Connectome; Neuroscience; Diffusion MRI; White matter; Connectomics; Grey matter; Psychology; Alzheimer's disease; Neuroimaging; Clustering coefficient; Tractography; Computer science; Disease; Cluster analysis; Medicine; Artificial intelligence; Magnetic resonance imaging; Functional connectivity; Pathology","score_opus":0.23436285183982716,"score_gpt":0.40772388790035974,"score_spread":0.17336103606053258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1743269311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97914183,0.0006679108,0.0063279686,0.010329726,0.00003030141,0.0011312095,0.000016853855,0.00025523387,0.0020989738],"genre_scores_gemma":[0.9928391,0.0000032534006,0.0032980363,0.003255835,0.00017579638,0.00009104916,0.00013611294,0.0000192582,0.00018157293],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987015,0.00012384463,0.00031024124,0.00034144116,0.00023925757,0.000283708],"domain_scores_gemma":[0.99883693,0.00023964324,0.00015128564,0.00054165034,0.00007284621,0.00015765755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005163698,0.00016186791,0.00030778622,0.00017445938,0.00023566728,0.000031760745,0.00021331778,0.000039490267,0.000023546474],"category_scores_gemma":[0.00021675225,0.00012034323,0.00011452296,0.001326236,0.000110870686,0.00007177269,0.00006812395,0.00030721544,0.0000065121694],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012979307,0.00011352424,0.85422325,0.00004287943,0.0005531618,0.0002409132,0.0048126746,0.0030795059,0.0017395352,0.08982853,0.044849966,0.00038625541],"study_design_scores_gemma":[0.0005588062,0.000039236293,0.91376334,0.00006425165,0.00040677466,0.000010777823,0.00034117867,0.0029670156,0.0000013430149,0.07691991,0.0047656326,0.00016174978],"about_ca_topic_score_codex":0.000021988077,"about_ca_topic_score_gemma":0.000016531147,"teacher_disagreement_score":0.05954006,"about_ca_system_score_codex":0.00006160374,"about_ca_system_score_gemma":0.000034987774,"threshold_uncertainty_score":0.49074546},"labels":[],"label_agreement":null},{"id":"W1749485375","doi":"10.1371/journal.pone.0139434","title":"Seeing More by Showing Less: Orientation-Dependent Transparency Rendering for Fiber Tractography Visualization","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health","keywords":"Visualization; Tractography; Computer science; Fiber bundle; Rendering (computer graphics); Bundle; Data visualization; Connectomics; Diffusion MRI; Artificial intelligence; Computer vision; Neuroscience; Connectome; Biology; Functional connectivity; Materials science; Medicine; Magnetic resonance imaging","score_opus":0.2423786497573033,"score_gpt":0.3739727231724838,"score_spread":0.1315940734151805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1749485375","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4654424,0.00030344405,0.5295554,0.0016140483,0.000026393202,0.0013744719,0.00006806937,0.0005721532,0.0010436466],"genre_scores_gemma":[0.91546434,0.00006372982,0.0827905,0.00030202643,0.000086662636,0.00039919087,0.0003343631,0.000051353585,0.0005078587],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99908924,0.000009127895,0.00021515276,0.00025735996,0.000268696,0.00016044042],"domain_scores_gemma":[0.9994507,0.00003559847,0.0000690917,0.00019504548,0.0001389391,0.000110619774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008467873,0.000106722284,0.00016930384,0.000078333374,0.000080089034,0.000017463011,0.00005928624,0.000043474723,0.000012626577],"category_scores_gemma":[0.00004879053,0.000111150184,0.000049442802,0.00019705328,0.000022923296,0.00014775578,0.000009442399,0.00009063256,0.0000025501424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048261377,0.007919673,0.06754226,0.0015804515,0.00059052784,0.000019115983,0.007369762,0.00030059463,0.8800677,0.0048731556,0.007385159,0.02186897],"study_design_scores_gemma":[0.0064894226,0.00096194603,0.0036017508,0.001482415,0.0015703279,0.000025651252,0.002607873,0.017752524,0.9459626,0.004679952,0.013805119,0.0010604276],"about_ca_topic_score_codex":0.000008472796,"about_ca_topic_score_gemma":0.0000011334323,"teacher_disagreement_score":0.45002192,"about_ca_system_score_codex":0.00004394322,"about_ca_system_score_gemma":0.000024419796,"threshold_uncertainty_score":0.4532573},"labels":[],"label_agreement":null},{"id":"W1762773937","doi":"10.1684/epd.2008.0217","title":"Pathways of seizure propagation from the temporal to the occipital lobe","year":2008,"lang":"en","type":"article","venue":"Epileptic Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Temporal lobe; Epilepsy; Neuroscience; Occipital lobe; Psychology; Audiology; Medicine","score_opus":0.052372395229716213,"score_gpt":0.29463392937806654,"score_spread":0.24226153414835033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1762773937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9115257,0.0001352408,0.048229184,0.03577519,0.00007084345,0.0013992502,0.00005307333,0.00016134205,0.0026501748],"genre_scores_gemma":[0.9941997,0.000063195876,0.003844845,0.0014649818,0.00007988932,0.00010497246,0.000042906424,0.000016172064,0.00018334518],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99934953,0.000022250157,0.00016817909,0.00016870376,0.00017160298,0.0001197098],"domain_scores_gemma":[0.9993195,0.000082987426,0.00006690101,0.00044787803,0.000040341416,0.00004239698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006587072,0.000088100285,0.00011417133,0.00001819492,0.00014652571,0.000004688646,0.00016194388,0.000025287392,0.000043163345],"category_scores_gemma":[0.00009037683,0.00004890024,0.00006396124,0.00020442982,0.00013300007,0.000036241367,0.000046730507,0.00013410929,0.000035180114],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047808918,0.001768727,0.4087493,0.00008993275,0.00018974104,0.000038079525,0.0180488,0.0008627451,0.023150757,0.021819208,0.3681908,0.15661381],"study_design_scores_gemma":[0.0014797074,0.0008095535,0.59552705,0.00016325632,0.0001473348,0.00005777733,0.0021057876,0.0022472434,0.0042047184,0.016572466,0.3762741,0.00041096893],"about_ca_topic_score_codex":0.00012817471,"about_ca_topic_score_gemma":0.000037992922,"teacher_disagreement_score":0.18677774,"about_ca_system_score_codex":0.0000132577425,"about_ca_system_score_gemma":0.00004491812,"threshold_uncertainty_score":0.19940941},"labels":[],"label_agreement":null},{"id":"W1775970683","doi":"10.1089/neu.2015.3948","title":"Long-Term Abnormalities in the Corpus Callosum of Female Concussed Athletes","year":2015,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Diffusion MRI; Concussion; White matter; Fractional anisotropy; Corticospinal tract; Athletes; Psychology; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Physical therapy; Neuroscience; Poison control; Radiology; Injury prevention","score_opus":0.24330807292608725,"score_gpt":0.40574201952635947,"score_spread":0.16243394660027222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1775970683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99561864,0.00030336398,0.00047393976,0.0024302823,0.00006201102,0.00021007165,0.000003468601,0.0000134704505,0.00088475464],"genre_scores_gemma":[0.9979539,0.00013572522,0.0009014796,0.0007902129,0.000104447754,0.0000065347845,0.0000010331215,0.000012126833,0.00009455568],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903697,0.000057812005,0.00042644565,0.00007637379,0.00028114146,0.00012124971],"domain_scores_gemma":[0.99910283,0.000120467375,0.00030182657,0.00021936525,0.0001791001,0.00007638676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002798732,0.00008405976,0.0002420877,0.00009826629,0.000018973213,0.000010286468,0.0001971796,0.000027760532,0.0000063987013],"category_scores_gemma":[0.00013026637,0.000053534914,0.000092173745,0.00015511738,0.00010484245,0.00009345577,0.000020953179,0.00029939212,0.00000135453],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009976967,0.0016277184,0.89193904,0.00032369778,0.00007068198,0.0030716201,0.005089994,0.00014765716,0.06636397,0.0051184273,0.005969197,0.019280322],"study_design_scores_gemma":[0.0031045706,0.0020838878,0.9527167,0.00042345776,0.00010604735,0.0051782243,0.00049385376,0.00006357256,0.025811763,0.0017300076,0.008135477,0.00015241352],"about_ca_topic_score_codex":0.0000066611815,"about_ca_topic_score_gemma":0.0000020529908,"teacher_disagreement_score":0.060777705,"about_ca_system_score_codex":0.000020817639,"about_ca_system_score_gemma":0.00006973139,"threshold_uncertainty_score":0.21830904},"labels":[],"label_agreement":null},{"id":"W1778022616","doi":"10.48550/arxiv.1207.0677","title":"Local Water Diffusion Phenomenon Clustering From High Angular Resolution\\n Diffusion Imaging (HARDI)","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Voxel; Computer science; Angular resolution (graph drawing); White matter; Artificial intelligence; Tractography; Diffusion; Cluster analysis; Pattern recognition (psychology); Magnetic resonance imaging; Computer vision; Physics; Mathematics; Medicine","score_opus":0.0774502445703158,"score_gpt":0.22902166133265325,"score_spread":0.15157141676233746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1778022616","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4590752,0.00009997853,0.538859,0.00029981136,0.00020436778,0.0004128503,0.000046103443,0.0003872177,0.00061544403],"genre_scores_gemma":[0.99366325,0.00042430862,0.003729201,0.00027013425,0.000315135,0.000006003747,0.00060898793,0.00007867747,0.0009043158],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979853,0.00006659645,0.00027113038,0.0010276374,0.00013114572,0.0005181909],"domain_scores_gemma":[0.99816513,0.000039076993,0.00016255083,0.0012489029,0.000110353794,0.00027398943],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011445678,0.00040525582,0.00046346174,0.00021556775,0.00026725794,0.000032880547,0.0003670417,0.00022991965,0.0001987468],"category_scores_gemma":[0.00000904856,0.0003821924,0.00022308933,0.00016568172,0.00019183404,0.00016678922,0.00198703,0.0008250414,0.00009174763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040188157,0.006151435,0.16622895,0.002307876,0.0011140425,0.004803434,0.004549842,0.24917991,0.46478382,0.039001606,0.0055502914,0.05230996],"study_design_scores_gemma":[0.0036054438,0.00010453645,0.032202147,0.0011710715,0.0014580801,0.000058158126,0.00038606577,0.86821157,0.010585406,0.049810607,0.0305565,0.0018504148],"about_ca_topic_score_codex":0.00081186154,"about_ca_topic_score_gemma":0.0000128358015,"teacher_disagreement_score":0.61903167,"about_ca_system_score_codex":0.00048698566,"about_ca_system_score_gemma":0.000036271762,"threshold_uncertainty_score":0.999863},"labels":[],"label_agreement":null},{"id":"W1780280682","doi":"10.1016/j.schres.2015.10.023","title":"Neuroimaging predictors of functional outcomes in schizophrenia at baseline and 6-month follow-up","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Canada Research Chairs; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Brain and Behaviour Research Institute, University of Wollongong; Canadian Institutes of Health Research; Ontario Mental Health Foundation; Centre for Addiction and Mental Health Foundation; Brain Research Foundation; Foundation for the National Institutes of Health","keywords":"Arcuate fasciculus; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Neuroimaging; Functional neuroimaging; Default mode network; Diffusion MRI; Audiology; Internal medicine; Neuroscience; Psychiatry; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.16042183449652586,"score_gpt":0.3977267967092128,"score_spread":0.23730496221268693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1780280682","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992529,0.00037804458,0.00060658297,0.004484793,0.00013287927,0.00071560906,0.000038260197,0.00014172122,0.0009731611],"genre_scores_gemma":[0.9894563,0.000094093586,0.008173446,0.00010211451,0.00013371767,0.0001154732,0.000049455022,0.000048095648,0.0018273037],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974738,0.00017805566,0.00043649084,0.0005494476,0.00090918026,0.00045306972],"domain_scores_gemma":[0.99816763,0.00037508024,0.000077291385,0.00060533505,0.0004057082,0.00036896576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012922847,0.00019411006,0.0004074674,0.00062120485,0.00012926302,0.000021916077,0.00017766375,0.00007874586,0.000040407944],"category_scores_gemma":[0.0011744493,0.00016860718,0.000077833385,0.0007904227,0.000382321,0.0001493619,0.00040287865,0.000712043,0.00002248135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011723535,0.00062834047,0.91705036,0.0001612695,0.00006303069,0.00012917141,0.00024105943,0.000064693406,0.033003654,0.005019203,0.016474279,0.015441406],"study_design_scores_gemma":[0.023756446,0.0009045876,0.932725,0.0002975233,0.00007364942,0.0002418526,0.00022105701,0.0072339433,0.007966684,0.011997322,0.014081228,0.0005006641],"about_ca_topic_score_codex":0.00009998642,"about_ca_topic_score_gemma":0.00007774413,"teacher_disagreement_score":0.02503697,"about_ca_system_score_codex":0.0001543451,"about_ca_system_score_gemma":0.00029603404,"threshold_uncertainty_score":0.68756014},"labels":[],"label_agreement":null},{"id":"W1784432185","doi":"10.1002/nbm.2992","title":"Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination","year":2013,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":153,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Saskatchewan; University of Manitoba","funders":"","keywords":"Magnetization transfer; Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Magnetic resonance imaging; Myelin; Nuclear magnetic resonance; Axon; Internal capsule; Chemistry; External capsule; Nuclear medicine; Pathology; Anatomy; Biology; Medicine; Central nervous system; Physics; Endocrinology; Radiology","score_opus":0.0570184849446915,"score_gpt":0.3443379311878083,"score_spread":0.2873194462431168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1784432185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97153646,0.00005208577,0.024838699,0.0028561195,0.000009783781,0.00048626607,0.000008232793,0.000018103547,0.00019422354],"genre_scores_gemma":[0.96264803,0.000093342875,0.036980614,0.00010545269,0.000008941067,0.000026103673,0.0000104024875,0.000007185379,0.00011992975],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999408,0.000017474249,0.00024184445,0.00011527751,0.00014778967,0.00006960771],"domain_scores_gemma":[0.9994874,0.000058216578,0.00012807555,0.00016270755,0.00013286753,0.000030735093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010939733,0.00006376892,0.00015324718,0.00012215199,0.000017141203,0.000001227626,0.000056010784,0.000033203505,0.000009947572],"category_scores_gemma":[0.00012952212,0.000040811035,0.000017088265,0.0002643728,0.00024145814,0.00006415814,0.000024401474,0.0000866095,3.7036216e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000134577385,0.00005075809,0.004475746,0.000072899,0.000004247501,8.556267e-8,0.00037013594,0.000057589805,0.98031,0.003503397,0.00009002606,0.011051616],"study_design_scores_gemma":[0.0015673257,0.00042122876,0.46815044,0.0002481746,0.000045370136,0.000012867326,0.00042251227,0.18402287,0.3355941,0.009376614,0.000039699215,0.000098813995],"about_ca_topic_score_codex":0.000050258233,"about_ca_topic_score_gemma":0.0000018020326,"teacher_disagreement_score":0.64471596,"about_ca_system_score_codex":0.000021616434,"about_ca_system_score_gemma":0.000017650427,"threshold_uncertainty_score":0.16642258},"labels":[],"label_agreement":null},{"id":"W1799381395","doi":"10.1016/j.neuroimage.2015.07.074","title":"Real diffusion-weighted MRI enabling true signal averaging and increased diffusion contrast","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Diffusion MRI; Diffusion; Noise (video); SIGNAL (programming language); Estimator; Computer science; Algorithm; Contrast (vision); Signal-to-noise ratio (imaging); Gaussian; Artificial intelligence; Statistics; Mathematics; Physics","score_opus":0.04526567435901944,"score_gpt":0.3122587677662398,"score_spread":0.2669930934072203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1799381395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9749466,0.0000821692,0.016896103,0.0019946294,0.000056336285,0.00062453136,0.000018811128,0.0005935349,0.004787279],"genre_scores_gemma":[0.9881164,0.00033740507,0.009667573,0.0012151656,0.00018779907,0.00003990845,0.000046584697,0.000058791018,0.00033040444],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985532,0.000059323134,0.00027885044,0.00050684536,0.0002905141,0.00031126713],"domain_scores_gemma":[0.9988302,0.00013351534,0.00010103564,0.00041857365,0.000118182674,0.00039851703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014542478,0.00022153239,0.00030315775,0.0001387845,0.00017295333,0.000050646748,0.00010741295,0.00006366714,0.000034119952],"category_scores_gemma":[0.00009831061,0.00019549395,0.000058217563,0.00022911369,0.00012170153,0.00017682901,0.00014927442,0.00035118594,0.000012764596],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040961243,0.00038698612,0.02291113,0.000055817527,0.000011996472,0.0004233705,0.00029433946,0.000002443673,0.95718914,0.0011599207,0.0026960224,0.014459198],"study_design_scores_gemma":[0.037656438,0.0028903147,0.3742752,0.0010259628,0.0008421511,0.0036600004,0.00076420896,0.13274863,0.2227136,0.01995126,0.20056674,0.0029054638],"about_ca_topic_score_codex":0.00012654305,"about_ca_topic_score_gemma":0.0000020064547,"teacher_disagreement_score":0.73447555,"about_ca_system_score_codex":0.000046418347,"about_ca_system_score_gemma":0.000063877065,"threshold_uncertainty_score":0.79720116},"labels":[],"label_agreement":null},{"id":"W1806292349","doi":"10.1167/15.12.434","title":"The reorganization of extrastriate cortex in patients with lobectomy","year":2015,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Hemispherectomy; Extrastriate cortex; Visual cortex; Ocular dominance; Neuroscience; Psychology; Cortex (anatomy); Neuroplasticity; Epilepsy","score_opus":0.02815280108009934,"score_gpt":0.33598243270137534,"score_spread":0.307829631621276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1806292349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916457,0.000044515415,0.007415339,0.00064159493,0.000024553156,0.00012270625,5.265317e-7,0.000005316234,0.00009976202],"genre_scores_gemma":[0.99504083,0.000036841793,0.004847003,0.000029014063,0.000019188526,3.8835518e-7,0.0000012090487,0.0000062037943,0.000019346378],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99951005,0.00001303726,0.0002110146,0.00003675178,0.0001858319,0.000043337033],"domain_scores_gemma":[0.99926865,0.000024688821,0.00024416792,0.000091746915,0.00033185628,0.000038906164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015533328,0.00003220717,0.00008901151,0.000048137743,0.000014979494,0.0000039384045,0.000046569614,0.000012921881,0.0000016180978],"category_scores_gemma":[0.00009646234,0.000017088267,0.000013917912,0.0001767628,0.000021887012,0.00006340279,0.000010304797,0.0000923281,4.8898255e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019294362,0.00079055125,0.93904793,0.000018320383,0.000017613602,0.000014217778,0.00021111376,0.00010277581,0.0130934045,0.00045598362,0.004233769,0.040084872],"study_design_scores_gemma":[0.0019550591,0.0011360866,0.9921709,0.00014852258,0.000016049886,0.000016633116,0.000028390376,0.00008659162,0.0012968354,0.00065776944,0.002463219,0.000023998478],"about_ca_topic_score_codex":0.0000012752528,"about_ca_topic_score_gemma":4.678916e-7,"teacher_disagreement_score":0.053122904,"about_ca_system_score_codex":0.000031033767,"about_ca_system_score_gemma":0.000044794288,"threshold_uncertainty_score":0.069683924},"labels":[],"label_agreement":null},{"id":"W1822844310","doi":"10.1016/j.neuroimage.2015.08.079","title":"STEAM — Statistical Template Estimation for Abnormality Mapping: A personalized DTI analysis technique with applications to the screening of preterm infants","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; Women's College Hospital; University of British Columbia; Hospital for Sick Children; BC Children's Hospital; University of Toronto; Children's & Women's Health Centre of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Government of Alberta","keywords":"Diffusion MRI; Computer science; Voxel; Artificial intelligence; Population; Smoothing; Template; Pipeline (software); White matter; Pattern recognition (psychology); Computer vision; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.13194532553374547,"score_gpt":0.3973218709353064,"score_spread":0.26537654540156097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1822844310","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01544441,0.000012216166,0.9790876,0.0014043864,0.0000046786017,0.003199468,0.00023904987,0.00017213917,0.0004360696],"genre_scores_gemma":[0.49387094,0.000002615952,0.5044292,0.0003428284,0.000019349762,0.0011369252,0.00009664568,0.000020885072,0.00008056242],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99880266,0.000045579745,0.00032266288,0.00035839994,0.00027425177,0.00019645307],"domain_scores_gemma":[0.99857175,0.0001775291,0.00017064347,0.0006379017,0.00027788998,0.00016425551],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033441224,0.00014711657,0.00030788544,0.0001422578,0.00011496111,0.000021707876,0.00017477748,0.00003676331,0.0000074624504],"category_scores_gemma":[0.00014855649,0.000106380656,0.00008485613,0.00085732044,0.00013510682,0.00008408877,0.00005898503,0.00016045851,0.0000023327252],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016660543,0.005101238,0.21336827,0.0037237676,0.0038530203,0.00024604454,0.008757159,0.0581374,0.29406464,0.09895849,0.044010703,0.2531187],"study_design_scores_gemma":[0.010099748,0.0048316633,0.2827608,0.0005684465,0.006846386,0.001023952,0.00085624674,0.3752501,0.057341788,0.011187246,0.24725437,0.0019792346],"about_ca_topic_score_codex":0.000026625317,"about_ca_topic_score_gemma":0.0000034713996,"teacher_disagreement_score":0.47842655,"about_ca_system_score_codex":0.000028373699,"about_ca_system_score_gemma":0.00006507742,"threshold_uncertainty_score":0.43380773},"labels":[],"label_agreement":null},{"id":"W1823166105","doi":"10.1371/journal.pone.0138910","title":"Spherical Deconvolution of Multichannel Diffusion MRI Data with Non-Gaussian Noise Models and Spatial Regularization","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Instituto de Salud Carlos III; European Regional Development Fund; Engineering and Physical Sciences Research Council","keywords":"Deconvolution; Voxel; Regularization (linguistics); Noise (video); Gaussian; Gaussian noise; Algorithm; Rician fading; Diffusion MRI; Computer science; Mathematics; Artificial intelligence; Physics; Magnetic resonance imaging","score_opus":0.15017531334030934,"score_gpt":0.314680585050419,"score_spread":0.16450527171010967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1823166105","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23747505,0.00003226049,0.76075304,0.0010058271,0.0000041227695,0.00042543752,0.000018734658,0.00006556407,0.0002199396],"genre_scores_gemma":[0.7914124,0.000062035426,0.20813814,0.00005581136,0.000041343294,0.000018294346,0.00014924839,0.000015671949,0.00010706482],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931985,0.000010232814,0.00013828393,0.0002396472,0.00020206564,0.00008992883],"domain_scores_gemma":[0.9992055,0.000012645639,0.000077150944,0.000486341,0.00010914875,0.00010916135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058424186,0.0000767049,0.000171244,0.000029915504,0.000030279985,0.0000050799713,0.00007638625,0.00003918594,0.0000027719066],"category_scores_gemma":[0.00004015779,0.00006295816,0.0000073060987,0.000099375226,0.000069884496,0.00013507655,0.0001073075,0.000079032325,0.0000011940099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026385866,0.01417117,0.06341548,0.0010177281,0.00029736402,0.00003770738,0.0016772782,0.0014882999,0.89105207,0.002745334,0.001410182,0.020048777],"study_design_scores_gemma":[0.0013747878,0.00034133866,0.004992169,0.00025305143,0.00019738913,0.000009986286,0.000034457193,0.96802765,0.022722693,0.0019097705,0.000037235746,0.00009949784],"about_ca_topic_score_codex":0.00008918844,"about_ca_topic_score_gemma":0.000011135458,"teacher_disagreement_score":0.9665393,"about_ca_system_score_codex":0.00002025781,"about_ca_system_score_gemma":0.000035297864,"threshold_uncertainty_score":0.25673592},"labels":[],"label_agreement":null},{"id":"W1826765467","doi":"10.1007/978-3-642-40760-4_64","title":"Diffusion Propagator Estimation from Sparse Measurements in a Tractography Framework","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Center for Research Resources; U.S. Public Health Service; National Institutes of Health","keywords":"Propagator; Diffusion MRI; Computer science; Tractography; Artificial intelligence; Diffusion; Voxel; Exponential function; Algorithm; Computer vision; Pattern recognition (psychology); Physics; Mathematics; Mathematical analysis","score_opus":0.05872241666313185,"score_gpt":0.3324979438030909,"score_spread":0.27377552713995906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1826765467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40986335,0.000020099655,0.5885399,0.0010841445,0.000050542963,0.00037935656,4.5098847e-7,0.000057198504,0.000004963604],"genre_scores_gemma":[0.5601325,0.0000030284443,0.43910947,0.0006787875,0.000029009138,0.000040680512,0.0000017634394,0.0000046415425,9.6962935e-8],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885327,0.000017202345,0.00018727493,0.00041021936,0.0003144879,0.0002175697],"domain_scores_gemma":[0.99932086,0.00010858001,0.000056004414,0.00037173711,0.00006652947,0.000076257485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013600235,0.00010934772,0.00014004567,0.00024046714,0.00006238453,0.000053878855,0.00021352702,0.000054308617,0.000015962452],"category_scores_gemma":[0.00017309176,0.0000888129,0.000025994701,0.0011362133,0.00014834716,0.00020542582,0.00007506833,0.0002852561,0.000010151581],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012692908,0.00027276383,0.22839803,0.000015450447,0.0000018733406,0.0000064184164,0.0005863791,0.0060742437,0.0733356,0.0000486772,0.0000130047165,0.6912349],"study_design_scores_gemma":[0.0003426883,0.000085246116,0.35829183,0.00036850857,0.0000046082755,0.000008290737,6.4120593e-7,0.5163373,0.0346535,0.089738294,0.000020645457,0.00014846606],"about_ca_topic_score_codex":0.00014297114,"about_ca_topic_score_gemma":0.0000101939095,"teacher_disagreement_score":0.6910864,"about_ca_system_score_codex":0.00006601056,"about_ca_system_score_gemma":0.00004767057,"threshold_uncertainty_score":0.36216852},"labels":[],"label_agreement":null},{"id":"W1831984264","doi":"10.1111/jon.12283","title":"The DTI Challenge: Toward Standardized Evaluation of Diffusion Tensor Imaging Tractography for Neurosurgery","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":172,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering","keywords":"Tractography; Diffusion MRI; Medicine; Neurosurgery; Pyramidal tracts; White matter; Medical physics; Radiology; Magnetic resonance imaging; Anatomy","score_opus":0.23813646896515533,"score_gpt":0.4263831107608204,"score_spread":0.18824664179566508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1831984264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.794384,0.005693147,0.11025164,0.084311485,0.0014390011,0.0023749582,0.000034761837,0.00017054623,0.0013404692],"genre_scores_gemma":[0.9926254,0.00055681303,0.005996389,0.0004827734,0.00025392423,0.000025189061,0.0000022810505,0.00004334,0.000013866208],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978088,0.00012814748,0.0007237801,0.00019019232,0.0009172914,0.00023176827],"domain_scores_gemma":[0.9957542,0.00042510443,0.00078892434,0.00032805288,0.0025424538,0.00016128486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002165199,0.00015739867,0.00037750686,0.0002448958,0.00013187206,0.00004159855,0.00018244138,0.000022643604,0.0000022242782],"category_scores_gemma":[0.0018204922,0.00010479162,0.00033426992,0.00026491418,0.0001240481,0.00022049798,0.000042431264,0.00032603816,2.824602e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00396665,0.0012686134,0.0768278,0.00028861678,0.00018134844,0.00015435458,0.0013102508,0.0006453142,0.21606557,0.00095753686,0.033124927,0.665209],"study_design_scores_gemma":[0.03566095,0.0034206142,0.19926564,0.0016836432,0.0042673713,0.0065067885,0.003693746,0.13861047,0.03593934,0.06070239,0.50894547,0.0013035594],"about_ca_topic_score_codex":0.000001616648,"about_ca_topic_score_gemma":1.487841e-7,"teacher_disagreement_score":0.66390544,"about_ca_system_score_codex":0.00006255356,"about_ca_system_score_gemma":0.00024163853,"threshold_uncertainty_score":0.42732784},"labels":[],"label_agreement":null},{"id":"W1834846057","doi":"10.1002/mrm.25852","title":"In vivo free‐breathing DTI and IVIM of the whole human heart using a real‐time slice‐followed SE‐EPI navigator‐based sequence: A reproducibility study in healthy volunteers","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche; LabEx PRIMES; Siemens USA","keywords":"Reproducibility; Intravoxel incoherent motion; Sequence (biology); Breathing; In vivo; Medicine; Nuclear medicine; Biomedical engineering; Magnetic resonance imaging; Chemistry; Diffusion MRI; Anatomy; Biology; Radiology; Chromatography","score_opus":0.14417269337912406,"score_gpt":0.4277169462949297,"score_spread":0.28354425291580565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1834846057","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9845334,0.001213238,0.000019308,0.011808209,0.00004720377,0.0021343892,0.000009899907,0.00005051678,0.00018381374],"genre_scores_gemma":[0.99405986,0.000037549118,0.004293059,0.0011967231,0.00006612136,0.0001379506,0.0000027700742,0.00003115105,0.00017480203],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99698514,0.00028265474,0.00086918153,0.0009835127,0.0005203924,0.0003591019],"domain_scores_gemma":[0.9974464,0.00014189543,0.00016319062,0.0019935803,0.00011115028,0.00014373845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002982992,0.00022464355,0.0007090652,0.0002355406,0.0000634933,0.0000062578483,0.0002759033,0.00008103819,0.000020399444],"category_scores_gemma":[0.0014108805,0.00017307428,0.00003700376,0.0012394675,0.00046863718,0.00008669636,0.00015093392,0.00054353726,5.8670423e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004336531,0.0007770868,0.88099927,0.00017562081,0.0000023184493,0.00013477948,0.005101506,0.0000988597,0.110004574,0.00003328289,0.0010790144,0.0011600468],"study_design_scores_gemma":[0.015129449,0.0042292005,0.9463899,0.003787303,0.00007433322,0.00014625983,0.0025681024,0.01805134,0.0018376175,0.0026234617,0.004761933,0.00040111403],"about_ca_topic_score_codex":0.016088014,"about_ca_topic_score_gemma":0.00086981,"teacher_disagreement_score":0.10816696,"about_ca_system_score_codex":0.00030237803,"about_ca_system_score_gemma":0.00022789103,"threshold_uncertainty_score":0.9904639},"labels":[],"label_agreement":null},{"id":"W1840441345","doi":"10.3389/fnana.2015.00069","title":"A stereotaxic, population-averaged T1w ovine brain atlas including cerebral morphology and tissue volumes","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Regional Development Fund; Freistaat Sachsen; Universität Leipzig; European Commission","keywords":"Brain morphometry; White matter; Population; Human brain; Brain size; Brain atlas; Biology; Anatomy; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.049700239167075354,"score_gpt":0.3387245445767364,"score_spread":0.28902430540966106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1840441345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97520614,0.00038726546,0.014928705,0.00760803,0.00025938213,0.000628797,0.000010044886,0.00023444188,0.0007371883],"genre_scores_gemma":[0.95395315,0.00003822607,0.04312007,0.0016099128,0.00008420135,0.00005554839,0.00004057427,0.00004305137,0.001055288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987706,0.00007046632,0.00028352393,0.00043256982,0.0001666584,0.00027621113],"domain_scores_gemma":[0.99927557,0.000044115888,0.00009271164,0.00034947545,0.000047803624,0.00019034262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014517609,0.00017658823,0.0003392995,0.00026952446,0.00007309261,0.000020448473,0.000117933414,0.00007769492,0.000012692441],"category_scores_gemma":[0.00023221056,0.00017952542,0.000031375486,0.0003280528,0.00009919253,0.0001504684,0.00013938101,0.000332296,0.0000052420132],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011971586,0.000100386926,0.867516,0.000043061733,0.000015623404,0.00026108994,0.00021079619,0.000025141357,0.0011495302,0.0007234206,0.10998985,0.019845419],"study_design_scores_gemma":[0.008608269,0.0008661474,0.6075121,0.00018246657,0.00012256335,0.0014713241,0.0004012581,0.026947828,0.0034382544,0.030169917,0.3193016,0.0009782331],"about_ca_topic_score_codex":0.00011495409,"about_ca_topic_score_gemma":0.000009218663,"teacher_disagreement_score":0.26000383,"about_ca_system_score_codex":0.00009185325,"about_ca_system_score_gemma":0.000035180474,"threshold_uncertainty_score":0.73208344},"labels":[],"label_agreement":null},{"id":"W1843575755","doi":"10.1007/11566465_16","title":"3D Curve Inference for Diffusion MRI Regularization","year":2005,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Diffusion MRI; Voxel; Regularization (linguistics); Inference; Imaging phantom; Artificial intelligence; Computer science; Mathematics; Algorithm; Physics; Magnetic resonance imaging; Medicine; Radiology; Optics","score_opus":0.03428829711341734,"score_gpt":0.34748213446659865,"score_spread":0.3131938373531813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1843575755","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014886357,0.000024820685,0.9791826,0.0052768923,0.00006402623,0.00042476025,0.0000014706415,0.00011767157,0.00002142471],"genre_scores_gemma":[0.5097185,0.000009011204,0.4890883,0.0010497192,0.00010337049,0.000019615592,0.0000037341752,0.0000044106946,0.0000034000548],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999141,0.000006949159,0.00013748455,0.000356429,0.0001640283,0.00019410411],"domain_scores_gemma":[0.9993332,0.00013215079,0.00004650912,0.00032861574,0.000106445405,0.000053089192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015234311,0.0000851533,0.0001051755,0.00012723885,0.00011989042,0.000032695578,0.00019180807,0.000036465437,0.0000039020324],"category_scores_gemma":[0.00015070285,0.00007176193,0.00002282035,0.0005893746,0.00015161856,0.00014479591,0.00009228085,0.00011650975,0.0000023796813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015572208,0.0000946519,0.0059899734,0.000020347725,8.9281787e-7,0.0000014500482,0.00025861285,0.024959883,0.028300442,0.0015017246,0.000030615345,0.93882585],"study_design_scores_gemma":[0.0003084308,0.00010785145,0.0048757386,0.00006664165,0.0000041618805,0.000017248287,1.34391e-7,0.9297436,0.04437613,0.018053314,0.002343217,0.00010354861],"about_ca_topic_score_codex":0.0000028808993,"about_ca_topic_score_gemma":0.0000050653357,"teacher_disagreement_score":0.9387223,"about_ca_system_score_codex":0.00006684451,"about_ca_system_score_gemma":0.00006732312,"threshold_uncertainty_score":0.2926367},"labels":[],"label_agreement":null},{"id":"W1847146623","doi":"10.1002/mrm.25363","title":"A model for extra‐axonal diffusion spectra with frequency‐dependent restriction","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Tortuosity; Diffusion; RADIUS; Spectral line; Monte Carlo method; White matter; Statistical physics; Materials science; Molecular physics; Physics; Biological system; Computational physics; Mechanics; Mathematics; Computer science; Thermodynamics","score_opus":0.05993902862841297,"score_gpt":0.32893073206625056,"score_spread":0.26899170343783757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1847146623","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1706146,0.0019102957,0.80704916,0.012955408,0.000063201274,0.0018297328,0.000010334401,0.0002183698,0.0053488915],"genre_scores_gemma":[0.85367763,0.001005339,0.14137512,0.00119576,0.00029123592,0.00058010605,0.000028531089,0.0000437634,0.0018025329],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986083,0.00001958438,0.00032732027,0.00042833603,0.0003335368,0.0002829418],"domain_scores_gemma":[0.9991903,0.00011629365,0.0000785178,0.00043022202,0.000080824015,0.00010386341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024225577,0.00017299272,0.0003086989,0.00014676472,0.00006661602,0.000005269684,0.000115357165,0.00006295274,0.00004303907],"category_scores_gemma":[0.0001628679,0.00012570916,0.00003095542,0.00027521656,0.00015838243,0.000043350203,0.00001844878,0.00024852046,0.0000024648489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022213112,0.0012418762,0.08958895,0.0005286389,0.000011604513,0.000110984874,0.0008826381,0.00091741554,0.20004359,0.096839316,0.011319156,0.5962945],"study_design_scores_gemma":[0.010795414,0.006047722,0.20694378,0.0015857825,0.00014833543,0.00029180592,0.00007991769,0.6045598,0.0010557061,0.12459758,0.0433652,0.0005289837],"about_ca_topic_score_codex":0.00006196249,"about_ca_topic_score_gemma":0.000045443623,"teacher_disagreement_score":0.68306303,"about_ca_system_score_codex":0.00007241906,"about_ca_system_score_gemma":0.000044121065,"threshold_uncertainty_score":0.51262707},"labels":[],"label_agreement":null},{"id":"W1847972783","doi":"10.1007/978-3-642-22092-0_58","title":"Rotation Invariant Completion Fields for Mapping Diffusion MRI Connectivity","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Rotation (mathematics); Imaging phantom; Spherical harmonics; Invariant (physics); Partial differential equation; Focus (optics); Artificial intelligence; Algorithm; Mathematics; Mathematical analysis; Physics","score_opus":0.09198212027283113,"score_gpt":0.3301112670399717,"score_spread":0.23812914676714053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1847972783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12568305,0.000006806837,0.8723743,0.0012301276,0.00009597266,0.0004918748,0.0000011583003,0.000086698055,0.000030031671],"genre_scores_gemma":[0.5950284,0.0000028793268,0.4041688,0.00072085107,0.00004335849,0.000029303823,0.0000025182967,0.0000035321318,3.7034434e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923897,0.000012147944,0.00013133863,0.0003262499,0.00012232471,0.00016899798],"domain_scores_gemma":[0.9994241,0.00013982423,0.00005491928,0.0002471684,0.00008985296,0.000044136097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023029798,0.00007785676,0.00011675118,0.00013013436,0.00014016613,0.000018230563,0.00013719968,0.000037877726,0.0000057531342],"category_scores_gemma":[0.00011211525,0.00006765648,0.000027758337,0.00042390855,0.000116783725,0.00010947512,0.00007361698,0.00012456148,0.0000012207382],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015685042,0.000543218,0.075133175,0.00016447739,0.000007688306,0.000021340087,0.0060490933,0.0048747123,0.13216917,0.008901144,0.00007706147,0.7719021],"study_design_scores_gemma":[0.00054265786,0.0002651047,0.109307624,0.00011349156,0.0000063927737,0.000047769674,0.0000020706705,0.7593282,0.05501559,0.07504603,0.00017377679,0.00015129226],"about_ca_topic_score_codex":0.00003689684,"about_ca_topic_score_gemma":0.000011715455,"teacher_disagreement_score":0.77175075,"about_ca_system_score_codex":0.000049733782,"about_ca_system_score_gemma":0.000039952924,"threshold_uncertainty_score":0.27589512},"labels":[],"label_agreement":null},{"id":"W1854006008","doi":"10.1016/j.jneumeth.2015.09.025","title":"A reliability assessment of constrained spherical deconvolution-based diffusion-weighted magnetic resonance imaging in individuals with chronic stroke","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Fractional anisotropy; Corticospinal tract; Tractography; Voxel; Superior longitudinal fasciculus; Magnetic resonance imaging; White matter; Stroke (engine); Effective diffusion coefficient; Arcuate fasciculus; Nuclear medicine; Psychology; Medicine; Radiology; Physics","score_opus":0.06964000050974346,"score_gpt":0.4333532296103157,"score_spread":0.36371322910057224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1854006008","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3861763,0.0003397519,0.6111612,0.0017589192,0.000078510595,0.00032571956,0.000007092123,0.000022684226,0.00012985853],"genre_scores_gemma":[0.4726101,0.000020604792,0.5271011,0.00022109452,0.000016368043,0.00000822138,2.4932643e-7,0.0000074179475,0.000014840121],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998017,0.0003161232,0.0006327287,0.00027288767,0.0005301692,0.00023108392],"domain_scores_gemma":[0.99830395,0.0003641571,0.0004660472,0.00032876557,0.00032773896,0.00020934234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016987943,0.00013193855,0.00039575272,0.00018763762,0.00004361784,0.00001553663,0.00024247267,0.000030069401,0.000008528749],"category_scores_gemma":[0.0008751857,0.00009533869,0.00007468951,0.0007290337,0.0005683215,0.00015053623,0.00004888485,0.0004069438,9.127094e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011754726,0.0006471136,0.4436099,0.000033869463,9.913447e-7,0.00007607771,0.00004439586,0.0007929492,0.5158205,0.00018192187,0.000069354304,0.038605392],"study_design_scores_gemma":[0.0030974578,0.0018753244,0.85700923,0.00024150997,0.00004348937,0.00042069893,0.000041015457,0.12045726,0.010803037,0.00081467157,0.0050577526,0.0001385617],"about_ca_topic_score_codex":0.000008748833,"about_ca_topic_score_gemma":7.897391e-7,"teacher_disagreement_score":0.50501746,"about_ca_system_score_codex":0.00022258842,"about_ca_system_score_gemma":0.0012166048,"threshold_uncertainty_score":0.38877988},"labels":[],"label_agreement":null},{"id":"W1854389798","doi":"","title":"Comparison of generalized autocalibrating partially parallel acquisitions and modified sensitivity encoding for diffusion tensor imaging.","year":2007,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Nuclear magnetic resonance; Nuclear medicine; White matter; Magnetic resonance imaging; Medicine; Scanner; Effective diffusion coefficient; Physics; Artificial intelligence; Computer science; Radiology","score_opus":0.11230532866843362,"score_gpt":0.3740393363990045,"score_spread":0.2617340077305709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1854389798","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32831493,0.00007732939,0.66762185,0.0017068953,0.000028326622,0.0014347838,0.000014766082,0.00018443735,0.00061668776],"genre_scores_gemma":[0.9274288,0.000011796856,0.071467124,0.00036518343,0.00007557185,0.0005522117,0.000026463245,0.000019361527,0.000053491218],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99898964,0.000021379712,0.0003430564,0.00024344493,0.000116536154,0.00028596932],"domain_scores_gemma":[0.99920386,0.00022639966,0.00015587431,0.00020060575,0.00008485415,0.00012842524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037956625,0.000111410554,0.00028098663,0.00007888781,0.00013975674,0.000015578293,0.00003410091,0.00003825812,0.0000013357441],"category_scores_gemma":[0.00015004222,0.00010301926,0.00006655289,0.000113760165,0.0000897748,0.00008082775,0.000046910856,0.00009320546,1.3769953e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009633684,0.0010608997,0.39301547,0.00032605915,0.00006694588,0.000032618467,0.000591218,0.0006895857,0.2837381,0.041093607,0.0015523047,0.2768698],"study_design_scores_gemma":[0.002422585,0.000060595237,0.76518035,0.00005365255,0.00015822456,0.0000709112,0.00010790872,0.16196787,0.06380764,0.0035817714,0.0023118262,0.00027668383],"about_ca_topic_score_codex":0.00001583749,"about_ca_topic_score_gemma":0.000006095305,"teacher_disagreement_score":0.5991139,"about_ca_system_score_codex":0.000023669543,"about_ca_system_score_gemma":0.000011214518,"threshold_uncertainty_score":0.42010036},"labels":[],"label_agreement":null},{"id":"W18545325","doi":"10.1007/978-3-642-23629-7_12","title":"Detecting Structure in Diffusion Tensor MR Images","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Structure tensor; Curse of dimensionality; Curvature; Feature (linguistics); Diffusion; Artificial intelligence; Differential (mechanical device); Manifold (fluid mechanics); Dimensionality reduction; Pattern recognition (psychology); Computer vision; Image (mathematics); Mathematics; Physics; Pure mathematics; Geometry; Magnetic resonance imaging","score_opus":0.045158095133525394,"score_gpt":0.31949255465252796,"score_spread":0.2743344595190026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W18545325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41738933,0.000021953707,0.5820369,0.00026627185,0.000050661445,0.00014588723,6.847612e-7,0.00006661188,0.000021676342],"genre_scores_gemma":[0.65069664,0.0000047947215,0.34873027,0.0005165527,0.00003988303,0.0000047696894,3.9711824e-7,0.0000061130013,6.178511e-7],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989951,0.000012493557,0.00015483928,0.00041472146,0.00016328075,0.0002595466],"domain_scores_gemma":[0.9994244,0.00006790361,0.000045644847,0.0003566787,0.000049027556,0.000056337045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012183591,0.0001086911,0.00013814392,0.00023333411,0.0000832532,0.000019631862,0.00024960178,0.00004279317,0.000012261022],"category_scores_gemma":[0.00012467986,0.00008574638,0.000021372072,0.000911167,0.00020191162,0.00011250294,0.00015888261,0.00031549434,0.0000015200765],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024232764,0.00008491995,0.17693174,0.000025711675,9.971185e-7,0.00007465974,0.0013557218,0.00086527935,0.24501179,0.00007021385,0.0000041272197,0.5755506],"study_design_scores_gemma":[0.00051572913,0.00018561388,0.35822815,0.00019088766,0.0000054209495,0.00022385652,0.0000028805628,0.09389675,0.5158971,0.030551514,0.000058600912,0.00024353963],"about_ca_topic_score_codex":0.00004736367,"about_ca_topic_score_gemma":0.000023109706,"teacher_disagreement_score":0.5753071,"about_ca_system_score_codex":0.000056890196,"about_ca_system_score_gemma":0.000040166567,"threshold_uncertainty_score":0.34966362},"labels":[],"label_agreement":null},{"id":"W1861127629","doi":"10.1007/978-3-642-18421-5_17","title":"A Texture Manifold for Curve-Based Morphometry of the Cerebral Cortex","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Artificial intelligence; Computer science; Orientation (vector space); Texture (cosmology); Computer vision; Salient; Geometry; Shape analysis (program analysis); Segmentation; Surface (topology); Pattern recognition (psychology); Image (mathematics); Mathematics","score_opus":0.056575578061976016,"score_gpt":0.3083700348121913,"score_spread":0.2517944567502153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1861127629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001959599,0.00012111773,0.9959203,0.0010804965,0.00021505776,0.0009821065,0.000035798337,0.00006792328,0.0013812388],"genre_scores_gemma":[0.69329923,0.00001244129,0.3013869,0.004129526,0.000235678,0.000042490865,0.000012881458,0.000055639128,0.00082522724],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99859554,0.000005689454,0.00027112899,0.000573051,0.00031578724,0.00023878069],"domain_scores_gemma":[0.9984185,0.00016861696,0.00023487856,0.0009413827,0.00017440393,0.00006221821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001613208,0.00023737352,0.0003377474,0.0002448994,0.00009714655,0.000016715718,0.0006863071,0.00015848326,0.000028113482],"category_scores_gemma":[0.000061405,0.00016175924,0.00016796078,0.0002892293,0.0004914817,0.000039977025,0.00019604525,0.0004638209,0.0000018658786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034774124,0.00054454186,0.011581253,0.0015803849,0.00008274161,0.00006693524,0.0006247457,0.0027243772,0.017720357,0.1792677,0.002200274,0.783259],"study_design_scores_gemma":[0.0025394172,0.0013837214,0.017815983,0.0036428054,0.000271237,0.00031096936,3.7640132e-7,0.121520035,0.07939004,0.7284815,0.043185305,0.0014586515],"about_ca_topic_score_codex":0.000008621957,"about_ca_topic_score_gemma":0.0000073326364,"teacher_disagreement_score":0.78180027,"about_ca_system_score_codex":0.0000736644,"about_ca_system_score_gemma":0.00025468445,"threshold_uncertainty_score":0.659635},"labels":[],"label_agreement":null},{"id":"W1870643104","doi":"10.1139/jpn.0741","title":"Corpus callosum abnormalities in women with borderline personality disorder and comorbid attention-deficit hyperactivity disorder","year":2007,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Borderline personality disorder; Psychology; Attention deficit hyperactivity disorder; Magnetic resonance imaging; Audiology; Neuroscience; Psychiatry; Medicine; Radiology","score_opus":0.024147707497322844,"score_gpt":0.32115468178687717,"score_spread":0.2970069742895543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1870643104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9880619,0.00038375639,0.006888378,0.004331485,0.000086668086,0.00012122656,0.00000487662,0.000013788311,0.00010793602],"genre_scores_gemma":[0.99553114,0.0005615846,0.003143891,0.0006401665,0.000042670188,0.0000032864446,3.4582067e-7,0.000008478213,0.0000684125],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991071,0.00002322787,0.0002678206,0.00018860918,0.000206276,0.00020696071],"domain_scores_gemma":[0.99944943,0.000058189504,0.00018522741,0.00011227572,0.000061165854,0.00013369322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003951271,0.00010619197,0.00019537758,0.00010802379,0.00013086441,0.00002303272,0.000067961686,0.00002759168,0.0000041451476],"category_scores_gemma":[0.000037995822,0.00007854091,0.00002133697,0.00025402027,0.00025677765,0.00024810527,0.000027038102,0.00033224156,1.0519808e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003390252,0.0003208653,0.9939075,0.000039188115,0.00000199793,0.000024153836,0.000035477675,0.0000075905355,0.00327596,0.0006349119,0.0000065139275,0.0014068277],"study_design_scores_gemma":[0.00093106355,0.00067113445,0.9938786,0.00006519435,0.00001383773,0.0012026499,0.00037997245,0.00008912346,0.000016540025,0.0003702758,0.0022942042,0.00008742573],"about_ca_topic_score_codex":0.000039594313,"about_ca_topic_score_gemma":0.00008918504,"teacher_disagreement_score":0.0074692797,"about_ca_system_score_codex":0.000017293904,"about_ca_system_score_gemma":0.00006317504,"threshold_uncertainty_score":0.32028052},"labels":[],"label_agreement":null},{"id":"W1902410198","doi":"10.3233/jad-150306","title":"White Matter Changes are Associated with Ventricular Expansion in Aging, Mild Cognitive Impairment, and Alzheimer’s Disease","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; National Institute on Aging; National Institutes of Health; IC Design Education Center; Canadian Institutes of Health Research; Biogen","keywords":"White matter; Neuroimaging; Diffusion MRI; Dementia; Neurodegeneration; Psychology; Cognitive decline; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Disease; Atrophy; Alzheimer's disease; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.07360605050306968,"score_gpt":0.33927411104680216,"score_spread":0.2656680605437325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1902410198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9673833,0.018696772,0.00022289362,0.01279085,0.000044913042,0.0007011005,0.00006895035,0.000047739042,0.000043485612],"genre_scores_gemma":[0.9971692,0.00016635512,0.0004040295,0.0020385867,0.00009298558,0.000038151964,0.000030059833,0.000036471905,0.000024187788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988195,0.00006576889,0.00028232933,0.0002296672,0.0003713054,0.00023144914],"domain_scores_gemma":[0.99818045,0.00003316756,0.00040057508,0.00018065708,0.00031233017,0.0008928105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017526765,0.00019187164,0.00031527944,0.00022714949,0.000047794332,0.00002573248,0.000072119765,0.000032596785,0.000028922297],"category_scores_gemma":[0.00006859625,0.00014535648,0.00007780168,0.00024752354,0.0000901609,0.0001815732,0.00005063719,0.0002481118,0.0000048671764],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094909314,0.00074415177,0.9900149,0.000016981567,0.00023423525,0.0020487492,0.00014865384,0.00001752611,0.000008334602,0.0000037620564,0.005452028,0.0003615712],"study_design_scores_gemma":[0.0030127561,0.00028587412,0.99159944,0.0011424391,0.0026117018,0.00008261836,0.00021004201,0.00014797876,0.00017128982,0.00022486008,0.00032919314,0.00018180803],"about_ca_topic_score_codex":0.0000036815534,"about_ca_topic_score_gemma":0.000002433603,"teacher_disagreement_score":0.029785875,"about_ca_system_score_codex":0.000042241485,"about_ca_system_score_gemma":0.00015073878,"threshold_uncertainty_score":0.59274656},"labels":[],"label_agreement":null},{"id":"W190629664","doi":"10.1007/978-3-642-40763-5_63","title":"Cardiac Fiber Inpainting Using Cartan Forms","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Villum Fonden","keywords":"Inpainting; Computer science; Connection (principal bundle); Interpolation (computer graphics); Curvature; Orientation (vector space); Artificial intelligence; Curvilinear coordinates; Computer vision; Fiber; Algorithm; Diffusion MRI; Tensor (intrinsic definition); Mathematics; Image (mathematics); Geometry; Materials science","score_opus":0.03970193718831911,"score_gpt":0.3337795257651178,"score_spread":0.2940775885767987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W190629664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3817677,0.000019431178,0.6171984,0.0006215366,0.000050462295,0.00022972986,3.003626e-7,0.00007312072,0.00003928636],"genre_scores_gemma":[0.63282835,0.000001630411,0.36638796,0.00068820897,0.00007428168,0.0000110595965,5.5273875e-7,0.0000063462335,0.0000016280658],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990563,0.000008663685,0.00013812548,0.00032966593,0.000184731,0.000282535],"domain_scores_gemma":[0.9993443,0.00009568973,0.0000403172,0.000357446,0.00008779984,0.00007443858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015745865,0.00009500613,0.00014085717,0.00012496828,0.00012518358,0.000058311103,0.0001774974,0.000031057527,0.00001590969],"category_scores_gemma":[0.000082870334,0.00007499496,0.000037221813,0.0007155576,0.00018645496,0.0002029676,0.00014089583,0.00018670231,0.000013035188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028917182,0.00004669469,0.04829767,0.000033662145,0.000004171046,0.00000995482,0.0004949656,0.010685552,0.15630999,0.000289324,0.000039509774,0.78378564],"study_design_scores_gemma":[0.00029497425,0.00011432412,0.032424036,0.00020975801,0.000014038322,0.0001071155,0.0000026031928,0.7972505,0.14247255,0.025804833,0.000949331,0.0003559488],"about_ca_topic_score_codex":0.000060287224,"about_ca_topic_score_gemma":0.0000010655723,"teacher_disagreement_score":0.78656495,"about_ca_system_score_codex":0.000081529375,"about_ca_system_score_gemma":0.00006234812,"threshold_uncertainty_score":0.30582058},"labels":[],"label_agreement":null},{"id":"W1929404890","doi":"10.1111/psyp.12565","title":"Microstructural white matter changes mediate age‐related cognitive decline on the Montreal Cognitive Assessment (MoCA)","year":2015,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University; Jewish General Hospital","funders":"","keywords":"Montreal Cognitive Assessment; Cognitive decline; White matter; Psychology; Cognition; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Gerontology; Cardiology; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Cognitive impairment; Disease; Dementia","score_opus":0.0625847552079232,"score_gpt":0.38543859345350506,"score_spread":0.3228538382455819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1929404890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95333064,0.000051094386,0.0005859873,0.03547188,0.0002455284,0.0010143225,0.00011349678,0.000172242,0.009014788],"genre_scores_gemma":[0.9805953,0.000058909834,0.0007909406,0.017036654,0.00019040222,0.00027417898,0.00032390904,0.00003564205,0.00069405895],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988502,0.00010278625,0.00019984756,0.00041246702,0.00014727816,0.0002873985],"domain_scores_gemma":[0.9990354,0.00024599183,0.0001358929,0.00027856452,0.00017172356,0.0001324113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009323068,0.00021268455,0.00029226605,0.000068272195,0.00009126318,0.000011914108,0.00012708231,0.000094693016,0.00015612191],"category_scores_gemma":[0.000057228288,0.000137461,0.000067945715,0.00017494189,0.00031536468,0.000028633463,0.0000821242,0.00041857891,0.00023575895],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008916511,0.0025359413,0.07905969,0.00013288154,0.0012020398,0.00065048784,0.005384069,0.00002391407,0.7015865,0.002219663,0.13386092,0.06442738],"study_design_scores_gemma":[0.005121074,0.0017541507,0.9320917,0.00016789522,0.0002504854,0.00017419392,0.0007048124,0.00026026525,0.010965539,0.046136227,0.0019404775,0.00043319564],"about_ca_topic_score_codex":0.00001885917,"about_ca_topic_score_gemma":0.0000069021053,"teacher_disagreement_score":0.853032,"about_ca_system_score_codex":0.000032754215,"about_ca_system_score_gemma":0.000030452153,"threshold_uncertainty_score":0.5605497},"labels":[],"label_agreement":null},{"id":"W1930375114","doi":"10.1109/isbi.2015.7163905","title":"Using 3D-SHORE and MAP-MRI to obtain both tractography and microstructural constrast from a clinical DMRI acquisition","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Human Connectome Project; Undersampling; Tractography; Diffusion MRI; Computer science; White matter; Artificial intelligence; Pattern recognition (psychology); Magnetic resonance imaging; Functional connectivity; Neuroscience; Radiology","score_opus":0.17042363007432199,"score_gpt":0.4361045140076044,"score_spread":0.26568088393328243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1930375114","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9282838,0.00013993435,0.06786389,0.0028726803,0.000039786817,0.0004007763,0.00004504398,0.0001355425,0.0002185201],"genre_scores_gemma":[0.70343316,0.000030270692,0.2947624,0.0016244622,0.00008926177,0.0000058729966,0.000025742343,0.000011492656,0.000017351791],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992079,0.00002197416,0.00022738072,0.00031604563,0.00008709465,0.00013958281],"domain_scores_gemma":[0.99937016,0.000060000806,0.000047442445,0.00018315094,0.00005151008,0.00028776418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010237077,0.00011469899,0.00020610745,0.000060538772,0.000049060298,0.000030744268,0.000035831115,0.00006561106,0.000018909524],"category_scores_gemma":[0.00002089108,0.000095795,0.000034304834,0.00009948272,0.00018088588,0.00007320147,0.000049412654,0.00014797765,0.0000019774927],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005382678,0.00021860277,0.79443765,0.000044857687,0.00007415282,0.00006409872,0.0006452699,0.000005584241,0.14158651,0.0017846309,0.010664215,0.049936157],"study_design_scores_gemma":[0.006973518,0.0013415106,0.89822495,0.0003949887,0.00052016956,0.0012236056,0.0022612624,0.007397469,0.013985595,0.025725521,0.040861182,0.0010902294],"about_ca_topic_score_codex":0.000071229704,"about_ca_topic_score_gemma":0.000005514246,"teacher_disagreement_score":0.2268985,"about_ca_system_score_codex":0.0000108480335,"about_ca_system_score_gemma":0.000027196551,"threshold_uncertainty_score":0.3906407},"labels":[],"label_agreement":null},{"id":"W1932112317","doi":"10.1002/ajmg.b.32354","title":"A magnetic resonance imaging family study of cortical thickness in schizophrenia","year":2015,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part B Neuropsychiatric Genetics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; University Grants Committee; Health Research Board; University of Calgary","keywords":"Schizophrenia (object-oriented programming); Abnormality; Psychology; Psychosis; Magnetic resonance imaging; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.04792218276242896,"score_gpt":0.3500492225481932,"score_spread":0.3021270397857643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1932112317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848606,0.009335229,0.002778834,0.0020156468,0.00038629473,0.00045110655,0.000004088182,0.000028478653,0.00013975255],"genre_scores_gemma":[0.97264326,0.0031366185,0.022889208,0.00094959344,0.00029686623,0.000012521972,0.000001054485,0.000059297734,0.000011601708],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99536693,0.0003541209,0.0015255857,0.00039187176,0.0019529342,0.00040854976],"domain_scores_gemma":[0.9972054,0.00019144271,0.0006560097,0.0006451742,0.0005044298,0.00079759327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008974549,0.0002707434,0.000785871,0.00040878856,0.000043379845,0.000016946788,0.0006572011,0.000065837645,0.000012587775],"category_scores_gemma":[0.0005260947,0.00023916064,0.00012565407,0.001483357,0.000529203,0.000029730129,0.00018847879,0.0010864484,0.0000040101695],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001219307,0.004589249,0.5690756,0.00004795227,0.000023764978,0.0009681889,0.00078612874,0.00049035705,0.0012122726,0.00011656059,0.0023050664,0.41916558],"study_design_scores_gemma":[0.01407097,0.019533131,0.92826664,0.00033899237,0.00054187665,0.0035277759,0.0037718792,0.008180578,0.00016506427,0.0009979279,0.019995145,0.00060999946],"about_ca_topic_score_codex":0.000023295308,"about_ca_topic_score_gemma":0.0000064226315,"teacher_disagreement_score":0.4185556,"about_ca_system_score_codex":0.00004257538,"about_ca_system_score_gemma":0.000772367,"threshold_uncertainty_score":0.9752688},"labels":[],"label_agreement":null},{"id":"W1947057053","doi":"10.1002/ca.22349","title":"Spinal diffusion tensor imaging: A comprehensive review with emphasis on spinal cord anatomy and clinical applications","year":2014,"lang":"en","type":"review","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Diffusion MRI; Tractography; Medicine; Spinal cord; Magnetic resonance imaging; Neuroscience; Anatomy; Radiology; Psychology","score_opus":0.20652838312261718,"score_gpt":0.5499473226266137,"score_spread":0.34341893950399655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1947057053","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000040318097,0.9859084,0.0038242762,0.0039294674,0.00008229375,0.0052540153,0.00005290388,0.00039630925,0.00051201246],"genre_scores_gemma":[0.00006390006,0.98079497,0.0095364,0.0072839004,0.00066576025,0.0011392673,0.00020143334,0.00014846819,0.00016590775],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9941377,0.00040647428,0.00262665,0.0018689402,0.00046690868,0.00049334654],"domain_scores_gemma":[0.9946166,0.0009926318,0.0013394065,0.0018646338,0.00042821604,0.00075851346],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00067794876,0.0008419457,0.004408171,0.00021764447,0.00024252439,0.000042681226,0.00050034607,0.00038631307,0.000038278973],"category_scores_gemma":[0.0003620027,0.0005763296,0.0011983158,0.00071941566,0.0011176165,0.000059576632,0.00030165844,0.0021593801,0.0001723087],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021117728,0.0006458598,0.0010805031,0.01678294,0.00012638324,0.00009633616,2.3627163e-7,4.2742156e-9,2.7635393e-8,0.0009546125,0.0051431847,0.9749587],"study_design_scores_gemma":[0.0010066294,0.0025810008,0.0017856137,0.056518268,0.0034203492,0.0009130185,0.000002523762,0.00001951019,5.864364e-8,0.00018375933,0.93301445,0.0005548121],"about_ca_topic_score_codex":0.000005056474,"about_ca_topic_score_gemma":6.491528e-7,"teacher_disagreement_score":0.9744039,"about_ca_system_score_codex":0.00007812318,"about_ca_system_score_gemma":0.00031317628,"threshold_uncertainty_score":0.99966884},"labels":[],"label_agreement":null},{"id":"W1947571038","doi":"10.1002/ana.24318","title":"Magnetic resonance imaging and histology correlation in the neocortex in temporal lobe epilepsy","year":2014,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Magnetic resonance imaging; Diffusion MRI; Neocortex; Epilepsy; Fractional anisotropy; Temporal lobe; Relaxometry; Epilepsy surgery; Pathology; Medicine; Correlation; Radiology; Nuclear medicine; Psychology; Neuroscience; Spin echo; Mathematics","score_opus":0.05706631913948104,"score_gpt":0.3483404934136802,"score_spread":0.2912741742741991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1947571038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9441649,0.0014053469,0.0012861992,0.051399205,0.000033252498,0.00033256828,0.0000015696048,0.000028462762,0.0013485007],"genre_scores_gemma":[0.9870076,0.00021123426,0.00047306105,0.012222586,0.000019890786,0.000030892854,0.0000039192796,0.000008054409,0.000022767974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925625,0.00011425304,0.00022167651,0.00020455272,0.0000528141,0.0001504254],"domain_scores_gemma":[0.99945474,0.00019198767,0.00007220649,0.00023497481,0.000025960997,0.000020154155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020955762,0.000069258254,0.00017297747,0.00011460624,0.000018190958,0.0000018787473,0.00008269146,0.000040550483,0.000005592387],"category_scores_gemma":[0.0001209051,0.000057635538,0.00001924601,0.0001541841,0.00016645924,0.000032872456,0.000028468985,0.00023373877,0.000001646899],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011390948,0.0000783634,0.94582653,0.000010794653,2.9395449e-7,0.0000450379,0.00009578132,0.000011789276,0.0008000128,0.0064366465,0.0010782531,0.04550256],"study_design_scores_gemma":[0.00035726343,0.0003698424,0.9296458,0.00001075648,0.000003460619,0.00022189763,0.000006015606,0.005434072,0.000037195423,0.01269631,0.0511756,0.000041778178],"about_ca_topic_score_codex":0.00008015863,"about_ca_topic_score_gemma":0.000037914124,"teacher_disagreement_score":0.05009735,"about_ca_system_score_codex":0.0000019899283,"about_ca_system_score_gemma":0.000009722855,"threshold_uncertainty_score":0.2350309},"labels":[],"label_agreement":null},{"id":"W1956119885","doi":"10.1002/hbm.22795","title":"Visualization and segmentation of reciprocal cerebrocerebellar pathways in the healthy and injured brain","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; Pediatric Oncology Group","funders":"Hospital for Sick Children","keywords":"Tractography; Diffusion MRI; White matter; Cerebellum; Neuroscience; Cohort; Psychology; Medicine; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.16246080296942378,"score_gpt":0.39720303049791067,"score_spread":0.2347422275284869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1956119885","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96519977,0.0001257006,0.026263077,0.007229784,0.000007594882,0.00063059846,0.0000028647783,0.000055858785,0.00048475535],"genre_scores_gemma":[0.99316615,0.000022253937,0.0031922131,0.0034819022,0.000032787193,0.000034860313,0.000032299762,0.0000110063565,0.000026510097],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999363,0.00006538463,0.00020185922,0.0001608729,0.00011592258,0.00009294966],"domain_scores_gemma":[0.9996148,0.0000858756,0.0000851869,0.00012890893,0.00003957334,0.00004570087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041868407,0.00006811295,0.0001177996,0.0000945591,0.000077780795,0.0000117010795,0.00003834631,0.000032586686,0.0000017021954],"category_scores_gemma":[0.000118973156,0.000056888253,0.000010343361,0.00018200409,0.000064762084,0.0000579524,0.000027725067,0.00008981531,3.1305385e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022214567,0.0004472398,0.1076176,0.0009700858,0.000023062941,0.000014221615,0.047759943,0.000011328286,0.5954318,0.19674496,0.023683986,0.027073639],"study_design_scores_gemma":[0.008031572,0.0020271514,0.80743325,0.00082917186,0.00005135224,0.00023081893,0.019222612,0.0060154223,0.004598793,0.11467766,0.03630638,0.00057579105],"about_ca_topic_score_codex":0.000018860237,"about_ca_topic_score_gemma":0.0000107408905,"teacher_disagreement_score":0.6998157,"about_ca_system_score_codex":0.000025887344,"about_ca_system_score_gemma":0.000021631939,"threshold_uncertainty_score":0.23198357},"labels":[],"label_agreement":null},{"id":"W1958816175","doi":"10.1111/jon.12268","title":"Quantitative Mapping of Human Brain Vertical‐Occipital Fasciculus","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fasciculus; Diffusion MRI; Fractional anisotropy; Tractography; Inferior longitudinal fasciculus; Medicine; Uncinate fasciculus; Superior longitudinal fasciculus; Neuroscience; Anatomy; Medial longitudinal fasciculus; Magnetic resonance imaging; Psychology; Radiology; Midbrain; Central nervous system","score_opus":0.19372760595790758,"score_gpt":0.4214888592713708,"score_spread":0.22776125331346322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1958816175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95493895,0.00016640902,0.03244832,0.010369184,0.00009931765,0.00014832644,0.0000020611017,0.00004665404,0.0017807536],"genre_scores_gemma":[0.9746676,0.000010811267,0.024400175,0.00074005284,0.000095456235,0.0000016502923,0.0000011512902,0.00002370276,0.000059397105],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99876934,0.000045775803,0.00054148893,0.00013771148,0.00033600297,0.00016967654],"domain_scores_gemma":[0.9987784,0.00012110468,0.00027337816,0.00021105714,0.0004209421,0.00019514078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003154363,0.000110737856,0.00033344148,0.00023211077,0.00004681903,0.000014965875,0.00014634279,0.000021676671,0.0000060104285],"category_scores_gemma":[0.0005646792,0.000094963776,0.00013836147,0.00027915824,0.00012406273,0.00020631892,0.00006113319,0.00034960837,0.0000032233459],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012904376,0.0002951665,0.015479048,0.00006145226,0.000040662475,0.00037334696,0.0007895283,0.000052120333,0.96775705,0.0052960822,0.007816312,0.0019102183],"study_design_scores_gemma":[0.021340538,0.017350698,0.41215077,0.0041182376,0.0011029394,0.020198757,0.010092558,0.021060828,0.3308055,0.0816063,0.078187056,0.0019858067],"about_ca_topic_score_codex":0.0000041635462,"about_ca_topic_score_gemma":1.5433177e-7,"teacher_disagreement_score":0.6369515,"about_ca_system_score_codex":0.000047770747,"about_ca_system_score_gemma":0.000087918364,"threshold_uncertainty_score":0.38725102},"labels":[],"label_agreement":null},{"id":"W1963512073","doi":"10.1002/cmr.b.20134","title":"Magnetic resonance imaging with composite (dual) gradients","year":2009,"lang":"en","type":"article","venue":"Concepts in Magnetic Resonance Part B","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Dental and Craniofacial Research; National Institute on Deafness and Other Communication Disorders; National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; National Institutes of Health","keywords":"Magnetic resonance imaging; Dual (grammatical number); Composite number; Nuclear magnetic resonance; Materials science; Functional magnetic resonance imaging; Psychology; Medicine; Physics; Neuroscience; Art; Radiology; Composite material","score_opus":0.026903926246213683,"score_gpt":0.3257950959079198,"score_spread":0.2988911696617061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963512073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7068531,0.20924823,0.0025068792,0.015876297,0.00031178375,0.004674765,0.00007082308,0.0013113976,0.05914675],"genre_scores_gemma":[0.9586507,0.0015569259,0.030972665,0.0040908307,0.00015395478,0.00022287454,0.000023557766,0.000057366957,0.0042711],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9978197,0.000050559556,0.00044796165,0.0007246273,0.0003582168,0.0005988861],"domain_scores_gemma":[0.9987409,0.00006783174,0.00009664826,0.0008173408,0.00010357532,0.00017371771],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012954963,0.00031228646,0.00041697884,0.00012832704,0.00012309918,0.000035941743,0.00023402474,0.000056509092,0.00013444181],"category_scores_gemma":[0.00004515595,0.00028140142,0.00006387399,0.00062378496,0.0003834173,0.00012540884,0.000051980307,0.00039747325,0.000040543695],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030438838,0.00037699076,0.13405316,0.000025774603,0.000001164963,0.0005124857,0.00027456778,0.00001548347,0.004272985,0.0040347558,0.006461828,0.8496664],"study_design_scores_gemma":[0.0021546073,0.0007982538,0.5090772,0.0005968297,0.000026335856,0.00026955706,0.000037482747,0.0011254601,0.0010944934,0.002193254,0.48227507,0.00035143452],"about_ca_topic_score_codex":0.000014792369,"about_ca_topic_score_gemma":0.00000620468,"teacher_disagreement_score":0.849315,"about_ca_system_score_codex":0.000096114265,"about_ca_system_score_gemma":0.000059596743,"threshold_uncertainty_score":0.9999638},"labels":[],"label_agreement":null},{"id":"W1963531852","doi":"10.1016/j.mri.2008.11.009","title":"Alteration of diffusion tensor parameters in postmortem brain","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Alberta Children's Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Autopsy; Postmortem Changes; White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Internal capsule; Anatomy; Brain tissue; Autolysis (biology); Fixation (population genetics); Pathology; Medicine; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Radiology","score_opus":0.028318049218847282,"score_gpt":0.32386317757864297,"score_spread":0.2955451283597957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963531852","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9684224,0.0022345996,0.0066299126,0.020478442,0.000023280696,0.0006221789,0.000004210867,0.000119187454,0.0014657544],"genre_scores_gemma":[0.9611309,0.00011259533,0.035836123,0.0025045737,0.000020271329,0.000022309494,0.000007820138,0.000012295938,0.00035311753],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991192,0.000019538646,0.0002866756,0.00024737514,0.00014511064,0.00018209522],"domain_scores_gemma":[0.99948704,0.00004876257,0.000068282374,0.00030741456,0.000044929115,0.0000435756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009211557,0.00010307064,0.00018332465,0.00011912613,0.000028419374,0.000010287524,0.000074378986,0.00001985878,0.000012500421],"category_scores_gemma":[0.00009179315,0.000097490614,0.000042822452,0.00025734756,0.00005555527,0.00007338181,0.000017373643,0.00013036256,0.000002785049],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077710385,0.00020286873,0.09983498,0.000020546873,4.3061345e-7,0.00005047236,0.00012547433,0.000026089003,0.13777672,0.0009571368,0.0010517675,0.75987583],"study_design_scores_gemma":[0.0009879064,0.00027083192,0.95273036,0.00027002514,0.000010929442,0.00008550079,0.000031094234,0.019937944,0.010248925,0.0030983705,0.012186632,0.00014150141],"about_ca_topic_score_codex":0.000026631895,"about_ca_topic_score_gemma":0.0000010510071,"teacher_disagreement_score":0.8528954,"about_ca_system_score_codex":0.00003081679,"about_ca_system_score_gemma":0.000017782711,"threshold_uncertainty_score":0.3975552},"labels":[],"label_agreement":null},{"id":"W1963887794","doi":"10.1371/journal.pone.0075061","title":"A Connectome-Based Comparison of Diffusion MRI Schemes","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"Centre Hospitalier Universitaire Vaudois; Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; École Polytechnique Fédérale de Lausanne","keywords":"Diffusion MRI; Diffusion imaging; Computer science; Connectome; Fractional anisotropy; Artificial intelligence; Human Connectome Project; Pattern recognition (psychology); Magnetic resonance imaging; Neuroscience; Medicine; Biology; Functional connectivity","score_opus":0.14972148776896047,"score_gpt":0.35274573444311697,"score_spread":0.2030242466741565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1963887794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848855,0.000071247305,0.009951324,0.003495936,0.0000029916519,0.00055404584,0.0000034456414,0.00017840591,0.00085706887],"genre_scores_gemma":[0.91888565,0.000015652207,0.08048516,0.00030355147,0.00001886803,0.00010114069,0.000014411885,0.0000123174395,0.0001632711],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99946916,0.0000073499523,0.0001558671,0.00012237027,0.00015309727,0.00009217621],"domain_scores_gemma":[0.9994446,0.00005165328,0.00006972652,0.00027261546,0.000106681066,0.0000547251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002122893,0.00006185333,0.0002140999,0.000048822374,0.000027465214,0.0000037845293,0.000054662458,0.000026960812,0.0001957614],"category_scores_gemma":[0.00004918994,0.00005354611,0.000030575487,0.00011125425,0.000049725542,0.000027203661,0.000023021306,0.000096132906,0.000040949406],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017989798,0.0028062698,0.08065689,0.00014176096,0.000019626876,4.6339255e-7,0.000027194572,0.0000010786448,0.91372657,0.00060082576,0.00093191804,0.0010693888],"study_design_scores_gemma":[0.0006555404,0.00022560322,0.016928855,0.00028975494,0.00007966625,5.930193e-7,0.00001972708,0.014797751,0.96528876,0.00061768503,0.0010173505,0.00007872847],"about_ca_topic_score_codex":0.000013415169,"about_ca_topic_score_gemma":3.074949e-7,"teacher_disagreement_score":0.070533834,"about_ca_system_score_codex":0.000011845425,"about_ca_system_score_gemma":0.000014044464,"threshold_uncertainty_score":0.2183547},"labels":[],"label_agreement":null},{"id":"W1964048159","doi":"10.1159/000097371","title":"Gross Anatomy of the Corpus Callosum in Alzheimer’s Disease: Regions of Degeneration and Their Neuropsychological Correlates","year":2006,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; Neuropsychology; Psychology; Degenerative disease; Dementia; Alzheimer's disease; Neuroscience; Audiology; Central nervous system disease; Anatomy; Disease; Medicine; Pathology; Cognition","score_opus":0.02145171469897885,"score_gpt":0.3069777132471275,"score_spread":0.2855259985481487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964048159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900893,0.0040349774,0.0040502017,0.0009940598,0.000021627526,0.0004969822,0.000036973357,0.00001598492,0.00025986976],"genre_scores_gemma":[0.9987252,0.0009669942,0.00010590668,0.00010371452,0.000009438058,0.000039565813,0.000030835727,0.0000072142625,0.000011163909],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945545,0.00003418359,0.00018442357,0.00017926583,0.000058571655,0.00008813283],"domain_scores_gemma":[0.9996649,0.00006487423,0.00009853769,0.00009439034,0.00004854667,0.000028761478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004048847,0.000084853484,0.00012586976,0.000056243854,0.000055573677,0.000004146171,0.000033224085,0.000025950554,0.0000043600976],"category_scores_gemma":[0.000027756992,0.000058903042,0.00004213883,0.0002451232,0.00019592325,0.00002833201,0.000038208458,0.00007447605,9.88877e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013710702,0.00032487678,0.9814659,0.000024338755,0.000030901374,0.000002086676,0.000062432795,0.0000068150616,0.0025496176,0.0038442046,0.00017080673,0.011380938],"study_design_scores_gemma":[0.0007850035,0.000059151054,0.9902491,0.000028080744,0.000195214,0.0000048406428,0.00007434935,0.0002766089,0.0007484061,0.0071379095,0.00037789918,0.0000634189],"about_ca_topic_score_codex":0.000046353543,"about_ca_topic_score_gemma":0.000030909985,"teacher_disagreement_score":0.0113175195,"about_ca_system_score_codex":0.0000021009325,"about_ca_system_score_gemma":0.000013235417,"threshold_uncertainty_score":0.24019964},"labels":[],"label_agreement":null},{"id":"W1964447312","doi":"10.1191/1352458504ms1036oa","title":"Cervical cord atrophy assessment on magnetic resonance imaging: PRO MiSe trial","year":2004,"lang":"en","type":"review","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Medicine; Magnetic resonance imaging; Multiple sclerosis; Atrophy; Spinal cord; Clinical trial; Cord; Nuclear medicine; Radiology; Surgery; Pathology","score_opus":0.26893492290091914,"score_gpt":0.4225708523278115,"score_spread":0.15363592942689236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964447312","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024118073,0.99242085,0.0019342329,0.00087507255,0.00056662,0.0033520274,0.00006588335,0.00023924507,0.0005219589],"genre_scores_gemma":[0.00026944067,0.9617783,0.035201192,0.00037767916,0.0012465987,0.0005755026,0.0000551452,0.00017203548,0.00032412686],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965044,0.00017455207,0.0012177895,0.00076326105,0.0007460132,0.0005939528],"domain_scores_gemma":[0.99755645,0.00022974994,0.00068246835,0.0008868486,0.00018151909,0.00046297623],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00032416105,0.00065586384,0.0016852643,0.0003163537,0.0003689133,0.00016199097,0.0004932498,0.00021250294,0.00016132939],"category_scores_gemma":[0.00017538374,0.00050733576,0.0010575295,0.0004413707,0.00016001928,0.000090526315,0.00012781302,0.0023567735,0.000075664146],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013410811,0.00066079735,0.000039856848,0.0012244519,0.000019816316,0.00010804872,0.0000058589026,0.0000014356622,0.00001409141,0.00008800831,0.0021723085,0.99432427],"study_design_scores_gemma":[0.017604645,0.0013898078,0.00040883632,0.024604555,0.00063763466,0.0007920388,0.0000033405324,0.000058592603,0.0000041128196,0.00017989759,0.95388776,0.00042880193],"about_ca_topic_score_codex":0.000005736004,"about_ca_topic_score_gemma":4.1863808e-7,"teacher_disagreement_score":0.9938955,"about_ca_system_score_codex":0.0008436849,"about_ca_system_score_gemma":0.00069969846,"threshold_uncertainty_score":0.9999448},"labels":[],"label_agreement":null},{"id":"W1964469261","doi":"10.1002/hbm.20995","title":"Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Centers for Disease Control and Prevention","keywords":"Diffusion MRI; Fractional anisotropy; Linear discriminant analysis; Psychology; Magnetic resonance imaging; Artificial intelligence; Medicine; Audiology; Nuclear medicine; Pattern recognition (psychology); Radiology; Computer science; Cognitive psychology","score_opus":0.02383509416645939,"score_gpt":0.29040974318599344,"score_spread":0.26657464901953404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964469261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.986308,0.000019637462,0.008007074,0.0042119958,0.00007299989,0.0005543436,0.000020813326,0.00047828286,0.00032685435],"genre_scores_gemma":[0.97390777,0.0000038823187,0.022988064,0.0023612978,0.00017718629,0.00005513131,0.00024120953,0.0000598848,0.00020559428],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987064,0.000018272007,0.00026154914,0.0004709601,0.00023303366,0.0003097978],"domain_scores_gemma":[0.99896824,0.00007549134,0.0001247201,0.00056363177,0.00011060805,0.00015731397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000063696054,0.00020929429,0.00024751519,0.00014411153,0.00042961477,0.000043360476,0.00014888884,0.000049312086,0.000112503345],"category_scores_gemma":[0.00006761493,0.00017236402,0.000058992402,0.00015859777,0.00012154092,0.00010461206,0.000087490305,0.00053261296,0.00002017123],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012961379,0.00024658252,0.7775729,0.000038526843,0.000016079628,0.0000075739395,0.00017775512,7.6831014e-7,0.21436745,0.0010450658,0.0037948133,0.002602916],"study_design_scores_gemma":[0.0020869782,0.00007952735,0.9845631,0.00018781326,0.000025939218,0.0000046528016,0.000040599316,0.00051590207,0.00015989704,0.0020449772,0.010080123,0.0002104787],"about_ca_topic_score_codex":0.00011485732,"about_ca_topic_score_gemma":0.000026777618,"teacher_disagreement_score":0.21420754,"about_ca_system_score_codex":0.00003397723,"about_ca_system_score_gemma":0.000022243212,"threshold_uncertainty_score":0.70288},"labels":[],"label_agreement":null},{"id":"W1964752900","doi":"10.1109/isbi.2014.6867974","title":"DTI-DeformIt: Generating ground-truth validation data for diffusion tensor image analysis tasks","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Artificial intelligence; Ground truth; Image (mathematics); Noise (video); Computer vision; Eigenvalues and eigenvectors; Diffusion; Pattern recognition (psychology); Mathematics","score_opus":0.11847501302179933,"score_gpt":0.3941550786239827,"score_spread":0.2756800656021834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964752900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07751589,0.0000071597756,0.9189877,0.001326988,0.000024009281,0.0004545538,0.00006757052,0.00029630342,0.0013198094],"genre_scores_gemma":[0.5192506,0.000016753303,0.4767344,0.0006201879,0.00020101765,0.000081781625,0.0021627736,0.000025385514,0.00090715656],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989337,0.000017859249,0.00026583203,0.00045609433,0.00014578871,0.00018077766],"domain_scores_gemma":[0.9983685,0.00012398325,0.00010977353,0.0012001747,0.000120046614,0.00007754928],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002556654,0.0001238441,0.00024144641,0.00013815043,0.0001869697,0.00004415735,0.00019939696,0.00004317904,0.00005438443],"category_scores_gemma":[0.00029004648,0.00009547709,0.000095363335,0.000366065,0.00003331224,0.00020583461,0.00014115704,0.00008763646,0.000009268144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016268337,0.0009254867,0.023349455,0.00029055192,0.00057189935,0.0000051297948,0.00012028794,0.00045017275,0.72177494,0.049787868,0.01672046,0.18584105],"study_design_scores_gemma":[0.0010554628,0.00016672509,0.00834121,0.00002287327,0.0014818588,0.000020666987,0.00005710224,0.9288252,0.020364558,0.0034170733,0.035945296,0.00030196158],"about_ca_topic_score_codex":0.000041855696,"about_ca_topic_score_gemma":0.0000056462754,"teacher_disagreement_score":0.92837507,"about_ca_system_score_codex":0.000027197639,"about_ca_system_score_gemma":0.000012583413,"threshold_uncertainty_score":0.38934425},"labels":[],"label_agreement":null},{"id":"W1965000453","doi":"10.1002/mrm.21977","title":"Aldehyde fixative solutions alter the water relaxation and diffusion properties of nervous tissue","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":309,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Fixative; Formaldehyde; Glutaraldehyde; Nervous tissue; Chemistry; Fixation (population genetics); Brain tissue; Paraformaldehyde; Central nervous system; Biophysics; Chromatography; Anatomy; Biochemistry; Biology; Neuroscience","score_opus":0.05351128851339552,"score_gpt":0.31812302749269455,"score_spread":0.264611738979299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965000453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89020604,0.00947073,0.0015796237,0.09630951,0.000029321549,0.0010888057,0.0000017867814,0.00006433339,0.0012498641],"genre_scores_gemma":[0.9945355,0.001414947,0.0013847048,0.0012343123,0.000070255825,0.00006321866,0.0000054375478,0.000008812817,0.0012827925],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991364,0.000035195568,0.00028038325,0.0001936352,0.00017642381,0.00017794532],"domain_scores_gemma":[0.9995231,0.00003545999,0.000056762205,0.0002850608,0.000062474835,0.000037139907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001813308,0.00010240916,0.00020587273,0.00007132972,0.00007741526,0.0000031503953,0.000075748176,0.00003717256,0.000037145415],"category_scores_gemma":[0.00011862579,0.00004561407,0.000014239057,0.00015694082,0.00032164587,0.000039178638,0.00003452,0.00017177698,0.0000022083457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120249504,0.00013857217,0.0022909418,0.000051439696,0.0000015554122,0.000013281408,0.0028456314,0.000006746742,0.64683354,0.0010872832,0.0018245069,0.34478623],"study_design_scores_gemma":[0.0031542277,0.0035174363,0.72495604,0.0024774864,0.00010251547,0.00022266386,0.0005961915,0.0048391735,0.11397166,0.016971719,0.12890038,0.0002905101],"about_ca_topic_score_codex":0.00008251442,"about_ca_topic_score_gemma":0.0000080754735,"teacher_disagreement_score":0.7226651,"about_ca_system_score_codex":0.00001989859,"about_ca_system_score_gemma":0.000010240657,"threshold_uncertainty_score":0.18600878},"labels":[],"label_agreement":null},{"id":"W1965033190","doi":"10.3171/jns-07/09/0509","title":"Diffusion tensor imaging analysis of long association bundles in the presence of an arteriovenous malformation","year":2007,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal; Hôpital Notre-Dame; Université de Montréal","funders":"","keywords":"Arcuate fasciculus; Medicine; Diffusion MRI; Anatomy; Inferior longitudinal fasciculus; Fasciculus; White matter; Superior longitudinal fasciculus; Magnetic resonance imaging; Radiology; Fractional anisotropy","score_opus":0.035055606811048044,"score_gpt":0.33693906236866666,"score_spread":0.30188345555761864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965033190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875488,0.000034795772,0.011425268,0.0007836363,0.000039414805,0.00010016176,0.0000035272224,0.000007113961,0.000057252204],"genre_scores_gemma":[0.99869627,0.000092250135,0.00092167174,0.00023163034,0.000037688606,0.0000010735131,0.0000037676382,0.0000059865642,0.000009677436],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872607,0.00006127222,0.00067434326,0.00006938645,0.00035995236,0.00010899671],"domain_scores_gemma":[0.9981294,0.00042718035,0.0010182685,0.00018073959,0.00021157847,0.00003279269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011324999,0.000059350252,0.00028139632,0.00062885555,0.000027190503,0.0000088974275,0.00009462474,0.00002343531,0.0000033203219],"category_scores_gemma":[0.00034287033,0.00004212876,0.00015181185,0.0008795344,0.000026987582,0.00022475776,0.000012713433,0.00017666261,1.0170775e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012498761,0.00043095628,0.90296984,0.000026336347,0.000030232412,0.000082014856,0.00033108567,0.0002800283,0.084316075,0.000020654626,0.000067627436,0.0113201905],"study_design_scores_gemma":[0.00015591283,0.000103356375,0.99146926,0.000058897134,0.0002050737,0.00014664305,0.000118418386,0.002934516,0.0045860107,0.000072148956,0.00011750716,0.000032273376],"about_ca_topic_score_codex":0.000009997563,"about_ca_topic_score_gemma":0.0000042039883,"teacher_disagreement_score":0.088499434,"about_ca_system_score_codex":0.00003997669,"about_ca_system_score_gemma":0.000021443911,"threshold_uncertainty_score":0.17179608},"labels":[],"label_agreement":null},{"id":"W1965146525","doi":"10.1016/j.neuroimage.2008.03.024","title":"FreeSurfer-initiated fully-automated subcortical brain segmentation in MRI using Large Deformation Diffeomorphic Metric Mapping","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":179,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; National Institutes of Health","keywords":"Putamen; Artificial intelligence; Segmentation; Thalamus; Computer science; Pattern recognition (psychology); Caudate nucleus; Hippocampus; Basal ganglia; Metric (unit); Neuroscience; Psychology; Central nervous system","score_opus":0.13714103280498316,"score_gpt":0.3705583009984875,"score_spread":0.23341726819350436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965146525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8976281,0.00003567133,0.099284634,0.0009684076,0.000047081667,0.000717235,0.000024520132,0.0009872813,0.0003070655],"genre_scores_gemma":[0.98023146,0.000074452524,0.017910972,0.0014550019,0.000040255076,0.00004498034,0.00016605345,0.000046271532,0.000030563828],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99832684,0.00010165541,0.0005078893,0.0003717568,0.0003027903,0.0003890719],"domain_scores_gemma":[0.99916345,0.00012511213,0.00014717103,0.00035647565,0.00009161188,0.0001161673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018225894,0.00019970497,0.00028952525,0.0005418826,0.00020304426,0.000020214316,0.00009982616,0.00007933701,0.00003784697],"category_scores_gemma":[0.00022973944,0.00020273819,0.00007521606,0.0014368017,0.0000810746,0.00030909022,0.00006479043,0.0003532642,0.000030958363],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015023934,0.0009694258,0.17002124,0.00016875929,0.00002264088,0.0011282656,0.00049167674,0.00043001774,0.822452,0.0003764496,0.0026704965,0.0011187892],"study_design_scores_gemma":[0.002878549,0.00016329429,0.6198351,0.00009231524,0.000040746254,0.0011149325,0.00006602183,0.3576733,0.016973352,0.00016419112,0.0006947342,0.00030351098],"about_ca_topic_score_codex":0.000028770715,"about_ca_topic_score_gemma":0.0000031060442,"teacher_disagreement_score":0.80547863,"about_ca_system_score_codex":0.00013203081,"about_ca_system_score_gemma":0.000054832366,"threshold_uncertainty_score":0.82674235},"labels":[],"label_agreement":null},{"id":"W1965400726","doi":"10.1016/j.neuroimage.2006.04.187","title":"Diffusion tensor imaging of time-dependent axonal and myelin degradation after corpus callosotomy in epilepsy patients","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":285,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; National Institutes of Health; University of Alberta","keywords":"White matter; Diffusion MRI; Corpus callosum; Fractional anisotropy; Myelin; Neuroscience; Tractography; Magnetic resonance imaging; Psychology; Medicine; Radiology; Central nervous system","score_opus":0.013631079485931348,"score_gpt":0.2664515432814151,"score_spread":0.2528204637954838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965400726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959744,0.000056035424,0.0021205833,0.0005231076,0.00002125018,0.0005295788,0.00003362917,0.000080598336,0.00066081574],"genre_scores_gemma":[0.9949154,0.000038723007,0.0041618696,0.00033620963,0.000033022217,0.000056599103,0.00005710912,0.000028637563,0.00037242324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989759,0.000028586863,0.00030939974,0.00031528546,0.00020554398,0.00016533193],"domain_scores_gemma":[0.9994843,0.000046977373,0.00010319095,0.00023783202,0.000078099816,0.000049614544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005757778,0.000131018,0.00019158545,0.00013614201,0.000030907293,0.000010563599,0.000053663687,0.000029800578,0.000028942077],"category_scores_gemma":[0.00003981415,0.0001224008,0.00003843147,0.00013499538,0.000079649,0.00009781416,0.000069091984,0.0001658394,0.0000090215],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009647419,0.0003006237,0.93021464,0.000028975477,9.55265e-7,0.000046332236,0.000008567177,0.0000039756005,0.06309063,0.00003961809,0.0002368696,0.0059323576],"study_design_scores_gemma":[0.0011631055,0.00006923308,0.9902395,0.00005950885,0.000019888206,0.00003004581,0.0000021110322,0.0019755452,0.004896848,0.0004244674,0.0010176812,0.000102044556],"about_ca_topic_score_codex":0.00008340536,"about_ca_topic_score_gemma":0.0000056459808,"teacher_disagreement_score":0.0600249,"about_ca_system_score_codex":0.0000286641,"about_ca_system_score_gemma":0.000013175992,"threshold_uncertainty_score":0.499136},"labels":[],"label_agreement":null},{"id":"W1965597062","doi":"10.1007/s00406-012-0383-y","title":"The effect of aerobic exercise on cortical architecture in patients with chronic schizophrenia: a randomized controlled MRI study","year":2012,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Aerobic exercise; Neuroplasticity; Schizophrenia (object-oriented programming); Medicine; Physical medicine and rehabilitation; Psychology; Physical therapy; Neuroscience; Psychiatry","score_opus":0.013416767832689924,"score_gpt":0.3244817430771266,"score_spread":0.3110649752444367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965597062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950322,0.00014752317,0.0008830235,0.00039631396,0.00015767058,0.0028221533,0.0000023456,0.000027712827,0.0005310535],"genre_scores_gemma":[0.99834144,0.0001896322,0.0012348009,0.0000941116,0.000055263085,0.000040434876,7.8003495e-7,0.00001733334,0.00002617982],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99721026,0.001242802,0.00073545286,0.0003357876,0.00023760248,0.0002380954],"domain_scores_gemma":[0.9966251,0.0024675499,0.00029765922,0.00044978812,0.000012762334,0.0001471118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013526004,0.00017014083,0.0008351897,0.00007564693,0.00012211438,0.000009439563,0.00023064332,0.000014429032,9.737347e-7],"category_scores_gemma":[0.0007301802,0.00008170195,0.00019685006,0.00018389033,0.0013208048,0.00003558083,0.000097988646,0.00051332865,8.983502e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.21925358,0.001743267,0.77166575,0.000036614783,0.00001699891,0.000001848296,0.00004424682,0.000023815111,0.00010061196,0.0005123901,0.0000071168784,0.0065937485],"study_design_scores_gemma":[0.15020186,0.0064711124,0.8426016,0.00022080145,0.00015134558,0.0000023511702,0.0000051696034,0.00012556663,0.000030286385,0.00009273191,0.00002483974,0.00007236365],"about_ca_topic_score_codex":7.438789e-7,"about_ca_topic_score_gemma":0.0000019370295,"teacher_disagreement_score":0.070935816,"about_ca_system_score_codex":0.000002401634,"about_ca_system_score_gemma":0.000029883222,"threshold_uncertainty_score":0.48665604},"labels":[],"label_agreement":null},{"id":"W1965738837","doi":"10.1016/j.nicl.2014.08.003","title":"Cellular correlates of longitudinal diffusion tensor imaging of axonal degeneration following hypoxic–ischemic cerebral infarction in neonatal rats","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Research Council Canada; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Cerebral peduncle; Diffusion MRI; Fractional anisotropy; Wallerian degeneration; Pathology; Cerebral cortex; Neuroscience; Medicine; Corpus callosum; Ischemia; Anatomy; Internal capsule; Biology; White matter; Cardiology; Magnetic resonance imaging","score_opus":0.060909995904924706,"score_gpt":0.3620996991850905,"score_spread":0.3011897032801658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965738837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96485025,0.000084195104,0.033710036,0.0005351257,0.00018743536,0.0003426576,0.0000061772407,0.00008060006,0.00020351252],"genre_scores_gemma":[0.9888886,0.00003887238,0.010574901,0.00020171906,0.00014640628,0.00001721023,0.000052721112,0.00003423331,0.000045338464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979101,0.00011832427,0.0009808873,0.0004949205,0.00027936904,0.00021643502],"domain_scores_gemma":[0.998632,0.00038749378,0.00032132812,0.0004513323,0.000110468645,0.00009733527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004711967,0.00017705152,0.00047640406,0.00015452347,0.000053189327,0.00000904174,0.00013282296,0.000096446296,0.000018667271],"category_scores_gemma":[0.0007764153,0.00017089251,0.00032354347,0.00025630253,0.00018881886,0.00016053562,0.0001127321,0.00051002065,0.000004858466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110219764,0.00018757742,0.70194644,0.00003277275,0.0000064144715,0.000017137914,0.000017409202,0.000023847548,0.29142493,0.00016183493,0.00013053312,0.0059409086],"study_design_scores_gemma":[0.0023019505,0.0003941253,0.8475857,0.00023081852,0.00013712121,0.00008007382,0.000019787627,0.04215791,0.105516456,0.00045274443,0.0009109265,0.0002123911],"about_ca_topic_score_codex":0.000015384607,"about_ca_topic_score_gemma":0.0000021344565,"teacher_disagreement_score":0.18590847,"about_ca_system_score_codex":0.000022309072,"about_ca_system_score_gemma":0.000045418405,"threshold_uncertainty_score":0.69687945},"labels":[],"label_agreement":null},{"id":"W1966454855","doi":"10.3389/fneur.2014.00240","title":"Subjectâ€“Motion Correction in HARDI Acquisitions: Choices and Consequences","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Children's Hospital of Philadelphia; National Institute on Drug Abuse; University of Alberta; University of Washington; National Institutes of Health","keywords":"Computer science; Outlier; Motion (physics); Artificial intelligence; Interpolation (computer graphics); Noise (video); Orientation (vector space); Computer vision; Mathematics","score_opus":0.023021209426620136,"score_gpt":0.3007784304700382,"score_spread":0.2777572210434181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966454855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91233546,0.00034494267,0.07161283,0.011812094,0.0009654828,0.0005753842,0.0000028329753,0.00019104005,0.002159936],"genre_scores_gemma":[0.98962915,0.0002602174,0.0072968104,0.0026084967,0.000052845262,0.000075762924,0.0000070831475,0.000009873193,0.000059773036],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992989,0.00008224844,0.00015754189,0.00026700398,0.00004900294,0.00014536099],"domain_scores_gemma":[0.9996774,0.00007518894,0.00004862682,0.00014783729,0.000016677915,0.00003425322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012697747,0.00007705164,0.00017667077,0.0002239531,0.00003717547,0.000006476607,0.000036783724,0.00007117468,0.000008003655],"category_scores_gemma":[0.00014003542,0.00007840048,0.000017188982,0.00016957772,0.00018823787,0.00006884253,0.00001950389,0.00022808029,0.0000017661353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014070433,0.000092032395,0.966101,0.000023420593,0.0000035968512,0.000034046232,0.00006212083,0.0000784453,0.0026073274,0.0015772926,0.005932305,0.023347704],"study_design_scores_gemma":[0.0011766085,0.00048552325,0.9158967,0.000037923815,0.000018656152,0.00041251833,0.000026514452,0.012067657,0.0014981271,0.040712908,0.027522203,0.00014465759],"about_ca_topic_score_codex":0.00004971399,"about_ca_topic_score_gemma":0.000024788656,"teacher_disagreement_score":0.07729368,"about_ca_system_score_codex":0.000016692062,"about_ca_system_score_gemma":0.00001071543,"threshold_uncertainty_score":0.31970787},"labels":[],"label_agreement":null},{"id":"W1966699768","doi":"10.1016/j.neuroimage.2010.10.028","title":"Robust clustering of massive tractography datasets","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Cluster analysis; Tractography; Computer science; Fiber; Voxel; Preprocessor; Diffusion MRI; Fiber tract; Artificial intelligence; Fiber bundle; Pattern recognition (psychology); Segmentation; Inference; Data mining","score_opus":0.07886799074879142,"score_gpt":0.34430207222581993,"score_spread":0.2654340814770285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966699768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8791752,0.000028726878,0.10135506,0.0038010704,0.00032267132,0.0011028389,0.000626114,0.0006777442,0.012910578],"genre_scores_gemma":[0.9232132,0.000024339666,0.07618649,0.00031898316,0.000046436635,0.00002213169,0.00008904179,0.00003007781,0.00006931527],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99930423,0.00000809948,0.0001822298,0.00024301073,0.00012095991,0.00014145228],"domain_scores_gemma":[0.999139,0.000046100842,0.00008853613,0.0006016583,0.000041643325,0.00008305859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046629753,0.00009910399,0.00016543192,0.00009642022,0.000041389307,0.000008548065,0.00012534493,0.000037163023,0.00007451505],"category_scores_gemma":[0.00007061306,0.00009223541,0.00007199563,0.00019732247,0.00011496041,0.00008579979,0.00006537552,0.00036500595,0.000007772624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030093406,0.00019366434,0.0042834417,0.00006346698,0.000005630161,0.00004675445,0.000017197166,0.000018956815,0.9862001,0.00050438446,0.0041552773,0.004481021],"study_design_scores_gemma":[0.0028137055,0.00082617457,0.26568133,0.00016275521,0.0002719014,0.0010977295,0.000053115717,0.011331473,0.41446137,0.0017060435,0.3008811,0.0007132994],"about_ca_topic_score_codex":0.0000092987375,"about_ca_topic_score_gemma":0.0000034809852,"teacher_disagreement_score":0.5717387,"about_ca_system_score_codex":0.0000026018618,"about_ca_system_score_gemma":0.000014998082,"threshold_uncertainty_score":0.3761251},"labels":[],"label_agreement":null},{"id":"W1966831294","doi":"10.1097/wnr.0b013e32834dc301","title":"White matter integrity and math performance in pediatric multiple sclerosis","year":2011,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Hospital for Sick Children; University of Toronto; York University","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Multiple sclerosis; Psychology; Cognition; Neuroscience; Audiology; Developmental psychology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.15051486782692222,"score_gpt":0.30392088421986124,"score_spread":0.15340601639293902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1966831294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99170864,0.000015424539,0.00024983162,0.00036052475,0.000027759763,0.00024036804,0.00000166962,0.00010982607,0.007285966],"genre_scores_gemma":[0.9894825,0.00022791265,0.0092189815,0.0006834898,0.000030804014,0.000053984626,0.0000031706804,0.00001880147,0.00028032216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993056,0.000006754448,0.00021312543,0.00025470078,0.00008338012,0.00013645677],"domain_scores_gemma":[0.999542,0.0000112820035,0.000070169466,0.00028704887,0.000027362525,0.00006216001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007101897,0.00009113944,0.00012793779,0.0000872542,0.000030473304,0.0000052839905,0.0000472041,0.000034399916,0.000032114793],"category_scores_gemma":[0.000023835832,0.0000794742,0.000023385966,0.00015887055,0.000037022786,0.00008836974,0.000053585747,0.00029868734,0.000020705025],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017296084,0.00007375579,0.9987419,0.000033096483,6.250747e-7,0.000037558108,0.00006217775,1.4032814e-7,0.00018666066,0.00003329897,0.00032413215,0.0004893631],"study_design_scores_gemma":[0.00019767902,0.00005498541,0.9976758,0.000016387341,0.0000141101755,0.00022717958,0.0000044766225,0.00023710768,0.0007426092,0.00008952252,0.0006725496,0.00006761354],"about_ca_topic_score_codex":0.000016970316,"about_ca_topic_score_gemma":0.0000021436529,"teacher_disagreement_score":0.00896915,"about_ca_system_score_codex":0.000010205827,"about_ca_system_score_gemma":0.000019135634,"threshold_uncertainty_score":0.3240864},"labels":[],"label_agreement":null},{"id":"W1967337284","doi":"10.1006/nimg.2000.0652","title":"Measurement of Cortical Thickness Using an Automated 3-D Algorithm: A Validation Study","year":2001,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":253,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Computer science; Cortex (anatomy); Grey matter; Cerebral cortex; Algorithm; Artificial intelligence; White matter; Pattern recognition (psychology); Medicine; Magnetic resonance imaging; Neuroscience; Psychology; Radiology","score_opus":0.18357196677323348,"score_gpt":0.42272643995512665,"score_spread":0.23915447318189317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967337284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8768789,0.000009602577,0.12119386,0.00017249135,0.000036586694,0.00078694854,0.000003939463,0.0007034223,0.00021424098],"genre_scores_gemma":[0.97331035,0.0000072201688,0.026426552,0.00013844742,0.000039956452,0.00002698579,0.0000066432017,0.000030289764,0.000013561421],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986957,0.00009743479,0.0002967165,0.00030777993,0.00043912412,0.00016329024],"domain_scores_gemma":[0.9990554,0.000017563505,0.00009830742,0.00049178826,0.00024130789,0.00009566891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026197752,0.00012049765,0.00021294777,0.00008838843,0.00008730141,0.000014465613,0.0000947278,0.000030804727,0.000018268915],"category_scores_gemma":[0.000097058415,0.000112993,0.00004239255,0.0003191399,0.000058335398,0.00012534112,0.000040905896,0.00018418685,0.0000038856615],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084830586,0.0036308537,0.027947817,0.000033111366,0.000021160527,0.00019606177,0.00014921716,0.00011211345,0.9570884,0.000058209793,0.0000929636,0.0105852755],"study_design_scores_gemma":[0.0032155972,0.0024152594,0.5454028,0.00014090896,0.0005056547,0.00096182665,0.00029678395,0.35178477,0.09355292,0.0002937547,0.0010059859,0.00042373553],"about_ca_topic_score_codex":0.00003129424,"about_ca_topic_score_gemma":9.987979e-7,"teacher_disagreement_score":0.86353546,"about_ca_system_score_codex":0.00004313887,"about_ca_system_score_gemma":0.000043644446,"threshold_uncertainty_score":0.4607721},"labels":[],"label_agreement":null},{"id":"W1967998939","doi":"10.1016/j.neuroimage.2013.04.018","title":"Surface fluid registration of conformal representation: Application to detect disease burden and genetic influence on hippocampus","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; U.S. National Library of Medicine; Takeda Pharmaceutical Company; National Institute of Neurological Disorders and Stroke; Genentech; National Institutes of Health; Servier; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; National Institute on Aging; Abbott Laboratories; Pfizer; BioClinica; Dana Foundation; Bayer HealthCare; National Institute of Mental Health; Novartis Pharmaceuticals Corporation; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Amorfix Life Sciences; Eli Lilly and Company; Roche","keywords":"Conformal map; Artificial intelligence; Computer vision; Surface (topology); Mean curvature; Conformal geometry; Computer science; Smoothing; Image registration; Feature (linguistics); Pattern recognition (psychology); Mathematics; Algorithm; Curvature; Geometry; Image (mathematics); Conformal field theory","score_opus":0.029985208639051502,"score_gpt":0.3289520843861529,"score_spread":0.2989668757471014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967998939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9795084,0.00003367466,0.014492652,0.0039031298,0.000010401512,0.0012951966,0.000008493311,0.0001184573,0.0006295738],"genre_scores_gemma":[0.98782927,0.00005537196,0.010925094,0.00081042544,0.000041924548,0.0001451325,0.000012575306,0.000017715156,0.00016249757],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99910724,0.000019166193,0.00024805721,0.0003165402,0.0001847494,0.00012426825],"domain_scores_gemma":[0.99899143,0.00005836486,0.00010273516,0.00054144155,0.00013237113,0.00017363548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033273504,0.0001073558,0.0001281486,0.0000516997,0.000054826458,0.000022268287,0.00008153074,0.000024422105,0.000011653495],"category_scores_gemma":[0.00013474963,0.00010507466,0.000028139146,0.00018371525,0.000077668876,0.0001313563,0.000039319766,0.00009391007,0.00003521722],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001281028,0.00003339484,0.0061576744,0.00008662489,0.0000045918505,0.000013317269,0.00006173599,0.0022508218,0.9341384,0.00040410372,0.0009674616,0.05575378],"study_design_scores_gemma":[0.00058800634,0.00047737692,0.92417216,0.00007044441,0.000058056135,0.00005883144,0.000019814875,0.009492979,0.057759892,0.0035523993,0.0035481253,0.00020188456],"about_ca_topic_score_codex":0.00008174197,"about_ca_topic_score_gemma":7.2933676e-7,"teacher_disagreement_score":0.9180145,"about_ca_system_score_codex":0.0000123898235,"about_ca_system_score_gemma":0.00002490687,"threshold_uncertainty_score":0.42848203},"labels":[],"label_agreement":null},{"id":"W1968301261","doi":"10.1016/j.media.2013.08.006","title":"Denoising and fast diffusion imaging with physically constrained sparse dictionary learning","year":2013,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Artificial intelligence; Computer science; Noise reduction; Dictionary learning; Diffusion MRI; Pattern recognition (psychology); Gaussian; Diffusion; Sparse approximation; Computer vision; Physics","score_opus":0.012633093816359044,"score_gpt":0.29270872219528005,"score_spread":0.280075628378921,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968301261","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4746985,0.00006802258,0.5140331,0.009081554,0.0000053109734,0.00022832555,0.0000017688737,0.00029385238,0.0015895915],"genre_scores_gemma":[0.97449744,0.00009604232,0.023859255,0.0010068796,0.00007565227,0.000045509907,0.000050852806,0.00002161813,0.00034674077],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873924,0.000035546,0.00021723296,0.00036379427,0.0004229248,0.00022128325],"domain_scores_gemma":[0.99914473,0.000101519974,0.000080997415,0.00022914211,0.00013229933,0.00031132775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010550502,0.00014772416,0.00032293034,0.00018375547,0.0001894587,0.00005028088,0.00007172412,0.000036513182,0.0005515422],"category_scores_gemma":[0.00015299057,0.00010856916,0.00009889206,0.00065516966,0.0004108119,0.00017304535,0.000080240636,0.00037399246,0.000021066093],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006610763,0.0006589556,0.46173117,0.00008084335,0.000809291,0.0005772265,0.00031240584,0.000058962833,0.16481507,0.00038319995,0.0012640276,0.36924273],"study_design_scores_gemma":[0.0026065018,0.00029527393,0.42653534,0.0003735696,0.0043281545,0.0007946094,0.0009540326,0.5554624,0.002814468,0.0011000608,0.0040349644,0.0007005887],"about_ca_topic_score_codex":0.00009726838,"about_ca_topic_score_gemma":0.000003343378,"teacher_disagreement_score":0.5554035,"about_ca_system_score_codex":0.00002210364,"about_ca_system_score_gemma":0.000036051923,"threshold_uncertainty_score":0.6039001},"labels":[],"label_agreement":null},{"id":"W1968326787","doi":"10.1371/journal.pone.0117759","title":"Voxel-Based Texture Analysis of the Brain","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates; Killam Trusts; University of Alberta","keywords":"Voxel; Pattern recognition (psychology); Voxel-based morphometry; Artificial intelligence; Computer science; Texture (cosmology); Statistical analysis; Medicine; Magnetic resonance imaging; Mathematics; Statistics; Radiology; Image (mathematics)","score_opus":0.18334773477366884,"score_gpt":0.3470493817397412,"score_spread":0.16370164696607237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968326787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9273025,0.00011188795,0.017273504,0.049928688,0.0000083953,0.00058796053,0.000038667775,0.00020428639,0.004544142],"genre_scores_gemma":[0.9856705,0.0000020721327,0.011461162,0.0020236734,0.000020297683,0.00002142706,0.0000128902875,0.000007685479,0.00078030024],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99956584,0.000012400135,0.00009046072,0.00009509937,0.00017632387,0.00005989436],"domain_scores_gemma":[0.99935025,0.00003719671,0.000051336778,0.00042004237,0.000093820694,0.000047369642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005837982,0.0000426336,0.00015497477,0.000061774226,0.000017748524,0.0000019718482,0.00008126323,0.000021308104,0.000020074256],"category_scores_gemma":[0.00016074533,0.000028229284,0.000067714805,0.00061602204,0.000045982328,0.000010878393,0.00002117839,0.00008551901,0.0000032645016],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015867656,0.006720938,0.39531243,0.00020217815,0.0022109947,0.000008197769,0.0003888254,0.00044756784,0.5607919,0.0050623305,0.025420418,0.0032755078],"study_design_scores_gemma":[0.0021461993,0.0004034262,0.21094571,0.00040503588,0.011431903,0.0000032749963,0.00008161611,0.07003092,0.68163836,0.004673513,0.017909046,0.00033097665],"about_ca_topic_score_codex":0.000006977266,"about_ca_topic_score_gemma":0.000002777699,"teacher_disagreement_score":0.18436672,"about_ca_system_score_codex":0.00001623362,"about_ca_system_score_gemma":0.000034566143,"threshold_uncertainty_score":0.11511567},"labels":[],"label_agreement":null},{"id":"W1968710739","doi":"10.4137/mri.s11149","title":"Measuring Restriction Sizes Using Diffusion Weighted Magnetic Resonance Imaging: A Review","year":2013,"lang":"en","type":"review","venue":"Magnetic Resonance Insights","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Health Research Council","keywords":"Diffusion; Spin echo; Magnetic resonance imaging; Nuclear magnetic resonance; Resonance (particle physics); Spin (aerodynamics); Diffusion MRI; Effective diffusion coefficient; Materials science; Physics; Atomic physics; Thermodynamics","score_opus":0.13278998106167303,"score_gpt":0.35619641840935345,"score_spread":0.22340643734768043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968710739","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000040796847,0.9910811,0.0003330038,0.00032954983,0.00022093728,0.0055710436,0.000027805027,0.00058041955,0.001815314],"genre_scores_gemma":[0.000006221009,0.97677046,0.01808568,0.00055247557,0.00039894026,0.0014146132,0.00009399197,0.00025393505,0.0024236771],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9947251,0.00028629752,0.0017138089,0.0016119521,0.00087513245,0.00078767445],"domain_scores_gemma":[0.9962416,0.00023698003,0.0007251707,0.002077414,0.00037678113,0.00034203022],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018954594,0.0011035942,0.0027440921,0.00048639067,0.00037883213,0.00009992329,0.0006157428,0.0003361828,0.00027266514],"category_scores_gemma":[0.00024069527,0.00087327213,0.00066845655,0.0017342446,0.00028003435,0.00023155424,0.00032152308,0.0011902282,0.00020287455],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011376851,0.00013685922,0.000021116097,0.01312477,0.000004397868,0.00012522445,0.000012039716,4.1341284e-8,0.00006052716,0.00027500917,0.0041178027,0.98211086],"study_design_scores_gemma":[0.00043116178,0.00016878733,0.000171959,0.11520837,0.0010088298,0.0005951521,0.0000024731141,0.00045588982,0.000011127149,0.0007037284,0.8805235,0.0007190474],"about_ca_topic_score_codex":0.00008515482,"about_ca_topic_score_gemma":0.000002824458,"teacher_disagreement_score":0.9813918,"about_ca_system_score_codex":0.00043120555,"about_ca_system_score_gemma":0.00047135574,"threshold_uncertainty_score":0.9993718},"labels":[],"label_agreement":null},{"id":"W1968795166","doi":"10.1016/j.neuroimage.2004.05.026","title":"Quantitative measurement of neurodegeneration in an ALS–PDC model using MR microscopy","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research and Materiel Command; McKnight Foundation; National Center for Research Resources; ALS Association; Natural Sciences and Engineering Research Council of Canada; Scottish Rite Charitable Foundation of Canada","keywords":"Neurodegeneration; Neuroscience; Medicine; Pathology; Psychology; Disease","score_opus":0.24835171843965798,"score_gpt":0.431423795188646,"score_spread":0.183072076748988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968795166","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8135785,0.00003601695,0.18526308,0.0004857503,0.000020566209,0.00039340352,0.000010040635,0.00007180925,0.0001408404],"genre_scores_gemma":[0.82020175,0.00002318041,0.17925742,0.000441845,0.000013935084,0.000016770653,0.000007376182,0.000029105357,0.000008601478],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989267,0.000032508673,0.00029374557,0.00033437437,0.0002468944,0.00016575604],"domain_scores_gemma":[0.9992735,0.000009587969,0.00010282689,0.0003814231,0.0001686364,0.00006402893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012737224,0.00012847701,0.00020158199,0.0001321873,0.000047402213,0.00001163451,0.00008743226,0.000032407792,0.000002365648],"category_scores_gemma":[0.000062095496,0.00013183936,0.00004546754,0.0001916089,0.000068559304,0.00018518146,0.000029168585,0.00017202274,0.0000019161926],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059583486,0.0002668049,0.00076724024,0.000023471082,0.0000014630722,0.000012574729,0.00010018371,0.03154068,0.9656102,0.0014719923,0.000013382729,0.00013239152],"study_design_scores_gemma":[0.0010929051,0.00047371845,0.0049070953,0.000092115886,0.000033538694,0.000027669146,0.000017641143,0.12979253,0.86013865,0.0032214213,0.00005551499,0.00014722657],"about_ca_topic_score_codex":0.00005225843,"about_ca_topic_score_gemma":0.000020709915,"teacher_disagreement_score":0.105471596,"about_ca_system_score_codex":0.00008392275,"about_ca_system_score_gemma":0.000108462315,"threshold_uncertainty_score":0.5376253},"labels":[],"label_agreement":null},{"id":"W1968931994","doi":"10.1016/j.schres.2014.03.034","title":"Genetic underpinnings of white matter ‘connectivity’: Heritability, risk, and heterogeneity in schizophrenia","year":2014,"lang":"en","type":"review","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Genome-wide association study; Polygene; White matter; Schizophrenia (object-oriented programming); Heritability; Biology; Candidate gene; Missing heritability problem; Genetic association; Genetics; Psychology; Quantitative trait locus; Gene; Medicine; Psychiatry; Single-nucleotide polymorphism; Genotype","score_opus":0.14795541773113713,"score_gpt":0.4495631878651363,"score_spread":0.3016077701339992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968931994","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050610054,0.94431955,0.0009615349,0.00035885663,0.000040405765,0.0031544135,0.00010219803,0.00011849564,0.0003345149],"genre_scores_gemma":[0.019409098,0.95427114,0.025255397,0.00003033203,0.00015673433,0.00058305,0.000030363133,0.00015392753,0.00010994574],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.995299,0.0010639881,0.0010299433,0.001245152,0.0006579921,0.0007039419],"domain_scores_gemma":[0.9966374,0.0008489215,0.00036216946,0.0016256537,0.00024234483,0.00028349366],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0018031113,0.000506816,0.0021750638,0.0010199444,0.00026595665,0.000046430283,0.0004792558,0.00040787263,0.00007271476],"category_scores_gemma":[0.00047514506,0.00044055804,0.00035577046,0.0013564123,0.00075924234,0.00007816302,0.0010013898,0.0025866237,0.00006844273],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004478943,0.00038694343,0.035007544,0.027089948,0.00009832432,0.000038801893,0.000059923965,0.0000017141399,0.000040908362,0.00043848215,0.00046663926,0.93592286],"study_design_scores_gemma":[0.005600872,0.0012779972,0.17313062,0.034894116,0.0010368574,0.0010270455,0.000031663676,0.0002938489,0.000122049416,0.022741038,0.7579128,0.0019310998],"about_ca_topic_score_codex":0.00015872344,"about_ca_topic_score_gemma":0.00010305131,"teacher_disagreement_score":0.9339918,"about_ca_system_score_codex":0.00019746205,"about_ca_system_score_gemma":0.00040497992,"threshold_uncertainty_score":0.9998046},"labels":[],"label_agreement":null},{"id":"W1969053905","doi":"10.3389/fpsyg.2015.00009","title":"Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm","year":2015,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Heart and Stroke Foundation; Sunnybrook Health Science Centre; University of Toronto","funders":"Economic and Social Research Council; Wellcome Trust","keywords":"Arcuate fasciculus; Psychology; Tractography; Neuroscience; Audiology; Diffusion MRI; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.058940382029320976,"score_gpt":0.3526427880386574,"score_spread":0.2937024060093364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969053905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7180973,0.000365594,0.2620803,0.009095417,0.0013177999,0.00110277,0.000014442937,0.00008201074,0.007844318],"genre_scores_gemma":[0.98811233,0.00004664726,0.010553107,0.0011321802,0.00003064093,0.00008065812,0.0000018608015,0.00001173258,0.000030840816],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99931073,0.0000701402,0.00018357582,0.00019023678,0.00010407598,0.00014122426],"domain_scores_gemma":[0.9994541,0.000024095782,0.00007121922,0.00038878454,0.000028920955,0.00003288211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018288082,0.00007963946,0.00014379443,0.00016582168,0.000022424963,0.0000024363735,0.00015633096,0.00006834389,0.000003430935],"category_scores_gemma":[0.0000439483,0.000049344817,0.000057493307,0.00050684804,0.00018228305,0.000022975617,0.00001997177,0.0003401722,0.0000021112762],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044155598,0.000770808,0.14360411,0.000008929526,0.000046957724,0.00003729364,0.00061295,0.00001619895,0.012011103,0.00060104154,0.01805114,0.8237979],"study_design_scores_gemma":[0.006144731,0.0012152168,0.76035523,0.00010737745,0.00008835988,0.00033420173,0.0012804694,0.00462088,0.029305963,0.12738915,0.06875676,0.000401665],"about_ca_topic_score_codex":0.00001924149,"about_ca_topic_score_gemma":0.000016082427,"teacher_disagreement_score":0.8233962,"about_ca_system_score_codex":0.00002887191,"about_ca_system_score_gemma":0.000014489514,"threshold_uncertainty_score":0.20122233},"labels":[],"label_agreement":null},{"id":"W1969164666","doi":"10.1007/s00256-011-1310-4","title":"Diffusion tensor imaging of the median nerve: intra-, inter-reader agreement, and agreement between two software packages","year":2011,"lang":"en","type":"article","venue":"Skeletal Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Diffusion MRI; Intraclass correlation; Medicine; Fractional anisotropy; Nuclear medicine; Limits of agreement; Effective diffusion coefficient; Software; Magnetic resonance imaging; Radiology; Computer science","score_opus":0.053217293732524686,"score_gpt":0.3252695101188046,"score_spread":0.2720522163862799,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969164666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9629041,0.00025374934,0.029105715,0.0058978857,0.00011325896,0.0006625912,0.000031713324,0.00009803854,0.00093293306],"genre_scores_gemma":[0.98816,0.000062269864,0.010915778,0.00046735696,0.00011472978,0.000038112757,0.000020225349,0.000018057404,0.00020344686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904823,0.000058918893,0.00027750852,0.00028542714,0.000094518655,0.00023541883],"domain_scores_gemma":[0.9992093,0.00007850292,0.00014245583,0.000430443,0.00005075679,0.00008855435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000110104964,0.00015004473,0.0002834173,0.00007022561,0.00007633643,0.0000030840374,0.0001691443,0.00004539642,0.00008785003],"category_scores_gemma":[0.00009480073,0.00009896187,0.00008231922,0.00010745822,0.00046367955,0.000041310737,0.00017519786,0.0002260793,0.000005450963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001664431,0.00007168247,0.9007033,0.000048985625,0.0000371075,0.0000130981825,0.00036498957,1.05463926e-7,0.013423876,0.0007188538,0.00077408977,0.08382726],"study_design_scores_gemma":[0.0011209782,0.00027825753,0.9703804,0.00012743712,0.00017242416,0.0002609467,0.00017201589,0.000053546446,0.012455199,0.009538684,0.005247627,0.0001924469],"about_ca_topic_score_codex":0.000064150176,"about_ca_topic_score_gemma":0.0000080971995,"teacher_disagreement_score":0.08363481,"about_ca_system_score_codex":0.00002527933,"about_ca_system_score_gemma":0.000017709372,"threshold_uncertainty_score":0.4035548},"labels":[],"label_agreement":null},{"id":"W1969637629","doi":"10.1016/j.neuroimage.2014.04.074","title":"Towards quantitative connectivity analysis: reducing tractography biases","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":353,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Voxel; Computer science; Diffusion MRI; Artificial intelligence; Probabilistic logic; Position (finance); Pattern recognition (psychology); Mathematics; Magnetic resonance imaging","score_opus":0.12397581088359226,"score_gpt":0.3996962134668545,"score_spread":0.27572040258326225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969637629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76450145,0.000055185978,0.2159459,0.0026112045,0.000049813392,0.00038789856,0.000026848053,0.00068291544,0.015738783],"genre_scores_gemma":[0.96718466,0.000038191003,0.031485576,0.0010443758,0.000051062132,0.000042131684,0.000025507208,0.000027699454,0.000100817546],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99882406,0.00008079599,0.00021467397,0.00047631553,0.00018555495,0.00021861131],"domain_scores_gemma":[0.99879473,0.00029368993,0.00010863571,0.0005830017,0.00009825103,0.00012165923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017654715,0.00016003683,0.00035002636,0.000340422,0.00011627856,0.00002882023,0.00010518755,0.000037360445,0.000057269135],"category_scores_gemma":[0.0006333473,0.0001463195,0.00026679158,0.0011970906,0.00012175812,0.00012018258,0.000038202652,0.00026079133,0.000014705216],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053126435,0.0025005117,0.1013269,0.00022197586,0.0010078487,0.00021781567,0.00075303676,0.0011307835,0.7127763,0.053632826,0.009555371,0.116345346],"study_design_scores_gemma":[0.0010940058,0.0010359538,0.8699104,0.000094536634,0.0018670614,0.00009819532,0.000082603205,0.02870124,0.064231604,0.0035051822,0.028843846,0.00053537043],"about_ca_topic_score_codex":0.000060404545,"about_ca_topic_score_gemma":0.000004293869,"teacher_disagreement_score":0.7685835,"about_ca_system_score_codex":0.000013881315,"about_ca_system_score_gemma":0.000021682645,"threshold_uncertainty_score":0.5966736},"labels":[],"label_agreement":null},{"id":"W1969880629","doi":"10.1093/cercor/10.5.454","title":"A New Anatomical Landmark for Reliable Identification of Human Area V5/MT: a Quantitative Analysis of Sulcal Patterning","year":2000,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":499,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Sulcus; Anatomy; Landmark; Cortex (anatomy); Superior temporal sulcus; Geology; Biology; Neuroscience; Computer science; Functional magnetic resonance imaging; Artificial intelligence","score_opus":0.07129634739844613,"score_gpt":0.38371110447618323,"score_spread":0.3124147570777371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969880629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92158866,0.000027688493,0.07729458,0.00026571535,0.000008066329,0.0003489189,0.00007595523,0.000053225547,0.0003371714],"genre_scores_gemma":[0.98775744,0.000011638067,0.01090807,0.00006528473,0.000020186628,0.000030454077,0.00027723046,0.000014308214,0.0009154059],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991064,0.000010885017,0.0004036759,0.00023845817,0.00011905122,0.00012154477],"domain_scores_gemma":[0.9992812,0.00005835178,0.00018560991,0.00030296264,0.00010687659,0.00006494439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088854846,0.00008721043,0.00034183296,0.00016273996,0.000046989528,0.0000061718156,0.00009012781,0.000043117456,0.00029609122],"category_scores_gemma":[0.00003377585,0.00008142705,0.00016923316,0.0004995629,0.000052353822,0.000054370994,0.000013177084,0.000084404644,0.0000024601595],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008196267,0.00049352885,0.3188467,0.00026391336,0.0009257292,0.000005521059,0.0007547143,0.0002470065,0.62827593,0.017853359,0.009541835,0.021972157],"study_design_scores_gemma":[0.0016959519,0.0006196394,0.88571453,0.00014229363,0.0022127,0.000007110038,0.0001285055,0.057331227,0.044003345,0.0060132686,0.0018762146,0.00025520893],"about_ca_topic_score_codex":0.00014815072,"about_ca_topic_score_gemma":0.000016401851,"teacher_disagreement_score":0.58427256,"about_ca_system_score_codex":0.000022675962,"about_ca_system_score_gemma":0.000030284215,"threshold_uncertainty_score":0.33204988},"labels":[],"label_agreement":null},{"id":"W1969886036","doi":"10.1016/j.neurobiolaging.2010.02.009","title":"Age-related decline in white matter tract integrity and cognitive performance: A DTI tractography and structural equation modeling study","year":2010,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":305,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of General Medical Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Cingulum (brain); White matter; Inferior longitudinal fasciculus; Corpus callosum; Uncinate fasciculus; Psychology; Diffusion MRI; Splenium; Superior longitudinal fasciculus; Corticospinal tract; Tractography; Cognition; Cognitive decline; Neuroscience; Fractional anisotropy; Audiology; Medicine; Magnetic resonance imaging; Dementia","score_opus":0.052617199970105506,"score_gpt":0.3485499098354151,"score_spread":0.2959327098653096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1969886036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982008,0.000021310858,0.00053803134,0.00067623315,0.000031298245,0.0004319095,0.0000040999253,0.000041941355,0.000054379543],"genre_scores_gemma":[0.99807626,0.000031312393,0.0015654303,0.0002662971,0.000012174081,0.000016154452,0.000016574622,0.000011483807,0.0000043333644],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928916,0.00003472515,0.00025214566,0.00025851536,0.00004110173,0.00012435259],"domain_scores_gemma":[0.9996533,0.000079671794,0.000080219965,0.000106838896,0.00004612348,0.000033853063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014491906,0.00010809562,0.00020866693,0.00017390803,0.00005067344,0.0000065089635,0.000038782844,0.000066758716,0.000008777743],"category_scores_gemma":[0.000026078851,0.000092682436,0.000021749227,0.00013475188,0.00015101641,0.00008980176,0.00004607866,0.0007637546,3.713649e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037170812,0.00007707268,0.98494834,0.000024992476,0.000006708059,0.0000048852235,0.00050283654,0.000024930745,0.012592406,0.000010025846,7.958389e-7,0.0017698323],"study_design_scores_gemma":[0.00095105445,0.00023849927,0.9703585,0.000055318527,0.000049747978,0.00010307485,0.00015718881,0.026696112,0.00082466536,0.00048705188,0.0000013436158,0.000077437784],"about_ca_topic_score_codex":0.000026601205,"about_ca_topic_score_gemma":0.000015816735,"teacher_disagreement_score":0.026671182,"about_ca_system_score_codex":0.000002718743,"about_ca_system_score_gemma":0.000008698219,"threshold_uncertainty_score":0.377948},"labels":[],"label_agreement":null},{"id":"W1970218933","doi":"10.3174/ajnr.a0742","title":"Preliminary Experience with Visualization of Intracortical Fibers by Focused High-Resolution Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; White matter; Anisotropy; Imaging phantom; Nuclear magnetic resonance; Fractional anisotropy; Biomedical engineering; Magnetic resonance imaging; Physics; Optics; Medicine","score_opus":0.018151319757508447,"score_gpt":0.32864973964086,"score_spread":0.31049841988335153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970218933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7112142,0.000039268823,0.28753564,0.001034704,0.000028718829,0.0001007472,0.0000014700605,0.000023713965,0.000021546522],"genre_scores_gemma":[0.9775115,0.00009192464,0.021696255,0.0006068208,0.00005658376,0.0000034745287,0.0000046811538,0.000021154901,0.000007564313],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99892765,0.000057711983,0.00046587584,0.00017360163,0.00017448088,0.00020069863],"domain_scores_gemma":[0.99875844,0.000173085,0.00058214285,0.00018049557,0.00018150502,0.00012434066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012643146,0.00011020609,0.00034555572,0.00015594771,0.000043106418,0.0000030105641,0.00010528756,0.000022545444,0.000006206947],"category_scores_gemma":[0.00011643992,0.0000840779,0.00004993733,0.00032036292,0.00061492936,0.00008491653,0.00002273017,0.00019839402,3.4769965e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041776416,0.00062407827,0.30193782,0.000024563395,0.000035761404,0.00032890806,0.0006014515,0.00012085601,0.597521,0.0008620315,0.001150865,0.09261505],"study_design_scores_gemma":[0.0023206633,0.016818391,0.9229899,0.00018241876,0.00022189792,0.00876491,0.00070743565,0.0026855208,0.042015582,0.00026678172,0.0027291125,0.0002974081],"about_ca_topic_score_codex":0.000015535335,"about_ca_topic_score_gemma":2.3372316e-7,"teacher_disagreement_score":0.6210521,"about_ca_system_score_codex":0.000038506336,"about_ca_system_score_gemma":0.00003445478,"threshold_uncertainty_score":0.34285975},"labels":[],"label_agreement":null},{"id":"W1970455232","doi":"10.1159/000088526","title":"Corpus Callosum in Neurodegenerative Diseases: Findings in Parkinson’s Disease","year":2005,"lang":"en","type":"review","venue":"Dementia and Geriatric Cognitive Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; NIH Clinical Center; National Institute on Aging; University of Alberta","keywords":"Corpus callosum; Degenerative disease; Parkinson's disease; Neuroscience; Disease; Central nervous system disease; Dementia; Psychology; Medicine; Pathology","score_opus":0.03978926997217109,"score_gpt":0.3575897639484629,"score_spread":0.31780049397629184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970455232","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015730077,0.99452734,0.00041264604,0.00024163268,0.0000500476,0.002579567,0.00033733025,0.00007053516,0.0002079052],"genre_scores_gemma":[0.011312389,0.9860659,0.00014980971,0.00025638138,0.00007373792,0.001293414,0.0006839444,0.00006581233,0.00009857799],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979236,0.000113268914,0.00056899915,0.00084108143,0.00017413546,0.00037891231],"domain_scores_gemma":[0.9991784,0.00017052154,0.00017083093,0.00021517466,0.000040447227,0.0002246003],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007805791,0.00045463842,0.0009843196,0.00056404073,0.00007633629,0.00003157416,0.0001047961,0.00010697384,0.000048456714],"category_scores_gemma":[0.00012909535,0.00042749825,0.00024541013,0.00079695956,0.000110723224,0.00009119521,0.00011709741,0.00042502754,0.000010507533],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006458124,0.00046182383,0.029430464,0.0019455511,0.000062650346,0.000084470856,0.000048318958,6.2466995e-7,2.2907777e-7,0.00009329234,0.00019631642,0.9676117],"study_design_scores_gemma":[0.0014173316,0.000074320575,0.04815549,0.0026957593,0.0021351161,0.000009330641,0.000042094,0.000048161644,2.278998e-7,0.00033514012,0.9445875,0.0004995272],"about_ca_topic_score_codex":0.00003019664,"about_ca_topic_score_gemma":0.000069699876,"teacher_disagreement_score":0.9671121,"about_ca_system_score_codex":0.00007399183,"about_ca_system_score_gemma":0.0002028522,"threshold_uncertainty_score":0.99981767},"labels":[],"label_agreement":null},{"id":"W1970921286","doi":"10.1118/1.3181244","title":"SU‐FF‐I‐123: Clinical Value of Diffusion‐Weighted MRI in White Matter in Vivo","year":2009,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"Splenium; White matter; Diffusion MRI; Nuclear magnetic resonance; Magnetic resonance imaging; Corpus callosum; Diffusion; Chemistry; Nuclear medicine; Relaxation (psychology); Effective diffusion coefficient; Materials science; Physics; Medicine; Anatomy; Radiology","score_opus":0.03935547254952559,"score_gpt":0.3827982810644111,"score_spread":0.3434428085148855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970921286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9100585,0.00003634559,0.048630293,0.034480255,0.00008049174,0.0005704087,0.000009071549,0.000117355,0.006017262],"genre_scores_gemma":[0.98870265,0.00014499767,0.0040602274,0.0066593075,0.00019345536,0.000016481477,0.000012133375,0.000016720169,0.00019402665],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99852496,0.000044932476,0.00055574026,0.00028129938,0.00037982088,0.00021322486],"domain_scores_gemma":[0.999217,0.00011903376,0.00008877726,0.000382105,0.00003417792,0.00015890517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023478185,0.00011940049,0.00039413577,0.00005861059,0.000015747275,0.0000031366058,0.00015754811,0.00011921361,0.00018605929],"category_scores_gemma":[0.00007838784,0.00009901628,0.00009089677,0.0003878838,0.00014812464,0.000042531527,0.000054785018,0.0005466779,0.00002455097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012642067,0.0032913685,0.94264555,0.000063035375,0.000007808814,0.000095865566,0.00015739043,0.0000070551228,0.0016250683,0.004754836,0.019512048,0.027713561],"study_design_scores_gemma":[0.0036128645,0.00036019168,0.9077204,0.0006534935,0.00003583938,0.000018564648,0.000015128563,0.005865228,0.004692221,0.06441057,0.012344993,0.00027054801],"about_ca_topic_score_codex":0.000012463269,"about_ca_topic_score_gemma":0.0000024309538,"teacher_disagreement_score":0.078644134,"about_ca_system_score_codex":0.000028412585,"about_ca_system_score_gemma":0.00006452196,"threshold_uncertainty_score":0.40377668},"labels":[],"label_agreement":null},{"id":"W1971120154","doi":"10.1016/j.schres.2012.02.015","title":"Diffusion tensor imaging tractography of the fornix and belief confidence in first-episode psychosis","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Douglas Mental Health University Institute; McGill University","funders":"Canadian Institutes of Health Research","keywords":"Fornix; Tractography; Diffusion MRI; Psychosis; Psychology; Medicine; Psychiatry; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.10104243861373237,"score_gpt":0.41056369593165964,"score_spread":0.3095212573179273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971120154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874069,0.0010059658,0.00047380466,0.009674688,0.000030426563,0.00075068703,0.000009780429,0.00004185602,0.0006058926],"genre_scores_gemma":[0.99416065,0.00052705436,0.0049258233,0.000116923395,0.000053479947,0.0001278656,0.0000018144855,0.000018273342,0.00006810904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987394,0.00007059776,0.00020818932,0.0002255328,0.00038106865,0.00037521942],"domain_scores_gemma":[0.99897546,0.000251029,0.000050242325,0.0004931464,0.00011081827,0.000119334734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055389776,0.000096708216,0.00016433996,0.00025073753,0.00017559706,0.000012722001,0.00018489677,0.000040156905,0.000020460055],"category_scores_gemma":[0.0002073782,0.000064741,0.00006205799,0.00074830436,0.0003622701,0.00010647845,0.00015590918,0.00054804794,0.000003872525],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000175672,0.00020952233,0.9741595,0.00005839237,0.0000034584116,0.0000012250301,0.00012996883,2.7184663e-7,0.011096332,0.0032992319,0.00085074134,0.010015726],"study_design_scores_gemma":[0.000806296,0.00004484289,0.98038536,0.0002557576,0.000010127003,0.000033834167,0.00006819528,0.00026517213,0.0061671752,0.0051185004,0.006767977,0.000076762415],"about_ca_topic_score_codex":0.0002905368,"about_ca_topic_score_gemma":0.00008198556,"teacher_disagreement_score":0.009938964,"about_ca_system_score_codex":0.000023770397,"about_ca_system_score_gemma":0.000014690634,"threshold_uncertainty_score":0.26400614},"labels":[],"label_agreement":null},{"id":"W1971405799","doi":"10.1016/j.media.2010.07.001","title":"Multiple q-shell diffusion propagator imaging","year":2010,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Association France Parkinson","keywords":"Diffusion MRI; Propagator; Computer science; Diffusion; Laplace transform; Fourier transform; SIGNAL (programming language); Diffusion equation; Algorithm; Artificial intelligence; Physics; Computer vision; Mathematical analysis; Mathematics","score_opus":0.01894291456037772,"score_gpt":0.3416434039444404,"score_spread":0.3227004893840627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971405799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55100864,0.000061916,0.4227734,0.020261941,0.00008896166,0.00046146818,0.000013657005,0.0007629416,0.0045671035],"genre_scores_gemma":[0.95167655,0.00004442142,0.045132652,0.0020924166,0.00019879239,0.000056242636,0.000075390024,0.00002609,0.0006974613],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984994,0.000020262676,0.00028870668,0.00039958803,0.0005340825,0.0002579843],"domain_scores_gemma":[0.99863386,0.00009602837,0.00007448857,0.000643662,0.00012782235,0.00042411155],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00023564401,0.00014384346,0.00032759682,0.00024258246,0.00012032273,0.000026793261,0.00019324606,0.000069945345,0.0017207053],"category_scores_gemma":[0.0009867597,0.000110823355,0.00026917682,0.0009236287,0.00023623138,0.00009042416,0.000114882125,0.0006041123,0.00009110149],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002989981,0.0006289234,0.3552921,0.00003588832,0.00019638575,0.00038285277,0.00004913628,6.7282764e-7,0.56754637,0.00022918859,0.005626551,0.069982044],"study_design_scores_gemma":[0.0032950945,0.00010505638,0.2246842,0.000106515006,0.005301327,0.0004360357,0.00011271447,0.44359902,0.10103973,0.0015590806,0.21882313,0.0009381081],"about_ca_topic_score_codex":0.000067607354,"about_ca_topic_score_gemma":0.00003232197,"teacher_disagreement_score":0.4665066,"about_ca_system_score_codex":0.00001633017,"about_ca_system_score_gemma":0.00005601537,"threshold_uncertainty_score":0.9991919},"labels":[],"label_agreement":null},{"id":"W1971698195","doi":"10.1016/j.schres.2012.08.026","title":"Alexithymia and reduced white matter integrity in schizophrenia: A diffusion tensor imaging study on impaired emotional self-awareness","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; White matter; Psychology; Fractional anisotropy; Schizophrenia (object-oriented programming); Diffusion MRI; Toronto Alexithymia Scale; Corpus callosum; Clinical psychology; Psychiatry; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.1105734440366848,"score_gpt":0.41577066083614433,"score_spread":0.30519721679945955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971698195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915862,0.00012411308,0.00012600714,0.005629263,0.00006971841,0.0017139256,0.000016158228,0.00025836285,0.00047622036],"genre_scores_gemma":[0.988284,0.000039310078,0.010501459,0.00019063549,0.00029534695,0.00039332322,0.000024877661,0.00006850526,0.00020254034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968916,0.0003133676,0.00041341237,0.0007220213,0.0008274144,0.0008321909],"domain_scores_gemma":[0.9983569,0.00019202218,0.00007000656,0.00077839906,0.00021890902,0.00038378712],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012880767,0.00029533444,0.00039667744,0.00078083586,0.00038115622,0.00007573653,0.00024595024,0.00010337078,0.000102868515],"category_scores_gemma":[0.0001512545,0.00024844904,0.000072525356,0.00090847415,0.00019821567,0.0002688215,0.00038703825,0.0017807011,0.00012318237],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001545134,0.0018400004,0.98867136,0.00005744531,0.000015146165,0.00003652243,0.00046322864,5.207541e-7,0.0037345008,0.00040930993,0.00095697487,0.0022698245],"study_design_scores_gemma":[0.0035109886,0.00025297177,0.99301046,0.00034577164,0.000018614199,0.00013258419,0.00043349818,0.0005788737,0.00042132285,0.000923075,0.00014848736,0.00022334499],"about_ca_topic_score_codex":0.000093598064,"about_ca_topic_score_gemma":0.000013935373,"teacher_disagreement_score":0.010375452,"about_ca_system_score_codex":0.00024582408,"about_ca_system_score_gemma":0.00016937108,"threshold_uncertainty_score":0.9999968},"labels":[],"label_agreement":null},{"id":"W1972541617","doi":"10.1016/j.baga.2011.06.029","title":"P28 Human medial forebrain bundle (MFB) and anterior thalamic radiations (ATR): Diffusion tensor imaging anatomical description of two affective pathways that promote a dynamic balance of opposite affects (SEEKING and GRIEF)","year":2011,"lang":"en","type":"article","venue":"Basal Ganglia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; Medial forebrain bundle; Neuroscience; Psychology; Bundle; Balance (ability); Forebrain; Medicine; Radiology; Central nervous system","score_opus":0.04191054394480809,"score_gpt":0.29892928450899536,"score_spread":0.2570187405641873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972541617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850165,0.0001988546,0.013365585,0.00018139572,0.000045570185,0.000877638,0.000049556635,0.000108341,0.00015654831],"genre_scores_gemma":[0.9887303,0.000062539555,0.010941802,0.00009640754,0.000032904874,0.00005337737,0.000025254149,0.00003668033,0.00002074136],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989998,0.000053168664,0.00023030804,0.0003524759,0.00015151303,0.00021273101],"domain_scores_gemma":[0.9992957,0.000059523663,0.00022276887,0.00025494132,0.00006588959,0.00010119009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015514834,0.00018403216,0.00034895222,0.00016145383,0.00010850352,0.000012724959,0.00007921245,0.000054613836,0.000006512969],"category_scores_gemma":[0.000057316658,0.00016752472,0.000065619985,0.0001486206,0.00025693665,0.00017815054,0.00009972857,0.00016992826,3.3649067e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007716775,0.00018916876,0.24867626,0.00013420302,0.000013474311,0.00001493598,0.0010505681,2.2602414e-7,0.7470608,0.0007031832,0.000026739237,0.0020532797],"study_design_scores_gemma":[0.0025096096,0.0005580638,0.8877498,0.00070863124,0.000163691,0.00007021186,0.00014483486,0.020891441,0.0752543,0.011681033,0.000009767236,0.00025860817],"about_ca_topic_score_codex":0.00007207372,"about_ca_topic_score_gemma":0.000032957974,"teacher_disagreement_score":0.6718065,"about_ca_system_score_codex":0.00004903746,"about_ca_system_score_gemma":0.00002284284,"threshold_uncertainty_score":0.68314594},"labels":[],"label_agreement":null},{"id":"W1973562248","doi":"10.1016/j.neuroimage.2006.07.024","title":"White matter growth as a mechanism of cognitive development in children","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":192,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; Hospital for Sick Children; SickKids Foundation; McMaster University; University of Toronto","funders":"Sick Kids Foundation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Cognition; Cognitive psychology; Neuroscience; Developmental psychology; Audiology; Magnetic resonance imaging; Medicine","score_opus":0.019398143052890362,"score_gpt":0.29172072513163827,"score_spread":0.27232258207874793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973562248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97846025,0.000013891038,0.0070494306,0.0007673356,0.000009522671,0.0005933773,0.000011129431,0.000095148775,0.012999942],"genre_scores_gemma":[0.989132,0.000006326092,0.008792906,0.0012720687,0.000021588217,0.00006408226,0.00003784794,0.000027368314,0.0006457967],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991834,0.000015026268,0.0002337135,0.00025606388,0.0001503784,0.00016137934],"domain_scores_gemma":[0.9996488,0.000025701325,0.000070346985,0.00015897994,0.000060892024,0.000035246205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048469665,0.00011138529,0.0001667777,0.00012609926,0.000026279133,0.0000064079077,0.00007385659,0.000029651608,0.000088554676],"category_scores_gemma":[0.000021755905,0.000108373424,0.000035849163,0.00019826203,0.000044931447,0.000049722763,0.00005619465,0.00015167009,0.000074871954],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005547394,0.00048281517,0.9714303,0.000033500804,0.000008139913,0.000057240835,0.00007640106,7.6882884e-7,0.020645754,0.0052649174,0.001339451,0.00060524215],"study_design_scores_gemma":[0.000632869,0.00005832692,0.9136599,0.00007354481,0.000016184118,0.00012803203,0.000005974353,0.000011995006,0.08066716,0.004511196,0.00014046412,0.00009440103],"about_ca_topic_score_codex":0.000041619627,"about_ca_topic_score_gemma":0.0000016218391,"teacher_disagreement_score":0.060021408,"about_ca_system_score_codex":0.000017308354,"about_ca_system_score_gemma":0.000033262037,"threshold_uncertainty_score":0.441934},"labels":[],"label_agreement":null},{"id":"W1973670636","doi":"10.2478/s13380-011-0018-1","title":"Gyral window mapping of typical cortical folding using MRI","year":2011,"lang":"en","type":"article","venue":"Translational Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; McGill University","keywords":"Gyrification; Occipital lobe; Anatomy; Lateralization of brain function; White matter; Temporal lobe; Frontal lobe; Parietal lobe; Occipital region; Psychology; Magnetic resonance imaging; Medicine; Cerebral cortex; Neuroscience; Radiology","score_opus":0.28190502056661515,"score_gpt":0.3853648685491616,"score_spread":0.10345984798254643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973670636","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.480391,0.000014578972,0.51780945,0.0003917843,0.000048502676,0.0001949133,0.0000062499325,0.00007482999,0.0010687035],"genre_scores_gemma":[0.8911073,0.0000053975273,0.10854964,0.00028699814,0.000020779735,0.0000039754377,0.0000011952748,0.000008034764,0.000016684779],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99919,0.0000136360095,0.0002046988,0.00022509239,0.00021833985,0.00014825158],"domain_scores_gemma":[0.99963963,0.00004044957,0.000048554575,0.00014845366,0.000046825866,0.00007610729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007475426,0.00007085805,0.00011462127,0.00007255641,0.00009171746,0.000004026811,0.000098347075,0.000024531511,0.000026719517],"category_scores_gemma":[0.000040512903,0.000066603105,0.000054162345,0.00031014893,0.00024595327,0.00010844668,0.000015991314,0.00013707914,0.0000015932023],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008840952,0.00019427987,0.09764992,0.000026275175,0.0000019750419,0.000014893688,0.00019231443,0.00015215349,0.86742103,0.03297006,0.000011719775,0.0012769704],"study_design_scores_gemma":[0.00038073937,0.00011345195,0.9146724,0.000055402492,0.000026785567,0.00018395272,0.00001150971,0.038486756,0.04029817,0.0050042877,0.0006431047,0.00012346804],"about_ca_topic_score_codex":0.0000032518362,"about_ca_topic_score_gemma":1.4204892e-7,"teacher_disagreement_score":0.82712287,"about_ca_system_score_codex":0.000007037854,"about_ca_system_score_gemma":0.000053833468,"threshold_uncertainty_score":0.2715996},"labels":[],"label_agreement":null},{"id":"W1974268522","doi":"10.1016/j.schres.2004.08.023","title":"Smaller corpus callosum subregions containing motor fibers in schizophrenia","year":2004,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); Neuroscience; Psychology; Anatomy; Medicine; Psychiatry","score_opus":0.1720332418465958,"score_gpt":0.4201316797792233,"score_spread":0.24809843793262748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974268522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9777074,0.00042746062,0.0016484926,0.013660263,0.000103235354,0.0016805173,0.00002513334,0.0004630936,0.0042844336],"genre_scores_gemma":[0.95809406,0.00023992395,0.03955942,0.00030698124,0.00025794806,0.00043968312,0.000037029382,0.0000806325,0.0009843098],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970721,0.00011130023,0.00043549354,0.0007311513,0.0007454223,0.00090453564],"domain_scores_gemma":[0.998112,0.00022151461,0.00006577725,0.0009145296,0.00029275246,0.0003934131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006923853,0.0002506342,0.00038887214,0.0007605482,0.0003318735,0.00006115299,0.00039896258,0.00016559311,0.00007621025],"category_scores_gemma":[0.00038051102,0.00024003425,0.00013391978,0.0013439943,0.00044766566,0.00015361916,0.00024184756,0.0016444043,0.00019612674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03900525,0.0042133443,0.038770825,0.00058128,0.00027051527,0.0047663623,0.0016535117,0.00062423164,0.32776254,0.46900776,0.013764048,0.09958033],"study_design_scores_gemma":[0.07469679,0.0063663004,0.35756034,0.0035465,0.00016130421,0.0020280408,0.001260839,0.0021320735,0.04402428,0.4226853,0.08253395,0.0030042988],"about_ca_topic_score_codex":0.00037604434,"about_ca_topic_score_gemma":0.00018756029,"teacher_disagreement_score":0.3187895,"about_ca_system_score_codex":0.00044390585,"about_ca_system_score_gemma":0.00064078515,"threshold_uncertainty_score":0.97883123},"labels":[],"label_agreement":null},{"id":"W1974674847","doi":"10.1371/journal.pone.0115229","title":"Gestational Age and Neonatal Brain Microstructure in Term Born Infants: A Birth Cohort Study","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council","keywords":"Gestational age; Internal capsule; Corpus callosum; Medicine; Fractional anisotropy; Diffusion MRI; White matter; Pediatrics; Pregnancy; Cohort; Neuroimaging; Cohort study; Obstetrics; Magnetic resonance imaging; Internal medicine; Pathology; Biology; Radiology","score_opus":0.03348481545723665,"score_gpt":0.30082018310346625,"score_spread":0.2673353676462296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974674847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969032,0.000023841372,0.00054921664,0.0014232615,0.0000035691864,0.00080227345,0.000024015188,0.00009018754,0.00018044472],"genre_scores_gemma":[0.98425865,0.000017416967,0.014432306,0.0008573413,0.00004097803,0.000102482256,0.0000465086,0.00001703724,0.00022729069],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993482,0.000019471776,0.00013721603,0.00022892623,0.00015588611,0.000110286564],"domain_scores_gemma":[0.999602,0.00006561099,0.00003751322,0.0002106421,0.00003046431,0.00005373745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088591776,0.000084277104,0.0001792127,0.00007194813,0.000037057143,0.0000121521125,0.000049707716,0.000027452856,0.000017003316],"category_scores_gemma":[0.00011481826,0.000077966506,0.000010960321,0.000108550375,0.000053008796,0.00004487806,0.00004220813,0.0001710638,0.0000027482884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034283486,0.00071569957,0.96567076,0.000042213527,0.000024657056,0.000035565627,0.0002842577,3.720628e-7,0.030351447,0.00022745148,0.000094594136,0.0025186853],"study_design_scores_gemma":[0.0008567021,0.00018604986,0.9953525,0.00006442557,0.000032133226,0.0000177259,0.00002842581,0.0001572178,0.0015406489,0.0010458616,0.0006382294,0.0000800605],"about_ca_topic_score_codex":0.00001807543,"about_ca_topic_score_gemma":0.000024621624,"teacher_disagreement_score":0.029681746,"about_ca_system_score_codex":0.000017262979,"about_ca_system_score_gemma":0.000012903243,"threshold_uncertainty_score":0.31793818},"labels":[],"label_agreement":null},{"id":"W1974790621","doi":"10.1016/j.neurobiolaging.2014.04.035","title":"Measuring brain atrophy with a generalized formulation of the boundary shift integral","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute for Health and Care Research; Canadian Institutes of Health Research; Engineering and Physical Sciences Research Council; Sparks; Medical Research Council","keywords":"Atrophy; Probabilistic logic; Imaging biomarker; Magnetic resonance imaging; Biomarker; Medicine; Artificial intelligence; Computer science; Pathology; Pattern recognition (psychology); Radiology; Biology","score_opus":0.04606133593290812,"score_gpt":0.29650136270906957,"score_spread":0.25044002677616145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974790621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97748786,0.000014921644,0.017941605,0.0039151185,0.000028997509,0.00020593937,0.0000020780005,0.000053451455,0.00035000534],"genre_scores_gemma":[0.9893297,0.0000033052502,0.009815675,0.00076688465,0.000029177987,0.000009081448,0.0000047143576,0.000012864209,0.000028600916],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994657,0.00005180277,0.00016926082,0.00014757286,0.000059483045,0.000106182255],"domain_scores_gemma":[0.99943507,0.00007286098,0.00014072264,0.00028741593,0.000044741482,0.000019183884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090962734,0.00007709316,0.00017701302,0.000050228187,0.000060025595,0.0000021624353,0.00009786251,0.000027965423,0.0000031279517],"category_scores_gemma":[0.000042015577,0.000047972586,0.00006057066,0.00012043249,0.00015575769,0.000029418665,0.00004516609,0.00014455058,3.5069684e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023235305,0.00011091732,0.24750249,0.00017095094,0.000043819797,0.0000014591185,0.00035626497,0.00031354933,0.72378606,0.02148394,0.0002754351,0.0057227863],"study_design_scores_gemma":[0.0019785757,0.0007253317,0.5581632,0.0003109801,0.000109776964,0.00010254674,0.000015131422,0.00141928,0.42178363,0.008653803,0.0065556956,0.00018204162],"about_ca_topic_score_codex":0.00001652827,"about_ca_topic_score_gemma":0.0000039743013,"teacher_disagreement_score":0.31066072,"about_ca_system_score_codex":0.000009130853,"about_ca_system_score_gemma":0.000022332153,"threshold_uncertainty_score":0.19562653},"labels":[],"label_agreement":null},{"id":"W1975017507","doi":"10.1016/j.neuroimage.2010.05.043","title":"Orientationally invariant indices of axon diameter and density from diffusion MRI","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":697,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Lundbeckfonden","keywords":"Axon; White matter; Diffusion MRI; Spherical mean; Corpus callosum; Magnetic resonance imaging; Human brain; Tractography; Fractional anisotropy; Neuroscience; Nuclear magnetic resonance; Anatomy; Physics; Biology; Mathematics; Mathematical analysis; Medicine; Radiology","score_opus":0.03159739527235598,"score_gpt":0.31454506195342613,"score_spread":0.28294766668107013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975017507","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99061126,0.0000095343685,0.007240654,0.0010355097,0.00005688801,0.00022828135,0.00003316525,0.000072048206,0.00071269233],"genre_scores_gemma":[0.94915605,0.000050059636,0.049883556,0.00073762843,0.00005525746,0.000011415258,0.000032351,0.000014245255,0.00005941824],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99937004,0.00001348547,0.00015054175,0.00024486647,0.00013636555,0.00008472565],"domain_scores_gemma":[0.999387,0.00011352608,0.000088023364,0.00028776148,0.000053305357,0.0000703764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046365265,0.00008239911,0.00013439539,0.000053634754,0.000049762402,0.000010844345,0.00006100759,0.000038337133,0.000046919522],"category_scores_gemma":[0.00009466952,0.000071622795,0.000029770486,0.000083778934,0.00011510349,0.0000765895,0.0000775974,0.00022865522,0.0000045984066],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029626688,0.00008982676,0.09695357,0.00001196199,0.000003447067,0.000017349614,0.00006907166,8.098663e-8,0.8985478,0.0009349538,0.00027129968,0.0030709705],"study_design_scores_gemma":[0.00046266222,0.000103820545,0.9016179,0.00001693327,0.000038574024,0.000035329547,0.000009413448,0.00019773841,0.09150344,0.0030881744,0.002852196,0.00007383697],"about_ca_topic_score_codex":0.000058798454,"about_ca_topic_score_gemma":0.000014440841,"teacher_disagreement_score":0.8070444,"about_ca_system_score_codex":0.0000032345908,"about_ca_system_score_gemma":0.000017118145,"threshold_uncertainty_score":0.2920693},"labels":[],"label_agreement":null},{"id":"W1975385958","doi":"10.1016/j.jpain.2012.01.017","title":"DTI 3T MRI assessment of lumbar stabilization muscles","year":2012,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Medicine; Oswestry Disability Index; Lumbar; Low back pain; Effective diffusion coefficient; Longissimus; Multifidus muscle; Tractography; Magnetic resonance imaging; Anatomy; Physical therapy; Radiology; Pathology","score_opus":0.08122468068329128,"score_gpt":0.4172462930282494,"score_spread":0.3360216123449581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975385958","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23227793,0.00022454062,0.7644693,0.002088337,0.00005465849,0.0001571311,0.0000023107905,0.00002013413,0.0007056422],"genre_scores_gemma":[0.9034452,0.00016645649,0.09598049,0.00021629871,0.00014017754,0.000002449862,0.0000015306471,0.0000084109115,0.000039012182],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938387,0.00005520891,0.00027341663,0.000038624832,0.00016509331,0.000083776795],"domain_scores_gemma":[0.99935824,0.000055840163,0.00026549632,0.00011813185,0.00012982443,0.000072490875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080949685,0.00004485274,0.00014027997,0.00006565748,0.000018610419,0.0000025441432,0.000046591173,0.000021017511,0.00004251228],"category_scores_gemma":[0.00011646711,0.000035420024,0.00006117231,0.000095597905,0.000024559384,0.000093266106,0.000011366875,0.00011677738,4.927312e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003298978,0.001435834,0.46295246,0.00024203821,0.000063399595,0.000011990001,0.0004249306,0.00015836206,0.455641,0.016722316,0.014884824,0.047429856],"study_design_scores_gemma":[0.0012791366,0.0009081725,0.8641859,0.00043413867,0.00019902909,0.00021099744,0.00044523831,0.0028766876,0.027745904,0.005128765,0.096404366,0.00018165096],"about_ca_topic_score_codex":9.909177e-7,"about_ca_topic_score_gemma":2.2043311e-7,"teacher_disagreement_score":0.67116725,"about_ca_system_score_codex":0.000041111274,"about_ca_system_score_gemma":0.00004120374,"threshold_uncertainty_score":0.14443867},"labels":[],"label_agreement":null},{"id":"W1975446567","doi":"10.1002/jmri.10205","title":"Serial quantitative diffusion tensor MRI of the premature brain: Development in newborns with and without injury","year":2002,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":328,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research; National Institutes of Health","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Medicine; Effective diffusion coefficient; Radiology","score_opus":0.0266579262998272,"score_gpt":0.30540103550898806,"score_spread":0.27874310920916084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975446567","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98087084,0.0047196266,0.0015364026,0.012170854,0.000033525368,0.0003811091,0.0000023435296,0.000011417665,0.00027385668],"genre_scores_gemma":[0.87404364,0.00051050296,0.12443705,0.00056272675,0.000044799788,0.000009192416,2.2779291e-7,0.000020128256,0.00037173682],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911976,0.000032602744,0.00035211575,0.0001263444,0.0002408198,0.00012837464],"domain_scores_gemma":[0.9993204,0.000051914976,0.0002809478,0.00016213322,0.00013698175,0.000047609607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014195815,0.0001041115,0.00023657718,0.00008733897,0.000048502374,0.000011572802,0.00010424019,0.00002094125,0.000014214832],"category_scores_gemma":[0.000107561755,0.000061510276,0.000031080686,0.00021125254,0.00013664998,0.00009262311,0.000046315286,0.00028712084,2.7983677e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008972704,0.00033949112,0.6988391,0.00012974764,0.000008705385,0.00005287549,0.0026780153,0.000022765647,0.0525873,0.00026191646,0.0031639382,0.24101883],"study_design_scores_gemma":[0.002031095,0.0004368015,0.9329374,0.0016849617,0.000034406203,0.000608161,0.00021518431,0.0016489051,0.0045698574,0.00028434064,0.05542209,0.00012682744],"about_ca_topic_score_codex":0.000003530562,"about_ca_topic_score_gemma":0.0000036482147,"teacher_disagreement_score":0.24089201,"about_ca_system_score_codex":0.000030489304,"about_ca_system_score_gemma":0.000045283177,"threshold_uncertainty_score":0.25083163},"labels":[],"label_agreement":null},{"id":"W1975596980","doi":"10.1002/mrm.24781","title":"Constrained diffusion kurtosis imaging using ternary quartics &amp; MLE","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Université de Sherbrooke","keywords":"Kurtosis; Ternary operation; Diffusion; Chemistry; Nuclear magnetic resonance; Mathematics; Statistics; Computer science; Physics; Thermodynamics","score_opus":0.06393749245486953,"score_gpt":0.35592426035750097,"score_spread":0.29198676790263145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975596980","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.956185,0.0051598744,0.015595556,0.017967347,0.00010881375,0.0012002501,0.0000036511242,0.00023488191,0.0035446582],"genre_scores_gemma":[0.9199425,0.00073632295,0.07483559,0.00279179,0.0002339166,0.00015786343,0.000015975405,0.000049249164,0.0012367617],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99839985,0.000034715948,0.0004891265,0.00039415454,0.0003044752,0.00037767118],"domain_scores_gemma":[0.9989931,0.000112388225,0.0000931637,0.000548003,0.000099383215,0.00015395666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015459987,0.00020455287,0.00037209707,0.00018449314,0.00007571175,0.000012836047,0.00014683376,0.00005085661,0.00080385274],"category_scores_gemma":[0.00020191637,0.00016766286,0.00004291772,0.00042176628,0.00040692821,0.00008891517,0.00006946916,0.00030404268,0.000040459636],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073795214,0.00030600003,0.32769382,0.000113504415,0.000003521297,0.00012284344,0.00052762084,0.000015713533,0.3174922,0.0004969253,0.008942791,0.34421128],"study_design_scores_gemma":[0.0076388936,0.00073386333,0.6525728,0.0031086605,0.0001588686,0.001038981,0.00074788596,0.12602237,0.0018955478,0.012223528,0.19306791,0.00079070154],"about_ca_topic_score_codex":0.0005850454,"about_ca_topic_score_gemma":0.000008822633,"teacher_disagreement_score":0.34342057,"about_ca_system_score_codex":0.00007602158,"about_ca_system_score_gemma":0.000036523918,"threshold_uncertainty_score":0.8801624},"labels":[],"label_agreement":null},{"id":"W1975760079","doi":"10.1016/j.neurobiolaging.2014.05.037","title":"Diffusion weighted imaging-based maximum density path analysis and classification of Alzheimer's disease","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Takeda Pharmaceuticals North America; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; U.S. National Library of Medicine; IXICO; Genentech Foundation; Servier; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; Roche; Elan; Novartis; U.S. Department of Defense; Eli Lilly and Company; AstraZeneca; Bristol-Myers Squibb Foundation; Merck; Alzheimer's Drug Discovery Foundation; Eisai; Abbott Fund; Alzheimer's Association; Bayer HealthCare","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Tractography; CTL*; Multiple sclerosis; Medicine; Artificial intelligence; Neuroscience; Psychology; Computer science; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.028035943194510245,"score_gpt":0.30318512917007656,"score_spread":0.2751491859755663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975760079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9311929,0.000079706304,0.06618085,0.00219388,0.000016680253,0.00017670845,0.0000107684855,0.00008125399,0.00006726865],"genre_scores_gemma":[0.9934115,0.000025543963,0.0060399934,0.00041793418,0.000013536634,0.000008651636,0.000068017325,0.000010872128,0.0000039800802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992302,0.00006443266,0.000237141,0.00029221326,0.00006261055,0.000113390306],"domain_scores_gemma":[0.9991508,0.00009049812,0.00020539212,0.00038220338,0.00009362992,0.00007746071],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000096164506,0.00010104747,0.0002887647,0.00021379927,0.000051638424,0.0000023529847,0.000059964907,0.000028225531,0.000006076878],"category_scores_gemma":[0.000035260415,0.00008931213,0.0000900648,0.0002781252,0.00022622394,0.00002538404,0.000042049265,0.00010038183,6.1182396e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057588844,0.00016044175,0.8397831,0.000041373696,0.00004348671,0.0000019152315,0.000012751889,0.000012029219,0.15515006,0.00046814154,0.000041775584,0.0042273463],"study_design_scores_gemma":[0.00038366305,0.00006514724,0.94017935,0.000029250874,0.0008365459,0.0000031180841,0.00000311612,0.027244639,0.030166233,0.00086574996,0.00015385635,0.0000693354],"about_ca_topic_score_codex":0.00001317818,"about_ca_topic_score_gemma":0.0000010517791,"teacher_disagreement_score":0.12498382,"about_ca_system_score_codex":0.000005586162,"about_ca_system_score_gemma":0.000016927861,"threshold_uncertainty_score":0.3642043},"labels":[],"label_agreement":null},{"id":"W1975879525","doi":"10.1117/12.878293","title":"Comparison between fourth and second order DT-MR image segmentations","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Diffusion MRI; Tensor (intrinsic definition); Segmentation; Image segmentation; Euclidean distance; Artificial intelligence; Random walker algorithm; Mathematics; Pattern recognition (psychology); Computer science; Voxel; Fractional anisotropy; Algorithm; Computer vision; Image (mathematics); Geometry; Magnetic resonance imaging","score_opus":0.04608585751868017,"score_gpt":0.3125824173644806,"score_spread":0.26649655984580045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975879525","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99191016,0.00004437886,0.00081057305,0.0019584338,0.0000414667,0.0006627246,0.00006166669,0.00012883802,0.0043817866],"genre_scores_gemma":[0.42357203,0.000055103446,0.5755904,0.000145358,0.00017210419,0.00015597338,0.0000150476035,0.00005016727,0.00024380587],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985349,8.852891e-9,0.0005351582,0.00033111105,0.00033612756,0.0002626854],"domain_scores_gemma":[0.9983522,0.000084548934,0.0002814046,0.00006354192,0.0010814766,0.00013681411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023188925,0.00022867658,0.00038702463,0.000085274056,0.00008874507,0.00004298265,0.0003471735,0.00010632064,0.000034847904],"category_scores_gemma":[0.00019846065,0.00019501435,0.0002573299,0.00026342424,0.00026879765,0.00034273823,0.00013385034,0.0003048346,0.000001317752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008177122,0.00025038698,0.016351176,0.0005893221,0.00039275494,1.5606271e-7,0.0005267373,0.0000027857889,0.6730259,0.3026211,0.005438542,0.0007193806],"study_design_scores_gemma":[0.0037370275,0.0013588268,0.06816769,0.0006996319,0.0010828644,0.00009603994,0.0035831027,0.015763197,0.87715816,0.01118936,0.016226232,0.0009378412],"about_ca_topic_score_codex":0.000005893342,"about_ca_topic_score_gemma":9.9011636e-8,"teacher_disagreement_score":0.5747798,"about_ca_system_score_codex":0.0000644032,"about_ca_system_score_gemma":0.000022745036,"threshold_uncertainty_score":0.79524547},"labels":[],"label_agreement":null},{"id":"W1976238938","doi":"10.2147/ndt.s4329","title":"Bipolar disorder and neurophysiologic mechanisms","year":2008,"lang":"en","type":"article","venue":"Neuropsychiatric Disease and Treatment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; University of British Columbia","keywords":"Uncinate fasciculus; Orbitofrontal cortex; Neuroscience; Bipolar disorder; Tractography; Diffusion MRI; Corpus callosum; Cognitive psychology; Psychology; Medicine; Cognition; Fractional anisotropy; Prefrontal cortex; Magnetic resonance imaging","score_opus":0.038044536969324055,"score_gpt":0.2908950098284775,"score_spread":0.2528504728591534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976238938","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932454,0.0034107713,0.00084276445,0.0016161127,0.000036308757,0.0004926417,0.000020936594,0.00020227156,0.00013277242],"genre_scores_gemma":[0.97893786,0.016236966,0.0034091596,0.00086750014,0.00005257617,0.00008813135,0.000016198068,0.000024540373,0.00036706412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993049,0.000017564582,0.00010312994,0.00035640955,0.00007655881,0.00014142066],"domain_scores_gemma":[0.99942625,0.000019358182,0.000032123626,0.0002552039,0.000014660317,0.0002524202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000065486965,0.00015611405,0.00014959193,0.00006363782,0.00019897809,0.0000070658502,0.000026690075,0.000016702705,0.000008899508],"category_scores_gemma":[0.0000069447983,0.00011265977,0.000052985142,0.00013800614,0.00007150687,0.00003444007,0.00003029916,0.000054709435,0.000007788214],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016656122,0.008250569,0.64741,0.0002228977,0.00024970705,0.0031792808,0.00018993761,0.000027378761,0.015040768,0.038302228,0.001490999,0.28397065],"study_design_scores_gemma":[0.0018408782,0.0015812167,0.96008396,0.000009345428,0.00036392058,0.00032579602,0.0000074317486,0.0003837279,0.00008255663,0.0047713374,0.030344049,0.00020578527],"about_ca_topic_score_codex":0.000012200119,"about_ca_topic_score_gemma":2.881216e-7,"teacher_disagreement_score":0.312674,"about_ca_system_score_codex":0.0000085096135,"about_ca_system_score_gemma":0.000026065625,"threshold_uncertainty_score":0.45941323},"labels":[],"label_agreement":null},{"id":"W1976839446","doi":"10.1007/s00429-010-0271-z","title":"Histochemical visualization and diffusion MRI at 7 Tesla in the TgCRND8 transgenic model of Alzheimer’s disease","year":2010,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg; St. Boniface Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Effective diffusion coefficient; Gliosis; Pathology; Magnetic resonance imaging; White matter; Alzheimer's disease; Neurology; Neuroscience; Atrophy; Genetically modified mouse; Neurodegeneration; Hippocampus; Medicine; Disease; Chemistry; Psychology; Transgene; Radiology","score_opus":0.03251908929101044,"score_gpt":0.3162464972375224,"score_spread":0.28372740794651197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976839446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9757349,0.00017598202,0.021902839,0.0017288391,0.000022045368,0.00032657225,0.000015223591,0.000027861126,0.00006573605],"genre_scores_gemma":[0.9979541,0.00004596733,0.0010788894,0.00074731064,0.0000384152,0.00001630106,0.000062853054,0.00000847953,0.00004768493],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995725,0.000010262225,0.000111460584,0.00015858232,0.0000851486,0.00006203374],"domain_scores_gemma":[0.9997223,0.000029550542,0.00003804894,0.0001474466,0.000019160427,0.000043482345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004362097,0.000070703776,0.000085418375,0.000039668597,0.00005580504,0.0000040665154,0.000023888437,0.000052777646,0.00001172079],"category_scores_gemma":[0.00002289417,0.00004877997,0.000020536732,0.00007843273,0.000077841745,0.000036111054,0.000014428336,0.00012790115,8.136425e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020407168,0.000039317863,0.0065044244,0.000035909863,0.000004360113,5.5307845e-7,0.00027398317,0.000018578085,0.9789759,0.007017629,0.0012449777,0.0056802984],"study_design_scores_gemma":[0.004503234,0.0004624496,0.5883227,0.00012309873,0.0008760861,0.00015929164,0.00015154664,0.23520236,0.061280444,0.08625916,0.022072623,0.00058704044],"about_ca_topic_score_codex":0.0000035572396,"about_ca_topic_score_gemma":0.0000050554586,"teacher_disagreement_score":0.91769546,"about_ca_system_score_codex":0.0000056383114,"about_ca_system_score_gemma":0.000010660187,"threshold_uncertainty_score":0.19891894},"labels":[],"label_agreement":null},{"id":"W1977068575","doi":"10.1016/j.jocn.2011.12.031","title":"Correlation between cognitive function and the association fibers in patients with Alzheimer’s disease using diffusion tensor imaging","year":2012,"lang":"en","type":"article","venue":"Journal of Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fasciculus; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Medicine; White matter; Dementia; Neuropsychology; Boston Naming Test; Inferior longitudinal fasciculus; Clinical Dementia Rating; Cognition; Internal medicine; Mini–Mental State Examination; Audiology; Cardiology; Magnetic resonance imaging; Psychiatry; Disease; Radiology","score_opus":0.11136910572180679,"score_gpt":0.4142269644688937,"score_spread":0.30285785874708687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977068575","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9815524,0.000050434497,0.016856113,0.0010467576,0.00018803035,0.0002742393,0.0000026146752,0.000008626192,0.000020790661],"genre_scores_gemma":[0.99824816,0.000029105118,0.0005684013,0.0009792413,0.00015936345,0.0000016838961,0.0000011098555,0.00000671456,0.000006195947],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884146,0.00012109545,0.00045714682,0.00011914564,0.00033244013,0.00012872556],"domain_scores_gemma":[0.9983067,0.00069490715,0.0006112037,0.00007542954,0.00016347812,0.00014829927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009346909,0.00006383324,0.00019483682,0.000061283274,0.000093414026,0.00001305747,0.000039492574,0.000022088996,0.0000010813498],"category_scores_gemma":[0.0018015606,0.000037207825,0.000053425738,0.0001979687,0.00017562194,0.00036832984,0.000029327535,0.0003387894,3.1985624e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005834963,0.00012745331,0.99617356,0.0000015273952,0.0000028840825,0.0000011286834,0.000013773091,0.000017839619,0.000013359358,0.000024405652,0.00001227398,0.0030282952],"study_design_scores_gemma":[0.0027144016,0.00013144847,0.9934826,0.00008254607,0.0002974304,0.0000048779275,0.000011205185,0.002963022,0.0000027503957,0.00018319882,0.00008622717,0.000040331353],"about_ca_topic_score_codex":0.0000015175377,"about_ca_topic_score_gemma":6.387716e-8,"teacher_disagreement_score":0.01669579,"about_ca_system_score_codex":0.000019273913,"about_ca_system_score_gemma":0.0000385435,"threshold_uncertainty_score":0.21567665},"labels":[],"label_agreement":null},{"id":"W1977168501","doi":"10.1016/j.schres.2015.01.019","title":"Abnormal white matter integrity in antipsychotic-naïve first-episode psychosis patients assessed by a DTI principal component analysis","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"White matter; Fractional anisotropy; Psychosis; Diffusion MRI; Antipsychotic; Psychology; Internal medicine; Schizophrenia (object-oriented programming); Medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.1532352842077878,"score_gpt":0.4333879517635373,"score_spread":0.2801526675557495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977168501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98552287,0.000064831554,0.0034857255,0.007890203,0.00005698269,0.0010767648,0.00008216776,0.00012765171,0.0016928117],"genre_scores_gemma":[0.9850797,0.000049706894,0.013444115,0.0002850678,0.00006089732,0.00032536846,0.00024280099,0.000043380853,0.0004689678],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99666804,0.00024103644,0.0005181905,0.00074227306,0.0011172085,0.0007132316],"domain_scores_gemma":[0.9977359,0.00014129726,0.000097779965,0.0009916585,0.00056505995,0.0004682585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010524285,0.00024287602,0.0004896562,0.0009033263,0.00015964426,0.00008068726,0.00043673516,0.00014371827,0.00017908694],"category_scores_gemma":[0.00016113737,0.00021687712,0.0001572066,0.0026156264,0.00021016663,0.00018446424,0.00022609001,0.0014915812,0.00022070706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012599139,0.0012441918,0.9615344,0.000036297944,0.00007352689,0.000013733607,0.00010376764,0.00002243084,0.00013405611,0.00011375171,0.03482802,0.0006359267],"study_design_scores_gemma":[0.003503211,0.0002615732,0.9821495,0.00008281517,0.000083629275,0.0000065681024,0.0000475287,0.0027602827,0.0004392424,0.0008421321,0.009581432,0.00024212807],"about_ca_topic_score_codex":0.0006931971,"about_ca_topic_score_gemma":0.00047006688,"teacher_disagreement_score":0.025246589,"about_ca_system_score_codex":0.00028618146,"about_ca_system_score_gemma":0.000065688815,"threshold_uncertainty_score":0.8843992},"labels":[],"label_agreement":null},{"id":"W1977223300","doi":"10.1016/j.nicl.2015.03.007","title":"Comparing a diffusion tensor and non-tensor approach to white matter fiber tractography in chronic stroke","year":2015,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Mitacs; Michael Smith Health Research BC","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Voxel; White matter; Corticospinal tract; Corpus callosum; Stroke (engine); Effective diffusion coefficient; Neuroscience; Magnetic resonance imaging; Medicine; Psychology; Physics; Radiology","score_opus":0.17217852856447868,"score_gpt":0.40780868229600287,"score_spread":0.23563015373152418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977223300","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98301166,0.000037355472,0.004707484,0.002861462,0.000050037735,0.0009246407,0.000009687571,0.00014602403,0.008251617],"genre_scores_gemma":[0.96200967,0.000040329458,0.033365227,0.0031772447,0.00019184903,0.00009600946,0.000011456185,0.000053302727,0.0010549015],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99809444,0.000070268165,0.0005727742,0.000720054,0.00021116876,0.00033128326],"domain_scores_gemma":[0.99868906,0.00012610134,0.00009244774,0.0006013133,0.00007370228,0.00041740717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003014943,0.00020748675,0.0005045969,0.00018586066,0.000044361193,0.000035043257,0.00014692129,0.00010098365,0.000020165808],"category_scores_gemma":[0.00014249742,0.00018174945,0.00012345595,0.00028621487,0.00015698066,0.00009231082,0.0001873918,0.00070332945,0.000097431985],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021109007,0.0006326882,0.9858997,0.000046267553,0.000006406745,0.000048588456,0.00006994974,0.0000383526,0.0023159357,0.000010502888,0.008489186,0.00223135],"study_design_scores_gemma":[0.002117529,0.00041918163,0.976268,0.0000600885,0.00003791797,0.00009974767,0.000022848157,0.0051506665,0.00006707169,0.00004553049,0.0155335935,0.00017781515],"about_ca_topic_score_codex":0.000011324737,"about_ca_topic_score_gemma":0.0000019324,"teacher_disagreement_score":0.028657746,"about_ca_system_score_codex":0.000040916606,"about_ca_system_score_gemma":0.000047503974,"threshold_uncertainty_score":0.7411527},"labels":[],"label_agreement":null},{"id":"W1977322234","doi":"10.1016/j.pain.2013.08.029","title":"Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia","year":2013,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research; Physicians' Services Incorporated Foundation","keywords":"Trigeminal neuralgia; White matter; Diffusion MRI; Medicine; Trigeminal nerve; Fractional anisotropy; Corpus callosum; Cingulum (brain); Anatomy; Fasciculus; Magnetic resonance imaging; Anesthesia; Radiology","score_opus":0.01801262259948639,"score_gpt":0.28827368561835376,"score_spread":0.2702610630188674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977322234","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9600229,0.00038716506,0.011718626,0.026141454,0.000029234101,0.00087106513,0.000010714603,0.00013540525,0.00068340957],"genre_scores_gemma":[0.9871547,0.000017122773,0.006438886,0.0049997913,0.000078602716,0.000112073874,0.000016771008,0.000024685954,0.001157349],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990227,0.00011552638,0.00023509693,0.0002803096,0.000093326955,0.00025303804],"domain_scores_gemma":[0.99946606,0.00009441928,0.000059713155,0.00024485443,0.000032533266,0.00010243601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050650456,0.00014565536,0.0002082816,0.00010131177,0.00005093013,0.000029118466,0.00007817981,0.000070938106,0.00025159254],"category_scores_gemma":[0.000100139776,0.00012396995,0.000039504,0.00017665149,0.00008102159,0.00009721027,0.00004428229,0.0003421677,0.000042316504],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009902349,0.00009311648,0.8051555,0.0002517003,0.000006952225,0.0001359917,0.00041571292,0.0000034644029,0.093020335,0.0002562169,0.052768327,0.04779362],"study_design_scores_gemma":[0.0009973673,0.00017781211,0.9795192,0.00020411235,0.000021683905,0.00070225407,0.00009868708,0.0028591207,0.0025109665,0.0033813447,0.009252886,0.00027459447],"about_ca_topic_score_codex":0.00004457526,"about_ca_topic_score_gemma":0.0000028226848,"teacher_disagreement_score":0.17436363,"about_ca_system_score_codex":0.00002488394,"about_ca_system_score_gemma":0.000018009245,"threshold_uncertainty_score":0.5055348},"labels":[],"label_agreement":null},{"id":"W1977436886","doi":"10.1016/j.neuroimage.2012.08.086","title":"Quantitative MRI in the very preterm brain: Assessing tissue organization and myelination using magnetization transfer, diffusion tensor and T1 imaging","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children; Toronto Centre for Phenogenomics","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Magnetization transfer; Concordance; Fractional anisotropy; Gestational age; Magnetic resonance imaging; Nuclear medicine; Psychology; Medicine; Radiology; Biology; Internal medicine","score_opus":0.05941181811663023,"score_gpt":0.36882342910063143,"score_spread":0.3094116109840012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977436886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8671383,0.00020691293,0.12833135,0.0035467246,0.000032209973,0.0005261986,0.0000036538763,0.000079533536,0.00013510705],"genre_scores_gemma":[0.9862745,0.0002489903,0.012282521,0.0010436851,0.00006026383,0.000011142386,0.00002681741,0.000033566714,0.000018534063],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991622,0.00009725865,0.00018530164,0.00023916923,0.00014384334,0.000172222],"domain_scores_gemma":[0.9994945,0.0001662528,0.000049154183,0.00016798377,0.00007485933,0.000047250378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019342333,0.00012553888,0.00012647307,0.00012095179,0.0001733835,0.00007782713,0.000046824232,0.000033572203,0.0000061816418],"category_scores_gemma":[0.00017778142,0.00010435489,0.000011535048,0.00035792618,0.00008592309,0.00058122736,0.00003231509,0.00016976029,0.0000010333697],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019363986,0.00013336429,0.13742742,0.00009405528,0.0000018103026,0.0000121651165,0.0017038614,0.000011843558,0.84901434,0.0013561303,0.00006910712,0.0101565095],"study_design_scores_gemma":[0.0007967669,0.00011097169,0.9614233,0.00011736385,0.00007194812,0.000398667,0.00041009937,0.02594942,0.009115957,0.00026481098,0.0011429713,0.0001977368],"about_ca_topic_score_codex":0.000010757785,"about_ca_topic_score_gemma":8.483663e-7,"teacher_disagreement_score":0.8398984,"about_ca_system_score_codex":0.000024079854,"about_ca_system_score_gemma":0.000013201305,"threshold_uncertainty_score":0.42554688},"labels":[],"label_agreement":null},{"id":"W1977585542","doi":"10.1016/j.neuroimage.2014.03.026","title":"Improved DTI registration allows voxel-based analysis that outperforms Tract-Based Spatial Statistics","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":180,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Dana Foundation; Canadian Institutes of Health Research; Mayo Foundation for Medical Education and Research; Mayo Clinic","keywords":"Voxel; Computer science; Artificial intelligence; Projection (relational algebra); Pipeline (software); Skeleton (computer programming); Pattern recognition (psychology); Diffusion MRI; Computer vision; Algorithm; Medicine; Magnetic resonance imaging","score_opus":0.055837149039628026,"score_gpt":0.3331731859203047,"score_spread":0.27733603688067665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977585542","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050244294,0.0000055764017,0.94531506,0.0021614719,0.00005835801,0.0005492355,0.000109108485,0.0004175892,0.0011393003],"genre_scores_gemma":[0.91510177,0.000005716303,0.08105011,0.0027274368,0.000101794474,0.00007689654,0.0005008813,0.000051317533,0.00038409894],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983856,0.00005673593,0.00036002844,0.00055856945,0.00033220608,0.00030684326],"domain_scores_gemma":[0.99830306,0.00018341023,0.00024749976,0.00094945915,0.00013691247,0.00017965873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000200002,0.00025160436,0.0003811215,0.00022508253,0.00014713121,0.000060527764,0.00016831802,0.00008070277,0.00009466039],"category_scores_gemma":[0.00023228794,0.0002268266,0.00019769043,0.0004121554,0.00012453478,0.00009813964,0.000020400938,0.00034948604,0.000018639832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012801421,0.0038841427,0.20931306,0.0006844169,0.0003090447,0.000284396,0.00012405103,0.0053529944,0.6083132,0.003264145,0.014319527,0.1528709],"study_design_scores_gemma":[0.001791983,0.00070254225,0.14385326,0.000022054837,0.0009473761,0.000011570387,0.000005331825,0.78738356,0.043093316,0.00030841943,0.0215191,0.00036151544],"about_ca_topic_score_codex":0.000102802034,"about_ca_topic_score_gemma":0.000045989356,"teacher_disagreement_score":0.86485744,"about_ca_system_score_codex":0.00004688995,"about_ca_system_score_gemma":0.000090448964,"threshold_uncertainty_score":0.924972},"labels":[],"label_agreement":null},{"id":"W1978373547","doi":"10.1007/s10334-003-0020-x","title":"Water self-diffusion tensor changes in an avian genetic developmental model of epilepsy","year":2003,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Siemens Canada","keywords":"Fractional anisotropy; Juvenile; Tectum; Diffusion MRI; Juvenile myoclonic epilepsy; Epilepsy; Anisotropy; Psychology; Stimulation; Endocrinology; Internal medicine; Neuroscience; Medicine; Biology; Physics; Central nervous system; Magnetic resonance imaging; Optics; Midbrain; Ecology","score_opus":0.04227321376209335,"score_gpt":0.3198672680626729,"score_spread":0.27759405430057954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978373547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979259,0.00053353835,0.0003042675,0.00048472668,0.000041953776,0.0004252076,0.000010313938,0.000030703737,0.0002434273],"genre_scores_gemma":[0.97645235,0.0015617154,0.02129137,0.00041839542,0.000058340553,0.00010526454,0.00003018645,0.000015633459,0.0000667255],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990404,0.00006674353,0.00030571903,0.00029676594,0.00006040899,0.00022995887],"domain_scores_gemma":[0.999661,0.000022221306,0.000050202914,0.00018474685,0.00003086378,0.000050932023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000176516,0.00014361198,0.00038598204,0.00007988721,0.000028645409,0.0000018184647,0.0000641899,0.000082319704,0.000059150898],"category_scores_gemma":[0.000023157645,0.00009830595,0.00000886726,0.00009401518,0.00022565099,0.000021165482,0.000035612808,0.000087393484,0.0000012719271],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007210915,0.00015959506,0.056842823,0.00006425494,0.0000012102765,0.0000071026016,0.0005130518,0.0000027055503,0.92567515,0.001998823,0.000007999296,0.014655171],"study_design_scores_gemma":[0.0039910786,0.0017312932,0.24130124,0.0004469418,0.00004381383,0.00008656736,0.00015725741,0.0011744985,0.6975093,0.050307054,0.0029167451,0.00033419675],"about_ca_topic_score_codex":0.000024808513,"about_ca_topic_score_gemma":0.000011790927,"teacher_disagreement_score":0.22816585,"about_ca_system_score_codex":0.000020262982,"about_ca_system_score_gemma":0.000021147649,"threshold_uncertainty_score":0.40088004},"labels":[],"label_agreement":null},{"id":"W1978566928","doi":"10.1016/j.brainres.2010.04.064","title":"Sex differences in the human corpus callosum microstructure: A combined T2 myelin-water and diffusion tensor magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University of Toronto; Hospital for Sick Children","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Magnetic resonance imaging; Splenium; Nuclear magnetic resonance; Tractography; Psychology; Anatomy; Medicine; Radiology; Physics","score_opus":0.0805886032352576,"score_gpt":0.40131832234716747,"score_spread":0.32072971911190984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978566928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98333055,0.00018754066,0.000017576413,0.014652841,0.000018248074,0.0015114581,0.0000055476185,0.00005667236,0.00021956145],"genre_scores_gemma":[0.99703354,0.000027778977,0.00046958865,0.0006021685,0.00006640529,0.00022102859,0.000010983062,0.000022120797,0.001546414],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99831027,0.00021392315,0.00021018271,0.0004216328,0.00043493972,0.00040908137],"domain_scores_gemma":[0.9988606,0.0003536538,0.000021156364,0.00058434246,0.00010092426,0.00007930853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000907057,0.00013188625,0.00019406258,0.00016729385,0.00037350025,0.00008347944,0.0003051662,0.00004480675,0.000040944054],"category_scores_gemma":[0.0001970267,0.00007561835,0.000023742767,0.00025642908,0.0004545842,0.00003638063,0.00024033143,0.001076342,0.0000042836846],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043516502,0.00027745482,0.552272,0.000016476111,0.0000011049625,0.00008835484,0.001117716,1.1689845e-8,0.43532732,0.00034184346,0.0010149432,0.009499237],"study_design_scores_gemma":[0.0013609183,0.00039539317,0.9830432,0.000032278596,0.0000059531844,0.00008910347,0.00063185097,0.00026338882,0.0020165425,0.0041617677,0.007894457,0.00010514241],"about_ca_topic_score_codex":0.00021088985,"about_ca_topic_score_gemma":0.0001156597,"teacher_disagreement_score":0.43331078,"about_ca_system_score_codex":0.00001551212,"about_ca_system_score_gemma":0.000021772814,"threshold_uncertainty_score":0.467623},"labels":[],"label_agreement":null},{"id":"W1979259237","doi":"10.3171/foc/2008/25/9/e3","title":"Advances in neuroimaging in patients with epilepsy","year":2008,"lang":"en","type":"review","venue":"Neurosurgical FOCUS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Neuroimaging; Magnetoencephalography; Diffusion MRI; Context (archaeology); Epilepsy; White matter; Tractography; Magnetic resonance imaging; Neuroscience; Epilepsy surgery; Medicine; Psychology; Radiology; Electroencephalography","score_opus":0.05241057053761931,"score_gpt":0.36225222530215495,"score_spread":0.3098416547645356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979259237","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00033116102,0.9941389,0.00009834154,0.00013386301,0.00006380754,0.0019488644,0.000023524526,0.00020746044,0.0030541017],"genre_scores_gemma":[0.0007659059,0.99790174,0.00061835797,0.00015309028,0.00005091956,0.0002871233,0.000052261432,0.00011467908,0.0000558974],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974654,0.00010871679,0.0007382684,0.0008752578,0.00035110358,0.00046129827],"domain_scores_gemma":[0.99872684,0.00022314151,0.00023139478,0.00062560086,0.00004194005,0.00015110044],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000046463458,0.0004843975,0.0016237785,0.00042097544,0.0000458932,0.000014875433,0.00022984593,0.00014042207,0.000015122718],"category_scores_gemma":[0.00007800025,0.00035603432,0.00023053602,0.0010997372,0.00014355038,0.00015364615,0.00009755875,0.0012342178,0.000023640412],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005559063,0.00042686966,0.018310416,0.00090213865,0.000002188358,0.0007534014,0.0000033325666,0.000002955091,6.862652e-8,0.00012045545,0.000057374662,0.9793652],"study_design_scores_gemma":[0.0011713377,0.00023077634,0.007179253,0.0042861775,0.00004715708,0.0002638136,2.5513415e-7,0.000007665303,4.73318e-7,0.00008209658,0.98642373,0.00030726547],"about_ca_topic_score_codex":0.0000048612987,"about_ca_topic_score_gemma":0.000002079393,"teacher_disagreement_score":0.98636633,"about_ca_system_score_codex":0.00009954818,"about_ca_system_score_gemma":0.00009412599,"threshold_uncertainty_score":0.99988914},"labels":[],"label_agreement":null},{"id":"W1979558268","doi":"10.1155/2013/350623","title":"Cognitive Intraindividual Variability and White Matter Integrity in Aging","year":2013,"lang":"en","type":"article","venue":"The Scientific World JOURNAL","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Neuropsychology; Effects of sleep deprivation on cognitive performance; Cognition; Neuroimaging; Audiology; Tractography; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.05593590842472349,"score_gpt":0.3424525621474851,"score_spread":0.2865166537227616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979558268","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9558011,0.000029737246,0.004817229,0.035152383,0.00015102197,0.00045473463,0.0000057990537,0.000034023906,0.0035539225],"genre_scores_gemma":[0.99223864,0.000005384734,0.004030003,0.0009297348,0.00007629161,0.00002186332,0.0000026852974,0.000007315594,0.0026880747],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991178,0.00009166212,0.00020922458,0.00020639962,0.00017130729,0.00020362745],"domain_scores_gemma":[0.99938905,0.00013039327,0.0000730971,0.0001986822,0.00012049491,0.00008830749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013947967,0.00007896201,0.00011356091,0.00016296683,0.0002963881,0.00023764279,0.00011770703,0.000015403868,0.0006594116],"category_scores_gemma":[0.000097393524,0.00004947737,0.000032158114,0.0004192517,0.0004188723,0.00016859104,0.000084931715,0.00078064465,0.00005435894],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021317406,0.00019431845,0.9342601,0.000025317719,0.000017054663,0.000014339335,0.0018285742,0.0000031616846,0.00333761,0.0007976323,0.024707455,0.034793142],"study_design_scores_gemma":[0.000440246,0.000015650283,0.9559885,0.0001591208,0.000027087068,0.0004742788,0.0003655185,0.0004669065,0.00045657108,0.038999293,0.002509648,0.000097177835],"about_ca_topic_score_codex":0.00000742344,"about_ca_topic_score_gemma":0.000008598179,"teacher_disagreement_score":0.038201664,"about_ca_system_score_codex":0.000034749482,"about_ca_system_score_gemma":0.000039621653,"threshold_uncertainty_score":0.7220094},"labels":[],"label_agreement":null},{"id":"W1979588596","doi":"10.1016/j.neuroimage.2010.03.076","title":"Spectral-based automatic labeling and refining of human cortical sulcal curves using expert-provided examples","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Korea Science and Engineering Foundation","keywords":"Artificial intelligence; Pattern recognition (psychology); Preprocessor; Set (abstract data type); Mathematics; Data set; Computer science; Matching (statistics); Statistics","score_opus":0.12950641096684598,"score_gpt":0.3993977662580669,"score_spread":0.2698913552912209,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979588596","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945116,0.000096024145,0.003658435,0.00090682483,0.000032763804,0.00022904116,0.0000052749706,0.00028438427,0.00027563804],"genre_scores_gemma":[0.8956641,0.000021763615,0.1032129,0.0009712387,0.000051158586,0.000014645414,0.000009192233,0.00003683679,0.000018183158],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989448,0.000033758944,0.00032255394,0.00031726967,0.00017350615,0.0002081093],"domain_scores_gemma":[0.9991118,0.00017734956,0.00011240042,0.00042756053,0.00005997751,0.00011092835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001286125,0.00014372003,0.00028029265,0.00008334447,0.00012938712,0.000016595754,0.00008805563,0.00004575019,0.000047273108],"category_scores_gemma":[0.00033517304,0.00013425027,0.00005265623,0.00014546629,0.00020392456,0.000074476564,0.00005106278,0.00042611882,0.0000011153184],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008468472,0.00008130439,0.0038643123,0.00016071892,0.0000028862946,0.00002419169,0.000028729686,9.372254e-7,0.9940753,0.00079729746,0.00008109482,0.00087476126],"study_design_scores_gemma":[0.0021060263,0.0006333411,0.11493415,0.0011250068,0.00020950071,0.00038958612,0.000051391446,0.047882948,0.82991344,0.00096209993,0.001283726,0.00050877297],"about_ca_topic_score_codex":0.00004162754,"about_ca_topic_score_gemma":0.0000048484185,"teacher_disagreement_score":0.16416185,"about_ca_system_score_codex":0.000009318998,"about_ca_system_score_gemma":0.00004405191,"threshold_uncertainty_score":0.5474567},"labels":[],"label_agreement":null},{"id":"W1979696665","doi":"10.1016/j.nicl.2014.05.012","title":"Anatomical and diffusion MRI of deep gray matter in pediatric spina bifida","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Putamen; White matter; Fractional anisotropy; Diffusion MRI; Thalamus; Basal ganglia; Anatomy; Grey matter; Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Central nervous system; Radiology","score_opus":0.049143666304319995,"score_gpt":0.3918213596880391,"score_spread":0.3426776933837191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979696665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867295,0.00004157653,0.008708767,0.0030861392,0.000059910886,0.0002880229,0.000002291102,0.00007010148,0.0010137089],"genre_scores_gemma":[0.9876448,0.0004865206,0.009689301,0.0019259432,0.00015816285,0.000013523745,0.000004762033,0.000027439768,0.000049539613],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985442,0.00009665269,0.0005871875,0.00045658296,0.00013431147,0.00018103878],"domain_scores_gemma":[0.9988596,0.00036631388,0.00012516325,0.00047344092,0.00003937062,0.00013611322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029958636,0.00012586974,0.00037121293,0.00012496399,0.000025777588,0.000007508401,0.0001062513,0.000093471484,0.000033616325],"category_scores_gemma":[0.0003307157,0.00010856613,0.00009174389,0.0002162785,0.00018348591,0.000047444188,0.00013031221,0.00044531934,0.000025870288],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075375196,0.00034678017,0.98825544,0.000059639307,0.000001276019,0.000018675704,0.0000079917345,5.6280345e-7,0.0022229466,0.00027711963,0.0008856118,0.007848565],"study_design_scores_gemma":[0.0011146764,0.00029090105,0.9905257,0.000018931927,0.00003760166,0.000039448412,0.0000020319965,0.0030802367,0.00024323458,0.001250625,0.0033016605,0.00009493152],"about_ca_topic_score_codex":0.0000049936134,"about_ca_topic_score_gemma":0.0000017964061,"teacher_disagreement_score":0.0077536334,"about_ca_system_score_codex":0.0000069817193,"about_ca_system_score_gemma":0.000012739731,"threshold_uncertainty_score":0.44271982},"labels":[],"label_agreement":null},{"id":"W1979757232","doi":"10.1016/j.neuroimage.2011.01.032","title":"Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":419,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Ground truth; Computer science; Diffusion MRI; Imaging phantom; Smoothness; Artificial intelligence; Diffusion; Algorithm; Data mining; Pattern recognition (psychology); Mathematics; Physics; Magnetic resonance imaging; Medicine; Optics","score_opus":0.31865904058259104,"score_gpt":0.43404562757906906,"score_spread":0.11538658699647802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979757232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9292902,0.00008276874,0.022023508,0.0004120756,0.00009191133,0.0015016283,0.00008094701,0.00034271536,0.046174243],"genre_scores_gemma":[0.97853523,0.00006329719,0.02083858,0.00025678982,0.000025611102,0.000081741724,0.000035076373,0.000032332995,0.00013133914],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99872774,0.000081480524,0.00025185282,0.00033175564,0.00044063086,0.00016656419],"domain_scores_gemma":[0.99891937,0.00009331498,0.00015987632,0.0004647579,0.0002875181,0.00007515103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026624693,0.00013828986,0.00020538444,0.00019082983,0.00006021266,0.0000049288556,0.000096865144,0.00004005449,0.00022619635],"category_scores_gemma":[0.00023973068,0.000120906254,0.00010165224,0.00033459696,0.00011725657,0.000070751776,0.000028509325,0.00017155037,0.000022476928],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001967234,0.004088942,0.0031034572,0.00016010577,0.000061146675,0.00010020648,0.0013313586,0.000016305035,0.8592746,0.017165707,0.004375963,0.108354926],"study_design_scores_gemma":[0.0059888056,0.007862316,0.6166697,0.00048547715,0.0012226221,0.00014423244,0.00025705094,0.053690247,0.2798365,0.027402936,0.005714541,0.0007255247],"about_ca_topic_score_codex":0.00003583809,"about_ca_topic_score_gemma":0.0000013637157,"teacher_disagreement_score":0.6135663,"about_ca_system_score_codex":0.000019179894,"about_ca_system_score_gemma":0.0000333597,"threshold_uncertainty_score":0.4930414},"labels":[],"label_agreement":null},{"id":"W1980193648","doi":"10.1017/s0317167100014669","title":"fMRI-Driven DTT Assessment of Corticospinal Tracts Prior to Cortex Resection","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cerebral peduncle; Diffusion MRI; Corticospinal tract; White matter; Glioma; Medicine; Magnetic resonance imaging; Tractography; Motor cortex; Cortex (anatomy); Radiology; Nuclear medicine; Neuroscience; Psychology; Internal capsule; Internal medicine","score_opus":0.07794176454895449,"score_gpt":0.3671880671293837,"score_spread":0.28924630258042916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980193648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849969,0.000116396404,0.00082575734,0.011208811,0.0002966248,0.0004517422,0.000006067306,0.000024712956,0.002072955],"genre_scores_gemma":[0.96791714,0.00013561315,0.028326143,0.0034153664,0.00015133624,0.000011496752,2.792465e-7,0.000011830303,0.000030792464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99656713,0.0003033586,0.00096264307,0.00046853078,0.0007752374,0.0009230969],"domain_scores_gemma":[0.99579287,0.00029195473,0.00079329126,0.00020210075,0.0008467061,0.0020730891],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0014577563,0.00024817445,0.00052137143,0.00092224573,0.0012814846,0.00027365665,0.0010838007,0.00012088496,0.00021498646],"category_scores_gemma":[0.0013381786,0.00017102987,0.00020427543,0.0014183762,0.0030131214,0.00070528476,0.000062174324,0.0010554079,0.0000039004276],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009418421,0.00012185362,0.97833973,0.000018377572,0.000016909089,0.001620475,0.00015430556,0.0024564592,0.0045922766,0.0018522074,0.0013120722,0.009421173],"study_design_scores_gemma":[0.00024576037,0.06623948,0.90767497,0.00006993686,0.00004075712,0.014809509,0.00009456743,0.0022956221,0.00032038277,0.0062043006,0.0018222035,0.00018250814],"about_ca_topic_score_codex":0.0009978034,"about_ca_topic_score_gemma":0.0058646756,"teacher_disagreement_score":0.07066474,"about_ca_system_score_codex":0.00023397406,"about_ca_system_score_gemma":0.002686947,"threshold_uncertainty_score":0.9997001},"labels":[],"label_agreement":null},{"id":"W1980234953","doi":"10.1016/j.schres.2015.01.005","title":"Effects of endurance training on brain structures in chronic schizophrenia patients and healthy controls","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Mental Health & Substance Use Services; University of British Columbia","funders":"Courant Forschungszentrum Geobiologie, Georg-August-Universität Göttingen; Georg-August-Universität Göttingen; Bristol-Myers Squibb","keywords":"Schizophrenia (object-oriented programming); Physical medicine and rehabilitation; Medicine; Endurance training; Neuroscience; Psychology; Physical therapy; Psychiatry","score_opus":0.12076892916585268,"score_gpt":0.42245545176386756,"score_spread":0.3016865225980149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980234953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99224657,0.00075500464,0.000108818705,0.0050278623,0.000036657646,0.0014927004,0.000013540849,0.000067038294,0.00025181795],"genre_scores_gemma":[0.994662,0.00011388957,0.004464179,0.00037695203,0.00011298796,0.00018303373,0.000013043187,0.000033680797,0.000040233426],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99793094,0.0002157108,0.0003138589,0.00043703857,0.00062578474,0.0004766892],"domain_scores_gemma":[0.9981967,0.0008686871,0.000079771125,0.00035106734,0.00021095411,0.0002927864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000610282,0.00016206807,0.00039076805,0.00042074543,0.00008951658,0.000018045854,0.00016993441,0.000119895376,0.000004162038],"category_scores_gemma":[0.0014756576,0.0001408131,0.000039368413,0.0005543892,0.00027985743,0.00007886836,0.00009430337,0.0010382787,0.0000058217884],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0511398,0.0013245891,0.015190073,0.002042322,0.00009432245,0.0001867014,0.0019924517,0.0001238059,0.29829028,0.1188977,0.009533534,0.5011844],"study_design_scores_gemma":[0.06136181,0.0066983197,0.8140104,0.0013031275,0.000030109104,0.000040952254,0.00014309175,0.0014840094,0.045957133,0.06207227,0.0063330308,0.00056578714],"about_ca_topic_score_codex":0.000051548326,"about_ca_topic_score_gemma":0.000022063334,"teacher_disagreement_score":0.7988203,"about_ca_system_score_codex":0.00023247713,"about_ca_system_score_gemma":0.00049989636,"threshold_uncertainty_score":0.57421917},"labels":[],"label_agreement":null},{"id":"W1980602340","doi":"10.1111/j.1749-6632.2002.tb07596.x","title":"Is the Cerebellum Important for Podokinetic Adaptation?","year":2002,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Deafness and Other Communication Disorders","keywords":"Medicine; Health science; Library science; Medical education","score_opus":0.30922424093643996,"score_gpt":0.416656914594485,"score_spread":0.10743267365804504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980602340","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08120431,0.0044668308,0.0029191899,0.90778637,0.000052033058,0.0013296177,0.000033192162,0.000059567043,0.0021489048],"genre_scores_gemma":[0.98063225,0.00061199116,0.00857032,0.008280923,0.000069534006,0.000015968697,1.8037956e-7,0.000005963518,0.0018128814],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991615,0.000011057881,0.00026445262,0.0001607471,0.00025778677,0.00014447843],"domain_scores_gemma":[0.9993997,0.00013540867,0.0002566363,0.00013235907,0.00003421239,0.00004165676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027533466,0.00006656549,0.00012537181,0.000036176956,0.00016447686,0.00000610304,0.00045259803,0.000031521984,0.000035806825],"category_scores_gemma":[0.000092783695,0.000034220848,0.000116168565,0.00040813434,0.0005084913,0.000047620902,0.00004252265,0.00009819273,0.0000014634708],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004642686,0.00021846066,0.005428301,0.000094835275,0.000049980572,1.143303e-7,0.0020611219,0.00026661283,0.040595215,0.061910953,0.840051,0.04927698],"study_design_scores_gemma":[0.00043765712,0.00042169946,0.018291475,0.0002547497,0.00009927795,0.000025123212,0.0004370431,0.01600491,0.43583605,0.21403742,0.31398216,0.00017242588],"about_ca_topic_score_codex":0.000018777417,"about_ca_topic_score_gemma":3.4436133e-7,"teacher_disagreement_score":0.89950544,"about_ca_system_score_codex":0.0000020431057,"about_ca_system_score_gemma":0.000020383644,"threshold_uncertainty_score":0.18735574},"labels":[],"label_agreement":null},{"id":"W1980949712","doi":"10.1117/12.911707","title":"Rician compressed sensing for fast and stable signal reconstruction in diffusion MRI","year":2012,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Undersampling; Computer science; Rician fading; Compressed sensing; Noise (video); Voxel; Algorithm; Decoding methods; Gaussian; Signal reconstruction; Reconstruction algorithm; Artificial intelligence; Stability (learning theory); Iterative reconstruction; Pattern recognition (psychology); Signal processing; Machine learning; Digital signal processing; Image (mathematics)","score_opus":0.022978919572354924,"score_gpt":0.2703057710605753,"score_spread":0.24732685148822037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980949712","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99375725,0.000077739205,0.0023169906,0.0021634593,0.00007451877,0.0009037333,0.000026050835,0.00007316493,0.00060711097],"genre_scores_gemma":[0.5614279,0.00010492103,0.4378518,0.000111117595,0.00027598883,0.000106512125,0.000008568107,0.000041107094,0.000072076466],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99879736,9.71403e-9,0.00041268225,0.00024244825,0.00024558417,0.00030191118],"domain_scores_gemma":[0.9989519,0.00010963188,0.00021093774,0.00003827937,0.0005870382,0.00010222228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031441028,0.00017961637,0.00029985115,0.00009418256,0.00007229244,0.00003307464,0.00015784836,0.00010454173,0.0000030934082],"category_scores_gemma":[0.00015722995,0.00015518158,0.00020310895,0.00019356846,0.00014120487,0.00035574546,0.00007790145,0.00021658013,1.7100511e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013035684,0.00013710112,0.0038272394,0.0004654292,0.00006951451,3.161544e-8,0.00017192762,0.00002827175,0.86836267,0.12283058,0.00063929084,0.0033375793],"study_design_scores_gemma":[0.004864148,0.00073480565,0.0146339545,0.0017413391,0.00042317164,0.00023416006,0.0035807323,0.316486,0.63763714,0.0075157974,0.011367098,0.0007816651],"about_ca_topic_score_codex":0.0000069954963,"about_ca_topic_score_gemma":8.697332e-8,"teacher_disagreement_score":0.4355348,"about_ca_system_score_codex":0.00010227512,"about_ca_system_score_gemma":0.000013431686,"threshold_uncertainty_score":0.63281214},"labels":[],"label_agreement":null},{"id":"W1981036581","doi":"10.1016/j.pscychresns.2011.06.017","title":"Progressive membrane phospholipid changes in first episode schizophrenia with high field magnetic resonance spectroscopy","year":2012,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Thalamus; Hippocampus; Internal medicine; Anterior cingulate cortex; Schizophrenia (object-oriented programming); Endocrinology; Cingulate cortex; Phospholipid; Gyrus; Neuroscience; Psychology; Medicine; Chemistry; Central nervous system; Psychiatry; Biochemistry; Membrane","score_opus":0.055889709712357995,"score_gpt":0.3798581099472489,"score_spread":0.3239684002348909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981036581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8718682,0.014480813,0.00047057724,0.10611805,0.00038262006,0.0026671996,0.000020276824,0.000536333,0.003455905],"genre_scores_gemma":[0.9350707,0.0008886563,0.060848635,0.001408624,0.0007352667,0.00066981185,0.00001235249,0.00010821,0.0002577651],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996984,0.00011365809,0.00028010536,0.0006823279,0.0006812269,0.0012586627],"domain_scores_gemma":[0.99825907,0.0002492581,0.00008098761,0.0009067513,0.00017014307,0.00033377847],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046625268,0.00028408592,0.00034500644,0.0004283095,0.00031174903,0.00006423187,0.00034259615,0.000064987835,0.00016620204],"category_scores_gemma":[0.00019936575,0.00024607897,0.000045741923,0.0015708283,0.00027810605,0.00024183102,0.00017595131,0.0013940028,0.000044312532],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018604767,0.0011526236,0.95532,0.00041175584,0.000011668643,0.00019842,0.00020567229,0.0000048051065,0.014246238,0.0058555254,0.009567413,0.011165398],"study_design_scores_gemma":[0.0077745076,0.0041221236,0.72803944,0.0028214783,0.00010260154,0.0018899494,0.00027999023,0.0009833777,0.14443034,0.005140475,0.103086665,0.0013290378],"about_ca_topic_score_codex":0.00017890215,"about_ca_topic_score_gemma":0.0001496401,"teacher_disagreement_score":0.22728056,"about_ca_system_score_codex":0.00008663413,"about_ca_system_score_gemma":0.00011070666,"threshold_uncertainty_score":0.99999917},"labels":[],"label_agreement":null},{"id":"W1981581208","doi":"10.1002/mrm.22786","title":"Preterm neonatal diffusion processing using detection and replacement of outliers prior to resampling","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Outlier; Resampling; Diffusion MRI; Voxel; Computer science; Artificial intelligence; Estimator; Diffusion; Computer vision; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Medicine; Radiology; Physics","score_opus":0.08458024766958966,"score_gpt":0.3526075372995314,"score_spread":0.26802728962994177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981581208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96579003,0.002434707,0.030140344,0.00041883026,0.00003248989,0.0007975284,0.0000011755614,0.000049324048,0.0003355645],"genre_scores_gemma":[0.9278334,0.0002120818,0.07153214,0.00024203405,0.000039402483,0.000049802282,0.000001042447,0.000018739527,0.00007138146],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99893856,0.000015646861,0.00035992617,0.00031568197,0.00019642766,0.00017375796],"domain_scores_gemma":[0.99946404,0.000027634316,0.00009628933,0.00026418443,0.000060617924,0.00008721376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021014866,0.000115214934,0.00024936965,0.00017753421,0.00005316132,0.0000026663758,0.000064018815,0.000035088924,0.000023374147],"category_scores_gemma":[0.0001713656,0.00009680498,0.000014715335,0.0003041355,0.00014470011,0.00004187862,0.000061916646,0.00014349903,3.1469455e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006891799,0.00006143374,0.035116825,0.0002035197,0.0000011915872,0.000021474962,0.0025382494,0.0000033559613,0.1259687,0.00003412804,0.000016559527,0.8353454],"study_design_scores_gemma":[0.006253444,0.006125165,0.86189985,0.0075258086,0.00016665072,0.0005099297,0.0016582392,0.035208803,0.05992504,0.0024507418,0.01773139,0.0005449242],"about_ca_topic_score_codex":0.00013640718,"about_ca_topic_score_gemma":0.000011845983,"teacher_disagreement_score":0.8348005,"about_ca_system_score_codex":0.00005003595,"about_ca_system_score_gemma":0.000021206048,"threshold_uncertainty_score":0.39475924},"labels":[],"label_agreement":null},{"id":"W1981639529","doi":"10.1161/strokeaha.109.573287","title":"Acute Corticospinal Tract Wallerian Degeneration Is Associated With Stroke Outcome","year":2010,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre","funders":"","keywords":"Medicine; Corticospinal tract; Wallerian degeneration; Stroke (engine); Effective diffusion coefficient; Magnetic resonance imaging; Radiology; Pyramidal tracts; Diffusion MRI; Cardiology; Pathology; Anatomy","score_opus":0.051155344151690096,"score_gpt":0.3530123602458715,"score_spread":0.3018570160941814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981639529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98383623,0.0000068378768,0.009900603,0.0031254007,0.00008065548,0.00037256966,0.00014619142,0.0002882497,0.002243239],"genre_scores_gemma":[0.97652495,0.000008934996,0.017092103,0.000930532,0.000099431425,0.00005931979,0.00007827681,0.000030061468,0.005176379],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991153,0.000007502814,0.00020562675,0.00024879526,0.00021038255,0.00021242311],"domain_scores_gemma":[0.9993038,0.000017645089,0.00011135679,0.0003511822,0.00009996302,0.00011604849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005919083,0.00013582033,0.0001973941,0.000052463532,0.0001099146,0.000024971616,0.000082547966,0.00007667425,0.00013440322],"category_scores_gemma":[0.000041466417,0.00010954399,0.00006617879,0.00009501862,0.000061185056,0.00008338507,0.000017851362,0.0004055677,0.000017368146],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103678714,0.00034312654,0.11675409,0.000007859852,0.00009119795,0.0000750576,0.00005855956,0.0000026407254,0.87424254,0.0013737729,0.0009088631,0.006038611],"study_design_scores_gemma":[0.004089658,0.001666523,0.6798835,0.000058026653,0.00073985994,0.00049406016,0.00004507694,0.0019654154,0.26149568,0.00037925167,0.048525445,0.00065753935],"about_ca_topic_score_codex":0.000007085659,"about_ca_topic_score_gemma":0.00002093648,"teacher_disagreement_score":0.61274683,"about_ca_system_score_codex":0.000031692387,"about_ca_system_score_gemma":0.00004572169,"threshold_uncertainty_score":0.4467074},"labels":[],"label_agreement":null},{"id":"W1982080133","doi":"10.1109/tbme.2012.2230262","title":"Multistructure Large Deformation Diffeomorphic Brain Registration","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Image registration; Artificial intelligence; Robustness (evolution); Diffeomorphism; Computer vision; Computer science; Brain morphometry; Matching (statistics); Pattern recognition (psychology); Neuroimaging; Neuroscience; Magnetic resonance imaging; Mathematics; Psychology; Medicine; Biology","score_opus":0.028345193542547557,"score_gpt":0.2996760640480542,"score_spread":0.27133087050550664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1982080133","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03234145,0.000021581645,0.9645393,0.0020479383,0.00025441247,0.00024832782,0.0000305506,0.0004573084,0.000059113845],"genre_scores_gemma":[0.98244756,0.000024482906,0.016672451,0.00044070426,0.00014873025,0.000071330105,0.000043917044,0.000025998996,0.00012481424],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991364,0.0000078005205,0.00021023813,0.00013963254,0.00022498582,0.00028097694],"domain_scores_gemma":[0.9994302,0.00005220251,0.000038100843,0.00022505685,0.000023254008,0.00023121336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010830257,0.00013352708,0.00013392085,0.0001450196,0.00009266775,0.000008952179,0.000051903677,0.000109351844,0.00005881123],"category_scores_gemma":[0.000020919579,0.00011969058,0.00007221242,0.00027090797,0.000034343197,0.00014993934,8.879091e-7,0.00034386222,0.000025130728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021118055,0.0029335108,0.00039275904,0.0006682192,0.00018177021,0.000037591915,0.0009404816,0.0056523974,0.82811403,0.007589548,0.0064723855,0.14680614],"study_design_scores_gemma":[0.0054266183,0.0007558882,0.020648528,0.0005669399,0.00030636703,0.0017692385,0.00012686756,0.3781089,0.23670983,0.00026517143,0.35403094,0.0012847161],"about_ca_topic_score_codex":0.0000036398596,"about_ca_topic_score_gemma":4.5268064e-7,"teacher_disagreement_score":0.95010614,"about_ca_system_score_codex":0.00007891862,"about_ca_system_score_gemma":0.000013851662,"threshold_uncertainty_score":0.48808402},"labels":[],"label_agreement":null},{"id":"W1983444688","doi":"10.1117/12.911770","title":"HARDI denoising using nonlocal means on S<sup>2</sup>","year":2012,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Noise reduction; Artificial intelligence; Filter (signal processing); Pattern recognition (psychology); Diffusion MRI; Voxel; Computer vision; Algorithm","score_opus":0.03767626150169793,"score_gpt":0.29729123398891316,"score_spread":0.2596149724872152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983444688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993081,0.00008195138,0.0013707991,0.0025512043,0.00009244609,0.0006742838,0.000030976422,0.00017812618,0.0019392441],"genre_scores_gemma":[0.6818583,0.000059324895,0.31654263,0.00040189794,0.00078055455,0.000105012434,0.00000871516,0.000094122195,0.00014943935],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99788976,1.2701658e-8,0.00057466025,0.00036140232,0.00066373,0.00051043543],"domain_scores_gemma":[0.9983619,0.00011588467,0.00027204846,0.00009316,0.00094283465,0.00021417972],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045288863,0.00032002552,0.0004351696,0.000119728415,0.00012384888,0.000054187643,0.00047878164,0.00016530222,0.000010876684],"category_scores_gemma":[0.00041247744,0.00026740925,0.0006040581,0.000338204,0.00022024731,0.0004613259,0.00014357181,0.00044625258,0.000002744694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012909841,0.00037285042,0.002358514,0.00041363077,0.00029767328,1.6895626e-7,0.00024310114,0.0006482998,0.56567484,0.42632276,0.0027182428,0.00082079007],"study_design_scores_gemma":[0.0029097726,0.0008544756,0.0032353043,0.0017898353,0.000982881,0.0003027698,0.0018287692,0.3737424,0.57378906,0.0024429865,0.037040163,0.0010816127],"about_ca_topic_score_codex":0.000006997184,"about_ca_topic_score_gemma":1.4552213e-8,"teacher_disagreement_score":0.42387977,"about_ca_system_score_codex":0.00024276953,"about_ca_system_score_gemma":0.00003108707,"threshold_uncertainty_score":0.9999778},"labels":[],"label_agreement":null},{"id":"W1983624319","doi":"10.3171/jns.2002.97.2.0388","title":"Functional topography of the low postcentral area","year":2002,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Postcentral gyrus; Tongue; Medicine; Sensory system; Magnetic resonance imaging; Anatomy; Radiology; Neuroscience; Pathology; Psychology","score_opus":0.09191322709090725,"score_gpt":0.2852543003152716,"score_spread":0.19334107322436433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983624319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889358,0.00018682341,0.00124245,0.008539595,0.00041752626,0.00010019061,0.0000051888583,0.000019472083,0.0005529391],"genre_scores_gemma":[0.99771637,0.00019650882,0.00039944827,0.0013235002,0.00013026215,0.0000012589757,3.16135e-7,0.000009810822,0.00022254213],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924713,0.000018806048,0.000327318,0.00006775888,0.00024001006,0.0000989947],"domain_scores_gemma":[0.999231,0.00008979246,0.00029947585,0.00018811668,0.00012870775,0.00006291513],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006866522,0.00006328891,0.00016330194,0.00012408222,0.000040302974,0.000005039672,0.00007615703,0.000021293567,0.000104687715],"category_scores_gemma":[0.000094381074,0.000040202187,0.00030061323,0.00032952146,0.00007474725,0.0000588193,0.000018277024,0.00023033551,0.0000012793713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025305973,0.0012261336,0.4137937,0.00007990048,0.00006338144,0.00017287173,0.000049780145,0.0001453956,0.34132993,0.00058286,0.2333722,0.00893078],"study_design_scores_gemma":[0.0007314096,0.0003198974,0.89797515,0.00027054016,0.00010689164,0.003791184,0.000013038291,0.0002967687,0.046418868,0.0010223828,0.048931733,0.0001221396],"about_ca_topic_score_codex":2.7297656e-7,"about_ca_topic_score_gemma":2.6540423e-8,"teacher_disagreement_score":0.48418143,"about_ca_system_score_codex":0.000009410096,"about_ca_system_score_gemma":0.000018443397,"threshold_uncertainty_score":0.16393976},"labels":[],"label_agreement":null},{"id":"W1983893112","doi":"10.1097/rct.0b013e3181c34626","title":"Magnetic Resonance Imaging Demonstration of a Single Lesion Causing Wallerian Degeneration in Ascending and Descending Tracts in the Spinal Cord","year":2010,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Wallerian degeneration; Medicine; Magnetic resonance imaging; Degeneration (medical); Lesion; Spinal cord; Anatomy; Cord; Pathology; Radiology; Surgery","score_opus":0.059073338291609497,"score_gpt":0.33484728021925364,"score_spread":0.27577394192764415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983893112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9526809,0.00066532294,0.045442175,0.00087123376,0.000102493104,0.00018116545,4.6351883e-7,0.000010675717,0.00004560284],"genre_scores_gemma":[0.9098308,0.000043209115,0.08991901,0.00009869316,0.000095759555,0.0000027080523,0.0000011117031,0.000008242958,4.4401554e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99902916,0.000057519115,0.00047571084,0.00012592535,0.00018691499,0.00012476831],"domain_scores_gemma":[0.999413,0.000049519003,0.00028270727,0.00012480476,0.00008827875,0.000041654534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039318076,0.00009465427,0.00019207619,0.0005037634,0.000056464483,0.000042312415,0.00007321143,0.00003760445,9.584184e-7],"category_scores_gemma":[0.000018800387,0.000075302254,0.00006655012,0.0005039965,0.000068660825,0.0001929067,0.000015752421,0.00038202453,2.7188298e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021596039,0.0002745924,0.14672492,0.000038380822,0.000002536641,0.00011150222,0.00020627744,0.000018449677,0.5228834,0.00033310472,0.000023502638,0.3291674],"study_design_scores_gemma":[0.00094794354,0.0006108095,0.9802554,0.0008436364,0.000031680003,0.0019970317,0.000059930902,0.0045274924,0.009910891,0.00032676203,0.00039587446,0.000092513554],"about_ca_topic_score_codex":0.0000057635966,"about_ca_topic_score_gemma":0.000021008555,"teacher_disagreement_score":0.8335305,"about_ca_system_score_codex":0.000021772194,"about_ca_system_score_gemma":0.000028682765,"threshold_uncertainty_score":0.30707368},"labels":[],"label_agreement":null},{"id":"W1983906797","doi":"10.1016/j.neuroimage.2011.11.094","title":"Diffusion tensor imaging of white matter tract evolution over the lifespan","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1149,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Canadian Language and Literacy Research Network; Alberta Innovates; Alberta Innovates - Health Solutions; Canada Foundation for Innovation","keywords":"Diffusion MRI; White matter; Diffusion; Physics; Geology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.04806129546345709,"score_gpt":0.30829549359883773,"score_spread":0.2602341981353806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983906797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9677789,0.000055571927,0.01456846,0.0030747983,0.00006984732,0.0005472408,0.000014835131,0.00020194045,0.013688403],"genre_scores_gemma":[0.9937635,0.000019035431,0.00350439,0.0019070941,0.000058615085,0.000026432808,0.0000041851968,0.000034976205,0.0006817892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991615,0.000031571348,0.0002200113,0.00024956188,0.0001598687,0.0001775136],"domain_scores_gemma":[0.99913925,0.000033996563,0.000119931065,0.0005907148,0.000060803555,0.000055287568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000734011,0.0001225278,0.00014953394,0.00007178204,0.0001288528,0.000006217926,0.00013940915,0.000023929602,0.00030150457],"category_scores_gemma":[0.00003261189,0.000084056766,0.000093818315,0.00016705101,0.00013431096,0.00010646273,0.00010006264,0.0002288977,0.000039324976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040401483,0.00023015022,0.94483674,0.000025500907,0.0000028909058,0.000021215017,0.00022000386,4.6450498e-7,0.049247295,0.00036728327,0.0042125126,0.0007955617],"study_design_scores_gemma":[0.00027104747,0.00005117778,0.99131083,0.000030015419,0.000046290435,0.0001266274,0.00002347925,0.00046906204,0.0026359195,0.00065207,0.004307602,0.00007585882],"about_ca_topic_score_codex":0.00003183521,"about_ca_topic_score_gemma":4.4652393e-7,"teacher_disagreement_score":0.046611376,"about_ca_system_score_codex":0.000018025175,"about_ca_system_score_gemma":0.000014791807,"threshold_uncertainty_score":0.34277353},"labels":[],"label_agreement":null},{"id":"W1984334616","doi":"10.1117/12.710434","title":"DT-MRI segmentation using graph cuts","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health","keywords":"Diffusion MRI; Segmentation; Voxel; Artificial intelligence; Image segmentation; Pattern recognition (psychology); Cut; Graph; Computer science; Tensor (intrinsic definition); Computer vision; Scale-space segmentation; Mathematics; Magnetic resonance imaging; Theoretical computer science; Geometry","score_opus":0.03143709235625768,"score_gpt":0.3093568050314218,"score_spread":0.27791971267516413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984334616","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916968,0.00006019162,0.0033730261,0.0019499141,0.00010555293,0.0007791724,0.00001962027,0.00016102743,0.0018546995],"genre_scores_gemma":[0.32815155,0.000117051655,0.6706614,0.00031117952,0.00039019366,0.00008976764,0.000014255264,0.00007463374,0.00018994932],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981235,4.981617e-9,0.00061572593,0.00035067555,0.00055880036,0.00035123888],"domain_scores_gemma":[0.9981298,0.000088800836,0.0003436055,0.00006662999,0.0012352125,0.000135949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050316483,0.0002460567,0.00032402118,0.00014045375,0.000094636816,0.000042931817,0.00039587406,0.00013225831,0.0000073060505],"category_scores_gemma":[0.00020563744,0.00021223302,0.00048434435,0.00043493198,0.00019581713,0.000341216,0.000100999394,0.0002960266,8.257746e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011184608,0.00012789681,0.0016296594,0.00026239577,0.00014688818,1.8148792e-7,0.00008149047,0.000044457287,0.79612225,0.1995324,0.0014952658,0.00044524603],"study_design_scores_gemma":[0.0020326395,0.0005278123,0.0054644165,0.0006346952,0.00048247766,0.0001461479,0.0014365538,0.01886796,0.95559955,0.005633458,0.008638447,0.00053584535],"about_ca_topic_score_codex":0.0000065094155,"about_ca_topic_score_gemma":8.657793e-8,"teacher_disagreement_score":0.66728836,"about_ca_system_score_codex":0.00017123447,"about_ca_system_score_gemma":0.000027100274,"threshold_uncertainty_score":0.8654611},"labels":[],"label_agreement":null},{"id":"W1985596631","doi":"10.1371/journal.pone.0074776","title":"White Matter Abnormalities and Structural Hippocampal Disconnections in Amnestic Mild Cognitive Impairment and Alzheimer’s Disease","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; National Institutes of Health; National Natural Science Foundation of China; University of California, San Diego; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Eisai; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Internal medicine; Alzheimer's disease; Medicine; Cardiology; Audiology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.07348012820763344,"score_gpt":0.30650409645271315,"score_spread":0.2330239682450797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985596631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99306995,0.00030339498,0.000085971704,0.005458257,0.000005085065,0.0008352919,0.000036885573,0.00006455017,0.00014062917],"genre_scores_gemma":[0.9961499,0.00007436689,0.002380126,0.0007891614,0.00003338423,0.0003692352,0.000027122796,0.000014934167,0.00016176295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994312,0.000014782745,0.00012630182,0.00019372949,0.0000859701,0.00014801849],"domain_scores_gemma":[0.99962115,0.00005145248,0.000029511255,0.00011596399,0.00003864537,0.0001432762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018852983,0.00010135146,0.00014323874,0.00006427343,0.00006784009,0.000024743067,0.000021863496,0.000017831664,0.00014536615],"category_scores_gemma":[0.0000156328,0.00008759607,0.000014411575,0.000064797474,0.00012320199,0.00013676066,0.000044438482,0.00011470452,0.000013880362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040470026,0.00022415532,0.99867845,0.00007900706,0.000038168553,0.000006153808,0.00024032836,5.0528456e-7,0.00020301293,0.00013377894,0.000121156634,0.00023480863],"study_design_scores_gemma":[0.0004855951,0.00007335373,0.9933214,0.00024488266,0.00023189723,0.000015629501,0.00019799962,0.0007834475,0.00030246674,0.004237233,0.0000032952955,0.00010277532],"about_ca_topic_score_codex":0.000051858424,"about_ca_topic_score_gemma":0.0000053758386,"teacher_disagreement_score":0.0053570303,"about_ca_system_score_codex":0.000013284433,"about_ca_system_score_gemma":0.000011734541,"threshold_uncertainty_score":0.3572064},"labels":[],"label_agreement":null},{"id":"W1986187732","doi":"10.1002/mus.23276","title":"Diffusion tensor MRI to assess skeletal muscle disruption following eccentric exercise","year":2011,"lang":"en","type":"article","venue":"Muscle & Nerve","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hamilton Health Sciences; McMaster University","funders":"","keywords":"Diffusion MRI; Skeletal muscle; Fractional anisotropy; Muscle biopsy; Magnetic resonance imaging; Medicine; Eccentric; Eccentric exercise; Vastus lateralis muscle; Anatomy; Effective diffusion coefficient; Biopsy; Internal medicine; Radiology; Muscle damage; Physics","score_opus":0.0953547086476023,"score_gpt":0.3426087067105918,"score_spread":0.24725399806298948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986187732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9531368,0.000086522705,0.04185984,0.0006608686,0.000161287,0.00097054144,0.000010494147,0.00054181623,0.002571843],"genre_scores_gemma":[0.9698394,0.00006345065,0.028649056,0.00040169168,0.00010995676,0.00018459078,0.000030755753,0.000054450284,0.0006666562],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99866784,0.000022163385,0.0002616372,0.00045496874,0.0002432247,0.00035017816],"domain_scores_gemma":[0.9990062,0.00002623648,0.000073419906,0.0005814347,0.00006574633,0.00024692557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112394424,0.00018899504,0.00025846888,0.00014674092,0.00015823505,0.00002119749,0.00016008264,0.000070386915,0.00011462787],"category_scores_gemma":[0.000047604448,0.00017008813,0.00019776946,0.00043733357,0.000023491442,0.00014839038,0.0001337931,0.00019302628,0.00010520843],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016537476,0.0026826542,0.037255846,0.0002150889,0.000048845643,0.0007670818,0.0020140721,0.000029202767,0.35065085,0.0027368648,0.006846864,0.59658724],"study_design_scores_gemma":[0.0012758074,0.00033818503,0.9327209,0.00033601216,0.00023514788,0.00003523057,0.00021449527,0.0011681465,0.012754008,0.0010592219,0.04936799,0.0004948787],"about_ca_topic_score_codex":0.000083251805,"about_ca_topic_score_gemma":0.0000035029198,"teacher_disagreement_score":0.895465,"about_ca_system_score_codex":0.00007243158,"about_ca_system_score_gemma":0.000019764637,"threshold_uncertainty_score":0.6935992},"labels":[],"label_agreement":null},{"id":"W1986384971","doi":"10.3109/02699052.2013.823659","title":"Moderate–severe traumatic brain injury causes delayed loss of white matter integrity: Evidence of fornix deterioration in the chronic stage of injury","year":2013,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University Health Network; University of Toronto; Toronto Rehabilitation Institute","funders":"Canadian Institutes of Health Research; Toronto Rehabilitation Institute","keywords":"Fornix; Traumatic brain injury; White matter; Fractional anisotropy; Medicine; Diffusion MRI; Magnetic resonance imaging; Internal medicine; Hippocampus; Radiology; Psychiatry","score_opus":0.07144293103194467,"score_gpt":0.3769062008827193,"score_spread":0.30546326985077465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986384971","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9827749,0.00014497676,0.0068623237,0.008452997,0.000022920387,0.001484052,0.00012847777,0.00004382975,0.000085501844],"genre_scores_gemma":[0.99375856,0.00008893609,0.0036907832,0.0017712001,0.000031958643,0.00028086788,0.000016736012,0.000034505963,0.00032645583],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99811643,0.00017430169,0.0008583634,0.0002975941,0.0003115619,0.00024176172],"domain_scores_gemma":[0.9981241,0.00036821896,0.0004578912,0.0007917418,0.0002071625,0.000050886483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005043813,0.0002124245,0.0004818195,0.0002164472,0.000057864036,0.000015205425,0.00031790524,0.00011699774,0.00022860836],"category_scores_gemma":[0.00025303534,0.00016218639,0.00011169749,0.0004699228,0.00026526346,0.0003747591,0.00011331532,0.00039463793,0.000011496043],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014873819,0.00085681624,0.056799382,0.0036047443,0.00009133858,0.000009100753,0.005066193,0.00008396421,0.8701102,0.0016582621,0.036697008,0.023535583],"study_design_scores_gemma":[0.003509417,0.009805307,0.33580855,0.010545384,0.00035078128,0.00018045766,0.0031653568,0.011444174,0.58718735,0.032187216,0.0040856595,0.0017303454],"about_ca_topic_score_codex":0.00021750547,"about_ca_topic_score_gemma":0.000045705325,"teacher_disagreement_score":0.28292286,"about_ca_system_score_codex":0.000084653235,"about_ca_system_score_gemma":0.00016224649,"threshold_uncertainty_score":0.6613769},"labels":[],"label_agreement":null},{"id":"W1986660440","doi":"10.1016/j.mri.2005.12.037","title":"Insights into brain microstructure from the T2 distribution","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":356,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); University of British Columbia","funders":"","keywords":"White matter; Magnetization transfer; Myelin; Fractional anisotropy; Nuclear magnetic resonance; Diffusion MRI; Chemistry; Multiple sclerosis; Pathology; Neuroscience; Central nervous system; Magnetic resonance imaging; Physics; Biology; Medicine; Radiology","score_opus":0.011278692546200186,"score_gpt":0.2781899913940416,"score_spread":0.2669112988478414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986660440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7701856,0.06049762,0.063930914,0.10022795,0.00018479933,0.0013655958,0.00013428064,0.0007403475,0.0027329302],"genre_scores_gemma":[0.98611504,0.000089381974,0.008630373,0.003580709,0.00033970052,0.00006902848,0.00029642254,0.000028578323,0.0008507517],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906594,0.00002569909,0.00021006296,0.00033510092,0.00016476093,0.00019844207],"domain_scores_gemma":[0.9992169,0.00011027627,0.0000604825,0.0005116741,0.000060286366,0.000040369185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037207614,0.00014798643,0.00013971252,0.000018929433,0.0002167313,0.00004972223,0.00013568101,0.00003066309,0.00004099416],"category_scores_gemma":[0.0000572293,0.00010560742,0.00005814292,0.00023105819,0.00019431753,0.00006870389,0.00006825978,0.000233944,0.00001791952],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082010534,0.00012447787,0.098467775,0.000024821138,0.0000035035168,0.00012679794,0.00026467626,0.0000126616505,0.25980964,0.014360786,0.24485268,0.38187018],"study_design_scores_gemma":[0.00037729662,0.000014855726,0.3705381,0.00004822232,0.00001489472,0.000030082969,0.000017645245,0.0009967559,0.004057397,0.026583506,0.59722763,0.000093616276],"about_ca_topic_score_codex":0.0005412135,"about_ca_topic_score_gemma":0.00002097663,"teacher_disagreement_score":0.38177657,"about_ca_system_score_codex":0.000057833447,"about_ca_system_score_gemma":0.000027329039,"threshold_uncertainty_score":0.43065456},"labels":[],"label_agreement":null},{"id":"W1986739789","doi":"10.3389/fnana.2015.00041","title":"Diffusion tensor imaging of the human cerebellar pathways and their interplay with cerebral macrostructure","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"John S. Dunn Foundation","keywords":"Cerebellum; Diffusion MRI; White matter; Neuroscience; Dentate nucleus; Cerebellar hemisphere; Anatomy; Deep cerebellar nuclei; Cerebellar cortex; Cerebrum; Tractography; Magnetic resonance imaging; Psychology; Central nervous system; Medicine; Radiology","score_opus":0.019353587729796753,"score_gpt":0.27526188517925204,"score_spread":0.2559082974494553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986739789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931999,0.00020246541,0.003992714,0.0011745935,0.00009604069,0.00044310963,0.000016274636,0.00006697741,0.0008079485],"genre_scores_gemma":[0.9930791,0.000014725038,0.0062503316,0.00049980014,0.000023254152,0.0000144835785,0.000004669197,0.00002891568,0.00008467827],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992511,0.000031285344,0.00016908847,0.00025956347,0.00012535402,0.00016358805],"domain_scores_gemma":[0.99934906,0.000011185059,0.000094623414,0.00040133446,0.000062242245,0.000081538565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054235938,0.00014494965,0.00021992045,0.000069816364,0.00006553711,0.0000108553095,0.00015320384,0.000031238906,0.0000022505005],"category_scores_gemma":[0.000027916118,0.00008318317,0.000036948528,0.00022193379,0.00023132416,0.00005809654,0.00012970004,0.00028502633,1.4404391e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046815858,0.000041013263,0.9867962,0.000028570224,0.000006048941,0.000015957641,0.00039176317,0.0000040885957,0.0042554955,0.00040094057,0.0043101716,0.003702956],"study_design_scores_gemma":[0.0063412357,0.00039883502,0.86110324,0.0005801976,0.00010683111,0.0009835332,0.0026650776,0.008468384,0.047600713,0.030109197,0.04104466,0.00059807795],"about_ca_topic_score_codex":0.000015056289,"about_ca_topic_score_gemma":0.0000026109697,"teacher_disagreement_score":0.12569292,"about_ca_system_score_codex":0.0000367061,"about_ca_system_score_gemma":0.000033505028,"threshold_uncertainty_score":0.33921114},"labels":[],"label_agreement":null},{"id":"W1987138508","doi":"10.1016/j.jad.2013.05.009","title":"Age of onset and corpus callosal morphology in major depression","year":2013,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Health Research Board","keywords":"Depression (economics); Psychology; Corpus callosum; Morphology (biology); Brain morphometry; Neuroscience; Medicine; Magnetic resonance imaging; Biology; Radiology","score_opus":0.017259921244291678,"score_gpt":0.3222138332380264,"score_spread":0.3049539119937347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987138508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931574,0.00023794631,0.005267839,0.00080356974,0.000019822462,0.00026376775,0.0000019191327,0.0000068396166,0.0002409385],"genre_scores_gemma":[0.99577034,0.00022280059,0.0038311833,0.00012761142,0.000009899307,0.000011485469,0.0000015567974,0.000008514799,0.000016640197],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99955714,0.00003133271,0.00017643618,0.0000794644,0.000073952375,0.00008167714],"domain_scores_gemma":[0.9995552,0.000102341204,0.00015027527,0.00008028729,0.00006356044,0.000048347647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000711785,0.00006076928,0.00019643849,0.00012790656,0.00001437846,0.000002599751,0.000041649186,0.000035343342,0.000014930044],"category_scores_gemma":[0.00011306927,0.000046858648,0.000039824732,0.00010480726,0.00009663177,0.00006634566,0.000022675891,0.00019308817,7.227961e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016341198,0.000337234,0.80891323,0.000036991336,0.000023166665,0.000053428175,0.00015724084,0.000013436359,0.15240791,0.000105292755,0.0009085484,0.036880095],"study_design_scores_gemma":[0.0014853136,0.00044870083,0.9840689,0.00008790573,0.000026196549,0.00027583365,0.00010504131,0.000065593944,0.0061732475,0.0069554793,0.00025729334,0.000050500807],"about_ca_topic_score_codex":0.00013043355,"about_ca_topic_score_gemma":0.000029764778,"teacher_disagreement_score":0.17515565,"about_ca_system_score_codex":0.00001884604,"about_ca_system_score_gemma":0.000019381809,"threshold_uncertainty_score":0.19108401},"labels":[],"label_agreement":null},{"id":"W1987611978","doi":"10.1002/mrm.21837","title":"Temporal stability of adaptive 3D radial MRI using multidimensional golden means","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Cancer Institute; Canadian Breast Cancer Research Alliance; Breast Cancer Alliance","keywords":"Undersampling; Symmetry in biology; Sampling (signal processing); Computer science; Radial line; Temporal resolution; Image resolution; Stability (learning theory); Projection (relational algebra); Artificial intelligence; Algorithm; Mathematics; Computer vision; Physics; Optics; Mathematical analysis","score_opus":0.08249435200894796,"score_gpt":0.3557246402436253,"score_spread":0.2732302882346774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987611978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96820277,0.005864731,0.014834401,0.007132762,0.00008840944,0.0014182178,0.00002009766,0.00012167857,0.0023169129],"genre_scores_gemma":[0.8379596,0.00022645952,0.16094628,0.00060946826,0.00013096097,0.000017668757,0.000010224401,0.000015104603,0.00008426879],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983719,0.000053348147,0.0005404199,0.00038811957,0.0003862264,0.00026000885],"domain_scores_gemma":[0.99905413,0.000119525124,0.00012434203,0.00046687445,0.00012596381,0.00010917223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032151537,0.00017618384,0.0004886649,0.00013395652,0.00003739211,0.0000014298121,0.00011213159,0.00006868012,0.00016776808],"category_scores_gemma":[0.0002006779,0.00014495938,0.000049107657,0.00043278918,0.0003819202,0.000049369388,0.000030080011,0.00028577307,0.0000017024507],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003023051,0.002210862,0.28442454,0.00020834163,0.000015890708,0.0004643373,0.0024728058,0.0003645118,0.27163535,0.00559968,0.0053239996,0.42425662],"study_design_scores_gemma":[0.008785891,0.0056256345,0.83920056,0.0019330706,0.00014892369,0.0002449813,0.00040400322,0.08459481,0.010387988,0.0071993624,0.040949102,0.00052565476],"about_ca_topic_score_codex":0.00026995852,"about_ca_topic_score_gemma":0.000015115604,"teacher_disagreement_score":0.554776,"about_ca_system_score_codex":0.00009348739,"about_ca_system_score_gemma":0.00008524785,"threshold_uncertainty_score":0.5911272},"labels":[],"label_agreement":null},{"id":"W1987990850","doi":"10.1159/000368442","title":"Age-Related Changes in Diffusion Tensor Imaging Metrics of Fornix Subregions in Healthy Humans","year":2015,"lang":"en","type":"article","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Fornix; Fractional anisotropy; Diffusion MRI; Hippocampal formation; White matter; Neuroscience; Hippocampus; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11243628212507754,"score_gpt":0.328259579016825,"score_spread":0.21582329689174745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987990850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99157524,0.00028412856,0.00069909083,0.006216315,0.00019280339,0.00033909484,0.000009556672,0.0000696618,0.0006141125],"genre_scores_gemma":[0.99797845,0.00028868215,0.0002922176,0.0011038891,0.00003587019,0.00003948084,0.000024523388,0.000021019274,0.00021585658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99894243,0.000041030224,0.00034131558,0.00028266257,0.00019390864,0.00019864186],"domain_scores_gemma":[0.999252,0.0002368862,0.00013015929,0.00018857609,0.000071316805,0.00012104577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020840067,0.00012203199,0.0002731407,0.0005570295,0.000042766616,0.00000852973,0.000030574214,0.000041378895,0.000010093505],"category_scores_gemma":[0.00021988864,0.00011257871,0.000042874257,0.00066584756,0.00010009759,0.000088940236,0.00004629436,0.00026241,0.000001853259],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004990227,0.0003602541,0.9923619,0.00006188758,0.000005231988,0.0001434687,0.00009657126,0.000011123803,0.0017344834,0.00089977524,0.0008495354,0.0029767551],"study_design_scores_gemma":[0.0017181803,0.00027850497,0.9869257,0.00011457997,0.000028134633,0.0002871051,0.00014781518,0.0012028841,0.00009025357,0.002336957,0.0067156204,0.00015424474],"about_ca_topic_score_codex":0.00005384953,"about_ca_topic_score_gemma":0.000017522958,"teacher_disagreement_score":0.0064032245,"about_ca_system_score_codex":0.000049696,"about_ca_system_score_gemma":0.00005735198,"threshold_uncertainty_score":0.45908266},"labels":[],"label_agreement":null},{"id":"W1988234649","doi":"10.1016/j.neubiorev.2014.11.006","title":"Drawing connections between white matter and numerical and mathematical cognition: A literature review","year":2014,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Superior longitudinal fasciculus; Diffusion MRI; Corpus callosum; Corona radiata (embryology); Neuroscience; Tractography; Fasciculus; Psychology; Inferior longitudinal fasciculus; Cognition; Cognitive psychology; Cognitive science; Fractional anisotropy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.19444804492370443,"score_gpt":0.4640190083500259,"score_spread":0.2695709634263215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988234649","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000003851885,0.9921023,0.004069667,0.0002610694,0.000049551647,0.0031304674,0.000063484295,0.00012448116,0.00019512014],"genre_scores_gemma":[0.000017052504,0.99048567,0.0048248284,0.0034313577,0.00012869693,0.0007613964,0.0000804322,0.000059283353,0.000211282],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972459,0.00015882583,0.0010119964,0.00097639783,0.00025664747,0.0003502189],"domain_scores_gemma":[0.99839073,0.000017180582,0.0004610561,0.0006997635,0.00006949433,0.00036175037],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00042750133,0.00054961257,0.0025631906,0.00015586449,0.00024028365,0.00014335205,0.00020610937,0.00018645464,0.000074618576],"category_scores_gemma":[0.0002442192,0.00038117132,0.00037898644,0.00084713823,0.00036667398,0.00016628204,0.0002005378,0.0008569861,0.00008586553],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[5.465284e-7,0.000051647054,0.0002781829,0.038723145,2.2731888e-7,0.000019801817,0.0000066474067,6.3578626e-10,0.000007820047,0.00008708467,0.0030018617,0.95782304],"study_design_scores_gemma":[0.0000636556,0.00010516937,0.00018783363,0.10530569,0.0016470427,0.001973701,5.3092293e-7,0.0000019121876,2.2695592e-7,0.000074294556,0.8903532,0.00028671997],"about_ca_topic_score_codex":3.1713364e-7,"about_ca_topic_score_gemma":3.1990016e-8,"teacher_disagreement_score":0.95753634,"about_ca_system_score_codex":0.00002888501,"about_ca_system_score_gemma":0.000049315222,"threshold_uncertainty_score":0.99986404},"labels":[],"label_agreement":null},{"id":"W1988561184","doi":"10.1016/j.clinph.2014.10.168","title":"9. Simultaneous imaging of the brain and spinal cord: Accounting for the brain-spine interaction into functional models of human motor system","year":2015,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Spinal cord; Neuroscience; Neuroimaging; Functional magnetic resonance imaging; Motor system; Neurophysiology; Presentation (obstetrics); Central nervous system; Human brain; Psychology; Sensory system; Nervous system; Medicine; Radiology","score_opus":0.14933393294480043,"score_gpt":0.43761675775798087,"score_spread":0.28828282481318046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988561184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9532286,0.000057547186,0.038673285,0.0067673433,0.00035816027,0.0007754552,0.000009562912,0.00006495596,0.00006510317],"genre_scores_gemma":[0.9965218,0.000008208929,0.0013479282,0.0017229513,0.00026760466,0.000039507016,0.000005592037,0.000019111987,0.00006734897],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891084,0.00008980113,0.0005193395,0.00027207987,0.000095274736,0.00011266622],"domain_scores_gemma":[0.99760157,0.0013954513,0.00033620797,0.00037004935,0.00024778652,0.00004894901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022719201,0.00010034496,0.00029181247,0.00002882469,0.000110498026,0.0000046913988,0.00014461708,0.000042861797,0.0000011114751],"category_scores_gemma":[0.0011391285,0.000061682644,0.00012762214,0.00007354821,0.0004176752,0.000045432636,0.00014777234,0.0002600531,5.7016905e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003931015,0.00045429598,0.0020886108,0.0005349922,0.00007611113,0.000009608466,0.00008155737,0.0023206512,0.9292402,0.019561797,0.0025706117,0.039130535],"study_design_scores_gemma":[0.005488306,0.010864173,0.11075665,0.0006554804,0.0004234985,0.0004165597,0.00064338004,0.8234296,0.004724871,0.026243642,0.015921365,0.0004324905],"about_ca_topic_score_codex":0.000017959537,"about_ca_topic_score_gemma":8.3406036e-7,"teacher_disagreement_score":0.92451537,"about_ca_system_score_codex":0.00001797718,"about_ca_system_score_gemma":0.000037366088,"threshold_uncertainty_score":0.25153452},"labels":[],"label_agreement":null},{"id":"W1989462236","doi":"10.1002/mrm.21527","title":"High‐resolution myelin water measurements in rat spinal cord","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Spinal cord; Myelin; Resolution (logic); Nuclear magnetic resonance; Myelin sheath; Chemistry; Neuroscience; Central nervous system; Biology; Physics; Computer science; Artificial intelligence","score_opus":0.12329312624909883,"score_gpt":0.3603831665679358,"score_spread":0.23709004031883696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989462236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9759827,0.006432961,0.0011394144,0.013683014,0.00017881343,0.0009898067,0.0000014638974,0.00012794632,0.0014638522],"genre_scores_gemma":[0.9855815,0.0016890478,0.009648074,0.0014277047,0.00019685939,0.00018584056,0.000020927211,0.000026856686,0.0012231625],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99821514,0.000046808134,0.0005066944,0.00040395765,0.00043544415,0.00039198602],"domain_scores_gemma":[0.9993382,0.000023648296,0.00004674222,0.00042399773,0.000074287,0.00009308957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003264877,0.00018076546,0.00038524778,0.00023708574,0.00005777691,0.0000023686225,0.0001385878,0.0000695013,0.00022168891],"category_scores_gemma":[0.00013548211,0.00013132837,0.000029500996,0.00039001252,0.0002826595,0.000051856467,0.00004408069,0.00034770466,0.000037005066],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042846883,0.0009964394,0.36192787,0.00022602094,0.0000056265576,0.0014140178,0.00068720605,0.00007198713,0.22363155,0.00075872603,0.023634104,0.38236174],"study_design_scores_gemma":[0.007932217,0.004159252,0.802171,0.0014697859,0.000032534004,0.0005221736,0.00005745186,0.0010288721,0.014342853,0.00265648,0.16525958,0.00036779259],"about_ca_topic_score_codex":0.00029762308,"about_ca_topic_score_gemma":0.000036682628,"teacher_disagreement_score":0.44024312,"about_ca_system_score_codex":0.0001312685,"about_ca_system_score_gemma":0.000033419936,"threshold_uncertainty_score":0.5355416},"labels":[],"label_agreement":null},{"id":"W1989653704","doi":"10.1002/jmri.20102","title":"Diffusion anisotropy in subcortical white matter and cortical gray matter: Changes with aging and the role of CSF‐suppression","year":2004,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":209,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Cerebrospinal fluid; Anisotropy; Psychology; Nuclear magnetic resonance; Medicine; Neuroscience; Magnetic resonance imaging; Physics; Radiology; Optics","score_opus":0.008772163671084085,"score_gpt":0.26853219880950296,"score_spread":0.2597600351384189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989653704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.960019,0.009050357,0.003579626,0.026905185,0.000014742743,0.00025342737,0.0000019487238,0.000009488707,0.00016621653],"genre_scores_gemma":[0.98109764,0.001403474,0.016652135,0.0007626341,0.000038751972,0.000008673878,5.8242114e-7,0.000017524479,0.00001857315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99910116,0.000040137347,0.0003026198,0.00015669382,0.00022257782,0.00017678518],"domain_scores_gemma":[0.99942803,0.00007931776,0.00017307536,0.00016808955,0.00007391859,0.00007756416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018615775,0.000117568794,0.00029711542,0.000102509795,0.00005576829,0.000024992412,0.00007880321,0.000021339825,0.000024375462],"category_scores_gemma":[0.000030172894,0.0000681387,0.00003038272,0.00012053633,0.00037425588,0.00009937306,0.00007011548,0.0003257422,5.7408477e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004966693,0.000081798964,0.9490698,0.000039541977,0.0000020585258,0.00006751772,0.00030514,0.0000045094353,0.031100743,0.00032663986,0.0000800458,0.018425532],"study_design_scores_gemma":[0.0037509936,0.0002311456,0.984091,0.0009350551,0.000065444685,0.0019475518,0.00021439248,0.00077488075,0.002607988,0.0035972935,0.0016922043,0.00009207354],"about_ca_topic_score_codex":0.000015284282,"about_ca_topic_score_gemma":0.000002618684,"teacher_disagreement_score":0.03502117,"about_ca_system_score_codex":0.00002086741,"about_ca_system_score_gemma":0.00002113856,"threshold_uncertainty_score":0.27786157},"labels":[],"label_agreement":null},{"id":"W1992049744","doi":"10.1159/000125684","title":"The Corticospinal Tract in the Kangaroo","year":2008,"lang":"en","type":"article","venue":"Brain Behavior and Evolution","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kensington Health","funders":"","keywords":"Corticospinal tract; Neuroscience; Pyramidal tracts; Psychology; Anatomy; Physical medicine and rehabilitation; Communication; Biology; Medicine; Magnetic resonance imaging; Diffusion MRI","score_opus":0.08109557937582283,"score_gpt":0.361586309226146,"score_spread":0.28049072985032314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992049744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909901,0.0002624865,0.0009838216,0.0070343274,0.000017559698,0.00037037634,0.0000018535138,0.00006299051,0.00027651052],"genre_scores_gemma":[0.99861664,0.000120010685,0.0004414769,0.0003733892,0.000034708115,0.00013575699,0.0000050600984,0.0000050417416,0.0002679466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995832,0.000020955978,0.00009844659,0.00009834363,0.00009299428,0.00010607783],"domain_scores_gemma":[0.9997101,0.0000604098,0.000024215902,0.00016658693,0.000015711137,0.000022992388],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000111040354,0.000048916863,0.0000518505,0.000020337442,0.00025173512,0.00000672393,0.00004927658,0.000022518823,0.0000018196499],"category_scores_gemma":[0.00003841774,0.000027934133,0.00002391467,0.00010708692,0.00011594933,0.000034145654,0.000009587516,0.00013916705,0.0000026120122],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006612991,0.00058823917,0.9330662,0.000008705399,0.0000021623616,0.00011503036,0.00052162696,0.0000014877352,0.011828334,0.009801376,0.0127796335,0.031221112],"study_design_scores_gemma":[0.00019011508,0.00007672347,0.98943406,0.0000069356183,0.000014615842,0.00073054346,0.000077956895,0.00008013026,0.000036905407,0.00042023437,0.008898082,0.00003367401],"about_ca_topic_score_codex":0.00003756045,"about_ca_topic_score_gemma":0.000011610133,"teacher_disagreement_score":0.05636792,"about_ca_system_score_codex":0.000024818402,"about_ca_system_score_gemma":0.000017125869,"threshold_uncertainty_score":0.19361685},"labels":[],"label_agreement":null},{"id":"W1992273569","doi":"10.1002/hbm.20734","title":"Handedness, motor skills and maturation of the corticospinal tract in the adolescent brain","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Centre Hospitalier de l’Université de Montréal; Cegep de Thetford; Université du Québec à Chicoutimi; Cégep de Jonquière; Cegep de Trois-Rivieres; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Heart And Stroke Foundation Of Quebec; Heart and Stroke Foundation of Canada","keywords":"Corticospinal tract; Psychology; Pyramidal tracts; White matter; Internal capsule; Testosterone (patch); Grey matter; Neuroscience; Hum; Magnetic resonance imaging; Laterality; Anatomy; Young adult; Physiology; Developmental psychology; Biology; Internal medicine; Medicine; Diffusion MRI","score_opus":0.051827367798209435,"score_gpt":0.34391305100881786,"score_spread":0.2920856832106084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992273569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9413329,0.00008822366,0.0064831716,0.0507128,0.000016468028,0.0008879723,0.000002467142,0.000049164693,0.00042683852],"genre_scores_gemma":[0.9914641,0.000009518093,0.0006977811,0.007627922,0.000047768317,0.000016544365,0.000004199657,0.0000057871416,0.0001263724],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99939793,0.000040540373,0.0001937972,0.00013727038,0.00012414262,0.000106301035],"domain_scores_gemma":[0.99955046,0.000057837664,0.00009316306,0.00025773814,0.000021443333,0.000019327537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018508983,0.000074759955,0.00011073337,0.000043610387,0.00012409955,0.000015964395,0.00009995088,0.000027067526,0.000004172155],"category_scores_gemma":[0.00008795332,0.000046661797,0.0000379152,0.0001438864,0.000069743466,0.00004332863,0.000016585655,0.00018540082,4.2059105e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028694776,0.0008393851,0.014135593,0.000119470795,0.0000051172965,0.000013230719,0.0016461512,0.000006997863,0.941998,0.023130402,0.004793946,0.013283019],"study_design_scores_gemma":[0.00031535164,0.00007305183,0.9881671,0.0002532858,0.000006801329,0.00004400153,0.00009299924,0.00013316573,0.00042029098,0.0059966957,0.0044468576,0.000050369123],"about_ca_topic_score_codex":0.0000035815683,"about_ca_topic_score_gemma":0.000002350076,"teacher_disagreement_score":0.9740315,"about_ca_system_score_codex":0.00001957706,"about_ca_system_score_gemma":0.000012747535,"threshold_uncertainty_score":0.19028129},"labels":[],"label_agreement":null},{"id":"W1992959576","doi":"10.1016/j.jns.2013.10.026","title":"Thalamic cramplike pain","year":2013,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; London Health Sciences Centre","funders":"","keywords":"Thalamus; Somatosensory system; Medicine; Magnetic resonance imaging; Stroke (engine); Infarction; Diffusion MRI; Neuroscience; Lesion; Psychology; Cardiology; Pathology; Radiology","score_opus":0.0903855334629715,"score_gpt":0.3541012514387433,"score_spread":0.2637157179757718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992959576","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92719024,0.00003975649,0.001962873,0.069441356,0.000079626334,0.00014401968,1.6668858e-7,0.000021913298,0.0011200468],"genre_scores_gemma":[0.98434967,0.00002610534,0.005825889,0.009618442,0.00007169948,0.0000036048978,1.6944137e-8,0.0000021536252,0.000102412],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99931026,0.000077684934,0.00017162235,0.00009031931,0.00022909087,0.00012101307],"domain_scores_gemma":[0.99943435,0.00017975377,0.00015455489,0.00011570917,0.000056551282,0.000059101876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047498182,0.000048750524,0.00010291106,0.000026837446,0.00012768175,0.00002593036,0.00034818496,0.000021904429,0.000085323525],"category_scores_gemma":[0.00043819292,0.000020140129,0.00009383128,0.00022231264,0.0002984849,0.00007976502,0.0000631353,0.00023876209,0.000007871385],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052886688,0.00055500056,0.74730045,0.000015771451,0.000013763208,0.00005604137,0.00004425456,0.00036563503,0.10931011,0.0069159474,0.0467103,0.08865985],"study_design_scores_gemma":[0.00024218607,0.002212284,0.8522325,0.00003102586,0.000025539572,0.001343984,0.000018204239,0.0028310847,0.0017768227,0.10849244,0.030708047,0.00008588134],"about_ca_topic_score_codex":0.0000017137359,"about_ca_topic_score_gemma":7.87175e-8,"teacher_disagreement_score":0.10753329,"about_ca_system_score_codex":0.0000049953915,"about_ca_system_score_gemma":0.000021794813,"threshold_uncertainty_score":0.109978005},"labels":[],"label_agreement":null},{"id":"W1993450982","doi":"10.1186/1532-429x-16-s1-p338","title":"Aberrant myocardial sheetlet mobility in hypertrophic cardiomyopathy detected using in vivo cardiovascular magnetic resonance diffusion tensor imaging","year":2014,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Imperial College London","keywords":"Hypertrophic cardiomyopathy; Medicine; Diffusion MRI; Magnetic resonance imaging; Angiology; Fractional anisotropy; Internal medicine; Cardiology; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.02090329498308082,"score_gpt":0.2593662823866934,"score_spread":0.23846298740361258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993450982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.66629064,0.32645142,0.005577242,0.00016119247,0.00022472852,0.00092523725,0.000010135557,0.00006163282,0.0002977763],"genre_scores_gemma":[0.95933676,0.021673238,0.017925154,0.00020080312,0.0006057637,0.00008981258,0.0000017073137,0.00012634699,0.000040439212],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9944359,0.0007371459,0.0014818857,0.0009335623,0.001596344,0.0008151364],"domain_scores_gemma":[0.9968181,0.000160001,0.00024607487,0.001983791,0.00051291205,0.00027910527],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0026877471,0.0005464889,0.0021808248,0.000659156,0.0001268464,0.000054277523,0.0004843283,0.00019606955,0.000022811213],"category_scores_gemma":[0.0007240824,0.00050590996,0.0024041084,0.001270148,0.00030956767,0.00024267062,0.00018146881,0.0011038803,0.00000388794],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072701863,0.00047726886,0.118618466,0.00026530487,0.00020280285,0.0025276956,0.00019034315,0.0072361813,0.013208602,0.000037044738,0.00013287937,0.8563764],"study_design_scores_gemma":[0.0067892266,0.00053439575,0.5788852,0.0010322427,0.0009473814,0.0038798295,0.000054882308,0.02254097,0.0010763133,0.00044428065,0.38317996,0.0006353066],"about_ca_topic_score_codex":0.0002738512,"about_ca_topic_score_gemma":0.0000061051915,"teacher_disagreement_score":0.8557411,"about_ca_system_score_codex":0.00043062406,"about_ca_system_score_gemma":0.00019671024,"threshold_uncertainty_score":0.9997392},"labels":[],"label_agreement":null},{"id":"W1993512345","doi":"10.1016/j.neuroimage.2011.01.013","title":"Image analysis and statistical inference in neuroimaging with R","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut National de la Santé et de la Recherche Médicale","keywords":"Neuroimaging; Computer science; Context (archaeology); Compiler; Graphics; Diffusion MRI; Data science; Artificial intelligence; Natural language processing; Programming language; Psychology; Computer graphics (images); Neuroscience","score_opus":0.07151616042765449,"score_gpt":0.3564647139602621,"score_spread":0.2849485535326076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993512345","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59266937,0.000022636208,0.39459834,0.0007816261,0.000010847126,0.00047304045,0.00002645241,0.00030987116,0.011107822],"genre_scores_gemma":[0.84119844,0.000039708528,0.15809786,0.000546277,0.000007718082,0.000028335691,0.000009611838,0.000022905037,0.00004914957],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989595,0.000031280182,0.00019335285,0.0004484617,0.00013311897,0.00023429871],"domain_scores_gemma":[0.99925756,0.00011847559,0.000051109648,0.00039904076,0.00004739817,0.00012638753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006670113,0.0001489341,0.00026512632,0.00028945794,0.000043437263,0.00002217142,0.000078531455,0.000021695294,0.00007944284],"category_scores_gemma":[0.00011402139,0.00012604074,0.00003111004,0.0007414685,0.00021805814,0.00014529224,0.000065792534,0.00029147134,0.000007883917],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019116417,0.00032194064,0.96073735,0.000058412843,0.00004119748,0.0014589165,0.00024365148,0.0000021965043,0.025308004,0.0036373446,0.00008476287,0.007915084],"study_design_scores_gemma":[0.0004662297,0.00018338182,0.9924373,0.000016732678,0.00022606397,0.00008636057,0.000016372407,0.003597616,0.0016104555,0.0009304313,0.00028937077,0.00013969501],"about_ca_topic_score_codex":0.00009363165,"about_ca_topic_score_gemma":0.000019976367,"teacher_disagreement_score":0.24852905,"about_ca_system_score_codex":0.000011670402,"about_ca_system_score_gemma":0.00002418039,"threshold_uncertainty_score":0.5139792},"labels":[],"label_agreement":null},{"id":"W1993585744","doi":"10.1002/cne.21048","title":"Efferent association pathways originating in the caudal prefrontal cortex in the macaque monkey","year":2006,"lang":"en","type":"article","venue":"The Journal of Comparative Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":228,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Centre National d’Etudes Spatiales","keywords":"Anatomy; Biology; Neuroscience; Superior longitudinal fasciculus; Gyrus; Superior parietal lobule; Fasciculus; Intraparietal sulcus; Cingulate cortex; Sulcus; Inferior parietal lobule; Limbic lobe; White matter; Posterior parietal cortex; Medicine; Central nervous system; Magnetic resonance imaging; Functional magnetic resonance imaging; Fractional anisotropy","score_opus":0.07048517042257545,"score_gpt":0.3602226539798041,"score_spread":0.2897374835572286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993585744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841845,0.00008507277,0.0012642478,0.012588336,0.000048531816,0.0004068235,0.0000026101643,0.000008865742,0.0014109912],"genre_scores_gemma":[0.99760586,0.000033197222,0.0001398353,0.0020237819,0.00014622882,0.000019607347,0.0000024073993,0.000005972881,0.00002308506],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99839795,0.0007185039,0.00038069338,0.000083597086,0.00025024728,0.0001690273],"domain_scores_gemma":[0.99826753,0.0010626706,0.00041074876,0.0001692033,0.00007615216,0.000013713953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006775698,0.00010035661,0.00024195245,0.00007202979,0.000079679376,0.000011447111,0.00029072407,0.000040328265,0.0000047480944],"category_scores_gemma":[0.000046658348,0.000047012112,0.000053102227,0.00020200376,0.00006708821,0.000052543037,0.000022263352,0.0009440837,0.0000025207305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004185826,0.004140097,0.6522382,0.00005726091,0.00012598882,0.0009250943,0.03449836,0.0077934847,0.18502548,0.07120706,0.037473314,0.0023298548],"study_design_scores_gemma":[0.0011316079,0.0009438356,0.9743974,0.00001984893,0.00005434269,0.0008704951,0.00038879993,0.0021271226,0.00153204,0.013109576,0.0053585977,0.000066326305],"about_ca_topic_score_codex":0.00005922529,"about_ca_topic_score_gemma":0.00012741484,"teacher_disagreement_score":0.32215923,"about_ca_system_score_codex":0.000058605325,"about_ca_system_score_gemma":0.000037379792,"threshold_uncertainty_score":0.41016263},"labels":[],"label_agreement":null},{"id":"W1994129529","doi":"10.1167/9.8.482","title":"Disconnection of cortical face network in prosopagnosia revealed by diffusion tensor imaging","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Inferior longitudinal fasciculus; Disconnection; Fusiform face area; White matter; Diffusion MRI; Psychology; Neuroscience; Temporal lobe; Fractional anisotropy; Tractography; Cortex (anatomy); Superior temporal sulcus; Anatomy; Lateralization of brain function; Face perception; Magnetic resonance imaging; Medicine; Perception; Epilepsy; Radiology","score_opus":0.0184613101705857,"score_gpt":0.35449915315018193,"score_spread":0.3360378429795962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994129529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98327196,0.00010938665,0.012482194,0.003713102,0.000101908394,0.00021400776,0.0000014087597,0.000016307482,0.0000897074],"genre_scores_gemma":[0.98482716,0.0001338369,0.014719894,0.00013090544,0.00012924186,0.0000031868299,0.0000020257996,0.000012211841,0.000041523577],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99914557,0.00002413378,0.0004317599,0.000102806436,0.00018137309,0.000114385984],"domain_scores_gemma":[0.99929595,0.00008292942,0.00029314,0.00014920633,0.00010617668,0.00007258673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026076887,0.00007119302,0.00021773859,0.000074503725,0.00003962568,0.0000068109393,0.00006585697,0.000038052563,0.000014875109],"category_scores_gemma":[0.00018729531,0.00005217649,0.000064212014,0.00017264963,0.00004937123,0.0001072232,0.000028984929,0.00052997185,8.143383e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016003588,0.00031103243,0.21669689,0.000018970437,0.000002384942,0.000017400913,0.000029188906,0.000018319362,0.7698635,0.00019861611,0.0043580206,0.008325674],"study_design_scores_gemma":[0.001527747,0.0005632216,0.9726339,0.0006839183,0.000049065744,0.00053881353,0.00004565783,0.005347121,0.011112011,0.001906596,0.00548741,0.00010455036],"about_ca_topic_score_codex":0.000003617683,"about_ca_topic_score_gemma":0.0000012244019,"teacher_disagreement_score":0.75875145,"about_ca_system_score_codex":0.000021484973,"about_ca_system_score_gemma":0.00002045199,"threshold_uncertainty_score":0.23024935},"labels":[],"label_agreement":null},{"id":"W1994146809","doi":"10.1016/j.neuroimage.2014.12.003","title":"Rotarod training in mice is associated with changes in brain structure observable with multimodal MRI","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Corpus callosum; Diffusion MRI; Fractional anisotropy; Hippocampus; White matter; Neuroscience; Psychology; Motor cortex; Motor coordination; Neuroplasticity; Rotarod performance test; Primary motor cortex; Cortex (anatomy); Motor learning; Medicine; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.04653404142261984,"score_gpt":0.3046889380935284,"score_spread":0.2581548966709086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994146809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983683,0.000010401362,0.0016230998,0.012912009,0.000013768129,0.0006677998,0.000031193464,0.00020623663,0.00085251604],"genre_scores_gemma":[0.97908306,0.000007235928,0.014943807,0.005468838,0.000039381383,0.0000612515,0.00003588817,0.00005921459,0.00030129496],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987434,0.000059215698,0.00016683842,0.00047781933,0.00019704639,0.00035567745],"domain_scores_gemma":[0.9992952,0.0001451668,0.00009580677,0.0003373244,0.000046916968,0.000079638434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001223891,0.00020295134,0.00032504936,0.00013903345,0.0000484617,0.000018008033,0.00012761661,0.00006707932,0.000027119055],"category_scores_gemma":[0.0001412154,0.0001634367,0.000020891017,0.0005243616,0.00007608759,0.00010104008,0.000031851167,0.00049136794,0.0000018398184],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079509063,0.000588103,0.24801148,0.00017804602,0.00004107713,0.00080487604,0.0052944846,0.0009463495,0.72311383,0.00062679336,0.0023338762,0.017265985],"study_design_scores_gemma":[0.010156022,0.0021137008,0.87939966,0.0010239382,0.00008279981,0.0003388056,0.00038691208,0.030556925,0.0521101,0.0014757317,0.021421632,0.00093379454],"about_ca_topic_score_codex":0.000083900915,"about_ca_topic_score_gemma":0.00082689995,"teacher_disagreement_score":0.67100376,"about_ca_system_score_codex":0.00005055837,"about_ca_system_score_gemma":0.00004857633,"threshold_uncertainty_score":0.66647553},"labels":[],"label_agreement":null},{"id":"W1994190062","doi":"10.1016/j.brainres.2009.10.031","title":"The macrostructural and microstructural abnormalities of corpus callosum in children with attention deficit/hyperactivity disorder: A combined morphometric and diffusion tensor MRI study","year":2009,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National High-tech Research and Development Program; National Natural Science Foundation of China","keywords":"Corpus callosum; Diffusion MRI; Abnormality; Fractional anisotropy; Psychology; Magnetic resonance imaging; Pathophysiology; Attention deficit hyperactivity disorder; Neuroscience; Medicine; Pathology; Psychiatry; Radiology","score_opus":0.03657203224725817,"score_gpt":0.3660293346083506,"score_spread":0.3294573023610924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994190062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955458,0.00029784764,0.00003640155,0.0026175322,0.0000044096864,0.0014429543,0.000014617362,0.00002646557,0.000013981746],"genre_scores_gemma":[0.9989782,0.00026177615,0.0005219902,0.000030073568,0.000009675055,0.000035853747,0.000012992976,0.000010852314,0.00013857815],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988403,0.00013141031,0.00018040312,0.00026150089,0.0003226184,0.0002637839],"domain_scores_gemma":[0.99920344,0.00030498474,0.000055438883,0.00025599377,0.00011974486,0.00006040962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003921627,0.000108251385,0.00019270316,0.00023403169,0.00028655896,0.000044496912,0.00009117876,0.00003225722,0.0000016158152],"category_scores_gemma":[0.00017103441,0.000066717635,0.000017851731,0.0006264032,0.00034692098,0.0000756999,0.00009879187,0.00036082562,1.7762564e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032931854,0.00014363979,0.96569836,0.000011318834,0.000008931321,0.000005363828,0.00006050194,6.4752015e-7,0.019925686,0.00020087328,0.00001569164,0.013599674],"study_design_scores_gemma":[0.0020225376,0.0011679018,0.9952335,0.000025840685,0.00000958591,0.00019597972,0.0004552052,0.00020353125,0.00019362723,0.00039782922,0.000024193107,0.000070297116],"about_ca_topic_score_codex":0.0005256925,"about_ca_topic_score_gemma":0.00008428801,"teacher_disagreement_score":0.029535118,"about_ca_system_score_codex":0.000028409557,"about_ca_system_score_gemma":0.000022701637,"threshold_uncertainty_score":0.27206662},"labels":[],"label_agreement":null},{"id":"W1994275622","doi":"10.1016/j.neuroimage.2013.01.069","title":"The acute phase of Wallerian degeneration: Longitudinal diffusion tensor imaging of the fornix following temporal lobe surgery","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; University of Alberta; Alberta Science and Research Authority; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Fornix; Wallerian degeneration; Temporal lobe; Diffusion MRI; Hippocampus; Epilepsy; Fractional anisotropy; Epilepsy surgery; Medicine; Pathology; Neuroscience; Radiology; Psychology; Internal medicine; Magnetic resonance imaging","score_opus":0.06141380470241224,"score_gpt":0.3439879654080169,"score_spread":0.28257416070560465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994275622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860224,0.0001141046,0.0045576114,0.007952577,0.00016277931,0.0007322268,0.000014555887,0.00008156492,0.0003621425],"genre_scores_gemma":[0.9967738,0.00006810129,0.0022360913,0.00036870033,0.0000708614,0.00007027397,0.0000123589125,0.000031236614,0.00036862097],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988003,0.000048713988,0.00041979193,0.00025001942,0.0002665977,0.00021460492],"domain_scores_gemma":[0.9986786,0.00016998641,0.00024618345,0.000709809,0.00013405838,0.00006134509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014441925,0.00014646012,0.00025575512,0.000050039696,0.0002693101,0.000029155917,0.00020344695,0.000024794947,0.000024872437],"category_scores_gemma":[0.00013628027,0.00008579384,0.00027660362,0.00025553888,0.00017094442,0.0001469917,0.00012637916,0.00017945006,0.0000043391015],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006190739,0.00028277337,0.2295483,0.00003867997,0.000030765008,0.00003174295,0.000046347817,0.000003288841,0.74606025,0.0002648175,0.009642035,0.01398908],"study_design_scores_gemma":[0.0028176266,0.0002732836,0.60442495,0.00031022058,0.00045264952,0.00035500608,0.00011320708,0.007836269,0.35664558,0.0018261281,0.024494907,0.00045016405],"about_ca_topic_score_codex":0.000036028297,"about_ca_topic_score_gemma":0.000002285489,"teacher_disagreement_score":0.38941467,"about_ca_system_score_codex":0.000016480162,"about_ca_system_score_gemma":0.000051743642,"threshold_uncertainty_score":0.34985712},"labels":[],"label_agreement":null},{"id":"W1994415119","doi":"10.3174/ajnr.a1154","title":"Attenuation of Lower-Thoracic, Lumbar, and Sacral Spinal Cord Motion: Implications for Imaging Human Spinal Cord Structure and Function","year":2008,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Spinal cord; Medicine; Lumbar; Anatomy; Lumbar Spinal Cord; Cord; Thoracic vertebrae; Lumbar vertebrae; Surgery","score_opus":0.06898080948246568,"score_gpt":0.39469832099787516,"score_spread":0.3257175115154095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994415119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9029104,0.00018910672,0.09289724,0.0036611117,0.00006237286,0.00023105062,0.000016555969,0.000021523152,0.000010637049],"genre_scores_gemma":[0.9819364,0.00025664852,0.017008014,0.0005747696,0.000178476,0.000009703703,0.00000982313,0.000019337465,0.0000068491304],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990987,0.00004916083,0.0004058488,0.00021792816,0.00007750246,0.00015085565],"domain_scores_gemma":[0.99878633,0.000041076542,0.00061434496,0.00018026037,0.00027007828,0.000107919426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000081985374,0.00012550977,0.0003830784,0.00016435918,0.00016448344,0.0000048532356,0.000068937705,0.000027562459,0.0000034007592],"category_scores_gemma":[0.000060565053,0.000116718635,0.000069203,0.00017897545,0.0006512951,0.000105380444,0.000023177572,0.00023086315,1.0885815e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036858805,0.00011099859,0.16349639,0.000055711203,0.00004442314,0.000029983159,0.000027432188,0.0000070128754,0.3396549,0.0019408144,0.0004657997,0.49048066],"study_design_scores_gemma":[0.0005766018,0.01549007,0.9655454,0.00003766638,0.0001393044,0.013537277,0.000034805835,0.00007582882,0.00058675546,0.0024434202,0.0014334088,0.000099466975],"about_ca_topic_score_codex":0.0000051840584,"about_ca_topic_score_gemma":4.991634e-7,"teacher_disagreement_score":0.802049,"about_ca_system_score_codex":0.000023506474,"about_ca_system_score_gemma":0.000040249965,"threshold_uncertainty_score":0.47596478},"labels":[],"label_agreement":null},{"id":"W1994429981","doi":"10.1016/j.neuroimage.2004.12.053","title":"Imaging brain connectivity in children with diverse reading ability","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":284,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; University of Alberta","keywords":"Diffusion MRI; Reading (process); White matter; Psychology; Neuroscience; Tractography; Fractional anisotropy; Neuroimaging; Cognition; Functional magnetic resonance imaging; Magnetoencephalography; Cognitive psychology; Magnetic resonance imaging; Medicine; Electroencephalography","score_opus":0.03108061756068215,"score_gpt":0.3271740039062844,"score_spread":0.2960933863456023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994429981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9819855,0.000014929453,0.0048912773,0.009298592,0.000008472002,0.0006092026,0.000010786344,0.00035037735,0.0028308295],"genre_scores_gemma":[0.9866147,0.000008940943,0.010445083,0.0026886035,0.000069423724,0.000035411955,0.000009723599,0.00002971669,0.00009838207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989625,0.00003792712,0.0001588029,0.00045268642,0.0001385465,0.00024949465],"domain_scores_gemma":[0.9992534,0.0000815726,0.000055258613,0.00048747048,0.000034448625,0.00008784124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014383628,0.00014331944,0.00018765977,0.000098861325,0.00007496218,0.000017645287,0.000095216994,0.000021243894,0.000032629257],"category_scores_gemma":[0.0001285438,0.00012863455,0.000042214833,0.000264241,0.000118024385,0.0002180155,0.0000662104,0.00033104233,0.000018075627],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004772006,0.0002052529,0.94331366,0.000008087244,0.0000039444017,0.0000341094,0.00004603222,0.000026791336,0.032136925,0.00033601525,0.0008533505,0.022988122],"study_design_scores_gemma":[0.000983194,0.00006339147,0.9874545,0.000028642151,0.000018229417,0.00032554026,0.000012827147,0.0011728606,0.005573073,0.00023770281,0.0039852657,0.00014481602],"about_ca_topic_score_codex":0.000054661672,"about_ca_topic_score_gemma":0.000012221295,"teacher_disagreement_score":0.04414081,"about_ca_system_score_codex":0.00007689972,"about_ca_system_score_gemma":0.000027049302,"threshold_uncertainty_score":0.52455646},"labels":[],"label_agreement":null},{"id":"W1994457811","doi":"10.1038/mp.2013.142","title":"The SORL1 gene and convergent neural risk for Alzheimer’s disease across the human lifespan","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Mental Health & Substance Use Services; University of British Columbia; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research","keywords":"Neuropathology; White matter; Alzheimer's disease; Fractional anisotropy; Biology; Psychology; Neuroscience; Disease; Pathology; Medicine","score_opus":0.03430807905002004,"score_gpt":0.3572886433012893,"score_spread":0.32298056425126925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994457811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9279124,0.005567188,0.013255997,0.050766323,0.00020346513,0.002051307,0.00004525349,0.00013945173,0.000058628535],"genre_scores_gemma":[0.9900658,0.000189238,0.0045856605,0.0040860004,0.00015260577,0.00074356043,0.000020623129,0.00003888046,0.00011762475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919516,0.000031566942,0.00016546102,0.00025075738,0.00010983304,0.00024719938],"domain_scores_gemma":[0.9990675,0.00003719225,0.00008410194,0.0006057784,0.000053378935,0.00015204554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009467962,0.00012842062,0.000098981385,0.000010517174,0.0007085028,0.000056830395,0.00015706496,0.000022820339,0.0000072992975],"category_scores_gemma":[0.000025413776,0.00007504292,0.00010953307,0.00006493551,0.0001729606,0.00002880821,0.00007081595,0.00016489932,0.0000072256084],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047057477,0.0011768484,0.56390357,0.00023432243,0.00095485273,0.000033155193,0.0005945242,0.00015797176,0.07979722,0.10264559,0.17041542,0.079615965],"study_design_scores_gemma":[0.003465901,0.0004904757,0.6978704,0.00006235401,0.0013071867,0.00010158538,0.00037734903,0.011106213,0.009617791,0.13653263,0.13831401,0.00075410533],"about_ca_topic_score_codex":0.000025694424,"about_ca_topic_score_gemma":0.000004277892,"teacher_disagreement_score":0.13396683,"about_ca_system_score_codex":0.0000058795367,"about_ca_system_score_gemma":0.000023968352,"threshold_uncertainty_score":0.5449302},"labels":[],"label_agreement":null},{"id":"W1994690989","doi":"10.1016/j.neurobiolaging.2014.04.037","title":"Brain connectivity and novel network measures for Alzheimer's disease classification","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Neuroimaging; Artificial intelligence; Pattern recognition (psychology); Tractography; Diffusion MRI; Classifier (UML); Disease; Cognitive impairment; Computer science; Machine learning; Alzheimer's disease; Cognition; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.10838974823109572,"score_gpt":0.35760022029145566,"score_spread":0.24921047206035996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994690989","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44076532,0.0002050032,0.5325157,0.025072616,0.00008876379,0.0008618295,0.000022592305,0.00021681884,0.00025134123],"genre_scores_gemma":[0.98745424,0.000016694366,0.010583596,0.0017495739,0.000095931835,0.000053735504,0.000018769242,0.00001340069,0.000014061602],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99945426,0.000029193134,0.00012422919,0.00023668425,0.000028713115,0.0001269493],"domain_scores_gemma":[0.9992211,0.00037553758,0.00008606469,0.00020498603,0.00005276572,0.00005958521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016455539,0.00007525037,0.00015633798,0.000031217398,0.00007598419,0.0000029300588,0.000044777877,0.000029656503,8.985917e-7],"category_scores_gemma":[0.0001654824,0.00006946478,0.000037085632,0.000055460987,0.00013389601,0.000025348812,0.000025011766,0.000078959805,2.904676e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004325776,0.00037553257,0.25159037,0.00019339005,0.00009750736,9.800135e-7,0.0000670902,0.0003675192,0.51827025,0.17087331,0.0072942716,0.050437193],"study_design_scores_gemma":[0.0012087792,0.00031664604,0.9372325,0.000077296565,0.00022018417,0.000023268278,0.000006803847,0.009653584,0.010572713,0.0131034795,0.027409432,0.00017529007],"about_ca_topic_score_codex":0.0000020932594,"about_ca_topic_score_gemma":6.6221776e-7,"teacher_disagreement_score":0.6856422,"about_ca_system_score_codex":0.000003860922,"about_ca_system_score_gemma":0.000013725063,"threshold_uncertainty_score":0.28326917},"labels":[],"label_agreement":null},{"id":"W1994726328","doi":"10.1016/j.neurobiolaging.2014.04.036","title":"Unified voxel- and tensor-based morphometry (UVTBM) using registration confidence","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Western University","funders":"National Institute of Mental Health; National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; National Institute on Aging; Michael Smith Health Research BC","keywords":"Voxel; Artificial intelligence; Computer science; Jacobian matrix and determinant; Normalization (sociology); Pattern recognition (psychology); Voxel-based morphometry; Image registration; Transformation (genetics); Computer vision; Mathematics; Medicine; Magnetic resonance imaging; White matter; Radiology","score_opus":0.08856435064750692,"score_gpt":0.3533324412531366,"score_spread":0.26476809060562967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1994726328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9162262,0.00002911765,0.08116156,0.0019067995,0.000030056184,0.00016369903,0.000002737905,0.00010161643,0.00037823519],"genre_scores_gemma":[0.97357094,0.0000177968,0.025222607,0.0010951895,0.000029587254,0.000003779487,0.000008818388,0.000011804046,0.000039498565],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999375,0.000039381557,0.00017967846,0.0002384536,0.000045904097,0.00012160906],"domain_scores_gemma":[0.99936974,0.00013692498,0.00013001262,0.0002594035,0.00006256743,0.000041323063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112983944,0.00008715854,0.00018405478,0.000103213184,0.00006028054,0.0000044686367,0.000055052125,0.000047534202,0.0000053299373],"category_scores_gemma":[0.00009223765,0.000082224695,0.000027544982,0.00013143617,0.0002198635,0.00003257917,0.00002245804,0.00013932424,7.8341566e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003459923,0.00004711892,0.05781948,0.00009845198,0.0000068700724,0.0000044957083,0.000018976418,0.00019701691,0.93490547,0.005525171,0.00012888492,0.0012134545],"study_design_scores_gemma":[0.0023608455,0.0009936244,0.23836239,0.00043755342,0.00021139576,0.00052646577,0.000054983462,0.041880894,0.70382226,0.005217171,0.0056565753,0.00047582077],"about_ca_topic_score_codex":0.00002065042,"about_ca_topic_score_gemma":5.728721e-7,"teacher_disagreement_score":0.2310832,"about_ca_system_score_codex":0.0000083067325,"about_ca_system_score_gemma":0.000022430037,"threshold_uncertainty_score":0.3353026},"labels":[],"label_agreement":null},{"id":"W1995050389","doi":"10.1109/tip.2007.904964","title":"Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institutes of Health","keywords":"Diffusion MRI; Image processing; Tensor (intrinsic definition); Magnetic resonance imaging; Artificial intelligence; Computer vision; Nuclear magnetic resonance; Computer science; Physics; Mathematics; Image (mathematics); Geometry; Radiology; Medicine","score_opus":0.0335951469893662,"score_gpt":0.3319622486764225,"score_spread":0.29836710168705627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995050389","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.093374625,0.00028774343,0.9046136,0.00029807346,0.00003938895,0.0002546187,0.000013581828,0.00024427698,0.00087406195],"genre_scores_gemma":[0.8554457,0.000075072916,0.14338757,0.00014733322,0.000028929286,0.000024024002,0.0000012786753,0.000032892836,0.00085722003],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990095,0.000007766947,0.00030238918,0.00027246668,0.00017588292,0.00023203305],"domain_scores_gemma":[0.9994194,0.00004106851,0.00007936144,0.0002574633,0.00012565234,0.00007709102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102917045,0.00014288686,0.0001874691,0.00018010449,0.00016017382,0.000019731819,0.000081085906,0.000046430883,0.000047930196],"category_scores_gemma":[0.000007551747,0.00012960275,0.00007587777,0.00032310965,0.00014149361,0.00016454534,0.0000018826079,0.00024386882,0.0000064332653],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011978202,0.00019241153,0.0001894709,0.00012008559,0.0000016518578,0.000020986354,0.00007934196,0.000015565956,0.6557858,0.0000026770092,0.00002933654,0.3434429],"study_design_scores_gemma":[0.0006421384,0.00024025673,0.009968698,0.00049629196,0.000054094653,0.00015916796,0.000052118223,0.0021343308,0.98458815,0.00013772526,0.0013538889,0.00017317216],"about_ca_topic_score_codex":0.000008759898,"about_ca_topic_score_gemma":0.0000010596222,"teacher_disagreement_score":0.7620711,"about_ca_system_score_codex":0.000035931225,"about_ca_system_score_gemma":0.000027328737,"threshold_uncertainty_score":0.52850467},"labels":[],"label_agreement":null},{"id":"W1995147563","doi":"10.1016/j.neuroimage.2015.03.036","title":"MRI-detectable changes in mouse brain structure induced by voluntary exercise","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Dentate gyrus; Neuroscience; Hippocampus; Psychology; Cerebellum; Striatum; Brain Structure and Function; Gyrus; Pons; Physical exercise; Medicine; Cognition; Internal medicine","score_opus":0.05864062415783312,"score_gpt":0.3284128462837369,"score_spread":0.2697722221259038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995147563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98520464,0.00015111102,0.0005331164,0.011811653,0.00006775722,0.00084640953,0.00010352196,0.00045949675,0.00082232215],"genre_scores_gemma":[0.9866296,0.00008278664,0.005477655,0.0048821485,0.00009273799,0.00009535351,0.0000837995,0.00008596008,0.0025699588],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99882793,0.000031403088,0.0001775446,0.00043415625,0.00021648589,0.00031246938],"domain_scores_gemma":[0.9990728,0.00003444158,0.00006267589,0.0005672293,0.00005702346,0.00020586117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008361,0.00019098098,0.00026579387,0.00013926219,0.000041271793,0.000021104635,0.00016686194,0.00008177141,0.00004312766],"category_scores_gemma":[0.00010269334,0.0001841391,0.000033241493,0.00034206812,0.00004814571,0.00012299651,0.000095575866,0.0004482087,0.000017198918],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008373824,0.000106410866,0.0024607643,0.000028713608,0.0000022160796,0.0000652328,0.000113859984,0.0000044568724,0.93336284,0.000024664538,0.058719892,0.0050272243],"study_design_scores_gemma":[0.003010289,0.00063610583,0.008285896,0.000107140106,0.000038443173,0.00015020552,0.00011815657,0.0011292391,0.85675573,0.0018506107,0.12738164,0.0005365577],"about_ca_topic_score_codex":0.00010637646,"about_ca_topic_score_gemma":0.00004156468,"teacher_disagreement_score":0.07660711,"about_ca_system_score_codex":0.00006041156,"about_ca_system_score_gemma":0.000046103163,"threshold_uncertainty_score":0.75089747},"labels":[],"label_agreement":null},{"id":"W1995568058","doi":"10.1002/jmri.22535","title":"Quality assessment of high angular resolution diffusion imaging data using bootstrap on Q‐ball reconstruction","year":2011,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Mental Health","keywords":"Computer science; Diffusion imaging; Angular resolution (graph drawing); Spherical harmonics; Voxel; Artificial intelligence; Diffusion MRI; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Medicine","score_opus":0.2011310254859495,"score_gpt":0.4171718896569978,"score_spread":0.2160408641710483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995568058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84632576,0.0036780334,0.14610001,0.0012065469,0.00033767213,0.0004180354,0.00003709226,0.00006360478,0.0018332618],"genre_scores_gemma":[0.75013876,0.0004253505,0.24910603,0.00015276941,0.00012272118,0.0000021814267,0.0000062684785,0.000022952898,0.00002296891],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979389,0.00010624832,0.00091250957,0.00033194193,0.00047866954,0.00023177263],"domain_scores_gemma":[0.99778473,0.000068527486,0.00089415687,0.00083631393,0.00031312287,0.00010313271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000820229,0.00017084942,0.00040418512,0.00024211415,0.000099658435,0.000017876719,0.00032132393,0.00003333396,0.00006502583],"category_scores_gemma":[0.0001455147,0.00015287996,0.000103547325,0.00023044944,0.00018765719,0.00038871187,0.00013121421,0.00041518858,5.89817e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000337273,0.00051880465,0.18043582,0.000098203425,0.000012034021,0.000119448334,0.00012178889,0.00003460525,0.1377712,0.0015557084,0.00046535282,0.67852974],"study_design_scores_gemma":[0.0019771275,0.0003748224,0.9288456,0.0013996375,0.00018098565,0.0021376533,0.00023627108,0.04835702,0.006361465,0.0053698234,0.004487688,0.0002719053],"about_ca_topic_score_codex":0.00015287832,"about_ca_topic_score_gemma":0.000001419551,"teacher_disagreement_score":0.7484098,"about_ca_system_score_codex":0.00013212078,"about_ca_system_score_gemma":0.00013411678,"threshold_uncertainty_score":0.6234264},"labels":[],"label_agreement":null},{"id":"W1995857959","doi":"10.1503/jpn.130280","title":"White matter tractography in early psychosis: clinical and neurocognitive associations","year":2014,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Medical Association; University of Sydney","keywords":"Inferior longitudinal fasciculus; Psychosis; White matter; Neurocognitive; Fractional anisotropy; Psychology; Diffusion MRI; Psychiatry; Superior longitudinal fasciculus; Fornix; Neuropsychology; Medicine; Clinical psychology; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.04788969070745097,"score_gpt":0.3834395871554806,"score_spread":0.3355498964480296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995857959","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980847,0.00006722309,0.00428301,0.013955302,0.00029136415,0.00011598828,0.0000033424758,0.00001172041,0.0004250525],"genre_scores_gemma":[0.9866093,0.0003216109,0.0069168997,0.0060089347,0.00011040772,0.0000031126779,1.3325926e-7,0.0000071938025,0.000022451006],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991101,0.00006463608,0.00038150762,0.00019351635,0.00013253209,0.00011772184],"domain_scores_gemma":[0.99940354,0.00007743965,0.00023795619,0.000100186175,0.000053666445,0.00012723848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035492185,0.00007554125,0.00018522952,0.00015788482,0.000072981864,0.000029552986,0.00007316268,0.000036384015,0.0000019868442],"category_scores_gemma":[0.00009442403,0.000062064115,0.00006505757,0.00028847458,0.00018058422,0.00018345013,0.000017444698,0.0003924577,7.161219e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002565624,0.00016082416,0.99801797,0.000006213842,0.0000011777837,0.0000019891297,0.000024366454,5.3009455e-7,0.00034714848,0.0003273053,0.0003465244,0.0007403009],"study_design_scores_gemma":[0.0005585184,0.00044632162,0.9939696,0.00006058906,0.000025177085,0.00018610213,0.000011770685,0.00006685909,0.000017029186,0.003590532,0.001013518,0.000053955187],"about_ca_topic_score_codex":0.0000010834877,"about_ca_topic_score_gemma":0.0000014787723,"teacher_disagreement_score":0.007946366,"about_ca_system_score_codex":0.000002153447,"about_ca_system_score_gemma":0.000020264431,"threshold_uncertainty_score":0.2530901},"labels":[],"label_agreement":null},{"id":"W1996515464","doi":"10.1118/1.2965947","title":"Poster - Thurs Eve-28: New brain diffusion analysis method: White matter grey matter dissasociation","year":2008,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Diffusion; White matter; Diffusion MRI; Diffusion imaging; Noise (video); Grey matter; Effective diffusion coefficient; White noise; Algorithm; Computer science; Mathematics; Physics; Statistics; Artificial intelligence; Medicine; Magnetic resonance imaging","score_opus":0.04249853042525955,"score_gpt":0.3641579012391296,"score_spread":0.3216593708138701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996515464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08407622,0.000026333073,0.80881244,0.102348804,0.00005060016,0.00043573903,0.00001138318,0.00021398652,0.0040245],"genre_scores_gemma":[0.89285105,0.000062625266,0.015919182,0.07130948,0.0009790452,0.0000949299,0.00039782663,0.000089916204,0.018295916],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983606,0.000057458365,0.000300109,0.00038686304,0.00063005544,0.0002649481],"domain_scores_gemma":[0.9988807,0.0001321166,0.00011903456,0.00048492686,0.00006837398,0.0003148761],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013706317,0.00018526471,0.00039712925,0.000081651255,0.00012993588,0.000013031108,0.00015508976,0.00011446877,0.0016373527],"category_scores_gemma":[0.000065116496,0.00015094902,0.00023976233,0.0006543545,0.000096157426,0.00011192617,0.00009384592,0.00035248316,0.0003289903],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024651281,0.00023319754,0.79076266,0.000021910551,0.000113152135,0.00002689157,0.00035085037,0.0000048200254,0.00065385987,0.00008463382,0.20015995,0.0075633856],"study_design_scores_gemma":[0.00078364747,0.000043381424,0.97595125,0.000058495225,0.00052371743,0.00005720605,0.000008877533,0.0012418913,0.001159968,0.0050998493,0.0148006305,0.00027108472],"about_ca_topic_score_codex":0.000038054928,"about_ca_topic_score_gemma":0.000001973255,"teacher_disagreement_score":0.8087749,"about_ca_system_score_codex":0.00005944833,"about_ca_system_score_gemma":0.000066737644,"threshold_uncertainty_score":0.99927527},"labels":[],"label_agreement":null},{"id":"W1996646045","doi":"10.1016/j.apmr.2008.07.005","title":"Use of Diffusion-Tensor Imaging in Traumatic Spinal Cord Injury to Identify Concomitant Traumatic Brain Injury","year":2008,"lang":"en","type":"article","venue":"Archives of Physical Medicine and Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Toronto Western Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Diffusion MRI; Traumatic brain injury; Concomitant; Spinal cord injury; Medicine; Physical medicine and rehabilitation; Traumatic injury; Spinal cord; Magnetic resonance imaging; Surgery; Radiology; Psychiatry","score_opus":0.0758355367029867,"score_gpt":0.4138940345652408,"score_spread":0.3380584978622541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996646045","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98628896,0.0000426035,0.0034711375,0.009313232,0.000015213712,0.0007438989,0.0000100373845,0.000030432668,0.00008445472],"genre_scores_gemma":[0.9789061,0.000040161274,0.020554982,0.00036327954,0.000042364834,0.000052412146,0.0000072597404,0.000015202978,0.000018259381],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988148,0.00007358923,0.00051182497,0.00025020092,0.00020929905,0.00014029405],"domain_scores_gemma":[0.9972991,0.0021281398,0.00014567198,0.00026460038,0.0000519163,0.000110614106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009887059,0.0001334027,0.00047579475,0.0003447533,0.000042245396,0.0000018671175,0.00006617439,0.000017015249,0.0000032660262],"category_scores_gemma":[0.0013864833,0.00010204038,0.000089841684,0.00028467714,0.0007425277,0.00010222518,0.000039972965,0.00014799942,7.064233e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016362824,0.00095304917,0.035918627,0.000953656,0.000014775477,0.000008360353,0.015624642,0.000007545323,0.7116135,0.0040035946,0.0006002755,0.22866572],"study_design_scores_gemma":[0.0009913825,0.0078038624,0.9648056,0.0029114413,0.00005338176,0.000021049935,0.001622771,0.0032578716,0.001994757,0.016184455,0.00021616385,0.00013725398],"about_ca_topic_score_codex":0.00009041686,"about_ca_topic_score_gemma":0.0000020982827,"teacher_disagreement_score":0.928887,"about_ca_system_score_codex":0.0000131183815,"about_ca_system_score_gemma":0.000022732891,"threshold_uncertainty_score":0.4161086},"labels":[],"label_agreement":null},{"id":"W1996774028","doi":"10.1016/j.neuroimage.2006.07.021","title":"Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":227,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Voxel; Region of interest; Diffusion MRI; Spatial normalization; Fractional anisotropy; Normalization (sociology); Computer science; Pattern recognition (psychology); Data set; Artificial intelligence; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09158179869847428,"score_gpt":0.3366103731330259,"score_spread":0.24502857443455162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996774028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97153115,0.000024287237,0.025340833,0.0014238374,0.000033147448,0.00029040716,0.000007899615,0.00008156663,0.0012668681],"genre_scores_gemma":[0.99165833,0.000016100541,0.008003674,0.00016584322,0.000013070254,0.0000146630355,0.00002746624,0.000020728263,0.000080148304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99895036,0.0000381251,0.00041311135,0.00030831838,0.00013692024,0.00015316039],"domain_scores_gemma":[0.9991318,0.00010970289,0.0001867466,0.00044796523,0.00008727586,0.00003653441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000076298085,0.00012492013,0.00031243736,0.00046812807,0.000021283124,0.0000044479625,0.00010926043,0.000022520844,0.00001173855],"category_scores_gemma":[0.00008653764,0.000118871954,0.00012820998,0.0008897182,0.00009120413,0.000048269834,0.000056928435,0.00014961639,0.0000010777337],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053481816,0.000818621,0.718965,0.00011628387,0.00001882388,0.00022231645,0.000025522404,0.00035378253,0.27292553,0.00061108405,0.00070611155,0.004702096],"study_design_scores_gemma":[0.0016063317,0.000102953076,0.94885206,0.00006877951,0.00018176532,0.0000121544945,0.000010881962,0.014283548,0.03370593,0.00014855652,0.0009138886,0.00011314865],"about_ca_topic_score_codex":0.00011282748,"about_ca_topic_score_gemma":0.000022266117,"teacher_disagreement_score":0.23921959,"about_ca_system_score_codex":0.000030681495,"about_ca_system_score_gemma":0.00002862358,"threshold_uncertainty_score":0.48474577},"labels":[],"label_agreement":null},{"id":"W1996945064","doi":"10.1016/j.mri.2014.07.011","title":"Using Copula distributions to support more accurate imaging-based diagnostic classifiers for neuropsychiatric disorders","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"National Institute of Mental Health; U.S. Public Health Service","keywords":"Generalizability theory; Multivariate statistics; Univariate; Artificial intelligence; Copula (linguistics); Computer science; Neuroimaging; Pattern recognition (psychology); Machine learning; Multivariate analysis; Medical imaging; Statistics; Mathematics; Medicine; Econometrics","score_opus":0.044158445106677616,"score_gpt":0.36313149011155466,"score_spread":0.31897304500487705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996945064","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020478953,0.00095635414,0.94876987,0.026184488,0.00024375335,0.0021715532,0.00017240945,0.0004922925,0.00053034024],"genre_scores_gemma":[0.8847485,0.000043431413,0.10829631,0.0056622163,0.00018577327,0.00061884656,0.00013203583,0.000111718975,0.00020113056],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978867,0.000041045652,0.00043981324,0.00072110404,0.00025331578,0.00065797876],"domain_scores_gemma":[0.9982727,0.00039799314,0.00013081284,0.00075466436,0.0001581205,0.0002856731],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017998135,0.00031559326,0.00032871205,0.00021466834,0.00035562937,0.000079063706,0.00026258948,0.00003212059,0.0000338035],"category_scores_gemma":[0.0009444722,0.00032379074,0.00016753536,0.0006831297,0.00020608652,0.00011720771,0.0000765485,0.00023436951,0.000015218943],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020170113,0.0004574098,0.3524549,0.00022334226,0.0000054831653,0.000034062963,0.000070855356,0.00136827,0.007050386,0.0034209162,0.027558608,0.6071541],"study_design_scores_gemma":[0.0020832473,0.00032936176,0.17879848,0.00019195305,0.00019346176,0.000078523444,0.00004206487,0.31582484,0.0004940166,0.002480494,0.49889266,0.00059090625],"about_ca_topic_score_codex":0.00003867075,"about_ca_topic_score_gemma":0.0000042782262,"teacher_disagreement_score":0.86426955,"about_ca_system_score_codex":0.000104347215,"about_ca_system_score_gemma":0.00012229182,"threshold_uncertainty_score":0.99992144},"labels":[],"label_agreement":null},{"id":"W1997040868","doi":"10.1016/j.neuroimage.2006.03.003","title":"Evidence of altered prefrontal–thalamic circuitry in schizophrenia: An optimized diffusion MRI study","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Medical Research Council; National Health and Medical Research Council","keywords":"Schizophrenia (object-oriented programming); Diffusion MRI; Neuroscience; Psychology; Prefrontal cortex; Cognitive psychology; Medicine; Psychiatry; Magnetic resonance imaging; Radiology; Cognition","score_opus":0.07816703362500697,"score_gpt":0.35940028564214754,"score_spread":0.28123325201714056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997040868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927555,0.00013859494,0.0046175104,0.00028776765,0.00004377826,0.0013519668,0.0000070970336,0.00021364415,0.0005841588],"genre_scores_gemma":[0.98740834,0.000076825105,0.012045036,0.00010668401,0.0000750054,0.00009605066,0.000013323355,0.00004178178,0.00013692617],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984339,0.00009752695,0.00045231904,0.000530571,0.00026040478,0.0002252856],"domain_scores_gemma":[0.9988035,0.00008262971,0.00014804481,0.0008392254,0.000059568632,0.000067013905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014745691,0.00018409212,0.0003682033,0.00017525184,0.000051337687,0.000015010797,0.00021544748,0.000045517332,0.000026679892],"category_scores_gemma":[0.000061476065,0.00017476903,0.00006966531,0.00032336556,0.00008542968,0.00023754883,0.00010210684,0.0003166479,0.000005274964],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006300201,0.0029535703,0.06674807,0.00007986768,0.0000048522734,0.00016093587,0.00011083447,0.0001827973,0.92547584,0.00013125251,0.00020619383,0.003315755],"study_design_scores_gemma":[0.00419517,0.0010678874,0.97309566,0.00027145323,0.00006690612,0.00008596453,0.000060485327,0.00370629,0.016259506,0.0009029358,0.000075472504,0.00021229073],"about_ca_topic_score_codex":0.00018950086,"about_ca_topic_score_gemma":0.000028414892,"teacher_disagreement_score":0.90921634,"about_ca_system_score_codex":0.00004197013,"about_ca_system_score_gemma":0.000039835173,"threshold_uncertainty_score":0.7126874},"labels":[],"label_agreement":null},{"id":"W1997403846","doi":"10.1016/j.neuroimage.2011.08.017","title":"Convergence and divergence of thickness correlations with diffusion connections across the human cerebral cortex","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":352,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Imperial Bank of Commerce","keywords":"Tractography; Connection (principal bundle); Diffusion MRI; Correlation; Diffusion; Cerebral cortex; Mathematics; Convergence (economics); Neuroscience; Physics; Psychology; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.07108956862805242,"score_gpt":0.33242430617664975,"score_spread":0.2613347375485973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997403846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97847074,0.000023277433,0.018404258,0.0004688061,0.000050163628,0.00044239094,0.000030351754,0.0001282992,0.001981686],"genre_scores_gemma":[0.99718726,0.000049131726,0.002011704,0.00025872572,0.00001699776,0.00003951488,0.000006843263,0.000017903094,0.0004119127],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992631,0.000024557754,0.00017532677,0.00025554813,0.0001301072,0.00015133792],"domain_scores_gemma":[0.99921685,0.00006214512,0.000113807364,0.00043036518,0.000111097,0.00006570611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006022544,0.00010933403,0.00014015114,0.000027114202,0.00039777896,0.000008140486,0.00011675155,0.000030477238,0.00008896381],"category_scores_gemma":[0.000034941302,0.00007299957,0.00003403922,0.00022255261,0.00050930865,0.00009267843,0.00010283377,0.00022785919,0.0000046272976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080649275,0.00034073397,0.81561804,0.000054458964,0.000018358229,0.000029372715,0.0019118635,0.000003394379,0.15618771,0.02442735,0.00046708214,0.0008609927],"study_design_scores_gemma":[0.00039417687,0.00023178825,0.99106157,0.000035867444,0.000057764842,0.00021244747,0.00021520453,0.00038628583,0.0054687117,0.0009426152,0.00090022734,0.00009336842],"about_ca_topic_score_codex":0.0001108047,"about_ca_topic_score_gemma":0.000019709116,"teacher_disagreement_score":0.1754435,"about_ca_system_score_codex":0.000006372159,"about_ca_system_score_gemma":0.000017198452,"threshold_uncertainty_score":0.30594343},"labels":[],"label_agreement":null},{"id":"W1997671128","doi":"10.1016/s0924-9338(13)76335-1","title":"1269 – Reduced Fractional Anisotropy In The Uncinate Fasciculus In Patients With Major Depression Carrying The Met-allele Of The Val66met Brain-derived Neurotrophic Factor Genotype","year":2013,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Uncinate fasciculus; Cingulum (brain); Fractional anisotropy; Psychology; Fornix; White matter; rs6265; Neuroscience; Brain-derived neurotrophic factor; Neurotrophic factors; Internal medicine; Hippocampus; Medicine; Magnetic resonance imaging","score_opus":0.02033858178127821,"score_gpt":0.271754700189662,"score_spread":0.2514161184083838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997671128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98956573,0.00008997767,0.00039375547,0.007553276,0.000121039964,0.0012183086,0.000011574861,0.000046149005,0.0010002039],"genre_scores_gemma":[0.9938667,0.0000075691187,0.0029705856,0.002908159,0.00008020146,0.00004839539,0.000012937976,0.000045123143,0.00006034044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985271,0.0003441832,0.00029719717,0.00029999288,0.0003223594,0.00020917963],"domain_scores_gemma":[0.99887866,0.000076513155,0.00020522632,0.0007175903,0.0000824541,0.00003958657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015656187,0.00016752946,0.00015959468,0.000066503126,0.00016611823,0.00002190581,0.00040919142,0.000026122334,0.00003348559],"category_scores_gemma":[0.00006961971,0.0000782078,0.00007148208,0.00041930532,0.00009455404,0.000087915105,0.00010142713,0.0004981585,0.00001238975],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039308032,0.0009247195,0.9281913,0.00007258202,0.00004529322,0.000008705534,0.0012557829,0.00028902132,0.057809275,0.0010925718,0.0073820925,0.0025355953],"study_design_scores_gemma":[0.0011371253,0.00015299305,0.996215,0.00010067243,0.00002193497,0.000009542037,0.00011627083,0.00006922644,0.00039304624,0.00042399915,0.0012661946,0.00009403773],"about_ca_topic_score_codex":0.000059416496,"about_ca_topic_score_gemma":0.00000871041,"teacher_disagreement_score":0.06802368,"about_ca_system_score_codex":0.00002912478,"about_ca_system_score_gemma":0.00006057787,"threshold_uncertainty_score":0.31892213},"labels":[],"label_agreement":null},{"id":"W1997903043","doi":"10.1016/j.neuroimage.2010.07.028","title":"Functional mapping in the corpus callosum: A 4T fMRI study of white matter","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Nova Scotia Health Research Foundation; Scottish Rite Charitable Foundation of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Functional connectivity; Psychology; Neuroscience; Cognitive psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07020572028637957,"score_gpt":0.3284273631834578,"score_spread":0.2582216428970782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997903043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98930234,0.0000048847382,0.0011572815,0.0050700563,0.00007199617,0.000674397,0.0000043740106,0.00006022405,0.0036544646],"genre_scores_gemma":[0.99558866,0.000002737018,0.0015830325,0.0022107698,0.00006594188,0.00009640642,0.000005406299,0.000018930235,0.0004280943],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99915934,0.000035448295,0.0002218944,0.00024087031,0.0002046482,0.00013781044],"domain_scores_gemma":[0.9992417,0.00006884493,0.00007148766,0.00053941074,0.000046818346,0.00003170061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012876853,0.00009854968,0.0001456428,0.00009660381,0.000078781835,0.000009506142,0.00014225495,0.000026960908,0.00012853349],"category_scores_gemma":[0.000033363325,0.00007193928,0.00004174292,0.00026975694,0.00006565955,0.000051403873,0.000073006886,0.00050578086,0.000025677506],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003370085,0.0010204393,0.8483567,0.000024920213,0.000004893925,0.00008814383,0.00072120404,0.000005653187,0.14138444,0.00025463442,0.0073413746,0.0007638555],"study_design_scores_gemma":[0.00065573474,0.00012149713,0.98954445,0.000009510718,0.000016804803,0.00015462564,0.00015300234,0.0000910462,0.00048157276,0.00026802983,0.0084423125,0.00006142645],"about_ca_topic_score_codex":0.000023617671,"about_ca_topic_score_gemma":0.000016805172,"teacher_disagreement_score":0.1411877,"about_ca_system_score_codex":0.000005868875,"about_ca_system_score_gemma":0.000015378455,"threshold_uncertainty_score":0.29335985},"labels":[],"label_agreement":null},{"id":"W1998022841","doi":"10.1016/j.eplepsyres.2012.10.007","title":"Abnormal white matter on diffusion tensor imaging in children with new-onset seizures","year":2012,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Diffusion MRI; Epilepsy; Internal capsule; Psychology; Effective diffusion coefficient; Medicine; Neuroscience; Cardiology; Magnetic resonance imaging; Radiology","score_opus":0.07209311510518958,"score_gpt":0.3991317184371558,"score_spread":0.3270386033319662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998022841","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98650366,0.00008140437,0.00066158036,0.007950369,0.000013373968,0.00074277486,0.000009081687,0.00010307765,0.0039346595],"genre_scores_gemma":[0.9921692,0.0000408757,0.0036116666,0.0010541496,0.0002248314,0.00010083239,0.000033471217,0.000044881217,0.0027201201],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983558,0.00006959098,0.0001611963,0.00029840047,0.00046372748,0.0006512996],"domain_scores_gemma":[0.9990583,0.00007865132,0.000029679253,0.0005174302,0.00006629169,0.00024961517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040966098,0.00013327929,0.00016021202,0.00033440648,0.00013312756,0.000026082722,0.00015064278,0.00003969842,0.00031540048],"category_scores_gemma":[0.00003591563,0.00009851613,0.00003218154,0.0004331192,0.00012642478,0.00013833701,0.00011462741,0.0007160216,0.00032292196],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014418464,0.00021019472,0.9634739,0.0000067011374,0.0000036625756,0.000007640139,0.00008513525,0.000002946649,0.00042887128,0.000095230855,0.03358914,0.0019523896],"study_design_scores_gemma":[0.00066692976,0.00012167761,0.99395406,0.00009347381,0.0000057174184,0.00033977535,0.00004594646,0.000056818102,0.0007020332,0.00012290003,0.0037825494,0.00010809761],"about_ca_topic_score_codex":0.0001316663,"about_ca_topic_score_gemma":0.0000040732393,"teacher_disagreement_score":0.030480178,"about_ca_system_score_codex":0.00007275443,"about_ca_system_score_gemma":0.00004995535,"threshold_uncertainty_score":0.41506162},"labels":[],"label_agreement":null},{"id":"W1998171409","doi":"10.1523/jneurosci.2818-13.2014","title":"Brain White Matter Development Is Associated with a Human-Specific Haplotype Increasing the Synthesis of Long Chain Fatty Acids","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; Centre for Addiction and Mental Health Foundation; Eli Lilly and Company; Canadian Institutes of Health Research; Dana Foundation; Sunovion; Brain and Behavior Research Foundation","keywords":"Haplotype; Polyunsaturated fatty acid; White matter; Biology; Fractional anisotropy; Human brain; Myelin; Genetics; Allele; Genotype; Single-nucleotide polymorphism; Fatty acid; Gene; Endocrinology; Biochemistry; Neuroscience; Central nervous system; Medicine","score_opus":0.054766966338126354,"score_gpt":0.3154604945272163,"score_spread":0.26069352818909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998171409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9534936,0.00001288058,0.0386711,0.007375569,0.000029686475,0.00013030693,0.000001290438,0.00002017012,0.0002654191],"genre_scores_gemma":[0.99142474,0.000011144259,0.0055059483,0.002889048,0.000029724806,0.000004669131,1.7994633e-7,0.0000152500525,0.00011926666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887145,0.0000842249,0.00033838607,0.00015663273,0.00039057492,0.00015872107],"domain_scores_gemma":[0.998841,0.00023441458,0.00046123695,0.00023662459,0.00015599013,0.00007072293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007140393,0.000098014265,0.00021728392,0.000100558806,0.00018059996,0.000027085529,0.0002628407,0.000022162985,0.00001039137],"category_scores_gemma":[0.00033207276,0.000058701957,0.000049188176,0.0003496669,0.00021568261,0.00010376352,0.000048392503,0.00022691436,0.0000015238497],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121111916,0.00029778393,0.5327067,0.000029075989,0.000013028273,0.000057913825,0.00052673934,0.000038371076,0.4588624,0.00014842917,0.001692451,0.005506008],"study_design_scores_gemma":[0.00019511385,0.00017525342,0.9608727,0.00026732078,0.000019174684,0.00043787446,0.000015228953,0.00014040968,0.034586754,0.0000680147,0.0031531935,0.00006893449],"about_ca_topic_score_codex":0.0000010049772,"about_ca_topic_score_gemma":6.745739e-7,"teacher_disagreement_score":0.42816603,"about_ca_system_score_codex":0.00003978645,"about_ca_system_score_gemma":0.000051493767,"threshold_uncertainty_score":0.23937964},"labels":[],"label_agreement":null},{"id":"W1998571354","doi":"10.1016/j.neuroscience.2013.12.019","title":"White matter correlates of cognitive inhibition during development: A diffusion tensor imaging study","year":2013,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute","keywords":"Diffusion MRI; White matter; Psychology; Neuroscience; Cognition; Cognitive psychology; Neuroimaging; Magnetic resonance imaging; Medicine","score_opus":0.029009078991713115,"score_gpt":0.3059221236972878,"score_spread":0.27691304470557465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998571354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99604374,0.0000048248676,0.00232151,0.00035767973,0.000030649364,0.00076870783,0.0000016395618,0.00009378258,0.00037748565],"genre_scores_gemma":[0.9980953,0.000003695157,0.0008567381,0.00052662333,0.0000085094225,0.000115143375,0.0000018540712,0.000012868779,0.00037932053],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914837,0.000013830312,0.00019492407,0.00029929134,0.00018607732,0.00015753375],"domain_scores_gemma":[0.9995688,0.000027099357,0.00008950958,0.00015393627,0.000102708604,0.000057923495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000398199,0.00009102861,0.00011219536,0.000099210534,0.0001408397,0.000019038165,0.00006099735,0.000011273906,0.000048196474],"category_scores_gemma":[0.000062449064,0.00007744113,0.000020591382,0.00027147852,0.0001162504,0.00018390875,0.00009870449,0.000116266856,0.00004020464],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007377915,0.00022989837,0.9787586,0.000011895324,3.7891104e-7,0.000008735438,0.0003054861,0.0000013297949,0.020111328,0.0000025965585,0.00003184965,0.00053055846],"study_design_scores_gemma":[0.00038943285,0.0000570902,0.9943832,0.000116917654,0.0000094673005,0.000064125146,0.00018325742,0.0005565324,0.004110665,0.00004219432,0.00001628427,0.00007081661],"about_ca_topic_score_codex":0.000005234068,"about_ca_topic_score_gemma":2.0522445e-7,"teacher_disagreement_score":0.016000662,"about_ca_system_score_codex":0.000014669212,"about_ca_system_score_gemma":0.000016608275,"threshold_uncertainty_score":0.31579578},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W1998604986","doi":"10.1038/sj.jcbfm.9600135","title":"MR Perfusion and Diffusion in Acute Ischemic Stroke: Human Gray and White Matter have Different Thresholds for Infarction","year":2005,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Perfusion; Infarction; White matter; Nuclear medicine; Medicine; Cerebral blood flow; Magnetic resonance imaging; Perfusion scanning; Effective diffusion coefficient; Voxel; Diffusion MRI; Stroke (engine); Cardiology; Internal medicine; Radiology; Myocardial infarction; Physics","score_opus":0.01812518800212716,"score_gpt":0.3014277858436252,"score_spread":0.283302597841498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998604986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99189824,0.00069263397,0.0018557804,0.0049879435,0.000051331634,0.00038006617,0.000016880113,0.000018865427,0.00009823104],"genre_scores_gemma":[0.9774172,0.000855735,0.02009256,0.0007029795,0.0004068081,0.000021100901,0.000009975435,0.000029097659,0.00046457537],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99891275,0.00002052231,0.0004586494,0.00020773539,0.0001988736,0.0002014403],"domain_scores_gemma":[0.9993435,0.000022640346,0.0002331685,0.00016760941,0.000092810275,0.00014024589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013705887,0.00018520534,0.00043095453,0.00022524172,0.00010175591,0.00003309428,0.000074800504,0.00008693348,0.000040322884],"category_scores_gemma":[0.0000120114155,0.00013601866,0.000108634726,0.00006232797,0.000056235975,0.00023913805,0.00006998955,0.0003850413,5.983445e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022656767,0.00040079112,0.28832012,0.000051100866,0.00006127473,0.000007303637,0.00036121058,0.000006451151,0.6959367,0.00013552642,0.002041782,0.012451204],"study_design_scores_gemma":[0.008724706,0.00041192333,0.89483654,0.00023917842,0.0009582235,0.0012134867,0.00007049112,0.0016790332,0.07023615,0.0010848287,0.020252036,0.00029339863],"about_ca_topic_score_codex":0.0000035127762,"about_ca_topic_score_gemma":0.000008049794,"teacher_disagreement_score":0.62570053,"about_ca_system_score_codex":0.000020103322,"about_ca_system_score_gemma":0.000012311896,"threshold_uncertainty_score":0.554668},"labels":[],"label_agreement":null},{"id":"W1998912534","doi":"10.1523/jneurosci.4563-11.2011","title":"Lifelong Bilingualism Maintains White Matter Integrity in Older Adults","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":407,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; York University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Corpus callosum; Psychology; White matter; Fractional anisotropy; Neuroscience of multilingualism; Diffusion MRI; Functional connectivity; Cognition; Neuroscience; Audiology; Developmental psychology; Cognitive psychology; Medicine; Magnetic resonance imaging","score_opus":0.08210191174784592,"score_gpt":0.3613664424519584,"score_spread":0.2792645307041125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998912534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890351,0.000017263937,0.007279358,0.002636581,0.000151706,0.00015389359,0.0000013144081,0.000021012527,0.00070375105],"genre_scores_gemma":[0.9814323,0.000046999307,0.014154524,0.0041572526,0.00005481389,0.000003098915,1.14297784e-7,0.000010091512,0.00014078601],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990844,0.00002484474,0.00034145,0.00017330398,0.00020356625,0.00017239599],"domain_scores_gemma":[0.99934685,0.000021348707,0.00019627219,0.00021064172,0.00010882997,0.00011606068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002299355,0.000082209415,0.00016195401,0.0001944984,0.000035235855,0.000011239566,0.00021503537,0.000029044879,0.00003160818],"category_scores_gemma":[0.0001622381,0.00006224456,0.000062639854,0.00035193926,0.000118833115,0.0001852553,0.000048136597,0.00050751015,0.0000049564724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018751841,0.00077386945,0.954417,0.000042353422,0.0000013314756,0.000889614,0.0020490948,0.000005010614,0.037404783,0.0004135266,0.0014592045,0.0023566782],"study_design_scores_gemma":[0.00039968325,0.00017711129,0.99353516,0.00018321723,0.0000067343826,0.0012342085,0.00009181098,0.00018402081,0.002716843,0.0006910837,0.0007166714,0.00006345213],"about_ca_topic_score_codex":0.000008575241,"about_ca_topic_score_gemma":0.0000017913736,"teacher_disagreement_score":0.03911815,"about_ca_system_score_codex":0.000031000458,"about_ca_system_score_gemma":0.00006405117,"threshold_uncertainty_score":0.25382593},"labels":[],"label_agreement":null},{"id":"W1999068634","doi":"10.1016/j.neuroimage.2013.05.065","title":"A new method for structural volume analysis of longitudinal brain MRI data and its application in studying the growth trajectories of anatomical brain structures in childhood","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":188,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Institute of Child Health and Human Development; National Institute for Health and Care Research; Canadian Institutes of Health Research; McLean Hospital","keywords":"Brain size; Longitudinal data; Volume (thermodynamics); Brain morphometry; Brain anatomy; Neuroscience; Computer science; Psychology; Medicine; Data mining; Magnetic resonance imaging; Radiology; Physics","score_opus":0.050849500093894204,"score_gpt":0.38315679766958416,"score_spread":0.33230729757568994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999068634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8845317,0.00012357185,0.1077327,0.0058939965,0.000009827915,0.0015454929,0.00012109524,0.000030113823,0.000011553183],"genre_scores_gemma":[0.95238733,0.000017345496,0.047156036,0.00023114808,0.000027112901,0.00007122205,0.000080064936,0.000017903249,0.000011842257],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987304,0.00007479912,0.0004104202,0.00046265658,0.00015393156,0.00016777676],"domain_scores_gemma":[0.9986261,0.00047428207,0.0001771036,0.00059515185,0.00007468786,0.000052632484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002447205,0.00013974271,0.00042462102,0.000281794,0.00003881575,0.0000145950635,0.00031375512,0.00004299088,0.0000098252085],"category_scores_gemma":[0.00045933278,0.00010711454,0.000060295137,0.0009439874,0.00006470209,0.00017149572,0.00015309673,0.00020815281,1.2620113e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020892253,0.00023019582,0.7163805,0.00027643514,0.00028413004,0.0000055076516,0.0018266715,0.00030645175,0.21997635,0.011229255,0.002357453,0.046918128],"study_design_scores_gemma":[0.0006559583,0.00007276329,0.91058505,0.000012083773,0.00018079286,0.000010152834,0.00007483852,0.080405205,0.0029645304,0.0048730774,0.00008430646,0.00008122241],"about_ca_topic_score_codex":0.00054676895,"about_ca_topic_score_gemma":0.00015704219,"teacher_disagreement_score":0.21701182,"about_ca_system_score_codex":0.00001591301,"about_ca_system_score_gemma":0.000039839266,"threshold_uncertainty_score":0.43680042},"labels":[],"label_agreement":null},{"id":"W1999743933","doi":"10.1503/jpn.110057","title":"Magnetic resonance imaging correlates of first-episode psychosis in young adult male patients: combined analysis of grey and white matter","year":2012,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Centre d'Imagerie BioMédicale","keywords":"White matter; Inferior longitudinal fasciculus; Fractional anisotropy; Grey matter; Superior longitudinal fasciculus; Arcuate fasciculus; Corpus callosum; Fasciculus; Psychosis; Psychology; Corticospinal tract; Diffusion MRI; Magnetic resonance imaging; Anatomy; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.012464151285470064,"score_gpt":0.28414364143033266,"score_spread":0.2716794901448626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999743933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99602276,0.0013450339,0.0006291755,0.0015817244,0.00018709486,0.00010856065,0.000009504551,0.0000040419454,0.000112111935],"genre_scores_gemma":[0.9950948,0.00065218715,0.003827003,0.00036833747,0.000012676951,0.0000029280807,4.884075e-7,0.0000066703205,0.00003490633],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990516,0.000023089151,0.00045270709,0.00014719131,0.00017633232,0.0001490968],"domain_scores_gemma":[0.9992414,0.00003538985,0.00036465452,0.00016119322,0.00011953984,0.00007778456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014913102,0.00009031079,0.000278606,0.00030608772,0.000045661003,0.000008122303,0.00009777565,0.000021186068,0.000012863565],"category_scores_gemma":[0.000053802713,0.00007490446,0.00006657212,0.0007138097,0.00017963012,0.00024610735,0.00003209476,0.00015757969,1.4350125e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007495853,0.00030500026,0.99833715,0.000038868435,0.000002880737,8.7691404e-7,0.00007984507,0.000007939413,0.00052072114,0.00008956425,0.0001667535,0.00037541377],"study_design_scores_gemma":[0.00058561476,0.00024786248,0.9969663,0.00016606865,0.00016609904,0.00008464251,0.00003342701,0.0013373757,0.00012721303,0.0001515393,0.00007383239,0.000060042854],"about_ca_topic_score_codex":0.00001762795,"about_ca_topic_score_gemma":0.000016746144,"teacher_disagreement_score":0.0031978274,"about_ca_system_score_codex":0.0000065937174,"about_ca_system_score_gemma":0.000006345478,"threshold_uncertainty_score":0.30545154},"labels":[],"label_agreement":null},{"id":"W2000237353","doi":"10.1016/j.neuroimage.2009.12.102","title":"Confirming white matter fMRI activation in the corpus callosum: Co-localization with DTI tractography","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Tractography; Diffusion MRI; Neuroscience; Functional magnetic resonance imaging; Psychology; Splenium; Magnetic resonance imaging; Brain mapping; Medicine; Radiology","score_opus":0.038046980275423296,"score_gpt":0.3292281667758019,"score_spread":0.2911811865003786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000237353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91472876,0.000003278091,0.061800145,0.009686671,0.000043692235,0.0010349015,0.0000077599,0.0002100433,0.012484747],"genre_scores_gemma":[0.9901285,0.000006634918,0.0032236744,0.006298421,0.000058510843,0.000095387135,0.000045797457,0.00003375895,0.00010927565],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991249,0.00003461611,0.00017811336,0.00028214944,0.00020216958,0.00017808568],"domain_scores_gemma":[0.9992764,0.00007441343,0.00009106644,0.00045658898,0.00005611903,0.000045402743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103183156,0.00013516382,0.00013222909,0.00012856646,0.000100158824,0.00004125452,0.00012620937,0.00005107694,0.0000668654],"category_scores_gemma":[0.00002414442,0.000093851755,0.000039238686,0.00039018982,0.00012050189,0.00015009796,0.0000119185315,0.00054762146,0.00001711468],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013753634,0.00036140086,0.6234804,0.00005137407,0.000006208239,0.000066035675,0.00039176166,0.000024124769,0.3657453,0.0012770754,0.0051533454,0.003305441],"study_design_scores_gemma":[0.0010076275,0.00018252223,0.9105673,0.00005413001,0.000039081333,0.00028370996,0.00006479836,0.0008634744,0.029307105,0.00043996147,0.056979444,0.00021084663],"about_ca_topic_score_codex":0.000021146332,"about_ca_topic_score_gemma":0.000014000181,"teacher_disagreement_score":0.3364382,"about_ca_system_score_codex":0.00000772815,"about_ca_system_score_gemma":0.0000197684,"threshold_uncertainty_score":0.38271636},"labels":[],"label_agreement":null},{"id":"W2000702830","doi":"10.1371/journal.pone.0091400","title":"Differential White Matter Connectivity in Early Mild Cognitive Impairment According to CSF Biomarkers","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Servier; Northern California Institute for Research and Education; University of California, San Diego; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Eisai; Synarc; University of Southern California; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Corpus callosum; Fractional anisotropy; Cerebrospinal fluid; Fasciculus; Dementia; Neuroimaging; Superior longitudinal fasciculus; Internal medicine; Inferior longitudinal fasciculus; Medicine; Psychology; Neuroscience; Pathology; Endocrinology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.06708939899797958,"score_gpt":0.31041641088758803,"score_spread":0.24332701188960845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2000702830","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9811892,0.0000028365203,0.013159362,0.0036175111,0.000011904889,0.00083976064,0.00001307002,0.00012224112,0.0010441378],"genre_scores_gemma":[0.9925872,0.0000036756906,0.005595806,0.0013490942,0.00006375035,0.00022621924,0.000011212753,0.000025384243,0.00013762462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991631,0.000030572137,0.00014980548,0.00028864294,0.00015552153,0.00021236419],"domain_scores_gemma":[0.9995048,0.00008088113,0.000041320553,0.00021055869,0.00005492757,0.00010747917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006398885,0.000114600036,0.00022979178,0.00012642822,0.000043354117,0.000016324584,0.00005994058,0.000034778906,0.00008320095],"category_scores_gemma":[0.000056130248,0.00011049143,0.00003817884,0.00017877678,0.000030505036,0.000058142246,0.000073221345,0.0001474425,0.00009630104],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022124487,0.0012981181,0.94959754,0.00005788151,0.000056230936,0.0000036960728,0.00013907488,2.7135368e-7,0.047665082,0.00004325842,0.00022413261,0.00069346215],"study_design_scores_gemma":[0.0010528811,0.00029273483,0.94041234,0.0005299699,0.0000973654,0.0000025353227,0.000045955425,0.00035214968,0.056710865,0.0003262264,0.000025701362,0.00015128103],"about_ca_topic_score_codex":0.000031372867,"about_ca_topic_score_gemma":0.000004993901,"teacher_disagreement_score":0.0113980565,"about_ca_system_score_codex":0.000051207844,"about_ca_system_score_gemma":0.000008010101,"threshold_uncertainty_score":0.450571},"labels":[],"label_agreement":null},{"id":"W2001443644","doi":"10.1007/s00415-011-6300-x","title":"Executive dysfunction in frontotemporal dementia is related to abnormalities in frontal white matter tracts","year":2011,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institutes of Natural Sciences; National Institute on Aging; National Institutes of Health","keywords":"Cingulum (brain); Fractional anisotropy; Psychology; White matter; Frontotemporal dementia; Audiology; Corpus callosum; Uncinate fasciculus; Executive dysfunction; Neuropsychology; Posterior cingulate; Atrophy; Frontal lobe; Neuroscience; Dementia; Cognition; Cardiology; Medicine; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.05085422040642587,"score_gpt":0.30905841470486195,"score_spread":0.2582041942984361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001443644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9876379,0.000052914613,0.0011626818,0.007949016,0.00012545516,0.00017866299,0.000002185949,0.0000134100555,0.0028778063],"genre_scores_gemma":[0.9901471,0.000022764398,0.003425883,0.0061402093,0.000025580077,0.0000080292775,0.0000011756119,0.000013780579,0.0002154858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999107,0.000051492312,0.00045417316,0.00013390523,0.00008903957,0.00016441324],"domain_scores_gemma":[0.9995642,0.000017751296,0.00018212045,0.00011791823,0.000049050464,0.00006898488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013240472,0.00008759676,0.00023146247,0.0002956269,0.000015634556,0.0000031479044,0.00007462117,0.00007141547,0.00023313705],"category_scores_gemma":[0.000016180242,0.0000788946,0.00005184601,0.00012819434,0.000031520125,0.00014761099,0.000026019205,0.00044213704,0.000018171198],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000883428,0.0001979728,0.9886306,0.000006572144,0.000014557842,0.00048732475,0.0015560696,0.000013102296,0.0013924219,0.00008366006,0.0064555425,0.00027874982],"study_design_scores_gemma":[0.0009932744,0.00087708805,0.99044305,0.0000250516,0.000026284566,0.0010204789,0.00007370738,0.00004542499,0.00063236256,0.0020481923,0.0037548072,0.000060287413],"about_ca_topic_score_codex":0.000049630562,"about_ca_topic_score_gemma":0.000024265872,"teacher_disagreement_score":0.0027007353,"about_ca_system_score_codex":0.000027109692,"about_ca_system_score_gemma":0.000024681738,"threshold_uncertainty_score":0.32172284},"labels":[],"label_agreement":null},{"id":"W2001696757","doi":"10.1016/j.neuroimage.2014.03.037","title":"Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":174,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Concordia University; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Anaesthetics Research Society; W. Garfield Weston Foundation; Ontario Mental Health Foundation; Garfield Weston Foundation; National Alliance for Research on Schizophrenia and Depression; Centre for Addiction and Mental Health Foundation; Marathon","keywords":"Template; Segmentation; Computer science; Artificial intelligence; Pattern recognition (psychology); High resolution; Resolution (logic); Cerebellum; Computer vision; Neuroscience; Biology; Geology; Remote sensing","score_opus":0.056387629759392835,"score_gpt":0.3236879625388993,"score_spread":0.2673003327795065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001696757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9424091,0.000010331648,0.056630503,0.00041752364,0.00001890826,0.00037840154,0.000011614643,0.00007037092,0.000053267624],"genre_scores_gemma":[0.9689925,0.000008431088,0.030732533,0.00014905268,0.00002161946,0.000009847099,0.000027204476,0.000017081386,0.000041777887],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992724,0.000054082095,0.00026564996,0.00017991172,0.00013613113,0.000091817696],"domain_scores_gemma":[0.99930114,0.00010499559,0.00020375043,0.00027499878,0.00008537299,0.000029774304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070296985,0.00008814585,0.00015365097,0.000047524758,0.00013640008,0.000006262619,0.000055661898,0.000031529617,0.000008213803],"category_scores_gemma":[0.0001369089,0.000069171736,0.000033252694,0.00014903858,0.00014096643,0.00006389297,0.00007178957,0.000067879846,5.536734e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010326391,0.00005094112,0.028017474,0.00006589734,0.0000039792285,3.3239365e-7,0.000026827953,0.0003042115,0.97033983,0.0006724823,0.00013430898,0.00037340994],"study_design_scores_gemma":[0.0005826825,0.00010696612,0.23659337,0.00006652907,0.000059023765,0.000022581098,0.0000064714927,0.08187458,0.6797485,0.0007446004,0.00012993116,0.00006481906],"about_ca_topic_score_codex":0.00007199371,"about_ca_topic_score_gemma":0.000007214661,"teacher_disagreement_score":0.29059136,"about_ca_system_score_codex":0.00002520868,"about_ca_system_score_gemma":0.000010344552,"threshold_uncertainty_score":0.28207415},"labels":[],"label_agreement":null},{"id":"W2001738903","doi":"10.1002/mrm.21260","title":"Investigation of human cervical and upper thoracic spinal cord motion: Implications for imaging spinal cord structure and function","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; Magnetic resonance imaging; Anatomy; Medicine; Diffusion MRI; Motion (physics); Cardiac cycle; Cord; Physics; Radiology; Cardiology","score_opus":0.07278503174635857,"score_gpt":0.4016625890271151,"score_spread":0.3288775572807565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001738903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9477044,0.0057402444,0.03569976,0.009699322,0.000042622036,0.0009207211,0.000011062711,0.00005766472,0.00012425387],"genre_scores_gemma":[0.97989506,0.00017523991,0.01886946,0.0007221952,0.00017395518,0.0000598228,0.000035932284,0.000018889508,0.00004945684],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99886775,0.00001668179,0.00042333803,0.00035146603,0.00014270595,0.00019803937],"domain_scores_gemma":[0.999304,0.00006118781,0.00012504608,0.00026188185,0.00013763247,0.000110247944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028620582,0.0001426692,0.0002668339,0.00018368382,0.00010138766,0.000006274524,0.000061170234,0.000058883008,0.00002074276],"category_scores_gemma":[0.00009321915,0.00012515942,0.000020726164,0.00031326705,0.0004590083,0.00006488643,0.000031600208,0.00019810507,1.6394587e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087614695,0.000016650773,0.2970349,0.00018592502,0.0000014010644,0.0000022388263,0.00003644507,1.10289086e-7,0.054310925,0.0045986907,0.00014562893,0.642791],"study_design_scores_gemma":[0.00091393705,0.0030630163,0.9572948,0.00041884268,0.000060186318,0.00012922993,0.00007163634,0.00017528613,0.0015190133,0.032541957,0.0037168749,0.00009517846],"about_ca_topic_score_codex":0.00003865358,"about_ca_topic_score_gemma":0.000014293056,"teacher_disagreement_score":0.66025996,"about_ca_system_score_codex":0.0000332004,"about_ca_system_score_gemma":0.00001794987,"threshold_uncertainty_score":0.5103853},"labels":[],"label_agreement":null},{"id":"W2001805220","doi":"10.1111/j.1528-1167.2007.01006.x","title":"Bilateral White Matter Diffusion Changes Persist after Epilepsy Surgery","year":2007,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Savoy Foundation; National Institutes of Health; University of Alberta; Fondation pour la Recherche Médicale","keywords":"Fornix; White matter; Splenium; Cingulum (brain); Diffusion MRI; Corpus callosum; Fractional anisotropy; Epilepsy; Medicine; Temporal lobe; Psychology; Anatomy; Neuroscience; Hippocampus; Magnetic resonance imaging; Radiology","score_opus":0.040881356948750246,"score_gpt":0.31324765616057015,"score_spread":0.27236629921181993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001805220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96923006,0.00011817541,0.010585968,0.014402258,0.00016572686,0.00038732495,0.000014998639,0.0003308715,0.0047645997],"genre_scores_gemma":[0.98265433,0.00006986161,0.0059455913,0.0061445395,0.0003170886,0.00006971663,0.000042829524,0.00004599828,0.004710064],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989096,0.000013711106,0.00022384491,0.00032977146,0.00016679338,0.00035627844],"domain_scores_gemma":[0.99921566,0.000073522366,0.00006861851,0.00044227153,0.000047760866,0.00015215421],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00018600308,0.00016650531,0.00024419068,0.00017363958,0.0000807391,0.000016651768,0.00006806665,0.00007460324,0.0010213756],"category_scores_gemma":[0.000015282843,0.0001417804,0.00012464946,0.00020644766,0.00007965959,0.00006078994,0.000060644652,0.00019809147,0.00029023562],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013438212,0.000099852434,0.96453536,0.000037632904,0.0000071655113,0.00012030804,0.000113433445,1.5213513e-7,0.0042444207,0.000054147582,0.02632403,0.004329112],"study_design_scores_gemma":[0.00016141686,0.000040666804,0.9076605,0.00008353656,0.000028594302,0.00013019456,0.000022598093,0.000026187021,0.0018241111,0.0001443336,0.08972069,0.0001572073],"about_ca_topic_score_codex":0.000007562023,"about_ca_topic_score_gemma":0.000004964006,"teacher_disagreement_score":0.063396655,"about_ca_system_score_codex":0.000046699402,"about_ca_system_score_gemma":0.000012510636,"threshold_uncertainty_score":0.9998918},"labels":[],"label_agreement":null},{"id":"W2002517543","doi":"10.1016/s8756-3282(00)00237-4","title":"Aging-induced osteopenia in avian cortical bone","year":2000,"lang":"en","type":"article","venue":"Bone","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Aging","keywords":"Rooster; Cortical bone; Osteopenia; Ageing; Anatomy; Osteoporosis; Internal medicine; Medicine; Bone mineral","score_opus":0.05894677940915273,"score_gpt":0.3552478083133669,"score_spread":0.29630102890421417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002517543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9811726,0.000068434965,0.0002716757,0.00573721,0.000012893976,0.0003652912,0.0000026787686,0.00018585876,0.012183321],"genre_scores_gemma":[0.98920596,0.000042012038,0.006066281,0.0012765251,0.000054949178,0.000053776508,0.000009477443,0.00002133407,0.0032696945],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99924695,0.000013601478,0.000205109,0.00022407176,0.00011026513,0.00019998047],"domain_scores_gemma":[0.9995096,0.000023175096,0.000022381628,0.00032926942,0.000016933811,0.00009866665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006908969,0.0000893239,0.00018547515,0.000058562557,0.000040472794,0.000007911528,0.00004853174,0.000041604475,0.0005203697],"category_scores_gemma":[0.00002659444,0.000085054264,0.000037111593,0.00021176644,0.000035113775,0.000043020184,0.000019515188,0.00024949666,0.0002760136],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005462525,0.0015742572,0.032183,0.00009355961,0.000018916167,0.0021990384,0.00041415947,0.000008435242,0.61658573,0.009450572,0.005911223,0.33101487],"study_design_scores_gemma":[0.0054607205,0.0008144561,0.6798719,0.0004282333,0.00010721923,0.0020063713,0.00005914135,0.0013168693,0.04497402,0.005658667,0.25854567,0.0007567016],"about_ca_topic_score_codex":0.00002787584,"about_ca_topic_score_gemma":0.0000074139466,"teacher_disagreement_score":0.6476889,"about_ca_system_score_codex":0.00003301087,"about_ca_system_score_gemma":0.000023220231,"threshold_uncertainty_score":0.5697683},"labels":[],"label_agreement":null},{"id":"W2002529139","doi":"10.1186/1471-2202-12-56","title":"Investigation of fMRI activation in the internal capsule","year":2011,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Internal capsule; Corpus callosum; White matter; Functional magnetic resonance imaging; Neuroscience; Magnetic resonance imaging; Psychology; Brain mapping; Medicine; Anatomy; Radiology","score_opus":0.2515510983112816,"score_gpt":0.3642218239612711,"score_spread":0.11267072564998953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002529139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9563939,0.0000016328926,0.041609727,0.00035395814,0.00002271058,0.0002012465,5.0601454e-7,0.000026215375,0.0013901117],"genre_scores_gemma":[0.9921321,0.0000033410847,0.0068969848,0.00089526677,0.000008602155,0.000021717748,4.9698895e-7,0.0000030650317,0.00003836932],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995775,0.000020963156,0.00010461467,0.00012242659,0.00011038819,0.000064075364],"domain_scores_gemma":[0.9996964,0.000019872958,0.000057945625,0.00018741729,0.000020165318,0.00001824512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011086089,0.00003533442,0.000044893284,0.00004921317,0.000024815525,0.0000035218698,0.00013546272,0.000009579983,0.0000029315459],"category_scores_gemma":[0.00011354641,0.000024743815,0.000014674694,0.00029153467,0.00012924505,0.00009093413,0.000020163343,0.000078848,9.683683e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010448232,0.00004003773,0.095103785,0.00001266005,9.2021295e-8,0.0000012840036,0.0005142721,0.0000029361204,0.8986262,0.0050628595,0.0001011473,0.0005242493],"study_design_scores_gemma":[0.000081643535,0.00006318249,0.63919723,0.000021194379,0.0000018419439,0.000014214385,0.000031459804,0.00059832336,0.3573801,0.0024547167,0.00013359889,0.000022489112],"about_ca_topic_score_codex":0.000034337372,"about_ca_topic_score_gemma":0.0000017170374,"teacher_disagreement_score":0.54409343,"about_ca_system_score_codex":0.000007063492,"about_ca_system_score_gemma":0.000026024887,"threshold_uncertainty_score":0.10090235},"labels":[],"label_agreement":null},{"id":"W2003174799","doi":"10.1002/ar.b.10024","title":"Quantitative 3D analysis of the canal network in cortical bone by micro‐computed tomography","year":2003,"lang":"en","type":"review","venue":"The Anatomical Record Part B The New Anatomist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":202,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Alberta Science and Research Authority; Genome Prairie; Genome Canada; University of Calgary","keywords":"Computer science; Cortical bone; X-ray microtomography; Computed tomography; Cortex (anatomy); Skeletonization; Biomedical engineering; Artificial intelligence; Anatomy; Neuroscience; Medicine; Biology","score_opus":0.06958574776986375,"score_gpt":0.3822171975412235,"score_spread":0.31263144977135976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003174799","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00089575216,0.99003696,0.0027779366,0.0025125048,0.00020382316,0.0027250447,0.00020814323,0.00009189151,0.00054793607],"genre_scores_gemma":[0.0006709348,0.9935148,0.0029439223,0.0015357074,0.00016897934,0.00022512914,0.00018216608,0.00010074625,0.00065762724],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963365,0.0007358346,0.0013090904,0.0006499762,0.00039306504,0.00057553087],"domain_scores_gemma":[0.9958853,0.0014289569,0.0007618879,0.0016127854,0.00009585168,0.00021519835],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000690837,0.00052612496,0.0023099936,0.00025502394,0.00026157414,0.000034499863,0.0009723841,0.00024534937,0.00008880163],"category_scores_gemma":[0.00018297479,0.00026150313,0.0014817496,0.0055348394,0.00071042066,0.00002912419,0.00021940176,0.0016065129,0.000008940142],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046151955,0.0008551244,0.0025206374,0.0012884953,0.0073740017,0.000047639864,0.00012201361,0.00010482293,0.00004731823,0.028644012,0.43185768,0.5266768],"study_design_scores_gemma":[0.00028474123,0.000058793477,0.00016614849,0.0014262332,0.006749631,0.000031019976,0.000011973485,0.0012795584,0.000012702741,0.00090853433,0.98878914,0.00028151364],"about_ca_topic_score_codex":0.00067237363,"about_ca_topic_score_gemma":0.0005776798,"teacher_disagreement_score":0.5569315,"about_ca_system_score_codex":0.00017428465,"about_ca_system_score_gemma":0.00047304702,"threshold_uncertainty_score":0.9999837},"labels":[],"label_agreement":null},{"id":"W2003343999","doi":"10.1016/j.neuroimage.2008.09.054","title":"Postmortem interval alters the water relaxation and diffusion properties of rat nervous tissue — Implications for MRI studies of human autopsy samples","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":129,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Spinal cord; White matter; In vivo; Central nervous system; Diffusion MRI; Autopsy; Fixation (population genetics); Nervous tissue; Chemistry; Perfusion; Pathology; Anatomy; Magnetic resonance imaging; Medicine; Biology; Neuroscience; Internal medicine; Radiology","score_opus":0.17544763227774493,"score_gpt":0.3810734649209096,"score_spread":0.20562583264316467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003343999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866235,0.00019169273,0.0033693644,0.008674515,0.000026586249,0.0009803285,0.000014334548,0.00007645842,0.00004318441],"genre_scores_gemma":[0.99575657,0.00031985063,0.0030877253,0.00025350024,0.000031995154,0.00015034109,0.000018459501,0.000021849222,0.00035969462],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99927634,0.00002544604,0.0002927695,0.00020827126,0.00007982888,0.00011731967],"domain_scores_gemma":[0.99925536,0.000061756,0.00012576913,0.00036296537,0.00016651792,0.000027637698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007207744,0.00010471024,0.00022130976,0.00005025406,0.00022624296,0.000004531751,0.00009174971,0.00002250275,0.0000019051229],"category_scores_gemma":[0.0000751578,0.000054771972,0.000051306128,0.0000656996,0.00036752506,0.00006663564,0.000090519556,0.000083772495,4.1005978e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034646928,0.00007226683,0.0028384284,0.00012899673,0.000010988507,9.789975e-7,0.0008919909,0.0000021698977,0.99289423,0.00050721905,0.0007670883,0.0018509933],"study_design_scores_gemma":[0.0006165819,0.00070342317,0.11218867,0.0001431648,0.000108776956,0.00017363674,0.00020594048,0.00014314431,0.8785024,0.0016381539,0.0054576728,0.0001183845],"about_ca_topic_score_codex":0.00001919131,"about_ca_topic_score_gemma":0.0000024851267,"teacher_disagreement_score":0.11439178,"about_ca_system_score_codex":0.00001137909,"about_ca_system_score_gemma":0.000010397713,"threshold_uncertainty_score":0.22335361},"labels":[],"label_agreement":null},{"id":"W2003370843","doi":"10.1093/brain/awn099","title":"Response monitoring, repetitive behaviour and anterior cingulate abnormalities in autism spectrum disorders (ASD)","year":2008,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":364,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Mental Health; U.S. Department of Energy","keywords":"Anterior cingulate cortex; Autism; Fractional anisotropy; Psychology; Diffusion MRI; Neuroscience; Autism spectrum disorder; Audiology; White matter; Cognition; Developmental psychology; Medicine; Magnetic resonance imaging","score_opus":0.03263168379777566,"score_gpt":0.32732045638226437,"score_spread":0.2946887725844887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003370843","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.978835,0.00014874699,0.00047655738,0.019718533,0.000029890682,0.00026306265,0.000008353034,0.00015257727,0.00036731517],"genre_scores_gemma":[0.9939413,0.0003676568,0.002841987,0.00028059343,0.000026646178,0.000046376063,0.0000025747474,0.000020500054,0.0024723837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930423,0.00004166194,0.00016317668,0.00022648119,0.00008394232,0.00018052588],"domain_scores_gemma":[0.9995946,0.000082362174,0.00004341606,0.0002136392,0.00000524179,0.000060683167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014384919,0.00009990899,0.00014810388,0.000117438656,0.00008506917,0.0000066087673,0.000042899574,0.00003687628,0.000012238584],"category_scores_gemma":[0.0000716448,0.000101134225,0.000030769257,0.00012042407,0.00013034405,0.00006756985,0.00004318552,0.00015463338,0.000002691092],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006974621,0.00017600394,0.9758892,0.000030154408,0.00000899831,0.0005895991,0.0031285994,0.0000026994555,0.013663054,0.0032037506,0.0006265167,0.0019839855],"study_design_scores_gemma":[0.0005659378,0.00014148223,0.9886682,0.00012893863,0.0000057205434,0.00034906156,0.00012628351,0.00002457944,0.003907941,0.002035964,0.0039394973,0.000106391424],"about_ca_topic_score_codex":0.00012566762,"about_ca_topic_score_gemma":0.0000116393285,"teacher_disagreement_score":0.019437939,"about_ca_system_score_codex":0.00003680167,"about_ca_system_score_gemma":0.000028668885,"threshold_uncertainty_score":0.41241342},"labels":[],"label_agreement":null},{"id":"W2003728643","doi":"10.1159/000323022","title":"Somatotopic Arrangement of the Corticospinal Tract at the Medullary Pyramid in the Human Brain","year":2011,"lang":"en","type":"article","venue":"European Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corticospinal tract; Diffusion MRI; Tractography; Human brain; Pyramidal tracts; Anatomy; Neuroscience; Medullary cavity; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.10066587102591618,"score_gpt":0.32900847486954216,"score_spread":0.22834260384362598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2003728643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95837164,0.000056980185,0.00009972305,0.022556828,0.00005216112,0.00056099717,0.0000024458443,0.00004338167,0.018255867],"genre_scores_gemma":[0.98438966,0.0000175292,0.00006523691,0.015136138,0.000048454192,0.00002670445,0.000002366259,0.000021673557,0.0002922593],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988958,0.00037168272,0.00024722837,0.00019477283,0.00012391538,0.00016659139],"domain_scores_gemma":[0.9990007,0.00008276795,0.0001260349,0.0007517375,0.000016609367,0.00002211047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029493828,0.00009732992,0.00012013763,0.000027497208,0.00012683879,0.0000033504718,0.0004221191,0.000018287279,0.000067443725],"category_scores_gemma":[0.000052377556,0.000047473666,0.0000721303,0.0001311015,0.00032657295,0.000015212541,0.0001631198,0.00033545872,0.000016585585],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030277076,0.0025199524,0.6575928,0.00012225159,0.000058603764,0.0012520098,0.006987501,0.000026379954,0.24530745,0.04429097,0.030223034,0.011316314],"study_design_scores_gemma":[0.00030380968,0.00027910256,0.9502689,0.000008653706,0.000023210105,0.0002988384,0.000020419,0.000013938666,0.0013210651,0.000796307,0.04662291,0.000042834003],"about_ca_topic_score_codex":0.000014757906,"about_ca_topic_score_gemma":0.0000099668805,"teacher_disagreement_score":0.29267615,"about_ca_system_score_codex":0.0000068924123,"about_ca_system_score_gemma":0.000009428976,"threshold_uncertainty_score":0.19359198},"labels":[],"label_agreement":null},{"id":"W2004087319","doi":"10.1021/bi100308d","title":"Interaction of Myelin Basic Protein with Actin in the Presence of Dodecylphosphocholine Micelles","year":2010,"lang":"en","type":"article","venue":"Biochemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Chemistry; Myelin; Actin; Myelin basic protein; Microfilament; Biophysics; Actin-binding protein; Citrullination; Cell biology; Biochemistry; Actin cytoskeleton; Cytoskeleton; Biology; Cell; Central nervous system","score_opus":0.026632719441036557,"score_gpt":0.3300988287992694,"score_spread":0.3034661093582328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004087319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9977393,0.000024472873,0.0003682856,0.00091165217,0.0000062143154,0.0002599843,0.0000049861437,0.000015983973,0.0006690925],"genre_scores_gemma":[0.99092877,0.000008406872,0.00878431,0.00003422034,0.000027140815,0.000055738,0.000007568881,0.000006308555,0.00014754162],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99958616,0.0000045555857,0.00013666488,0.00011783072,0.00009538788,0.000059375132],"domain_scores_gemma":[0.99945295,0.000040856477,0.00010406618,0.0003336255,0.00005178296,0.000016691858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007399606,0.000056172168,0.00008675773,0.000016749374,0.000010463097,0.0000021113492,0.00010621875,0.00003568034,0.000015162648],"category_scores_gemma":[0.00008041403,0.00003680293,0.000021122345,0.00012682875,0.00008812713,0.000019187542,0.000016707747,0.00023325642,4.3438914e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009848898,0.00012942705,0.0012145822,0.00007277267,0.0000019864551,0.0000015947749,0.000045561155,0.0000010099653,0.9972254,0.000048224072,0.00011009092,0.0010508697],"study_design_scores_gemma":[0.00022465196,0.000037889607,0.0014047016,0.00013027954,0.000007778821,0.000030909654,0.00012558763,0.00008729656,0.9969134,0.00007174966,0.0009317605,0.000034043325],"about_ca_topic_score_codex":0.000031116433,"about_ca_topic_score_gemma":0.0000040813884,"teacher_disagreement_score":0.008416024,"about_ca_system_score_codex":0.0000055257246,"about_ca_system_score_gemma":0.000034100172,"threshold_uncertainty_score":0.15007798},"labels":[],"label_agreement":null},{"id":"W2004299377","doi":"10.1007/s00247-009-1255-0","title":"Abnormal fetal cerebral laminar organization in cobblestone complex as seen on post-mortem MRI and DTI","year":2009,"lang":"en","type":"article","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Medicine; Cerebrum; Neuroradiology; Autopsy; Tractography; Fractional anisotropy; Pathology; Laminar flow; Fetus; Anatomy; Magnetic resonance imaging; Radiology; Neurology; Central nervous system; Pregnancy; Internal medicine; Biology","score_opus":0.028408956034250157,"score_gpt":0.31547368378788654,"score_spread":0.2870647277536364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004299377","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895764,0.00019678997,0.001741422,0.006895363,0.000031819745,0.00038770415,0.000009630726,0.00017221263,0.0009886513],"genre_scores_gemma":[0.9913754,0.0005436606,0.004608931,0.0028789907,0.0002898915,0.000009287788,0.00014393499,0.000017484621,0.0001324363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991584,0.000034505374,0.00021842422,0.0002930729,0.00007599678,0.00021960384],"domain_scores_gemma":[0.99950945,0.000062722684,0.000074822645,0.00019880342,0.00006873017,0.000085488406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007427059,0.0001269476,0.00024377424,0.00017857544,0.000063324485,0.0000042218844,0.00007189381,0.00009028628,0.00005302165],"category_scores_gemma":[0.000100139834,0.000119914956,0.000018523322,0.00043934243,0.00005271981,0.000050882154,0.00002342488,0.00021108822,0.000027723894],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032325368,0.0006808469,0.9466753,0.00006803701,0.000014738863,0.00035241287,0.00033932945,0.00013318336,0.010073143,0.016263463,0.013886617,0.011189702],"study_design_scores_gemma":[0.0010698594,0.0010072048,0.99339986,0.000004610038,0.000043672684,0.0012577312,0.0000200665,0.00042522428,0.00023948777,0.00093595317,0.0014537157,0.000142611],"about_ca_topic_score_codex":0.000017918232,"about_ca_topic_score_gemma":0.0000013945664,"teacher_disagreement_score":0.046724588,"about_ca_system_score_codex":0.000045953173,"about_ca_system_score_gemma":0.000047296187,"threshold_uncertainty_score":0.48899898},"labels":[],"label_agreement":null},{"id":"W2004302472","doi":"10.1017/s0317167100015560","title":"Tractography in the Study of the Human Brain: A Neurosurgical Perspective","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; White matter; Arcuate fasciculus; Superior longitudinal fasciculus; Diffusion MRI; Neuroscience; Inferior longitudinal fasciculus; Corpus callosum; Uncinate fasciculus; Corticospinal tract; Psychology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09812529099306126,"score_gpt":0.3664611723238286,"score_spread":0.2683358813307673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004302472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9809194,0.0003414938,0.000008929914,0.015969442,0.00021029529,0.00042252472,0.0000029982784,0.000009393915,0.002115519],"genre_scores_gemma":[0.99462545,0.000036133606,0.00026989277,0.0048862216,0.00016186487,0.0000068757195,4.52638e-8,0.0000075495986,0.000005962016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962002,0.0011463414,0.00071810343,0.000307367,0.0007672513,0.00086073234],"domain_scores_gemma":[0.99751884,0.0006468777,0.000613652,0.00024490568,0.00027904008,0.0006966942],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0037825126,0.00021298404,0.00038440857,0.000621154,0.0017490507,0.00015528823,0.0018253142,0.00008293148,0.00003460534],"category_scores_gemma":[0.001487197,0.0001022286,0.00025586953,0.0023070734,0.004833654,0.00047975828,0.000060776623,0.0015644976,3.152519e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025406809,0.00026003615,0.99355507,0.000002191266,0.0000050411204,0.0005740851,0.0016923766,0.00015716464,0.00010609706,0.0030296533,0.00029265514,0.0003002387],"study_design_scores_gemma":[0.00032930606,0.027411403,0.94523114,0.000019541203,0.000038034672,0.015934283,0.0022978014,0.000041898693,0.000035513385,0.007178774,0.0013736637,0.00010866198],"about_ca_topic_score_codex":0.0011524991,"about_ca_topic_score_gemma":0.011808053,"teacher_disagreement_score":0.048323937,"about_ca_system_score_codex":0.00010418317,"about_ca_system_score_gemma":0.00073022954,"threshold_uncertainty_score":0.9995505},"labels":[],"label_agreement":null},{"id":"W2004421347","doi":"10.1016/j.neurobiolaging.2006.09.013","title":"Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls","year":2006,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":281,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute of Mental Health","keywords":"Parahippocampal gyrus; Overtraining; Linear discriminant analysis; Gyrus; Medicine; Temporal lobe; Neuroscience; Pathology; Pattern recognition (psychology); Psychology; Artificial intelligence; Computer science; Epilepsy","score_opus":0.08276855514881212,"score_gpt":0.34811652876147176,"score_spread":0.2653479736126596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004421347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959345,0.000090017624,0.0010733912,0.0011165993,0.00014755977,0.00048672452,0.00022027252,0.0005621743,0.0003687506],"genre_scores_gemma":[0.9943743,0.000010761522,0.003920983,0.00093920174,0.00008170492,0.000036279213,0.0005927227,0.000031351166,0.000012716693],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984655,0.00011689225,0.0004838942,0.00045389592,0.00015456034,0.0003252733],"domain_scores_gemma":[0.99890536,0.00019144571,0.00024949628,0.00037914125,0.00019237683,0.000082197475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007045415,0.0002170191,0.000438814,0.00006961176,0.000113111106,0.000012064384,0.0001762585,0.00011552267,0.00003482078],"category_scores_gemma":[0.000036451605,0.00019793707,0.000084049294,0.0001329334,0.00018377467,0.000070131005,0.0000668896,0.00032434647,0.000013949644],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002711058,0.0005631034,0.6101194,0.000012166748,0.00021890971,0.000024300542,0.000071876806,0.00024152272,0.38412637,0.00010113888,0.0031347044,0.0011153969],"study_design_scores_gemma":[0.0029017837,0.00036022923,0.85596436,0.00007720698,0.00038174796,0.000009223785,0.000008410281,0.0015659162,0.13707139,0.00060794054,0.00080343167,0.00024838743],"about_ca_topic_score_codex":0.000830202,"about_ca_topic_score_gemma":0.000034960423,"teacher_disagreement_score":0.24705498,"about_ca_system_score_codex":0.000022592145,"about_ca_system_score_gemma":0.000049551665,"threshold_uncertainty_score":0.80716395},"labels":[],"label_agreement":null},{"id":"W2005112198","doi":"10.1016/j.neulet.2007.04.049","title":"Fronto-striatal connections in the human brain: A probabilistic diffusion tractography study","year":2007,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":359,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University; Toronto Western Hospital; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Putamen; Neuroscience; Caudate nucleus; Basal ganglia; Thalamus; Premotor cortex; Prefrontal cortex; Striatum; Tractography; Dorsolateral prefrontal cortex; Supplementary motor area; Primary motor cortex; Psychology; Human brain; Diffusion MRI; Motor cortex; Biology; Anatomy; Functional magnetic resonance imaging; Medicine; Central nervous system; Dorsum; Magnetic resonance imaging; Dopamine","score_opus":0.07575795002800048,"score_gpt":0.3728317952173892,"score_spread":0.29707384518938873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005112198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9640929,0.000001954825,0.009407602,0.024912635,0.00006931985,0.0012088727,0.0000029454695,0.00012215743,0.00018161754],"genre_scores_gemma":[0.979901,9.889869e-7,0.00028459614,0.019649543,0.00005307736,0.00008119568,0.0000027072742,0.000009824091,0.000017046712],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988117,0.000045989702,0.00021353152,0.00037609073,0.00029059904,0.00026206387],"domain_scores_gemma":[0.9992891,0.00016392741,0.000058850233,0.00041658396,0.000014456164,0.000057057703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004071434,0.0001064317,0.00011199739,0.00017509512,0.0002819011,0.0000352769,0.00024578508,0.000018667368,0.0000033359393],"category_scores_gemma":[0.00017056696,0.00007593583,0.00005456247,0.00080752687,0.00022063682,0.00009498301,0.00003353304,0.00032316442,0.0000014125823],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018429197,0.0011793402,0.2534897,0.000006669926,7.77824e-7,0.00013987397,0.00072945363,0.000016411223,0.74176794,0.0007876767,0.0011707686,0.00069292483],"study_design_scores_gemma":[0.00058941625,0.00032480358,0.9920053,0.000011496033,0.000013525013,0.00008751234,0.00031737724,0.000059334943,0.0003725246,0.0001974565,0.0059297485,0.00009153333],"about_ca_topic_score_codex":0.000056221386,"about_ca_topic_score_gemma":0.00006357398,"teacher_disagreement_score":0.7413954,"about_ca_system_score_codex":0.000027114495,"about_ca_system_score_gemma":0.000009683193,"threshold_uncertainty_score":0.30965734},"labels":[],"label_agreement":null},{"id":"W2005300500","doi":"10.1016/j.neulet.2011.01.070","title":"Genetic and environmental influences on structural variability of the brain in pediatric twin: Deformation based morphometry","year":2011,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"Putamen; Brain morphometry; Corpus callosum; Heritability; Voxel-based morphometry; Twin study; Brain size; Voxel; Globus pallidus; Biology; Neuroimaging; White matter; Atrophy; Neuroscience; Psychology; Evolutionary biology; Genetics; Medicine; Central nervous system; Magnetic resonance imaging; Basal ganglia","score_opus":0.03058218078312898,"score_gpt":0.2707102656751852,"score_spread":0.24012808489205623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005300500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99703366,0.0000020486157,0.0010119405,0.0016668215,0.00003228856,0.00021581484,0.0000045378933,0.000013983079,0.000018904615],"genre_scores_gemma":[0.9895959,0.000003574167,0.0017735128,0.008607637,0.000007959119,0.000006749691,4.0121014e-7,0.0000033243734,9.747017e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942786,0.00003360104,0.00012719852,0.00017262873,0.00014524096,0.0000934895],"domain_scores_gemma":[0.99965525,0.00004321535,0.000064180036,0.00020826627,0.0000025120485,0.000026574107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008128568,0.000057602287,0.00006145334,0.00007257843,0.000044932043,0.000003910299,0.00010885522,0.000013875819,0.0000035852668],"category_scores_gemma":[0.00007802264,0.000039701958,0.000018569672,0.0002549513,0.0002220206,0.000068832625,0.000031559848,0.000106377054,2.5187012e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064811893,0.000019243407,0.8620829,0.000009361579,6.683263e-8,0.0000010198901,0.000052446107,0.0000915148,0.13743849,0.000014540089,0.000010738039,0.00027319853],"study_design_scores_gemma":[0.00012510216,0.000049711267,0.98506576,0.0000045056654,0.0000040694586,0.000009276217,0.000004912119,0.0024540708,0.012117104,0.0001190796,0.0000120202285,0.00003437073],"about_ca_topic_score_codex":0.0000070791007,"about_ca_topic_score_gemma":2.4311078e-7,"teacher_disagreement_score":0.12532139,"about_ca_system_score_codex":0.000018529887,"about_ca_system_score_gemma":0.000009329134,"threshold_uncertainty_score":0.16189988},"labels":[],"label_agreement":null},{"id":"W2005487413","doi":"10.1002/hbm.21484","title":"Whole‐brain white matter disruption in semantic and nonfluent variants of primary progressive aphasia","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network; Health Sciences Centre; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; University of Toronto; Heart and Stroke Foundation of Canada","keywords":"White matter; Primary progressive aphasia; Diffusion MRI; Fractional anisotropy; Atrophy; Pathology; Grey matter; Audiology; Psychology; Neuroscience; Voxel-based morphometry; Medicine; Magnetic resonance imaging; Frontotemporal dementia; Radiology; Dementia","score_opus":0.08366397990442903,"score_gpt":0.33407337270708753,"score_spread":0.2504093928026585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005487413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9742736,0.00009393134,0.015637979,0.005389822,0.000013895257,0.00091697596,0.0000060733055,0.00010117018,0.0035665128],"genre_scores_gemma":[0.9826296,0.0000028765814,0.014778396,0.0019708069,0.000029746669,0.00008689174,0.00002414583,0.000025430283,0.0004520978],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99911004,0.000033491528,0.000288426,0.00028110945,0.00010590906,0.000181002],"domain_scores_gemma":[0.99946404,0.000029877223,0.00013827384,0.0002808146,0.00003349074,0.00005349402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017048574,0.000121231686,0.00023124501,0.00018187168,0.00006524099,0.000009158449,0.00007170397,0.00004575489,0.000068049914],"category_scores_gemma":[0.000020873787,0.00011699556,0.00003455373,0.00015810975,0.00011360119,0.00010039192,0.00007378794,0.00015617222,0.000007975391],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048914073,0.0003990443,0.47800466,0.00071398914,0.0000238741,0.00015757608,0.0044065127,0.000001112492,0.5084796,0.0017903317,0.0033160094,0.0026583897],"study_design_scores_gemma":[0.0006056508,0.00006880192,0.9934557,0.0005389051,0.0000132092755,0.000096116935,0.00010388607,0.000076940065,0.00021116182,0.0035906867,0.0011281187,0.00011083885],"about_ca_topic_score_codex":0.000008862041,"about_ca_topic_score_gemma":0.0000018438882,"teacher_disagreement_score":0.515451,"about_ca_system_score_codex":0.00003185332,"about_ca_system_score_gemma":0.000013178563,"threshold_uncertainty_score":0.47709405},"labels":[],"label_agreement":null},{"id":"W2005495240","doi":"10.1523/jneurosci.1619-09.2010","title":"<i>In Vivo</i>Diffusion Tensor Imaging and Histopathology of the Fimbria-Fornix in Temporal Lobe Epilepsy","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":215,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Savoy Foundation; National Institutes of Health; University of Alberta; National Center for Research Resources; Directorate for Biological Sciences; Fondation pour la Recherche Médicale","keywords":"Fornix; Temporal lobe; Diffusion MRI; White matter; Anatomy; Pathology; Hippocampus; Fractional anisotropy; Medicine; Neuroscience; Biology; Epilepsy; Magnetic resonance imaging; Radiology","score_opus":0.02665710038749993,"score_gpt":0.32383076454889814,"score_spread":0.29717366416139823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2005495240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918277,0.000027673774,0.00047357247,0.007165974,0.00024988432,0.000115997296,0.0000018223942,0.000004938354,0.00013240789],"genre_scores_gemma":[0.99525005,0.000059781778,0.0030413994,0.0015063616,0.000032175965,0.0000016372823,2.4707013e-8,0.000005721496,0.00010282276],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99926615,0.000025348292,0.00030715397,0.00013228747,0.0001512212,0.00011783845],"domain_scores_gemma":[0.9994225,0.000043226344,0.00025145835,0.00018545594,0.000049233502,0.00004811031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002625788,0.00006033871,0.00016067729,0.00013015715,0.00003703383,0.0000056375934,0.00017944623,0.000019971727,0.0000037088807],"category_scores_gemma":[0.00031931966,0.0000396874,0.000038692968,0.0002692066,0.00029263893,0.00012035002,0.00007277926,0.00042690436,1.11234506e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011990939,0.000053068583,0.32623324,0.000004636404,3.1882273e-8,0.00005767055,0.000025268477,0.0000022059057,0.6730708,0.00010103076,0.00014439093,0.00029566302],"study_design_scores_gemma":[0.00046325897,0.00010151255,0.9661915,0.00006301826,0.0000053523872,0.0028485951,0.0000146135735,0.00090958044,0.015173764,0.0010843169,0.013099021,0.000045480097],"about_ca_topic_score_codex":0.000010741022,"about_ca_topic_score_gemma":0.0000064819487,"teacher_disagreement_score":0.65789706,"about_ca_system_score_codex":0.000013805398,"about_ca_system_score_gemma":0.00005037705,"threshold_uncertainty_score":0.18547107},"labels":[],"label_agreement":null},{"id":"W2006080132","doi":"10.1016/j.neuroimage.2005.07.008","title":"Neuroanatomical differences between mouse strains as shown by high-resolution 3D MRI","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto; Hospital for Sick Children","funders":"Canada Foundation for Innovation; Canadian Institutes of Health Research; Ontario Innovation Trust; Burroughs Wellcome Fund","keywords":"Neuroanatomy; Magnetic resonance imaging; Hippocampus; Strain (injury); High resolution; Artificial intelligence; Standard deviation; Biology; Lateral ventricles; Metric (unit); Anatomy; Pattern recognition (psychology); Neuroscience; Computer science; Mathematics; Medicine; Radiology; Geology; Statistics","score_opus":0.04755365049794241,"score_gpt":0.330409585953324,"score_spread":0.28285593545538157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006080132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9599964,0.000052920434,0.018755123,0.016989667,0.00003989929,0.00058670895,0.00017379365,0.0008745236,0.0025309587],"genre_scores_gemma":[0.98302305,0.00014057025,0.011576717,0.0026125321,0.00030840654,0.000046157078,0.00010951025,0.000060151142,0.0021229235],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983459,0.00005059152,0.00032327184,0.0005824402,0.00031311813,0.00038464498],"domain_scores_gemma":[0.9989513,0.000078732664,0.00009774292,0.00058102683,0.00005089649,0.00024027117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006450121,0.0002434597,0.0003155481,0.000094608666,0.00014768355,0.00004353285,0.00023457239,0.000086703054,0.00014156473],"category_scores_gemma":[0.00008149605,0.00022528837,0.000092064,0.00020327202,0.00017868256,0.00017355267,0.000096055235,0.00051358645,0.0001416908],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013680018,0.0012840965,0.02688173,0.00008079241,0.00005577046,0.00013934354,0.00012241669,0.00004592288,0.7575565,0.006871928,0.116408885,0.090415806],"study_design_scores_gemma":[0.0038228193,0.0015265165,0.29676712,0.000080809565,0.00040211025,0.00030344364,0.00003233725,0.010109221,0.16769378,0.00256193,0.51538783,0.0013120667],"about_ca_topic_score_codex":0.000034036184,"about_ca_topic_score_gemma":0.0000021699373,"teacher_disagreement_score":0.5898627,"about_ca_system_score_codex":0.000049729046,"about_ca_system_score_gemma":0.000036705187,"threshold_uncertainty_score":0.9186993},"labels":[],"label_agreement":null},{"id":"W2006419171","doi":"10.1002/hbm.21437","title":"Transcallosal sensorimotor fiber tract structure‐function relationships","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health","keywords":"Corpus callosum; Neuroscience; White matter; Diffusion MRI; Psychology; Fiber tract; Inhibitory postsynaptic potential; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.21177140730277447,"score_gpt":0.3344824964312587,"score_spread":0.12271108912848425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006419171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75249314,0.00005116673,0.1928206,0.0032961392,0.00011075077,0.0013586354,0.000025256812,0.0014764256,0.04836791],"genre_scores_gemma":[0.9683277,0.0000014031109,0.029120388,0.0006564117,0.0001650745,0.00002989423,0.000046450306,0.000034069344,0.0016185949],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99916357,0.000040590414,0.000223229,0.00027220015,0.0001205155,0.00017991192],"domain_scores_gemma":[0.99942625,0.00005722617,0.00007016748,0.00031536017,0.000044838795,0.0000861645],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001146156,0.00012840757,0.00014474151,0.00011481769,0.00031160898,0.000010754747,0.000064225285,0.00007983076,0.00092293485],"category_scores_gemma":[0.000047850273,0.00012569944,0.000081726525,0.00015484009,0.00005776003,0.00010121117,0.00001144949,0.00038765118,0.000041770014],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009872483,0.0003753306,0.02667169,0.00016619117,0.000072405135,0.000050834144,0.0025565599,0.000010210301,0.8891198,0.059810054,0.01325257,0.007815625],"study_design_scores_gemma":[0.0005995711,0.00013411278,0.89225745,0.00008185584,0.00006379262,0.00011719571,0.000104907085,0.00010917946,0.0015168263,0.03283273,0.07195557,0.00022679353],"about_ca_topic_score_codex":0.000008126011,"about_ca_topic_score_gemma":0.0000018764628,"teacher_disagreement_score":0.887603,"about_ca_system_score_codex":0.000034476918,"about_ca_system_score_gemma":0.000014398264,"threshold_uncertainty_score":0.99999034},"labels":[],"label_agreement":null},{"id":"W2007069085","doi":"10.1615/critrevbiomedeng.v40.i1.10","title":"Diffusion Tensor Imaging in the Human Spinal Cord: Development, Limitations, and Clinical Applications","year":2012,"lang":"en","type":"review","venue":"Critical Reviews in Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Diffusion MRI; White matter; Spinal cord; Spinal cord injury; Multiple sclerosis; Magnetic resonance imaging; Neuroscience; Medicine; Amyotrophic lateral sclerosis; Tractography; Diffusion imaging; Myelitis; Pathology; Radiology; Psychology","score_opus":0.325175588118223,"score_gpt":0.5154178681987168,"score_spread":0.19024228008049382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007069085","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008410531,0.9684547,0.028575996,0.0006284441,0.00006246165,0.002077418,0.0000052928212,0.000083286715,0.00010394974],"genre_scores_gemma":[0.00021227487,0.9646399,0.032362565,0.00030147744,0.0003060536,0.0020105157,0.00010639723,0.00004951112,0.000011298485],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99696016,0.00014434665,0.0016671252,0.000518401,0.0002544337,0.00045555754],"domain_scores_gemma":[0.9979651,0.0010651703,0.00012287151,0.0005213141,0.00003142583,0.0002941266],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014413918,0.0003673651,0.0013502758,0.00033218486,0.00009632737,0.000028996456,0.00030809746,0.00021074996,0.00001078001],"category_scores_gemma":[0.0016416676,0.00024710337,0.00021971577,0.0007340652,0.00031237648,0.000065387656,0.00015418412,0.0013281143,0.000030682186],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000013720819,0.000266513,0.00015976025,0.0066473554,0.0000036924566,0.000017048305,0.000007635577,7.0902195e-9,0.0000019059225,0.0040429253,0.000082861414,0.98876894],"study_design_scores_gemma":[0.00014450226,0.000043811968,0.0015124158,0.014137199,0.00025108544,0.00020083165,0.0000070514598,0.000051663043,6.2936394e-8,0.00010051835,0.98332,0.00023086985],"about_ca_topic_score_codex":0.0000015197078,"about_ca_topic_score_gemma":6.767441e-7,"teacher_disagreement_score":0.988538,"about_ca_system_score_codex":0.000112007176,"about_ca_system_score_gemma":0.000076169985,"threshold_uncertainty_score":0.9999981},"labels":[],"label_agreement":null},{"id":"W2007162694","doi":"10.1002/mrm.10270","title":"Human erythrocyte ghosts: Exploring the origins of multiexponential water diffusion in a model biological tissue with magnetic resonance","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Permeability (electromagnetism); Chemistry; Extracellular; Diffusion; Biophysics; Compartment (ship); Cellular compartment; Membrane; Membrane permeability; Cell membrane; Nuclear magnetic resonance; Biological system; Cell; Thermodynamics; Biochemistry; Physics","score_opus":0.11531456346379637,"score_gpt":0.3327923303412229,"score_spread":0.21747776687742654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007162694","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98314553,0.00982479,0.000701601,0.0045033405,0.000037268168,0.0010660252,0.000004710428,0.0000792637,0.000637438],"genre_scores_gemma":[0.98837894,0.0041069775,0.0055546407,0.00043055165,0.00011100843,0.00052204257,0.000007898903,0.000035789162,0.0008521534],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9979315,0.00006201877,0.0006248419,0.000524181,0.00039824794,0.0004592279],"domain_scores_gemma":[0.99902374,0.00008176618,0.00007760174,0.0006709079,0.000063949396,0.00008202548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024574026,0.00026265613,0.00053192466,0.000196624,0.00008666309,0.0000056247454,0.00028082053,0.00007510994,0.0002462204],"category_scores_gemma":[0.00007248089,0.000138886,0.000034959867,0.00047518377,0.00066275656,0.000069637426,0.00010676448,0.0004795719,0.0000072944017],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009102806,0.0016710046,0.061361186,0.00024981864,0.0000049107043,0.00064438,0.006518044,0.00043393986,0.38151345,0.0039383145,0.0015169594,0.5412377],"study_design_scores_gemma":[0.017986204,0.0100573795,0.58871895,0.0049671414,0.00011396895,0.00036541492,0.0008206506,0.10276172,0.027788907,0.0035553908,0.2418372,0.0010270841],"about_ca_topic_score_codex":0.0003960171,"about_ca_topic_score_gemma":0.00008972528,"teacher_disagreement_score":0.5402106,"about_ca_system_score_codex":0.00011818161,"about_ca_system_score_gemma":0.000011079916,"threshold_uncertainty_score":0.56636065},"labels":[],"label_agreement":null},{"id":"W2007276643","doi":"10.1002/mrm.20008","title":"MR properties of excised neural tissue following experimentally induced inflammation","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Inflammation; Histopathology; Magnetization transfer; Sciatic nerve; Brain tissue; Chemistry; Pathology; Nuclear magnetic resonance; Necrosis; Anatomy; Medicine; Magnetic resonance imaging; Internal medicine; Physics; Radiology","score_opus":0.07435044444015612,"score_gpt":0.3554056399747598,"score_spread":0.2810551955346037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007276643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877098,0.004925711,0.00036353312,0.005146869,0.00006298785,0.0008099574,4.3313474e-7,0.00008664032,0.0008940306],"genre_scores_gemma":[0.9939211,0.00014844017,0.005163961,0.00030236066,0.00010058183,0.00016640488,0.000005136074,0.00002237099,0.00016967308],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987773,0.000019335714,0.00045888335,0.00024858478,0.00030355912,0.0001923793],"domain_scores_gemma":[0.99944454,0.000018858998,0.000089224515,0.00033886544,0.000047180085,0.00006132138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013254695,0.00014299706,0.00033603085,0.00014157033,0.0000338558,0.0000034902002,0.000117677446,0.000051804705,0.00003628014],"category_scores_gemma":[0.00015059726,0.00011331839,0.000035492045,0.0003460321,0.0001353261,0.00007644576,0.00003555606,0.00018028633,0.0000036329125],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000071992385,0.00006211367,0.0016503148,0.00005284599,0.0000014404985,0.00004213017,0.00078737794,0.00001571534,0.9474585,0.00027334958,0.00003032994,0.049553912],"study_design_scores_gemma":[0.0048626103,0.0015131735,0.041252475,0.00184949,0.000034697783,0.000052846764,0.0004488232,0.0004038887,0.9435785,0.0012443115,0.0045688143,0.00019036853],"about_ca_topic_score_codex":0.00015053312,"about_ca_topic_score_gemma":0.0000068312947,"teacher_disagreement_score":0.049363546,"about_ca_system_score_codex":0.00007091355,"about_ca_system_score_gemma":0.00004399478,"threshold_uncertainty_score":0.462099},"labels":[],"label_agreement":null},{"id":"W2007565673","doi":"10.1002/hbm.21257","title":"The neural basis of central proprioceptive processing in older versus younger adults: An important sensory role for right putamen","year":2011,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":169,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Vlaamse regering","keywords":"Proprioception; Putamen; Functional magnetic resonance imaging; Psychology; Neuroscience; Somatosensory system; Secondary somatosensory cortex; Physical medicine and rehabilitation; Medicine","score_opus":0.08311152885122405,"score_gpt":0.3365693510946376,"score_spread":0.2534578222434135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007565673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99277055,0.0001508294,0.0032721835,0.0010624045,0.000035875637,0.0016543916,0.000013113175,0.00014980981,0.00089083886],"genre_scores_gemma":[0.99071026,0.000008091461,0.008635198,0.00021969904,0.000075488875,0.0001841115,0.000017668444,0.000029731918,0.00011975453],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99893004,0.00002628263,0.00033653516,0.0002819532,0.000114824616,0.00031033758],"domain_scores_gemma":[0.99933493,0.00004946132,0.00018143347,0.00027513463,0.00009443558,0.00006458683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017616538,0.00012816864,0.00017577558,0.000073755604,0.00022626155,0.00001395186,0.0001266057,0.000043045777,0.000015770182],"category_scores_gemma":[0.000060902876,0.00009608429,0.000061667575,0.0001285019,0.00013061221,0.0001489332,0.000031834923,0.00016288027,3.4298495e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041513136,0.0022000063,0.08170658,0.0012890854,0.00013870547,0.00011547875,0.07382589,0.000023542625,0.68859136,0.028080465,0.001519055,0.11835851],"study_design_scores_gemma":[0.008557628,0.0013407215,0.9045141,0.0011165198,0.00013034513,0.000057800215,0.014869701,0.020784734,0.023897573,0.013434683,0.010512407,0.0007837863],"about_ca_topic_score_codex":0.000035588713,"about_ca_topic_score_gemma":0.00003328095,"teacher_disagreement_score":0.8228075,"about_ca_system_score_codex":0.000052526917,"about_ca_system_score_gemma":0.000036587928,"threshold_uncertainty_score":0.39182037},"labels":[],"label_agreement":null},{"id":"W2007618085","doi":"10.1016/j.neuroimage.2007.11.031","title":"In vivo DTI of the healthy and injured cat spinal cord at high spatial and angular resolution","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche Médicale; Canada Research Chairs","keywords":"Spinal cord; Tractography; Diffusion MRI; Neuroscience; Spinal cord injury; Anatomy; Medicine; Fractional anisotropy; Lumbar Spinal Cord; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.04383841280079468,"score_gpt":0.3602793689420522,"score_spread":0.3164409561412575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007618085","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99346524,0.000102079706,0.0015321932,0.0041845804,0.000044789052,0.0004016241,0.000011452545,0.000033716286,0.00022432767],"genre_scores_gemma":[0.99517554,0.00010307693,0.003161845,0.0013575535,0.00004749125,0.0000069907355,0.0000014841904,0.000013536686,0.00013245943],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999304,0.00002317852,0.00018808724,0.00021716024,0.00011674941,0.00015083904],"domain_scores_gemma":[0.99953663,0.00003063513,0.00007857652,0.00026809084,0.000026267895,0.000059778944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012396318,0.00008125347,0.00013613096,0.00006288605,0.00006799741,0.0000036354488,0.00004951864,0.00003487538,0.000007666158],"category_scores_gemma":[0.000051847106,0.00006509604,0.000019926078,0.00015300038,0.00016110369,0.000040065737,0.00009911244,0.0001309668,4.830043e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023387081,0.00014666007,0.04638192,0.00012861977,0.0000029069172,0.00006748512,0.0000736789,6.464368e-7,0.9340591,0.00162226,0.0017126433,0.013465379],"study_design_scores_gemma":[0.0008786454,0.00078405516,0.92619103,0.0000474469,0.000017820825,0.00016481467,0.0000079683,0.00014527925,0.059845336,0.00071896636,0.011124044,0.00007457932],"about_ca_topic_score_codex":0.00025488564,"about_ca_topic_score_gemma":0.0000938639,"teacher_disagreement_score":0.87980914,"about_ca_system_score_codex":0.000034521632,"about_ca_system_score_gemma":0.000016307093,"threshold_uncertainty_score":0.26545396},"labels":[],"label_agreement":null},{"id":"W2007640411","doi":"10.1016/j.neuroimage.2014.03.069","title":"Individual differences in white matter anatomy predict dissociable components of reading skill in adults","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Uncinate fasciculus; Psychology; Diffusion MRI; Corpus callosum; Supramarginal gyrus; Reading (process); Neuroscience; Angular gyrus; Superior longitudinal fasciculus; Fractional anisotropy; Cognitive psychology; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Linguistics","score_opus":0.03304497735832924,"score_gpt":0.30976057988034167,"score_spread":0.27671560252201244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007640411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943384,0.000010717573,0.00040144566,0.0009902798,0.000026569847,0.0003573889,0.000026148322,0.00006574386,0.0037832998],"genre_scores_gemma":[0.99701554,0.000020812056,0.002196494,0.0005096721,0.000022826347,0.00004070545,0.000035814875,0.000022484353,0.00013566692],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99889046,0.000055950175,0.0003198228,0.00030579165,0.00019890074,0.00022908178],"domain_scores_gemma":[0.99941576,0.000087567816,0.00010996198,0.00030192724,0.000026229012,0.000058567784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012822726,0.00012626062,0.0003000062,0.00019328155,0.000024281895,0.000009571661,0.00015759471,0.000045181696,0.000043495806],"category_scores_gemma":[0.00006435503,0.000117659554,0.000039238857,0.0002965484,0.00007741945,0.00009799212,0.0000849247,0.00027054007,0.000009614777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034896046,0.00019165849,0.99578696,0.000071614326,0.0000021385224,0.000012018454,0.00017937449,0.00000197844,0.0025067525,0.00013211474,0.00045413032,0.0006263521],"study_design_scores_gemma":[0.00090840645,0.00008280105,0.99573016,0.00031690876,0.000009754118,0.000009205668,0.000022495873,0.0008934019,0.0008877238,0.00056908146,0.00048312056,0.000086921726],"about_ca_topic_score_codex":0.000056109002,"about_ca_topic_score_gemma":0.0000067535198,"teacher_disagreement_score":0.003647633,"about_ca_system_score_codex":0.000021073238,"about_ca_system_score_gemma":0.000008839235,"threshold_uncertainty_score":0.47980174},"labels":[],"label_agreement":null},{"id":"W2007805846","doi":"10.1089/brain.2011.0005","title":"Superficially Located White Matter Structures Commonly Seen in the Human and the Macaque Brain with Diffusion Tensor Imaging","year":2011,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Center for Research Resources; National Institute on Aging; NIH Clinical Center; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; Johns Hopkins University","keywords":"Macaque; White matter; Neuroscience; Diffusion MRI; Human brain; Psychology; Brain mapping; Tractography; Fiber tract; Rhesus macaque; Functional organization; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.04069078313531951,"score_gpt":0.301647007924365,"score_spread":0.2609562247890455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007805846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94159937,0.000023315706,0.00487237,0.049876254,0.000008170397,0.00096687535,0.000008124353,0.00009966459,0.0025458287],"genre_scores_gemma":[0.98459977,0.000002839156,0.00097125117,0.0141568445,0.000037081365,0.0000835547,0.000008741198,0.000026497999,0.00011340359],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989858,0.0002158893,0.00015936386,0.00030199045,0.00013512892,0.00020182319],"domain_scores_gemma":[0.9988825,0.00048009085,0.00007049427,0.0004844021,0.000043895656,0.000038615522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036612016,0.00016444379,0.00022412623,0.00006363951,0.00024575015,0.000032867327,0.00017465724,0.0000371996,0.00004315204],"category_scores_gemma":[0.00009826835,0.00008514507,0.000034563644,0.00019855978,0.00040359632,0.00007764803,0.00008115565,0.00037566217,0.0000024937187],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002786127,0.0001265732,0.97532725,0.000028480841,0.000012461189,0.000042194064,0.0025493174,0.0000017462803,0.004512038,0.012625212,0.0022838716,0.0022122662],"study_design_scores_gemma":[0.001678404,0.000062465435,0.98204774,0.000044436387,0.000027567003,0.00026096698,0.00033592037,0.0003972238,0.00067592517,0.013466298,0.0008713156,0.0001317689],"about_ca_topic_score_codex":0.0006346586,"about_ca_topic_score_gemma":0.00040410232,"teacher_disagreement_score":0.04300039,"about_ca_system_score_codex":0.000020043919,"about_ca_system_score_gemma":0.000022144306,"threshold_uncertainty_score":0.3472115},"labels":[],"label_agreement":null},{"id":"W2007845370","doi":"10.1002/1522-2594(200007)44:1<110::aid-mrm16>3.0.co;2-n","title":"Spreading waves of transient and prolonged decreases in water diffusion after subarachnoid hemorrhage in rats","year":2000,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources","keywords":"Cortical spreading depression; Subarachnoid hemorrhage; Effective diffusion coefficient; Perforation; Cortex (anatomy); Anesthesia; Diffusion; Nuclear magnetic resonance; Medicine; Depolarization; Magnetic resonance imaging; Neuroscience; Internal medicine; Materials science; Physics; Radiology; Psychology","score_opus":0.019873147470301753,"score_gpt":0.2907193973764593,"score_spread":0.2708462499061575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007845370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891037,0.0060962765,0.000032374224,0.0034459599,0.000009188188,0.00069762795,0.0000016362507,0.00002598813,0.00058726995],"genre_scores_gemma":[0.9951169,0.0011980755,0.0027228578,0.00039305724,0.000029774337,0.00018574177,0.000007375264,0.000017011087,0.00032919893],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987591,0.000039656665,0.0004385025,0.00032059118,0.00017504083,0.000267145],"domain_scores_gemma":[0.99956596,0.00005689341,0.000025163232,0.00027056978,0.000016339249,0.00006505929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002253672,0.0001446295,0.00040143193,0.00022601643,0.000013068225,0.0000024524177,0.000070747265,0.00005652301,0.00030852112],"category_scores_gemma":[0.000054991226,0.00010101961,0.000018179175,0.00028421025,0.00021772824,0.00004422051,0.000020221514,0.00023055864,0.0000015853933],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001329355,0.00050106616,0.327707,0.00042837963,6.4131643e-7,0.0007993899,0.0025352756,0.000009293061,0.124389276,0.000027969958,0.00003878737,0.5422336],"study_design_scores_gemma":[0.0034970865,0.0006273768,0.9729208,0.0010565404,0.000020688087,0.000100359146,0.000104638406,0.0033519305,0.014732525,0.0007419945,0.00269626,0.00014981747],"about_ca_topic_score_codex":0.0002014509,"about_ca_topic_score_gemma":0.000107021595,"teacher_disagreement_score":0.6452138,"about_ca_system_score_codex":0.00002993838,"about_ca_system_score_gemma":0.000010712933,"threshold_uncertainty_score":0.411946},"labels":[],"label_agreement":null},{"id":"W2008071439","doi":"10.1249/01.mss.0000386540.28706.a6","title":"Use Of Diffusion Tensor Magnetic Resonance Imaging For Assessment Of Musculoskeletal Structure Following An Acute Bout Of Downhill Running","year":2010,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Creatine kinase; Skeletal muscle; Medicine; Isometric exercise; Muscle biopsy; Fractional anisotropy; Sarcolemma; Nuclear medicine; Nuclear magnetic resonance; Internal medicine; Biopsy; Radiology; Physics","score_opus":0.027616277414583515,"score_gpt":0.3694757063335947,"score_spread":0.3418594289190112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008071439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99667376,0.00006747446,0.0016434201,0.00034799447,0.00017399268,0.0009845425,0.00001801793,0.000038242404,0.000052547795],"genre_scores_gemma":[0.9155331,0.00008677867,0.084171176,0.000057125602,0.000035838944,0.000038627866,0.000015637346,0.000019972831,0.00004171892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977993,0.0000070092424,0.0006623877,0.00048218202,0.0007061241,0.00034299478],"domain_scores_gemma":[0.9984492,0.00006203295,0.0003433069,0.000727776,0.0002808436,0.00013681261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006452402,0.00017862239,0.00058417796,0.00039081404,0.000091436894,0.0000058191054,0.0002965191,0.000044682263,0.0000278124],"category_scores_gemma":[0.00019436382,0.00013596112,0.00009471669,0.0007871685,0.00096990244,0.0003411712,0.00009055525,0.00028954743,2.8652508e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028497801,0.000088973036,0.5591806,0.00005423088,1.752651e-7,0.000013406884,0.0002163273,0.00000812481,0.3840418,0.000042386167,0.000017388293,0.056308113],"study_design_scores_gemma":[0.00084506767,0.00034212845,0.98721427,0.0008744191,0.00013565349,0.00002603265,0.00022972614,0.005098077,0.0041842274,0.00055808335,0.00036458208,0.00012776503],"about_ca_topic_score_codex":0.00011574099,"about_ca_topic_score_gemma":0.000008248806,"teacher_disagreement_score":0.42803365,"about_ca_system_score_codex":0.000031995514,"about_ca_system_score_gemma":0.00017493813,"threshold_uncertainty_score":0.55443335},"labels":[],"label_agreement":null},{"id":"W2008221065","doi":"10.1002/mrm.10250","title":"Orientational diffusion reflects fiber structure within a voxel","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Canada Research Chairs","keywords":"Diffusion; Voxel; Diffusion MRI; Fiber; Orientation (vector space); Effective diffusion coefficient; Fiber bundle; Nuclear magnetic resonance; Materials science; Geometry; Physics; Mathematics; Magnetic resonance imaging; Computer science; Artificial intelligence","score_opus":0.057334700175877544,"score_gpt":0.35096536060955075,"score_spread":0.2936306604336732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008221065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9324913,0.012520621,0.0007670292,0.029651511,0.00023888177,0.0015229108,0.000020626037,0.0003311124,0.022456015],"genre_scores_gemma":[0.9366075,0.0008749969,0.037697755,0.0044643497,0.0004110594,0.00013199459,0.000043771695,0.000050757073,0.019717854],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986162,0.000025380548,0.00036586815,0.00037652042,0.00038226164,0.00023373977],"domain_scores_gemma":[0.9992778,0.00007588216,0.00007824083,0.000393834,0.000068437104,0.0001058187],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008546182,0.0001645471,0.00027447654,0.00014493606,0.000060637103,0.000005143787,0.00011363868,0.00006895052,0.0032242206],"category_scores_gemma":[0.00021501772,0.00012659274,0.000026540656,0.00055133447,0.00020620866,0.000045650726,0.00003554181,0.0003435798,0.000034369186],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041713443,0.000783679,0.07341824,0.0002753484,0.000009100041,0.0007057692,0.0040444997,0.0000626658,0.09750438,0.009212282,0.11632068,0.69724625],"study_design_scores_gemma":[0.006529225,0.0017131887,0.33013877,0.0012109145,0.000070288275,0.000640774,0.0001626322,0.013071446,0.0019093027,0.014700707,0.6294039,0.0004488429],"about_ca_topic_score_codex":0.000028535549,"about_ca_topic_score_gemma":0.000011393443,"teacher_disagreement_score":0.6967974,"about_ca_system_score_codex":0.000059430367,"about_ca_system_score_gemma":0.000015244132,"threshold_uncertainty_score":0.997687},"labels":[],"label_agreement":null},{"id":"W2008293972","doi":"10.1016/j.neuroimage.2011.08.005","title":"Cortical thickness is associated with gait disturbances in cerebral small vessel disease","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Gait; Cortex (anatomy); Cerebral cortex; Parietal lobe; Posterior cingulate; Neuroscience; Hyperintensity; Posterior parietal cortex; Prefrontal cortex; Orbitofrontal cortex; Psychology; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Cognition; Radiology","score_opus":0.09264949612268991,"score_gpt":0.3086791810961475,"score_spread":0.2160296849734576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008293972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879913,0.000051257986,0.0030172733,0.0019687796,0.000035003344,0.0005551549,0.000040644132,0.00037255848,0.0059680464],"genre_scores_gemma":[0.993935,0.000023172803,0.0027473008,0.002545311,0.000027478784,0.00008557711,0.000022761627,0.000042374788,0.0005710628],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988485,0.00004277564,0.00020434745,0.00044083336,0.00017319224,0.0002903638],"domain_scores_gemma":[0.9991478,0.00006734871,0.00007382612,0.00045229692,0.000061504674,0.00019722979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000067356494,0.000170043,0.00023156214,0.00005094314,0.00006985106,0.000015197359,0.00014417368,0.000040490297,0.00008293514],"category_scores_gemma":[0.0001638604,0.00013735487,0.000052810254,0.00030214607,0.00018460292,0.000093823495,0.00005394693,0.00041109463,0.000016243099],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071770715,0.0016180876,0.98364925,0.000084854684,0.000022720038,0.0015775956,0.0004590811,0.0000014905498,0.004584806,0.003277119,0.0026512449,0.0013560503],"study_design_scores_gemma":[0.000817259,0.00016347268,0.9941133,0.000109876084,0.0000652403,0.0000325099,0.000015925629,0.0003666772,0.0014554278,0.0013983413,0.001294239,0.00016771932],"about_ca_topic_score_codex":0.000022956778,"about_ca_topic_score_gemma":0.000009319198,"teacher_disagreement_score":0.0104640685,"about_ca_system_score_codex":0.000029439869,"about_ca_system_score_gemma":0.00005605134,"threshold_uncertainty_score":0.56011695},"labels":[],"label_agreement":null},{"id":"W2008410132","doi":"10.1167/3.9.205","title":"Texture regions are more easily detected than texture edges","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University","funders":"","keywords":"Texture (cosmology); Texture filtering; Classification of discontinuities; Artificial intelligence; Octave (electronics); Texture compression; Mathematics; Pattern recognition (psychology); Physics; Computer science; Image texture; Optics; Image (mathematics); Image processing; Mathematical analysis","score_opus":0.03576059417332198,"score_gpt":0.36665611878628984,"score_spread":0.33089552461296784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008410132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92299926,0.0004861534,0.025999563,0.04896461,0.00035020418,0.00039048196,0.000009408143,0.00018685819,0.00061346625],"genre_scores_gemma":[0.9833497,0.00013287932,0.015162799,0.0004811873,0.000482346,0.0000029444618,0.0000027070084,0.000024022447,0.000361453],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992086,0.000013257929,0.0002666311,0.00013270862,0.00024708835,0.00013167827],"domain_scores_gemma":[0.99878246,0.0000466821,0.0003565446,0.00033601042,0.0003141215,0.00016418964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010063137,0.00011567439,0.0002182869,0.00013789568,0.00010182147,0.000017624214,0.00015519721,0.000118780765,0.000031173262],"category_scores_gemma":[0.00020224242,0.00007913518,0.00014529315,0.0002082911,0.00006859643,0.00011483015,0.000034660694,0.00097561657,0.000006144654],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020907242,0.0004018381,0.019945139,0.0000437264,0.000028397546,0.00024508784,0.00013689783,0.0000060467473,0.87141025,0.0005788262,0.05871231,0.04828239],"study_design_scores_gemma":[0.0009235217,0.00050482043,0.8441885,0.0004976825,0.00011247496,0.0031200915,0.00011596865,0.00022901494,0.016019728,0.0032096633,0.13092126,0.00015729282],"about_ca_topic_score_codex":0.0000015820805,"about_ca_topic_score_gemma":0.0000036030299,"teacher_disagreement_score":0.85539055,"about_ca_system_score_codex":0.000019091654,"about_ca_system_score_gemma":0.000046627163,"threshold_uncertainty_score":0.42386228},"labels":[],"label_agreement":null},{"id":"W2008478214","doi":"10.1109/mmbia.2012.6164747","title":"Multi-region competitive tractography via graph-based random walks","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Random walk; Computer science; Tractography; Artificial intelligence; Mathematics; Diffusion MRI; Statistics; Medicine; Magnetic resonance imaging","score_opus":0.07566835506820181,"score_gpt":0.3519483959716024,"score_spread":0.2762800409034006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008478214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012323538,0.00011680518,0.97952986,0.0017900969,0.000045477977,0.00064027344,0.0000035669061,0.0005500346,0.005000374],"genre_scores_gemma":[0.8908463,0.000027944268,0.10692135,0.0018492811,0.000059565664,0.00009650909,0.000025535062,0.00002060471,0.00015291294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993294,0.000019849147,0.00014814294,0.00016660942,0.00010426724,0.00023172011],"domain_scores_gemma":[0.9993775,0.00007696946,0.00005112811,0.0002780199,0.000057632376,0.00015873607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006548552,0.00012223347,0.00017802972,0.00012782203,0.00007244216,0.000005293709,0.0000550249,0.000045483244,0.00006297801],"category_scores_gemma":[0.000014482959,0.000096298,0.00015065448,0.0002481239,0.00010048509,0.00008150992,0.000011493367,0.00015949033,0.00002162551],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017378833,0.009434703,0.5674124,0.00024601925,0.00021132924,0.00007023419,0.000540206,0.000028758514,0.2914231,0.05341372,0.012737012,0.06274467],"study_design_scores_gemma":[0.024659188,0.00057199085,0.4831067,0.00025426745,0.00049065973,0.00037484354,0.0002288785,0.00682174,0.1788933,0.002337901,0.30112582,0.0011347061],"about_ca_topic_score_codex":0.000016603637,"about_ca_topic_score_gemma":0.0000018142216,"teacher_disagreement_score":0.87852275,"about_ca_system_score_codex":0.00001273416,"about_ca_system_score_gemma":0.000009385671,"threshold_uncertainty_score":0.39269185},"labels":[],"label_agreement":null},{"id":"W2008655880","doi":"10.1016/j.mri.2008.01.047","title":"Is diffusion anisotropy an accurate monitor of myelination?","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":229,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of British Columbia Hospital","funders":"Killam Trusts; Bundesministerium für Bildung und Forschung","keywords":"Fractional anisotropy; Anisotropy; Diffusion MRI; White matter; Myelin; Thermal diffusivity; Nuclear magnetic resonance; Chemistry; Diffusion; Materials science; Physics; Neuroscience; Psychology; Thermodynamics; Optics; Magnetic resonance imaging; Medicine","score_opus":0.05355865973126047,"score_gpt":0.35313685121888166,"score_spread":0.2995781914876212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008655880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9738294,0.003561952,0.016853945,0.0035068165,0.000054652548,0.0005156367,0.000020518757,0.00026501899,0.0013920595],"genre_scores_gemma":[0.94150746,0.0009353108,0.055478983,0.00067176204,0.00009016512,0.00004463812,0.000010417612,0.000030210704,0.0012310273],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989732,0.000017918728,0.00027384917,0.00030757257,0.00023209566,0.00019537463],"domain_scores_gemma":[0.9991316,0.000027063525,0.000097603544,0.0004962544,0.00016211832,0.00008536503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051728053,0.00012872201,0.00019159121,0.000087508226,0.00013314534,0.000008255182,0.00013264138,0.000024757777,0.00010084014],"category_scores_gemma":[0.000037591446,0.000121300654,0.000056367342,0.00024626296,0.00016861701,0.00014856817,0.000052835127,0.000130588,0.000012069304],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012280916,0.00059108465,0.32196915,0.000064834196,0.0000026347561,0.00011752779,0.00066922733,0.0000060206194,0.20848376,0.0012445048,0.004319994,0.46240845],"study_design_scores_gemma":[0.0011639438,0.00029056545,0.86875373,0.00013145516,0.000030568088,0.00030677623,0.00007532065,0.021707596,0.04008474,0.0018409451,0.06538011,0.00023423758],"about_ca_topic_score_codex":0.000035010267,"about_ca_topic_score_gemma":2.477662e-7,"teacher_disagreement_score":0.5467846,"about_ca_system_score_codex":0.000025941687,"about_ca_system_score_gemma":0.00003367038,"threshold_uncertainty_score":0.4946497},"labels":[],"label_agreement":null},{"id":"W2008774262","doi":"10.1016/j.neuroimage.2014.08.057","title":"Framework for integrated MRI average of the spinal cord white and gray matter: The MNI–Poly–AMU template","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Institut pour la Recherche sur la Moelle épinière et l'Encéphale; Agence Nationale de la Recherche; Multiple Sclerosis Society; National Multiple Sclerosis Society","keywords":"Gray (unit); White matter; Spinal cord; Medicine; Nuclear medicine; Neuroscience; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.0454597134860813,"score_gpt":0.3494802753450847,"score_spread":0.3040205618590034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008774262","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22268416,0.00019764742,0.72995454,0.041247603,0.0002842205,0.0023711745,0.00009717492,0.00027875544,0.0028847067],"genre_scores_gemma":[0.97018147,0.00004487646,0.023965105,0.005078585,0.00007495639,0.000082381026,0.0000050291446,0.000040150626,0.0005274357],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991236,0.000050555358,0.00022377989,0.00028383255,0.00012788805,0.00019038512],"domain_scores_gemma":[0.99887896,0.00013644624,0.00014263876,0.0007175831,0.00007015642,0.000054211036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013511328,0.00015133587,0.0002041563,0.000035569115,0.00017309655,0.000024831019,0.00022718089,0.000049628874,0.000022991084],"category_scores_gemma":[0.00014549235,0.0000851223,0.0000926029,0.00020011753,0.00023543336,0.000043470776,0.00009713416,0.00037683762,0.0000067753144],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004005671,0.0009341382,0.2430606,0.0015012163,0.0001457076,0.000036969355,0.00071239716,0.000044584584,0.34287274,0.1462249,0.09171274,0.16874835],"study_design_scores_gemma":[0.0016731331,0.0019051655,0.49760276,0.0007505743,0.0002630173,0.00042607434,0.000060717484,0.0033336012,0.04377681,0.061486527,0.38826287,0.00045873632],"about_ca_topic_score_codex":0.000008752799,"about_ca_topic_score_gemma":0.000001322336,"teacher_disagreement_score":0.7474973,"about_ca_system_score_codex":0.000008482597,"about_ca_system_score_gemma":0.000015415068,"threshold_uncertainty_score":0.34711868},"labels":[],"label_agreement":null},{"id":"W2008839569","doi":"10.1016/j.neurobiolaging.2015.02.022","title":"Superficial white matter as a novel substrate of age-related cognitive decline","year":2015,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas College; McGill University; Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Ontario Mental Health Foundation; Centre for Addiction and Mental Health Foundation; Centre for Addiction and Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Cognitive decline; White matter; Psychology; Gerontology; Medicine; Dementia; Internal medicine; Magnetic resonance imaging; Disease","score_opus":0.07380426568641628,"score_gpt":0.35419184202728377,"score_spread":0.2803875763408675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008839569","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99242646,0.000024823172,0.0012730326,0.0024344577,0.00005631458,0.00025015164,0.000022607559,0.00007249337,0.0034396942],"genre_scores_gemma":[0.99565417,0.000010356838,0.002786801,0.0012213464,0.000027809196,0.000009790969,0.00004727087,0.000020159114,0.0002223226],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920106,0.000026689484,0.0003193943,0.00022900462,0.00006563708,0.0001582382],"domain_scores_gemma":[0.9993662,0.000073291994,0.00014522893,0.0001812168,0.00016860354,0.0000654155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100295,0.000110783505,0.00028784448,0.00009866591,0.000021162923,0.0000020370435,0.00008624984,0.00006744746,0.00004213403],"category_scores_gemma":[0.000055518165,0.000101067526,0.00006075704,0.00017147078,0.00029423487,0.00003456319,0.000072953844,0.00020699106,0.000021589687],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003403434,0.0005319536,0.6460458,0.00008663634,0.00006743341,0.00005785995,0.00067613093,0.00006250592,0.34969252,0.001357394,0.0006502556,0.00043117208],"study_design_scores_gemma":[0.0046278867,0.001262173,0.674059,0.00032619847,0.00027737042,0.0006652254,0.00027573804,0.00020421254,0.31282306,0.00435597,0.0008023462,0.00032084784],"about_ca_topic_score_codex":0.000022321065,"about_ca_topic_score_gemma":0.0000018992498,"teacher_disagreement_score":0.036869477,"about_ca_system_score_codex":0.0000076458255,"about_ca_system_score_gemma":0.000050362578,"threshold_uncertainty_score":0.4121414},"labels":[],"label_agreement":null},{"id":"W2009202887","doi":"10.1016/j.nic.2012.12.002","title":"White Matter Anatomy","year":2013,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Diffusion MRI; White matter; Neuroradiologist; Medicine; Anatomy; Diffusion imaging; Neuroscience; Magnetic resonance imaging; Radiology; Biology","score_opus":0.10557107316373823,"score_gpt":0.43338817946058045,"score_spread":0.32781710629684224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009202887","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004574429,0.99156034,0.0017642789,0.00090332347,0.00017333831,0.0020102966,0.00014879448,0.00038403983,0.003009828],"genre_scores_gemma":[0.000022813769,0.97423685,0.021858763,0.0021107332,0.00014500672,0.00023133442,0.00026151046,0.00019786382,0.0009351236],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99695957,0.00008542711,0.0013452749,0.00086153415,0.00032063518,0.00042755264],"domain_scores_gemma":[0.9964006,0.00030504234,0.0012362658,0.001618937,0.0002043895,0.00023477],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000069525,0.0005662835,0.0023798516,0.00035399394,0.00006815442,0.000026689442,0.0005106092,0.00010890565,0.00021564701],"category_scores_gemma":[0.000102029364,0.00048725915,0.0008483869,0.00082572526,0.00034472797,0.000104555824,0.0002622954,0.0011439726,0.00070637773],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032239273,0.00013054861,0.014628888,0.0045629814,0.00004434533,0.000027558866,0.0000052911,8.6607287e-7,7.630631e-8,0.000005330599,0.014563218,0.9660277],"study_design_scores_gemma":[0.00014163948,0.00009825664,0.0024921678,0.002134385,0.0007914848,0.0001478454,0.0000013357121,0.000045168385,1.7014692e-7,0.000032598433,0.9937827,0.00033227634],"about_ca_topic_score_codex":0.000008733476,"about_ca_topic_score_gemma":2.2152621e-7,"teacher_disagreement_score":0.97921944,"about_ca_system_score_codex":0.000037994414,"about_ca_system_score_gemma":0.0002274433,"threshold_uncertainty_score":0.9997579},"labels":[],"label_agreement":null},{"id":"W2010286633","doi":"10.1016/j.neuroimage.2009.11.039","title":"Group specific optimisation of fMRI processing steps for child and adult data","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Institute for Christian Studies; University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Motion (physics); Preprocessor; Artificial intelligence; Reproducibility; Functional magnetic resonance imaging; Computer science; Nonparametric statistics; Rotation (mathematics); Noise (video); Pattern recognition (psychology); Psychology; Statistics; Mathematics; Computer vision; Neuroscience","score_opus":0.09800500822373821,"score_gpt":0.36397871861428577,"score_spread":0.26597371039054757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010286633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22464328,0.0014810668,0.7126684,0.04076495,0.00008841553,0.0050380463,0.00036735227,0.0010243477,0.01392413],"genre_scores_gemma":[0.85453194,0.0003289805,0.14345613,0.0013039378,0.00009652168,0.00001648523,0.00019212574,0.000021248656,0.000052630603],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992642,0.0000070297942,0.00018083591,0.00033750353,0.00009614716,0.00011432494],"domain_scores_gemma":[0.9992412,0.000023139019,0.00009201321,0.0005244698,0.00007130295,0.000047918817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006164723,0.000089977315,0.00014497792,0.000049651117,0.00007483641,0.000016514197,0.00012241969,0.000024857341,0.0000030798356],"category_scores_gemma":[0.000058837948,0.00008442665,0.000021747763,0.00010887629,0.00005270178,0.00017166365,0.00004123399,0.000104993735,5.736674e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003219953,0.00059286813,0.0008120759,0.0003752593,0.0000069311986,0.000012378111,0.00013207013,0.0000061449823,0.38949576,0.009820121,0.011250811,0.5871736],"study_design_scores_gemma":[0.011300465,0.00441184,0.25688022,0.001322769,0.0005150375,0.001171678,0.00027648732,0.053708516,0.152507,0.020638647,0.49587673,0.0013905873],"about_ca_topic_score_codex":7.358914e-7,"about_ca_topic_score_gemma":1.716251e-7,"teacher_disagreement_score":0.62988865,"about_ca_system_score_codex":0.0000061031865,"about_ca_system_score_gemma":0.0000083709765,"threshold_uncertainty_score":0.34428188},"labels":[],"label_agreement":null},{"id":"W2010675754","doi":"10.1212/01.wnl.0000203412.56752.88","title":"White matter lesions and cognition","year":2006,"lang":"en","type":"letter","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Leukoaraiosis; White matter; Fractional anisotropy; Diffusion MRI; Hyperintensity; Medicine; Dementia; Neurology; Magnetic resonance imaging; Neuroradiology; Cognition; Vascular dementia; Stroke (engine); Psychology; Radiology; Pathology; Psychiatry; Physics; Disease","score_opus":0.04329229764664002,"score_gpt":0.3161124401590012,"score_spread":0.2728201425123612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010675754","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050769937,0.000042243817,0.0011793541,0.9833201,0.000066924345,0.00037228462,0.000046746467,0.00020325858,0.009692085],"genre_scores_gemma":[0.0056066713,0.000040684205,0.0013351686,0.9883109,0.0008018138,0.00010494298,0.0005182675,0.000059874586,0.0032217274],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913394,0.000031421623,0.0001555254,0.00039268754,0.000080423364,0.00020597862],"domain_scores_gemma":[0.99948764,0.000059307382,0.0000732735,0.00031373082,0.000036236655,0.000029816105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000016652772,0.00016291524,0.0002367687,0.000116620446,0.000056259807,0.0000083104105,0.000054383883,0.0003922435,0.00017051044],"category_scores_gemma":[0.000004483232,0.00015417593,0.000048512444,0.000060468625,0.00012933036,0.000018889878,0.00005256305,0.0013366154,0.00013368981],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011351996,0.000014499228,0.006800577,0.000039478935,0.0000039786855,0.00030735,0.000001526634,1.6125368e-7,0.00010051437,0.000016142683,0.9924638,0.000240584],"study_design_scores_gemma":[0.00020066026,0.00018593657,0.05483122,0.000013323254,0.000105092215,0.00088821433,6.902394e-8,0.000013432722,0.000024030154,0.0025219677,0.94111085,0.000105186555],"about_ca_topic_score_codex":0.000007941022,"about_ca_topic_score_gemma":0.000001016438,"teacher_disagreement_score":0.05135297,"about_ca_system_score_codex":0.00000429775,"about_ca_system_score_gemma":0.000012686697,"threshold_uncertainty_score":0.62871116},"labels":[],"label_agreement":null},{"id":"W2010789651","doi":"10.1016/j.nicl.2013.04.002","title":"Assessing a standardised approach to measuring corticospinal integrity after stroke with DTI","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; European Commission; Wellcome Trust","keywords":"Internal capsule; Corticospinal tract; Diffusion MRI; Fractional anisotropy; Region of interest; White matter; Stroke (engine); Voxel; Pyramidal tracts; Psychology; Primary motor cortex; Physical medicine and rehabilitation; Motor cortex; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.25681073015730477,"score_gpt":0.4491802418842155,"score_spread":0.19236951172691075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010789651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78778416,0.00001432232,0.20367602,0.0018820309,0.000048799528,0.0011014066,0.000009849374,0.00035927616,0.005124157],"genre_scores_gemma":[0.8292315,0.000008832572,0.16720702,0.0028276178,0.0001504566,0.00031468246,0.0000055188,0.00005108887,0.00020326713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977976,0.0000959964,0.0005694213,0.0007537046,0.00041286825,0.0003704187],"domain_scores_gemma":[0.9982063,0.0001532357,0.00011723336,0.0007965719,0.0002839877,0.00044265977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032617323,0.00022779254,0.00045745325,0.00007962237,0.00009758219,0.00016093279,0.00017091783,0.000085319276,0.00008203781],"category_scores_gemma":[0.0005105249,0.0001741681,0.00015761337,0.00023350508,0.00020891344,0.00028751936,0.00013216696,0.0010742032,0.00008063329],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002324387,0.005539509,0.826155,0.00029645182,0.00014378545,0.0005824715,0.0001816851,0.00003948287,0.03130232,0.0005632586,0.006611448,0.12626022],"study_design_scores_gemma":[0.0012128844,0.00074385246,0.99120927,0.00011864495,0.00010651176,0.00017442688,0.000051874355,0.001103626,0.0005839294,0.00013822867,0.0043060174,0.00025075043],"about_ca_topic_score_codex":0.00001098619,"about_ca_topic_score_gemma":7.5837556e-7,"teacher_disagreement_score":0.16505428,"about_ca_system_score_codex":0.00004609928,"about_ca_system_score_gemma":0.0001327108,"threshold_uncertainty_score":0.7102369},"labels":[],"label_agreement":null},{"id":"W2011034179","doi":"10.3389/fnhum.2014.00715","title":"Using fMRI non-local means denoising to uncover activation in sub-cortical structures at 1.5 T for guided HARDI tractography","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Functional magnetic resonance imaging; Diffusion MRI; Artificial intelligence; Thalamus; Pattern recognition (psychology); Neuroimaging; Noise reduction; Magnetic resonance imaging; Neuroscience; Computer vision; Psychology; Medicine; Radiology","score_opus":0.08443746703451681,"score_gpt":0.37853514445630126,"score_spread":0.29409767742178444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011034179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46310005,0.0000021875403,0.53612345,0.00016042896,0.000108637345,0.00042984734,0.0000021444678,0.000033588614,0.000039681403],"genre_scores_gemma":[0.9348056,0.0000026890339,0.063665584,0.0013812566,0.000045511682,0.000051049275,0.0000044473577,0.0000241414,0.000019751651],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99855363,0.000033936933,0.0002980726,0.0005382387,0.00023337631,0.00034272904],"domain_scores_gemma":[0.99939716,0.000046846642,0.00007498371,0.00032650906,0.000040613406,0.00011386346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021075211,0.000146151,0.00023633982,0.0003728608,0.00021990908,0.0000309931,0.00018849086,0.000054051998,0.0000012633911],"category_scores_gemma":[0.00024922527,0.00014577806,0.00006407657,0.00060625345,0.000204642,0.00016890561,0.00006487023,0.00021416914,1.226868e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000811791,0.00008555046,0.067586325,0.000032604687,0.0000011270923,0.0000042181923,0.00013108284,0.011827531,0.91445214,0.0009036909,0.0024137942,0.0024807663],"study_design_scores_gemma":[0.0017305445,0.000426989,0.41324598,0.00020956309,0.00003576706,0.000032383323,0.0000578106,0.23998655,0.32246774,0.012292383,0.0090009365,0.00051332806],"about_ca_topic_score_codex":0.000019208916,"about_ca_topic_score_gemma":0.000009829355,"teacher_disagreement_score":0.5919844,"about_ca_system_score_codex":0.0001852516,"about_ca_system_score_gemma":0.000027307766,"threshold_uncertainty_score":0.5944657},"labels":[],"label_agreement":null},{"id":"W2011246142","doi":"10.1016/j.pain.2014.05.026","title":"Diffusion imaging in trigeminal neuralgia reveals abnormal trigeminal nerve and brain white matter","year":2014,"lang":"en","type":"letter","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Ontario Brain Institute; University of Toronto; Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Neurosurgery; Health science; University hospital; Library science; Medicine; Neuroscience; Trigeminal neuralgia; Psychology; Medical education; Family medicine; Psychiatry","score_opus":0.0271682825366193,"score_gpt":0.30762864157266223,"score_spread":0.28046035903604294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011246142","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065973257,0.00025128637,0.025874125,0.96448714,0.00006000201,0.0009683878,0.00003000679,0.00020508801,0.001526639],"genre_scores_gemma":[0.029652996,0.00006146353,0.0068014497,0.9516349,0.0015550384,0.0002377822,0.00047373687,0.00014302724,0.009439623],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975036,0.00044621015,0.0005352078,0.0007031215,0.00027866158,0.0005332059],"domain_scores_gemma":[0.99838454,0.0006291581,0.00023574187,0.0005984214,0.000047133337,0.000105029],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013881112,0.00040589715,0.00059659156,0.0003508542,0.0000883265,0.00004976959,0.00019317234,0.00026661408,0.00019202537],"category_scores_gemma":[0.00021097646,0.00036735623,0.0001221167,0.00021097506,0.00012949978,0.000080478545,0.00012073641,0.0017159521,0.000036625068],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003304185,0.000026867354,0.093683325,0.0003243063,0.0000033200804,0.00062126725,0.000046085108,2.4618873e-7,0.0011026699,0.0000097456905,0.89458615,0.009562986],"study_design_scores_gemma":[0.0010455174,0.00011169951,0.053558078,0.0010755936,0.00009049902,0.0011350953,0.000015873546,0.0023756444,0.00007838703,0.0014378849,0.9384728,0.00060293375],"about_ca_topic_score_codex":0.00003514463,"about_ca_topic_score_gemma":0.0000011202228,"teacher_disagreement_score":0.043886658,"about_ca_system_score_codex":0.0000785543,"about_ca_system_score_gemma":0.0000267591,"threshold_uncertainty_score":0.9998778},"labels":[],"label_agreement":null},{"id":"W2011842664","doi":"10.1016/j.neuroimage.2006.10.041","title":"An unbiased iterative group registration template for cortical surface analysis","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":417,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Gyrification; Template; Computer science; Artificial intelligence; Laterality; Lateralization of brain function; Pattern recognition (psychology); Set (abstract data type); Surface (topology); Computer vision; Mathematics; Psychology; Cerebral cortex; Neuroscience; Geometry","score_opus":0.08922525473517356,"score_gpt":0.4146023594206589,"score_spread":0.3253771046854853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011842664","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37805727,0.000005963955,0.6198562,0.0005872795,0.000017801003,0.0004971169,0.000029359813,0.00023136332,0.00071769237],"genre_scores_gemma":[0.9039759,0.000006202941,0.09452591,0.0009228637,0.00006473557,0.000021606764,0.0002196531,0.00002547959,0.00023761384],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99886566,0.000029806368,0.00029071988,0.000420223,0.00015609768,0.00023747678],"domain_scores_gemma":[0.99893034,0.0001946779,0.000099592085,0.0005014909,0.000118540745,0.00015537586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027410837,0.000131932,0.00022419491,0.00010591936,0.00014447456,0.00003539178,0.00008488972,0.00004824977,0.000020148724],"category_scores_gemma":[0.00009910893,0.00012573547,0.00012927623,0.000536744,0.00008046276,0.00014896692,0.0000116773645,0.00018918025,0.000004424542],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047351728,0.00051054097,0.016711934,0.000030489675,0.00007225047,0.0001037926,0.00009328229,0.00013813768,0.9720858,0.0059705195,0.0014118982,0.0023978557],"study_design_scores_gemma":[0.0030107878,0.0027088865,0.71504027,0.000038246228,0.0019173439,0.0001409313,0.000117974734,0.06763953,0.17156667,0.0025721393,0.03454901,0.0006982238],"about_ca_topic_score_codex":0.000010876993,"about_ca_topic_score_gemma":0.000017095654,"teacher_disagreement_score":0.8005191,"about_ca_system_score_codex":0.000028508042,"about_ca_system_score_gemma":0.000015981086,"threshold_uncertainty_score":0.5127344},"labels":[],"label_agreement":null},{"id":"W2011879949","doi":"10.1017/s1355617708080533","title":"Regional atrophy of the corpus callosum in dementia","year":2008,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Corpus callosum; Dementia; Atrophy; Psychology; Medicine; Cognitive impairment; Audiology; Magnetic resonance imaging; Cognition; Disease; Neuroscience; Internal medicine; Radiology","score_opus":0.10458125889835851,"score_gpt":0.356042039643284,"score_spread":0.2514607807449255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011879949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96615297,0.00007097961,0.0007382566,0.031942915,0.00032779863,0.00011711905,0.0000034096493,0.000008130969,0.000638421],"genre_scores_gemma":[0.98944503,0.000343869,0.003585022,0.00625992,0.00013220012,0.0000025898462,3.596588e-7,0.0000068340446,0.00022415453],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989468,0.000038718827,0.00038618728,0.00010561625,0.00043734998,0.000085317435],"domain_scores_gemma":[0.9991607,0.00006569043,0.0003813486,0.00019785836,0.00016071269,0.000033656772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001255886,0.00007078755,0.00013624846,0.000018144054,0.0000618124,0.0000036751114,0.00053542596,0.000040391413,0.000031627067],"category_scores_gemma":[0.00011128345,0.00003505557,0.00045996052,0.00018704472,0.00024182232,0.00003777197,0.00011655715,0.00048310077,9.373361e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048336526,0.0013501974,0.73035514,0.000010876083,0.00017419933,0.00008614076,0.00016444395,0.00035078093,0.1861699,0.0025958486,0.07714781,0.0011112647],"study_design_scores_gemma":[0.00070141436,0.000100500074,0.964907,0.000044941124,0.000022655555,0.0014806302,0.000008088583,0.000119104065,0.0013325667,0.0022502984,0.028994856,0.000037953654],"about_ca_topic_score_codex":0.0000032925545,"about_ca_topic_score_gemma":2.9835454e-7,"teacher_disagreement_score":0.23455182,"about_ca_system_score_codex":0.000043277814,"about_ca_system_score_gemma":0.000039112892,"threshold_uncertainty_score":0.20988593},"labels":[],"label_agreement":null},{"id":"W2011955966","doi":"10.1016/j.neuropsychologia.2013.03.014","title":"Functional organisation of visual pathways in a patient with no optic chiasm","year":2013,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canada Research Chairs","keywords":"Neuroscience; Psychology; Visual cortex; Retinotopy; Optic chiasm; Corpus callosum; Cortex (anatomy); Decussation; Visual system; Functional magnetic resonance imaging; Retina; Anatomy; Optic nerve; Medicine","score_opus":0.0428630383913633,"score_gpt":0.3065219515066142,"score_spread":0.2636589131152509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011955966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935795,0.0000049514,0.0021541482,0.00043655417,0.000041388255,0.0004856138,0.0000018447065,0.00010212293,0.00319386],"genre_scores_gemma":[0.9898489,0.000007093254,0.009191161,0.0007497321,0.000023572577,0.000097947624,0.000011603097,0.000018131757,0.000051830757],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999334,0.00001733466,0.00018347755,0.00022224215,0.00012831857,0.00011464268],"domain_scores_gemma":[0.9995471,0.000026207526,0.00007940231,0.00021433989,0.00009182953,0.000041070864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000024073768,0.00008667317,0.000119326236,0.000075331816,0.00001984439,0.0000047773133,0.000041395313,0.00003194277,0.00022195106],"category_scores_gemma":[0.000034512836,0.00006567237,0.000020725083,0.00019613231,0.00005760354,0.000055323268,0.000018818831,0.00016007827,0.00011373138],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030383747,0.0016599811,0.059743047,0.000045627065,0.000011547029,0.00010243503,0.00017384192,0.00006459227,0.91247165,0.0016071605,0.0037556777,0.02006061],"study_design_scores_gemma":[0.0008877697,0.0019758039,0.9868198,0.00003946558,0.000010928077,0.0002933682,0.00003429182,0.00047437203,0.008340264,0.00050172705,0.0005131433,0.00010905968],"about_ca_topic_score_codex":0.0000070578726,"about_ca_topic_score_gemma":2.1230588e-7,"teacher_disagreement_score":0.92707676,"about_ca_system_score_codex":0.000016451604,"about_ca_system_score_gemma":0.00001869041,"threshold_uncertainty_score":0.26780415},"labels":[],"label_agreement":null},{"id":"W2012658403","doi":"10.1249/01.mss.0000355604.40179.ef","title":"Use Of Diffusion Tensor Magnetic Resonance Imaging For Assessment Of Musculoskeletal Structure Following High-force Eccentric Exercise: A Case Study","year":2009,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Magnetic resonance imaging; Medicine; Diffusion MRI; Isometric exercise; Eccentric; Skeletal muscle; Anatomy; Physical medicine and rehabilitation; Radiology; Physical therapy; Physics","score_opus":0.030806539661709906,"score_gpt":0.36364710678208717,"score_spread":0.33284056712037724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012658403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941046,0.00034641934,0.0017269786,0.00045881563,0.00013346647,0.0031260638,0.0000110518195,0.000070601716,0.000021990023],"genre_scores_gemma":[0.9757863,0.00018892215,0.023669012,0.00009221281,0.000038457223,0.00008930905,0.000009086223,0.000022899994,0.000103771716],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969682,0.000016954265,0.00084482855,0.00072469754,0.0009780951,0.0004672283],"domain_scores_gemma":[0.99826103,0.00009058807,0.00032700686,0.00084359344,0.00028998897,0.00018781368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006564708,0.00027120195,0.0008055789,0.00064286706,0.00017449119,0.000012782458,0.00028478712,0.000040499504,0.000026426407],"category_scores_gemma":[0.00021457944,0.00020960231,0.00011213129,0.0018080636,0.00046282768,0.00032894313,0.00008639613,0.00023854428,7.303674e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008025491,0.0006673049,0.6897457,0.0000830482,2.6455714e-7,0.001360124,0.0006073593,0.00006943127,0.011424714,0.00002362229,0.0000692715,0.29586887],"study_design_scores_gemma":[0.0021572958,0.0008769571,0.9863689,0.0013497318,0.00027019356,0.0003073686,0.0013755345,0.0061350144,0.0003042968,0.0005219905,0.000121530735,0.00021116534],"about_ca_topic_score_codex":0.0003138737,"about_ca_topic_score_gemma":0.000007245173,"teacher_disagreement_score":0.2966232,"about_ca_system_score_codex":0.00011326287,"about_ca_system_score_gemma":0.00017038727,"threshold_uncertainty_score":0.8547334},"labels":[],"label_agreement":null},{"id":"W2012970094","doi":"10.1007/s00381-010-1189-8","title":"Mapping of the cortical spinal tracts using magnetoencephalography and diffusion tensor tractography in pediatric brain tumor patients","year":2010,"lang":"en","type":"article","venue":"Child s Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Tractography; Magnetoencephalography; Diffusion MRI; Medicine; Corticospinal tract; White matter; Brain tumor; Cortex (anatomy); Motor cortex; Pyramidal tracts; Neurosurgery; Magnetic resonance imaging; Fiber tract; Neuroscience; Radiology; Anatomy; Pathology; Electroencephalography; Psychology","score_opus":0.020060007233097688,"score_gpt":0.2726924076174076,"score_spread":0.2526324003843099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2012970094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979535,0.00007535612,0.00048251156,0.00035428503,0.00009442274,0.0007548624,0.000008586494,0.00006798535,0.00020850508],"genre_scores_gemma":[0.9974039,0.000009435638,0.002288557,0.0001716148,0.00008272098,0.000019879193,0.0000026074356,0.000019303667,0.0000019813624],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989562,0.000034860892,0.00035744804,0.00026259315,0.00019106864,0.00019781524],"domain_scores_gemma":[0.9993191,0.000041761163,0.00017942223,0.00031531334,0.00005430769,0.0000901387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010689308,0.00013539255,0.00024244461,0.00023688185,0.00012980572,0.000010146105,0.00011215875,0.000060482267,0.000001310323],"category_scores_gemma":[0.000065616216,0.00009591187,0.00010203716,0.00057449477,0.00012125298,0.00004810855,0.000051152503,0.00045965033,3.1532275e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000290003,0.00024996712,0.98057675,0.00034849084,0.000003054887,0.000010321519,0.00010815738,0.0000034099144,0.017200198,0.00058574317,0.000009890685,0.0008750196],"study_design_scores_gemma":[0.0006900446,0.00009676708,0.9976971,0.0003207543,0.000033411838,0.00019381648,0.00007616165,0.00036094047,0.00028705347,0.000061949846,0.00009052689,0.00009147075],"about_ca_topic_score_codex":0.000034172474,"about_ca_topic_score_gemma":0.000006756666,"teacher_disagreement_score":0.017120356,"about_ca_system_score_codex":0.00001736656,"about_ca_system_score_gemma":0.000025411364,"threshold_uncertainty_score":0.39111724},"labels":[],"label_agreement":null},{"id":"W2013013539","doi":"10.1016/j.neuroscience.2006.08.080","title":"Development of a high resolution three-dimensional surgical atlas of the murine head for strains 129S1/SvImJ and C57Bl/6J using magnetic resonance imaging and micro-computed tomography","year":2006,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Skull; Brain atlas; Atlas (anatomy); Coordinate system; Surgical planning; Magnetic resonance imaging; Computer science; Neuroscience; Anatomy; Biology; Medicine; Computer vision; Radiology","score_opus":0.04056885429120004,"score_gpt":0.3086936459224558,"score_spread":0.26812479163125574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013013539","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98795307,0.0005550554,0.010474227,0.00048896845,0.00004138901,0.00042834604,0.000019364054,0.000028487393,0.000011109065],"genre_scores_gemma":[0.861624,0.0000072574376,0.13822696,0.000088704124,0.000018072751,0.000011222821,0.0000018707589,0.000007896836,0.0000140375905],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99909216,0.000012332831,0.00024525032,0.0003077912,0.00017801036,0.00016446786],"domain_scores_gemma":[0.99956334,0.000046453017,0.00010373272,0.0001797384,0.00006865687,0.000038073707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102336664,0.000094458264,0.00014627897,0.000070894544,0.00017184754,0.00000813604,0.000087940556,0.000018450146,4.7070824e-7],"category_scores_gemma":[0.000020663963,0.0000731923,0.000032674125,0.00033842996,0.0004648699,0.000047645848,0.00010445772,0.00007644242,1.7282973e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006441546,0.00015990506,0.058940765,0.00007412993,6.2144755e-7,0.000006192524,0.000025649328,0.00012501919,0.92802155,0.0020505742,0.000056573626,0.010474611],"study_design_scores_gemma":[0.0007599535,0.00008436908,0.9266015,0.0001626192,0.000015305981,0.00020521962,0.0000025672737,0.028185172,0.03844816,0.0009815537,0.0044605024,0.00009308033],"about_ca_topic_score_codex":0.000043064625,"about_ca_topic_score_gemma":0.000011353904,"teacher_disagreement_score":0.8895734,"about_ca_system_score_codex":0.00001206067,"about_ca_system_score_gemma":0.000056146695,"threshold_uncertainty_score":0.2984695},"labels":[],"label_agreement":null},{"id":"W2013160622","doi":"10.1016/j.media.2013.03.009","title":"Tractometer: Towards validation of tractography pipelines","year":2013,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":236,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Artificial intelligence; Seeding; Pattern recognition (psychology); Computer vision; Mathematics; Diffusion MRI; Engineering; Magnetic resonance imaging","score_opus":0.04430028071975608,"score_gpt":0.3782283427137563,"score_spread":0.33392806199400027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013160622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5676335,0.000082703096,0.4217497,0.008003238,0.00001484765,0.0002840244,0.000009957248,0.00017417036,0.0020478433],"genre_scores_gemma":[0.96484166,0.00015495888,0.034038648,0.00058151555,0.00005709708,0.00006138909,0.000089170346,0.000012250186,0.00016330059],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99869597,0.000026916905,0.00039439366,0.00022579618,0.00051125424,0.00014565827],"domain_scores_gemma":[0.9989781,0.000068248264,0.00012074843,0.00037990787,0.00024992783,0.00020307442],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017694487,0.00010442169,0.0003765496,0.00045679178,0.000028751223,0.000014365214,0.0001307727,0.00007100028,0.0027279195],"category_scores_gemma":[0.00034838569,0.00007989846,0.00037709024,0.0016977988,0.00014987316,0.00014001716,0.00002742389,0.00017488266,0.000029224275],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049457147,0.002442563,0.12154736,0.00024029338,0.0021861065,0.000073192576,0.00026946227,0.00001439045,0.2814159,0.00026651038,0.014260258,0.5772345],"study_design_scores_gemma":[0.0016016376,0.00033749102,0.47920343,0.00011856545,0.0062377597,0.00006589269,0.00017807036,0.019640377,0.47438848,0.0036198432,0.014055159,0.0005532997],"about_ca_topic_score_codex":0.00017975902,"about_ca_topic_score_gemma":0.0000016620709,"teacher_disagreement_score":0.5766812,"about_ca_system_score_codex":0.000009040467,"about_ca_system_score_gemma":0.000031334825,"threshold_uncertainty_score":0.9981837},"labels":[],"label_agreement":null},{"id":"W2013162191","doi":"10.1016/j.neuroimage.2007.07.033","title":"Evidence of slow maturation of the superior longitudinal fasciculus in early childhood by diffusion tensor imaging","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"Neuroscience; Diffusion MRI; Superior longitudinal fasciculus; White matter; Tractography; Fiber tract; Myelin; Inferior longitudinal fasciculus; Uncinate fasciculus; Population; Fasciculus; Biology; Medial longitudinal fasciculus; Psychology; Anatomy; Fractional anisotropy; Central nervous system; Medicine; Magnetic resonance imaging","score_opus":0.036335385181827946,"score_gpt":0.3188146849552961,"score_spread":0.28247929977346814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013162191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99349785,0.00022574187,0.0037852614,0.0016478924,0.000039519546,0.000506783,0.000008252493,0.00004931428,0.00023938429],"genre_scores_gemma":[0.99753857,0.00007305116,0.0019889008,0.00025491742,0.000024593157,0.000009504968,0.0000025014315,0.000019206647,0.000088749104],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989377,0.000026633688,0.000349828,0.00025471675,0.0002530292,0.00017807735],"domain_scores_gemma":[0.9991798,0.00009898635,0.00014818912,0.00044649842,0.00008405567,0.000042472413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016623933,0.000112049136,0.00019103757,0.00008432564,0.00004883652,0.000008061342,0.00016298346,0.000027831056,0.000009117306],"category_scores_gemma":[0.0001992574,0.00008238578,0.00007934199,0.00038707777,0.00013686737,0.00015157333,0.00008582371,0.00024055805,0.0000019035667],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006121611,0.00014585203,0.31185222,0.00003335095,0.0000012262858,0.0000115554185,0.00011084771,0.0000013452927,0.68370354,0.000050173716,0.00020056237,0.0038281197],"study_design_scores_gemma":[0.0003081283,0.00007237681,0.8751322,0.00026864954,0.000017770502,0.000050960487,0.000021135333,0.00014875471,0.123719454,0.00007550645,0.00012765457,0.000057427187],"about_ca_topic_score_codex":0.00005276102,"about_ca_topic_score_gemma":0.000003649634,"teacher_disagreement_score":0.5632799,"about_ca_system_score_codex":0.000024932036,"about_ca_system_score_gemma":0.000024179664,"threshold_uncertainty_score":0.33595943},"labels":[],"label_agreement":null},{"id":"W2013322489","doi":"10.1016/j.eplepsyres.2013.12.001","title":"Bilateral white matter abnormality in children with frontal lobe epilepsy","year":2013,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"Splenium; Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Epilepsy; Medicine; Abnormality; Frontal lobe; Lateralization of brain function; Cardiology; Ictal; Psychology; Internal medicine; Magnetic resonance imaging; Audiology; Neuroscience; Anatomy; Psychiatry; Radiology","score_opus":0.06578619303712097,"score_gpt":0.38007455127018824,"score_spread":0.3142883582330673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013322489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9817671,0.000033336597,0.00062928605,0.006523017,0.000012032765,0.0016679994,0.000014228208,0.00012148612,0.009231523],"genre_scores_gemma":[0.9874846,0.000027486956,0.007766609,0.0006591598,0.0001137623,0.00057310524,0.000058023743,0.000044533936,0.0032727723],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99798524,0.00011413372,0.00027268755,0.0004912288,0.0004845284,0.00065219507],"domain_scores_gemma":[0.99880624,0.0000496182,0.000038879847,0.0007164042,0.00017831405,0.00021057014],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00042532317,0.00016210822,0.0002536564,0.00026863566,0.00012254385,0.000059982136,0.00024355187,0.000078782454,0.0020238978],"category_scores_gemma":[0.000021799266,0.00012275207,0.000049926526,0.00054667826,0.0002670709,0.00023848566,0.00016164895,0.00090099446,0.0012641473],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058232945,0.0001803674,0.98216575,0.000014671634,0.00001071524,0.000020228761,0.000067953966,0.0000030942442,0.00053153886,0.00012064602,0.015782548,0.0010442485],"study_design_scores_gemma":[0.0007373296,0.00021430866,0.995386,0.00006078593,0.0000052296677,0.00024161108,0.00003144836,0.00015050422,0.0006098177,0.001123919,0.0013012985,0.00013776773],"about_ca_topic_score_codex":0.00078532915,"about_ca_topic_score_gemma":0.000023912098,"teacher_disagreement_score":0.014481249,"about_ca_system_score_codex":0.00011221425,"about_ca_system_score_gemma":0.0000655259,"threshold_uncertainty_score":0.9995135},"labels":[],"label_agreement":null},{"id":"W2013700088","doi":"10.1007/s00381-007-0466-7","title":"Preserved structural integrity of white matter adjacent to low-grade tumors","year":2007,"lang":"en","type":"article","venue":"Child s Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"Epilepsy Society; Göteborgs Läkaresällskap; University of Toronto; Johns Hopkins University","keywords":"Medicine; White matter; Tractography; Fractional anisotropy; Magnetic resonance imaging; Diffusion MRI; Hyperintensity; Pyramidal tracts; Pathology; Nuclear medicine; Radiology; Anatomy","score_opus":0.03603578317029175,"score_gpt":0.3228802208097341,"score_spread":0.28684443763944234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2013700088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9805161,0.00006443945,0.010715143,0.0025673432,0.000092184964,0.0010642832,0.000025621246,0.00028610686,0.0046688234],"genre_scores_gemma":[0.99232274,0.0000012699384,0.0064573647,0.0006148346,0.00014730832,0.00003074881,0.00001603048,0.000033721186,0.0003759802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987408,0.000022269947,0.00043390703,0.00030141964,0.00021837781,0.00028324907],"domain_scores_gemma":[0.9989277,0.00002502854,0.0001302009,0.00062912185,0.00009570077,0.00019222114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016211673,0.00016303537,0.00033607296,0.000108578846,0.00011276677,0.00000761471,0.00019135143,0.000058077236,0.000028495708],"category_scores_gemma":[0.000018952675,0.00013153418,0.000105052786,0.00022828225,0.000042837848,0.00004162289,0.00012792283,0.000286559,0.000027379803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048356556,0.00036861154,0.93596643,0.003459652,0.000096072945,0.00018878779,0.0017923134,0.00020643008,0.030157374,0.009048713,0.01552904,0.0027029917],"study_design_scores_gemma":[0.00051714346,0.000118002594,0.9574653,0.0011820944,0.000039729413,0.00044160595,0.00031565005,0.0002777296,0.036171287,0.00007912847,0.003179502,0.00021285376],"about_ca_topic_score_codex":0.000056028177,"about_ca_topic_score_gemma":0.0000100903,"teacher_disagreement_score":0.021498825,"about_ca_system_score_codex":0.00010236478,"about_ca_system_score_gemma":0.000018229664,"threshold_uncertainty_score":0.5363808},"labels":[],"label_agreement":null},{"id":"W2014773891","doi":"10.1002/mrm.20839","title":"Exploratory data analysis reveals visuovisual interhemispheric transfer in functional magnetic resonance imaging","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; Dalhousie University","funders":"","keywords":"Corpus callosum; Functional magnetic resonance imaging; Visual field; Splenium; Psychology; Neuroscience; Magnetic resonance imaging; White matter","score_opus":0.06520448534042662,"score_gpt":0.34690002665317227,"score_spread":0.28169554131274566,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014773891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.681252,0.24382822,0.045574497,0.015016277,0.00029674426,0.0027046169,0.00012312068,0.0006207312,0.010583781],"genre_scores_gemma":[0.98589,0.0016511851,0.0071503352,0.001597258,0.00034974673,0.00032645618,0.00029908257,0.00006669408,0.0026692757],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966168,0.0001046243,0.0010282958,0.0011177879,0.00058257626,0.00054993056],"domain_scores_gemma":[0.9980473,0.00020646855,0.00007528951,0.0014475031,0.00010048584,0.00012294453],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006244791,0.000348126,0.000779377,0.00053103373,0.00006568154,0.000016779735,0.00048653947,0.000085812695,0.000656638],"category_scores_gemma":[0.000168103,0.00031840702,0.00008073438,0.00282741,0.00045081877,0.00019548972,0.00013904522,0.0005489366,0.000013090972],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004346524,0.00065547763,0.7446652,0.00012093119,0.000008351123,0.0006236889,0.00023171879,0.000086137195,0.019162804,0.00088746473,0.017940132,0.21518342],"study_design_scores_gemma":[0.0029766455,0.00027905643,0.88058895,0.0006236,0.00021188057,0.00008245807,0.00018257998,0.017589731,0.00024031405,0.0013440044,0.09554142,0.00033937552],"about_ca_topic_score_codex":0.0004719224,"about_ca_topic_score_gemma":0.00024894602,"teacher_disagreement_score":0.30463794,"about_ca_system_score_codex":0.00014755488,"about_ca_system_score_gemma":0.000080098675,"threshold_uncertainty_score":0.9999268},"labels":[],"label_agreement":null},{"id":"W2015088173","doi":"10.1016/j.neuroimage.2008.07.038","title":"Quantifying development: Investigating highly myelinated voxels in preadolescent corpus callosum","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Voxel; Corpus callosum; White matter; Psychology; Correlation; Wechsler Adult Intelligence Scale; Audiology; Mathematics; Cognition; Artificial intelligence; Neuroscience; Medicine; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.2040757350056761,"score_gpt":0.3643571969460059,"score_spread":0.16028146194032977,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015088173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99373186,0.00008286541,0.0026958927,0.001214079,0.000052895764,0.00057013985,0.0000035612768,0.0005257353,0.0011229478],"genre_scores_gemma":[0.95934016,0.00009092741,0.03876,0.0013466816,0.00004196799,0.000059938146,0.000026473033,0.000053229123,0.0002806063],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99844074,0.000039054143,0.00043974546,0.00047362116,0.00025153498,0.00035531522],"domain_scores_gemma":[0.9991891,0.000054979082,0.00011569173,0.00040810934,0.00007678108,0.00015536013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010368577,0.00020262632,0.00027845765,0.00017422857,0.00017528163,0.000013323899,0.00014383173,0.000059995593,0.0000086007185],"category_scores_gemma":[0.00019343865,0.0002037064,0.000048262787,0.0004692757,0.000117304386,0.00011474389,0.000098287026,0.00046929732,0.00004258557],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051361672,0.0004729555,0.4035586,0.0001976661,0.000009430438,0.0011857662,0.0006235372,0.000054910503,0.58154446,0.0006634062,0.0010528876,0.010585008],"study_design_scores_gemma":[0.001492693,0.00010788854,0.79166776,0.00042689586,0.000018892746,0.0006966177,0.000019217972,0.0025013639,0.17823713,0.00018794989,0.024247002,0.00039658567],"about_ca_topic_score_codex":0.000026076885,"about_ca_topic_score_gemma":0.000009709313,"teacher_disagreement_score":0.40330735,"about_ca_system_score_codex":0.00007749668,"about_ca_system_score_gemma":0.00013161864,"threshold_uncertainty_score":0.83069056},"labels":[],"label_agreement":null},{"id":"W2015100231","doi":"10.1016/j.neuroimage.2013.05.080","title":"Structural connectivity of visuotopic intraparietal sulcus","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Hotchkiss Brain Institute; Health Research Board","keywords":"Intraparietal sulcus; Neuroscience; Posterior parietal cortex; Psychology; Functional magnetic resonance imaging; Functional specialization; Retinotopy; Cortex (anatomy); Parietal lobe; Superior temporal gyrus; Cytoarchitecture; Visual cortex","score_opus":0.05488832759881571,"score_gpt":0.3393625634760009,"score_spread":0.2844742358771852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015100231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992891,0.000018053572,0.0017421137,0.0014609759,0.000043887947,0.0005107038,0.00000681811,0.00017121923,0.0031552054],"genre_scores_gemma":[0.9948759,0.000009053008,0.0043342025,0.00043465337,0.00004544778,0.000040868174,0.000006410735,0.00001762956,0.00023581868],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993356,0.000017107786,0.00016825667,0.0002159317,0.000113419155,0.00014972342],"domain_scores_gemma":[0.99936104,0.000050557705,0.00006774133,0.000363703,0.00008379801,0.000073162875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000025047653,0.00009900444,0.00018643732,0.00004658726,0.000041592306,0.000011114617,0.00008206441,0.000030172183,0.00021285845],"category_scores_gemma":[0.00007266536,0.000085283085,0.00006517433,0.00013606936,0.00012820654,0.0001165584,0.0000478682,0.00017869964,0.000027415075],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029404922,0.00012844933,0.054504965,0.00008748442,0.0000134222755,0.000024541436,0.000054301046,0.000003579803,0.91008425,0.005758457,0.0027354932,0.02657568],"study_design_scores_gemma":[0.0006439532,0.00028563922,0.8579874,0.00001884268,0.00003272607,0.00015957918,0.000012588378,0.0018248613,0.13014112,0.005325517,0.0034226908,0.00014508706],"about_ca_topic_score_codex":0.00004479697,"about_ca_topic_score_gemma":6.4104734e-7,"teacher_disagreement_score":0.8034824,"about_ca_system_score_codex":0.0000105079325,"about_ca_system_score_gemma":0.000018262988,"threshold_uncertainty_score":0.34777433},"labels":[],"label_agreement":null},{"id":"W2015120800","doi":"10.1016/j.neuroimage.2006.03.036","title":"Reproducibility and reliability of MR measurements in white matter: Clinical implications","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Multiple Sclerosis Society","keywords":"Reproducibility; Reliability (semiconductor); White matter; Magnetization transfer; Nuclear magnetic resonance; Repeatability; Coefficient of variation; Nuclear medicine; Chemistry; Magnetic resonance imaging; Statistics; Mathematics; Physics; Medicine; Radiology; Thermodynamics","score_opus":0.1300008462921184,"score_gpt":0.40965703221596395,"score_spread":0.27965618592384556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015120800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98341316,0.00002831885,0.0012338076,0.010241634,0.000021197624,0.0006372012,0.000016769844,0.00008760485,0.004320287],"genre_scores_gemma":[0.98578745,0.00002359326,0.013440185,0.00047586203,0.000033419274,0.000043443848,0.000010568602,0.00001573352,0.00016973831],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99815214,0.0000781949,0.00059433206,0.0009187973,0.000117677875,0.00013883307],"domain_scores_gemma":[0.99780405,0.00007524694,0.00012352897,0.001834733,0.00011011709,0.00005230443],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087445934,0.00009652614,0.0002544884,0.000056194123,0.000031904725,0.0000058967253,0.00008308465,0.000041063056,0.00001710281],"category_scores_gemma":[0.00042506715,0.000091584625,0.000061203275,0.00022122334,0.00019770424,0.000066431305,0.00007366941,0.00021485802,0.000006100746],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002558209,0.00039909733,0.98273534,0.000041040534,7.4314204e-7,0.0000011314035,0.0000042118304,0.0000035280543,0.014412269,0.000089052584,0.001625788,0.000662203],"study_design_scores_gemma":[0.00037854398,0.00005956627,0.99059117,0.000017769078,0.000017208926,0.000017143117,0.00000116318,0.00003297688,0.0026767526,0.004674641,0.0014733428,0.000059735034],"about_ca_topic_score_codex":0.000047923484,"about_ca_topic_score_gemma":0.000005932822,"teacher_disagreement_score":0.012206377,"about_ca_system_score_codex":0.000021591008,"about_ca_system_score_gemma":0.000025888432,"threshold_uncertainty_score":0.37347126},"labels":[],"label_agreement":null},{"id":"W2015151082","doi":"10.1016/j.neuroimage.2004.07.045","title":"Cortical thickness analysis examined through power analysis and a population simulation","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":722,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Reproducibility; Smoothing; Population; Gaussian; Mathematics; Statistical power; Sensitivity (control systems); Statistics; Physics","score_opus":0.05721126659594612,"score_gpt":0.37907689528163796,"score_spread":0.32186562868569185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015151082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5796494,0.0000172837,0.41871595,0.0007146008,0.000010161871,0.000216458,0.000008079725,0.00019961126,0.0004684505],"genre_scores_gemma":[0.97734666,0.000021923575,0.021553226,0.0008411527,0.000023505008,0.000018327124,0.000107442414,0.000019788533,0.000068003894],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988445,0.000035768615,0.00027253368,0.00045152463,0.00022229044,0.00017340327],"domain_scores_gemma":[0.9991564,0.00010316848,0.000092639595,0.00047528162,0.000083835075,0.00008866995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079879006,0.00014578353,0.00034851948,0.00030532014,0.00012958016,0.000033472712,0.000055000648,0.000059576305,0.000044933127],"category_scores_gemma":[0.0001451786,0.00013490752,0.00017762835,0.002106191,0.000072477094,0.00017350011,0.000041809122,0.00020786855,0.000005472854],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039971934,0.001090143,0.81789654,0.00008366704,0.0020437087,0.00025376046,0.0007975507,0.09575767,0.0618885,0.013964399,0.000035612127,0.0057886927],"study_design_scores_gemma":[0.0004487646,0.00008699226,0.975711,0.000005954183,0.0034948941,0.000015085793,0.0000110106175,0.017385203,0.0005701005,0.0018386594,0.0003052566,0.00012710661],"about_ca_topic_score_codex":0.00010672538,"about_ca_topic_score_gemma":0.000014949936,"teacher_disagreement_score":0.39769724,"about_ca_system_score_codex":0.00003804724,"about_ca_system_score_gemma":0.000013069083,"threshold_uncertainty_score":0.55013686},"labels":[],"label_agreement":null},{"id":"W2015159159","doi":"10.1111/epi.12581","title":"Disrupted anatomic white matter network in left mesial temporal lobe epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; University of Alberta","keywords":"White matter; Diffusion MRI; Tractography; Precuneus; Temporal lobe; Epilepsy; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.0237875007295809,"score_gpt":0.315016801856946,"score_spread":0.2912293011273651,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015159159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8333332,0.00011480064,0.1104323,0.021825982,0.0003239518,0.0014484989,0.000018286752,0.0008230244,0.031679958],"genre_scores_gemma":[0.9742166,0.00001995234,0.020607907,0.0034116246,0.0003730803,0.000048056365,0.000064701184,0.000050275718,0.0012078509],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986639,0.0000572559,0.00034787087,0.0003938921,0.00014992004,0.00038714334],"domain_scores_gemma":[0.99912596,0.000052945088,0.00009500231,0.00056646584,0.00003093113,0.00012869955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020318502,0.00018780708,0.00033408406,0.00009852748,0.00006898937,0.000017849026,0.00015025117,0.00008769977,0.00057210104],"category_scores_gemma":[0.000027547625,0.00017433638,0.00008638674,0.00025618167,0.00008196979,0.000082900726,0.00006808308,0.00033919892,0.00027538577],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000538575,0.00007127541,0.94743264,0.000018287858,0.000005165367,0.000017612849,0.00003956359,0.00006177085,0.0002987539,0.0019982425,0.048626084,0.0013767345],"study_design_scores_gemma":[0.00077877706,0.000083517894,0.8872424,0.00009427867,0.00002356856,0.00007960005,0.000008526362,0.0039042342,0.00019360713,0.0055966787,0.101780966,0.00021388609],"about_ca_topic_score_codex":0.000021186263,"about_ca_topic_score_gemma":0.0000133312715,"teacher_disagreement_score":0.14088336,"about_ca_system_score_codex":0.000056652687,"about_ca_system_score_gemma":0.000025772197,"threshold_uncertainty_score":0.71092314},"labels":[],"label_agreement":null},{"id":"W2015504855","doi":"10.1016/s0221-0363(07)89845-3","title":"Imagerie de diffusion : principes et applications cliniques","year":2007,"lang":"fr","type":"article","venue":"Journal de Radiologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ste. Anne's Hospital","funders":"","keywords":"Medicine; Nuclear medicine; Abscess; Diffusion MRI; Radiology; Magnetic resonance imaging; Surgery","score_opus":0.10111008318735644,"score_gpt":0.4514325129580886,"score_spread":0.3503224297707322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015504855","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022547845,0.012711761,0.93494743,0.019288125,0.00031328615,0.00054257433,0.000019289113,0.00031083642,0.009318824],"genre_scores_gemma":[0.202369,0.08243128,0.69454736,0.00860163,0.004766514,0.0001436034,0.000022780676,0.00009858566,0.0070192697],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978104,0.00018359286,0.0006724209,0.00030383875,0.00017120296,0.0008584944],"domain_scores_gemma":[0.99778384,0.0007291616,0.0003598997,0.00044062725,0.00016332573,0.0005231457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026895127,0.00023590622,0.00034384942,0.00015525024,0.00032077738,0.00007364987,0.00031607336,0.0002655434,0.00010392619],"category_scores_gemma":[0.00055269606,0.00021290188,0.00021769071,0.00026407724,0.00031241178,0.00019104341,0.00010607525,0.0014986359,0.00004422229],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002499574,0.0012461795,0.07290745,0.00022416876,0.00011055988,0.0024835537,0.0005302023,0.00016950436,0.1287755,0.059938226,0.046859927,0.6865048],"study_design_scores_gemma":[0.0004994592,0.0003469335,0.06023699,0.0003021488,0.00014447178,0.012377046,0.00016052401,0.00058408995,0.0069880835,0.06812691,0.84997314,0.00026022914],"about_ca_topic_score_codex":0.00001390974,"about_ca_topic_score_gemma":0.0000026540995,"teacher_disagreement_score":0.80311316,"about_ca_system_score_codex":0.00072804984,"about_ca_system_score_gemma":0.0004492806,"threshold_uncertainty_score":0.8681887},"labels":[],"label_agreement":null},{"id":"W2015629981","doi":"10.1016/j.neuroimage.2015.02.051","title":"Cerebral maturation in the early preterm period—A magnetization transfer and diffusion tensor imaging study using voxel-based analysis","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children; SickKids Foundation","funders":"Canadian Institutes of Health Research; Hospital for Sick Children","keywords":"White matter; Diffusion MRI; Voxel; Effective diffusion coefficient; Fractional anisotropy; Magnetization transfer; Linear regression; Gestational age; Magnetic resonance imaging; Nuclear medicine; Nuclear magnetic resonance; Medicine; Physics; Radiology; Mathematics; Biology; Statistics","score_opus":0.0695145498264368,"score_gpt":0.3393055475365746,"score_spread":0.2697909977101378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015629981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9658434,0.000027627277,0.031547833,0.0013451003,0.000017612183,0.0009914564,0.000006378128,0.00009541952,0.00012522282],"genre_scores_gemma":[0.99656415,0.0000029878108,0.002713141,0.00057158514,0.000034454664,0.00004516122,0.00002190221,0.000022623386,0.000024003484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988959,0.00012257577,0.00022658943,0.00034986905,0.0002483661,0.00015673107],"domain_scores_gemma":[0.99940974,0.000032424312,0.000040503284,0.00037420518,0.00007814726,0.00006495766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017391237,0.00014082031,0.00019047683,0.00023278384,0.00010095808,0.000090254944,0.00009068559,0.0000243823,0.000006635434],"category_scores_gemma":[0.00004496912,0.00010604091,0.000053494972,0.00069000194,0.000061613886,0.00016793208,0.000023110742,0.00019504527,0.0000010561971],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002044693,0.00034395908,0.9738777,0.000017989842,0.0000095188025,0.0000812414,0.0019900415,0.00017548855,0.021615665,0.000024464018,0.000026580577,0.0016328389],"study_design_scores_gemma":[0.0011123158,0.00019813063,0.8992709,0.0000124003,0.00031424483,0.000036484267,0.00034966654,0.09825661,0.0002098673,0.000049409777,0.00008777702,0.00010222757],"about_ca_topic_score_codex":0.000071608476,"about_ca_topic_score_gemma":0.0000140434295,"teacher_disagreement_score":0.09808113,"about_ca_system_score_codex":0.000030520965,"about_ca_system_score_gemma":0.000025272762,"threshold_uncertainty_score":0.4324223},"labels":[],"label_agreement":null},{"id":"W2016628198","doi":"10.1111/1467-7687.00369","title":"Mapping the development of white matter tracts with diffusion tensor imaging","year":2002,"lang":"en","type":"article","venue":"Developmental Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Corpus callosum; White matter; Fractional anisotropy; Psychology; Gyrus; Neuroscience; Audiology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06617429555506825,"score_gpt":0.2921760564081526,"score_spread":0.22600176085308432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016628198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96456563,0.000017361563,0.020415805,0.002585486,0.000017239317,0.00033046002,7.5328796e-7,0.00006245601,0.012004823],"genre_scores_gemma":[0.8116224,0.0000033842728,0.18713056,0.0006437537,0.000005895039,0.000026907017,0.0000010467272,0.0000073847937,0.0005586986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989713,0.0000042807824,0.00019952169,0.00024739493,0.00035381512,0.00022370489],"domain_scores_gemma":[0.99960726,0.00001471371,0.00007701956,0.00016489321,0.0000648264,0.00007126925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015311793,0.00009403458,0.000095123796,0.0000976215,0.00054351595,0.000016326167,0.0002037249,0.000008772065,0.00013318453],"category_scores_gemma":[0.0000116710025,0.000055439265,0.000013676529,0.0006472657,0.00036168593,0.0001357163,0.00014894323,0.000090177666,0.000036680787],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008276911,0.00010218044,0.8718053,0.00002190906,0.0000038330713,0.000007651245,0.0077458215,0.0000023170367,0.08968105,0.00005001146,0.00051406224,0.03005759],"study_design_scores_gemma":[0.00020129765,0.000009690983,0.9622025,0.00011346226,0.0000033714632,0.00019055413,0.00077741535,0.0004706165,0.025455521,0.000021015334,0.010441908,0.00011263355],"about_ca_topic_score_codex":0.0000014182534,"about_ca_topic_score_gemma":9.986377e-7,"teacher_disagreement_score":0.16671476,"about_ca_system_score_codex":0.00009152757,"about_ca_system_score_gemma":0.00007663592,"threshold_uncertainty_score":0.41803405},"labels":[],"label_agreement":null},{"id":"W2016960129","doi":"10.1016/j.neuroimage.2011.09.009","title":"Establishing the reproducibility of two approaches to quantify white matter tract integrity in stroke","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Science Council; Canada Research Chairs; Michael Smith Health Research BC","keywords":"White matter; Corticospinal tract; Fractional anisotropy; Diffusion MRI; Internal capsule; Stroke (engine); Psychology; Physical medicine and rehabilitation; Tractography; Pyramidal tracts; Medicine; Physical therapy; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.39545437201811084,"score_gpt":0.37861795609384064,"score_spread":0.01683641592427021,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2016960129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9722494,0.000016128184,0.007003022,0.006963299,0.000045619952,0.00085593696,0.000022211003,0.000103002996,0.012741402],"genre_scores_gemma":[0.9702171,0.0000041762005,0.028311318,0.0010789568,0.000037852573,0.00006147719,0.0000036016963,0.00002501141,0.00026048548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998397,0.00009083016,0.00035059126,0.0007968999,0.00015807597,0.00020661727],"domain_scores_gemma":[0.99759305,0.00010458986,0.000098779805,0.0020933237,0.000044038283,0.00006624969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090389483,0.00013196722,0.00024039247,0.0000971309,0.00004108731,0.000016273281,0.0002672064,0.0000329196,0.00006463604],"category_scores_gemma":[0.00051785307,0.000094915544,0.000077989,0.00033250282,0.000113110706,0.00015561181,0.0001341842,0.00062100845,0.000016703752],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079612764,0.00051982014,0.9749154,0.00005275027,0.0000030452054,0.00001877261,0.00093317067,0.0000063250277,0.0186161,0.0009830187,0.00079057424,0.0030813944],"study_design_scores_gemma":[0.00022668445,0.000086492066,0.9679754,0.000032873242,0.000019392051,0.00003753311,0.00008644391,0.0001585625,0.029106442,0.0013069579,0.00087705697,0.00008618413],"about_ca_topic_score_codex":0.00020667107,"about_ca_topic_score_gemma":0.000019108504,"teacher_disagreement_score":0.021308295,"about_ca_system_score_codex":0.00002108925,"about_ca_system_score_gemma":0.000025389892,"threshold_uncertainty_score":0.38705435},"labels":[],"label_agreement":null},{"id":"W2017077053","doi":"10.1002/mrm.24120","title":"The effect of concomitant gradient fields on diffusion tensor imaging","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University Hospital Foundation; Canada Foundation for Innovation; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"Dephasing; Diffusion MRI; Diffusion; Physics; Nuclear magnetic resonance; Isocenter; Imaging phantom; Magnetic field; Amplitude; Pulsed field gradient; Pulse sequence; Computational physics; Magnetic resonance imaging; Optics; Condensed matter physics; Quantum mechanics","score_opus":0.025679313783316685,"score_gpt":0.33510791589481165,"score_spread":0.309428602111495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017077053","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9589686,0.018612728,0.00040915492,0.015131704,0.00020603961,0.0009871239,0.0000019301822,0.00006523073,0.005617504],"genre_scores_gemma":[0.9968612,0.0012676428,0.000437782,0.0006680304,0.0001541908,0.00011130244,0.000002275619,0.000015623878,0.0004819303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989277,0.00005913195,0.00031218267,0.00016711067,0.00024943615,0.00028441445],"domain_scores_gemma":[0.9986958,0.000665318,0.00007792572,0.00044966696,0.000028258937,0.00008301093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046769792,0.00013070516,0.00028854297,0.00006870414,0.000066225686,0.0000022463414,0.00011953761,0.000031048596,0.000033773485],"category_scores_gemma":[0.00044847289,0.000069477675,0.000040459367,0.00021027592,0.00027732606,0.000021152344,0.000036883546,0.00025833902,0.0000045173456],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003444578,0.00008728544,0.60552967,0.000058760743,0.0000016988575,0.000019428737,0.00021659958,0.0000013735194,0.0041278186,0.0016189206,0.0054025557,0.38259143],"study_design_scores_gemma":[0.0026515734,0.002527814,0.80300397,0.0008727267,0.000046131972,0.00007691491,0.00008327063,0.001131618,0.0042678183,0.00049121823,0.18472913,0.00011779169],"about_ca_topic_score_codex":0.000037347825,"about_ca_topic_score_gemma":0.0000021348005,"teacher_disagreement_score":0.38247362,"about_ca_system_score_codex":0.000036865975,"about_ca_system_score_gemma":0.000006760866,"threshold_uncertainty_score":0.28332174},"labels":[],"label_agreement":null},{"id":"W2017219549","doi":"10.1167/10.7.614","title":"Adaptation to Up/Down Head Rotation in Face Selective Cortical Areas","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; York University","funders":"","keywords":"Adaptation (eye); Fusiform face area; Psychology; Face (sociological concept); Lateralization of brain function; Cognitive psychology; Right hemisphere; Laterality; Sulcus; Occipital lobe; Neuroscience; Face perception; Perception","score_opus":0.048445987923890946,"score_gpt":0.4115470657456437,"score_spread":0.36310107782175277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017219549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87927294,0.00001130282,0.11607251,0.00414998,0.00008950506,0.00022467421,7.8316356e-7,0.000018141742,0.00016017533],"genre_scores_gemma":[0.95870036,0.000016906086,0.04084629,0.00029171622,0.00007825464,0.0000051837287,0.0000017536607,0.0000085161,0.00005103957],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993581,0.00001813932,0.00026432803,0.000091057576,0.00018359271,0.000084789914],"domain_scores_gemma":[0.99941206,0.000061965824,0.000120291435,0.00009440975,0.00021178012,0.00009949609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017842751,0.000055816254,0.00012888754,0.00015161077,0.000031701038,0.000009408692,0.000045762,0.000039139282,0.000012429258],"category_scores_gemma":[0.00030983225,0.00004547962,0.0000382369,0.00023063058,0.000014763925,0.00011735948,0.0000114772465,0.000442154,0.00000777462],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006352348,0.00037588674,0.009194182,0.000012236981,0.0000070419032,0.000033185348,0.00096659065,0.0005784748,0.8715855,0.0008532015,0.001857728,0.11390077],"study_design_scores_gemma":[0.0014042621,0.0015303965,0.94814485,0.0002403598,0.000033104294,0.0004353571,0.00026113458,0.010951003,0.0265174,0.0032944914,0.007071299,0.00011631091],"about_ca_topic_score_codex":0.000007915371,"about_ca_topic_score_gemma":0.000017313565,"teacher_disagreement_score":0.9389507,"about_ca_system_score_codex":0.000048747424,"about_ca_system_score_gemma":0.000052081145,"threshold_uncertainty_score":0.19209637},"labels":[],"label_agreement":null},{"id":"W2017283521","doi":"10.1016/j.mri.2013.12.006","title":"In vivo longitudinal Myelin Water Imaging in rat spinal cord following dorsal column transection injury","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; International Collaboration On Repair Discoveries","funders":"Canadian Institutes of Health Research","keywords":"Myelin; Ex vivo; Spinal cord injury; Spinal cord; In vivo; Anatomy; Pathology; Medicine; Posterior column; Diffuse axonal injury; Chemistry; Central nervous system; Biology; Internal medicine","score_opus":0.022089067594348564,"score_gpt":0.3245697248524415,"score_spread":0.3024806572580929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017283521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9719559,0.0018633185,0.015609978,0.0076618856,0.00034182897,0.0008695669,0.0000040287023,0.00022598737,0.0014675362],"genre_scores_gemma":[0.990772,0.00005926426,0.0070276633,0.0011862512,0.00014117785,0.00017741178,0.000005931882,0.000057536377,0.0005727797],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976172,0.00008874646,0.0006357955,0.00070639024,0.0003164148,0.000635497],"domain_scores_gemma":[0.9992538,0.000046781493,0.00006726967,0.0004946939,0.000052341195,0.0000850856],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005848835,0.0002762299,0.0004152704,0.00034245884,0.00011180438,0.00006598094,0.00018546788,0.000043240674,0.00013526401],"category_scores_gemma":[0.000072494084,0.0002581443,0.00013438874,0.0004227702,0.000120048135,0.00031177848,0.00006734496,0.0004733466,0.000022490267],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006866864,0.00017379478,0.4008776,0.000060782644,0.0000014072334,0.00034584006,0.00014314322,0.000018486311,0.22756006,0.00021137489,0.0010678312,0.368853],"study_design_scores_gemma":[0.007122725,0.0011564565,0.48582464,0.0017421314,0.00010916471,0.0008107993,0.00018578499,0.061307993,0.105789125,0.0071999035,0.32733756,0.0014137175],"about_ca_topic_score_codex":0.00030229497,"about_ca_topic_score_gemma":0.000040847717,"teacher_disagreement_score":0.3674393,"about_ca_system_score_codex":0.00015753454,"about_ca_system_score_gemma":0.000032475866,"threshold_uncertainty_score":0.99998707},"labels":[],"label_agreement":null},{"id":"W2017712084","doi":"10.1006/brcg.1999.1179","title":"Cognitive Rehabilitation in Clinical Neuropsychology","year":2000,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University; Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Receiver operating characteristic; Pathology; Glioma; Region of interest; Chemistry; Nuclear medicine; Internal medicine; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07793029866147806,"score_gpt":0.44464794458901363,"score_spread":0.3667176459275356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017712084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9771444,0.000026247013,0.00084927765,0.009057408,0.000012008799,0.00034789357,0.0000050530475,0.00007768077,0.01248004],"genre_scores_gemma":[0.99231344,0.00016570558,0.0018150426,0.005290921,0.000040983297,0.000058289574,0.000038224294,0.000007761252,0.0002696372],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9994566,0.000058206668,0.00017415948,0.00019741073,0.000039581148,0.000074077434],"domain_scores_gemma":[0.9995381,0.00030457563,0.000021192414,0.00006666674,0.00002969072,0.000039739105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013093301,0.000047924223,0.000091714865,0.00004590961,0.000024595056,0.0000039749775,0.000012048834,0.00004071994,0.00012008503],"category_scores_gemma":[0.0002184442,0.00004759589,0.000024661194,0.00010991723,0.00010336759,0.000040106992,0.000004606209,0.00013173647,0.000030751347],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028012358,0.00032553042,0.018028533,0.00001552549,0.000003309206,0.00001749523,0.00007636228,1.3144752e-7,0.00089924614,0.0008096692,0.0012024173,0.97834164],"study_design_scores_gemma":[0.0017760886,0.0005795789,0.97341794,0.00009586859,0.000020182973,0.000094665826,0.000064911954,0.00015659882,0.000077642995,0.014104659,0.009540034,0.000071835195],"about_ca_topic_score_codex":0.0000018592135,"about_ca_topic_score_gemma":0.000001434529,"teacher_disagreement_score":0.9782698,"about_ca_system_score_codex":0.0000035369378,"about_ca_system_score_gemma":0.000007066959,"threshold_uncertainty_score":0.19409041},"labels":[],"label_agreement":null},{"id":"W2018045853","doi":"10.1016/j.schres.2014.04.026","title":"White matter changes in early phase schizophrenia and cannabis use: An update and systematic review of diffusion tensor imaging studies","year":2014,"lang":"en","type":"review","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Capital District Health Authority; Nova Scotia Health Authority; Dalhousie University","funders":"","keywords":"Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Medicine; Psychology; Psychiatry; Radiology; Magnetic resonance imaging","score_opus":0.15938023987410593,"score_gpt":0.4821144066455719,"score_spread":0.322734166771466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018045853","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012304521,0.99163,0.00002713593,0.0018592793,0.00001759792,0.005056265,0.00006864592,0.00008061959,0.000029990551],"genre_scores_gemma":[0.00018121224,0.993601,0.0037618233,0.00019717193,0.0000746755,0.0013133644,0.000054332406,0.00016082801,0.00065556046],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99626964,0.0007891851,0.0009752736,0.0008858063,0.00057119573,0.0005089232],"domain_scores_gemma":[0.9974494,0.00028115558,0.00043535468,0.0012028472,0.00037027022,0.00026098825],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016321284,0.000486194,0.0032205246,0.0010752673,0.00014011914,0.000072967996,0.00029568523,0.00012632714,0.00003164467],"category_scores_gemma":[0.0006585587,0.00034755113,0.00012652278,0.0008827235,0.00049144763,0.0001549265,0.0004894733,0.0009498477,0.00002573128],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000088641646,0.00010859954,0.00042790323,0.91842324,0.00006109269,0.00004116939,0.00003987437,3.164413e-9,0.000008581176,0.00025668243,0.0010064055,0.07953783],"study_design_scores_gemma":[0.0014543143,0.0002673733,0.00052717567,0.94538325,0.00099212,0.00031744022,0.000029580817,0.000031858573,0.0000036201343,0.0002889722,0.05028561,0.00041869012],"about_ca_topic_score_codex":0.000043143686,"about_ca_topic_score_gemma":0.000037219135,"teacher_disagreement_score":0.079119146,"about_ca_system_score_codex":0.00008989206,"about_ca_system_score_gemma":0.00011401117,"threshold_uncertainty_score":0.99989766},"labels":[],"label_agreement":null},{"id":"W2018703198","doi":"10.1016/j.neurobiolaging.2013.12.001","title":"Non-Gaussian water diffusion in aging white matter","year":2013,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; National Institute on Drug Abuse; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"White matter; Diffusion MRI; Neuroimaging; Multivariate statistics; Kurtosis; Voxel; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Psychology; Radiology; Statistics; Mathematics","score_opus":0.020178301769400483,"score_gpt":0.29429660337560554,"score_spread":0.27411830160620504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018703198","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9831173,0.000007773038,0.0006557532,0.013687408,0.000044226865,0.00032385357,9.124925e-7,0.00006639732,0.0020963822],"genre_scores_gemma":[0.99375975,0.000016825494,0.0028729113,0.0026952366,0.000032581982,0.00004412888,0.000014428739,0.000020988937,0.0005431681],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920124,0.000018682002,0.00023008202,0.00025849353,0.000039190672,0.00025231994],"domain_scores_gemma":[0.99957836,0.000019758689,0.00004844426,0.00028456107,0.000026974285,0.000041922936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048666894,0.00010973439,0.00021091047,0.00015334415,0.000036253223,0.000005100407,0.00009254059,0.0000477869,0.000249525],"category_scores_gemma":[0.0000029359855,0.00007885602,0.000043515145,0.000087587694,0.00008679097,0.00006646356,0.000099977995,0.0002244993,0.00011207122],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038785297,0.000051125742,0.6774107,0.000036421385,0.0000023708637,0.000005816351,0.00016060812,0.000008399068,0.3209779,0.000017564573,0.0008523017,0.00047289467],"study_design_scores_gemma":[0.00043444065,0.00006218217,0.8992097,0.0001018514,0.000010338355,0.000057834786,0.000027139024,0.0002297819,0.098286115,0.00050493976,0.00097155623,0.00010414522],"about_ca_topic_score_codex":0.00004272476,"about_ca_topic_score_gemma":0.0000013397754,"teacher_disagreement_score":0.22269179,"about_ca_system_score_codex":0.000012550343,"about_ca_system_score_gemma":0.0000054400825,"threshold_uncertainty_score":0.3215655},"labels":[],"label_agreement":null},{"id":"W2018708850","doi":"10.1152/jn.01044.2011","title":"Transcallosal inhibition in patients with callosal infarction","year":2012,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Corpus callosum; Transcranial magnetic stimulation; Lesion; Infarction; Medicine; Silent period; Neurology; Stimulation; Neuroscience; Psychology; Anatomy; Cardiology; Pathology; Myocardial infarction","score_opus":0.028558945835012405,"score_gpt":0.3017571126646538,"score_spread":0.27319816682964143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018708850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980155,0.000004606635,0.0011163158,0.0006191122,0.000060074974,0.000113008995,0.0000012184779,0.000012905432,0.000057214555],"genre_scores_gemma":[0.9971062,0.000017164359,0.0021518555,0.00056251796,0.00013720384,0.000003088584,0.000004376685,0.000012173786,0.0000054423326],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99945885,0.000029952947,0.00021409194,0.0000646789,0.00009982486,0.00013258937],"domain_scores_gemma":[0.99962074,0.00002132197,0.000121326746,0.000080718426,0.000086171196,0.000069733076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002121575,0.00006525937,0.00016262798,0.00011382687,0.0000164969,0.0000016142911,0.000023144847,0.000031340875,0.00000877507],"category_scores_gemma":[0.000018511704,0.000046719684,0.00004077081,0.0001248128,0.000041800184,0.00013834317,0.000007661974,0.0002637082,0.0000026665798],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033704974,0.0028843777,0.28676912,0.000051860563,0.00003404622,0.0000747696,0.00016845218,0.00031123543,0.6995969,0.0009174858,0.00022857524,0.005592711],"study_design_scores_gemma":[0.001306015,0.001267834,0.9946911,0.000027784572,0.000022351058,0.00014931236,0.0000030717138,0.0000161985,0.0012386335,0.00018259506,0.0010506825,0.000044427983],"about_ca_topic_score_codex":0.0000011857655,"about_ca_topic_score_gemma":9.92054e-8,"teacher_disagreement_score":0.707922,"about_ca_system_score_codex":0.000025226896,"about_ca_system_score_gemma":0.000016736796,"threshold_uncertainty_score":0.19051734},"labels":[],"label_agreement":null},{"id":"W2018985403","doi":"10.3389/neuro.05.014.2009","title":"Could sex differences in white matter be explained by g ratio?","year":2009,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institutes of Health; Canadian Institutes of Health Research; Royal Society","keywords":"White matter; Myelin; Axon; Myelin sheath; Disconnection; Magnetic resonance imaging; Sex ratio; Nerve conduction velocity; Anatomy; Neuroscience; Nuclear magnetic resonance; Psychology; Biology; Medicine; Physics; Central nervous system; Population; Philosophy; Radiology","score_opus":0.02562428583731719,"score_gpt":0.3002404656535699,"score_spread":0.2746161798162527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018985403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8404597,0.00059402327,0.06571275,0.076254606,0.00031140432,0.0018604185,0.000041539468,0.00046362725,0.014301947],"genre_scores_gemma":[0.97721493,0.0001438509,0.01011546,0.010073293,0.000026472086,0.00007614784,0.000027547881,0.000020852602,0.0023014734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989051,0.000034061588,0.00027021236,0.0003645882,0.00016302925,0.0002629796],"domain_scores_gemma":[0.99949884,0.00001859524,0.000057679816,0.00032899278,0.000017769504,0.000078102865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058937312,0.00016145644,0.00029743015,0.0002088526,0.00003599569,0.000017966333,0.0001520684,0.00006266124,0.00004799018],"category_scores_gemma":[0.000019712064,0.00015285968,0.000039492497,0.0003667995,0.000057454115,0.00011105168,0.000021643042,0.000343272,0.000005178911],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035802037,0.00016103043,0.6922717,0.000010585836,0.000002603885,0.000058082067,0.000106495616,0.0000028791856,0.00088677765,0.00011505964,0.3041472,0.0022017441],"study_design_scores_gemma":[0.0030771792,0.0003297752,0.87218285,0.00013333766,0.000033970045,0.00006734598,0.00032056705,0.008526807,0.0051587243,0.007316448,0.10224553,0.0006074677],"about_ca_topic_score_codex":0.0000057527427,"about_ca_topic_score_gemma":0.0000013770202,"teacher_disagreement_score":0.20190167,"about_ca_system_score_codex":0.000050441773,"about_ca_system_score_gemma":0.000019699317,"threshold_uncertainty_score":0.62334365},"labels":[],"label_agreement":null},{"id":"W2018989691","doi":"10.1016/j.neurobiolaging.2003.08.011","title":"The influence of sex on limbic volume and perfusion in AD","year":2003,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Sunnybrook Health Science Centre; University of Toronto; Health Sciences Centre","funders":"Medical Research Council Canada; Ontario Mental Health Foundation","keywords":"Limbic system; Limbic lobe; Atrophy; Posterior cingulate; Anterior cingulate cortex; Orbitofrontal cortex; Cingulate cortex; Perfusion; Magnetic resonance imaging; Neuroimaging; Medicine; Psychology; Alzheimer's disease; Cortex (anatomy); Neuroscience; Pathology; Internal medicine; Central nervous system; Prefrontal cortex; Radiology; Disease; Cognition","score_opus":0.024136816797427844,"score_gpt":0.31136517178810413,"score_spread":0.2872283549906763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018989691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99818647,0.00007756961,0.000026747462,0.001222308,0.0000092474575,0.00012504983,7.5934173e-7,0.00001589305,0.00033598035],"genre_scores_gemma":[0.9986598,0.00034345378,0.0005659012,0.00030904802,0.0000022738666,0.00000605848,5.5142704e-7,0.0000050604494,0.00010787373],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996042,0.000034495206,0.00012913755,0.0001224477,0.000025778592,0.0000839376],"domain_scores_gemma":[0.9996228,0.00011736209,0.00005575321,0.00016979848,0.000019896393,0.000014353518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086476626,0.00004739955,0.000105836225,0.00004218454,0.000035355966,9.3671844e-7,0.000043234682,0.000022681523,0.0000016985404],"category_scores_gemma":[0.000069039736,0.00003413622,0.00001414443,0.00008026251,0.00015723158,0.000012000954,0.000021324739,0.00012608364,5.899075e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049747265,0.00013080967,0.3171329,0.000053791817,0.000004196377,0.000006095633,0.0002470681,0.0002950798,0.6694683,0.002730139,0.00012690983,0.009754987],"study_design_scores_gemma":[0.0006018107,0.00067783694,0.8401887,0.00016175605,0.000013469328,0.00007758726,0.00006671077,0.00016663136,0.14603676,0.001673549,0.010246298,0.00008891887],"about_ca_topic_score_codex":0.000003664296,"about_ca_topic_score_gemma":9.4899383e-7,"teacher_disagreement_score":0.52343154,"about_ca_system_score_codex":0.000004309522,"about_ca_system_score_gemma":0.000010220377,"threshold_uncertainty_score":0.13920346},"labels":[],"label_agreement":null},{"id":"W2019737946","doi":"10.1002/mrm.22365","title":"Reconstruction of the orientation distribution function in single‐ and multiple‐shell q‐ball imaging within constant solid angle","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":381,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Army Research Office; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Office of Naval Research; U.S. Public Health Service; Defense Advanced Research Projects Agency; McGill University; W. M. Keck Foundation; National Institutes of Health; National Science Foundation","keywords":"Orientation (vector space); Dimensionless quantity; Sharpening; Geometry; Diffusion MRI; Distribution function; Mathematical analysis; Physics; Mathematics; Computer science; Artificial intelligence; Mechanics; Magnetic resonance imaging","score_opus":0.02405833203071902,"score_gpt":0.29755789276882655,"score_spread":0.27349956073810755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019737946","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932416,0.0007589834,0.0021243608,0.0024119697,0.00027301224,0.0006161821,0.000011452858,0.000036311514,0.0005261337],"genre_scores_gemma":[0.9973474,0.0001141603,0.0021714978,0.00016960368,0.000060756094,0.00003146298,0.000022237526,0.000010747574,0.00007213795],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989462,0.00003421117,0.00043389175,0.0002634051,0.00017790332,0.0001443838],"domain_scores_gemma":[0.9993495,0.00009332381,0.00015740156,0.00027523315,0.0000839354,0.000040630195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002844289,0.00010844651,0.00020858871,0.000089113266,0.00004334713,0.0000045766838,0.000059672937,0.000049712755,0.00002393922],"category_scores_gemma":[0.0004671529,0.00007997841,0.000018884804,0.00042994064,0.00049738307,0.00007130267,0.000028494267,0.00034726583,5.3038235e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013556701,0.000088205525,0.51534826,0.000041481497,7.65103e-7,0.000005336598,0.00021402555,0.000008939125,0.3482636,0.00069789705,0.00012448581,0.13507146],"study_design_scores_gemma":[0.0030745552,0.00037567827,0.95910215,0.00081332127,0.000039538663,0.00027153303,0.0005600812,0.011759983,0.015235825,0.0038258617,0.004807447,0.00013401256],"about_ca_topic_score_codex":0.00013788659,"about_ca_topic_score_gemma":0.00019564308,"teacher_disagreement_score":0.44375393,"about_ca_system_score_codex":0.000049874547,"about_ca_system_score_gemma":0.000030470008,"threshold_uncertainty_score":0.3261425},"labels":[],"label_agreement":null},{"id":"W2019795338","doi":"10.1016/j.neuroimage.2008.07.009","title":"Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":583,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; University of California, Los Angeles; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"White matter; Diffusion MRI; Atlas (anatomy); Fiber tract; Neuroscience; Anatomy; Human brain; Cortex (anatomy); Neuroimaging; Biology; Magnetic resonance imaging; Medicine","score_opus":0.03712681418569049,"score_gpt":0.33040838274800466,"score_spread":0.2932815685623142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019795338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99121684,0.000014265627,0.00081868895,0.006495399,0.000021980253,0.0004189438,0.000022619954,0.000053835334,0.0009374399],"genre_scores_gemma":[0.99606043,0.000010492741,0.0011804015,0.002013567,0.000040255873,0.000030008272,0.000034087785,0.00003308213,0.00059767766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988279,0.000054792763,0.00039277278,0.0003623327,0.00018270545,0.00017954523],"domain_scores_gemma":[0.99935305,0.00002903028,0.000103321276,0.000417254,0.000031525346,0.00006581647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007154259,0.00014749815,0.00026046633,0.00015297877,0.00008156522,0.000015039845,0.00010625765,0.000057126414,0.00018674275],"category_scores_gemma":[0.000011178608,0.00014243145,0.000046338624,0.00015717899,0.00019709705,0.000102469974,0.00007555506,0.00026291702,0.000019349121],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002331926,0.00011601222,0.8122605,0.00004051728,0.0000026933592,0.000033936267,0.00014337731,0.000006025744,0.17410643,0.00015235464,0.013009643,0.00010514628],"study_design_scores_gemma":[0.00047719793,0.000057150206,0.9870246,0.000022680775,0.000014088121,0.00013930743,0.000016108781,0.000114071154,0.0104528135,0.0008619072,0.000713503,0.000106540065],"about_ca_topic_score_codex":0.000018937966,"about_ca_topic_score_gemma":0.000006198668,"teacher_disagreement_score":0.1747641,"about_ca_system_score_codex":0.000028309529,"about_ca_system_score_gemma":0.0000118198395,"threshold_uncertainty_score":0.5808186},"labels":[],"label_agreement":null},{"id":"W2020108690","doi":"10.1007/s00221-001-0921-8","title":"Stereological evaluation of neurons and glia in the monkey dorsal lateral geniculate nucleus following an early cerebral hemispherectomy","year":2002,"lang":"en","type":"article","venue":"Experimental Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Parvocellular cell; Neuroscience; Cytoarchitecture; Biology; Magnocellular cell; Brainstem; Lateral geniculate nucleus; Geniculate; Population; Nissl body; Thalamus; Visual cortex; Anatomy; Central nervous system; Nucleus; Medicine","score_opus":0.303410708727518,"score_gpt":0.4882797532445474,"score_spread":0.1848690445170294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020108690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995461,0.00035053134,0.000010571309,0.0018183076,0.000013577957,0.0008498916,0.000002806215,0.000038087062,0.0014552469],"genre_scores_gemma":[0.998266,0.000006429235,0.0011653793,0.00022641293,0.000026911966,0.00016088963,0.0000067015135,0.00001614471,0.00012514401],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981464,0.000413226,0.00019126164,0.0003111078,0.0006631571,0.0002748179],"domain_scores_gemma":[0.999368,0.00014701218,0.000027354674,0.00033550075,0.00005236027,0.00006976189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000819614,0.000097464326,0.00014170478,0.00007498768,0.00011519534,0.000033212935,0.00016639511,0.0000505716,0.00018411817],"category_scores_gemma":[0.0000986876,0.00007143615,0.000050883536,0.0002599569,0.00017477387,0.0001265945,0.000109145905,0.00034532815,0.0000059544404],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018740066,0.0013652472,0.07756062,0.000018848634,0.000024256078,0.00011128482,0.005818949,0.000016434873,0.901769,0.0010979143,0.0011946139,0.010835464],"study_design_scores_gemma":[0.0074395756,0.0032681876,0.71519905,0.00013230053,0.000046249632,0.0002075847,0.0029399602,0.06810278,0.19830106,0.0023401552,0.0015943202,0.00042879593],"about_ca_topic_score_codex":0.00013190252,"about_ca_topic_score_gemma":0.0000038131832,"teacher_disagreement_score":0.7034679,"about_ca_system_score_codex":0.000058164103,"about_ca_system_score_gemma":0.000013352819,"threshold_uncertainty_score":0.29130816},"labels":[],"label_agreement":null},{"id":"W2020130186","doi":"10.1007/s10548-013-0343-5","title":"The Role of Left Inferior Fronto-Occipital Fascicle in Verbal Perseveration: A Brain Electrostimulation Mapping Study","year":2013,"lang":"en","type":"article","venue":"Brain Topography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Perseveration; Fascicle; White matter; Stimulation; Medicine; Neuroscience; Psychology; Anatomy; Radiology; Magnetic resonance imaging; Cognition","score_opus":0.01787890440456127,"score_gpt":0.29982240863826876,"score_spread":0.2819435042337075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020130186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98967624,0.00016588857,0.002564439,0.005214988,0.000018309907,0.0014641141,0.0000032128753,0.00009823788,0.0007945852],"genre_scores_gemma":[0.9974899,0.000010361634,0.0017640841,0.00040987114,0.00004280683,0.00014863758,0.000011796066,0.000014772122,0.0001077648],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990771,0.000051870054,0.0002807109,0.00021937562,0.00017413797,0.00019679507],"domain_scores_gemma":[0.99929374,0.00017425639,0.00008253628,0.00032237667,0.00007962863,0.00004745868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017284261,0.00010904322,0.0001574977,0.00014922301,0.0001319568,0.00003330667,0.00010600856,0.000036534566,0.000034278586],"category_scores_gemma":[0.000096100164,0.000088116976,0.00008455132,0.0003889637,0.00007303525,0.00014990434,0.000036909354,0.00015335529,0.000005092286],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006352361,0.000668269,0.82394314,0.000013592734,0.000041187595,0.000003663741,0.0033113186,0.000042398722,0.13750856,0.0027856636,0.0020841665,0.029534537],"study_design_scores_gemma":[0.0010661376,0.00048333278,0.97244024,0.00002842367,0.000013057444,0.000013113852,0.0026129754,0.003435,0.0017579875,0.0069302563,0.01107707,0.000142376],"about_ca_topic_score_codex":0.00012228335,"about_ca_topic_score_gemma":0.000067262205,"teacher_disagreement_score":0.14849715,"about_ca_system_score_codex":0.000026922027,"about_ca_system_score_gemma":0.000027845308,"threshold_uncertainty_score":0.3593306},"labels":[],"label_agreement":null},{"id":"W2020823327","doi":"10.1016/j.bandc.2009.06.002","title":"Growth of white matter in the adolescent brain: Myelin or axon?","year":2009,"lang":"en","type":"review","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":433,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Canadian Institutes of Health Research","keywords":"White matter; Myelin; Neuroscience; Psychology; Axon; Magnetic resonance imaging; Human brain; Brain Structure and Function; Brain size; Neuroimaging; Central nervous system; Medicine; Radiology","score_opus":0.1178505650643618,"score_gpt":0.3971825772982026,"score_spread":0.2793320122338408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020823327","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000031400014,0.9630286,0.0029508402,0.025104906,0.000023734357,0.003454701,0.000088151355,0.000093571456,0.0052240845],"genre_scores_gemma":[0.00059335603,0.9860467,0.0007287254,0.01179724,0.0000961035,0.00017711945,0.00020095844,0.000022241857,0.0003375688],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991404,0.000081761355,0.00032124404,0.00022834096,0.000114108196,0.000114147624],"domain_scores_gemma":[0.99943435,0.00014578174,0.00014549465,0.00020351844,0.000040069695,0.000030779316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016428082,0.00016414,0.00048158452,0.00011742872,0.000043032433,0.000008856349,0.000078799516,0.000091902206,0.000046883128],"category_scores_gemma":[0.00006096541,0.000098268145,0.00010334999,0.00025317114,0.0000534886,0.000026874513,0.000027247219,0.00027957835,0.000010996636],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021999966,0.0001802656,0.00003867577,0.005771169,0.000007663691,0.000018458815,0.000052996962,5.0652402e-9,0.000003713528,0.00025351063,0.021741256,0.9719103],"study_design_scores_gemma":[0.0003994696,0.00013443634,0.0020252399,0.01527105,0.00026819212,0.00036013342,0.000027869244,0.0000029487626,0.000005128095,0.0014925775,0.9798536,0.00015940536],"about_ca_topic_score_codex":0.0000013758363,"about_ca_topic_score_gemma":0.0000014439362,"teacher_disagreement_score":0.97175086,"about_ca_system_score_codex":0.000013060678,"about_ca_system_score_gemma":0.000039171136,"threshold_uncertainty_score":0.40072587},"labels":[],"label_agreement":null},{"id":"W2020896724","doi":"10.1016/j.pscychresns.2003.09.003","title":"MRI volumetry of the vermis and the cerebellar hemispheres in men with schizophrenia","year":2004,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Philippe Pinel de Montréal","funders":"Kuopion Yliopistollinen Sairaala","keywords":"Cerebellar vermis; Schizophrenia (object-oriented programming); Cerebellum; Psychology; Magnetic resonance imaging; Neuroscience; Anatomy; Medicine; Psychiatry; Radiology","score_opus":0.04733860088722303,"score_gpt":0.36825973906920956,"score_spread":0.32092113818198653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020896724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89367294,0.0014108358,0.00079787086,0.09412602,0.000045147768,0.0014545697,0.0000055081905,0.00008338627,0.008403695],"genre_scores_gemma":[0.99027836,0.00032222303,0.0086196335,0.00044252642,0.00006498586,0.000062567655,8.802618e-7,0.000034833793,0.00017396772],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99845916,0.00012863183,0.00022837806,0.0003588892,0.0004902582,0.00033466256],"domain_scores_gemma":[0.9988273,0.00015385433,0.00007077292,0.00076692743,0.00010311568,0.000078072415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005213594,0.00012784207,0.00020579866,0.00011138869,0.00024912332,0.000032645537,0.00032833722,0.00002728959,0.000007904998],"category_scores_gemma":[0.00012967121,0.00007031502,0.00005427643,0.0009698015,0.00095430826,0.000073586336,0.00021933691,0.0008787317,0.00000211098],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003825095,0.00073781866,0.89771795,0.00063602964,0.0000745448,0.0000481025,0.0007576054,0.00041035312,0.023936989,0.057904966,0.005962361,0.007988192],"study_design_scores_gemma":[0.035442077,0.00067039294,0.7506577,0.0023422586,0.0001805312,0.0012477118,0.0019798754,0.005752053,0.020994982,0.1686637,0.011376574,0.0006921554],"about_ca_topic_score_codex":0.00021243066,"about_ca_topic_score_gemma":0.00003895909,"teacher_disagreement_score":0.14706025,"about_ca_system_score_codex":0.000035936922,"about_ca_system_score_gemma":0.00021561066,"threshold_uncertainty_score":0.3817701},"labels":[],"label_agreement":null},{"id":"W2021173709","doi":"10.1016/j.neuroimage.2014.12.008","title":"The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Radiological Society of North America","keywords":"Diffusion MRI; In vivo; Axon; Diffusion; Biomedical engineering; Chemistry; Materials science; Neuroscience; Physics; Biology; Medicine; Magnetic resonance imaging; Radiology; Biotechnology; Thermodynamics","score_opus":0.032876289973721905,"score_gpt":0.3480370503872482,"score_spread":0.3151607604135263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021173709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949987,0.00001551795,0.0020175397,0.00056071917,0.000020928923,0.0003197121,0.000014315628,0.000047763107,0.0020048032],"genre_scores_gemma":[0.99697864,0.0000994182,0.0027570268,0.00006813814,0.000015652882,0.00001831767,0.0000027209207,0.000018406823,0.00004167983],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99928474,0.000030612024,0.00022808489,0.00018080139,0.0001290904,0.00014664402],"domain_scores_gemma":[0.9989721,0.00034431924,0.00011722636,0.0004880923,0.000033768938,0.00004448005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009528764,0.000102500875,0.00019052692,0.00007744635,0.000034380995,0.0000049864025,0.000108969405,0.000021921916,0.0000110983065],"category_scores_gemma":[0.00020489536,0.000064318396,0.00009851067,0.00014792375,0.000106305386,0.000025945697,0.000043617707,0.00014749278,0.0000016669242],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023901249,0.0008764646,0.061312634,0.00006195126,0.000010701032,0.0000090400445,0.00009711775,0.00013701846,0.90124476,0.0028246846,0.002112281,0.03107434],"study_design_scores_gemma":[0.0010475088,0.001952258,0.7284862,0.00018171441,0.000029007955,0.000016568021,0.000010302965,0.015976904,0.24649955,0.0036388338,0.0020304078,0.00013078982],"about_ca_topic_score_codex":0.000050926214,"about_ca_topic_score_gemma":0.0000025821396,"teacher_disagreement_score":0.6671735,"about_ca_system_score_codex":0.000019231331,"about_ca_system_score_gemma":0.000010647449,"threshold_uncertainty_score":0.26228282},"labels":[],"label_agreement":null},{"id":"W2021577051","doi":"10.1523/jneurosci.3464-13.2014","title":"Frontal White Matter Tracts Sustaining Speech Production in Primary Progressive Aphasia","year":2014,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":191,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Aging","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"White matter; Primary progressive aphasia; Neuroscience; Diffusion MRI; Speech production; Arcuate fasciculus; Inferior frontal gyrus; Supplementary motor area; Broca's area; Tractography; Psychology; Superior longitudinal fasciculus; Medicine; Fractional anisotropy; Cognition; Functional magnetic resonance imaging; Frontotemporal dementia; Magnetic resonance imaging; Pathology; Computer science; Disease; Speech recognition","score_opus":0.0360008379895664,"score_gpt":0.3397036808807934,"score_spread":0.303702842891227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021577051","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98508674,0.0000271902,0.0051961737,0.008153196,0.00019716551,0.00024551054,3.8954988e-7,0.00002500234,0.001068603],"genre_scores_gemma":[0.9827571,0.000014410271,0.015153377,0.0016577671,0.00015469916,0.000004831027,3.1449034e-7,0.000010898833,0.0002465946],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999057,0.000029013107,0.00028352512,0.00018919505,0.00027186406,0.00016938231],"domain_scores_gemma":[0.999358,0.000018301393,0.00027683235,0.00016423844,0.00010270297,0.00007991704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027328258,0.000077602104,0.00016361357,0.0001708538,0.00005145081,0.000023285587,0.00013552468,0.000020962494,0.000004754583],"category_scores_gemma":[0.00020956509,0.000062115745,0.000042470787,0.00029827261,0.000102246755,0.00032269268,0.000029700266,0.00032456085,0.0000021606327],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020278884,0.00060440105,0.45776358,0.000084331594,0.0000017132085,0.000856399,0.00030936158,0.00017789211,0.50611234,0.00006130289,0.0031434891,0.030682413],"study_design_scores_gemma":[0.00040494974,0.0003925218,0.9779979,0.00014844512,0.0000121569665,0.007168942,0.000034620276,0.00029841557,0.008145242,0.00041930992,0.004895072,0.000082426304],"about_ca_topic_score_codex":4.1755874e-7,"about_ca_topic_score_gemma":1.372945e-7,"teacher_disagreement_score":0.52023435,"about_ca_system_score_codex":0.00006117255,"about_ca_system_score_gemma":0.000064984255,"threshold_uncertainty_score":0.25330067},"labels":[],"label_agreement":null},{"id":"W2021708425","doi":"10.1016/j.clineuro.2011.12.045","title":"Diffusion tensor imaging as a surrogate marker for outcome after perimesencephalic subarachnoid hemorrhage","year":2012,"lang":"en","type":"article","venue":"Clinical Neurology and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Heart and Stroke Foundation; University of Toronto; St. Michael's Hospital","funders":"Brain Aneurysm Foundation; Heart and Stroke Foundation of Canada","keywords":"Medicine; Diffusion MRI; Subarachnoid hemorrhage; White matter; Biomarker; Imaging biomarker; Neuroimaging; Surrogate endpoint; Radiology; Intensive care medicine; Neuroscience; Magnetic resonance imaging; Internal medicine; Psychiatry","score_opus":0.08683934149102515,"score_gpt":0.40735841419512275,"score_spread":0.32051907270409763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021708425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9856125,0.00035909054,0.0007834365,0.01161228,0.00060398853,0.00058924546,0.00001662456,0.00025879013,0.00016402216],"genre_scores_gemma":[0.96264136,0.00010624986,0.0010660843,0.035094712,0.00035398654,0.00021208022,0.000011629465,0.00005789512,0.00045602582],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978994,0.00015056254,0.0006846837,0.00059908105,0.00011061095,0.00055563246],"domain_scores_gemma":[0.9975469,0.0013798107,0.00015964637,0.00049483724,0.00005746857,0.00036134775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005954542,0.00024396594,0.00051685644,0.00010104924,0.00016102452,0.0000159174,0.00008941986,0.00015492724,0.0000559167],"category_scores_gemma":[0.001081874,0.00020696873,0.00027441655,0.0001290906,0.00043961013,0.00014585316,0.00014602911,0.00059248833,0.000032298612],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011896293,0.00034799165,0.9896057,0.00006237272,0.0000030425317,0.00017421255,0.0000075750304,6.1840936e-8,0.0019810754,0.00015259703,0.00029521342,0.006180489],"study_design_scores_gemma":[0.0008175548,0.00032173988,0.9708917,0.000005608882,0.00010628743,0.0012387711,0.0000031752559,0.00068185973,0.00025163047,0.0004187718,0.025062436,0.00020046068],"about_ca_topic_score_codex":0.0000018225368,"about_ca_topic_score_gemma":1.2847947e-7,"teacher_disagreement_score":0.024767222,"about_ca_system_score_codex":0.000004102306,"about_ca_system_score_gemma":0.000020738991,"threshold_uncertainty_score":0.84399396},"labels":[],"label_agreement":null},{"id":"W2021865008","doi":"10.1016/j.neuroimage.2008.12.028","title":"Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Diffusion MRI; Cluster analysis; Fractional anisotropy; Artificial intelligence; Region of interest; Tractography; White matter; Computer science; Pattern recognition (psychology); Voxel; Intraclass correlation; Magnetic resonance imaging; Mathematics; Statistics; Medicine; Radiology; Reproducibility","score_opus":0.1766558596002192,"score_gpt":0.3989820601226853,"score_spread":0.22232620052246607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021865008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5714622,0.00017135656,0.4270976,0.00011884956,0.000020695561,0.0003561081,0.000015649182,0.000105234794,0.00065227924],"genre_scores_gemma":[0.5413318,0.00012931065,0.45822167,0.00015896389,0.00001638985,0.000015575628,0.0000041752255,0.000027437818,0.000094613315],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989693,0.000047802187,0.00027836132,0.00032945766,0.0002101442,0.0001649375],"domain_scores_gemma":[0.99919206,0.00014410153,0.00013615319,0.0003384375,0.00013146765,0.000057807345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010804313,0.00013717236,0.00024072776,0.00019552234,0.00010753529,0.0000048597954,0.00008524529,0.00004109017,0.000011347853],"category_scores_gemma":[0.00012713477,0.00013226122,0.00009142567,0.00046385248,0.00013455968,0.00010488687,0.00005233761,0.00019110664,0.0000011565779],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072881325,0.0003342274,0.002400231,0.000049552942,0.0000021162855,0.00003762164,0.000219184,0.000044887354,0.98058695,0.00024430035,0.00002595401,0.015982086],"study_design_scores_gemma":[0.0016031961,0.0008147665,0.74741465,0.00017486575,0.00007340315,0.0008510932,0.00006625796,0.21147594,0.034748442,0.0000789333,0.0024692772,0.00022918149],"about_ca_topic_score_codex":0.000024534133,"about_ca_topic_score_gemma":8.9582437e-7,"teacher_disagreement_score":0.9458385,"about_ca_system_score_codex":0.00001709767,"about_ca_system_score_gemma":0.000019860587,"threshold_uncertainty_score":0.5393456},"labels":[],"label_agreement":null},{"id":"W2021874511","doi":"10.3171/2014.10.peds13644","title":"Postshunt lateral ventricular volume, white matter integrity, and intellectual outcomes in spina bifida and hydrocephalus","year":2015,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Medicine; Hydrocephalus; Lateral ventricles; Diffusion MRI; White matter; Fractional anisotropy; Shunt (medical); Ventricular system; Ventricle; Cerebral ventricle; Brain size; Spina bifida; Third ventricle; Fourth ventricle; Cardiology; Magnetic resonance imaging; Anatomy; Radiology; Surgery","score_opus":0.05589107948892645,"score_gpt":0.32050279834077006,"score_spread":0.2646117188518436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2021874511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9930019,0.0005323513,0.0005858629,0.005477202,0.00018116525,0.00013750768,0.0000047474464,0.00002117342,0.000058085767],"genre_scores_gemma":[0.9959067,0.0008590912,0.0015659159,0.0012671965,0.00017144691,0.0000028491281,0.0000016335553,0.000025089435,0.00020004169],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987776,0.00004664889,0.00053200976,0.00018071149,0.0002665983,0.00019642536],"domain_scores_gemma":[0.99904305,0.00015950612,0.0002471794,0.00014452302,0.00015810932,0.0002476238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003347393,0.00015371678,0.0004031286,0.00059937,0.00002908558,0.000043048163,0.00007501897,0.000067197725,0.000010894143],"category_scores_gemma":[0.000536331,0.00012307469,0.00008030054,0.00044226646,0.00005722202,0.00018008756,0.000099062236,0.0006619656,0.0000057214042],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000076138946,0.00011931916,0.9882037,0.000031660995,0.000004241752,0.00062239636,0.00008646682,0.000007021936,0.00009231103,0.0000043432096,0.01031271,0.00043969607],"study_design_scores_gemma":[0.00090990367,0.00041364774,0.9847044,0.00003885719,0.00008775074,0.005012595,0.00003978869,0.000367983,0.000074664764,0.0004432128,0.0077412166,0.00016602188],"about_ca_topic_score_codex":0.000005669553,"about_ca_topic_score_gemma":3.911504e-7,"teacher_disagreement_score":0.0043901987,"about_ca_system_score_codex":0.000047834023,"about_ca_system_score_gemma":0.000082978644,"threshold_uncertainty_score":0.501884},"labels":[],"label_agreement":null},{"id":"W2022237952","doi":"10.1016/j.media.2014.06.003","title":"Multi-shell diffusion signal recovery from sparse measurements","year":2014,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Academy of Finland","keywords":"Algorithm; SIGNAL (programming language); Diffusion; Computer science; Range (aeronautics); Mathematics; Mathematical optimization; Physics","score_opus":0.08600627826693114,"score_gpt":0.35698312701008417,"score_spread":0.27097684874315303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022237952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09048844,0.00006340701,0.90526736,0.002575752,0.000027873346,0.00016188377,0.0000137710185,0.00021678528,0.0011847395],"genre_scores_gemma":[0.8207242,0.00015961056,0.17329389,0.0042133606,0.0002625056,0.000047125428,0.0003023561,0.000034558463,0.00096237246],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99810565,0.00008196532,0.00034684865,0.00045754688,0.0007756705,0.00023229817],"domain_scores_gemma":[0.9987069,0.00012578416,0.000101398946,0.000578084,0.00011545956,0.00037237286],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00035944566,0.00016002932,0.00043342606,0.00019308738,0.0000913471,0.000022263204,0.00019374462,0.00009761743,0.0024926811],"category_scores_gemma":[0.00057524815,0.00012944154,0.00031014794,0.00064060075,0.00011816803,0.00007673289,0.00009601643,0.00028565034,0.00015446778],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019343245,0.00272014,0.19963294,0.00005120737,0.0020789606,0.00019171939,0.00011021751,0.000053167474,0.53967506,0.000031721753,0.014476351,0.2407851],"study_design_scores_gemma":[0.0060714055,0.0004201558,0.2647662,0.0003183022,0.012149483,0.000028459068,0.00006203706,0.5850134,0.06367485,0.002342124,0.06409203,0.0010615772],"about_ca_topic_score_codex":0.00022849064,"about_ca_topic_score_gemma":0.000039581715,"teacher_disagreement_score":0.73197347,"about_ca_system_score_codex":0.000043905882,"about_ca_system_score_gemma":0.000032463326,"threshold_uncertainty_score":0.99841917},"labels":[],"label_agreement":null},{"id":"W2022349962","doi":"10.1002/hbm.20576","title":"Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity","year":2008,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":191,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Resting state fMRI; Multiple sclerosis; Neuroscience; Functional connectivity; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.1757230029556175,"score_gpt":0.278575081015041,"score_spread":0.10285207805942354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022349962","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9543512,0.000010974898,0.04316445,0.0009391769,0.000026615779,0.00080017734,0.00003379904,0.00039542944,0.00027816027],"genre_scores_gemma":[0.99269766,0.000011859233,0.0062551643,0.00048803553,0.00006580928,0.0001257409,0.000034735418,0.000046864898,0.00027411818],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985086,0.00007727676,0.0003055263,0.0005011314,0.00025333962,0.00035413873],"domain_scores_gemma":[0.9990274,0.00036370812,0.00010521001,0.0002888543,0.000074856005,0.00013997263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019963356,0.00023267938,0.00032492445,0.0001947002,0.00048095136,0.000013104307,0.00007535132,0.0000697036,0.000032603664],"category_scores_gemma":[0.000129916,0.00022414046,0.000097167176,0.000330418,0.00025071244,0.00016584047,0.00002059968,0.0004836169,0.0000067481874],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025184444,0.00034961937,0.18324426,0.000075931275,0.000022809465,0.00014537065,0.0011495387,0.00034002576,0.81333643,0.0002545661,0.00025431722,0.0005753049],"study_design_scores_gemma":[0.003614613,0.00023771373,0.9858846,0.00035586,0.00001664972,0.00015665115,0.00017359229,0.004339059,0.003069949,0.00048783675,0.0013414278,0.00032203074],"about_ca_topic_score_codex":0.00013247259,"about_ca_topic_score_gemma":0.00012358825,"teacher_disagreement_score":0.81026644,"about_ca_system_score_codex":0.00012364649,"about_ca_system_score_gemma":0.00007133071,"threshold_uncertainty_score":0.9140183},"labels":[],"label_agreement":null},{"id":"W2023527865","doi":"10.1002/mrm.23254","title":"Six is enough? Comparison of diffusion parameters measured using six or more diffusion‐encoding gradient directions with deterministic tractography","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Alberta Science and Research Authority; Canadian Institutes of Health Research; Alberta Innovates; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Diffusion; Tractography; Diffusion MRI; Encoding (memory); Statistical physics; Computer science; Nuclear magnetic resonance; Algorithm; Artificial intelligence; Physics; Medicine; Magnetic resonance imaging; Radiology; Quantum mechanics","score_opus":0.154233227715255,"score_gpt":0.37176231237995006,"score_spread":0.21752908466469506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023527865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99116457,0.0023012012,0.003625849,0.00074821734,0.00009095855,0.0010339196,0.000010289711,0.00011557168,0.0009094503],"genre_scores_gemma":[0.9540017,0.0007192104,0.044654567,0.00029996954,0.000040101702,0.00011284149,0.0000069886814,0.000042586988,0.00012202431],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978546,0.000050806146,0.0007189786,0.0005145192,0.0004990591,0.00036205136],"domain_scores_gemma":[0.9986095,0.00019324197,0.00027700892,0.00061879196,0.00013236058,0.00016909897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017465113,0.0002892813,0.00072890153,0.00038482033,0.00012908588,0.0000051784095,0.00018892993,0.00008735712,0.00013297754],"category_scores_gemma":[0.00021417165,0.0001962445,0.00007709134,0.0010405036,0.0006273677,0.000055110402,0.000046554876,0.00036168817,9.2903974e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021169737,0.0025879717,0.72177297,0.00043078727,0.000028734587,0.00027650534,0.014651402,0.000021496113,0.07301864,0.0002592343,0.00055206,0.18428323],"study_design_scores_gemma":[0.005630687,0.006616143,0.9290792,0.005058336,0.00059483165,0.00043372053,0.00286226,0.022045385,0.011233488,0.0004984229,0.01529371,0.0006538564],"about_ca_topic_score_codex":0.0005487328,"about_ca_topic_score_gemma":0.000088226916,"teacher_disagreement_score":0.20730619,"about_ca_system_score_codex":0.000062850966,"about_ca_system_score_gemma":0.000049491566,"threshold_uncertainty_score":0.80026186},"labels":[],"label_agreement":null},{"id":"W2023600537","doi":"10.1310/3bxl-18w0-fpj4-f1gy","title":"Intrinsic Factors Influencing Post Stroke Brain Reorganization","year":2005,"lang":"en","type":"review","venue":"Topics in Stroke Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Victoria Hospital; St Joseph's Health Care","funders":"Canadian Stroke Network; Heart and Stroke Foundation of Canada","keywords":"Lesion; Stroke (engine); Stroke recovery; Spontaneous recovery; Physical medicine and rehabilitation; Neuroscience; Motor cortex; Motor function; Psychology; Medicine; Cortex (anatomy); Rehabilitation; Surgery; Stimulation","score_opus":0.05787192778041632,"score_gpt":0.39277183861708725,"score_spread":0.3348999108366709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023600537","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006957822,0.98316586,0.0011934036,0.0033194332,0.00018757385,0.0036570013,0.00019048597,0.0005101117,0.0008183246],"genre_scores_gemma":[0.00079609023,0.9716248,0.0243494,0.00020797785,0.00041262928,0.00021792101,0.00053366635,0.000108789194,0.0017487389],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980582,0.00011771014,0.0007616712,0.0005370201,0.00026652997,0.0002588565],"domain_scores_gemma":[0.99802786,0.0006981056,0.00032872354,0.00064268505,0.00021552737,0.00008711505],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018077978,0.00034610607,0.0009615807,0.00057718414,0.0000682976,0.000026682805,0.00016483932,0.0003065617,0.000033210825],"category_scores_gemma":[0.0017341292,0.00031974135,0.00026951134,0.0005498657,0.00008169553,0.00016293538,0.00007397578,0.0006877488,0.000020634854],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004924575,0.000093157316,0.001704751,0.0030450283,0.000016701384,0.0000027178392,0.00033093026,0.000003586063,0.000043466738,0.0020941435,0.0001687842,0.9924918],"study_design_scores_gemma":[0.00023453445,0.000215982,0.0026315497,0.0029260477,0.0001640033,0.00001621439,0.00015304223,0.000008376412,0.000014903513,0.00021811452,0.99315584,0.00026138526],"about_ca_topic_score_codex":0.0000186654,"about_ca_topic_score_gemma":0.000013064086,"teacher_disagreement_score":0.99298704,"about_ca_system_score_codex":0.0007336407,"about_ca_system_score_gemma":0.00022620127,"threshold_uncertainty_score":0.9999255},"labels":[],"label_agreement":null},{"id":"W2023735007","doi":"10.1016/j.cmpb.2010.06.011","title":"Wavelets and fuzzy relational classifiers: A novel diffusion-weighted image analysis system for pediatric metabolic brain diseases","year":2010,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University; Hospital for Sick Children","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Categorization; Wavelet; Diffusion MRI; Fuzzy logic; Computer vision; Radiology; Medicine; Magnetic resonance imaging","score_opus":0.07758830664647474,"score_gpt":0.39900391453390194,"score_spread":0.3214156078874272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023735007","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1183311,0.0008145785,0.8763256,0.0031494403,0.00013743779,0.0010079761,0.000036423786,0.00017430613,0.00002312628],"genre_scores_gemma":[0.07616415,0.00013470059,0.9223594,0.0003392645,0.0005150301,0.00023256309,0.00020410132,0.000022512262,0.000028300197],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986195,0.00006012731,0.00040349865,0.0005210148,0.00015317753,0.00024268654],"domain_scores_gemma":[0.99859184,0.0005432859,0.00014055359,0.00032274608,0.00011462975,0.00028697378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058585225,0.00020270157,0.00055449427,0.00056974636,0.00011537907,0.000032636726,0.000084997475,0.000105280145,0.0000041639173],"category_scores_gemma":[0.00010846232,0.00015130184,0.000105345076,0.0012061156,0.00023007148,0.000069540554,0.000100211575,0.00025869047,2.3155572e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012467564,0.00053420477,0.106072515,0.0005380354,0.00019753695,0.000016188113,0.00018915876,3.0474794e-7,0.016475786,0.015126158,0.00029183025,0.8604336],"study_design_scores_gemma":[0.0075940434,0.0007858111,0.67933613,0.00019087392,0.0033327146,0.00029677313,0.00008681284,0.2316963,0.00022996445,0.006610394,0.0692267,0.0006134882],"about_ca_topic_score_codex":0.000010352126,"about_ca_topic_score_gemma":0.0000016813211,"teacher_disagreement_score":0.8598201,"about_ca_system_score_codex":0.000012255548,"about_ca_system_score_gemma":0.000035601846,"threshold_uncertainty_score":0.616991},"labels":[],"label_agreement":null},{"id":"W2023855780","doi":"10.1002/hbm.20248","title":"Inference for magnitudes and delays of responses in the FIAC data using BRAINSTAT/FMRISTAT","year":2006,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Smoothing; Inference; Novelty; Magnitude (astronomy); Computer science; Voxel; Mathematics; Psychology; Artificial intelligence; Statistics; Physics","score_opus":0.32076986253226,"score_gpt":0.4558225273935523,"score_spread":0.1350526648612923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2023855780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8518602,0.0001553982,0.14333051,0.0032663133,0.0000050914996,0.00073895266,0.00007416162,0.0000523895,0.00051697734],"genre_scores_gemma":[0.94927233,0.00001018532,0.04978155,0.0006988324,0.00003729972,0.000028281305,0.00008259701,0.000011719773,0.000077213204],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993202,0.000037735826,0.00021802564,0.00021332558,0.00008249825,0.00012820333],"domain_scores_gemma":[0.99881667,0.0006030459,0.00008217831,0.00044377873,0.00003962437,0.000014714718],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039965397,0.000077097146,0.00013226223,0.00010017328,0.00013172442,0.000019037669,0.00017228226,0.000022373873,0.000002781276],"category_scores_gemma":[0.000288519,0.00006340693,0.000017313128,0.00013766636,0.0001142869,0.000083743915,0.000089763904,0.00009204924,1.297943e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110765985,0.00019087568,0.043095134,0.0005735195,0.00001487954,0.000025403984,0.0014528141,0.00006103547,0.86990845,0.07194512,0.0090476405,0.003574332],"study_design_scores_gemma":[0.0032134296,0.00033922377,0.7146627,0.0012256776,0.00010411145,0.0001599452,0.0021728596,0.023519956,0.0022838514,0.1190411,0.13269351,0.0005836729],"about_ca_topic_score_codex":0.00008172168,"about_ca_topic_score_gemma":0.000043232456,"teacher_disagreement_score":0.86762464,"about_ca_system_score_codex":0.000012596078,"about_ca_system_score_gemma":0.000025580768,"threshold_uncertainty_score":0.25856593},"labels":[],"label_agreement":null},{"id":"W2024559117","doi":"10.1117/12.2043493","title":"A dual spherical model for multi-shell diffusion imaging","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spherical harmonics; Diffusion; Spherical mean; Kurtosis; Parametric statistics; Metric (unit); Algorithm; Spherical shell; Physics; Computer science; Mathematical analysis; Mathematics; Shell (structure)","score_opus":0.03398852031043575,"score_gpt":0.29615372903892545,"score_spread":0.2621652087284897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024559117","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9545953,0.00003752999,0.038471337,0.004827943,0.00007443353,0.0010163715,0.00004094114,0.00020268129,0.0007334467],"genre_scores_gemma":[0.24193068,0.000048321053,0.75644463,0.0003905885,0.0003222657,0.00036680608,0.000013498663,0.00008042334,0.0004027667],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99816436,8.179052e-9,0.00057169853,0.00044576838,0.0004419156,0.0003762575],"domain_scores_gemma":[0.9981004,0.00012266915,0.00028421733,0.00008262324,0.0012576444,0.00015242425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037191628,0.00028591687,0.0004211417,0.000066210785,0.00010433463,0.000051454135,0.0004363276,0.000117496864,0.0000040845116],"category_scores_gemma":[0.00062707404,0.00023560741,0.0006310376,0.00020002002,0.00020379842,0.00025905017,0.00015971417,0.00029141814,8.222698e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012201381,0.00025076218,0.0005978282,0.00039945045,0.00008506221,4.7081794e-8,0.000088372886,0.00016775564,0.70434463,0.28983596,0.0031549674,0.0009531829],"study_design_scores_gemma":[0.0016430852,0.00020881946,0.00051082985,0.00022554466,0.00017044027,0.000026955038,0.00018078044,0.92749804,0.060595416,0.0030054862,0.0056860633,0.00024856633],"about_ca_topic_score_codex":0.0000031935608,"about_ca_topic_score_gemma":4.528087e-8,"teacher_disagreement_score":0.92733026,"about_ca_system_score_codex":0.00011372776,"about_ca_system_score_gemma":0.00002752736,"threshold_uncertainty_score":0.96077913},"labels":[],"label_agreement":null},{"id":"W2024966367","doi":"10.1016/j.neuroimage.2014.07.030","title":"Structural network analysis of brain development in young preterm neonates","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; BC Children's Hospital; University of Toronto; Simon Fraser University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Michael Smith Health Research BC; Government of Alberta","keywords":"Connectome; Diffusion MRI; Brain development; Connectomics; White matter; Tractography; Neuroscience; Fractional anisotropy; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity","score_opus":0.03382792514136341,"score_gpt":0.32506724283525584,"score_spread":0.29123931769389244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2024966367","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98989576,0.000020310335,0.007115499,0.00065388344,0.00002670027,0.00023366018,0.000003246882,0.00009445922,0.0019564733],"genre_scores_gemma":[0.9762089,0.0000055495602,0.023008805,0.0005339421,0.000028218214,0.000020390973,0.000029790901,0.000015570982,0.00014880302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911165,0.0000331743,0.000279914,0.0002563422,0.0001331836,0.00018574206],"domain_scores_gemma":[0.9993864,0.00009897049,0.00009140167,0.00033531862,0.00003775592,0.0000501147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116681214,0.00010491705,0.00028237092,0.00017980393,0.000036647747,0.000007445192,0.000103152146,0.000027778291,0.000026374752],"category_scores_gemma":[0.00008982014,0.00009619839,0.00007222315,0.0007322083,0.000049805258,0.000044374956,0.000054407723,0.00014095634,0.0000017850439],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081632475,0.000064419626,0.9245553,0.000064951055,0.000104014005,0.000020171454,0.00030188682,0.0019660948,0.04139002,0.0023772686,0.0007299812,0.028344266],"study_design_scores_gemma":[0.0002964062,0.000048044298,0.9714686,0.000024113795,0.0001050651,0.00001073156,0.0000029989972,0.019974258,0.004056274,0.00047970738,0.0034392728,0.00009449726],"about_ca_topic_score_codex":0.000015895188,"about_ca_topic_score_gemma":0.000033731638,"teacher_disagreement_score":0.046913337,"about_ca_system_score_codex":0.000019847901,"about_ca_system_score_gemma":0.00001690713,"threshold_uncertainty_score":0.39228565},"labels":[],"label_agreement":null},{"id":"W2025558610","doi":"10.1016/j.neuroimage.2014.05.017","title":"Pathways linking regional hyperintensities in the brain and slower gait","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Nursing Research; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"Hyperintensity; Gait; Digit symbol substitution test; Psychology; Physical medicine and rehabilitation; Cognition; Executive dysfunction; Neuroscience; Medicine; Magnetic resonance imaging; Pathology; Neuropsychology; Radiology","score_opus":0.08320849423806391,"score_gpt":0.31674733620989903,"score_spread":0.2335388419718351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025558610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9315373,0.00007237294,0.0070689856,0.049409855,0.00003760614,0.0004038161,0.000003578155,0.00021029028,0.011256241],"genre_scores_gemma":[0.9704412,0.000041907042,0.0033150462,0.02586967,0.0000924723,0.000028874167,0.0000060133775,0.000017632496,0.00018713438],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993781,0.000041434545,0.000114385315,0.00021409059,0.00011595133,0.00013604194],"domain_scores_gemma":[0.99939865,0.00020614742,0.000029263707,0.00030675167,0.000026716973,0.000032479056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016319657,0.00008631915,0.00011202116,0.00004936648,0.00006692555,0.000022209168,0.00008248157,0.000023985544,0.000004953728],"category_scores_gemma":[0.00011286157,0.000062511615,0.000030458361,0.00009750277,0.00010675759,0.000046806843,0.0000407379,0.0002457438,0.0000056115027],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002528715,0.00059129484,0.042565312,0.00028580552,0.000015103076,0.00064690836,0.003696512,0.000020289664,0.61771375,0.18107106,0.059947394,0.093193725],"study_design_scores_gemma":[0.0011974251,0.00038035747,0.3507563,0.0001671432,0.000026633326,0.0015517063,0.00027883198,0.003982054,0.0022233692,0.021035377,0.6181126,0.0002882081],"about_ca_topic_score_codex":0.000005805541,"about_ca_topic_score_gemma":0.0000016427917,"teacher_disagreement_score":0.6154904,"about_ca_system_score_codex":0.000006160365,"about_ca_system_score_gemma":0.00000860322,"threshold_uncertainty_score":0.25491497},"labels":[],"label_agreement":null},{"id":"W2025904718","doi":"10.1089/neu.2012.2818","title":"Combining Whole-Brain Voxel-Wise Analysis with <i>In Vivo</i> Tractography of Diffusion Behavior after Sports-Related Concussion in Adolescents: A Preliminary Report","year":2013,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; University of British Columbia","funders":"Centers for Disease Control and Prevention","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Concussion; Tractography; Voxel; Traumatic brain injury; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Poison control; Radiology; Psychiatry; Injury prevention","score_opus":0.028456270786747027,"score_gpt":0.32057474693283416,"score_spread":0.29211847614608716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025904718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969608,0.00009103622,0.00045678875,0.0017269249,0.00002694397,0.00064467324,0.000003393771,0.000024423933,0.00006497441],"genre_scores_gemma":[0.99819005,0.00003754609,0.0012914096,0.00030808427,0.000014581112,0.0000618849,0.000003893327,0.000030276684,0.00006227576],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979291,0.000057403664,0.0011202712,0.0002591318,0.0004313577,0.00020276748],"domain_scores_gemma":[0.998399,0.00004936641,0.0008692744,0.0003589733,0.00017760546,0.00014577332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021421547,0.00018267118,0.00058191706,0.00091884885,0.00002553291,0.000011682114,0.00011701998,0.00008220322,0.000042248532],"category_scores_gemma":[0.000051374107,0.00013401853,0.00025014186,0.0012254354,0.00009163454,0.00023581693,0.000032436088,0.0005989426,4.4411792e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007208195,0.0016136569,0.9227565,0.000057329442,0.000029143335,0.0041480367,0.00020597494,0.000059993075,0.06724763,0.0000026649698,0.00011827662,0.0030399587],"study_design_scores_gemma":[0.0020885726,0.0009637043,0.99022937,0.0014615987,0.0004039732,0.0016436019,0.00009065348,0.0002479795,0.0025329718,0.000054055363,0.0001613397,0.00012220563],"about_ca_topic_score_codex":0.00003759676,"about_ca_topic_score_gemma":0.000007740687,"teacher_disagreement_score":0.06747283,"about_ca_system_score_codex":0.000032404085,"about_ca_system_score_gemma":0.000046599722,"threshold_uncertainty_score":0.5465117},"labels":[],"label_agreement":null},{"id":"W2026088781","doi":"10.1016/j.neuropsychologia.2008.02.017","title":"Ipsilateral cortical representation of tactile and painful information in acallosal and callosotomized subjects","year":2008,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Corpus callosum; Insula; Neuroscience; Functional magnetic resonance imaging; Neuroplasticity; Magnetic resonance imaging; Stimulation; Agenesis; Agenesis of the corpus callosum; Sensory stimulation therapy; Cingulate cortex; Audiology; Anatomy; Medicine; Central nervous system; Radiology","score_opus":0.06905991710939997,"score_gpt":0.3613725698606633,"score_spread":0.29231265275126334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026088781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99670935,0.000010319725,0.0015386587,0.00063382083,0.000018533596,0.0003121237,0.000002364979,0.00006370302,0.00071109954],"genre_scores_gemma":[0.9953509,0.00016372841,0.003782655,0.00062949106,0.000009595413,0.000023545726,0.000008865536,0.0000060968487,0.000025121697],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994077,0.00003875905,0.00023055321,0.0001450617,0.00008292224,0.00009497231],"domain_scores_gemma":[0.99961764,0.00007946116,0.00006717248,0.0001542339,0.00003206413,0.000049445774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053357944,0.000067580804,0.0001542809,0.000086376,0.00003089484,0.0000045192537,0.000028679935,0.00004591901,0.0000064915266],"category_scores_gemma":[0.00017534095,0.00006058649,0.00001700411,0.00015249975,0.00013166927,0.00014939725,0.000027067503,0.00018450782,0.0000017107367],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010625393,0.00019844473,0.8817447,0.00006255208,0.0000072688613,0.0001106222,0.00046594132,0.000008193863,0.10856179,0.0008495074,0.00079231284,0.0061361557],"study_design_scores_gemma":[0.001545708,0.00017878151,0.9930406,0.000015778549,0.0000075956436,0.00038220774,0.000013798518,0.001053289,0.003277742,0.00017783932,0.00025409393,0.00005256983],"about_ca_topic_score_codex":0.000012753506,"about_ca_topic_score_gemma":4.197623e-7,"teacher_disagreement_score":0.11129592,"about_ca_system_score_codex":0.000006190268,"about_ca_system_score_gemma":0.0000088764955,"threshold_uncertainty_score":0.24706455},"labels":[],"label_agreement":null},{"id":"W2026527527","doi":"10.1016/j.jpsychires.2010.07.007","title":"Fronto-temporal disconnectivity and clinical short-term outcome in first episode psychosis: A DTI-tractography study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Uncinate fasciculus; Fractional anisotropy; Psychosis; Cingulum (brain); White matter; Inferior longitudinal fasciculus; Psychology; Superior longitudinal fasciculus; Diffusion MRI; Fasciculus; Tractography; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.22425807753606666,"score_gpt":0.5432082754350517,"score_spread":0.31895019789898504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026527527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898776,0.00025092432,0.0010649735,0.0073252767,0.00031320014,0.0008642112,0.000003917162,0.000022552837,0.0002773617],"genre_scores_gemma":[0.9851915,0.00042674263,0.013716372,0.000052534207,0.0005208402,0.000037996364,8.8653246e-7,0.000025268499,0.000027808352],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973323,0.00021260965,0.0010754531,0.00036343708,0.0006698136,0.0003464114],"domain_scores_gemma":[0.9981911,0.0004767676,0.00022050219,0.00053324393,0.0002513754,0.00032699766],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0038182691,0.00014880799,0.0005149557,0.00088299863,0.00015446534,0.00005330334,0.00030862234,0.00011767118,0.000022318105],"category_scores_gemma":[0.000390738,0.00011204253,0.00022703785,0.00091372855,0.00020865157,0.00016440591,0.00008951993,0.0030591576,0.0000025432994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030841856,0.002752113,0.9900202,0.000028485085,0.000033994864,0.00009387074,0.00006736509,2.2053771e-7,0.000107553424,0.00008481551,0.0012342533,0.005268711],"study_design_scores_gemma":[0.0018438981,0.0017224399,0.99173504,0.0000371591,0.000054549313,0.00022527068,0.00017493522,0.00005476786,0.0000070849433,0.0017166497,0.0023289146,0.000099313045],"about_ca_topic_score_codex":0.0001818436,"about_ca_topic_score_gemma":0.001457719,"teacher_disagreement_score":0.012651398,"about_ca_system_score_codex":0.000032334938,"about_ca_system_score_gemma":0.000060167815,"threshold_uncertainty_score":0.9992408},"labels":[],"label_agreement":null},{"id":"W2027359048","doi":"10.1016/j.schres.2014.09.037","title":"A diffusion tensor imaging family study of the fornix in schizophrenia","year":2014,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"KU Leuven; Canadian Institutes of Health Research; European Commission; University of Calgary","keywords":"Fornix; Fractional anisotropy; Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Psychology; Neuroimaging; Abnormality; Neuroscience; Psychosis; Psychiatry; Magnetic resonance imaging; Medicine; Radiology; Hippocampus","score_opus":0.10979172091697886,"score_gpt":0.4104373090531239,"score_spread":0.30064558813614506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027359048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99395686,0.00008029606,0.00029746382,0.0022195065,0.00004088213,0.0016437725,0.0000045551606,0.00009253232,0.0016641241],"genre_scores_gemma":[0.9958005,0.000025038791,0.0034604238,0.00011580241,0.00009643964,0.00021702186,0.000002724299,0.000041044827,0.00024100435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99751246,0.00032753486,0.00039572865,0.000479242,0.00083678454,0.00044826776],"domain_scores_gemma":[0.99808246,0.00026657706,0.0000837619,0.0011908637,0.0002640827,0.00011227398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010542703,0.00015797873,0.00030570448,0.00041017638,0.0002562191,0.00002564153,0.0004937108,0.000048456346,0.000014016009],"category_scores_gemma":[0.000546926,0.00010756872,0.000084913976,0.0013236741,0.00024894602,0.000070639144,0.00048731462,0.0009808539,0.000019864978],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004403491,0.004144731,0.6203099,0.0001828616,0.00003079581,0.000043375534,0.0008642212,0.00004049966,0.18967731,0.013573495,0.0027779925,0.16395137],"study_design_scores_gemma":[0.0068323165,0.0004956747,0.9686207,0.00027231887,0.000023241233,0.000027575114,0.0006441907,0.004515796,0.002396109,0.012972768,0.0030246652,0.00017464],"about_ca_topic_score_codex":0.000234472,"about_ca_topic_score_gemma":0.0000761379,"teacher_disagreement_score":0.34831086,"about_ca_system_score_codex":0.000076128395,"about_ca_system_score_gemma":0.00011296969,"threshold_uncertainty_score":0.4386525},"labels":[],"label_agreement":null},{"id":"W2027591786","doi":"10.1186/1471-2202-9-84","title":"Detecting functional magnetic resonance imaging activation in white matter: Interhemispheric transfer across the corpus callosum","year":2008,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; Dalhousie University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Dalhousie University; L'Oreal USA","keywords":"Corpus callosum; White matter; Functional magnetic resonance imaging; Neuroscience; Magnetic resonance imaging; Psychology; Brain mapping; Medicine; Radiology","score_opus":0.06101308915189367,"score_gpt":0.3137955577162156,"score_spread":0.2527824685643219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027591786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87121123,0.00008909261,0.12650011,0.001363325,0.00009367834,0.00034283425,0.0000026817636,0.000116953066,0.0002800994],"genre_scores_gemma":[0.994704,0.000028498449,0.0016018809,0.0027708786,0.000038213668,0.00009993586,0.0000010481044,0.00001880698,0.00073675736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998821,0.00002902185,0.0002126441,0.00041521006,0.00023140587,0.00029070312],"domain_scores_gemma":[0.9994674,0.000078601755,0.00003608354,0.0003266902,0.000040470743,0.00005075967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011533793,0.00012021321,0.000107755564,0.000035058198,0.0003143669,0.000024995199,0.00018115192,0.000019118923,0.000021589158],"category_scores_gemma":[0.00009532277,0.00009558918,0.000044928845,0.00061049685,0.0003123493,0.00017488666,0.000057093355,0.00028038232,0.000008159839],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050965446,0.000058553636,0.7705262,0.0000124305225,9.216863e-8,0.000013630066,0.00018763253,0.00012481588,0.22315134,0.000028966173,0.00017860648,0.0056667705],"study_design_scores_gemma":[0.00032676538,0.000038726597,0.97458905,0.000044984135,0.0000024894327,0.00047321687,0.00003997887,0.00670734,0.01401947,0.000060375118,0.003596932,0.00010066003],"about_ca_topic_score_codex":0.00001614597,"about_ca_topic_score_gemma":0.000008190531,"teacher_disagreement_score":0.20913188,"about_ca_system_score_codex":0.000049420225,"about_ca_system_score_gemma":0.0000495355,"threshold_uncertainty_score":0.38980138},"labels":[],"label_agreement":null},{"id":"W2028110903","doi":"10.1002/mrm.21640","title":"DWI of the spinal cord with reduced FOV single‐shot EPI","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":267,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Echo-planar imaging; Sagittal plane; Spinal cord; Physics; Field of view; Nuclear magnetic resonance; Single shot; Magnetic resonance imaging; Pulse (music); Diffusion MRI; SIGNAL (programming language); Nuclear medicine; Biomedical engineering; Optics; Medicine; Computer science; Anatomy; Radiology; Detector","score_opus":0.12057208484698714,"score_gpt":0.3621718104925367,"score_spread":0.24159972564554957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028110903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96276134,0.0056322324,0.00042894343,0.020809742,0.000067234105,0.0008594246,0.0000023932148,0.00007343146,0.009365259],"genre_scores_gemma":[0.9911579,0.00058018236,0.005560965,0.0010027698,0.00010565459,0.00007241872,0.000001971261,0.000023322738,0.0014948524],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99877334,0.000028842904,0.0003201459,0.00028512737,0.00036927973,0.00022324474],"domain_scores_gemma":[0.99903023,0.000047325582,0.000119691504,0.00064509484,0.000091209724,0.00006644977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011729014,0.0001460456,0.00034624236,0.00007915885,0.00006109244,0.0000012191979,0.00020206327,0.000041747804,0.00005776538],"category_scores_gemma":[0.00017870082,0.000085755266,0.000035855977,0.0006251807,0.0008205674,0.000024437175,0.000043493274,0.00027808698,0.0000020033365],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045419424,0.0011425893,0.1898847,0.00037246468,0.000013016956,0.00064644474,0.0007935841,0.000015069335,0.41787043,0.0031445373,0.019159177,0.36241606],"study_design_scores_gemma":[0.0028186557,0.007227084,0.86163855,0.0022650089,0.000054807646,0.0012163549,0.00009126702,0.000120669465,0.017699677,0.00080086064,0.10588581,0.00018123734],"about_ca_topic_score_codex":0.00005793105,"about_ca_topic_score_gemma":0.000008803102,"teacher_disagreement_score":0.6717539,"about_ca_system_score_codex":0.00004139442,"about_ca_system_score_gemma":0.00006408055,"threshold_uncertainty_score":0.34969983},"labels":[],"label_agreement":null},{"id":"W2028382446","doi":"10.1002/mrm.22873","title":"Insight into in vivo magnetization exchange in human white matter regions","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Magnetization transfer; Relaxation (psychology); Chemistry; Magnetization; Nuclear magnetic resonance; Relaxometry; Magnetic resonance imaging; Biophysics; Chemical physics; Physics; Central nervous system; Magnetic field; Neuroscience; Biology; Spin echo","score_opus":0.06512422960414306,"score_gpt":0.3303473079514085,"score_spread":0.26522307834726544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028382446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7719634,0.014318201,0.0030596855,0.02903174,0.00018410783,0.0035921896,0.0000060522193,0.0002882606,0.17755632],"genre_scores_gemma":[0.97678226,0.0019043955,0.010899014,0.00353955,0.0001304655,0.0005920282,0.000019548448,0.000059479804,0.0060732313],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99834067,0.00006029952,0.0005819199,0.0004652436,0.00022461724,0.00032727496],"domain_scores_gemma":[0.99918896,0.00003606076,0.000082706756,0.000559467,0.000046088,0.000086694774],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00024189308,0.00020109797,0.00039223523,0.00060841197,0.000034981153,0.000003909582,0.00018183881,0.00010058113,0.002122712],"category_scores_gemma":[0.00006841181,0.00018044122,0.00002533987,0.0010532376,0.00024809022,0.00008575235,0.0000658236,0.0003778587,0.000019198222],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105401574,0.00038955561,0.95635456,0.00016675168,8.0321325e-7,0.0003314477,0.007924473,0.0000024436818,0.006476671,0.0018632615,0.009168547,0.01721608],"study_design_scores_gemma":[0.0021360742,0.00050763594,0.9142459,0.0009861039,0.000011090969,0.00004007317,0.00015793965,0.0002599702,0.0004612282,0.007181255,0.07382605,0.00018669823],"about_ca_topic_score_codex":0.0009448437,"about_ca_topic_score_gemma":0.0009755357,"teacher_disagreement_score":0.20481884,"about_ca_system_score_codex":0.000108962195,"about_ca_system_score_gemma":0.00002181514,"threshold_uncertainty_score":0.9987895},"labels":[],"label_agreement":null},{"id":"W2028655791","doi":"10.1016/j.neuroimage.2014.03.029","title":"Fast and accurate modelling of longitudinal and repeated measures neuroimaging data","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":214,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Wellcome Trust; Synarc; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Longitudinal data; Psychology; Cognitive psychology; Computer science; Econometrics; Neuroscience; Data mining; Mathematics","score_opus":0.22642524957313795,"score_gpt":0.36751344285178345,"score_spread":0.1410881932786455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028655791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47744182,0.00026803094,0.51742905,0.002241175,0.000034376473,0.00041144033,0.000043147647,0.00029672173,0.0018342125],"genre_scores_gemma":[0.9758855,0.00037191427,0.023241434,0.00032893603,0.0000430655,0.0000056784816,0.000025546284,0.000034850473,0.000063075575],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987904,0.00004088278,0.00025270064,0.0005763239,0.00016072145,0.00017897051],"domain_scores_gemma":[0.99868596,0.00009840334,0.000112646776,0.0009168397,0.00007971884,0.00010644693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019993985,0.00015070308,0.000256205,0.000085417385,0.000090013964,0.00003140385,0.0001597435,0.000026772062,0.0000029613266],"category_scores_gemma":[0.00016796877,0.00014002291,0.000021699972,0.00014404138,0.00018194308,0.0002125446,0.00029028952,0.00022549322,0.0000011026631],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005055558,0.000494059,0.15859817,0.0009701482,0.000079773345,0.00023634598,0.00032445128,0.002195045,0.58665574,0.0052597974,0.0030253753,0.24165556],"study_design_scores_gemma":[0.0014352261,0.00030858917,0.09130242,0.00019475081,0.00023736089,0.0008717132,0.000023486324,0.88053524,0.011937275,0.0018673266,0.010909569,0.0003770483],"about_ca_topic_score_codex":0.000023688557,"about_ca_topic_score_gemma":9.161735e-7,"teacher_disagreement_score":0.8783402,"about_ca_system_score_codex":0.000003903578,"about_ca_system_score_gemma":0.000013325305,"threshold_uncertainty_score":0.5709969},"labels":[],"label_agreement":null},{"id":"W2028729341","doi":"10.1109/bmei.2011.6098482","title":"Model-free marginal orientation distribution function reconstruction in single-shell Q-Ball imaging","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Orientation (vector space); Computer science; Angular resolution (graph drawing); Artificial intelligence; Iterative reconstruction; Imaging phantom; Tomographic reconstruction; Diffusion MRI; Marginal distribution; Computer vision; Algorithm; Mathematics; Physics; Optics; Geometry","score_opus":0.11157469956844793,"score_gpt":0.30634302494673565,"score_spread":0.19476832537828773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028729341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15061016,0.000016084317,0.8323703,0.000524599,0.0000821941,0.0003507566,0.000011927713,0.0003256248,0.015708355],"genre_scores_gemma":[0.9241031,0.000018275987,0.075151235,0.00021807585,0.000038041846,0.000053927182,0.00012320874,0.0000152075745,0.00027896394],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999205,0.000012586805,0.00023167231,0.00027707274,0.00011006999,0.00016358026],"domain_scores_gemma":[0.9994645,0.000009235499,0.00007405593,0.0003106158,0.000085856416,0.00005574068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008770956,0.00010355345,0.00010730424,0.00009436091,0.000053955497,0.000009475693,0.0000576662,0.000037606733,0.000089498506],"category_scores_gemma":[0.000033519096,0.00010215943,0.00003948049,0.00023754739,0.000052632164,0.00026981893,0.00002959305,0.00014502146,0.000012010976],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015888005,0.0015973719,0.32092658,0.00013322626,0.000026208689,0.000038112074,0.00043972634,0.00044290046,0.18391553,0.11903905,0.0064122,0.3654403],"study_design_scores_gemma":[0.005848752,0.0006979812,0.27886137,0.00033637742,0.00026663844,0.00090511667,0.0006409046,0.3653735,0.08628189,0.25421295,0.0056577353,0.0009167978],"about_ca_topic_score_codex":0.00004886733,"about_ca_topic_score_gemma":0.000014123205,"teacher_disagreement_score":0.77349293,"about_ca_system_score_codex":0.0001567651,"about_ca_system_score_gemma":0.000023849954,"threshold_uncertainty_score":0.41659406},"labels":[],"label_agreement":null},{"id":"W2028748733","doi":"10.1016/j.nicl.2013.07.006","title":"Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":364,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; GE Healthcare; Genentech; National Institutes of Health; U.S. National Library of Medicine; Takeda Pharmaceutical Company; IXICO; Servier; Eisai; Northern California Institute for Research and Education; Synarc; Bayer HealthCare; Meso Scale Diagnostics; Medpace; DoD Alzheimer's Disease Neuroimaging Initiative; BioClinica; Pfizer; Biogen; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; National Institute on Aging; Abbott Laboratories; National Center for Research Resources; F. Hoffmann-La Roche","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Psychology; Neuroimaging; Cingulum (brain); Alzheimer's Disease Neuroimaging Initiative; Dementia; Alzheimer's disease; Neuroscience; Medicine; Nuclear medicine; Cognitive impairment; Magnetic resonance imaging; Cognition; Disease; Internal medicine; Radiology","score_opus":0.17854415510055016,"score_gpt":0.4330612784330466,"score_spread":0.25451712333249643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028748733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99381495,0.0005016377,0.0021119472,0.001963201,0.00006365199,0.00078505505,0.000006935468,0.00012888499,0.0006237424],"genre_scores_gemma":[0.99543124,0.00016972594,0.003700705,0.00048625795,0.0000914454,0.00007027806,0.000010327423,0.000027789312,0.000012229225],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847823,0.00019927061,0.00048239587,0.00044615378,0.00019408365,0.00019986612],"domain_scores_gemma":[0.9980964,0.0010829195,0.00012503497,0.00037433254,0.00011952978,0.00020174783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005320403,0.00013686137,0.0003474553,0.00007404019,0.000049006325,0.000019770863,0.000111828005,0.00004856468,0.000008574025],"category_scores_gemma":[0.0012263285,0.00012539851,0.00010071918,0.00015849141,0.00030121816,0.00014529063,0.00011891653,0.00042547824,0.000004807489],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002131701,0.00038836623,0.9595954,0.00015788921,0.00001830147,0.00008926843,0.0000190761,0.000009034579,0.0038333435,0.00064383954,0.00046279145,0.034569535],"study_design_scores_gemma":[0.0007971945,0.00010877995,0.9947354,0.0002811278,0.000065725595,0.00003003089,0.0000060334555,0.00076638954,0.0005308758,0.0016912466,0.0008809036,0.000106259824],"about_ca_topic_score_codex":0.0000565147,"about_ca_topic_score_gemma":0.0000013627798,"teacher_disagreement_score":0.03514005,"about_ca_system_score_codex":0.000009219011,"about_ca_system_score_gemma":0.000040273728,"threshold_uncertainty_score":0.5113603},"labels":[],"label_agreement":null},{"id":"W2029334347","doi":"10.1016/j.neuroimage.2007.03.041","title":"Integrity of white matter in the corpus callosum correlates with bimanual co-ordination skills","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":273,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Wellcome Trust","keywords":"Corpus callosum; White matter; Variation (astronomy); Tractography; Ordination; Psychology; Diffusion MRI; Neuroscience; Magnetic resonance imaging; Biology; Medicine","score_opus":0.03087854053533767,"score_gpt":0.34634432292921036,"score_spread":0.3154657823938727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029334347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9514519,0.000018402246,0.03370044,0.0035464033,0.000028352415,0.0006248153,0.00001268996,0.000082193284,0.010534829],"genre_scores_gemma":[0.99222875,0.00001596795,0.005342053,0.0019657542,0.000025065714,0.00001887163,0.000020320786,0.000020612846,0.00036263533],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914694,0.000033345455,0.00023921815,0.00021924265,0.0001821192,0.0001791114],"domain_scores_gemma":[0.9992546,0.00016209087,0.000104488674,0.00036786665,0.00007387668,0.000037088055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026442707,0.00011414628,0.00016393466,0.00011884912,0.00005739188,0.000008189303,0.00013371951,0.00004191576,0.000033786575],"category_scores_gemma":[0.000045273424,0.00007443495,0.00003833948,0.00030819158,0.00015007025,0.00007816274,0.000031289037,0.00046025767,0.000014800064],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001357176,0.0005013352,0.97417414,0.00004517682,0.000004753181,0.00012266423,0.0004713669,0.0000046766095,0.01758004,0.0009956028,0.0027305952,0.0032339124],"study_design_scores_gemma":[0.0006171987,0.00025260952,0.9825082,0.000058035854,0.000026119773,0.00026581384,0.000071461225,0.00011204027,0.010401147,0.000483571,0.0051111397,0.000092664195],"about_ca_topic_score_codex":0.000018531491,"about_ca_topic_score_gemma":0.000009422891,"teacher_disagreement_score":0.040776845,"about_ca_system_score_codex":0.000021851514,"about_ca_system_score_gemma":0.000017942823,"threshold_uncertainty_score":0.30353695},"labels":[],"label_agreement":null},{"id":"W2029665903","doi":"10.1016/j.media.2011.01.005","title":"Extracting skeletal muscle fiber fields from noisy diffusion tensor data","year":2011,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Canada Research Chairs","keywords":"Smoothing; Diffusion MRI; Noise (video); Tensor (intrinsic definition); Noise reduction; Artificial intelligence; Pattern recognition (psychology); Mathematics; Fiber; Synthetic data; SIGNAL (programming language); Computer science; Algorithm; Computer vision; Geometry","score_opus":0.1199979832209549,"score_gpt":0.37935965336528793,"score_spread":0.25936167014433303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029665903","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38293886,0.00020432606,0.5955779,0.0067895157,0.000054138924,0.00031684665,0.00012534366,0.00054945325,0.013443631],"genre_scores_gemma":[0.88411784,0.00016569396,0.11139059,0.0018670246,0.00027742036,0.000023518685,0.00074700697,0.000029297722,0.001381579],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984352,0.000033686,0.00032283802,0.0005335751,0.00045287146,0.0002218565],"domain_scores_gemma":[0.99807554,0.00015090367,0.000099880766,0.0013306888,0.000068747184,0.00027424048],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00020473823,0.0001373666,0.0003405049,0.0001272695,0.000097822456,0.000015736983,0.00041370586,0.00011370004,0.011532795],"category_scores_gemma":[0.0006775911,0.000108843,0.00017435948,0.0005479286,0.0001243307,0.00016896428,0.00034149,0.00041883232,0.00014142568],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007714307,0.0025370924,0.062174987,0.00006500159,0.0017174954,0.0019008443,0.00071251247,0.0000016027478,0.019906549,0.000097125456,0.033637878,0.87717175],"study_design_scores_gemma":[0.0022752099,0.00022181132,0.6173186,0.00022673847,0.012561139,0.00009565859,0.00041594208,0.14549552,0.0058771814,0.002114331,0.21233514,0.0010627562],"about_ca_topic_score_codex":0.0007747508,"about_ca_topic_score_gemma":0.0000467189,"teacher_disagreement_score":0.876109,"about_ca_system_score_codex":0.000014522503,"about_ca_system_score_gemma":0.000030700758,"threshold_uncertainty_score":0.9893708},"labels":[],"label_agreement":null},{"id":"W2029713109","doi":"10.1038/sj.mp.4001337","title":"Abnormalities of myelination in schizophrenia detected in vivo with MRI, and post-mortem with analysis of oligodendrocyte proteins","year":2003,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":436,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health; U.S. Public Health Service","keywords":"White matter; Corpus callosum; Oligodendrocyte; Myelin; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Neuroscience; Myelin oligodendrocyte glycoprotein; Internal medicine; Endocrinology; Medicine; Magnetic resonance imaging; Central nervous system; Psychiatry","score_opus":0.008951304575866462,"score_gpt":0.2668794506618652,"score_spread":0.25792814608599873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029713109","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754165,0.00025008817,0.023275208,0.00019824994,0.000004144767,0.00048101044,0.0000123783375,0.000025511254,0.00033691764],"genre_scores_gemma":[0.91479504,0.000028492695,0.08502374,0.000056660025,0.000002109144,0.00005951187,0.000008068744,0.000014943838,0.000011413079],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992459,0.00003387103,0.00025222468,0.0002061417,0.00014987733,0.00011200677],"domain_scores_gemma":[0.99946195,0.000010797658,0.00012839628,0.0002714341,0.00009316089,0.000034253768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000074628384,0.00010745532,0.0002733465,0.0004958191,0.00001576891,0.000003208327,0.000043689168,0.0000348,0.000005828645],"category_scores_gemma":[0.000016097578,0.00008918627,0.000033086762,0.0012149533,0.000060801765,0.000042506857,0.0000091647335,0.000113103444,5.8529515e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016573333,0.00090557925,0.7133818,0.00063280977,0.00047727596,0.00007424543,0.00040911755,0.0018674773,0.24481235,0.035276752,0.0000064048013,0.00049883587],"study_design_scores_gemma":[0.0046465895,0.0011857473,0.59641165,0.00067945436,0.00086239754,0.00012675971,0.0004356802,0.0016830376,0.3926249,0.00095879455,0.000050404768,0.00033456282],"about_ca_topic_score_codex":0.00010181304,"about_ca_topic_score_gemma":0.00067436724,"teacher_disagreement_score":0.14781258,"about_ca_system_score_codex":0.000016232556,"about_ca_system_score_gemma":0.0000928352,"threshold_uncertainty_score":0.36369106},"labels":[],"label_agreement":null},{"id":"W2029753145","doi":"10.1016/j.jsb.2014.09.009","title":"Changes in tissue directionality reflect differences in myelin content after demyelination in mice spinal cords","year":2014,"lang":"en","type":"article","venue":"Journal of Structural Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Luxol fast blue stain; Myelin; Multiple sclerosis; White matter; Pathology; Spinal cord; Demyelinating Disorder; Anatomy; Biology; Neuroscience; Medicine; Magnetic resonance imaging; Central nervous system; Immunology","score_opus":0.10685348356387424,"score_gpt":0.4028782614716706,"score_spread":0.29602477790779635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029753145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99317926,0.00024718678,0.00047715686,0.0058167246,0.00010557275,0.00012606684,0.000002826216,0.000007571541,0.00003765625],"genre_scores_gemma":[0.9958512,0.00011005524,0.003520527,0.00033627462,0.0001450208,0.000012378205,0.0000033731724,0.0000041337707,0.000017012278],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992292,0.0000914736,0.00035840448,0.00012649271,0.00006710048,0.0001273122],"domain_scores_gemma":[0.9995827,0.00006464284,0.00018023489,0.000059352016,0.00007937066,0.0000336768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023338082,0.00008192791,0.00027589573,0.0002322424,0.000012267248,0.0000036137756,0.000067844274,0.00006902584,0.000022482487],"category_scores_gemma":[0.00015307564,0.000058540143,0.00002581748,0.00016473157,0.00006289608,0.00004508778,0.000018988156,0.000298536,6.680384e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000497092,0.000025647058,0.84002995,0.000016936967,0.0000033915564,0.000014811858,0.00004544495,0.0000018241607,0.115260445,0.00047904905,0.0000065617646,0.043618824],"study_design_scores_gemma":[0.00060808426,0.00056007074,0.98357576,0.00010220263,0.000005440486,0.00016222322,0.000020560856,0.00011460947,0.006145427,0.007977608,0.0006713714,0.000056636807],"about_ca_topic_score_codex":0.000103383725,"about_ca_topic_score_gemma":0.0006211278,"teacher_disagreement_score":0.14354579,"about_ca_system_score_codex":0.00009449028,"about_ca_system_score_gemma":0.000019012916,"threshold_uncertainty_score":0.23871978},"labels":[],"label_agreement":null},{"id":"W2029896563","doi":"10.1111/j.1492-7535.2004.01110.x","title":"Reply to letter on diffusion study","year":2004,"lang":"en","type":"article","venue":"Hemodialysis International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Columbia university; Library science; Citation; Health science; Center (category theory); Medicine; Sociology; Media studies; Computer science; Medical education","score_opus":0.04926919476538716,"score_gpt":0.36341337031121623,"score_spread":0.3141441755458291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2029896563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88669336,0.0000014984928,0.037720613,0.06711513,0.00013963185,0.00053577096,0.000007128235,0.00019779644,0.0075890706],"genre_scores_gemma":[0.9516966,0.000002700884,0.010890333,0.036051072,0.00031136264,0.00011234328,0.000021969885,0.000015008255,0.00089865143],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991359,0.0000076305705,0.0001642774,0.00029119314,0.0003076231,0.00009336549],"domain_scores_gemma":[0.9994529,0.00001973389,0.000037775237,0.0003416997,0.000076799435,0.00007111518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006312258,0.00008620935,0.000116016214,0.00016705229,0.000051985207,0.000016778238,0.00012376207,0.000015658952,0.00011167018],"category_scores_gemma":[0.00007124538,0.000075117314,0.0000717808,0.00015681602,0.000013379254,0.000034224504,0.00006154728,0.00010719189,0.0001929257],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025935194,0.027704224,0.29574504,0.000034040197,0.0009598846,0.00093057513,0.0046625803,0.009029025,0.2383337,0.051174555,0.23585145,0.13298139],"study_design_scores_gemma":[0.005398811,0.0012967295,0.20451573,0.00012925758,0.00017784214,0.00008123408,0.00012416462,0.00046201827,0.040782303,0.006991725,0.73955756,0.00048261325],"about_ca_topic_score_codex":0.00002898846,"about_ca_topic_score_gemma":0.0000020709292,"teacher_disagreement_score":0.50370616,"about_ca_system_score_codex":0.00012434908,"about_ca_system_score_gemma":0.000013658507,"threshold_uncertainty_score":0.3063195},"labels":[],"label_agreement":null},{"id":"W2030109209","doi":"10.1039/c4sm00676c","title":"Micro-heterogeneity metrics for diffusion in soft matter","year":2014,"lang":"en","type":"article","venue":"Soft Matter","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; U.S. Public Health Service","keywords":"Microbead (research); Soft matter; Diffusion; Tracking (education); Computer science; Biological system; Physics; Chemistry; Biology","score_opus":0.04407521153950298,"score_gpt":0.3407877974561752,"score_spread":0.2967125859166722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030109209","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52469903,0.000051918098,0.4607835,0.0128203,0.00006413073,0.00073258183,0.000014657618,0.00014298475,0.0006908858],"genre_scores_gemma":[0.9200893,0.000011114692,0.050114002,0.028035441,0.0001254559,0.00016050205,0.000043898996,0.00005983742,0.0013604597],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992311,0.00001272177,0.00017305597,0.00028079,0.00008495711,0.00021736191],"domain_scores_gemma":[0.9993991,0.000088822846,0.000051166906,0.0003662715,0.000035750032,0.000058877915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010069831,0.00011550225,0.00018289335,0.000102154896,0.000052095125,0.000014176657,0.000095132804,0.000057949874,0.00021775144],"category_scores_gemma":[0.000030585885,0.000103617494,0.0000765805,0.00012690354,0.000036848578,0.000039165006,0.00006056447,0.00012625834,0.00045722086],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000551872,0.00024024078,0.7026118,0.00018551378,0.000007794391,0.000002777025,0.000073382726,0.0000037055315,0.18860623,0.000054708362,0.096832484,0.011326142],"study_design_scores_gemma":[0.0024816727,0.00016429712,0.5027236,0.00017179929,0.00008414295,0.00008097961,0.000012435524,0.0026910938,0.08008588,0.01090588,0.40010357,0.00049468694],"about_ca_topic_score_codex":0.000010599644,"about_ca_topic_score_gemma":0.0000033779133,"teacher_disagreement_score":0.4106695,"about_ca_system_score_codex":0.00002556489,"about_ca_system_score_gemma":0.0000063100565,"threshold_uncertainty_score":0.58768016},"labels":[],"label_agreement":null},{"id":"W2030134080","doi":"10.1109/prni.2012.11","title":"Connectivity-informed Sparse Classifiers for fMRI Brain Decoding","year":2012,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Decoding methods; Artificial intelligence; Functional magnetic resonance imaging; Curse of dimensionality; Classifier (UML); Regularization (linguistics); Pattern recognition (psychology); Neural coding; Diffusion MRI; Prior probability; Neuroimaging; Machine learning; Magnetic resonance imaging; Neuroscience; Bayesian probability; Psychology; Algorithm","score_opus":0.2169931629477163,"score_gpt":0.4294514363842008,"score_spread":0.2124582734364845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030134080","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013611958,0.00008772297,0.928642,0.02090634,0.0003240937,0.0033390068,0.000071304465,0.0010786748,0.031938937],"genre_scores_gemma":[0.624534,0.00012956621,0.36159232,0.00506281,0.0005661946,0.0016557537,0.00030840407,0.000101819365,0.006049124],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99874485,0.0000120105005,0.00030527217,0.00042397776,0.00013306105,0.00038083317],"domain_scores_gemma":[0.9983126,0.00048566228,0.00018087562,0.0007138925,0.00010257315,0.00020437942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021500434,0.00025911877,0.00042149323,0.00012566595,0.00010501222,0.000027115924,0.00015688455,0.00023519568,0.000088096465],"category_scores_gemma":[0.00043353694,0.00023373964,0.00023345646,0.00008002257,0.000075415344,0.000073943804,0.00027035378,0.00053484057,0.000018411802],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005385403,0.00087248883,0.011815759,0.0032245708,0.0003666619,0.00001606418,0.00060116214,0.00010871442,0.01787093,0.2521879,0.55835724,0.15403995],"study_design_scores_gemma":[0.0021469332,0.00018141021,0.004156836,0.0006035811,0.00043557046,0.00011731014,0.00018687075,0.010691868,0.029344706,0.050801404,0.90028393,0.0010495695],"about_ca_topic_score_codex":0.000014664732,"about_ca_topic_score_gemma":0.000008292334,"teacher_disagreement_score":0.61092204,"about_ca_system_score_codex":0.00017242476,"about_ca_system_score_gemma":0.00019882155,"threshold_uncertainty_score":0.9531626},"labels":[],"label_agreement":null},{"id":"W2030642834","doi":"10.1038/jcbfm.2012.69","title":"Penumbra Detection using PWI/DWI Mismatch MRI in a Rat Stroke Model with and without Comorbidity: Comparison of Methods","year":2012,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Penumbra; Medicine; Perfusion; Diffusion MRI; Nuclear medicine; Effective diffusion coefficient; Stroke (engine); Lesion; Perfusion scanning; Magnetic resonance imaging; Radiology; Cardiology; Ischemia; Pathology; Physics","score_opus":0.10254098968316133,"score_gpt":0.4187287059527386,"score_spread":0.31618771626957726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030642834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7058006,0.0015171395,0.2921495,0.00020622597,0.00006593679,0.00020116488,0.0000045913052,0.000016315682,0.000038523638],"genre_scores_gemma":[0.5745781,0.00013055847,0.42506397,0.00006373495,0.00012389665,0.000003373962,7.442081e-7,0.000020223215,0.000015437074],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998578,0.00012042682,0.00062597677,0.00014979788,0.0002672896,0.00025850133],"domain_scores_gemma":[0.99877506,0.00004768668,0.0005744353,0.00022686613,0.0001818815,0.00019408225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059634325,0.00018502864,0.0007943411,0.00024379295,0.000058790563,0.000015817244,0.00009829893,0.0000812914,0.000006541509],"category_scores_gemma":[0.000046500496,0.00014202337,0.00010401107,0.00024561465,0.00009043112,0.00037520588,0.00004531893,0.0005646851,2.0497144e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070456,0.0014002948,0.19011354,0.00018620436,0.00024600714,0.000005779566,0.0016140513,0.0043724123,0.7783934,0.00041288856,0.000094467345,0.022456408],"study_design_scores_gemma":[0.006681708,0.00042793519,0.028481591,0.00031404084,0.0022723263,0.0018367161,0.00039139576,0.24261253,0.712946,0.0009850364,0.0026793682,0.0003713611],"about_ca_topic_score_codex":0.000023835244,"about_ca_topic_score_gemma":0.0000052139017,"teacher_disagreement_score":0.23824011,"about_ca_system_score_codex":0.000023893659,"about_ca_system_score_gemma":0.00006814966,"threshold_uncertainty_score":0.57915455},"labels":[],"label_agreement":null},{"id":"W2030691940","doi":"10.1203/pdr.0b013e3182110f7e","title":"Noninvasive MRI Measures of Microstructural and Cerebrovascular Changes During Normal Swine Brain Development","year":2011,"lang":"en","type":"article","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Toronto; University Health Network; Thornhill Medical (Canada); Hospital for Sick Children","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Cerebral blood flow; Medicine; Brain development; Human brain; Cardiology; Neuroimaging; Magnetic resonance imaging; Internal medicine; Neuroscience; Radiology; Psychology","score_opus":0.21616468121463356,"score_gpt":0.383783386415188,"score_spread":0.16761870520055444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030691940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972942,0.00048262667,0.00049498427,0.0007657317,0.00001247022,0.00045981957,0.000004106448,0.000049819755,0.00043624785],"genre_scores_gemma":[0.96905196,0.001083337,0.029236536,0.00003292417,0.00016008625,0.00007399327,0.000006347821,0.000021037145,0.0003337967],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988124,0.000041595835,0.00017709249,0.0002617734,0.0003956234,0.00031156547],"domain_scores_gemma":[0.9992031,0.000094781564,0.000048221038,0.00026757107,0.00026352494,0.00012280613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038695245,0.00009613547,0.00017117865,0.0002965859,0.00014503306,0.000007821123,0.00012244706,0.00004520889,0.000042503187],"category_scores_gemma":[0.00018516672,0.00008200517,0.000031299554,0.00038952858,0.000121054596,0.000045500434,0.0001882823,0.00026339883,0.0000052647006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022854886,0.00022914543,0.8409317,0.0013950131,0.000083860294,0.00008204791,0.0037474143,0.0000011096831,0.14142673,0.00036177094,0.0023595886,0.00915305],"study_design_scores_gemma":[0.0007098871,0.00015316755,0.62101424,0.000028435203,0.000026522823,0.00018358769,0.0000983446,0.0000063363204,0.37537155,0.00020309875,0.0020832175,0.00012163284],"about_ca_topic_score_codex":0.000059721206,"about_ca_topic_score_gemma":0.000015154787,"teacher_disagreement_score":0.23394482,"about_ca_system_score_codex":0.00003518754,"about_ca_system_score_gemma":0.00012298016,"threshold_uncertainty_score":0.3344074},"labels":[],"label_agreement":null},{"id":"W2031448494","doi":"10.1016/j.neurobiolaging.2014.05.039","title":"Does MRI scan acceleration affect power to track brain change?","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; U.S. National Library of Medicine; Takeda Pharmaceuticals North America; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; Servier; Innogenetics; Eisai; Bayer HealthCare; National Institute of Mental Health; Pfizer; Novartis Pharmaceuticals Corporation; National Institute on Drug Abuse; AstraZeneca; Eli Lilly and Company; National Institute of General Medical Sciences; Northern California Institute for Research and Education; Roche; Alzheimer's Drug Discovery Foundation; Merck; National Institute on Aging; Alzheimer's Association","keywords":"Atrophy; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Medicine; Magnetic resonance imaging; Affect (linguistics); Nuclear medicine; Psychology; Neuroscience; Disease; Radiology; Internal medicine","score_opus":0.056274466005025184,"score_gpt":0.3609224230133714,"score_spread":0.30464795700834624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031448494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94027513,0.00000883809,0.010787123,0.046938527,0.00014860327,0.0006027862,0.0000058641363,0.00024207917,0.0009910692],"genre_scores_gemma":[0.98550993,0.000009940635,0.005758715,0.008345975,0.0001206412,0.000054445394,0.000012551429,0.000018825483,0.00016896267],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993125,0.000048746926,0.0001500585,0.00027590065,0.00004523965,0.00016751607],"domain_scores_gemma":[0.99941635,0.000118646305,0.00006603962,0.00029671565,0.000041546195,0.000060678685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119870194,0.000100013654,0.00019319436,0.00010329001,0.000052104704,0.0000048704496,0.00009043238,0.000043325097,0.000026996322],"category_scores_gemma":[0.00006508202,0.00006881045,0.000047339145,0.00012973131,0.00005995083,0.000048586888,0.00004417775,0.00013017167,0.000011038814],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005768486,0.00014320761,0.039142083,0.00007484359,0.000014746872,0.000003909764,0.00045495096,0.000026890884,0.9323764,0.0026865292,0.007579358,0.017439397],"study_design_scores_gemma":[0.0008172452,0.0013006927,0.32053816,0.00016408043,0.000044923563,0.000058747133,0.000029132332,0.00028679686,0.59017813,0.0011004648,0.08518983,0.00029177082],"about_ca_topic_score_codex":0.0000069864864,"about_ca_topic_score_gemma":0.0000039566603,"teacher_disagreement_score":0.34219825,"about_ca_system_score_codex":0.000010949693,"about_ca_system_score_gemma":0.0000075403696,"threshold_uncertainty_score":0.28060088},"labels":[],"label_agreement":null},{"id":"W2031559738","doi":"10.1227/01.neu.0000163089.31657.08","title":"Sensory and Motor Interhemispheric Integration after Section of Different Portions of the Anterior Corpus Callosum in Nonepileptic Patients","year":2005,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canada Research Chairs","keywords":"Corpus callosum; Somatosensory system; Medicine; Sensory system; Anatomy; Neuroscience; Anterior commissure; Psychology; Audiology","score_opus":0.021206452959562062,"score_gpt":0.2734464932492773,"score_spread":0.2522400402897152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031559738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99868464,0.000025055426,0.0005309504,0.00027905375,0.00009831706,0.00029569695,0.000012252761,0.000023063403,0.00005095573],"genre_scores_gemma":[0.9992246,0.00008469267,0.000261661,0.00021642774,0.000027355229,0.00005248184,0.0000033178044,0.000012157837,0.00011732387],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993272,0.00002488757,0.00032756772,0.00014154005,0.00009935229,0.00007945093],"domain_scores_gemma":[0.9995255,0.000044626286,0.00015001865,0.00019966543,0.0000525277,0.000027648797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003126757,0.00008085091,0.00017053515,0.00006239999,0.000016426453,0.0000028585803,0.000029894241,0.00003199435,0.000009529327],"category_scores_gemma":[0.00006282739,0.000058005375,0.000063971194,0.00012494615,0.000062699626,0.000046646637,0.000033896584,0.0001315423,2.7675569e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013389955,0.00034473182,0.6129666,0.000048278427,0.000002723205,0.0000014815894,0.000057275523,0.000004004713,0.37828633,0.00000868304,0.00006145709,0.008084523],"study_design_scores_gemma":[0.0002295523,0.00009023531,0.9579065,0.00016690824,0.000016401138,0.000012786269,0.000006445108,0.0007936897,0.040561296,0.000022699212,0.00015003163,0.000043496395],"about_ca_topic_score_codex":0.000007848578,"about_ca_topic_score_gemma":0.000008075373,"teacher_disagreement_score":0.34493983,"about_ca_system_score_codex":0.000026767313,"about_ca_system_score_gemma":0.000009665345,"threshold_uncertainty_score":0.23653905},"labels":[],"label_agreement":null},{"id":"W2031619354","doi":"10.1016/j.schres.2006.04.027","title":"Deficit in schizophrenia to recruit the striatum in implicit learning: A functional magnetic resonance imaging investigation","year":2006,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Institute for Biodiagnostics; University of Manitoba","funders":"","keywords":"Schizophrenia (object-oriented programming); Striatum; Psychology; Functional magnetic resonance imaging; Neuroscience; Ventral striatum; Antipsychotic; Audiology; Psychiatry; Medicine; Dopamine","score_opus":0.10089276205348557,"score_gpt":0.37331671164439606,"score_spread":0.2724239495909105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031619354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97463065,0.001592596,0.00049487577,0.019485155,0.000046123794,0.0018192222,0.000009037876,0.0001870474,0.0017352588],"genre_scores_gemma":[0.9902693,0.00006422096,0.006859974,0.000273526,0.0002725765,0.00083662465,0.00004315925,0.00005608339,0.0013245582],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99694175,0.0003121779,0.00051444315,0.0007092489,0.00078436226,0.00073803356],"domain_scores_gemma":[0.9985153,0.00040677094,0.000060464816,0.00062754506,0.00023577274,0.00015412013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014497805,0.00021124637,0.00026223,0.0008716894,0.00027834577,0.00008538737,0.0003237503,0.00008356501,0.00006123044],"category_scores_gemma":[0.00061757583,0.00017965127,0.00006452514,0.0029935017,0.00024163234,0.00013452653,0.00023131132,0.0018077713,0.000113286704],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006549672,0.000535276,0.5173091,0.00009470578,0.0000057285547,0.00021504327,0.00029681035,0.0017012908,0.18339147,0.08993436,0.01545358,0.18451293],"study_design_scores_gemma":[0.0026969777,0.00018709833,0.9343061,0.0002599562,0.0000068581458,0.00006668097,0.00010326891,0.0031108349,0.001880944,0.038966585,0.018185975,0.00022872195],"about_ca_topic_score_codex":0.001048469,"about_ca_topic_score_gemma":0.00060423807,"teacher_disagreement_score":0.41699696,"about_ca_system_score_codex":0.00032811085,"about_ca_system_score_gemma":0.0003744325,"threshold_uncertainty_score":0.78539675},"labels":[],"label_agreement":null},{"id":"W2031846748","doi":"10.1016/j.cortex.2014.04.016","title":"The DCDC2/intron 2 deletion and white matter disorganization: Focus on developmental dyslexia","year":2014,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke","keywords":"Splenium; Dyslexia; Corpus callosum; Fractional anisotropy; Psychology; White matter; Diffusion MRI; Superior longitudinal fasciculus; Lateralization of brain function; Neuropsychology; Arcuate fasciculus; Neuroscience; Audiology; Reading (process); Medicine; Magnetic resonance imaging; Cognition","score_opus":0.01653911360927793,"score_gpt":0.276337482238475,"score_spread":0.25979836862919703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031846748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59946305,0.000117564094,0.29578534,0.06644482,0.0001533783,0.0011560986,0.000006803208,0.0005226398,0.036350332],"genre_scores_gemma":[0.9940241,0.00004459818,0.0030793392,0.0014061756,0.00006617087,0.000026505806,0.000013703284,0.000016906515,0.0013225108],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999586,0.0000097028815,0.00009165401,0.00014859978,0.00007259214,0.00009146341],"domain_scores_gemma":[0.9997208,0.000029890667,0.000032083557,0.00015061702,0.000027827313,0.000038788607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004193597,0.00006556886,0.000062345054,0.00001733511,0.00015799732,0.00001846976,0.000041448453,0.000020374435,0.000049739712],"category_scores_gemma":[0.000019864377,0.00004571829,0.000011220257,0.00007118823,0.00004787448,0.000024137791,0.000027234282,0.00007456976,0.00008835056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019307951,0.00023395295,0.5453773,0.000055409382,0.000034523964,0.000008559303,0.00034187705,0.0000064013757,0.026404126,0.04830633,0.09983603,0.2792024],"study_design_scores_gemma":[0.00044090327,0.00012666457,0.845889,0.000034797486,0.000022952558,0.000092679555,0.00002972029,0.00052129966,0.0029834034,0.007122515,0.14260884,0.00012726946],"about_ca_topic_score_codex":0.0000010063189,"about_ca_topic_score_gemma":0.0000016729928,"teacher_disagreement_score":0.39456108,"about_ca_system_score_codex":0.000024133802,"about_ca_system_score_gemma":0.000008334265,"threshold_uncertainty_score":0.18643378},"labels":[],"label_agreement":null},{"id":"W2032234501","doi":"10.1002/jmri.20651","title":"Diffusion tensor imaging in evaluation of human skeletal muscle injury","year":2006,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":213,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton","funders":"Johns Hopkins University","keywords":"Diffusion MRI; Fractional anisotropy; Effective diffusion coefficient; Skeletal muscle; Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Anatomy; Nuclear medicine; Biomedical engineering; Physics; Radiology","score_opus":0.03270774088411862,"score_gpt":0.3580757512026797,"score_spread":0.3253680103185611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032234501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98756313,0.007791277,0.00095490046,0.0016728014,0.000050268824,0.0003216996,0.0000031753575,0.000023110502,0.0016196576],"genre_scores_gemma":[0.99148107,0.0001222021,0.007998147,0.00012614831,0.00015091643,0.000011501938,0.0000027113501,0.000023815302,0.000083496256],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981738,0.00006858868,0.0007518077,0.00017851935,0.00062374806,0.00020353394],"domain_scores_gemma":[0.9987373,0.000043217886,0.00043808625,0.00025592445,0.00047679315,0.000048679798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008028166,0.00012828743,0.0002904066,0.0003232669,0.00005333167,0.000015039849,0.00013420799,0.00002147641,0.00005958373],"category_scores_gemma":[0.00012900544,0.000115450144,0.00011134133,0.0002876697,0.00011617879,0.00018178564,0.000042548876,0.0002768215,0.0000011690486],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027571226,0.00026173145,0.27296454,0.00002415798,7.5532796e-7,0.000042977947,0.00004444555,0.000029826106,0.24674827,0.00017190068,0.00092792057,0.47875592],"study_design_scores_gemma":[0.0017013963,0.00013416568,0.9744532,0.0004697812,0.00007570485,0.00020974089,0.00006721354,0.007679986,0.0031225937,0.0049171248,0.0070564155,0.00011267651],"about_ca_topic_score_codex":0.000060290222,"about_ca_topic_score_gemma":0.0000030926096,"teacher_disagreement_score":0.7014887,"about_ca_system_score_codex":0.00012042096,"about_ca_system_score_gemma":0.00008270898,"threshold_uncertainty_score":0.47079203},"labels":[],"label_agreement":null},{"id":"W2032321212","doi":"10.1007/s00429-005-0045-1","title":"Large-scale morphometric analysis of neuroanatomy and neuropathology","year":2005,"lang":"en","type":"article","venue":"Anatomy and Embryology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuropathology; Neuroanatomy; Neuroimaging; Neuroscience; Brain research; Pipeline (software); Computer science; Data science; Medicine; Medical physics; Pathology; Disease; Psychology","score_opus":0.023360660036086653,"score_gpt":0.3367737933823231,"score_spread":0.31341313334623644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032321212","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895812,0.0011304107,0.005218216,0.0028983937,0.000013239624,0.000121389014,0.000014450656,0.0000652938,0.00095736346],"genre_scores_gemma":[0.9915707,0.001282939,0.005065862,0.0018940348,0.000021563206,0.000012162736,0.000014325821,0.0000101773,0.00012823958],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924326,0.00003241823,0.00020157984,0.00029378067,0.000056525998,0.00017244669],"domain_scores_gemma":[0.999466,0.00008195853,0.000072372386,0.00024300607,0.000049195904,0.000087494314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009278175,0.000096337804,0.00036458802,0.00065990805,0.00005451042,0.000002342101,0.000050766423,0.00006540156,0.000034785502],"category_scores_gemma":[0.000043731245,0.000087770895,0.000059389986,0.0010812093,0.00017068554,0.000044192424,0.00007566218,0.00014678956,0.0000020827888],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013142159,0.0005648738,0.90931964,0.00008377185,0.0003790419,0.0001576803,0.00032959876,0.000043767974,0.010812448,0.030252656,0.0014697477,0.046455372],"study_design_scores_gemma":[0.0010402193,0.00030604276,0.88907075,0.000006072267,0.0013644942,0.0006013018,0.00008324998,0.01714669,0.0017210392,0.0007839013,0.08770152,0.00017471207],"about_ca_topic_score_codex":0.000009798182,"about_ca_topic_score_gemma":0.000012402265,"teacher_disagreement_score":0.086231776,"about_ca_system_score_codex":0.000005059909,"about_ca_system_score_gemma":0.000009913609,"threshold_uncertainty_score":0.3579193},"labels":[],"label_agreement":null},{"id":"W2032585403","doi":"10.7490/f1000research.1552.1","title":"Differences in the Role of Context on Polar and Translational Glass Patterns","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University","funders":"","keywords":"Open peer review; Plant biology; Context (archaeology); Neuroscience; Polar; Physiology; Biology; Medicine; Botany; Physics; Paleontology","score_opus":0.08744461820397366,"score_gpt":0.31603049951423123,"score_spread":0.2285858813102576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032585403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9854025,0.000059017457,0.0031567353,0.0012862247,0.000002416722,0.00016882994,0.000011122883,0.00001740533,0.009895737],"genre_scores_gemma":[0.99834174,0.00002041552,0.0011502301,0.00044122752,0.0000050740528,0.000011826461,0.0000022116947,0.000002130245,0.000025144474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997864,0.0000076072724,0.0000625777,0.00005835476,0.000049765713,0.000035317942],"domain_scores_gemma":[0.99985677,0.00003530908,0.000013777335,0.00007596177,0.000007835375,0.000010359314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027019412,0.00002952093,0.000053198994,0.000019562793,0.000010634301,0.0000011056953,0.000032169653,0.000010350769,0.00003963866],"category_scores_gemma":[0.0000031502543,0.000016815575,0.00001066487,0.00002749369,0.00002758223,0.000013108004,0.0000031454729,0.000048595753,5.998249e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021087213,0.00010708571,0.91928303,0.0000046918863,0.0000021111853,7.556038e-7,0.00066906156,1.2366471e-8,0.0010363869,0.06294598,0.000016675573,0.015913142],"study_design_scores_gemma":[0.0001700514,0.00009249043,0.9835047,0.000018708248,0.0000051048924,0.0000056852095,0.00029827314,0.00012291869,0.0054632556,0.009553436,0.0007424781,0.000022889752],"about_ca_topic_score_codex":0.00009809112,"about_ca_topic_score_gemma":0.00002107969,"teacher_disagreement_score":0.064221695,"about_ca_system_score_codex":8.3746465e-7,"about_ca_system_score_gemma":0.0000033668184,"threshold_uncertainty_score":0.068571925},"labels":[],"label_agreement":null},{"id":"W2032891048","doi":"10.2214/ajr.09.2517","title":"Evaluation of Diffusion Tensor Imaging and Fiber Tractography of the Median Nerve: Preliminary Results on Intrasubject Variability and Precision of Measurements","year":2009,"lang":"en","type":"article","venue":"American Journal of Roentgenology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"Medicine; Diffusion MRI; Tractography; Fractional anisotropy; Effective diffusion coefficient; Nuclear medicine; Fiber; Nerve fiber; Magnetic resonance imaging; Radiology; Anatomy","score_opus":0.054078883348146464,"score_gpt":0.35089731278864056,"score_spread":0.2968184294404941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032891048","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99554616,0.00015870208,0.00063392543,0.0031954448,0.000022572733,0.0002987899,0.0000074503128,0.000004255155,0.00013269091],"genre_scores_gemma":[0.99391747,0.00015668273,0.005822725,0.000078411125,0.000014757383,0.0000020495252,0.0000010070487,0.0000055433375,0.000001344594],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984788,0.00029572632,0.00054527377,0.00014220423,0.00044598553,0.000092069706],"domain_scores_gemma":[0.99798477,0.00018473544,0.00096542947,0.00025682832,0.00055813586,0.000050102422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012716108,0.00008415517,0.00032794208,0.00016181747,0.000027977298,0.0000013626684,0.00009240575,0.000023467737,0.0000040120835],"category_scores_gemma":[0.00076315296,0.000055220524,0.000071779796,0.00023070979,0.0003909783,0.00004075737,0.000026293399,0.00016841054,2.4021876e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020234392,0.00054655573,0.07536258,0.000021148362,0.000049933962,0.0000017588419,0.00039633858,0.00008411103,0.14257994,0.000019443898,0.000053217496,0.7788615],"study_design_scores_gemma":[0.0015774843,0.004747981,0.96308005,0.00023933906,0.0003878475,0.00018007311,0.00014336788,0.00052428374,0.026629921,0.0024039098,0.000038026068,0.000047726146],"about_ca_topic_score_codex":0.000012191223,"about_ca_topic_score_gemma":5.0326275e-7,"teacher_disagreement_score":0.8877175,"about_ca_system_score_codex":0.000026483849,"about_ca_system_score_gemma":0.000056921308,"threshold_uncertainty_score":0.22518276},"labels":[],"label_agreement":null},{"id":"W2033328586","doi":"10.1016/j.jalz.2012.05.2076","title":"P3‐402: Detection of PCC functional connectivity characteristics in subcortical vascular mild cognitive impairment: A resting‐state fMRI study","year":2012,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Resting state fMRI; Neuroimaging; Diffusion MRI; Medicine; Posterior cingulate; Dementia; Montreal Cognitive Assessment; Neuroscience; Spatial normalization; Neurology; Psychology; Temporal lobe; Voxel; Cognitive impairment; Cognition; Internal medicine; Radiology; Magnetic resonance imaging; Disease; Epilepsy","score_opus":0.07365815354748648,"score_gpt":0.33650352653085674,"score_spread":0.2628453729833703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033328586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9840953,0.0016604826,0.012711281,0.000089651694,0.00009971364,0.0011607568,0.00001751055,0.0000991771,0.000066146255],"genre_scores_gemma":[0.9984525,0.000039086706,0.0010400723,0.000091880815,0.000078773905,0.0002324464,0.000035117937,0.00002783113,0.0000022944728],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986541,0.000085391854,0.0004120751,0.00028614208,0.00025598778,0.00030627154],"domain_scores_gemma":[0.9992159,0.00011878355,0.0001624801,0.0002517937,0.0001339594,0.00011709515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035639518,0.0001640058,0.00028125863,0.00012105068,0.00008246158,0.000007818523,0.000051075698,0.000043562464,0.000046457302],"category_scores_gemma":[0.000086116925,0.00016353141,0.000082772574,0.00027301797,0.00008386379,0.00014386272,0.00007363446,0.00023999964,0.000017755952],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051158573,0.0038678816,0.9519128,0.000018761546,0.002464719,0.000013990551,0.00035935035,0.0000017766833,0.019567437,0.00007231834,0.000053988908,0.021155382],"study_design_scores_gemma":[0.0014013468,0.0004967168,0.9625023,0.000041773565,0.0050564595,0.000018750807,0.00009480995,0.00021207776,0.02972458,0.00009037038,0.00021277982,0.00014806002],"about_ca_topic_score_codex":0.00008995281,"about_ca_topic_score_gemma":0.000017561322,"teacher_disagreement_score":0.02100732,"about_ca_system_score_codex":0.000013965903,"about_ca_system_score_gemma":0.000030510033,"threshold_uncertainty_score":0.6668617},"labels":[],"label_agreement":null},{"id":"W2033352952","doi":"10.1016/j.jpain.2009.01.103","title":"Cerebral cortical thickness in a subject lacking large myelinated afferents","year":2009,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Somatosensory system; Precuneus; Insula; Medicine; Neuroscience; Cortex (anatomy); Anatomy; Cerebral cortex; Prefrontal cortex; Psychology; Audiology; Functional magnetic resonance imaging; Cognition","score_opus":0.049992112272739746,"score_gpt":0.36996607430645817,"score_spread":0.3199739620337184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033352952","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90141714,0.000094204464,0.08957408,0.00828519,0.00003902432,0.00016908237,0.000001797905,0.00004766124,0.00037184064],"genre_scores_gemma":[0.99083143,0.000027222244,0.007068372,0.001916899,0.000096822434,0.0000012664412,0.0000018526854,0.000008529377,0.000047609392],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991347,0.00010440371,0.00032658697,0.00008680014,0.00017298228,0.00017448337],"domain_scores_gemma":[0.99947935,0.000097485914,0.00013544723,0.00011522269,0.00008801868,0.000084463085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008547771,0.00007464672,0.00021483921,0.00013154175,0.000031763662,0.00000922806,0.00008063708,0.00004713888,0.000025555495],"category_scores_gemma":[0.00039297974,0.000059006907,0.00007188501,0.00020940974,0.000015972359,0.00006339641,0.000011883283,0.0005002574,0.000002222686],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013459629,0.004105563,0.726963,0.00015505486,0.00005394935,0.002311673,0.0011385698,0.000060988288,0.14267038,0.013840073,0.010982066,0.09637276],"study_design_scores_gemma":[0.0039374083,0.0012534775,0.9625366,0.0008041843,0.00007000261,0.00086064264,0.00020317236,0.004967633,0.004689721,0.013348398,0.007109732,0.00021904538],"about_ca_topic_score_codex":0.00000144618,"about_ca_topic_score_gemma":0.0000018683027,"teacher_disagreement_score":0.23557362,"about_ca_system_score_codex":0.00005538481,"about_ca_system_score_gemma":0.00004541242,"threshold_uncertainty_score":0.24062319},"labels":[],"label_agreement":null},{"id":"W2033515328","doi":"10.1016/j.yebeh.2014.06.020","title":"Reliability and variability of diffusion tensor imaging (DTI) tractography in pediatric epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"University of Oxford; Health Research Board","keywords":"Tractography; Diffusion MRI; Fractional anisotropy; White matter; Uncinate fasciculus; Psychology; Medicine; Nuclear medicine; Radiology; Magnetic resonance imaging","score_opus":0.02306039480292636,"score_gpt":0.31451833347525704,"score_spread":0.29145793867233066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033515328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9940367,0.00005352309,0.003903881,0.00052338117,0.000051339302,0.00086660765,0.00001919234,0.00015718045,0.00038820834],"genre_scores_gemma":[0.98377,0.00017708878,0.015591589,0.00013046019,0.000071432936,0.0001915863,0.000016315016,0.000028970398,0.000022551374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99827045,0.00010728239,0.00054403226,0.000570431,0.00020425707,0.0003035594],"domain_scores_gemma":[0.99856853,0.00023167886,0.00016864289,0.00075244554,0.00011293688,0.00016575702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061173446,0.00019390327,0.00041535526,0.00022272707,0.00006313014,0.000009060639,0.00011772026,0.00008222576,0.000035138037],"category_scores_gemma":[0.0003735968,0.00017494922,0.00012217472,0.00046213233,0.0002311575,0.000106713844,0.00008143281,0.0003692767,0.0000023897987],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038026767,0.00075225736,0.9719446,0.00006214596,8.017377e-7,0.0000044939325,0.000056135537,0.0000010103895,0.00873866,0.00021806048,0.000058126465,0.01812571],"study_design_scores_gemma":[0.0007403531,0.0001128455,0.99576056,0.000033607757,0.00013147331,0.00002230568,0.000016618013,0.00033944915,0.00071070116,0.0012161005,0.0007657154,0.00015028937],"about_ca_topic_score_codex":0.00007298474,"about_ca_topic_score_gemma":0.0000029692449,"teacher_disagreement_score":0.023815969,"about_ca_system_score_codex":0.000040164123,"about_ca_system_score_gemma":0.00002781859,"threshold_uncertainty_score":0.7134222},"labels":[],"label_agreement":null},{"id":"W2033516072","doi":"10.1016/j.neuroimage.2008.06.031","title":"Arrested development and disrupted callosal microstructure following pediatric traumatic brain injury: relation to neurobehavioral outcomes","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Traumatic brain injury; Diffusion MRI; Psychology; Neuropsychology; Diffuse axonal injury; Neuroscience; Medicine; Audiology; Psychiatry; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.07929021529102213,"score_gpt":0.36616433801510045,"score_spread":0.2868741227240783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033516072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99234146,0.000017916665,0.0023538051,0.003988223,0.000088833855,0.0007630175,0.000010960516,0.00037233578,0.0000634654],"genre_scores_gemma":[0.96612805,0.000008194635,0.031092761,0.002195834,0.000042666878,0.000058853733,0.000033791304,0.000054784443,0.00038508556],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99867487,0.00003304262,0.00034171474,0.0004498718,0.00023394682,0.00026658422],"domain_scores_gemma":[0.99927354,0.00006393651,0.000078759695,0.00034236078,0.0000342699,0.00020712492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056719913,0.00022865577,0.00029076583,0.00018476984,0.0002991346,0.000030851035,0.000094953255,0.000061622835,0.0000060643865],"category_scores_gemma":[0.00014677165,0.00020975654,0.00007719244,0.000387354,0.000048774873,0.000121638666,0.000080547834,0.0003079551,0.000014055173],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007863303,0.00019369996,0.87569326,0.000064162174,0.000011212837,0.0005259734,0.0011823234,0.000007159142,0.11424698,0.00007390173,0.0032369974,0.004685702],"study_design_scores_gemma":[0.0005644385,0.00011438468,0.9926574,0.0000150465285,0.00005648238,0.00018986741,0.000010651158,0.00004816367,0.0016165981,0.000044041048,0.0044880775,0.0001948267],"about_ca_topic_score_codex":0.000008322959,"about_ca_topic_score_gemma":0.0000021783903,"teacher_disagreement_score":0.11696416,"about_ca_system_score_codex":0.000036760164,"about_ca_system_score_gemma":0.00006759453,"threshold_uncertainty_score":0.85536236},"labels":[],"label_agreement":null},{"id":"W2033793704","doi":"10.1016/j.neuroimage.2010.05.049","title":"Atlas-guided tract reconstruction for automated and comprehensive examination of the white matter anatomy","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":293,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Atlas (anatomy); White matter; Anatomy; Medicine; Medical physics; Computer science; Radiology; Magnetic resonance imaging","score_opus":0.04376621060552617,"score_gpt":0.34485028561503145,"score_spread":0.3010840750095053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033793704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99390787,0.0000054595453,0.0010506072,0.0029056328,0.00010082689,0.0007475727,0.000021833706,0.00018286917,0.0010773146],"genre_scores_gemma":[0.98293555,0.0000069494213,0.016253147,0.00050011545,0.00003174493,0.000046873403,0.000008844645,0.000019505405,0.00019729363],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994467,0.000019889936,0.00017227347,0.00019377303,0.00007632527,0.00009104404],"domain_scores_gemma":[0.9993612,0.000057165107,0.000118529664,0.00029393184,0.00013656964,0.000032591015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047988466,0.00008445942,0.00012657823,0.000051292223,0.000072278795,0.000010334462,0.00005947084,0.000041730727,0.00002114537],"category_scores_gemma":[0.00004501011,0.00006430355,0.000047789716,0.00011916538,0.00013743876,0.000076929806,0.000027356207,0.00017426959,0.0000020839548],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019333756,0.00008343959,0.06525552,0.00011383844,0.0000059843724,0.0000021063586,0.00006901104,0.000002659496,0.91657233,0.0003903123,0.004473686,0.013011755],"study_design_scores_gemma":[0.00050780934,0.000047144607,0.95071363,0.00002281525,0.000035939007,0.0004382657,0.0000141650735,0.005473029,0.036716104,0.00026424532,0.005704966,0.00006189245],"about_ca_topic_score_codex":0.0000021999574,"about_ca_topic_score_gemma":7.362886e-7,"teacher_disagreement_score":0.8854581,"about_ca_system_score_codex":0.0000059140857,"about_ca_system_score_gemma":0.000012261484,"threshold_uncertainty_score":0.26222226},"labels":[],"label_agreement":null},{"id":"W2033810762","doi":"10.1080/02841850802555646","title":"Effects of gradient encoding and number of signal averages on fractional anisotropy and fiber density index in vivo at 1.5 tesla","year":2008,"lang":"en","type":"article","venue":"Acta Radiologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"In vivo; Fractional anisotropy; Medicine; Physics; Diffusion MRI; Nuclear medicine; Biology; Genetics; Radiology; Magnetic resonance imaging","score_opus":0.02930522639298808,"score_gpt":0.29935467057932097,"score_spread":0.27004944418633287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033810762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9986457,0.00005765119,0.00032161362,0.00017833934,0.000006518601,0.00020460413,0.0000038602525,0.000022644159,0.0005590253],"genre_scores_gemma":[0.99636394,0.0005598019,0.0027672537,0.00013527054,0.000016354346,0.000014301538,0.0000019915597,0.000005244826,0.00013583634],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999499,0.000025104076,0.00012852094,0.00017883585,0.00007688758,0.00009163301],"domain_scores_gemma":[0.99935764,0.0004092197,0.00007855324,0.00009365042,0.000020860649,0.00004007392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043434295,0.00008018823,0.0002091993,0.000040692383,0.000053426967,9.1080915e-7,0.000028506676,0.0000521,0.000059604394],"category_scores_gemma":[0.000073801195,0.00006260336,0.000024563788,0.000065732,0.00015983461,0.000026919375,0.00003968527,0.0001181997,6.35248e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002451283,0.00019792271,0.6064528,0.000065191045,0.000015360225,0.000071073686,0.000104485014,0.000013514731,0.39051792,0.00061274663,0.0011491125,0.00055473903],"study_design_scores_gemma":[0.0007135509,0.0002954521,0.8701035,0.00006746752,0.000015967073,0.00050196727,0.000005465815,0.00019027949,0.12583251,0.0009466221,0.0012457839,0.000081458],"about_ca_topic_score_codex":0.00001300463,"about_ca_topic_score_gemma":3.295597e-7,"teacher_disagreement_score":0.26468542,"about_ca_system_score_codex":0.0000297479,"about_ca_system_score_gemma":0.0000080865575,"threshold_uncertainty_score":0.2552891},"labels":[],"label_agreement":null},{"id":"W2034026137","doi":"10.1016/j.parkreldis.2012.03.008","title":"Intact limbic-prefrontal connections and reduced amygdala volumes in Parkinson's disease with mild depressive symptoms","year":2012,"lang":"en","type":"article","venue":"Parkinsonism & Related Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Amygdala; Uncinate fasciculus; Psychology; Corpus callosum; White matter; Neuroscience; Prefrontal cortex; Diffusion MRI; Limbic system; Hippocampus; Internal medicine; Medicine; Magnetic resonance imaging; Central nervous system","score_opus":0.016036217061060246,"score_gpt":0.28172435509058524,"score_spread":0.265688138029525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034026137","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9892735,0.0037155943,0.0010086746,0.0025484264,0.000082867984,0.0009838968,0.000020178553,0.00037067948,0.0019962075],"genre_scores_gemma":[0.9956361,0.0018219191,0.0014622397,0.0002559526,0.000037733877,0.00039296973,0.000056415985,0.00006946997,0.00026721516],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984841,0.00005797423,0.00028450138,0.0004842172,0.00018665084,0.0005025992],"domain_scores_gemma":[0.9988988,0.00009262641,0.0001296358,0.00042777948,0.000033584816,0.00041754945],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008649639,0.0002833287,0.00029554096,0.00019331642,0.00021402747,0.00002604893,0.00010043128,0.00011814411,0.00003493677],"category_scores_gemma":[0.0000682283,0.00025422702,0.00007431794,0.00036946198,0.00025338653,0.00027470957,0.00006790193,0.0004840905,0.000013451454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075782434,0.0015509399,0.9147641,0.00008866986,0.00021304874,0.000040011128,0.0016159907,0.00014963475,0.0025569657,0.0024982449,0.00087442505,0.07489012],"study_design_scores_gemma":[0.0034878177,0.00029427075,0.7061591,0.0002758317,0.00032761897,0.00011608041,0.00035555623,0.0018326073,0.00058549887,0.002162499,0.28381968,0.0005834098],"about_ca_topic_score_codex":0.000131437,"about_ca_topic_score_gemma":0.000038330643,"teacher_disagreement_score":0.28294525,"about_ca_system_score_codex":0.0000872017,"about_ca_system_score_gemma":0.0000640044,"threshold_uncertainty_score":0.999991},"labels":[],"label_agreement":null},{"id":"W2034644191","doi":"10.1002/jmri.21425","title":"3T MR with diffusion tensor imaging and single‐voxel spectroscopy in giant axonal neuropathy","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"National Center for Research Resources","keywords":"Creatine; Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Choline; Effective diffusion coefficient; Magnetic resonance imaging; Medicine; Nuclear medicine; Nuclear magnetic resonance; Pathology; Chemistry; Internal medicine; Radiology; Physics","score_opus":0.0246229344886476,"score_gpt":0.2799159646964428,"score_spread":0.2552930302077952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034644191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96897775,0.010717194,0.010775471,0.008272107,0.00005482324,0.00030129918,0.000002990921,0.00005240798,0.0008459792],"genre_scores_gemma":[0.9076146,0.001827285,0.08908792,0.0011047145,0.00016313989,0.000008083213,8.433457e-7,0.00004664063,0.00014676273],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99845594,0.00003821354,0.0005028059,0.000291033,0.00038222352,0.00032978161],"domain_scores_gemma":[0.9990841,0.00007862091,0.00027252242,0.00024881342,0.00016268327,0.00015324351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016729545,0.00020399103,0.00037138132,0.00026417655,0.000111653455,0.00003044482,0.000130716,0.000018468554,0.000018359597],"category_scores_gemma":[0.00009726155,0.00015825726,0.00006364471,0.00029627985,0.00027929823,0.00022365195,0.000060241353,0.0005155781,0.000001510696],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047503112,0.00037714405,0.6551318,0.000037772716,0.0000023119412,0.0047924295,0.00020779565,0.000009206574,0.27639776,0.00010917199,0.001008388,0.061451167],"study_design_scores_gemma":[0.002923875,0.00065909897,0.93646544,0.0007871164,0.000046739366,0.025980685,0.00010590923,0.005126818,0.005294781,0.00050964765,0.02184907,0.0002508166],"about_ca_topic_score_codex":0.000012951333,"about_ca_topic_score_gemma":0.0000012509831,"teacher_disagreement_score":0.28133363,"about_ca_system_score_codex":0.00007711144,"about_ca_system_score_gemma":0.00008437931,"threshold_uncertainty_score":0.6453544},"labels":[],"label_agreement":null},{"id":"W2034758511","doi":"10.1155/2014/963032","title":"Automatic Detection and Quantification of Acute Cerebral Infarct by Fuzzy Clustering and Histographic Characterization on Diffusion Weighted MR Imaging and Apparent Diffusion Coefficient Map","year":2014,"lang":"en","type":"article","venue":"BioMed Research International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Central University; National Science Council","keywords":"Artificial intelligence; Pattern recognition (psychology); Segmentation; Effective diffusion coefficient; Magnetic resonance imaging; Diffusion MRI; Cluster analysis; Computer science; Fuzzy logic; Similarity (geometry); Medicine; Nuclear medicine; Radiology; Image (mathematics)","score_opus":0.03968038319729568,"score_gpt":0.3558230829756875,"score_spread":0.3161426997783918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2034758511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9235914,0.000043265325,0.07161184,0.0039201775,0.00012635616,0.00052233395,0.000043091182,0.00008115807,0.000060409133],"genre_scores_gemma":[0.99790406,0.00034777698,0.0011515924,0.000070665315,0.000057307185,0.00007438011,0.00029368926,0.000018248955,0.00008225646],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986738,0.00007862206,0.00026890505,0.00035716675,0.00045335846,0.00016817669],"domain_scores_gemma":[0.9992934,0.000092798255,0.00012969655,0.00018703527,0.0001874261,0.00010965228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035656831,0.00011579213,0.00014490332,0.00060373195,0.00018979995,0.000050349983,0.000079663565,0.00004739426,0.000009815727],"category_scores_gemma":[0.00005880483,0.00010177131,0.0000231912,0.00024065506,0.00027415605,0.00009710837,0.00014964052,0.00018119982,0.0000013054942],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011063806,0.00015469771,0.005400193,0.00008910672,0.000016313928,7.4945007e-7,0.0000783849,3.2322856e-7,0.89866704,0.0005927146,0.00009913166,0.09479072],"study_design_scores_gemma":[0.0017551612,0.00041625422,0.2160917,0.00042100335,0.000040537892,0.000065926804,0.000049097667,0.7179275,0.04761564,0.0007454986,0.014678541,0.00019309708],"about_ca_topic_score_codex":0.000028282238,"about_ca_topic_score_gemma":0.0000018160964,"teacher_disagreement_score":0.8510514,"about_ca_system_score_codex":0.00007395176,"about_ca_system_score_gemma":0.000010687093,"threshold_uncertainty_score":0.41501135},"labels":[],"label_agreement":null},{"id":"W2036436660","doi":"10.1002/nbm.1586","title":"Considerations for measuring the fractional anisotropy of metabolites with diffusion tensor spectroscopy","year":2010,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Nuclear magnetic resonance; Isotropy; Chemistry; Thermal diffusivity; Nuclear magnetic resonance spectroscopy; White matter; Spectroscopy; Diffusion; Attenuation; Analytical Chemistry (journal); Physics; Optics; Chromatography; Magnetic resonance imaging; Thermodynamics; Medicine","score_opus":0.05586982234251825,"score_gpt":0.35314608839945283,"score_spread":0.2972762660569346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036436660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87614167,0.0001685881,0.08474673,0.036188558,0.000113295646,0.0016664143,0.000049153357,0.00012962827,0.00079598115],"genre_scores_gemma":[0.8486829,0.00003960442,0.15027323,0.0006122934,0.0001698055,0.00012910848,0.00001644355,0.000014062493,0.000062571475],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993047,0.000008264019,0.00021209272,0.00016861035,0.0001777315,0.00012859366],"domain_scores_gemma":[0.9991352,0.000293117,0.00009034926,0.00027837223,0.00014720725,0.00005578762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014616066,0.00008951496,0.0001938947,0.00011994963,0.00009289034,0.000004659088,0.00005291231,0.000035429777,0.000081905906],"category_scores_gemma":[0.00031224018,0.000050458773,0.00003272483,0.00022225798,0.0002463133,0.000036229947,0.000014188352,0.00022178295,8.9410133e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008927578,0.00014504009,0.015617753,0.00002434037,0.0000108411705,0.0000024036412,0.00006126275,0.0000023374375,0.96954644,0.013521258,0.00065899815,0.00032003527],"study_design_scores_gemma":[0.005828515,0.0010665713,0.26589906,0.00025167284,0.00027839706,0.00047836432,0.00030991933,0.002199651,0.6214024,0.040170286,0.061849836,0.00026533275],"about_ca_topic_score_codex":0.000027872713,"about_ca_topic_score_gemma":0.00002185168,"teacher_disagreement_score":0.34814405,"about_ca_system_score_codex":0.000015128942,"about_ca_system_score_gemma":0.00007126818,"threshold_uncertainty_score":0.2057649},"labels":[],"label_agreement":null},{"id":"W2036945687","doi":"10.1002/hbm.20197","title":"Sensorimotor organization in double cortex syndrome","year":2005,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroscience; Sensory system; Somatosensory system; Thalamus; Insular cortex; Supplementary motor area; Motor cortex; Psychology; Cortex (anatomy); Primary motor cortex; Stimulus (psychology); White matter; Magnetic resonance imaging; Functional magnetic resonance imaging; Medicine; Stimulation","score_opus":0.07614635344089178,"score_gpt":0.3461406210362564,"score_spread":0.26999426759536466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036945687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9748153,0.000016895257,0.012934823,0.008004106,0.000015145307,0.00050098455,0.0000012812707,0.00040941132,0.0033020321],"genre_scores_gemma":[0.98671794,0.000004876959,0.009321616,0.0016203397,0.00008993361,0.000022530328,0.000036919395,0.000029035984,0.0021568132],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99934375,0.00000891168,0.00018944855,0.00021317707,0.000089580586,0.00015512899],"domain_scores_gemma":[0.99958456,0.000020596526,0.00004959666,0.00024138774,0.000055305085,0.000048539423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008010201,0.00008440357,0.00013314665,0.00013537955,0.0001027403,0.000013570651,0.00006122408,0.000038212842,0.000140572],"category_scores_gemma":[0.00003502169,0.00009127505,0.000018352272,0.00043730866,0.00002767399,0.00007895393,0.000030811963,0.00014420538,0.00005945036],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011821565,0.00024176715,0.040390234,0.000087080014,0.00001124552,0.00010594087,0.0005057423,0.00006667953,0.9224925,0.026107969,0.0080479905,0.0019310071],"study_design_scores_gemma":[0.0017777787,0.00006033787,0.8551114,0.00019360559,0.000011051621,0.00042084718,0.000070603885,0.0005578166,0.0021857815,0.0013331542,0.1380343,0.00024331326],"about_ca_topic_score_codex":0.000009314384,"about_ca_topic_score_gemma":0.0000042575284,"teacher_disagreement_score":0.92030674,"about_ca_system_score_codex":0.00008678377,"about_ca_system_score_gemma":0.000017359132,"threshold_uncertainty_score":0.37220883},"labels":[],"label_agreement":null},{"id":"W2036969062","doi":"10.1523/jneurosci.3979-14.2015","title":"Functional Consequences of Neurite Orientation Dispersion and Density in Humans across the Adult Lifespan","year":2015,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; McGill University; Douglas Mental Health University Institute; Douglas College; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Centre for Addiction and Mental Health; National Institutes of Health; W. Garfield Weston Foundation; National Alliance for Research on Schizophrenia and Depression","keywords":"Neuroscience; Diffusion MRI; Psychology; White matter; Fractional anisotropy; Hippocampal formation; Functional specialization; Hippocampus; Connectome; Resting state fMRI; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.10312702425535138,"score_gpt":0.38539053470223344,"score_spread":0.2822635104468821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036969062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99184006,0.000025012916,0.003098039,0.00482579,0.00010489199,0.00008002203,0.0000017501159,0.00000520717,0.000019201003],"genre_scores_gemma":[0.9983535,0.00009946433,0.00067044207,0.0008131043,0.000030048865,0.0000011369292,1.9436725e-7,0.0000024680123,0.000029662406],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999355,0.000027042634,0.00019942412,0.000095867246,0.00024762482,0.00007501425],"domain_scores_gemma":[0.9994002,0.000045663604,0.00018770351,0.00008946022,0.00021181417,0.00006517704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024873333,0.000042136224,0.000092489114,0.000043465872,0.00006574365,0.000012381169,0.000076584955,0.000012080998,4.6801986e-7],"category_scores_gemma":[0.00038550733,0.00002664751,0.000022955504,0.00021804965,0.0004012641,0.0001582159,0.000031176547,0.00014774679,1.712751e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015663475,0.000116121955,0.4247632,0.000012196922,8.393839e-7,0.00004199029,0.0006768827,0.00012169608,0.5712686,0.0012122364,0.00036247284,0.0012671155],"study_design_scores_gemma":[0.00046908055,0.00036281263,0.98242694,0.000046773184,0.000009010517,0.0006304379,0.00031387282,0.00042201384,0.013345055,0.0012673985,0.0006721851,0.000034422905],"about_ca_topic_score_codex":0.000010745163,"about_ca_topic_score_gemma":0.0000031596226,"teacher_disagreement_score":0.55792356,"about_ca_system_score_codex":0.000015351525,"about_ca_system_score_gemma":0.000060438222,"threshold_uncertainty_score":0.14784743},"labels":[],"label_agreement":null},{"id":"W2037701101","doi":"10.1016/j.neuroimage.2014.09.005","title":"Interpolation of diffusion weighted imaging datasets","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Lundbeckfonden","keywords":"Interpolation (computer graphics); Diffusion MRI; Voxel; Tractography; Artificial intelligence; Computer science; Image resolution; Bicubic interpolation; Orientation (vector space); Computer vision; Pattern recognition (psychology); Linear interpolation; Mathematics; Image (mathematics); Magnetic resonance imaging; Geometry; Medicine","score_opus":0.03212920246301052,"score_gpt":0.33635614610364456,"score_spread":0.304226943640634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037701101","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5675648,0.00004744123,0.4127242,0.0043878127,0.00013802489,0.00073649205,0.00012316264,0.0006462011,0.013631877],"genre_scores_gemma":[0.97924536,0.000017660428,0.01977565,0.0006566736,0.000035272802,0.000009227092,0.00016350727,0.000022113283,0.000074555384],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99931943,0.000024535004,0.00019818646,0.00022272908,0.00012289143,0.000112218186],"domain_scores_gemma":[0.99927115,0.00005613617,0.00009586044,0.00047949678,0.000041697236,0.00005566773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006673663,0.000087875276,0.0001456567,0.0000849846,0.00004131549,0.000007242783,0.00008751589,0.000016315666,0.000042148804],"category_scores_gemma":[0.000087141045,0.00007911711,0.000043919936,0.0001390279,0.000061860206,0.0000896403,0.00007433274,0.0001253985,0.0000137625975],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006147004,0.00017498941,0.02754707,0.000073212635,0.0000030097617,0.000008208677,0.00002869705,5.2074233e-7,0.9245425,0.002768685,0.007923391,0.036868244],"study_design_scores_gemma":[0.0034861253,0.0004961882,0.2923674,0.00039625922,0.0001924938,0.00042139753,0.000030187992,0.1932445,0.16529368,0.009786219,0.33375195,0.0005335966],"about_ca_topic_score_codex":0.000009952383,"about_ca_topic_score_gemma":2.8241644e-7,"teacher_disagreement_score":0.75924885,"about_ca_system_score_codex":0.000007544823,"about_ca_system_score_gemma":0.000007837284,"threshold_uncertainty_score":0.32263023},"labels":[],"label_agreement":null},{"id":"W2037972318","doi":"10.1109/tbme.2011.2181167","title":"Robust White Matter Lesion Segmentation in FLAIR MRI","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Fluid-attenuated inversion recovery; Voxel; Segmentation; Artificial intelligence; Computer science; Hyperintensity; Artifact (error); Pattern recognition (psychology); Ground truth; Image segmentation; White matter; Thresholding; Partial volume; Computer vision; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.071193842667303,"score_gpt":0.2907695990275098,"score_spread":0.21957575636020682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2037972318","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016436467,0.0000064275637,0.98174644,0.00078878365,0.00013257928,0.00026000495,0.000007391324,0.00025819475,0.0003637168],"genre_scores_gemma":[0.8988312,0.00007600903,0.10036841,0.0003206215,0.00003281211,0.00012846343,0.000009164216,0.00003390526,0.00019944174],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922633,0.000006353972,0.00021262364,0.00021857911,0.00015260905,0.00018349646],"domain_scores_gemma":[0.99963355,0.000017925604,0.000021411714,0.00019299403,0.00001340814,0.00012069725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056973484,0.00012033414,0.00013261329,0.0002715796,0.000034614488,0.000004589188,0.00005937589,0.0000761378,0.00025082368],"category_scores_gemma":[0.0000018206327,0.000113877635,0.00005426184,0.00034810873,0.00003654632,0.000075382304,0.0000011064471,0.00028905307,0.00006248108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009535217,0.008366715,0.008636249,0.0012221767,0.00023674383,0.00064730796,0.0041463976,0.12527393,0.6129292,0.000622894,0.007434919,0.22952993],"study_design_scores_gemma":[0.0077638146,0.0016475432,0.13653503,0.0019022155,0.0003087851,0.00074775255,0.00036487577,0.37858683,0.4509389,0.00041022018,0.018933227,0.0018607903],"about_ca_topic_score_codex":0.00001305722,"about_ca_topic_score_gemma":0.0000014637635,"teacher_disagreement_score":0.88239473,"about_ca_system_score_codex":0.00007395427,"about_ca_system_score_gemma":0.0000133773965,"threshold_uncertainty_score":0.46437952},"labels":[],"label_agreement":null},{"id":"W2038418010","doi":"10.1016/j.pscychresns.2006.11.011","title":"Three-dimensional volumetric analysis and reconstruction of amygdala and hippocampal head, body and tail","year":2007,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":133,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; University of Alberta","funders":"","keywords":"Hippocampus; Hippocampal formation; Amygdala; Medicine; Neuroscience; Magnetic resonance imaging; Nuclear medicine; Psychology; Radiology","score_opus":0.0851289550881558,"score_gpt":0.4149626736721997,"score_spread":0.32983371858404387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038418010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98509145,0.0016321108,0.00896442,0.0034966026,0.00005269668,0.00036180922,0.000008197692,0.00007359728,0.00031913051],"genre_scores_gemma":[0.9630198,0.00035687393,0.036324997,0.0001342664,0.00007953792,0.000010428825,0.000005137905,0.000023286311,0.0000456727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99831957,0.00005105196,0.0003221507,0.0005368513,0.0004016196,0.00036874798],"domain_scores_gemma":[0.99884886,0.00027331783,0.000091052556,0.00034326434,0.00019685841,0.00024662376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008649246,0.00013825587,0.00029157495,0.0012839604,0.00024610295,0.00003599812,0.000066671964,0.000046403635,0.000017377926],"category_scores_gemma":[0.00017045227,0.00013390687,0.00005635871,0.0019481255,0.0005416557,0.00012949413,0.00014375594,0.0005363565,0.0000011228561],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082764265,0.000082848135,0.9286434,0.00008767884,0.00005293754,0.000009639041,0.000017686438,9.404792e-7,0.009598208,0.00050673477,0.00020776759,0.06070938],"study_design_scores_gemma":[0.0006684236,0.00023301541,0.9773572,0.00006995055,0.00018326551,0.0005647566,0.000062438005,0.014496878,0.00043791032,0.005402245,0.0003919335,0.00013198865],"about_ca_topic_score_codex":0.00012456188,"about_ca_topic_score_gemma":0.00004730746,"teacher_disagreement_score":0.060577393,"about_ca_system_score_codex":0.000019147084,"about_ca_system_score_gemma":0.000036947404,"threshold_uncertainty_score":0.5460564},"labels":[],"label_agreement":null},{"id":"W2038568172","doi":"10.1016/j.neuroimage.2007.12.053","title":"Microstructural maturation of the human brain from childhood to adulthood","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1440,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Diffusion MRI; Brain development; Neuroscience; Human brain; Diffusion imaging; Psychology; Magnetic resonance imaging; Brain morphometry; Medicine","score_opus":0.035499247140400605,"score_gpt":0.3177595942313928,"score_spread":0.2822603470909922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038568172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98989606,0.000012495378,0.0006413477,0.0082314145,0.000048529688,0.00049822335,0.000054521974,0.00011412093,0.00050327444],"genre_scores_gemma":[0.98632264,0.0000046351624,0.0083772065,0.004934618,0.000089528054,0.000016276115,0.00002551728,0.000022733133,0.0002068649],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99929124,0.000023537119,0.00018726525,0.00023425352,0.00014448339,0.000119209595],"domain_scores_gemma":[0.9992466,0.000030989464,0.000077796096,0.00053594465,0.000050995586,0.000057695226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018539393,0.00010067773,0.00013975374,0.000034962257,0.0001507569,0.00000594164,0.00015643693,0.000027569118,0.000027606193],"category_scores_gemma":[0.00008544862,0.0000734186,0.000076738324,0.00019412009,0.00007754039,0.000049164824,0.00007946737,0.00018661308,0.000010012686],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000129995005,0.00004924371,0.0060295975,0.0000046334926,0.000002823245,0.0000070754704,0.00026181847,0.0000016685261,0.9863722,0.00019539076,0.006434612,0.00062796765],"study_design_scores_gemma":[0.00030408418,0.000059154398,0.81140405,0.000022703623,0.000011526422,0.00010150395,0.000008771665,0.000009761778,0.18359363,0.0006100945,0.0038152118,0.000059482543],"about_ca_topic_score_codex":0.000021474667,"about_ca_topic_score_gemma":0.0000013837807,"teacher_disagreement_score":0.8053745,"about_ca_system_score_codex":0.0000125951265,"about_ca_system_score_gemma":0.000020799742,"threshold_uncertainty_score":0.29939237},"labels":[],"label_agreement":null},{"id":"W2039002182","doi":"10.1167/9.8.772","title":"The organization of inter-hemispheric projections from areas 17 and 18 in the human splenium, studied with DTI probabilistic fiber tracking","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Splenium; Corpus callosum; Diffusion MRI; Occipital lobe; Neuroscience; Cortex (anatomy); Anatomy; Visual cortex; Dorsum; Magnetic resonance imaging; Psychology; Biology; Medicine","score_opus":0.04060653980845177,"score_gpt":0.3605347643817167,"score_spread":0.319928224573265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039002182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958226,0.000032764925,0.0022229694,0.0014472075,0.000017217613,0.0002608002,0.0000011047244,0.000009113859,0.00018621238],"genre_scores_gemma":[0.9959755,0.000038392747,0.0038280722,0.00004019627,0.000060232705,0.0000044839044,0.0000016844609,0.000009053141,0.000042363263],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99950564,0.000020409463,0.0002262688,0.00007263113,0.000121766316,0.000053305852],"domain_scores_gemma":[0.99926263,0.00013019756,0.00022928671,0.00015299156,0.00020595922,0.000018960876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001810833,0.000054493426,0.000108405155,0.000028323344,0.00011725223,0.000020089798,0.00008162198,0.000021525611,0.000019054994],"category_scores_gemma":[0.00015289905,0.000025884197,0.000017746881,0.00021269436,0.00007668923,0.00006249335,0.000019292711,0.00029856764,1.8496893e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027825712,0.0013226754,0.15487355,0.00008993897,0.00007802057,0.00003175056,0.0034489697,0.00006826686,0.7855264,0.00075160427,0.005892244,0.047638323],"study_design_scores_gemma":[0.0014083852,0.0008866042,0.9779991,0.0005886505,0.0001789157,0.0004971357,0.0008369667,0.00025662553,0.007727085,0.003292023,0.0062207766,0.00010771242],"about_ca_topic_score_codex":0.000011955672,"about_ca_topic_score_gemma":0.000028545657,"teacher_disagreement_score":0.82312554,"about_ca_system_score_codex":0.000014456256,"about_ca_system_score_gemma":0.000025874591,"threshold_uncertainty_score":0.12971444},"labels":[],"label_agreement":null},{"id":"W2039147736","doi":"10.1016/j.bandc.2009.04.002","title":"A choice reaction time index of callosal anatomical homotopy","year":2009,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Index (typography); Cognitive psychology; Corpus callosum; Audiology; Neuroscience; Choice reaction time; Cognition; Computer science; Medicine","score_opus":0.030500184692867152,"score_gpt":0.3391868692968782,"score_spread":0.30868668460401105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039147736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9831311,0.000028994147,0.005127491,0.006977095,0.0000063666025,0.00029125036,0.0000083778505,0.00013632691,0.00429298],"genre_scores_gemma":[0.997105,0.000023828301,0.0012043968,0.0014394297,0.00004311463,0.000008954367,0.00004016873,0.0000044884973,0.00013062457],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99967605,0.00000814738,0.00008891658,0.00010708687,0.00006181697,0.000057973237],"domain_scores_gemma":[0.99977857,0.0000343491,0.00003498846,0.000073537754,0.000039051916,0.00003947612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034400986,0.00004542854,0.000085982654,0.00004441751,0.000025172449,0.0000032608439,0.000014102581,0.00003617652,0.0000075613366],"category_scores_gemma":[0.0000523046,0.000043485918,0.000021460139,0.00008210514,0.000031963555,0.000042245756,0.0000050343415,0.000075508746,0.0000042383813],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000095505755,0.00019814372,0.00090023584,0.000016756474,0.000005667027,0.000004019203,0.000019434372,5.2355173e-8,0.877867,0.002522228,0.001673061,0.11669791],"study_design_scores_gemma":[0.0029960677,0.0009257983,0.8463689,0.00025691275,0.00013317971,0.0003500372,0.00003425527,0.0040627583,0.061623022,0.05507404,0.027900584,0.00027446283],"about_ca_topic_score_codex":0.0000051543975,"about_ca_topic_score_gemma":2.7422644e-7,"teacher_disagreement_score":0.84546864,"about_ca_system_score_codex":0.000009811291,"about_ca_system_score_gemma":0.000009318537,"threshold_uncertainty_score":0.17733043},"labels":[],"label_agreement":null},{"id":"W2039257006","doi":"10.1002/ana.20334","title":"Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy","year":2004,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":272,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fornix; Cingulum (brain); Diffusion MRI; Temporal lobe; Fractional anisotropy; White matter; Epilepsy; Magnetic resonance imaging; Tractography; Limbic system; Neuroscience; Hippocampal sclerosis; Psychology; Medicine; Hippocampus; Radiology; Central nervous system","score_opus":0.11135876017310625,"score_gpt":0.3787210650055335,"score_spread":0.26736230483242723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039257006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97698075,0.000048140122,0.00021377055,0.021785952,0.00003707095,0.00021578278,0.0000065739487,0.00008890356,0.000623087],"genre_scores_gemma":[0.9903699,0.0002128651,0.0009159431,0.008264831,0.000042687887,0.000020770942,0.00001958808,0.000018071807,0.00013532859],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990819,0.000031332114,0.00030812275,0.00023404934,0.000088723646,0.00025583914],"domain_scores_gemma":[0.99949235,0.00002992602,0.00008758865,0.00027391492,0.00005221768,0.000064021326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007406544,0.00011649066,0.00026090108,0.00016587271,0.00002763774,0.0000036093315,0.000102162936,0.00007941357,0.00002072817],"category_scores_gemma":[0.000018441619,0.00010493645,0.000070627284,0.00017454228,0.00013826395,0.00007443841,0.00006762166,0.00024009698,0.0000072089406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013883419,0.0014613844,0.90746117,0.00015690047,0.000021753725,0.0010289934,0.0005155252,0.0005127585,0.05760535,0.02408354,0.0010159457,0.0047483197],"study_design_scores_gemma":[0.001742917,0.002397501,0.8952824,0.00007447802,0.00001322212,0.0005792558,0.000009882987,0.00015340158,0.023567924,0.051184814,0.02479003,0.00020420145],"about_ca_topic_score_codex":0.00013468531,"about_ca_topic_score_gemma":0.000012336769,"teacher_disagreement_score":0.034037422,"about_ca_system_score_codex":0.000004927342,"about_ca_system_score_gemma":0.000030354868,"threshold_uncertainty_score":0.4279184},"labels":[],"label_agreement":null},{"id":"W2039280993","doi":"10.1016/j.neuroimage.2015.02.029","title":"Ultra-high resolution in-vivo 7.0 T structural imaging of the human hippocampus reveals the endfolial pathway","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Center for Research Resources; GE Healthcare; National Institutes of Health","keywords":"Hippocampal formation; Subiculum; Neuroscience; Hippocampus; Fornix; White matter; Neuroanatomy; Biology; Anatomy; In vivo; Entorhinal cortex; Medicine; Magnetic resonance imaging; Dentate gyrus","score_opus":0.05387784350167023,"score_gpt":0.33130764774635746,"score_spread":0.2774298042446872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039280993","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99014294,0.00005607023,0.00024262456,0.0043438496,0.00015758628,0.0006822095,0.000030483097,0.00011022917,0.004233991],"genre_scores_gemma":[0.9976967,0.000006505418,0.00081561314,0.00096919126,0.0001272962,0.00003634201,0.0000048102456,0.000027784228,0.00031575933],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987705,0.00011652796,0.00031416296,0.00027851886,0.00028252555,0.00023776584],"domain_scores_gemma":[0.9988337,0.00006700274,0.00016570638,0.00077062804,0.000093815506,0.00006912401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002225158,0.00014213556,0.00019083836,0.000057636305,0.00013610917,0.00001603214,0.0002947825,0.000031111264,0.000013687764],"category_scores_gemma":[0.00021441128,0.000086837405,0.000084313026,0.0003028522,0.00025148297,0.00009241503,0.00008914868,0.00038298062,0.0000026369512],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052934804,0.0000775079,0.07614726,0.00003836311,0.0000046449754,0.000041506155,0.00035653936,0.000066358254,0.9048759,0.009063365,0.0068747285,0.002400931],"study_design_scores_gemma":[0.0027986828,0.0002259727,0.6009326,0.00021277012,0.000093689625,0.00060246146,0.00020759187,0.0009062995,0.28409278,0.09568979,0.0138520505,0.00038530806],"about_ca_topic_score_codex":0.00009506184,"about_ca_topic_score_gemma":0.000007852179,"teacher_disagreement_score":0.6207831,"about_ca_system_score_codex":0.00005394476,"about_ca_system_score_gemma":0.00005626715,"threshold_uncertainty_score":0.35411268},"labels":[],"label_agreement":null},{"id":"W2039575924","doi":"10.1117/12.2043750","title":"Characterizing the spatial distribution of microhemorrhages resulting from Traumatic Brain Injury (TBI)","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Susceptibility weighted imaging; Corpus callosum; White matter; Diffusion MRI; Traumatic brain injury; Brain atlas; Medicine; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Computer science; Pathology; Radiology","score_opus":0.023114660498243976,"score_gpt":0.28060359176946736,"score_spread":0.2574889312712234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039575924","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9863548,0.00002894049,0.0012989915,0.010989915,0.00007851449,0.0006054079,0.000158426,0.00009530048,0.00038968798],"genre_scores_gemma":[0.92870975,0.000039663893,0.07032701,0.0002682976,0.00038500232,0.000118763666,0.00005748795,0.000043569955,0.000050466508],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982782,3.442375e-8,0.0007022648,0.00031261175,0.0004479733,0.00025889254],"domain_scores_gemma":[0.9981169,0.0003141329,0.00054145115,0.000098481265,0.0008536075,0.00007543578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056921167,0.0002305709,0.00040060637,0.000046719117,0.000097097334,0.00004474064,0.00054970407,0.000115938696,0.0000056342355],"category_scores_gemma":[0.0012109367,0.00016861837,0.00043429696,0.00022776924,0.00024715185,0.00021462527,0.00013415515,0.0003390681,6.6032294e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010863712,0.00010405192,0.00047107253,0.0003220982,0.00012171929,3.1413798e-8,0.00018677965,0.000006120203,0.914731,0.08029404,0.001415633,0.0022387991],"study_design_scores_gemma":[0.0013596506,0.00046143818,0.019647485,0.0010356798,0.000329067,0.000022143586,0.00089531735,0.04555541,0.91941345,0.003147328,0.0077866022,0.00034641288],"about_ca_topic_score_codex":0.000029784756,"about_ca_topic_score_gemma":1.0058413e-7,"teacher_disagreement_score":0.07714672,"about_ca_system_score_codex":0.000086765365,"about_ca_system_score_gemma":0.000019553449,"threshold_uncertainty_score":0.68760574},"labels":[],"label_agreement":null},{"id":"W2039631898","doi":"10.1097/00001756-200105250-00037","title":"Magnetic resonance imaging predicts neuropathology from soman-mediated seizures in the rodent","year":2001,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Department of National Defence; University of Saskatchewan; Royal University Hospital","funders":"","keywords":"Soman; Neuropathology; Hippocampus; Piriform cortex; Neuroscience; Thalamus; Status epilepticus; Entorhinal cortex; Pathology; Medicine; Chemistry; Epilepsy; Nuclear magnetic resonance; Psychology; Acetylcholinesterase; Physics","score_opus":0.04068828987462686,"score_gpt":0.32208652882462796,"score_spread":0.2813982389500011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039631898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9822061,0.0011350685,0.00048402738,0.00973963,0.00011767571,0.0006657743,0.00001406629,0.00036144102,0.0052761827],"genre_scores_gemma":[0.9893001,0.00040190478,0.0009057884,0.008776705,0.00014455197,0.00014082245,0.00004756598,0.000036924826,0.0002456459],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984852,0.00007562316,0.00038258385,0.0004951487,0.0002745189,0.00028691182],"domain_scores_gemma":[0.9988375,0.00014616956,0.00010856395,0.00079540064,0.00004400867,0.00006837944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014260202,0.00016124183,0.00020044479,0.00008945321,0.00006941451,0.000019047613,0.00021556675,0.000035859146,0.00003988991],"category_scores_gemma":[0.00027092278,0.00012324916,0.000054907705,0.00035365063,0.00011919526,0.00006790697,0.0000715508,0.00040628784,0.000022200478],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008084376,0.00029942667,0.931577,0.000007029329,0.000001271814,0.026922224,0.00019968163,0.000010207904,0.016325995,0.00014976686,0.0049926755,0.01943387],"study_design_scores_gemma":[0.0004261472,0.00009256498,0.8645893,0.000024615441,0.000022189197,0.0048043374,0.000022776976,0.0009610617,0.00030859714,0.0010139302,0.12764165,0.00009288016],"about_ca_topic_score_codex":0.000080813574,"about_ca_topic_score_gemma":0.000011203606,"teacher_disagreement_score":0.12264898,"about_ca_system_score_codex":0.000018070195,"about_ca_system_score_gemma":0.000044391043,"threshold_uncertainty_score":0.5025955},"labels":[],"label_agreement":null},{"id":"W2040016992","doi":"10.1016/j.neuroimage.2012.10.086","title":"Unbiased tensor-based morphometry: Improved robustness and sample size estimates for Alzheimer's disease clinical trials","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; University of California, San Diego; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; National Center for Research Resources; F. Hoffmann-La Roche; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Bayer HealthCare; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Synarc","keywords":"Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Sample size determination; Statistical power; Magnetic resonance imaging; Atrophy; Robustness (evolution); Clinical trial; Psychology; Medicine; Alzheimer's disease; Disease; Neuroscience; Internal medicine; Statistics; Radiology; Mathematics; Biology","score_opus":0.32498342244630846,"score_gpt":0.48478028006484475,"score_spread":0.1597968576185363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040016992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42589357,0.0018041824,0.5466303,0.0140552595,0.0005381146,0.007858705,0.001507384,0.0016044279,0.00010805798],"genre_scores_gemma":[0.71208054,0.000053234016,0.2840982,0.002814433,0.00035712626,0.00040560303,0.00007296661,0.00008373561,0.000034142486],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980662,0.0001526023,0.0006787826,0.00050970697,0.00015070249,0.00044203657],"domain_scores_gemma":[0.9878778,0.010417362,0.0002754543,0.0006725384,0.0001239953,0.00063285395],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011733198,0.00025995958,0.0006953085,0.000085498,0.00014743404,0.000041002408,0.00012169704,0.00007823742,0.000050001865],"category_scores_gemma":[0.021724202,0.0002181572,0.00026892847,0.00021534604,0.00021502646,0.00014020657,0.000058935122,0.000248761,0.00000337091],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007346835,0.0057883924,0.6932869,0.0008316361,0.0003803837,0.00008467763,0.000037714155,0.00018187653,0.15149546,0.0012132354,0.028966062,0.11038686],"study_design_scores_gemma":[0.013163361,0.0012054255,0.76614755,0.00015835869,0.0042614373,0.000055891443,0.000024416131,0.14796679,0.02442074,0.0023401843,0.039165404,0.0010904194],"about_ca_topic_score_codex":0.000008777529,"about_ca_topic_score_gemma":2.1092501e-7,"teacher_disagreement_score":0.286187,"about_ca_system_score_codex":0.000013429207,"about_ca_system_score_gemma":0.000074310985,"threshold_uncertainty_score":0.98651624},"labels":[],"label_agreement":null},{"id":"W2040052605","doi":"10.1016/j.nicl.2014.10.006","title":"48 echo T2 myelin imaging of white matter in first-episode schizophrenia: Evidence for aberrant myelination","year":2014,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Alberta; University of British Columbia","funders":"","keywords":"Splenium; White matter; Psychosis; Schizophrenia (object-oriented programming); Corpus callosum; Psychology; Audiology; Myelin; Internal medicine; Physiology; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Central nervous system; Radiology","score_opus":0.13971360487475387,"score_gpt":0.437893839152159,"score_spread":0.29818023427740514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040052605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57157165,0.00022398331,0.36817396,0.055039223,0.0005091652,0.0028269195,0.00003805605,0.0004072327,0.0012098528],"genre_scores_gemma":[0.9338726,0.00017148805,0.061769363,0.0033685379,0.00029958852,0.00016983111,0.000016912405,0.00005941568,0.00027229695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975303,0.00011820866,0.0011107372,0.00070643687,0.00022743978,0.00030689145],"domain_scores_gemma":[0.99717647,0.0013651707,0.0003086409,0.0008177106,0.00020751575,0.00012450234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009877598,0.0002056845,0.0005308959,0.00016491374,0.00010174952,0.000016282453,0.00025274357,0.000095036,0.000053808057],"category_scores_gemma":[0.0024519507,0.00019626057,0.0002491298,0.00025950442,0.00021449827,0.00020772182,0.00015156726,0.00052510935,0.0000490088],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007709737,0.0005227513,0.9640954,0.0002809042,0.0000074592076,0.000015754715,0.00006317116,0.000057896024,0.003199046,0.00029436414,0.01107807,0.01961418],"study_design_scores_gemma":[0.0035183337,0.00036162895,0.9252232,0.00071602844,0.00011034891,0.00005581435,0.000009386627,0.049293835,0.0017181303,0.0037785494,0.014918611,0.0002961725],"about_ca_topic_score_codex":0.00001623439,"about_ca_topic_score_gemma":0.000015209749,"teacher_disagreement_score":0.36230093,"about_ca_system_score_codex":0.000030395562,"about_ca_system_score_gemma":0.000034335753,"threshold_uncertainty_score":0.80032736},"labels":[],"label_agreement":null},{"id":"W2040187618","doi":"10.1159/000103689","title":"Motor Fiber Distribution within the Cerebral Peduncle","year":2007,"lang":"en","type":"article","venue":"Confinia Neurologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Cerebral peduncle; Neuroscience; Medicine; Anatomy; Physical medicine and rehabilitation; Distribution (mathematics); Psychology; Radiology; Mathematics; Magnetic resonance imaging","score_opus":0.06084176426775483,"score_gpt":0.33440825758654874,"score_spread":0.2735664933187939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040187618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95104957,0.00004683729,0.011640709,0.021234216,0.00013873595,0.00085328915,0.000044256376,0.00064050243,0.014351877],"genre_scores_gemma":[0.9913437,0.0000075611238,0.0013269671,0.0054162913,0.00014163558,0.00003760914,0.000038129932,0.000013108292,0.0016750329],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99918944,0.000022206115,0.00019702948,0.0002551166,0.00012383815,0.00021235345],"domain_scores_gemma":[0.9992325,0.00014050351,0.0000808419,0.00041036715,0.000054548527,0.00008129766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020539695,0.00010887024,0.00012050889,0.000017870196,0.00016662321,0.0000135937535,0.00013703834,0.00005952268,0.00019158916],"category_scores_gemma":[0.00016594952,0.00006730582,0.00006594699,0.00014661759,0.00016477276,0.000024898,0.000058028978,0.00031603425,0.000117632466],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004024729,0.0020277458,0.12341562,0.000121363344,0.00011335918,0.0010848929,0.00051895424,0.00007204831,0.252826,0.3859359,0.13980827,0.09005113],"study_design_scores_gemma":[0.00048526394,0.00062363344,0.3790036,0.0000071737577,0.00004915853,0.00030719096,0.000014067315,0.00031802242,0.008371571,0.0033337635,0.60734344,0.00014313906],"about_ca_topic_score_codex":0.0000049113587,"about_ca_topic_score_gemma":0.0000011404945,"teacher_disagreement_score":0.46753514,"about_ca_system_score_codex":0.000012037264,"about_ca_system_score_gemma":0.000021952916,"threshold_uncertainty_score":0.27446514},"labels":[],"label_agreement":null},{"id":"W2040977327","doi":"10.1002/ajmg.a.33305","title":"Magnetic resonance imaging of a unique mutation in a family with Pelizaeus–Merzbacher disease","year":2010,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part A","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Leukodystrophy; Hypotonia; Magnetic resonance imaging; Dysarthria; Nystagmus; Spasticity; Medicine; Disease; Pathology; Internal medicine; Radiology","score_opus":0.020936927887984853,"score_gpt":0.33612421771584367,"score_spread":0.3151872898278588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040977327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9784462,0.0016149352,0.01351534,0.006044508,0.000037884085,0.00017895475,0.0000039494976,0.0000149679645,0.00014329665],"genre_scores_gemma":[0.96206933,0.0007726427,0.03605685,0.00095945905,0.00008065187,0.000013015669,0.0000018535445,0.000022553799,0.000023616902],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9985451,0.000047177087,0.00045153455,0.00014833068,0.00063843915,0.00016942718],"domain_scores_gemma":[0.99881387,0.00008517811,0.00029608235,0.0002476734,0.00019011003,0.00036710943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003286748,0.00010639757,0.0002951102,0.00013556182,0.000016648555,0.0000055048554,0.00018800239,0.000025520367,0.000047167185],"category_scores_gemma":[0.00023143995,0.00008230264,0.000056280143,0.00039274045,0.0005766557,0.000029942848,0.000031111063,0.0005457377,0.0000010811173],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007098667,0.00067325804,0.3116688,0.000050074024,0.0000130516655,0.0011924756,0.00038327446,0.000042272648,0.013066597,0.00044302133,0.0007723923,0.67098486],"study_design_scores_gemma":[0.0034556198,0.002517383,0.925021,0.0012340037,0.00019968153,0.0017858064,0.00054057786,0.00760506,0.0020276248,0.0015599565,0.053721078,0.00033224444],"about_ca_topic_score_codex":0.000019518136,"about_ca_topic_score_gemma":0.0000080491145,"teacher_disagreement_score":0.6706526,"about_ca_system_score_codex":0.000015930218,"about_ca_system_score_gemma":0.0004161294,"threshold_uncertainty_score":0.33562046},"labels":[],"label_agreement":null},{"id":"W2041765815","doi":"10.1016/j.neuroimage.2011.02.043","title":"Distribution of collateral fibers in the monkey cervical spinal cord detected with diffusion-weighted magnetic resonance imaging","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Lundbeckfonden","keywords":"White matter; Diffusion MRI; Spinal cord; Magnetic resonance imaging; Fractional anisotropy; Anatomy; Nuclear magnetic resonance; Fiber bundle; Fiber; Chemistry; Materials science; Physics; Neuroscience; Medicine; Radiology; Biology","score_opus":0.03891913667255878,"score_gpt":0.29721808275488787,"score_spread":0.25829894608232906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041765815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99487185,0.00014437747,0.00220264,0.00083599926,0.000021976595,0.00064308546,0.000030260857,0.000115623654,0.0011341971],"genre_scores_gemma":[0.99441946,0.00003797879,0.004963356,0.00041378752,0.000022075348,0.00006087581,0.000024216497,0.000021813154,0.000036420442],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99894625,0.000055573964,0.0002506687,0.000302916,0.00021640233,0.00022821674],"domain_scores_gemma":[0.9992758,0.000040717958,0.00008451858,0.00046750816,0.000076562974,0.000054870212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006403374,0.0001454614,0.00018164369,0.00005920019,0.000065742846,0.000009885067,0.00018206173,0.000028349361,0.00003533387],"category_scores_gemma":[0.00002452626,0.00009925154,0.000043248354,0.0004916516,0.00019707292,0.0000674991,0.000049950184,0.00027326058,0.0000033663819],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013162429,0.0021915454,0.6747241,0.00025609843,0.000009515693,0.001975601,0.00080624875,0.000001812419,0.11491061,0.0026847401,0.002455675,0.1868216],"study_design_scores_gemma":[0.0009978542,0.0010253948,0.98856586,0.00010194551,0.00003219393,0.0002653242,0.000030205703,0.0012039506,0.0042076036,0.00046761322,0.0029913639,0.00011070335],"about_ca_topic_score_codex":0.000087640554,"about_ca_topic_score_gemma":0.0000074450527,"teacher_disagreement_score":0.31384173,"about_ca_system_score_codex":0.000024631867,"about_ca_system_score_gemma":0.00002652233,"threshold_uncertainty_score":0.40473604},"labels":[],"label_agreement":null},{"id":"W2041846560","doi":"10.1016/j.jradio.2012.02.019","title":"Tractographie du nerf médian à 3T : optimisation des paramètres d’acquisition et mesure des paramètres de diffusivité","year":2012,"lang":"fr","type":"article","venue":"Journal de radiologie diagnostique et interventionnelle","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.09967813379439042,"score_gpt":0.40383946021281664,"score_spread":0.3041613264184262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041846560","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55965376,0.04279117,0.3817011,0.01369518,0.00071426015,0.00054302,0.00008427683,0.0002530316,0.00056419376],"genre_scores_gemma":[0.8471024,0.09958222,0.04936078,0.0015685345,0.0014535937,0.00023935377,0.00011383146,0.000086687025,0.0004925848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954784,0.001635874,0.00095143256,0.0004140362,0.0002585159,0.0012617612],"domain_scores_gemma":[0.9957426,0.0021266034,0.00066047854,0.00042323917,0.00029746568,0.00074956997],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0031761378,0.0005074353,0.00057225314,0.00038185925,0.0006605911,0.00022352755,0.00037235327,0.0004532124,0.00091394736],"category_scores_gemma":[0.0031032083,0.0004836577,0.0008467348,0.0004178782,0.00070537376,0.0012341696,0.00011518263,0.0015256222,0.000046588637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028614697,0.0050396034,0.7993327,0.0006655281,0.00048174016,0.0006564397,0.004883273,0.008541873,0.0035657973,0.026503356,0.06145109,0.08859249],"study_design_scores_gemma":[0.0015355892,0.0011286072,0.8582078,0.0043914295,0.00056842004,0.008786668,0.0014971179,0.0017832455,0.004528187,0.10308737,0.013869344,0.0006161882],"about_ca_topic_score_codex":0.00024847497,"about_ca_topic_score_gemma":0.00005725128,"teacher_disagreement_score":0.33234033,"about_ca_system_score_codex":0.00076227885,"about_ca_system_score_gemma":0.00018586853,"threshold_uncertainty_score":0.99999934},"labels":[],"label_agreement":null},{"id":"W2042245762","doi":"10.1016/j.schres.2010.03.027","title":"Disrupted integrity of the fornix in first-episode schizophrenia","year":2010,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research","keywords":"Fornix; Schizophrenia (object-oriented programming); Fractional anisotropy; Psychosis; Stage (stratigraphy); Medicine; Psychology; Internal medicine; Psychiatry; Diffusion MRI; Magnetic resonance imaging; Radiology; Hippocampus; Biology","score_opus":0.11892978607288768,"score_gpt":0.426580314473805,"score_spread":0.30765052840091733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042245762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98530406,0.000055245393,0.00021552615,0.011253936,0.00009781939,0.0010810433,0.000027072856,0.000100321195,0.0018649797],"genre_scores_gemma":[0.9819981,0.000043485983,0.01716286,0.00006401349,0.00012128926,0.00020157438,0.000008311301,0.00003409339,0.00036627924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979984,0.00010667688,0.00037075407,0.00041173882,0.0006467227,0.00046570814],"domain_scores_gemma":[0.99786353,0.00032813963,0.000076232755,0.001278962,0.00030695915,0.00014615837],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009420302,0.00015242015,0.000276275,0.0003071667,0.00023196667,0.0000219883,0.00061057095,0.00015193589,0.00011546704],"category_scores_gemma":[0.0012104564,0.00010445589,0.00012885692,0.0014536126,0.0006372482,0.00008402972,0.0003984912,0.0032615322,0.000035407826],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005265645,0.0018489083,0.4060288,0.00044747975,0.000049755155,0.000060613762,0.0003256767,0.000013351885,0.33294493,0.17705776,0.010178378,0.06577868],"study_design_scores_gemma":[0.0048437044,0.00028060493,0.76533383,0.00045793154,0.000028604354,0.00013168999,0.00007297619,0.0021655,0.112583145,0.081086054,0.032674894,0.0003410856],"about_ca_topic_score_codex":0.00041988562,"about_ca_topic_score_gemma":0.0022394578,"teacher_disagreement_score":0.359305,"about_ca_system_score_codex":0.00005894297,"about_ca_system_score_gemma":0.00018827397,"threshold_uncertainty_score":0.999038},"labels":[],"label_agreement":null},{"id":"W2042564460","doi":"10.1002/mrm.22131","title":"Characterizing healthy and diseased white matter using quantitative magnetization transfer and multicomponent <i>T</i><sub>2</sub> relaxometry: A unified view via a four‐pool model","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Relaxometry; Magnetization transfer; White matter; Magnetization; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Relaxation (psychology); Physics; Magnetic field; Spin echo; Neuroscience; Radiology; Medicine","score_opus":0.06480513998380737,"score_gpt":0.3337138529243339,"score_spread":0.26890871294052654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042564460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88708884,0.0070358976,0.08585579,0.018556364,0.0000222303,0.0012723682,0.000010835476,0.00008143383,0.0000762646],"genre_scores_gemma":[0.96518946,0.0048505617,0.022422252,0.007330955,0.00004473998,0.000073734285,0.000024924246,0.000036750713,0.000026654792],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99824136,0.000071608956,0.00053074677,0.00054267736,0.0002734257,0.0003401666],"domain_scores_gemma":[0.9992359,0.00008325436,0.000079254496,0.000315751,0.000072445364,0.0002133583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023429147,0.00026745122,0.00052137964,0.00027448763,0.00009822027,0.000014826116,0.000071883,0.00007675043,0.000018139643],"category_scores_gemma":[0.00005749204,0.00023474202,0.00002995999,0.00049276487,0.0002226388,0.000117061325,0.000024401343,0.0003027175,0.0000017122951],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012921764,0.0003736285,0.028650533,0.0005680947,0.0000061971677,0.00010588623,0.0015218648,0.00012800517,0.78799623,0.0006705482,0.00014417658,0.17854264],"study_design_scores_gemma":[0.00450687,0.0015031608,0.61985785,0.0017131505,0.00013894403,0.00016776395,0.00007772008,0.36747414,0.0013836905,0.0019895989,0.00082099845,0.00036611676],"about_ca_topic_score_codex":0.000019268491,"about_ca_topic_score_gemma":0.000004002543,"teacher_disagreement_score":0.7866126,"about_ca_system_score_codex":0.00006131371,"about_ca_system_score_gemma":0.000033629723,"threshold_uncertainty_score":0.95725024},"labels":[],"label_agreement":null},{"id":"W2042794599","doi":"10.1117/12.2043103","title":"Resolving complex fibre architecture by means of sparse spherical deconvolution in the presence of isotropic diffusion","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deconvolution; Isotropy; Diffusion MRI; Blind deconvolution; Image resolution; Computer science; Resolution (logic); Angular resolution (graph drawing); Artificial intelligence; Physics; Algorithm; Optics; Mathematics","score_opus":0.02265219539031553,"score_gpt":0.2706733839628472,"score_spread":0.24802118857253164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042794599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99110436,0.000057101483,0.002829503,0.0045409487,0.000027156464,0.0005966892,0.000028407298,0.000039898787,0.0007759072],"genre_scores_gemma":[0.82020795,0.000074204196,0.17936535,0.00011330054,0.00009292106,0.00007310905,0.000009522146,0.000025999689,0.00003764007],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984053,5.8287664e-8,0.0005863357,0.00026702546,0.0005135652,0.0002277506],"domain_scores_gemma":[0.99865675,0.00023620365,0.0003624006,0.00009209997,0.0005950335,0.00005751881],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037457485,0.0001860751,0.0003739803,0.000060030026,0.000044332384,0.00001565712,0.0006026994,0.0001032305,0.000006906511],"category_scores_gemma":[0.00064852013,0.00013286823,0.00031127338,0.0003177703,0.00030063218,0.00013269375,0.00012343805,0.00031774683,1.7569342e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009837483,0.00019961226,0.0022381893,0.0004820378,0.000047836795,3.865375e-8,0.00023411724,0.00013285181,0.8493695,0.14392425,0.0026593108,0.00061384443],"study_design_scores_gemma":[0.0051099686,0.002622806,0.051777236,0.002863555,0.0005166342,0.00011084305,0.0030039644,0.31405044,0.5705468,0.020902112,0.027640484,0.00085511303],"about_ca_topic_score_codex":0.000017713099,"about_ca_topic_score_gemma":2.5082736e-7,"teacher_disagreement_score":0.3139176,"about_ca_system_score_codex":0.00005869383,"about_ca_system_score_gemma":0.000016332931,"threshold_uncertainty_score":0.5418209},"labels":[],"label_agreement":null},{"id":"W2043236948","doi":"10.1118/1.4811155","title":"Gray matter parcellation constrained full brain fiber bundling with diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Diffusion MRI; Bundle; Fiber bundle; Computer science; Cluster analysis; Artificial intelligence; Segmentation; Tractography; Consistency (knowledge bases); Pattern recognition (psychology); Computer vision; Medicine; Magnetic resonance imaging","score_opus":0.02028938762671474,"score_gpt":0.29402567756381554,"score_spread":0.2737362899371008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043236948","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38812697,0.00002797446,0.53645515,0.062949225,0.000042234897,0.0010757563,0.0000059108916,0.00049763644,0.010819144],"genre_scores_gemma":[0.98163015,0.0000065494078,0.009719408,0.007209772,0.00027225318,0.00007899341,0.00005181222,0.000038265873,0.0009928256],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989286,0.00001619217,0.00018805219,0.000266085,0.00037167818,0.00022938423],"domain_scores_gemma":[0.99924314,0.00011938946,0.00006963122,0.00027763538,0.00008889227,0.00020133944],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006682868,0.00014127386,0.00018615792,0.000026473002,0.000090289315,0.000020990341,0.000078948025,0.000042320444,0.0013447347],"category_scores_gemma":[0.000049725062,0.00010062394,0.000047806978,0.00014281432,0.00021494624,0.00008916981,0.00004333274,0.0002854448,0.00033937584],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000153696,0.001206937,0.31001917,0.00032960874,0.000070428374,0.00012233417,0.00040050733,0.00003706215,0.06510596,0.0018600695,0.10301856,0.5176757],"study_design_scores_gemma":[0.01879497,0.0015310552,0.41881755,0.0043961075,0.0007340391,0.0023382602,0.00045013658,0.13951589,0.047596373,0.13611378,0.22592501,0.0037868202],"about_ca_topic_score_codex":0.000029573263,"about_ca_topic_score_gemma":5.522965e-7,"teacher_disagreement_score":0.5935032,"about_ca_system_score_codex":0.00002527855,"about_ca_system_score_gemma":0.00003731635,"threshold_uncertainty_score":0.99956816},"labels":[],"label_agreement":null},{"id":"W2043379623","doi":"10.1155/2008/789539","title":"The Connectivity of the Human Pulvinar: A Diffusion Tensor Imaging Tractography Study","year":2007,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Superior colliculus; Neuroscience; Diffusion MRI; Tractography; Thalamus; Human brain; Visual cortex; Lateral geniculate nucleus; Visual system; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.03121094351563305,"score_gpt":0.39334704502979956,"score_spread":0.36213610151416653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043379623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9497353,0.00018275356,0.029385442,0.019381419,0.00059467106,0.0002869934,0.000004227525,0.000029312549,0.00039988576],"genre_scores_gemma":[0.99822503,0.00002860586,0.0009491057,0.00045756972,0.000288916,0.0000032206235,0.0000012818642,0.000014077992,0.000032172204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980767,0.000049610626,0.0006498295,0.00013741285,0.0009080528,0.00017842358],"domain_scores_gemma":[0.99819696,0.00034632062,0.00056171743,0.00023760594,0.0005492747,0.000108102686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010662415,0.00011143896,0.00019169724,0.00023528111,0.0001957863,0.000035781864,0.00054971233,0.000018453009,0.000010773737],"category_scores_gemma":[0.0003828329,0.00005833634,0.00023877929,0.0002837774,0.00045064167,0.000115940566,0.00015083916,0.00046005822,4.7440284e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001206615,0.0012278514,0.8300267,0.0000056705962,0.000100407495,0.00019303268,0.00023816447,4.6012894e-7,0.08734277,0.0004933735,0.0010346123,0.0792163],"study_design_scores_gemma":[0.0016277187,0.0001367134,0.97308725,0.00021807935,0.00009688345,0.0013164751,0.0010211051,0.00025263504,0.0031823097,0.0033310896,0.015642075,0.00008766168],"about_ca_topic_score_codex":0.000027956223,"about_ca_topic_score_gemma":0.000003414821,"teacher_disagreement_score":0.14306056,"about_ca_system_score_codex":0.00007401708,"about_ca_system_score_gemma":0.000049668164,"threshold_uncertainty_score":0.23788868},"labels":[],"label_agreement":null},{"id":"W2043948336","doi":"10.1001/jamapsychiatry.2013.865","title":"APOE ϵ 4, Aging, and Effects on White Matter Across the Adult Life Span","year":2013,"lang":"en","type":"letter","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Family medicine; Neurology; Otorhinolaryngology; Subspecialty; Psychiatry; Gerontology","score_opus":0.0173784978577727,"score_gpt":0.31277386654120337,"score_spread":0.2953953686834307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043948336","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010701455,0.00033625995,0.0004496196,0.98291266,0.0006398905,0.0012340139,0.00004729452,0.00027860643,0.003400198],"genre_scores_gemma":[0.002772818,0.000114859075,0.0045189816,0.9753489,0.007830278,0.00043306203,0.000112234025,0.00014018315,0.008728715],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99825233,0.000055759105,0.00028383863,0.00064472365,0.00029536674,0.00046798057],"domain_scores_gemma":[0.99822587,0.00013162958,0.00021252087,0.0012277741,0.000080948004,0.00012125192],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00007505801,0.00041098092,0.0003991215,0.00007032367,0.00022389929,0.00014059064,0.00028792137,0.0004722004,0.00009997247],"category_scores_gemma":[0.000034038745,0.0002712497,0.00015215913,0.0001334355,0.00014296122,0.00006874626,0.000119380915,0.0026855392,0.00048050162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015497968,0.00003080096,0.0275466,0.00054016476,0.00003441397,0.000015322885,0.0000862196,1.9108805e-7,0.00000848694,0.00009229285,0.96956193,0.0020680835],"study_design_scores_gemma":[0.0008248849,0.00012855555,0.05439031,0.0007762007,0.00010908037,0.00013076248,0.00002119687,0.000025163565,0.00003518465,0.0017893151,0.9414559,0.000313468],"about_ca_topic_score_codex":0.000024315637,"about_ca_topic_score_gemma":0.0000019349252,"teacher_disagreement_score":0.02810605,"about_ca_system_score_codex":0.000033285683,"about_ca_system_score_gemma":0.0000631147,"threshold_uncertainty_score":0.99997395},"labels":[],"label_agreement":null},{"id":"W2044093652","doi":"10.1109/isbi.2014.6868055","title":"A preliminary study on the effect of motion correction on HARDI reconstruction","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Calgary; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering","keywords":"Interpolation (computer graphics); Diffusion MRI; Motion (physics); Orientation (vector space); Diffusion; Voxel; Computer vision; Computer science; Artificial intelligence; Volume (thermodynamics); Fiber; Diffusion imaging; Mathematics; Physics; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.03671896397938755,"score_gpt":0.3329350652472624,"score_spread":0.29621610126787484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044093652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96204764,0.0000010057195,0.024971448,0.00090669387,0.00014878661,0.0010855134,4.4605733e-7,0.00016522083,0.010673224],"genre_scores_gemma":[0.9990231,0.000001506839,0.000257906,0.00012989715,0.000050712486,0.000120103854,0.0000019367906,0.000009070954,0.00040575946],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99949837,0.0000861172,0.00010908914,0.00014885199,0.00010302809,0.000054539727],"domain_scores_gemma":[0.9993487,0.00024380093,0.000059690006,0.00030436128,0.000025423275,0.00001803577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002146484,0.00006836663,0.00010920572,0.00004957836,0.00006170538,0.0000032104674,0.00003303183,0.00002116315,0.00001889935],"category_scores_gemma":[0.00014431312,0.000038992737,0.000041329335,0.00010023527,0.00002788282,0.000020556545,0.000009707448,0.00012555048,0.000014957733],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016337761,0.000808195,0.09731524,0.00004241254,0.000038408813,0.0000013324793,0.00013096718,0.00017939601,0.015398798,0.0027517206,0.0075655147,0.87413424],"study_design_scores_gemma":[0.0018979885,0.04219287,0.4850737,0.00026714883,0.00019697222,0.00013121335,0.00022144993,0.014500229,0.452572,0.0008188842,0.0019625132,0.00016506544],"about_ca_topic_score_codex":0.0000087601375,"about_ca_topic_score_gemma":3.4993053e-7,"teacher_disagreement_score":0.8739692,"about_ca_system_score_codex":0.000020594502,"about_ca_system_score_gemma":0.0000023376533,"threshold_uncertainty_score":0.15900776},"labels":[],"label_agreement":null},{"id":"W2044166387","doi":"10.1016/j.pscychresns.2014.12.004","title":"Comparison of grey matter volume and thickness for analysing cortical changes in chronic schizophrenia: A matter of surface area, grey/white matter intensity contrast, and curvature","year":2014,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Dietmar Hopp Stiftung","keywords":"Grey matter; White matter; Magnetic resonance imaging; Voxel-based morphometry; Volume (thermodynamics); Grey level; Anatomy; Psychology; Medicine; Physics; Radiology; Optics","score_opus":0.08532282439859742,"score_gpt":0.4130633234266466,"score_spread":0.32774049902804914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044166387","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94805574,0.00055061426,0.0141701875,0.03608903,0.000058263206,0.00085683225,0.000026951735,0.00003355308,0.00015884789],"genre_scores_gemma":[0.98382324,0.000035817815,0.01490956,0.0009410644,0.00008710942,0.000038177728,0.000013449726,0.00004827804,0.00010331792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979356,0.00017024623,0.00046879603,0.0005999439,0.00032673683,0.0004986955],"domain_scores_gemma":[0.99852186,0.00027626622,0.00016940475,0.0005132736,0.0003743738,0.00014482072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006956925,0.00021433258,0.00068831275,0.0003273517,0.000142727,0.000049190905,0.00016162379,0.00008229809,0.00005463188],"category_scores_gemma":[0.00010209616,0.00019737153,0.00006783791,0.0004311895,0.0005567249,0.00012955915,0.00019806474,0.00096436654,0.0000053720214],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036182842,0.00011803479,0.96381515,0.00076956226,0.000019886893,0.0000016901253,0.000118621094,0.000018256524,0.03071289,0.000099231365,0.0036462743,0.00031856788],"study_design_scores_gemma":[0.0012996496,0.00024145171,0.9604207,0.00054433214,0.00008443426,0.0000814322,0.000112000074,0.033935007,0.0011024392,0.001617942,0.00038923245,0.00017135816],"about_ca_topic_score_codex":0.000057494057,"about_ca_topic_score_gemma":0.00007075445,"teacher_disagreement_score":0.035767503,"about_ca_system_score_codex":0.000038472517,"about_ca_system_score_gemma":0.0000618975,"threshold_uncertainty_score":0.8048577},"labels":[],"label_agreement":null},{"id":"W2044271030","doi":"10.1016/j.mri.2007.03.010","title":"Efficacy of motion artifact reduction in neonatal DW segmented EPI at 3 T using phase correction by numerical optimization and segment data swapping","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Lawson Health Research Institute","funders":"","keywords":"Percentile; Artifact (error); Diffusion MRI; Noise (video); Noise reduction; Nuclear medicine; Population; Reduction (mathematics); Distortion (music); Mathematics; Medicine; Artificial intelligence; Computer science; Magnetic resonance imaging; Radiology; Image (mathematics); Statistics","score_opus":0.04959400590207793,"score_gpt":0.36294686813294436,"score_spread":0.31335286223086645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044271030","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35087344,0.0019314901,0.6461641,0.0003028179,0.0000783571,0.0005160347,0.000012961763,0.00007447474,0.000046318502],"genre_scores_gemma":[0.92227376,0.00026789826,0.07690682,0.00006538403,0.00005318473,0.0000125489305,0.00026508752,0.000029990311,0.00012531503],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986677,0.000029176244,0.00041827638,0.0004586751,0.00019488463,0.00023125636],"domain_scores_gemma":[0.9992711,0.000051367966,0.00016010617,0.00039546753,0.000052259544,0.00006968954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028334142,0.00013761068,0.00019378113,0.00014920422,0.00009237662,0.000014317886,0.00007780786,0.000033045424,0.000031168893],"category_scores_gemma":[0.000087779095,0.00015031852,0.00002189845,0.00038692504,0.00009637469,0.00022319487,0.000117102434,0.00015622086,8.8324305e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037780072,0.00029535263,0.010585153,0.000034281125,0.0000026273751,0.000014892475,0.000154952,0.0021224616,0.21195593,0.0000049546666,0.0004165527,0.77403504],"study_design_scores_gemma":[0.0028379145,0.0001234784,0.0124650635,0.00027998976,0.00004802599,0.00036348042,0.00012996088,0.93608534,0.043816213,0.000015646674,0.0036580623,0.00017683925],"about_ca_topic_score_codex":0.000091563,"about_ca_topic_score_gemma":0.0000011802994,"teacher_disagreement_score":0.9339629,"about_ca_system_score_codex":0.000190899,"about_ca_system_score_gemma":0.00001808263,"threshold_uncertainty_score":0.61298114},"labels":[],"label_agreement":null},{"id":"W2044697134","doi":"10.1002/mrm.22971","title":"Results for diffusion‐weighted imaging with a fourth‐channel gradient insert","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Alberta","funders":"","keywords":"SIGNAL (programming language); Diffusion; Noise (video); Signal-to-noise ratio (imaging); Nuclear magnetic resonance; Insert (composites); Gradient echo; Image quality; Imaging phantom; Physics; Spin echo; Diffusion MRI; Acoustics; Optics; Materials science; Magnetic resonance imaging; Computer science; Image (mathematics); Artificial intelligence; Medicine","score_opus":0.0636049603211421,"score_gpt":0.3142896367512062,"score_spread":0.2506846764300641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044697134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7184181,0.019171193,0.12733401,0.06470259,0.0005186196,0.012026721,0.00011027519,0.0014301047,0.056288343],"genre_scores_gemma":[0.85603976,0.0017193704,0.13395463,0.0036943294,0.00028387553,0.0012995562,0.00006864771,0.000098304474,0.002841504],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99831116,0.000020291713,0.00047274661,0.0005349099,0.0002621031,0.0003987784],"domain_scores_gemma":[0.9988837,0.00011565528,0.00011482845,0.0005952306,0.0001382771,0.00015230685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023666669,0.0002259901,0.0003946129,0.0002193708,0.00007738152,0.0000042009947,0.00017392008,0.000043428885,0.000037131707],"category_scores_gemma":[0.0001786005,0.00015648488,0.000041234463,0.0004837701,0.00029267714,0.000051667277,0.000042875214,0.00023383948,0.0000035837063],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019511435,0.0029106096,0.10026577,0.0006580534,0.000029662233,0.0016089013,0.01249334,0.00000664246,0.013037788,0.011944207,0.059649996,0.7778836],"study_design_scores_gemma":[0.03262708,0.0077562975,0.5048239,0.004111906,0.0002335725,0.00079635554,0.0008915892,0.026651472,0.002805229,0.02796746,0.3904477,0.00088739535],"about_ca_topic_score_codex":0.00022557063,"about_ca_topic_score_gemma":0.000042490145,"teacher_disagreement_score":0.7769962,"about_ca_system_score_codex":0.000054047436,"about_ca_system_score_gemma":0.000040134615,"threshold_uncertainty_score":0.6381268},"labels":[],"label_agreement":null},{"id":"W2045092603","doi":"10.1109/isbi.2012.6235604","title":"Diffusion tensor image processing using biquaternions","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Convolution (computer science); Diffusion MRI; Fourier transform; Image processing; Computer science; Artificial intelligence; Tensor (intrinsic definition); Quaternion; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Image (mathematics); Mathematical analysis; Magnetic resonance imaging; Geometry; Artificial neural network","score_opus":0.12843603228419348,"score_gpt":0.4108350481169518,"score_spread":0.28239901583275834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045092603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58399713,0.00008794128,0.40767112,0.00158894,0.000023073,0.00027246543,0.000001781128,0.00048507555,0.0058725094],"genre_scores_gemma":[0.7662047,0.000012057718,0.2324472,0.0005063902,0.000101483485,0.000012465241,0.000004337258,0.000017527056,0.00069384684],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995114,0.0000052660657,0.00010319757,0.00010930344,0.00008114284,0.0001896754],"domain_scores_gemma":[0.999639,0.000008951232,0.000033045686,0.00017298998,0.000043639175,0.00010237149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004325345,0.00007149418,0.000087780325,0.000048343238,0.000104626146,0.000010252338,0.000033539192,0.00002370322,0.00007154513],"category_scores_gemma":[0.0000174973,0.000053552267,0.000031293916,0.00012289546,0.000035859717,0.00015052779,0.000037941405,0.00008577087,0.00002666585],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012753237,0.00033782097,0.08685711,0.000053956963,0.0000033571637,0.0000035840856,0.000105370294,8.9442403e-7,0.8917567,0.0014866628,0.00075835374,0.018623408],"study_design_scores_gemma":[0.0023871702,0.00022480785,0.29790372,0.0006513554,0.0004196723,0.0019214961,0.00056716247,0.06641756,0.42815515,0.0036665709,0.19649495,0.0011903656],"about_ca_topic_score_codex":0.000011231485,"about_ca_topic_score_gemma":1.2240918e-7,"teacher_disagreement_score":0.46360156,"about_ca_system_score_codex":0.000024576593,"about_ca_system_score_gemma":0.000012446777,"threshold_uncertainty_score":0.21837981},"labels":[],"label_agreement":null},{"id":"W2045137447","doi":"10.1016/j.nicl.2013.04.006","title":"Evaluation of white matter myelin water fraction in chronic stroke","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Myelin; Internal capsule; Stroke (engine); Fractional anisotropy; Multiple sclerosis; Cerebrum; Internal medicine; Neuroscience; Medicine; Pathology; Psychology; Magnetic resonance imaging; Central nervous system; Radiology; Physics; Immunology","score_opus":0.16892122773044577,"score_gpt":0.4599771192522647,"score_spread":0.29105589152181893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045137447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882536,0.000026520933,0.0028362502,0.0052371393,0.00008050207,0.0009618458,0.0000037876532,0.00006760136,0.0025327646],"genre_scores_gemma":[0.99476665,0.000054533997,0.0033131018,0.0010970721,0.00016387313,0.00014987848,0.000018960276,0.000026580901,0.0004093602],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982204,0.00018868192,0.00064686633,0.0003632535,0.00038819533,0.00019262444],"domain_scores_gemma":[0.9988971,0.00009972682,0.00010907855,0.0005170259,0.0003070383,0.000070053764],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009245563,0.000107616375,0.00026669644,0.000097782424,0.000033705455,0.000008735855,0.00008713035,0.00008661456,0.0015962266],"category_scores_gemma":[0.00021059882,0.00008346765,0.00010954787,0.000093404386,0.000101696154,0.0001617951,0.000079938676,0.00044408307,0.00046294986],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008980069,0.0008953637,0.618285,0.00008499143,0.000023935692,0.000013919679,0.000062578205,0.00023164053,0.28817713,0.000026926182,0.010301421,0.08180729],"study_design_scores_gemma":[0.0015362022,0.000282015,0.9600455,0.000044785524,0.00010959356,0.000018451661,0.000008155316,0.018087542,0.014534692,0.0012120438,0.004019185,0.00010178926],"about_ca_topic_score_codex":0.000019456691,"about_ca_topic_score_gemma":0.0000021442543,"teacher_disagreement_score":0.34176055,"about_ca_system_score_codex":0.00009169733,"about_ca_system_score_gemma":0.00007772499,"threshold_uncertainty_score":0.99931645},"labels":[],"label_agreement":null},{"id":"W2045141677","doi":"10.1097/wno.0b013e3181a58ef8","title":"Combined Functional MRI and Diffusion Tensor Imaging Analysis of Visual Motion Pathways","year":2009,"lang":"en","type":"article","venue":"Journal of Neuro-Ophthalmology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Tractography; Superior colliculus; Thalamus; Neuroscience; Diffusion MRI; Visual cortex; Visual system; White matter; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.05239082641162501,"score_gpt":0.3446779752253634,"score_spread":0.2922871488137384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045141677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983965,0.00007184917,0.012137916,0.0034762213,0.00006662981,0.000108574684,0.0000046019372,0.000039490722,0.00012973484],"genre_scores_gemma":[0.996576,0.000061785904,0.0027794063,0.0004642975,0.000070475486,0.0000015153671,0.0000072010007,0.000016191647,0.000023095183],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99894094,0.000054597134,0.0004837979,0.00017962647,0.00020466036,0.0001363755],"domain_scores_gemma":[0.9989107,0.00014191697,0.00044861156,0.00016243842,0.00023639435,0.00009991757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014227338,0.00011656869,0.0004468465,0.00052601163,0.000057416593,0.000006208843,0.00006346204,0.000045435587,0.00002844085],"category_scores_gemma":[0.00012941103,0.000097119686,0.0001810712,0.00042925318,0.00008292741,0.00008489874,0.00002857335,0.00026098828,7.067607e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007786908,0.0012028784,0.48924342,0.000022759548,0.00017205936,0.0012610266,0.000051285617,0.00027146825,0.4994851,0.00086862367,0.00046976728,0.0061729215],"study_design_scores_gemma":[0.00087814307,0.001372061,0.9757454,0.00002010774,0.00061748823,0.009822995,0.000018134744,0.0074016717,0.0018268797,0.0021122103,0.00011295717,0.00007196914],"about_ca_topic_score_codex":0.0000016073768,"about_ca_topic_score_gemma":2.2299835e-8,"teacher_disagreement_score":0.49765822,"about_ca_system_score_codex":0.000021717566,"about_ca_system_score_gemma":0.000023838646,"threshold_uncertainty_score":0.3960426},"labels":[],"label_agreement":null},{"id":"W2045419273","doi":"10.1016/j.jneumeth.2009.08.022","title":"Visualizing the entire cortical myelination pattern in marmosets with magnetic resonance imaging","year":2009,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Institutes of Health","keywords":"Marmoset; Callithrix; Neuroscience; Visual cortex; Myelin; Cortex (anatomy); Gyrus; Biology; Cerebral cortex; Neuroplasticity; Temporal cortex; Auditory cortex; Primate; Central nervous system","score_opus":0.08844842152530552,"score_gpt":0.47037164696912986,"score_spread":0.38192322544382434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045419273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19253358,0.00083858427,0.7859592,0.019945538,0.0001522479,0.0003046947,8.489494e-7,0.00003444306,0.00023090054],"genre_scores_gemma":[0.85853326,0.00014260782,0.13680993,0.004396511,0.00006328117,0.0000035430428,1.3029256e-7,0.00000867756,0.000042035612],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99881697,0.0001892058,0.00033269142,0.00017257626,0.00030653874,0.00018199599],"domain_scores_gemma":[0.99928343,0.00016180014,0.00018622319,0.00019544708,0.00010304781,0.000070069385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009437173,0.00008726222,0.00016402116,0.0001211292,0.0000969348,0.000036004945,0.00019974392,0.000014200682,0.000004120341],"category_scores_gemma":[0.0004240655,0.00005262208,0.00004431403,0.0004940739,0.00014010748,0.00016495127,0.00002376088,0.0004231575,3.020979e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045111377,0.00012656453,0.01618942,0.000004412463,1.934342e-7,0.00017487654,0.000094733165,0.000017617227,0.2572266,0.0001579632,0.00009544458,0.7258671],"study_design_scores_gemma":[0.0005416446,0.00075213215,0.9577121,0.00017742316,0.00002439903,0.0020692747,0.000053400934,0.016188115,0.009004733,0.0013628078,0.012022036,0.0000919],"about_ca_topic_score_codex":0.0000014885497,"about_ca_topic_score_gemma":2.6670423e-7,"teacher_disagreement_score":0.9415227,"about_ca_system_score_codex":0.00003514473,"about_ca_system_score_gemma":0.000050953156,"threshold_uncertainty_score":0.21458662},"labels":[],"label_agreement":null},{"id":"W2045560368","doi":"10.1002/mrm.20777","title":"Diffusion tensor spectroscopy (DTS) of human brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Metabolite; Phosphocreatine; Chemistry; Nuclear magnetic resonance; Creatine; Effective diffusion coefficient; Human brain; Magnetic resonance imaging; Physics; Biology; Neuroscience; Medicine; Biochemistry; Endocrinology","score_opus":0.04192396674393264,"score_gpt":0.3738882482614556,"score_spread":0.331964281517523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045560368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9282794,0.0059836064,0.0011670333,0.05021873,0.00003450659,0.0008090277,0.000004320838,0.00013873698,0.013364616],"genre_scores_gemma":[0.96204865,0.0009405482,0.029007234,0.0030271232,0.00035705435,0.00007794265,0.0000139839185,0.000035634537,0.00449183],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986972,0.000023672319,0.0004554009,0.0003038551,0.00028147167,0.00023836807],"domain_scores_gemma":[0.9991836,0.00009025693,0.000092720875,0.00049754156,0.000053685457,0.000082186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019595552,0.00014375469,0.00039008472,0.00016873129,0.000038488226,0.00000192044,0.00014164242,0.000053136344,0.00048953306],"category_scores_gemma":[0.00018619813,0.000113963695,0.000038111215,0.00037010072,0.000294329,0.000031176638,0.000041397656,0.00024910847,0.000010192158],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101794125,0.00035654937,0.06704184,0.00008192395,0.0000015277527,0.000039717244,0.000300902,0.0000027853082,0.7821977,0.0031021582,0.020936245,0.12583682],"study_design_scores_gemma":[0.0036371988,0.0019745075,0.6439797,0.0009602106,0.000032804004,0.0000804765,0.00008591303,0.001061805,0.020530919,0.003792912,0.32367107,0.00019246861],"about_ca_topic_score_codex":0.00006818231,"about_ca_topic_score_gemma":0.00001924086,"teacher_disagreement_score":0.76166683,"about_ca_system_score_codex":0.000051284118,"about_ca_system_score_gemma":0.000018468061,"threshold_uncertainty_score":0.53600436},"labels":[],"label_agreement":null},{"id":"W2045674645","doi":"10.1016/j.neuroimage.2010.11.089","title":"Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":240,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Institut pour la Recherche sur la Moelle épinière et l'Encéphale","keywords":"Fractional anisotropy; Magnetization transfer; Diffusion MRI; White matter; Spinal cord; Magnetic resonance imaging; Atrophy; Spinal cord injury; Medicine; Nuclear magnetic resonance; Nuclear medicine; Pathology; Radiology; Physics","score_opus":0.07255519224948061,"score_gpt":0.3258924484806467,"score_spread":0.2533372562311661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2045674645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9695146,0.00003433113,0.028734157,0.0006908579,0.0000058114715,0.0005743042,0.000002044516,0.000073147516,0.000370764],"genre_scores_gemma":[0.99367726,0.00009547075,0.005692978,0.00039803502,0.000021080616,0.000056237728,0.000017812934,0.00001562287,0.000025498168],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994057,0.000043376083,0.00013021125,0.00022466361,0.0001043866,0.000091669695],"domain_scores_gemma":[0.9997366,0.0000121775465,0.000025178044,0.00015432984,0.00004050923,0.000031227046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000723744,0.000093467635,0.00008390444,0.00008083817,0.00011073669,0.000018483634,0.000040502036,0.00003181916,0.0000070471497],"category_scores_gemma":[0.000012261337,0.000066034365,0.000009383675,0.00017234929,0.00007591671,0.000097177,0.000012363952,0.00014073838,4.6008626e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006993631,0.00021605435,0.037519593,0.00005804285,0.0000022476156,0.000038238006,0.0006074748,7.6766e-7,0.90998036,0.0039253053,0.000053225285,0.04689935],"study_design_scores_gemma":[0.0008642306,0.00165533,0.9733878,0.000033416083,0.000038688133,0.0001262262,0.000033980083,0.0006236252,0.02211026,0.00073314033,0.00030071544,0.000092632086],"about_ca_topic_score_codex":0.000017466695,"about_ca_topic_score_gemma":0.000038197115,"teacher_disagreement_score":0.93586814,"about_ca_system_score_codex":0.0000071882637,"about_ca_system_score_gemma":0.000006773732,"threshold_uncertainty_score":0.2692803},"labels":[],"label_agreement":null},{"id":"W2046091688","doi":"10.1159/000356219","title":"Improved Frontoparietal White Matter Integrity in Overweight Children Is Associated with Attendance at an After-School Exercise Program","year":2014,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Population and Public Health","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; National Science Foundation","keywords":"Overweight; Attendance; Aerobic exercise; Medicine; Physical therapy; Intervention (counseling); Cardiovascular fitness; Psychology; Obesity; Physical fitness; Psychiatry; Internal medicine","score_opus":0.01956911779889504,"score_gpt":0.29149615676303087,"score_spread":0.27192703896413584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046091688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996428,0.00000734508,0.0012778253,0.0005945827,0.00003607986,0.0010162914,0.000023677298,0.00023536474,0.0003808112],"genre_scores_gemma":[0.97023183,0.000008000631,0.024449188,0.004048425,0.0000137254765,0.00039409776,0.00003598382,0.000030247775,0.00078850053],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99828476,0.000027844488,0.00025378092,0.00074170675,0.00028446448,0.00040743573],"domain_scores_gemma":[0.99928325,0.000011037171,0.0001022165,0.00032887576,0.000043920165,0.0002306868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012510589,0.00022919527,0.00024939148,0.00008204622,0.00014232064,0.00005504368,0.00024535554,0.00005698489,0.00007699288],"category_scores_gemma":[0.000044421664,0.00018864442,0.000034479242,0.000442893,0.00023667728,0.00033662727,0.0001695484,0.00035442636,0.000023515002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008945776,0.000374055,0.9876151,0.0000067291485,0.0000012717397,0.00001376665,0.000103135884,4.904957e-7,0.009143056,0.0000032830014,0.0003192443,0.0023304236],"study_design_scores_gemma":[0.00058650365,0.00023292155,0.98992664,0.000106073625,0.0000098850805,0.000111840935,0.000007495635,0.0012974895,0.006760547,0.0000310374,0.00069054816,0.00023900268],"about_ca_topic_score_codex":0.000024313435,"about_ca_topic_score_gemma":0.00005192267,"teacher_disagreement_score":0.026196191,"about_ca_system_score_codex":0.00019996635,"about_ca_system_score_gemma":0.000076320124,"threshold_uncertainty_score":0.76926965},"labels":[],"label_agreement":null},{"id":"W2046264394","doi":"10.1016/j.neuroimage.2008.12.046","title":"The effect of template choice on morphometric analysis of pediatric brain data","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":148,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Brain morphometry; Brain size; Normalization (sociology); Spatial normalization; Human brain; Medicine; Biomedical engineering; Nuclear medicine; Neuroscience; Biology; Radiology; Magnetic resonance imaging","score_opus":0.0847654776393003,"score_gpt":0.4045926656445653,"score_spread":0.319827188005265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046264394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99202204,0.00022463771,0.0020703888,0.00318429,0.000029382676,0.00056477636,0.00012379797,0.00011782761,0.0016628643],"genre_scores_gemma":[0.9983804,0.00021746769,0.00069044466,0.00041923844,0.000054368906,0.0000066949797,0.00005693085,0.000013423311,0.00016101306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989142,0.00006516728,0.00028871288,0.0003215513,0.00025917217,0.00015120892],"domain_scores_gemma":[0.9966474,0.0014588499,0.0002039228,0.0015927305,0.000044172302,0.00005288484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030258234,0.000117274474,0.0003371103,0.0005161166,0.000065196145,0.000008254252,0.00041557345,0.00002719347,0.0000088882325],"category_scores_gemma":[0.0011211277,0.00007738281,0.000121396304,0.0033307802,0.00005443702,0.000054151606,0.00007836122,0.0001934419,0.0000035826406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009981873,0.0010686727,0.46711287,0.00028334107,0.00064119004,0.000115598414,0.000040323328,0.0005447081,0.26865223,0.001112465,0.09096438,0.16846602],"study_design_scores_gemma":[0.000699775,0.0017305271,0.96338135,0.000010523421,0.0017717265,0.000007999119,0.0000010092153,0.0033836525,0.01856173,0.000058833626,0.010287764,0.000105115796],"about_ca_topic_score_codex":0.000011062135,"about_ca_topic_score_gemma":7.054726e-7,"teacher_disagreement_score":0.49626845,"about_ca_system_score_codex":0.0000087468325,"about_ca_system_score_gemma":0.000012256787,"threshold_uncertainty_score":0.31555793},"labels":[],"label_agreement":null},{"id":"W2046933782","doi":"10.1016/j.neuroimage.2013.06.030","title":"Collaborative patch-based super-resolution for diffusion-weighted images","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministerio de Ciencia e Innovación; CHIST-ERA; Agence Nationale de la Recherche","keywords":"Diffusion MRI; Image resolution; Fractional anisotropy; Computer vision; Computer science; Angular resolution (graph drawing); Artificial intelligence; Interpolation (computer graphics); Anisotropic diffusion; Resolution (logic); Diffusion; Image (mathematics); Superresolution; Anisotropy; Tracking (education); Mathematics; Physics; Optics; Magnetic resonance imaging","score_opus":0.032529069693619024,"score_gpt":0.32801279861863425,"score_spread":0.29548372892501523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046933782","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5218151,0.00019031148,0.4146818,0.04646272,0.0002143021,0.0084833475,0.00042146922,0.0018605106,0.005870406],"genre_scores_gemma":[0.8641477,0.00005231545,0.12752225,0.0046139844,0.00015527013,0.0016139516,0.00019730855,0.000086556895,0.0016106485],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99885845,0.00003170334,0.00023164961,0.00042031624,0.00016913841,0.00028873407],"domain_scores_gemma":[0.9987556,0.0001643605,0.00007983595,0.00047973005,0.00038339084,0.0001371299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004790539,0.00018692235,0.00022760371,0.000099280165,0.00018449224,0.000043841057,0.00011261644,0.000056942066,0.00014440996],"category_scores_gemma":[0.0001359206,0.00016188844,0.000098070865,0.0003274231,0.0001282559,0.00015963065,0.000039000526,0.00017177589,0.000069792164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016648606,0.0005677794,0.0036383527,0.0000992181,0.000011110323,0.000020525635,0.000048036123,0.00000779542,0.8631154,0.0010693872,0.12009014,0.011165801],"study_design_scores_gemma":[0.008000885,0.0018241379,0.13149585,0.00018321256,0.0002356063,0.00007022752,0.00012615559,0.07997911,0.3993604,0.010721617,0.36701456,0.0009882533],"about_ca_topic_score_codex":0.000035554713,"about_ca_topic_score_gemma":0.0000013158188,"teacher_disagreement_score":0.46375498,"about_ca_system_score_codex":0.000037745096,"about_ca_system_score_gemma":0.00006844674,"threshold_uncertainty_score":0.6601619},"labels":[],"label_agreement":null},{"id":"W2047361139","doi":"10.1016/s0006-8993(02)04160-4","title":"Topographical anatomy of the cerebellum in the guinea pig, Cavia porcellus","year":2003,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Cavia; Guinea pig; Anatomy; Cerebellum; New guinea; Biology; Neuroscience; History","score_opus":0.16978598072589077,"score_gpt":0.48733316726173453,"score_spread":0.3175471865358438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047361139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77791953,0.00041475217,0.0011455509,0.14505695,0.000039706352,0.0024681115,0.000009516316,0.00007031052,0.0728756],"genre_scores_gemma":[0.99651957,0.000039838746,0.001015658,0.0008897034,0.000023950406,0.000083659295,0.0000018767154,0.000011730351,0.0014140093],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985406,0.0003453978,0.00016975887,0.00018834656,0.00049012236,0.00026581498],"domain_scores_gemma":[0.9986301,0.00046354136,0.000026753429,0.0007291168,0.00010458263,0.000045907345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013929737,0.000062621744,0.00010710823,0.00013077859,0.00011401597,0.00000947055,0.0003373962,0.000046714642,0.000055501663],"category_scores_gemma":[0.00071577,0.00003476259,0.00006634308,0.0013386431,0.00038175634,0.000016709073,0.00007099418,0.0006260792,0.0000049346563],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009545114,0.0011759168,0.16296388,0.00016784207,0.000023311904,0.00012031483,0.0011404001,0.0000097786615,0.060226787,0.62545526,0.13887073,0.009750352],"study_design_scores_gemma":[0.0011308711,0.00024355481,0.16056366,0.000116028656,0.000011070121,0.00016153482,0.0007905057,0.000244418,0.021349993,0.052534025,0.76271456,0.00013975344],"about_ca_topic_score_codex":0.00008521898,"about_ca_topic_score_gemma":0.000020763297,"teacher_disagreement_score":0.62384385,"about_ca_system_score_codex":0.000022221873,"about_ca_system_score_gemma":0.00008468952,"threshold_uncertainty_score":0.27200374},"labels":[],"label_agreement":null},{"id":"W2047768580","doi":"10.1503/jpn.100082","title":"White matter microstructure in patients with obsessive–compulsive disorder","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; White matter; Obsessive compulsive; Psychology; Internal medicine; Medicine; Cardiology; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.008944740036156664,"score_gpt":0.2848020489133342,"score_spread":0.2758573088771776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047768580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941504,0.000020598914,0.0008818223,0.0044687698,0.0003017396,0.000110254805,0.0000032834125,0.0000055558994,0.000057595047],"genre_scores_gemma":[0.98260796,0.000013624443,0.01527502,0.002008107,0.00004823878,0.0000011212677,4.0073442e-7,0.000007292478,0.000038226462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994562,0.000007623191,0.00016454389,0.0001382065,0.00012861607,0.0001048131],"domain_scores_gemma":[0.9995652,0.000008444664,0.00016279801,0.00012366341,0.00006444636,0.000075452044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038482485,0.00007474199,0.000118485594,0.00008247213,0.000058550035,0.00001818153,0.00009455573,0.000023941853,0.000010180162],"category_scores_gemma":[0.000012915826,0.00004874008,0.000023220866,0.0001952081,0.00013253276,0.00014950737,0.000020996622,0.00040942483,4.3395943e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006570002,0.00011496029,0.9965251,0.000009023606,4.9550886e-7,0.0000040127698,0.000018139486,0.0000061971127,0.0027475718,0.00008240869,0.00020543876,0.00022092584],"study_design_scores_gemma":[0.0007552313,0.00028004576,0.99691135,0.00004137867,0.000009050878,0.00021594283,0.000010273304,0.000014328075,0.00008924248,0.00052463374,0.0010952346,0.000053277585],"about_ca_topic_score_codex":6.2078425e-7,"about_ca_topic_score_gemma":0.0000031983782,"teacher_disagreement_score":0.014393197,"about_ca_system_score_codex":0.0000030593997,"about_ca_system_score_gemma":0.000041800275,"threshold_uncertainty_score":0.19875628},"labels":[],"label_agreement":null},{"id":"W2047853664","doi":"10.1002/mrm.10708","title":"Quantitative diffusion imaging with steady‐state free precession","year":2004,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Steady-state free precession imaging; Nuclear magnetic resonance; Effective diffusion coefficient; Diffusion MRI; Diffusion; Precession; SIGNAL (programming language); Echo-planar imaging; Relaxation (psychology); Diffusion imaging; Spin echo; Flip angle; Physics; Magnetic resonance imaging; Computer science; Condensed matter physics; Radiology","score_opus":0.037498526013615294,"score_gpt":0.35814868133528527,"score_spread":0.32065015532166996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047853664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8935974,0.016338374,0.036086876,0.042236842,0.000090832684,0.0017346271,0.000010536166,0.0003890304,0.009515452],"genre_scores_gemma":[0.8901281,0.0029990107,0.10289393,0.0021266793,0.00009967885,0.00024036637,0.000021009746,0.00007077976,0.0014204554],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99850345,0.000026692805,0.00034227857,0.0004392118,0.00038421236,0.0003041494],"domain_scores_gemma":[0.99900925,0.000087333334,0.000096323536,0.000603055,0.000089827336,0.00011422695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017580592,0.00020085122,0.00034303952,0.00017908332,0.00007190832,0.000007019131,0.0001871588,0.000030367139,0.00006421003],"category_scores_gemma":[0.00019517573,0.0001359828,0.000023285635,0.00055977196,0.00036206326,0.000086923224,0.00007338104,0.0003340077,0.000008525428],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025250977,0.001116828,0.18365498,0.00037573013,0.000008550611,0.001544652,0.0050273193,0.00027490393,0.11205866,0.010807294,0.0048792604,0.6777267],"study_design_scores_gemma":[0.024460139,0.0068843765,0.7927773,0.013475547,0.00011232708,0.00068147475,0.0015408756,0.0039160317,0.006027819,0.078132376,0.07119255,0.0007991802],"about_ca_topic_score_codex":0.00023474361,"about_ca_topic_score_gemma":0.000053595224,"teacher_disagreement_score":0.6769275,"about_ca_system_score_codex":0.000094067866,"about_ca_system_score_gemma":0.000057011493,"threshold_uncertainty_score":0.5545218},"labels":[],"label_agreement":null},{"id":"W2048126458","doi":"10.1002/nbm.1581","title":"The influence of white matter fibre orientation on MR signal phase and decay","year":2010,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":138,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Parkinson Canada; Universidad de Guanajuato; Parkinson Society Canada; Michael Smith Health Research BC","keywords":"White matter; Diffusion MRI; Nuclear magnetic resonance; Phase (matter); Orientation (vector space); SIGNAL (programming language); Spin echo; Diffusion; Physics; Magnetic resonance imaging; Contrast (vision); Echo (communications protocol); Materials science; Chemistry; Optics; Medicine; Mathematics; Geometry; Radiology; Computer science","score_opus":0.021627259033592475,"score_gpt":0.3680753547450776,"score_spread":0.3464480957114851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048126458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896274,0.000022792614,0.00050335727,0.009110004,0.000023071156,0.0002695082,0.000008099505,0.000024371755,0.00041135505],"genre_scores_gemma":[0.99691904,0.000043634907,0.0016984806,0.0010842896,0.00005369361,0.000030311821,0.0000145088425,0.000008437067,0.00014761464],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994284,0.000007896626,0.0001882577,0.00014408535,0.00013140342,0.00009994513],"domain_scores_gemma":[0.99949926,0.0000927858,0.000067157845,0.00022885478,0.000050411138,0.000061517254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001265048,0.000068717825,0.000107697866,0.000088552835,0.000064667714,0.0000031032325,0.000058229496,0.00003347276,0.000048278594],"category_scores_gemma":[0.00003553509,0.000042761203,0.000012092579,0.000227783,0.00025222485,0.000033986376,0.000025651756,0.00018692657,0.0000041236053],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022377058,0.00020333855,0.105704814,0.000054316108,0.000005436889,0.0000112353555,0.00032996334,0.00000697531,0.8716356,0.0013554108,0.0022185142,0.018250607],"study_design_scores_gemma":[0.00542797,0.0014530903,0.8065564,0.00040990688,0.00005253864,0.00014220359,0.00014228943,0.0005233197,0.10936069,0.0025552923,0.073189326,0.00018697772],"about_ca_topic_score_codex":0.000010043796,"about_ca_topic_score_gemma":0.0000037290206,"teacher_disagreement_score":0.7622749,"about_ca_system_score_codex":0.000008778229,"about_ca_system_score_gemma":0.00001812714,"threshold_uncertainty_score":0.17437513},"labels":[],"label_agreement":null},{"id":"W2048918010","doi":"10.1016/j.neuroimage.2011.03.065","title":"Cerebello–thalamo–cerebral connections in pediatric brain tumor patients: Impact on working memory","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; British Columbia Children's Hospital; University of Toronto; Princess Margaret Cancer Centre; Hospital for Sick Children","funders":"C17 Council","keywords":"Working memory; White matter; Diffusion MRI; Fractional anisotropy; Medicine; Psychology; Brain tumor; Cerebellar Degeneration; Neuroscience; Cerebellum; Cognition; Magnetic resonance imaging; Radiology; Pathology","score_opus":0.06917056003496626,"score_gpt":0.3261621009068251,"score_spread":0.2569915408718589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048918010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97871435,0.000018826167,0.00044226955,0.0007745119,0.00011982961,0.000755026,0.000015348623,0.0003814084,0.01877845],"genre_scores_gemma":[0.9953382,0.00001728488,0.0020597677,0.0020732982,0.00013320295,0.00007828936,0.00001863721,0.00006637977,0.00021494363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985935,0.00004759196,0.0003069973,0.0004923593,0.00019029378,0.00036923276],"domain_scores_gemma":[0.9990092,0.00011351549,0.00012156611,0.0005484259,0.00005243463,0.00015487979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008980468,0.0002352357,0.00025290772,0.00032658115,0.00009658284,0.000016239655,0.0001532571,0.00004768891,0.0001592467],"category_scores_gemma":[0.00018728116,0.00020906578,0.00013706308,0.00058174867,0.000061698105,0.000121297904,0.00006833775,0.0005223501,0.00008028446],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028727038,0.0019880969,0.9856828,0.000060773596,0.000010852003,0.00028611437,0.00036703792,0.000038374077,0.0016724408,0.0016364448,0.0044500227,0.0035197677],"study_design_scores_gemma":[0.0016498977,0.00067829806,0.99268746,0.000055403863,0.000037163176,0.00005765841,0.000019326648,0.0001000516,0.0026191866,0.00112267,0.0007468844,0.00022601018],"about_ca_topic_score_codex":0.00008116241,"about_ca_topic_score_gemma":0.000008114776,"teacher_disagreement_score":0.018563507,"about_ca_system_score_codex":0.00012514023,"about_ca_system_score_gemma":0.00006775637,"threshold_uncertainty_score":0.8525455},"labels":[],"label_agreement":null},{"id":"W2049221173","doi":"10.1523/jneurosci.2650-08.2008","title":"Practice Makes Cortex: Figure 1.","year":2008,"lang":"en","type":"review","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Neuroscience; White matter; Magnetic resonance imaging; Gray (unit); Psychology; Variety (cybernetics); Neuroimaging; Cortex (anatomy); Brain morphometry; Computer science; Cognitive science; Artificial intelligence; Medicine; Nuclear medicine; Radiology","score_opus":0.19392571049719864,"score_gpt":0.4707699922771978,"score_spread":0.27684428177999915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049221173","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000023590128,0.9952851,0.0018506019,0.00094722747,0.00027520166,0.00032372595,0.000006191065,0.000038684,0.0012709331],"genre_scores_gemma":[0.0000070880237,0.98898923,0.008619682,0.0014071055,0.00022901066,0.0000074430372,9.670106e-7,0.000030135592,0.00070934073],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99835765,0.0000614522,0.00066043524,0.00025557092,0.00048205745,0.00018285672],"domain_scores_gemma":[0.9976186,0.0002472654,0.0013342951,0.00038215544,0.00024462817,0.00017302984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014093918,0.00020528708,0.00089409313,0.00021669168,0.00010438331,0.000026321437,0.00040250193,0.00007861635,0.0000051883876],"category_scores_gemma":[0.0012764906,0.00014125142,0.00039833467,0.0006046848,0.00018009602,0.00023960014,0.000058062244,0.0009297861,0.000011454986],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014617281,0.00029471098,0.000004353358,0.0013132395,0.000010044947,0.0026805343,0.000013613782,9.295687e-7,0.00026405256,0.00020578869,0.020216634,0.9749815],"study_design_scores_gemma":[0.00007411789,0.00026848388,0.000045853947,0.0027160028,0.00024884465,0.06303054,0.0000021574683,0.000004410502,0.0000033549438,0.000024345187,0.9334867,0.00009516606],"about_ca_topic_score_codex":3.1398005e-7,"about_ca_topic_score_gemma":1.1667285e-8,"teacher_disagreement_score":0.9748863,"about_ca_system_score_codex":0.000058019126,"about_ca_system_score_gemma":0.00052489503,"threshold_uncertainty_score":0.5760066},"labels":[],"label_agreement":null},{"id":"W2049366374","doi":"10.1117/12.2043591","title":"A new method for joint susceptibility artefact correction and super-resolution for dMRI","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Image resolution; Computer science; Diffusion MRI; Distortion (music); Resolution (logic); Artificial intelligence; Nuclear magnetic resonance; Magnetic resonance imaging; Computer vision; Physics; Pattern recognition (psychology); Telecommunications","score_opus":0.030748187588681305,"score_gpt":0.3079255326921042,"score_spread":0.2771773451034229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049366374","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8280941,0.000029114186,0.16209136,0.0074033393,0.00016136398,0.0017007486,0.000040075418,0.00014728116,0.00033261173],"genre_scores_gemma":[0.10370095,0.000043492746,0.8947194,0.00018773587,0.00047494727,0.0004559569,0.000018412724,0.000053851345,0.0003452289],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985184,1.6585702e-8,0.0004984211,0.00042563654,0.00027588586,0.00028164752],"domain_scores_gemma":[0.998066,0.00026043365,0.0002455056,0.00006800317,0.0012203215,0.00013971416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000695604,0.00022619225,0.00039217254,0.00007392352,0.00010290225,0.00004666201,0.00022093207,0.00013805412,0.0000036397553],"category_scores_gemma":[0.0011723128,0.0001915688,0.0004917438,0.00015445398,0.0001058005,0.00023712176,0.000068197856,0.00019942375,2.1917712e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022623078,0.000094145646,0.0002430899,0.00054529484,0.00011341391,6.1200085e-9,0.00007467845,0.00003373956,0.6641632,0.31777737,0.011464105,0.0052647227],"study_design_scores_gemma":[0.003286992,0.0018245112,0.0026841948,0.0004530591,0.00050722604,0.000056523175,0.0005047001,0.53837794,0.3923005,0.023968682,0.035583775,0.0004519051],"about_ca_topic_score_codex":0.00001339808,"about_ca_topic_score_gemma":2.6100162e-7,"teacher_disagreement_score":0.73262805,"about_ca_system_score_codex":0.00012436067,"about_ca_system_score_gemma":0.000031681488,"threshold_uncertainty_score":0.7811949},"labels":[],"label_agreement":null},{"id":"W2049696735","doi":"10.1097/rli.0b013e31817e909f","title":"Diffusion Tensor Magnetic Resonance Imaging of the Human Calf","year":2008,"lang":"en","type":"article","venue":"Investigative Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Nuclear magnetic resonance; Anisotropy; Physics; Nuclear medicine; Medicine; Optics; Radiology","score_opus":0.07464072198649016,"score_gpt":0.3268939290368986,"score_spread":0.25225320705040843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049696735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99134153,0.0010105687,0.0003518961,0.0053497963,0.00002977997,0.0003440047,0.00000878979,0.000079045654,0.0014845687],"genre_scores_gemma":[0.990878,0.000073953095,0.00652314,0.0017126899,0.00005194982,0.00004374081,0.000004168062,0.000015099764,0.0006972654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992835,0.00006844732,0.00019920063,0.00021448222,0.00008368487,0.00015070084],"domain_scores_gemma":[0.99932843,0.00006567801,0.00009567734,0.0003799814,0.00007042652,0.000059781414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046012978,0.00009778072,0.000205113,0.0000405854,0.00016939174,8.766193e-7,0.00013856089,0.00003498561,0.000019908015],"category_scores_gemma":[0.00015967875,0.00006613417,0.000058756457,0.00018556569,0.0020134524,0.00002195256,0.0000680527,0.00021041208,0.0000035010462],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070915976,0.000044335073,0.5950779,0.000009855069,0.0000020927757,0.00002064045,0.00025038508,0.0000017246117,0.39110288,0.008467884,0.0038858848,0.001129338],"study_design_scores_gemma":[0.00038746215,0.00009863343,0.93112713,0.00005720557,0.000016045815,0.00066648313,0.000016669792,0.00017760666,0.04101695,0.013054802,0.01330592,0.00007508319],"about_ca_topic_score_codex":0.000031560863,"about_ca_topic_score_gemma":0.0000011394061,"teacher_disagreement_score":0.3500859,"about_ca_system_score_codex":0.000028533696,"about_ca_system_score_gemma":0.000044274744,"threshold_uncertainty_score":0.74186486},"labels":[],"label_agreement":null},{"id":"W2049756811","doi":"10.1016/j.neuroimage.2008.04.243","title":"Detection of multiple pathways in the spinal cord using q-ball imaging","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Fondation pour la Recherche Médicale; Canada Research Chairs; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Spinal cord; Diffusion MRI; White matter; Magnetic resonance imaging; Neuroscience; Anatomy; Diffusion imaging; Medicine; Biology; Radiology","score_opus":0.14833073701900817,"score_gpt":0.360337032967762,"score_spread":0.2120062959487538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049756811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9712117,0.00007100681,0.027383411,0.00032392133,0.000030785195,0.00035593894,0.0000038191815,0.000089217596,0.00053023535],"genre_scores_gemma":[0.99404967,0.000040416544,0.005227576,0.0005927605,0.00004320782,0.000017859233,0.0000017606963,0.000018764198,0.000007970015],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992455,0.000035653084,0.0002043933,0.00020629288,0.00015559288,0.00015255176],"domain_scores_gemma":[0.99944925,0.000041015646,0.00008264685,0.00035417915,0.000044451263,0.000028446524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008801274,0.0000932861,0.00013434909,0.00009148568,0.00009201187,0.0000049303285,0.00010967441,0.000017774359,0.0000025725672],"category_scores_gemma":[0.00009236296,0.00007508346,0.00005873548,0.00028359765,0.00011456813,0.000076796714,0.000032663218,0.00023273444,0.0000025639347],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014016283,0.0001306297,0.025340999,0.000024652141,0.0000010884099,0.0001809166,0.00006875676,0.000012396313,0.96383065,0.000064650696,0.00003415023,0.010170956],"study_design_scores_gemma":[0.0014806531,0.00065526296,0.74466527,0.0001324843,0.000042680553,0.0034654608,0.00012287837,0.02405318,0.21993199,0.0006138461,0.004609518,0.00022676226],"about_ca_topic_score_codex":0.000055796012,"about_ca_topic_score_gemma":0.0000029496127,"teacher_disagreement_score":0.74389863,"about_ca_system_score_codex":0.00002247971,"about_ca_system_score_gemma":0.000023904626,"threshold_uncertainty_score":0.30618146},"labels":[],"label_agreement":null},{"id":"W2049895116","doi":"10.1523/jneurosci.2388-08.2008","title":"Dissociating the Human Language Pathways with High Angular Resolution Diffusion Fiber Tractography","year":2008,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":447,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Tractography; Macaque; Neuroscience; Angular gyrus; Superior temporal sulcus; Anatomy; Human brain; Psychology; Superior longitudinal fasciculus; Planum temporale; Fasciculus; Superior temporal gyrus; Primate; Diffusion MRI; Biology; Perception; Functional magnetic resonance imaging; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.05336429195147954,"score_gpt":0.3222376690851621,"score_spread":0.26887337713368253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049895116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99534297,0.000044050103,0.0029636207,0.0012874728,0.000029860214,0.00010880459,0.0000020610325,0.00003176499,0.00018940718],"genre_scores_gemma":[0.9959311,0.00005360805,0.0032116899,0.00057951687,0.00008100515,0.0000026568325,5.203007e-7,0.000009073093,0.000130862],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992107,0.000025794612,0.00018176473,0.000115103496,0.00033885884,0.00012779066],"domain_scores_gemma":[0.99937844,0.000039495277,0.00026693215,0.0001811703,0.00007155426,0.00006241593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013178596,0.000067530964,0.00011156842,0.0000691996,0.00038670909,0.000013153707,0.00015002435,0.000016622565,0.0000037454092],"category_scores_gemma":[0.000075821874,0.000037226735,0.000063705455,0.00035546458,0.00018669218,0.00012238599,0.000024683182,0.0002733682,4.7503121e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017892531,0.00014270193,0.010220096,0.000004534302,0.0000014223625,0.00023142107,0.00044798283,0.000030942265,0.98741347,0.00022898258,0.0003423765,0.00091817294],"study_design_scores_gemma":[0.00050265423,0.00071892084,0.976414,0.00009135284,0.000035661822,0.0026768171,0.00012180699,0.0002198952,0.013841342,0.00028636883,0.004995181,0.00009596654],"about_ca_topic_score_codex":0.0000071419668,"about_ca_topic_score_gemma":4.853514e-7,"teacher_disagreement_score":0.97357213,"about_ca_system_score_codex":0.000017813312,"about_ca_system_score_gemma":0.000026536472,"threshold_uncertainty_score":0.29742926},"labels":[],"label_agreement":null},{"id":"W2050722132","doi":"10.1002/mrm.10411","title":"Is multicomponent <i>T</i><sub>2</sub> a good measure of myelin content in peripheral nerve?","year":2003,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"College of Science and Health","keywords":"Myelin; Wallerian degeneration; Remyelination; Sciatic nerve; Myelin sheath; Relaxation (psychology); Chemistry; Peripheral nerve; Pathology; Neuroscience; Nuclear magnetic resonance; Anatomy; Biology; Medicine; Central nervous system; Physics","score_opus":0.08002056620811958,"score_gpt":0.3213260548635613,"score_spread":0.2413054886554417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050722132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9734742,0.01507031,0.0008635258,0.0072053736,0.00007331197,0.0011193894,0.0000068511126,0.000059007092,0.0021280048],"genre_scores_gemma":[0.9901925,0.0014983831,0.0062065846,0.0015863426,0.00004888265,0.00019328714,0.0000057369425,0.00003344272,0.00023486014],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.997964,0.00008901078,0.00073383964,0.0004354321,0.00042706478,0.00035061096],"domain_scores_gemma":[0.99900025,0.00009759348,0.00012405102,0.0005420461,0.000118009644,0.00011802514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043978912,0.00022452786,0.00060541346,0.00018152515,0.000024665682,0.0000030212298,0.00014189487,0.00008650803,0.000098493256],"category_scores_gemma":[0.00035070258,0.00018554211,0.000068002,0.00051151396,0.00027211697,0.000030692292,0.000029224128,0.00039703515,0.0000044450503],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031626318,0.0008617208,0.16427037,0.0002198561,0.0000062727627,0.0002377885,0.0010668591,0.000022210636,0.710998,0.0021207468,0.0020438922,0.11783604],"study_design_scores_gemma":[0.015185719,0.0020441564,0.707694,0.003788695,0.000086876236,0.00027642996,0.000674812,0.0026699423,0.15883158,0.0021820297,0.10603107,0.0005347296],"about_ca_topic_score_codex":0.00019923091,"about_ca_topic_score_gemma":0.000044663233,"teacher_disagreement_score":0.5521664,"about_ca_system_score_codex":0.00010121806,"about_ca_system_score_gemma":0.000059418566,"threshold_uncertainty_score":0.75661874},"labels":[],"label_agreement":null},{"id":"W2051116857","doi":"10.1016/j.jpeds.2009.12.030","title":"Tractography-Based Quantitation of Corticospinal Tract Development in Premature Newborns","year":2010,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Corticospinal tract; Tractography; Diffusion MRI; Physical medicine and rehabilitation; Radiology; Magnetic resonance imaging","score_opus":0.044990503329603165,"score_gpt":0.35032872804986065,"score_spread":0.3053382247202575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051116857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743204,0.00013994648,0.024257055,0.0009944998,0.000060157843,0.00015940027,0.00000168269,0.000009873761,0.000056996443],"genre_scores_gemma":[0.93058705,0.00011230121,0.069117375,0.00007988789,0.00008739249,0.0000016728906,0.0000014853449,0.000007981456,0.0000048531974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99922615,0.000017858476,0.00040146353,0.000045994457,0.00022461415,0.00008388944],"domain_scores_gemma":[0.99906725,0.00014263285,0.00042462145,0.00013238116,0.0001858657,0.000047272115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003932948,0.000062585576,0.00014494338,0.00019550657,0.00002601092,0.0000037101333,0.000109858105,0.000044505105,0.000006536795],"category_scores_gemma":[0.0001488686,0.000040967716,0.00005557717,0.00036152147,0.000034767807,0.00005332498,0.000006364148,0.0005156804,5.2703865e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001450902,0.0039026684,0.53628224,0.0008242038,0.00002095288,0.000093528564,0.002045891,0.0010726129,0.41466326,0.0022292973,0.0017257553,0.035688676],"study_design_scores_gemma":[0.00085834984,0.0003467022,0.9843208,0.00004798566,0.00016204506,0.00015960989,0.000068553374,0.00013005729,0.010753721,0.00065567327,0.0024195444,0.00007694552],"about_ca_topic_score_codex":0.0000026808227,"about_ca_topic_score_gemma":0.0000054636985,"teacher_disagreement_score":0.44803855,"about_ca_system_score_codex":0.000012291098,"about_ca_system_score_gemma":0.00019594059,"threshold_uncertainty_score":0.22404033},"labels":[],"label_agreement":null},{"id":"W2051523173","doi":"10.1016/j.pscychresns.2011.11.002","title":"Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits","year":2012,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; White matter; Psychology; Diffusion MRI; Psychopathy; Amygdala; Uncinate fasciculus; Orbitofrontal cortex; Conduct disorder; Neuroimaging; Neuroscience; Functional magnetic resonance imaging; Prefrontal cortex; Developmental psychology; Magnetic resonance imaging; Medicine; Personality; Cognition; Psychoanalysis","score_opus":0.192752080837448,"score_gpt":0.4060632442863208,"score_spread":0.2133111634488728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051523173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98110855,0.0004284578,0.0014560015,0.014395664,0.00018314087,0.0016057083,0.00009532432,0.00014851244,0.0005786559],"genre_scores_gemma":[0.9943631,0.000033233773,0.003670953,0.0009018178,0.00024294689,0.00033943198,0.00011071828,0.00010200205,0.0002357651],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961933,0.0004149266,0.00050888734,0.0008326391,0.0008435268,0.0012067243],"domain_scores_gemma":[0.998534,0.0002574748,0.000113437905,0.0005503031,0.00018098106,0.00036377757],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007562224,0.00036689988,0.0004387545,0.00065963937,0.00029697665,0.00008650351,0.00026170732,0.000094739386,0.0002763746],"category_scores_gemma":[0.00013518672,0.00028997188,0.00009872312,0.0012672965,0.00031956923,0.0007858316,0.00013125144,0.001797314,0.000026641366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019059548,0.0008066606,0.9933694,0.00014755667,0.000015866608,0.000033359098,0.00045606305,0.00022678572,0.0016982846,0.00038879865,0.00052460923,0.00042665028],"study_design_scores_gemma":[0.0038745906,0.0002980973,0.9902023,0.00026733117,0.000025545256,0.00049865345,0.000707462,0.0023662497,0.00005316024,0.0012229743,0.00015342404,0.00033022556],"about_ca_topic_score_codex":0.00022055654,"about_ca_topic_score_gemma":0.00041623125,"teacher_disagreement_score":0.013493846,"about_ca_system_score_codex":0.00017531605,"about_ca_system_score_gemma":0.0004442923,"threshold_uncertainty_score":0.99995524},"labels":[],"label_agreement":null},{"id":"W2051586848","doi":"10.1177/0269881110363314","title":"Anterior internal capsule volumes increase in patients with schizophrenia switched from typical antipsychotics to olanzapine","year":2010,"lang":"en","type":"article","venue":"Journal of Psychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of British Columbia; University of Calgary","funders":"Eli Lilly Canada; AstraZeneca Canada; Pfizer","keywords":"Internal capsule; Corpus callosum; Olanzapine; External capsule; White matter; Schizophrenia (object-oriented programming); Psychology; Antipsychotic; Internal medicine; Medicine; Magnetic resonance imaging; Cardiology; Anesthesia; Neuroscience; Psychiatry; Radiology","score_opus":0.01478368326062822,"score_gpt":0.34369535028801035,"score_spread":0.3289116670273821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051586848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939921,0.000034453882,0.0028305587,0.0022026428,0.0005660191,0.00029295188,0.000016877215,0.000023798175,0.000040632473],"genre_scores_gemma":[0.94854903,0.000032933458,0.048959784,0.002011342,0.0003850976,0.0000081048875,0.000004119495,0.000024841733,0.00002471512],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989252,0.000029559918,0.00047289112,0.0002006376,0.00017559988,0.00019611255],"domain_scores_gemma":[0.99901825,0.000037450867,0.00025286732,0.00020121256,0.00021297642,0.00027723875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011342196,0.00014217025,0.0003611538,0.00025772347,0.000026444839,0.00001135887,0.00021070137,0.0000755454,0.0002627074],"category_scores_gemma":[0.000060723072,0.000109397864,0.000064126296,0.00021581637,0.00006558228,0.000082967446,0.000034715154,0.000854156,0.00001649363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03683612,0.0016820802,0.47122535,0.000013181132,0.00009707683,0.00020456202,0.000112927366,0.000004915788,0.4694228,0.000030826006,0.009601056,0.010769125],"study_design_scores_gemma":[0.012787604,0.001062745,0.97792524,0.00010109855,0.00008376354,0.0001292387,0.000008412048,0.00007367204,0.002746216,0.00035829097,0.0046007605,0.00012298174],"about_ca_topic_score_codex":0.000015392134,"about_ca_topic_score_gemma":0.000014478149,"teacher_disagreement_score":0.50669986,"about_ca_system_score_codex":0.00003249701,"about_ca_system_score_gemma":0.00006184158,"threshold_uncertainty_score":0.44611156},"labels":[],"label_agreement":null},{"id":"W2052758289","doi":"10.1523/jneurosci.4611-09.2010","title":"Training of Working Memory Impacts Structural Connectivity","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":536,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Aging","funders":"","keywords":"Working memory; White matter; Working memory training; Corpus callosum; Neuroscience; Intraparietal sulcus; Fractional anisotropy; Psychology; Diffusion MRI; Short-term memory; Cognitive psychology; Cognition; Posterior parietal cortex; Medicine; Magnetic resonance imaging","score_opus":0.16608175240736123,"score_gpt":0.40057248613907814,"score_spread":0.23449073373171692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052758289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99574375,0.000011547594,0.0027297675,0.00073179987,0.00029232673,0.00006585092,8.551982e-7,0.000016145608,0.000407959],"genre_scores_gemma":[0.98977405,0.0000105395875,0.009737585,0.00035671057,0.00009854628,4.603464e-7,4.401275e-8,0.000006241044,0.000015805666],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99931705,0.0000114665445,0.00022887318,0.000098595454,0.00022047818,0.00012354642],"domain_scores_gemma":[0.9992307,0.000078858124,0.00033110374,0.00015576369,0.000094114024,0.000109461005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021873685,0.000058568137,0.00016848993,0.00009166108,0.000059432507,0.000010778371,0.00015329555,0.000020034453,0.0000046937066],"category_scores_gemma":[0.0006210109,0.000044154425,0.00006680765,0.00023321556,0.00017920633,0.00014488642,0.000026838705,0.00042263308,1.2387261e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001668691,0.000017199896,0.0070820637,0.000005275873,6.291535e-7,0.000023815515,0.00009430467,0.0000135890705,0.9828587,0.0002492805,0.000018996641,0.00961943],"study_design_scores_gemma":[0.0006274212,0.0005980504,0.7512348,0.0001359419,0.000035481266,0.0060759173,0.000089774745,0.0018262098,0.23370104,0.0027248,0.002827736,0.00012283771],"about_ca_topic_score_codex":0.0000010325301,"about_ca_topic_score_gemma":6.543612e-7,"teacher_disagreement_score":0.7491577,"about_ca_system_score_codex":0.00000851483,"about_ca_system_score_gemma":0.00009792007,"threshold_uncertainty_score":0.1836154},"labels":[],"label_agreement":null},{"id":"W2053324294","doi":"10.1159/000102806","title":"The Computer Brain Atlas: lts Use in Stereotaxic Surgery","year":2007,"lang":"en","type":"article","venue":"Confinia Neurologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Atlas (anatomy); Brain atlas; Stereotaxic surgery; Stereotaxy; Computer science; Artificial intelligence; Stereotactic surgery; Computer vision; Computer graphics (images); Terminal (telecommunication); Anatomy; Medicine; Neuroscience; Psychology; Surgery","score_opus":0.12076347041034677,"score_gpt":0.3422939545131749,"score_spread":0.22153048410282813,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053324294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9709632,0.00005501958,0.008776207,0.018558053,0.00011944869,0.0004678327,0.000004191709,0.0002794034,0.00077666197],"genre_scores_gemma":[0.98242104,0.00010030562,0.0019243008,0.015075545,0.00009711509,0.000029988221,0.00000881445,0.000018325189,0.00032455014],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887556,0.00005373784,0.00031597464,0.00030910148,0.00011464961,0.00033097577],"domain_scores_gemma":[0.9972615,0.0020639144,0.00008774875,0.00046354457,0.000040234343,0.00008305372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004004637,0.00012748437,0.00019764277,0.00008033608,0.000108242195,0.000031495718,0.00013363325,0.00006367311,0.000016203725],"category_scores_gemma":[0.00029530044,0.000084574756,0.000075970354,0.0002332062,0.00015424029,0.000041650303,0.00007551227,0.00033772606,0.0000276177],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015277026,0.0007606252,0.58064276,0.000040622126,0.000039266844,0.003014553,0.00015071804,0.000029555798,0.020110615,0.013336104,0.13005218,0.25029525],"study_design_scores_gemma":[0.000237679,0.00018287619,0.7069319,0.000011288382,0.000005922339,0.00014282874,0.0000029448086,0.00025263635,0.0003844532,0.00052806764,0.2912286,0.00009080237],"about_ca_topic_score_codex":0.000011827149,"about_ca_topic_score_gemma":0.000026068466,"teacher_disagreement_score":0.25020447,"about_ca_system_score_codex":0.0000111097725,"about_ca_system_score_gemma":0.000022083883,"threshold_uncertainty_score":0.34488583},"labels":[],"label_agreement":null},{"id":"W2053610521","doi":"10.3389/fnins.2014.00427","title":"High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft; Wellcome Trust","keywords":"Kurtosis; Diffusion MRI; White matter; Image resolution; Partial volume; Artificial intelligence; Computer science; Nuclear magnetic resonance; Computer vision; Physics; Magnetic resonance imaging; Mathematics; Medicine; Radiology","score_opus":0.02711487761857282,"score_gpt":0.2998774151171251,"score_spread":0.2727625374985523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053610521","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49199948,0.00089932163,0.49590692,0.008260348,0.0009601901,0.0007610182,0.00002471399,0.00052212185,0.0006658786],"genre_scores_gemma":[0.92704785,0.000156769,0.068952195,0.002790192,0.000033367727,0.00006515502,0.00002182913,0.000031192132,0.00090146397],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833524,0.000030370176,0.00024331665,0.00060819945,0.0003508468,0.0004320076],"domain_scores_gemma":[0.99918014,0.000012515674,0.00011720147,0.00036432035,0.00010092702,0.00022489857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016676752,0.00016432739,0.00021831297,0.00017740054,0.00020419747,0.000033504693,0.00023937246,0.000035592293,0.0000023455093],"category_scores_gemma":[0.0002819874,0.00015638841,0.00003654142,0.00067392277,0.00023216044,0.0003730735,0.00017547271,0.000208866,0.0000032865273],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022298918,0.00025503818,0.053514462,0.000035738776,6.566556e-7,0.0000492375,0.0001841377,0.00039068566,0.8588751,0.00013757951,0.05063524,0.03569911],"study_design_scores_gemma":[0.009004779,0.0009476535,0.09454087,0.00066681055,0.00010417104,0.0004683223,0.0009477419,0.3933608,0.17757732,0.008343662,0.3123436,0.0016943088],"about_ca_topic_score_codex":0.000030262261,"about_ca_topic_score_gemma":0.0000011761815,"teacher_disagreement_score":0.68129784,"about_ca_system_score_codex":0.00030350813,"about_ca_system_score_gemma":0.00007648395,"threshold_uncertainty_score":0.63773346},"labels":[],"label_agreement":null},{"id":"W2053838094","doi":"10.1016/j.neuroimage.2013.05.074","title":"The Human Connectome Project and beyond: Initial applications of 300mT/m gradients","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":391,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; Siemens; Consortia for Improving Medicine with Innovation and Technology","keywords":"Human Connectome Project; Tractography; Diffusion MRI; Human brain; Connectome; Neuroscience; Connectomics; Computer science; Diffusion; Psychology; Biomedical engineering; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Functional connectivity; Radiology","score_opus":0.05761848994976977,"score_gpt":0.37787842772149494,"score_spread":0.3202599377717252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053838094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96157324,0.000159619,0.0045816763,0.00506634,0.000040931922,0.0043253954,0.000042917247,0.00038886876,0.023820993],"genre_scores_gemma":[0.9956799,0.000085879634,0.0024079345,0.00063173193,0.00005047961,0.0006806945,0.000014601456,0.000024626584,0.0004241619],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926203,0.00002204134,0.00020802142,0.0002276724,0.00012073131,0.000159485],"domain_scores_gemma":[0.99920213,0.00010651272,0.00009175473,0.00044449902,0.0000970678,0.000058052607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005617176,0.00009856634,0.00013680586,0.000062301624,0.00022471811,0.00002682376,0.00012190771,0.00002510057,0.000013833155],"category_scores_gemma":[0.000039909166,0.00007146043,0.000040352093,0.00019211222,0.00027053777,0.000078609875,0.00007644601,0.00016551951,0.000011949138],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004822597,0.000828945,0.020525016,0.00025212392,0.000054986936,0.000021151009,0.0004128688,6.198921e-7,0.72580034,0.09993211,0.028803367,0.12332026],"study_design_scores_gemma":[0.003967564,0.0015414541,0.3817658,0.00009515711,0.0002818081,0.00059010537,0.00043597136,0.00078807207,0.085355364,0.08127543,0.44311446,0.00078879675],"about_ca_topic_score_codex":0.000038212118,"about_ca_topic_score_gemma":0.0000014806119,"teacher_disagreement_score":0.64044493,"about_ca_system_score_codex":0.000007920658,"about_ca_system_score_gemma":0.000018535993,"threshold_uncertainty_score":0.2914072},"labels":[],"label_agreement":null},{"id":"W2054050201","doi":"10.1117/12.878216","title":"Second order DTMR image segmentation using random walker","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Johns Hopkins University","keywords":"Computer science; Image segmentation; Computer vision; Artificial intelligence; Segmentation; Image (mathematics)","score_opus":0.03613040605175855,"score_gpt":0.2914629178595661,"score_spread":0.2553325118078075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054050201","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99169004,0.000042378928,0.0019356731,0.00079891813,0.00008682732,0.00087880134,0.000032650758,0.00013574683,0.004398988],"genre_scores_gemma":[0.21910132,0.000074909345,0.77970624,0.0002501711,0.00024054189,0.00018705703,0.000012814665,0.000080584316,0.00034633803],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983679,9.647495e-9,0.0005667388,0.00035202608,0.0004167064,0.0002965844],"domain_scores_gemma":[0.9978809,0.00005946475,0.0003277147,0.0000711465,0.0015472125,0.00011360854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030660143,0.00025548536,0.0003665703,0.00009481849,0.00008296688,0.0000412689,0.0003903176,0.000120331504,0.00007582518],"category_scores_gemma":[0.00023726553,0.00021227432,0.00042488988,0.000321745,0.00021673535,0.0004559806,0.000110701025,0.00028082062,0.0000018188916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019344711,0.00016597421,0.0005303339,0.00035424106,0.0002074033,1.8389503e-7,0.00019984704,0.000009714576,0.8876774,0.10897719,0.0014578218,0.00022648713],"study_design_scores_gemma":[0.0035700016,0.00040319224,0.0019998874,0.00039759735,0.00046448814,0.00010314613,0.0009323132,0.034343537,0.9483613,0.004272137,0.00469762,0.0004548002],"about_ca_topic_score_codex":0.0000062801155,"about_ca_topic_score_gemma":4.9828827e-8,"teacher_disagreement_score":0.7777706,"about_ca_system_score_codex":0.00012199641,"about_ca_system_score_gemma":0.000033795324,"threshold_uncertainty_score":0.86562955},"labels":[],"label_agreement":null},{"id":"W2054766524","doi":"10.4137/mri.s10692","title":"Diffusion Tensor Metric Measurements as a Function of Diffusion Time in the Rat Central Nervous System","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance Insights","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Grey matter; Diffusion MRI; White matter; Fractional anisotropy; Diffusion; Physics; Thermal diffusivity; Anisotropy; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Medicine; Thermodynamics; Optics","score_opus":0.04734002903679904,"score_gpt":0.2858887376946053,"score_spread":0.23854870865780628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054766524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868079,0.0066819903,0.0006000134,0.0003142605,0.00012160913,0.0010969588,0.0000020041628,0.00010002304,0.0042752847],"genre_scores_gemma":[0.9976802,0.00017382672,0.000853473,0.00027030235,0.00011192056,0.000114250746,0.000009281583,0.000020275977,0.0007664828],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99853045,0.0001017405,0.00034083374,0.00022862418,0.0004861287,0.0003122481],"domain_scores_gemma":[0.9991725,0.00007153046,0.000118169126,0.00047419223,0.00007766177,0.0000859357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016760115,0.0001568211,0.00025035092,0.00017336663,0.000090019515,0.000010389825,0.00014723557,0.00006763275,0.00003875823],"category_scores_gemma":[0.00007396457,0.00009885984,0.00006933547,0.00069253374,0.000059333554,0.00008495954,0.000046226512,0.000176109,0.00004192791],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010424318,0.00319043,0.18107252,0.00050039036,0.000015390551,0.000065384025,0.0024883095,0.000014803295,0.4171498,0.005739407,0.0048725316,0.38384858],"study_design_scores_gemma":[0.0010861792,0.0005335888,0.926764,0.00030341785,0.0000848006,0.00008279793,0.00012228904,0.0008906465,0.0033506937,0.00021696847,0.06641576,0.00014884071],"about_ca_topic_score_codex":0.000050397583,"about_ca_topic_score_gemma":0.0000024995722,"teacher_disagreement_score":0.7456915,"about_ca_system_score_codex":0.000090922054,"about_ca_system_score_gemma":0.00002225248,"threshold_uncertainty_score":0.40313873},"labels":[],"label_agreement":null},{"id":"W2055302062","doi":"10.1002/mrm.20680","title":"Characterization of the NMR behavior of white matter in bovine brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Chemistry; Relaxation (psychology); Nuclear magnetic resonance; Relaxometry; Magnetization transfer; Analytical Chemistry (journal); Chromatography; Magnetic resonance imaging; Central nervous system; Biology; Physics; Spin echo; Endocrinology","score_opus":0.02681640786326605,"score_gpt":0.3202426312526226,"score_spread":0.29342622338935653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055302062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96205753,0.00047351973,0.00021184508,0.035810802,0.000020111616,0.00063199096,0.0000069081375,0.000012912654,0.0007743875],"genre_scores_gemma":[0.99367577,0.00017344508,0.0020933545,0.0019921414,0.000063548,0.00010542145,0.000010394607,0.000015392947,0.0018705372],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99899,0.000029803643,0.00047554923,0.00017319845,0.00019962346,0.00013181615],"domain_scores_gemma":[0.9993504,0.000038570088,0.0001295429,0.00041023488,0.000045502933,0.000025750436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017267268,0.00009165663,0.00027223513,0.00012318544,0.000014753485,7.161408e-7,0.00013417845,0.000040570645,0.0003297664],"category_scores_gemma":[0.00007926968,0.00006356645,0.000026458536,0.000478876,0.00020224067,0.000033994325,0.000052993677,0.00016856383,0.0000023402977],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050907718,0.0001722223,0.74773437,0.000053792577,3.7171787e-7,0.0000042435804,0.00035697725,0.000002375677,0.21257769,0.00011347719,0.0006200702,0.03831349],"study_design_scores_gemma":[0.0009109519,0.00018446281,0.96687746,0.0005092748,0.000012835255,0.000017090868,0.000016687904,0.0002764959,0.0065283193,0.0000708533,0.024548233,0.000047319292],"about_ca_topic_score_codex":0.000036894082,"about_ca_topic_score_gemma":0.00002726239,"teacher_disagreement_score":0.21914308,"about_ca_system_score_codex":0.000029030314,"about_ca_system_score_gemma":0.000020277885,"threshold_uncertainty_score":0.36107108},"labels":[],"label_agreement":null},{"id":"W2055343237","doi":"10.1007/s10851-012-0377-4","title":"Analysis of Scalar Maps for the Segmentation of the Corpus Callosum in Diffusion Tensor Fields","year":2012,"lang":"en","type":"article","venue":"Journal of Mathematical Imaging and Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Diffusion MRI; Scalar (mathematics); Segmentation; Artificial intelligence; Watershed; Computer science; Computer vision; Image segmentation; Visualization; Computation; Context (archaeology); Pattern recognition (psychology); Mathematics; Algorithm; Geometry; Geology; Magnetic resonance imaging","score_opus":0.0417378077631324,"score_gpt":0.3923569160794435,"score_spread":0.3506191083163111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055343237","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78701925,0.000361613,0.20803565,0.0042676525,0.000027954333,0.00023740223,0.000004045454,0.000003810658,0.000042645628],"genre_scores_gemma":[0.9865691,0.00010705057,0.013153606,0.0001161358,0.000021705253,0.000003562639,7.10214e-7,0.0000045674806,0.000023576373],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99936366,0.00002091689,0.00034826118,0.000043633914,0.00015236587,0.000071166745],"domain_scores_gemma":[0.99913687,0.00036130843,0.00025352807,0.00012958077,0.000086893255,0.00003184542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040348613,0.00004747264,0.00021330561,0.00009200202,0.000034421224,0.000004421399,0.00006024084,0.00001856982,0.0000055349215],"category_scores_gemma":[0.00018572398,0.000022364007,0.00012405554,0.00019180524,0.00006548722,0.000056599067,0.000029567746,0.00010666573,7.38334e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038712492,0.0019908268,0.6736102,0.0007873792,0.0003183432,0.0000028420725,0.0021222075,0.00018093846,0.20916915,0.007406318,0.001500131,0.10252453],"study_design_scores_gemma":[0.0026098043,0.00039266224,0.7715463,0.001588025,0.0038561074,0.00022793093,0.001145524,0.15287331,0.04101656,0.023578955,0.0009966234,0.00016817942],"about_ca_topic_score_codex":0.0000023342166,"about_ca_topic_score_gemma":2.4378096e-7,"teacher_disagreement_score":0.19954985,"about_ca_system_score_codex":0.000010752759,"about_ca_system_score_gemma":0.000006844482,"threshold_uncertainty_score":0.09119778},"labels":[],"label_agreement":null},{"id":"W2055993761","doi":"10.1016/s0221-0363(10)70050-0","title":"IRM de diffusion et encéphale","year":2010,"lang":"fr","type":"review","venue":"Journal de Radiologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital Notre-Dame","funders":"","keywords":"Medicine; Diffusion MRI; Ischemia; Diffusion imaging; Magnetic resonance imaging; Radiology; Cerebral ischaemia; Effective diffusion coefficient; Nuclear medicine; Cardiology","score_opus":0.17000355134787423,"score_gpt":0.45796209045333286,"score_spread":0.28795853910545866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055993761","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004932851,0.89412016,0.09501371,0.004878048,0.0010636472,0.0006281272,0.000044587854,0.00018657373,0.0035718626],"genre_scores_gemma":[0.00017566883,0.92320627,0.069456264,0.0015796425,0.0029016305,0.00008203369,0.00003698091,0.0000827549,0.0024787625],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972003,0.000450647,0.0008061741,0.00041464824,0.00021756816,0.0009106396],"domain_scores_gemma":[0.9971226,0.0008193149,0.0006851594,0.0006574207,0.00011419475,0.0006013402],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0015429073,0.00047887952,0.0012583177,0.00019546415,0.000307809,0.000072109586,0.0006309307,0.0007845243,0.00035301162],"category_scores_gemma":[0.0013304186,0.00036204339,0.00068389525,0.00025009035,0.00025122578,0.00010543432,0.00015624278,0.0055549694,0.00015808322],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013860458,0.000219798,0.0006804623,0.0012599307,0.00005180012,0.0013735237,0.00003814663,0.0000090341555,0.0033550751,0.0034661589,0.015232943,0.97429925],"study_design_scores_gemma":[0.00029489538,0.00024659865,0.00066194776,0.0056859893,0.00056944235,0.049415853,0.000013125334,0.00016244002,0.000060883256,0.0072767176,0.935309,0.00030313837],"about_ca_topic_score_codex":0.000008038979,"about_ca_topic_score_gemma":9.729234e-7,"teacher_disagreement_score":0.9739961,"about_ca_system_score_codex":0.000890228,"about_ca_system_score_gemma":0.0012238184,"threshold_uncertainty_score":0.9998832},"labels":[],"label_agreement":null},{"id":"W2056509200","doi":"10.1016/j.mri.2009.05.038","title":"Spinal fMRI investigation of human spinal cord function over a range of innocuous thermal sensory stimuli and study-related emotional influences","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Brainstem; Neuroscience; Spinal cord; Locus coeruleus; Sensory system; Functional magnetic resonance imaging; Inhibitory postsynaptic potential; Reticular formation; Anatomy; Psychology; Central nervous system; Periaqueductal gray; Medicine; Midbrain","score_opus":0.051803747408831875,"score_gpt":0.3523926906083048,"score_spread":0.30058894319947294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056509200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956258,0.002529436,0.00030862656,0.00064033654,0.000020110387,0.0005503909,0.0000046861833,0.00007661242,0.00024400401],"genre_scores_gemma":[0.9973899,0.000033464894,0.0021736857,0.00023917266,0.00003690431,0.000017607335,0.0000048188,0.000012826368,0.00009162659],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99878174,0.00004566719,0.00043776975,0.00029716524,0.00027912462,0.00015854427],"domain_scores_gemma":[0.9993224,0.000020019852,0.00020634607,0.00024417217,0.00014992883,0.00005713506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001590018,0.00014794813,0.00025128925,0.00014986015,0.00009085912,0.000011619002,0.000072200986,0.00003193042,0.000031749667],"category_scores_gemma":[0.00003743162,0.00014134528,0.000041423413,0.00029865158,0.00030035037,0.00013430716,0.000030663155,0.00018957724,9.07079e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055008155,0.00018439096,0.5302883,0.000056590885,0.00000522395,0.00001663476,0.00013815828,0.000010520107,0.22776732,0.0006879196,0.000045304932,0.24024957],"study_design_scores_gemma":[0.0012754566,0.0035276602,0.9893639,0.00029434013,0.00006776739,0.00004496923,0.00007407948,0.0008979517,0.0017914806,0.0024335955,0.000116133335,0.00011264746],"about_ca_topic_score_codex":0.000050353934,"about_ca_topic_score_gemma":8.5759626e-7,"teacher_disagreement_score":0.45907566,"about_ca_system_score_codex":0.00002155645,"about_ca_system_score_gemma":0.000032847624,"threshold_uncertainty_score":0.5763893},"labels":[],"label_agreement":null},{"id":"W2057123686","doi":"10.1016/j.bandl.2013.06.007","title":"Potential and limitations of diffusion MRI tractography for the study of language","year":2013,"lang":"en","type":"review","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; Psychology; Magnetic resonance imaging; Sensitivity (control systems); Neuroscience; Artificial intelligence; Computer science; Radiology; Medicine","score_opus":0.0932722955506512,"score_gpt":0.397243869124542,"score_spread":0.3039715735738908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057123686","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005426902,0.98925626,0.0018623916,0.00020264075,0.000013298981,0.0030348832,0.000072484625,0.000030947227,0.00010016152],"genre_scores_gemma":[0.009602753,0.9874793,0.0021500625,0.00006176429,0.000045795183,0.00033004678,0.000055845972,0.000024974817,0.000249406],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994191,0.000029235618,0.00023783346,0.00016426512,0.000074955075,0.00007461034],"domain_scores_gemma":[0.99883574,0.00065806386,0.00017634901,0.0002688738,0.000027397964,0.000033594137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000845371,0.00012234444,0.00046499606,0.000095845055,0.000049710638,0.0000070262527,0.000067242516,0.0000537644,0.0000057735115],"category_scores_gemma":[0.00009642388,0.00007134748,0.000120004326,0.00012257061,0.00007369736,0.000017017132,0.000040295537,0.00011509797,1.6576064e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005024842,0.00019964138,0.0000067004908,0.0019371372,0.000051038565,0.000002432423,0.0014983176,4.3764423e-8,0.0003070872,0.00014314226,0.00042269783,0.9954267],"study_design_scores_gemma":[0.0015991111,0.0009353918,0.0012123715,0.0025060314,0.0026348378,0.000100211466,0.012441369,0.00009182367,0.000044042405,0.000085339154,0.97807044,0.00027903254],"about_ca_topic_score_codex":0.00004443302,"about_ca_topic_score_gemma":0.000008338609,"teacher_disagreement_score":0.9951477,"about_ca_system_score_codex":0.000002335922,"about_ca_system_score_gemma":0.000012305313,"threshold_uncertainty_score":0.29094657},"labels":[],"label_agreement":null},{"id":"W2057236586","doi":"10.1016/j.neuro.2009.07.007","title":"Altered myelination and axonal integrity in adults with childhood lead exposure: A diffusion tensor imaging study","year":2009,"lang":"en","type":"article","venue":"NeuroToxicology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Child and Family Research Institute","funders":"National Center for Research Resources; National Institute of Environmental Health Sciences; National Cancer Institute; NIH Clinical Center; National Institutes of Health","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Splenium; Lead exposure; Psychology; Neuroscience; Physiology; Magnetic resonance imaging; Internal medicine; Medicine","score_opus":0.031435246139275876,"score_gpt":0.3300036538207122,"score_spread":0.2985684076814363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057236586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99156773,0.0000338716,0.000846429,0.0050576827,0.000021561722,0.00213115,0.000002025299,0.00015149298,0.00018808385],"genre_scores_gemma":[0.9946334,0.000035007943,0.002793967,0.0022240859,0.00005863975,0.00021157524,0.000007554897,0.000015553105,0.000020248826],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989638,0.00006578504,0.00022175611,0.0004260455,0.0001234424,0.00019916837],"domain_scores_gemma":[0.9995074,0.000051845658,0.000075237556,0.00024273644,0.000058111826,0.000064656655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008304372,0.00014561345,0.0002289968,0.00015690197,0.000066634915,0.000010111684,0.000069487316,0.000044430406,0.0000065339827],"category_scores_gemma":[0.00008418153,0.0001184286,0.0000201451,0.00020421307,0.00006496415,0.00007255891,0.00003876192,0.00047765436,0.0000016774842],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007139893,0.0034823585,0.8798403,0.000015755038,0.000004339515,0.00019049244,0.00061247824,0.0000029084754,0.023648141,0.00023466504,0.00007925264,0.09117532],"study_design_scores_gemma":[0.0035383878,0.0029773675,0.9907538,0.000062515915,0.000016883434,0.00035210588,0.00012230617,0.00080620596,0.00058527116,0.0004817365,0.00020061748,0.000102795704],"about_ca_topic_score_codex":0.000008816153,"about_ca_topic_score_gemma":0.00002435269,"teacher_disagreement_score":0.11091351,"about_ca_system_score_codex":0.000030240632,"about_ca_system_score_gemma":0.000027091206,"threshold_uncertainty_score":0.4829378},"labels":[],"label_agreement":null},{"id":"W2057327718","doi":"10.1097/01.rli.0000261935.41188.39","title":"Diffusion-Tensor Imaging at 3 T","year":2007,"lang":"en","type":"article","venue":"Investigative Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Medicine; Diffusion imaging; Confidence interval; Anisotropy; Nuclear medicine; Magnetic resonance imaging; Nuclear magnetic resonance; Physics; Radiology; Optics; Internal medicine","score_opus":0.0760410469570088,"score_gpt":0.3612716232919629,"score_spread":0.2852305763349541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057327718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95983416,0.0002320516,0.020670306,0.0095934225,0.0000728423,0.00036185255,0.000006594852,0.00036393772,0.008864837],"genre_scores_gemma":[0.95154816,0.000034794026,0.04013526,0.0068434128,0.00016347998,0.000028675397,0.000026528784,0.0000258818,0.0011938253],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911195,0.000025968182,0.00020505511,0.00029633378,0.000076591605,0.00028411564],"domain_scores_gemma":[0.99921227,0.00016623485,0.00007845045,0.00028247997,0.00006703379,0.00019356121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001505818,0.00012303733,0.000207961,0.000093250914,0.0001235931,0.0000025797024,0.00007861861,0.000048385322,0.000067204914],"category_scores_gemma":[0.00021042388,0.00010490354,0.000054288954,0.00016689443,0.000783394,0.00003346192,0.000074886084,0.00019849213,0.000065971995],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005895535,0.00005532337,0.4906749,0.000013238627,0.00001558036,0.00019861895,0.00020085902,0.0000016874031,0.47497454,0.016776018,0.012056851,0.0049733943],"study_design_scores_gemma":[0.0009001294,0.00015230378,0.7117446,0.000048352947,0.000045451397,0.002580641,0.000071045004,0.00039500746,0.101564,0.035604406,0.14663593,0.0002580999],"about_ca_topic_score_codex":0.000008370484,"about_ca_topic_score_gemma":0.000002510567,"teacher_disagreement_score":0.37341055,"about_ca_system_score_codex":0.00011337741,"about_ca_system_score_gemma":0.000026498083,"threshold_uncertainty_score":0.42778423},"labels":[],"label_agreement":null},{"id":"W2057477305","doi":"10.1016/j.compmedimag.2014.07.002","title":"Detection of temporal lobe epilepsy using support vector machines in multi-parametric quantitative MR imaging","year":2014,"lang":"en","type":"article","venue":"Computerized Medical Imaging and Graphics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research","keywords":"Support vector machine; Pattern recognition (psychology); Artificial intelligence; Epilepsy; Temporal lobe; Computer science; Diffusion MRI; Parametric statistics; Principal component analysis; Fractional anisotropy; Magnetic resonance imaging; Mathematics; Radiology; Medicine; Psychology; Neuroscience; Statistics","score_opus":0.0627627876946144,"score_gpt":0.3776114421191385,"score_spread":0.3148486544245241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057477305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33848885,0.00025164138,0.6598964,0.0009073418,0.000108715096,0.00020815812,0.000003977165,0.00011810361,0.0000168045],"genre_scores_gemma":[0.8905671,0.00012077271,0.10853032,0.000675526,0.000049261784,0.000011833626,0.000015901416,0.00002561566,0.000003633655],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985082,0.00009333567,0.00046581117,0.000384473,0.00029376944,0.0002543941],"domain_scores_gemma":[0.9989918,0.000260519,0.00017331481,0.0002551773,0.000111081165,0.00020811032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050871255,0.00018818144,0.00044133278,0.0005158261,0.00009027006,0.000019690602,0.00011852612,0.00005842856,0.000005821345],"category_scores_gemma":[0.00046740673,0.00017142571,0.00008887058,0.0007759703,0.0003935531,0.00010627927,0.000104403414,0.00041901102,6.738323e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002190781,0.00059292174,0.75775355,0.00050820626,0.000040881925,0.00014429349,0.00032076915,0.000029006113,0.058031686,0.003477934,0.000090810056,0.17879088],"study_design_scores_gemma":[0.0018673987,0.00008419598,0.06005863,0.0002880491,0.000040424286,0.00025067074,0.000021404087,0.9341142,0.0011556221,0.0011855598,0.00076047675,0.00017332265],"about_ca_topic_score_codex":0.00017151119,"about_ca_topic_score_gemma":0.0000067420397,"teacher_disagreement_score":0.93408525,"about_ca_system_score_codex":0.00002276102,"about_ca_system_score_gemma":0.000056172827,"threshold_uncertainty_score":0.6990537},"labels":[],"label_agreement":null},{"id":"W2057517058","doi":"10.1093/brain/aws153","title":"Assessing the risk of central post-stroke pain of thalamic origin by lesion mapping","year":2012,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Thalamus; Lesion; Magnetic resonance imaging; Medicine; Stroke (engine); Odds ratio; Neuroscience; Psychology; Pathology; Radiology","score_opus":0.06828368282082552,"score_gpt":0.3703583069288995,"score_spread":0.30207462410807395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057517058","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89598936,0.00027550122,0.09997574,0.0028932078,0.000024455067,0.00026057273,0.00004344067,0.00005454459,0.00048315828],"genre_scores_gemma":[0.98680216,0.0000433818,0.012352004,0.00044898604,0.000052235915,0.000009178171,0.000016668562,0.000012736844,0.00026263084],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99934846,0.00009905854,0.00017426292,0.00008875944,0.000112882044,0.00017655203],"domain_scores_gemma":[0.99923754,0.0002899076,0.00015430397,0.00024306113,0.000032924585,0.00004224448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053404464,0.00006689894,0.00012623266,0.00003353191,0.000050410377,0.000004493511,0.000075161595,0.000029153493,0.000012128782],"category_scores_gemma":[0.000268351,0.000045781428,0.000061878876,0.00009768967,0.00006825784,0.00008119145,0.000027014588,0.00013733376,0.0000010479669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005938321,0.00010584997,0.15569031,0.00004049711,0.000011147492,3.86948e-7,0.00019381147,0.0000019690037,0.8101716,0.0007052946,0.0035870569,0.029486142],"study_design_scores_gemma":[0.0008203153,0.0001527416,0.59473306,0.00034467422,0.00011215855,0.00003942841,0.0012257162,0.0020345424,0.30009487,0.00093447533,0.0992865,0.00022150546],"about_ca_topic_score_codex":0.000044405224,"about_ca_topic_score_gemma":3.764848e-7,"teacher_disagreement_score":0.5100767,"about_ca_system_score_codex":0.000018660527,"about_ca_system_score_gemma":0.00002146463,"threshold_uncertainty_score":0.18669124},"labels":[],"label_agreement":null},{"id":"W2057680708","doi":"10.1523/jneurosci.1312-06.2006","title":"Genetic Contributions to Human Brain Morphology and Intelligence","year":2006,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":291,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"White matter; Corpus callosum; Cortex (anatomy); Posterior cingulate; Brain morphometry; Cingulate cortex; Temporal cortex; Posterior parietal cortex; Psychology; Neuroscience; Anatomy; Biology; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.05568312087274402,"score_gpt":0.4015405996213333,"score_spread":0.3458574787485893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057680708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75112855,0.00004289932,0.23507793,0.0134646725,0.00004590513,0.00011349182,0.0000042630863,0.000017582648,0.00010467545],"genre_scores_gemma":[0.98601717,0.000020815325,0.010904448,0.0028290113,0.0000732926,0.0000026878488,1.319513e-7,0.0000045675424,0.0001478656],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99940884,0.000013647489,0.00022039903,0.00012169965,0.00011692648,0.0001185134],"domain_scores_gemma":[0.99951655,0.00004153051,0.000101743535,0.00011773555,0.00012034878,0.00010210743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009930042,0.000050590363,0.00010981117,0.00010438146,0.00009503877,0.000014714591,0.00010767639,0.000014674359,0.0000026661241],"category_scores_gemma":[0.00022173411,0.000042074542,0.000026857198,0.00023606187,0.00014625415,0.000049887098,0.000037654845,0.000133359,0.0000012877822],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000054606326,0.00005162425,0.004423051,0.0000020452314,2.46585e-7,0.000080759695,0.0000054632415,0.0000824824,0.98940563,0.0032766056,0.001808114,0.0008585177],"study_design_scores_gemma":[0.0002291032,0.0010074829,0.9069034,0.000038666956,0.000020170815,0.006637787,0.000007703204,0.00033410027,0.03643893,0.015142293,0.033141386,0.00009898991],"about_ca_topic_score_codex":0.0000051446405,"about_ca_topic_score_gemma":5.9744065e-7,"teacher_disagreement_score":0.9529667,"about_ca_system_score_codex":0.000019161607,"about_ca_system_score_gemma":0.000029256129,"threshold_uncertainty_score":0.17157501},"labels":[],"label_agreement":null},{"id":"W2058065446","doi":"10.3109/02699052.2013.794968","title":"Neurometabolic and microstructural alterations following a sports-related concussion in female athletes","year":2013,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":97,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Hôpital Saint-Luc; Université de Montréal","funders":"","keywords":"Concussion; Athletes; Medicine; Injury prevention; Physical therapy; Poison control; Occupational safety and health; Suicide prevention; Sports medicine; Human factors and ergonomics; Physical medicine and rehabilitation; Psychology; Medical emergency; Pathology","score_opus":0.023313523626571516,"score_gpt":0.3233919355875211,"score_spread":0.3000784119609496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058065446","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99350166,0.00017974782,0.00011549708,0.005098198,0.000046994493,0.00057932746,0.000005152301,0.00013201713,0.00034139893],"genre_scores_gemma":[0.99197537,0.000043886557,0.0055770306,0.0017062823,0.000026257174,0.00009066246,0.000021464772,0.000019682213,0.0005393769],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992871,0.000017642335,0.00022061555,0.00023204018,0.00008297669,0.00015960423],"domain_scores_gemma":[0.99960655,0.000048441027,0.000047131183,0.00020268686,0.00002068253,0.00007450511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055015593,0.00010360139,0.00016754058,0.00011578431,0.00007583124,0.000025081335,0.000042347532,0.000044239438,0.000063940504],"category_scores_gemma":[0.00008260969,0.000087768974,0.00004581123,0.00023261522,0.000052228923,0.00014033771,0.00004341123,0.00017306225,0.0000096457015],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015959477,0.00005570535,0.089666374,0.000024306544,0.000009347894,0.00002884993,0.0003347733,0.0000017547721,0.8515836,0.0019184536,0.0027553565,0.053605545],"study_design_scores_gemma":[0.0010252771,0.00011652877,0.9598389,0.00019284699,0.000030022147,0.00013203025,0.00007675748,0.000821248,0.015577056,0.006743467,0.015193253,0.0002526073],"about_ca_topic_score_codex":0.000026396176,"about_ca_topic_score_gemma":7.0817924e-7,"teacher_disagreement_score":0.87017256,"about_ca_system_score_codex":0.000013167987,"about_ca_system_score_gemma":0.000017900478,"threshold_uncertainty_score":0.3579115},"labels":[],"label_agreement":null},{"id":"W2058457174","doi":"10.1007/s00429-012-0466-6","title":"Understanding white matter integrity stability for bilinguals on language status and reading performance","year":2012,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Psychology; Fractional anisotropy; White matter; Neuroscience of multilingualism; Reading (process); Diffusion MRI; Audiology; Age of Acquisition; Cognitive psychology; Developmental psychology; Cognition; Linguistics; Neuroscience; Medicine","score_opus":0.11788817718121347,"score_gpt":0.3463011893353268,"score_spread":0.2284130121541133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058457174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9675754,0.00006946624,0.030578943,0.00085733604,0.00006909049,0.00036361496,0.000026251812,0.000066636,0.00039326804],"genre_scores_gemma":[0.9951077,0.000019479361,0.003418796,0.0011567835,0.00014043975,0.000014819337,0.000035508998,0.000012582253,0.000093863775],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949527,0.00001160169,0.0000949571,0.00017060371,0.00005709382,0.00017049622],"domain_scores_gemma":[0.99964434,0.0000886163,0.00003937661,0.00013384089,0.000018594175,0.00007521237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000120275145,0.000089081856,0.000107426335,0.000046448647,0.00011955297,0.000013921806,0.00001197578,0.000052510233,0.00003529115],"category_scores_gemma":[0.00004863333,0.00006933056,0.000017335375,0.000060359518,0.000045023455,0.00010866828,0.000013790496,0.0001615657,5.4617607e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034081936,0.00002842292,0.95827705,0.0002468146,0.0000133832755,2.0469946e-7,0.001223991,0.0000016192978,0.02355019,0.003781851,0.0013821142,0.011153516],"study_design_scores_gemma":[0.0008499977,0.0004030756,0.97312945,0.00008840263,0.00007710626,0.00004625873,0.0013215418,0.00039816165,0.010454726,0.005601702,0.007424639,0.0002049259],"about_ca_topic_score_codex":0.0000033708513,"about_ca_topic_score_gemma":0.0000013092828,"teacher_disagreement_score":0.027532334,"about_ca_system_score_codex":0.000058484282,"about_ca_system_score_gemma":0.000007680993,"threshold_uncertainty_score":0.28272182},"labels":[],"label_agreement":null},{"id":"W2059013849","doi":"10.1016/j.pscychresns.2007.11.007","title":"Diffusion tensor imaging tractography and reliability analysis for limbic and paralimbic white matter tracts","year":2008,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"White matter; Cingulum (brain); Diffusion MRI; Uncinate fasciculus; Fractional anisotropy; Fornix; Inferior longitudinal fasciculus; Tractography; Psychology; Parahippocampal gyrus; Medicine; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Radiology; Hippocampus; Temporal lobe","score_opus":0.10378085638715982,"score_gpt":0.40735516343047434,"score_spread":0.3035743070433145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059013849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9466754,0.0006603406,0.010316636,0.040261563,0.00005716693,0.0012371585,0.000027121094,0.00021322425,0.0005513527],"genre_scores_gemma":[0.96023697,0.0007368557,0.036897916,0.0014818147,0.00011348304,0.00020113634,0.000025790314,0.00006149944,0.00024455888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973657,0.00013006745,0.00039881957,0.0010070159,0.00042968898,0.00066872145],"domain_scores_gemma":[0.9982094,0.0003404206,0.00009657664,0.0007449014,0.00025788133,0.00035082517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057524006,0.00025833587,0.00043421317,0.0008915563,0.0007689294,0.00008671882,0.00015163238,0.000049268994,0.0000251943],"category_scores_gemma":[0.00014273057,0.00022986958,0.00021820325,0.0013335039,0.00059273664,0.0002586344,0.00013263905,0.00071386877,0.0000047324183],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013120787,0.00025775074,0.9945601,0.00014540588,0.000030875475,0.000016795664,0.00010540137,0.0000064057267,0.0015770158,0.000082647835,0.0022532984,0.0008330808],"study_design_scores_gemma":[0.0007921983,0.00012589838,0.9865395,0.00004875362,0.00021091169,0.00035434964,0.00008406408,0.005168705,0.000054672288,0.0027633673,0.0036532332,0.0002043692],"about_ca_topic_score_codex":0.000032011714,"about_ca_topic_score_gemma":0.0000025204852,"teacher_disagreement_score":0.03877975,"about_ca_system_score_codex":0.000024882305,"about_ca_system_score_gemma":0.00005742763,"threshold_uncertainty_score":0.9373809},"labels":[],"label_agreement":null},{"id":"W2059177186","doi":"10.1016/j.neuroimage.2004.03.041","title":"Diffusion tensor imaging detects early Wallerian degeneration of the pyramidal tract after ischemic stroke","year":2004,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":436,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Pyramidal tracts; Fractional anisotropy; Cerebral peduncle; Wallerian degeneration; Stroke (engine); Medicine; Corticospinal tract; Cardiology; Neuroscience; Pathology; Magnetic resonance imaging; Anatomy; Psychology; Internal capsule; Radiology; Physics; White matter","score_opus":0.022563115463479087,"score_gpt":0.2820871390897093,"score_spread":0.25952402362623017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059177186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99065167,0.000053326472,0.0047725355,0.002787258,0.00006353019,0.00048047473,0.000018732973,0.00014797611,0.0010244738],"genre_scores_gemma":[0.9935727,0.000023858101,0.005069916,0.0008596962,0.00008309054,0.000053644457,0.0000043005753,0.000040516323,0.00029224865],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990365,0.000018439836,0.00023172205,0.00029713078,0.00021941614,0.00019678978],"domain_scores_gemma":[0.9991875,0.000017836495,0.00010754134,0.0005504984,0.000069398375,0.00006719909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043818374,0.00014895387,0.00015796263,0.00005865509,0.0000918071,0.000020221658,0.0001377768,0.00003711701,0.000018216677],"category_scores_gemma":[0.000058810332,0.00011019553,0.00012387308,0.00016479488,0.00011823469,0.00012108991,0.000076162316,0.00027393794,0.000008440178],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043734108,0.00012818036,0.027560107,0.00001857601,0.000002060101,0.00002571233,0.00006311949,0.000013992273,0.9693811,0.00006114431,0.00008197409,0.0026203054],"study_design_scores_gemma":[0.00081374124,0.00007588947,0.50818473,0.00005981107,0.000042735905,0.000120497665,0.000008744037,0.00021638004,0.48690948,0.00016906393,0.003287917,0.000111018024],"about_ca_topic_score_codex":0.000023068027,"about_ca_topic_score_gemma":0.0000024527913,"teacher_disagreement_score":0.48247162,"about_ca_system_score_codex":0.000038880313,"about_ca_system_score_gemma":0.00004020897,"threshold_uncertainty_score":0.4493643},"labels":[],"label_agreement":null},{"id":"W2059189228","doi":"10.1002/mrm.21132","title":"Partial <i>k</i>‐space reconstruction in single‐shot diffusion‐weighted echo‐planar imaging","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Echo (communications protocol); Direct-conversion receiver; k-space; Physics; Artifact (error); Planar; Echo-planar imaging; Sampling (signal processing); Truncation (statistics); Homodyne detection; Nuclear magnetic resonance; Optics; Computer vision; Computer science; Magnetic resonance imaging; Fourier transform; Detector","score_opus":0.042459987427275275,"score_gpt":0.3291119296082759,"score_spread":0.28665194218100065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059189228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92949826,0.009054451,0.010214052,0.020810023,0.00038404213,0.0014291503,0.0000050382673,0.00035174453,0.02825322],"genre_scores_gemma":[0.9773612,0.0010689802,0.01862997,0.001784708,0.00036851384,0.000072102885,0.000019848938,0.00004490835,0.00064974977],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99791676,0.00004002325,0.0006662481,0.00052722846,0.00034520024,0.0005045314],"domain_scores_gemma":[0.9989985,0.00018366273,0.00011862886,0.00048191866,0.000065807275,0.00015148855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054427277,0.00022584604,0.0004262613,0.00042863496,0.000057601024,0.000007594854,0.00014171151,0.00008368178,0.0001727747],"category_scores_gemma":[0.00024120699,0.00019794363,0.00003906801,0.0009548223,0.0003327427,0.000084206855,0.00003462828,0.00050120184,0.000009465766],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044215692,0.00032177137,0.30646893,0.00005510698,0.000001501925,0.00064408465,0.00043943524,0.0000018273862,0.1583165,0.0009063964,0.0018174199,0.5305849],"study_design_scores_gemma":[0.009550003,0.0010319295,0.7144344,0.0030414348,0.000065160435,0.001621925,0.00092276686,0.0044351695,0.018558819,0.007443473,0.23824187,0.0006530504],"about_ca_topic_score_codex":0.00022109688,"about_ca_topic_score_gemma":0.00011857448,"teacher_disagreement_score":0.52993184,"about_ca_system_score_codex":0.00017362428,"about_ca_system_score_gemma":0.000033313077,"threshold_uncertainty_score":0.8071907},"labels":[],"label_agreement":null},{"id":"W2059786519","doi":"10.1117/12.878423","title":"Shape anisotropy: tensor distance to anisotropy measure","year":2011,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Diffusion MRI; Tensor (intrinsic definition); Anisotropy; Fractional anisotropy; Physics; Euclidean distance; Isotropy; Tensor field; Measure (data warehouse); Mathematical analysis; Mathematics; Computer science; Artificial intelligence; Exact solutions in general relativity; Geometry; Optics; Magnetic resonance imaging","score_opus":0.03755359466630674,"score_gpt":0.2768961986355143,"score_spread":0.23934260396920753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059786519","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98905665,0.00006049571,0.0016178247,0.00415963,0.00008757753,0.0009797901,0.000056319528,0.00023737198,0.0037443575],"genre_scores_gemma":[0.3925372,0.00007949255,0.6058912,0.00048176618,0.00027519025,0.00031237927,0.000006448715,0.000087144756,0.00032913708],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979649,8.201853e-9,0.00056786713,0.0004763563,0.00059444667,0.0003964313],"domain_scores_gemma":[0.9976504,0.00004945418,0.00026351932,0.00010717199,0.0017114311,0.00021802724],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026510895,0.00030955081,0.0004339639,0.00009270265,0.00009120106,0.000040784864,0.00070934795,0.0001344123,0.000029187597],"category_scores_gemma":[0.00043678953,0.0002545547,0.00051386596,0.0004066967,0.0001985967,0.0002906259,0.00015884229,0.00032263144,0.000004368981],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020090562,0.00018324645,0.0012515385,0.00021764086,0.00014558791,2.4890474e-7,0.00015286691,0.0000038867906,0.48082894,0.5124848,0.004044474,0.00048585437],"study_design_scores_gemma":[0.0040897415,0.0029353295,0.023608206,0.0017585774,0.00094631215,0.00020713096,0.0022311155,0.023934085,0.85141754,0.018058248,0.06925375,0.0015599718],"about_ca_topic_score_codex":0.0000062591666,"about_ca_topic_score_gemma":6.9995146e-8,"teacher_disagreement_score":0.60427344,"about_ca_system_score_codex":0.0001476908,"about_ca_system_score_gemma":0.000032626453,"threshold_uncertainty_score":0.99999064},"labels":[],"label_agreement":null},{"id":"W2059955071","doi":"10.1016/j.jcjo.2013.11.003","title":"Diffusion-weighted imaging in posterior ischemic optic neuropathy","year":2014,"lang":"en","type":"letter","venue":"Canadian Journal of Ophthalmology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Neuroimaging; Ischemia; Medicine; Stroke (engine); Extracellular; Diffusion imaging; Ischemic stroke; Nuclear medicine; Pathology; Cardiology; Radiology; Chemistry; Physics","score_opus":0.040146222436392355,"score_gpt":0.31031148746373977,"score_spread":0.2701652650273474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059955071","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38561726,0.00079229625,0.00018558536,0.60252494,0.0005814716,0.00042314176,0.000027646733,0.000019890771,0.009827785],"genre_scores_gemma":[0.75488424,0.000015556876,0.005271752,0.23574805,0.0020851705,0.000022315544,0.00008693143,0.00017143322,0.0017145701],"study_design_codex":"case_report","study_design_gemma":"case_report","domain_scores_codex":[0.9982585,0.00009566932,0.0006529335,0.00031116084,0.00014760158,0.00053415744],"domain_scores_gemma":[0.9983933,0.000116378775,0.0004513953,0.0004625348,0.00019905387,0.0003773248],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00014429163,0.00028263207,0.00067521277,0.000926226,0.000062472216,0.000023867622,0.00038722396,0.00030780444,0.0003721097],"category_scores_gemma":[0.00014615052,0.0002656506,0.0001824284,0.00022296827,0.00019726549,0.00005855705,0.000030772408,0.0023863206,0.00001933752],"study_design_candidate":"case_report","study_design_consensus":"case_report","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032859356,0.00002320658,0.022911822,0.00011329563,0.000017319631,0.52355236,0.000048013993,0.0000012351942,0.0020968684,0.000014180803,0.45046446,0.00072440546],"study_design_scores_gemma":[0.0005178567,0.00019220232,0.003664825,0.00033850226,0.00006730595,0.698009,0.00000529464,0.000065317174,0.00009297287,0.00033623414,0.29650345,0.00020700468],"about_ca_topic_score_codex":0.00047868307,"about_ca_topic_score_gemma":0.0000051201473,"teacher_disagreement_score":0.36926696,"about_ca_system_score_codex":0.00022827044,"about_ca_system_score_gemma":0.0008527069,"threshold_uncertainty_score":0.99997956},"labels":[],"label_agreement":null},{"id":"W2059991735","doi":"10.1016/j.jmr.2013.10.012","title":"A pulse sequence optimization method for assessment of nucleus size in q-space analysis of idealized cells","year":2013,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; Thunder Bay Regional Research Institute","funders":"","keywords":"Nucleus; Monte Carlo method; Impulse (physics); Pulse (music); Physics; Propagator; Gaussian; Sequence (biology); Pulse sequence; Chemistry; Computational physics; Mathematics; Nuclear magnetic resonance; Optics; Statistics; Classical mechanics; Biology; Quantum mechanics","score_opus":0.05521449007641873,"score_gpt":0.4072630609447733,"score_spread":0.3520485708683546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059991735","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0838541,0.00090956956,0.91171414,0.0022913804,0.000024267527,0.00081571296,0.000027366228,0.000010213285,0.00035326462],"genre_scores_gemma":[0.243983,0.0007259839,0.7550119,0.000097131306,0.000010573009,0.000030529645,0.0000012521274,0.000009465544,0.0001301611],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878263,0.000056798686,0.00068166404,0.00012944189,0.00023145304,0.00011803213],"domain_scores_gemma":[0.9982292,0.00039875263,0.0006567002,0.0002413928,0.00041715158,0.00005679328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040403346,0.00008551513,0.000519446,0.00022658992,0.000013152382,0.0000061735777,0.00013257166,0.00003936687,0.0001286355],"category_scores_gemma":[0.00024071682,0.00007181168,0.00016923333,0.00072374824,0.0000493198,0.00007699701,0.000019684856,0.00012513834,1.2707572e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003065475,0.0006563587,0.0106457565,0.0002562347,0.00012136346,0.000016407961,0.0002006002,0.08469003,0.82785034,0.0023273274,0.0009377653,0.071991295],"study_design_scores_gemma":[0.0027317852,0.0013234557,0.17222653,0.000358017,0.0009191817,0.000036529447,0.000080171,0.78864,0.027488021,0.0023165762,0.0037253092,0.0001544154],"about_ca_topic_score_codex":0.00006169329,"about_ca_topic_score_gemma":0.0000018261766,"teacher_disagreement_score":0.8003623,"about_ca_system_score_codex":0.000051216884,"about_ca_system_score_gemma":0.000084877945,"threshold_uncertainty_score":0.29283953},"labels":[],"label_agreement":null},{"id":"W2060591289","doi":"10.1038/sj.jcbfm.9600294","title":"The Relationship between Diffusion Anisotropy and Time of Onset after Stroke","year":2006,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Medicine; White matter; Stroke (engine); Effective diffusion coefficient; Nuclear medicine; Nuclear magnetic resonance; Internal medicine; Pathology; Magnetic resonance imaging; Cardiology; Gastroenterology; Radiology; Physics","score_opus":0.02281011005075334,"score_gpt":0.28900441803984217,"score_spread":0.26619430798908883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060591289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99260515,0.0018786874,0.0030046874,0.002119553,0.000039174818,0.00016325433,0.000041559368,0.000019256104,0.00012869317],"genre_scores_gemma":[0.97085965,0.00012994783,0.027893675,0.000081953374,0.00039746598,0.000004782777,0.0000052001024,0.000017954546,0.0006093499],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989164,0.000053603144,0.00050692866,0.000105621846,0.0002715029,0.000145943],"domain_scores_gemma":[0.99884516,0.00035922354,0.00034831063,0.00022259091,0.00013952727,0.00008519441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023731378,0.00011377392,0.0003274135,0.00009711875,0.00010980585,0.000020043382,0.00010324912,0.000056725094,0.000016729315],"category_scores_gemma":[0.00015456318,0.00007223672,0.00013762547,0.0001323184,0.000115522686,0.00011541082,0.000043392305,0.00032057002,0.000002647648],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025372722,0.00025204913,0.97028995,0.00002955073,0.00009029865,0.000022529119,0.00007463686,0.0000067682518,0.018585706,0.005071403,0.0015303444,0.0037930585],"study_design_scores_gemma":[0.0012461124,0.00012615902,0.9710759,0.00005531892,0.00056575314,0.00016708003,0.000008950638,0.00005862511,0.006148941,0.013485274,0.006989331,0.00007258617],"about_ca_topic_score_codex":0.000006352421,"about_ca_topic_score_gemma":7.186441e-7,"teacher_disagreement_score":0.024888989,"about_ca_system_score_codex":0.00000783554,"about_ca_system_score_gemma":0.00003744158,"threshold_uncertainty_score":0.2945728},"labels":[],"label_agreement":null},{"id":"W2060830357","doi":"10.1016/j.media.2011.10.001","title":"Tumor invasion margin on the Riemannian space of brain fibers","year":2011,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Athabasca University; University of Alberta","funders":"","keywords":"Geodesic; Glioma; Margin (machine learning); Diffusion MRI; Magnetic resonance imaging; Fiber tract; Lesion; Brain tumor; Infiltration (HVAC); Computer science; Medicine; Mathematics; Pathology; Radiology; Mathematical analysis; Physics; Cancer research","score_opus":0.07676911403623363,"score_gpt":0.3431612832338788,"score_spread":0.2663921691976452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060830357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5488384,0.00010379298,0.22568454,0.17880367,0.000040332063,0.00094603,0.000028096749,0.0003863201,0.04516882],"genre_scores_gemma":[0.97568136,0.000041758394,0.01621716,0.0068510454,0.00004192521,0.000040186347,0.000017860217,0.000018178465,0.0010905074],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99887234,0.000056301953,0.00023953522,0.00023713543,0.0004411292,0.00015358614],"domain_scores_gemma":[0.99883366,0.00021337968,0.00010501842,0.0006175912,0.000065838234,0.00016450018],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00038107755,0.00010324829,0.0002838016,0.00016574166,0.000059347756,0.0000046202126,0.00020576672,0.0000384503,0.0022105873],"category_scores_gemma":[0.0008294351,0.00006271633,0.00022684534,0.0009222735,0.00027747423,0.00003263641,0.000064789245,0.00025051075,0.000038244718],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011713195,0.0067782803,0.110115506,0.0005516649,0.005479281,0.0031818943,0.005528027,0.000018854444,0.11989139,0.07372029,0.5820141,0.09154944],"study_design_scores_gemma":[0.0035996914,0.0017810172,0.2708242,0.0010127712,0.009852976,0.00022080881,0.0018004936,0.030676018,0.5332184,0.020983428,0.12471298,0.0013172474],"about_ca_topic_score_codex":0.00010784767,"about_ca_topic_score_gemma":0.000012167523,"teacher_disagreement_score":0.45730108,"about_ca_system_score_codex":0.000016597669,"about_ca_system_score_gemma":0.000036249778,"threshold_uncertainty_score":0.9987015},"labels":[],"label_agreement":null},{"id":"W2060887411","doi":"10.1097/wnr.0000000000000247","title":"Cerebellum-specific 18F-FDG PET analysis for the detection of subregional glucose metabolism changes in spinocerebellar ataxia","year":2014,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Spinocerebellar ataxia; Spatial normalization; Cerebellum; Pet imaging; Normalization (sociology); Neuroscience; Nuclear medicine; Cerebellar cortex; Ataxia; Positron emission tomography; Medicine; Biology; Magnetic resonance imaging; Radiology","score_opus":0.06487165848581244,"score_gpt":0.3206678162297925,"score_spread":0.25579615774398007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060887411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77712935,0.0006900818,0.2147882,0.00473807,0.00019015296,0.0015225986,0.000030265963,0.00020906472,0.0007022069],"genre_scores_gemma":[0.995928,0.00045858853,0.0025584954,0.0004545127,0.00015182559,0.00018817312,0.000032540625,0.000027777123,0.00020008427],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998819,0.000027843602,0.00036247447,0.00037593185,0.0002272101,0.00018753747],"domain_scores_gemma":[0.998698,0.00015233131,0.0002695408,0.0006993022,0.0001255689,0.000055248598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002751623,0.0001402197,0.00035176123,0.00024029368,0.00008416108,0.000009087415,0.00013274458,0.00002958107,0.000018696705],"category_scores_gemma":[0.00010518684,0.00010672314,0.00019159263,0.0007409119,0.00010080726,0.00003902856,0.000041601146,0.0001716568,0.000002099677],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007971388,0.0010991107,0.17597865,0.00030835325,0.00065916573,0.00019437207,0.00026745358,0.00068609643,0.69304645,0.014312781,0.0030524775,0.10959798],"study_design_scores_gemma":[0.0006654323,0.00018112315,0.42435217,0.000016313603,0.00063764123,0.00035294346,0.000020920068,0.005185959,0.14503925,0.0015616242,0.42180732,0.00017932581],"about_ca_topic_score_codex":0.00004011359,"about_ca_topic_score_gemma":0.00006434905,"teacher_disagreement_score":0.5480072,"about_ca_system_score_codex":0.000019451407,"about_ca_system_score_gemma":0.000022218836,"threshold_uncertainty_score":0.43520436},"labels":[],"label_agreement":null},{"id":"W2060995849","doi":"10.1016/j.pediatrneurol.2012.09.005","title":"Diffusion Tensor Imaging of Sports-Related Concussion in Adolescents","year":2013,"lang":"en","type":"article","venue":"Pediatric Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary; Child and Family Research Institute; University of British Columbia Hospital; University of British Columbia","funders":"","keywords":"Concussion; Fractional anisotropy; Diffusion MRI; White matter; Athletes; Medicine; Physical therapy; Poison control; Psychology; Injury prevention; Magnetic resonance imaging; Radiology","score_opus":0.01501533166526708,"score_gpt":0.28747167375349775,"score_spread":0.27245634208823066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060995849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99541444,0.00013911109,0.00026332072,0.0031279454,0.000068451496,0.00050270685,0.0000011942128,0.000109126704,0.00037369557],"genre_scores_gemma":[0.99811286,0.00030715286,0.00039877676,0.0010084962,0.000055332086,0.000035021516,0.0000045342713,0.000020308136,0.000057548874],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990502,0.000027490025,0.00033911548,0.00026208966,0.00011938192,0.00020174368],"domain_scores_gemma":[0.99945456,0.000028832532,0.00013863208,0.0002528433,0.000055706092,0.000069451584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051409206,0.000101736405,0.00021666454,0.00022058947,0.000021942831,0.0000020328775,0.000078822835,0.000059562757,0.00007093335],"category_scores_gemma":[0.000056477646,0.000085534026,0.00004484056,0.00031606056,0.00005250313,0.000038800346,0.00006905976,0.0002835504,0.000020519326],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032239383,0.00012841912,0.9907748,0.000034348814,4.963543e-7,0.000035486304,0.000012622243,0.0000036102322,0.0038295584,0.0000597008,0.0004478715,0.0046408167],"study_design_scores_gemma":[0.0007916928,0.00007546959,0.9958134,0.00001758039,0.000022731354,0.000083275874,0.0000027519225,0.001259595,0.0001906504,0.0014626667,0.00021428484,0.00006586543],"about_ca_topic_score_codex":0.00003524918,"about_ca_topic_score_gemma":2.156813e-7,"teacher_disagreement_score":0.0050386055,"about_ca_system_score_codex":0.000008171185,"about_ca_system_score_gemma":0.000019803147,"threshold_uncertainty_score":0.34879762},"labels":[],"label_agreement":null},{"id":"W2061108093","doi":"10.1002/mrm.22019","title":"Robust correction of spike noise: Application to diffusion tensor imaging","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Heart and Stroke Foundation; University of Toronto; Health Sciences Centre; Sunnybrook Health Science Centre","funders":"","keywords":"Computer science; Diffusion MRI; Outlier; Artificial intelligence; Noise (video); Redundancy (engineering); Pattern recognition (psychology); Spike (software development); Noise reduction; Normalization (sociology); Computer vision; Algorithm; Magnetic resonance imaging; Image (mathematics)","score_opus":0.03172189684513755,"score_gpt":0.32552512427018004,"score_spread":0.2938032274250425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061108093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.62373877,0.008270794,0.26154634,0.08172079,0.00041781666,0.0048700697,0.000008509188,0.0005958124,0.01883106],"genre_scores_gemma":[0.9769073,0.0005231951,0.018209562,0.002950788,0.00017928758,0.00012316566,0.00001540392,0.000021053853,0.0010702073],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998685,0.000017310656,0.00043418157,0.000371263,0.00027869391,0.00021355678],"domain_scores_gemma":[0.9991381,0.000054760847,0.00009823561,0.00048805756,0.00011698585,0.00010384448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018026358,0.00014520595,0.00032782566,0.00024173448,0.000038566217,0.0000029184207,0.00012277767,0.00004028666,0.000050965347],"category_scores_gemma":[0.00022508604,0.00012321168,0.000031676715,0.00073470594,0.00009692893,0.000038329148,0.00002485685,0.0001977159,0.000008477182],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001363773,0.00018039008,0.0507952,0.000025303068,4.0503093e-7,0.0000124656735,0.00014297491,0.0001350863,0.10516135,0.0002588219,0.005220992,0.8379306],"study_design_scores_gemma":[0.0012065485,0.0008273105,0.8912441,0.00067648175,0.000026544934,0.000064418135,0.000085818705,0.023441296,0.0025527058,0.00082525326,0.07890933,0.00014019446],"about_ca_topic_score_codex":0.00010036995,"about_ca_topic_score_gemma":0.0000058138085,"teacher_disagreement_score":0.8404489,"about_ca_system_score_codex":0.0000661599,"about_ca_system_score_gemma":0.000018945435,"threshold_uncertainty_score":0.50244266},"labels":[],"label_agreement":null},{"id":"W2061222352","doi":"10.1007/s004010100458","title":"Differential passage of [14C]sucrose and [3H]inulin across rat blood-brain barrier after cerebral ischemia","year":2001,"lang":"en","type":"article","venue":"Acta Neuropathologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Institute for Biological Sciences","funders":"","keywords":"Inulin; Ischemia; Blood–brain barrier; Biophysics; Chemistry; Vesicular transport protein; Sucrose; Diffusion; Vesicle; Pathology; Internal medicine; Biology; Medicine; Biochemistry; Membrane; Central nervous system","score_opus":0.031025491483959732,"score_gpt":0.3210774926010767,"score_spread":0.290052001117117,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061222352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99502057,0.000074705276,0.00063862425,0.0028904548,0.000047572496,0.00038082752,0.000056431236,0.00021681335,0.0006739918],"genre_scores_gemma":[0.9937198,0.00016315153,0.002462227,0.0020415434,0.00010058248,0.00008500638,0.000016762386,0.000039311293,0.0013715801],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985378,0.00006614957,0.00031977892,0.0005327331,0.00017921085,0.00036433575],"domain_scores_gemma":[0.9989574,0.000111239795,0.00012818346,0.0005842775,0.000057041154,0.00016183671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000097952936,0.00023856551,0.00035512663,0.00004468387,0.00010825355,0.000028942906,0.00016959653,0.00011133106,0.00021673502],"category_scores_gemma":[0.00022756202,0.00018797549,0.000105904,0.00017844434,0.00032574288,0.000093801136,0.00022548599,0.00037339624,0.0000070060855],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023669389,0.00025033703,0.063554384,0.00003347436,0.00000697876,0.0007774021,0.00013955105,1.8042851e-7,0.9320367,0.000077274715,0.00085315894,0.0020338856],"study_design_scores_gemma":[0.0033961828,0.0012640142,0.52072,0.000114920396,0.00023877755,0.003525799,0.00008653935,0.00012501546,0.41184482,0.0009443911,0.057085693,0.0006538851],"about_ca_topic_score_codex":0.0000021179942,"about_ca_topic_score_gemma":7.182311e-7,"teacher_disagreement_score":0.52019185,"about_ca_system_score_codex":0.000007725294,"about_ca_system_score_gemma":0.000013673728,"threshold_uncertainty_score":0.7665418},"labels":[],"label_agreement":null},{"id":"W2062073930","doi":"10.1111/j.1749-6632.2009.05063.x","title":"MRI Measures of Alzheimer's Disease and the AddNeuroMed Study","year":2009,"lang":"en","type":"article","venue":"Annals of the New York Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":128,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Commission","keywords":"Neuroimaging; Alzheimer's disease; Magnetic resonance imaging; Pipeline (software); Protocol (science); Medicine; Disease; Nuclear medicine; Psychology; Computer science; Artificial intelligence; Pathology; Radiology; Neuroscience","score_opus":0.260902865287491,"score_gpt":0.42548356885769506,"score_spread":0.16458070357020405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062073930","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71568936,0.005485467,0.00006477536,0.27706793,0.00001659042,0.0011423305,0.000007764239,0.000032070817,0.00049369945],"genre_scores_gemma":[0.99646986,0.0004727487,0.00063717563,0.0023322804,0.000026414213,0.0000051280144,6.2617204e-8,0.0000028093948,0.00005349766],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9990133,0.000055431596,0.00025071396,0.00017016444,0.0004009717,0.000109400375],"domain_scores_gemma":[0.9993934,0.000103607876,0.00023842978,0.00015564357,0.00003287342,0.00007603976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005653588,0.000073693795,0.00021194937,0.00004978088,0.00010934873,0.0000049921923,0.00041380845,0.000017476912,0.0000024079197],"category_scores_gemma":[0.00015898228,0.000035869,0.00008070863,0.00040413742,0.001087218,0.000055287663,0.00006632325,0.00011719086,1.7157087e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003865355,0.0046777693,0.12790428,0.00019860438,0.00069787557,0.0000038339103,0.008348758,0.0011839658,0.17679611,0.17917596,0.24908249,0.24806501],"study_design_scores_gemma":[0.0012807916,0.00069637195,0.7445061,0.00024310942,0.00042271265,0.000008437323,0.00036797248,0.00033859367,0.13385566,0.11301498,0.0051323273,0.00013290026],"about_ca_topic_score_codex":0.000018184788,"about_ca_topic_score_gemma":1.7587195e-7,"teacher_disagreement_score":0.6166019,"about_ca_system_score_codex":7.29099e-7,"about_ca_system_score_gemma":0.000038806385,"threshold_uncertainty_score":0.40059003},"labels":[],"label_agreement":null},{"id":"W2062097146","doi":"10.1109/bmei.2011.6098483","title":"Estimation of orientation distribution function using spherical ridgelet basis with minimum L&lt;inf&gt;2&lt;/inf&gt; norm","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Orientation (vector space); Diffusion MRI; Angular resolution (graph drawing); Basis function; Image resolution; Norm (philosophy); Artificial intelligence; Mathematics; Computer science; Physics; Nuclear magnetic resonance; Magnetic resonance imaging; Mathematical analysis; Geometry; Combinatorics","score_opus":0.06009109494979183,"score_gpt":0.31535724471641574,"score_spread":0.25526614976662393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062097146","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35204795,0.000009917814,0.64573985,0.00011217771,0.000034898334,0.00038545785,0.000021376689,0.00018049007,0.0014679108],"genre_scores_gemma":[0.8469514,0.000011647187,0.1523505,0.00010898361,0.000045617515,0.000048636666,0.0003290602,0.000023911407,0.00013020681],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988191,0.000021087082,0.00036664974,0.00031960403,0.00027630318,0.00019722935],"domain_scores_gemma":[0.9990494,0.00003537287,0.00023370233,0.00035826492,0.00022484502,0.000098393866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010432176,0.00017118495,0.00023184881,0.000060695922,0.000108111984,0.000010455557,0.00006193354,0.00007751736,0.0001641259],"category_scores_gemma":[0.00005788378,0.00014201248,0.00006351449,0.00048656703,0.000113775335,0.00026483636,0.000028512255,0.00011749766,0.000012739031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005493128,0.0041021197,0.060561813,0.0008002418,0.0003592634,0.000050173498,0.0012785129,0.0038053517,0.54973966,0.1167234,0.0118811205,0.24520521],"study_design_scores_gemma":[0.00490803,0.0038926601,0.24269336,0.00047585284,0.0017094165,0.0003533871,0.0003605648,0.27651063,0.4497644,0.0065859947,0.011655644,0.0010900509],"about_ca_topic_score_codex":0.000052722076,"about_ca_topic_score_gemma":0.0000075850057,"teacher_disagreement_score":0.4949035,"about_ca_system_score_codex":0.00011227652,"about_ca_system_score_gemma":0.000060667026,"threshold_uncertainty_score":0.5791101},"labels":[],"label_agreement":null},{"id":"W2062170532","doi":"10.1016/s0361-9230(00)00434-2","title":"Maturation of white matter in the human brain: a review of magnetic resonance studies","year":2001,"lang":"en","type":"review","venue":"Brain Research Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":871,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fondation Brain Canada","keywords":"White matter; Diffusion MRI; Magnetic resonance imaging; Magnetization transfer; Psychology; Grey matter; T2 relaxation; Nuclear magnetic resonance; Diffusion imaging; Tractography; Neuroscience; Brain Structure and Function; Brain development; Relaxation (psychology); Neuroimaging; Medicine; Physics; Radiology","score_opus":0.3087303040642021,"score_gpt":0.5306154438457288,"score_spread":0.22188513978152669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062170532","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000040252808,0.92235917,0.000011264937,0.07174868,0.0000068398,0.003263449,0.000023912868,0.000018648689,0.0025640095],"genre_scores_gemma":[0.000004233603,0.9886959,0.0011386869,0.002882142,0.00007398461,0.0011708614,0.000060725994,0.000044339406,0.005929118],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.996477,0.0010287026,0.0009867569,0.00043551,0.00073245016,0.00033957],"domain_scores_gemma":[0.996594,0.0015646637,0.00031017174,0.0011058646,0.00038273606,0.00004256506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032653967,0.00023849694,0.001363971,0.00033837816,0.00011498807,0.0000081998605,0.0005253537,0.00010643777,0.0004950065],"category_scores_gemma":[0.0015569482,0.00015283932,0.00024820145,0.0013092741,0.00045372412,0.000015349151,0.00026981687,0.0009808943,0.000057818877],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009062443,0.00012675606,0.000027568383,0.14051288,0.000011302396,0.00003658635,0.000092111455,1.4766617e-8,0.000007715495,0.00070150604,0.6733456,0.18512887],"study_design_scores_gemma":[0.00012196781,0.00014475788,0.00028431826,0.15821424,0.00005080988,0.000085818276,0.000033474742,1.8015426e-7,0.0000011295804,0.00027690225,0.84069824,0.00008818576],"about_ca_topic_score_codex":0.000015852662,"about_ca_topic_score_gemma":0.0000025470906,"teacher_disagreement_score":0.18504068,"about_ca_system_score_codex":0.00007688014,"about_ca_system_score_gemma":0.00010794866,"threshold_uncertainty_score":0.6232606},"labels":[],"label_agreement":null},{"id":"W2062776012","doi":"10.1002/mrm.21936","title":"Myelin water measurement in the spinal cord","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Calgary; University of Alberta","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Multiple sclerosis; Myelin; Spinal cord; Magnetic resonance imaging; White matter; Lumbar; Context (archaeology); T2 relaxation; Nuclear medicine; Medicine; Nuclear magnetic resonance; Biomedical engineering; Anatomy; Central nervous system; Neuroscience; Radiology; Biology; Physics; Internal medicine","score_opus":0.1187628976268697,"score_gpt":0.38112381621288133,"score_spread":0.2623609185860116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062776012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5351776,0.032767612,0.002649999,0.406503,0.0001491571,0.0031319864,0.0000015505858,0.00020934544,0.019409785],"genre_scores_gemma":[0.9876535,0.00072042784,0.001997268,0.009161701,0.00015997818,0.00010147176,0.0000030483163,0.000009365773,0.00019326598],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99852556,0.00004598936,0.00035917643,0.0002727618,0.0005030443,0.00029346268],"domain_scores_gemma":[0.99938935,0.000018590275,0.000028196968,0.00046162697,0.000056346977,0.00004587587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076023984,0.00013243768,0.00024511703,0.00011786717,0.00003282482,0.0000049304526,0.00019769713,0.000037878683,0.000079078185],"category_scores_gemma":[0.0001309426,0.000070585535,0.000025514777,0.00031601335,0.00012362695,0.000024705658,0.000015289294,0.00033954278,0.000014538953],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063695444,0.00031956472,0.006718277,0.000035645902,7.5769356e-7,0.00031943587,0.00046414637,0.0000027683202,0.021444274,0.0015955861,0.0068068258,0.96165574],"study_design_scores_gemma":[0.0020713357,0.0041363006,0.6760705,0.0008829479,0.00001907098,0.00015059007,0.00015140983,0.00023871407,0.0010717491,0.0096963225,0.3053779,0.00013316634],"about_ca_topic_score_codex":0.000050939158,"about_ca_topic_score_gemma":0.000017149552,"teacher_disagreement_score":0.9615226,"about_ca_system_score_codex":0.000065931294,"about_ca_system_score_gemma":0.000018858069,"threshold_uncertainty_score":0.28783944},"labels":[],"label_agreement":null},{"id":"W2062791478","doi":"10.3389/fninf.2014.00008","title":"Dipy, a library for the analysis of diffusion MRI data","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1462,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Eye Institute; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Diffusion; Data science; Information retrieval; Physics","score_opus":0.0558102439165102,"score_gpt":0.3277539162915454,"score_spread":0.2719436723750352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062791478","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006219411,0.000069129266,0.98932976,0.0026044308,0.00012084022,0.00061745045,0.00013913489,0.00008712112,0.00081271894],"genre_scores_gemma":[0.14892355,0.001576641,0.84528553,0.0027168426,0.000093418115,0.00007919694,0.00090346107,0.00004602886,0.00037532032],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993048,0.000010548906,0.00033294567,0.00011625827,0.00011680701,0.000118683514],"domain_scores_gemma":[0.9985059,0.00019057331,0.00014083547,0.0011105062,0.0000172097,0.000034997312],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001271762,0.000077918,0.0002512822,0.00021050633,0.000048328824,0.000012159382,0.00039464684,0.000026586285,0.0000032914766],"category_scores_gemma":[0.00014209081,0.00005339005,0.00007403376,0.00061897154,0.00006711702,0.00020894584,0.00019595568,0.000112727364,4.1361105e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029463504,0.00041270847,0.18663414,0.0005352843,0.00048001992,0.000002375187,0.00078962394,0.003923359,0.00023742487,0.0068960455,0.64040464,0.15938972],"study_design_scores_gemma":[0.0002607241,0.000039792678,0.011403311,0.000016815662,0.00039054936,0.0000013581277,0.0000654514,0.804363,0.00010226847,0.00072036526,0.18259068,0.0000456703],"about_ca_topic_score_codex":0.0000012271354,"about_ca_topic_score_gemma":4.877849e-7,"teacher_disagreement_score":0.80043966,"about_ca_system_score_codex":0.0000057118204,"about_ca_system_score_gemma":0.000017141105,"threshold_uncertainty_score":0.2177183},"labels":[],"label_agreement":null},{"id":"W2062848294","doi":"10.1038/jcbfm.2014.178","title":"Longitudinal Changes in Resting-State Brain Activity in a Capsular Infarct Model","year":2014,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute","funders":"","keywords":"Internal capsule; Medicine; Lesion; Thalamus; Positron emission tomography; Cardiology; Diaschisis; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Internal medicine; Psychology; Pathology; Cerebellum; Radiology; White matter","score_opus":0.04612121435652345,"score_gpt":0.3257840182514854,"score_spread":0.27966280389496195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062848294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97384894,0.00030130838,0.015415818,0.009897957,0.000062880325,0.00025147252,0.0000067931583,0.000035323985,0.00017947971],"genre_scores_gemma":[0.953763,0.0001638918,0.044821218,0.0008362381,0.0002509832,0.000016153748,0.0000015203149,0.000033052984,0.00011395369],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99846095,0.000109705965,0.0004888284,0.00025012225,0.0003440838,0.00034629178],"domain_scores_gemma":[0.9989267,0.000104332205,0.00034818257,0.0003166935,0.00013394632,0.00017012285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000822485,0.00020191613,0.00064164377,0.00046747673,0.000039919385,0.000021752134,0.00019415736,0.00007362706,0.000010438681],"category_scores_gemma":[0.0004759551,0.00017256543,0.00012646917,0.00044176012,0.00006247151,0.00024155094,0.00006895441,0.0008139977,0.0000015033972],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016171216,0.0037904694,0.16310239,0.00040099703,0.0002511286,0.00090655935,0.0023242836,0.030805673,0.63509524,0.0052181133,0.0022001183,0.15428789],"study_design_scores_gemma":[0.014884172,0.0008196231,0.62711275,0.0009612526,0.00051248726,0.001771529,0.00003834996,0.20715955,0.09826997,0.03779315,0.009878399,0.00079876004],"about_ca_topic_score_codex":0.000050173843,"about_ca_topic_score_gemma":0.000105991494,"teacher_disagreement_score":0.5368253,"about_ca_system_score_codex":0.000037282258,"about_ca_system_score_gemma":0.00009913454,"threshold_uncertainty_score":0.70370144},"labels":[],"label_agreement":null},{"id":"W2062861273","doi":"10.1016/j.neuroimage.2003.09.026","title":"Focal white matter density changes in schizophrenia: reduced inter-hemispheric connectivity","year":2003,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; White matter; Internal capsule; Anterior commissure; Psychology; Magnetic resonance imaging; Splenium; Schizophreniform disorder; Neuroscience; Anatomy; Psychosis; Medicine; Schizoaffective disorder; Radiology; Psychiatry","score_opus":0.04078560463149062,"score_gpt":0.3139178719540914,"score_spread":0.27313226732260076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2062861273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788786,0.000023248214,0.006912699,0.00488503,0.00007872013,0.0004834137,0.000005124931,0.00023917522,0.008493975],"genre_scores_gemma":[0.9872477,0.000020827314,0.009180972,0.0026571439,0.000044221964,0.00007225831,0.000005049244,0.00004261256,0.0007291792],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988607,0.00007061793,0.00017772183,0.00048426757,0.00012044708,0.00028621752],"domain_scores_gemma":[0.99918973,0.000055048557,0.00006356491,0.00053929264,0.000046824054,0.000105540006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000105250016,0.00018304423,0.00027261165,0.00008024248,0.000057882065,0.000019410512,0.000094804716,0.00006054431,0.0002250013],"category_scores_gemma":[0.00013494841,0.00018054504,0.00006117735,0.0003309595,0.00008841936,0.000078380835,0.00006022043,0.00043203452,0.000073359224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031612103,0.00064866577,0.29783535,0.000116036674,0.000012194922,0.00041781977,0.00012303618,0.000004352123,0.6817674,0.00088356837,0.010910303,0.0069651487],"study_design_scores_gemma":[0.0022469687,0.00026713518,0.7499357,0.00011421916,0.000050253424,0.0008642373,0.000036057878,0.00028103052,0.22642788,0.0021441062,0.017192092,0.00044034328],"about_ca_topic_score_codex":0.000010003603,"about_ca_topic_score_gemma":0.000022238204,"teacher_disagreement_score":0.45533952,"about_ca_system_score_codex":0.000052151507,"about_ca_system_score_gemma":0.000029836616,"threshold_uncertainty_score":0.7362413},"labels":[],"label_agreement":null},{"id":"W2063001897","doi":"10.1002/nbm.782","title":"The basis of anisotropic water diffusion in the nervous system – a technical review","year":2002,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4574,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Diffusion MRI; Anisotropy; White matter; Fractional anisotropy; Neuroscience; Nervous system; Diffusion; Spinal cord; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Physics; Medicine; Biology; Optics; Radiology; Thermodynamics","score_opus":0.09857988122117965,"score_gpt":0.3996108336205039,"score_spread":0.30103095239932426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063001897","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000029340497,0.9906184,0.00007552987,0.0052384925,0.000039354378,0.0029402326,0.000033193875,0.00007617091,0.000975682],"genre_scores_gemma":[0.000104534,0.9973308,0.00042364383,0.0005744733,0.00012634465,0.0010472997,0.00016354739,0.000039305072,0.00019006018],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99751586,0.00020178015,0.0011825041,0.0003756487,0.00041096524,0.00031327276],"domain_scores_gemma":[0.99799126,0.00041182616,0.000281691,0.001203218,0.000048123966,0.00006389301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007091627,0.00030947625,0.0016019304,0.00024386057,0.000065606255,0.000005630256,0.00055699446,0.00017679011,0.00007894923],"category_scores_gemma":[0.0001808949,0.00011607422,0.00025236036,0.001098477,0.00026302846,0.000015773903,0.0001277162,0.0007035911,0.000020994534],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004688248,0.0001582409,0.000008985225,0.048700247,0.000011095914,0.00010195971,0.000019950467,1.22894654e-8,0.000028955546,0.00033795784,0.01742424,0.93320364],"study_design_scores_gemma":[0.00021140379,0.0001257231,0.00003644848,0.11352743,0.0003462301,0.00057839125,0.000015377216,0.0000066842567,0.0000022050033,0.000023044722,0.8850324,0.00009465241],"about_ca_topic_score_codex":0.000026295405,"about_ca_topic_score_gemma":0.0000053244894,"teacher_disagreement_score":0.933109,"about_ca_system_score_codex":0.00018937844,"about_ca_system_score_gemma":0.000050109207,"threshold_uncertainty_score":0.4733369},"labels":[],"label_agreement":null},{"id":"W2063414088","doi":"10.1089/neu.2010.1721","title":"Bimanual Coordination and Corpus Callosum Microstructure in Young Adults with Traumatic Brain Injury: A Diffusion Tensor Imaging Study","year":2011,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"Vlaamse regering; Fonds Wetenschappelijk Onderzoek; Australian Government","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Traumatic brain injury; Motor coordination; Sensory system; White matter; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.06213891591036967,"score_gpt":0.34266421574404854,"score_spread":0.28052529983367885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063414088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997067,0.000045439134,0.000834138,0.0011892704,0.00003960591,0.0007072703,0.0000036288268,0.00003279324,0.000080877624],"genre_scores_gemma":[0.995193,0.00002563677,0.004372828,0.00029534087,0.000038926715,0.000014086295,0.0000011310968,0.000029697278,0.000029377548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998968,0.000052972675,0.00041899164,0.000203368,0.00019454375,0.00016213873],"domain_scores_gemma":[0.9992173,0.00004126386,0.00031552094,0.0001764209,0.00014732651,0.00010221663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013866145,0.00015717177,0.00029841647,0.00027530963,0.000059873782,0.000019552619,0.00009837773,0.000028722292,0.0000070745655],"category_scores_gemma":[0.00006999954,0.00011409386,0.00004056453,0.00023929808,0.00007309248,0.00017948987,0.000031182262,0.00042186052,3.746776e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017430553,0.0009644302,0.93476444,0.00007599825,0.000018204342,0.00055618654,0.0048957523,0.0000012416186,0.029030005,0.000038498103,0.00018855269,0.02772365],"study_design_scores_gemma":[0.0032535014,0.0019894307,0.98826677,0.0002868152,0.00006440356,0.003474456,0.0010833179,0.00041058607,0.0007186614,0.00023678633,0.000098539625,0.00011672824],"about_ca_topic_score_codex":0.00005774033,"about_ca_topic_score_gemma":0.00003535962,"teacher_disagreement_score":0.053502347,"about_ca_system_score_codex":0.000036520978,"about_ca_system_score_gemma":0.000025998292,"threshold_uncertainty_score":0.46526125},"labels":[],"label_agreement":null},{"id":"W2063571138","doi":"10.1002/mrm.24235","title":"Fast diffusion tensor imaging and tractography of the whole cervical spinal cord using point spread function corrected echo planar imaging","year":2012,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; H. Lundbeck A/S; Lundbeckfonden","keywords":"Echo-planar imaging; Diffusion MRI; Point spread function; Tractography; Nuclear magnetic resonance; Planar; Spinal cord; Conus medullaris; Point (geometry); Echo (communications protocol); Physics; Magnetic resonance imaging; Tensor (intrinsic definition); Nuclear medicine; Medicine; Radiology; Computer science; Optics; Mathematics","score_opus":0.03672965975405169,"score_gpt":0.3230837666907384,"score_spread":0.2863541069366867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063571138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701609,0.012806193,0.009335875,0.0058806366,0.00026164675,0.0008153423,0.000009164823,0.00009719804,0.0006330202],"genre_scores_gemma":[0.9934646,0.00029290913,0.0048043285,0.0011231017,0.0001955983,0.00002731768,0.0000074789336,0.000028492494,0.00005619344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985741,0.000055165117,0.00042675115,0.00029610604,0.00031009645,0.0003378119],"domain_scores_gemma":[0.9991588,0.00007890691,0.00015781911,0.00040622527,0.00007870774,0.0001195437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002441413,0.00019172725,0.0003423961,0.00019057673,0.00009618033,0.0000062949553,0.00011497066,0.00004153343,0.00004318637],"category_scores_gemma":[0.0001327652,0.00013144882,0.00005253556,0.00057055475,0.00043013718,0.00010309513,0.000065816275,0.0003795323,9.425877e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038198094,0.00013612778,0.73932153,0.000068027184,0.0000017061282,0.000010647892,0.00015677727,0.0000010302033,0.062675126,0.00008072038,0.00042423623,0.1967421],"study_design_scores_gemma":[0.0012684575,0.00033771567,0.98105335,0.0011361784,0.0000929902,0.00038926874,0.00044825187,0.0054554166,0.0004510506,0.00042423655,0.008817782,0.00012530797],"about_ca_topic_score_codex":0.00020411932,"about_ca_topic_score_gemma":0.0000061118444,"teacher_disagreement_score":0.24173182,"about_ca_system_score_codex":0.000042251482,"about_ca_system_score_gemma":0.000018225473,"threshold_uncertainty_score":0.53603274},"labels":[],"label_agreement":null},{"id":"W2064055696","doi":"10.1016/j.neuroimage.2007.03.015","title":"Minimum detectable change in water diffusion using 3-T magnetic resonance imaging","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Multiple Sclerosis Society; Health Research Board","keywords":"Fractional anisotropy; Diffusion MRI; Corpus callosum; Corticospinal tract; White matter; Putamen; Magnetic resonance imaging; Nuclear medicine; Optic radiation; Nuclear magnetic resonance; Effective diffusion coefficient; Psychology; Medicine; Physics; Neuroscience; Radiology","score_opus":0.07009384273387445,"score_gpt":0.35069178110586047,"score_spread":0.280597938371986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064055696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909611,0.00079110515,0.004572772,0.0010411451,0.0000764995,0.0006881537,0.0000030408971,0.0002481044,0.0016180794],"genre_scores_gemma":[0.98517674,0.00007584993,0.012024904,0.0022072487,0.00013377359,0.000033226523,0.000005947411,0.00005685732,0.00028545273],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99858975,0.000019022777,0.0002803566,0.00042143208,0.00017651099,0.0005129371],"domain_scores_gemma":[0.9993377,0.000038616985,0.000037329555,0.00044382384,0.000040779647,0.000101757854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018766381,0.0001668144,0.00019398265,0.00021154374,0.00008823237,0.000018044408,0.00011088893,0.000038162078,0.00006057777],"category_scores_gemma":[0.000032812928,0.00014144341,0.00005141,0.0002860885,0.000073245836,0.00015473223,0.00011902186,0.00028549283,0.000022093196],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007020043,0.000114709925,0.055329643,0.000024384262,2.654458e-7,0.00049097085,0.00013227138,6.3033053e-7,0.8869762,0.000029787328,0.000056852943,0.056774076],"study_design_scores_gemma":[0.0022407866,0.0002222951,0.61492807,0.00026157012,0.00004025525,0.00077659293,0.000046048153,0.017862946,0.29003856,0.00065855763,0.07243271,0.00049162516],"about_ca_topic_score_codex":0.00009588609,"about_ca_topic_score_gemma":0.000011079089,"teacher_disagreement_score":0.59693766,"about_ca_system_score_codex":0.00006170772,"about_ca_system_score_gemma":0.000010108772,"threshold_uncertainty_score":0.5767895},"labels":[],"label_agreement":null},{"id":"W2064143475","doi":"10.1016/j.nicl.2012.09.010","title":"Mesial temporal sclerosis is linked with more widespread white matter changes in temporal lobe epilepsy","year":2012,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Temporal lobe; White matter; Cingulum (brain); Diffusion MRI; Hippocampal sclerosis; Corpus callosum; Epilepsy; Fractional anisotropy; Anatomy; Tractography; Limbic system; Neuroscience; Pathology; Psychology; Medicine; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.16390137192324708,"score_gpt":0.40934046853501627,"score_spread":0.2454390966117692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064143475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95072645,0.000085998734,0.0016939556,0.044340283,0.00022632917,0.0011439426,0.000046978697,0.0003936423,0.0013424415],"genre_scores_gemma":[0.9514924,0.00013389718,0.02496677,0.021607803,0.0006711314,0.00014927318,0.000052570245,0.00011000271,0.00081615103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99739647,0.00013154648,0.0007255295,0.0007504705,0.00035338232,0.0006425954],"domain_scores_gemma":[0.9980088,0.00024254888,0.0002462011,0.0010049939,0.00009274559,0.00040469543],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047261216,0.00034759144,0.0006623479,0.00013215217,0.000082332204,0.00003469749,0.00024968476,0.00019856801,0.0003446147],"category_scores_gemma":[0.00014946975,0.00028445086,0.00017442605,0.00042532504,0.00042367258,0.00025550308,0.00017063279,0.0009830691,0.00018548434],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003100346,0.00066887843,0.97755194,0.00003571696,0.000011171838,0.00006843431,0.00010723973,4.7289913e-7,0.0011507286,0.000019471254,0.018372586,0.0017033446],"study_design_scores_gemma":[0.0017512878,0.0005109224,0.97126335,0.00018831073,0.00008155966,0.00013197337,0.00003371013,0.00012398155,0.0008850891,0.00007129844,0.024661222,0.00029727494],"about_ca_topic_score_codex":0.000029623505,"about_ca_topic_score_gemma":0.00001568384,"teacher_disagreement_score":0.023272814,"about_ca_system_score_codex":0.000038277758,"about_ca_system_score_gemma":0.00006156479,"threshold_uncertainty_score":0.9999608},"labels":[],"label_agreement":null},{"id":"W2064172315","doi":"10.1007/s00247-012-2428-9","title":"Diffusion tensor imaging and fiber tractography in brain malformations","year":2013,"lang":"en","type":"review","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Diffusion MRI; Tractography; Neuroradiology; White matter; Medicine; Neuroscience; Magnetic resonance imaging; Radiology; Neurology; Psychology; Psychiatry","score_opus":0.06199651685777737,"score_gpt":0.3736353183857824,"score_spread":0.31163880152800505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064172315","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00034585904,0.9961714,0.00043455872,0.00087645877,0.000043991582,0.0013581939,0.000026056416,0.000137665,0.0006058291],"genre_scores_gemma":[0.00003189264,0.99294806,0.005413083,0.0002633426,0.00030005325,0.0005396348,0.0001482347,0.00004333579,0.00031234062],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986131,0.00008058926,0.00055227015,0.00039767826,0.000068503854,0.00028785324],"domain_scores_gemma":[0.9988735,0.0003988528,0.00024392961,0.0003491303,0.000028879349,0.000105759405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011900275,0.0002764395,0.0010080327,0.00074766803,0.000060286726,0.000011989866,0.000113366565,0.00018875844,0.000077874436],"category_scores_gemma":[0.000103967475,0.00021494368,0.00018530537,0.0005495942,0.00008476535,0.00007610048,0.00006517467,0.00057836296,0.000054607142],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019051056,0.00006270933,0.0059754634,0.002580514,0.000009136492,0.000021574682,0.000019608067,1.596053e-7,8.55831e-7,0.00015180091,0.012651212,0.97852504],"study_design_scores_gemma":[0.00023641018,0.000030333507,0.0033289918,0.00026193925,0.00032481036,0.001230628,0.0000039591073,0.000044224787,3.488136e-8,0.0002906298,0.99405265,0.00019537333],"about_ca_topic_score_codex":0.00001221839,"about_ca_topic_score_gemma":3.5761494e-7,"teacher_disagreement_score":0.98140144,"about_ca_system_score_codex":0.00004040618,"about_ca_system_score_gemma":0.00005916102,"threshold_uncertainty_score":0.87651485},"labels":[],"label_agreement":null},{"id":"W2064222308","doi":"10.1016/j.neurobiolaging.2014.05.038","title":"Empowering imaging biomarkers of Alzheimer's disease","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; U.S. National Library of Medicine; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; National Institutes of Health; Servier; Innogenetics; Eli Lilly and Company; AstraZeneca; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Synarc; Roche; Abbott Fund; National Institute on Aging; Alzheimer's Association; Genentech Foundation; Alzheimer's Drug Discovery Foundation; Amorfix Life Sciences","keywords":"Atrophy; Biomarker; Alzheimer's disease; Medicine; Internal medicine; Cardiology; Disease; Pathology; Biology","score_opus":0.03521939433595887,"score_gpt":0.35274108243259944,"score_spread":0.31752168809664055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064222308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9808624,0.00036245832,0.012215516,0.0037374618,0.0001114581,0.00031091901,0.0000106137895,0.00022358012,0.0021656395],"genre_scores_gemma":[0.99264306,0.0000307542,0.006789291,0.0004639288,0.000027336207,0.000008136136,0.000009787591,0.000018561943,0.000009152034],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99930054,0.00003077454,0.00024137388,0.00022549146,0.000050503673,0.00015133679],"domain_scores_gemma":[0.9993134,0.00007323361,0.00014309837,0.00034751985,0.00005029063,0.00007242014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000098146935,0.000096018724,0.00022161164,0.00011538819,0.000034071738,0.0000015484081,0.00009099074,0.000018101715,0.00001098749],"category_scores_gemma":[0.000053290918,0.000090652575,0.00008282772,0.00011815154,0.00021557671,0.00003467682,0.00006778229,0.00009666884,0.0000016959077],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009711372,0.00017278707,0.41102877,0.00017318456,0.00008043873,0.000012027486,0.00007429651,0.00006946476,0.56587046,0.0029724212,0.0007480762,0.018700944],"study_design_scores_gemma":[0.0011509474,0.00021752543,0.57463765,0.00036023982,0.0003886741,0.00007800291,0.000035663277,0.002975341,0.40997598,0.0024183926,0.00746273,0.00029887017],"about_ca_topic_score_codex":0.0000068134996,"about_ca_topic_score_gemma":9.234625e-8,"teacher_disagreement_score":0.16360885,"about_ca_system_score_codex":0.000004550085,"about_ca_system_score_gemma":0.00001760383,"threshold_uncertainty_score":0.36967045},"labels":[],"label_agreement":null},{"id":"W2064604305","doi":"10.1016/j.ejrad.2008.04.048","title":"A comparison of rapid-scanning X-ray fluorescence mapping and magnetic resonance imaging to localize brain iron distribution","year":2008,"lang":"en","type":"article","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg; Royal University Hospital; University of Saskatchewan","funders":"University of Saskatchewan","keywords":"Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Pathology; Iron levels; In vivo; Susceptibility weighted imaging; Nuclear medicine; Radiology; Biology; Internal medicine","score_opus":0.0521245954782197,"score_gpt":0.32791722401583545,"score_spread":0.27579262853761577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064604305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64340264,0.0079717925,0.34260467,0.0053078835,0.000067924506,0.0002085661,0.000008382027,0.00004058668,0.00038756794],"genre_scores_gemma":[0.95276237,0.00032103827,0.046329368,0.00043176085,0.00010062953,0.0000011301254,0.000003785522,0.000016835329,0.000033078122],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988823,0.00019198937,0.0004915495,0.00016048468,0.00010492492,0.00016878652],"domain_scores_gemma":[0.9992326,0.0000981443,0.00026676344,0.00016914222,0.00010867209,0.00012469605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004054044,0.00010021058,0.00032955475,0.000099821285,0.00007939474,0.0000037765867,0.0001244238,0.000013020251,0.000007378574],"category_scores_gemma":[0.0002646565,0.00008990491,0.000049496688,0.0001723545,0.00023284077,0.000047214853,0.000051109462,0.00025308516,0.0000020953728],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046725353,0.00019138775,0.2186034,0.00008287355,0.000012912207,0.0011176148,0.002103613,0.00033104833,0.35719186,0.0005035901,0.04468402,0.37471044],"study_design_scores_gemma":[0.0014240576,0.0016821678,0.7957807,0.0005096415,0.000037276888,0.010379118,0.0002026487,0.00249696,0.003071471,0.000060576876,0.1841687,0.0001866431],"about_ca_topic_score_codex":0.0000012551333,"about_ca_topic_score_gemma":4.1820886e-8,"teacher_disagreement_score":0.57717735,"about_ca_system_score_codex":0.00003256823,"about_ca_system_score_gemma":0.00002673357,"threshold_uncertainty_score":0.36662158},"labels":[],"label_agreement":null},{"id":"W2065568422","doi":"10.1097/npt.0b013e3182a3d353","title":"Motor Skill Learning Is Associated With Diffusion Characteristics of White Matter in Individuals With Chronic Stroke","year":2013,"lang":"en","type":"article","venue":"Journal of Neurologic Physical Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BGC Engineering (Canada)","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Psychology; Stroke (engine); Physical medicine and rehabilitation; Internal capsule; Motor learning; Rehabilitation; Physical therapy; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.02487291509713849,"score_gpt":0.2957891210714161,"score_spread":0.27091620597427757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065568422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967296,0.000018240838,0.00043571048,0.002416597,0.00000816094,0.00029660508,0.0000061046057,0.000019189634,0.00006978141],"genre_scores_gemma":[0.9977243,0.00012481316,0.00056030496,0.0013455983,0.00007844793,0.000016043055,0.0000025582342,0.0000216101,0.00012631192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991115,0.00006318208,0.00027302682,0.00013515288,0.00025195477,0.00016519925],"domain_scores_gemma":[0.9990188,0.00010613516,0.0005315873,0.00014143193,0.00014031082,0.00006176081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070784045,0.00013289369,0.0004242497,0.00009051226,0.00003857452,0.000009427901,0.00011186664,0.00004057569,0.000055426623],"category_scores_gemma":[0.000022236876,0.00007544507,0.00007310212,0.00016598195,0.000084555286,0.00010220196,0.000026460586,0.00058002584,0.0000033196445],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031017762,0.0010653064,0.8517302,0.000012519077,0.000053496235,0.000037025347,0.0003071172,0.000042248434,0.14285809,0.00001147167,0.00011110935,0.0034612077],"study_design_scores_gemma":[0.001629916,0.0059442283,0.9885634,0.000082884515,0.000025481579,0.00006368338,0.000006960709,0.00045705715,0.0023217567,0.00041460825,0.00041175316,0.00007827463],"about_ca_topic_score_codex":0.000001653874,"about_ca_topic_score_gemma":7.946427e-8,"teacher_disagreement_score":0.14053634,"about_ca_system_score_codex":0.000028492303,"about_ca_system_score_gemma":0.00003053757,"threshold_uncertainty_score":0.30765605},"labels":[],"label_agreement":null},{"id":"W2065679937","doi":"10.3389/fnagi.2014.00142","title":"Correlations between Limbic White Matter and Cognitive Function in Temporal-Lobe Epilepsy, Preliminary Findings","year":2014,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates","keywords":"Fornix; Fractional anisotropy; Temporal lobe; Diffusion MRI; Cingulum (brain); Hippocampal sclerosis; White matter; Psychology; Limbic system; Neuroscience; Epilepsy; Neuropsychology; Hippocampus; Hippocampal formation; Mesial temporal lobe epilepsy; Cognition; Medicine; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.028998416454080186,"score_gpt":0.29729655322361,"score_spread":0.2682981367695298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065679937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6014995,0.0000539458,0.39413112,0.0028202676,0.00023989184,0.00046720318,0.0000069480493,0.00010302757,0.00067807717],"genre_scores_gemma":[0.98941827,0.000020542577,0.008304343,0.0016808748,0.000033749355,0.00005384827,0.000011937077,0.000017888104,0.0004585214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988642,0.00004596443,0.00022559665,0.00047585674,0.00014271554,0.0002457045],"domain_scores_gemma":[0.9995607,0.00007877684,0.0000664668,0.00019020532,0.000023146324,0.00008070187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020757849,0.00012477131,0.00019248859,0.00033993807,0.00011616163,0.00002899578,0.00009717428,0.000044865952,0.0000038019225],"category_scores_gemma":[0.00013682255,0.00012947046,0.000023605948,0.000605111,0.00022988221,0.00022898505,0.000077296296,0.0003322576,0.0000045980973],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019677711,0.000034346616,0.99551237,0.000016318283,5.7368584e-7,0.000004831737,0.000103193546,0.000020888543,0.0003142824,0.000033823824,0.0015045719,0.0024351534],"study_design_scores_gemma":[0.00039993902,0.00017178494,0.9880349,0.00017974932,0.000025846733,0.000019555651,0.00005104298,0.007962637,0.000117428324,0.0014823932,0.0014369835,0.00011774186],"about_ca_topic_score_codex":0.000009945584,"about_ca_topic_score_gemma":0.0000010265284,"teacher_disagreement_score":0.3879188,"about_ca_system_score_codex":0.000031162082,"about_ca_system_score_gemma":0.000019123017,"threshold_uncertainty_score":0.5279652},"labels":[],"label_agreement":null},{"id":"W2065883186","doi":"10.1002/hbm.20598","title":"Robust S1, S2, and thalamic activations in individual subjects with vibrotactile stimulation at 1.5 and 3.0 T","year":2008,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Thalamus; Functional magnetic resonance imaging; Somatosensory system; Sensory stimulation therapy; Neuroscience; Thalamic stimulator; Sensory system; Stimulation; Movement disorders; Psychology; Deep brain stimulation; Magnetic resonance imaging; Medicine; Radiology; Pathology; Parkinson's disease","score_opus":0.16101917893180656,"score_gpt":0.3273490108830669,"score_spread":0.16632983195126033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065883186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99165857,0.000024327755,0.0059760786,0.0010384402,0.0000031848522,0.00044257837,0.0000033995782,0.00011552328,0.0007379067],"genre_scores_gemma":[0.9908513,0.000018771736,0.008351589,0.0003126551,0.000028027498,0.000050255592,0.000050951774,0.000019069574,0.00031737142],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993676,0.000016631735,0.00012674465,0.00024824974,0.000104207764,0.00013658301],"domain_scores_gemma":[0.99961126,0.00009726082,0.00006034467,0.00016017347,0.000021736028,0.000049225415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056601555,0.00010006628,0.00013252898,0.00015914445,0.00030860212,0.000012480254,0.000031433465,0.000036813526,0.000016466347],"category_scores_gemma":[0.00003317979,0.000094783056,0.000010720557,0.00018083057,0.000090664806,0.00012849114,0.00005307673,0.00015120054,0.0000014258618],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004794278,0.00012881325,0.71031004,0.00009772436,0.000021984908,0.000055349003,0.0023798603,0.00034820617,0.2820218,0.0020189716,0.0016555018,0.00091378996],"study_design_scores_gemma":[0.0008401284,0.00006919255,0.99503094,0.000120233555,0.000009367413,0.00021831128,0.00009105452,0.0008385391,0.00062271353,0.0006500012,0.0013986566,0.000110887435],"about_ca_topic_score_codex":0.00001855075,"about_ca_topic_score_gemma":0.000022178512,"teacher_disagreement_score":0.28472084,"about_ca_system_score_codex":0.000042672706,"about_ca_system_score_gemma":0.00001635138,"threshold_uncertainty_score":0.3865141},"labels":[],"label_agreement":null},{"id":"W2066276013","doi":"10.1155/2012/143705","title":"Characterization of DTI Indices in the Cervical, Thoracic, and Lumbar Spinal Cord in Healthy Humans","year":2012,"lang":"en","type":"article","venue":"Radiology Research and Practice","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; International Spinal Research Trust","keywords":"Medicine; Lumbar; Spinal cord; Anatomy; Thoracic vertebrae; Lumbar vertebrae","score_opus":0.30846501872392934,"score_gpt":0.5519831817347898,"score_spread":0.24351816301086043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066276013","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97874665,0.0011305321,0.00021174403,0.018708536,0.000008633872,0.00043450706,0.0000032748032,0.000008373942,0.0007477595],"genre_scores_gemma":[0.99182886,0.0058918605,0.0012419441,0.00087671774,0.00006393735,0.00006479443,0.000013026789,0.0000051738725,0.000013676892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988186,0.0005447773,0.0001538331,0.00013660014,0.00011447546,0.00023170798],"domain_scores_gemma":[0.9989136,0.00074929575,0.0000655397,0.00015444249,0.000053751974,0.00006340301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021494525,0.00004834316,0.00013080756,0.00014400446,0.00007875603,0.0000079674965,0.00006564979,0.000056563993,0.0000074850213],"category_scores_gemma":[0.0006760616,0.000035504418,0.0000064079827,0.00028305227,0.000263156,0.00021502821,0.000039130875,0.0005015384,0.0000016042678],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0127919335,0.0017632752,0.69882315,0.000584863,0.000025696725,0.00007777716,0.0038619991,1.1815414e-7,0.1727095,0.031873014,0.000366193,0.07712247],"study_design_scores_gemma":[0.0003540948,0.0020315251,0.96862954,0.000038509555,0.000008850781,0.0006276594,0.00063620205,0.00001706639,0.0002869021,0.0007891953,0.026536506,0.00004396387],"about_ca_topic_score_codex":0.000059406102,"about_ca_topic_score_gemma":0.000010623087,"teacher_disagreement_score":0.26980636,"about_ca_system_score_codex":0.000014528416,"about_ca_system_score_gemma":0.00003269403,"threshold_uncertainty_score":0.21789627},"labels":[],"label_agreement":null},{"id":"W2066289270","doi":"10.1159/000089233","title":"Regional Variability in the Prevalence of Cerebral White Matter Lesions: An MRI Study in 9 European Countries (CASCADE)","year":2005,"lang":"en","type":"article","venue":"Neuroepidemiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"European Commission","keywords":"Medicine; Dementia; Population; Hyperintensity; European population; Disease; Demography; Gerontology; Pediatrics; Environmental health; Pathology; Magnetic resonance imaging","score_opus":0.10366682734672028,"score_gpt":0.3945010594416823,"score_spread":0.290834232094962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066289270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9640261,0.000036530466,0.0015518011,0.032392055,0.000018727815,0.0009163319,0.000010329321,0.00005138947,0.0009967573],"genre_scores_gemma":[0.9842421,0.000109023415,0.00351956,0.011863841,0.000075136144,0.000073777366,0.0000052963164,0.000016439975,0.00009483613],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99637675,0.0021955466,0.0005986876,0.0004557446,0.00011413686,0.00025914353],"domain_scores_gemma":[0.99808383,0.00093406014,0.00014589194,0.000753423,0.000040124556,0.000042679567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002479852,0.00013062092,0.00031449512,0.00009645307,0.000042330557,0.0000030468032,0.00030843852,0.000040998402,0.00008198557],"category_scores_gemma":[0.00047446837,0.00009300151,0.000043347278,0.00019610605,0.00021799574,0.00009357855,0.00008313656,0.00044405003,0.000017226184],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006273601,0.0005547807,0.99521506,0.000043947344,0.0000016018234,0.000016000364,0.0003988989,0.000116782256,0.00011261019,0.0013851642,0.0017359273,0.00035651994],"study_design_scores_gemma":[0.00041310283,0.00025811332,0.99107695,0.000025632577,0.000016685748,0.000099418976,0.000060179424,0.00046179583,0.000017623624,0.0010750453,0.006430684,0.00006477124],"about_ca_topic_score_codex":0.0000357855,"about_ca_topic_score_gemma":0.00004207962,"teacher_disagreement_score":0.020528216,"about_ca_system_score_codex":0.000027765753,"about_ca_system_score_gemma":0.000030584746,"threshold_uncertainty_score":0.37924916},"labels":[],"label_agreement":null},{"id":"W2066385232","doi":"10.1002/hbm.22018","title":"Callosal fiber length and interhemispheric connectivity in adults with autism: Brain overgrowth and underconnectivity","year":2012,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Corpus callosum; Psychology; Neuroscience; Tractography; Autism spectrum disorder; Brain size; Diffusion MRI; Fiber; Autism; Audiology; Anatomy; Biology; Magnetic resonance imaging; Developmental psychology; Medicine; Chemistry","score_opus":0.043277788979686434,"score_gpt":0.31120925597148474,"score_spread":0.2679314669917983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066385232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9845585,0.0001235388,0.0079530375,0.0047744485,0.000008767076,0.00045076103,0.0000031271218,0.00016027185,0.001967527],"genre_scores_gemma":[0.99462926,0.000011211608,0.0039726524,0.0010196009,0.00004741053,0.000055756875,0.0000073294564,0.000028663964,0.00022813569],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99905205,0.00005237226,0.00015369746,0.0003427994,0.00009669993,0.00030238018],"domain_scores_gemma":[0.9992597,0.0003002115,0.000066991866,0.00022089483,0.000015522362,0.00013666636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025276144,0.00017014293,0.0002470382,0.00007760772,0.00013675772,0.000018370905,0.000043267548,0.00006096092,0.000031922795],"category_scores_gemma":[0.00011350667,0.00015651624,0.000022059958,0.00016786816,0.00015530142,0.00021753497,0.00009043585,0.0002947016,0.0000016983598],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041115668,0.0008945165,0.7570591,0.0011062677,0.00009751529,0.00007991062,0.0071221595,0.0000052438095,0.13172643,0.07509097,0.003723263,0.022683457],"study_design_scores_gemma":[0.0017099286,0.00019962322,0.9878691,0.0005521889,0.000014245503,0.00024069918,0.00031587481,0.00036287153,0.0002573279,0.0039113676,0.0042968667,0.00026994688],"about_ca_topic_score_codex":0.00010066203,"about_ca_topic_score_gemma":0.00008043458,"teacher_disagreement_score":0.23080994,"about_ca_system_score_codex":0.00006738795,"about_ca_system_score_gemma":0.000016002206,"threshold_uncertainty_score":0.6382547},"labels":[],"label_agreement":null},{"id":"W2067121405","doi":"10.1017/s0033291715000239","title":"Resilience and corpus callosum microstructure in adolescence","year":2015,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; SickKids Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Hospital for Sick Children; Université de Montréal","funders":"Medical Research Council; Fondation de France; Bundesministerium für Bildung und Forschung; Assistance publique-Hôpitaux de Paris; Agence Nationale de la Recherche; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Fractional anisotropy; Psychology; White matter; Anterior cingulate cortex; Diffusion MRI; Neuroticism; Clinical psychology; Personality; Psychiatry; Medicine; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.13766458626818556,"score_gpt":0.4330908503318179,"score_spread":0.2954262640636323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067121405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9620193,0.0012495423,0.005164685,0.02610587,0.00011143689,0.00048266086,0.000002575056,0.00018241629,0.0046814918],"genre_scores_gemma":[0.98620087,0.00025047132,0.008433768,0.0048232162,0.00009319667,0.000021263266,0.000004071028,0.000007746124,0.00016542888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99910444,0.000022157968,0.00019569005,0.0003497894,0.00014942119,0.00017852832],"domain_scores_gemma":[0.99936885,0.000040891307,0.000042461485,0.00027276954,0.000047839087,0.00022716416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015273038,0.00010773164,0.00022252499,0.000061597035,0.000021238337,0.0000029182563,0.00009391765,0.00007179403,0.000020911035],"category_scores_gemma":[0.00038361322,0.000069861344,0.000012395349,0.00026406572,0.00042365378,0.00002692146,0.00003770749,0.00031369666,0.000006082706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001077995,0.00069919816,0.5888121,0.000105936815,0.0000072590024,0.0009193231,0.0006880551,0.000006744767,0.18640769,0.009028514,0.03416242,0.17808473],"study_design_scores_gemma":[0.0025188967,0.0010760752,0.9683873,0.00027800753,0.00001498218,0.0010801438,0.00011082123,0.00010176269,0.0004354488,0.01558987,0.010262001,0.00014465894],"about_ca_topic_score_codex":0.000014089277,"about_ca_topic_score_gemma":0.0000018788542,"teacher_disagreement_score":0.3795752,"about_ca_system_score_codex":0.000023735465,"about_ca_system_score_gemma":0.0000051163106,"threshold_uncertainty_score":0.28488627},"labels":[],"label_agreement":null},{"id":"W2067187753","doi":"10.1177/1073858407300598","title":"Neural Substrates of Blindsight After Hemispherectomy","year":2007,"lang":"en","type":"review","venue":"The Neuroscientist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Blindsight; Hemispherectomy; Psychology; Neuroscience; Cognitive psychology; Neural substrate; Neural correlates of consciousness; Cognitive science; Epilepsy; Visual perception; Perception; Cognition","score_opus":0.20662972790212267,"score_gpt":0.45329818095269264,"score_spread":0.24666845305056997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067187753","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021073126,0.99614614,0.00029109576,0.0000984573,0.00030544054,0.0010707094,0.00006576528,0.00014033644,0.0016713482],"genre_scores_gemma":[0.00077623606,0.9947492,0.0004910243,0.00025328744,0.00012636863,0.00013054756,0.000028588052,0.0000668557,0.0033778914],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985155,0.000045332003,0.00048268377,0.00042470152,0.00026459788,0.00026720148],"domain_scores_gemma":[0.9985296,0.0001654133,0.00028529525,0.0008712258,0.000058156056,0.00009030344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015227782,0.0002757034,0.00076019415,0.00010725865,0.00008328011,0.000027083226,0.00036610075,0.00008986906,0.000065965825],"category_scores_gemma":[0.000049205777,0.00016478132,0.00038583716,0.0007591922,0.00038642582,0.00003319953,0.000116405376,0.00049307593,0.000022309847],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038573988,0.0002949132,0.0000625697,0.00805817,0.000024762467,0.00019622975,0.00001446933,4.2453814e-7,0.00040648627,0.000446438,0.0037121577,0.9867448],"study_design_scores_gemma":[0.00009225237,0.00004410494,0.00009398155,0.0012711129,0.00036068374,0.00046964505,7.769561e-7,0.000009757522,0.0003801926,0.000045022833,0.99710613,0.00012635857],"about_ca_topic_score_codex":0.0000028269508,"about_ca_topic_score_gemma":8.9071204e-7,"teacher_disagreement_score":0.99339396,"about_ca_system_score_codex":0.000021781936,"about_ca_system_score_gemma":0.00006771182,"threshold_uncertainty_score":0.67195874},"labels":[],"label_agreement":null},{"id":"W2067560632","doi":"10.1016/j.neuroimage.2012.11.065","title":"Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":168,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Human brain; Somatosensory system; Secondary somatosensory cortex; Cortex (anatomy); Cerebral cortex; Diffusion; Nuclear magnetic resonance; Anisotropy; Neuroscience; Chemistry; Physics; Psychology; Optics; Magnetic resonance imaging; Medicine","score_opus":0.09156158250146589,"score_gpt":0.4080880453359844,"score_spread":0.3165264628345185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067560632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9692724,0.000017227596,0.029393777,0.00031061366,0.000016636594,0.0006653125,0.000020330757,0.000033792578,0.00026992033],"genre_scores_gemma":[0.99397534,0.000007559201,0.0055155936,0.0003369323,0.00001438347,0.000062852756,0.000041738098,0.000014714955,0.000030874333],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99913526,0.000060558534,0.00026510566,0.00019031198,0.00015917896,0.00018958132],"domain_scores_gemma":[0.9992575,0.00021193801,0.00010830155,0.00036376985,0.000027127058,0.00003133013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002879336,0.00008561975,0.00020120305,0.00027581182,0.000055838147,0.000008104909,0.0001055036,0.000022932858,0.000018528961],"category_scores_gemma":[0.00005991025,0.0000690505,0.000102883205,0.0009972573,0.00004805315,0.00007035652,0.000021762658,0.000139348,4.769016e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003801963,0.00035993883,0.20209116,0.0000439371,0.000008281524,0.0000037706825,0.00038175686,0.00018966086,0.79574883,0.0008482962,0.000042579188,0.00024379755],"study_design_scores_gemma":[0.0008878271,0.000075360986,0.9698153,0.00002876242,0.00021681495,0.0000030165886,0.00008907001,0.008294713,0.019777345,0.00025036358,0.0004888616,0.000072552386],"about_ca_topic_score_codex":0.000053918826,"about_ca_topic_score_gemma":0.00005625476,"teacher_disagreement_score":0.7759715,"about_ca_system_score_codex":0.00002937354,"about_ca_system_score_gemma":0.0000109675375,"threshold_uncertainty_score":0.28157976},"labels":[],"label_agreement":null},{"id":"W2067685553","doi":"10.1007/s11682-013-9225-4","title":"Neuronal fiber bundle lengths in healthy adult carriers of the ApoE4 allele: A quantitative tractography DTI study","year":2013,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; DNA Genotek","keywords":"Tractography; Neuropsychology; Bundle; Allele; Neuroscience; Fiber bundle; Fiber; Diffusion MRI; Medicine; Psychology; Anatomy; Biology; Radiology; Magnetic resonance imaging; Genetics; Materials science; Cognition; Gene","score_opus":0.04570244697338806,"score_gpt":0.3642923779320556,"score_spread":0.31858993095866756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067685553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9903406,0.00009592577,0.00009033924,0.007887482,0.00002457637,0.0013454558,0.000014447621,0.000058248686,0.00014291875],"genre_scores_gemma":[0.9948489,0.000020407322,0.0033738103,0.0012150351,0.000013034682,0.00037627324,0.000004740582,0.000021863627,0.00012589962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903494,0.000063302,0.00025876553,0.00028603507,0.00016133646,0.00019560769],"domain_scores_gemma":[0.9993264,0.00010775221,0.00009543132,0.00029522378,0.00009515678,0.00008001213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009889393,0.00012913904,0.00019796919,0.000111740155,0.00009073429,0.000016236032,0.000099545854,0.000021957292,0.00003325229],"category_scores_gemma":[0.00008029136,0.000095789816,0.000065355496,0.00029900993,0.00018691624,0.00009259228,0.00004932354,0.0002787951,0.0000022036158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084760206,0.0025597801,0.93627876,0.00005335407,0.000012219356,0.000010816953,0.0016930163,0.0000020383968,0.012912822,0.00027482485,0.004074696,0.04204292],"study_design_scores_gemma":[0.0013620551,0.000480355,0.99357516,0.00005759777,0.00007309448,0.00003663649,0.0021524464,0.0001495322,0.0005637838,0.00015510156,0.0012679027,0.00012633334],"about_ca_topic_score_codex":0.0006171552,"about_ca_topic_score_gemma":0.00002825388,"teacher_disagreement_score":0.057296406,"about_ca_system_score_codex":0.0000133103795,"about_ca_system_score_gemma":0.000036895824,"threshold_uncertainty_score":0.39061952},"labels":[],"label_agreement":null},{"id":"W2067685645","doi":"10.1109/tip.2009.2035886","title":"On Approximation of Orientation Distributions by Means of Spherical Ridgelets","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Diffusion MRI; Voxel; Orientation (vector space); Computer science; Computation; Artificial intelligence; Visualization; Image resolution; Tractography; Multiresolution analysis; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Wavelet transform; Wavelet; Discrete wavelet transform; Geometry","score_opus":0.02645157815047293,"score_gpt":0.33669853003422534,"score_spread":0.3102469518837524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067685645","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033178292,0.00002019818,0.9648014,0.00087427156,0.000018382945,0.00029746565,0.00008238967,0.0001259877,0.00060165155],"genre_scores_gemma":[0.9237041,0.00001859332,0.0760066,0.00012558531,0.000009017672,0.000032392792,0.000035064975,0.00001232636,0.000056333112],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912864,0.000015458192,0.0003081121,0.00021167098,0.00021331427,0.00012279887],"domain_scores_gemma":[0.9993726,0.00003909004,0.00015882081,0.00020153576,0.00017334065,0.000054605378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056485405,0.000113350834,0.00018653234,0.00007777119,0.00011620866,0.000009801784,0.000057542355,0.0000461218,0.00002193957],"category_scores_gemma":[0.00001678667,0.00010830598,0.0000753481,0.0004243179,0.00009854051,0.00016236264,3.9662993e-7,0.00018381141,0.0000027328035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022537263,0.0018542873,0.000012157368,0.0001507038,0.00001174232,0.0000016161522,0.00016178514,0.00057319336,0.7813519,0.00070043735,0.00053353235,0.21442327],"study_design_scores_gemma":[0.0005890624,0.00047159207,0.00029631288,0.00020022104,0.00008307217,0.000014171272,0.00004410904,0.00853038,0.9871035,0.002427727,0.00013446446,0.00010534488],"about_ca_topic_score_codex":0.000003179634,"about_ca_topic_score_gemma":1.9451267e-7,"teacher_disagreement_score":0.8905258,"about_ca_system_score_codex":0.00005520722,"about_ca_system_score_gemma":0.000042265237,"threshold_uncertainty_score":0.44165897},"labels":[],"label_agreement":null},{"id":"W2068145240","doi":"10.1016/j.jpeds.2010.05.026","title":"Extreme Premature Birth is not Associated with Impaired Development of Brain Microstructure","year":2010,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Medicine; Gestation; Magnetic resonance imaging; Gestational age; Internal medicine; Pregnancy; Radiology; Biology","score_opus":0.03924320301362916,"score_gpt":0.29975218516747376,"score_spread":0.2605089821538446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068145240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99195665,0.00009630415,0.0035289621,0.0041001197,0.000053788433,0.00018107897,0.000017548686,0.000024405757,0.000041141393],"genre_scores_gemma":[0.955153,0.00006162992,0.043638434,0.0006959602,0.00018592727,0.0000011768882,0.0000029457644,0.000020601321,0.0002403562],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991378,0.000019878551,0.00034210394,0.00006876692,0.00030536274,0.00012606158],"domain_scores_gemma":[0.9986086,0.00014950996,0.0006067637,0.00021675995,0.00034340756,0.00007498653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003803478,0.00010332712,0.00021040537,0.00008914833,0.000074939635,0.0000063148887,0.00018579474,0.00007458567,0.000020299023],"category_scores_gemma":[0.00022335547,0.00005668916,0.000053668424,0.0003046468,0.000059453265,0.0000447024,0.00003177669,0.0006318499,6.2727435e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078289845,0.0003803583,0.04679005,0.0002427781,0.00007185031,0.00003395483,0.004435766,0.000019174327,0.9058976,0.00012274554,0.035073645,0.006149185],"study_design_scores_gemma":[0.0050507253,0.0011588993,0.629234,0.00025346,0.0011601256,0.0022390888,0.00038895683,0.00008868404,0.3229422,0.0022666696,0.0346539,0.00056327967],"about_ca_topic_score_codex":8.093407e-7,"about_ca_topic_score_gemma":0.0000041512385,"teacher_disagreement_score":0.5829554,"about_ca_system_score_codex":0.000025550244,"about_ca_system_score_gemma":0.00024179781,"threshold_uncertainty_score":0.27451086},"labels":[],"label_agreement":null},{"id":"W2068330969","doi":"10.1371/journal.pone.0056733","title":"The Relationship between Cortical Blood Flow and Sub-Cortical White-Matter Health across the Adult Age Span","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Nursing Research; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institutes of Health; Canadian Institutes of Health Research; Centre d'Imagerie BioMédicale","keywords":"White matter; Diffusion MRI; Cerebral blood flow; Neuroscience; Medicine; Young adult; Physiology; Pathology; Psychology; Cardiology; Magnetic resonance imaging; Internal medicine","score_opus":0.11822694693061801,"score_gpt":0.347580490753677,"score_spread":0.22935354382305895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068330969","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91022605,0.000068368616,0.0017904053,0.08674457,0.0000060049156,0.0008549807,0.000015021385,0.00012345123,0.0001711762],"genre_scores_gemma":[0.989177,0.00007352486,0.0069475435,0.0029884542,0.00013769194,0.00021552977,0.000020718933,0.000025498934,0.00041403944],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887836,0.000073083356,0.00027728302,0.00022384615,0.00022611015,0.0003213335],"domain_scores_gemma":[0.9983277,0.0008541097,0.00006365881,0.00050065253,0.00008125115,0.0001726418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018202793,0.00010923674,0.00019656811,0.00001330027,0.0006319581,0.00006444981,0.00011370169,0.000048582133,0.000020967009],"category_scores_gemma":[0.0004382164,0.00006361178,0.00003489221,0.0001233562,0.00029853862,0.00005669577,0.0000796535,0.00059258327,0.00010523645],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000921285,0.00026513205,0.99565697,0.000040182196,0.000032673284,0.0000021614642,0.00020436199,1.6562734e-7,0.00068988575,0.0011838501,0.001389888,0.00052551145],"study_design_scores_gemma":[0.00028778266,0.00010889495,0.994871,0.00008473379,0.00010720171,0.000012350085,0.000052950174,0.00034105574,0.00072911073,0.0032151388,0.00011758676,0.000072158255],"about_ca_topic_score_codex":0.000019809444,"about_ca_topic_score_gemma":0.000010909206,"teacher_disagreement_score":0.08375612,"about_ca_system_score_codex":0.000017894696,"about_ca_system_score_gemma":0.00002143747,"threshold_uncertainty_score":0.48605743},"labels":[],"label_agreement":null},{"id":"W2068562622","doi":"10.1016/j.neuroimage.2007.10.048","title":"Tactile-associated recruitment of the cervical cord is altered in patients with multiple sclerosis","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Fondazione Italiana Sclerosi Multipla","keywords":"Spinal cord; Multiple sclerosis; Cord; Medicine; Voxel; White matter; Magnetic resonance imaging; Functional magnetic resonance imaging; Lesion; Pathology; Radiology; Surgery; Psychiatry","score_opus":0.14085646941828112,"score_gpt":0.33817751071618235,"score_spread":0.19732104129790123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068562622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99678844,0.0000043117184,0.00047087963,0.00084014743,0.000038764516,0.0011585106,0.00003561387,0.0000667976,0.00059653644],"genre_scores_gemma":[0.9965895,0.000007844297,0.0017729286,0.0014543483,0.000012083607,0.00003698582,0.000011662456,0.000026465705,0.00008820042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900746,0.00002543383,0.00025349078,0.00024851758,0.00025486547,0.0002102053],"domain_scores_gemma":[0.99916327,0.000089024696,0.00014268268,0.00045510515,0.0000897098,0.000060210506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085012274,0.00011346513,0.0001823969,0.00005900486,0.000047382844,0.000005196547,0.00012703947,0.000038387585,0.00001843858],"category_scores_gemma":[0.00009278136,0.00007801859,0.000055343568,0.00038955797,0.00007771837,0.00004473051,0.00006787613,0.00023937182,0.0000029236269],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041315888,0.00076855934,0.9792271,0.000014478023,0.000007456394,0.0000037034101,0.00005833805,0.0000012196019,0.012828546,0.000029637253,0.00066341815,0.0059843794],"study_design_scores_gemma":[0.0019394013,0.0003228905,0.9735672,0.00008676993,0.000021100315,0.0000014249988,0.0000067484593,0.000062462,0.022005375,0.000036571088,0.0018827785,0.000067291934],"about_ca_topic_score_codex":0.000038626713,"about_ca_topic_score_gemma":0.000022163034,"teacher_disagreement_score":0.00917683,"about_ca_system_score_codex":0.00006248752,"about_ca_system_score_gemma":0.000018689907,"threshold_uncertainty_score":0.31815055},"labels":[],"label_agreement":null},{"id":"W2069243625","doi":"10.1016/j.neuroimage.2012.06.064","title":"Rapid whole cerebrum myelin water imaging using a 3D GRASE sequence","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":276,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Cerebrum; Sequence (biology); Myelin; Chemistry; Neuroscience; Biology; Central nervous system; Biochemistry","score_opus":0.132648105994973,"score_gpt":0.37151191621320556,"score_spread":0.23886381021823255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069243625","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9215004,0.0005561471,0.059377424,0.009946159,0.00038031556,0.0011922785,0.000059666905,0.0014034562,0.005584176],"genre_scores_gemma":[0.9519493,0.000043190437,0.043101102,0.0040203845,0.00033585913,0.000035129782,0.000038069255,0.00008047987,0.00039647662],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985099,0.000042293777,0.00025451859,0.00037079642,0.00020357719,0.00061893364],"domain_scores_gemma":[0.9989536,0.000030195808,0.000060577793,0.00065272703,0.00006611112,0.00023678548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016000746,0.00021204607,0.00021864183,0.000112598806,0.00017667936,0.000033533033,0.00013620158,0.00003509993,0.00014299063],"category_scores_gemma":[0.000048749433,0.00017015007,0.000094693336,0.00017307392,0.00013253423,0.0003805923,0.00013684087,0.00034343623,0.00018548108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019343639,0.0001343443,0.010685117,0.000034829467,0.00000410805,0.00007994595,0.00009839927,0.0000051178145,0.97673196,0.000100475765,0.0015642389,0.010542146],"study_design_scores_gemma":[0.001396102,0.00011820915,0.0140309725,0.00014140326,0.00021812515,0.0025022575,0.00006738954,0.0131569365,0.46911392,0.0007633686,0.49775732,0.0007340112],"about_ca_topic_score_codex":0.000019990837,"about_ca_topic_score_gemma":1.7802716e-7,"teacher_disagreement_score":0.507618,"about_ca_system_score_codex":0.00005427477,"about_ca_system_score_gemma":0.000024471577,"threshold_uncertainty_score":0.6938518},"labels":[],"label_agreement":null},{"id":"W2069494733","doi":"10.1371/journal.pone.0073021","title":"Diffusion Weighted Image Denoising Using Overcomplete Local PCA","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":447,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Agence Nationale de la Recherche","keywords":"Noise reduction; Pattern recognition (psychology); Artificial intelligence; Noise (video); Computer science; Diffusion; Principal component analysis; Filter (signal processing); Non-local means; Diffusion MRI; Signal-to-noise ratio (imaging); Diffusion process; Mathematics; Image denoising; Image (mathematics); Computer vision; Statistics; Physics; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.12655914984200248,"score_gpt":0.31722485969303177,"score_spread":0.1906657098510293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069494733","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8471729,0.000049649734,0.15004194,0.0011765286,0.0000063200655,0.00050853443,0.0000028744876,0.00029326216,0.00074799726],"genre_scores_gemma":[0.72865397,0.000026677486,0.2703631,0.00057880225,0.00008374907,0.000033132805,0.000012411433,0.00003219025,0.00021596506],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991931,0.000012002623,0.0001653022,0.00022392618,0.00020635583,0.00019934966],"domain_scores_gemma":[0.9993371,0.000030076293,0.000054599896,0.00033745027,0.0001363802,0.00010440895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002601689,0.000107866785,0.00019501211,0.00006189911,0.000112203124,0.000022301003,0.00006959177,0.00003850846,0.00021062419],"category_scores_gemma":[0.000025587244,0.00009800578,0.00003509755,0.00018423372,0.00008107241,0.00012891111,0.00007574127,0.00017400183,0.000117611424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011071481,0.00059286365,0.0019287848,0.00006413346,0.000018187198,0.00000757342,0.00001935078,6.685349e-7,0.9946243,0.00021858522,0.00023879904,0.0022756616],"study_design_scores_gemma":[0.0021604246,0.00032800421,0.035382945,0.0018078218,0.0005680165,0.000116381576,0.00006410997,0.30482087,0.63964015,0.01266506,0.0017857164,0.0006605135],"about_ca_topic_score_codex":0.000066383625,"about_ca_topic_score_gemma":5.017787e-7,"teacher_disagreement_score":0.35498416,"about_ca_system_score_codex":0.00005273173,"about_ca_system_score_gemma":0.000017931883,"threshold_uncertainty_score":0.399656},"labels":[],"label_agreement":null},{"id":"W2069831612","doi":"10.1002/jmri.21076","title":"Application of voxelwise analysis in the detection of regions of reduced fractional anisotropy in multiple sclerosis patients","year":2007,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Fluid-attenuated inversion recovery; Multiple sclerosis; Diffusion MRI; White matter; Nuclear medicine; Spatial normalization; Medicine; Radiology; Pathology; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Psychiatry","score_opus":0.038915548621932514,"score_gpt":0.3127707706016108,"score_spread":0.27385522197967826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069831612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8854621,0.00089669327,0.11286501,0.0004348486,0.00001548732,0.00026882743,0.000006551171,0.000004203686,0.00004626108],"genre_scores_gemma":[0.98617,0.00028020612,0.013460946,0.00004413917,0.000021576205,0.000009385428,0.0000029840858,0.000007745089,0.0000030380468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854153,0.000043196233,0.00083706935,0.000119506534,0.00034358498,0.00011510146],"domain_scores_gemma":[0.99838597,0.00021631419,0.0007862535,0.00024455422,0.00033795074,0.000028947943],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005549303,0.000077115124,0.00029309568,0.0005600976,0.00002352842,0.000002777386,0.00013653305,0.000027608685,0.0000030339086],"category_scores_gemma":[0.00022594557,0.00006251283,0.00013416978,0.0012804798,0.00010737541,0.00010000612,0.000016101796,0.00022006647,8.999633e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002887643,0.0005115139,0.64831483,0.000025327377,0.000008274377,0.0000028315308,0.00018449163,0.00018926078,0.24895164,0.000082036626,0.000019637564,0.10142141],"study_design_scores_gemma":[0.0009888527,0.00015340242,0.965202,0.00013410696,0.00010552423,0.000015242753,0.0001432936,0.0040908433,0.02823848,0.00046263137,0.00042300255,0.00004263532],"about_ca_topic_score_codex":0.0001246107,"about_ca_topic_score_gemma":0.000029504756,"teacher_disagreement_score":0.31688717,"about_ca_system_score_codex":0.00006147511,"about_ca_system_score_gemma":0.000031442025,"threshold_uncertainty_score":0.25491995},"labels":[],"label_agreement":null},{"id":"W2069922847","doi":"10.1038/sj.npp.1301347","title":"Focal Gray Matter Changes in Schizophrenia across the Course of the Illness: A 5-Year Follow-Up Study","year":2007,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":311,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Gray (unit); Magnetic resonance imaging; Psychology; Caudate nucleus; Voxel; Voxel-based morphometry; Olanzapine; Schizophrenia (object-oriented programming); Neuroscience; Medicine; Psychiatry; Nuclear medicine; Radiology","score_opus":0.034378644205534305,"score_gpt":0.396604617838392,"score_spread":0.3622259736328577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069922847","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987298,0.000040972296,0.00015943217,0.010008264,0.0006681052,0.0014076871,0.000012887233,0.00006230853,0.0003423557],"genre_scores_gemma":[0.9929686,0.000032252614,0.000112764115,0.0062761917,0.00015001086,0.00015034815,0.000001104964,0.00003529564,0.00027338325],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987651,0.0001205377,0.0002826489,0.000323541,0.00016588139,0.0003423086],"domain_scores_gemma":[0.9990387,0.00016172849,0.00012980413,0.00054471754,0.00006598713,0.000059095062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003441357,0.00015895732,0.00023892982,0.00005504354,0.00013603624,0.000006264633,0.00036552892,0.00005295788,0.00008440974],"category_scores_gemma":[0.000024857341,0.00009223183,0.00007916073,0.00052749686,0.00027634914,0.000024926054,0.00014275123,0.0005309726,0.000019159994],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045216107,0.002822447,0.53937125,0.00005101402,0.00008714981,0.00015813939,0.00316774,0.000010690554,0.4063338,0.00026922874,0.01639685,0.026810057],"study_design_scores_gemma":[0.0064179027,0.00041135194,0.9648802,0.00001889567,0.00008691262,0.00009814614,0.00076768483,0.000024417513,0.012165538,0.00021384616,0.014784684,0.00013037006],"about_ca_topic_score_codex":0.000016153495,"about_ca_topic_score_gemma":0.00014005949,"teacher_disagreement_score":0.42550898,"about_ca_system_score_codex":0.000019523366,"about_ca_system_score_gemma":0.000024775942,"threshold_uncertainty_score":0.3761105},"labels":[],"label_agreement":null},{"id":"W2070125936","doi":"10.1111/j.1085-9489.2005.10107.x","title":"Histological and magnetic resonance analysis of sciatic nerves in the tellurium model of neuropathy","year":2005,"lang":"en","type":"article","venue":"Journal of the Peripheral Nervous System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Toronto; Women's College Hospital; Sunnybrook Health Science Centre","funders":"","keywords":"Myelin; Sciatic nerve; Weanling; Hindlimb; Anatomy; Myelin sheath; Pathology; Atrophy; Magnetic resonance imaging; Medicine; Paralysis; Axonal degeneration; Chemistry; Internal medicine; Central nervous system; Surgery","score_opus":0.042761520594179786,"score_gpt":0.2955533619228332,"score_spread":0.2527918413286534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070125936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927525,0.0026414348,0.0014404233,0.002756241,0.000019796022,0.00017948258,0.0000052756955,0.000007742016,0.00019712967],"genre_scores_gemma":[0.99462175,0.00009502011,0.004861559,0.00024384452,0.000040970965,0.000004667229,1.6101488e-7,0.000007174607,0.00012487562],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988474,0.00012305308,0.0005783347,0.000097148564,0.00025226217,0.000101787904],"domain_scores_gemma":[0.99904454,0.00006861127,0.00045319946,0.00030374396,0.000097648786,0.00003223956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035195472,0.000084894775,0.00042217033,0.00011157441,0.00004021871,0.0000063597795,0.00025673365,0.000031120584,0.0000029176442],"category_scores_gemma":[0.000059010647,0.00004276484,0.00019489518,0.000465488,0.0001177287,0.00004163152,0.000039899372,0.00020443884,8.133617e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011351923,0.0020323065,0.27639475,0.0012587165,0.00038374664,0.00017356015,0.008348015,0.31757557,0.32908073,0.010938397,0.001751516,0.0509275],"study_design_scores_gemma":[0.000922515,0.00060071674,0.38085428,0.00045825727,0.0013600459,0.0009825797,0.00056215434,0.61159515,0.0012294182,0.0002709285,0.0010254061,0.0001385835],"about_ca_topic_score_codex":0.000013287297,"about_ca_topic_score_gemma":0.000007657219,"teacher_disagreement_score":0.3278513,"about_ca_system_score_codex":0.000057889323,"about_ca_system_score_gemma":0.000033021846,"threshold_uncertainty_score":0.17438996},"labels":[],"label_agreement":null},{"id":"W2070753161","doi":"10.1002/nbm.951","title":"MR properties of excised neural tissue following experimentally induced demyelination","year":2005,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Myelin; Sciatic nerve; Histopathology; Nuclear magnetic resonance; Magnetization transfer; Relaxation (psychology); Quantitative assessment; Magnetic resonance imaging; Chemistry; Anatomy; Pathology; Central nervous system; Biology; Medicine; Endocrinology; Physics; Neuroscience; Radiology","score_opus":0.10304264220097002,"score_gpt":0.39545321888825574,"score_spread":0.2924105766872857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070753161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900524,0.00058558653,0.0007304861,0.007281838,0.000045359688,0.00056417944,0.0000010597499,0.0001159174,0.0006231959],"genre_scores_gemma":[0.9911533,0.000030831754,0.0076484727,0.00073278224,0.00014791281,0.000079902406,0.000015917218,0.000020054815,0.00017082471],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990422,0.00001460125,0.00035478378,0.00020449028,0.00022600946,0.0001578832],"domain_scores_gemma":[0.9995549,0.000015182505,0.00008103522,0.0002303308,0.000042806136,0.000075791715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012002496,0.00011350979,0.00024454805,0.00022470276,0.000029832354,0.0000029543994,0.000087619985,0.000053610853,0.000033511682],"category_scores_gemma":[0.00007039064,0.00009084027,0.00003926294,0.00035972224,0.00007009757,0.00009107355,0.000033881526,0.0001332299,0.0000051603456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040986648,0.00015236606,0.0011570185,0.000031154766,0.000005377923,0.000008075794,0.000311218,0.0000036310837,0.96929777,0.000058420916,0.00014704968,0.028786905],"study_design_scores_gemma":[0.0018497843,0.00034757753,0.005902886,0.000305929,0.000026611133,0.000025417417,0.00019318971,0.0017005346,0.98431206,0.0000627488,0.005163297,0.00010997905],"about_ca_topic_score_codex":0.000034320845,"about_ca_topic_score_gemma":0.0000028742663,"teacher_disagreement_score":0.028676925,"about_ca_system_score_codex":0.00008329156,"about_ca_system_score_gemma":0.000033794637,"threshold_uncertainty_score":0.3704359},"labels":[],"label_agreement":null},{"id":"W2071252649","doi":"10.1145/1993886.1993909","title":"Diversification improves interpolation","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interpolation (computer graphics); Computer science; Diversification (marketing strategy); Artificial intelligence; Business","score_opus":0.15029607006859882,"score_gpt":0.35099958668034065,"score_spread":0.20070351661174182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071252649","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1167729,0.000014847099,0.6175531,0.0011867798,0.00003806253,0.00044376793,0.000001408416,0.0007322205,0.2632569],"genre_scores_gemma":[0.9038487,0.000008442181,0.09478208,0.0002997826,0.000012086274,0.000012382469,0.0000053200847,0.0000041155376,0.0010270602],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997925,0.0000017745397,0.000053485874,0.000081272534,0.000029582876,0.00004134722],"domain_scores_gemma":[0.99979043,0.0000035239461,0.000018801366,0.00013654724,0.00002612407,0.000024596931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000015658461,0.000028227343,0.000032444703,0.00002680182,0.000022156895,0.0000017076471,0.00002542973,0.000012367453,0.00014475432],"category_scores_gemma":[0.000007655123,0.000023355795,0.000017061018,0.000050807277,0.000017160426,0.0000497804,0.000013077457,0.000033209606,0.000038360282],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000122060395,0.00038816952,0.0600215,0.000028500743,0.000018774084,0.0000043321656,0.0007407591,4.9676437e-8,0.6292304,0.17698905,0.0080224695,0.12443394],"study_design_scores_gemma":[0.000580203,0.00033213836,0.7104104,0.000028635792,0.0000703627,0.00004936783,0.00026834715,0.0037345341,0.22845952,0.02624927,0.029616276,0.0002009292],"about_ca_topic_score_codex":0.000013530011,"about_ca_topic_score_gemma":2.707743e-7,"teacher_disagreement_score":0.7870758,"about_ca_system_score_codex":0.0000072405105,"about_ca_system_score_gemma":0.0000042352654,"threshold_uncertainty_score":0.15849583},"labels":[],"label_agreement":null},{"id":"W2071297770","doi":"10.1016/j.neuroimage.2006.09.016","title":"Segmentation of thalamic nuclei using a modified k-means clustering algorithm and high-resolution quantitative magnetic resonance imaging at 1.5 T","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Segmentation; Artificial intelligence; Magnetic resonance imaging; Computer science; Cluster analysis; Brain atlas; Similarity (geometry); Pattern recognition (psychology); Thalamus; Reproducibility; Euclidean distance; Surgical planning; Computer vision; Nuclear medicine; Medicine; Mathematics; Radiology; Image (mathematics)","score_opus":0.04463760690121317,"score_gpt":0.3221354639266813,"score_spread":0.27749785702546814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071297770","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57877916,0.0008340919,0.4188098,0.00034173642,0.000038342903,0.0005273743,0.00005124523,0.00015854384,0.00045970493],"genre_scores_gemma":[0.69994545,0.00008350771,0.29958373,0.00012842941,0.000033762783,0.00001927154,0.000026116726,0.00003961162,0.00014011862],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893355,0.00003865923,0.00028839867,0.00036312715,0.00017336993,0.00020290638],"domain_scores_gemma":[0.9994334,0.000055661636,0.00014130004,0.00025672128,0.00007208707,0.000040852323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007039101,0.00015161974,0.00020532992,0.00011579367,0.00013158428,0.000016370972,0.000057110654,0.00002728747,0.000009621314],"category_scores_gemma":[0.00001960074,0.0001605809,0.00004220705,0.00019694088,0.00016394632,0.00015040078,0.000094187504,0.00012334615,0.0000019931115],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008858637,0.00010895686,0.0041718977,0.00007755184,0.0000024339479,0.00005107466,0.00009112663,0.0011234852,0.96407014,0.0011020637,0.00015498279,0.028957708],"study_design_scores_gemma":[0.0012708408,0.00017117494,0.108692996,0.00012957271,0.00007704399,0.0002373839,0.000049761682,0.8592379,0.02832814,0.0012759921,0.00033875662,0.00019042421],"about_ca_topic_score_codex":0.00024802057,"about_ca_topic_score_gemma":0.0000065973377,"teacher_disagreement_score":0.935742,"about_ca_system_score_codex":0.00006428882,"about_ca_system_score_gemma":0.000014617943,"threshold_uncertainty_score":0.6548299},"labels":[],"label_agreement":null},{"id":"W2071509460","doi":"10.1002/ana.20772","title":"Pyramidal tract maturation after brain injury in newborns with heart disease","year":2006,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; White matter; Medicine; Diffusion MRI; Magnetic resonance imaging; Pyramidal tracts; Traumatic brain injury; Corticospinal tract; Tractography; Perioperative; Autopsy; Population; Cardiology; Pathology; Anesthesia; Radiology; Anatomy","score_opus":0.04713136753085785,"score_gpt":0.36660210204259863,"score_spread":0.3194707345117408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071509460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8896762,0.000035896643,0.0004126422,0.10938062,0.0000092360915,0.00023955427,0.000014479467,0.00005563824,0.00017572517],"genre_scores_gemma":[0.97996557,0.00001204475,0.0006028848,0.019202182,0.00005368738,0.000058937687,0.000018273244,0.000015764588,0.000070632224],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937224,0.000028212527,0.00017128579,0.00019827779,0.00007725405,0.00015270645],"domain_scores_gemma":[0.9995862,0.00004074295,0.00005172408,0.00022740901,0.000042810112,0.000051101677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042704756,0.00008262626,0.00014966806,0.0000983416,0.000013106607,0.0000033015172,0.000039852184,0.000037870745,0.000013453958],"category_scores_gemma":[0.000023576245,0.00007050357,0.000033638004,0.00014429651,0.000088363005,0.000063342464,0.000014231105,0.00015885381,0.000003518612],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01365402,0.0022239564,0.867594,0.00013274085,0.000008773618,0.0006624691,0.000046163183,0.0003749401,0.06681866,0.0036152513,0.04056605,0.0043030004],"study_design_scores_gemma":[0.00023298262,0.0004887041,0.9676473,0.000012646959,0.000007079927,0.000039976392,5.8189255e-7,0.000113379196,0.0027127925,0.004459234,0.02422751,0.00005779843],"about_ca_topic_score_codex":0.000034118493,"about_ca_topic_score_gemma":0.00000830266,"teacher_disagreement_score":0.10005334,"about_ca_system_score_codex":0.000002056533,"about_ca_system_score_gemma":0.000026228336,"threshold_uncertainty_score":0.2875052},"labels":[],"label_agreement":null},{"id":"W2071666283","doi":"10.1016/j.neuroimage.2014.12.058","title":"A new compression format for fiber tracking datasets","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Connectomics; Diffusion MRI; Data compression; Tractography; Pipeline (software); Lossless compression; Compression (physics); JPEG 2000; Artificial intelligence; Algorithm; Image compression; Connectome; Image processing","score_opus":0.2118934394563405,"score_gpt":0.4215440450161156,"score_spread":0.20965060555977508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071666283","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03439998,0.0003209043,0.9276668,0.013937893,0.0003369814,0.004080906,0.0007350015,0.001991159,0.0165304],"genre_scores_gemma":[0.1850217,0.000045396384,0.8012225,0.0055195335,0.00047646018,0.00020233827,0.001319817,0.00015378275,0.00603846],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992846,0.000008985142,0.00015863158,0.00023330105,0.00013382942,0.00018061299],"domain_scores_gemma":[0.999191,0.00005101313,0.00005794396,0.00043020965,0.000052662814,0.0002172107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006323695,0.00010486213,0.00014721876,0.00004374127,0.000059224185,0.000024368415,0.00010747333,0.00002907955,0.000029776666],"category_scores_gemma":[0.00010582621,0.00009131915,0.000052125324,0.00009181697,0.000021179094,0.00018242665,0.00006319663,0.00012980287,0.000050053986],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001731756,0.00010018905,0.00046003138,0.00006517533,0.0000045445854,0.000024751342,0.00006357661,0.000014796753,0.017906103,0.00055806205,0.9121495,0.06848008],"study_design_scores_gemma":[0.0014093533,0.0001793618,0.0011322219,0.00004910781,0.000036252448,0.00017156615,0.000009415902,0.0017335148,0.011247965,0.0015484943,0.9823706,0.00011215404],"about_ca_topic_score_codex":0.000008690141,"about_ca_topic_score_gemma":3.704386e-7,"teacher_disagreement_score":0.15062173,"about_ca_system_score_codex":0.000020942187,"about_ca_system_score_gemma":0.00004923151,"threshold_uncertainty_score":0.37238866},"labels":[],"label_agreement":null},{"id":"W2071833700","doi":"10.1155/2008/320195","title":"Accurate Anisotropic Fast Marching for Diffusion‐Based Geodesic Tractography","year":2007,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Dr Hadwen Trust for Humane Research","keywords":"Fast marching method; Geodesic; Computer science; Robustness (evolution); Tractography; Diffusion MRI; Algorithm; Noisy data; Computation; Perturbation (astronomy); Anisotropy; Mathematics; Mathematical analysis; Physics","score_opus":0.044136633047763454,"score_gpt":0.4014732143271156,"score_spread":0.35733658127935214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071833700","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.071961276,0.000087403474,0.91605836,0.0111351535,0.00037194105,0.00015663925,0.000015580983,0.000048009344,0.00016564308],"genre_scores_gemma":[0.8765852,0.000028988567,0.12096281,0.0017498637,0.0006002574,0.0000049220844,0.000024904853,0.000019834402,0.000023250048],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985322,0.000010908704,0.000542263,0.0001496082,0.0005482196,0.00021680247],"domain_scores_gemma":[0.9986832,0.0002427113,0.00032621025,0.00011360752,0.00042020564,0.00021407488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041041267,0.00011171012,0.00018667962,0.00056358805,0.00006409756,0.000038255643,0.00028403537,0.00003209577,0.000036455098],"category_scores_gemma":[0.00017411738,0.000090680565,0.00023475642,0.00018780406,0.00015319814,0.00014877568,0.000037763613,0.00028944144,0.0000015702066],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007786847,0.0009182448,0.018155612,0.000047765905,0.00014324601,0.0006457404,0.000102665705,0.000016558675,0.1931157,0.001281634,0.002813731,0.7819804],"study_design_scores_gemma":[0.020664401,0.0013399298,0.21761695,0.0023291402,0.0005407434,0.011594123,0.0005951128,0.068204254,0.0535576,0.02202584,0.6005105,0.0010214606],"about_ca_topic_score_codex":0.0000041407166,"about_ca_topic_score_gemma":3.3577092e-7,"teacher_disagreement_score":0.8046239,"about_ca_system_score_codex":0.0000792588,"about_ca_system_score_gemma":0.00008266526,"threshold_uncertainty_score":0.3697846},"labels":[],"label_agreement":null},{"id":"W2072158614","doi":"10.1016/j.neuroimage.2014.03.056","title":"Gray matter volume is associated with rate of subsequent skill learning after a long term training intervention","year":2014,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"FP7 People: Marie-Curie Actions; University of Oxford; Fundação para a Ciência e a Tecnologia; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Term (time); Intervention (counseling); Training (meteorology); Volume (thermodynamics); Gray (unit); Psychology; Physical medicine and rehabilitation; Medicine; Psychiatry; Geography; Physics; Nuclear medicine","score_opus":0.0337410118784554,"score_gpt":0.3098381530670533,"score_spread":0.2760971411885979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072158614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96351975,0.000013694281,0.03401158,0.0009776918,0.000023521756,0.00030346346,0.000007939899,0.00018216514,0.0009602138],"genre_scores_gemma":[0.99470335,0.000006722724,0.0012730297,0.0014212488,0.000031125404,0.000066780485,0.00003218882,0.00005493045,0.0024106281],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989325,0.00009765587,0.00027349888,0.00033104816,0.0001370812,0.0002282567],"domain_scores_gemma":[0.99926156,0.00005137321,0.00020665016,0.00031167656,0.00009598739,0.00007275612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019727042,0.00015870808,0.00027030497,0.000094813644,0.000052908654,0.000021104615,0.00008347809,0.000042694443,0.00022582815],"category_scores_gemma":[0.000095789954,0.00013638337,0.00011298637,0.00017741759,0.0001003854,0.00010915727,0.000043392647,0.00032455276,0.000031180334],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002234968,0.0003647604,0.92944056,0.00017854232,0.000054198314,0.0001368709,0.0008298697,0.000017049426,0.055699058,0.000051963678,0.0008570531,0.0121465735],"study_design_scores_gemma":[0.00096073764,0.0004571545,0.98754424,0.0004190666,0.00009939221,0.0000666453,0.000017284598,0.0008020207,0.0079986965,0.00013228816,0.0013453226,0.00015714581],"about_ca_topic_score_codex":0.000008756616,"about_ca_topic_score_gemma":0.0000032113596,"teacher_disagreement_score":0.05810368,"about_ca_system_score_codex":0.000028764449,"about_ca_system_score_gemma":0.000011301468,"threshold_uncertainty_score":0.5561552},"labels":[],"label_agreement":null},{"id":"W2072188503","doi":"10.1016/j.neuroimage.2013.06.033","title":"Locally linear embedding (LLE) for MRI based Alzheimer's disease classification","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; Genentech; IXICO; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Synarc; Bayer HealthCare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Medpace; AstraZeneca; Bristol-Myers Squibb; Eli Lilly and Company; Novartis Pharmaceuticals Corporation; National Center for Research Resources; F. Hoffmann-La Roche; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; University of California, San Diego; U.S. Department of Veterans Affairs","keywords":"Neuroimaging; Artificial intelligence; Linear discriminant analysis; Multivariate statistics; Pattern recognition (psychology); Logistic regression; Alzheimer's Disease Neuroimaging Initiative; Support vector machine; Medical diagnosis; Machine learning; Linear classifier; Computer science; Alzheimer's disease; Medicine; Disease; Psychology; Pathology; Neuroscience","score_opus":0.10974908995374599,"score_gpt":0.3852019442355012,"score_spread":0.2754528542817552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072188503","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014622372,0.0001158734,0.9457029,0.03296873,0.00009628966,0.0035658218,0.000056883844,0.0009907946,0.0018803003],"genre_scores_gemma":[0.78851825,0.000034838013,0.20270287,0.006535386,0.00023048081,0.0012311229,0.00016153193,0.00009779651,0.00048775348],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988791,0.000020326968,0.00024205785,0.00044329322,0.00016170344,0.00025352967],"domain_scores_gemma":[0.99872667,0.00011930851,0.000092360395,0.00062765245,0.0001836836,0.00025032007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006276532,0.00016328924,0.00016834,0.000083271814,0.00013277485,0.000034000852,0.00013430105,0.000039974322,0.00009604119],"category_scores_gemma":[0.0001345533,0.00015359449,0.0001219374,0.00015910057,0.000079278165,0.00014590434,0.000030897863,0.00016942277,0.00011062216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00092677964,0.0023936802,0.017188841,0.00059891376,0.000098734236,0.00012304424,0.00008073459,0.0014983605,0.58233637,0.012252862,0.2454708,0.13703087],"study_design_scores_gemma":[0.0013093,0.00022471359,0.059122987,0.00007261486,0.000229174,0.000012088073,0.000012382046,0.8049894,0.009787961,0.0018289905,0.12210413,0.00030628513],"about_ca_topic_score_codex":0.0000047972703,"about_ca_topic_score_gemma":1.5272681e-7,"teacher_disagreement_score":0.803491,"about_ca_system_score_codex":0.00002128414,"about_ca_system_score_gemma":0.00007118103,"threshold_uncertainty_score":0.62634015},"labels":[],"label_agreement":null},{"id":"W2072919309","doi":"10.1016/j.jad.2010.04.004","title":"MRI signal hyperintensities and treatment remission of geriatric depression","year":2010,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Center for Advanced Brain Imaging; National Institutes of Health; National Institute of Mental Health; University of Toronto; City University of New York","keywords":"Escitalopram; Depression (economics); Internal medicine; Placebo; Hamilton Rating Scale for Depression; Rating scale; Psychology; Psychiatry; Hyperintensity; Medicine; Major depressive disorder; Antidepressant; Magnetic resonance imaging; Pathology; Hippocampus; Cognition","score_opus":0.016451164568308387,"score_gpt":0.31600761588824366,"score_spread":0.2995564513199353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072919309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919177,0.00020548003,0.006537349,0.00059422833,0.000041960386,0.0001706727,0.0000016833095,0.0000119758815,0.0005188955],"genre_scores_gemma":[0.991982,0.0008304714,0.007059074,0.00002864841,0.000047826477,0.000003811192,6.4249855e-7,0.000009156998,0.000038390248],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999609,0.000013391358,0.0001443995,0.0000801193,0.00008967868,0.00006340373],"domain_scores_gemma":[0.9994801,0.00007892082,0.0001722931,0.00008826653,0.00011856771,0.000061835744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006176362,0.00007243079,0.00018068895,0.00009797644,0.000036423095,0.0000033531069,0.000028115002,0.00003301862,0.000012924284],"category_scores_gemma":[0.000054417633,0.000048650312,0.00007006371,0.00007886597,0.000068225905,0.000053965516,0.000014018712,0.00015216987,1.6827461e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034734682,0.00031102754,0.08609324,0.00002534209,0.00003848239,0.000008952859,0.0002114494,0.000015541307,0.70918876,0.00010958174,0.0003330622,0.20331724],"study_design_scores_gemma":[0.0046308152,0.004267574,0.5761896,0.00026742776,0.0003548264,0.0010722965,0.00085142115,0.0006813811,0.3913595,0.005484334,0.014595833,0.00024503746],"about_ca_topic_score_codex":0.000018635299,"about_ca_topic_score_gemma":0.000005777825,"teacher_disagreement_score":0.4900963,"about_ca_system_score_codex":0.000017399469,"about_ca_system_score_gemma":0.00003267859,"threshold_uncertainty_score":0.19839022},"labels":[],"label_agreement":null},{"id":"W2073169643","doi":"10.1002/1522-2594(200103)45:3<415::aid-mrm1054>3.0.co;2-m","title":"MR properties of rat sciatic nerve following trauma","year":2001,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Sciatic nerve; Fractional anisotropy; Magnetization transfer; Medicine; Histopathology; Degeneration (medical); Anatomy; Regeneration (biology); T2 relaxation; Nerve injury; Diffusion MRI; Axonal degeneration; Pathology; Magnetic resonance imaging; Anesthesia; Radiology; Biology","score_opus":0.0813412628426224,"score_gpt":0.34189166416312317,"score_spread":0.2605504013205008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073169643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96885884,0.01829937,0.0003873491,0.008523848,0.00010102912,0.0006635818,4.821486e-7,0.00009077629,0.00307475],"genre_scores_gemma":[0.9912179,0.0008574359,0.0044417437,0.0005814772,0.00009989831,0.00011214975,0.0000028674954,0.000024776331,0.002661729],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986379,0.000029482828,0.00047548927,0.00027917232,0.00032383116,0.0002541276],"domain_scores_gemma":[0.9993072,0.000053199772,0.000081249236,0.00042902713,0.000055214925,0.00007407552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024815236,0.00014720895,0.00044294182,0.00015991248,0.000037285205,0.000003174814,0.00014492321,0.000047622812,0.000088905166],"category_scores_gemma":[0.0002772474,0.000108752734,0.00006178707,0.0006084839,0.00022801875,0.00005073184,0.00003215155,0.00020335393,0.0000049937266],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040529447,0.0005271046,0.2524232,0.00039829384,0.000010478269,0.0006707864,0.0013557774,0.000017509767,0.23864977,0.0009502866,0.004763578,0.49982792],"study_design_scores_gemma":[0.013348418,0.004628937,0.5662341,0.012386515,0.00034267793,0.0007466163,0.001260192,0.0067289923,0.056420345,0.006947497,0.33010632,0.0008493697],"about_ca_topic_score_codex":0.00011744996,"about_ca_topic_score_gemma":0.0000115231005,"teacher_disagreement_score":0.49897856,"about_ca_system_score_codex":0.000041135758,"about_ca_system_score_gemma":0.000031388143,"threshold_uncertainty_score":0.4434808},"labels":[],"label_agreement":null},{"id":"W2073715614","doi":"10.1016/j.rbmret.2007.12.012","title":"Développement clinique de l’IRM du tenseur de diffusion de la moelle épinière dans un contexte de lésion médullaire","year":2008,"lang":"fr","type":"article","venue":"IRBM","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institutes of Health Research; Université de Montréal","funders":"","keywords":"Physics; Humanities; Nuclear medicine; Medicine; Philosophy","score_opus":0.04400854159892869,"score_gpt":0.3520319567962167,"score_spread":0.308023415197288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073715614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60649586,0.001634119,0.36617762,0.022502592,0.00013743671,0.000570439,0.000035469788,0.000363272,0.0020832212],"genre_scores_gemma":[0.89508104,0.025434202,0.0702201,0.004630756,0.0006099205,0.0001729254,0.000032569533,0.00010230455,0.0037161836],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976323,0.00034940155,0.00046677902,0.00048577253,0.00022045734,0.000845259],"domain_scores_gemma":[0.99826425,0.00039876075,0.00017882968,0.0005921103,0.00010112447,0.00046489434],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005870618,0.00032276593,0.0003601123,0.00007500453,0.00055154506,0.00002049504,0.00027410054,0.00031323585,0.000114331335],"category_scores_gemma":[0.0003036733,0.00033097688,0.00017480954,0.00020992596,0.0004595719,0.00006942575,0.00018065283,0.0006848916,0.00005521661],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034917123,0.0028723334,0.4428687,0.00037976386,0.00008745595,0.003475643,0.011872604,0.00034202964,0.35976663,0.01871795,0.04952588,0.10974182],"study_design_scores_gemma":[0.0037317998,0.0007086535,0.38044173,0.0015841501,0.00029262668,0.007332265,0.00067588524,0.021778356,0.11234454,0.022788297,0.447496,0.0008257199],"about_ca_topic_score_codex":0.00045351437,"about_ca_topic_score_gemma":0.000016204162,"teacher_disagreement_score":0.3979701,"about_ca_system_score_codex":0.00073394954,"about_ca_system_score_gemma":0.00050079776,"threshold_uncertainty_score":0.9999142},"labels":[],"label_agreement":null},{"id":"W2073864473","doi":"10.1002/ca.21190","title":"An anatomically based imaging sign to detect adventitial cyst derived from the superior tibiofibular joint","year":2011,"lang":"en","type":"article","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Medicine; Sign (mathematics); Cyst; Joint (building); Anatomy; Radiology","score_opus":0.11539035306917172,"score_gpt":0.3994710658256264,"score_spread":0.2840807127564547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073864473","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8405531,0.00007374721,0.15185374,0.00568746,0.00011334259,0.00084571773,0.000062215964,0.0004406542,0.0003700411],"genre_scores_gemma":[0.8935266,0.000015640982,0.09667591,0.009369261,0.0002478896,0.000064455526,0.000043279113,0.000043516884,0.00001343359],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99816805,0.00013054961,0.0006040553,0.0006061253,0.00019179477,0.00029944998],"domain_scores_gemma":[0.9981599,0.0002257307,0.000100882324,0.0009828726,0.00012906281,0.00040158755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037131502,0.00019496921,0.00036860714,0.00005125236,0.00015076018,0.000029265439,0.00036333464,0.00008428855,0.00034986692],"category_scores_gemma":[0.00031917993,0.0001414366,0.00024249856,0.00021201035,0.00025852738,0.00008643186,0.00010292322,0.00042004418,0.000108325534],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019601923,0.0026892752,0.2812504,0.000060835206,0.00021929246,0.001701502,0.0004697562,0.000011803334,0.36195663,0.0027444202,0.010563279,0.3363726],"study_design_scores_gemma":[0.0040744706,0.0013736418,0.78100634,0.0003132981,0.00044460027,0.000092690294,0.00016806941,0.010128112,0.11117835,0.01257166,0.077738576,0.0009101875],"about_ca_topic_score_codex":0.00014985379,"about_ca_topic_score_gemma":0.000013302673,"teacher_disagreement_score":0.49975595,"about_ca_system_score_codex":0.000034935314,"about_ca_system_score_gemma":0.000106246174,"threshold_uncertainty_score":0.5767617},"labels":[],"label_agreement":null},{"id":"W2073930583","doi":"10.1002/cne.22418","title":"Morphological patterns of the postcentral sulcus in the human brain","year":2010,"lang":"en","type":"article","venue":"The Journal of Comparative Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Postcentral gyrus; Sulcus; Intraparietal sulcus; Anatomy; Central sulcus; Biology; Gyrus; Parietal lobe; Superior temporal sulcus; Functional magnetic resonance imaging; Neuroscience; Motor cortex","score_opus":0.09557299371483786,"score_gpt":0.40270061112847916,"score_spread":0.3071276174136413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073930583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95318365,0.000017200475,0.00042057142,0.045745935,0.000063997635,0.00023483203,0.0000029739435,0.000005218787,0.00032562783],"genre_scores_gemma":[0.993932,0.000009601908,0.0000831275,0.005862639,0.00008484733,0.000003312581,4.5623221e-7,0.0000046042514,0.000019428273],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989624,0.00037986474,0.00031148794,0.00006732727,0.00014860301,0.00013031585],"domain_scores_gemma":[0.99877745,0.00051341415,0.0002969467,0.0003109906,0.00007567541,0.00002554524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043125765,0.000079167505,0.00022686293,0.000037726142,0.00007418998,0.000003507658,0.00048827232,0.000038534887,0.00003091309],"category_scores_gemma":[0.000059121307,0.000031557283,0.00008315625,0.00012000408,0.00030862252,0.000024125688,0.000056661265,0.0011984623,0.000001042253],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047109203,0.00050859485,0.17591433,0.000006007456,0.000020465875,0.0000920456,0.0017805328,0.00010022537,0.7982428,0.017927323,0.0047994293,0.00013716935],"study_design_scores_gemma":[0.00064139045,0.0008733628,0.97087705,0.000008811993,0.000036941998,0.0034718148,0.000085447165,0.000061010767,0.011592084,0.0069694147,0.005344956,0.00003771564],"about_ca_topic_score_codex":0.000006882526,"about_ca_topic_score_gemma":0.00001958386,"teacher_disagreement_score":0.7949627,"about_ca_system_score_codex":0.0000035242117,"about_ca_system_score_gemma":0.0000222508,"threshold_uncertainty_score":0.5206789},"labels":[],"label_agreement":null},{"id":"W2074145542","doi":"10.1016/j.nicl.2013.06.012","title":"Intra-individual variability in information processing speed reflects white matter microstructure in multiple sclerosis","year":2013,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Montreal Neurological Institute and Hospital; Health Sciences Centre; McGill University","funders":"Dalhousie University; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Genome Canada","keywords":"White matter; Neuropsychology; Medicine; Diffusion MRI; Multiple sclerosis; Audiology; Cognition; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.13430656742771432,"score_gpt":0.3834667417872672,"score_spread":0.24916017435955287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074145542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898257,0.0000064457236,0.002626241,0.005179618,0.000075459735,0.0012155853,0.000017027662,0.00015219893,0.0009016975],"genre_scores_gemma":[0.97027487,0.00001817217,0.022516174,0.00694277,0.00007324395,0.000063396976,0.000054701984,0.000024620509,0.00003206596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978975,0.00016173102,0.0009686635,0.00044867778,0.00019570524,0.00032773596],"domain_scores_gemma":[0.99877816,0.0002838659,0.00018617825,0.0005090993,0.00011555733,0.0001271596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006080457,0.00018704386,0.0003640473,0.00016277538,0.000053173302,0.00008899448,0.0001870097,0.00016759295,0.00014671263],"category_scores_gemma":[0.0010744802,0.00017213286,0.00008108964,0.00045784286,0.00017612711,0.00067031797,0.00012534148,0.0009670553,0.00013440601],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006858001,0.00023031651,0.95916176,0.00006355309,0.000001917108,0.0000071840436,0.00014451166,0.000009752399,0.0068108323,0.000005941641,0.002278587,0.031217044],"study_design_scores_gemma":[0.0013905662,0.000077839446,0.99302506,0.00010130404,0.000012810382,0.000028042576,0.000021973745,0.0028502138,0.00082016474,0.0006761149,0.0008525473,0.00014334501],"about_ca_topic_score_codex":0.000031136184,"about_ca_topic_score_gemma":0.000008259713,"teacher_disagreement_score":0.0338633,"about_ca_system_score_codex":0.000050249888,"about_ca_system_score_gemma":0.000070170165,"threshold_uncertainty_score":0.70193744},"labels":[],"label_agreement":null},{"id":"W2074890469","doi":"10.1016/j.jalz.2014.07.074","title":"P4‐303: COGNITIVE FUNCTION AND TRACTOGRAPHY OF WHITE MATTER TRACTS CROSSING HYPERINTENSITIES IN ELDERLY PERSONS","year":2014,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Queen's University","funders":"","keywords":"Memory span; Wechsler Adult Intelligence Scale; Fractional anisotropy; Stroop effect; Psychology; Hyperintensity; Diffusion MRI; Audiology; Dementia; White matter; Fluid-attenuated inversion recovery; Boston Naming Test; Neuropsychology; Cognition; Magnetic resonance imaging; Medicine; Neuroscience; Internal medicine; Working memory; Radiology","score_opus":0.04368040369058914,"score_gpt":0.3070907065569883,"score_spread":0.26341030286639916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074890469","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9844131,0.0026481166,0.010179184,0.00084703235,0.000035088695,0.00028671933,0.0000098196715,0.000059343824,0.0015215941],"genre_scores_gemma":[0.99470776,0.000017571518,0.004418338,0.0007556267,0.000024086547,0.00003102395,0.000016869804,0.000019026746,0.000009681314],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99934524,0.000019743911,0.00018736436,0.0002122315,0.00008697417,0.00014841731],"domain_scores_gemma":[0.99963534,0.000042695996,0.00007907098,0.00013203408,0.0000630187,0.00004783681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007526346,0.00010815746,0.00017222708,0.0001269081,0.000107748754,0.000020770398,0.000028513368,0.00003937961,0.000048305443],"category_scores_gemma":[0.0000087710305,0.00010487009,0.000050593713,0.0001261901,0.00018006514,0.00011700172,0.0000250733,0.00013260245,0.000004876275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028977482,0.00039515964,0.85569674,0.00004901203,0.001541488,0.000007355432,0.0017656593,0.0000026683285,0.05982761,0.00048061417,0.00084393105,0.079099976],"study_design_scores_gemma":[0.0008442685,0.00027787246,0.97770107,0.00012094455,0.003858565,0.000037990423,0.00037054115,0.00012051011,0.013093758,0.00052192615,0.0029020705,0.00015047734],"about_ca_topic_score_codex":0.000033865792,"about_ca_topic_score_gemma":0.000008600172,"teacher_disagreement_score":0.12200433,"about_ca_system_score_codex":0.0000012502879,"about_ca_system_score_gemma":0.000010346993,"threshold_uncertainty_score":0.4276478},"labels":[],"label_agreement":null},{"id":"W2075433159","doi":"10.1016/j.neuroimage.2007.01.006","title":"In vivo fiber tracking in the rat brain on a clinical 3T MRI system using a high strength insert gradient coil","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials","funders":"National Institute on Alcohol Abuse and Alcoholism; Heart and Stroke Foundation of Canada","keywords":"Splenium; Fractional anisotropy; Diffusion MRI; Corpus callosum; White matter; Biomedical engineering; Human brain; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Computer science; Neuroscience; Medicine; Physics; Psychology; Radiology","score_opus":0.11416610691376267,"score_gpt":0.4208602769058249,"score_spread":0.3066941699920622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075433159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99022263,0.000018793267,0.001971911,0.004620317,0.00013644683,0.0008199001,0.000008426053,0.0001495777,0.002051977],"genre_scores_gemma":[0.98988867,0.000018324146,0.0037756197,0.0058905534,0.00017300028,0.000029567138,0.0000038278877,0.00004118819,0.00017925727],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99810714,0.00016987132,0.00061124226,0.00047961093,0.00026800128,0.00036415207],"domain_scores_gemma":[0.9984237,0.00071165245,0.00013188235,0.0006138446,0.00003326623,0.00008563656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009485052,0.0001876501,0.0003140012,0.00019143417,0.00007639032,0.000027713699,0.00019944941,0.000076043914,0.000015109414],"category_scores_gemma":[0.00020370304,0.00014394934,0.00009674388,0.0005251116,0.00009023507,0.00009271113,0.000046788664,0.0007387284,0.000012375312],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00556186,0.01727604,0.2331253,0.0016904869,0.00010290783,0.04396495,0.005946054,0.0014965885,0.3958531,0.1062525,0.08721977,0.101510435],"study_design_scores_gemma":[0.01750541,0.0043996247,0.5312798,0.0035145406,0.0002695438,0.0038754065,0.0018208027,0.022009809,0.054198273,0.0024555125,0.35668233,0.001988955],"about_ca_topic_score_codex":0.000090313646,"about_ca_topic_score_gemma":0.000041943844,"teacher_disagreement_score":0.34165484,"about_ca_system_score_codex":0.00011154635,"about_ca_system_score_gemma":0.000036598307,"threshold_uncertainty_score":0.58700836},"labels":[],"label_agreement":null},{"id":"W2075738639","doi":"10.1016/j.pain.2012.04.003","title":"White matter brain and trigeminal nerve abnormalities in temporomandibular disorder","year":2012,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; University Health Network; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; White matter; Diffusion MRI; Internal capsule; Fractional anisotropy; Neuroscience; Medicine; Psychology; Prefrontal cortex; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.027414624017866887,"score_gpt":0.3166459926550091,"score_spread":0.2892313686371422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075738639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92218876,0.0012151215,0.049767982,0.021752987,0.000022961289,0.0005147845,0.0000099100125,0.0001423113,0.004385198],"genre_scores_gemma":[0.98950714,0.000022742459,0.0057931542,0.0021669224,0.000058303493,0.00007068318,0.000015761618,0.000014573961,0.0023506996],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994739,0.00007146925,0.000117624855,0.00010312883,0.00005750385,0.00017636867],"domain_scores_gemma":[0.99965644,0.000106559055,0.000024466372,0.000143618,0.0000075642606,0.00006133203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006671948,0.00007162633,0.000106648746,0.00005571458,0.000029177805,0.000006284243,0.000027785723,0.000026496375,0.00011820487],"category_scores_gemma":[0.000050424303,0.00006192455,0.000018176841,0.00007826985,0.000039072376,0.00007762844,0.000024600782,0.00009853381,0.000013357554],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010254664,0.000054893317,0.98856217,0.000037939844,0.0000018435702,0.000004718327,0.00030753354,3.2156584e-7,0.00016898874,0.00046264645,0.008554984,0.0018336806],"study_design_scores_gemma":[0.0004932825,0.000053384487,0.85516906,0.00007115924,0.000013068484,0.000085037085,0.00035089883,0.00036024465,0.00022889115,0.0014772309,0.14154893,0.00014882527],"about_ca_topic_score_codex":0.000023796576,"about_ca_topic_score_gemma":0.0000035676046,"teacher_disagreement_score":0.13339314,"about_ca_system_score_codex":0.000012520763,"about_ca_system_score_gemma":0.0000048674638,"threshold_uncertainty_score":0.25252098},"labels":[],"label_agreement":null},{"id":"W2076609203","doi":"10.1371/journal.pone.0053678","title":"Reliable Identification of Deep Sulcal Pits: The Effects of Scan Session, Scanner, and Surface Extraction Tool","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Korea Science and Engineering Foundation; National Research Foundation of Korea; National Research Foundation","keywords":"Scanner; Neuroimaging; White matter; Artificial intelligence; Similarity (geometry); Pattern recognition (psychology); Nuclear medicine; Computer science; Magnetic resonance imaging; Biology; Medicine; Radiology; Neuroscience; Image (mathematics)","score_opus":0.03248149711368872,"score_gpt":0.2956015678760396,"score_spread":0.2631200707623509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076609203","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933813,0.00026726583,0.004291375,0.0011006339,0.000012464661,0.0007880862,0.000002059125,0.000051274248,0.00010554064],"genre_scores_gemma":[0.9922477,0.00039751665,0.006798578,0.00005801764,0.000019934609,0.00007312051,0.000005709343,0.000011811026,0.00038762312],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99940336,0.00001703746,0.00021204785,0.00013180915,0.00015911473,0.00007665679],"domain_scores_gemma":[0.9992153,0.00012387321,0.00015203672,0.00030113195,0.00017773613,0.000029899198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088310095,0.000058219885,0.00013869359,0.000025954803,0.000050347982,0.0000070820824,0.000052415493,0.000031529235,0.000015059938],"category_scores_gemma":[0.00018492849,0.00004232398,0.000018049028,0.0001387838,0.00007670048,0.00010640757,0.000023702583,0.00009693333,0.0000045431707],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011303285,0.00041111713,0.005264243,0.00028996693,0.000016106294,1.9531092e-7,0.00004239409,0.0000045797774,0.9911041,0.00024266068,0.0003393479,0.0022739556],"study_design_scores_gemma":[0.00023197065,0.00009422321,0.061478555,0.0002606063,0.000111844995,0.0000037253146,0.000027671573,0.0027664783,0.93374753,0.0011605155,0.00007094036,0.00004594539],"about_ca_topic_score_codex":0.000058195208,"about_ca_topic_score_gemma":8.0936445e-7,"teacher_disagreement_score":0.057356603,"about_ca_system_score_codex":0.000014077086,"about_ca_system_score_gemma":0.000011880991,"threshold_uncertainty_score":0.1725922},"labels":[],"label_agreement":null},{"id":"W2076623026","doi":"10.1016/j.neuroimage.2011.04.068","title":"Wallerian degeneration after spinal cord lesions in cats detected with diffusion tensor imaging","year":2011,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Christopher and Dana Reeve Foundation","keywords":"Wallerian degeneration; Diffusion MRI; CATS; Spinal cord; Degeneration (medical); Medicine; Pathology; Neuroscience; Anatomy; Psychology; Radiology; Magnetic resonance imaging; Internal medicine","score_opus":0.0766308467582226,"score_gpt":0.32317191193837425,"score_spread":0.24654106518015165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076623026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98484355,0.000058726207,0.012027264,0.0008131176,0.000033556516,0.00060360663,0.0000070133083,0.00029835288,0.0013148013],"genre_scores_gemma":[0.9695497,0.00003609369,0.029124124,0.00079103204,0.000043601834,0.00016400372,0.000011509732,0.000048220147,0.00023172401],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989456,0.000029260305,0.00021304548,0.00041498273,0.00014496526,0.00025213102],"domain_scores_gemma":[0.99929607,0.0000101783935,0.00006458496,0.00044810856,0.00007311354,0.000107967455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004214103,0.00017180921,0.00016601871,0.00016071011,0.000082799765,0.000016136286,0.00008815034,0.00003245549,0.00008176538],"category_scores_gemma":[0.000031883887,0.00014181128,0.00003909436,0.00027411274,0.00008199887,0.00013155771,0.000054450265,0.00025874926,0.000019384592],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051577273,0.0008880658,0.29767612,0.000084743115,0.00000936205,0.0015944266,0.00025731727,0.0000035670869,0.60673696,0.00037551922,0.00034386772,0.08687235],"study_design_scores_gemma":[0.00081243867,0.0006786107,0.974394,0.000099078075,0.00004216673,0.00029454587,0.000019817535,0.00091408787,0.020087754,0.00015073254,0.002322142,0.00018460114],"about_ca_topic_score_codex":0.000063623746,"about_ca_topic_score_gemma":0.000037504793,"teacher_disagreement_score":0.6767179,"about_ca_system_score_codex":0.000028527922,"about_ca_system_score_gemma":0.000032851596,"threshold_uncertainty_score":0.57828957},"labels":[],"label_agreement":null},{"id":"W2077459260","doi":"10.1016/j.neuroimage.2015.03.039","title":"Developmental synchrony of thalamocortical circuits in the neonatal brain","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Ministry of Education - Singapore; National Medical Research Council; National Research Foundation Singapore; Singapore Institute for Clinical Sciences; National University of Singapore; Ministry of Health -Singapore","keywords":"Thalamus; Neuroscience; Cortex (anatomy); Cerebral cortex; Diffusion MRI; Psychology; Temporal cortex; Functional magnetic resonance imaging; Anatomy; Biology; Magnetic resonance imaging; Medicine","score_opus":0.12667462552934863,"score_gpt":0.365192266885537,"score_spread":0.2385176413561884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077459260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9694709,0.000060648432,0.0054213046,0.008742313,0.000029587849,0.0006726859,0.000010294884,0.00010975693,0.015482506],"genre_scores_gemma":[0.99379253,0.0000057585353,0.0038862424,0.0021148156,0.000031716198,0.000039450264,0.000007844528,0.0000155361,0.00010611504],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99916095,0.000039613125,0.00020674645,0.0001953597,0.00023830442,0.0001590387],"domain_scores_gemma":[0.9995259,0.000106975785,0.000041460968,0.00021793832,0.00003814253,0.000069587004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016859433,0.00008899263,0.00013930876,0.00005838037,0.000021554102,0.0000074164086,0.00016154895,0.000026802223,0.000014530193],"category_scores_gemma":[0.00026132105,0.00006578905,0.000037297305,0.00025346896,0.00011646948,0.00006148151,0.00005523753,0.00021851636,0.000017530248],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002754057,0.0022691842,0.2627011,0.00026821392,0.00003499785,0.0032016044,0.0055867345,0.000024282152,0.42639527,0.029635554,0.07957151,0.19003618],"study_design_scores_gemma":[0.0033944163,0.00068462413,0.8532828,0.00011575869,0.000047713715,0.003411803,0.00080572336,0.00083129236,0.03292626,0.0051531834,0.098980725,0.00036570668],"about_ca_topic_score_codex":0.000008295453,"about_ca_topic_score_gemma":0.0000021961805,"teacher_disagreement_score":0.5905817,"about_ca_system_score_codex":0.000031167743,"about_ca_system_score_gemma":0.00009415643,"threshold_uncertainty_score":0.26827997},"labels":[],"label_agreement":null},{"id":"W2078272321","doi":"10.1016/j.schres.2006.09.009","title":"Cerebral grey, white matter and csf in never-medicated, first-episode schizophrenia","year":2006,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":189,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Grey matter; White matter; Psychology; Internal capsule; Cingulum (brain); Lateral ventricles; Schizophrenia (object-oriented programming); Thalamus; Anterior cingulate cortex; Caudate nucleus; Insular cortex; Voxel-based morphometry; Psychosis; Limbic lobe; Parahippocampal gyrus; Cardiology; Neuroscience; Medicine; Fractional anisotropy; Magnetic resonance imaging; Temporal lobe; Psychiatry; Radiology; Cognition","score_opus":0.06080943112424795,"score_gpt":0.3661039390312939,"score_spread":0.30529450790704593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078272321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9425717,0.0006054753,0.00073258014,0.047484253,0.000056916844,0.0013831233,0.000036567366,0.0003222153,0.006807145],"genre_scores_gemma":[0.9735807,0.0001475106,0.021970207,0.00049602514,0.000339933,0.00031412308,0.00006722043,0.00007755505,0.0030067258],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971439,0.00011310796,0.0004450154,0.00077140064,0.0007039477,0.00082260364],"domain_scores_gemma":[0.9985184,0.00016553536,0.00006368135,0.00078703783,0.00020232867,0.0002630161],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006178664,0.0002541437,0.00036611198,0.0006669549,0.00029216678,0.000093095456,0.00030572273,0.00016823856,0.0003850704],"category_scores_gemma":[0.00011159225,0.00023195047,0.00007190668,0.0011158534,0.0005071315,0.0002947715,0.00033933067,0.001307101,0.00036333466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019005813,0.0004937152,0.87561476,0.00022928885,0.000019045448,0.00024629838,0.000050921677,0.000016912358,0.002156323,0.0111350715,0.1012172,0.0069198874],"study_design_scores_gemma":[0.004510854,0.0001772821,0.9339144,0.00027271363,0.000019399682,0.00026954382,0.000027391618,0.0011212013,0.0013030325,0.025139954,0.03289602,0.000348215],"about_ca_topic_score_codex":0.00087553664,"about_ca_topic_score_gemma":0.0005200458,"teacher_disagreement_score":0.06832118,"about_ca_system_score_codex":0.00013365649,"about_ca_system_score_gemma":0.000101059275,"threshold_uncertainty_score":0.9458665},"labels":[],"label_agreement":null},{"id":"W2078369932","doi":"10.1016/j.mric.2009.02.001","title":"Diffusion and Perfusion MR Imaging of Acute Ischemic Stroke","year":2009,"lang":"en","type":"review","venue":"Magnetic Resonance Imaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"","keywords":"Medicine; Diffusion imaging; Perfusion; Perfusion scanning; Stroke (engine); Diffusion MRI; Acute stroke; Ischemia; Radiology; Brain ischemia; Ischemic stroke; Magnetic resonance imaging; Cardiology; Internal medicine","score_opus":0.033716420910521065,"score_gpt":0.36830664241992006,"score_spread":0.334590221509399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078369932","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011293185,0.9954976,0.0009347899,0.00031329223,0.00005006929,0.0010714957,0.00025568382,0.00012061535,0.00062713603],"genre_scores_gemma":[0.00039134716,0.9700627,0.028402006,0.0003075607,0.00007559909,0.000058836173,0.00015863216,0.00008966043,0.0004536935],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967816,0.00006602465,0.0014844603,0.0008461562,0.00041180983,0.00040993938],"domain_scores_gemma":[0.99690634,0.0002992332,0.0012660348,0.001133288,0.00021871616,0.00017639901],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014993931,0.0005481944,0.0022782248,0.00030455342,0.00008556409,0.00001634956,0.00039677147,0.00008494761,0.000023965616],"category_scores_gemma":[0.00015195513,0.00048261846,0.0005149371,0.00056300947,0.0006372516,0.00008301279,0.00031274586,0.00073969085,0.0000051975544],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002672727,0.00015364993,0.006615955,0.0016575167,0.000010203091,0.000029681676,0.00001859153,1.3285847e-7,0.000045275723,0.0000035691094,0.0010035072,0.9904352],"study_design_scores_gemma":[0.00045367525,0.0002689281,0.004430717,0.0069647534,0.0013156718,0.00019180245,0.0000068413806,0.0006447508,0.000009505616,0.000026209927,0.98533046,0.00035668426],"about_ca_topic_score_codex":0.00002163933,"about_ca_topic_score_gemma":4.5102314e-7,"teacher_disagreement_score":0.9900785,"about_ca_system_score_codex":0.000041939536,"about_ca_system_score_gemma":0.00020727616,"threshold_uncertainty_score":0.99976254},"labels":[],"label_agreement":null},{"id":"W2078510704","doi":"10.1097/wnr.0000000000000204","title":"The relationship between uncinate fasciculus white matter integrity and verbal memory proficiency in children","year":2014,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Population and Public Health","funders":"National Heart, Lung, and Blood Institute","keywords":"Uncinate fasciculus; Fractional anisotropy; Psychology; Fasciculus; White matter; Verbal memory; Diffusion MRI; Audiology; Inferior longitudinal fasciculus; Developmental psychology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.06031355565817511,"score_gpt":0.3418536438509589,"score_spread":0.2815400881927838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078510704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98769724,0.000016363008,0.001202949,0.006366195,0.0000252015,0.00046737338,0.0000021659005,0.00010080196,0.0041217282],"genre_scores_gemma":[0.99818516,0.0000051801608,0.0005334054,0.000517476,0.000059204518,0.00004872428,0.00001117762,0.000016325037,0.00062337494],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990789,0.000042809992,0.00027063207,0.0002866826,0.00015301444,0.00016795637],"domain_scores_gemma":[0.999245,0.00014208938,0.000098492055,0.00041767748,0.000033055192,0.00006367103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033081297,0.00009952195,0.00013319124,0.000050927716,0.00014515285,0.000020033722,0.00008595161,0.000042835913,0.0000040250566],"category_scores_gemma":[0.00026492053,0.00006919781,0.00003057417,0.00018670782,0.00011546989,0.00006258934,0.00006648742,0.00050883926,0.000011269274],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000055171154,0.000016841914,0.99753505,0.0000058279293,0.0000013215864,0.0000048710526,0.000028498858,5.974721e-7,0.000052853316,0.00064172107,0.00045491607,0.0012519881],"study_design_scores_gemma":[0.00017584799,0.000053631677,0.99461764,0.00001542533,0.000016811584,0.00020643456,0.0000065658155,0.00005989668,0.00020943134,0.003892538,0.00068026496,0.00006548428],"about_ca_topic_score_codex":0.000019431393,"about_ca_topic_score_gemma":0.00000215924,"teacher_disagreement_score":0.01048791,"about_ca_system_score_codex":0.000020776224,"about_ca_system_score_gemma":0.00003052783,"threshold_uncertainty_score":0.2821805},"labels":[],"label_agreement":null},{"id":"W2078989713","doi":"10.1523/jneurosci.3048-13.2013","title":"Motor Skill Learning Induces Changes in White Matter Microstructure and Myelination","year":2013,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":425,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"University of Oxford; National Institute for Health and Care Research; Oxford University Hospitals NHS Foundation Trust; Cancer Research UK; Wellcome Trust","keywords":"Fractional anisotropy; White matter; Psychology; Motor cortex; Motor learning; Neuroscience; Neuroplasticity; Lateralization of brain function; Cortex (anatomy); Myelin; Diffusion MRI; Medicine; Magnetic resonance imaging; Central nervous system","score_opus":0.030655539956320164,"score_gpt":0.3225949208676715,"score_spread":0.29193938091135135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078989713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893561,0.00003189318,0.00055080955,0.009833765,0.00004874258,0.00011199899,4.331211e-7,0.000008817825,0.000057420835],"genre_scores_gemma":[0.99465096,0.00009985763,0.003365937,0.0015533151,0.000042962994,0.0000036946562,1.2530727e-7,0.000005675528,0.00027745808],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99954534,0.000014220602,0.00013297106,0.000101893,0.00011495792,0.00009065032],"domain_scores_gemma":[0.99965936,0.000017798498,0.0001391087,0.000058996993,0.0000722351,0.000052489497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072947434,0.000051222938,0.00009313097,0.00013638652,0.000042089596,0.00003053179,0.00006826955,0.00002004454,0.000012893008],"category_scores_gemma":[0.0000851271,0.00003863562,0.0000141132505,0.00016209613,0.00006388133,0.00019391364,0.000027862781,0.00025596202,0.0000016004134],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041625526,0.000016399967,0.12573576,0.000008213672,1.8925314e-7,0.00001084158,0.00010668437,0.000010050087,0.8719273,0.000007387328,0.00016209327,0.0020108665],"study_design_scores_gemma":[0.00014088949,0.00016128193,0.99128693,0.000044050546,0.0000031304821,0.0006308938,0.000037245773,0.00032322822,0.0056354306,0.0002954192,0.0014050878,0.00003642699],"about_ca_topic_score_codex":0.0000017047622,"about_ca_topic_score_gemma":3.1451634e-7,"teacher_disagreement_score":0.86629194,"about_ca_system_score_codex":0.000012377306,"about_ca_system_score_gemma":0.000011971263,"threshold_uncertainty_score":0.15755148},"labels":[],"label_agreement":null},{"id":"W2079334797","doi":"10.1503/jpn.100041","title":"Complementary diffusion tensor imaging study of the corpus callosum in patients with first-episode and chronic schizophrenia","year":2011,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Xiangya Hospital, Central South University; Central South University","keywords":"Corpus callosum; Diffusion MRI; Schizophrenia (object-oriented programming); Fractional anisotropy; White matter; Psychology; Magnetic resonance imaging; Neuroimaging; Pathological; Neuroscience; Medicine; Psychiatry; Internal medicine; Radiology","score_opus":0.03079589462467696,"score_gpt":0.28912233874947996,"score_spread":0.258326444124803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079334797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99845654,0.00010164177,0.00018065519,0.0008440819,0.00011457677,0.00028374614,0.0000023563298,0.000004578897,0.000011844685],"genre_scores_gemma":[0.99751204,0.000075356445,0.0021381015,0.00024555577,0.000017739561,0.0000021672663,8.48819e-8,0.0000055382743,0.0000034191532],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993351,0.000021549355,0.00023579052,0.00013778162,0.00017587763,0.00009390068],"domain_scores_gemma":[0.99951214,0.000014954403,0.00023231743,0.00014795286,0.00004032853,0.00005231827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007520658,0.000072184564,0.00013238504,0.00006993792,0.00011138579,0.0000057929888,0.0001175722,0.000007434115,0.000001842715],"category_scores_gemma":[0.00001419313,0.000041608277,0.0000179113,0.00018128697,0.00014964493,0.00010099666,0.000067759116,0.00017349403,2.2825215e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018988851,0.000672704,0.99797827,0.00001871907,0.0000011865205,0.000003198465,0.00007748222,0.0000024511319,0.00054715364,0.00005505009,0.00003150222,0.0004224063],"study_design_scores_gemma":[0.0022143454,0.0014667367,0.9954751,0.00014272943,0.00002851045,0.00007529559,0.000057971556,0.00011914144,0.00010635991,0.0001979061,0.00007424058,0.000041639774],"about_ca_topic_score_codex":0.000027020555,"about_ca_topic_score_gemma":0.000108160144,"teacher_disagreement_score":0.0025031348,"about_ca_system_score_codex":0.000010505994,"about_ca_system_score_gemma":0.000029923343,"threshold_uncertainty_score":0.16967362},"labels":[],"label_agreement":null},{"id":"W2079501536","doi":"10.1016/j.neurobiolaging.2006.05.018","title":"Age and gender effects on human brain anatomy: A voxel-based morphometric study in healthy elderly","year":2006,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":325,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute on Aging; AGE-WELL; Deutsches Krebsforschungszentrum","keywords":"Corpus callosum; Grey matter; Voxel; White matter; Temporal lobe; Posterior cingulate; Magnetic resonance imaging; Basal ganglia; Brain size; Human brain; Parietal lobe; Psychology; Voxel-based morphometry; Anatomy; Brain mapping; Cingulate cortex; Frontal lobe; Cortex (anatomy); Medicine; Neuroscience; Central nervous system; Radiology","score_opus":0.06552498220250581,"score_gpt":0.3924909855949094,"score_spread":0.3269660033924036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079501536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970924,0.000062991916,0.00029258354,0.0015566226,0.000019217623,0.00072584563,0.0000020273765,0.000099873236,0.00014844061],"genre_scores_gemma":[0.9970309,0.0000038861676,0.0008612374,0.0019781073,0.000026815846,0.00004749678,0.00001215676,0.000019359903,0.000020000776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990573,0.000099025594,0.00022618602,0.0003500804,0.0000682406,0.00019918282],"domain_scores_gemma":[0.99928313,0.00031386403,0.000085117805,0.00026025396,0.000017856704,0.000039756505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014529201,0.000124847,0.00028433953,0.00053671474,0.000059543876,0.000004614873,0.00007868049,0.00004487672,0.000002102573],"category_scores_gemma":[0.00003417968,0.00011659899,0.000031080406,0.00046444952,0.00008139334,0.000016855663,0.000032447617,0.00025270402,8.5978115e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012366116,0.0012164597,0.92537713,0.00021539583,0.000010202175,0.00033031305,0.00008017569,0.00004524541,0.06893834,0.0006091592,0.0005249708,0.0025289739],"study_design_scores_gemma":[0.0022882207,0.0027076472,0.98788804,0.00003769874,0.00001853814,0.000015375796,0.000008432565,0.000031448057,0.0059237843,0.00078316085,0.00020652235,0.00009116092],"about_ca_topic_score_codex":0.00008026105,"about_ca_topic_score_gemma":0.000013834948,"teacher_disagreement_score":0.06301455,"about_ca_system_score_codex":0.000025002666,"about_ca_system_score_gemma":0.000016766544,"threshold_uncertainty_score":0.4754769},"labels":[],"label_agreement":null},{"id":"W2079848144","doi":"10.1016/j.jalz.2010.05.569","title":"P1‐022: Characterizing abnormal white matter structure in primary progressive aphasia","year":2010,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Health Sciences Centre; University Health Network; University of Toronto","funders":"","keywords":"Primary progressive aphasia; Diffusion MRI; White matter; Fractional anisotropy; Audiology; Arcuate fasciculus; Voxel; Nuclear medicine; Uncinate fasciculus; SMA*; Psychology; Boston Naming Test; Inferior longitudinal fasciculus; Medicine; Neuroscience; Dementia; Cognition; Pathology; Radiology; Neuropsychology; Mathematics; Magnetic resonance imaging; Frontotemporal dementia; Disease","score_opus":0.02388996777428627,"score_gpt":0.30671116162288425,"score_spread":0.282821193848598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079848144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881336,0.0024292925,0.00032653153,0.0045280033,0.00022271553,0.0011007595,0.000040125724,0.00024117705,0.002977806],"genre_scores_gemma":[0.96413743,0.00001334682,0.032464374,0.0028834224,0.0001480415,0.00011829878,0.00016566407,0.000042492647,0.000026911852],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988897,0.000013464952,0.00027337408,0.00034861226,0.0001614358,0.00031343204],"domain_scores_gemma":[0.9992769,0.00001075416,0.00012370762,0.00045165498,0.000043143125,0.0000938687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058770693,0.00018372167,0.00020741312,0.00010789385,0.00007626775,0.000030963987,0.00015484421,0.00008520539,0.000798134],"category_scores_gemma":[0.000003728473,0.00016828057,0.000056180117,0.0001745715,0.00008233075,0.00020345878,0.00010239477,0.00051856996,0.000055754965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006731983,0.00021172767,0.57328486,0.000022881219,0.0006507369,0.00015907735,0.00014606246,4.6676064e-7,0.38458076,0.00029782212,0.0037495987,0.0368287],"study_design_scores_gemma":[0.00071766344,0.000055449982,0.8981186,0.000045125933,0.0016287754,0.00039664516,0.000010259117,0.000034459852,0.053628083,0.00025062117,0.044834077,0.0002801973],"about_ca_topic_score_codex":0.0000047089634,"about_ca_topic_score_gemma":0.0000041028206,"teacher_disagreement_score":0.33095267,"about_ca_system_score_codex":0.0000048916118,"about_ca_system_score_gemma":0.000034828587,"threshold_uncertainty_score":0.8739008},"labels":[],"label_agreement":null},{"id":"W2079987516","doi":"10.1016/j.neuroimage.2005.09.068","title":"The NIH MRI study of normal brain development","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":538,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Generalizability theory; Voxel; Population; Protocol (science); Diffusion MRI; Medicine; Sample size determination; Neuroimaging; Database; Magnetic resonance imaging; Medical physics; Psychology; Pathology; Computer science; Radiology; Statistics; Developmental psychology; Psychiatry","score_opus":0.041257074273638845,"score_gpt":0.3354868080599654,"score_spread":0.29422973378632655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079987516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835839,0.000033593635,0.0038210799,0.003620705,0.000035514273,0.00079209975,0.0000021571104,0.0001765914,0.007934359],"genre_scores_gemma":[0.99244446,0.000006576366,0.0048164153,0.00039251216,0.000046985795,0.00006134952,0.000004414273,0.000020284417,0.00220698],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992029,0.000023804652,0.00024698512,0.00018711621,0.00018551442,0.0001537002],"domain_scores_gemma":[0.99933887,0.00009731693,0.0000763473,0.00040302033,0.00005321894,0.000031202937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001029286,0.00008836502,0.00011512358,0.000035250243,0.00016049403,0.000011498916,0.0001255309,0.000014113987,0.000007885511],"category_scores_gemma":[0.000032002972,0.00006267745,0.000030083722,0.00015893116,0.00005932914,0.00003352836,0.000069082045,0.00013743664,0.000010059944],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049765897,0.008971388,0.24613848,0.0001553517,0.000079608944,0.00045942995,0.0012645547,0.00018766343,0.4317776,0.009698754,0.20026329,0.10050621],"study_design_scores_gemma":[0.0011718698,0.00045617268,0.6014654,0.0000149728785,0.000028729552,0.000061912884,0.00012038089,0.00014422851,0.03684711,0.00043660635,0.35911518,0.00013741342],"about_ca_topic_score_codex":0.000022568398,"about_ca_topic_score_gemma":0.000015461763,"teacher_disagreement_score":0.3949305,"about_ca_system_score_codex":0.000013041067,"about_ca_system_score_gemma":0.000030189844,"threshold_uncertainty_score":0.2555912},"labels":[],"label_agreement":null},{"id":"W2080094149","doi":"10.3389/fninf.2014.00059","title":"Real-time multi-peak tractography for instantaneous connectivity display","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"Tractography; Computer science; Voxel; Diffusion MRI; Artificial intelligence; Pattern recognition (psychology); Human Connectome Project; Imaging phantom; Computer vision; Functional connectivity; Magnetic resonance imaging","score_opus":0.02914577916448745,"score_gpt":0.3089900371262589,"score_spread":0.2798442579617714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080094149","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16555141,0.000015259731,0.8265944,0.000617661,0.00023893964,0.0016874453,0.00006837714,0.00044898692,0.0047774855],"genre_scores_gemma":[0.31651595,0.00027411955,0.6819395,0.0006699122,0.00005589058,0.00014673261,0.00007654645,0.000057894762,0.0002634689],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998965,0.000020044185,0.00039528188,0.00019059471,0.00013586627,0.00029321332],"domain_scores_gemma":[0.9990831,0.00015501933,0.00014910908,0.00045179963,0.0000501976,0.00011075363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016342921,0.0001758214,0.00034554052,0.0002101454,0.00008942303,0.00002092203,0.00013950537,0.00006932938,0.0000022238933],"category_scores_gemma":[0.00023466742,0.00016566901,0.00011654853,0.00026389887,0.00009223526,0.00016851835,0.000031787953,0.0002243008,0.000005265495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034286296,0.005973222,0.20268133,0.004446153,0.00032754513,0.0002256607,0.0052298447,0.0034600873,0.06677373,0.03391631,0.2799826,0.3935549],"study_design_scores_gemma":[0.0034177138,0.0006866298,0.01568833,0.00014284499,0.000096983,0.00016760742,0.00015250966,0.86012477,0.0021098868,0.00326492,0.11367589,0.0004719124],"about_ca_topic_score_codex":0.000003098791,"about_ca_topic_score_gemma":0.0000014120836,"teacher_disagreement_score":0.85666466,"about_ca_system_score_codex":0.000041341602,"about_ca_system_score_gemma":0.000026095422,"threshold_uncertainty_score":0.67557865},"labels":[],"label_agreement":null},{"id":"W2080329798","doi":"10.1063/1.4818797","title":"Some classes of renormalizable tensor models","year":2013,"lang":"en","type":"article","venue":"Journal of Mathematical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Tensor (intrinsic definition); Rank (graph theory); Physics; Mathematical physics; Function (biology); Tensor field; Tensor density; Simple (philosophy); Theoretical physics; Mathematics; Pure mathematics; Exact solutions in general relativity; Combinatorics; Quantum mechanics; Philosophy","score_opus":0.10338835903557786,"score_gpt":0.3527400115788212,"score_spread":0.24935165254324332,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080329798","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16235638,0.0002145202,0.8265798,0.003372395,0.00003360536,0.0004632304,0.000004080431,0.000057847687,0.0069181533],"genre_scores_gemma":[0.77493405,0.00012937984,0.22398949,0.00032615958,0.00024212217,0.0000092246155,6.428326e-7,0.000022890878,0.00034601745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992263,0.000008341202,0.00039453138,0.000054832235,0.00021520126,0.00010084267],"domain_scores_gemma":[0.99908644,0.00009288179,0.0002739429,0.0001905976,0.0002735213,0.00008258782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000746451,0.00007100761,0.00030840148,0.000029659408,0.000017521734,0.0000072864195,0.00009112869,0.000026275566,0.000040146613],"category_scores_gemma":[0.000058280377,0.000048638998,0.00011978062,0.00008548894,0.00006326759,0.00028540895,0.00002494782,0.00016191187,0.00001635605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047011876,0.001957488,0.00016532032,0.00076858146,0.000101845726,0.000015378811,0.00019957409,0.00077253225,0.087444276,0.88084745,0.022260088,0.0054204226],"study_design_scores_gemma":[0.0002497404,0.00016173025,0.000086737076,0.00018899344,0.00006335686,0.00010296211,0.000028078353,0.010034503,0.018431574,0.970319,0.00028554827,0.000047774247],"about_ca_topic_score_codex":7.207565e-7,"about_ca_topic_score_gemma":3.2619072e-9,"teacher_disagreement_score":0.6125777,"about_ca_system_score_codex":0.000014610733,"about_ca_system_score_gemma":0.00003137155,"threshold_uncertainty_score":0.19834407},"labels":[],"label_agreement":null},{"id":"W2080423736","doi":"10.1016/j.nurt.2007.05.004","title":"Magnetic Resonance Imaging of Myelin","year":2007,"lang":"en","type":"review","venue":"Neurotherapeutics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":324,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada","keywords":"Myelin; Diffusion imaging; Magnetic resonance imaging; Diffusion MRI; Magnetization transfer; Neuroscience; Nuclear magnetic resonance; Neurology; T2 relaxation; In vivo magnetic resonance spectroscopy; Relaxation (psychology); Medicine; Psychology; Physics; Radiology; Central nervous system","score_opus":0.19439852431245547,"score_gpt":0.44790907994188484,"score_spread":0.25351055562942937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080423736","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[5.5864984e-7,0.99370444,0.0025007133,0.00009907181,0.000058725313,0.0010208458,0.000030457477,0.000175301,0.0024099003],"genre_scores_gemma":[0.0000038681524,0.9884536,0.009505244,0.0009799469,0.000119540746,0.0000619887,0.0000153919,0.0001359371,0.00072443264],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998506,0.000035871417,0.00060735067,0.00038188702,0.00021711612,0.00025177829],"domain_scores_gemma":[0.9986582,0.00014746434,0.00024308416,0.0007974692,0.00008030973,0.00007349658],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009864184,0.00030203845,0.0009830812,0.0002066453,0.000033435146,0.0000073666015,0.0002159792,0.00011358624,0.00003903388],"category_scores_gemma":[0.000020428186,0.00026258003,0.00031972775,0.00045221826,0.00014204485,0.000019184155,0.00003618919,0.0005144925,0.000020783347],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000053330114,0.000061079445,0.000032775242,0.002417972,0.0000043098235,0.00002533057,0.0000047583317,3.1594535e-8,0.00001636425,0.0004498415,0.00016953798,0.99681264],"study_design_scores_gemma":[0.00014671397,0.00008738734,0.00003298902,0.003570285,0.0004021156,0.00026511698,0.0000011014428,0.000022598912,0.000038820133,0.00013711919,0.99512905,0.000166702],"about_ca_topic_score_codex":0.0000015700546,"about_ca_topic_score_gemma":1.433815e-7,"teacher_disagreement_score":0.996646,"about_ca_system_score_codex":0.000035436267,"about_ca_system_score_gemma":0.000119907316,"threshold_uncertainty_score":0.99998266},"labels":[],"label_agreement":null},{"id":"W2081139805","doi":"10.1371/journal.pone.0072375","title":"White Matter Deficits in Psychopathic Offenders and Correlation with Factor Structure","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ministry of Community Safety and Correctional Services; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Alliance for Research on Schizophrenia and Depression; American Psychiatric Institute for Research and Education; AstraZeneca; Pfizer","keywords":"White matter; Fractional anisotropy; Psychology; Psychopathy; Diffusion MRI; Amygdala; Orbitofrontal cortex; Prefrontal cortex; Neuroscience; Voxel; Personality; Medicine; Magnetic resonance imaging; Artificial intelligence; Cognition; Computer science","score_opus":0.06043499436491861,"score_gpt":0.2714874023309725,"score_spread":0.2110524079660539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081139805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99379146,0.000026717582,0.0019517839,0.003207231,0.00000343699,0.00051787985,0.000005385017,0.000060335522,0.00043578146],"genre_scores_gemma":[0.98409253,0.000017096554,0.014836319,0.0007264048,0.000014784645,0.000045272336,0.0000103622615,0.00001552744,0.00024171085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99957675,0.0000065974787,0.000082664104,0.00015011738,0.00009446841,0.00008942411],"domain_scores_gemma":[0.99973285,0.000012158918,0.000032539116,0.00014806271,0.000034021723,0.000040381852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000008819239,0.00006856933,0.00010595852,0.000052970176,0.00002009829,0.0000093485705,0.000022504099,0.000034886674,0.00015928816],"category_scores_gemma":[0.0000057621537,0.000053583208,0.0000061218875,0.00009134713,0.000027871725,0.00007395176,0.0000089048945,0.00016298937,0.000021520773],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016562346,0.00012815403,0.97968096,0.00005317671,0.000007939017,0.0000012595228,0.000095775904,0.0000031372044,0.019421246,0.00004730111,0.00018633732,0.0003581543],"study_design_scores_gemma":[0.00042201614,0.000077537785,0.9955495,0.00017257212,0.00002520492,0.0000125521165,0.00001867774,0.0010538518,0.001572885,0.0010011472,0.00001845344,0.00007558989],"about_ca_topic_score_codex":0.0000075283533,"about_ca_topic_score_gemma":0.000004330925,"teacher_disagreement_score":0.017848361,"about_ca_system_score_codex":0.000013620644,"about_ca_system_score_gemma":0.0000060944076,"threshold_uncertainty_score":0.21850598},"labels":[],"label_agreement":null},{"id":"W2081608119","doi":"10.1016/j.jmr.2006.09.008","title":"Anisotropic diffusion of metabolites in peripheral nerve using diffusion weighted magnetic resonance spectroscopy at ultra-high field","year":2006,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Nuclear magnetic resonance; Chemistry; Phosphocreatine; Anisotropy; Effective diffusion coefficient; Creatine; Diffusion; Diffusion MRI; Nuclear magnetic resonance spectroscopy; Fractional anisotropy; Choline; White matter; Taurine; Analytical Chemistry (journal); Magnetic resonance imaging; Biochemistry; Endocrinology; Physics; Amino acid","score_opus":0.016745045602997374,"score_gpt":0.28950365755501134,"score_spread":0.27275861195201395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081608119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9562535,0.040375456,0.001563138,0.0009965516,0.000089090085,0.00033193492,0.000009954354,0.000023150998,0.00035717836],"genre_scores_gemma":[0.9082195,0.004190772,0.08599133,0.00020912664,0.0002383948,0.000009906,0.0000035552964,0.000036529043,0.0011008551],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9979553,0.000070059396,0.0009076581,0.00028553078,0.00045057043,0.000330875],"domain_scores_gemma":[0.9987865,0.000110843735,0.0004486298,0.00038642946,0.00017698109,0.00009061992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013684691,0.00022754286,0.0005909372,0.00019808659,0.00007852831,0.00001500749,0.00022021173,0.00009994806,0.0002220635],"category_scores_gemma":[0.00007632104,0.00018863544,0.00015949868,0.00046003074,0.00012960595,0.00010641938,0.00006074705,0.00037561532,0.0000013194621],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006567889,0.00042274114,0.08065733,0.000059285263,0.0000018312176,0.0001518175,0.00005934099,0.000016700438,0.9009242,0.000757619,0.00070945837,0.015582889],"study_design_scores_gemma":[0.004002354,0.0021206653,0.7151271,0.00079667347,0.00010190741,0.0006329869,0.000027444774,0.002219794,0.23028387,0.004123499,0.04028798,0.00027571453],"about_ca_topic_score_codex":0.00022855605,"about_ca_topic_score_gemma":0.00002353179,"teacher_disagreement_score":0.67064035,"about_ca_system_score_codex":0.0001410594,"about_ca_system_score_gemma":0.00006725387,"threshold_uncertainty_score":0.769233},"labels":[],"label_agreement":null},{"id":"W2081768396","doi":"10.1016/j.eplepsyres.2014.08.023","title":"Diffusion abnormalities of the corpus callosum in patients with malformations of cortical development and epilepsy","year":2014,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundação de Amparo à Pesquisa do Estado de São Paulo; Canadian Institutes of Health Research; Alberta Innovates; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Alberta Innovates - Health Solutions","keywords":"Polymicrogyria; Corpus callosum; Cortical dysplasia; Epilepsy; Diffusion MRI; Fractional anisotropy; White matter; Splenium; Magnetic resonance imaging; Schizencephaly; Medicine; Psychology; Pathology; Neuroscience; Radiology","score_opus":0.06345972487955862,"score_gpt":0.35026828277603755,"score_spread":0.28680855789647897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081768396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964726,0.000011769677,0.0013408777,0.0004099297,0.000007913531,0.00049722084,0.0000060483967,0.0000121964595,0.0012414199],"genre_scores_gemma":[0.9938078,0.00001546934,0.005877342,0.00003778544,0.0000067737337,0.000052738447,0.000009536429,0.000008756449,0.0001838032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989131,0.00009101628,0.00027122925,0.0001232416,0.00042136878,0.00018003957],"domain_scores_gemma":[0.99918985,0.00018989811,0.000060482707,0.00028809998,0.00021557801,0.00005609208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042194207,0.000061564,0.0001563196,0.000113258095,0.00010035666,0.0000042486217,0.00010401689,0.000031849086,0.000011586556],"category_scores_gemma":[0.00017971291,0.0000381944,0.000016463871,0.00029173758,0.0003456648,0.000043753087,0.00013592168,0.00028167493,0.0000013703125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010541844,0.00022405974,0.9880209,0.00008717751,0.0000037108873,3.1426353e-7,0.00030566167,0.0000020882271,0.0005019577,0.0058636777,0.00008694498,0.004798116],"study_design_scores_gemma":[0.00070679054,0.00022197432,0.99140024,0.00016329352,0.0000042812662,0.0000024191497,0.000061143066,0.00025445514,0.004666964,0.0004086751,0.0020697932,0.00003995594],"about_ca_topic_score_codex":0.000031000338,"about_ca_topic_score_gemma":0.00001269243,"teacher_disagreement_score":0.0054550027,"about_ca_system_score_codex":0.000029471796,"about_ca_system_score_gemma":0.00006389557,"threshold_uncertainty_score":0.15575226},"labels":[],"label_agreement":null},{"id":"W2081828863","doi":"10.1016/j.neuroimage.2013.05.054","title":"Networks of anatomical covariance","year":2013,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":434,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Covariance; Neuroscience; Diffusion MRI; Neuroimaging; Cognition; Computer science; Neuroplasticity; Psychology; Functional connectivity; Artificial intelligence; Cognitive psychology; Mathematics; Magnetic resonance imaging; Medicine; Statistics","score_opus":0.16851715130382555,"score_gpt":0.42858435873199624,"score_spread":0.2600672074281707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081828863","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016659499,0.97975284,0.01647497,0.00008991329,0.000072172086,0.0013844859,0.000028770859,0.0002118339,0.001983335],"genre_scores_gemma":[0.000012722843,0.9850955,0.013581983,0.00021436857,0.00014194135,0.00019765463,0.000068498826,0.00009417517,0.0005931531],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99854594,0.000052262156,0.0005535262,0.00046546382,0.00014886814,0.0002339586],"domain_scores_gemma":[0.99840003,0.00014286191,0.00034138424,0.00092475006,0.00007269477,0.000118281685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059143236,0.0003004189,0.0013913376,0.00011319593,0.000031458105,0.000012259299,0.00024933982,0.00017918734,0.0000940981],"category_scores_gemma":[0.000071401424,0.00024280448,0.00039874724,0.00037394723,0.0001417515,0.000046283538,0.000119376404,0.00069358875,0.000066221786],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032641578,0.00009211512,0.0000038233497,0.004385527,0.000022138007,0.000042786938,9.917575e-7,0.0000011693094,0.000025634457,0.0013228927,0.0072131227,0.98688656],"study_design_scores_gemma":[0.0001092834,0.00005572199,0.000018185387,0.0025232115,0.00037999,0.00023992955,2.2770367e-7,0.00023779315,0.000008546937,0.0000933651,0.9961801,0.00015364772],"about_ca_topic_score_codex":0.0000034159164,"about_ca_topic_score_gemma":4.516682e-8,"teacher_disagreement_score":0.988967,"about_ca_system_score_codex":0.00003008347,"about_ca_system_score_gemma":0.00009412243,"threshold_uncertainty_score":0.990128},"labels":[],"label_agreement":null},{"id":"W2081903382","doi":"10.1109/jbhi.2014.2367026","title":"Multimodality Neurological Data Visualization With Multi-VOI-Based DTI Fiber Dynamic Integration","year":2014,"lang":"en","type":"article","venue":"IEEE Journal of Biomedical and Health Informatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CancerCare Manitoba; University of Winnipeg; Centre for Imaging Technology Commercialization; Western University","funders":"Canadian Institutes of Health Research","keywords":"Multimodality; Visualization; Computer science; Data visualization; Medical imaging; Artificial intelligence; Computer vision; World Wide Web","score_opus":0.17133119978234487,"score_gpt":0.44995263127333024,"score_spread":0.2786214314909854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081903382","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043870095,0.000025984424,0.9443337,0.0114149805,0.00005003425,0.0002283456,0.00001894561,0.000041035153,0.000016895372],"genre_scores_gemma":[0.5898816,0.00023274418,0.40107137,0.008523669,0.00011125952,0.0000041975745,0.00014730397,0.000012197832,0.000015686432],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985753,0.00004251375,0.0008209262,0.00008785589,0.00031658373,0.0001567666],"domain_scores_gemma":[0.99862456,0.00007667378,0.00059965666,0.0002547243,0.00014876704,0.00029561698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084836443,0.000104140054,0.00028518407,0.00012013319,0.000096926415,0.00001816106,0.00013624215,0.000071142924,0.00000934526],"category_scores_gemma":[0.00013291267,0.000062862935,0.000025065265,0.00016310951,0.0001660537,0.00018650484,0.0000291006,0.00033595995,0.0000023566593],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007765763,0.0019059515,0.0076490575,0.0019401244,0.00005526993,0.00002034636,0.00078557024,0.00026012442,0.00048227422,0.00062339567,0.00975882,0.9757425],"study_design_scores_gemma":[0.0020518557,0.0020380742,0.015357854,0.0002879202,0.000038303355,0.00028673463,0.000034180823,0.9477173,0.000055167835,0.00012291827,0.03192123,0.00008842608],"about_ca_topic_score_codex":0.00000587519,"about_ca_topic_score_gemma":0.000002888367,"teacher_disagreement_score":0.97565407,"about_ca_system_score_codex":0.000030138866,"about_ca_system_score_gemma":0.0001658107,"threshold_uncertainty_score":0.2563476},"labels":[],"label_agreement":null},{"id":"W2082320904","doi":"10.1109/mmbia.2012.6164765","title":"Reconstruction of HARDI using compressed sensing and its application to contrast HARDI","year":2012,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion imaging; Compressed sensing; Contrast (vision); Artificial intelligence; Diffusion MRI; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging","score_opus":0.08458415834292106,"score_gpt":0.36080407214977606,"score_spread":0.276219913806855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082320904","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4444585,0.000058433667,0.55360985,0.00032879531,0.000022694232,0.00043760444,0.000003985079,0.00008536212,0.0009947735],"genre_scores_gemma":[0.8869357,0.000012474736,0.11272676,0.0002032517,0.00006081357,0.0000066581715,0.0000032892508,0.000010103825,0.000040955936],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99954987,0.000008665113,0.00014514133,0.000121464924,0.00006207831,0.0001128125],"domain_scores_gemma":[0.99959886,0.000021820544,0.000057407244,0.00014609053,0.00008192718,0.00009391648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006596252,0.000062656596,0.00014195373,0.000050981962,0.00004579904,0.000003758604,0.000017713955,0.000026391926,0.000008151499],"category_scores_gemma":[0.000019761364,0.000058968923,0.000020604406,0.00010434119,0.00002546155,0.00008286403,0.00002216442,0.00005400987,0.0000029397863],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001711062,0.000023592576,0.0037435477,0.000025924142,0.000006594461,1.1787983e-7,0.000027620354,0.000014516424,0.9408973,0.0014110865,0.00007843982,0.053754177],"study_design_scores_gemma":[0.00055421685,0.00004585509,0.020461082,0.00011871364,0.0001040858,0.00044438825,0.00008177039,0.042644195,0.9247612,0.00033909903,0.010279021,0.00016640723],"about_ca_topic_score_codex":0.000024998197,"about_ca_topic_score_gemma":5.937529e-7,"teacher_disagreement_score":0.44247717,"about_ca_system_score_codex":0.000018489693,"about_ca_system_score_gemma":0.000007299615,"threshold_uncertainty_score":0.2404683},"labels":[],"label_agreement":null},{"id":"W2082419792","doi":"10.1089/neu.2007.0462","title":"Characterizing White Matter Damage in Rat Spinal Cord with Quantitative MRI and Histology","year":2008,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Health Canada","keywords":"Luxol fast blue stain; White matter; Fractional anisotropy; Myelin; Anatomy; Corticospinal tract; Spinal cord; Pathology; Diffusion MRI; Superior longitudinal fasciculus; Axon; Fasciculus; Magnetic resonance imaging; Diffuse axonal injury; Spinal cord injury; Medicine; Biology; Central nervous system; Traumatic brain injury; Neuroscience; Internal medicine; Radiology","score_opus":0.14436926360356772,"score_gpt":0.3889712740701122,"score_spread":0.2446020104665445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082419792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98845273,0.00006385696,0.002293311,0.008581393,0.000034041434,0.00014216869,0.0000010365592,0.000012671615,0.00041879262],"genre_scores_gemma":[0.97690785,0.00019118687,0.020834994,0.0018598399,0.000037778173,0.0000049585956,6.34992e-7,0.000017395148,0.00014537042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935466,0.000027866785,0.0002648446,0.00012725804,0.00010351733,0.000121872756],"domain_scores_gemma":[0.99949586,0.000027753187,0.00021856655,0.00011532071,0.000071169314,0.00007133094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005672254,0.00009208483,0.0002494735,0.0001620914,0.000044567038,0.000005680049,0.000058420846,0.000023422666,0.000019197245],"category_scores_gemma":[0.000014797361,0.0000708591,0.000030796284,0.00012110119,0.00013002437,0.00013440581,0.000016810667,0.00035512852,0.0000029719529],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0061871638,0.0004260324,0.8175204,0.00011141922,0.000026308591,0.008138886,0.00069959974,0.000009836781,0.15973106,0.0005050307,0.0038244918,0.0028197959],"study_design_scores_gemma":[0.0010007548,0.0029321527,0.96890914,0.00015305524,0.000022791648,0.016676974,0.000042021304,0.00005241501,0.001576707,0.000091094575,0.008459654,0.000083260646],"about_ca_topic_score_codex":0.0000017950134,"about_ca_topic_score_gemma":0.0000015145067,"teacher_disagreement_score":0.15815435,"about_ca_system_score_codex":0.000022249285,"about_ca_system_score_gemma":0.000029233328,"threshold_uncertainty_score":0.28895503},"labels":[],"label_agreement":null},{"id":"W2083057497","doi":"10.1038/jcbfm.2012.37","title":"Changes in Callosal Motor Fiber Integrity after Subcortical Stroke of the Pyramidal Tract","year":2012,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Jewish General Hospital; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Pyramidal tracts; Corpus callosum; Stroke (engine); Fiber tract; Disinhibition; Medicine; Corticospinal tract; Fractional anisotropy; Motor cortex; Cardiology; Neuroscience; Internal medicine; Magnetic resonance imaging; Pathology; Anatomy; Psychology; Radiology; Stimulation; Psychiatry","score_opus":0.0344381441143804,"score_gpt":0.31213845907551646,"score_spread":0.27770031496113606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083057497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995353,0.0010205487,0.00021140484,0.002761939,0.00022289211,0.00024713975,0.000035276727,0.000015130037,0.00013265689],"genre_scores_gemma":[0.9813639,0.000111435955,0.017089557,0.0004175915,0.0007667592,0.000013011672,9.0348595e-7,0.000023157889,0.00021366987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859846,0.00007355078,0.0005203265,0.00011528032,0.0003888874,0.00030351095],"domain_scores_gemma":[0.9990416,0.000064299216,0.00027457386,0.00029129614,0.00014211026,0.00018611421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034550746,0.00015731996,0.00048333354,0.00013077681,0.000025865555,0.000008869932,0.00019610846,0.000103675644,0.00023475509],"category_scores_gemma":[0.00017527072,0.00009586549,0.0002728049,0.00019236613,0.00012791977,0.00018133863,0.00006763032,0.0009477856,0.000003947343],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010692745,0.0052420334,0.77558976,0.00016177673,0.00024252386,0.00009383431,0.0009776708,0.000010213517,0.19165406,0.0030307618,0.0007247586,0.021203313],"study_design_scores_gemma":[0.0014532527,0.00013798494,0.91559553,0.00010658551,0.00049890525,0.00052876724,0.000035161003,0.000065823886,0.07448001,0.00037517492,0.006607737,0.00011505687],"about_ca_topic_score_codex":0.000012306676,"about_ca_topic_score_gemma":0.000007226608,"teacher_disagreement_score":0.14000575,"about_ca_system_score_codex":0.000022219396,"about_ca_system_score_gemma":0.00007511781,"threshold_uncertainty_score":0.41177097},"labels":[],"label_agreement":null},{"id":"W2083427562","doi":"10.1016/j.mri.2008.01.038","title":"Spatial normalization, bulk motion correction and coregistration for functional magnetic resonance imaging of the human cervical spinal cord and brainstem","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Canada Research Chairs","keywords":"Brainstem; Functional magnetic resonance imaging; Spinal cord; Magnetic resonance imaging; Normalization (sociology); Spatial normalization; Region of interest; Computer science; Artificial intelligence; Neuroscience; Pattern recognition (psychology); Medicine; Psychology; Radiology","score_opus":0.03731751727197344,"score_gpt":0.3007095883055636,"score_spread":0.2633920710335902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2083427562","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.716315,0.018956838,0.25438252,0.0059422744,0.0004927828,0.0026367435,0.000046887188,0.0002839279,0.0009430901],"genre_scores_gemma":[0.99460167,0.0002509026,0.0036850884,0.00043328753,0.00016612804,0.00012642804,0.000029231982,0.000031687756,0.0006755579],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99862355,0.00003591066,0.0004058118,0.00044129795,0.0002661654,0.00022726433],"domain_scores_gemma":[0.9991323,0.000057591064,0.00017854136,0.00031737093,0.00024527646,0.00006895868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001376577,0.0001854555,0.00021383587,0.00008508029,0.00048377534,0.00002884464,0.000085153624,0.000038089092,0.000017540444],"category_scores_gemma":[0.00010847088,0.00016744144,0.00005867827,0.00023375092,0.00048882427,0.00015639953,0.00006526741,0.00017261792,5.250945e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029597036,0.00008526148,0.52366155,0.000100419595,0.0000011331355,0.000006020829,0.000071028575,0.0000098203045,0.01025264,0.0017041723,0.0013651346,0.46244684],"study_design_scores_gemma":[0.0011574284,0.00030889493,0.9400907,0.00020501805,0.00004018692,0.00074187753,0.000029494482,0.03922417,0.0016775806,0.00068890024,0.015681498,0.00015422307],"about_ca_topic_score_codex":0.0001168232,"about_ca_topic_score_gemma":0.000015190479,"teacher_disagreement_score":0.4622926,"about_ca_system_score_codex":0.000048869657,"about_ca_system_score_gemma":0.000052088482,"threshold_uncertainty_score":0.6828064},"labels":[],"label_agreement":null},{"id":"W2084113628","doi":"10.1227/01.neu.0000367613.09324.da","title":"In Vivo Visualization of Cranial Nerve Pathways in Humans Using Diffusion-Based Tractography","year":2010,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Queen's University; University of Toronto","funders":"","keywords":"Tractography; Anatomy; Medicine; Cranial nerves; Diffusion MRI; Magnetic resonance imaging; Radiology","score_opus":0.0596501691124415,"score_gpt":0.3452522085990344,"score_spread":0.2856020394865929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084113628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99520564,0.0000049076107,0.003989041,0.00017754121,0.00014093671,0.0002709184,0.000011347232,0.00007012729,0.00012951402],"genre_scores_gemma":[0.9977713,0.000009145929,0.0016010767,0.0005032471,0.000050525512,0.000022844693,0.000007215921,0.000028243554,0.0000063617995],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990686,0.00002904709,0.0003601037,0.00023431242,0.00014957976,0.00015831096],"domain_scores_gemma":[0.9993816,0.00013736675,0.000118507574,0.00027341951,0.000041166153,0.000047942314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012245621,0.00010636845,0.00022507457,0.0004393593,0.000030275785,0.0000063358357,0.000056714947,0.0000706244,0.000046243727],"category_scores_gemma":[0.00010204314,0.00010770808,0.00008826881,0.0006270167,0.000068737536,0.000075814765,0.000015653926,0.00025239176,4.0623402e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004015156,0.00034807588,0.22492939,0.000026030904,4.3201013e-7,0.000040806186,0.000025542853,0.00006391266,0.7739478,0.0003769749,0.00004784555,0.00015305499],"study_design_scores_gemma":[0.0021232096,0.00020047357,0.5811397,0.00027736346,0.00003371036,0.00003945604,0.000017826887,0.03412961,0.37609437,0.0018717644,0.0036829326,0.00038962203],"about_ca_topic_score_codex":0.00006585041,"about_ca_topic_score_gemma":0.000023743456,"teacher_disagreement_score":0.3978534,"about_ca_system_score_codex":0.000010445507,"about_ca_system_score_gemma":0.00004951186,"threshold_uncertainty_score":0.43922082},"labels":[],"label_agreement":null},{"id":"W2084169411","doi":"10.1002/jmri.22577","title":"Impact of outliers on diffusion tensor and Q‐ball imaging: Clinical implications and correction strategies","year":2011,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"European Commission","keywords":"Diffusion MRI; Outlier; Medicine; Radiology; Computer science; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Artificial intelligence","score_opus":0.08333704346863446,"score_gpt":0.4001292119955707,"score_spread":0.31679216852693626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084169411","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98888093,0.003448376,0.0041028867,0.0015280445,0.00009420472,0.00024851208,0.000004839758,0.00003336831,0.0016588342],"genre_scores_gemma":[0.9860529,0.002287188,0.011350324,0.00015702086,0.000068095105,0.0000049917858,5.5099883e-7,0.000018769379,0.00006019421],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989131,0.00003741963,0.0005606784,0.00019640186,0.00014037405,0.0001520175],"domain_scores_gemma":[0.9988649,0.000123632,0.0004021129,0.00023289218,0.000237191,0.0001392677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002513372,0.00013226249,0.0003065287,0.00015764014,0.000065966735,0.00002239124,0.00008356561,0.000027710379,0.00001571762],"category_scores_gemma":[0.0001582703,0.000100189754,0.000117282434,0.00012558042,0.00023538603,0.00017614792,0.000038098766,0.0003210421,5.51973e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020823826,0.00019689482,0.7030746,0.000011459381,0.0000055078285,0.000014744136,0.00013953929,0.0000015739794,0.0057978923,0.0002259088,0.0009552649,0.2893684],"study_design_scores_gemma":[0.0008543483,0.00082592154,0.9918783,0.00019362316,0.00007265651,0.0009171448,0.0001715336,0.0014702234,0.0001475229,0.0019907025,0.0013931035,0.00008496363],"about_ca_topic_score_codex":0.000029726227,"about_ca_topic_score_gemma":5.3709255e-7,"teacher_disagreement_score":0.28928342,"about_ca_system_score_codex":0.00003213482,"about_ca_system_score_gemma":0.00008447476,"threshold_uncertainty_score":0.40856197},"labels":[],"label_agreement":null},{"id":"W2084428331","doi":"10.1016/j.apmr.2008.08.211","title":"Use of Diffusion Tensor Imaging to Examine Subacute White Matter Injury Progression in Moderate to Severe Traumatic Brain Injury","year":2008,"lang":"en","type":"article","venue":"Archives of Physical Medicine and Rehabilitation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Glasgow Coma Scale; White matter; Traumatic brain injury; Medicine; Diffuse axonal injury; Anesthesia; Cardiology; Psychology; Magnetic resonance imaging; Radiology; Pathology; Psychiatry","score_opus":0.042605697692409884,"score_gpt":0.36168818275181747,"score_spread":0.31908248505940756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084428331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.969652,0.000013917419,0.0038149972,0.025444081,0.000008650499,0.00092592096,0.000011601863,0.000027948307,0.00010086346],"genre_scores_gemma":[0.95498556,0.000014716701,0.043857846,0.00089932315,0.000040087365,0.00008108326,0.000013169977,0.000018059432,0.00009017825],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989558,0.00006268953,0.00036834853,0.00028316476,0.0001876471,0.00014233492],"domain_scores_gemma":[0.9985467,0.0009242991,0.00009363749,0.0002571372,0.0000547701,0.00012346501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007055898,0.00013436825,0.00038635166,0.0003435525,0.00003979653,0.0000019839424,0.000052051164,0.000017110526,0.0000042104593],"category_scores_gemma":[0.0004223387,0.000096529424,0.000053158125,0.00029680273,0.0002932923,0.000106878935,0.00006051484,0.00012317149,0.0000012594694],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001368132,0.0008555145,0.26103282,0.0006776066,0.000010195782,0.000005335847,0.024095016,0.00008276725,0.59442264,0.00039833796,0.0021924975,0.11485912],"study_design_scores_gemma":[0.00079227303,0.0030191832,0.97881186,0.0025216944,0.000029744851,0.000014395415,0.00038723057,0.0066654305,0.0037418955,0.0036031383,0.00026884789,0.0001443171],"about_ca_topic_score_codex":0.000031695272,"about_ca_topic_score_gemma":0.0000013337398,"teacher_disagreement_score":0.71777904,"about_ca_system_score_codex":0.000010817179,"about_ca_system_score_gemma":0.000013508849,"threshold_uncertainty_score":0.39363557},"labels":[],"label_agreement":null},{"id":"W2084489466","doi":"10.1016/j.jelectrocard.2008.12.003","title":"Image-based models of cardiac structure with applications in arrhythmia and defibrillation studies","year":2009,"lang":"en","type":"article","venue":"Journal of Electrocardiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Heart, Lung, and Blood Institute; Biotechnology and Biological Sciences Research Council","keywords":"Defibrillation; Computer science; Diffusion MRI; Set (abstract data type); Computational model; Finite element method; Algorithm; Artificial intelligence; Magnetic resonance imaging; Medicine; Cardiology; Structural engineering; Engineering","score_opus":0.030540775169632745,"score_gpt":0.335656917742491,"score_spread":0.30511614257285824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084489466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8277798,0.0060269455,0.16299799,0.002408361,0.000010230186,0.00043540268,0.0000048352063,0.000020871877,0.0003155154],"genre_scores_gemma":[0.9361207,0.00085246336,0.06283276,0.00009655315,0.00008279988,0.0000039191536,0.0000029310684,0.000006233505,0.0000016640283],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99943376,0.00002975478,0.0002512244,0.00010130672,0.000079315316,0.00010466367],"domain_scores_gemma":[0.9993437,0.000069174945,0.00020876585,0.00012384285,0.00022183124,0.000032676588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008728171,0.00008014681,0.00044062125,0.00014623071,0.000022426835,0.0000019866714,0.000029674084,0.0000415067,2.9981553e-7],"category_scores_gemma":[0.000023635272,0.00005667236,0.000053547126,0.00018252188,0.00007685177,0.00005886814,0.00000479997,0.00017536212,3.0757363e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015007427,0.00008866382,0.043275908,0.00016716454,0.0004614694,0.0000398955,0.0002901337,0.012787657,0.875177,0.02338418,0.00039145225,0.042435687],"study_design_scores_gemma":[0.005912884,0.01256178,0.39527154,0.00059257157,0.0014615993,0.006371876,0.0005014485,0.005403506,0.18330657,0.381475,0.0063744094,0.0007668134],"about_ca_topic_score_codex":6.0555016e-7,"about_ca_topic_score_gemma":4.9816055e-7,"teacher_disagreement_score":0.69187045,"about_ca_system_score_codex":0.000037433645,"about_ca_system_score_gemma":0.00008081089,"threshold_uncertainty_score":0.23110318},"labels":[],"label_agreement":null},{"id":"W2084775462","doi":"10.1109/tpami.2012.184","title":"3D Stochastic Completion Fields for Mapping Connectivity in Diffusion MRI","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Pattern Analysis and Machine Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Spherical harmonics; Computer science; Artificial intelligence; Probability density function; Algorithm; Invariant (physics); Orientation (vector space); Imaging phantom; Computer vision; Mathematics; Geometry; Mathematical analysis; Physics","score_opus":0.06916264017012254,"score_gpt":0.34744422112829176,"score_spread":0.27828158095816924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084775462","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047353808,0.000046379377,0.9514006,0.000678694,0.000045358724,0.00036304348,0.000035366207,0.00005525952,0.0000215425],"genre_scores_gemma":[0.9954135,0.00011903224,0.0038145927,0.00042445876,0.00002547364,0.0001227088,0.000015862215,0.000011055245,0.000053362586],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992286,0.000022532748,0.0002298912,0.00024000583,0.00009572205,0.00018326189],"domain_scores_gemma":[0.9994444,0.0001676956,0.00005740975,0.00020901207,0.00003605119,0.00008542531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001473113,0.00012439315,0.00025899193,0.00032961238,0.000111487265,0.000010690091,0.000047054655,0.000048173177,0.00006233797],"category_scores_gemma":[0.00000757951,0.00011152248,0.00012903623,0.0004152881,0.000036527683,0.000067187604,0.0000019882395,0.00020322425,0.0000031429877],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013403148,0.0013807063,0.030101875,0.000117189,0.0002582678,0.0000025462687,0.00064580847,0.023818126,0.005101661,0.00016961456,0.000020347848,0.9382498],"study_design_scores_gemma":[0.000752603,0.00042771548,0.078437164,0.00020215193,0.001441822,0.000053220563,0.00019935753,0.855697,0.06066557,0.00087759236,0.0006693288,0.00057652354],"about_ca_topic_score_codex":0.00031532146,"about_ca_topic_score_gemma":0.00026815978,"teacher_disagreement_score":0.9480596,"about_ca_system_score_codex":0.00003526888,"about_ca_system_score_gemma":0.0000051165525,"threshold_uncertainty_score":0.45477545},"labels":[],"label_agreement":null},{"id":"W2085683875","doi":"10.4236/jbise.2014.78060","title":"Assessment of Mechanical Properties of Muscles from Multi-Parametric Magnetic Resonance Imaging","year":2014,"lang":"en","type":"article","venue":"Journal of Biomedical Science and Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital Notre-Dame; Philips (Canada); Polytechnique Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Rigor mortis; Magnetic resonance imaging; Principal component analysis; Medicine; Biomedical engineering; Materials science; Anatomy; Radiology; Computer science; Artificial intelligence","score_opus":0.035716416079520565,"score_gpt":0.313309431973785,"score_spread":0.27759301589426444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085683875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8444721,0.0012258801,0.15354449,0.00059803075,0.000059586488,0.000068766654,0.00000165364,0.000013573167,0.00001594051],"genre_scores_gemma":[0.8639572,0.00015080812,0.135814,0.00003472584,0.0000363111,0.0000013141176,1.2028869e-7,0.000003973844,0.0000014934991],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990016,0.000006131363,0.00032111185,0.00010355839,0.0004501478,0.00011741045],"domain_scores_gemma":[0.99943006,0.000056183195,0.00011717589,0.000106573425,0.00015529695,0.00013470436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005405992,0.00005733646,0.00020831586,0.00023053934,0.000024727378,0.0000074026525,0.00013726781,0.000019399304,0.0000032968621],"category_scores_gemma":[0.0005413076,0.00003951622,0.000033421307,0.0005208061,0.00028667494,0.00009089907,0.000052681768,0.00014127951,7.1001914e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004597383,0.000075049276,0.001391572,0.000036747282,0.0000016372308,0.0000027445976,0.000018582119,0.000016870852,0.92748487,0.00024737127,0.000009612189,0.07071035],"study_design_scores_gemma":[0.0011449567,0.00063409476,0.3276361,0.0012051929,0.00006304018,0.00014565185,0.00007641939,0.5139743,0.15028511,0.00026874957,0.004423932,0.00014244195],"about_ca_topic_score_codex":0.000011044702,"about_ca_topic_score_gemma":7.849243e-8,"teacher_disagreement_score":0.77719975,"about_ca_system_score_codex":0.000025991672,"about_ca_system_score_gemma":0.00007360184,"threshold_uncertainty_score":0.16114248},"labels":[],"label_agreement":null},{"id":"W2085715764","doi":"10.1073/pnas.1422824112","title":"Hydration water mobility is enhanced around tau amyloid fibers","year":2015,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche; European Molecular Biology Laboratory; Centre National de la Recherche Scientifique; European Commission; Engineering and Physical Sciences Research Council; French Infrastructure for Integrated Structural Biology","keywords":"Fiber; Molecular dynamics; Chemistry; Neutron scattering; Diffusion; Chemical physics; Molecule; Core (optical fiber); Biophysics; Crystallography; Scattering; Materials science; Computational chemistry; Composite material; Thermodynamics; Organic chemistry; Physics; Optics","score_opus":0.12171947923610736,"score_gpt":0.38347568506141116,"score_spread":0.2617562058253038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085715764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97786224,0.000021324377,0.00006199487,0.01367382,0.000008821101,0.00030816707,0.0000058105134,0.00003285718,0.00802495],"genre_scores_gemma":[0.9918252,0.000009900215,0.0068550827,0.00091172016,0.000049990074,0.000024451674,3.0715782e-7,0.0000034175819,0.00031990506],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99872154,0.0000023549794,0.00022941153,0.00021428471,0.0007240273,0.000108381995],"domain_scores_gemma":[0.9993988,0.00002551289,0.00016608529,0.000012638103,0.00035156595,0.00004536305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064217864,0.00006655873,0.00011412098,0.000072666495,0.00009825309,0.000010759127,0.00027822301,0.000044023738,0.000008478837],"category_scores_gemma":[0.00020074713,0.000038504542,0.00005025794,0.00034137766,0.0005479329,0.00030378497,0.000077783436,0.00011801471,0.0000024841424],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021133927,0.000068431735,0.0018293413,0.000032685057,0.0000046501914,1.8965562e-9,0.00031784654,0.000031109583,0.98820597,0.0071521946,0.002019096,0.00031756292],"study_design_scores_gemma":[0.0001413973,0.000051527604,0.0064723077,0.000031792813,0.000009753283,0.0000055818778,0.00011076061,0.0007087074,0.8851508,0.10638889,0.0008863933,0.00004209305],"about_ca_topic_score_codex":0.0000031256313,"about_ca_topic_score_gemma":9.301486e-9,"teacher_disagreement_score":0.10305515,"about_ca_system_score_codex":0.00004782507,"about_ca_system_score_gemma":0.000028365419,"threshold_uncertainty_score":0.20188817},"labels":[],"label_agreement":null},{"id":"W2086269292","doi":"10.1109/isbi.2013.6556459","title":"K-confidence: Assessing uncertainty in tractography using K optimal paths","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Johns Hopkins University","keywords":"Tractography; Computer science; Confidence interval; Artificial intelligence; Mathematics; Diffusion MRI; Statistics; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.0967022986631205,"score_gpt":0.3991294447365487,"score_spread":0.30242714607342824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086269292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8517028,0.00003186074,0.14268033,0.0010046196,0.000015752445,0.0004303726,6.9629704e-7,0.00018813665,0.0039454354],"genre_scores_gemma":[0.8498191,0.000014872332,0.14945948,0.0005551993,0.000025169134,0.00004385907,0.000003284196,0.000012371671,0.000066648485],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99930465,0.00001155795,0.00018503057,0.00020822814,0.00010316382,0.00018738375],"domain_scores_gemma":[0.9995618,0.00004045923,0.000042757187,0.00022644593,0.000057641788,0.00007093521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006618848,0.00009141403,0.00014382551,0.00012587514,0.0000468976,0.000038574686,0.000058858688,0.00004203182,0.00020278487],"category_scores_gemma":[0.000023873448,0.00007636853,0.00005368692,0.00031404026,0.0000555712,0.00023549548,0.000022395388,0.00018845142,0.000010707731],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033251818,0.00089902483,0.15162322,0.00011857572,0.000030357609,0.00010648045,0.0003616247,0.0042141913,0.7091772,0.025921473,0.002123655,0.105390936],"study_design_scores_gemma":[0.0027537001,0.0002829706,0.48935458,0.0007656081,0.000118103795,0.0005851471,0.002268231,0.41298214,0.035218142,0.045201577,0.009338887,0.0011308935],"about_ca_topic_score_codex":0.0004054999,"about_ca_topic_score_gemma":0.0000021156848,"teacher_disagreement_score":0.6739591,"about_ca_system_score_codex":0.00003404038,"about_ca_system_score_gemma":0.00003589355,"threshold_uncertainty_score":0.31142184},"labels":[],"label_agreement":null},{"id":"W2086568497","doi":"10.1016/j.neuroimage.2006.01.042","title":"Mapping anatomical correlations across cerebral cortex (MACACC) using cortical thickness from MRI","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":559,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Cerebral cortex; Cortex (anatomy); Correlation; Neuroscience; Tractography; Anterior cingulate cortex; Population; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Mathematics; Cognition; Geometry","score_opus":0.06033597840904665,"score_gpt":0.3592093956409723,"score_spread":0.2988734172319257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086568497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76477087,0.000037203943,0.23130012,0.0013014682,0.0001295878,0.00041205445,0.00011383983,0.00051472924,0.0014201412],"genre_scores_gemma":[0.95930237,0.000008961122,0.038797054,0.0010335017,0.00033695568,0.000024009994,0.00014825191,0.00006655142,0.00028236886],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981776,0.00005297732,0.00043961595,0.00060515164,0.00027764516,0.00044703906],"domain_scores_gemma":[0.9988199,0.00019031485,0.00012442327,0.00061265397,0.000099178265,0.0001535426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008131323,0.00023025909,0.000323552,0.00007578318,0.00036309302,0.00006486538,0.00016783044,0.00011908812,0.000120579476],"category_scores_gemma":[0.00008603639,0.00023327865,0.00013855465,0.0004016732,0.0002494217,0.00016846182,0.00014373087,0.0007225959,0.000051088853],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000116861236,0.00066144014,0.25114706,0.0000383688,0.000027422275,0.00045553717,0.00015302029,0.00025474592,0.73507047,0.0055186874,0.004853516,0.0017028754],"study_design_scores_gemma":[0.0013360074,0.000054241973,0.8964812,0.00007717275,0.00008812216,0.00042262254,0.00008560727,0.079671,0.004432644,0.0039871978,0.012986301,0.0003778746],"about_ca_topic_score_codex":0.00023459046,"about_ca_topic_score_gemma":0.000009123319,"teacher_disagreement_score":0.73063785,"about_ca_system_score_codex":0.00007477566,"about_ca_system_score_gemma":0.000061212755,"threshold_uncertainty_score":0.95128274},"labels":[],"label_agreement":null},{"id":"W2087093896","doi":"10.1007/s00723-008-0095-7","title":"Quantitative Assessment of Injury in Rat Spinal Cords In Vivo by MRI of Water Diffusion Tensor","year":2008,"lang":"en","type":"article","venue":"Applied Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; White matter; Spinal cord; In vivo; Spinal cord injury; Pathology; Magnetic resonance imaging; Medicine; Anatomy; Radiology; Biology","score_opus":0.02979164940260054,"score_gpt":0.3440886748256232,"score_spread":0.3142970254230227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087093896","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99335665,0.00044470569,0.0021269186,0.0004499319,0.000012978414,0.00079683267,0.00001736489,0.000025299803,0.0027693105],"genre_scores_gemma":[0.9641018,0.0010737123,0.034081426,0.00013659272,0.0000064301053,0.00019160795,0.000006100745,0.000017103042,0.00038524013],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99889606,0.000016902874,0.00041341718,0.00027418847,0.00020600944,0.00019339708],"domain_scores_gemma":[0.99949515,0.000034397446,0.00008836706,0.00030117488,0.00004490144,0.000036025816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009490993,0.00012435144,0.00033767908,0.00011032937,0.0000217238,0.0000012896725,0.000102956205,0.000048943268,0.00005275274],"category_scores_gemma":[0.000010809773,0.00009922699,0.000031312487,0.00025193446,0.00020978728,0.000024281557,0.00005904048,0.00017780197,0.0000017581301],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004263237,0.00047608375,0.025731562,0.00007321355,0.0000010772167,0.0000146234315,0.00013240342,0.000005936156,0.9615218,0.0037115065,0.0016004582,0.006305025],"study_design_scores_gemma":[0.0033867531,0.0026610524,0.29103553,0.0003764439,0.00002154811,0.00002813118,0.00012479367,0.0019087765,0.6493215,0.0022972194,0.048506387,0.00033187988],"about_ca_topic_score_codex":0.000060579267,"about_ca_topic_score_gemma":0.000003632125,"teacher_disagreement_score":0.3122003,"about_ca_system_score_codex":0.00003711918,"about_ca_system_score_gemma":0.00003539541,"threshold_uncertainty_score":0.40463594},"labels":[],"label_agreement":null},{"id":"W2088897607","doi":"10.1560/e0wu-7ffh-31m6-vlyt","title":"Diffusion MR in Biological Systems: Tissue Compartments and Exchange","year":2003,"lang":"en","type":"article","venue":"Israel Journal of Chemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Chemistry; Tortuosity; Diffusion; Effective diffusion coefficient; Extracellular; Intracellular; Permeability (electromagnetism); Anomalous diffusion; Biophysics; Membrane; Thermodynamics; Porosity; Innovation diffusion; Physics; Biochemistry; Magnetic resonance imaging","score_opus":0.0774085790768602,"score_gpt":0.3612994564860374,"score_spread":0.2838908774091772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088897607","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99551433,0.0017830114,0.00083962415,0.0002465453,0.000021271184,0.00008825151,0.0000019632264,0.0000120255845,0.0014929774],"genre_scores_gemma":[0.99731994,0.00056778925,0.0017893569,0.00009451176,0.000049053077,0.0000046753116,0.0000016764254,0.000005600139,0.00016739998],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99951404,0.000013110724,0.00021681971,0.00008231388,0.00008652958,0.000087210996],"domain_scores_gemma":[0.99964553,0.000025633199,0.00011804484,0.000090624184,0.00004043941,0.000079735284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010066889,0.00006479022,0.00018223868,0.000022204104,0.000017711509,0.000006592412,0.00004204015,0.00004547247,0.000016975957],"category_scores_gemma":[0.000049279093,0.000048679394,0.000020442556,0.00005829192,0.000038359056,0.000025135489,0.000015135272,0.00016383128,8.262181e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047748883,0.0002652899,0.067898385,0.00014793231,0.00000902235,0.00017950732,0.000033296303,0.0000028008221,0.929143,0.00014522547,0.00088014186,0.0012476481],"study_design_scores_gemma":[0.004590059,0.00039665692,0.027081728,0.0010620366,0.0000658249,0.008617246,0.00047697584,0.00011427794,0.7004657,0.0012180295,0.25559893,0.0003125884],"about_ca_topic_score_codex":0.0000013986099,"about_ca_topic_score_gemma":4.8368747e-8,"teacher_disagreement_score":0.25471878,"about_ca_system_score_codex":0.000030176046,"about_ca_system_score_gemma":0.000014610203,"threshold_uncertainty_score":0.19850881},"labels":[],"label_agreement":null},{"id":"W2089346380","doi":"10.1016/j.neuroimage.2010.08.076","title":"Myelin water and T2 relaxation measurements in the healthy cervical spinal cord at 3.0T: Repeatability and changes with age","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Michael Smith Health Research BC; University of British Columbia; Cervical Spine Research Society","keywords":"White matter; Grey matter; Myelin; Spinal cord; Cohort; Confidence interval; Repeatability; Medicine; Nuclear medicine; Population; T2 relaxation; Magnetic resonance imaging; Psychology; Internal medicine; Central nervous system; Chemistry; Neuroscience; Radiology","score_opus":0.11607692546983402,"score_gpt":0.368692942884262,"score_spread":0.252616017414428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089346380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9732231,0.00002810348,0.00016036122,0.025468912,0.000021317408,0.00064372935,0.000003849792,0.000065707376,0.0003849311],"genre_scores_gemma":[0.9940315,0.000057665555,0.0028363408,0.002857856,0.00005036571,0.00007525595,0.000016294725,0.000016411994,0.000058302194],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99909234,0.00005385499,0.00012562262,0.00035758986,0.00019002828,0.00018053799],"domain_scores_gemma":[0.9993886,0.000033192337,0.000043545777,0.00042642793,0.000036545036,0.00007171528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003067402,0.00011142832,0.00013525835,0.000042128508,0.000118230026,0.000020798172,0.00006641237,0.000038515227,0.000011185491],"category_scores_gemma":[0.00005821691,0.0000639429,0.000012085943,0.00008120252,0.00017824332,0.000056651344,0.00006866311,0.00037619963,0.0000025448255],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003194012,0.00039985782,0.41042215,0.0003131429,0.0000068291556,0.0001871749,0.0005632401,3.0293512e-7,0.55025864,0.00041129743,0.00047519224,0.033768177],"study_design_scores_gemma":[0.00084589614,0.0011509816,0.97439295,0.000026888169,0.000024372339,0.0003784527,0.000016818236,0.000049159633,0.0068711913,0.0003770089,0.015766805,0.00009947754],"about_ca_topic_score_codex":0.00002577648,"about_ca_topic_score_gemma":0.00022420177,"teacher_disagreement_score":0.5639708,"about_ca_system_score_codex":0.000016516124,"about_ca_system_score_gemma":0.0000088669785,"threshold_uncertainty_score":0.26075158},"labels":[],"label_agreement":null},{"id":"W2090877723","doi":"10.3389/fpsyt.2013.00175","title":"A Comparison of Neuroimaging Findings in Childhood Onset Schizophrenia and Autism Spectrum Disorder: A Review of the Literature","year":2013,"lang":"en","type":"review","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Ontario Brain Institute","keywords":"Neuroimaging; Autism spectrum disorder; White matter; Diffusion MRI; Psychology; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; Neuroscience; Autism; Brain size; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.024290084968578367,"score_gpt":0.3572098224094052,"score_spread":0.3329197374408268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090877723","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00016091375,0.9939778,0.00020358377,0.0026098082,0.0005056642,0.0022275588,0.000048422065,0.000033692944,0.00023259451],"genre_scores_gemma":[0.00017295558,0.9689499,0.030327613,0.00019755185,0.000025144724,0.0001357529,0.00003158691,0.00007074487,0.00008871707],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982274,0.000100931975,0.00088365696,0.00041969353,0.00016013085,0.00020819448],"domain_scores_gemma":[0.9986643,0.00002721016,0.0005237218,0.00072389276,0.000010543669,0.0000503402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012534834,0.00032194497,0.0017908752,0.00039097032,0.00002967298,0.000009068011,0.0003076538,0.0001457735,0.000011330918],"category_scores_gemma":[0.000053007894,0.00022792282,0.00027250597,0.0011516011,0.00013959911,0.000045784815,0.00012593629,0.0009697455,9.065002e-7],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001702373,0.00081495784,0.12958519,0.2093723,0.00007837089,0.0000040291784,0.00020594332,2.2024439e-7,5.615282e-7,0.001972875,0.09348338,0.56446517],"study_design_scores_gemma":[0.00064221496,0.000068044,0.01698764,0.48188007,0.00044234085,0.00012794207,0.000023373012,0.000021342794,8.5072173e-7,0.004211425,0.49530694,0.00028780877],"about_ca_topic_score_codex":0.000008300504,"about_ca_topic_score_gemma":0.0000031482637,"teacher_disagreement_score":0.56417733,"about_ca_system_score_codex":0.00003295932,"about_ca_system_score_gemma":0.00015775385,"threshold_uncertainty_score":0.9294423},"labels":[],"label_agreement":null},{"id":"W2091142169","doi":"10.1523/jneurosci.0553-08.2008","title":"Thalamic Shape: A Possible Endophenotype","year":2008,"lang":"en","type":"letter","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"","keywords":"Endophenotype; Neuroscience; Schizophrenia (object-oriented programming); Thalamus; Mechanism (biology); Psychology; Sensory system; Cortex (anatomy); Cognition; Psychiatry","score_opus":0.10145203816079809,"score_gpt":0.3574402962795016,"score_spread":0.2559882581187035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091142169","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013392179,0.000480175,0.0042690425,0.9755389,0.0011504862,0.0005223894,0.000023140416,0.00015396874,0.004469695],"genre_scores_gemma":[0.026360957,0.0017951402,0.009444127,0.9565821,0.0025141092,0.000007824332,0.0000035624603,0.000068589456,0.0032235568],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983111,0.000028304044,0.0004422486,0.00028924423,0.00064372935,0.00028539533],"domain_scores_gemma":[0.9986125,0.00007369816,0.0006078951,0.00040758273,0.0002016342,0.00009668757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008853126,0.00019340977,0.0003990961,0.00027532983,0.000115078714,0.000030166242,0.00048779644,0.00014146703,0.000013113282],"category_scores_gemma":[0.00020627693,0.00015027041,0.00021177222,0.00041489626,0.00025098896,0.00015230697,0.00006969185,0.0021537526,0.000009526565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000146072,0.000058439986,0.0002611061,0.000040170686,0.0000027739927,0.0036277522,0.000013947919,0.000003911335,0.035817605,0.000014496323,0.9588882,0.0012569921],"study_design_scores_gemma":[0.00023553219,0.00044857318,0.0038116258,0.0001449908,0.000048288977,0.024803244,0.0000010267707,0.0001910459,0.0010246766,0.00036103936,0.9687963,0.0001336517],"about_ca_topic_score_codex":0.0000010998016,"about_ca_topic_score_gemma":2.2808074e-8,"teacher_disagreement_score":0.034792926,"about_ca_system_score_codex":0.00005731311,"about_ca_system_score_gemma":0.0003051935,"threshold_uncertainty_score":0.9357103},"labels":[],"label_agreement":null},{"id":"W2091333100","doi":"10.1007/bf02668216","title":"Evolution of β-amyloid induced neuropathology: magnetic resonance imaging and anatomical comparisons in the rodent hippocampus","year":2002,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Saskatoon City Hospital; University of Saskatchewan; Royal University Hospital","funders":"Medical Research Council Canada","keywords":"Hippocampus; Hippocampal formation; Pathology; Magnetic resonance imaging; Neuropathology; Edema; Medicine; Necrosis; Amyloid (mycology); Chemistry; Internal medicine; Radiology; Disease","score_opus":0.038701672800783744,"score_gpt":0.322324467651281,"score_spread":0.28362279485049724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091333100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9601489,0.035116576,0.00015368726,0.0036406433,0.00008938693,0.00054135395,0.000013674095,0.000026323862,0.00026946524],"genre_scores_gemma":[0.9945322,0.0037218693,0.00079143554,0.0006931528,0.00012768191,0.0000935687,0.000008353533,0.000013497389,0.000018201396],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985741,0.00021414984,0.0004549589,0.00039564905,0.000095448995,0.00026571137],"domain_scores_gemma":[0.99930966,0.000163131,0.000108035594,0.0003410206,0.000034750672,0.000043410735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035745045,0.00017808305,0.00048502343,0.00010165004,0.00005455808,0.000004938964,0.00013315938,0.000078578094,0.00002997016],"category_scores_gemma":[0.00011817455,0.00012788309,0.000016359272,0.000281778,0.0007951349,0.0000333939,0.00007839869,0.0002543124,0.0000013026117],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020483151,0.0003221924,0.2539798,0.000105273146,0.000001188182,0.000070760114,0.00069202075,7.811067e-7,0.47919902,0.01778125,0.00043660717,0.24720626],"study_design_scores_gemma":[0.0023322133,0.0008679928,0.9622759,0.00033187942,0.000037348742,0.00025717632,0.00016505698,0.001294983,0.003481123,0.02426535,0.0045266175,0.00016432341],"about_ca_topic_score_codex":0.000119031596,"about_ca_topic_score_gemma":0.000008453158,"teacher_disagreement_score":0.7082961,"about_ca_system_score_codex":0.000024575036,"about_ca_system_score_gemma":0.000011994402,"threshold_uncertainty_score":0.52149206},"labels":[],"label_agreement":null},{"id":"W2091386625","doi":"10.1016/j.mri.2010.07.004","title":"Diffusion tensor fiber tractography of the olfactory tract","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Diffusion MRI; Tractography; Fiber tract; Olfactory system; Anatomy; Magnetic resonance imaging; Neuroscience; Medicine; Biology; Radiology","score_opus":0.027235621884554757,"score_gpt":0.2935040094184016,"score_spread":0.26626838753384685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091386625","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98370445,0.001335918,0.00040071682,0.004383989,0.00011921495,0.00056589395,0.000015908436,0.00014923884,0.009324698],"genre_scores_gemma":[0.9873526,0.0000708609,0.010293042,0.0005739622,0.00006538042,0.000035254012,0.0000017865409,0.000028343744,0.0015787778],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9990909,0.000015153283,0.00023132122,0.00024920751,0.00021471671,0.00019869312],"domain_scores_gemma":[0.9990303,0.00006594951,0.000098740835,0.00066025194,0.00008394043,0.00006080598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079089456,0.00012767583,0.00016478995,0.000065205655,0.00009574741,0.000011516538,0.00019106684,0.00003484557,0.00033657474],"category_scores_gemma":[0.00008720208,0.000087117056,0.00014263048,0.0002525587,0.00027218557,0.0000589043,0.000055573473,0.00044938276,0.0000098229275],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016629256,0.00020131968,0.33174443,0.000020546055,8.9873475e-7,0.0000071104737,0.000051043797,3.6706084e-7,0.2775954,0.0004416794,0.00084920827,0.38907135],"study_design_scores_gemma":[0.00028535587,0.00002588317,0.77383727,0.000051776777,0.000022209366,0.00007543539,0.000010750451,0.0002615744,0.009614459,0.00066790194,0.21506867,0.00007870275],"about_ca_topic_score_codex":0.000029494446,"about_ca_topic_score_gemma":0.000001339974,"teacher_disagreement_score":0.44209284,"about_ca_system_score_codex":0.0000072923303,"about_ca_system_score_gemma":0.00003312008,"threshold_uncertainty_score":0.36852574},"labels":[],"label_agreement":null},{"id":"W2091741867","doi":"10.1088/0031-9155/52/6/n01","title":"Preservation of diffusion tensor properties during spatial normalization by use of tensor imaging and fibre tracking on a normal brain database","year":2007,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":114,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Spatial normalization; White matter; Normalization (sociology); Tractography; Scanner; Computer science; Artificial intelligence; Fractional anisotropy; Pattern recognition (psychology); Magnetic resonance imaging; Voxel; Nuclear magnetic resonance; Computer vision; Physics; Medicine; Radiology","score_opus":0.27148354941588937,"score_gpt":0.4017654255244735,"score_spread":0.1302818761085841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091741867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9649311,0.00015147665,0.033144508,0.0014453962,0.000011468133,0.0002564774,0.00001557677,0.000018072647,0.00002595703],"genre_scores_gemma":[0.99791646,0.00028453764,0.0012404023,0.0003496453,0.00007921551,0.000006785251,0.00009645233,0.000008720758,0.000017775781],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99937725,0.000020726271,0.00025692052,0.00016804795,0.00006501714,0.00011203987],"domain_scores_gemma":[0.9995419,0.00010368828,0.00012513598,0.00012684701,0.000073183866,0.000029269107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013556781,0.00008458583,0.00020464354,0.00008280233,0.000034555684,0.0000017122456,0.000028993949,0.000029146191,0.0000016498976],"category_scores_gemma":[0.00019849237,0.000060573424,0.00001102066,0.000119284916,0.00019887809,0.000121605386,0.000042979915,0.000105609986,3.6408437e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019815222,0.00007221294,0.23354298,0.00014628381,0.0000025691215,0.0000013989937,0.00018869714,0.000005607721,0.752623,0.0003898607,0.000060377264,0.012768828],"study_design_scores_gemma":[0.0035229202,0.0009110781,0.62745625,0.0015289062,0.00006910128,0.00004305331,0.00032457308,0.0128789935,0.35078645,0.00093680434,0.001323763,0.00021811147],"about_ca_topic_score_codex":0.0002610151,"about_ca_topic_score_gemma":0.000007692989,"teacher_disagreement_score":0.4018366,"about_ca_system_score_codex":0.0000083233945,"about_ca_system_score_gemma":0.0000063901325,"threshold_uncertainty_score":0.24701126},"labels":[],"label_agreement":null},{"id":"W2092497652","doi":"10.1016/j.neuroimage.2009.01.002","title":"Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: Application to normal elderly and Alzheimer's disease participants","year":2009,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":596,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health","keywords":"White matter; Atlas (anatomy); Diffusion MRI; Spatial normalization; Fractional anisotropy; Image warping; Artificial intelligence; Segmentation; Pattern recognition (psychology); Brain atlas; Cartography; Nuclear medicine; Computer science; Medicine; Magnetic resonance imaging; Anatomy; Radiology; Voxel; Geography","score_opus":0.05788558248088984,"score_gpt":0.3439735161238967,"score_spread":0.2860879336430069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092497652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.594271,0.000048902835,0.3928955,0.011750454,0.000009684676,0.000720071,0.000054316555,0.00017264888,0.00007744435],"genre_scores_gemma":[0.98109704,0.0000028367854,0.009532785,0.008992133,0.00004485179,0.00008071081,0.00016160568,0.000026704889,0.000061326675],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99844795,0.000050357703,0.0003497411,0.000483525,0.00025979712,0.00040861906],"domain_scores_gemma":[0.99873275,0.000050267416,0.00014340412,0.0006006894,0.00008483395,0.0003880756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015573476,0.0002110101,0.0002960444,0.000610548,0.00018903463,0.000063950494,0.000111764384,0.000043075735,0.000029815827],"category_scores_gemma":[0.000059641356,0.00020591276,0.000115220246,0.0017105086,0.000035384666,0.00021943013,0.000044998516,0.00017484746,0.000049315986],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003620807,0.001104084,0.84974605,0.00011359586,0.00015981817,0.00008866477,0.0003001739,0.0040960857,0.12364138,0.00021697077,0.004044064,0.016127018],"study_design_scores_gemma":[0.0005604161,0.00012925414,0.8608538,0.000019530346,0.0007831742,0.000009454027,0.000010697841,0.1327688,0.0011490904,0.0001182767,0.0033954058,0.00020214454],"about_ca_topic_score_codex":0.0000058346227,"about_ca_topic_score_gemma":0.0000015713063,"teacher_disagreement_score":0.38682604,"about_ca_system_score_codex":0.00003508723,"about_ca_system_score_gemma":0.000027610784,"threshold_uncertainty_score":0.8396879},"labels":[],"label_agreement":null},{"id":"W2092640753","doi":"10.1016/j.neuroimage.2012.03.062","title":"Brain white matter organisation in adolescence is related to childhood cerebral responses to facial expressions and harm avoidance","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec; Université Laval","funders":"","keywords":"Uncinate fasciculus; Inferior longitudinal fasciculus; Psychology; White matter; Fractional anisotropy; Superior longitudinal fasciculus; Tractography; Cingulum (brain); Fasciculus; N400; Neuroscience; Audiology; Event-related potential; Medicine; Electroencephalography; Magnetic resonance imaging","score_opus":0.031860111538509074,"score_gpt":0.3332742195678561,"score_spread":0.301414108029347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092640753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9598991,0.000022557091,0.00188128,0.036464065,0.00004815285,0.00077793986,0.000038247053,0.00016258091,0.00070608075],"genre_scores_gemma":[0.9653414,0.000008770892,0.009591161,0.023429954,0.0000517936,0.00006687056,0.0000055064465,0.000041155225,0.0014633843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988226,0.00005972394,0.00023345719,0.00038321537,0.00018288725,0.00031807006],"domain_scores_gemma":[0.99920636,0.000059317885,0.00004711172,0.00039681114,0.000036148413,0.00025426425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013681031,0.0001559133,0.0001710818,0.00017151088,0.00009750721,0.0000237034,0.00010092947,0.0000506469,0.00015777681],"category_scores_gemma":[0.00025895677,0.0001529164,0.00002728936,0.00034073045,0.000039721977,0.00020234213,0.00013544099,0.00029775593,0.00022739779],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010763915,0.00020468756,0.65970856,0.000019301156,0.0000017823252,0.000011458783,0.0033852689,0.0000018281287,0.30755726,0.00006788498,0.0271759,0.0017584227],"study_design_scores_gemma":[0.0003786147,0.00007348481,0.9678356,0.000098534016,0.000007630988,0.00006812506,0.000052480864,0.000013098434,0.016947094,0.00011619142,0.014263879,0.00014526272],"about_ca_topic_score_codex":0.000005621079,"about_ca_topic_score_gemma":9.584388e-7,"teacher_disagreement_score":0.30812705,"about_ca_system_score_codex":0.00004061319,"about_ca_system_score_gemma":0.00002526162,"threshold_uncertainty_score":0.623575},"labels":[],"label_agreement":null},{"id":"W2092674859","doi":"10.3389/fnhum.2014.00507","title":"Investigating the contribution of ventral-lexical and dorsal-sublexical pathways during reading in bilinguals","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Arcuate fasciculus; Superior longitudinal fasciculus; Fasciculus; Psychology; Diffusion MRI; White matter; Inferior longitudinal fasciculus; Uncinate fasciculus; Lateralization of brain function; Reading (process); Dorsum; Neuroscience; Lexical decision task; Tractography; Cognitive psychology; Fractional anisotropy; Audiology; Anatomy; Cognition; Biology; Linguistics; Medicine; Magnetic resonance imaging","score_opus":0.046715731891005974,"score_gpt":0.33029396921269505,"score_spread":0.2835782373216891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092674859","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776699,0.000041388914,0.021336576,0.00048534654,0.000067832596,0.00026995144,0.000001122741,0.000041002822,0.00008688263],"genre_scores_gemma":[0.99637127,0.00002345573,0.0032813333,0.0002629556,0.000021093214,0.000020338488,0.0000012146867,0.000007639449,0.0000106847065],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990172,0.000058586935,0.00027275048,0.0002877573,0.0001483418,0.00021537009],"domain_scores_gemma":[0.99956435,0.000056268316,0.00008975086,0.00021637928,0.000020221656,0.000053058382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037755794,0.000080668586,0.00018045132,0.000111735506,0.00013164488,0.000014632821,0.00013149201,0.000033484208,4.6432e-7],"category_scores_gemma":[0.00070596766,0.00006412345,0.00002246828,0.0003455037,0.0005102656,0.000077714794,0.000068088484,0.000256353,4.0353175e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010892692,0.000060850805,0.49375302,0.000031796993,4.346584e-7,0.000007674788,0.0002542349,0.00019394343,0.48895702,0.015770929,0.000032852204,0.0009263581],"study_design_scores_gemma":[0.0009505897,0.00018133057,0.8346687,0.00031996035,0.00001046192,0.000052366184,0.00009107174,0.03781625,0.09364519,0.031674817,0.0004296705,0.00015958786],"about_ca_topic_score_codex":0.000008682212,"about_ca_topic_score_gemma":0.0000013464424,"teacher_disagreement_score":0.39531183,"about_ca_system_score_codex":0.000034687968,"about_ca_system_score_gemma":0.000018786086,"threshold_uncertainty_score":0.26148784},"labels":[],"label_agreement":null},{"id":"W2093104890","doi":"10.1002/hbm.20908","title":"Regional impact of field strength on voxel‐based morphometry results","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Voxel-based morphometry; Voxel; Context (archaeology); Grey matter; Psychology; Artificial intelligence; Computer science; Medicine; Magnetic resonance imaging; White matter; Biology; Radiology","score_opus":0.1310161375736174,"score_gpt":0.4094893649152951,"score_spread":0.2784732273416777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093104890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93614024,0.000037377264,0.018404728,0.028959107,0.000016821365,0.0005527877,0.000032181437,0.00039375338,0.015463036],"genre_scores_gemma":[0.9883843,0.0000032970822,0.006591521,0.0045272866,0.00008448756,0.000006265476,0.000057159315,0.000010765635,0.00033492516],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99919534,0.000015922855,0.00024221423,0.00023205504,0.00015742067,0.00015703686],"domain_scores_gemma":[0.9991295,0.00020280019,0.00012154147,0.00043031026,0.000046772948,0.00006910243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112983485,0.000111940186,0.00018017867,0.00020705441,0.000086642816,0.000006776724,0.000094078816,0.000047091926,0.00004144915],"category_scores_gemma":[0.00018345911,0.00009876868,0.00013437239,0.00024674105,0.000033838664,0.000028337585,0.0000108012855,0.00020339413,0.000003717331],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046228143,0.00082781113,0.0033929595,0.00006473227,0.000041006388,0.000047564914,0.00019125403,0.00024660167,0.6883354,0.014596894,0.2771789,0.014614551],"study_design_scores_gemma":[0.0041971635,0.0040882137,0.9227031,0.0011228948,0.0000341018,0.000042244064,0.00005788679,0.0022161526,0.01774446,0.013923056,0.033417165,0.0004535532],"about_ca_topic_score_codex":0.000015490565,"about_ca_topic_score_gemma":4.135289e-7,"teacher_disagreement_score":0.91931015,"about_ca_system_score_codex":0.00004715803,"about_ca_system_score_gemma":0.000032511718,"threshold_uncertainty_score":0.40276697},"labels":[],"label_agreement":null},{"id":"W2093963221","doi":"10.1016/j.diii.2012.04.024","title":"3T tractography of the median nerve: Optimisation of acquisition parameters and normative diffusion values","year":2012,"lang":"en","type":"article","venue":"Diagnostic and Interventional Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital Notre-Dame","funders":"","keywords":"Tractography; Diffusion MRI; Medicine; Fractional anisotropy; Wrist; Median nerve; Radiology; Nuclear medicine; Magnetic resonance imaging; Anatomy","score_opus":0.033812575761842115,"score_gpt":0.33169020221550183,"score_spread":0.2978776264536597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093963221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9747674,0.00071140355,0.022601679,0.0014432096,0.000046544203,0.00023523917,0.00002247443,0.000016138152,0.00015591946],"genre_scores_gemma":[0.9934325,0.00011501084,0.0062415595,0.00012916343,0.000020178737,0.000022546115,0.000024537027,0.0000060624943,0.000008446211],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994822,0.000029476458,0.00021111273,0.000084245214,0.00011249712,0.000080459424],"domain_scores_gemma":[0.9993486,0.0003005584,0.00014919059,0.0000923617,0.00006358248,0.000045726214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011617837,0.0000663162,0.00011067745,0.0000682055,0.000050625848,0.0000054459083,0.00003361426,0.00001549421,0.000014975742],"category_scores_gemma":[0.00017219449,0.00004852564,0.00008588106,0.00008944588,0.00020136707,0.00017515995,0.00004550127,0.00006968214,2.3614079e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029376311,0.00048392988,0.95235354,0.00023335972,0.000035694262,7.034847e-7,0.00079116435,0.0000063066686,0.012121947,0.007857888,0.00027358177,0.02581254],"study_design_scores_gemma":[0.0003580306,0.00006252566,0.9728866,0.0006200227,0.00010149686,0.00004143091,0.00028018697,0.0009544964,0.015474852,0.009101208,0.000059788556,0.000059338963],"about_ca_topic_score_codex":0.000019434405,"about_ca_topic_score_gemma":1.9468276e-7,"teacher_disagreement_score":0.025753202,"about_ca_system_score_codex":0.000007777456,"about_ca_system_score_gemma":0.0000046149808,"threshold_uncertainty_score":0.1978818},"labels":[],"label_agreement":null},{"id":"W2094458055","doi":"10.1016/j.neuroimage.2005.12.056","title":"Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"ZonMw","keywords":"White matter; Zygosity; Endophenotype; Voxel-based morphometry; Lateralization of brain function; Psychology; Voxel; Monozygotic twin; Twin study; Neuroscience; Medicine; Magnetic resonance imaging; Biology; Heritability; Genetics; Cognition","score_opus":0.04199888810913025,"score_gpt":0.31163004703146924,"score_spread":0.26963115892233896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094458055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96132445,0.000086045606,0.035206214,0.0023729932,0.000029864446,0.0007905236,0.000033925582,0.000102635524,0.00005333337],"genre_scores_gemma":[0.94800943,0.000019101542,0.050197285,0.0014124595,0.00007399539,0.00005185411,0.000020251418,0.000053029333,0.00016257307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888855,0.000025371977,0.0002054218,0.0004862272,0.00010729898,0.00028711063],"domain_scores_gemma":[0.9993707,0.000094982846,0.00007870542,0.00033690003,0.00003214283,0.000086593755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008061358,0.00020734624,0.00030692702,0.00023551786,0.00010626828,0.00004447799,0.00006219172,0.00003801941,0.000007396844],"category_scores_gemma":[0.000031666033,0.00019282178,0.000041592844,0.00023675761,0.00015311984,0.00008014368,0.000063833104,0.00019387106,0.0000018113852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020125162,0.00024599102,0.7186388,0.00032083306,0.000005498657,0.00014748487,0.000031343803,0.000061136394,0.27838647,0.00013273345,0.00053150643,0.0012969916],"study_design_scores_gemma":[0.0019824742,0.00017464091,0.95949316,0.00012664373,0.00009018481,0.00025030595,0.000017416032,0.016698778,0.01875791,0.0016273777,0.0004942158,0.0002868905],"about_ca_topic_score_codex":0.000085730535,"about_ca_topic_score_gemma":0.00006657707,"teacher_disagreement_score":0.25962856,"about_ca_system_score_codex":0.000031426378,"about_ca_system_score_gemma":0.000020677546,"threshold_uncertainty_score":0.7863044},"labels":[],"label_agreement":null},{"id":"W2095347447","doi":"10.3389/fnhum.2014.01028","title":"Diffusion tensor imaging and white matter abnormalities in patients with disorders of consciousness","year":2015,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Neuroimaging; Diffusion MRI; Persistent vegetative state; White matter; Consciousness; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology; Minimally conscious state","score_opus":0.031144971538291762,"score_gpt":0.3251342267248881,"score_spread":0.29398925518659635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095347447","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023105696,0.95140755,0.015639726,0.00036514152,0.0006578183,0.006976449,0.00017924423,0.00020435794,0.0014640185],"genre_scores_gemma":[0.017954916,0.9753152,0.0053780014,0.00036849003,0.000021733595,0.0002468278,0.00005199566,0.000105164596,0.00055766955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985193,0.000053632615,0.00041317136,0.0005092845,0.00025274834,0.00025185337],"domain_scores_gemma":[0.99924064,0.000016532267,0.00024138654,0.00038188195,0.0000456348,0.00007394038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012257244,0.0002456396,0.00083712465,0.00046940622,0.000059160608,0.000019526919,0.00021871396,0.000047215366,0.0000022480285],"category_scores_gemma":[0.000024186844,0.00018860919,0.000045806886,0.0004582816,0.0006777038,0.000138903,0.00013242298,0.000307935,1.5417619e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000098930395,0.0001134685,0.95180297,0.0016222971,8.226255e-7,0.0000060166526,0.000066463326,0.000002553979,4.000756e-7,0.000017920673,0.00067572534,0.045681488],"study_design_scores_gemma":[0.0020044611,0.00031654513,0.5050446,0.011665619,0.00018391409,0.000039885672,0.00012542689,0.00023502999,8.516548e-7,0.00082481187,0.47880322,0.0007556394],"about_ca_topic_score_codex":0.00001134886,"about_ca_topic_score_gemma":0.0000030922529,"teacher_disagreement_score":0.47812748,"about_ca_system_score_codex":0.00006518713,"about_ca_system_score_gemma":0.00006124895,"threshold_uncertainty_score":0.769126},"labels":[],"label_agreement":null},{"id":"W2095486621","doi":"10.1016/j.schres.2008.09.013","title":"Quetiapine alleviates the cuprizone-induced white matter pathology in the brain of C57BL/6 mouse","year":2008,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Manitoba","funders":"","keywords":"White matter; Myelin; Quetiapine; Myelin basic protein; Western blot; Internal medicine; Pharmacology; Schizophrenia (object-oriented programming); Endocrinology; Medicine; Pathology; Neuroscience; Chemistry; Central nervous system; Biology; Magnetic resonance imaging; Biochemistry; Psychiatry","score_opus":0.18268207295172567,"score_gpt":0.42693069997681654,"score_spread":0.24424862702509087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095486621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89823496,0.00013780668,0.00019554308,0.09928254,0.000009744445,0.0008597824,0.0000063183516,0.000045296234,0.0012280002],"genre_scores_gemma":[0.9937042,0.0002108406,0.0030934385,0.0014393438,0.00008558072,0.00026534603,0.000011798676,0.0000290514,0.001160385],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980707,0.0004293569,0.0002950786,0.00031103982,0.0005004005,0.00039340797],"domain_scores_gemma":[0.9981969,0.00050778297,0.000057947695,0.0010190682,0.00016232669,0.000055987162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012065361,0.00012314004,0.00022347811,0.00021926852,0.00022384293,0.000011844854,0.000526541,0.000073703966,0.00009195821],"category_scores_gemma":[0.00028281886,0.00006896029,0.000072831965,0.00075425056,0.00048126496,0.000050732364,0.0001758458,0.0010007665,0.00009501114],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028958875,0.0016164554,0.16639033,0.00022609708,0.00005746981,0.00080664014,0.005407369,0.000019048726,0.617999,0.026180927,0.17184454,0.006556237],"study_design_scores_gemma":[0.0060981163,0.0012822783,0.86056226,0.00019804297,0.00003049183,0.0021358205,0.0008849314,0.0004474625,0.07576368,0.022385884,0.029758766,0.00045223886],"about_ca_topic_score_codex":0.000074072,"about_ca_topic_score_gemma":0.000031193646,"teacher_disagreement_score":0.69417197,"about_ca_system_score_codex":0.000029577819,"about_ca_system_score_gemma":0.00011056103,"threshold_uncertainty_score":0.4347888},"labels":[],"label_agreement":null},{"id":"W2095552504","doi":"10.1016/s0028-3932(00)00048-8","title":"Comparison of overall brain volume and midsagittal corpus callosum surface area as obtained from NMR scans and direct anatomical measures: a within-subject study on autopsy brains","year":2000,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Magnetic resonance imaging; Volume (thermodynamics); Brain size; Psychology; Nuclear medicine; Displacement (psychology); Anatomy; Chemistry; Nuclear magnetic resonance; Neuroscience; Medicine; Radiology; Physics","score_opus":0.0745647637020618,"score_gpt":0.3801860399936065,"score_spread":0.3056212762915447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095552504","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925371,0.00010168387,0.00022167689,0.0021065567,0.000046947596,0.00096388394,0.00007088087,0.00035254084,0.003598771],"genre_scores_gemma":[0.9957577,0.0000498258,0.0013283405,0.0021118396,0.000032439024,0.000021106094,0.000019971034,0.00005182859,0.0006269475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99792624,0.00018998126,0.00045655167,0.0008302004,0.00032169078,0.00027532468],"domain_scores_gemma":[0.998642,0.0002885772,0.0001534774,0.0006572872,0.00006332582,0.00019531442],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017425253,0.0003054265,0.0006136531,0.000079952966,0.00011847838,0.00003184518,0.00016925776,0.00010904274,0.00005588465],"category_scores_gemma":[0.00021918684,0.00026866037,0.000066849665,0.00024190042,0.00029229734,0.000059343733,0.00005253243,0.00043120026,0.0000106630305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023068418,0.0038991685,0.85479546,0.000026274709,0.00012849714,0.00027811233,0.0021077076,0.00015543042,0.105747074,0.00023788787,0.0071464484,0.023171129],"study_design_scores_gemma":[0.0033406173,0.0034711992,0.9823754,0.00008286774,0.00010991011,0.00010694447,0.00015689354,0.0034069999,0.0018270166,0.0004747915,0.0043236357,0.00032374883],"about_ca_topic_score_codex":0.00020368746,"about_ca_topic_score_gemma":0.00001735852,"teacher_disagreement_score":0.12757994,"about_ca_system_score_codex":0.000031099826,"about_ca_system_score_gemma":0.00003444847,"threshold_uncertainty_score":0.9999766},"labels":[],"label_agreement":null},{"id":"W2095984111","doi":"10.1093/cercor/bhr361","title":"Axonal Fiber Terminations Concentrate on Gyri","year":2011,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Education and Early Childhood Development","funders":"National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute; National Institute on Aging","keywords":"Macaque; Neuroscience; Cerebral cortex; Cortex (anatomy); Diffusion MRI; Biology; Anatomy; Magnetic resonance imaging; Medicine","score_opus":0.13788488699399906,"score_gpt":0.3467944257352,"score_spread":0.2089095387412009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095984111","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5428694,0.000038126233,0.0036749952,0.0024654896,0.00013832144,0.0009656038,0.00005287193,0.0008055521,0.44898966],"genre_scores_gemma":[0.9821212,0.000008863174,0.008631586,0.0015413587,0.00006846937,0.00004863989,0.000028247043,0.000018616487,0.0075329673],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99941385,0.0000076107476,0.00012380951,0.00020383623,0.00009539632,0.00015549012],"domain_scores_gemma":[0.99952406,0.000016649205,0.00004386267,0.00027223217,0.00004805877,0.00009512169],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000022821463,0.00009132681,0.00010475106,0.00003809523,0.000070444825,0.000005921338,0.000071911425,0.000033979995,0.0014463098],"category_scores_gemma":[0.000015386626,0.00007915273,0.000052529598,0.000098428885,0.00007570638,0.000049720424,0.000021954233,0.00014595548,0.00033419457],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006206634,0.0029863769,0.091373906,0.00015365252,0.00014710227,0.00045517282,0.0010576538,0.000003877702,0.035140246,0.4651716,0.13682228,0.26606748],"study_design_scores_gemma":[0.0014067969,0.0007059561,0.7419257,0.00012131271,0.00010816413,0.00022852197,0.00004667719,0.00054115633,0.03454574,0.0153085925,0.20465569,0.00040567812],"about_ca_topic_score_codex":0.0000057624898,"about_ca_topic_score_gemma":6.3287575e-7,"teacher_disagreement_score":0.6505518,"about_ca_system_score_codex":0.000025917541,"about_ca_system_score_gemma":0.000029440813,"threshold_uncertainty_score":0.9994665},"labels":[],"label_agreement":null},{"id":"W2097277305","doi":"10.1371/journal.pone.0133352","title":"Spatio-Temporal Regularization for Longitudinal Registration to Subject-Specific 3d Template","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute on Aging; University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; U.S. Food and Drug Administration; National Institutes of Health; Eisai; Genentech; Multiple Sclerosis Society; Foundation for the National Institutes of Health; Multiple Sclerosis Society of Canada; Northern California Institute for Research and Education; McGill University; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; Elan; Novartis; Medpace; GlaxoSmithKline; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Pfizer; Synarc; Alzheimer's Association","keywords":"Segmentation; Regularization (linguistics); Computer science; Artificial intelligence; Pattern recognition (psychology); Statistical power; Mathematics; Statistics","score_opus":0.27448312858531554,"score_gpt":0.35020603899020414,"score_spread":0.0757229104048886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097277305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2889318,0.000044412063,0.6955302,0.0097928215,0.000036788453,0.002512896,0.00003426784,0.00051242195,0.0026044408],"genre_scores_gemma":[0.6425323,0.000018853141,0.35403663,0.00018820418,0.00022936144,0.00031299004,0.00038871265,0.00003092245,0.002262047],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991355,0.0000096484255,0.00020452723,0.00027547506,0.00023357317,0.00014125557],"domain_scores_gemma":[0.9991061,0.000021302812,0.00008375613,0.0003523761,0.00029537908,0.00014106781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013603625,0.00009416825,0.00016422645,0.00007754789,0.000067713416,0.000022296219,0.000060535767,0.000043766508,0.0000090652],"category_scores_gemma":[0.000120287295,0.0000968376,0.000028210696,0.00021036535,0.00002421763,0.00009470367,0.000018366933,0.000074327625,0.000026240896],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00499814,0.01017624,0.22148354,0.0009990616,0.00037907035,0.0000657098,0.0013510704,0.00032951622,0.47239858,0.07523651,0.19033043,0.02225211],"study_design_scores_gemma":[0.0062913024,0.00459082,0.042207163,0.0011147306,0.00067926676,0.000098039214,0.00010592966,0.013611724,0.65597767,0.040105846,0.23396349,0.0012540465],"about_ca_topic_score_codex":0.000009730909,"about_ca_topic_score_gemma":0.000009271397,"teacher_disagreement_score":0.35360047,"about_ca_system_score_codex":0.00007632731,"about_ca_system_score_gemma":0.000047175396,"threshold_uncertainty_score":0.39489228},"labels":[],"label_agreement":null},{"id":"W2097840523","doi":"10.1109/hisb.2011.19","title":"Consistent Information Content Estimation for Diffusion Tensor MR Images","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Estimator; Diffusion MRI; Entropy estimation; Computer science; Artificial intelligence; Entropy (arrow of time); Tensor (intrinsic definition); Curse of dimensionality; Pattern recognition (psychology); Segmentation; Context (archaeology); Image segmentation; Image registration; Thresholding; Mathematics; Computer vision; Image (mathematics); Statistics","score_opus":0.19970581124354295,"score_gpt":0.34873286810613935,"score_spread":0.1490270568625964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097840523","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026330711,0.000010016207,0.9614866,0.0017306576,0.000032455715,0.0012223034,0.00001667536,0.0003621352,0.0088084545],"genre_scores_gemma":[0.5716483,0.000022227907,0.4258874,0.0014006123,0.000013379285,0.0002553197,0.000077287186,0.0000083273035,0.0006871117],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995395,0.0000032912708,0.00019707515,0.00009039312,0.000072797084,0.000096978496],"domain_scores_gemma":[0.9995018,0.000024813897,0.0000727007,0.00018181025,0.00016683683,0.000051985277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047529426,0.00007090583,0.000100702615,0.00005474805,0.00006425661,0.000008791879,0.000034702494,0.000026901578,0.00005089121],"category_scores_gemma":[0.00008364035,0.000053668624,0.00005246932,0.000048037862,0.00003563062,0.0001917503,0.000018611994,0.000043720574,0.000025739699],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012501492,0.0014751609,0.029564854,0.000684577,0.00009127569,0.0000072949315,0.0014203977,0.000020926083,0.18553934,0.22306153,0.061721165,0.49516335],"study_design_scores_gemma":[0.0065621044,0.0016114303,0.24205773,0.00026180941,0.0003709784,0.0002541206,0.0008887361,0.0653941,0.5631436,0.020442871,0.09832477,0.0006877773],"about_ca_topic_score_codex":0.000018428056,"about_ca_topic_score_gemma":3.4704044e-7,"teacher_disagreement_score":0.5453176,"about_ca_system_score_codex":0.000022748982,"about_ca_system_score_gemma":0.000012754269,"threshold_uncertainty_score":0.2188543},"labels":[],"label_agreement":null},{"id":"W2098063347","doi":"10.1093/neuonc/nov113","title":"High-definition fiber tractography for the evaluation of perilesional white matter tracts in high-grade glioma surgery","year":2015,"lang":"en","type":"review","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Fiber tract; Medicine; Glioma; Radiology; Magnetic resonance imaging","score_opus":0.28399379551971277,"score_gpt":0.44856462093393445,"score_spread":0.1645708254142217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098063347","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0043520764,0.9703712,0.00079511857,0.0098249065,0.0011792249,0.011676872,0.0006831644,0.0002159934,0.00090143277],"genre_scores_gemma":[0.0043364256,0.97970414,0.0071624056,0.0011338862,0.0005703819,0.0056212633,0.001274049,0.00016988837,0.000027537722],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99728924,0.00046331956,0.0009563176,0.0005214711,0.0004774682,0.0002921861],"domain_scores_gemma":[0.9954012,0.0028233912,0.00076919724,0.00056875544,0.0003468149,0.0000906414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012238858,0.0003364863,0.0015786662,0.00056602753,0.000061009057,0.000009809469,0.00018798458,0.0003853906,0.00020701428],"category_scores_gemma":[0.0003019259,0.00024004039,0.00051365193,0.0006323456,0.000162821,0.00007104128,0.00004653248,0.00059810723,0.000028718501],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011768598,0.0007112948,0.00011922046,0.0022056347,0.0000598846,0.000031638825,0.00003602456,0.000016070293,0.00027422194,0.00048149916,0.034754593,0.96119225],"study_design_scores_gemma":[0.000832625,0.00024649536,0.0015057748,0.0009254103,0.0015830625,0.0004181701,0.000007330426,0.000027848633,0.000042551954,0.0022779566,0.9919434,0.00018937643],"about_ca_topic_score_codex":0.000014045205,"about_ca_topic_score_gemma":0.000005326657,"teacher_disagreement_score":0.9610028,"about_ca_system_score_codex":0.00022665568,"about_ca_system_score_gemma":0.0008426428,"threshold_uncertainty_score":0.97885627},"labels":[],"label_agreement":null},{"id":"W2100031669","doi":"10.1002/hbm.20994","title":"Patterns of cortical degeneration in an elderly cohort with cerebral small vessel disease","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Psychology; White matter; Cerebral cortex; Temporal lobe; Neuroscience; Magnetic resonance imaging; Prefrontal cortex; Frontal lobe; Neuroimaging; Medicine; Cognition","score_opus":0.06349540230440086,"score_gpt":0.33181173404350434,"score_spread":0.26831633173910346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100031669","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9629298,0.0000027024792,0.035408925,0.0010443995,0.000010832294,0.00039607307,0.0000054560596,0.00008716045,0.0001146877],"genre_scores_gemma":[0.9904128,8.5225224e-7,0.008839034,0.00042368838,0.00007510662,0.00007054522,0.000083054365,0.000019917597,0.00007502434],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993068,0.00002187593,0.00019364122,0.00023569344,0.00010210603,0.0001398729],"domain_scores_gemma":[0.9994029,0.000029243343,0.00005907374,0.00034084244,0.000050300652,0.00011768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000104918065,0.00008920084,0.00013897415,0.00006866128,0.00007526134,0.000013091401,0.00007297679,0.00003237188,0.000032830627],"category_scores_gemma":[0.00003550055,0.00008131491,0.000023198028,0.0000889406,0.00004972755,0.00006864001,0.000019155399,0.00026405664,9.389328e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001612394,0.00010954652,0.65736485,0.000035429206,0.0000023285643,0.000012570294,0.00007067967,0.000006861245,0.33428973,0.007708443,0.00003644062,0.00034700037],"study_design_scores_gemma":[0.0004512048,0.00012666937,0.99526614,0.00008555116,0.000015941361,0.000009332778,0.000032123244,0.0007930984,0.0017782232,0.0009185933,0.00042786717,0.00009524127],"about_ca_topic_score_codex":0.000021193513,"about_ca_topic_score_gemma":0.00016291927,"teacher_disagreement_score":0.3379013,"about_ca_system_score_codex":0.000012705569,"about_ca_system_score_gemma":0.00003194602,"threshold_uncertainty_score":0.3315926},"labels":[],"label_agreement":null},{"id":"W2100154344","doi":"10.1007/s10851-008-0071-8","title":"High Angular Resolution Diffusion MRI Segmentation Using Region-Based Statistical Surface Evolution","year":2008,"lang":"en","type":"article","venue":"Journal of Mathematical Imaging and Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften; McGill University","keywords":"Diffusion MRI; Segmentation; Angular resolution (graph drawing); Orientation (vector space); Computer science; Artificial intelligence; Tensor (intrinsic definition); Diffusion; Imaging phantom; Image resolution; Fiber; Synthetic data; Pattern recognition (psychology); Surface (topology); Image segmentation; Computer vision; Algorithm; Physics; Mathematics; Magnetic resonance imaging; Materials science; Optics; Geometry","score_opus":0.05149532651747536,"score_gpt":0.37590472275786785,"score_spread":0.3244093962403925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100154344","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39587826,0.00010469303,0.6027174,0.0011220037,0.000024262425,0.000108729546,0.0000015418256,0.000027927137,0.000015190267],"genre_scores_gemma":[0.64561975,0.000066207256,0.35413843,0.000091425194,0.000050591123,7.800636e-7,0.0000041006456,0.000012779384,0.000015924712],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998875,0.000055217606,0.0004399715,0.00015367939,0.00033397,0.00014214059],"domain_scores_gemma":[0.9991089,0.00015887756,0.00025548134,0.00015267779,0.00018820191,0.00013582707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024536625,0.00011521664,0.0002580954,0.00008886648,0.00018987931,0.000017746475,0.00004395969,0.00003953863,0.000012582043],"category_scores_gemma":[0.00014395438,0.00008949772,0.00006304164,0.00013304863,0.00015121698,0.00016967395,0.000025128442,0.0002169345,0.0000021800915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021012432,0.0046278774,0.062060185,0.0015028125,0.00010050224,0.0018738748,0.000989335,0.008594408,0.83878416,0.035879243,0.016145382,0.027340965],"study_design_scores_gemma":[0.0023593772,0.0005134401,0.017458607,0.0012136128,0.00022982965,0.0056921765,0.00013867617,0.9352648,0.005069465,0.03151679,0.00031402783,0.00022915249],"about_ca_topic_score_codex":0.000007630102,"about_ca_topic_score_gemma":4.3055348e-8,"teacher_disagreement_score":0.92667043,"about_ca_system_score_codex":0.00011706876,"about_ca_system_score_gemma":0.00005489094,"threshold_uncertainty_score":0.36496112},"labels":[],"label_agreement":null},{"id":"W2101143723","doi":"10.3389/fnhum.2013.00845","title":"Network efficiency in autism spectrum disorder and its relation to brain overgrowth","year":2013,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds Québécois de la Recherche sur la Nature et les Technologies; Compute Canada","keywords":"Autism spectrum disorder; Brain size; Autism; Tractography; Neuroscience; Psychology; Diffusion MRI; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.023411599221681373,"score_gpt":0.2995723087445292,"score_spread":0.2761607095228479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101143723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85270727,0.0001256403,0.13215446,0.012996611,0.00019585252,0.0010724172,0.0000011744064,0.00010218634,0.00064440083],"genre_scores_gemma":[0.9919936,0.000028912678,0.005270459,0.0020758135,0.000021580367,0.00008629501,0.0000012285865,0.000013602016,0.0005085152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888456,0.000025392108,0.00019894786,0.00043504804,0.00014565085,0.00031040798],"domain_scores_gemma":[0.9996171,0.00002171413,0.00004395987,0.00021512489,0.0000070585,0.000095037474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012242785,0.00010384493,0.00014461976,0.00020371456,0.00012136194,0.000027724434,0.0001404963,0.0000330829,0.0000065511467],"category_scores_gemma":[0.00010127454,0.00010380255,0.000014741645,0.00080628274,0.00009198124,0.0001933682,0.00008429421,0.00020348781,0.000001775127],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024621451,0.00026792724,0.9038957,0.000035982812,6.2947606e-7,0.000032117692,0.00034649693,0.0073106587,0.026919657,0.045651488,0.013292413,0.0022223126],"study_design_scores_gemma":[0.00031025,0.00018667908,0.93800837,0.000055432225,0.0000019288516,0.000011075306,0.000010366559,0.031722073,0.00012192303,0.027475609,0.0019688744,0.00012741321],"about_ca_topic_score_codex":0.000025106936,"about_ca_topic_score_gemma":0.0000051659276,"teacher_disagreement_score":0.13928634,"about_ca_system_score_codex":0.000049464856,"about_ca_system_score_gemma":0.000015250079,"threshold_uncertainty_score":0.4232945},"labels":[],"label_agreement":null},{"id":"W2101310005","doi":"10.3174/ajnr.a4312","title":"Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months","year":2015,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; Hospital for Sick Children; University of British Columbia; SickKids Foundation; BC Children's Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Canadian Child Health Clinician Scientist Program; Michael Smith Health Research BC; Child and Family Research Institute","keywords":"Medicine; Cognition; Pediatrics; Psychiatry","score_opus":0.05201122306081865,"score_gpt":0.3546413930039905,"score_spread":0.3026301699431718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101310005","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97475857,0.0000767633,0.022964971,0.0017391255,0.00006159136,0.00025173544,0.00008009183,0.000021596265,0.000045553094],"genre_scores_gemma":[0.983208,0.000086793494,0.014978664,0.0015999454,0.000056942285,0.00001251029,0.000010085178,0.000022131488,0.000024924844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903345,0.00011843559,0.00035780165,0.00017588543,0.00013471984,0.00017969833],"domain_scores_gemma":[0.99865806,0.0004610722,0.00038045354,0.00012199138,0.00015944763,0.00021897133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114905546,0.00013113524,0.00046634322,0.00016029633,0.000023803967,0.0000051866937,0.00008001045,0.000029041628,0.0000060850853],"category_scores_gemma":[0.0005851402,0.00010812347,0.000042531912,0.0001051863,0.0004463994,0.000037641745,0.000029875273,0.00027653563,0.0000010947449],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014988531,0.00022996188,0.96208644,0.000013768996,0.000031856016,0.00075992016,0.00019566454,0.000067060486,0.0037570286,0.000028966842,0.00093295344,0.030397527],"study_design_scores_gemma":[0.0029172609,0.0072145932,0.9828457,0.000052276504,0.000099556535,0.002018003,0.00010167613,0.002151338,0.0005045467,0.00033744567,0.0016267111,0.00013087824],"about_ca_topic_score_codex":0.000038930106,"about_ca_topic_score_gemma":0.0000055858195,"teacher_disagreement_score":0.03026665,"about_ca_system_score_codex":0.00004732262,"about_ca_system_score_gemma":0.00011495357,"threshold_uncertainty_score":0.44091475},"labels":[],"label_agreement":null},{"id":"W2101810272","doi":"10.1016/j.medengphy.2014.02.021","title":"Special Issue on Cerebral Autoregulation: Measurement and modelling","year":2014,"lang":"en","type":"editorial","venue":"Medical Engineering & Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Autoregulation; Cerebral autoregulation; Computer science; Neuroscience; Medicine; Engineering; Psychology; Internal medicine; Blood pressure","score_opus":0.03640128165501212,"score_gpt":0.29165094523028123,"score_spread":0.2552496635752691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101810272","genre_codex":"methods","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000035688725,0.000071826995,0.66541237,0.0012775606,0.3302396,0.0004784239,0.000023102215,0.00064083544,0.0018206062],"genre_scores_gemma":[0.00062781177,0.00004268809,0.007933597,0.00012981062,0.9907303,0.000053602937,0.00012909625,0.000097705386,0.00025543128],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972338,0.000011074754,0.00029711766,0.0004602182,0.0017349827,0.00026282298],"domain_scores_gemma":[0.9989008,0.00016309175,0.00008324698,0.00041671083,0.00015186233,0.00028429917],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002536931,0.00031520493,0.0004711007,0.000054380453,0.00005940823,0.000023257717,0.00013868396,0.0003922443,0.000051347186],"category_scores_gemma":[0.0004455974,0.0002988348,0.000093135975,0.000110709836,0.000059516427,0.000032483807,0.00006436161,0.0011655429,0.000020100479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001802397,0.000069090485,0.000003167224,0.00025568646,0.00002829255,0.000009347294,0.000020638166,0.0074766814,0.000007401589,0.0015945057,0.96972215,0.02079503],"study_design_scores_gemma":[0.00038737126,0.00009351721,0.000010541831,0.0006365592,0.00006390446,0.0000029319087,4.5912614e-7,0.16432182,0.00007839751,0.0003759644,0.83382344,0.00020510648],"about_ca_topic_score_codex":0.000004953315,"about_ca_topic_score_gemma":1.9226935e-7,"teacher_disagreement_score":0.66049063,"about_ca_system_score_codex":0.00015333138,"about_ca_system_score_gemma":0.00014934417,"threshold_uncertainty_score":0.99994636},"labels":[],"label_agreement":null},{"id":"W2102318727","doi":"10.1109/nfsi-icfbi.2007.4387703","title":"Evaluating the Accuracy of an Anisotropic Finite-Volume Head Model for the EEG Forward Problem","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Head (geology); Finite volume method; Computer science; Magnitude (astronomy); Anisotropy; Electroencephalography; Physics; Mechanics; Optics; Geology","score_opus":0.22172727369997325,"score_gpt":0.4806607083890419,"score_spread":0.25893343468906865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102318727","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058959205,0.000042775344,0.93266493,0.005732136,0.000009747365,0.0015899374,0.000008286417,0.00011838361,0.0008746242],"genre_scores_gemma":[0.6736149,0.000015885102,0.32384983,0.0010056011,0.000030630712,0.00015981073,0.0000073350284,0.000016468512,0.0012995092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992125,0.000010803472,0.00025512613,0.00017101318,0.00016312826,0.00018741863],"domain_scores_gemma":[0.99852633,0.000641308,0.00011324026,0.00052716606,0.00014979087,0.00004216665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050652295,0.00008589397,0.00012036641,0.000024567402,0.00018257284,0.000009679155,0.00018538252,0.000028168684,0.000016633518],"category_scores_gemma":[0.00026449442,0.00004430207,0.00007266463,0.00012831425,0.0000728898,0.00007045689,0.000043116062,0.00012139791,0.0000018571004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007174189,0.0007558462,0.002821656,0.0002789664,0.000089212255,0.0000020985378,0.0015697092,0.042715,0.13233545,0.11564794,0.0048059905,0.6982607],"study_design_scores_gemma":[0.00043084208,0.00039695372,0.002134766,0.000020114412,0.00006689589,0.00000778923,0.00010135546,0.9723787,0.0028476473,0.01785837,0.0036982056,0.000058363694],"about_ca_topic_score_codex":0.000022342074,"about_ca_topic_score_gemma":0.000017732043,"teacher_disagreement_score":0.9296637,"about_ca_system_score_codex":0.000018677722,"about_ca_system_score_gemma":0.000053038166,"threshold_uncertainty_score":0.1806586},"labels":[],"label_agreement":null},{"id":"W2102334389","doi":"10.1016/j.ccl.2012.10.011","title":"Syncope—Now in Its Golden Era","year":2012,"lang":"en","type":"article","venue":"Cardiology Clinics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Libin Cardiovascular Institute of Alberta","funders":"","keywords":"Medicine; Internuclear ophthalmoplegia; Medial longitudinal fasciculus; Midbrain; Diffusion MRI; Fractional anisotropy; Anatomy; Cardiology; Pathology; Internal medicine; Multiple sclerosis; Radiology; Magnetic resonance imaging; Central nervous system","score_opus":0.12880143680477668,"score_gpt":0.4324582693958911,"score_spread":0.3036568325911144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102334389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93122303,0.0038159236,0.018337153,0.0069714547,0.0008583722,0.0011173879,0.000025029105,0.0005356267,0.037116002],"genre_scores_gemma":[0.991234,0.0007910197,0.00512003,0.0016833155,0.0004469719,0.00007011907,0.000016249262,0.000019022073,0.0006192521],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992437,0.000044523556,0.00022832559,0.0001775813,0.000047908445,0.0002579894],"domain_scores_gemma":[0.99931085,0.00015153916,0.000050096598,0.00035248807,0.000039635663,0.00009539444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027729644,0.00008576009,0.00030833247,0.000052855114,0.00002421801,0.0000012222737,0.000079519064,0.00012448635,0.000013909277],"category_scores_gemma":[0.00022097334,0.000078072866,0.000087811626,0.00012814095,0.0000614872,0.00004929621,0.000056563207,0.00036029154,0.00017654168],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004058803,0.00009646122,0.97073555,0.000027390533,0.000031123567,0.000054014978,0.0000487915,0.000048196205,0.0011577528,0.004309883,0.0138889775,0.009561288],"study_design_scores_gemma":[0.00074724737,0.000111894515,0.46641374,0.00003676272,0.000066705055,0.0003404042,0.00002366237,0.00014291395,0.00056965824,0.0012224307,0.5301594,0.00016516901],"about_ca_topic_score_codex":3.9419047e-7,"about_ca_topic_score_gemma":2.520619e-7,"teacher_disagreement_score":0.51627046,"about_ca_system_score_codex":0.000033314805,"about_ca_system_score_gemma":0.000030165489,"threshold_uncertainty_score":0.31837192},"labels":[],"label_agreement":null},{"id":"W2102604017","doi":"10.1016/j.jalz.2011.05.670","title":"P1‐389: Effect of Apolipoprotein E on cortical thickness and resting‐state brain function in Alzheimer's disease","year":2011,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Apolipoprotein E; Resting state fMRI; Medicine; Dementia; Cardiology; Internal medicine; Audiology; Psychology; Nuclear medicine; Disease; Radiology","score_opus":0.0604710601115722,"score_gpt":0.32822705156706145,"score_spread":0.26775599145548923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102604017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834379,0.008657208,0.0030749924,0.0010408203,0.00008796999,0.0020678223,0.000018833753,0.00025634794,0.0013580805],"genre_scores_gemma":[0.9967125,0.00003928396,0.002550845,0.0004324113,0.000026439737,0.00018211306,0.000018773804,0.00003246484,0.0000051679644],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9988262,0.00010301866,0.00030565925,0.00035902573,0.00017678346,0.00022930698],"domain_scores_gemma":[0.9991629,0.00013361732,0.00010873399,0.00039487204,0.000034982353,0.00016488686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028236595,0.00017672437,0.00024563528,0.00011630838,0.00007065081,0.0000067510446,0.00007779983,0.00004554302,0.00004214261],"category_scores_gemma":[0.0000951159,0.00015300493,0.00005512245,0.00018165256,0.00014525572,0.00007477206,0.00006656857,0.0002440233,0.000010359694],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008708453,0.0016555453,0.36546856,0.00015194275,0.00432719,0.00025687128,0.00065786665,0.000016453889,0.05280934,0.013790859,0.0021767041,0.5499802],"study_design_scores_gemma":[0.003172544,0.002581932,0.82546896,0.0003680804,0.014404973,0.00003337828,0.00002108813,0.00071191834,0.14491996,0.0056843515,0.0021515938,0.00048121277],"about_ca_topic_score_codex":0.0001288774,"about_ca_topic_score_gemma":0.000013211656,"teacher_disagreement_score":0.549499,"about_ca_system_score_codex":0.0000035327275,"about_ca_system_score_gemma":0.000025273743,"threshold_uncertainty_score":0.623936},"labels":[],"label_agreement":null},{"id":"W2103375347","doi":"10.1109/tmi.2011.2142189","title":"Spatially Regularized Compressed Sensing for High Angular Resolution Diffusion Imaging","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Compressed sensing; Computer science; Iterative reconstruction; Sampling (signal processing); Perspective (graphical); Diffusion; Minification; Artificial intelligence; Diffusion MRI; Image resolution; Computer vision; Encoding (memory); Algorithm; Reconstruction algorithm; Reduction (mathematics); Magnetic resonance imaging; Mathematics; Physics","score_opus":0.04798995004900583,"score_gpt":0.3162274920248334,"score_spread":0.2682375419758276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2103375347","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00866484,0.00004368136,0.98427933,0.004742649,0.00035595006,0.0008266841,0.000018955023,0.0006842884,0.00038360138],"genre_scores_gemma":[0.8054893,0.000055166067,0.19202547,0.0019760458,0.00012829089,0.00007690589,0.000025060892,0.000068761015,0.00015500371],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806064,0.000057554287,0.0004344973,0.00053281203,0.00050106115,0.00041343056],"domain_scores_gemma":[0.99871635,0.00015142979,0.00011435103,0.0005356956,0.00017282655,0.00030931667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028583314,0.00024405384,0.00033288196,0.00022842485,0.0003993362,0.000023434464,0.00015511694,0.000083459294,0.00017168245],"category_scores_gemma":[0.00006257227,0.00023272837,0.0001799299,0.00024770666,0.0002479281,0.00015191156,0.000005122363,0.00050055917,0.000010817577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011796807,0.0014323035,0.0002858375,0.00021410824,0.000089019566,0.00029381787,0.00067587115,0.00015338129,0.365499,0.001350074,0.0016862716,0.62714064],"study_design_scores_gemma":[0.0055698664,0.0001715023,0.0009844787,0.000928602,0.00044256894,0.0005721691,0.00015023277,0.7140624,0.265271,0.006939254,0.0042938814,0.00061403675],"about_ca_topic_score_codex":0.00018846421,"about_ca_topic_score_gemma":0.000007920896,"teacher_disagreement_score":0.79682446,"about_ca_system_score_codex":0.0000937177,"about_ca_system_score_gemma":0.000089562935,"threshold_uncertainty_score":0.94903874},"labels":[],"label_agreement":null},{"id":"W2104545915","doi":"10.1016/j.neuroimage.2008.10.054","title":"Mathematical methods for diffusion MRI processing","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; U.S. Public Health Service","keywords":"Diffusion MRI; Focus (optics); Computer science; Diffusion; White matter; Image processing; Segmentation; Artificial intelligence; Magnetic resonance imaging; Computer vision; Physics; Image (mathematics); Medicine; Optics; Radiology","score_opus":0.14868572963379884,"score_gpt":0.46108824227450507,"score_spread":0.31240251264070623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104545915","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015800279,0.000058178728,0.9759268,0.002717913,0.00001953009,0.00069299404,0.0000032114722,0.00041625262,0.0043647964],"genre_scores_gemma":[0.057217896,0.00006454831,0.93921614,0.0016432968,0.000083883904,0.00017236458,0.0000085284655,0.000046850426,0.0015464826],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.999246,0.000019281706,0.00018123974,0.0002789831,0.00009147917,0.000182996],"domain_scores_gemma":[0.9993599,0.00011758528,0.00005347959,0.00031364008,0.00006767725,0.000087691056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000091086185,0.00010936158,0.00019149041,0.000050634124,0.00018187253,0.000009051093,0.00007940765,0.000034858745,0.000025817024],"category_scores_gemma":[0.00015512265,0.000091736525,0.00008320402,0.00013507667,0.000094483396,0.00006449793,0.000043526168,0.00014507095,0.000013232629],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012617775,0.0007043313,0.0009359231,0.00042826193,0.0000068704203,0.00008328083,0.000228735,0.000002464284,0.7888979,0.005085347,0.012256285,0.19124448],"study_design_scores_gemma":[0.0028606313,0.00075573724,0.014538698,0.00022659538,0.00018770852,0.0037766763,0.000033115262,0.07679646,0.18085183,0.049960434,0.6693931,0.00061897474],"about_ca_topic_score_codex":3.321209e-7,"about_ca_topic_score_gemma":1.5126895e-8,"teacher_disagreement_score":0.65713686,"about_ca_system_score_codex":0.000013497158,"about_ca_system_score_gemma":0.000028991712,"threshold_uncertainty_score":0.37409067},"labels":[],"label_agreement":null},{"id":"W2105050326","doi":"10.1016/s0197-4580(02)00013-1","title":"A reliable MR measurement of medial temporal lobe width from the Sunnybrook Dementia Study","year":2002,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Women's College Hospital; University of Toronto","funders":"","keywords":"Temporal lobe; Hippocampus; Anterior commissure; Parahippocampal gyrus; Midbrain; Neuroscience; Hippocampal formation; Posterior commissure; Anatomy; Psychology; Medicine; Central nervous system; Epilepsy","score_opus":0.10307489958571628,"score_gpt":0.31592283895431383,"score_spread":0.21284793936859756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105050326","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99456435,0.00042561864,0.00077442406,0.0028474014,0.00010255277,0.00069461606,0.000012165633,0.00008594073,0.00049294706],"genre_scores_gemma":[0.9962034,0.00006866339,0.003099814,0.00047696792,0.00006437529,0.00003077928,0.0000074516897,0.000015814569,0.000032738364],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989982,0.00006450549,0.00033848276,0.00026440292,0.00016995087,0.00016441563],"domain_scores_gemma":[0.9991146,0.00008743571,0.00018618711,0.00047007832,0.00010586892,0.000035833153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020388793,0.00011472655,0.00026807623,0.00004348298,0.00006758647,0.0000026872347,0.00018806735,0.000032737265,0.00009039081],"category_scores_gemma":[0.000053170963,0.000082059596,0.00006484034,0.00013519917,0.00016463886,0.000028246068,0.000088843975,0.0001934701,0.0000047201643],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051480252,0.00083246036,0.8668078,0.000022002647,0.00012840758,0.000010016101,0.0004991778,0.000023475895,0.12232536,0.00008322887,0.007918879,0.0012976734],"study_design_scores_gemma":[0.0066655953,0.0036371355,0.6839259,0.00046225626,0.0014229392,0.000058490907,0.00056049577,0.00076964276,0.2756889,0.0019108425,0.024352262,0.00054555445],"about_ca_topic_score_codex":0.00012957824,"about_ca_topic_score_gemma":0.000017820903,"teacher_disagreement_score":0.18288194,"about_ca_system_score_codex":0.000014722091,"about_ca_system_score_gemma":0.000017239716,"threshold_uncertainty_score":0.33462933},"labels":[],"label_agreement":null},{"id":"W2105528651","doi":"10.1016/j.neuroimage.2007.11.033","title":"Complementary information from multi-exponential T2 relaxation and diffusion tensor imaging reveals differences between multiple sclerosis lesions","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Killam Trusts; Multiple Sclerosis Society","keywords":"Diffusion MRI; Fractional anisotropy; Multiple sclerosis; White matter; Nuclear magnetic resonance; T2 relaxation; Myelin; Lesion; Magnetic resonance imaging; Thermal diffusivity; Pathology; Medicine; Nuclear medicine; Neuroscience; Physics; Radiology; Psychology; Central nervous system","score_opus":0.1298048725404124,"score_gpt":0.33436079605896957,"score_spread":0.20455592351855717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105528651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8241466,0.000029735618,0.17317799,0.0014357807,0.000043605898,0.00061375863,0.00017452771,0.00027263677,0.000105337596],"genre_scores_gemma":[0.94957244,0.00010233136,0.04870966,0.00091740885,0.00012577644,0.000023317145,0.0004965222,0.000023404875,0.000029120738],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99863994,0.000037464037,0.00047590182,0.00032794496,0.00025172817,0.00026699947],"domain_scores_gemma":[0.99891603,0.0002783299,0.00022228326,0.00034278262,0.00008422681,0.00015633435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015721029,0.00018951554,0.0002444997,0.00017222585,0.00031327846,0.000054150387,0.00010632425,0.00004609776,0.000033306518],"category_scores_gemma":[0.00015917677,0.00017483183,0.00006040658,0.00016906032,0.00011136982,0.00047259466,0.00014909421,0.0002667405,0.00001763795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045149365,0.00008315468,0.7890499,0.00001810882,0.0000062560866,0.000005710421,0.000157717,2.8666523e-7,0.1612842,0.000030255831,0.00048768165,0.048831552],"study_design_scores_gemma":[0.0013886334,0.000057090892,0.98914,0.000110503584,0.000066688444,0.000009348119,0.000118260126,0.0022328808,0.00444176,0.00027789685,0.0020010336,0.00015590861],"about_ca_topic_score_codex":0.00029432363,"about_ca_topic_score_gemma":0.000012728292,"teacher_disagreement_score":0.20009007,"about_ca_system_score_codex":0.000038270835,"about_ca_system_score_gemma":0.000010128407,"threshold_uncertainty_score":0.7129435},"labels":[],"label_agreement":null},{"id":"W2105728290","doi":"10.1111/j.1600-0447.2009.01389.x","title":"Morphology of the corpus callosum in treatment‐resistant schizophrenia and major depression","year":2009,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Medical Research Council; National Health and Medical Research Council; China Scholarship Council","keywords":"Corpus callosum; Depression (economics); Treatment-resistant depression; Schizophrenia (object-oriented programming); Psychology; Medicine; Major depressive disorder; Neuroscience; Psychiatry","score_opus":0.02488008501270776,"score_gpt":0.3194196018808942,"score_spread":0.2945395168681864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105728290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9853238,0.0006618849,0.00009718298,0.0078160195,0.000036366368,0.00057186227,0.000010719821,0.00006894267,0.005413238],"genre_scores_gemma":[0.9921418,0.00027842485,0.0067174505,0.000248776,0.000027507047,0.000022936023,0.0000029685023,0.000015973117,0.0005441788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992982,0.000022251203,0.00019467421,0.0002453799,0.000085956264,0.00015351624],"domain_scores_gemma":[0.99937636,0.000027828832,0.0001075845,0.00040955306,0.00001372723,0.000064949105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002798551,0.00011571444,0.00020811675,0.00010304689,0.000058484413,0.000004199521,0.00010026041,0.000056509445,0.000022264754],"category_scores_gemma":[0.000015598916,0.00007334033,0.00005337882,0.00033631286,0.00007375981,0.000022080034,0.00002697206,0.000110069675,0.0000012654668],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001924403,0.0015872753,0.67833436,0.000039366307,0.000030321407,0.000038092836,0.00010330728,0.0000012623848,0.26230577,0.005907638,0.0070280256,0.042700164],"study_design_scores_gemma":[0.002699435,0.0005725142,0.978822,0.00007164813,0.000086791486,0.00013059545,0.0000090881695,0.00003772179,0.003794792,0.0036495319,0.010017678,0.00010819],"about_ca_topic_score_codex":0.00006257329,"about_ca_topic_score_gemma":0.000014822329,"teacher_disagreement_score":0.30048764,"about_ca_system_score_codex":0.000035352958,"about_ca_system_score_gemma":0.000029556888,"threshold_uncertainty_score":0.2990732},"labels":[],"label_agreement":null},{"id":"W2105775214","doi":"10.1109/42.925291","title":"Penalized discriminant analysis of [/sup 15/O]-water PET brain images with prediction error selection of smoothness and regularization hyperparameters","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute of Mental Health","keywords":"Hyperparameter; Mathematics; Artificial intelligence; Covariance; Smoothness; Smoothing; Pattern recognition (psychology); Computer science; Covariance matrix; Regularization (linguistics); Algorithm; Statistics; Mathematical analysis","score_opus":0.025316644421795632,"score_gpt":0.31685698515474287,"score_spread":0.2915403407329472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105775214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2952895,0.000011769039,0.70136684,0.0028987136,0.000020700736,0.00023949449,0.000019819054,0.0000898685,0.00006333569],"genre_scores_gemma":[0.99070126,0.00012062808,0.008526839,0.0003007199,0.000014678249,0.000060036145,0.000041577838,0.000026057416,0.00020821362],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855846,0.000060979044,0.00039389357,0.00033845316,0.00045678602,0.00019140633],"domain_scores_gemma":[0.9992723,0.00010341289,0.00010794426,0.00024538004,0.00015021002,0.00012075749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002236874,0.000158173,0.00039075766,0.00052701036,0.00011241447,0.000011104082,0.00006807643,0.000044150296,0.00014865087],"category_scores_gemma":[0.000028360428,0.000113456146,0.00011349889,0.00082838413,0.00032208636,0.00016805003,0.000002346955,0.00024478385,5.4623416e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029497035,0.0029449183,0.04794537,0.00064830296,0.0019823955,0.00018005988,0.00161985,0.021152962,0.7775923,0.00017547536,0.0005459565,0.1422627],"study_design_scores_gemma":[0.0036807489,0.00060387136,0.026141742,0.00066949124,0.005798322,0.0012150768,0.0005271897,0.5400796,0.41984335,0.0002729079,0.00075590634,0.00041180482],"about_ca_topic_score_codex":0.00008461893,"about_ca_topic_score_gemma":0.000013181197,"teacher_disagreement_score":0.6954118,"about_ca_system_score_codex":0.000038704442,"about_ca_system_score_gemma":0.000039634604,"threshold_uncertainty_score":0.46266073},"labels":[],"label_agreement":null},{"id":"W2106003398","doi":"10.1093/cercor/12.11.1218","title":"Asymmetry of the Uncinate Fasciculus: A Post-mortem Study of Normal Subjects and Patients with Schizophrenia","year":2002,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":205,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Queen's University; Wellcome Trust","keywords":"Uncinate fasciculus; Fasciculus; Inferior longitudinal fasciculus; Anatomy; Psychology; White matter; Neuroscience; Medicine; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.021300954928712566,"score_gpt":0.2541216520114659,"score_spread":0.23282069708275335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106003398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99846923,0.00003634842,0.00003497746,0.00014902983,0.000016646587,0.000740148,0.000014980289,0.000038265847,0.0005003561],"genre_scores_gemma":[0.99908245,0.0000043744035,0.0006402207,0.00011475562,0.00001087235,0.000014584645,0.0000035673843,0.000015503867,0.000113690585],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925923,0.000019082278,0.00019375878,0.00018954895,0.00021986502,0.00011848425],"domain_scores_gemma":[0.99923617,0.00001886479,0.00014876835,0.00037915754,0.0001641492,0.0000529158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003122251,0.000105362014,0.00019904904,0.000052079875,0.000059293725,0.0000038943363,0.00009977792,0.000024685745,0.000019431844],"category_scores_gemma":[0.000026623764,0.000063829786,0.000032980304,0.00028718592,0.00009734896,0.000059099948,0.00008204541,0.00013603785,0.0000010883755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000184223,0.0010223015,0.99007124,0.000059727543,0.000035235327,0.0000033337312,0.00029457518,0.0000012832784,0.002122612,0.00023031898,0.00013627415,0.0058388505],"study_design_scores_gemma":[0.0022951977,0.001246083,0.9937788,0.000056477136,0.00008691578,0.000010892984,0.00015556594,0.000119263495,0.0021024067,0.000037082224,0.000039184953,0.000072095485],"about_ca_topic_score_codex":0.00003794943,"about_ca_topic_score_gemma":0.000017813385,"teacher_disagreement_score":0.005766755,"about_ca_system_score_codex":0.000012254708,"about_ca_system_score_gemma":0.000013354297,"threshold_uncertainty_score":0.26029032},"labels":[],"label_agreement":null},{"id":"W2106241798","doi":"10.1016/s0720-048x(02)00305-4","title":"Diffusion weighted magnetic resonance imaging in stroke","year":2003,"lang":"en","type":"review","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canada Research Chairs","keywords":"Penumbra; Medicine; Magnetic resonance imaging; Diffusion MRI; Stroke (engine); Artifact (error); Effective diffusion coefficient; Radiology; Diffusion; Hyperintensity; Diffusion imaging; Ischemia; Artificial intelligence; Cardiology; Computer science","score_opus":0.05855231441885334,"score_gpt":0.35037951051591465,"score_spread":0.2918271960970613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106241798","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004607868,0.9937672,0.001933319,0.00017640076,0.00015676103,0.00029565376,0.000007793112,0.000026114092,0.0035906532],"genre_scores_gemma":[0.000032132382,0.9850667,0.013797789,0.0002335027,0.00023341655,0.000004272803,0.0000076512815,0.000078060315,0.0005464691],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99759364,0.00076576433,0.0010121497,0.0002600268,0.00011797003,0.00025044542],"domain_scores_gemma":[0.9986772,0.000118357035,0.0006554036,0.0003614493,0.000071385846,0.00011620978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005698327,0.00026043106,0.0012624684,0.00043513087,0.000033157605,0.000007768995,0.00028259138,0.00004800864,0.00004895324],"category_scores_gemma":[0.000093257724,0.00019480303,0.000314121,0.00024961584,0.00011435039,0.000035608173,0.000054462438,0.0010088065,0.000024014074],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017168197,0.000055344113,0.00016797139,0.00030541923,0.0000048371653,0.0020892464,0.000009599019,9.87555e-8,0.000024541603,0.00013696402,0.0027512286,0.9944376],"study_design_scores_gemma":[0.00063571014,0.00025521033,0.00037254585,0.0043751383,0.00018199254,0.022947095,0.0000029323294,0.000005603463,8.563869e-7,0.000059291997,0.9710287,0.00013493908],"about_ca_topic_score_codex":2.8589557e-7,"about_ca_topic_score_gemma":6.8807e-8,"teacher_disagreement_score":0.99430263,"about_ca_system_score_codex":0.00010312255,"about_ca_system_score_gemma":0.00011394972,"threshold_uncertainty_score":0.79438365},"labels":[],"label_agreement":null},{"id":"W2106440018","doi":"10.1109/iccv.2007.4409086","title":"On the Differential Geometry of 3D Flow Patterns: Generalized Helicoids and Diffusion MRI Analysis","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Curvature; Geometry; Helicoid; Differential geometry; Differential (mechanical device); Geometric analysis; Computer graphics; Computer science; Mathematics; Mathematical analysis; Artificial intelligence; Differential equation; Physics; Ordinary differential equation","score_opus":0.032409438905135486,"score_gpt":0.3280144220940771,"score_spread":0.29560498318894163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106440018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63043505,0.000014397075,0.36832467,0.00076794386,0.0000076070028,0.00013348053,0.000006423386,0.000042711472,0.00026773053],"genre_scores_gemma":[0.98785925,0.00017774265,0.010666763,0.0008401726,0.00003936236,0.000010152233,0.000021750278,0.000009480762,0.00037532308],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99936867,0.000011931863,0.00017772484,0.00017418432,0.00015273977,0.00011474054],"domain_scores_gemma":[0.9994087,0.00011158632,0.00005354137,0.00034046592,0.00003418192,0.000051494695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009584234,0.000086102715,0.00018791397,0.00016993062,0.00005550146,0.000006001129,0.000058863225,0.000032917418,0.0003134448],"category_scores_gemma":[0.00002214812,0.00004906865,0.00007776523,0.0003571468,0.000046026376,0.000013150562,0.0000504174,0.000095509575,0.0000013889875],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005852107,0.0014674012,0.3444751,0.00013408129,0.000757629,0.000025054884,0.0002628069,0.000085933076,0.5072059,0.036870193,0.002698925,0.10543178],"study_design_scores_gemma":[0.002144232,0.00044354488,0.78121555,0.000087896165,0.0013805534,0.000020977246,0.00010237073,0.04774353,0.16186136,0.0026664173,0.0020023282,0.00033121594],"about_ca_topic_score_codex":0.000044661076,"about_ca_topic_score_gemma":0.0000099701965,"teacher_disagreement_score":0.4367405,"about_ca_system_score_codex":0.000009815466,"about_ca_system_score_gemma":0.0000031149264,"threshold_uncertainty_score":0.34320006},"labels":[],"label_agreement":null},{"id":"W2106610784","doi":"10.1093/schbul/sbr193","title":"The Incidence and Nature of Cerebellar Findings in Schizophrenia: A Quantitative Review of fMRI Literature","year":2012,"lang":"en","type":"review","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Institut universitaire en santé mentale de Montréal; Cegep de Sainte Foy; Home and Community Care Support Services; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Cerebellum; Neuroscience; Schizophrenia (object-oriented programming); Neuroimaging; Psychology; Functional magnetic resonance imaging; Functional neuroimaging; Cognition; Magnetic resonance imaging; Cerebellar hemisphere; Audiology; Medicine; Psychiatry; Radiology","score_opus":0.04360327085431317,"score_gpt":0.3700997363761323,"score_spread":0.32649646552181916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106610784","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007513322,0.99572444,0.000026978796,0.0018631138,0.00006038765,0.0019041941,0.000117450734,0.000043059434,0.0001852435],"genre_scores_gemma":[0.00012439144,0.97907084,0.02006252,0.00017106836,0.00006366603,0.00022892939,0.0000866884,0.00006693568,0.00012495244],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974263,0.00022021354,0.0011350998,0.0005264434,0.0003607967,0.00033118253],"domain_scores_gemma":[0.9971766,0.00077896577,0.00077344937,0.00090701564,0.0002450186,0.000118978794],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008080814,0.0004849039,0.0020243912,0.00024725555,0.000096256175,0.000018312767,0.0004253878,0.00046563748,0.000037046277],"category_scores_gemma":[0.0008013787,0.0003113613,0.00038077208,0.0010429892,0.00035391832,0.00004558912,0.00025557616,0.0020940672,0.000014243031],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046224054,0.00019480578,0.00006075555,0.24656492,0.00017548185,0.000038363858,0.00009930567,3.2712556e-8,0.000028942362,0.029815732,0.006673527,0.7158859],"study_design_scores_gemma":[0.00033785985,0.00008439056,0.00009363095,0.20293051,0.0005974587,0.0001950804,0.000005484934,4.6632945e-7,0.000024346256,0.0004190218,0.7951048,0.00020694752],"about_ca_topic_score_codex":0.0000076218557,"about_ca_topic_score_gemma":0.000003242855,"teacher_disagreement_score":0.7884313,"about_ca_system_score_codex":0.000051542494,"about_ca_system_score_gemma":0.00020760777,"threshold_uncertainty_score":0.99993384},"labels":[],"label_agreement":null},{"id":"W2107019320","doi":"10.3174/ajnr.a1985","title":"Alteration of Human Fetal Subplate Layer and Intermediate Zone During Normal Development on MR and Diffusion Tensor Imaging","year":2010,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Hospital for Sick Children","funders":"","keywords":"Subplate; White matter; Diffusion MRI; Intensity (physics); Medicine; Magnetic resonance imaging; Anatomy; Pathology; Cerebral cortex; Optics; Radiology; Internal medicine; Physics","score_opus":0.020538207827025694,"score_gpt":0.3140670428816063,"score_spread":0.2935288350545806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107019320","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979647,0.0000140522525,0.0010167188,0.0008378655,0.000050310427,0.0000789367,0.0000011477646,0.0000133717085,0.000022888236],"genre_scores_gemma":[0.99445206,0.00005764642,0.0050849426,0.00029758603,0.00007766852,0.0000024848016,0.0000015167858,0.000013273917,0.000012834158],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993143,0.000029792855,0.00031301178,0.00013435849,0.00008957005,0.00011893584],"domain_scores_gemma":[0.9993287,0.000053016123,0.00034178921,0.00010201607,0.000083377905,0.00009110896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000986987,0.00009349672,0.00027652417,0.000155396,0.000070391325,0.0000056806116,0.000051396797,0.000015532707,0.0000043632763],"category_scores_gemma":[0.00004447913,0.000075293094,0.00002684943,0.00006104203,0.00030229578,0.000059787304,0.0000401032,0.00033814786,2.9940296e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000111146706,0.00004561124,0.15144788,0.000010470263,0.000008380852,0.00005903729,0.00013802471,0.0000017989431,0.83103746,0.000043102355,0.000010641146,0.017086448],"study_design_scores_gemma":[0.0008076905,0.0010655166,0.9536914,0.00004794806,0.000027390537,0.004223678,0.000042138574,0.00018586418,0.039331466,0.00004074954,0.00045328154,0.00008285818],"about_ca_topic_score_codex":0.0000040757836,"about_ca_topic_score_gemma":0.0000016207571,"teacher_disagreement_score":0.80224353,"about_ca_system_score_codex":0.000011200379,"about_ca_system_score_gemma":0.000020061705,"threshold_uncertainty_score":0.3070363},"labels":[],"label_agreement":null},{"id":"W2107294026","doi":"10.1016/j.neuroimage.2005.03.016","title":"Diffusion tensor imaging of neurodevelopment in children and young adults","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":355,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Splenium; Corpus callosum; Diffusion MRI; Caudate nucleus; Effective diffusion coefficient; Psychology; Magnetic resonance imaging; Putamen; Young adult; Internal capsule; Medicine; White matter; Nuclear magnetic resonance; Neuroscience; Developmental psychology; Radiology; Physics","score_opus":0.015803536626992305,"score_gpt":0.2876446576296194,"score_spread":0.2718411210026271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107294026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996043,0.00008853291,0.0004898218,0.002096172,0.0000132495,0.00042439732,0.0000069954053,0.00009953846,0.0007382547],"genre_scores_gemma":[0.98602223,0.00024303401,0.012825184,0.00070910505,0.000030345662,0.00001787886,0.0000092952905,0.000023763185,0.00011913667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991651,0.000013666446,0.00023294092,0.00030621706,0.00012232146,0.00015976281],"domain_scores_gemma":[0.9995758,0.000016941003,0.000063611515,0.0002505735,0.000032706186,0.000060347207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047936705,0.000111819674,0.00016475057,0.000120250144,0.000032209446,0.000006763994,0.000065796026,0.000017310498,0.000010039683],"category_scores_gemma":[0.000043976343,0.00010441566,0.000027165772,0.00015114126,0.00006326585,0.000083538005,0.00008636756,0.00016925283,0.000003444163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041861746,0.00014811421,0.91926074,0.000016561884,0.000001445835,0.000013896824,0.0000792081,0.0000021319142,0.036085073,0.00006886739,0.0002768318,0.04400526],"study_design_scores_gemma":[0.0008379595,0.000035954865,0.99212646,0.00005648632,0.000009216947,0.00025925512,0.000006243203,0.0011212665,0.0045613237,0.000044452237,0.00086009584,0.000081292055],"about_ca_topic_score_codex":0.000027781338,"about_ca_topic_score_gemma":0.0000027831743,"teacher_disagreement_score":0.07286571,"about_ca_system_score_codex":0.000016166456,"about_ca_system_score_gemma":0.000013171202,"threshold_uncertainty_score":0.4257947},"labels":[],"label_agreement":null},{"id":"W2107480447","doi":"10.1007/s11538-010-9589-1","title":"Restricted Diffusion in Cellular Media: (1+1)-Dimensional Model","year":2010,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Diffusion; Space (punctuation); Membrane; Biological system; Eigenfunction; Cellular compartment; Physics; Biophysics; Chemistry; Cell; Computer science; Biology; Eigenvalues and eigenvectors; Quantum mechanics","score_opus":0.04201676429705043,"score_gpt":0.3194109647560132,"score_spread":0.2773942004589628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107480447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97044957,0.000020809739,0.017291555,0.008652861,0.000025063713,0.00030616726,0.00000924297,0.00008340361,0.0031613223],"genre_scores_gemma":[0.8233257,0.000010519263,0.17614014,0.00029385005,0.000025314055,0.00003159405,0.000020506921,0.000011240836,0.0001411389],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992812,0.000016393962,0.00029185394,0.00018642018,0.000079629295,0.00014446075],"domain_scores_gemma":[0.99925554,0.0002930631,0.000062774365,0.0002761986,0.00004619563,0.00006624499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010622822,0.00008599199,0.00025160096,0.00007394204,0.000017093593,0.0000010519334,0.00008793881,0.00013312843,0.00045636998],"category_scores_gemma":[0.0005135681,0.000065046814,0.00004607207,0.00007945894,0.00017642842,0.0000031771813,0.000076307784,0.00030183137,0.000049822796],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004793114,0.00049365225,0.00046623827,0.00004207125,0.000002855672,0.0000089296655,0.00002165407,0.0000057248167,0.8584244,0.1382137,0.0015487957,0.00072403013],"study_design_scores_gemma":[0.0024841942,0.00032947687,0.00422442,0.0002068291,0.000062327024,0.0001605497,0.000018515937,0.038760427,0.12932892,0.798299,0.025766406,0.00035891787],"about_ca_topic_score_codex":0.0000044973704,"about_ca_topic_score_gemma":5.3985605e-7,"teacher_disagreement_score":0.7290955,"about_ca_system_score_codex":0.000006181902,"about_ca_system_score_gemma":0.000020126487,"threshold_uncertainty_score":0.49969313},"labels":[],"label_agreement":null},{"id":"W2107996484","doi":"10.1109/iembs.2006.260314","title":"A High-Resolution Anisotropic Finite-Volume Head Model for EEG Source Analysis","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Head (geology); Finite volume method; Electroencephalography; Source model; Computer science; Volume (thermodynamics); Geology; Mechanics; Physics; Theoretical computer science; Medicine","score_opus":0.05098986032001237,"score_gpt":0.33408588071218825,"score_spread":0.2830960203921759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107996484","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03588172,0.000026929787,0.9603142,0.002398503,0.0000064059814,0.00037822934,0.000024248217,0.00039834608,0.00057137606],"genre_scores_gemma":[0.7027126,0.000006707746,0.2799525,0.00044970808,0.00004474088,0.00011946298,0.00013226032,0.000014932327,0.016567126],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992619,0.0000054182233,0.00019106701,0.0002577095,0.000098946155,0.00018491568],"domain_scores_gemma":[0.99945635,0.000035305573,0.000053899133,0.0003303731,0.00007569896,0.000048395763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037582282,0.00009859287,0.00020382897,0.00013450946,0.000099738485,0.0000113424385,0.000059204107,0.00004425127,0.000036731424],"category_scores_gemma":[0.00001885224,0.000088538975,0.00015504818,0.00037455015,0.000033743574,0.00004359419,0.00002118965,0.00006803725,0.000011118326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018684265,0.00083322707,0.025685593,0.000081796024,0.0002149698,0.000004281515,0.00004420542,0.7800715,0.020329844,0.11825085,0.047507484,0.0067894105],"study_design_scores_gemma":[0.00043428637,0.000063575906,0.0072547984,0.00000469786,0.00038073704,0.0000021279732,0.0000035567823,0.96817845,0.0005213636,0.008343211,0.01472063,0.00009256162],"about_ca_topic_score_codex":0.0002587108,"about_ca_topic_score_gemma":0.00005977261,"teacher_disagreement_score":0.68036175,"about_ca_system_score_codex":0.000044764158,"about_ca_system_score_gemma":0.000019308456,"threshold_uncertainty_score":0.36105147},"labels":[],"label_agreement":null},{"id":"W2108343092","doi":"10.1371/journal.pone.0073692","title":"Network Dynamics Underlying Speed-Accuracy Trade-Offs in Response to Errors","year":2013,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Mental Health","keywords":"Diffusion MRI; Fractional anisotropy; Anterior cingulate cortex; Neuroscience; Reciprocal; Computer science; Intraparietal sulcus; Functional magnetic resonance imaging; Psychology; Medicine; Cognition; Magnetic resonance imaging","score_opus":0.1641656758659303,"score_gpt":0.35369675644844095,"score_spread":0.18953108058251064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108343092","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9553003,0.00003108487,0.0036262218,0.03868934,0.000011573876,0.0011835785,0.0000041615162,0.00026409872,0.00088968384],"genre_scores_gemma":[0.933922,0.000018803847,0.06261426,0.0026743806,0.000053668846,0.00013000004,0.000011710336,0.00003552408,0.00053968374],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990573,0.00003396921,0.00021879027,0.0002444474,0.00016783325,0.0002776459],"domain_scores_gemma":[0.99920046,0.00019172042,0.00004833798,0.00039475004,0.000029470975,0.00013524678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001233613,0.00011225614,0.00021532027,0.00009534993,0.00005466054,0.000015866108,0.000107798376,0.000046233257,0.000053122865],"category_scores_gemma":[0.0002384867,0.00011357894,0.00002889792,0.00041346837,0.000029082972,0.00008717233,0.00003798029,0.0002441399,0.00009335366],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00270934,0.006812368,0.12362896,0.00039851293,0.00017043613,0.00017603123,0.0014169543,0.001316035,0.80973727,0.00796884,0.014676018,0.030989248],"study_design_scores_gemma":[0.0024677883,0.0014895139,0.8721747,0.0022004652,0.00022410852,0.000059283684,0.00053031096,0.082187235,0.008392133,0.024789015,0.0044746883,0.0010107959],"about_ca_topic_score_codex":0.000034245637,"about_ca_topic_score_gemma":0.000014744891,"teacher_disagreement_score":0.8013451,"about_ca_system_score_codex":0.00013534052,"about_ca_system_score_gemma":0.000029243842,"threshold_uncertainty_score":0.4631615},"labels":[],"label_agreement":null},{"id":"W2108677211","doi":"10.1215/15228517-2006-002","title":"Diffusion tensor imaging of white matter after cranial radiation in children for medulloblastoma: Correlation with IQ","year":2006,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":192,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; SickKids Foundation; Hospital for Sick Children; McMaster University; University of Toronto","funders":"","keywords":"White matter; Fractional anisotropy; Internal capsule; Diffusion MRI; Corpus callosum; Effective diffusion coefficient; Nuclear medicine; Medicine; Intelligence quotient; Correlation; Psychology; Magnetic resonance imaging; Pathology; Radiology; Neuroscience; Cognition","score_opus":0.008528242953704352,"score_gpt":0.28372072296481327,"score_spread":0.2751924800111089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108677211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.958244,0.000025674426,0.035430606,0.004524212,0.000047806658,0.0011565733,0.000018644587,0.00007259825,0.00047985275],"genre_scores_gemma":[0.98664796,0.00000893247,0.011581521,0.0012162462,0.00012685724,0.00027028265,0.000063282394,0.000032794804,0.000052132367],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914044,0.00003168938,0.0002827057,0.00027124118,0.00009830953,0.00017563286],"domain_scores_gemma":[0.99945706,0.000095079675,0.00015915847,0.0001874168,0.00006811434,0.0000331946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058481397,0.00011614321,0.0002325648,0.00015702155,0.0000489263,0.000003615888,0.00004994014,0.00006369302,0.000031354797],"category_scores_gemma":[0.000021083268,0.00010029498,0.00004460771,0.00015998777,0.000079235586,0.00007287054,0.000030394482,0.00015619262,0.0000051407706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052798406,0.0002179573,0.95886624,0.000013772124,0.0000025375982,0.00000919577,0.000049709222,0.00011766608,0.035870176,0.00006974583,0.0010512874,0.003203727],"study_design_scores_gemma":[0.0025674799,0.0004091792,0.9848064,0.000026157317,0.0000551758,0.00022980926,0.000006810171,0.0029885317,0.002223679,0.00035772932,0.0062356037,0.00009341741],"about_ca_topic_score_codex":0.00003092418,"about_ca_topic_score_gemma":0.000014929246,"teacher_disagreement_score":0.033646498,"about_ca_system_score_codex":0.000081313,"about_ca_system_score_gemma":0.000042568132,"threshold_uncertainty_score":0.40899107},"labels":[],"label_agreement":null},{"id":"W2109181684","doi":"10.1523/jneurosci.5302-10.2011","title":"Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1238,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Fondation pour la Recherche Médicale","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Brain size; Longitudinal study; Brain development; Psychology; Human brain; Neuroscience; Anatomy; Physiology; Internal medicine; Biology; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.10227087953948731,"score_gpt":0.3613307277025508,"score_spread":0.2590598481630635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109181684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97948813,0.000040157825,0.019711781,0.00035942704,0.00006375767,0.00008883173,0.0000011291285,0.000021189562,0.00022558153],"genre_scores_gemma":[0.92064875,0.000012601611,0.07895614,0.00030401227,0.000043169995,0.0000018910256,3.0379368e-7,0.00000829723,0.000024808573],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990255,0.000014419661,0.0004294143,0.00015686669,0.00025471908,0.000119077056],"domain_scores_gemma":[0.9991711,0.000028278086,0.00039842754,0.00017246355,0.0001272639,0.000102490296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015825838,0.00008173743,0.00020279693,0.000105108884,0.00009974682,0.000008110075,0.00023824298,0.00001821269,0.00000855776],"category_scores_gemma":[0.00017020745,0.00006643297,0.000058971153,0.00017704457,0.00012346855,0.00014994596,0.00006573613,0.00019135725,8.118206e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021534328,0.00030259395,0.050711773,0.000010221941,0.00000382409,0.00004215503,0.0017685504,5.59689e-7,0.94112444,0.00016920187,0.00013552982,0.005709595],"study_design_scores_gemma":[0.00031014,0.00030770423,0.83464897,0.00014670505,0.00001496275,0.00013268659,0.000049169375,0.00001043374,0.16211508,0.0012072441,0.0009997346,0.00005715837],"about_ca_topic_score_codex":0.000005578513,"about_ca_topic_score_gemma":0.0000013791928,"teacher_disagreement_score":0.7839372,"about_ca_system_score_codex":0.000019178648,"about_ca_system_score_gemma":0.00008487584,"threshold_uncertainty_score":0.2709058},"labels":[],"label_agreement":null},{"id":"W2109345578","doi":"10.3389/fnins.2015.00396","title":"Assessing intracortical myelin in the living human brain using myelinated cortical thickness","year":2015,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McMaster University; National Alliance for Research on Schizophrenia and Depression; Brain and Behavior Research Foundation","keywords":"Cortex (anatomy); Myelin; Neuroscience; Cerebral cortex; Magnetic resonance imaging; Gyrus; Medicine; Anatomy; Psychology; Central nervous system; Radiology","score_opus":0.1664601240308233,"score_gpt":0.42879533086726257,"score_spread":0.2623352068364393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109345578","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73388106,0.000040377738,0.2621295,0.002954092,0.00025088075,0.0003474116,7.2359256e-7,0.00008675428,0.0003092301],"genre_scores_gemma":[0.96190673,0.000007533467,0.0347818,0.0031859872,0.000053994594,0.000023159935,0.0000010827846,0.00001653354,0.000023156168],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982293,0.00020644533,0.00034856892,0.00044704237,0.00038867386,0.0003799217],"domain_scores_gemma":[0.9992078,0.00016127389,0.00006965264,0.00038401547,0.000052668365,0.00012457222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010467944,0.00013152564,0.00021305625,0.00019514574,0.00016143266,0.00010558945,0.00035980257,0.00006231579,0.0000013830338],"category_scores_gemma":[0.002048457,0.000103641265,0.000032737804,0.0011045426,0.00044741543,0.0003265439,0.00011045475,0.0007203792,8.0538314e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040151306,0.00080817903,0.74436766,0.000049946557,0.0000014487682,0.00060410623,0.0014850093,0.0010282391,0.23911959,0.0039039662,0.0030976783,0.0054940255],"study_design_scores_gemma":[0.0006714383,0.0001893355,0.666525,0.00035996505,0.000023533103,0.0004496267,0.0015998634,0.322263,0.00064298284,0.005301167,0.0016643448,0.00030975413],"about_ca_topic_score_codex":0.000022180997,"about_ca_topic_score_gemma":0.0000028904979,"teacher_disagreement_score":0.32123476,"about_ca_system_score_codex":0.00011590162,"about_ca_system_score_gemma":0.0001350566,"threshold_uncertainty_score":0.4226368},"labels":[],"label_agreement":null},{"id":"W2110036421","doi":"10.1093/cercor/bhs188","title":"Oligodendrocyte Genes, White Matter Tract Integrity, and Cognition in Schizophrenia","year":2012,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"White matter; Oligodendrocyte; Schizophrenia (object-oriented programming); Neuroscience; Cognition; Psychology; Biology; Medicine; Magnetic resonance imaging; Psychiatry; Central nervous system; Myelin","score_opus":0.053820338088351544,"score_gpt":0.33025606637381033,"score_spread":0.2764357282854588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110036421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921775,0.00037637583,0.0014990969,0.00115451,0.00004302831,0.00031194926,0.000010788026,0.000108834436,0.004317946],"genre_scores_gemma":[0.99100554,0.00009130852,0.0073279073,0.0010306148,0.0001166119,0.00004207412,0.00003954863,0.000021181157,0.00032523306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99936324,0.000014153819,0.0001548738,0.00017767993,0.00007990541,0.00021015198],"domain_scores_gemma":[0.99963564,0.000014620116,0.000041208514,0.00017294269,0.000021999935,0.00011358101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000609166,0.00010764499,0.0001493065,0.00008282979,0.000037287056,0.0000122981455,0.0000419564,0.000058398156,0.00016935523],"category_scores_gemma":[0.000007153102,0.00009773033,0.000029970586,0.000108556706,0.00004953101,0.00017067604,0.00004234365,0.0003235373,0.000085355496],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011465307,0.00022355128,0.9726899,0.000055394376,0.000006430341,0.0000106208045,0.00007531608,1.08739556e-7,0.010814157,0.0011664627,0.0016980671,0.013145307],"study_design_scores_gemma":[0.00067145535,0.000046033798,0.99092925,0.000058610112,0.000034478635,0.00033305096,0.000018999976,0.0000787978,0.0035485611,0.0008429165,0.0033199606,0.00011786745],"about_ca_topic_score_codex":0.0000122225865,"about_ca_topic_score_gemma":0.0000048223665,"teacher_disagreement_score":0.018239336,"about_ca_system_score_codex":0.000025631005,"about_ca_system_score_gemma":0.0000145194,"threshold_uncertainty_score":0.39853272},"labels":[],"label_agreement":null},{"id":"W2110450380","doi":"10.1017/s1355617713001148","title":"Relations between White Matter Maturation and Reaction Time in Childhood","year":2013,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Toronto; Hospital for Sick Children","funders":"National Cancer Institute","keywords":"White matter; White (mutation); Psychology; Developmental psychology; Cognitive science; Medicine; Biology; Magnetic resonance imaging; Genetics; Radiology","score_opus":0.028634120435631686,"score_gpt":0.3185484023873168,"score_spread":0.2899142819516851,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110450380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92476463,0.00001010635,0.00046201926,0.07286344,0.00008086149,0.00017064967,0.0000023951804,0.000014357957,0.0016315337],"genre_scores_gemma":[0.990336,0.000032157604,0.005141635,0.0034558834,0.00017141286,0.0000064295364,0.0000026034272,0.0000075405032,0.00084636075],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993178,0.000027857484,0.00029460623,0.00010660392,0.00018481894,0.000068279005],"domain_scores_gemma":[0.9994783,0.000060778813,0.00021618907,0.000103052254,0.000101322556,0.000040351817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011659883,0.00006363668,0.00010516806,0.000030004425,0.000045235905,0.000026418837,0.00013375864,0.00005048471,0.0001071165],"category_scores_gemma":[0.000063487365,0.00003873119,0.00012296901,0.000112085945,0.00004909965,0.00016985399,0.00004706612,0.00043331104,0.000038893475],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003651894,0.00021552648,0.87433684,0.0000028747536,0.000032238368,0.0000030876315,0.0001004175,0.000008093634,0.07669297,0.00007414397,0.046796657,0.0017006077],"study_design_scores_gemma":[0.00031795824,0.000045350498,0.9935578,0.00002954107,0.000013642572,0.00024168775,0.000009625071,0.00012769725,0.000065126056,0.003244402,0.0023123883,0.00003474143],"about_ca_topic_score_codex":0.000001771348,"about_ca_topic_score_gemma":6.038156e-8,"teacher_disagreement_score":0.11922097,"about_ca_system_score_codex":0.00004448944,"about_ca_system_score_gemma":0.000008948053,"threshold_uncertainty_score":0.18825449},"labels":[],"label_agreement":null},{"id":"W2110484413","doi":"10.1007/978-3-540-85988-8_17","title":"Streamline Flows for White Matter Fibre Pathway Segmentation in Diffusion MRI","year":2008,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Voxel; Tractography; Computer science; Segmentation; Diffusion MRI; Artificial intelligence; White matter; Pairwise comparison; Consistency (knowledge bases); Algorithm; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging","score_opus":0.031290538802596725,"score_gpt":0.31535869955669005,"score_spread":0.2840681607540933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110484413","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30791193,0.000012366269,0.6890461,0.0025413278,0.00004891247,0.00038727417,0.000003138834,0.00004178094,0.0000071890813],"genre_scores_gemma":[0.58545774,0.000008972764,0.4131348,0.0012858828,0.00005651695,0.000036371413,0.000009136652,0.000006210987,0.0000043554355],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907947,0.000008876395,0.00017239313,0.00037271596,0.00015814051,0.00020838284],"domain_scores_gemma":[0.9995077,0.00008403571,0.00004195989,0.00026956722,0.000050527146,0.000046179313],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000099406905,0.000098865545,0.00012902814,0.00017334522,0.000099170225,0.000014592022,0.00014885746,0.00003404157,0.000009336292],"category_scores_gemma":[0.00002390762,0.00008235634,0.000027225735,0.00057761214,0.00010580745,0.000118377175,0.00007465565,0.00012790484,0.0000036356892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012278058,0.00040612853,0.44088474,0.000101255704,0.0000023814716,0.00006406986,0.0022310845,0.049302656,0.14668047,0.00004268504,0.00029443772,0.3598673],"study_design_scores_gemma":[0.0012544934,0.00026511916,0.17388192,0.00016946232,0.0000040428613,0.00016080981,0.0000016969997,0.729243,0.08926692,0.0051089386,0.00041464975,0.00022898254],"about_ca_topic_score_codex":0.000008252296,"about_ca_topic_score_gemma":0.000013823445,"teacher_disagreement_score":0.6799403,"about_ca_system_score_codex":0.00007099114,"about_ca_system_score_gemma":0.00005552548,"threshold_uncertainty_score":0.3358394},"labels":[],"label_agreement":null},{"id":"W2111438395","doi":"10.1016/j.clinimag.2004.08.001","title":"Diffusion and magnetization transfer MRI of brain infarct, infection, and tumor in children","year":2005,"lang":"en","type":"article","venue":"Clinical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre","funders":"","keywords":"Medicine; Magnetization transfer; Diffusion MRI; Parenchyma; Differential diagnosis; Magnetic resonance imaging; Pathology; Brain tumor; Effective diffusion coefficient; Radiology; Nuclear medicine","score_opus":0.03196621140562356,"score_gpt":0.3844727147642563,"score_spread":0.35250650335863276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111438395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97380966,0.00014054887,0.018604955,0.006947608,0.000008403796,0.00029372165,0.0000021214055,0.000055107284,0.00013785102],"genre_scores_gemma":[0.9922713,0.0005058492,0.005363603,0.001743072,0.00006119428,0.000010644655,0.0000068215804,0.000011308931,0.00002618848],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993,0.00002652743,0.00033283787,0.00020189217,0.000053529602,0.0000852177],"domain_scores_gemma":[0.99966866,0.00008534918,0.000034556062,0.00012359988,0.00002948046,0.000058333626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018538212,0.00006692001,0.00016099669,0.00007318793,0.000027311356,0.000006563977,0.000021785398,0.000022388971,0.000009620968],"category_scores_gemma":[0.00013327102,0.00006198031,0.000026137011,0.00011690897,0.0001467844,0.00008556437,0.000030660918,0.00016561856,7.486054e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013739423,0.00009672635,0.9318937,0.000014274892,0.0000015456149,6.899103e-7,0.000023194107,0.0000026972082,0.002304832,0.00018181867,0.00010541162,0.06536135],"study_design_scores_gemma":[0.0009940213,0.00005355071,0.991764,0.00008886387,0.00001756678,0.000061876584,0.000003001761,0.003684515,0.00050141383,0.0005468315,0.0022250225,0.00005931386],"about_ca_topic_score_codex":0.000027853052,"about_ca_topic_score_gemma":0.0000053785943,"teacher_disagreement_score":0.06530204,"about_ca_system_score_codex":0.0000072665302,"about_ca_system_score_gemma":0.000010273552,"threshold_uncertainty_score":0.25274837},"labels":[],"label_agreement":null},{"id":"W2111508341","doi":"10.1002/mrm.21277","title":"Regularized, fast, and robust analytical Q‐ball imaging","year":2007,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":847,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften; McGill University","keywords":"Unit sphere; Regularization (linguistics); Spherical harmonics; Imaging phantom; Tikhonov regularization; Mathematics; Laplace transform; Mathematical analysis; Algorithm; Computer science; Inverse problem; Artificial intelligence; Physics; Optics","score_opus":0.05022523487800512,"score_gpt":0.3508908641564233,"score_spread":0.30066562927841817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111508341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50913125,0.055430412,0.23198724,0.111123785,0.00028412227,0.003140394,0.000009444409,0.0008806162,0.08801272],"genre_scores_gemma":[0.84162706,0.0027262864,0.14096193,0.0072812233,0.0006226921,0.00007437503,0.000020623145,0.0000861367,0.0065996596],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9984903,0.000016817274,0.00041792245,0.000419798,0.00028083223,0.00037434054],"domain_scores_gemma":[0.9991452,0.00014508102,0.00005261236,0.0004149049,0.000061418395,0.00018076829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055477786,0.00016709931,0.00035097587,0.00021300184,0.000048050068,0.0000069666467,0.000102704966,0.000051334082,0.00011754814],"category_scores_gemma":[0.00024335845,0.00013734112,0.00002737649,0.0004702829,0.00046918128,0.000044770237,0.000060386614,0.00034097163,0.0000047217545],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024436825,0.00013667667,0.19726795,0.00007637612,0.000002710137,0.0007121992,0.00019687506,0.000005785408,0.0058839717,0.006707443,0.0055504125,0.7832152],"study_design_scores_gemma":[0.0035373843,0.00042391915,0.81643194,0.00066016323,0.0000673493,0.0007493824,0.00023608639,0.021043047,0.00027773762,0.0038717655,0.15245058,0.00025067298],"about_ca_topic_score_codex":0.000061049395,"about_ca_topic_score_gemma":0.000012767831,"teacher_disagreement_score":0.7829646,"about_ca_system_score_codex":0.000050496903,"about_ca_system_score_gemma":0.000021242024,"threshold_uncertainty_score":0.56006086},"labels":[],"label_agreement":null},{"id":"W2111552401","doi":"10.1016/j.neurobiolaging.2014.07.045","title":"Cortical surface biomarkers for predicting cognitive outcomes using group l2,1 norm","year":2014,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Division of Biological Infrastructure; National Center for Research Resources; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; National Institutes of Health; U.S. National Library of Medicine; IXICO; Genentech Foundation; Servier; Eisai; Elan; Division of Information and Intelligent Systems; Northern California Institute for Research and Education; Pfizer; Biogen; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb Foundation; U.S. Department of Defense; Eli Lilly and Company; Roche; Merck; Alzheimer's Drug Discovery Foundation; National Institute on Aging; Alzheimer's Association; National Institute of Biomedical Imaging and Bioengineering; Takeda Pharmaceuticals North America; Canadian Institutes of Health Research; National Science Foundation","keywords":"Neuroimaging; Cognition; Predictive power; Feature selection; Cognitive psychology; Machine learning; Correlation; Artificial intelligence; Regression; Psychology; Computer science; Set (abstract data type); Neuroscience; Mathematics","score_opus":0.07321909421608658,"score_gpt":0.37643393259099434,"score_spread":0.30321483837490776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111552401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9070282,0.000013487722,0.09113927,0.0009197239,0.000080654696,0.00045243595,0.000019262747,0.00015294987,0.0001940127],"genre_scores_gemma":[0.9619607,0.0000066750345,0.03716881,0.00074070616,0.000040581803,0.000013923343,0.00002556886,0.000025759098,0.000017325141],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990884,0.000047204405,0.00026794217,0.00030405936,0.00005218294,0.00024021509],"domain_scores_gemma":[0.9987193,0.0008164404,0.00013958437,0.00017954336,0.00008614019,0.00005898735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018153666,0.00012719484,0.0003041413,0.000059391874,0.00011759791,0.0000038101264,0.00007294119,0.000059723716,0.0000041129147],"category_scores_gemma":[0.00029915615,0.00011321048,0.000097971046,0.00010073579,0.00021570081,0.000040049465,0.00005653619,0.00016770745,9.646368e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010645406,0.00012267094,0.7603636,0.000109603425,0.000072826326,0.000001980518,0.000057602792,0.00004043744,0.23630118,0.0010998667,0.00006543146,0.0016583578],"study_design_scores_gemma":[0.0055037187,0.0018865818,0.7593268,0.00060010084,0.00085992063,0.00027368628,0.00026257182,0.048566684,0.17863652,0.0016743043,0.0017775872,0.0006314936],"about_ca_topic_score_codex":0.000011328994,"about_ca_topic_score_gemma":7.4798044e-7,"teacher_disagreement_score":0.057664674,"about_ca_system_score_codex":0.000014486134,"about_ca_system_score_gemma":0.000015354972,"threshold_uncertainty_score":0.46165895},"labels":[],"label_agreement":null},{"id":"W2111627180","doi":"10.1016/j.media.2009.01.004","title":"Directional functions for orientation distribution estimation","year":2009,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Spherical harmonics; Orientation (vector space); Interpolation (computer graphics); Spherical coordinate system; Computer science; Unit sphere; Tractography; Geodesic; Algorithm; Diffusion MRI; Artificial intelligence; Mathematics; Computer vision; Mathematical analysis; Geometry; Image (mathematics)","score_opus":0.03070482850914545,"score_gpt":0.3971433175471677,"score_spread":0.36643848903802223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111627180","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006793665,0.000016394439,0.9803461,0.011834591,0.000025524101,0.00024097362,0.000053638993,0.00022188041,0.00046725513],"genre_scores_gemma":[0.9032915,0.000029836961,0.08878592,0.0013148823,0.0001819562,0.00016030794,0.005293769,0.000008826432,0.00093298143],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990873,0.000012757345,0.00022145867,0.00023704984,0.0003148306,0.00012661553],"domain_scores_gemma":[0.9993493,0.000070053684,0.00006376034,0.00019097528,0.00018527824,0.0001406575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015923577,0.00007882801,0.00017425625,0.00012477158,0.00015535273,0.000017509376,0.000044273493,0.000053723008,0.0002459835],"category_scores_gemma":[0.0005626415,0.000070322225,0.00020319286,0.0009427979,0.0000511582,0.00011174156,0.000006781728,0.00010527919,0.000015747843],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003701963,0.0023031572,0.011874453,0.000070186914,0.0010355491,0.000033697306,0.00009416044,0.00090818765,0.016294105,0.015430977,0.097095564,0.85448974],"study_design_scores_gemma":[0.0018723585,0.0005037973,0.18429676,0.000048531885,0.005976167,0.00007377211,0.000054319993,0.7229784,0.007883253,0.013216169,0.06272858,0.0003678643],"about_ca_topic_score_codex":0.000007462496,"about_ca_topic_score_gemma":0.0000022288925,"teacher_disagreement_score":0.89649785,"about_ca_system_score_codex":0.00006600474,"about_ca_system_score_gemma":0.000040245213,"threshold_uncertainty_score":0.28676572},"labels":[],"label_agreement":null},{"id":"W2112055941","doi":"10.1016/s0197-4580(03)00121-0","title":"Linear width of the medial temporal lobe can discriminate Alzheimer’s disease from normal aging: the Sunnybrook Dementia Study","year":2003,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Women's College Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"Ontario Mental Health Foundation","keywords":"Temporal lobe; Alzheimer's disease; Dementia; Parahippocampal gyrus; Audiology; Diagnostic accuracy; Psychology; Logistic regression; Hippocampus; Hippocampal sclerosis; Healthy aging; Medicine; Neuroscience; Disease; Nuclear medicine; Internal medicine; Gerontology; Epilepsy","score_opus":0.06874226434264971,"score_gpt":0.3363374797879582,"score_spread":0.2675952154453085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112055941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99403113,0.00024094347,0.0002794479,0.0041917968,0.00018152944,0.00076334283,0.000048871334,0.00005775024,0.00020517294],"genre_scores_gemma":[0.9978453,0.000023768996,0.00118843,0.000763532,0.000063546846,0.000034955225,0.000022705692,0.000023753342,0.00003399973],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99878967,0.0001963703,0.00034571227,0.0003105368,0.00013302431,0.00022469001],"domain_scores_gemma":[0.99882364,0.00013118015,0.00023125805,0.0006750135,0.000063360516,0.00007552046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015591676,0.00016375148,0.00025921577,0.000043948527,0.00015036346,0.000004102656,0.00030577052,0.000029619361,0.000024773943],"category_scores_gemma":[0.00006775023,0.00009844091,0.000113914066,0.00016397757,0.0004108359,0.000033783257,0.00015142722,0.0002923089,0.0000010608682],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055926954,0.00041110866,0.9871264,0.000015676262,0.00011303423,0.000013407747,0.00051547465,0.00006152366,0.010370306,0.00046276714,0.00041768083,0.00043667285],"study_design_scores_gemma":[0.0017931085,0.00041083028,0.8847303,0.00010791033,0.0018324122,0.000022439088,0.00035818008,0.00016625744,0.105062,0.0018576842,0.0033975374,0.00026135147],"about_ca_topic_score_codex":0.00014869419,"about_ca_topic_score_gemma":0.000039099832,"teacher_disagreement_score":0.10239613,"about_ca_system_score_codex":0.0000084369085,"about_ca_system_score_gemma":0.00008327164,"threshold_uncertainty_score":0.4014304},"labels":[],"label_agreement":null},{"id":"W2112080959","doi":"10.1016/j.jbiomech.2011.07.017","title":"Computational methods for quantifying in vivo muscle fascicle curvature from ultrasound images","year":2011,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fascicle; Curvature; In vivo; Ultrasound; Computer science; Biomedical engineering; Anatomy; Medicine; Biology; Radiology; Mathematics; Geometry","score_opus":0.1880739847070206,"score_gpt":0.44513381723734263,"score_spread":0.25705983253032205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112080959","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03267195,0.00032351178,0.9658891,0.0006942707,0.00011541803,0.00019217357,0.000042155523,0.000026503363,0.000044926735],"genre_scores_gemma":[0.29433486,0.00006968556,0.70505637,0.00043997276,0.000061305,0.0000053821814,0.0000049650616,0.000014726278,0.000012749116],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992768,0.000028449911,0.0003400347,0.0001250184,0.00010804819,0.00012161424],"domain_scores_gemma":[0.9991532,0.0002262774,0.0002324081,0.00012462883,0.00019562809,0.00006788994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003462124,0.00008465934,0.00021611186,0.00016253936,0.00004068345,0.000011922,0.000110447094,0.00005829102,0.0000399779],"category_scores_gemma":[0.00013646159,0.0000725229,0.00010758141,0.00022900941,0.000021382282,0.00012543888,0.000019145516,0.0002187752,7.4362106e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010342774,0.0002246452,0.00023010372,0.000022954628,0.000029039385,0.000013480515,0.00023607083,0.000007014674,0.94495267,0.0015066772,0.0013172376,0.051356684],"study_design_scores_gemma":[0.0017994662,0.00047585886,0.0025009213,0.00020431908,0.00013442637,0.00024598622,0.0002311612,0.017378915,0.70090026,0.2559214,0.019999502,0.00020777741],"about_ca_topic_score_codex":0.000011247418,"about_ca_topic_score_gemma":9.144438e-7,"teacher_disagreement_score":0.26166293,"about_ca_system_score_codex":0.000039987186,"about_ca_system_score_gemma":0.000048851638,"threshold_uncertainty_score":0.2957398},"labels":[],"label_agreement":null},{"id":"W2112277156","doi":"10.1371/journal.pone.0019698","title":"Negative Associations between Corpus Callosum Midsagittal Area and IQ in a Representative Sample of Healthy Children and Adolescents","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Douglas Mental Health University Institute; McGill University","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; University of California, Los Angeles; U.S. Department of Health and Human Services; Washington University in St. Louis; National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; University of Texas Health Science Center at Houston; McGill University","keywords":"Corpus callosum; Correlation; Intelligence quotient; Wechsler Adult Intelligence Scale; Psychology; Cohort; Population; Sample size determination; Developmental psychology; Audiology; Medicine; Cognition; Clinical psychology; Internal medicine; Psychiatry; Neuroscience","score_opus":0.1681180949783102,"score_gpt":0.34374196256376877,"score_spread":0.17562386758545856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112277156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99755794,0.00005222614,0.0007137296,0.0005017189,0.0000018288982,0.0006694429,0.00032508787,0.000041910323,0.00013611706],"genre_scores_gemma":[0.977084,0.00015377523,0.022495875,0.00013359112,0.000016584172,0.000033447934,0.0000565427,0.000011872733,0.000014344455],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993164,0.000028356375,0.00020315118,0.00021094276,0.00011984161,0.00012132614],"domain_scores_gemma":[0.999465,0.00011497653,0.00012615576,0.00014651439,0.000066640874,0.00008072142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060021935,0.000077616976,0.00026887527,0.00007432166,0.000038544415,0.0000028512873,0.000037170117,0.000036404857,0.0000046827736],"category_scores_gemma":[0.00023867306,0.000077565666,0.000015869246,0.00014291241,0.00011010339,0.000053666252,0.000053423486,0.0001574882,4.867138e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000450101,0.00060581404,0.99707407,0.000027170141,0.00004615297,0.0000010084929,0.0006749915,2.0167754e-8,0.0010670259,0.000116187744,0.000026882453,0.00031569012],"study_design_scores_gemma":[0.00078027666,0.00019444828,0.9832248,0.00020189025,0.00008444647,0.0000015810554,0.00003581203,0.000020143552,0.011866734,0.0035287817,9.92419e-7,0.000060065293],"about_ca_topic_score_codex":0.00086723675,"about_ca_topic_score_gemma":0.000037470465,"teacher_disagreement_score":0.021782147,"about_ca_system_score_codex":0.000029684137,"about_ca_system_score_gemma":0.000019915615,"threshold_uncertainty_score":0.3163036},"labels":[],"label_agreement":null},{"id":"W2112492995","doi":"10.1093/brain/awv136","title":"Longitudinal changes in free-water within the substantia nigra of Parkinson’s disease","year":2015,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":220,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Centre for Movement Disorders","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke","keywords":"Substantia nigra; Parkinson's disease; Central nervous system disease; Internal medicine; Medicine; Psychology; Disease","score_opus":0.11004181301854678,"score_gpt":0.3445685490962396,"score_spread":0.2345267360776928,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112492995","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.877062,0.0005645122,0.0018530651,0.119369306,0.000053300533,0.00047461217,0.000025010851,0.000092294984,0.000505901],"genre_scores_gemma":[0.9962003,0.000017931205,0.0019889122,0.001015143,0.00005186079,0.000056810473,0.0000108162085,0.00001214446,0.00064608484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949723,0.00002346212,0.00010982985,0.00013269926,0.000121842015,0.00011492709],"domain_scores_gemma":[0.9994255,0.000029204186,0.000033728844,0.0003932085,0.000035091278,0.00008328648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021314612,0.00006273307,0.00009977268,0.000050734823,0.000017157627,0.000004426929,0.00011073355,0.000017669783,0.000012189082],"category_scores_gemma":[0.000115573675,0.000037333768,0.00002337786,0.00012960685,0.00008709281,0.000027872913,0.000049050523,0.00009599441,0.000004635902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008950567,0.0008345088,0.743738,0.00021960803,0.000038624705,0.00040113626,0.0037636622,0.00008582246,0.03423718,0.026270473,0.1826518,0.00686411],"study_design_scores_gemma":[0.002824585,0.00031212353,0.48129144,0.00032077424,0.000090867376,0.000092807764,0.00043195984,0.0011038014,0.06672439,0.06439374,0.38207805,0.00033546754],"about_ca_topic_score_codex":0.00005684541,"about_ca_topic_score_gemma":0.00015128878,"teacher_disagreement_score":0.26244658,"about_ca_system_score_codex":0.000016279399,"about_ca_system_score_gemma":0.000028543032,"threshold_uncertainty_score":0.15224268},"labels":[],"label_agreement":null},{"id":"W2112875098","doi":"10.1002/mrm.20578","title":"Magnetic resonance imaging and mathematical modeling of progressive formalin fixation of the human brain","year":2005,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":110,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; University of Alberta Hospital; Alberta Hospital Edmonton","funders":"","keywords":"Fixation (population genetics); Magnetic resonance imaging; White matter; Nuclear magnetic resonance; Effective diffusion coefficient; T2 relaxation; Nuclear medicine; Human brain; Spin–lattice relaxation; Spin–spin relaxation; Diffusion imaging; Chemistry; Medicine; Physics; Radiology","score_opus":0.03702979127081108,"score_gpt":0.34881635186098475,"score_spread":0.3117865605901737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112875098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85307586,0.08806667,0.0046241414,0.047261495,0.000029102206,0.0022694194,0.000011531237,0.000090216345,0.0045715948],"genre_scores_gemma":[0.98170227,0.00030568952,0.016611641,0.0005878299,0.00008337749,0.00010059999,0.0000032488517,0.00002271882,0.0005826236],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998488,0.000041119034,0.00065703806,0.0002628393,0.00033865013,0.00021233073],"domain_scores_gemma":[0.999081,0.000116640134,0.00017363984,0.00046716072,0.00010920309,0.000052332576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034782922,0.00014749552,0.0003712164,0.00010856636,0.000053623156,0.0000032955086,0.00016787296,0.00004424811,0.000121320714],"category_scores_gemma":[0.0003339813,0.00010192672,0.000038905575,0.00033879137,0.00049714796,0.000063808475,0.00008373167,0.00023281544,0.0000011280192],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018862622,0.00046563684,0.04877376,0.0007372669,0.0000027744268,0.000023191611,0.0020789944,0.0001751334,0.04190486,0.023372661,0.0016477598,0.8806293],"study_design_scores_gemma":[0.007533684,0.0017120661,0.27457073,0.009595326,0.00015691898,0.0004275826,0.0005661247,0.61452407,0.0069893817,0.048997834,0.034441434,0.0004848307],"about_ca_topic_score_codex":0.000026183143,"about_ca_topic_score_gemma":0.000005560395,"teacher_disagreement_score":0.8801445,"about_ca_system_score_codex":0.000029597702,"about_ca_system_score_gemma":0.000027255986,"threshold_uncertainty_score":0.41564512},"labels":[],"label_agreement":null},{"id":"W2113986781","doi":"10.1109/tmi.2007.907699","title":"Impact of an Improved Combination of Signals From Array Coils in Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier de l’Université de Montréal","funders":"McGill University","keywords":"Diffusion MRI; Noise (video); Tensor (intrinsic definition); Computation; Noise reduction; SIGNAL (programming language); Diffusion; Signal-to-noise ratio (imaging); Anisotropic diffusion; Reduction (mathematics); Algorithm; Mathematics; Anisotropy; Computer science; Physics; Optics; Artificial intelligence; Image (mathematics); Magnetic resonance imaging; Geometry","score_opus":0.02657158651949947,"score_gpt":0.3661632366776523,"score_spread":0.33959165015815285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113986781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.457179,0.000024882496,0.5417814,0.0005333548,0.000044689783,0.00024305414,0.000021871649,0.00007166158,0.00010005481],"genre_scores_gemma":[0.9905368,0.000047493624,0.009042606,0.0002519177,0.000032712593,0.000019784851,0.000020146868,0.000032455282,0.000016058044],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99825853,0.00004719816,0.0006343071,0.00032773888,0.00045678113,0.00027547125],"domain_scores_gemma":[0.99878377,0.00025815304,0.0001835631,0.00037737726,0.00015004544,0.0002471043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045175434,0.00017560653,0.00037441246,0.00038153614,0.00005775193,0.0000070115243,0.00014970549,0.000066862674,0.00017557984],"category_scores_gemma":[0.000066643246,0.00015377223,0.00016654572,0.000420576,0.00021643615,0.00018558688,0.0000021491876,0.00048223604,0.0000017687073],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024386046,0.001632196,0.013663533,0.000028485701,0.000019314955,0.00003178087,0.00019514018,0.00009102526,0.7925092,0.000009649497,0.000018700712,0.19155714],"study_design_scores_gemma":[0.0051347883,0.00046082892,0.16427407,0.0009129633,0.00014385302,0.00009610904,0.0003456574,0.12325,0.7035152,0.0014617906,0.000053521322,0.00035124764],"about_ca_topic_score_codex":0.0007598912,"about_ca_topic_score_gemma":0.00002427082,"teacher_disagreement_score":0.5333578,"about_ca_system_score_codex":0.00011722733,"about_ca_system_score_gemma":0.00010071462,"threshold_uncertainty_score":0.62706494},"labels":[],"label_agreement":null},{"id":"W2114187925","doi":"10.1002/mrm.22292","title":"Tensor kernels for simultaneous fiber model estimation and tractography","year":2010,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Diffusion MRI; Tractography; Orientation (vector space); Voxel; Tensor (intrinsic definition); Computer science; Fiber; Mathematics; Smoothness; Artificial intelligence; Biological system; Pattern recognition (psychology); Mathematical analysis; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.04190387894637874,"score_gpt":0.35813438768860023,"score_spread":0.31623050874222147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114187925","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8752245,0.0038537125,0.091356814,0.022445166,0.000103410595,0.0034235327,0.00003409748,0.00034042317,0.0032183959],"genre_scores_gemma":[0.77583224,0.00031704947,0.22095463,0.00094024173,0.00009243382,0.00027894555,0.000015451074,0.000028271284,0.0015407657],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907833,0.000005911215,0.00026689944,0.0003066728,0.0001449024,0.00019725633],"domain_scores_gemma":[0.9991892,0.00029118257,0.000052752006,0.00030048672,0.000075143646,0.000091238726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001484513,0.00013258209,0.00025047318,0.00012451036,0.00004558804,0.000005588263,0.00006994487,0.00007444768,0.000056879533],"category_scores_gemma":[0.00053387694,0.000106039115,0.00002827972,0.0001928639,0.0002395248,0.000037883077,0.000014849182,0.0002757446,0.0000021932478],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015088862,0.00011659393,0.0030014105,0.0001020492,0.0000016398121,0.000022435781,0.00018914715,0.00034944905,0.022696823,0.0014388127,0.0017920048,0.9701387],"study_design_scores_gemma":[0.0022202136,0.00058955804,0.01802295,0.00020059425,0.00004980725,0.00012355958,0.000020669746,0.85901827,0.0005172903,0.017062882,0.10200981,0.00016439844],"about_ca_topic_score_codex":0.000015465353,"about_ca_topic_score_gemma":0.0000072580033,"teacher_disagreement_score":0.96997434,"about_ca_system_score_codex":0.000008496633,"about_ca_system_score_gemma":0.000018098692,"threshold_uncertainty_score":0.43241495},"labels":[],"label_agreement":null},{"id":"W2114448824","doi":"10.1016/j.neuroimage.2013.05.022","title":"Diffusion imaging quality control via entropy of principal direction distribution","year":2013,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; University of Washington","keywords":"Diffusion MRI; Computer science; Artificial intelligence; Voxel; Image quality; Entropy (arrow of time); Computer vision; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.03213628797906214,"score_gpt":0.33877909879691825,"score_spread":0.3066428108178561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114448824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73560417,0.000033755725,0.25926307,0.0028266832,0.00008741028,0.000928042,0.000043001834,0.00036119414,0.0008526763],"genre_scores_gemma":[0.9972819,0.000029613977,0.0018451721,0.00043352868,0.000066949404,0.00009050978,0.00006830667,0.000021131475,0.00016290158],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99890685,0.000060182152,0.00033858075,0.00029293683,0.00020568151,0.00019573847],"domain_scores_gemma":[0.9990733,0.00007954181,0.0001759532,0.0004142406,0.00016269115,0.00009426636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010045714,0.00012839747,0.00023200994,0.00004405825,0.00008143493,0.000014614022,0.00007563519,0.000029931301,0.00008100182],"category_scores_gemma":[0.00015396789,0.00011530917,0.00010010968,0.00015803867,0.00009777124,0.00015159335,0.000044831322,0.00018922372,0.000029557274],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045803397,0.00022188362,0.05265251,0.00003928575,0.00000427656,0.000004519403,0.000011030389,0.000002314473,0.9268553,0.0010832952,0.00085016014,0.018229617],"study_design_scores_gemma":[0.0012843198,0.0001044313,0.9255286,0.00003603205,0.000050198218,0.000060148832,0.000008057414,0.008529896,0.053103223,0.0016797166,0.009473134,0.00014223851],"about_ca_topic_score_codex":0.00012736917,"about_ca_topic_score_gemma":5.2671174e-7,"teacher_disagreement_score":0.87375206,"about_ca_system_score_codex":0.000046336263,"about_ca_system_score_gemma":0.000014330469,"threshold_uncertainty_score":0.47021714},"labels":[],"label_agreement":null},{"id":"W2115624928","doi":"10.1371/journal.pone.0139897","title":"Myelination Is Associated with Processing Speed in Early Childhood: Preliminary Insights","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Corpus callosum; White matter; Occipital lobe; Magnetic resonance imaging; Myelin; Neuroimaging; Cerebellum; Working memory; Brain size; Neuroscience; Medicine; Audiology; Psychology; Central nervous system; Cognition; Radiology","score_opus":0.11173615169629753,"score_gpt":0.3044314697803395,"score_spread":0.192695318084042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115624928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952829,0.00010361524,0.0004372678,0.001701537,0.0000022985869,0.00051894167,0.0000023031494,0.00022350853,0.0017276448],"genre_scores_gemma":[0.99150395,0.000012760073,0.0075518033,0.00042304455,0.000036837133,0.000038936745,0.000029114031,0.00002460024,0.00037895172],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992714,0.000012870124,0.00013765812,0.00019220677,0.00026514693,0.000120726996],"domain_scores_gemma":[0.999489,0.000016487207,0.00007925401,0.00016101763,0.00017828184,0.000075925665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005549636,0.000085259664,0.0001651401,0.000097526994,0.000033706237,0.000011803421,0.000051553146,0.000045307464,0.0000030569008],"category_scores_gemma":[0.00010847241,0.00007282893,0.000011517282,0.00034039162,0.00003016953,0.00013281476,0.000021100986,0.00017887431,0.000009217127],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022270065,0.073113255,0.6920206,0.00075501215,0.0006427987,0.000622852,0.061193228,0.00010251744,0.124565996,0.0015690575,0.0033184437,0.03986923],"study_design_scores_gemma":[0.0036238045,0.0018727563,0.9102279,0.0025645867,0.0002614761,0.0000179792,0.00016502604,0.006388269,0.069062,0.0053322283,0.00014356535,0.000340402],"about_ca_topic_score_codex":0.000008331392,"about_ca_topic_score_gemma":0.00000217436,"teacher_disagreement_score":0.2182073,"about_ca_system_score_codex":0.00007802381,"about_ca_system_score_gemma":0.00007442731,"threshold_uncertainty_score":0.29698777},"labels":[],"label_agreement":null},{"id":"W2116129675","doi":"10.3389/fneur.2014.00216","title":"Beyond Crossing Fibers: Bootstrap Probabilistic Tractography Using Complex Subvoxel Fiber Geometries","year":2014,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital; McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Diffusion MRI; Fiber; Computer science; Probabilistic logic; Artificial intelligence; Voxel; Fiber tract; Human Connectome Project; Pipeline (software); Pattern recognition (psychology); Magnetic resonance imaging; Neuroscience; Psychology; Functional connectivity; Materials science","score_opus":0.0797998667514669,"score_gpt":0.3461417527134482,"score_spread":0.26634188596198133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116129675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8423895,0.0001854594,0.15007465,0.0039018574,0.00027584593,0.0007110692,0.00001367358,0.000284963,0.002162934],"genre_scores_gemma":[0.8924568,0.000015673115,0.10484603,0.0024161418,0.00009256649,0.000036321024,0.000023337765,0.000044871238,0.000068253285],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986097,0.00006680036,0.00032514596,0.00047616466,0.00012561289,0.00039654176],"domain_scores_gemma":[0.9991928,0.00010931607,0.00011752488,0.00043225277,0.000049896218,0.000098217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015407005,0.00018824478,0.00039550528,0.0004639192,0.00018454136,0.0000382836,0.00015064665,0.00012217794,0.000020418867],"category_scores_gemma":[0.00014117124,0.00019481171,0.000098930555,0.00062521826,0.00069697463,0.00009760306,0.000050283765,0.0004268541,0.0000025434836],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017544528,0.001833802,0.78903425,0.000630493,0.00013715932,0.00031020082,0.00068797707,0.004787715,0.043098986,0.009347209,0.04970542,0.09867235],"study_design_scores_gemma":[0.0047062887,0.0014175784,0.44731644,0.00009050171,0.00020466108,0.00087185286,0.00006596578,0.05579166,0.0021742238,0.12505047,0.36136878,0.0009415739],"about_ca_topic_score_codex":0.00003139391,"about_ca_topic_score_gemma":0.0000033455997,"teacher_disagreement_score":0.34171778,"about_ca_system_score_codex":0.000022508655,"about_ca_system_score_gemma":0.00005780583,"threshold_uncertainty_score":0.7944191},"labels":[],"label_agreement":null},{"id":"W2116280131","doi":"10.1109/iembs.2007.4352289","title":"Methodology for MR diffusion tensor imaging of the cat spinal cord","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Spinal cord; Diffusion MRI; Tractography; Echo-planar imaging; Magnetic resonance imaging; Lumbar Spinal Cord; Orientation (vector space); Nuclear magnetic resonance; Biomedical engineering; Materials science; Medicine; Radiology; Physics; Mathematics; Geometry","score_opus":0.22922831001119828,"score_gpt":0.4391316978561263,"score_spread":0.20990338784492804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116280131","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6948091,0.00003469637,0.29695055,0.0053467816,0.000065574815,0.0008357475,0.0000043104146,0.00011662836,0.0018365971],"genre_scores_gemma":[0.8778245,0.000017516439,0.12119165,0.00054792856,0.000057217047,0.000047189285,0.0000014558703,0.00001340246,0.0002991762],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992604,0.0000030038782,0.0002125579,0.00021973443,0.000102346356,0.00020192815],"domain_scores_gemma":[0.99916875,0.00006950675,0.00015275205,0.00013642448,0.0004181646,0.00005441577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000302478,0.000096468626,0.00018562387,0.000057076413,0.00009098515,0.000007981039,0.00016636135,0.00003787207,0.000009404816],"category_scores_gemma":[0.00036132568,0.00006658094,0.00007117921,0.00015601574,0.00017292892,0.000045837518,0.00008006808,0.00011508553,9.047803e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004866425,0.00006537825,0.0994265,0.00015704853,0.000005482711,7.473904e-7,0.00017994626,2.0601913e-8,0.79830694,0.03915054,0.00077721,0.06144354],"study_design_scores_gemma":[0.0013007813,0.00084050064,0.2991489,0.0005103897,0.0001830223,0.00029191762,0.0011133004,0.001753247,0.61601335,0.047317684,0.03123258,0.0002943571],"about_ca_topic_score_codex":0.000008281786,"about_ca_topic_score_gemma":6.45934e-7,"teacher_disagreement_score":0.1997224,"about_ca_system_score_codex":0.000025050558,"about_ca_system_score_gemma":0.000041508636,"threshold_uncertainty_score":0.2715092},"labels":[],"label_agreement":null},{"id":"W2116458236","doi":"10.1503/jpn.110028","title":"Effects of early-life adversity on white matter diffusivity changes in patients at risk for major depression","year":2011,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Science Foundation Ireland","keywords":"Fractional anisotropy; Splenium; Corpus callosum; Fornix; Superior longitudinal fasciculus; Late life depression; White matter; Psychology; Tractography; Inferior longitudinal fasciculus; Uncinate fasciculus; Major depressive disorder; Depression (economics); Psychiatry; Clinical psychology; Medicine; Neuroscience; Magnetic resonance imaging; Cognition; Hippocampus","score_opus":0.024895342494898987,"score_gpt":0.2900436814675633,"score_spread":0.2651483389726643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116458236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99784863,0.000027843613,0.0011775692,0.0004493865,0.00019545294,0.0002506998,0.0000067035367,0.000005055335,0.000038670907],"genre_scores_gemma":[0.9958089,0.00007924989,0.003240397,0.0008067051,0.000025924757,0.000003906268,1.3117445e-7,0.000005360162,0.000029442988],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945086,0.00002395202,0.00015554707,0.00014201357,0.00012860382,0.000099050936],"domain_scores_gemma":[0.9994278,0.000040087605,0.0002982787,0.00010774533,0.000037126698,0.00008895834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009327964,0.00006690112,0.0001437479,0.00009505513,0.00007382139,0.000002645924,0.00008690346,0.000024777628,0.0000030226267],"category_scores_gemma":[0.000066820045,0.00004972075,0.000043011394,0.000100025216,0.00006423298,0.00007537334,0.000042195545,0.0001325689,3.1386645e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005589432,0.00040425718,0.99348736,0.00006769242,9.1912233e-7,0.0000013302526,0.000051067393,6.579433e-7,0.0049520144,0.000014616698,0.00022043072,0.00024069997],"study_design_scores_gemma":[0.0011890604,0.0012111426,0.9881748,0.00012574122,0.000028841225,0.000007694739,0.0000028091267,0.000015434685,0.008820513,0.0003153418,0.00006723194,0.000041415817],"about_ca_topic_score_codex":0.000002675796,"about_ca_topic_score_gemma":0.0000025134411,"teacher_disagreement_score":0.0053125974,"about_ca_system_score_codex":0.000008496963,"about_ca_system_score_gemma":0.000013708938,"threshold_uncertainty_score":0.20275535},"labels":[],"label_agreement":null},{"id":"W2116470411","doi":"10.2522/ptj.20060164","title":"Answering the Call: The Influence of Neuroimaging and Electrophysiological Evidence on Rehabilitation","year":2007,"lang":"en","type":"review","venue":"Physical Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Neuroimaging; Magnetoencephalography; Neuroscience; Functional neuroimaging; Electrophysiology; Psychology; Rehabilitation; Diffusion MRI; Functional magnetic resonance imaging; Neuroplasticity; Modalities; Sensory system; Magnetic resonance imaging; Electroencephalography; Physical medicine and rehabilitation; Medicine; Radiology","score_opus":0.18520377911512395,"score_gpt":0.46857158022069806,"score_spread":0.28336780110557414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116470411","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05620783,0.9392863,0.00047771801,0.0017522657,0.000015037626,0.0020816678,0.000004044604,0.0001227491,0.0000523745],"genre_scores_gemma":[0.045125194,0.9536565,0.00031170313,0.0005710082,0.00012912603,0.00016767386,0.0000022837396,0.000028465058,0.000008069512],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99887097,0.00013137075,0.000269681,0.0003460924,0.00020530102,0.00017657827],"domain_scores_gemma":[0.996275,0.0028295382,0.0001859119,0.00060999405,0.00006146617,0.00003810016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019501144,0.00022724316,0.00061772333,0.00003867298,0.00010982056,0.0000125628985,0.00024246468,0.000044084278,7.69129e-7],"category_scores_gemma":[0.00022403976,0.000099224,0.00023208368,0.000342618,0.00041018537,0.00004535019,0.000050659688,0.00063332747,0.000002625599],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005246128,0.00010646614,0.000010427258,0.0006317065,0.000019452153,0.0000016766201,0.000059877235,0.000011140606,0.0031269332,0.002639229,0.000033153094,0.9933075],"study_design_scores_gemma":[0.00023771379,0.0028208585,0.008193456,0.010022374,0.00027075264,0.000041946827,0.000009692674,0.00016392469,0.00034495193,0.008605908,0.9689157,0.0003727226],"about_ca_topic_score_codex":0.000004977611,"about_ca_topic_score_gemma":3.6717495e-8,"teacher_disagreement_score":0.99293476,"about_ca_system_score_codex":0.000027061737,"about_ca_system_score_gemma":0.000033911252,"threshold_uncertainty_score":0.40462372},"labels":[],"label_agreement":null},{"id":"W2116949112","doi":"10.1002/hbm.22522","title":"Diagnostic classification of arterial spin labeling and structural MRI in presenile early stage dementia","year":2014,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Biogen Idec; Genentech; Takeda Pharmaceutical Company; IXICO; Servier; Eisai; Medpace; Eli Lilly and Company; Synarc; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; BioClinica; National Institute on Aging; Abbott Laboratories; Bayer HealthCare; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche","keywords":"Dementia; Atrophy; Frontotemporal dementia; Voxel; Neuroimaging; Region of interest; Medicine; Vascular dementia; Population; Cerebral blood flow; Magnetic resonance imaging; Pathology; Radiology; Psychology; Nuclear medicine; Internal medicine; Disease; Psychiatry","score_opus":0.06534631252162783,"score_gpt":0.34961993735697416,"score_spread":0.28427362483534635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116949112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9705777,0.000024395651,0.02768082,0.0009846829,0.000017107903,0.0003551997,0.0000036596869,0.00005937566,0.0002970561],"genre_scores_gemma":[0.9905725,0.000007094729,0.009113255,0.000108801076,0.00007189002,0.000034803652,0.000019653706,0.000012723883,0.000059268124],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993251,0.000032202373,0.00023528672,0.0001980203,0.00008482258,0.00012456269],"domain_scores_gemma":[0.9994895,0.00013945204,0.00009966371,0.00020762946,0.000027305663,0.000036489837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014606789,0.00007640567,0.00014165477,0.0000971311,0.00007355217,0.000015285328,0.000055849934,0.000030726213,0.000019942543],"category_scores_gemma":[0.0001612407,0.00007853976,0.00001840942,0.000092778864,0.000064007654,0.000063974694,0.00003889178,0.000105662686,0.0000010196604],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000931845,0.000025217289,0.1316339,0.00012627369,0.000008513184,0.0000017010954,0.00038384716,0.000025461746,0.8496652,0.016748434,0.00023948196,0.0011326105],"study_design_scores_gemma":[0.00060987275,0.00005768467,0.9871141,0.00013850565,0.0000120765235,0.0000025032882,0.000048524795,0.0041036685,0.00088958244,0.004228516,0.0027151846,0.000079786136],"about_ca_topic_score_codex":0.00003547922,"about_ca_topic_score_gemma":0.000012467018,"teacher_disagreement_score":0.8554802,"about_ca_system_score_codex":0.000013251895,"about_ca_system_score_gemma":0.000006958874,"threshold_uncertainty_score":0.32027584},"labels":[],"label_agreement":null},{"id":"W2116953988","doi":"10.1109/isspit.2006.270854","title":"Bilateral Filtering of Diffusion Tensor MR Images","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Smoothing; Mathematics; Euclidean distance; Diffusion MRI; Tensor (intrinsic definition); Scalar (mathematics); Divergence (linguistics); Interpolation (computer graphics); Artificial intelligence; Mathematical analysis; Pattern recognition (psychology); Algorithm; Computer science; Image (mathematics); Geometry; Statistics","score_opus":0.03816979315600405,"score_gpt":0.3283772684908604,"score_spread":0.29020747533485636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2116953988","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9264476,0.00002375958,0.0514172,0.0017737937,0.000012939642,0.00020608139,0.0000063218226,0.00027349294,0.019838862],"genre_scores_gemma":[0.9277001,0.00001191829,0.06693685,0.00011637289,0.00003512436,0.000009418743,0.0000073144056,0.000008679697,0.005174216],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99966896,0.000002173066,0.000109949564,0.00009450134,0.00005345723,0.00007097907],"domain_scores_gemma":[0.9997586,0.000010256746,0.000026937776,0.00015969672,0.00002685722,0.000017626515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000014091231,0.000046091733,0.00008496029,0.000034383746,0.000019275649,0.000002642411,0.00002933692,0.000013773836,0.000075755204],"category_scores_gemma":[0.000004799125,0.0000339158,0.00003121164,0.000059840422,0.000028551569,0.000024518638,0.000026531074,0.00003927836,0.0000046001674],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008739672,0.00007091309,0.020892216,0.000017932844,0.0000010636417,0.000004695691,0.00000311258,0.0000039054135,0.9729875,0.001168826,0.0031471457,0.0016939566],"study_design_scores_gemma":[0.00036637502,0.000078785204,0.18564093,0.000047867954,0.00001593324,0.000054397136,0.0000060426455,0.0006014555,0.7934164,0.002601018,0.017090498,0.00008033891],"about_ca_topic_score_codex":0.00005492339,"about_ca_topic_score_gemma":4.8565664e-7,"teacher_disagreement_score":0.17957114,"about_ca_system_score_codex":0.000006004395,"about_ca_system_score_gemma":0.0000033962958,"threshold_uncertainty_score":0.13830462},"labels":[],"label_agreement":null},{"id":"W2117555148","doi":"10.1002/mrm.23292","title":"Somatotopic arrangement of thermal sensory regions in the healthy human spinal cord determined by means of spinal cord functional MRI","year":2011,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Brainstem; Spinal cord; Sensory system; Neuroscience; Anatomy; Dermatome; Stimulus (psychology); Sensory stimulation therapy; Stimulation; Neurophysiology; Medicine; Psychology","score_opus":0.14372576778989582,"score_gpt":0.37612321436519336,"score_spread":0.23239744657529754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2117555148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98358583,0.0036336412,0.0019872775,0.0063528917,0.00006334902,0.0011610864,0.000009541385,0.00003606956,0.0031702868],"genre_scores_gemma":[0.9943411,0.0004615846,0.0034863225,0.0011578663,0.00008495873,0.00018284075,0.000011626554,0.000017468643,0.00025625122],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998321,0.00008312932,0.00066589337,0.00029258514,0.00038442694,0.0002529524],"domain_scores_gemma":[0.9990653,0.000058216006,0.00020770615,0.0005347374,0.000074416166,0.00005966128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035794382,0.00016444725,0.00040773756,0.00015954152,0.00004779947,0.0000013582246,0.0002178939,0.000053739783,0.00016236505],"category_scores_gemma":[0.000055109027,0.000117773525,0.000050828297,0.00034703457,0.0005104905,0.000029458703,0.000032847558,0.00029567356,0.0000013937741],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.01571,0.003700264,0.3232038,0.0013451796,0.000026118038,0.0003965568,0.002518185,0.0000049669416,0.21398981,0.021667365,0.019497009,0.39794075],"study_design_scores_gemma":[0.0030652515,0.012848554,0.96338195,0.0009318126,0.000049574126,0.000101455844,0.00048715388,0.0001277619,0.0016409332,0.0022265294,0.0149997845,0.00013926833],"about_ca_topic_score_codex":0.0003178981,"about_ca_topic_score_gemma":0.000043919666,"teacher_disagreement_score":0.64017814,"about_ca_system_score_codex":0.00003866613,"about_ca_system_score_gemma":0.0000423008,"threshold_uncertainty_score":0.48026648},"labels":[],"label_agreement":null},{"id":"W2118432137","doi":"10.1002/hbm.20828","title":"The rate of visuomotor adaptation correlates with cerebellar white‐matter microstructure","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":101,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; International Brain Research Organization; Wellcome Trust","keywords":"Cerebellum; Neuroscience; Psychology; White matter; Premotor cortex; Fractional anisotropy; Anatomy; Biology; Magnetic resonance imaging; Dorsum; Medicine","score_opus":0.03510674973222959,"score_gpt":0.3013756091440133,"score_spread":0.2662688594117837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118432137","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8918729,0.00014517459,0.07480351,0.028591512,0.000029070223,0.0010229585,0.000006460883,0.00022558607,0.0033028265],"genre_scores_gemma":[0.9891565,0.000008013792,0.00657303,0.002653982,0.000047186226,0.000012177917,0.00001826482,0.000015754898,0.0015151034],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99942917,0.000021846277,0.00017566883,0.00016356328,0.00007320696,0.00013656435],"domain_scores_gemma":[0.9994268,0.00005979606,0.00012686556,0.00028297096,0.00007125416,0.000032328404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009788935,0.000098584955,0.00012489705,0.000043852702,0.00025612794,0.000019578083,0.0000828336,0.00003257225,0.000029182862],"category_scores_gemma":[0.000016966409,0.000065326865,0.000035860405,0.00013438758,0.000085374035,0.000041268308,0.000012834112,0.0001540812,0.0000056282474],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006323207,0.00004496366,0.01810355,0.000050535535,0.000022243776,0.000007301527,0.0011135406,0.0001117752,0.9546168,0.0070123794,0.016796092,0.0020576087],"study_design_scores_gemma":[0.00081061997,0.00029597737,0.9398998,0.0003068298,0.000038939852,0.00008284844,0.00039948628,0.0008120253,0.0043972437,0.016444638,0.0363099,0.00020169983],"about_ca_topic_score_codex":0.000002450734,"about_ca_topic_score_gemma":0.0000015025146,"teacher_disagreement_score":0.9502195,"about_ca_system_score_codex":0.00001642466,"about_ca_system_score_gemma":0.000013619391,"threshold_uncertainty_score":0.26639524},"labels":[],"label_agreement":null},{"id":"W2119543919","doi":"10.1109/tmi.2003.816961","title":"Retrospective evaluation of intersubject brain registration","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":202,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Cancer Institute","keywords":"Image registration; Artificial intelligence; Computer science; Normalization (sociology); Spatial normalization; Matching (statistics); Computer vision; Focus (optics); Transformation (genetics); Pattern recognition (psychology); Mathematics; Image (mathematics); Statistics; Voxel","score_opus":0.0647567008747169,"score_gpt":0.3928816999721583,"score_spread":0.3281249990974414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119543919","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019506322,0.00003795669,0.9670876,0.0049987333,0.00014531244,0.0004363812,0.0000051454867,0.00013902446,0.007643482],"genre_scores_gemma":[0.9940879,0.00003048227,0.004754113,0.0008448368,0.000024375866,0.000083042396,0.0000035021055,0.000019206122,0.00015254045],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983312,0.000110596884,0.00029035757,0.00026679318,0.00085852196,0.00014256522],"domain_scores_gemma":[0.99914324,0.00008607763,0.000091388,0.0003105868,0.00024710383,0.00012160325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000892618,0.00010855882,0.00017431223,0.00014275186,0.00008101729,0.000007381747,0.00006522892,0.000048768787,0.00042927792],"category_scores_gemma":[0.00035751043,0.000102795406,0.00009695371,0.0003078111,0.00015433616,0.00009288863,5.329684e-7,0.00036252686,0.000008094052],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034365756,0.002932224,0.004274411,0.00019911792,0.00021553112,0.00006826554,0.00096124754,0.0011670572,0.13276364,0.013255867,0.008821611,0.83499736],"study_design_scores_gemma":[0.008890318,0.0007159587,0.0075585535,0.0013848244,0.0010366143,0.0012083614,0.00081323896,0.17132063,0.7750311,0.02196799,0.0092841,0.00078832905],"about_ca_topic_score_codex":0.00001285852,"about_ca_topic_score_gemma":0.0000050848403,"teacher_disagreement_score":0.9745816,"about_ca_system_score_codex":0.00016047685,"about_ca_system_score_gemma":0.00020025729,"threshold_uncertainty_score":0.47002923},"labels":[],"label_agreement":null},{"id":"W2120710153","doi":"10.1073/pnas.0407259102","title":"Choice reaction time performance correlates with diffusion anisotropy in white matter pathways supporting visuospatial attention","year":2005,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":365,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Cancer Institute; National Institute on Aging; GlaxoSmithKline","keywords":"Fractional anisotropy; Psychology; White matter; Corpus callosum; Superior parietal lobule; Neuroscience; Diffusion MRI; Precuneus; Working memory; Lateralization of brain function; Parietal lobe; Functional magnetic resonance imaging; Audiology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.03621497310292623,"score_gpt":0.3217695213953885,"score_spread":0.2855545482924623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120710153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931123,0.000005757423,0.000012569215,0.0048423493,0.0000031329962,0.00023311806,0.000003111743,0.000023558328,0.0017640626],"genre_scores_gemma":[0.9928906,0.000015393562,0.0065747206,0.00026043985,0.000053076994,0.000016258868,7.424746e-7,0.000005189666,0.0001835676],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989417,0.0000022128436,0.00026031258,0.00018663736,0.0004952331,0.00011388373],"domain_scores_gemma":[0.9994392,0.000027891607,0.0003722557,0.000009305531,0.00013076876,0.000020613914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032690584,0.00007078362,0.00010896361,0.00012241043,0.00011366817,0.00000820571,0.00015985066,0.00004123735,0.000010895134],"category_scores_gemma":[0.00005565359,0.000045983223,0.000029560826,0.00044768816,0.00021737434,0.0004400426,0.00004776843,0.00016394744,0.000003262155],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019595898,0.000049738355,0.47075212,0.00002477865,0.0000012540547,3.3161853e-9,0.000033638935,0.000028265535,0.5279893,0.00048445992,0.00013050504,0.00048634064],"study_design_scores_gemma":[0.00023945513,0.00007928679,0.9232652,0.00020708401,0.000010412197,0.000024591838,0.000018915642,0.014450058,0.06062115,0.00089990685,0.00013025558,0.0000536461],"about_ca_topic_score_codex":0.0000024066467,"about_ca_topic_score_gemma":4.438888e-8,"teacher_disagreement_score":0.46736816,"about_ca_system_score_codex":0.00004630489,"about_ca_system_score_gemma":0.000014438563,"threshold_uncertainty_score":0.18751414},"labels":[],"label_agreement":null},{"id":"W2121502050","doi":"10.1002/hbm.20779","title":"Lateralization of the arcuate fasciculus from childhood to adulthood and its relation to cognitive abilities in children","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":292,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Arcuate fasciculus; Lateralization of brain function; Psychology; Fractional anisotropy; Tractography; White matter; Cognition; Uncinate fasciculus; Inferior longitudinal fasciculus; Fasciculus; Audiology; Diffusion MRI; Developmental psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.03397784302624989,"score_gpt":0.31338961164840223,"score_spread":0.27941176862215233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121502050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881288,0.00002795021,0.0043860613,0.006180303,0.0000053290387,0.0010113757,0.00001529535,0.000053676325,0.00019120451],"genre_scores_gemma":[0.995964,0.00000445024,0.001183649,0.002698643,0.0000331576,0.00002817459,0.00003336435,0.00000843611,0.00004611596],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993826,0.000031899013,0.00019061072,0.00020583415,0.000089326546,0.00009971757],"domain_scores_gemma":[0.99967515,0.000039028822,0.000056070934,0.00013999587,0.000047880836,0.00004187757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000787236,0.00007803104,0.00012220896,0.000099638564,0.00008535074,0.00000918043,0.00005350827,0.000027238013,0.00000557669],"category_scores_gemma":[0.00016910674,0.00006613458,0.000022534381,0.00023478914,0.00001550302,0.000054626016,0.000037664846,0.00009422637,0.0000018618305],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000680837,0.0004361253,0.43388098,0.0000544412,0.000042637337,0.0000024706244,0.03967119,0.00034722686,0.48686814,0.020589884,0.00063146866,0.017407363],"study_design_scores_gemma":[0.00036723382,0.00006555189,0.9875979,0.00048564796,0.0000087585795,0.0000033351555,0.00013545148,0.00009510426,0.0019898564,0.009138396,0.00004499677,0.000067786845],"about_ca_topic_score_codex":0.000021885982,"about_ca_topic_score_gemma":0.000004146529,"teacher_disagreement_score":0.5537169,"about_ca_system_score_codex":0.000022464332,"about_ca_system_score_gemma":0.000009431016,"threshold_uncertainty_score":0.269689},"labels":[],"label_agreement":null},{"id":"W2121696795","doi":"10.1007/s00429-015-1078-8","title":"Blindness alters the microstructure of the ventral but not the dorsal visual stream","year":2015,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Visual system; Neuroscience; Inferior longitudinal fasciculus; Psychology; Visual cortex; Dorsum; Fasciculus; Anatomy; Medicine; Magnetic resonance imaging","score_opus":0.03405517960995518,"score_gpt":0.3140185209566567,"score_spread":0.27996334134670153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121696795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852563,0.0001332467,0.0017186803,0.011989393,0.0003089204,0.0004433096,0.000038738704,0.00003985065,0.000071570335],"genre_scores_gemma":[0.9963021,0.000006870861,0.00019023173,0.003037878,0.00023243872,0.00000991995,0.000017101494,0.000012014916,0.00019142438],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99938715,0.000038696373,0.00013170562,0.00015818472,0.00016553095,0.00011872072],"domain_scores_gemma":[0.9994364,0.000060376024,0.00009610076,0.00030466774,0.00006381391,0.000038646616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008387795,0.00010624999,0.0001066147,0.000017616794,0.00016782834,0.00001830744,0.00010726043,0.000059580736,0.000008806466],"category_scores_gemma":[0.000059841714,0.00004527432,0.00005360944,0.00015562585,0.00023250171,0.00003838422,0.00005427297,0.0002580459,3.631894e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021351941,0.00014196635,0.030721614,0.00013663116,0.00020825927,0.0000068559366,0.0037512628,0.00033613073,0.7701343,0.012216259,0.056430116,0.12378136],"study_design_scores_gemma":[0.0024674586,0.0006471176,0.7378103,0.00007226944,0.00041216993,0.00068918976,0.0016263018,0.0011814653,0.09406965,0.022117367,0.13861999,0.00028672384],"about_ca_topic_score_codex":0.000029707318,"about_ca_topic_score_gemma":0.00000606865,"teacher_disagreement_score":0.7070887,"about_ca_system_score_codex":0.000015243983,"about_ca_system_score_gemma":0.000045556953,"threshold_uncertainty_score":0.18462332},"labels":[],"label_agreement":null},{"id":"W2121823099","doi":"10.1017/cjn.2014.34","title":"Greater Loss of White Matter Integrity in Postural Instability and Gait Difficulty Subtype of Parkinson's Disease","year":2014,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Superior longitudinal fasciculus; Corpus callosum; Medicine; Voxel; Fasciculus; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.04805718819940654,"score_gpt":0.3013091439172459,"score_spread":0.25325195571783937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121823099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917464,0.00019177006,0.000057974943,0.007377065,0.00009716497,0.0001552586,0.000014486387,0.0000073853535,0.00035244302],"genre_scores_gemma":[0.99578446,0.00011894481,0.0025397877,0.0014948768,0.000046828613,0.0000019725062,2.8341145e-7,0.000006128321,0.000006727112],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975195,0.00042220805,0.0007349447,0.00037776795,0.00038689043,0.00055872166],"domain_scores_gemma":[0.99763256,0.0002580091,0.0005683026,0.00016491502,0.00033489702,0.0010413206],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0018574672,0.00019694606,0.00048978685,0.0005280803,0.0005317805,0.000063846615,0.00065640867,0.000089308975,0.000050239065],"category_scores_gemma":[0.0012197391,0.00012446906,0.00013165404,0.00072590535,0.005833147,0.00037332342,0.000078735946,0.00084755645,3.3029477e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001311639,0.000035134417,0.99818826,0.00001942188,0.000002493036,0.000353657,0.00015659974,0.0001147457,0.000081835016,0.00031154606,0.000051858337,0.0005532619],"study_design_scores_gemma":[0.00022674109,0.009207097,0.9784125,0.000056342276,0.000022090642,0.002913449,0.000043413755,0.0005463467,0.00008876485,0.007884667,0.00048974634,0.000108815075],"about_ca_topic_score_codex":0.000682552,"about_ca_topic_score_gemma":0.0073484443,"teacher_disagreement_score":0.019775756,"about_ca_system_score_codex":0.00007596329,"about_ca_system_score_gemma":0.00078756193,"threshold_uncertainty_score":0.9968724},"labels":[],"label_agreement":null},{"id":"W2121839970","doi":"10.1109/isbi.2006.1624924","title":"The Biological Basis of Diffusion Tractography","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Tractography; White matter; Diffusion MRI; Diffusion; Anisotropic diffusion; Isotropy; Anisotropy; Diffusion imaging; Nuclear magnetic resonance; Computation; Magnetic resonance imaging; Physics; Computer science; Optics; Algorithm; Radiology; Medicine","score_opus":0.05916588426768305,"score_gpt":0.3382784821585658,"score_spread":0.2791125978908828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121839970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9235139,0.00013941388,0.03538703,0.006349937,0.0000129218615,0.00028197412,0.0000031041372,0.00021099347,0.03410075],"genre_scores_gemma":[0.99000776,0.00014100852,0.009329696,0.00014595919,0.0000195414,0.000013455227,0.0000035983596,0.000002940988,0.00033606583],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9997364,0.0000046949376,0.000090248155,0.00006654907,0.000045042056,0.000057033456],"domain_scores_gemma":[0.99973494,0.000061115345,0.000024855017,0.00014551755,0.00002053254,0.0000130647595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003099496,0.000031668573,0.000054225555,0.000016546179,0.00004821608,0.0000019441386,0.00003749331,0.000017031916,0.0000190008],"category_scores_gemma":[0.0000095855,0.00001508632,0.000049618793,0.00010578894,0.00007683561,0.0000068139434,0.000012565274,0.00004365631,0.000001384636],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056916273,0.0004962463,0.19573866,0.000008387158,0.000006669331,0.000002714367,0.000005784871,9.444176e-7,0.554222,0.17630434,0.0122081265,0.060949225],"study_design_scores_gemma":[0.0002792618,0.0001519646,0.667048,0.000010944833,0.000014876735,0.000017332603,0.000021112328,0.0000934562,0.12529927,0.024360117,0.18264312,0.000060591843],"about_ca_topic_score_codex":0.000019857289,"about_ca_topic_score_gemma":0.0000013137488,"teacher_disagreement_score":0.4713093,"about_ca_system_score_codex":0.0000020750215,"about_ca_system_score_gemma":0.0000025996878,"threshold_uncertainty_score":0.061520226},"labels":[],"label_agreement":null},{"id":"W2122506124","doi":"10.1503/jpn.110180","title":"Is depression a disconnection syndrome? Meta-analysis of diffusion tensor imaging studies in patients with MDD","year":2012,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":469,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Superior longitudinal fasciculus; Occipital lobe; Tractography; Voxel; Frontal lobe; Uncinate fasciculus; Psychology; Fasciculus; Neuroscience; Major depressive disorder; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.20798261876247473,"score_gpt":0.4386985490390744,"score_spread":0.23071593027659967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122506124","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010405059,0.988094,0.0006399066,0.0002772332,0.00018592147,0.00036302608,0.000019652767,0.000008159295,0.0000070394217],"genre_scores_gemma":[0.04140219,0.95572203,0.0026016685,0.00018774139,0.000026393536,0.000014973719,0.000001976654,0.000018289704,0.000024731447],"study_design_codex":"observational","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9984499,0.00007281563,0.0006989546,0.00028902286,0.00034266207,0.0001466219],"domain_scores_gemma":[0.99822384,0.0000749474,0.0012235864,0.00026968928,0.00011830741,0.000089632355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025109298,0.00021413053,0.0018550882,0.00071554555,0.00007901219,0.00001079118,0.00013784599,0.00003880672,0.0000049356345],"category_scores_gemma":[0.000047464215,0.00011357874,0.00059754995,0.0011938299,0.00016188841,0.00022008964,0.000064886946,0.00034437666,1.0703358e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018944839,0.0027426062,0.8837606,0.009632891,0.009095034,0.000055585344,0.00019633053,0.00002014644,0.00004318573,0.000095990305,0.00016714486,0.094001055],"study_design_scores_gemma":[0.0012573805,0.0013021777,0.32639506,0.008055116,0.62040156,0.0017952764,0.00007820982,0.00009175901,0.000012066825,0.00023078897,0.039782066,0.0005985398],"about_ca_topic_score_codex":0.0000015083577,"about_ca_topic_score_gemma":7.9965906e-7,"teacher_disagreement_score":0.61130655,"about_ca_system_score_codex":0.000021402746,"about_ca_system_score_gemma":0.000053987056,"threshold_uncertainty_score":0.46316066},"labels":[],"label_agreement":null},{"id":"W2122622288","doi":"10.1002/mds.22081","title":"Diffusion‐weighted imaging and magnetization transfer imaging of tardive and edentulous orodyskinesia","year":2008,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Putamen; Tardive dyskinesia; Basal ganglia; Globus pallidus; Magnetic resonance imaging; Caudate nucleus; Medicine; Dyskinesia; Neuroradiology; Diffusion MRI; Neurology; Psychology; Nuclear medicine; Internal medicine; Neuroscience; Radiology; Parkinson's disease; Central nervous system; Schizophrenia (object-oriented programming); Psychiatry; Disease","score_opus":0.013971641627157668,"score_gpt":0.2620241154697185,"score_spread":0.24805247384256082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122622288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91456723,0.0009358611,0.07730092,0.0055349986,0.000021498408,0.00059252506,0.0000101661535,0.00011240603,0.00092439714],"genre_scores_gemma":[0.99298304,0.0020785744,0.0031026201,0.001609327,0.000013883478,0.000036528956,0.000025162186,0.000021262338,0.00012960611],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992976,0.000009966103,0.00018302037,0.00023753922,0.00013746951,0.00013436795],"domain_scores_gemma":[0.999693,0.000016345288,0.00003329274,0.00015688804,0.000042135354,0.000058373775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031601146,0.00011831114,0.00015461356,0.00008974818,0.000113155445,0.000006234564,0.000035480025,0.000014432388,0.000028900242],"category_scores_gemma":[0.0000074995305,0.00010959884,0.000030604104,0.00012588958,0.00015697334,0.00007662564,0.000036882615,0.00006390053,4.3368036e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007236694,0.00027247425,0.9003161,0.00010979134,0.000017581284,0.000015184773,0.0006446043,0.0000050162066,0.057046402,0.0018597002,0.0014245183,0.038216237],"study_design_scores_gemma":[0.0040829084,0.00015969122,0.94941396,0.00013201428,0.00015434825,0.00002594319,0.0006023239,0.011029408,0.007830804,0.021885851,0.004275491,0.00040725642],"about_ca_topic_score_codex":0.000065503256,"about_ca_topic_score_gemma":0.000003893068,"teacher_disagreement_score":0.07841581,"about_ca_system_score_codex":0.000014003583,"about_ca_system_score_gemma":0.000010715472,"threshold_uncertainty_score":0.4469311},"labels":[],"label_agreement":null},{"id":"W2122735696","doi":"10.1016/j.brainres.2009.07.046","title":"The relations between white matter and declarative memory in older children and adolescents","year":2009,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; SickKids Foundation; Hospital for Sick Children; McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research; Sick Kids Foundation","keywords":"Uncinate fasciculus; White matter; Psychology; Cingulum (brain); Inferior longitudinal fasciculus; Diffusion MRI; Neuroscience; Cognitive psychology; Superior longitudinal fasciculus; Episodic memory; Recall; Audiology; Tractography; Cognition; Fractional anisotropy; Magnetic resonance imaging; Medicine","score_opus":0.07944380354018539,"score_gpt":0.4314518269975476,"score_spread":0.3520080234573622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122735696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9005932,0.00028126052,0.00060831057,0.09561219,0.0000023155628,0.0009531402,0.000006408917,0.000032398475,0.0019107325],"genre_scores_gemma":[0.9963214,0.00006835335,0.0009532472,0.00070029736,0.000035347282,0.000029251849,0.0000074532727,0.000008025405,0.0018766382],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999253,0.00008897203,0.0001065258,0.00019307155,0.00016393287,0.00019449659],"domain_scores_gemma":[0.9994663,0.00019423148,0.000015329855,0.00020772967,0.000046052322,0.00007037269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043170163,0.0000546722,0.00007913609,0.0001005797,0.00021399494,0.000029499204,0.00006430432,0.00003589174,0.000008606751],"category_scores_gemma":[0.00010031208,0.000039380906,0.000010580215,0.0002328329,0.00017093033,0.00004835836,0.000057745885,0.00041471276,0.0000115211415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013639676,0.000030363375,0.9733299,0.0000042647007,0.0000025696718,0.000002403303,0.00017339895,2.56417e-7,0.00021876185,0.00032152623,0.014604497,0.011298445],"study_design_scores_gemma":[0.00036334133,0.00004402654,0.9945632,0.00007609003,0.000002640502,0.000011793964,0.00003584108,0.000026524367,0.00010107761,0.004009284,0.00072893,0.000037233003],"about_ca_topic_score_codex":0.000009668602,"about_ca_topic_score_gemma":0.0000048008505,"teacher_disagreement_score":0.095728144,"about_ca_system_score_codex":0.000021189418,"about_ca_system_score_gemma":0.00002030957,"threshold_uncertainty_score":0.18017437},"labels":[],"label_agreement":null},{"id":"W2122954083","doi":"10.3174/ajnr.a2698","title":"Systematic Differences between Lean and Obese Adolescents in Brain Spin-Lattice Relaxation Time: A Quantitative Study","year":2011,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; School of Medicine, New York University; York University","keywords":"Medicine; Brain size; Obesity; Voxel; Internal medicine; Endocrinology; Magnetic resonance imaging; Radiology","score_opus":0.09885539507677374,"score_gpt":0.3763667851637285,"score_spread":0.2775113900869548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122954083","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966923,0.000060028564,0.002126632,0.00057891663,0.000019760839,0.00047004526,0.0000013027843,0.000019106328,0.000031888714],"genre_scores_gemma":[0.99535066,0.00003905413,0.0042638653,0.0002846795,0.000024652603,0.00001053684,5.0488075e-7,0.000014228233,0.00001180953],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987182,0.00031935118,0.0005380059,0.00017561199,0.000109180364,0.00013966273],"domain_scores_gemma":[0.99864936,0.00032204282,0.00069038384,0.00016568026,0.00007945424,0.000093053546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030844208,0.00011539981,0.00066474866,0.00023646661,0.000030641222,0.0000044300064,0.0001216784,0.000020294103,0.000002446433],"category_scores_gemma":[0.0004880221,0.00008829905,0.000041042284,0.00027750942,0.00024255333,0.0000736348,0.000029357136,0.00031173753,0.0000033908511],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018691468,0.00037251678,0.99403435,0.0002623335,0.00005410962,0.00015453693,0.0020131979,6.8410804e-7,0.0015689943,0.00018711784,0.000025412397,0.0011398257],"study_design_scores_gemma":[0.00065469526,0.006648464,0.98917675,0.00090019597,0.00012921884,0.00055499596,0.0011591043,0.00010753045,0.000031334635,0.0005571843,0.0000026462537,0.00007786688],"about_ca_topic_score_codex":0.00002789987,"about_ca_topic_score_gemma":0.0000022328961,"teacher_disagreement_score":0.0062759477,"about_ca_system_score_codex":0.000024276571,"about_ca_system_score_gemma":0.000026683858,"threshold_uncertainty_score":0.3600731},"labels":[],"label_agreement":null},{"id":"W2125392828","doi":"","title":"Fluid-attenuated inversion recovery preparation: not an improvement over conventional diffusion-weighted imaging at 3T in acute ischemic stroke.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre","funders":"","keywords":"Fluid-attenuated inversion recovery; Medicine; Diffusion imaging; Nuclear medicine; Effective diffusion coefficient; Stroke (engine); Ischemic stroke; Magnetic resonance imaging; Diffusion MRI; Neuroimaging; Ischemia; Radiology; Cardiology","score_opus":0.028903660215779798,"score_gpt":0.29894726671571964,"score_spread":0.27004360649993986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2125392828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989962,0.00004688227,0.0019616669,0.005098548,0.00007032803,0.0014397536,0.00005297724,0.0002343026,0.0011335682],"genre_scores_gemma":[0.987535,0.000115228315,0.0034279067,0.0027674886,0.0001470344,0.001378528,0.00038842295,0.000029844314,0.0042105527],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99856424,0.0000206548,0.00035283796,0.00045181677,0.00027770043,0.00033275547],"domain_scores_gemma":[0.9992224,0.00002900247,0.00012299548,0.00038939595,0.000070590904,0.00016563635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014053106,0.00016756923,0.00019210925,0.00015539459,0.000103349856,0.000021207738,0.00011051661,0.000057184716,0.0001301711],"category_scores_gemma":[0.000021473143,0.00016196792,0.00008086079,0.00019413412,0.000053195326,0.00035760892,0.0001266385,0.00017712255,0.000019350276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014800689,0.00089402805,0.02589734,0.000038079714,0.00006421789,0.00003490204,0.000090102265,0.000028966957,0.77775246,0.00023038803,0.039746985,0.15374245],"study_design_scores_gemma":[0.007582927,0.00017483313,0.27356187,0.00007424288,0.00019523149,0.00010023234,0.000031167903,0.037404764,0.5171188,0.00041947898,0.16272588,0.00061055366],"about_ca_topic_score_codex":0.000019278634,"about_ca_topic_score_gemma":0.0000111182335,"teacher_disagreement_score":0.26063365,"about_ca_system_score_codex":0.00043446006,"about_ca_system_score_gemma":0.000030409108,"threshold_uncertainty_score":0.660486},"labels":[],"label_agreement":null},{"id":"W2126026099","doi":"10.1016/j.neuroimage.2008.04.264","title":"A non-invasive method to relate the timing of neural activity to white matter microstructural integrity","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Mental Health","keywords":"White matter; Magnetoencephalography; Neuroscience; Saccadic masking; Diffusion MRI; Fractional anisotropy; Psychology; Visual cortex; Latency (audio); Neurophysiology; Electroencephalography; Eye movement; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.08420897776048947,"score_gpt":0.3782083580321031,"score_spread":0.29399938027161365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126026099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9397814,0.0000039049114,0.040120978,0.018094987,0.0000524414,0.0008385928,0.000025178597,0.000094872084,0.0009876171],"genre_scores_gemma":[0.8931116,0.0000044101666,0.0987423,0.0072989995,0.000052245105,0.000051742925,0.000002572203,0.00003473349,0.0007014311],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988915,0.000058591122,0.00021919995,0.0003999644,0.00017356197,0.00025718153],"domain_scores_gemma":[0.9988537,0.00013395502,0.00009174357,0.00067343394,0.00010632224,0.00014084742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010424844,0.00017912801,0.00027849016,0.00009349545,0.00015542492,0.000011738579,0.00022526135,0.00004201639,0.000058674625],"category_scores_gemma":[0.00010114874,0.00012905963,0.000117417316,0.0003791522,0.000097455675,0.000091473405,0.00020723288,0.0005476163,0.000054015447],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014830858,0.000048689886,0.028551647,0.000031510903,0.0000076229535,0.000070567046,0.00068194506,0.00004372381,0.95629835,0.000011926133,0.011673722,0.0024319757],"study_design_scores_gemma":[0.00025781643,0.00018744338,0.7023523,0.00003915204,0.00003552907,0.0007332273,0.000019351975,0.00055580965,0.29367653,0.00009163883,0.001911052,0.00014018807],"about_ca_topic_score_codex":0.00004696528,"about_ca_topic_score_gemma":0.0000024796973,"teacher_disagreement_score":0.67380065,"about_ca_system_score_codex":0.000029572551,"about_ca_system_score_gemma":0.000034787656,"threshold_uncertainty_score":0.5262899},"labels":[],"label_agreement":null},{"id":"W2126390643","doi":"10.1139/jpn.0924","title":"Neuregulin 1 genetic variation and anterior cingulum integrity in patients with schizophrenia and healthy controls","year":2009,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Neuroscience; Medicine; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.016826759179006577,"score_gpt":0.30625820729598835,"score_spread":0.2894314481169818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126390643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901793,0.00023674231,0.003431553,0.005901757,0.0000579409,0.00016594745,0.0000010465264,0.000008911745,0.000016778613],"genre_scores_gemma":[0.9764095,0.00023260592,0.021457102,0.0018535664,0.000034371784,8.2230787e-7,6.216706e-8,0.00000488499,0.000007097407],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994327,0.000020740175,0.00020303746,0.00015066935,0.00010330288,0.00008959667],"domain_scores_gemma":[0.9996114,0.000012308423,0.00017056709,0.00007388957,0.000032889253,0.00009897819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009628168,0.00006817517,0.00015035683,0.000102599595,0.000055836328,0.000021207652,0.000035341243,0.000020458057,7.140211e-7],"category_scores_gemma":[0.000039912255,0.000049278424,0.0000106849275,0.0001364619,0.000075671174,0.00010689424,0.000009591138,0.00020945232,3.994346e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009074162,0.0002830975,0.98062533,0.000023738707,0.0000010141543,0.000008223512,0.000041903535,0.000002951555,0.007936396,0.00047306213,0.000028822837,0.009668024],"study_design_scores_gemma":[0.001853247,0.0021045639,0.9941624,0.00010227727,0.000011668893,0.00020084938,0.000003577541,0.00026889198,0.000022830878,0.0011602421,0.00006606291,0.000043403914],"about_ca_topic_score_codex":0.0000016844302,"about_ca_topic_score_gemma":0.000001887678,"teacher_disagreement_score":0.01802555,"about_ca_system_score_codex":0.000004750293,"about_ca_system_score_gemma":0.00003879256,"threshold_uncertainty_score":0.20095158},"labels":[],"label_agreement":null},{"id":"W2127078620","doi":"10.1093/brain/awl111","title":"Unconscious vision: new insights into the neuronal correlate of blindsight using diffusion tractography","year":2006,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":176,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"University of Oxford; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust; Centre for Interdisciplinary Research in Rehabilitation","keywords":"Blindsight; Psychology; Neuroscience; Visual cortex; Stimulus (psychology); Cognitive psychology; Visual perception; Perception","score_opus":0.03215465323883735,"score_gpt":0.3285023049916865,"score_spread":0.2963476517528491,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127078620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9499549,0.00038793462,0.03967959,0.008181063,0.00006785247,0.0003801417,0.0000015277072,0.000119979515,0.0012269875],"genre_scores_gemma":[0.98934597,0.000033234493,0.008822251,0.0010856212,0.00013877291,0.0000056080803,0.000011941012,0.000020509853,0.0005360664],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926084,0.000026108748,0.00022945095,0.00019610919,0.00017393818,0.00011356215],"domain_scores_gemma":[0.99933463,0.00013566887,0.000109803004,0.00032313963,0.000040359664,0.000056400277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051061157,0.00010490688,0.0001450609,0.000105796724,0.000117878284,0.0000097637885,0.00010344845,0.000047537098,0.000020273803],"category_scores_gemma":[0.000026664955,0.00006913008,0.00009528776,0.00039772465,0.00012584048,0.000050680057,0.00004507043,0.00018706814,0.0000029538257],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016495095,0.0006383107,0.008517303,0.000039868588,0.000019816707,0.000042656575,0.00071747205,0.00034063333,0.90188557,0.013175446,0.030763239,0.04369475],"study_design_scores_gemma":[0.0036529852,0.0006848496,0.2377716,0.00037310028,0.00021175975,0.00024926307,0.00008492469,0.017194955,0.045747068,0.09951447,0.59400856,0.0005064484],"about_ca_topic_score_codex":0.00018054835,"about_ca_topic_score_gemma":0.000025035799,"teacher_disagreement_score":0.85613847,"about_ca_system_score_codex":0.00001281369,"about_ca_system_score_gemma":0.00005163069,"threshold_uncertainty_score":0.28190428},"labels":[],"label_agreement":null},{"id":"W2128207744","doi":"10.1002/mrm.20948","title":"Apparent diffusion coefficients from high angular resolution diffusion imaging: Estimation and applications","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":241,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA); McGill University; University of Minnesota; National Science Foundation","keywords":"Spherical harmonics; Diffusion MRI; Gaussian; Isotropy; Anisotropy; Tensor (intrinsic definition); Diffusion; Smoothing; Anisotropic diffusion; Mathematical analysis; Statistical physics; Mathematics; Physics; Computer science; Optics; Geometry; Computer vision","score_opus":0.017829009052379653,"score_gpt":0.3000969946516066,"score_spread":0.28226798559922694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128207744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6660178,0.017247101,0.30516204,0.007661895,0.000093901486,0.0021047448,0.000032793567,0.00032135416,0.0013584122],"genre_scores_gemma":[0.9774868,0.00095211633,0.019562518,0.00047513857,0.0002677107,0.0003981946,0.0003734353,0.000031444924,0.0004526599],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998335,0.000032371252,0.00046640314,0.0005436205,0.0003664037,0.00025621278],"domain_scores_gemma":[0.99912095,0.00009798673,0.00011476332,0.0005015015,0.00007231807,0.00009250151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014212744,0.00020077614,0.00031228244,0.0001944164,0.00012951347,0.000012853722,0.000109153436,0.00006423211,0.000070400725],"category_scores_gemma":[0.00006597276,0.0001725397,0.00002530161,0.00045270962,0.00029048856,0.000056891826,0.00007964318,0.00021449156,0.0000067871197],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015390472,0.0007551527,0.12071961,0.000075803444,0.0000018169932,0.00004794274,0.00017689273,0.00018923164,0.047699064,0.0045992597,0.0045723966,0.8210089],"study_design_scores_gemma":[0.002726944,0.00019979225,0.76860297,0.00055589125,0.00006244409,0.00003779528,0.000066426444,0.10119183,0.0004479983,0.016172448,0.109717585,0.00021789571],"about_ca_topic_score_codex":0.0015670252,"about_ca_topic_score_gemma":0.000032653905,"teacher_disagreement_score":0.820791,"about_ca_system_score_codex":0.00009315162,"about_ca_system_score_gemma":0.000017598646,"threshold_uncertainty_score":0.7035965},"labels":[],"label_agreement":null},{"id":"W2128224240","doi":"10.1016/j.jalz.2011.05.134","title":"IC‐P‐068: Declines in entorhinal cortex structural connectivity in amnestic mild cognitive impairment","year":2011,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University; Centre for Research on Brain Language and Music","funders":"","keywords":"Entorhinal cortex; Voxel; Probabilistic logic; Artificial intelligence; Pattern recognition (psychology); White matter; Hippocampus; Nuclear medicine; Computer science; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.10465410566856506,"score_gpt":0.3634386714035538,"score_spread":0.25878456573498876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128224240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99438435,0.003026777,0.0007975637,0.00022844516,0.000080037564,0.00089963304,0.00001523336,0.00010690085,0.00046104047],"genre_scores_gemma":[0.9938676,0.00004903427,0.005388118,0.0004163989,0.000035922585,0.00017565444,0.000038132035,0.000024407022,0.0000047830645],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987673,0.000042480835,0.00033744026,0.00038885942,0.00014877279,0.00031511887],"domain_scores_gemma":[0.99943644,0.000065854285,0.000100694735,0.00023668354,0.00006337293,0.00009698092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011919784,0.00018951025,0.00025480436,0.00014724142,0.000049634702,0.000008256151,0.0001021129,0.000052837553,0.00020413645],"category_scores_gemma":[0.000032564127,0.00017961877,0.000060110728,0.00025717483,0.00010148216,0.00012211365,0.00007628833,0.00023199935,0.000025078636],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043859595,0.0007037934,0.97853637,0.000015185898,0.0007726929,0.00022870724,0.00076323876,0.0000014229972,0.003201579,0.0010373787,0.00019386543,0.014107152],"study_design_scores_gemma":[0.0015046857,0.0002338307,0.9803799,0.0000801523,0.0016242645,0.00004551696,0.00010122408,0.00032153988,0.013207233,0.002159448,0.00014424861,0.00019799203],"about_ca_topic_score_codex":0.00048404193,"about_ca_topic_score_gemma":0.0002929585,"teacher_disagreement_score":0.01390916,"about_ca_system_score_codex":0.000015681333,"about_ca_system_score_gemma":0.000045017565,"threshold_uncertainty_score":0.73246413},"labels":[],"label_agreement":null},{"id":"W2128297135","doi":"10.1007/s00429-013-0666-8","title":"Investigating the ventral-lexical, dorsal-sublexical model of basic reading processes using diffusion tensor imaging","year":2013,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Saskatchewan; University of Alberta","funders":"","keywords":"Diffusion MRI; Dorsum; Reading (process); Neuroscience; Psychology; Neurology; Cognitive psychology; Cognitive science; Computer science; Linguistics; Biology; Medicine; Anatomy; Magnetic resonance imaging","score_opus":0.04938317891747021,"score_gpt":0.3053841916655988,"score_spread":0.2560010127481286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128297135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92542803,0.00014651133,0.07078602,0.0030826274,0.000026912665,0.0003661678,0.000004596687,0.000083591425,0.00007551494],"genre_scores_gemma":[0.98524106,0.000023628523,0.013066142,0.0014986133,0.000086100365,0.000017010057,0.000012728534,0.000017817578,0.000036909965],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930626,0.000015510224,0.00019579139,0.00021167056,0.00012646372,0.00014430827],"domain_scores_gemma":[0.99947846,0.0000817855,0.00010579354,0.00017584088,0.00010224727,0.000055895103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005414984,0.00011157593,0.00014198259,0.000045789595,0.00019719717,0.00003195877,0.000044883323,0.000044763474,0.000016442336],"category_scores_gemma":[0.00016331086,0.00007229497,0.00002946777,0.0001916037,0.00015036754,0.00017307111,0.000038430484,0.00018610868,3.8397846e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002964821,0.000028599501,0.021901479,0.00023736022,0.000012510257,6.234213e-7,0.0003407328,0.00073224487,0.943007,0.0016813958,0.0008949898,0.031133434],"study_design_scores_gemma":[0.0011181757,0.00016331105,0.0890361,0.000746825,0.0002608732,0.0002760565,0.0005558707,0.7378711,0.039043777,0.12937877,0.0011709037,0.00037823696],"about_ca_topic_score_codex":0.000035045956,"about_ca_topic_score_gemma":5.2723726e-7,"teacher_disagreement_score":0.9039632,"about_ca_system_score_codex":0.00001558868,"about_ca_system_score_gemma":0.00003908937,"threshold_uncertainty_score":0.29481032},"labels":[],"label_agreement":null},{"id":"W2128462670","doi":"10.1177/1073858413513502","title":"The Language Connectome","year":2013,"lang":"en","type":"review","venue":"The Neuroscientist","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":338,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Neuroscience; Uncinate fasciculus; Fasciculus; Superior longitudinal fasciculus; Medial longitudinal fasciculus; Inferior longitudinal fasciculus; Fiber tract; Psychology; Tractography; Diffusion MRI; Medicine; Central nervous system; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.16843741861229986,"score_gpt":0.45281744539152263,"score_spread":0.2843800267792228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128462670","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000060575385,0.9945534,0.0001824975,0.0009622563,0.0004143281,0.0016466943,0.000032075823,0.00022114244,0.0019815748],"genre_scores_gemma":[0.000010636118,0.9749343,0.00012199969,0.00049162,0.00015013387,0.00040843553,0.000018653494,0.000051265404,0.023812963],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988788,0.00008251665,0.00025776954,0.0003267335,0.00020026507,0.00025394693],"domain_scores_gemma":[0.9981442,0.00036641108,0.0001807156,0.0012096243,0.000028739827,0.00007031166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016092118,0.00020581472,0.00043736276,0.000041995474,0.00050382136,0.000126268,0.00056827656,0.000046824487,0.000026131927],"category_scores_gemma":[0.00016221694,0.00008742455,0.00024909552,0.00039310983,0.0003653716,0.000024501638,0.0001917729,0.00047257709,0.00032887873],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[8.816216e-7,0.000025531912,3.8550044e-7,0.0006406896,0.0000074178215,0.000020012052,0.00000865089,2.0691182e-8,0.00006756543,0.002989454,0.031933684,0.9643057],"study_design_scores_gemma":[0.000042725827,0.000020497748,0.000004907681,0.0004989096,0.00018811203,0.00042456386,0.000003880652,0.000007809106,0.000012773322,0.000105889165,0.9986057,0.00008418842],"about_ca_topic_score_codex":0.000005404443,"about_ca_topic_score_gemma":6.3774905e-7,"teacher_disagreement_score":0.96667206,"about_ca_system_score_codex":0.000027011301,"about_ca_system_score_gemma":0.00005711776,"threshold_uncertainty_score":0.42271805},"labels":[],"label_agreement":null},{"id":"W2129393522","doi":"10.1111/j.1552-6569.2009.00430.x","title":"Investigating Agenesis of the Corpus Callosum Using Functional MRI: A Study Examining Interhemispheric Coordination of Motor Control","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; Ottawa Hospital; University of Toronto; Toronto Western Hospital; University of Ottawa","funders":"National Cancer Institute","keywords":"Corpus callosum; Medicine; Agenesis of the corpus callosum; Corpus Callosum Agenesis; Magnetic resonance imaging; Agenesis; White matter; Functional magnetic resonance imaging; Asymptomatic; Neuroscience; Anatomy; Psychology; Radiology; Pathology","score_opus":0.09708305232098167,"score_gpt":0.3415592975450382,"score_spread":0.24447624522405653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2129393522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9753018,0.000032962984,0.02306578,0.0009394303,0.0002557636,0.00031737736,0.0000025748036,0.000017531524,0.00006679695],"genre_scores_gemma":[0.98788613,0.000003054865,0.011691135,0.0002157487,0.00014497213,0.000004356788,2.7603986e-7,0.00002505012,0.000029291008],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985883,0.00007457836,0.00070829975,0.00014661583,0.00036276528,0.000119424214],"domain_scores_gemma":[0.99774414,0.00022337088,0.0011975723,0.00027425305,0.000492429,0.00006824423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038758802,0.00012226545,0.00034267033,0.00012712025,0.00009168241,0.000010217944,0.00018469316,0.000025981919,0.000013731579],"category_scores_gemma":[0.00070754485,0.00008923029,0.000113473136,0.0003366941,0.00019339219,0.0001424124,0.00006432792,0.0004893956,1.0530675e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027341497,0.00011910658,0.21575134,0.000026818854,0.000022240241,0.000005987256,0.00012131818,0.00022332379,0.78243846,0.000028404389,0.000047890706,0.0011877653],"study_design_scores_gemma":[0.0032418687,0.00076252536,0.9000813,0.0005307289,0.0005450236,0.0013740396,0.0006039643,0.030612532,0.061271004,0.00049827737,0.00030630638,0.00017246937],"about_ca_topic_score_codex":0.000020929885,"about_ca_topic_score_gemma":0.000001169932,"teacher_disagreement_score":0.72116745,"about_ca_system_score_codex":0.00003073544,"about_ca_system_score_gemma":0.00010004291,"threshold_uncertainty_score":0.36387056},"labels":[],"label_agreement":null},{"id":"W2130808757","doi":"10.1523/eneuro.0003-15.2015","title":"Synergistic Effects of Age on Patterns of White and Gray Matter Volume across Childhood and Adolescence","year":2015,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; National Institute on Drug Abuse; Alberta Children's Hospital Foundation; Universities Space Research Association; National Institutes of Health; Children's Hospital Foundation; Government of Canada; McGill University","keywords":"White matter; Gray (unit); Psychology; Voxel; Neuroscience; Anatomy; Developmental psychology; Magnetic resonance imaging; Biology; Medicine; Artificial intelligence; Computer science","score_opus":0.022789641840295485,"score_gpt":0.3077530727363132,"score_spread":0.2849634308960177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130808757","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99599254,0.000045453147,0.0031611018,0.00041425056,0.000022140892,0.00020364411,0.00001544033,0.00003096766,0.00011444161],"genre_scores_gemma":[0.99839586,0.000031998985,0.00070167775,0.0005969734,0.000019780216,0.000011689665,0.000003216981,0.000015042644,0.0002237456],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995242,0.0000148359495,0.00011044987,0.00016783233,0.00008851096,0.00009417613],"domain_scores_gemma":[0.9995741,0.000040577557,0.000058933307,0.0002271186,0.000024590034,0.000074675365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003463543,0.00007806788,0.00015655931,0.00002477918,0.000023103788,0.0000034319023,0.000042331103,0.000020482034,0.0000019061042],"category_scores_gemma":[0.00006542359,0.00006667559,0.00001688668,0.000048138267,0.000071654045,0.000021006923,0.00006732569,0.00008835421,0.0000017322345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044745135,0.00027069263,0.94093066,0.0005513191,0.000008157934,0.0000766108,0.0007431462,0.000007925677,0.053008623,0.00015947335,0.0010894237,0.0031091892],"study_design_scores_gemma":[0.00050237804,0.00029362738,0.96592593,0.00027198,0.000021369173,0.000023326204,0.0000098508035,0.000031550415,0.03214744,0.0002201435,0.0004910955,0.000061285726],"about_ca_topic_score_codex":0.000008880315,"about_ca_topic_score_gemma":6.776349e-7,"teacher_disagreement_score":0.024995258,"about_ca_system_score_codex":0.0000038303715,"about_ca_system_score_gemma":0.000005328534,"threshold_uncertainty_score":0.27189517},"labels":[],"label_agreement":null},{"id":"W2130874647","doi":"10.1016/j.neuroimage.2006.02.046","title":"Clustered functional MRI of overt speech production","year":2006,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":152,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; Baycrest Hospital; University of Toronto; Sunnybrook Health Science Centre; Toronto Rehabilitation Institute; Health Sciences Centre","funders":"","keywords":"Speech production; Vowel; Psychology; Neurocomputational speech processing; Functional magnetic resonance imaging; Motor cortex; Neuroscience; Cerebellum; Audiology; Motor control; Speech recognition; Computer science; Speech perception; Medicine; Perception","score_opus":0.05686309059751046,"score_gpt":0.3182292509501781,"score_spread":0.2613661603526677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130874647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8777815,0.000101215184,0.06088799,0.014679807,0.00044074154,0.0014308057,0.000033316395,0.0008765271,0.043768093],"genre_scores_gemma":[0.9728689,0.000023103035,0.020636583,0.00043484216,0.00033896999,0.000026947491,0.000047620953,0.000029937302,0.0055930885],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99921864,0.000011885613,0.00019903234,0.00027016547,0.00018193969,0.00011835333],"domain_scores_gemma":[0.9994103,0.000017857199,0.00008031098,0.00036647773,0.000094847856,0.000030239871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048018006,0.00008937905,0.00013281216,0.00007266106,0.000044597637,0.0000053037993,0.000046002227,0.000027796967,0.000057944722],"category_scores_gemma":[0.000038500413,0.00008488823,0.00006302644,0.0001977722,0.00007144123,0.00007390821,0.000029864144,0.00013465428,0.0000184763],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010461174,0.0003739786,0.009567018,0.000060954848,0.000004887431,0.00002403487,0.0000051378083,0.000076996505,0.9096326,0.0017421157,0.07498287,0.003424758],"study_design_scores_gemma":[0.00085537037,0.00023129265,0.34736228,0.000049820148,0.000070171314,0.000633024,0.00000628005,0.00068602106,0.5275532,0.0057479087,0.11661583,0.0001888194],"about_ca_topic_score_codex":0.000018509203,"about_ca_topic_score_gemma":0.0000014738465,"teacher_disagreement_score":0.38207945,"about_ca_system_score_codex":0.00001867366,"about_ca_system_score_gemma":0.000022451963,"threshold_uncertainty_score":0.34616414},"labels":[],"label_agreement":null},{"id":"W2131173886","doi":"10.1109/nebec.2013.92","title":"Entropic Framework for Nonrigid Registration of Diffusion Tensor Images","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Robustness (evolution); Diffusion MRI; Structure tensor; Image registration; Computer vision; Tensor (intrinsic definition); Distortion (music); Artificial intelligence; Computer science; Noise (video); Mathematics; Image (mathematics); Geometry","score_opus":0.054502831960675305,"score_gpt":0.36635368968041493,"score_spread":0.31185085771973964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131173886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08535761,0.000022307293,0.90121776,0.008897955,0.000017536127,0.0010212144,0.0000051002016,0.00014223535,0.003318263],"genre_scores_gemma":[0.5614832,0.00003919191,0.4357872,0.00039513115,0.000045736313,0.00015328708,0.000011330327,0.000008608708,0.0020763427],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99958366,0.00000308169,0.00014577969,0.000119715995,0.000067105466,0.00008065913],"domain_scores_gemma":[0.99948597,0.00007039458,0.00006733525,0.00023510215,0.00010663809,0.00003457424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000019614981,0.000053050222,0.00010190083,0.000025643336,0.000028860935,0.000005926331,0.000038903796,0.00003413483,0.000106420375],"category_scores_gemma":[0.00010115926,0.00003956826,0.00004401898,0.0000548934,0.000035954847,0.000045718058,0.000011371333,0.00005490675,0.000009325108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044788067,0.00034805364,0.012582307,0.00015589844,0.0000121593785,7.955431e-7,0.000035224275,0.0000017261691,0.65297145,0.27759203,0.031901438,0.024354128],"study_design_scores_gemma":[0.001194864,0.0007522334,0.16212255,0.00022288153,0.00009081925,0.00002825972,0.0001082912,0.0021082961,0.3432949,0.44587466,0.043956243,0.00024601436],"about_ca_topic_score_codex":0.000021406946,"about_ca_topic_score_gemma":2.0635063e-7,"teacher_disagreement_score":0.47612557,"about_ca_system_score_codex":0.000008469061,"about_ca_system_score_gemma":0.000009040151,"threshold_uncertainty_score":0.16135468},"labels":[],"label_agreement":null},{"id":"W2132148195","doi":"10.1016/j.neuroimage.2012.02.083","title":"Very large fMRI study using the IMAGEN database: Sensitivity–specificity and population effect modeling in relation to the underlying anatomy","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto; Montreal Neurological Institute and Hospital","funders":"","keywords":"Voxel; Contrast (vision); Generalization; Artificial intelligence; Computer science; Gaussian; Population; Statistical model; Mixture model; Statistics; Pattern recognition (psychology); Mathematics; Medicine; Physics","score_opus":0.15176380843462187,"score_gpt":0.4096907333328081,"score_spread":0.25792692489818625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132148195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8881193,0.00005665847,0.1090553,0.0011171609,0.00004619122,0.0014465969,0.000009359994,0.000087040666,0.00006238408],"genre_scores_gemma":[0.99693483,0.000010440939,0.002432516,0.0004387585,0.00009022052,0.00003708858,0.000018716672,0.000029782579,0.000007636265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987675,0.0002741693,0.00020177042,0.00028944825,0.00020168857,0.00026542452],"domain_scores_gemma":[0.99911964,0.00021082746,0.00005737889,0.00051684456,0.000029317367,0.00006597277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009806923,0.00013996077,0.00016311937,0.00009716532,0.0003094735,0.000038348368,0.000061199746,0.000025925889,0.000002236143],"category_scores_gemma":[0.00015853225,0.00009402993,0.000030755047,0.00036397154,0.000020168127,0.00031797698,0.00014694473,0.00035351337,0.0000033253796],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002257012,0.00066994823,0.8645594,0.00007802788,0.000021744758,0.00008734188,0.0018356727,0.0050498485,0.11835309,0.0011187838,0.00018282319,0.007817591],"study_design_scores_gemma":[0.00058479246,0.00008165622,0.68908197,0.0000481769,0.000084268075,0.00009509663,0.0002864038,0.3087353,0.00047323856,0.00007498022,0.00031354936,0.00014056984],"about_ca_topic_score_codex":0.00019465653,"about_ca_topic_score_gemma":0.000040377538,"teacher_disagreement_score":0.30368546,"about_ca_system_score_codex":0.00005981211,"about_ca_system_score_gemma":0.000008928282,"threshold_uncertainty_score":0.3834429},"labels":[],"label_agreement":null},{"id":"W2132465749","doi":"10.1038/nm.3390","title":"Quantifying the local tissue volume and composition in individual brains with magnetic resonance imaging","year":2013,"lang":"en","type":"article","venue":"Nature Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":317,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Eye Institute","keywords":"Neuroimaging; Brain tissue; Robustness (evolution); Magnetic resonance imaging; Measure (data warehouse); Computer science; Population; Range (aeronautics); Artificial intelligence; Diffusion MRI; Neuroscience; Pattern recognition (psychology); Biology; Medicine; Data mining; Radiology; Materials science","score_opus":0.030104168357260323,"score_gpt":0.3416549283681054,"score_spread":0.3115507600108451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132465749","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69122714,0.03755323,0.032740343,0.23359753,0.00009821375,0.0024804526,0.000009736249,0.0003257564,0.0019675815],"genre_scores_gemma":[0.9891441,0.00012621927,0.004732411,0.0056153974,0.00011601531,0.00007468221,0.000024931709,0.000019758076,0.00014652386],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99913865,0.000025844109,0.00016265434,0.00025014335,0.00023810842,0.00018461976],"domain_scores_gemma":[0.99947894,0.000087357635,0.000046417957,0.00025166382,0.0000679215,0.000067731766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014210754,0.00012544682,0.000185654,0.00009288041,0.00008604496,0.000012804683,0.00009435585,0.000064198925,0.00005345244],"category_scores_gemma":[0.000040022285,0.00007223561,0.000009108448,0.00030971246,0.00039520994,0.00007866974,0.00003887463,0.00074053183,0.0000052021724],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012076408,0.00013945885,0.2727216,0.00012601606,0.000008519799,0.0001747881,0.0011671876,0.0000070779356,0.029892424,0.005898553,0.02142961,0.668314],"study_design_scores_gemma":[0.0017557058,0.00038064097,0.9405192,0.0006944098,0.000058673573,0.0007026367,0.0003209149,0.003301762,0.0015544592,0.0010381156,0.04952228,0.0001512094],"about_ca_topic_score_codex":0.00009489612,"about_ca_topic_score_gemma":0.000019956922,"teacher_disagreement_score":0.6681628,"about_ca_system_score_codex":0.00002611047,"about_ca_system_score_gemma":0.000016479644,"threshold_uncertainty_score":0.32172835},"labels":[],"label_agreement":null},{"id":"W2132888467","doi":"10.1002/hbm.21004","title":"Diffusion tensor‐based regional gray matter tissue segmentation using the international consortium for brain mapping atlases","year":2010,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Diffusion MRI; White matter; Putamen; Fractional anisotropy; Statistical parametric mapping; Neuroimaging; Segmentation; Nuclear medicine; Magnetic resonance imaging; Medicine; Neuroscience; Artificial intelligence; Psychology; Computer science; Radiology","score_opus":0.12066255001764276,"score_gpt":0.388374009611986,"score_spread":0.2677114595943432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132888467","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46350148,0.000007768836,0.48123506,0.053366765,0.00014119699,0.0011222261,0.000019426569,0.00018479596,0.00042130033],"genre_scores_gemma":[0.8675892,0.0000017665527,0.10064484,0.02818526,0.0007363837,0.00032648526,0.00037077127,0.000068795,0.0020765436],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998788,0.00003238455,0.00033145287,0.00037055963,0.0002395861,0.00023800913],"domain_scores_gemma":[0.9988444,0.00038003607,0.00020687358,0.000368617,0.0001339004,0.000066179455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003003958,0.00017566244,0.00017140222,0.00017367936,0.00068820926,0.000071957824,0.00020802903,0.00006717696,0.00022051293],"category_scores_gemma":[0.00013811131,0.00014431584,0.00009857338,0.00013977193,0.00017318764,0.00010336054,0.0000654906,0.00028446937,0.000010558769],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001594015,0.000058870988,0.0113415895,0.000042103533,0.000013681795,0.000003426184,0.00013727254,0.000020175125,0.95982987,0.0037730462,0.024179656,0.0005843983],"study_design_scores_gemma":[0.0035300613,0.00015118711,0.19784951,0.00059376063,0.0000873477,0.00030899778,0.00087488396,0.02549101,0.02211453,0.014865084,0.7334121,0.00072150765],"about_ca_topic_score_codex":0.000026077505,"about_ca_topic_score_gemma":0.000009874155,"teacher_disagreement_score":0.9377153,"about_ca_system_score_codex":0.00006367878,"about_ca_system_score_gemma":0.000037425172,"threshold_uncertainty_score":0.58850294},"labels":[],"label_agreement":null},{"id":"W2133479279","doi":"10.1139/jpn.0850","title":"Alterations of white matter integrity in adults with major depressive disorder: a magnetic resonance imaging study","year":2008,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; White matter; Internal capsule; Diffusion MRI; Magnetic resonance imaging; Major depressive disorder; Depression (economics); Psychology; Late life depression; Internal medicine; Cardiology; Medicine; Superior longitudinal fasciculus; Uncinate fasciculus; Radiology; Amygdala","score_opus":0.018899181319814138,"score_gpt":0.30794645292724077,"score_spread":0.2890472716074266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133479279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99190325,0.0008924177,0.0030116,0.003795592,0.000063130836,0.00025680062,0.0000033642732,0.0000070393544,0.00006678624],"genre_scores_gemma":[0.99008566,0.00020207399,0.009102091,0.0005273783,0.000025140123,0.000008695131,1.2151843e-7,0.0000067157744,0.00004214011],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999202,0.00003035449,0.0003042262,0.00017919565,0.00017715672,0.00010705819],"domain_scores_gemma":[0.9994782,0.000020390888,0.00019447047,0.00016395676,0.00008199472,0.000060976683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008379141,0.00008158713,0.00016756351,0.00012820208,0.00014250322,0.0000068601666,0.00010991223,0.000010854824,0.0000049587],"category_scores_gemma":[0.000026715757,0.00005865059,0.000026779262,0.00032390808,0.0001881906,0.00018752708,0.000035509725,0.00029751178,1.7432494e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016053175,0.00051894377,0.99785095,0.000018705137,3.881648e-7,0.000047888847,0.00033040417,0.000011568132,0.00055704406,0.00003901783,0.000102064216,0.00036251513],"study_design_scores_gemma":[0.0013276181,0.00086223055,0.995031,0.00024227727,0.000015479405,0.0015492289,0.00016804572,0.0003235453,0.000095466006,0.00019250083,0.00013738355,0.000055195993],"about_ca_topic_score_codex":0.000010227093,"about_ca_topic_score_gemma":0.000020659534,"teacher_disagreement_score":0.0060904906,"about_ca_system_score_codex":0.0000058045125,"about_ca_system_score_gemma":0.000076254415,"threshold_uncertainty_score":0.23917016},"labels":[],"label_agreement":null},{"id":"W2135798489","doi":"10.1007/s10334-013-0424-1","title":"Assessment of diffusion tensor imaging indices in calf muscles following postural change from standing to supine position","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Supine position; Diffusion MRI; Position (finance); Medicine; Anatomy; Physical medicine and rehabilitation; Biomedical engineering; Radiology; Magnetic resonance imaging; Anesthesia","score_opus":0.04162330151471324,"score_gpt":0.37133367090713076,"score_spread":0.32971036939241755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135798489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99386424,0.0013431928,0.0003875197,0.0033263077,0.00010528544,0.00084049004,0.000031567834,0.000024832756,0.00007653842],"genre_scores_gemma":[0.9936142,0.0005710043,0.0044687716,0.00080043107,0.00019458619,0.00023593858,0.00009413592,0.000012388215,0.000008537155],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990308,0.000053960866,0.00034449753,0.00028618213,0.0000866365,0.00019787937],"domain_scores_gemma":[0.999575,0.00008438911,0.00008804894,0.00016942792,0.000031618667,0.000051521514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014873501,0.0001361275,0.00042379493,0.000115139555,0.00003474032,0.000005550548,0.00006564052,0.00004783829,0.00004714887],"category_scores_gemma":[0.00003949931,0.00010348966,0.000014998356,0.000173443,0.00011985321,0.00007002206,0.00007612259,0.0000982562,8.3143965e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027076412,0.0000463372,0.2599477,0.000027303216,0.0000014640055,0.0000077948625,0.00023649969,1.0462561e-7,0.70266074,0.0005498295,0.000012791194,0.036482375],"study_design_scores_gemma":[0.0011357934,0.00039127213,0.9813113,0.000825266,0.000019291416,0.0000046291575,0.00013480785,0.0001577264,0.0085719,0.0071735424,0.00017918799,0.000095268035],"about_ca_topic_score_codex":0.0016789512,"about_ca_topic_score_gemma":0.000014696018,"teacher_disagreement_score":0.7213636,"about_ca_system_score_codex":0.000036309775,"about_ca_system_score_gemma":0.000009824926,"threshold_uncertainty_score":0.4220186},"labels":[],"label_agreement":null},{"id":"W2135993898","doi":"10.1161/strokeaha.115.008815","title":"Reduction of Diffusion-Weighted Imaging Contrast of Acute Ischemic Stroke at Short Diffusion Times","year":2015,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Diffusion MRI; Stroke (engine); Effective diffusion coefficient; Ischemia; Diffusion imaging; White matter; Diffusion; Magnetic resonance imaging; Cardiology; Nuclear magnetic resonance; Radiology","score_opus":0.027844593141929067,"score_gpt":0.31585404930161387,"score_spread":0.2880094561596848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2135993898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841589,0.00014828963,0.006154779,0.0007405533,0.00007968482,0.00041289278,0.0001588312,0.00014293805,0.008003181],"genre_scores_gemma":[0.9862846,0.0001286684,0.0097464835,0.000037481404,0.000080075675,0.000025285755,0.00009040276,0.000026378906,0.0035805975],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989405,0.000014507981,0.00033448383,0.00025234823,0.0002798806,0.00017827231],"domain_scores_gemma":[0.9991119,0.000022638884,0.00014904403,0.00038620547,0.00020122038,0.00012900922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007732612,0.00014070969,0.00031207874,0.00010976482,0.000047633035,0.0000034570628,0.00010226104,0.00004833942,0.000045304118],"category_scores_gemma":[0.000023953311,0.00012176859,0.00010440409,0.00012676489,0.00015861455,0.000073883966,0.00011722903,0.00014764386,0.000004317549],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019733029,0.00014267307,0.014409972,0.000021010554,0.000031590007,0.000004300648,0.00007618619,7.1541075e-7,0.9742781,0.00014305765,0.006124995,0.0045700734],"study_design_scores_gemma":[0.0013320998,0.00016684132,0.0052486854,0.000110224704,0.00025652326,0.00015725133,0.00014740955,0.0015144541,0.98124206,0.00020225218,0.009480826,0.00014137143],"about_ca_topic_score_codex":0.000025889356,"about_ca_topic_score_gemma":5.7614255e-7,"teacher_disagreement_score":0.009161287,"about_ca_system_score_codex":0.000071857714,"about_ca_system_score_gemma":0.000044895824,"threshold_uncertainty_score":0.49655792},"labels":[],"label_agreement":null},{"id":"W2137502570","doi":"10.1016/j.jagp.2014.09.008","title":"White Matter Microstructural Integrity Is Associated with Executive Function and Processing Speed in Older Adults with Coronary Artery Disease","year":2014,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Sunnybrook Health Science Centre; Heart and Stroke Foundation; Toronto Rehabilitation Institute; Health Sciences Centre; Sunnybrook Hospital; University of Toronto","funders":"National Institute on Aging; Canadian Institutes of Health Research; Pfizer Canada; National Institutes of Health; Elan Pharma International; Toronto Rehabilitation Institute; W. Garfield Weston Foundation; Ontario Ministry of Health and Long-Term Care; Canada Foundation for Innovation; Lundbeck Canada; Alzheimer Society; Pfizer; Heart and Stroke Foundation of Canada; Ontario Brain Institute; Alzheimer's Drug Discovery Foundation; F. Hoffmann-La Roche","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Cognitive decline; Diffusion MRI; Coronary artery disease; Cognition; Cardiology; Psychology; Neurocognitive; Medicine; Population; Executive dysfunction; Stroke (engine); Hyperintensity; Internal medicine; Audiology; Neuroscience; Dementia; Radiology; Disease; Neuropsychology; Magnetic resonance imaging","score_opus":0.007438545404216487,"score_gpt":0.25857659288771967,"score_spread":0.25113804748350316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137502570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98967093,0.00015923889,0.0055413577,0.004242445,0.000054640794,0.0002364332,0.000007631553,0.000025799425,0.000061521234],"genre_scores_gemma":[0.98741144,0.000024061892,0.0103971595,0.001973847,0.000120070574,0.0000048568622,0.000007128764,0.000027230295,0.0000342176],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990487,0.00004646153,0.00030543146,0.00023246583,0.0001818939,0.00018502379],"domain_scores_gemma":[0.9989323,0.000025992023,0.0005716406,0.00014829486,0.00015357375,0.0001681769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000095753916,0.00017026882,0.000340748,0.00017771326,0.00005977971,0.000021875228,0.000065834756,0.000026608397,0.000014553848],"category_scores_gemma":[0.000011688057,0.00011631307,0.000045205572,0.00046562136,0.00019380354,0.00016710145,0.000014994474,0.00042617554,7.253823e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002907985,0.00015542623,0.9905332,0.000039343704,0.000030540843,0.000017150807,0.00022615105,0.0000027367994,0.0000486678,0.0000050873077,0.0006566635,0.0053770547],"study_design_scores_gemma":[0.0023226943,0.001140037,0.99371547,0.0006460389,0.0001721506,0.00073222455,0.0005831597,0.00013260337,0.000005919114,0.00037592082,0.000027394219,0.00014636922],"about_ca_topic_score_codex":0.0000067950164,"about_ca_topic_score_gemma":0.0000035793616,"teacher_disagreement_score":0.0052306857,"about_ca_system_score_codex":0.000048949478,"about_ca_system_score_gemma":0.00013864058,"threshold_uncertainty_score":0.47431093},"labels":[],"label_agreement":null},{"id":"W2137565679","doi":"10.1093/brain/awt370","title":"Inferring a dual-stream model of mentalizing from associative white matter fibres disconnection","year":2014,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Mentalization; Arcuate fasciculus; Psychology; Neuroscience; Superior longitudinal fasciculus; Disconnection; Population; White matter; Cognitive psychology; Tractography; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.05117913465380517,"score_gpt":0.335571645426195,"score_spread":0.2843925107723898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137565679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7996174,0.000008603977,0.1872742,0.0068174787,0.000015268217,0.00022365569,0.000053113818,0.00011827398,0.0058719926],"genre_scores_gemma":[0.97670054,0.0000024555914,0.021445794,0.0011372721,0.000045263274,0.000028823604,0.000037749047,0.000015434724,0.0005866405],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995302,0.000018330562,0.00013341219,0.00014701708,0.00008271375,0.00008835522],"domain_scores_gemma":[0.99961394,0.00008134069,0.000087769986,0.00016564096,0.00002074261,0.00003055053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059071626,0.00006790037,0.00013152322,0.00003714332,0.000037083206,0.0000062180193,0.000029733585,0.00002741422,0.000032176384],"category_scores_gemma":[0.00005700398,0.00006266943,0.000042034197,0.00005777747,0.000024512028,0.000064691085,0.0000372426,0.000072607516,0.0000074099157],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059348306,0.00024405641,0.3353227,0.00006342051,0.00007262406,0.0000017781604,0.0020552478,0.0009923317,0.6271038,0.0063600154,0.019428205,0.008296466],"study_design_scores_gemma":[0.0024654022,0.000285124,0.35583332,0.00067905494,0.00017817445,0.000015613658,0.0005393529,0.26204118,0.2856917,0.08648822,0.0052384683,0.0005443675],"about_ca_topic_score_codex":0.00005364049,"about_ca_topic_score_gemma":0.0000060504244,"teacher_disagreement_score":0.34141207,"about_ca_system_score_codex":0.00003266258,"about_ca_system_score_gemma":0.000007632025,"threshold_uncertainty_score":0.25555852},"labels":[],"label_agreement":null},{"id":"W2137788518","doi":"10.1007/s00259-002-0816-3","title":"Limbic system perfusion in Alzheimer's disease measured by MRI-coregistered HMPAO SPET","year":2002,"lang":"en","type":"article","venue":"European Journal of Nuclear Medicine and Molecular Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"","keywords":"Limbic lobe; Limbic system; Posterior cingulate; Orbitofrontal cortex; Entorhinal cortex; Cingulate cortex; Basal forebrain; Hippocampus; Thalamus; Perfusion; Medicine; Anterior cingulate cortex; Parahippocampal gyrus; Cortex (anatomy); Internal medicine; Neuroscience; Temporal lobe; Pathology; Psychology; Prefrontal cortex; Central nervous system; Radiology","score_opus":0.05604775810994017,"score_gpt":0.29053013528331767,"score_spread":0.2344823771733775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137788518","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56119436,0.10439652,0.025719244,0.26005146,0.00057550875,0.0018049164,0.000020442021,0.00060239626,0.045635168],"genre_scores_gemma":[0.9919699,0.0008218536,0.002292857,0.0046907533,0.00013243839,7.984359e-7,0.0000033743543,0.00007127239,0.000016744181],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985956,0.00016352913,0.0004913247,0.00022936045,0.00032042107,0.0001997722],"domain_scores_gemma":[0.99898154,0.000018726954,0.00025665454,0.00029237263,0.00010731051,0.00034342936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044559647,0.00016503294,0.00032095262,0.00021197478,0.00006940626,0.00002075304,0.0001443291,0.00001117386,0.000031647778],"category_scores_gemma":[0.0001010387,0.00013796223,0.000079924874,0.00017049252,0.0001413143,0.000096366464,0.0000575554,0.00034226233,0.000010492069],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006763569,0.0007156847,0.007794991,0.00034006915,0.00017385147,0.033385687,0.0026900214,0.000022022288,0.5267263,0.00074828323,0.29586136,0.13086535],"study_design_scores_gemma":[0.014147249,0.0017443033,0.021013238,0.009236963,0.0020148722,0.01098887,0.0025478501,0.02042521,0.0016968161,0.00012582024,0.91509664,0.00096215575],"about_ca_topic_score_codex":0.0000035137134,"about_ca_topic_score_gemma":4.4794092e-8,"teacher_disagreement_score":0.6192353,"about_ca_system_score_codex":0.000036934765,"about_ca_system_score_gemma":0.00000974448,"threshold_uncertainty_score":0.56259364},"labels":[],"label_agreement":null},{"id":"W2138296888","doi":"10.1109/isspit.2006.270855","title":"DTMRI Segmentation using DT-Snakes and DT-Livewire","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Smoothing; Segmentation; Interpolation (computer graphics); Tensor (intrinsic definition); Image segmentation; Diffusion MRI; Divergence (linguistics); Artificial intelligence; Mathematics; Scalar (mathematics); Computer vision; Computer science; Image (mathematics); Pattern recognition (psychology); Algorithm; Geometry; Magnetic resonance imaging","score_opus":0.08870102002145859,"score_gpt":0.3813279861171943,"score_spread":0.29262696609573574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138296888","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82076925,0.00011979519,0.16447395,0.0019502895,0.000015852023,0.00035385884,0.0000039159922,0.0003035629,0.012009502],"genre_scores_gemma":[0.81116855,0.00003203369,0.18626973,0.00050876214,0.00007208258,0.000013957619,0.000014533651,0.000012980735,0.0019073448],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996265,0.0000041679564,0.00009206472,0.00013535298,0.00006143804,0.00008043333],"domain_scores_gemma":[0.999797,0.000013057147,0.000027278875,0.000109898814,0.000024620145,0.000028185164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002206616,0.00005786437,0.00007093047,0.00003381894,0.00006468283,0.000010596039,0.000016905109,0.00001888379,0.000041218438],"category_scores_gemma":[0.0000037119464,0.00004921509,0.000015682721,0.00007424377,0.000035591354,0.00006128083,0.00001476128,0.0000460082,0.0000035104133],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027351296,0.00019575903,0.05824492,0.000070161244,0.0000112038815,0.000020617124,0.000058566413,0.00008730982,0.8764892,0.023748148,0.009156723,0.03189003],"study_design_scores_gemma":[0.0037605455,0.0004496502,0.2466838,0.00027139235,0.00038748613,0.0010380456,0.0009015652,0.03980682,0.5977336,0.031042082,0.07696603,0.0009589813],"about_ca_topic_score_codex":0.00007679822,"about_ca_topic_score_gemma":0.0000035075225,"teacher_disagreement_score":0.2787556,"about_ca_system_score_codex":0.000018776504,"about_ca_system_score_gemma":0.000008408939,"threshold_uncertainty_score":0.20069331},"labels":[],"label_agreement":null},{"id":"W2138757700","doi":"10.1016/j.physd.2009.03.016","title":"Shocks and finite-time singularities in Hele-Shaw flow","year":2009,"lang":"en","type":"article","venue":"Physica D Nonlinear Phenomena","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Gravitational singularity; Hele-Shaw flow; Flow (mathematics); Mechanics; Computer science; Geology; Mathematics; Physics; Mathematical analysis; Open-channel flow","score_opus":0.03371506156988059,"score_gpt":0.3118802008721207,"score_spread":0.2781651393022401,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138757700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89078623,0.0012334695,0.012522047,0.032244284,0.0000680078,0.0024452736,0.00021553364,0.0016120741,0.058873083],"genre_scores_gemma":[0.90511876,0.000121735495,0.09057335,0.0024141457,0.000636563,0.000032274656,0.000099412995,0.000036242163,0.00096753216],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992372,0.000011353534,0.00016330116,0.0002703151,0.000105479856,0.00021239434],"domain_scores_gemma":[0.999512,0.000059382124,0.00003747815,0.00028059055,0.000031034022,0.00007948695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045995395,0.000138879,0.00024322602,0.00007690205,0.00005653421,0.00001816535,0.000067878194,0.000028123159,0.00002166336],"category_scores_gemma":[0.000029026249,0.00013394625,0.000040587773,0.00020705968,0.00006590814,0.00008247775,0.000033521497,0.0001918101,0.000023499515],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070819823,0.0066379067,0.005636898,0.00033775344,0.000096160824,0.00019007197,0.003162149,0.001032646,0.28945917,0.0121952165,0.004456701,0.67608714],"study_design_scores_gemma":[0.00669217,0.0023634785,0.035526183,0.00080548786,0.00021165254,0.00010412614,0.00024526764,0.6057709,0.02714992,0.1192514,0.2000764,0.0018030282],"about_ca_topic_score_codex":0.000004630254,"about_ca_topic_score_gemma":5.106e-7,"teacher_disagreement_score":0.6742841,"about_ca_system_score_codex":0.000030413496,"about_ca_system_score_gemma":0.000021661854,"threshold_uncertainty_score":0.5462169},"labels":[],"label_agreement":null},{"id":"W2139009850","doi":"10.1002/mrm.20962","title":"Effects of temperature and aldehyde fixation on tissue water diffusion properties, studied in an erythrocyte ghost tissue model","year":2006,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke","keywords":"Ex vivo; Fixative; Glutaraldehyde; Fixation (population genetics); In vivo; Chemistry; Agarose; Biophysics; Permeability (electromagnetism); Membrane; Biomedical engineering; Chromatography; Biochemistry; Biology; In vitro","score_opus":0.024414676383765144,"score_gpt":0.30789144914706434,"score_spread":0.2834767727632992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139009850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98878217,0.005963993,0.00013178411,0.0035085124,0.00002304622,0.0012956201,0.0000032190396,0.000048836228,0.00024281631],"genre_scores_gemma":[0.9955287,0.0010513151,0.0019341448,0.00046352323,0.00007727136,0.00019445572,0.000038255297,0.000021490017,0.000690873],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99876595,0.000040967618,0.00036387204,0.0003678566,0.00024156515,0.00021977696],"domain_scores_gemma":[0.9995083,0.000049138423,0.00005243197,0.00028852155,0.000052220716,0.000049370992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013532091,0.00017768862,0.00039780533,0.0001678846,0.00003833849,0.0000043564874,0.000075866636,0.000083909246,0.000011760425],"category_scores_gemma":[0.0000652926,0.00011338906,0.000010274877,0.00020532364,0.00017435162,0.000054393833,0.000039267605,0.00024146863,0.0000013952399],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024787305,0.0003529326,0.003510499,0.00027526444,6.8286823e-7,0.000056242072,0.0005468989,0.00013272802,0.9641078,0.00017832771,0.0006162444,0.029974507],"study_design_scores_gemma":[0.008197362,0.0049266857,0.2708658,0.003566344,0.000064514,0.00004375595,0.00009524233,0.014686448,0.68053,0.0029308414,0.013708333,0.00038466573],"about_ca_topic_score_codex":0.00021863753,"about_ca_topic_score_gemma":0.000076760065,"teacher_disagreement_score":0.2835778,"about_ca_system_score_codex":0.000046843004,"about_ca_system_score_gemma":0.000013836033,"threshold_uncertainty_score":0.46238717},"labels":[],"label_agreement":null},{"id":"W2139169840","doi":"10.1016/j.schres.2012.06.042","title":"White matter tract abnormalities in first-episode psychosis","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Royal Columbian Hospital","funders":"Canadian Institutes of Health Research; Fraser Health Authority","keywords":"Diffusion MRI; Fractional anisotropy; Internal capsule; White matter; Coronal plane; Psychosis; Psychology; Magnetic resonance imaging; External capsule; Audiology; Medicine; Neuroscience; Psychiatry; Radiology","score_opus":0.14377782658362623,"score_gpt":0.4326362121774551,"score_spread":0.2888583855938289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139169840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95243645,0.00056214706,0.0005288218,0.024059057,0.000076743105,0.0009251615,0.00001917404,0.00019285578,0.02119957],"genre_scores_gemma":[0.98330265,0.00015973973,0.012347756,0.00039011976,0.0002552103,0.0004264334,0.000013866147,0.000039710787,0.00306454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826676,0.000082721046,0.00023922417,0.0002668331,0.0004322343,0.0007122582],"domain_scores_gemma":[0.99894327,0.0001463047,0.000028469893,0.00057561375,0.000090185,0.00021615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007348918,0.0001262457,0.00019066384,0.00038658423,0.00015193831,0.000029699044,0.00018795412,0.000076404845,0.000739807],"category_scores_gemma":[0.000059718226,0.000112079855,0.00006443832,0.00062966323,0.00015269933,0.00023661948,0.00009619564,0.0007857298,0.000681267],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002145762,0.00033080776,0.96937776,0.000062995816,0.000004301417,0.000008211254,0.00018612383,0.0000015146375,0.00013668658,0.001915763,0.02628472,0.0014765275],"study_design_scores_gemma":[0.0007479943,0.00006658074,0.9294171,0.000105806845,0.0000064939773,0.00008284433,0.0000700723,0.000057537603,0.001041457,0.0022958925,0.06597365,0.00013458528],"about_ca_topic_score_codex":0.00018214177,"about_ca_topic_score_gemma":0.00005971663,"teacher_disagreement_score":0.039960686,"about_ca_system_score_codex":0.00009505588,"about_ca_system_score_gemma":0.000019392464,"threshold_uncertainty_score":0.87565356},"labels":[],"label_agreement":null},{"id":"W2139297841","doi":"10.1093/brain/aws222","title":"Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language","year":2012,"lang":"en","type":"review","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":489,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Fasciculus; Neuroscience; Uncinate fasciculus; Context (archaeology); Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Biology; Tractography; Medicine; Diffusion MRI","score_opus":0.08037340626828889,"score_gpt":0.42540054813581935,"score_spread":0.3450271418675305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139297841","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014528826,0.99043965,0.00008534227,0.0061407955,0.000023626566,0.0011697125,0.00008257894,0.000027096708,0.0018858769],"genre_scores_gemma":[0.0041782176,0.9917954,0.0006510362,0.002488475,0.00017576446,0.0002526113,0.00007546215,0.000030649557,0.00035238222],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992532,0.00011905627,0.00023743435,0.00014848288,0.000116171985,0.00012561414],"domain_scores_gemma":[0.99838096,0.0010953912,0.00015609692,0.0003186124,0.000020260457,0.000028681792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037166345,0.0001311385,0.00044550947,0.00006018731,0.000041920164,0.000006682225,0.00011224902,0.000061250124,0.000014294789],"category_scores_gemma":[0.00014298326,0.00006587727,0.00010450659,0.00018301887,0.00019037855,0.000010951121,0.000037178193,0.00030234476,0.0000031367863],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012488829,0.00010801608,0.000056087298,0.002350748,0.00006968276,0.000034815897,0.00049305346,1.1561445e-7,0.000035347213,0.056720357,0.011238972,0.92888033],"study_design_scores_gemma":[0.00023629755,0.000020589343,0.00009994476,0.0005417257,0.00021045057,0.00039016406,0.0001710684,0.000006094961,0.0000036310755,0.0007479572,0.9975038,0.000068243295],"about_ca_topic_score_codex":0.00002478413,"about_ca_topic_score_gemma":0.000007657669,"teacher_disagreement_score":0.9862649,"about_ca_system_score_codex":0.000018002163,"about_ca_system_score_gemma":0.000053692496,"threshold_uncertainty_score":0.26863968},"labels":[],"label_agreement":null},{"id":"W2139416445","doi":"10.1002/hbm.20117","title":"Visualization of thalamic nuclei on high resolution, multi‐averaged T<sub>1</sub> and T<sub>2</sub> maps acquired at 1.5 T","year":2005,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Heart and Stroke Foundation of Canada","keywords":"Thalamus; Hum; Visualization; Nuclear magnetic resonance; Magnetic resonance imaging; Resolution (logic); Physics; Neuroscience; Nucleus; Nuclear medicine; Artificial intelligence; Psychology; Medicine; Computer science; Radiology","score_opus":0.051634184724053726,"score_gpt":0.31657758807169245,"score_spread":0.2649434033476387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139416445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9702364,0.00008228329,0.026147595,0.00207706,0.000028573602,0.00073486613,0.000018458542,0.00040322117,0.00027154526],"genre_scores_gemma":[0.9940462,0.00012353717,0.0036946647,0.001524565,0.00016843155,0.00006286168,0.0001793917,0.000071403534,0.00012890965],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983336,0.00008266699,0.0004787863,0.0005238154,0.00026253096,0.00031863802],"domain_scores_gemma":[0.9988837,0.000113803566,0.00026778426,0.00051234773,0.000110898785,0.000111440866],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002676373,0.0002462036,0.00033492176,0.00026875024,0.00043719655,0.000021444392,0.0001167513,0.00011619339,0.000012864477],"category_scores_gemma":[0.00012901335,0.0002639226,0.000081330334,0.00028806037,0.00017772001,0.00013663604,0.00012425624,0.00015904335,0.000023760847],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004268379,0.00015487798,0.0009041612,0.000094774776,0.000017790271,0.0000060625302,0.00034554396,0.00010852027,0.98395807,0.007369179,0.0041397973,0.0028585296],"study_design_scores_gemma":[0.0030078837,0.0002508217,0.21182679,0.00074933073,0.000067731096,0.00006658619,0.00007581412,0.00601058,0.76475376,0.003006338,0.00967617,0.00050818856],"about_ca_topic_score_codex":0.000005405029,"about_ca_topic_score_gemma":0.000012711187,"teacher_disagreement_score":0.2192043,"about_ca_system_score_codex":0.00018091066,"about_ca_system_score_gemma":0.00002004845,"threshold_uncertainty_score":0.9999813},"labels":[],"label_agreement":null},{"id":"W2139784227","doi":"10.1093/brain/awl256","title":"Spatial patterns of cortical thinning in mild cognitive impairment and Alzheimer's disease","year":2006,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":382,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Montreal Neurological Institute and Hospital; Hospital for Sick Children; Jewish General Hospital; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research","keywords":"Atrophy; Temporal lobe; Magnetic resonance imaging; Dementia; Alzheimer's disease; Cortex (anatomy); Cerebral cortex; Frontal lobe; Neuroscience; Degenerative disease; Temporal cortex; Psychology; Disease; Medicine; Central nervous system disease; Pathology; Radiology; Epilepsy","score_opus":0.04068057329156473,"score_gpt":0.3452087382727024,"score_spread":0.30452816498113766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139784227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9828263,0.00013762695,0.012935797,0.003475962,0.0000063094644,0.00038397103,0.000035945755,0.000044495195,0.00015358854],"genre_scores_gemma":[0.99806255,0.0000081206745,0.0011217769,0.00067883753,0.00003271021,0.000034751552,0.00002822472,0.000008839854,0.000024175291],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99955493,0.00001501218,0.0001332408,0.00013206818,0.000073302625,0.00009143192],"domain_scores_gemma":[0.9997356,0.000081414226,0.00003168874,0.000080682854,0.000016876245,0.000053765947],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047523554,0.000055952085,0.00009810979,0.000039397764,0.000017842176,0.0000027245364,0.00001881182,0.000015330505,0.0000123062655],"category_scores_gemma":[0.000031479372,0.000051494757,0.000020473295,0.000042897023,0.000045726025,0.000018999917,0.00002672651,0.00008417427,7.5872384e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019877982,0.00040614736,0.988729,0.00003762711,0.000009789132,0.00007327224,0.000077908444,0.0000035878077,0.0021355033,0.0019953605,0.0005127988,0.005820202],"study_design_scores_gemma":[0.00074196985,0.00007366633,0.9946328,0.0001439741,0.0000400019,0.0000063263633,0.000025568923,0.0007793952,0.002254232,0.0010370616,0.00021278599,0.000052254618],"about_ca_topic_score_codex":0.00019226065,"about_ca_topic_score_gemma":0.000014173959,"teacher_disagreement_score":0.015236259,"about_ca_system_score_codex":0.0000072747625,"about_ca_system_score_gemma":0.000015738256,"threshold_uncertainty_score":0.20998953},"labels":[],"label_agreement":null},{"id":"W2139854474","doi":"10.1503/jpn.090177","title":"White-matter abnormalities in adolescents with long-term inhalant and cannabis use: a diffusion magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"White matter; Intoxicative inhalant; Psychosocial; Cannabis; Fractional anisotropy; Diffusion MRI; Psychiatry; Psychology; Medicine; Pediatrics; Magnetic resonance imaging; Clinical psychology; Radiology","score_opus":0.017109069483508214,"score_gpt":0.30101840219703285,"score_spread":0.28390933271352464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2139854474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99619067,0.00033820598,0.00019830024,0.0028740787,0.00016005129,0.0002163141,0.0000015577725,0.000009635667,0.000011193426],"genre_scores_gemma":[0.99754447,0.000117612195,0.001128863,0.001068217,0.00004489657,0.0000048039615,6.6485235e-8,0.000009102173,0.000081967264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992029,0.000022322052,0.00023524111,0.00020374298,0.00018470378,0.000151086],"domain_scores_gemma":[0.99955016,0.000006611893,0.00013081158,0.00015904948,0.00004548155,0.00010789854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013016275,0.000102030994,0.00015031872,0.00013296887,0.00009344807,0.000055824847,0.000092555754,0.00001527787,0.000002662665],"category_scores_gemma":[0.000018978828,0.00007198727,0.000016108548,0.000186004,0.00018192886,0.00028960517,0.000048950635,0.00039718623,1.3964964e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094498646,0.00030124284,0.9955918,0.000033382643,1.8590897e-7,0.00009298623,0.000108443324,4.513752e-7,0.0030146015,0.000013147678,0.000047042366,0.00070219743],"study_design_scores_gemma":[0.0008288158,0.00049894134,0.99532527,0.00035525378,0.000015478257,0.002588031,0.000063932064,0.00006361249,0.00004409082,0.000046746714,0.000096002004,0.000073857234],"about_ca_topic_score_codex":0.000011785953,"about_ca_topic_score_gemma":0.00006930929,"teacher_disagreement_score":0.0029705106,"about_ca_system_score_codex":0.0000052202095,"about_ca_system_score_gemma":0.000044415177,"threshold_uncertainty_score":0.29355556},"labels":[],"label_agreement":null},{"id":"W2140306145","doi":"","title":"Diffusion tensor tractography of the limbic system.","year":2005,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":273,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fornix; Diffusion MRI; Tractography; White matter; Fractional anisotropy; Limbic system; Cingulum (brain); Medicine; Neuroscience; Subarachnoid space; Cerebrospinal fluid; Pathology; Psychology; Magnetic resonance imaging; Radiology; Central nervous system; Hippocampus","score_opus":0.04929022505852533,"score_gpt":0.27706968315224256,"score_spread":0.22777945809371725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140306145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97390413,0.00018649928,0.0013829606,0.008935554,0.000061452854,0.001835311,0.000009839694,0.00031571457,0.013368518],"genre_scores_gemma":[0.99713063,0.000023120137,0.0013761852,0.00034661885,0.000070157665,0.0006048147,0.0000011214626,0.000010128863,0.00043723974],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995338,0.000009302253,0.00012909652,0.000103349725,0.00010723222,0.000117247495],"domain_scores_gemma":[0.9995202,0.000019906223,0.00006506316,0.000318998,0.000030240059,0.000045588145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055111737,0.000051447856,0.0000971704,0.00003978099,0.00003974389,0.0000027215876,0.00008320521,0.000023250217,0.000002599491],"category_scores_gemma":[0.000023694904,0.00003144716,0.00008409809,0.00019009504,0.000047015594,0.00002219129,0.000025651521,0.00008655306,0.0000017557355],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105517756,0.0010431842,0.18874145,0.0003411238,0.000046286914,0.000004516809,0.00012746753,0.000014649438,0.024167737,0.014641434,0.0068483236,0.76391834],"study_design_scores_gemma":[0.00026939102,0.000009732629,0.935269,0.000028365977,0.00003989983,0.00003224257,0.000017765758,0.00008245704,0.012360391,0.000084185434,0.05176474,0.000041827374],"about_ca_topic_score_codex":0.000003546622,"about_ca_topic_score_gemma":6.242947e-7,"teacher_disagreement_score":0.7638765,"about_ca_system_score_codex":0.000018891658,"about_ca_system_score_gemma":0.0000046816867,"threshold_uncertainty_score":0.1282378},"labels":[],"label_agreement":null},{"id":"W2140382254","doi":"10.1002/jmri.21166","title":"Minimum detectable difference of MR diffusion maps in acute ischemic stroke","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Fondation pour la Recherche Médicale","keywords":"Diffusion MRI; Fractional anisotropy; Region of interest; Medicine; Effective diffusion coefficient; Nuclear medicine; Stroke (engine); White matter; Acute stroke; Magnetic resonance imaging; Radiology; Internal medicine; Physics","score_opus":0.02539094773858129,"score_gpt":0.29523405280556747,"score_spread":0.26984310506698617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140382254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98699397,0.0076251286,0.0027435168,0.0011766753,0.000044685425,0.00018638828,0.000008297122,0.000020205147,0.0012011426],"genre_scores_gemma":[0.9669182,0.0034074394,0.028287202,0.00018407567,0.00005345324,0.000007803333,0.0000010100301,0.000020504365,0.0011203187],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99865854,0.000022002256,0.0005985184,0.00016962325,0.0003184779,0.00023286557],"domain_scores_gemma":[0.99906176,0.000077724486,0.00033927703,0.00027368177,0.00015933026,0.00008819408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013005902,0.00013504075,0.00038596292,0.0002106391,0.000044663913,0.0000060314933,0.00019605365,0.000031614058,0.000026028458],"category_scores_gemma":[0.00009229867,0.00011458593,0.000106629144,0.00025050668,0.00014655365,0.000107185755,0.00006432311,0.00038731674,0.0000014629246],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019902557,0.00018916167,0.18130536,0.00003389643,0.0000033628662,0.00036327523,0.0001400991,0.000004052692,0.746982,0.000014988122,0.0016792223,0.06908556],"study_design_scores_gemma":[0.005060943,0.00082337495,0.76506174,0.0014388821,0.00013171227,0.007332605,0.0001411417,0.0047308314,0.16872099,0.0007439085,0.045464184,0.00034970333],"about_ca_topic_score_codex":0.0000121479625,"about_ca_topic_score_gemma":7.0924636e-7,"teacher_disagreement_score":0.5837564,"about_ca_system_score_codex":0.000051276988,"about_ca_system_score_gemma":0.000089284345,"threshold_uncertainty_score":0.46726784},"labels":[],"label_agreement":null},{"id":"W2141254413","doi":"10.1109/iembs.2008.4650072","title":"Advanced MR diffusion characterization of neural tissue using directional diffusion kurtosis analysis","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Hong Kong; School of Medicine, New York University; York University; University of Texas Southwestern Medical Center","keywords":"Kurtosis; Diffusion MRI; Diffusion; Tensor (intrinsic definition); Gaussian; Eigenvalues and eigenvectors; Nuclear magnetic resonance; Artificial intelligence; Algorithm; Mathematics; Physics; Computer science; Pattern recognition (psychology); Biological system; Statistics; Geometry; Medicine; Biology; Thermodynamics","score_opus":0.057458511628273215,"score_gpt":0.3444837264798528,"score_spread":0.2870252148515796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141254413","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82570755,0.000010898112,0.17326814,0.00030234654,0.000027696515,0.00023422565,0.000010404361,0.00015590416,0.0002828293],"genre_scores_gemma":[0.9709577,0.0001899901,0.027523492,0.00016752875,0.000048263544,0.000018247914,0.0001585481,0.000017539873,0.00091867696],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991025,0.000016871223,0.00028010158,0.00026041234,0.000212954,0.0001271679],"domain_scores_gemma":[0.9993565,0.00002424382,0.0001463413,0.0002778466,0.00012393617,0.000071124494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002872937,0.00011834657,0.0002803075,0.00025028264,0.00015295761,0.00000338263,0.00005439642,0.00004565916,0.000181374],"category_scores_gemma":[0.000021499614,0.000102491766,0.00011383057,0.0008740458,0.00006522121,0.00011287619,0.000048938076,0.00009081548,0.0000023076761],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037260594,0.00016952872,0.045067612,0.000010010095,0.000023938359,0.0000032112443,0.000030983705,0.00008414795,0.9502612,0.000063524836,0.000008569731,0.0042400155],"study_design_scores_gemma":[0.0005250446,0.00011370292,0.51449686,0.000028906092,0.00036699328,0.000073578536,0.000010973005,0.05849007,0.4237883,0.00004147167,0.0019016624,0.00016243137],"about_ca_topic_score_codex":0.000040096274,"about_ca_topic_score_gemma":0.0000014606067,"teacher_disagreement_score":0.52647287,"about_ca_system_score_codex":0.00003777509,"about_ca_system_score_gemma":0.00001672692,"threshold_uncertainty_score":0.4179493},"labels":[],"label_agreement":null},{"id":"W2141293175","doi":"10.1017/s0317167100005801","title":"Tumor Effects on Cerebral White Matter as Characterized by Diffusion Tensor Tractography","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; Western University","funders":"","keywords":"White matter; Diffusion MRI; Corticospinal tract; Anaplastic astrocytoma; Astrocytoma; Corpus callosum; Tractography; Brain tumor; Pathology; Infiltration (HVAC); Fiber tract; Glioma; Medicine; Magnetic resonance imaging; Radiology; Materials science; Cancer research","score_opus":0.027948970278026657,"score_gpt":0.2981608682350211,"score_spread":0.2702118979569944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141293175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98618376,0.00024991567,0.0002682386,0.009332846,0.0003678529,0.00038226732,0.000011725034,0.000043369295,0.0031600273],"genre_scores_gemma":[0.9703738,0.00008847033,0.00320687,0.025901707,0.0003227778,0.000006412657,8.252176e-7,0.000020248393,0.00007887512],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99612504,0.00031413822,0.0008206819,0.00060253247,0.00077704195,0.001360547],"domain_scores_gemma":[0.9959303,0.0005555088,0.0007260818,0.00020266829,0.0002927064,0.002292718],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0022575245,0.00037105026,0.0005582896,0.00110537,0.0018400067,0.00035356297,0.0011186205,0.00014984967,0.00023047642],"category_scores_gemma":[0.0006464739,0.00024164544,0.00032021975,0.0012921242,0.0032975478,0.00055153697,0.0000444759,0.0015348872,0.000013900524],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024411811,0.00007439684,0.9865688,0.000011240333,0.000007659032,0.005195649,0.00006584003,0.000014860268,0.000884344,0.00020414725,0.001920737,0.004808215],"study_design_scores_gemma":[0.0006379052,0.05969904,0.8729048,0.00009408757,0.000054496057,0.039356638,0.000062225874,0.00006742222,0.0016694536,0.0059028533,0.01919643,0.0003546551],"about_ca_topic_score_codex":0.00020564217,"about_ca_topic_score_gemma":0.0011417265,"teacher_disagreement_score":0.113664,"about_ca_system_score_codex":0.00015322414,"about_ca_system_score_gemma":0.000804768,"threshold_uncertainty_score":0.99945945},"labels":[],"label_agreement":null},{"id":"W2142009729","doi":"10.1016/s0304-3940(02)01333-2","title":"Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins","year":2003,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; McMaster University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Heritability; Corpus callosum; Concordance; Dizygotic twins; Trait; Brain morphometry; Biology; Twin study; Magnetic resonance imaging; Dizygotic twin; Psychology; Audiology; Developmental psychology; Physiology; Evolutionary biology; Neuroscience; Genetics; Medicine","score_opus":0.05944971591487432,"score_gpt":0.35070261120484103,"score_spread":0.29125289528996673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142009729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99517184,0.000003871098,0.00062746863,0.0034883763,0.000039703118,0.000568354,0.0000018794843,0.000029380326,0.00006909332],"genre_scores_gemma":[0.98529047,0.000005810308,0.00148684,0.013134662,0.000008088328,0.00002507442,8.417571e-8,0.000011538508,0.00003741819],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990164,0.00005730271,0.00018890917,0.00035728226,0.00019790625,0.00018217527],"domain_scores_gemma":[0.99933517,0.00004322048,0.00005890516,0.00047718178,0.000015134092,0.00007036855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009688795,0.00009723898,0.00013532478,0.000045129287,0.00009489453,0.0000154173,0.0001950432,0.000016651456,0.0000028466432],"category_scores_gemma":[0.00011019197,0.000072521325,0.000025877132,0.0002938737,0.00033010577,0.00006034158,0.000052181415,0.00015588735,2.6523355e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021919986,0.0001644229,0.3535919,0.0000044489248,2.7285822e-7,0.000014863219,0.000117845615,0.0000119314345,0.6458239,0.00009954628,0.00003616597,0.00013254993],"study_design_scores_gemma":[0.00047354767,0.0003460717,0.9635454,0.000014836428,0.000017257304,0.000055407432,0.000029034092,0.00029966538,0.034269735,0.00019287011,0.00066403946,0.000092142334],"about_ca_topic_score_codex":0.000021712503,"about_ca_topic_score_gemma":0.000008446747,"teacher_disagreement_score":0.61155415,"about_ca_system_score_codex":0.000014020208,"about_ca_system_score_gemma":0.000020308815,"threshold_uncertainty_score":0.2957334},"labels":[],"label_agreement":null},{"id":"W2142154934","doi":"10.1002/mrm.25107","title":"Biomimetic phantom for the validation of diffusion magnetic resonance imaging","year":2014,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; University of Manchester; Cancer Research UK; European Commission; Ministère des relations internationales et de la Francophonie","keywords":"Imaging phantom; Diffusion MRI; Materials science; Fractional anisotropy; Scanner; White matter; Magnetic resonance imaging; Biomedical engineering; Nuclear magnetic resonance; Reproducibility; Diffusion; Nuclear medicine; Medicine; Optics; Physics; Chemistry; Radiology","score_opus":0.038696166987334316,"score_gpt":0.34343851739133896,"score_spread":0.30474235040400466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142154934","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4703535,0.24164431,0.18408678,0.08654834,0.00077504956,0.009593582,0.0000499531,0.0005301832,0.0064182733],"genre_scores_gemma":[0.9764125,0.0030075647,0.016975591,0.0014581062,0.0003102834,0.00051166385,0.000021518197,0.00005479284,0.0012480293],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982552,0.0000586123,0.0005915222,0.00042028844,0.00035503987,0.00031931585],"domain_scores_gemma":[0.9981225,0.0007607126,0.00015379293,0.0007431013,0.00014925403,0.000070647206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006696721,0.00020023828,0.00042020742,0.00017974623,0.0000947388,0.000007262978,0.00027027674,0.00004935121,0.00010113383],"category_scores_gemma":[0.00078703626,0.0001352759,0.00006638644,0.00057659677,0.0004640083,0.000045780605,0.00006033279,0.0001942312,0.000003877282],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019887814,0.00013372388,0.029182129,0.00012120443,0.0000010150791,0.000004480533,0.00021071604,0.000006699662,0.042027917,0.0021484648,0.0029183975,0.92304635],"study_design_scores_gemma":[0.0057846145,0.001593921,0.34657875,0.0014158436,0.00015459633,0.00007505956,0.00013853452,0.05554759,0.012839561,0.009746345,0.5658467,0.0002784947],"about_ca_topic_score_codex":0.00009702481,"about_ca_topic_score_gemma":0.000005028019,"teacher_disagreement_score":0.9227679,"about_ca_system_score_codex":0.00003911913,"about_ca_system_score_gemma":0.000028828665,"threshold_uncertainty_score":0.5516391},"labels":[],"label_agreement":null},{"id":"W2142285493","doi":"10.1002/mrm.21595","title":"Evidence for enhanced functional activity of cervical cord in relapsing multiple sclerosis","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; White matter; Multiple sclerosis; Cord; Diffusion MRI; Fractional anisotropy; Medicine; Proprioception; Corticospinal tract; Cervical spondylosis; Pyramidal tracts; Lesion; Magnetic resonance imaging; Neuroscience; Anatomy; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Surgery","score_opus":0.3082848132474972,"score_gpt":0.38552145026359746,"score_spread":0.07723663701610028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142285493","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9601595,0.004751528,0.029830113,0.0038328376,0.00007342516,0.000975529,0.000004673357,0.000050840405,0.00032157026],"genre_scores_gemma":[0.9777009,0.0030816202,0.018161185,0.0003316902,0.00009097911,0.00030220265,0.000004922139,0.000018683266,0.00030784137],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99866045,0.00003207556,0.00041867094,0.00037011635,0.0002817804,0.0002369412],"domain_scores_gemma":[0.99846953,0.000913411,0.00010378225,0.000344232,0.000103419115,0.00006559709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025380225,0.00013432892,0.00041100648,0.00016475056,0.00004693202,0.0000011899123,0.00010174094,0.000068556285,0.000092033784],"category_scores_gemma":[0.0014995352,0.00011895273,0.00004785058,0.0005346014,0.00034451377,0.00007379027,0.000034980683,0.00025438488,0.0000015308129],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035254844,0.00044637293,0.15120395,0.0002289114,0.0000023063558,0.000026999594,0.00034801514,0.00004179465,0.5752339,0.00020383237,0.0017029598,0.26703548],"study_design_scores_gemma":[0.0035581915,0.0011073855,0.9632513,0.0026777934,0.000015126435,0.00003620978,0.000033242224,0.0035965338,0.022616575,0.00061127567,0.0023829849,0.000113390844],"about_ca_topic_score_codex":0.000144168,"about_ca_topic_score_gemma":0.00004601689,"teacher_disagreement_score":0.81204736,"about_ca_system_score_codex":0.000086387314,"about_ca_system_score_gemma":0.00006711698,"threshold_uncertainty_score":0.48507518},"labels":[],"label_agreement":null},{"id":"W2142415773","doi":"10.3109/02699052.2011.589791","title":"Focal thinning of the posterior corpus callosum: Normal variant or post-traumatic?","year":2011,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal","funders":"","keywords":"Corpus callosum; Traumatic brain injury; Medicine; Audiology; Anatomy; Psychiatry","score_opus":0.08515711006078454,"score_gpt":0.3405493260268062,"score_spread":0.2553922159660217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142415773","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.976735,0.000033759552,0.007852111,0.006564036,0.00015585577,0.0009166093,0.00006896278,0.0002492283,0.007424449],"genre_scores_gemma":[0.9648966,0.0000053776016,0.029132636,0.0047882027,0.00005202147,0.00004263516,0.000004928012,0.000028800314,0.0010488003],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99921674,0.00002932866,0.00027310677,0.00016623922,0.00014722806,0.00016733611],"domain_scores_gemma":[0.99916047,0.00007069538,0.00012765455,0.00049844483,0.00008040943,0.000062318526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012578808,0.00010742984,0.00017703096,0.000043304568,0.00007801058,0.0000052368123,0.00019950733,0.000052458105,0.00015018362],"category_scores_gemma":[0.00017399783,0.00006592323,0.000082042505,0.00016600893,0.00013437198,0.00005942546,0.00012512616,0.00019448817,0.0000092792625],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003535069,0.0016299731,0.022939611,0.00060528476,0.00017223106,0.0002927355,0.011338309,0.0000015875,0.74489355,0.046828188,0.025981955,0.14178152],"study_design_scores_gemma":[0.0028360186,0.0042459248,0.60476935,0.0013034003,0.00040237582,0.003803744,0.0010652501,0.00075909955,0.32638267,0.008104273,0.045427166,0.0009007651],"about_ca_topic_score_codex":0.00010165631,"about_ca_topic_score_gemma":0.000008101964,"teacher_disagreement_score":0.5818297,"about_ca_system_score_codex":0.000018628214,"about_ca_system_score_gemma":0.000080499645,"threshold_uncertainty_score":0.26882714},"labels":[],"label_agreement":null},{"id":"W2142441078","doi":"10.25011/cim.v31i4.4830","title":"QUANTITATIVE EXAMINATION OF A NOVEL CLUSTERING METHOD USING MAGNETIC RESONANCE DIFFUSION TENSOR TRACTOGRAPHY","year":2008,"lang":"en","type":"article","venue":"Clinical and investigative medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cluster analysis; Diffusion MRI; Tractography; Voxel; Artificial intelligence; Pattern recognition (psychology); Population; Computer science; Tensor (intrinsic definition); Mathematics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.5045214186943121,"score_gpt":0.47147405844462525,"score_spread":0.03304736024968685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142441078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8028808,0.00096573564,0.19235149,0.002972282,0.000046259345,0.0004105888,0.000007810729,0.000053627413,0.00031135516],"genre_scores_gemma":[0.64050335,0.00067847973,0.3578511,0.0007565805,0.00008004097,0.0000143868365,0.0000076026827,0.000014794556,0.00009363834],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986079,0.000103140344,0.00061704003,0.00035022217,0.0001918199,0.00012993091],"domain_scores_gemma":[0.99876994,0.0004192089,0.00022416218,0.0002041871,0.00020732154,0.00017520646],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00045703558,0.00014510675,0.0004980839,0.00012691916,0.000102207305,0.0000014218718,0.000059504076,0.00007252383,0.0000120739],"category_scores_gemma":[0.0013145217,0.00010517636,0.0000650926,0.00040074336,0.005320774,0.00008020775,0.000051063053,0.00028484533,3.539863e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039089294,0.0013281626,0.278405,0.00036703437,0.00005011763,0.000053627966,0.0033982613,0.000018693341,0.58072233,0.018169662,0.00039185767,0.116704315],"study_design_scores_gemma":[0.0026090487,0.0024858469,0.9278373,0.0008314712,0.00011758459,0.00015903414,0.0002579061,0.058284722,0.0022031178,0.0035426877,0.0015264611,0.0001447855],"about_ca_topic_score_codex":0.000041690986,"about_ca_topic_score_gemma":0.0000016299846,"teacher_disagreement_score":0.6494323,"about_ca_system_score_codex":0.000008748591,"about_ca_system_score_gemma":0.000030758507,"threshold_uncertainty_score":0.99738616},"labels":[],"label_agreement":null},{"id":"W2143099998","doi":"10.1002/jmri.22101","title":"Human cervical spinal cord funiculi: Investigation with magnetic resonance diffusion tensor imaging","year":2010,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; National Research Council Institute for Biodiagnostics","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Spinal cord; Tractography; Magnetic resonance imaging; Anatomy; Region of interest; Dorsum; Medicine; Neuroscience; Biology; Radiology","score_opus":0.028948994662278654,"score_gpt":0.32143986664219054,"score_spread":0.29249087197991186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143099998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96827936,0.014221141,0.0020113103,0.013261924,0.000194646,0.0006060673,0.0000065758472,0.00015807946,0.0012609222],"genre_scores_gemma":[0.91603804,0.00031639577,0.08064405,0.0017645801,0.00050824333,0.000029295303,0.0000040594105,0.00007900796,0.0006163628],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9975029,0.000055679848,0.00081692066,0.00045111933,0.0006974398,0.00047592926],"domain_scores_gemma":[0.99786705,0.000060152932,0.0005042193,0.00063963863,0.00058820366,0.00034072855],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003788927,0.0003270151,0.00047884719,0.00027729775,0.00027431324,0.00009646893,0.0003814614,0.000059533355,0.00014787783],"category_scores_gemma":[0.00016184365,0.0002599281,0.00014172288,0.00048530978,0.00053531793,0.00034897067,0.000105457046,0.0012849983,0.000009441897],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058018975,0.00018574929,0.3899745,0.00006194891,0.0000024111437,0.0005372437,0.000058933005,0.0000016738667,0.13534541,0.00078348734,0.0023733287,0.4700951],"study_design_scores_gemma":[0.002230418,0.001449485,0.86911255,0.00083899114,0.00011436562,0.005435198,0.000074447635,0.0017344097,0.001816974,0.0018501488,0.11502281,0.00032020867],"about_ca_topic_score_codex":0.000025513857,"about_ca_topic_score_gemma":0.0000074255404,"teacher_disagreement_score":0.47913802,"about_ca_system_score_codex":0.00007235385,"about_ca_system_score_gemma":0.00015523624,"threshold_uncertainty_score":0.9999853},"labels":[],"label_agreement":null},{"id":"W2143697715","doi":"10.3174/ajnr.a2224","title":"Abnormal Axial Diffusivity in the Deep Gray Nuclei and Dorsal Brain Stem in Infantile Spasm Treated with Vigabatrin","year":2010,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Dorsum; White matter; Anatomy; Magnetic resonance imaging; Radiology","score_opus":0.014277262608107117,"score_gpt":0.29000282609636463,"score_spread":0.2757255634882575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143697715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99372613,0.00001962158,0.0004885058,0.0054799127,0.000028161392,0.00017497115,0.0000027011142,0.000016717842,0.000063275016],"genre_scores_gemma":[0.9969378,0.000072193536,0.0016627513,0.0012236688,0.0000749871,0.00000747352,0.000001104096,0.000016832346,0.0000032043374],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990379,0.00016190977,0.00030916306,0.00017140935,0.00010640892,0.00021319088],"domain_scores_gemma":[0.9990024,0.00040167852,0.00026858656,0.0002150005,0.000039898045,0.00007244381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023492155,0.00012809831,0.00039801226,0.00020300625,0.000035430123,0.000009627007,0.00016466895,0.00003503622,0.00000412591],"category_scores_gemma":[0.000068303976,0.00007891351,0.000040859613,0.00040384365,0.0005245091,0.0000738,0.000026507269,0.0009005549,4.8012936e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073849765,0.00025189144,0.918928,0.000007314868,0.000010928933,0.0010607019,0.0005879895,0.000021642993,0.041564077,0.00046950064,0.00009203383,0.03626739],"study_design_scores_gemma":[0.0014483035,0.0020085066,0.9804151,0.000020437148,0.000025254563,0.012328232,0.00021780781,0.00019392063,0.0003001109,0.00011107274,0.0028326528,0.00009859816],"about_ca_topic_score_codex":0.00008654246,"about_ca_topic_score_gemma":0.0001243777,"teacher_disagreement_score":0.06148707,"about_ca_system_score_codex":0.000012643734,"about_ca_system_score_gemma":0.000036619134,"threshold_uncertainty_score":0.39125127},"labels":[],"label_agreement":null},{"id":"W2143815825","doi":"10.1016/j.jpsychires.2004.10.001","title":"Volumetric MRI measurement of caudate nuclei in antipsychotic-naïve patients suffering from a first episode of psychosis","year":2004,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychosis; Antipsychotic; Psychology; Psychiatry; Caudate nucleus; Schizophrenia (object-oriented programming); Medicine; Neuroscience","score_opus":0.13584859674759248,"score_gpt":0.4156573796592648,"score_spread":0.2798087829116723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143815825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98540765,0.0009783489,0.009083968,0.0034520028,0.00017226102,0.00055910955,0.000016687007,0.000010711007,0.000319286],"genre_scores_gemma":[0.955848,0.0019360314,0.04203368,0.000027453023,0.00010602363,0.000010834424,0.0000019326533,0.000027534963,0.000008507238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966811,0.000083571176,0.0010743882,0.00024288186,0.0015974547,0.00032058757],"domain_scores_gemma":[0.99747,0.00012750388,0.0005509541,0.0004686474,0.0012163672,0.00016650368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012660179,0.00013131219,0.0004802286,0.0016381046,0.000064163956,0.00001157027,0.00036808016,0.00007462178,0.000027761933],"category_scores_gemma":[0.00038417027,0.00011293746,0.00018635573,0.0025997676,0.00009977759,0.000099605255,0.000057491412,0.0007141507,0.000004418487],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009416511,0.003197642,0.97815794,0.0002633053,0.00009271568,0.000017467652,0.0002251763,0.00026238474,0.0037607676,0.0001933553,0.0055650994,0.0073224916],"study_design_scores_gemma":[0.0058005964,0.0018010563,0.9769492,0.0008473828,0.00007748578,0.000016249178,0.00008145047,0.00010673916,0.0046838913,0.006948128,0.0025510094,0.00013682184],"about_ca_topic_score_codex":0.00069845654,"about_ca_topic_score_gemma":0.00006053668,"teacher_disagreement_score":0.032949712,"about_ca_system_score_codex":0.00026283422,"about_ca_system_score_gemma":0.00013185208,"threshold_uncertainty_score":0.4605456},"labels":[],"label_agreement":null},{"id":"W2143830079","doi":"10.1016/s0278-2626(02)00011-8","title":"Division of the corpus callosum into subregions","year":2002,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Percentile; Factor (programming language); Psychology; Division (mathematics); Artificial intelligence; Pattern recognition (psychology); Neuroscience; Statistics; Cognitive psychology; Computer science; Mathematics; Arithmetic","score_opus":0.07165951081883656,"score_gpt":0.3178279892003294,"score_spread":0.24616847838149283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143830079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9134612,0.00043008348,0.023613237,0.049391136,0.00005028377,0.0007416976,0.000014666157,0.00017212317,0.012125557],"genre_scores_gemma":[0.9971514,0.00011676727,0.0008470805,0.0013564209,0.00001528641,0.000016958791,0.0000057757184,0.0000051015504,0.00048525026],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99973387,0.000009983233,0.00006979822,0.00008034851,0.00006094667,0.000045033088],"domain_scores_gemma":[0.9997638,0.000035523277,0.000031921663,0.00011182612,0.000032381027,0.000024553634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022680644,0.000036621066,0.000052666634,0.00001874944,0.00006736937,0.000002884047,0.000023744833,0.000019298806,0.000020367392],"category_scores_gemma":[0.00004582837,0.000025531404,0.000026002837,0.00008851621,0.00007688836,0.00002095239,0.00002174927,0.00005615026,0.000003140292],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042787728,0.0007065226,0.017694358,0.00019733202,0.000025502966,0.000008956069,0.0007220713,0.0000010493775,0.3626262,0.030331833,0.039258152,0.54838526],"study_design_scores_gemma":[0.0048920233,0.00087435,0.43777737,0.0012955886,0.00034787256,0.000497122,0.0003427396,0.0075374427,0.16432568,0.2063089,0.17522454,0.0005763835],"about_ca_topic_score_codex":0.000005154698,"about_ca_topic_score_gemma":0.000001558197,"teacher_disagreement_score":0.5478088,"about_ca_system_score_codex":0.0000039804395,"about_ca_system_score_gemma":0.000002574896,"threshold_uncertainty_score":0.10411404},"labels":[],"label_agreement":null},{"id":"W2143997687","doi":"10.1016/j.neuroimage.2007.04.062","title":"Reduced microstructural integrity of the white matter underlying anterior cingulate cortex is associated with increased saccadic latency in schizophrenia","year":2007,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; U.S. Public Health Service; GlaxoSmithKline","keywords":"White matter; Cingulum (brain); Anterior cingulate cortex; Psychology; Neuroscience; Fractional anisotropy; Diffusion MRI; Cingulate cortex; Saccadic masking; Schizophrenia (object-oriented programming); Posterior cingulate; Cortex (anatomy); Eye movement; Medicine; Magnetic resonance imaging; Central nervous system; Psychiatry; Cognition; Radiology","score_opus":0.040767312626619055,"score_gpt":0.3253026185730904,"score_spread":0.28453530594647136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143997687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99709815,0.000020072222,0.00029818073,0.0013216857,0.000042255015,0.00053837255,0.000024047516,0.00009624138,0.0005609957],"genre_scores_gemma":[0.9953123,0.000005955358,0.0025639012,0.0018738153,0.000014948258,0.0000073220026,0.000009181023,0.000041351883,0.00017126932],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99869436,0.000047526588,0.00040372738,0.00035480384,0.00019951217,0.0003000714],"domain_scores_gemma":[0.9990127,0.000054968903,0.00024624442,0.00051811576,0.000095594885,0.000072395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000177696,0.00019152426,0.00031518095,0.00013193562,0.000086059095,0.000017525797,0.00019399283,0.00007315779,0.000062256615],"category_scores_gemma":[0.00008249836,0.00013332225,0.00008657098,0.0005769846,0.00018959523,0.00009004646,0.00007865238,0.0006533926,0.0000043867662],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022127837,0.000059998645,0.32529983,0.000023699215,0.000009123886,0.00005106496,0.00012479979,4.45703e-7,0.67353225,0.000012072927,0.0001247372,0.0005407382],"study_design_scores_gemma":[0.0012450797,0.0000803601,0.9568615,0.00032645933,0.000040995008,0.00014366336,0.000021378508,0.000106745196,0.040763725,0.0002633099,0.000026235753,0.00012054279],"about_ca_topic_score_codex":0.00009305183,"about_ca_topic_score_gemma":0.000037015532,"teacher_disagreement_score":0.6327685,"about_ca_system_score_codex":0.00006727015,"about_ca_system_score_gemma":0.000059516395,"threshold_uncertainty_score":0.5436723},"labels":[],"label_agreement":null},{"id":"W2144240799","doi":"10.1016/j.mri.2015.02.022","title":"In vivo 3T and ex vivo 7T diffusion tensor imaging of prostate cancer: Correlation with histology","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Ex vivo; In vivo; Prostate cancer; Fractional anisotropy; Diffusion MRI; Effective diffusion coefficient; Prostate; Prostatectomy; Medicine; Nuclear medicine; Magnetic resonance imaging; Histology; Pathology; Cancer; Nuclear magnetic resonance; Radiology; Internal medicine; Biology; Physics","score_opus":0.02095815390188491,"score_gpt":0.3002256656263203,"score_spread":0.27926751172443537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144240799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94615245,0.026402434,0.007530702,0.014505535,0.0001197485,0.0014714397,0.000028282191,0.00020164414,0.0035877433],"genre_scores_gemma":[0.97834694,0.00086497917,0.017537517,0.0007455593,0.000043119227,0.00014293364,0.0000039166525,0.00004506949,0.0022699737],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988479,0.000027612019,0.0002970767,0.00037798047,0.00018941847,0.00026002902],"domain_scores_gemma":[0.9992851,0.000043938413,0.00014122485,0.00029013222,0.00014181074,0.00009779125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011845344,0.00016171054,0.00028309898,0.00015748301,0.000042757776,0.000011349161,0.00007387572,0.000023526783,0.000038433398],"category_scores_gemma":[0.00005584389,0.00014040823,0.000020336234,0.00027454653,0.000267991,0.00015262926,0.00006315305,0.00018505762,0.0000012846111],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022135841,0.00007553474,0.9249508,0.00005372095,9.539914e-7,0.0000827996,0.00049678725,0.000031539643,0.011678509,0.00037293285,0.002426393,0.0596087],"study_design_scores_gemma":[0.008411362,0.0005710242,0.57389325,0.0014576095,0.00013668394,0.0012400172,0.00072042283,0.11493657,0.008579929,0.005086946,0.28424162,0.0007245565],"about_ca_topic_score_codex":0.00050963514,"about_ca_topic_score_gemma":0.000023698336,"teacher_disagreement_score":0.3510575,"about_ca_system_score_codex":0.000096228,"about_ca_system_score_gemma":0.00007890113,"threshold_uncertainty_score":0.5725681},"labels":[],"label_agreement":null},{"id":"W2145381610","doi":"10.3389/fnhum.2014.00653","title":"A review of structural neuroimaging in schizophrenia: from connectivity to connectomics","year":2014,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":259,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Neuroimaging; Connectomics; Cingulum (brain); Corpus callosum; Neuroscience; Schizophrenia (object-oriented programming); White matter; Diffusion MRI; Uncinate fasciculus; Psychology; Thalamus; Functional connectivity; Connectome; Fractional anisotropy; Medicine; Magnetic resonance imaging; Psychiatry","score_opus":0.08628941262075396,"score_gpt":0.4099322611949404,"score_spread":0.32364284857418646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2145381610","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005670092,0.98470026,0.011538858,0.00018071046,0.0004410677,0.0023141392,0.00007941453,0.00009106965,0.0000874821],"genre_scores_gemma":[0.0010012618,0.9859331,0.010776428,0.0019468077,0.00005865231,0.00017770192,0.000030806175,0.000060229144,0.00001501401],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9970416,0.00020075378,0.0009950415,0.001105607,0.00027173857,0.00038527534],"domain_scores_gemma":[0.998122,0.00014818099,0.00047846863,0.0010475308,0.000051407926,0.00015246095],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034506316,0.00041176987,0.0023835925,0.0006214478,0.000071247596,0.00002144555,0.0007204146,0.00009564119,0.0000054781967],"category_scores_gemma":[0.0008763448,0.00038137988,0.00025349655,0.0014284853,0.00028131553,0.000108874316,0.0002712509,0.0008553275,7.8951564e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004615951,0.00020137322,0.004663959,0.087519914,0.000011164824,0.0001522203,0.00006020176,0.00003632445,0.0004307457,0.0011216529,0.0065337606,0.89922255],"study_design_scores_gemma":[0.00066173624,0.00018964242,0.0024193004,0.1626623,0.00024626433,0.00009530487,0.000003826693,0.0009997285,0.000033824417,0.0016234915,0.83037937,0.00068523403],"about_ca_topic_score_codex":0.000047607675,"about_ca_topic_score_gemma":0.000006722075,"teacher_disagreement_score":0.8985373,"about_ca_system_score_codex":0.00016829708,"about_ca_system_score_gemma":0.00016540434,"threshold_uncertainty_score":0.9998638},"labels":[],"label_agreement":null},{"id":"W2146011728","doi":"10.1109/isbi.2008.4541156","title":"Two novel methods for computing the 3D cardiac midwall","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Endocardium; Cardiac Ventricle; Computation; Streamlines, streaklines, and pathlines; Computer science; Visualization; Image processing; Diffusion MRI; Orientation (vector space); Artificial intelligence; Pipeline (software); Computer vision; Image (mathematics); Ventricle; Algorithm; Mathematics; Geometry; Physics; Cardiology; Medicine; Mechanics","score_opus":0.20091248527696082,"score_gpt":0.4897017434989566,"score_spread":0.2887892582219958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146011728","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002222616,0.000079609934,0.98452735,0.0041030296,0.00004180628,0.00057962077,0.0000032136597,0.00023244137,0.008210338],"genre_scores_gemma":[0.05338215,0.000021276295,0.9430702,0.0021037387,0.00013300552,0.000055691948,0.0000055539044,0.000015274214,0.0012131423],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995534,0.000012684984,0.000111961286,0.00014926499,0.000047022797,0.00012567999],"domain_scores_gemma":[0.9992955,0.00029587958,0.00003203737,0.00028443104,0.000056339708,0.000035837344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001785203,0.0000647392,0.00012712892,0.00001673465,0.00018125032,0.0000035634073,0.00007210091,0.000015490752,0.000006568519],"category_scores_gemma":[0.000061775914,0.000040630795,0.00008239861,0.00009176734,0.000061010982,0.00001635274,0.000037851605,0.000093194525,0.0000028323668],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008883345,0.00047923488,0.006475844,0.000087559325,0.00014003729,0.0000050273716,0.00076347915,0.0002088421,0.3128345,0.1992374,0.051030353,0.4286489],"study_design_scores_gemma":[0.00079095614,0.000080161095,0.003967944,0.000017754275,0.00007528722,0.0001422833,0.00004658645,0.035488803,0.039618578,0.0020525483,0.9175696,0.00014952451],"about_ca_topic_score_codex":0.000014981894,"about_ca_topic_score_gemma":1.8629468e-7,"teacher_disagreement_score":0.86653924,"about_ca_system_score_codex":0.000012952985,"about_ca_system_score_gemma":0.000018843759,"threshold_uncertainty_score":0.16568758},"labels":[],"label_agreement":null},{"id":"W2146726024","doi":"10.1038/mp.2013.44","title":"White-matter microstructure and gray-matter volumes in adolescents with subthreshold bipolar symptoms","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; University of Toronto; Toronto Rehabilitation Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Assistance publique-Hôpitaux de Paris; Institut National de la Santé et de la Recherche Médicale","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Psychology; Corpus callosum; Diffusion MRI; Bipolar disorder; Uncinate fasciculus; Population; Cardiology; Medicine; Internal medicine; Mood; Psychiatry; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.005979382664349936,"score_gpt":0.24881925806507507,"score_spread":0.24283987540072513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146726024","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870613,0.001142675,0.0029089923,0.007831701,0.000053073243,0.0006897734,0.000005630606,0.00007792933,0.00022888281],"genre_scores_gemma":[0.978195,0.000014135866,0.01154779,0.009923705,0.00003347539,0.000084794636,0.000012819519,0.000056060995,0.00013220761],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990136,0.000016079362,0.00018362305,0.00039266652,0.00012787794,0.00026612854],"domain_scores_gemma":[0.9993252,0.0000017043978,0.000056980043,0.0004666341,0.000038097416,0.000111375026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022962506,0.00020257154,0.00020324597,0.00012075833,0.00004744924,0.000038363884,0.00010036223,0.000070512324,0.000101429985],"category_scores_gemma":[0.0000015520549,0.0001636022,0.000044350247,0.00020052055,0.0000965346,0.00008214888,0.00004859576,0.00030154543,0.000089550194],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001836317,0.00007626689,0.98767734,0.00011417779,0.000008408825,0.000010742626,0.000021020458,0.0000024764904,0.008029858,0.00004841974,0.0037767095,0.00021619503],"study_design_scores_gemma":[0.0007914573,0.000070968614,0.9951326,0.00038452385,0.00003198043,0.00021448387,0.000017445329,0.00005181079,0.00079641276,0.001217688,0.0010891858,0.00020141352],"about_ca_topic_score_codex":0.000037316197,"about_ca_topic_score_gemma":0.000010621671,"teacher_disagreement_score":0.008866331,"about_ca_system_score_codex":0.000016897282,"about_ca_system_score_gemma":0.000022047818,"threshold_uncertainty_score":0.66715044},"labels":[],"label_agreement":null},{"id":"W2146949897","doi":"10.1016/j.neuroimage.2008.09.053","title":"Sensitivity of voxel-based morphometry analysis to choice of imaging protocol at 3 T","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Montreal Neurological Institute and Hospital","keywords":"Voxel; Contrast (vision); Mathematics; Population; Voxel-based morphometry; Artificial intelligence; Nuclear medicine; Pattern recognition (psychology); Statistics; White matter; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07714037351573723,"score_gpt":0.38587030552009705,"score_spread":0.30872993200435983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146949897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8469742,0.0000050379113,0.12549014,0.0015270257,0.000014418711,0.024050085,0.000082847524,0.0002545552,0.0016017074],"genre_scores_gemma":[0.973028,0.0000010711634,0.0223109,0.0008869422,0.000023665065,0.0035061587,0.000012041478,0.000029171088,0.00020203486],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987785,0.000057781635,0.0003340823,0.00036591204,0.00027745162,0.00018625282],"domain_scores_gemma":[0.9985428,0.000198511,0.00018726368,0.0007519966,0.0001958787,0.00012357988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001338156,0.00014417787,0.00041835362,0.00043063465,0.00006876306,0.0000025349675,0.00009030444,0.000024285955,0.00004944256],"category_scores_gemma":[0.00029178642,0.00013947506,0.00021162088,0.0015602637,0.0001576351,0.000050923736,0.000095966934,0.0001390556,0.000007544511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009715709,0.00025581903,0.3254258,0.00008520515,0.000026405607,0.000091823305,0.000016987497,0.00023007038,0.6720044,0.000011389844,0.0009967228,0.0007582289],"study_design_scores_gemma":[0.00058653555,0.00010076836,0.53725153,0.000024546533,0.00017784101,0.000049483995,0.0000018838042,0.0050829984,0.45005253,0.000008079854,0.006556374,0.000107406675],"about_ca_topic_score_codex":0.000080116355,"about_ca_topic_score_gemma":0.0000052129294,"teacher_disagreement_score":0.22195187,"about_ca_system_score_codex":0.000037467486,"about_ca_system_score_gemma":0.00004323463,"threshold_uncertainty_score":0.5687628},"labels":[],"label_agreement":null},{"id":"W2147009297","doi":"10.1093/brain/awp233","title":"Language networks in semantic dementia","year":2009,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":270,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"Fractional anisotropy; Arcuate fasciculus; Inferior longitudinal fasciculus; Uncinate fasciculus; Splenium; Corpus callosum; Superior longitudinal fasciculus; Diffusion MRI; Fasciculus; Psychology; White matter; Temporal lobe; Frontal lobe; Tractography; Neuroscience; Anatomy; Magnetic resonance imaging; Medicine; Radiology; Epilepsy","score_opus":0.029399449068715416,"score_gpt":0.35335782232605056,"score_spread":0.3239583732573351,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147009297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.69328326,0.0011350684,0.23459989,0.056072544,0.00003756254,0.00086223,0.0000021023827,0.0006300981,0.0133772595],"genre_scores_gemma":[0.9862199,0.00001267206,0.007803143,0.0054933606,0.000043118296,0.000008114575,0.000008351374,0.0000056434706,0.00040571514],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99967915,0.00000632835,0.00007581874,0.0000987233,0.000038532802,0.00010145811],"domain_scores_gemma":[0.99978554,0.000015631907,0.00001472815,0.00015189638,0.0000049353675,0.000027289036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048319787,0.000041052022,0.00006655958,0.00003572009,0.000013587143,0.0000036029064,0.000034425102,0.000018411345,0.00002150235],"category_scores_gemma":[0.00002040245,0.000038366827,0.000018324332,0.00012549997,0.000009098515,0.000017905575,0.000008033646,0.000085085405,0.000007242126],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011185258,0.001039468,0.06938989,0.000055026347,0.00003105051,0.000778708,0.0008123301,0.00059416995,0.1874795,0.03655287,0.124915905,0.57823926],"study_design_scores_gemma":[0.0019920913,0.00030571187,0.87601596,0.00022571339,0.00005359821,0.000164062,0.00009836141,0.019717982,0.005911244,0.008605605,0.086574815,0.00033486087],"about_ca_topic_score_codex":0.0000056198023,"about_ca_topic_score_gemma":0.0000029033613,"teacher_disagreement_score":0.8066261,"about_ca_system_score_codex":0.00000864808,"about_ca_system_score_gemma":0.0000051117436,"threshold_uncertainty_score":0.15645538},"labels":[],"label_agreement":null},{"id":"W2147493105","doi":"10.1186/1471-2377-6-21","title":"Intrahemispheric dysfunction in primary motor cortex without corpus callosum: a transcranial magnetic stimulation study","year":2006,"lang":"en","type":"article","venue":"BMC Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Transcranial magnetic stimulation; Silent period; Primary motor cortex; Motor cortex; Neuroscience; Psychology; Evoked potential; Inhibitory postsynaptic potential; Pyramidal tracts; Cortex (anatomy); Stimulation; Medicine; Audiology","score_opus":0.026072855804647854,"score_gpt":0.2902690699066231,"score_spread":0.26419621410197525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147493105","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791808,0.000042708492,0.018078111,0.00033092368,0.00008153761,0.0015475174,0.0000037356506,0.000254661,0.0004799714],"genre_scores_gemma":[0.99524575,0.00000863011,0.0033592395,0.00069634925,0.0001284622,0.00023657252,0.000027947879,0.000035733276,0.00026128194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879813,0.000073223404,0.00033529315,0.00042797698,0.0001429754,0.00022237845],"domain_scores_gemma":[0.99946636,0.00006747042,0.00007465067,0.00030433582,0.00003949542,0.000047680645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007244128,0.0001561595,0.00027007065,0.0000949197,0.000043415614,0.000006734665,0.000074551004,0.000073341624,0.000035891255],"category_scores_gemma":[0.000018298053,0.00015700344,0.000047408466,0.00025081626,0.000068689675,0.00004676492,0.000019982372,0.00027974902,0.000009864078],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001329812,0.0010525315,0.842609,0.00003200388,0.0000024209298,0.00007508554,0.000020107595,0.00027764626,0.15134732,0.00004482626,0.00008742269,0.0031218436],"study_design_scores_gemma":[0.0030947372,0.0021201074,0.9886935,0.0000053386866,0.000059179445,0.00014838514,0.0000023393284,0.0045889956,0.00009012596,0.00044093656,0.00064684346,0.000109538974],"about_ca_topic_score_codex":0.00015209078,"about_ca_topic_score_gemma":0.00015878401,"teacher_disagreement_score":0.15125719,"about_ca_system_score_codex":0.000038111586,"about_ca_system_score_gemma":0.000049437014,"threshold_uncertainty_score":0.64024144},"labels":[],"label_agreement":null},{"id":"W2147598339","doi":"10.1117/12.710417","title":"Tensor dissimilarity based adaptive seeding algorithm for DT-MRI visualization with streamtubes","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Seeding; Visualization; Diffusion MRI; Computer science; Tensor (intrinsic definition); Structure tensor; Artificial intelligence; Orientation (vector space); Algorithm; Computer vision; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Image (mathematics); Physics; Geometry","score_opus":0.026369610051325185,"score_gpt":0.2991909955680276,"score_spread":0.2728213855167024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147598339","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9001193,0.000031964155,0.09477631,0.0023462842,0.00006235946,0.0015428601,0.00011738132,0.00022592246,0.00077764364],"genre_scores_gemma":[0.18545327,0.000032171476,0.81337696,0.00024685462,0.00034914108,0.00029543924,0.000036940077,0.00008831181,0.00012089925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99800265,9.494855e-9,0.00057108887,0.00045057974,0.00057040376,0.00040526324],"domain_scores_gemma":[0.9968947,0.0002175473,0.00035239232,0.00007068347,0.0023064325,0.00015823275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005359874,0.0003124931,0.00041655768,0.00013195995,0.00013031773,0.000053156306,0.00038382525,0.00015752352,0.0000046609466],"category_scores_gemma":[0.00029888866,0.00024387543,0.00042822366,0.0004037333,0.00023326221,0.00032835788,0.00006733853,0.00026695558,2.4043575e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00087043404,0.0006078366,0.0026885038,0.0008196431,0.00051610207,4.672028e-7,0.00016414131,0.00014327178,0.43804583,0.5489814,0.0028830157,0.0042793443],"study_design_scores_gemma":[0.0038005644,0.0021022821,0.0055634123,0.0010633474,0.0006906588,0.00005478052,0.0018146891,0.42085996,0.55366707,0.002215697,0.0074800067,0.00068753003],"about_ca_topic_score_codex":0.0000050659023,"about_ca_topic_score_gemma":1.420791e-7,"teacher_disagreement_score":0.7186007,"about_ca_system_score_codex":0.00017845725,"about_ca_system_score_gemma":0.000045595385,"threshold_uncertainty_score":0.99449515},"labels":[],"label_agreement":null},{"id":"W2147829144","doi":"10.1503/jpn.110132","title":"Impaired interhemispheric connectivity in medication-naive patients with major depressive disorder","year":2012,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health","keywords":"Fractional anisotropy; Major depressive disorder; Corpus callosum; Diffusion MRI; Psychology; Internal medicine; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology; Amygdala","score_opus":0.018805148923943193,"score_gpt":0.31266258975702876,"score_spread":0.29385744083308557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147829144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98766804,0.00023992066,0.009640661,0.0020525542,0.0001872293,0.00014206121,0.0000017957016,0.0000101985015,0.000057557096],"genre_scores_gemma":[0.99437904,0.00006688945,0.004841753,0.00063619844,0.000052452186,0.000005779579,3.4892804e-7,0.0000063374114,0.0000111695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993736,0.000020818341,0.00018618586,0.00011555773,0.00016615208,0.00013766],"domain_scores_gemma":[0.99943805,0.000036980113,0.00022213481,0.00011244765,0.00005643003,0.00013396524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011074009,0.00007251502,0.00012953635,0.00005764433,0.00006285619,0.000007747481,0.00008274822,0.0000195876,0.0000048220595],"category_scores_gemma":[0.00009513234,0.00004938243,0.000024275574,0.00022691376,0.0001229709,0.00028313824,0.000024116047,0.00019561795,2.4094078e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080636426,0.0004301642,0.9970747,0.000013733166,0.0000014810275,0.0000014093285,0.000051251405,0.000003158215,0.0010934494,0.00015870635,0.00010594826,0.0009853133],"study_design_scores_gemma":[0.0009881665,0.00032805285,0.9971385,0.00008313614,0.000020666237,0.00013489259,0.000034408524,0.00006403556,0.00034767934,0.00031578387,0.0004900419,0.000054608507],"about_ca_topic_score_codex":0.0000026875573,"about_ca_topic_score_gemma":0.0000020355142,"teacher_disagreement_score":0.0067110495,"about_ca_system_score_codex":0.000012699875,"about_ca_system_score_gemma":0.000052494543,"threshold_uncertainty_score":0.20137571},"labels":[],"label_agreement":null},{"id":"W2147848903","doi":"10.1002/hbm.20739","title":"Probabilistic topography of human corpus callosum using cytoarchitectural parcellation and high angular resolution diffusion imaging tractography","year":2009,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":188,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Science Council","keywords":"Tractography; Corpus callosum; Diffusion MRI; Neuroscience; Population; Somatosensory system; Artificial intelligence; Computer science; Psychology; Pattern recognition (psychology); Computer vision; Cartography; Magnetic resonance imaging; Medicine; Geography","score_opus":0.055970219345086614,"score_gpt":0.3309406591190847,"score_spread":0.2749704397739981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147848903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9585142,0.00014093895,0.03928417,0.0010465448,0.000013632741,0.0005883368,0.000004178452,0.00019289996,0.00021506585],"genre_scores_gemma":[0.9878745,0.000007772239,0.011642552,0.00030357274,0.00007475961,0.00000915463,0.00005388583,0.000019244757,0.00001456515],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988362,0.000048136124,0.00035351558,0.0003505317,0.00018242073,0.00022917383],"domain_scores_gemma":[0.99930394,0.00004752341,0.00019373898,0.00030490314,0.000071068,0.00007883776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016264549,0.0001729459,0.00025736797,0.00038686526,0.00037222495,0.00002305786,0.00006982487,0.000046766738,0.000006862888],"category_scores_gemma":[0.00003211942,0.00016756277,0.00010271012,0.00035797787,0.00020341584,0.000078730765,0.00003380484,0.00020426868,1.3415962e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014788445,0.00008377951,0.01356772,0.00007959853,0.000006555216,0.00000713131,0.0002904113,0.000049483668,0.97480273,0.00700909,0.00003868255,0.004050029],"study_design_scores_gemma":[0.0009934417,0.00027233435,0.91295606,0.0005307336,0.000081713726,0.00009749624,0.00009816104,0.009072005,0.0024875621,0.07246079,0.0006445597,0.000305122],"about_ca_topic_score_codex":0.000082968705,"about_ca_topic_score_gemma":0.0000043118066,"teacher_disagreement_score":0.9723152,"about_ca_system_score_codex":0.000034658613,"about_ca_system_score_gemma":0.000008888073,"threshold_uncertainty_score":0.68330115},"labels":[],"label_agreement":null},{"id":"W2147896272","doi":"10.1111/jgs.13644","title":"Resistance Training and White Matter Lesion Progression in Older Women: Exploratory Analysis of a 12‐Month Randomized Controlled Trial","year":2015,"lang":"en","type":"article","venue":"Journal of the American Geriatrics Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"Canadian Institutes of Health Research; Vancouver Foundation","keywords":"Medicine; Randomized controlled trial; Hyperintensity; Magnetic resonance imaging; Internal medicine; Physical therapy; Radiology","score_opus":0.047272915626346584,"score_gpt":0.3483704515841584,"score_spread":0.30109753595781186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147896272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896733,0.00042096234,0.005579171,0.0030762784,0.000058942373,0.0010952442,0.0000026115615,0.0000106882835,0.00008276692],"genre_scores_gemma":[0.97796094,0.00052084017,0.020587953,0.0006088353,0.00008895046,0.000101570346,6.7486536e-7,0.000014711444,0.00011551224],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9982961,0.0002649603,0.0007785051,0.00013214367,0.00037770774,0.00015059262],"domain_scores_gemma":[0.99732774,0.00026710916,0.0018954139,0.00022646607,0.00017552136,0.00010772175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020621826,0.00011577312,0.001588119,0.00016420189,0.00004157329,0.000013076974,0.00012310027,0.00003238736,0.0000046386926],"category_scores_gemma":[0.00031127382,0.00006611354,0.0006466527,0.001008826,0.00026367191,0.00007618133,0.000049175243,0.00025773243,7.4221575e-8],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.9422877,0.00060320727,0.02713737,0.000049624738,0.001108125,0.000009164005,0.018939812,0.0002514671,0.0015786678,0.00002230251,0.006599375,0.0014131764],"study_design_scores_gemma":[0.9755274,0.0004682192,0.012171062,0.00014615977,0.0021382526,0.000013380573,0.006458358,0.0017116093,0.00007030714,0.00060225424,0.0005332828,0.00015971683],"about_ca_topic_score_codex":0.0000020290138,"about_ca_topic_score_gemma":7.9599147e-7,"teacher_disagreement_score":0.03323969,"about_ca_system_score_codex":0.00012763664,"about_ca_system_score_gemma":0.00016268062,"threshold_uncertainty_score":0.2696032},"labels":[],"label_agreement":null},{"id":"W2148466603","doi":"10.1002/mds.25820","title":"Patterns of cortical thinning in idiopathic rapid eye movement sleep behavior disorder","year":2014,"lang":"en","type":"article","venue":"Movement Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal General Hospital; Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Institut Universitaire de Gériatrie de Montréal; Université du Québec à Montréal","funders":"Canadian Institutes of Health Research","keywords":"White matter; REM sleep behavior disorder; Parasomnia; Lingual gyrus; Psychology; Rapid eye movement sleep; Diffusion MRI; Polysomnography; Dementia with Lewy bodies; Neuroscience; Magnetic resonance imaging; Dementia; Eye movement; Medicine; Pathology; Electroencephalography; Functional magnetic resonance imaging; Disease; Radiology","score_opus":0.022996424498755066,"score_gpt":0.31647922209112866,"score_spread":0.2934827975923736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148466603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9095368,0.0001343281,0.08419157,0.0039921226,0.000053099433,0.001024939,0.000009548976,0.0001315297,0.0009261038],"genre_scores_gemma":[0.9929001,0.0001684619,0.0015902,0.0047791693,0.000021124823,0.00039079148,0.000023053955,0.00003568633,0.0000914265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99855936,0.000043335676,0.00046701467,0.0003397603,0.00029398446,0.00029652542],"domain_scores_gemma":[0.99927676,0.00003061638,0.0001194607,0.00045648735,0.000035771045,0.000080905986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023102222,0.0001782234,0.0002993644,0.00012954496,0.00005749308,0.000007974192,0.00013314461,0.000054029904,0.000091347436],"category_scores_gemma":[0.000052312113,0.0001689414,0.00009503467,0.00017966685,0.000056132645,0.000057452602,0.000090912814,0.00026296888,0.0000045543507],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003416544,0.0010592015,0.9427744,0.000093300616,0.000011960556,0.0000030916126,0.00016199483,0.000091546324,0.009868225,0.004861414,0.00008208062,0.04095862],"study_design_scores_gemma":[0.0018524815,0.00051338424,0.97432524,0.00018582515,0.00007343492,1.9423724e-7,0.00036970567,0.0042198086,0.00418451,0.012226581,0.001797982,0.0002508599],"about_ca_topic_score_codex":0.00014534933,"about_ca_topic_score_gemma":0.000056942463,"teacher_disagreement_score":0.083363324,"about_ca_system_score_codex":0.00005518138,"about_ca_system_score_gemma":0.000014640396,"threshold_uncertainty_score":0.68892306},"labels":[],"label_agreement":null},{"id":"W2148828979","doi":"10.1016/j.neuroimage.2007.12.035","title":"Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1889,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute on Aging; University of California, Los Angeles; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Johns Hopkins University","keywords":"White matter; Diffusion MRI; Atlas (anatomy); Brain atlas; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Orientation (vector space); Magnetic resonance imaging; Medicine; Mathematics; Anatomy; Radiology","score_opus":0.060239750217129635,"score_gpt":0.3295501962829788,"score_spread":0.2693104460658492,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148828979","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98673546,0.000007749629,0.00237723,0.0053139688,0.000042258795,0.00053616415,0.000013697801,0.0003273402,0.004646151],"genre_scores_gemma":[0.9846928,0.00001494355,0.0056563797,0.008374874,0.00006279964,0.000060873943,0.00003115562,0.00007449905,0.0010316847],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856454,0.000054996803,0.00027479796,0.0005559643,0.0002287848,0.0003209218],"domain_scores_gemma":[0.9989091,0.00005073449,0.000077716766,0.00078005966,0.00004355122,0.00013879992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060349765,0.00021789965,0.00023473566,0.0002481621,0.00013017222,0.000021179994,0.00014629697,0.000036873378,0.00017598132],"category_scores_gemma":[0.000024021161,0.0001980341,0.000072060364,0.0002629392,0.000101208396,0.00016356574,0.000051633702,0.00038245769,0.000175911],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011689196,0.0003593562,0.9546696,0.00001961075,5.951748e-7,0.00056653883,0.000045063938,0.000043098204,0.040014815,0.000009795258,0.0031731515,0.000981484],"study_design_scores_gemma":[0.0010538725,0.0001724869,0.9792202,0.000072155955,0.000010283642,0.00026282662,0.0000063741086,0.011617519,0.0018772781,0.000056755096,0.0054620034,0.000188239],"about_ca_topic_score_codex":0.000012672036,"about_ca_topic_score_gemma":0.0000019345857,"teacher_disagreement_score":0.038137536,"about_ca_system_score_codex":0.00004127678,"about_ca_system_score_gemma":0.000024664012,"threshold_uncertainty_score":0.80755967},"labels":[],"label_agreement":null},{"id":"W2149314739","doi":"10.1016/j.media.2006.06.009","title":"3D curve inference for diffusion MRI regularization and fibre tractography☆","year":2006,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Tractography; Regularization (linguistics); Diffusion MRI; Inference; Artificial intelligence; Computer science; Mathematics; Pattern recognition (psychology); Magnetic resonance imaging; Medicine; Radiology","score_opus":0.019148141866167187,"score_gpt":0.3437552625796552,"score_spread":0.324607120713488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149314739","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03584045,0.000097905286,0.95826185,0.004895807,0.000006619108,0.00025440648,0.000016388407,0.00013139042,0.00049520854],"genre_scores_gemma":[0.875179,0.00032837057,0.12197487,0.0007405258,0.00013870095,0.0001102177,0.0006094702,0.000020588492,0.0008982404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904054,0.00001750873,0.00023576687,0.00028971772,0.00026984533,0.00014663076],"domain_scores_gemma":[0.9993047,0.00012886745,0.00007503729,0.00025689867,0.000110202105,0.0001242798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000136272,0.000101976286,0.00025462234,0.00021300839,0.00009694041,0.000023085391,0.00006611558,0.00007885619,0.00011286941],"category_scores_gemma":[0.00022540115,0.000083169165,0.00014757227,0.0007940628,0.00013995603,0.00007870367,0.0000334864,0.0001230022,0.0000014401666],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002538866,0.0024832375,0.5430996,0.00053313695,0.0010239185,0.00014516531,0.00020464872,0.00008926561,0.13374206,0.014565481,0.022881314,0.28097832],"study_design_scores_gemma":[0.00288384,0.00035595434,0.51853704,0.00019221618,0.005965773,0.000052012485,0.00005230208,0.3808227,0.010679129,0.026578112,0.053223845,0.0006570852],"about_ca_topic_score_codex":0.00006142188,"about_ca_topic_score_gemma":0.000016545308,"teacher_disagreement_score":0.83933854,"about_ca_system_score_codex":0.0000112009175,"about_ca_system_score_gemma":0.000023110131,"threshold_uncertainty_score":0.339154},"labels":[],"label_agreement":null},{"id":"W2149542669","doi":"10.1109/isbi.2011.5872557","title":"Exact integration of diffusion orientation distribution functions for graph-based diffusion MRI analysis","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Graph; Weighting; Diffusion MRI; Weight function; Numerical integration; Algorithm; Applied mathematics; Computer science; Numerical analysis; Tractography; Probabilistic logic; Mathematical optimization; Mathematics; Theoretical computer science; Mathematical analysis; Artificial intelligence","score_opus":0.06433255133012311,"score_gpt":0.34262245062817825,"score_spread":0.27828989929805514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149542669","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18491215,0.000005186719,0.8136048,0.00023655346,0.000028247574,0.0005637051,0.00008394217,0.00014551339,0.00041996382],"genre_scores_gemma":[0.9475118,0.000020491661,0.0494914,0.00007946058,0.00001864368,0.0001869075,0.0024054921,0.000010950301,0.00027488678],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992128,0.00001531178,0.00028494716,0.00024503443,0.0001335674,0.00010836055],"domain_scores_gemma":[0.99916893,0.000051074356,0.000154526,0.0003155785,0.00025072627,0.00005913604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008740882,0.00010431391,0.00019174741,0.00022227978,0.000112689886,0.0000048080815,0.000045323643,0.00005405596,0.000118442375],"category_scores_gemma":[0.00005365028,0.00008299933,0.00021615814,0.00085193553,0.000053241554,0.000081795755,0.000012636799,0.00006646711,0.00000192755],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018614443,0.004452904,0.18555138,0.00020967156,0.00035096298,0.0000020757082,0.0005220995,0.00021981173,0.6888567,0.057821177,0.005330246,0.054821536],"study_design_scores_gemma":[0.0026330359,0.0012954517,0.54631937,0.000095999276,0.0031249712,0.0000044790186,0.000430361,0.10209485,0.33186376,0.0076988214,0.0040852814,0.00035362292],"about_ca_topic_score_codex":0.000099566685,"about_ca_topic_score_gemma":0.000023939758,"teacher_disagreement_score":0.76411337,"about_ca_system_score_codex":0.000043656808,"about_ca_system_score_gemma":0.00002016686,"threshold_uncertainty_score":0.33846143},"labels":[],"label_agreement":null},{"id":"W2150163312","doi":"10.1093/brain/awh454","title":"Diffusion-weighted and perfusion MRI demonstrates parenchymal changes in complex partial status epilepticus","year":2005,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":331,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Toronto","keywords":"Status epilepticus; Ictal; Effective diffusion coefficient; Epilepsy; Perfusion; Medicine; Magnetic resonance imaging; Nuclear medicine; Hippocampal formation; Thalamus; Diffusion MRI; Cortex (anatomy); Radiology; Psychology; Neuroscience; Internal medicine","score_opus":0.05183154374311538,"score_gpt":0.33663910558971083,"score_spread":0.28480756184659545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150163312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9682332,0.00015599986,0.0020282771,0.028249592,0.000010782366,0.00042144518,0.000018213523,0.00015477584,0.0007276912],"genre_scores_gemma":[0.97707164,0.00034834826,0.020673338,0.0014660707,0.00012157113,0.000058530142,0.00006294382,0.000015107127,0.00018245494],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99921995,0.000024839524,0.00015556577,0.0002484748,0.00010042093,0.00025075636],"domain_scores_gemma":[0.99955815,0.00008171428,0.000041476233,0.00017493602,0.000021534952,0.00012219812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000649259,0.000111804286,0.00016605142,0.000082154045,0.00007325394,0.000012355528,0.000041639225,0.00004625924,0.0001426231],"category_scores_gemma":[0.000038508122,0.00009604531,0.000019684961,0.00014148123,0.00009211073,0.00004224632,0.00005446677,0.00013945522,0.000009300481],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020215644,0.0006891247,0.16896892,0.000051961604,0.00000792963,0.00006104488,0.00076689274,0.000010545348,0.43884376,0.003949966,0.013865495,0.3725822],"study_design_scores_gemma":[0.0030716613,0.0004825101,0.54289854,0.00015165716,0.000035202982,0.00015866135,0.00023348905,0.041910257,0.0190457,0.0017014839,0.3899011,0.00040977032],"about_ca_topic_score_codex":0.000033740605,"about_ca_topic_score_gemma":0.00011347294,"teacher_disagreement_score":0.41979808,"about_ca_system_score_codex":0.000029176716,"about_ca_system_score_gemma":0.000020772808,"threshold_uncertainty_score":0.3916614},"labels":[],"label_agreement":null},{"id":"W2150217906","doi":"10.1007/978-3-540-69960-6_37","title":"BrainLab Image Guided System","year":2009,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Vendor; Frame (networking); Neurosurgery; Medical physics; Computer science; Field (mathematics); Medicine; Radiology","score_opus":0.08059601785721211,"score_gpt":0.3538708462215804,"score_spread":0.2732748283643683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150217906","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000016734065,0.00010390875,0.017073426,0.0024210773,0.000024230698,0.00065406103,0.00001651721,0.0013055176,0.9783996],"genre_scores_gemma":[0.00036587263,0.000101882346,0.06620599,0.0019577825,0.0002119051,0.000018944766,0.00006694664,0.00007460525,0.93099606],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99899876,0.000002410937,0.00029830073,0.00037019534,0.00017976313,0.00015057079],"domain_scores_gemma":[0.9988888,0.000019562973,0.000119056276,0.0007441403,0.00011849278,0.00010995596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046965222,0.00024521528,0.00037893362,0.00010069673,0.00004799275,0.000013177539,0.00011265419,0.00015868105,0.00034753213],"category_scores_gemma":[0.000009668882,0.00020971446,0.00015684114,0.000021760989,0.00005503454,0.000028233278,0.000041865456,0.00030305883,0.00045131875],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071529157,0.000014072505,0.000001156431,0.00013361903,0.000017393992,0.0001331482,0.0000028643235,9.0200594e-8,0.0011338259,0.8235646,0.15837406,0.016618038],"study_design_scores_gemma":[0.00022253071,0.00006192117,0.000018341863,0.00041729986,0.00010328786,0.00050644844,0.0000021625044,0.000044725497,0.00065044063,0.014022597,0.9837363,0.00021394971],"about_ca_topic_score_codex":0.0000028742168,"about_ca_topic_score_gemma":2.1395724e-7,"teacher_disagreement_score":0.8253622,"about_ca_system_score_codex":0.00010970624,"about_ca_system_score_gemma":0.00004526765,"threshold_uncertainty_score":0.85519075},"labels":[],"label_agreement":null},{"id":"W2150270487","doi":"10.1161/strokeaha.108.529958","title":"Corticospinal Tract Pre-Wallerian Degeneration","year":2009,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Medicine; Hemiparesis; Corticospinal tract; Cerebral peduncle; Stroke (engine); Wallerian degeneration; Abnormality; Diffusion MRI; Pediatric stroke; Physical medicine and rehabilitation; Cardiology; Radiology; Magnetic resonance imaging; Internal capsule; Ischemia; Ischemic stroke; Pathology; Angiography; Psychiatry","score_opus":0.05426073657291517,"score_gpt":0.3636700214783051,"score_spread":0.30940928490538994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150270487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8818246,0.00010120168,0.096957244,0.0076179095,0.000045296463,0.00045832564,0.00001096599,0.00040311637,0.012581305],"genre_scores_gemma":[0.97237265,0.000030083156,0.024801731,0.00094511645,0.00012187187,0.00001623314,0.000019329724,0.000006801726,0.0016861603],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99957037,0.0000042559027,0.00010528099,0.00013215705,0.00008386659,0.000104060215],"domain_scores_gemma":[0.9996866,0.000004094494,0.000031847238,0.00019173896,0.000027975278,0.000057768342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022390126,0.00005934307,0.0000789018,0.000026744676,0.000050013874,0.00000954678,0.000035483485,0.000023866856,0.00003852405],"category_scores_gemma":[0.000014535477,0.000054283406,0.000036810987,0.000052136656,0.0000144545265,0.0000448959,0.0000044974645,0.00008909465,0.0000115688035],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103231054,0.00046404803,0.005143174,0.000010458762,0.00000731596,0.00003237887,0.000060557297,0.000033923985,0.8076938,0.012373189,0.0024959652,0.17158201],"study_design_scores_gemma":[0.00088706653,0.0012795407,0.7767211,0.00003797053,0.000066177585,0.00021158827,0.000013379985,0.0015077506,0.1140082,0.0032128717,0.10184321,0.00021110862],"about_ca_topic_score_codex":0.0000018082795,"about_ca_topic_score_gemma":4.1749968e-7,"teacher_disagreement_score":0.77157795,"about_ca_system_score_codex":0.000019156125,"about_ca_system_score_gemma":0.000019097299,"threshold_uncertainty_score":0.22136131},"labels":[],"label_agreement":null},{"id":"W2150487281","doi":"10.1684/epd.2012.0547","title":"White matter abnormalities revealed by DTI correlate with interictal grey matter FDG‐PET metabolism in focal childhood epilepsies","year":2012,"lang":"en","type":"article","venue":"Epileptic Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Fondation Pierre Deniker pour la Recherche et la Prévention en Santé Mentale","keywords":"White matter; Grey matter; Diffusion MRI; Fractional anisotropy; Ictal; Effective diffusion coefficient; Epilepsy; Psychology; Magnetic resonance imaging; Pathology; Medicine; Nuclear medicine; Neuroscience; Radiology","score_opus":0.011589455473755474,"score_gpt":0.2632453850574837,"score_spread":0.25165592958372823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150487281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96348566,0.00049328944,0.0069326838,0.009372411,0.00017704019,0.0010426744,0.00006147096,0.0002596336,0.018175125],"genre_scores_gemma":[0.98631227,0.00012390126,0.005004706,0.0045052734,0.00008008172,0.00031838662,0.00010634168,0.00008747237,0.0034615726],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99831355,0.000057957357,0.0004136246,0.00036503843,0.00021990972,0.0006299224],"domain_scores_gemma":[0.9991185,0.000056901292,0.00013304868,0.0004789642,0.000034229055,0.00017834731],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001406527,0.00032455102,0.00044661853,0.00015638614,0.00008441644,0.000032069423,0.00016803782,0.000064316846,0.0012603039],"category_scores_gemma":[0.000017837874,0.000266628,0.00010155246,0.00027649407,0.0002396386,0.00040569453,0.00009325692,0.00044608326,0.0004207199],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085009655,0.00047552068,0.95340395,0.00005676157,0.00004001215,0.000006597906,0.0011854781,0.0000076283964,0.000056721274,0.00031698917,0.043483846,0.00088147825],"study_design_scores_gemma":[0.0012673419,0.000107288986,0.9747557,0.00014585859,0.000098701,0.00016771896,0.00055339443,0.00005038333,0.000030798034,0.00064551464,0.021828474,0.00034880705],"about_ca_topic_score_codex":0.00005620206,"about_ca_topic_score_gemma":0.000016478903,"teacher_disagreement_score":0.022826593,"about_ca_system_score_codex":0.000042364794,"about_ca_system_score_gemma":0.000021857632,"threshold_uncertainty_score":0.9999786},"labels":[],"label_agreement":null},{"id":"W2150737561","doi":"10.1017/s0317167100004479","title":"Diffusion Tensor Imaging Abnormalities in Focal Cortical Dysplasia","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Alberta","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Cortical dysplasia; Hyperintensity; Magnetic resonance imaging; Medicine; Effective diffusion coefficient; Nuclear medicine; Lesion; Pathology; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.05064500833068652,"score_gpt":0.3202816174225774,"score_spread":0.26963660909189086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150737561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9761816,0.00065134256,0.00022990075,0.019687854,0.00021105436,0.00018434512,0.0000053708427,0.000034440047,0.0028140822],"genre_scores_gemma":[0.9824616,0.00032193374,0.010172909,0.0066896426,0.00029743978,0.000004389401,2.94087e-7,0.000013105515,0.000038737846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9963271,0.0004018666,0.00094228104,0.0004762588,0.0006296244,0.0012228474],"domain_scores_gemma":[0.99710804,0.0004395902,0.0004292964,0.00016148004,0.00029716195,0.0015644308],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.002311492,0.00028075083,0.00048716943,0.0010183932,0.0015511721,0.0003116531,0.0010155931,0.00011694913,0.00013960557],"category_scores_gemma":[0.0015746141,0.00019299785,0.00019724229,0.001086452,0.0052314103,0.0008757107,0.000067895126,0.0016462049,0.000004430088],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073113144,0.000055104196,0.98513305,0.0000047251688,0.0000028809488,0.0041653705,0.00015771655,0.0007600037,0.00011509694,0.0018002033,0.0004920054,0.007240715],"study_design_scores_gemma":[0.000686507,0.022124214,0.84965706,0.00010349843,0.00004500959,0.08968324,0.00031099305,0.009776165,0.000200151,0.012401208,0.014638399,0.00037356425],"about_ca_topic_score_codex":0.00047235837,"about_ca_topic_score_gemma":0.013863456,"teacher_disagreement_score":0.13547601,"about_ca_system_score_codex":0.00029714633,"about_ca_system_score_gemma":0.0017471634,"threshold_uncertainty_score":0.99974865},"labels":[],"label_agreement":null},{"id":"W2151033012","doi":"10.1007/s00429-014-0956-9","title":"Puberty and testosterone shape the corticospinal tract during male adolescence","year":2014,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Université du Québec à Chicoutimi; Cégep de Jonquière; University of Toronto; Montreal Neurological Institute and Hospital; University of Calgary; McGill University; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"Testosterone (patch); White matter; Psychology; Mediation; Internal medicine; Young adult; Developmental psychology; Endocrinology; Physiology; Biology; Magnetic resonance imaging; Medicine","score_opus":0.021608274228481706,"score_gpt":0.27129703040430697,"score_spread":0.24968875617582525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151033012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98803955,0.0001254459,0.0072297277,0.004102216,0.000034151195,0.00020144056,0.000002739782,0.000065063294,0.00019967806],"genre_scores_gemma":[0.99701387,0.000028111743,0.00091782404,0.0016399866,0.00013312724,0.000009008003,0.0000055458995,0.00000881429,0.00024373262],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995697,0.000012033581,0.000083461295,0.0001763379,0.00006548296,0.000092959184],"domain_scores_gemma":[0.9997069,0.000035389297,0.000039510727,0.0001519776,0.000018965377,0.000047227917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040007235,0.00007647124,0.00008134968,0.000019701978,0.0001512253,0.000019241765,0.0000242258,0.0000339785,0.000027109696],"category_scores_gemma":[0.000044416345,0.000049074988,0.000013229256,0.00005879844,0.00007349806,0.000058673984,0.000021777352,0.0001473007,7.4806854e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028396267,0.00005430271,0.1925874,0.00019979516,0.000015958045,0.0000069549483,0.00013442615,0.0000062069294,0.39980656,0.0026412886,0.0012675371,0.40299562],"study_design_scores_gemma":[0.00032202536,0.00015459358,0.9870537,0.000031442945,0.000032818458,0.0007211976,0.000014216591,0.00082465465,0.0009976629,0.0013088578,0.008477691,0.00006115372],"about_ca_topic_score_codex":0.0000032840887,"about_ca_topic_score_gemma":0.0000012574164,"teacher_disagreement_score":0.7944663,"about_ca_system_score_codex":0.0000060270836,"about_ca_system_score_gemma":0.000004545704,"threshold_uncertainty_score":0.200122},"labels":[],"label_agreement":null},{"id":"W2151048581","doi":"10.1074/jbc.m113.515445","title":"Extracellular Monomeric Tau Protein Is Sufficient to Initiate the Spread of Tau Protein Pathology","year":2014,"lang":"en","type":"article","venue":"Journal of Biological Chemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Occupational Cancer Research Centre","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Wellcome Trust","keywords":"Extracellular; Endogeny; Tau protein; Tau pathology; Fibril; Protein aggregation; In vivo; Biophysics; Cell biology; Chemistry; Biology; Neuroscience; Biochemistry; Alzheimer's disease; Pathology; Medicine; Disease; Genetics","score_opus":0.062232143607083124,"score_gpt":0.3219237744916447,"score_spread":0.2596916308845616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151048581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96360254,0.00025090677,0.031734306,0.0036274935,0.000010028751,0.0003743914,0.0000065996715,0.00002242973,0.00037129322],"genre_scores_gemma":[0.98878884,0.000024257162,0.010401458,0.00037491295,0.0001285238,0.000045285313,0.0000023109562,0.0000088283705,0.00022559594],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999021,0.000040384028,0.00045823815,0.00017126295,0.00013729617,0.00017183427],"domain_scores_gemma":[0.99899507,0.000052163567,0.00039406712,0.00029387357,0.00014791572,0.00011689044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035553335,0.00011871602,0.00031041732,0.000023725626,0.000040864863,0.0000056617046,0.000233529,0.000100768426,0.00008195837],"category_scores_gemma":[0.000347156,0.000065915076,0.00013179785,0.00015127791,0.00016720369,0.000016141712,0.000074617485,0.0003745988,0.000004463204],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082476836,0.00019086215,0.00041074597,0.000034693836,0.00000764691,0.000025490925,0.000031712796,0.0000065347626,0.996685,0.00014080829,0.00018427894,0.0021997225],"study_design_scores_gemma":[0.00028578515,0.00064377335,0.001416539,0.00011129599,0.000018568404,0.00030032036,0.00003947815,0.000043374475,0.9828966,0.0017993994,0.012361491,0.000083344356],"about_ca_topic_score_codex":0.000001476639,"about_ca_topic_score_gemma":1.7747919e-8,"teacher_disagreement_score":0.025186276,"about_ca_system_score_codex":0.000026393298,"about_ca_system_score_gemma":0.00003187723,"threshold_uncertainty_score":0.26879388},"labels":[],"label_agreement":null},{"id":"W2151103091","doi":"10.1109/tmi.2011.2111422","title":"Perception-Based Visualization of Manifold-Valued Medical Images Using Distance-Preserving Dimensionality Reduction","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; Johns Hopkins University","keywords":"Artificial intelligence; Pixel; Isomap; Mathematics; Nonlinear dimensionality reduction; Computer vision; Pattern recognition (psychology); Manifold (fluid mechanics); Euclidean distance; Similarity (geometry); Dimensionality reduction; Computer science; Image (mathematics)","score_opus":0.07963247697012278,"score_gpt":0.3814565320296012,"score_spread":0.30182405505947846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151103091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04140207,0.00003520152,0.9559763,0.0011805764,0.0002273578,0.00034208395,0.000014250053,0.00030606805,0.0005160582],"genre_scores_gemma":[0.9609873,0.0000637992,0.03814492,0.0005566723,0.00008328173,0.000046280467,0.000016859574,0.000046828398,0.000054052805],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973931,0.00011346965,0.0005827411,0.00045314684,0.0011839381,0.00027360333],"domain_scores_gemma":[0.9986902,0.00009016988,0.00015694556,0.00047029663,0.0002344668,0.0003579514],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00047992324,0.00020896916,0.00031698076,0.00022938616,0.0002477551,0.000010017142,0.00019501909,0.00012549292,0.002242617],"category_scores_gemma":[0.000118522934,0.00019621591,0.00017313269,0.00044072882,0.00033773496,0.00019502113,0.0000054839484,0.00046315792,0.000008409738],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034129615,0.01855537,0.026785266,0.0028267906,0.00053857156,0.00085607124,0.0027769934,0.0027210058,0.56015944,0.011656948,0.004070197,0.3656404],"study_design_scores_gemma":[0.0034775042,0.00024463594,0.0075419545,0.002823158,0.0005661083,0.0008002648,0.0006878067,0.7235201,0.25657246,0.002591755,0.00042574844,0.00074849534],"about_ca_topic_score_codex":0.0001942397,"about_ca_topic_score_gemma":0.0000032470525,"teacher_disagreement_score":0.9195852,"about_ca_system_score_codex":0.0001304871,"about_ca_system_score_gemma":0.00025506475,"threshold_uncertainty_score":0.99866945},"labels":[],"label_agreement":null},{"id":"W2151299940","doi":"10.1046/j.1528-1157.2003.55902.x","title":"Recurrent Nonstatus Generalized Seizures Alter the Developing Chicken Brain","year":2003,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Epilepsy; Magnetic resonance imaging; Psychology; Internal medicine; Medicine; Endocrinology; Neuroscience; Radiology","score_opus":0.07597483513792062,"score_gpt":0.37231616077027696,"score_spread":0.2963413256323563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151299940","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34212595,0.001912468,0.4519774,0.15824534,0.0006359921,0.0030697703,0.000032778687,0.0011958347,0.04080446],"genre_scores_gemma":[0.71073574,0.00057089527,0.2579385,0.02573087,0.00028385714,0.00040309358,0.00004814385,0.00008214232,0.004206783],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99916875,0.000061511804,0.00018460769,0.0002294308,0.00012835022,0.00022734393],"domain_scores_gemma":[0.9993397,0.00008953779,0.00005843877,0.00040317263,0.0000426998,0.00006642275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016003834,0.000120840436,0.00014568321,0.000038809296,0.00016006157,0.000017271135,0.00009841108,0.000033042244,0.00008379409],"category_scores_gemma":[0.00015597076,0.00008074455,0.00006351732,0.0001922174,0.0000710419,0.000034496803,0.000029738225,0.00021309829,0.00004156328],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008889651,0.00018855637,0.007191812,0.00006401501,0.00006974777,0.000072132934,0.000570944,0.000024053561,0.015245595,0.591857,0.3405326,0.044094644],"study_design_scores_gemma":[0.00049774157,0.000049123864,0.008431184,0.00005570853,0.000024527799,0.000200459,0.000022184766,0.00017513942,0.0074314354,0.009485125,0.9734778,0.00014958691],"about_ca_topic_score_codex":0.000005179439,"about_ca_topic_score_gemma":0.0000016237675,"teacher_disagreement_score":0.6329452,"about_ca_system_score_codex":0.000041460535,"about_ca_system_score_gemma":0.00007774347,"threshold_uncertainty_score":0.32926673},"labels":[],"label_agreement":null},{"id":"W2151907388","doi":"10.1038/mp.2012.188","title":"Elevated serum measures of lipid peroxidation and abnormal prefrontal white matter in euthymic bipolar adults: toward peripheral biomarkers of bipolar disorder","year":2013,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Center for Advancing Translational Sciences; Fogarty International Center; National Institute for Health and Care Research; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Fractional anisotropy; White matter; Bipolar disorder; Diffusion MRI; Psychology; Internal medicine; Lipid peroxidation; Analysis of variance; Biomarker; Endocrinology; Neuroscience; Medicine; Chemistry; Magnetic resonance imaging; Cognition; Oxidative stress; Biochemistry","score_opus":0.01313908495907106,"score_gpt":0.2599156324976838,"score_spread":0.24677654753861272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2151907388","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984915,0.0031648232,0.0080229025,0.0029906228,0.000056491244,0.0006998376,0.00002634667,0.000048219983,0.00007576576],"genre_scores_gemma":[0.98069584,0.00017638782,0.018565113,0.00038523757,0.000018843979,0.00006356742,0.000036771733,0.000036457324,0.000021767515],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989173,0.000045401317,0.00037296637,0.00028776235,0.00017954811,0.00019701557],"domain_scores_gemma":[0.9993745,0.0000053553736,0.00013983593,0.00032205842,0.000089038345,0.0000692093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006671424,0.0001677026,0.00024554238,0.00017202695,0.000025884043,0.000008800614,0.00009917852,0.000077084405,0.00011079247],"category_scores_gemma":[0.000010943097,0.00015737065,0.0000760067,0.00026209987,0.0001054263,0.00012758569,0.00004591912,0.0001610179,0.0000047001363],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000093269016,0.00019231404,0.8630491,0.00020340699,0.00003566642,0.0000010152569,0.00015509254,0.000009157995,0.13231447,0.00007046304,0.00024284986,0.0036332242],"study_design_scores_gemma":[0.0014357646,0.00023898859,0.98010945,0.0002501086,0.00004637035,0.000037201888,0.00035208193,0.00079412037,0.014935341,0.00026032736,0.0013420859,0.00019815871],"about_ca_topic_score_codex":0.00021202829,"about_ca_topic_score_gemma":0.00002369656,"teacher_disagreement_score":0.11737914,"about_ca_system_score_codex":0.000021617403,"about_ca_system_score_gemma":0.00004025266,"threshold_uncertainty_score":0.6417389},"labels":[],"label_agreement":null},{"id":"W2152024551","doi":"10.1139/jpn.0416","title":"Cotard’s syndrome with schizophreniform disorder can be successfully treated with electroconvulsive therapy: case report","year":2004,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Electroconvulsive therapy; Schizophreniform disorder; Medicine; Magnetic resonance imaging; Atrophy; Schizophrenia (object-oriented programming); Ventricle; Psychosis; Antipsychotic; Pediatrics; Psychiatry; Radiology; Cardiology; Internal medicine","score_opus":0.02057064078617056,"score_gpt":0.30333214825229476,"score_spread":0.2827615074661242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152024551","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9804009,0.00015480675,0.004637505,0.014394698,0.000045558605,0.0002689506,0.0000043911405,0.000036441044,0.00005673117],"genre_scores_gemma":[0.9884877,0.0002344859,0.009514337,0.0016442046,0.0000370364,0.000009138268,8.8928977e-7,0.000017790935,0.000054385564],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.999011,0.000011123724,0.0002690741,0.00025761596,0.00025156426,0.00019965577],"domain_scores_gemma":[0.9991014,0.000012470659,0.00034716123,0.00022337663,0.00013223931,0.00018336523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009297131,0.00015209621,0.00022962686,0.00011522209,0.0002216937,0.00003512006,0.000101341895,0.00002622727,0.0000025668305],"category_scores_gemma":[0.000015294732,0.00009095165,0.000042091393,0.00045105562,0.00023918408,0.00020522128,0.000012269098,0.0003239848,8.898929e-8],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0057758405,0.002896089,0.57560647,0.00015533075,0.00010446385,0.35923812,0.00028280576,0.0006151989,0.046016145,0.0065648146,0.0002508799,0.0024938562],"study_design_scores_gemma":[0.002453909,0.0058598476,0.03813056,0.00012469006,0.00006814167,0.9476422,0.000060698465,0.000013529459,0.003875001,0.00064134155,0.0009812064,0.0001488818],"about_ca_topic_score_codex":0.000051689658,"about_ca_topic_score_gemma":0.000071283226,"teacher_disagreement_score":0.58840406,"about_ca_system_score_codex":0.000021838574,"about_ca_system_score_gemma":0.00036056293,"threshold_uncertainty_score":0.37089005},"labels":[],"label_agreement":null},{"id":"W2152573143","doi":"10.1002/hbm.22877","title":"Age‐related changes in the topological organization of the white matter structural connectome across the human lifespan","year":2015,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":226,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Key Research and Development Program of China; National Science Fund for Distinguished Young Scholars; Fundamental Research Funds for the Central Universities; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Connectome; White matter; Neuroscience; Human brain; Psychology; Functional connectivity; Biology; Medicine; Magnetic resonance imaging","score_opus":0.10241650907414852,"score_gpt":0.3699829839895887,"score_spread":0.26756647491544017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152573143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9419439,0.000013602804,0.0002256163,0.05649637,0.00002787241,0.0005310636,0.0000036160304,0.00006798601,0.0006899786],"genre_scores_gemma":[0.9936161,8.5794795e-7,0.00012145628,0.005626831,0.00007691446,0.000025710326,0.000022193362,0.00001595439,0.0004939867],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991479,0.00012989476,0.00020802775,0.00017116521,0.00016405631,0.00017893894],"domain_scores_gemma":[0.99925363,0.000072861076,0.0001259617,0.0004537276,0.00006732179,0.000026473968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003621507,0.000103317194,0.00014529689,0.00003319314,0.000341625,0.000029659413,0.0003267711,0.000054867858,0.00008481845],"category_scores_gemma":[0.00013184095,0.000050613744,0.000033431956,0.00042648686,0.00029220013,0.00003352502,0.0001355631,0.00029572408,0.0000051173147],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000063782086,0.000070404676,0.7938964,0.00005629095,0.000023368762,0.000018752748,0.03400111,0.000051135954,0.12426286,0.037415855,0.010043458,0.00015403012],"study_design_scores_gemma":[0.00039005335,0.000034773817,0.9824963,0.00005435026,0.000010117881,0.0000587982,0.002467955,0.000040114362,0.0003756102,0.011626162,0.0023688928,0.00007683323],"about_ca_topic_score_codex":0.00001885556,"about_ca_topic_score_gemma":0.00003915096,"teacher_disagreement_score":0.18859999,"about_ca_system_score_codex":0.000031104293,"about_ca_system_score_gemma":0.000009626949,"threshold_uncertainty_score":0.2627538},"labels":[],"label_agreement":null},{"id":"W2153291416","doi":"10.1109/fbit.2007.52","title":"Brain Differences Visualized in the Blind Using Tensor Manifold Statistics and Diffusion Tensor Imaging","year":2007,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Diffusion MRI; Fractional anisotropy; Tensor (intrinsic definition); Geodesic; Cartesian tensor; Mathematics; Scalar (mathematics); Tensor density; Symmetric tensor; Tensor field; Univariate; Euclidean distance; Manifold (fluid mechanics); Riemannian manifold; Metric (unit); Mathematical analysis; Artificial intelligence; Pattern recognition (psychology); Pure mathematics; Multivariate statistics; Statistics; Geometry; Computer science; Magnetic resonance imaging; Exact solutions in general relativity; Medicine","score_opus":0.09949310874390531,"score_gpt":0.4247981532152353,"score_spread":0.32530504447132996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153291416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7129353,0.00005024665,0.28286937,0.0029520844,0.000011707691,0.00043636153,0.0000075459557,0.00007640128,0.0006609604],"genre_scores_gemma":[0.90018755,0.000051625007,0.096411355,0.0029960861,0.000042095377,0.000009025913,0.000007569621,0.0000153762,0.00027932765],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991729,0.000024821435,0.00022392864,0.00021454813,0.00015844026,0.00020531754],"domain_scores_gemma":[0.9993012,0.00034912134,0.000057079254,0.00019924989,0.000039958308,0.0000534109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027247658,0.000111875815,0.00015494468,0.00010749314,0.00010369485,0.00002863316,0.00007301636,0.000025466146,0.000024818746],"category_scores_gemma":[0.0001051869,0.00006900249,0.000018727145,0.00018274579,0.0000738931,0.000043096974,0.000042960033,0.00015959065,0.0000014048688],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002837407,0.0004989457,0.80206084,0.00008664116,0.000010744379,0.00027717274,0.0008039896,9.606031e-7,0.11312521,0.047420666,0.002046285,0.033384793],"study_design_scores_gemma":[0.0025633082,0.00011098646,0.9505954,0.00012541823,0.000067515524,0.00045800663,0.0014207112,0.029404545,0.0014038961,0.0088165,0.0047632554,0.0002705061],"about_ca_topic_score_codex":0.000086852786,"about_ca_topic_score_gemma":0.00002077969,"teacher_disagreement_score":0.18725221,"about_ca_system_score_codex":0.000019477473,"about_ca_system_score_gemma":0.000011392348,"threshold_uncertainty_score":0.281384},"labels":[],"label_agreement":null},{"id":"W2153399392","doi":"10.1007/978-3-319-19992-4_5","title":"A Compressed-Sensing Approach for Super-Resolution Reconstruction of Diffusion MRI","year":2015,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Computer science; Compressed sensing; Diffusion; Computer vision; Artificial intelligence; Resolution (logic); Algorithm; Physics","score_opus":0.07223077402635684,"score_gpt":0.33255021830840115,"score_spread":0.2603194442820443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153399392","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06957772,0.000033081345,0.929243,0.000543696,0.0001055737,0.00040596744,0.0000015901542,0.0000642688,0.000025075504],"genre_scores_gemma":[0.4963589,0.0000022070808,0.50348586,0.00009519522,0.000046973513,0.0000043207688,0.0000028115267,0.000003428234,3.283805e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991914,0.00001224283,0.00016161056,0.0003027696,0.00017485097,0.00015714634],"domain_scores_gemma":[0.99935496,0.00006906567,0.000060895723,0.00026788795,0.00018424084,0.00006293134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022554913,0.00007541342,0.00014462436,0.00014736729,0.00007840124,0.000014366246,0.00011823765,0.00003707922,3.2806875e-7],"category_scores_gemma":[0.000100392455,0.000064310545,0.000029058303,0.00050058495,0.00026888333,0.000097062584,0.00007214881,0.00010479406,1.7969096e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100743404,0.00016383747,0.005081636,0.00008606569,0.000002857502,0.0000017806069,0.0007792068,0.07937158,0.13281253,0.00037311058,0.00005311045,0.7811735],"study_design_scores_gemma":[0.00040906816,0.00012740225,0.00064114085,0.000060574803,0.000005377388,0.00011100563,0.000002323608,0.94146234,0.050093707,0.0069460035,0.000077449884,0.000063601336],"about_ca_topic_score_codex":0.000020106912,"about_ca_topic_score_gemma":0.0000016186482,"teacher_disagreement_score":0.86209077,"about_ca_system_score_codex":0.00006670786,"about_ca_system_score_gemma":0.00007778562,"threshold_uncertainty_score":0.2622508},"labels":[],"label_agreement":null},{"id":"W2154288487","doi":"10.1016/j.neuroimage.2010.05.019","title":"Selective effects of aging on brain white matter microstructure: A diffusion tensor imaging tractography study","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Johns Hopkins University","keywords":"Diffusion MRI; Tractography; White matter; Psychology; Neuroscience; Nuclear magnetic resonance; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.010962183111987139,"score_gpt":0.30519724965844625,"score_spread":0.2942350665464591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154288487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99246955,0.000011156219,0.00098904,0.0039667254,0.0001247795,0.0013660182,0.000010330595,0.00022930048,0.00083309144],"genre_scores_gemma":[0.9922038,0.0000035399355,0.0031346933,0.0042782817,0.00007934099,0.00006708888,0.0000067300152,0.000068355104,0.00015817296],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986668,0.000054281336,0.00025405348,0.0005309286,0.0002246211,0.00026931096],"domain_scores_gemma":[0.99872106,0.0002807663,0.00014625971,0.0006584988,0.00009415013,0.00009928986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007955357,0.00024710508,0.0003118472,0.00026459928,0.000115438466,0.00002558483,0.00015189979,0.00004069819,0.00003324904],"category_scores_gemma":[0.00014146464,0.00020557035,0.00013591343,0.00041473255,0.00011852205,0.00008685538,0.00006974705,0.00079402316,0.000012336851],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033428085,0.00037502655,0.44186762,0.000050652976,0.0000063528837,0.000050808016,0.00016642954,3.8222356e-7,0.5548766,0.000013734143,0.0015060601,0.0010528855],"study_design_scores_gemma":[0.0010742677,0.0003188465,0.9183379,0.000055908054,0.000058715457,0.00010302828,0.000026393369,0.00005709474,0.07861137,0.0002103371,0.000997383,0.00014878897],"about_ca_topic_score_codex":0.0000114849645,"about_ca_topic_score_gemma":0.0000021444182,"teacher_disagreement_score":0.47647023,"about_ca_system_score_codex":0.00001067506,"about_ca_system_score_gemma":0.000014937571,"threshold_uncertainty_score":0.8382916},"labels":[],"label_agreement":null},{"id":"W2154641379","doi":"10.1109/cvprw.2008.4563000","title":"Dealing with uncertainty in the principal directions of tensors","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Eigenvalues and eigenvectors; Tensor (intrinsic definition); Isotropy; Mathematics; Principal component analysis; Invariant (physics); Anisotropy; Tensor density; Monte Carlo method; Upper and lower bounds; Symmetric tensor; Principal axis theorem; Diffusion MRI; Multivariate statistics; Mathematical analysis; Cartesian tensor; Statistical physics; Tensor field; Geometry; Exact solutions in general relativity; Physics; Statistics; Quantum mechanics; Mathematical physics","score_opus":0.0950029987130292,"score_gpt":0.352952443618063,"score_spread":0.2579494449050338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154641379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96337914,0.000023741133,0.007263421,0.002568148,0.0000029623452,0.0003233065,0.0000013503768,0.000097095384,0.026340825],"genre_scores_gemma":[0.98389274,0.00007937074,0.015375201,0.00029228118,0.000008934834,0.0000305887,0.0000013498337,0.000004550566,0.0003150008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99971145,0.000005916293,0.00008052118,0.0000730796,0.00007068715,0.000058315076],"domain_scores_gemma":[0.9997316,0.000039076847,0.000021476293,0.00016471485,0.000029022007,0.000014089508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003904956,0.000035198158,0.00006559101,0.000031873053,0.000043673554,7.118798e-7,0.000037531772,0.00000949857,0.000011704462],"category_scores_gemma":[0.000015038846,0.000018666466,0.000016078237,0.00016636497,0.00006670787,0.000012632124,0.0000062519152,0.000078020224,8.5335955e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043888224,0.0017517313,0.7022122,0.00010455909,0.00006097384,0.00026368754,0.003832544,0.009008527,0.019704547,0.24272121,0.0022753775,0.017625727],"study_design_scores_gemma":[0.002393479,0.00088005554,0.7974952,0.00026069224,0.00010333567,0.0026814362,0.0014000583,0.008084852,0.020545775,0.0031066379,0.16267462,0.00037388172],"about_ca_topic_score_codex":0.000108321794,"about_ca_topic_score_gemma":0.000024786958,"teacher_disagreement_score":0.23961459,"about_ca_system_score_codex":0.000008144997,"about_ca_system_score_gemma":0.000014924387,"threshold_uncertainty_score":0.07611964},"labels":[],"label_agreement":null},{"id":"W2155842404","doi":"10.1186/s12968-014-0087-8","title":"In vivo cardiovascular magnetic resonance diffusion tensor imaging shows evidence of abnormal myocardial laminar orientations and mobility in hypertrophic cardiomyopathy","year":2014,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":190,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Imperial College London; British Heart Foundation; School of Medicine, New York University; York University","keywords":"Diastole; Systole; Hypertrophic cardiomyopathy; Cardiology; Medicine; Internal medicine; Laminar flow; Diffusion MRI; Magnetic resonance imaging; Physics; Radiology; Mechanics; Blood pressure","score_opus":0.02008538652450102,"score_gpt":0.27364397560279036,"score_spread":0.2535585890782893,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155842404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60624015,0.38975665,0.0027507269,0.00026813883,0.00011933886,0.0006572171,0.000008545659,0.000019947254,0.00017930624],"genre_scores_gemma":[0.9375194,0.051409844,0.010445835,0.0001431719,0.00027176779,0.00009158824,7.5021904e-7,0.000051423438,0.000066228735],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99603933,0.0005083943,0.0011819145,0.0006369081,0.0011715544,0.0004618999],"domain_scores_gemma":[0.99754864,0.0002713811,0.00022546339,0.0012890296,0.0004797439,0.00018574098],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0024722896,0.00034465437,0.0015641584,0.0004479447,0.00008138956,0.00002847502,0.0003148882,0.00011401339,0.000014994866],"category_scores_gemma":[0.0008367616,0.0003191089,0.0012075184,0.00083050894,0.00038755234,0.0003845476,0.00015521588,0.0006244916,0.0000012453718],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008056872,0.000471985,0.2814271,0.0005879454,0.00014766867,0.001136498,0.000493159,0.001706543,0.007388508,0.0002469876,0.00020753073,0.7053804],"study_design_scores_gemma":[0.0041062706,0.00091018365,0.74485475,0.001473833,0.0007893168,0.002368621,0.000119650795,0.0033767046,0.0012993822,0.00053942367,0.23976496,0.00039691167],"about_ca_topic_score_codex":0.00016486722,"about_ca_topic_score_gemma":0.000005879145,"teacher_disagreement_score":0.7049835,"about_ca_system_score_codex":0.00015306263,"about_ca_system_score_gemma":0.00013570477,"threshold_uncertainty_score":0.9999261},"labels":[],"label_agreement":null},{"id":"W2156040424","doi":"10.3174/ajnr.a3553","title":"Novel White Matter Tract Integrity Metrics Sensitive to Alzheimer Disease Progression","year":2013,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":154,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; National Institute of Neurological Disorders and Stroke; York University","keywords":"White matter; Corpus callosum; Medicine; Diffusion MRI; Pathology; Neuroscience; Alzheimer's disease; Neurodegeneration; Magnetic resonance imaging; Disease; Biology; Radiology","score_opus":0.06452016962225685,"score_gpt":0.3792456606411035,"score_spread":0.3147254910188466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156040424","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89623094,0.000043818713,0.056078937,0.04678604,0.000104203675,0.0004887542,0.000011198127,0.000045190347,0.00021094929],"genre_scores_gemma":[0.92263925,0.00003188726,0.06650978,0.010607754,0.00013503214,0.00001946354,0.000002693211,0.00002626264,0.000027903987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989686,0.000079278914,0.00035476792,0.00021635857,0.00015571057,0.00022527092],"domain_scores_gemma":[0.99847645,0.00014639908,0.00036236187,0.00026009418,0.00032044644,0.00043423544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010108779,0.00014421617,0.00041324698,0.0002753674,0.000040869418,0.000012020511,0.00013481418,0.000025218209,0.000045533707],"category_scores_gemma":[0.00016148911,0.00010567631,0.00012143846,0.00047995948,0.00022338846,0.00010507844,0.000045352466,0.0005437681,0.000051081817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068663317,0.0012376256,0.7708977,0.000016021344,0.00012402597,0.0005419592,0.00027009382,0.00007137333,0.06393471,0.0001520482,0.028925197,0.13314262],"study_design_scores_gemma":[0.00031908008,0.0017058441,0.9875766,0.000047089223,0.0001588024,0.003620668,0.00007608318,0.00017462701,0.0007797135,0.00010669403,0.00530196,0.0001328167],"about_ca_topic_score_codex":0.000009786725,"about_ca_topic_score_gemma":7.1229174e-8,"teacher_disagreement_score":0.21667893,"about_ca_system_score_codex":0.000029601835,"about_ca_system_score_gemma":0.000061771694,"threshold_uncertainty_score":0.43093547},"labels":[],"label_agreement":null},{"id":"W2156127840","doi":"10.1016/j.neuroimage.2005.05.014","title":"Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques","year":2005,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":173,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University Health Centre; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Imaging phantom; Anisotropic diffusion; Tracking (education); Anisotropy; Tensor (intrinsic definition); Fiber; Diffusion; Computer science; Computer vision; Artificial intelligence; Physics; Mathematics; Geometry; Optics; Materials science","score_opus":0.07984183456497795,"score_gpt":0.3637643607038004,"score_spread":0.28392252613882246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156127840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93703353,0.00004365187,0.056013472,0.0043673217,0.000016282847,0.0011178597,0.00003041473,0.0006838917,0.0006935484],"genre_scores_gemma":[0.83913726,0.000061361214,0.15923147,0.00095645693,0.00012068032,0.00006345313,0.0000964469,0.000047669735,0.00028521975],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987182,0.00003426168,0.00023232243,0.0006107031,0.00021449715,0.00019002885],"domain_scores_gemma":[0.9990406,0.000066073946,0.00009057885,0.0005842254,0.00007409639,0.00014442913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011725493,0.00019081128,0.00023459445,0.0001323072,0.00017764432,0.00006327538,0.00009648218,0.000054125652,0.00001473461],"category_scores_gemma":[0.00007019434,0.0001570666,0.000018056666,0.00018514802,0.00007131946,0.00024985723,0.00015081701,0.00023351746,0.000005163854],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049363606,0.00066687475,0.050676614,0.00013595498,0.000008660861,0.000022899965,0.00016301696,0.00014811987,0.4495429,0.000053995314,0.0020049016,0.4960824],"study_design_scores_gemma":[0.0020141962,0.0011484755,0.3745882,0.00042109343,0.00021118335,0.00026249656,0.000027239206,0.1245421,0.161109,0.000038273985,0.3350605,0.0005772153],"about_ca_topic_score_codex":0.00001728976,"about_ca_topic_score_gemma":0.000011031438,"teacher_disagreement_score":0.49550518,"about_ca_system_score_codex":0.00003320704,"about_ca_system_score_gemma":0.000016018737,"threshold_uncertainty_score":0.64049906},"labels":[],"label_agreement":null},{"id":"W2156721104","doi":"10.1016/j.jad.2012.04.047","title":"Corpus callosal morphology in early onset adolescent depression","year":2012,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of Calgary","funders":"","keywords":"Corpus callosum; Major depressive disorder; White matter; Depression (economics); Psychology; Diffusion MRI; Magnetic resonance imaging; Audiology; Age of onset; Psychiatry; Neuroscience; Medicine; Internal medicine; Cognition; Radiology; Disease","score_opus":0.02806847152146154,"score_gpt":0.34516273907371925,"score_spread":0.3170942675522577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156721104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98692405,0.0004670515,0.011305525,0.00068282185,0.0000976229,0.00023280527,0.0000021089024,0.000017423932,0.00027056856],"genre_scores_gemma":[0.9975348,0.00019395365,0.0018541162,0.00031062344,0.000066116074,0.000009441927,0.0000013935227,0.000015067243,0.000014479361],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993584,0.000051911902,0.00019262111,0.00008470526,0.00012418552,0.00018814525],"domain_scores_gemma":[0.9994913,0.0000693143,0.00015969975,0.000112371425,0.00005830754,0.00010901281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001532113,0.000086163556,0.00019421837,0.000151912,0.000026159169,0.0000031056145,0.000061992796,0.00004838868,0.0000089780115],"category_scores_gemma":[0.00011458675,0.00006900799,0.00007739654,0.00016032798,0.000056766163,0.00011659997,0.000024835022,0.00038058442,0.000003993607],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018440504,0.00054537767,0.9783826,0.000010222839,0.000010038743,0.000017513072,0.00012449134,0.000010851883,0.006418414,0.000049250597,0.00082262675,0.0134242335],"study_design_scores_gemma":[0.0010859481,0.00027891883,0.9927321,0.00009157848,0.000028326835,0.00032920783,0.000054645563,0.000016009655,0.0031763369,0.0005771189,0.0015646562,0.000065134394],"about_ca_topic_score_codex":0.000032663236,"about_ca_topic_score_gemma":0.000009940059,"teacher_disagreement_score":0.0143495435,"about_ca_system_score_codex":0.0000773316,"about_ca_system_score_gemma":0.0000310992,"threshold_uncertainty_score":0.28140643},"labels":[],"label_agreement":null},{"id":"W2157049741","doi":"10.1177/1550059413476031","title":"Neurofeedback Training Induces Changes in White and Gray Matter","year":2013,"lang":"en","type":"article","venue":"Clinical EEG and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":158,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fractional anisotropy; Neurofeedback; White matter; Diffusion MRI; Psychology; Neuroscience; Audiology; Gray (unit); Magnetic resonance imaging; Corpus callosum; Cognition; Neuroimaging; Electroencephalography; Medicine; Nuclear medicine","score_opus":0.1997951354628762,"score_gpt":0.42816003467488056,"score_spread":0.22836489921200437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157049741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788402,0.000029376006,0.00019318372,0.02012896,0.000073440126,0.00025108352,0.0000012789595,0.000049774797,0.00043274558],"genre_scores_gemma":[0.9844954,0.0003566495,0.00094696047,0.013758092,0.00003190232,0.00003567306,4.128789e-7,0.0000091454685,0.00036577156],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99908113,0.000031369644,0.00020704755,0.0004125958,0.00008055125,0.00018728658],"domain_scores_gemma":[0.99946666,0.00013881401,0.000050824914,0.00017349859,0.000017312927,0.00015289165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015449281,0.00008718139,0.00017937561,0.000054746157,0.00006404697,0.000035675686,0.00007690846,0.000040388648,0.000018134078],"category_scores_gemma":[0.00019861288,0.00006839277,0.000018273371,0.0001879787,0.00041379945,0.00011103095,0.00008559122,0.00027121542,0.000009227582],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013893324,0.00013649797,0.8890065,0.00003119164,6.2661206e-7,0.000026812493,0.00018658668,0.0000011045637,0.063710414,0.00020441094,0.001364899,0.045317084],"study_design_scores_gemma":[0.00023836695,0.00018582436,0.9948347,0.000034525645,0.000004276913,0.000069537826,0.0000319732,0.00048663034,0.0003026633,0.0006682159,0.0030690047,0.00007424284],"about_ca_topic_score_codex":0.000005568308,"about_ca_topic_score_gemma":0.0000017501285,"teacher_disagreement_score":0.10582826,"about_ca_system_score_codex":0.0000021353792,"about_ca_system_score_gemma":0.000012196326,"threshold_uncertainty_score":0.2788976},"labels":[],"label_agreement":null},{"id":"W2157436069","doi":"10.1016/j.bandl.2012.10.009","title":"Diffusion tensor imaging correlates of reading ability in dysfluent and non-impaired readers","year":2013,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Health Solutions","keywords":"Psychology; Reading (process); Diffusion MRI; Fractional anisotropy; Fluency; Cognitive psychology; White matter; Word recognition; Dyslexia; Audiology; Voxel; Neuroscience; Developmental psychology; Linguistics; Magnetic resonance imaging","score_opus":0.015969177001500072,"score_gpt":0.30021340216458997,"score_spread":0.2842442251630899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157436069","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958882,0.00021899343,0.0005324914,0.0026159075,0.0000055913183,0.00035910838,0.0000023534317,0.00005993414,0.00031742748],"genre_scores_gemma":[0.99599236,0.000041992018,0.0033255338,0.0004864461,0.000008945877,0.000023448285,0.0000053949557,0.000008595951,0.000107300984],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995564,0.000011634705,0.00012974215,0.00015629777,0.00004644262,0.00009948905],"domain_scores_gemma":[0.9996604,0.00008688211,0.00003666903,0.00014951869,0.000015232711,0.000051328476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000808906,0.00006477909,0.00013080504,0.000055568285,0.000023998435,0.0000064612436,0.000022942986,0.00002189666,0.000014485444],"category_scores_gemma":[0.00010017281,0.000052407733,0.000015514082,0.00007151534,0.000086284585,0.000048013957,0.000033930864,0.00008554986,9.3542155e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018190409,0.00007908221,0.6491558,0.00011955807,0.0000029485675,0.000014255888,0.0030282685,6.327904e-7,0.31418428,0.0001120675,0.0006598634,0.03262507],"study_design_scores_gemma":[0.00059289485,0.00003740527,0.9880788,0.00016200989,0.000008718327,0.000033164906,0.0021587028,0.0055976,0.0028339734,0.00030787312,0.00011561412,0.00007325103],"about_ca_topic_score_codex":0.00032867782,"about_ca_topic_score_gemma":0.0000036421804,"teacher_disagreement_score":0.338923,"about_ca_system_score_codex":0.000010876456,"about_ca_system_score_gemma":0.00000496082,"threshold_uncertainty_score":0.21371254},"labels":[],"label_agreement":null},{"id":"W2157453960","doi":"10.1093/brain/awr099","title":"White matter damage in primary progressive aphasias: a diffusion tensor tractography study","year":2011,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":310,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"White matter; Diffusion MRI; Primary progressive aphasia; Tractography; Medicine; Psychology; Neuroscience; Magnetic resonance imaging; Pathology; Radiology; Dementia; Frontotemporal dementia; Disease","score_opus":0.06289204211024735,"score_gpt":0.33334876634951954,"score_spread":0.2704567242392722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157453960","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98604965,0.00003222641,0.0007418867,0.0021053876,0.000013281059,0.0015896473,0.0000059129834,0.00018195492,0.009280032],"genre_scores_gemma":[0.98357004,0.0000042285997,0.012543505,0.0028026816,0.000027995102,0.0003631483,0.00001401228,0.000031366744,0.00064301654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991659,0.000035422185,0.00020034636,0.00029373448,0.00012283996,0.00018175536],"domain_scores_gemma":[0.9994197,0.00002614227,0.000069513044,0.00039061927,0.000028091325,0.00006597237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092829105,0.00012308183,0.000184891,0.00018631594,0.000038974427,0.000007838702,0.000100526064,0.000037647773,0.00019149431],"category_scores_gemma":[0.000016096194,0.00010092801,0.000054472133,0.0003165815,0.000058863967,0.00007327154,0.000055220426,0.00020329688,0.00002508958],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000083422805,0.0017262979,0.9900446,0.000022210348,0.000006412464,0.00018892995,0.0013298123,4.733102e-8,0.0017253889,0.00003140354,0.002592841,0.0022486465],"study_design_scores_gemma":[0.0009912631,0.0002594868,0.9961502,0.00005948774,0.000018175191,0.000041459585,0.00027701253,0.000011997218,0.00015605062,0.00037426638,0.0015578313,0.00010276916],"about_ca_topic_score_codex":0.000011339172,"about_ca_topic_score_gemma":0.0000041462804,"teacher_disagreement_score":0.011801618,"about_ca_system_score_codex":0.000018359806,"about_ca_system_score_gemma":0.000013611709,"threshold_uncertainty_score":0.4115725},"labels":[],"label_agreement":null},{"id":"W2157938614","doi":"10.1523/jneurosci.3578-12.2013","title":"Early Musical Training and White-Matter Plasticity in the Corpus Callosum: Evidence for a Sensitive Period","year":2013,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":392,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Concordia University","funders":"Canadian Institutes of Health Research; McGill University","keywords":"Corpus callosum; White matter; Diffusion MRI; Period (music); Fractional anisotropy; Neuroscience; Neuroplasticity; Training (meteorology); Psychology; Audiology; Medicine; Magnetic resonance imaging; Physics","score_opus":0.15077021660382442,"score_gpt":0.37685208010264803,"score_spread":0.22608186349882362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157938614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9610305,0.000007699622,0.02596851,0.012610591,0.00003866853,0.00030504438,0.0000014384169,0.0000063253046,0.000031220065],"genre_scores_gemma":[0.9902095,0.000015433288,0.00557893,0.0040910672,0.000055130677,0.000016344515,3.4378626e-8,0.0000052254504,0.000028300527],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993021,0.000028795579,0.00019926723,0.00014114984,0.00018603387,0.0001426764],"domain_scores_gemma":[0.99928445,0.0003341103,0.00012285697,0.00008553183,0.00010294549,0.000070081274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016556426,0.00006437904,0.00013909586,0.00006021488,0.00007762716,0.0000530608,0.00011961117,0.000016423599,0.000002154578],"category_scores_gemma":[0.0005872894,0.00003983249,0.00003866953,0.00016062375,0.00019377377,0.00024615315,0.00002462637,0.00023952822,8.993116e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020279115,0.00027605722,0.14776178,0.00005858926,0.0000029870941,0.0003463875,0.0076201013,0.000063057225,0.8343188,0.00039702907,0.002149748,0.006802673],"study_design_scores_gemma":[0.00026448604,0.0005316494,0.9928615,0.00012652062,0.000014062408,0.0022296705,0.00016762446,0.0026408338,0.0003218995,0.00037898347,0.00041397117,0.000048762915],"about_ca_topic_score_codex":0.0000038506005,"about_ca_topic_score_gemma":6.095434e-7,"teacher_disagreement_score":0.84509975,"about_ca_system_score_codex":0.000013185246,"about_ca_system_score_gemma":0.000043165044,"threshold_uncertainty_score":0.16243218},"labels":[],"label_agreement":null},{"id":"W2158262458","doi":"10.1016/j.mri.2008.01.015","title":"Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study","year":2008,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Stroke (engine); Medicine; Lesion; Magnetic resonance imaging; Cardiology; Nuclear medicine; Internal medicine; Nuclear magnetic resonance; Pathology; Radiology; Physics","score_opus":0.029512316993541083,"score_gpt":0.2961076474598769,"score_spread":0.2665953304663358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158262458","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906581,0.00083879946,0.005221517,0.0012600154,0.000039567272,0.001055622,0.000052689997,0.0003010569,0.000572625],"genre_scores_gemma":[0.984625,0.00014659835,0.01358513,0.0002840364,0.000059523954,0.0001463713,0.000022547807,0.0000569755,0.0010738437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99834514,0.000046252826,0.00039022666,0.00045829662,0.00041764928,0.0003424619],"domain_scores_gemma":[0.9987635,0.00006503526,0.0002480734,0.00056139275,0.00026827242,0.000093741124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009647078,0.00023122846,0.00039943538,0.00014415759,0.00026758,0.0000186433,0.0001649539,0.000023394343,0.000044500423],"category_scores_gemma":[0.00010706398,0.00020450926,0.000071457005,0.00049436965,0.00024622027,0.00014405655,0.00009156856,0.00024570443,0.0000036568852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015003972,0.0007867223,0.9516565,0.000009839225,0.0000112528505,0.00023988758,0.00027014723,0.0000058713454,0.032994702,0.00006717037,0.00060404756,0.013203779],"study_design_scores_gemma":[0.0031608962,0.0004477551,0.98577106,0.0002148481,0.00016853906,0.0003266156,0.0003942823,0.0036771747,0.0017364672,0.0000990152,0.0037567243,0.00024660767],"about_ca_topic_score_codex":0.000058941456,"about_ca_topic_score_gemma":0.000006876521,"teacher_disagreement_score":0.034114536,"about_ca_system_score_codex":0.00007498484,"about_ca_system_score_gemma":0.000081768485,"threshold_uncertainty_score":0.8339645},"labels":[],"label_agreement":null},{"id":"W2158459641","doi":"10.1007/s10618-015-0408-z","title":"Tractome: a visual data mining tool for brain connectivity analysis","year":2015,"lang":"en","type":"article","venue":"Data Mining and Knowledge Discovery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Visualization; Scalability; Artificial intelligence; Visual analytics; Process (computing); Set (abstract data type); Data visualization; Data set; Data mining; Machine learning; Human–computer interaction; Database","score_opus":0.27892127732114425,"score_gpt":0.467167125821036,"score_spread":0.18824584849989173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158459641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76474565,0.0007577817,0.22818337,0.001171681,0.000088624394,0.0005163038,0.0037248975,0.00019798834,0.00061372],"genre_scores_gemma":[0.9444284,0.000038123675,0.041282214,0.00028200413,0.00025571417,0.000056734672,0.012535791,0.00003299324,0.0010880674],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855113,0.000039718692,0.000250619,0.0008041965,0.000117422394,0.00023692088],"domain_scores_gemma":[0.99741375,0.0006418268,0.000100705176,0.0016260506,0.00007845301,0.00013920978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076642836,0.00016920586,0.00039110243,0.00016456409,0.000118629796,0.00010585613,0.00040741885,0.000059214086,0.0000032243977],"category_scores_gemma":[0.0015322581,0.0001528625,0.000049693583,0.00046563998,0.00009493291,0.00089637213,0.00075899815,0.00010351983,0.0000023614277],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009473392,0.0020162135,0.14905389,0.00044149472,0.0014504973,0.00005170154,0.0030057568,0.000008809001,0.0038655552,0.0009300299,0.42803633,0.4101924],"study_design_scores_gemma":[0.006815442,0.0010812785,0.044259015,0.00044907935,0.0061201537,0.00019182684,0.00552628,0.5073028,0.001123767,0.00040797167,0.4252391,0.0014833062],"about_ca_topic_score_codex":0.000018407147,"about_ca_topic_score_gemma":0.0000613604,"teacher_disagreement_score":0.507294,"about_ca_system_score_codex":0.000024929494,"about_ca_system_score_gemma":0.00017640651,"threshold_uncertainty_score":0.6233552},"labels":[],"label_agreement":null},{"id":"W2159161559","doi":"10.1186/alzrt200","title":"Role of emerging neuroimaging modalities in patients with cognitive impairment: a review from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012","year":2013,"lang":"en","type":"review","venue":"Alzheimer s Research & Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Douglas College; Parkwood Institute; Université de Sherbrooke; Université Laval; Montreal Neurological Institute and Hospital; St Joseph's Health Care; Western University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Alzheimer's Association","keywords":"Neuroimaging; Dementia; Positron emission tomography; Modalities; Magnetic resonance imaging; Cognition; Medicine; Psychology; Medical physics; Disease; Psychiatry; Radiology; Pathology","score_opus":0.33295218630888307,"score_gpt":0.4519153971752655,"score_spread":0.11896321086638245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159161559","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022946624,0.9875282,8.254579e-7,0.0026878978,0.000005459749,0.0070193633,0.0002747216,0.000009861504,0.0001790287],"genre_scores_gemma":[0.020451985,0.9764608,0.00008310032,0.00024086153,0.000016007993,0.002605735,0.0000920715,0.00004097605,0.00000843213],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99791455,0.0005483378,0.00041336092,0.00035845963,0.00041629229,0.0003490126],"domain_scores_gemma":[0.99727374,0.0014428952,0.0002307125,0.0005708702,0.00036520624,0.00011656961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031545322,0.00027685417,0.0008287676,0.00016932853,0.00016570814,0.000024574872,0.00021604756,0.000049663107,0.00012806499],"category_scores_gemma":[0.00005108209,0.000133169,0.00010962747,0.00037054098,0.00050591095,0.000037199723,0.000045809174,0.00037621747,0.0000037711438],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005278103,0.00030498207,0.004036708,0.00036710425,0.00095397426,0.0000033141678,0.00039487038,5.0461836e-8,0.0000010239789,0.00033821524,0.0005208887,0.9930261],"study_design_scores_gemma":[0.00255257,0.00310244,0.017070442,0.07660591,0.0033012503,0.000007967998,0.00056676636,0.0000313775,0.00013304771,0.0011156682,0.8949858,0.00052675226],"about_ca_topic_score_codex":0.040508755,"about_ca_topic_score_gemma":0.0027186465,"teacher_disagreement_score":0.99249935,"about_ca_system_score_codex":0.000060888033,"about_ca_system_score_gemma":0.00044010716,"threshold_uncertainty_score":0.9658806},"labels":[],"label_agreement":null},{"id":"W2159251430","doi":"10.1038/npp.2013.93","title":"Alterations of Superficial White Matter in Schizophrenia and Relationship to Cognitive Performance","year":2013,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Occupational Cancer Research Centre; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; National Alliance for Research on Schizophrenia and Depression; Centre for Addiction and Mental Health; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Cognition; Neuroscience; Effects of sleep deprivation on cognitive performance; Psychology; Diffusion MRI; Neuroimaging; Frontal lobe; Audiology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.0418119389417659,"score_gpt":0.3579025808085616,"score_spread":0.3160906418667957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159251430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891116,0.000011713452,0.0005669152,0.0035671548,0.0000431397,0.00074501627,0.0000043336163,0.000041426883,0.0059086904],"genre_scores_gemma":[0.99242955,0.000023838735,0.0035422295,0.002952052,0.000039483606,0.00021841207,0.0000034179993,0.000023729404,0.0007672943],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994146,0.000029988,0.00018713652,0.00020149328,0.000046947276,0.00011980187],"domain_scores_gemma":[0.99967,0.00006792222,0.00003449987,0.000099743585,0.00005456151,0.000073227675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028396364,0.00007670863,0.0001245318,0.00018531756,0.00003344495,0.0000048311504,0.00003907148,0.000029637333,0.0006532826],"category_scores_gemma":[0.000024330762,0.000076409044,0.000014250087,0.00024738707,0.000063534084,0.00006498132,0.000027085964,0.0001669299,0.00019746406],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020178972,0.00013885845,0.88958305,0.00003220039,0.0000043426553,0.000004321168,0.0001261505,0.000014409799,0.101967864,0.00023501866,0.0039995047,0.0036924835],"study_design_scores_gemma":[0.0010125804,0.00015789097,0.99608874,0.000028360568,0.000015809193,0.000034992772,0.0000087103,0.00037322086,0.0016203276,0.00011873701,0.00048069446,0.00005993313],"about_ca_topic_score_codex":0.000004665225,"about_ca_topic_score_gemma":0.0000012952147,"teacher_disagreement_score":0.106505685,"about_ca_system_score_codex":0.0000068098325,"about_ca_system_score_gemma":0.000012618976,"threshold_uncertainty_score":0.71529865},"labels":[],"label_agreement":null},{"id":"W2159481232","doi":"10.1093/neuonc/nos160","title":"Clinical and neuroanatomical predictors of cerebellar mutism syndrome","year":2012,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":141,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; Pediatric Oncology Group; University of Toronto; SickKids Foundation; Hospital for Sick Children; University of Calgary","funders":"Pediatric Oncology Group of Ontario; C17 Council","keywords":"Cerebellum; Medicine; White matter; Medulloblastoma; Magnetic resonance imaging; Psychology; Pathology; Radiology; Internal medicine","score_opus":0.06592830632750624,"score_gpt":0.39698570053557347,"score_spread":0.33105739420806723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159481232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99316806,0.00017501866,0.0006893306,0.0031597393,0.00033386517,0.00040793896,0.00000957687,0.0001554124,0.0019010603],"genre_scores_gemma":[0.99308056,0.00044777544,0.0042401836,0.0019787832,0.00016483245,0.000024943252,0.000005036107,0.000029527779,0.000028375594],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878603,0.00011677293,0.00043146763,0.00027890693,0.0001163038,0.0002705315],"domain_scores_gemma":[0.9987446,0.0004385704,0.0001357349,0.00035510855,0.00003841924,0.0002875628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021577442,0.000121852,0.0004315549,0.000074258685,0.000039831564,0.0000021550693,0.00009410274,0.00016292813,0.0000296765],"category_scores_gemma":[0.00025323758,0.000109925604,0.00008298633,0.0001305086,0.0004236465,0.000060215974,0.00013431319,0.00045052948,0.000012370837],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001234202,0.0009116626,0.89398247,0.000054655422,0.000032674787,0.00015666478,0.00007374653,5.4136916e-7,0.068225026,0.0036687846,0.0054186527,0.027351698],"study_design_scores_gemma":[0.0015446632,0.0018705975,0.45615566,0.000019940977,0.00019923507,0.004590169,0.00001739649,0.00017132198,0.0068864105,0.0006489974,0.5277437,0.00015190634],"about_ca_topic_score_codex":0.0000035702096,"about_ca_topic_score_gemma":3.1242286e-7,"teacher_disagreement_score":0.52232504,"about_ca_system_score_codex":0.000021738408,"about_ca_system_score_gemma":0.00006389903,"threshold_uncertainty_score":0.44826362},"labels":[],"label_agreement":null},{"id":"W2159593426","doi":"10.1007/978-3-642-15711-0_3","title":"Extraction of the Plane of Minimal Cross-Sectional Area of the Corpus Callosum Using Template-Driven Segmentation","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Western University; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Corpus callosum; Segmentation; Computer science; Artificial intelligence; Bottleneck; Plane (geometry); Pattern recognition (psychology); Cross section (physics); Magnetic resonance imaging; Artificial neural network; Computer vision; Anatomy; Mathematics; Physics; Geometry; Medicine; Radiology","score_opus":0.061906115286102466,"score_gpt":0.37233952337964477,"score_spread":0.3104334080935423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2159593426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5674793,0.0000022345296,0.432124,0.00009370296,0.00016276339,0.00012487508,0.000003976553,0.0000057565503,0.0000033932047],"genre_scores_gemma":[0.8840323,7.487741e-7,0.11585362,0.00007331081,0.000032893036,0.0000024452781,8.078258e-7,0.0000031268535,7.2897683e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992913,0.000011799272,0.00020254662,0.00015994407,0.00025170037,0.00008270644],"domain_scores_gemma":[0.9992694,0.000115229945,0.0002014195,0.00027939564,0.00011861197,0.000015920114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012651375,0.00005516858,0.00008847731,0.00005738833,0.000082982886,0.000007711007,0.00022693147,0.000036812213,0.000004248097],"category_scores_gemma":[0.0000709764,0.000033820957,0.000037987913,0.00044683673,0.0005528453,0.00006856317,0.000086171305,0.00020253906,6.2888326e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009246034,0.000026321004,0.30714113,0.000009965567,9.433641e-7,1.9776205e-7,0.000057511257,0.010155139,0.68035036,0.000036562084,6.6284787e-7,0.0022119621],"study_design_scores_gemma":[0.00010612216,0.000027917662,0.42319465,0.000030249272,0.0000037337807,0.000052145624,3.2164576e-7,0.0659576,0.5096777,0.00092262874,0.0000042868364,0.000022669721],"about_ca_topic_score_codex":0.000046402845,"about_ca_topic_score_gemma":0.000019379753,"teacher_disagreement_score":0.31655303,"about_ca_system_score_codex":0.000025360634,"about_ca_system_score_gemma":0.00009430197,"threshold_uncertainty_score":0.20369816},"labels":[],"label_agreement":null},{"id":"W2160990082","doi":"10.1017/neu.2013.2","title":"Altered cingulum bundle microstructure in autism spectrum disorder","year":2013,"lang":"en","type":"article","venue":"Acta Neuropsychiatrica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Autism spectrum disorder; Cingulum (brain); Spectrum disorder; Microstructure; Spectrum (functional analysis); Autism; Nuclear magnetic resonance; Medicine; Materials science; Magnetic resonance imaging; Diffusion MRI; Radiology; Physics; Psychiatry; Composite material; Fractional anisotropy","score_opus":0.01670888438164793,"score_gpt":0.28807336737073463,"score_spread":0.2713644829890867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160990082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9202125,0.00016868186,0.0010141495,0.07289538,0.00030966502,0.0011569059,0.000010392481,0.00040608482,0.0038262415],"genre_scores_gemma":[0.9866803,0.00015225746,0.009482306,0.0026646724,0.00015199944,0.000077204175,0.000015155778,0.000056653225,0.0007194344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998749,0.000025674797,0.0002846981,0.0004456662,0.00013514215,0.00035981424],"domain_scores_gemma":[0.9991154,0.000033725715,0.00009081482,0.0006166363,0.000016880173,0.00012653157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002598763,0.00019379894,0.00023051407,0.00018261833,0.00008184249,0.000032735188,0.00018775334,0.000064634856,0.00024292457],"category_scores_gemma":[0.000028017908,0.00017361403,0.000080687634,0.0005841898,0.00005365882,0.000109912195,0.00007783248,0.00042867736,0.00009105415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019466378,0.0030639141,0.5303674,0.00025252454,0.000054678265,0.00009111402,0.00047234,0.000037487287,0.26242903,0.012558084,0.1704678,0.020010991],"study_design_scores_gemma":[0.0011811908,0.0003267178,0.85877645,0.000026610021,0.000031391657,0.00026426252,0.00002163271,0.00047853964,0.0005052936,0.01610793,0.12197742,0.00030255847],"about_ca_topic_score_codex":0.00017344106,"about_ca_topic_score_gemma":0.000010290718,"teacher_disagreement_score":0.32840908,"about_ca_system_score_codex":0.000028660037,"about_ca_system_score_gemma":0.00003609411,"threshold_uncertainty_score":0.7079775},"labels":[],"label_agreement":null},{"id":"W2161083511","doi":"10.1038/srep05644","title":"A mechanical model predicts morphological abnormalities in the developing human brain","year":2014,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":212,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Division of Civil, Mechanical and Manufacturing Innovation; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Gyrification; Polymicrogyria; Neuroscience; Human brain; Lissencephaly; Epilepsy; Autism; Magnetic resonance imaging; Psychology; Biology; Medicine; Computer science; Cerebral cortex; Developmental psychology","score_opus":0.10402899669616991,"score_gpt":0.36289679983913736,"score_spread":0.2588678031429674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161083511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8555254,0.000012345876,0.13063739,0.008679259,0.0002092363,0.0005630655,0.0000010111966,0.00019507439,0.004177234],"genre_scores_gemma":[0.97884464,0.0000010718817,0.018380506,0.00152006,0.0000384076,0.00010187256,0.000020026702,0.0000088429015,0.0010845601],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986037,0.000046877187,0.0003465946,0.00044960444,0.00032826298,0.0002249463],"domain_scores_gemma":[0.9990127,0.000060304865,0.00009890609,0.00072036294,0.000055263503,0.00005246779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017362075,0.00009064186,0.00014396026,0.000082992614,0.00024095239,0.00006480435,0.00013584128,0.000046893445,0.00001427625],"category_scores_gemma":[0.00030121012,0.000059230446,0.00005028931,0.0002845471,0.00019405673,0.00006605291,0.00007479919,0.00019418522,0.000004453408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003620675,0.0007713144,0.013649549,0.0001765298,0.000017443888,0.0027536845,0.002859159,0.0011519798,0.37302005,0.4729986,0.12749788,0.005067594],"study_design_scores_gemma":[0.0003562284,0.00011251152,0.0091892965,0.00015168492,0.000024935509,0.004421082,0.00014122222,0.02654002,0.00955334,0.84479517,0.10443068,0.00028380856],"about_ca_topic_score_codex":0.0000054884395,"about_ca_topic_score_gemma":0.0000045037523,"teacher_disagreement_score":0.37179658,"about_ca_system_score_codex":0.000030869756,"about_ca_system_score_gemma":0.000058277365,"threshold_uncertainty_score":0.24153475},"labels":[],"label_agreement":null},{"id":"W2161345835","doi":"10.1093/cercor/bht334","title":"Gray- and White-Matter Anatomy of Absolute Pitch Possessors","year":2013,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Baycrest Hospital; Centre for Addiction and Mental Health","funders":"Danmarks Grundforskningsfond; National Research Foundation","keywords":"Gray (unit); White matter; Anatomy; Absolute (philosophy); White (mutation); Biology; Medicine; Magnetic resonance imaging; Philosophy; Nuclear medicine; Radiology","score_opus":0.02514172140313974,"score_gpt":0.3254385219395622,"score_spread":0.30029680053642244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161345835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98894465,0.000054616834,0.0013631883,0.0035939899,0.00001979894,0.00038855654,0.000006025432,0.000092397204,0.0055367486],"genre_scores_gemma":[0.99018705,0.000024129815,0.0072192657,0.0010295837,0.000026036301,0.00004105439,0.000010343611,0.00001853865,0.0014439882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99941105,0.000006271004,0.00016577744,0.00019021578,0.000084956766,0.00014175358],"domain_scores_gemma":[0.99947435,0.000015347028,0.00006590467,0.0002811623,0.00007559735,0.0000876228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000023115359,0.00009200397,0.00017007432,0.000052991334,0.000034496403,0.00001051447,0.000062082676,0.000035847486,0.0005244726],"category_scores_gemma":[0.000007845198,0.000076667246,0.00003839351,0.00011715888,0.00009391561,0.00009331636,0.000049302045,0.0001107038,0.00006810259],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020418618,0.00014329482,0.91337216,0.00015881138,0.000028294804,0.000007755648,0.00012421978,6.8033887e-7,0.029161088,0.0026480616,0.04717399,0.007161245],"study_design_scores_gemma":[0.00030596665,0.00006468489,0.99077845,0.000032973094,0.000022675942,0.000051136176,0.000028685268,0.00021605293,0.0016501959,0.003746179,0.0030140982,0.00008891676],"about_ca_topic_score_codex":0.000050436985,"about_ca_topic_score_gemma":0.0000014770517,"teacher_disagreement_score":0.077406295,"about_ca_system_score_codex":0.0000092247465,"about_ca_system_score_gemma":0.000012299812,"threshold_uncertainty_score":0.5742607},"labels":[],"label_agreement":null},{"id":"W2161569157","doi":"10.1016/j.neuroimage.2012.08.071","title":"Predicting the location of human perirhinal cortex, Brodmann's area 35, from MRI","year":2012,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Center for Research Resources; National Center for Complementary and Alternative Medicine; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Servier; Eisai; Dana Foundation; Bayer HealthCare; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; Genentech; Biogen Idec; Northern California Institute for Research and Education; Massachusetts General Hospital; Bristol-Myers Squibb; Eli Lilly and Company; AstraZeneca; Novartis Pharmaceuticals Corporation; Boston University; BioClinica; Pfizer; Alzheimer's Association; Amorfix Life Sciences; Alzheimer's Drug Discovery Foundation; Merck; National Center for Complementary and Integrative Health; National Institute on Aging; Abbott Laboratories; Ellison Medical Foundation; Foundation for the National Institutes of Health","keywords":"Perirhinal cortex; Neuroscience; Cortex (anatomy); Psychology; Temporal lobe","score_opus":0.07028257376445625,"score_gpt":0.34914359511337956,"score_spread":0.2788610213489233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161569157","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98297006,0.00020932348,0.010251588,0.0017207998,0.000084967534,0.00047658436,0.00002169508,0.00024377159,0.0040211887],"genre_scores_gemma":[0.9963567,0.000032350308,0.0023422253,0.0006033601,0.00025268295,0.00003841372,0.000043108514,0.000029898427,0.0003012134],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991212,0.00003337606,0.00023580578,0.00021025269,0.00019645962,0.00020288974],"domain_scores_gemma":[0.9990053,0.00008455936,0.00014692795,0.0005873964,0.00009590451,0.00007989102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010515445,0.00011792056,0.00016008582,0.000038352853,0.00015386136,0.000011548863,0.00014813748,0.000033391872,0.000058555794],"category_scores_gemma":[0.00008246929,0.000089355286,0.000053464544,0.00021529052,0.00013152401,0.00013431531,0.00006877254,0.00026264522,0.000011515199],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004261913,0.00036795923,0.25513962,0.00006819797,0.00001788305,0.0000076123315,0.00061895186,0.000009389674,0.734401,0.001929813,0.0050045336,0.0023924476],"study_design_scores_gemma":[0.00046679738,0.00017745032,0.9459913,0.000112415764,0.00014043681,0.000066403554,0.00013342481,0.0012838221,0.037819568,0.00061296346,0.013054652,0.00014076321],"about_ca_topic_score_codex":0.00006134352,"about_ca_topic_score_gemma":0.0000019183703,"teacher_disagreement_score":0.6965814,"about_ca_system_score_codex":0.000018202247,"about_ca_system_score_gemma":0.00002040934,"threshold_uncertainty_score":0.3643803},"labels":[],"label_agreement":null},{"id":"W2161773156","doi":"10.1176/appi.neuropsych.11080180","title":"Human Medial Forebrain Bundle (MFB) and Anterior Thalamic Radiation (ATR): Imaging of Two Major Subcortical Pathways and the Dynamic Balance of Opposite Affects in Understanding Depression","year":2012,"lang":"en","type":"article","venue":"Journal of Neuropsychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":344,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medial forebrain bundle; Neuroscience; Diffusion MRI; Forebrain; Psychology; Prefrontal cortex; Anatomy; Medicine; Magnetic resonance imaging; Cognition; Central nervous system; Dopaminergic","score_opus":0.027651643584099807,"score_gpt":0.3289981292353504,"score_spread":0.30134648565125055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161773156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98899287,0.001608919,0.00764083,0.0013095372,0.0001296802,0.0002438768,0.0000038859325,0.0000099614135,0.00006045958],"genre_scores_gemma":[0.9971739,0.00030624314,0.0022570344,0.00014065586,0.00009800426,0.0000029346568,0.0000010119998,0.000018440773,0.0000017472864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990682,0.000089388544,0.00041057653,0.000109268745,0.00017052877,0.00015206046],"domain_scores_gemma":[0.9991727,0.00013200277,0.0004446265,0.00014466415,0.000026319309,0.00007972283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035808605,0.000102329286,0.00030194272,0.0001481494,0.000058960886,0.000008785996,0.00007575212,0.000025827223,0.0000016554424],"category_scores_gemma":[0.0000575315,0.00007098431,0.0000661482,0.0001264317,0.00018610428,0.00017516708,0.000047297483,0.00027023803,4.907816e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027100215,0.00015640096,0.7617276,0.00011472737,0.000010954915,0.000007828409,0.00027328028,0.000004738768,0.23399502,0.0024992693,0.00003166602,0.00090752216],"study_design_scores_gemma":[0.0060735308,0.00033247238,0.977222,0.00062310183,0.0001468561,0.0010735162,0.00017041084,0.0046161623,0.002477546,0.0071529252,0.000006923189,0.000104522434],"about_ca_topic_score_codex":0.0000040487203,"about_ca_topic_score_gemma":0.0000030427377,"teacher_disagreement_score":0.23151748,"about_ca_system_score_codex":0.000031754524,"about_ca_system_score_gemma":0.000023468998,"threshold_uncertainty_score":0.2894656},"labels":[],"label_agreement":null},{"id":"W2162089114","doi":"10.1109/cvprw.2009.5204044","title":"3D stochastic completion fields for fiber tractography","year":2009,"lang":"en","type":"article","venue":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Tractography; Random walk; Stochastic differential equation; Statistical physics; Brownian motion; Computer science; Monte Carlo method; Diffusion; Stochastic process; Voxel; Diffusion MRI; Anomalous diffusion; Algorithm; Mathematical optimization; Applied mathematics; Mathematics; Physics; Artificial intelligence; Statistics","score_opus":0.10372641488124447,"score_gpt":0.35089019035030916,"score_spread":0.2471637754690647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162089114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022755928,0.00002328409,0.97089446,0.0047485856,0.00024828577,0.0008573062,0.000051217143,0.00030853754,0.00011240068],"genre_scores_gemma":[0.66855276,0.00014962128,0.3095549,0.020414475,0.00078495604,0.00006989287,0.00036045598,0.000030810163,0.00008210089],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985094,0.000034514716,0.0003502225,0.0005999741,0.00020933062,0.0002965497],"domain_scores_gemma":[0.9989535,0.00017737673,0.00013974505,0.00029901348,0.0002497796,0.00018059119],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000116323376,0.00029913854,0.00036424721,0.000094209114,0.00022510899,0.00013424133,0.00011714103,0.00018133449,0.00008047677],"category_scores_gemma":[0.0000028218747,0.00027274466,0.00027479528,0.00018162646,0.00007012206,0.000118873795,0.000027743421,0.00038704497,0.000028582666],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054466112,0.00029179896,0.000024963243,0.000035131226,0.000022790397,0.0000032430362,0.00011746918,0.00016377516,0.00009027653,0.00004618608,0.027519368,0.9716305],"study_design_scores_gemma":[0.00289686,0.0030568433,0.013604763,0.0012256517,0.00011128705,0.0001233507,0.000015679727,0.9677145,0.00014387292,0.0038951684,0.006530942,0.0006810639],"about_ca_topic_score_codex":0.0000014712548,"about_ca_topic_score_gemma":4.319691e-7,"teacher_disagreement_score":0.9709495,"about_ca_system_score_codex":0.000021820884,"about_ca_system_score_gemma":0.000020792193,"threshold_uncertainty_score":0.99997246},"labels":[],"label_agreement":null},{"id":"W2162686834","doi":"10.1093/cercor/bhn102","title":"Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography","year":2008,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1143,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; University of Alberta","funders":"National Center for Research Resources","keywords":"Diffusion MRI; Tractography; Neuroscience; Cerebral cortex; Functional connectivity; Cortex (anatomy); Connectome; Connectomics; Human brain; Brain mapping; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.059787037910828435,"score_gpt":0.3299080363253019,"score_spread":0.27012099841447346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162686834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913107,0.000040309482,0.0071645305,0.00020938618,0.000049639537,0.0005764122,0.000039872495,0.00020373403,0.00040537043],"genre_scores_gemma":[0.99672556,0.000024462463,0.0027433457,0.00028495266,0.000077322846,0.000020523561,0.00002501633,0.000051167503,0.000047663474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982142,0.000048240487,0.0005327766,0.0005428021,0.00025752373,0.00040448472],"domain_scores_gemma":[0.9989638,0.00006294932,0.00023596096,0.00048780412,0.00009524648,0.00015428406],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000956384,0.00026581867,0.0005441615,0.00040981852,0.0001928708,0.000010451262,0.00016000815,0.00008785212,0.00013185527],"category_scores_gemma":[0.00003537865,0.00025448742,0.00021423913,0.0004945746,0.00020687866,0.00017511162,0.00010688718,0.00044500997,0.0000017261852],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026390024,0.000253518,0.73964626,0.000045373246,0.000008562164,0.00006537435,0.00012179773,0.0000015594192,0.25899544,0.0002468758,0.000049080703,0.00053976726],"study_design_scores_gemma":[0.0013633952,0.00008325502,0.9808708,0.00021980566,0.000029785242,0.0003458701,0.00018530752,0.0050224504,0.010961673,0.0004915066,0.00016811486,0.00025806192],"about_ca_topic_score_codex":0.0004647729,"about_ca_topic_score_gemma":0.000029566734,"teacher_disagreement_score":0.24803376,"about_ca_system_score_codex":0.000097102784,"about_ca_system_score_gemma":0.000050033228,"threshold_uncertainty_score":0.99999076},"labels":[],"label_agreement":null},{"id":"W2162816954","doi":"10.1002/jmri.21297","title":"White matter microstructural abnormalities in children with spina bifida myelomeningocele and hydrocephalus: A diffusion tensor tractography study of the association pathways","year":2008,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Hydrocephalus; Spina bifida; Tractography; Medicine; Psychology; Magnetic resonance imaging; Pediatrics; Radiology","score_opus":0.012804420850700734,"score_gpt":0.24395829573139563,"score_spread":0.2311538748806949,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162816954","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971959,0.0014557113,0.000030125759,0.0008290905,0.0000151587765,0.00038926242,0.0000043511545,0.000010014709,0.00007037188],"genre_scores_gemma":[0.9972809,0.0002430737,0.0021307843,0.00020187578,0.000036383324,0.000008661043,5.1347536e-7,0.00001615725,0.0000816701],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989147,0.000043106138,0.0004133776,0.00014235859,0.00031827664,0.00016817702],"domain_scores_gemma":[0.9991655,0.000031048872,0.00046183597,0.00017084231,0.00013043733,0.000040330466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014657289,0.00012364566,0.0002676381,0.00016585128,0.000096019445,0.00001538722,0.000111939335,0.000021324382,0.000008018152],"category_scores_gemma":[0.000024513884,0.00007821376,0.000055945235,0.00030729693,0.00010161326,0.0001446645,0.00004122149,0.00030322868,1.7104769e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007475089,0.00013796425,0.9929341,0.0000103233815,0.0000054470665,0.000015543656,0.00128544,0.000004313914,0.0028777148,0.0000016808112,0.000085962645,0.0025667222],"study_design_scores_gemma":[0.0019119246,0.00037303168,0.9944153,0.00017318582,0.000044959546,0.0018165852,0.00048233193,0.000066475,0.0004007404,0.00006503093,0.0001706771,0.0000797757],"about_ca_topic_score_codex":0.00003900098,"about_ca_topic_score_gemma":0.0000031838438,"teacher_disagreement_score":0.0024869465,"about_ca_system_score_codex":0.000045070883,"about_ca_system_score_gemma":0.00003157528,"threshold_uncertainty_score":0.31894645},"labels":[],"label_agreement":null},{"id":"W2162936913","doi":"10.1093/brain/awq040","title":"Diffusion tensor tractography findings in schizophrenia across the adult lifespan","year":2010,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":146,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of General Medical Sciences; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); White matter; Splenium; Diffusion MRI; Fasciculus; Corpus callosum; Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Tractography; Corticospinal tract; Schizophrenia (object-oriented programming); Arcuate fasciculus; Medicine; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.02431946233022715,"score_gpt":0.34301939368738643,"score_spread":0.3186999313571593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162936913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96870303,0.000009502671,0.00047302866,0.029837986,0.00004383393,0.00038392478,0.000011521299,0.0001557707,0.00038139572],"genre_scores_gemma":[0.9901784,0.000016820282,0.005702185,0.0035344276,0.0001036278,0.00008210306,0.000009363128,0.000020540205,0.0003525495],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99931943,0.000012291395,0.00014741847,0.00020750474,0.000111534,0.00020182386],"domain_scores_gemma":[0.99935675,0.000121927966,0.000036060326,0.00038696162,0.00003533744,0.000062973304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013120161,0.00009540347,0.000113038164,0.00005857171,0.00012110832,0.000018999635,0.00013838404,0.00006385261,0.000027391286],"category_scores_gemma":[0.0002574609,0.00006329797,0.000066162305,0.00031965648,0.0001169771,0.000042818334,0.00004522187,0.00053597725,0.000017889952],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022324528,0.00040880853,0.17895836,0.000027182854,0.000008043977,0.00003103361,0.0009241261,7.5973065e-7,0.7329189,0.0112663,0.012195464,0.06303778],"study_design_scores_gemma":[0.001258005,0.00006396831,0.9089742,0.000050452203,0.000008544802,0.000082437065,0.00011468049,0.00024648875,0.007102884,0.0025615378,0.07940165,0.00013517882],"about_ca_topic_score_codex":0.00003630909,"about_ca_topic_score_gemma":0.00009138481,"teacher_disagreement_score":0.7300158,"about_ca_system_score_codex":0.0000060773864,"about_ca_system_score_gemma":0.000013563824,"threshold_uncertainty_score":0.25812164},"labels":[],"label_agreement":null},{"id":"W2163195251","doi":"10.1109/iembs.2005.1615707","title":"Application of T1 and T2 Maps for Stereotactic Deep-Brain Neurosurgery Planning","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials","funders":"","keywords":"Neurosurgery; Computer science; Medical physics; Artificial intelligence; Medicine; Radiology","score_opus":0.06052932144412724,"score_gpt":0.36866807953033265,"score_spread":0.3081387580862054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163195251","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0884902,0.00012307533,0.8992411,0.009459635,0.000011577056,0.00090098806,0.000008786261,0.0002173994,0.0015472512],"genre_scores_gemma":[0.9157038,0.000014375604,0.08162219,0.00192544,0.0000615508,0.0001512794,0.000019192608,0.000017295306,0.00048489455],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99953204,0.000004669677,0.00015847065,0.00016004276,0.0000523511,0.00009242178],"domain_scores_gemma":[0.9995069,0.00016329414,0.00006737629,0.00018813081,0.000029672416,0.00004460997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000652442,0.00006174751,0.0001184669,0.000051749354,0.000033849483,0.0000043649693,0.000030148094,0.000023030885,0.0000041828157],"category_scores_gemma":[0.00004619167,0.000055483866,0.000028791632,0.0000706138,0.000028994466,0.000054426055,0.000017076754,0.000053219224,0.0000012460898],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032886982,0.00049174635,0.059224483,0.00050783355,0.000038339276,0.0000044661033,0.00029436842,0.0001390759,0.47599515,0.042521764,0.017325,0.40312892],"study_design_scores_gemma":[0.002015432,0.00040315103,0.050677594,0.00010806916,0.00013057866,0.00024402779,0.000117191434,0.05753199,0.12357495,0.0085377265,0.75628114,0.00037818076],"about_ca_topic_score_codex":0.0000017467203,"about_ca_topic_score_gemma":4.884375e-7,"teacher_disagreement_score":0.8272136,"about_ca_system_score_codex":0.0000068751847,"about_ca_system_score_gemma":0.0000075313123,"threshold_uncertainty_score":0.22625665},"labels":[],"label_agreement":null},{"id":"W2163304592","doi":"10.3389/fnhum.2014.00589","title":"Functional MRI activation in white matter during the Symbol Digit Modalities Test","year":2014,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Surrey Memorial Hospital; Fraser Health; Izaak Walton Killam Health Centre; Simon Fraser University; University of Calgary; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts; Nova Scotia Health Research Foundation","keywords":"Numerical digit; White matter; Modalities; Symbol (formal); Test (biology); Neuroscience; Psychology; Medicine; Arithmetic; Computer science; Magnetic resonance imaging; Biology; Mathematics; Radiology","score_opus":0.03062915196513463,"score_gpt":0.28595587735899664,"score_spread":0.25532672539386203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163304592","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85726094,0.0000041712306,0.13503672,0.0049180193,0.00017906104,0.0004147069,0.0000029396192,0.000098745826,0.0020846718],"genre_scores_gemma":[0.9948875,0.0000051098,0.0009824609,0.001505842,0.000055444845,0.0000876384,0.0000026488178,0.000012773164,0.0024606222],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999121,0.000022062844,0.00017346011,0.00030583856,0.00018162436,0.00019599668],"domain_scores_gemma":[0.99954927,0.00003636619,0.000054735494,0.00030832618,0.000018192513,0.00003309362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093684386,0.00009176367,0.0001085392,0.0001535623,0.00017276645,0.000038167487,0.00016315446,0.00002263696,0.000012022453],"category_scores_gemma":[0.00008006226,0.00007355917,0.000024343422,0.00032349792,0.00021879653,0.00020631257,0.00005540917,0.0002262017,0.0000014748643],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010190621,0.00006419245,0.9736178,0.00001826758,2.3459587e-7,0.000001503765,0.00009299706,0.0009325016,0.021382064,0.00039495304,0.0033536814,0.00013164562],"study_design_scores_gemma":[0.00024395813,0.00003677601,0.98602873,0.000042374602,0.000001977019,0.000010291295,0.000046881192,0.00399335,0.0042528054,0.003242394,0.0020185357,0.000081932194],"about_ca_topic_score_codex":0.0000048563443,"about_ca_topic_score_gemma":0.0000012757932,"teacher_disagreement_score":0.1376265,"about_ca_system_score_codex":0.0000654054,"about_ca_system_score_gemma":0.000012531712,"threshold_uncertainty_score":0.29996556},"labels":[],"label_agreement":null},{"id":"W2163397436","doi":"10.1016/j.media.2011.02.002","title":"Recent advances in diffusion MRI modeling: Angular and radial reconstruction","year":2011,"lang":"en","type":"review","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Diffusion MRI; Diffusion; Artificial intelligence; Bridge (graph theory); Sampling (signal processing); SIGNAL (programming language); Diffusion imaging; Emphasis (telecommunications); Magnetic resonance imaging; Computer vision; Machine learning; Physics","score_opus":0.07453154444029955,"score_gpt":0.39947682010072955,"score_spread":0.32494527566042997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163397436","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017783534,0.9168292,0.08184118,0.0002603411,0.000039586797,0.00041504396,0.00000958126,0.000089789144,0.00049747544],"genre_scores_gemma":[0.000007277109,0.987476,0.011874658,0.00010549313,0.00013080894,0.00012289522,0.00018187163,0.000032427502,0.00006859795],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980034,0.000099837074,0.000713412,0.0006367953,0.00031003347,0.00023648309],"domain_scores_gemma":[0.99889374,0.00006261908,0.00020401366,0.00048316916,0.0000712248,0.00028521256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030575533,0.0002893916,0.0016177479,0.0007043547,0.00005815921,0.000014918632,0.00015154331,0.00027241258,0.00045813542],"category_scores_gemma":[0.00028927688,0.0002207067,0.00040274352,0.0013950107,0.00017750252,0.00012341117,0.00010194598,0.00066137925,0.000008766554],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006041128,0.00007661056,0.00005811694,0.0007253652,0.00010851216,0.000052187155,0.000010730227,8.595562e-7,5.745606e-7,0.00003225277,0.000041750394,0.998887],"study_design_scores_gemma":[0.0002310351,0.000029274112,0.000005991686,0.0023752442,0.0046203844,0.00018333181,0.00000905094,0.015433076,9.365258e-7,0.0004010102,0.9765002,0.00021047352],"about_ca_topic_score_codex":0.000023846478,"about_ca_topic_score_gemma":0.000024122844,"teacher_disagreement_score":0.99867654,"about_ca_system_score_codex":0.00008225021,"about_ca_system_score_gemma":0.00011430618,"threshold_uncertainty_score":0.90001583},"labels":[],"label_agreement":null},{"id":"W2163622527","doi":"10.1007/978-1-84882-299-3_3","title":"A Variational Approach to the Registration of Tensor-Valued Images","year":2009,"lang":"en","type":"book-chapter","venue":"Advances in pattern recognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Compatibility (geochemistry); Tensor field; Tensor (intrinsic definition); Mathematics; Energy functional; Smoothness; Constraint (computer-aided design); Mathematical analysis; Computer science; Artificial intelligence; Applied mathematics; Geometry; Exact solutions in general relativity; Geology","score_opus":0.0761410596768305,"score_gpt":0.33942633749361084,"score_spread":0.26328527781678035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163622527","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010237639,0.0007371436,0.3359111,0.0023214864,0.00008100196,0.0020385822,0.00030603286,0.00012898106,0.6583733],"genre_scores_gemma":[0.18260342,0.016303679,0.5598065,0.016029686,0.0029446615,0.0021715104,0.010889367,0.00048659588,0.20876458],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987325,0.000016781336,0.00045138775,0.00038159278,0.00028997057,0.00012778997],"domain_scores_gemma":[0.9990142,0.0000614868,0.00033723205,0.00036679168,0.00017986454,0.000040417188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015164696,0.00020079887,0.00028637005,0.00016617076,0.000043153243,0.000009555748,0.00011888905,0.000111838366,0.00003305763],"category_scores_gemma":[0.000055621244,0.00016384198,0.00009055956,0.000078920035,0.00006389789,0.000102338745,0.00002353025,0.00032429796,0.000023077037],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078090554,0.0001506499,0.00014126423,0.00015146042,0.000015561847,0.0000062797044,0.000052886277,0.000105453095,0.00021118134,0.0063093435,0.00095828983,0.99181956],"study_design_scores_gemma":[0.002152293,0.0010481823,0.009610434,0.003638064,0.00050137675,0.0003901741,0.000062748986,0.002032456,0.0025081653,0.5286727,0.44812956,0.001253872],"about_ca_topic_score_codex":0.0000071668005,"about_ca_topic_score_gemma":0.000008214714,"teacher_disagreement_score":0.99056566,"about_ca_system_score_codex":0.00006398505,"about_ca_system_score_gemma":0.00003267341,"threshold_uncertainty_score":0.6681282},"labels":[],"label_agreement":null},{"id":"W2164021478","doi":"10.1186/1471-244x-13-264","title":"Multimodal neuroimaging of frontal white matter microstructure in early phase schizophrenia: the impact of early adolescent cannabis use","year":2013,"lang":"en","type":"article","venue":"BMC Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Western University; Dalhousie University","funders":"","keywords":"White matter; Diffusion MRI; Neuroimaging; Neuroscience; Schizophrenia (object-oriented programming); Psychology; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.026435281785758914,"score_gpt":0.33064953069887687,"score_spread":0.30421424891311794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164021478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99549216,0.00009466941,0.001644472,0.0015569164,0.00009379213,0.00094106863,0.00008758766,0.000043718344,0.00004562165],"genre_scores_gemma":[0.973556,0.000005419006,0.025874741,0.0003113496,0.00007680089,0.000045356293,0.000010796293,0.000039714632,0.00007984603],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988842,0.000037616635,0.00040110658,0.0002818004,0.00014430702,0.0002509392],"domain_scores_gemma":[0.99898565,0.000012707898,0.00020462558,0.00062318123,0.000086680986,0.00008715256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004422444,0.0001975141,0.00028950625,0.00012760343,0.000041622407,0.000023920913,0.00019284798,0.00005934215,0.00007648233],"category_scores_gemma":[0.000014287857,0.00013495266,0.00020359458,0.000239003,0.00013900112,0.00018402866,0.00006139445,0.00039304755,0.000011771547],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030200928,0.0003161235,0.97451437,0.000057018715,0.000011527276,5.4889006e-7,0.00016641134,0.00003191513,0.018051403,0.000020319732,0.006249772,0.00027857503],"study_design_scores_gemma":[0.0022449421,0.00018223442,0.99582916,0.00013619376,0.000027987764,0.00003807407,0.000034078534,0.0005339814,0.00050783675,0.00032537399,0.00002714617,0.00011300162],"about_ca_topic_score_codex":0.0027038078,"about_ca_topic_score_gemma":0.000051019008,"teacher_disagreement_score":0.024230268,"about_ca_system_score_codex":0.00003614143,"about_ca_system_score_gemma":0.00012299589,"threshold_uncertainty_score":0.5503209},"labels":[],"label_agreement":null},{"id":"W2165564750","doi":"10.1016/j.clineuro.2006.06.005","title":"Magnetoencephalography and diffusion tensor imaging in gelastic seizures secondary to a cingulate gyrus lesion","year":2006,"lang":"en","type":"article","venue":"Clinical Neurology and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Ictal; Diffusion MRI; Lesion; Magnetoencephalography; Temporal lobe; Gelastic seizure; Gyrus; Neuroscience; Electroencephalography; Epilepsy; Magnetic resonance imaging; Radiology; Pathology; Psychology; Hypothalamic hamartoma; Internal medicine","score_opus":0.047973460715509876,"score_gpt":0.3575992250779697,"score_spread":0.3096257643624598,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165564750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9897167,0.00029679763,0.00045320176,0.00870426,0.00016376743,0.00033500706,0.0000063098796,0.00014795148,0.00017600725],"genre_scores_gemma":[0.98321044,0.0005399686,0.00053395005,0.015465994,0.00011668396,0.00002945192,0.0000064513697,0.00002695286,0.0000700853],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99822116,0.00013003113,0.0005728298,0.0006863116,0.000083252846,0.00030640746],"domain_scores_gemma":[0.99842507,0.0010185192,0.000090555484,0.00026632033,0.00002703687,0.00017252895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024519875,0.00018262766,0.00039568255,0.00026812806,0.00011219804,0.00001569383,0.00005763025,0.00010788352,0.000009237858],"category_scores_gemma":[0.00028042292,0.00016403342,0.000083237144,0.00025212776,0.0003498498,0.00005957099,0.00014555414,0.00058950845,0.000003445347],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000406978,0.0001898423,0.97181684,0.000022851511,0.0000012591448,0.0007276546,0.0000054383386,0.0000064414776,0.0064070155,0.000101728605,0.0015685742,0.018745383],"study_design_scores_gemma":[0.0005221904,0.00043075142,0.98609996,0.00003155445,0.000022094671,0.000721685,0.0000013690311,0.0006171167,0.000065496315,0.002288351,0.009070521,0.00012894023],"about_ca_topic_score_codex":0.000020977011,"about_ca_topic_score_gemma":0.0000053246144,"teacher_disagreement_score":0.018616443,"about_ca_system_score_codex":0.0000023824398,"about_ca_system_score_gemma":0.000018721636,"threshold_uncertainty_score":0.6689089},"labels":[],"label_agreement":null},{"id":"W2165848433","doi":"10.1186/1471-2202-13-107","title":"Both projection and commissural pathways are disrupted in individuals with chronic stroke: investigating microstructural white matter correlates of motor recovery","year":2012,"lang":"en","type":"article","venue":"BMC Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; Michael Smith Health Research BC; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Internal capsule; Fractional anisotropy; Corpus callosum; White matter; Stroke (engine); Diffusion MRI; Chronic stroke; Psychology; Sensory system; Physical medicine and rehabilitation; Corticospinal tract; Motor function; Medicine; Neuroscience; Magnetic resonance imaging; Rehabilitation","score_opus":0.052673132173399695,"score_gpt":0.3054686125792752,"score_spread":0.2527954804058755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165848433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99810535,0.00007375488,0.0010121216,0.0001429922,0.00005070513,0.00048040441,0.000034823617,0.000050381135,0.000049469658],"genre_scores_gemma":[0.98920166,0.0000125237,0.01036705,0.00022314583,0.000023911953,0.000037746777,0.0000038137264,0.00001376725,0.00011637487],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99918747,0.000029740697,0.00018393376,0.00023225894,0.0001392279,0.00022736045],"domain_scores_gemma":[0.99949366,0.000043828157,0.00017338524,0.00018759302,0.000021412901,0.00008013009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009643579,0.00010995066,0.00015580401,0.00009431116,0.00007559651,0.000019475116,0.0000763644,0.00002852788,0.0000029386645],"category_scores_gemma":[0.00006889842,0.00008632925,0.000018696644,0.00028314628,0.00027442467,0.0002838719,0.00006160376,0.00017943983,6.489881e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011280754,0.000023054528,0.8757701,0.00005422775,4.1604986e-7,6.507071e-7,0.00008573085,0.000017594342,0.123839684,0.000020421396,0.000021956183,0.00015488715],"study_design_scores_gemma":[0.00029586663,0.00020886086,0.98730236,0.00014292188,0.000009940673,0.0001611046,0.0000500062,0.0009855226,0.010633182,0.000039017184,0.0000843328,0.00008690278],"about_ca_topic_score_codex":0.000018460678,"about_ca_topic_score_gemma":0.0000070106225,"teacher_disagreement_score":0.113206506,"about_ca_system_score_codex":0.00003361409,"about_ca_system_score_gemma":0.000046610516,"threshold_uncertainty_score":0.35204047},"labels":[],"label_agreement":null},{"id":"W2166106056","doi":"10.1016/j.eplepsyres.2014.03.006","title":"Tractography of Meyer's Loop asymmetries","year":2014,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Alberta Innovates; National Research Council Institute for Biodiagnostics","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Uncinate fasciculus; Diffusion MRI; Temporal lobe; Anatomy; Nuclear medicine; Fasciculus; Epilepsy; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Radiology; Fractional anisotropy","score_opus":0.2188368223898774,"score_gpt":0.47567185241368376,"score_spread":0.25683503002380637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166106056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8008265,0.0005407772,0.04565535,0.010854725,0.00007121033,0.0014207849,0.000023147677,0.00043873434,0.14016879],"genre_scores_gemma":[0.9877432,0.00015784272,0.011026457,0.0001300239,0.00008182601,0.000057743662,0.000008598322,0.0000198338,0.00077445793],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988002,0.00008335754,0.00018496669,0.00022018954,0.00044900627,0.00026224385],"domain_scores_gemma":[0.9986285,0.00039790676,0.000037873837,0.0005292838,0.0002919324,0.00011452017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008255759,0.000068570815,0.00018718195,0.000387905,0.00008879759,0.000009776291,0.0001581585,0.000047298257,0.000076027005],"category_scores_gemma":[0.00051371456,0.000058170055,0.00007969208,0.0010042961,0.00031786223,0.000044258668,0.00006411539,0.00039764217,0.000035059576],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038333252,0.0012823902,0.28889835,0.00041590314,0.000076520366,0.000019552877,0.00023952908,0.0000049008086,0.19908144,0.19979578,0.064457215,0.24534509],"study_design_scores_gemma":[0.0010998079,0.0014146668,0.20540117,0.00017551023,0.000030661224,0.00003931123,0.00012969083,0.0005596744,0.30051208,0.040022407,0.45040587,0.00020915634],"about_ca_topic_score_codex":0.000025355732,"about_ca_topic_score_gemma":0.0000010555681,"teacher_disagreement_score":0.38594866,"about_ca_system_score_codex":0.000012982256,"about_ca_system_score_gemma":0.000035057554,"threshold_uncertainty_score":0.2372106},"labels":[],"label_agreement":null},{"id":"W2166238599","doi":"10.71781/27554","title":"Étude de la substance blanche par diffusion tensiorelle : tractographie des fibres d'association de la région temporo-pariéto-occipitale","year":2007,"lang":"fr","type":"dissertation","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Physics; Humanities; Philosophy","score_opus":0.03907964895021424,"score_gpt":0.38250335156357795,"score_spread":0.3434237026133637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166238599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97690475,0.001588526,0.0051564565,0.0002926408,0.00014164291,0.0013793777,0.00008180435,0.00003848235,0.014416311],"genre_scores_gemma":[0.9208562,0.0047189216,0.06626465,0.000115588795,0.00029678363,0.00019730329,0.00093247823,0.00012295567,0.006495142],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969647,0.00037400625,0.00068413664,0.0007806155,0.00041995302,0.0007766012],"domain_scores_gemma":[0.9966921,0.0014528008,0.00075023394,0.00056597433,0.00023300447,0.00030588385],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017712227,0.0005007064,0.0006293349,0.00024887227,0.0005929016,0.0002280033,0.0005325442,0.0009245723,0.00035564942],"category_scores_gemma":[0.0005404116,0.00051796593,0.0002342473,0.00066353625,0.00034258518,0.00027921385,0.000082820916,0.0010618799,0.00007229265],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059537357,0.0016724858,0.4642269,0.0002604989,0.00013764379,0.00025647355,0.006770916,0.00008604155,0.40511632,0.00031298344,0.0035873312,0.11697704],"study_design_scores_gemma":[0.0019385573,0.00026965787,0.7237036,0.0022935998,0.0006857166,0.00013576218,0.0019136708,0.0008276794,0.18484393,0.004169743,0.07840301,0.0008150389],"about_ca_topic_score_codex":0.0004765855,"about_ca_topic_score_gemma":0.0007401532,"teacher_disagreement_score":0.25947672,"about_ca_system_score_codex":0.0006226112,"about_ca_system_score_gemma":0.00029123353,"threshold_uncertainty_score":0.9997272},"labels":[],"label_agreement":null},{"id":"W2166318116","doi":"10.3233/jad-140519","title":"Tract Based Spatial Statistic Reveals No Differences in White Matter Microstructural Organization between Carriers and Non-Carriers of the APOE ɛ4 and ɛ2 Alleles in Young Healthy Adolescents","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; SickKids Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Hospital for Sick Children; Université de Montréal","funders":"IXICO; King's College London; National Institute for Health and Care Research; South London and Maudsley NHS Foundation Trust","keywords":"Apolipoprotein E; Allele; White matter; Diffusion MRI; Psychology; Neuroimaging; Genetics; Biology; Medicine; Internal medicine; Magnetic resonance imaging; Neuroscience; Disease; Gene","score_opus":0.03557124961063087,"score_gpt":0.3120112037721963,"score_spread":0.27643995416156547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166318116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99657667,0.00029117454,0.00096646236,0.0017435959,0.00004522314,0.0003017957,0.000067335546,0.0000038005567,0.000003919386],"genre_scores_gemma":[0.9980885,0.000029648252,0.0014888056,0.00031709354,0.00004821374,0.0000024381984,0.00000886724,0.000014291869,0.0000021760156],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991193,0.00006314178,0.00038750446,0.00012301916,0.00018816687,0.00011887745],"domain_scores_gemma":[0.9991493,0.000024958554,0.00029274973,0.00012034905,0.0001494405,0.00026316967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011836378,0.00010404811,0.00026284184,0.00010398103,0.000031188516,0.000014308239,0.00007389256,0.000029512963,0.000007928482],"category_scores_gemma":[0.000115718554,0.00007340496,0.0000266822,0.00014938378,0.00011204215,0.0000916919,0.000025933312,0.0001843148,2.4055893e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018156672,0.00003917542,0.9986252,0.00005492138,0.000013182842,0.000008691212,0.00021054431,0.0000069318066,0.00041227302,8.7400787e-7,0.0002071476,0.00023949704],"study_design_scores_gemma":[0.0013356156,0.00009131114,0.9974386,0.00028143605,0.00018656265,0.000013623737,0.00007423854,0.00018179206,0.00016914916,0.00015732521,0.000005068181,0.000065248256],"about_ca_topic_score_codex":0.000060860442,"about_ca_topic_score_gemma":0.000010398914,"teacher_disagreement_score":0.0015117726,"about_ca_system_score_codex":0.000029558927,"about_ca_system_score_gemma":0.00017132882,"threshold_uncertainty_score":0.29933676},"labels":[],"label_agreement":null},{"id":"W2166628049","doi":"10.1016/j.neuroimage.2008.01.028","title":"Labeling of ambiguous subvoxel fibre bundle configurations in high angular resolution diffusion MRI","year":2008,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Fiber bundle; Tractography; Bundle; Diffusion MRI; Orientation (vector space); Computer science; Artificial intelligence; Inference; Tracking (education); Computer vision; Mathematics; Algorithm; Geometry; Materials science; Magnetic resonance imaging","score_opus":0.05627328459219187,"score_gpt":0.315476799707365,"score_spread":0.2592035151151731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2166628049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9833355,0.000105520194,0.012672792,0.0019093564,0.000043731903,0.00046882688,0.00002736941,0.00019782849,0.001239071],"genre_scores_gemma":[0.98239076,0.00034850347,0.016310085,0.00036337983,0.00004412609,0.000033610937,0.000057261877,0.000029624029,0.00042266952],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989777,0.0000341173,0.00031190974,0.0002991884,0.00018547244,0.00019158352],"domain_scores_gemma":[0.9992484,0.000038472543,0.00010292036,0.00045590696,0.000089995956,0.000064320826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060137176,0.00012185317,0.00022742579,0.00015174049,0.00011236106,0.000005188441,0.0000909051,0.000054510823,0.000029060988],"category_scores_gemma":[0.0000888874,0.00012345854,0.000058843376,0.00037362648,0.00012717985,0.00009738542,0.000046801135,0.000239352,0.0000104094925],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000647317,0.0004988869,0.006354151,0.00004674468,0.0000031154782,0.00012244629,0.00013629226,0.00013664512,0.98909235,0.0013236501,0.0013382925,0.00088268035],"study_design_scores_gemma":[0.0041438355,0.0011182362,0.7062154,0.00033708048,0.00008826555,0.0008656698,0.0000843651,0.01068339,0.255159,0.0026865222,0.0180769,0.00054134],"about_ca_topic_score_codex":0.000239109,"about_ca_topic_score_gemma":0.000008319871,"teacher_disagreement_score":0.7339334,"about_ca_system_score_codex":0.000032182386,"about_ca_system_score_gemma":0.00004237338,"threshold_uncertainty_score":0.5034493},"labels":[],"label_agreement":null},{"id":"W2167776784","doi":"10.1016/j.jneumeth.2011.07.026","title":"A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images","year":2011,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"Scanning electron microscope; Electron microscope; Microscope; Materials science; Computer science; Artificial intelligence; Biomedical engineering; Optics; Physics; Medicine; Composite material","score_opus":0.2303427529505041,"score_gpt":0.5002429240959286,"score_spread":0.26990017114542453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167776784","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.207457,0.000292806,0.79131657,0.00033941594,0.00013301068,0.00029988625,0.0000015032373,0.000093306444,0.00006647618],"genre_scores_gemma":[0.15435518,0.0001028793,0.8451538,0.00028246237,0.000029589239,0.000013804476,1.9764755e-7,0.000021952084,0.000040129256],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985389,0.00021177913,0.0004940376,0.00028734028,0.00017016326,0.00029774645],"domain_scores_gemma":[0.9989208,0.00021845216,0.0003836296,0.00016691971,0.00018382372,0.00012639562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002312257,0.00013536756,0.00034416805,0.0003817549,0.0001163197,0.000039851297,0.00019170363,0.000042516862,0.000001171557],"category_scores_gemma":[0.0009472904,0.000115980205,0.00008790961,0.0006126801,0.00010459467,0.00030882133,0.00006152524,0.00035469592,7.89209e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000734385,0.000045540175,0.00084649894,0.000040560273,0.0000026752616,0.000037792855,0.00021427913,0.000029861083,0.99099606,0.00002321892,0.00005916025,0.0076309396],"study_design_scores_gemma":[0.00066771364,0.0004158521,0.03181888,0.00024438815,0.000059149632,0.0013298399,0.00007084129,0.020361364,0.9427129,0.0016144724,0.0005785549,0.00012601804],"about_ca_topic_score_codex":0.00001276335,"about_ca_topic_score_gemma":3.5922915e-7,"teacher_disagreement_score":0.053837214,"about_ca_system_score_codex":0.000057350928,"about_ca_system_score_gemma":0.00008027605,"threshold_uncertainty_score":0.47295356},"labels":[],"label_agreement":null},{"id":"W2167908150","doi":"10.1016/j.media.2012.07.002","title":"Symmetric positive semi-definite Cartesian Tensor fiber orientation distributions (CT-FOD)","year":2012,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute on Aging; National Center for Research Resources; McGill University; Johns Hopkins University","keywords":"Tensor (intrinsic definition); Diffusion MRI; Cartesian coordinate system; Mathematics; Tensor field; Cartesian tensor; Mathematical analysis; Orientation (vector space); Convolution (computer science); Artificial intelligence; Geometry; Computer science; Tensor density; Magnetic resonance imaging; Exact solutions in general relativity; Artificial neural network","score_opus":0.029280580250433053,"score_gpt":0.35686157417974923,"score_spread":0.32758099392931617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2167908150","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1338401,0.00056519336,0.830072,0.015348608,0.00007598068,0.00066745444,0.00036392265,0.0006233675,0.018443372],"genre_scores_gemma":[0.9809087,0.0001013192,0.014946348,0.0012222606,0.00020643331,0.000095554584,0.0011859189,0.000022886348,0.001310598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983249,0.000060622482,0.00034162952,0.0003192238,0.0005614759,0.00039215304],"domain_scores_gemma":[0.9984876,0.00020334424,0.00010697875,0.00045862328,0.0001959537,0.00054749486],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002641244,0.00016430348,0.0003687653,0.0004125216,0.00017234529,0.00002302371,0.00011546112,0.00005937154,0.0012638844],"category_scores_gemma":[0.00080402545,0.00013816936,0.00030483934,0.0033293688,0.00017655533,0.00015455103,0.000061700484,0.00032396385,0.00023929635],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001370743,0.0054302798,0.68282247,0.00017505563,0.0049286145,0.00090052345,0.00075443106,0.0000189788,0.009289758,0.022366172,0.043055046,0.23012161],"study_design_scores_gemma":[0.0021975003,0.00025547566,0.83659744,0.00014908281,0.018954353,0.0006406564,0.00036123107,0.012162097,0.019325541,0.0012153214,0.10705783,0.0010834573],"about_ca_topic_score_codex":0.00009037536,"about_ca_topic_score_gemma":0.0000042849542,"teacher_disagreement_score":0.8470686,"about_ca_system_score_codex":0.00010347465,"about_ca_system_score_gemma":0.000045321023,"threshold_uncertainty_score":0.9996491},"labels":[],"label_agreement":null},{"id":"W2168301017","doi":"10.1017/s1461145712000314","title":"Striatal glutamate and the conversion to psychosis: a prospective 1H-MRS imaging study","year":2012,"lang":"en","type":"article","venue":"The International Journal of Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Instituto Carlos Slim de la Salud; Consejo Nacional de Ciencia y Tecnología; University of California Institute for Mexico and the United States; Sistema Nacional de Investigadores; Eli Lilly and Company","keywords":"Psychosis; Striatum; Glutamate receptor; Psychology; Abnormality; Internal medicine; Proton magnetic resonance; Psychiatry; Medicine; Audiology; Neuroscience; Nuclear magnetic resonance; Dopamine","score_opus":0.03647671716841642,"score_gpt":0.40207527755291245,"score_spread":0.365598560384496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168301017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9440777,0.00015408908,0.0010106245,0.052549273,0.0011724517,0.0007471129,0.0000041175413,0.000024171588,0.0002604965],"genre_scores_gemma":[0.9892941,0.00018333203,0.0003906346,0.009374597,0.0006456587,0.00003872492,3.4776022e-7,0.000015707292,0.000056884277],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99899983,0.00012340861,0.00030413724,0.00012275338,0.0002984434,0.00015141112],"domain_scores_gemma":[0.99902457,0.00022529368,0.00024294257,0.00014033791,0.00025750368,0.000109351815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052880275,0.000103766026,0.00017262565,0.00011456919,0.000093794355,0.000025846783,0.00037143865,0.0000121269995,0.000037516536],"category_scores_gemma":[0.00008851769,0.000056536683,0.00007203062,0.00012575473,0.00014614458,0.00012589918,0.00012911428,0.00037666847,0.0000105313975],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.037300393,0.0035617007,0.62968147,0.000022137343,0.0015672777,0.0002904617,0.009856183,0.0000898408,0.21868108,0.004474641,0.064248316,0.030226527],"study_design_scores_gemma":[0.031708784,0.0013548092,0.88878036,0.00009202946,0.00093076495,0.006433788,0.0019604794,0.00052265753,0.0072382893,0.0022968783,0.058380686,0.0003004711],"about_ca_topic_score_codex":0.0000062137296,"about_ca_topic_score_gemma":2.2197517e-7,"teacher_disagreement_score":0.25909892,"about_ca_system_score_codex":0.00004532171,"about_ca_system_score_gemma":0.000019160108,"threshold_uncertainty_score":0.2305499},"labels":[],"label_agreement":null},{"id":"W2168389179","doi":"10.1016/j.media.2009.10.003","title":"A filtered approach to neural tractography using the Watson directional function","year":2009,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of Mental Health; Fogarty International Center; National Institutes of Health","keywords":"Tractography; Computer science; Diffusion MRI; Noise (video); Fiber; Artificial intelligence; Kalman filter; SIGNAL (programming language); Noise reduction; Algorithm; Mathematics; Computer vision","score_opus":0.072124928754897,"score_gpt":0.37745874984233835,"score_spread":0.30533382108744134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168389179","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06577556,0.000053371397,0.920331,0.011491376,0.00002122606,0.0002476178,0.000004751482,0.0001920843,0.00188299],"genre_scores_gemma":[0.94949347,0.000014838574,0.043168426,0.0068732705,0.00020140251,0.000034386616,0.000060931045,0.000010489634,0.00014281749],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870527,0.000042079773,0.00022872619,0.0003189453,0.0005068207,0.0001981337],"domain_scores_gemma":[0.99921453,0.000045539164,0.000052777912,0.00037553758,0.00008491724,0.00022667817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020235419,0.00012002363,0.00024573551,0.00027523987,0.00016802941,0.000030472305,0.00013151397,0.000052547657,0.00017096342],"category_scores_gemma":[0.00013227647,0.00007751039,0.0003258815,0.00208674,0.00008015209,0.00007489305,0.000023644221,0.00029085597,0.0000044921944],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001044438,0.006996253,0.03562695,0.00008606718,0.0037693311,0.00020686976,0.0009527945,0.003462776,0.2996705,0.0025128392,0.047341645,0.59832954],"study_design_scores_gemma":[0.001251548,0.0005369382,0.32480177,0.000053706168,0.008565912,0.00034671818,0.00023764896,0.6248523,0.004758628,0.0017166787,0.03225326,0.0006248566],"about_ca_topic_score_codex":0.00003586964,"about_ca_topic_score_gemma":0.0000020686828,"teacher_disagreement_score":0.8837179,"about_ca_system_score_codex":0.000025655356,"about_ca_system_score_gemma":0.000021091202,"threshold_uncertainty_score":0.3160782},"labels":[],"label_agreement":null},{"id":"W2168728070","doi":"10.1017/s0317167100009756","title":"Damage of White Matter in the Parietal Lobe Results in Anomic Alexia of Kana","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Kana; Parietal lobe; Psychology; White matter; Action (physics); White (mutation); Neuroscience; Medicine; Computer science; Physics; Biology; Artificial intelligence; Kanji","score_opus":0.05302311584205827,"score_gpt":0.3208565431386705,"score_spread":0.26783342729661225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168728070","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849664,0.00011128977,0.000018283317,0.011297759,0.0001682784,0.00019533784,0.000015616615,0.0000048622433,0.0032221752],"genre_scores_gemma":[0.9937894,0.00009870066,0.0036713225,0.002350962,0.000067979614,0.0000025740424,3.2952255e-7,0.000006492096,0.000012272195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99702764,0.0003838887,0.0010974855,0.00034331027,0.0004801179,0.00066755776],"domain_scores_gemma":[0.99780226,0.00045406123,0.0007977731,0.0002387446,0.00021328333,0.000493852],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003998712,0.00018749523,0.00045915594,0.0009108676,0.0005017089,0.00008184338,0.0015348385,0.00012134073,0.00006704831],"category_scores_gemma":[0.0012414162,0.00011230042,0.00015417697,0.0014547565,0.0054872674,0.00040653237,0.000061128056,0.0015678043,7.3278426e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009948966,0.000051533592,0.9956125,0.000008080686,0.0000020230675,0.0011803359,0.00043535393,0.0005041708,0.0006025228,0.00071424287,0.00034875417,0.00044096337],"study_design_scores_gemma":[0.00038247328,0.011995893,0.9677136,0.0000490998,0.000015686604,0.008321479,0.00017680608,0.0005574915,0.000291632,0.009353311,0.001024844,0.000117714175],"about_ca_topic_score_codex":0.0013249588,"about_ca_topic_score_gemma":0.064862095,"teacher_disagreement_score":0.063537136,"about_ca_system_score_codex":0.000052107272,"about_ca_system_score_gemma":0.0013165976,"threshold_uncertainty_score":0.9972192},"labels":[],"label_agreement":null},{"id":"W2169459006","doi":"10.1177/1352458506070928","title":"Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology","year":2006,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":492,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Myelin; Luxol fast blue stain; Multiple sclerosis; Pathology; Relaxometry; Magnetic resonance imaging; Histopathology; Remyelination; Nuclear magnetic resonance; Chemistry; Medicine; Nuclear medicine; Central nervous system; Radiology; Physics; Internal medicine; Immunology; Spin echo","score_opus":0.1417452837391413,"score_gpt":0.3052127361807104,"score_spread":0.16346745244156907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169459006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87042046,0.00038593763,0.12351907,0.004350922,0.00012215508,0.00055430207,0.000022122751,0.00020891489,0.00041611586],"genre_scores_gemma":[0.9147881,0.00010367548,0.084228985,0.00039661408,0.00013377087,0.0000944911,0.000041348303,0.000056478097,0.00015653885],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99819523,0.000084002015,0.0005713439,0.00038845808,0.0002585634,0.00050240237],"domain_scores_gemma":[0.9989839,0.00015620085,0.00018384203,0.00032022753,0.00022163763,0.00013419749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002978929,0.000242738,0.00034428257,0.00035614433,0.0003951694,0.00005870511,0.00014969781,0.00006727625,0.00005439209],"category_scores_gemma":[0.000111426845,0.00017830214,0.00011436635,0.00028380912,0.00023122808,0.00028309337,0.000053861928,0.00067274953,0.00004503584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025796844,0.00044371575,0.6571402,0.000010727232,0.0000073524534,0.000087777786,0.0003267005,0.002156828,0.33461383,0.00026495208,0.0012888429,0.0034010988],"study_design_scores_gemma":[0.00474372,0.00019259522,0.95992225,0.0004879548,0.00006908626,0.00075504516,0.0002667752,0.014026115,0.015157327,0.0008253447,0.0032220932,0.00033168792],"about_ca_topic_score_codex":0.00016584291,"about_ca_topic_score_gemma":0.00015546563,"teacher_disagreement_score":0.3194565,"about_ca_system_score_codex":0.00022415433,"about_ca_system_score_gemma":0.00005405874,"threshold_uncertainty_score":0.727095},"labels":[],"label_agreement":null},{"id":"W2169504979","doi":"10.1007/978-3-642-15705-9_80","title":"Biomarkers for Identifying First-Episode Schizophrenia Patients Using Diffusion Weighted Imaging","year":2010,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Center for Research Resources; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Diffusion MRI; Classifier (UML); Support vector machine; Affine transformation; Feature selection; Population; Kernel (algebra); Magnetic resonance imaging; Mathematics; Medicine","score_opus":0.03512895276646575,"score_gpt":0.3378100518769688,"score_spread":0.302681099110503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2169504979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42193696,0.000009986421,0.57685,0.00049625646,0.00027314044,0.00034915356,0.0000020862276,0.000080307116,0.0000021389142],"genre_scores_gemma":[0.5444708,0.0000014007633,0.4551268,0.00029683195,0.00007598226,0.000013808714,0.000003904192,0.000010317288,1.7691163e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867624,0.0000070240144,0.00020988638,0.0005341717,0.00024119634,0.00033148786],"domain_scores_gemma":[0.99908644,0.00014660976,0.00008898073,0.00043007906,0.0001518455,0.00009602129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018597375,0.000144659,0.00015352502,0.00028887542,0.00036784474,0.00008248731,0.00030474528,0.000041668714,0.000003869352],"category_scores_gemma":[0.0001537892,0.00012582513,0.000052393738,0.00079855695,0.00027278496,0.00021813133,0.00019736208,0.0002554924,0.0000011350469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011285562,0.00021058226,0.23162177,0.000081960956,0.0000055280925,0.000009119222,0.00022915073,0.0006216406,0.26188117,0.00016369877,0.000028234484,0.50503427],"study_design_scores_gemma":[0.0010932694,0.000040848787,0.028303916,0.00014400338,0.000013206205,0.000032941047,2.988854e-7,0.9100903,0.050281245,0.009576469,0.00023578657,0.00018767352],"about_ca_topic_score_codex":0.00004126435,"about_ca_topic_score_gemma":0.00003295357,"teacher_disagreement_score":0.9094687,"about_ca_system_score_codex":0.000067497924,"about_ca_system_score_gemma":0.000044711775,"threshold_uncertainty_score":0.51309997},"labels":[],"label_agreement":null},{"id":"W2170383010","doi":"10.1007/s00256-008-0577-6","title":"Diffusion tensor imaging and fiber tractography of the median nerve at 1.5T: optimization of b value","year":2008,"lang":"en","type":"article","venue":"Skeletal Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; University Health Network; Mount Sinai Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Medicine; Fractional anisotropy; Effective diffusion coefficient; Nuclear medicine; Nerve fiber; Image quality; Median nerve; Tractography; Nuclear magnetic resonance; Magnetic resonance imaging; Radiology; Image (mathematics); Anatomy; Physics","score_opus":0.02166906536808541,"score_gpt":0.2826039610703224,"score_spread":0.26093489570223694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170383010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912913,0.00029932565,0.005075364,0.0022613178,0.00003385767,0.00028869748,0.000011078043,0.00003677185,0.0007022855],"genre_scores_gemma":[0.9853265,0.00027370156,0.014047393,0.00015798921,0.000030390931,0.000012258932,0.00001163706,0.000012572772,0.0001275474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99944466,0.000034952405,0.00018907356,0.00015381155,0.00007230206,0.000105198356],"domain_scores_gemma":[0.99948835,0.00007251525,0.00012295127,0.0002315744,0.000045601344,0.00003899863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042782092,0.000076999764,0.00019480915,0.00006642736,0.0000705721,5.355812e-7,0.00006373303,0.000042634125,0.000027862301],"category_scores_gemma":[0.000054522094,0.00005237153,0.00008191975,0.00015527521,0.0004848755,0.000025371684,0.000051793217,0.00009896257,5.1704296e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015101933,0.00033581664,0.6995048,0.00016854027,0.000060973678,0.000036806156,0.0006249779,0.0018352703,0.27682546,0.002855921,0.001710156,0.015890252],"study_design_scores_gemma":[0.0016633148,0.00030964473,0.9507275,0.0000949414,0.00014923105,0.0030721866,0.000043241434,0.015008319,0.020245584,0.0020280296,0.0064434987,0.00021446052],"about_ca_topic_score_codex":0.000013192203,"about_ca_topic_score_gemma":5.0180523e-7,"teacher_disagreement_score":0.25657988,"about_ca_system_score_codex":0.000010944459,"about_ca_system_score_gemma":0.000013615264,"threshold_uncertainty_score":0.2135649},"labels":[],"label_agreement":null},{"id":"W2170628400","doi":"10.1109/iembs.2007.4353343","title":"Analysis of Cardiac Diffusion Tensor Magnetic Resonance Images Using Sparse Representation","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Diffusion MRI; Heaviside step function; Sparse approximation; Representation (politics); Tensor (intrinsic definition); Artificial intelligence; Noise reduction; Noise (video); Magnetic resonance imaging; Pattern recognition (psychology); Structure tensor; Computer science; Diffusion; Signal-to-noise ratio (imaging); Basis (linear algebra); Algorithm; Mathematics; Image (mathematics); Physics; Mathematical analysis; Geometry; Radiology","score_opus":0.09405092578367139,"score_gpt":0.3739980428284507,"score_spread":0.27994711704477937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170628400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97855175,0.00035034897,0.01790654,0.00022884058,0.000017693523,0.00035094362,0.000011572953,0.00011225218,0.0024700637],"genre_scores_gemma":[0.96827555,0.00028843767,0.030943189,0.000066297354,0.000034133063,0.000013766304,0.000010720252,0.000013279978,0.00035463175],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99901044,0.0000031565305,0.00028494882,0.00031214772,0.00020659422,0.00018268719],"domain_scores_gemma":[0.9990768,0.00003402005,0.00015142633,0.00018230196,0.00047872274,0.00007671911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015907804,0.000108507214,0.0003165742,0.0002907431,0.00005870973,0.000016013248,0.000087867134,0.00004826023,0.000036320907],"category_scores_gemma":[0.00012669488,0.000101641315,0.000109603876,0.0010579927,0.000121680445,0.00010328045,0.000052820826,0.000115219744,0.0000015476185],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005565837,0.00005732296,0.47530532,0.000032644766,0.000023511473,0.0000018670577,0.00022996315,9.0723415e-7,0.49197406,0.0010961059,0.00010549764,0.031117136],"study_design_scores_gemma":[0.00020011995,0.00009769921,0.8659671,0.0001113564,0.0009181659,0.000008883988,0.00035774853,0.008493768,0.1209183,0.00065322017,0.0021276963,0.00014595437],"about_ca_topic_score_codex":0.000043394837,"about_ca_topic_score_gemma":6.597066e-7,"teacher_disagreement_score":0.39066178,"about_ca_system_score_codex":0.00003272357,"about_ca_system_score_gemma":0.000025081226,"threshold_uncertainty_score":0.41448125},"labels":[],"label_agreement":null},{"id":"W2170975082","doi":"10.1016/j.neuroimage.2010.03.072","title":"Age-related regional variations of the corpus callosum identified by diffusion tensor tractography","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":215,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Corpus callosum; Diffusion MRI; Tractography; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.033527946524591165,"score_gpt":0.3067254980784151,"score_spread":0.2731975515538239,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170975082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835739,0.000027446153,0.002852464,0.009095317,0.0002868233,0.0007821824,0.000075631215,0.00028169312,0.0030245439],"genre_scores_gemma":[0.9943877,0.000040700063,0.002561339,0.00095920474,0.000035793622,0.00003758965,0.000044819055,0.00003367469,0.0018992126],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998974,0.000031522373,0.00029458976,0.00028878753,0.00025150296,0.00015959133],"domain_scores_gemma":[0.9988457,0.00009178996,0.00017983891,0.0007052698,0.00009798552,0.0000794198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068549125,0.00012851287,0.00017103972,0.00007725883,0.00015200116,0.00001525305,0.00021642697,0.00008042415,0.00006244967],"category_scores_gemma":[0.00012237593,0.000094155155,0.00017238814,0.0004234522,0.0002871224,0.000063181666,0.00006440558,0.00058872224,0.0000071913023],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015016673,0.00027296098,0.009325532,0.000010730017,0.000007626546,0.000009704389,0.000029540914,5.061754e-7,0.9752545,0.0034058685,0.0108807655,0.0007872471],"study_design_scores_gemma":[0.0012359028,0.00010337595,0.85123885,0.000044969776,0.00016481294,0.00023396258,0.000007949261,0.0005180429,0.040949736,0.006751946,0.098540984,0.00020948904],"about_ca_topic_score_codex":0.00003217553,"about_ca_topic_score_gemma":0.0000057763227,"teacher_disagreement_score":0.9343048,"about_ca_system_score_codex":0.00000623468,"about_ca_system_score_gemma":0.000026209347,"threshold_uncertainty_score":0.3839536},"labels":[],"label_agreement":null},{"id":"W2171152497","doi":"10.1007/s00429-011-0321-1","title":"Structural organization of the prefrontal white matter pathways in the adult and aging brain measured by diffusion tensor imaging","year":2011,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Neuroscience; Psychology; Prefrontal cortex; Tractography; Magnetic resonance imaging; Medicine; Cognition; Radiology","score_opus":0.017907791253062827,"score_gpt":0.23075747573004704,"score_spread":0.2128496844769842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171152497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9913649,0.00008984519,0.0026063146,0.005347997,0.00004748032,0.0003801879,0.00001993392,0.000032373722,0.000110963454],"genre_scores_gemma":[0.99556434,0.000008377388,0.0005874632,0.003706503,0.000034033797,0.000006468018,0.000030211888,0.000015590897,0.000047029887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938047,0.000046943544,0.00015536071,0.00019532304,0.000121240126,0.00010065283],"domain_scores_gemma":[0.9995962,0.000028132614,0.00008926811,0.00019922652,0.00006406866,0.000023100923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058261714,0.0001077313,0.000106732004,0.00003861409,0.00011598176,0.0000125142915,0.00005930864,0.00004098851,0.000029793635],"category_scores_gemma":[0.000054634755,0.00006112327,0.000018439294,0.00017962068,0.000083614934,0.000095052375,0.000040319566,0.0001617819,1.9211603e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032190608,0.000010480599,0.866355,0.000029463694,0.00000435949,6.8250455e-7,0.0015825287,6.468653e-7,0.12087472,0.00035302978,0.002341903,0.008415001],"study_design_scores_gemma":[0.00042923962,0.000029196086,0.99295306,0.000038293907,0.00002721016,0.00011474155,0.0005123816,0.00021847055,0.0032090286,0.0021802469,0.00021900915,0.00006909835],"about_ca_topic_score_codex":0.000042847776,"about_ca_topic_score_gemma":0.0000121691655,"teacher_disagreement_score":0.12659809,"about_ca_system_score_codex":0.000012469759,"about_ca_system_score_gemma":0.000007996328,"threshold_uncertainty_score":0.24925347},"labels":[],"label_agreement":null},{"id":"W2171212208","doi":"10.1016/j.schres.2012.04.011","title":"Compassionate allowance for people with schizophrenia?","year":2012,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Alexithymia; White matter; Psychology; Schizophrenia (object-oriented programming); Fractional anisotropy; Toronto Alexithymia Scale; Corpus callosum; Clinical psychology; Psychiatry; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.16402728078681908,"score_gpt":0.4408004998953637,"score_spread":0.2767732191085446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171212208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9180281,0.0011195104,0.0503062,0.01965279,0.00016232427,0.004516289,0.000090427195,0.0008434957,0.0052808733],"genre_scores_gemma":[0.8426396,0.000059295307,0.15431173,0.00015309257,0.0004060188,0.0010329888,0.000049079357,0.00006315686,0.0012850426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978407,0.00006120129,0.00021133154,0.00040224975,0.0006299268,0.00085459475],"domain_scores_gemma":[0.99810684,0.00030409946,0.000052485575,0.0007011639,0.0004230338,0.00041235512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068287016,0.000179366,0.00030248627,0.00023814534,0.00045133484,0.000036281705,0.0002456755,0.000074003794,0.00006421855],"category_scores_gemma":[0.00016167754,0.00013494107,0.0000833297,0.000750506,0.00021865098,0.00020046605,0.00012341388,0.0006301857,0.000109218454],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.04269301,0.003719232,0.08267073,0.0011048731,0.00027726832,0.00004191096,0.0007712082,0.000042114338,0.12222826,0.47359657,0.14822365,0.12463118],"study_design_scores_gemma":[0.019377422,0.0022988669,0.280557,0.0008205349,0.0001637454,0.00064165116,0.00029787558,0.0028560734,0.066883706,0.028500367,0.5963398,0.0012629539],"about_ca_topic_score_codex":0.000017657927,"about_ca_topic_score_gemma":0.000013067789,"teacher_disagreement_score":0.44811615,"about_ca_system_score_codex":0.00008821174,"about_ca_system_score_gemma":0.00019270003,"threshold_uncertainty_score":0.5502737},"labels":[],"label_agreement":null},{"id":"W2171548242","doi":"10.3174/ajnr.a3283","title":"Evaluation of a Practical Visual MRI Rating Scale of Brain White Matter Hyperintensities for Clinicians Based on Largest Lesion Size Regardless of Location","year":2012,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institutes of Health","keywords":"Hyperintensity; Medicine; Rating scale; Reproducibility; Cognition; White matter; Visual analogue scale; Audiology; Montreal Cognitive Assessment; Magnetic resonance imaging; Cognitive impairment; Radiology; Physical therapy; Psychology; Psychiatry; Developmental psychology; Statistics","score_opus":0.1209894688439421,"score_gpt":0.4572396465836188,"score_spread":0.3362501777396767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171548242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90856713,0.000019765566,0.08117684,0.009783154,0.00006753329,0.00030832124,0.000007669709,0.0000068675963,0.00006272472],"genre_scores_gemma":[0.9637751,0.0000148133695,0.034563567,0.0015024014,0.00010156282,0.0000126980785,0.0000035968337,0.000019230463,0.0000070591495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984464,0.00036502976,0.0006524557,0.00011721409,0.00027620123,0.00014271424],"domain_scores_gemma":[0.99599767,0.0013214677,0.0013149013,0.00018966453,0.0011145137,0.00006177638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001328613,0.000093358525,0.0005048833,0.00013104224,0.000023548964,0.0000014415212,0.00006224376,0.000036459765,0.000011581447],"category_scores_gemma":[0.0017510366,0.00007894113,0.00011402922,0.00017854906,0.0003245392,0.00007330835,0.000012936264,0.00018544299,4.3233476e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006034981,0.002666802,0.551276,0.00038571827,0.0001267496,0.0000064819924,0.000877719,0.0047352077,0.40122986,0.00040168545,0.004056539,0.028202225],"study_design_scores_gemma":[0.0039546345,0.016625168,0.8728401,0.0006212665,0.0010295422,0.0011660754,0.001820943,0.042605363,0.05786027,0.00033212948,0.0008964824,0.00024803673],"about_ca_topic_score_codex":0.0000040889786,"about_ca_topic_score_gemma":4.8605483e-7,"teacher_disagreement_score":0.34336957,"about_ca_system_score_codex":0.000032817086,"about_ca_system_score_gemma":0.000159449,"threshold_uncertainty_score":0.32191256},"labels":[],"label_agreement":null},{"id":"W2172252744","doi":"10.1002/ana.20030","title":"Diffusion tensor fiber tracking shows distinct corticostriatal circuits in humans","year":2004,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":550,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; W. M. Keck Foundation","keywords":"Neuroscience; Diffusion MRI; Striatum; Tracing; Functional magnetic resonance imaging; Psychology; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.1683074227627158,"score_gpt":0.3952873803303854,"score_spread":0.22697995756766962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172252744","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9884361,0.000044225173,0.0006824329,0.009670175,0.000026061707,0.00028996493,0.000013397841,0.00007779224,0.00075983896],"genre_scores_gemma":[0.9965262,0.00006488927,0.00022662056,0.0030123857,0.000045476732,0.000023329343,0.000014564837,0.000019481226,0.00006709175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990958,0.000021662232,0.0002922491,0.0002694686,0.00009828342,0.00022251517],"domain_scores_gemma":[0.99942017,0.00006659134,0.000103295,0.00028896044,0.00006143477,0.000059567636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000062531435,0.00010261117,0.00024348145,0.00010690454,0.000034246084,0.000003205432,0.00009260995,0.00006690064,0.000046998168],"category_scores_gemma":[0.00014213315,0.000095840056,0.00006777677,0.00014977627,0.00009900648,0.000047130627,0.000044090844,0.00025116073,0.000010849188],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008920037,0.003706794,0.4757071,0.00020998683,0.000043094416,0.0014749634,0.0005374123,0.0004677291,0.4065416,0.008484252,0.0018097762,0.100125305],"study_design_scores_gemma":[0.0012819316,0.0009296229,0.96595126,0.000049569855,0.000020300373,0.00016335158,0.0000048363686,0.000049413116,0.015246758,0.006679502,0.009495624,0.0001278185],"about_ca_topic_score_codex":0.000030436193,"about_ca_topic_score_gemma":0.000015537506,"teacher_disagreement_score":0.49024418,"about_ca_system_score_codex":0.0000049689925,"about_ca_system_score_gemma":0.000022906415,"threshold_uncertainty_score":0.3908244},"labels":[],"label_agreement":null},{"id":"W2175900216","doi":"10.1016/j.media.2015.10.012","title":"Sparse Reconstruction Challenge for diffusion MRI: Validation on a physical phantom to determine which acquisition scheme and analysis method to use?","year":2015,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":90,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Cancer Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Computer science; Imaging phantom; Diffusion MRI; Artificial intelligence; Set (abstract data type); Data set; Iterative reconstruction; Neuroimaging; Pattern recognition (psychology); Protocol (science); Data mining; Machine learning; Medical physics; Magnetic resonance imaging; Nuclear medicine; Medicine; Radiology","score_opus":0.10680281640726129,"score_gpt":0.42206878803914777,"score_spread":0.31526597163188647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2175900216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32221928,0.0000058984438,0.6687893,0.008342382,0.000013030387,0.00043644675,0.000026593356,0.00010167896,0.00006535399],"genre_scores_gemma":[0.5740762,0.000036461486,0.42376256,0.0012295034,0.00019756224,0.0002689073,0.0002777956,0.000024144523,0.00012688222],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99802685,0.00009539791,0.0003529748,0.0006851916,0.00059199135,0.00024757354],"domain_scores_gemma":[0.9979675,0.00024909782,0.00011148639,0.00049344316,0.00045082867,0.00072766125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005739021,0.00020097129,0.00063943316,0.00089367287,0.0000997185,0.00005327125,0.00010461234,0.00009602678,0.00006131171],"category_scores_gemma":[0.0009047346,0.00017183764,0.00026084477,0.0029391781,0.0000444214,0.00017776803,0.00008710661,0.00016706705,0.000014435551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022513485,0.0036013944,0.041209817,0.00018742308,0.0060344506,0.00010182049,0.0020263202,0.0009840211,0.17088953,0.0013775728,0.0043611387,0.76697516],"study_design_scores_gemma":[0.0022821387,0.0014218893,0.020517835,0.00014115647,0.015103999,0.000049082242,0.00018128182,0.91915005,0.03371868,0.0016021922,0.005229607,0.00060210726],"about_ca_topic_score_codex":0.000057659476,"about_ca_topic_score_gemma":0.000034293582,"teacher_disagreement_score":0.918166,"about_ca_system_score_codex":0.00009225272,"about_ca_system_score_gemma":0.000037510832,"threshold_uncertainty_score":0.70073354},"labels":[],"label_agreement":null},{"id":"W2178761095","doi":"10.1016/j.neuroimage.2015.10.061","title":"A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; Stiftelsen för Strategisk Forskning; Vetenskapsrådet; Stiftelsen för Strategisk Forskning","keywords":"Computer science; Voxel; Diffusion MRI; Compressed sensing; Algorithm; Artificial intelligence; Image resolution; Regularization (linguistics); Computer vision; Pattern recognition (psychology); Magnetic resonance imaging","score_opus":0.10546400796500113,"score_gpt":0.32256278767892554,"score_spread":0.2170987797139244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2178761095","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15099028,0.00023486336,0.8434868,0.0025758129,0.000098315875,0.0011055877,0.000025934129,0.0004886095,0.0009938133],"genre_scores_gemma":[0.8169026,0.00004125658,0.18170875,0.00081849145,0.0001781091,0.00004656697,0.00011529884,0.00005204732,0.00013686891],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987153,0.00004011652,0.00024480166,0.0004986269,0.00020527634,0.00029591352],"domain_scores_gemma":[0.99911886,0.000049754697,0.000083151186,0.00040664533,0.00015189945,0.00018970155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016524056,0.0001864754,0.00025687442,0.0001210786,0.00018365624,0.000046432317,0.00006232347,0.00004610225,0.0000014755415],"category_scores_gemma":[0.00015450017,0.00017893674,0.000066880944,0.00014391766,0.00013580415,0.0001683743,0.00012254261,0.00021434222,0.0000027237822],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054374285,0.00057832926,0.0026581613,0.00030739643,0.000015952994,0.000061847175,0.00025996994,0.00043531632,0.93054366,0.0028522376,0.027345117,0.03439829],"study_design_scores_gemma":[0.004173116,0.00036842463,0.021163369,0.00011836228,0.00016677138,0.0006939772,0.00012588526,0.92626613,0.015218564,0.0034420907,0.027821952,0.00044135365],"about_ca_topic_score_codex":0.000077837474,"about_ca_topic_score_gemma":7.86063e-7,"teacher_disagreement_score":0.92583084,"about_ca_system_score_codex":0.00006603127,"about_ca_system_score_gemma":0.000034734454,"threshold_uncertainty_score":0.72968286},"labels":[],"label_agreement":null},{"id":"W2180021448","doi":"","title":"Rapid alterations in diffusion-weighted images with anatomic correlates in a rodent model of status epilepticus.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital","funders":"","keywords":"Piriform cortex; Status epilepticus; Retrosplenial cortex; Hippocampal formation; Medicine; Entorhinal cortex; Neuroscience; Hippocampus; Effective diffusion coefficient; Cortex (anatomy); Pilocarpine; Temporal lobe; Epilepsy; Epileptogenesis; Amygdala; Pathology; Magnetic resonance imaging; Psychology; Internal medicine; Radiology","score_opus":0.038755409744673223,"score_gpt":0.2804857950530955,"score_spread":0.24173038530842228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180021448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984341,0.0001727492,0.0111605795,0.0014110117,0.000009628806,0.0012340542,0.000016369304,0.00007636811,0.0015781914],"genre_scores_gemma":[0.9906333,0.0008364542,0.006582368,0.0001506936,0.000008751567,0.0014548362,0.000021690941,0.000017866247,0.00029403422],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99912924,0.000015180786,0.0002606027,0.00021142985,0.00011543505,0.00026813056],"domain_scores_gemma":[0.999496,0.000044529243,0.00007187025,0.00025693566,0.000045603163,0.00008509141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007232058,0.00009877721,0.00020031208,0.00022427402,0.000022434726,0.0000066907605,0.000059170125,0.000032319575,0.000006369294],"category_scores_gemma":[0.000033270604,0.000079813726,0.000025529735,0.0003942417,0.00006406025,0.00008488351,0.000027842605,0.00016705258,0.0000010141036],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010848909,0.0026389086,0.7782527,0.00008810543,0.00002815314,0.00013009858,0.0008241635,0.005756124,0.009418359,0.004299155,0.0008076084,0.19667171],"study_design_scores_gemma":[0.0031006353,0.00007336001,0.849241,0.00009716571,0.00003871629,0.000041378866,0.00008256492,0.13729085,0.0055232844,0.0036895922,0.00062403793,0.0001973977],"about_ca_topic_score_codex":0.000087370885,"about_ca_topic_score_gemma":0.000052803553,"teacher_disagreement_score":0.19647431,"about_ca_system_score_codex":0.000079172714,"about_ca_system_score_gemma":0.000034964374,"threshold_uncertainty_score":0.32547092},"labels":[],"label_agreement":null},{"id":"W2181270872","doi":"10.3389/fnhum.2015.00585","title":"Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study","year":2015,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Manitoba; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"Diffusion MRI; Default mode network; White matter; Tractography; Resting state fMRI; Neuroscience; Human Connectome Project; Salience (neuroscience); Artificial intelligence; Task-positive network; Psychology; Neuroimaging; Computer science; Pattern recognition (psychology); Functional magnetic resonance imaging; Medicine; Functional connectivity; Magnetic resonance imaging; Radiology","score_opus":0.0468302688176115,"score_gpt":0.3404702059645135,"score_spread":0.293639937146902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2181270872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9579098,0.000096563985,0.04016605,0.00030750316,0.00008842277,0.0012123395,0.000010516238,0.000070547176,0.00013825859],"genre_scores_gemma":[0.99172354,0.000018704679,0.007573796,0.0005063004,0.000022978782,0.00008301435,0.0000020060158,0.000018947254,0.000050728424],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99841475,0.00008618262,0.00034096607,0.0006125905,0.00026074087,0.00028475912],"domain_scores_gemma":[0.9991544,0.00003887881,0.00015804177,0.0003608512,0.00009219648,0.00019562228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023781988,0.00017726838,0.00032903938,0.00018527318,0.00014693488,0.00004217898,0.00017512718,0.000026247411,6.3262763e-7],"category_scores_gemma":[0.000119415745,0.000154229,0.000026179832,0.00041729977,0.00069696154,0.00031439384,0.00007030024,0.0001959605,4.7397243e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059725666,0.00038446859,0.9933541,0.000018578266,0.0000010910979,0.000023234394,0.0005638452,0.0007757444,0.003350472,0.000054319145,0.0011699017,0.0002445269],"study_design_scores_gemma":[0.001367469,0.0005105708,0.95318496,0.00007049352,0.000045215565,0.00006782669,0.0006001069,0.040716253,0.000063513624,0.0030752355,0.00013103413,0.00016733566],"about_ca_topic_score_codex":0.000037021306,"about_ca_topic_score_gemma":0.000005719622,"teacher_disagreement_score":0.04016915,"about_ca_system_score_codex":0.000023388819,"about_ca_system_score_gemma":0.00002430432,"threshold_uncertainty_score":0.6289276},"labels":[],"label_agreement":null},{"id":"W2182563485","doi":"10.1016/j.nicl.2015.11.019","title":"Translating state-of-the-art spinal cord MRI techniques to clinical use: A systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI","year":2015,"lang":"en","type":"review","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":225,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; McMaster University; University of Toronto","funders":"","keywords":"Spinal cord; Medicine; Neuroscience; Diffusion MRI; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.5799579797304347,"score_gpt":0.6054766709107983,"score_spread":0.02551869118036354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182563485","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006736092,0.98440385,0.0018182291,0.0017188012,0.0005338166,0.010822315,0.0001457532,0.00031655957,0.00017328931],"genre_scores_gemma":[0.00003766317,0.95623666,0.039765235,0.00265897,0.00035233295,0.0004942943,0.000024419136,0.00017621297,0.00025423904],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9813652,0.0030670182,0.01237024,0.0017617388,0.0009017542,0.0005340571],"domain_scores_gemma":[0.9843155,0.0062458655,0.00474568,0.002997463,0.0010712486,0.00062424754],"candidate_categories":["metaresearch","metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.010940905,0.00089430035,0.012239175,0.00020365721,0.00012112868,0.000034552068,0.000935744,0.0004909473,0.000005452446],"category_scores_gemma":[0.028601378,0.00059913984,0.00288424,0.0009290572,0.001447128,0.00015458417,0.0008721152,0.0030644801,0.000018001523],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014040388,0.0004143739,0.00048093006,0.5429722,0.0002525803,0.000057992867,0.0000081579565,1.4764096e-8,9.0859436e-7,0.000044512162,0.0076090423,0.44801888],"study_design_scores_gemma":[0.00038578978,0.0024102735,0.00015546501,0.5293326,0.0050252397,0.0002805455,0.000008103346,0.0000095565165,0.0000021323763,0.000098566125,0.4619305,0.0003612442],"about_ca_topic_score_codex":0.000002977933,"about_ca_topic_score_gemma":0.00000233562,"teacher_disagreement_score":0.45432147,"about_ca_system_score_codex":0.00005531605,"about_ca_system_score_gemma":0.00081181974,"threshold_uncertainty_score":0.999646},"labels":[],"label_agreement":null},{"id":"W2182991436","doi":"10.1007/978-3-642-22092-0_23","title":"Anisotropic Diffusion of Tensor Fields for Fold Shape Analysis on Surfaces","year":2011,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Diffusion MRI; Sulcus; Anisotropy; Isotropy; Geometry; Anisotropic diffusion; Surface (topology); Fold (higher-order function); Tractography; Computer science; Physics; Anatomy; Mathematics; Optics; Biology; Magnetic resonance imaging","score_opus":0.06319671666251693,"score_gpt":0.3342538968793565,"score_spread":0.2710571802168396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2182991436","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39742476,0.000009459647,0.6020365,0.0003201323,0.000024194951,0.0001445478,0.0000014316446,0.000025994286,0.000012986851],"genre_scores_gemma":[0.69384557,0.0000060498774,0.3056015,0.00051679416,0.00001674168,0.0000082128945,9.88587e-7,0.0000029817018,0.000001138759],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992961,0.0000060343773,0.00013322999,0.0002900579,0.00013357698,0.00014099038],"domain_scores_gemma":[0.9993827,0.00012289826,0.00005575028,0.00032786277,0.00007380897,0.000037007663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008685277,0.000072779396,0.00016937812,0.00021046987,0.000055125314,0.000006989197,0.00019736942,0.000033073742,0.000011449895],"category_scores_gemma":[0.000059183058,0.000054614688,0.00006081941,0.0009095125,0.00013032752,0.00003918065,0.000058094884,0.00008281944,4.9196126e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002234816,0.00081670826,0.33399853,0.00012400525,0.00006309849,0.000016177011,0.0023578021,0.0192854,0.073148526,0.002747114,0.000040224495,0.5671789],"study_design_scores_gemma":[0.00034381283,0.00070449326,0.15852015,0.00005420333,0.00006982157,0.0000045902066,9.885475e-7,0.69888854,0.12892723,0.01231398,0.00005460102,0.0001176079],"about_ca_topic_score_codex":0.000020837842,"about_ca_topic_score_gemma":0.000008300327,"teacher_disagreement_score":0.67960316,"about_ca_system_score_codex":0.000016618676,"about_ca_system_score_gemma":0.000022507045,"threshold_uncertainty_score":0.22271223},"labels":[],"label_agreement":null},{"id":"W2184177600","doi":"10.62721/diffusion-fundamentals.18.669","title":"Velocity-sensitised Magnetic Resonance Imaging of foams","year":2013,"lang":"en","type":"article","venue":"Diffusion fundamentals.","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Materials science; Venturi effect; Magnetic resonance imaging; Magnetic field; Rheology; Optics; Nuclear magnetic resonance; Mechanics; Physics; Composite material","score_opus":0.028707815078479876,"score_gpt":0.30339981011966,"score_spread":0.27469199504118014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184177600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98768246,0.0013437268,0.0019053821,0.0028270003,0.000053736654,0.00084031536,0.000015591171,0.00021714215,0.0051146303],"genre_scores_gemma":[0.9796003,0.00017855005,0.01740972,0.0014156416,0.000030301393,0.00008056517,0.000023922694,0.000026166908,0.001234795],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99911684,0.000014490483,0.00024799278,0.00024298484,0.00019101359,0.0001866747],"domain_scores_gemma":[0.9993476,0.000034426852,0.00008006814,0.0003625054,0.0000798559,0.00009552476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042516553,0.0001179487,0.000198812,0.00007279597,0.00007546359,0.0000143234665,0.000081649276,0.000026342792,0.0006406447],"category_scores_gemma":[0.000022463511,0.00010759221,0.000069809284,0.00017652924,0.00012981873,0.00007377221,0.00009485179,0.000112057736,0.00008563285],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003250882,0.00039261393,0.063543886,0.000053378215,0.0000029715952,0.000018686886,0.00013065679,4.0109805e-7,0.53627235,0.000991363,0.010205586,0.3883556],"study_design_scores_gemma":[0.002308011,0.0002688481,0.8215304,0.0003527253,0.000048224934,0.00017469263,0.0002923346,0.0051454306,0.087206416,0.00461749,0.07771498,0.0003404502],"about_ca_topic_score_codex":0.000086633925,"about_ca_topic_score_gemma":4.3703199e-7,"teacher_disagreement_score":0.7579865,"about_ca_system_score_codex":0.000039501818,"about_ca_system_score_gemma":0.000015856587,"threshold_uncertainty_score":0.701461},"labels":[],"label_agreement":null},{"id":"W2186454342","doi":"10.1503/jpn.130079","title":"Cognitive impairment with and without depression history: an analysis of white matter microstructure","year":2014,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Late life depression; White matter; Corpus callosum; Fractional anisotropy; Cingulum (brain); Depression (economics); Superior longitudinal fasciculus; Psychology; Internal capsule; Diffusion MRI; Medicine; Internal medicine; Hyperintensity; Corona radiata (embryology); Cardiology; Psychiatry; Magnetic resonance imaging; Cognition; Neuroscience; Radiology","score_opus":0.018963606810451044,"score_gpt":0.31604544411668034,"score_spread":0.2970818373062293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2186454342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98406786,0.00012195435,0.014811832,0.0008126711,0.000058169982,0.000072485345,0.0000034226848,0.0000057562816,0.000045849352],"genre_scores_gemma":[0.9884775,0.000048115617,0.010010101,0.0013986387,0.000026356993,9.851465e-7,4.955269e-7,0.0000052636387,0.000032538475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994542,0.000023940647,0.00015978579,0.0001586599,0.00013094314,0.00007249908],"domain_scores_gemma":[0.9994451,0.000010580373,0.00025973213,0.00011027675,0.00006915277,0.000105150924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000101192716,0.00007079275,0.00019461087,0.00014788055,0.00006985451,0.000006666374,0.00005321545,0.000018262284,0.000006898866],"category_scores_gemma":[0.000009334308,0.000045613673,0.00003300529,0.00017028178,0.00018590866,0.0001221311,0.000021936623,0.0001260037,3.3617894e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016306306,0.0000724162,0.9830769,0.00001818667,0.000008363537,9.930886e-7,0.00008823526,0.000014768667,0.01628193,0.000035838275,0.00007045052,0.00016890766],"study_design_scores_gemma":[0.00046026122,0.00083298545,0.9956661,0.00008713027,0.00041682526,0.0004039033,0.000035845715,0.0008796584,0.00067962805,0.00011030052,0.00037659073,0.000050811155],"about_ca_topic_score_codex":0.0000014272664,"about_ca_topic_score_gemma":0.0000019454505,"teacher_disagreement_score":0.015602302,"about_ca_system_score_codex":0.000007397018,"about_ca_system_score_gemma":0.000031829433,"threshold_uncertainty_score":0.18600716},"labels":[],"label_agreement":null},{"id":"W2188887891","doi":"10.1007/978-3-642-38899-6_52","title":"Atlases of Cardiac Fiber Differential Geometry","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Helicoid; Normalization (sociology); Curvature; Computer science; Artificial intelligence; Geometry; Algorithm; Mathematics; Pattern recognition (psychology)","score_opus":0.03304658311309931,"score_gpt":0.30185528153546654,"score_spread":0.2688086984223672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188887891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003955586,0.0003252802,0.9891316,0.0004539316,0.00027423957,0.00062437163,0.000021123124,0.00011625746,0.0050975843],"genre_scores_gemma":[0.53207195,0.00034220677,0.45902032,0.0009286029,0.0009898203,0.000047240013,0.000048142225,0.00009836907,0.006453348],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985756,0.000005164792,0.00026733044,0.0005459361,0.00037930752,0.00022664882],"domain_scores_gemma":[0.99877375,0.00016003204,0.00014578679,0.00068761775,0.00014666651,0.00008613395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068273315,0.00022773918,0.0004409175,0.00034761356,0.000053115902,0.000024987929,0.0003381667,0.00013236742,0.00023841132],"category_scores_gemma":[0.000036854617,0.000187183,0.0001250285,0.00020549819,0.0005730426,0.00006236,0.0002785726,0.00040988013,0.00003321221],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012678715,0.00005494163,0.0003437288,0.00014750587,0.000021557504,0.000012594378,0.00006688291,0.0003932335,0.006277232,0.003796334,0.00041214423,0.98846114],"study_design_scores_gemma":[0.0017537278,0.0021523496,0.017386466,0.0062052556,0.0005731258,0.00038099368,6.6483705e-7,0.055922322,0.2819414,0.43653974,0.19344774,0.0036961918],"about_ca_topic_score_codex":0.000012248343,"about_ca_topic_score_gemma":5.7319915e-7,"teacher_disagreement_score":0.984765,"about_ca_system_score_codex":0.00006575892,"about_ca_system_score_gemma":0.00010356638,"threshold_uncertainty_score":0.76331013},"labels":[],"label_agreement":null},{"id":"W2193227159","doi":"10.3233/jad-150049","title":"Non-Linear Association between Cerebral Amyloid Deposition and White Matter Microstructure in Cognitively Healthy Older Adults","year":2015,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; U.S. Department of Defense","keywords":"Fractional anisotropy; White matter; Pittsburgh compound B; Diffusion MRI; Amyloid (mycology); Neuroimaging; Psychology; Cognition; Medicine; Internal medicine; Neuroscience; Pathology; Magnetic resonance imaging; Cognitive impairment","score_opus":0.035232916105586674,"score_gpt":0.334160483947288,"score_spread":0.2989275678417013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2193227159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98733664,0.0005925228,0.0012551595,0.01032878,0.00004341411,0.0003336939,0.0000469716,0.0000147171995,0.000048081958],"genre_scores_gemma":[0.9920298,0.000029265278,0.0055298274,0.002040829,0.00029690002,0.0000069585835,0.000032572392,0.000018772658,0.000015073614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991348,0.000029724304,0.00033488672,0.00013828123,0.00021439414,0.00014791827],"domain_scores_gemma":[0.9989218,0.000020705469,0.00031985255,0.000090208465,0.00026632007,0.0003811294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001328437,0.0001039508,0.00021988919,0.00011815708,0.000032990825,0.000015664184,0.000042170235,0.00005269809,0.000011500481],"category_scores_gemma":[0.00002998556,0.00009045621,0.00005861264,0.0001159985,0.00002457325,0.0001785406,0.000022463597,0.00027611238,0.000006216675],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049380725,0.0001003169,0.9936978,0.000024423662,0.000051119296,0.0000365546,0.00018328172,0.0000032781445,0.00008737812,0.0000010881112,0.0043107774,0.0010101603],"study_design_scores_gemma":[0.0024514107,0.00014608284,0.9956211,0.00021537823,0.0004293084,0.000052899057,0.000061573155,0.00011499347,0.0004716758,0.0001780983,0.00017238874,0.00008513403],"about_ca_topic_score_codex":0.000007779598,"about_ca_topic_score_gemma":8.0205876e-7,"teacher_disagreement_score":0.008287951,"about_ca_system_score_codex":0.00007287501,"about_ca_system_score_gemma":0.0001064913,"threshold_uncertainty_score":0.36886972},"labels":[],"label_agreement":null},{"id":"W2194834710","doi":"10.3171/2015.6.jns142203","title":"Identifying preoperative language tracts and predicting postoperative functional recovery using HARDI q-ball fiber tractography in patients with gliomas","year":2015,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Cancer Institute; National Defense Science and Engineering Graduate; National Institutes of Health; U.S. Department of Defense","keywords":"Diffusion MRI; Medicine; Tractography; White matter; Segmentation; Glioma; Fiber tract; Surgical planning; Brain mapping; Neuroscience; Radiology; Magnetic resonance imaging; Artificial intelligence; Computer science; Psychology","score_opus":0.08442622157027459,"score_gpt":0.3243280770015919,"score_spread":0.2399018554313173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2194834710","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99797386,0.00012746875,0.0012236884,0.00022582641,0.00010733206,0.00022688314,0.000009283113,0.000021388532,0.00008425576],"genre_scores_gemma":[0.99452025,0.000016487897,0.0049820067,0.00032664856,0.00008342278,0.0000040371874,0.0000055110227,0.000024547944,0.000037117665],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99889606,0.00006269245,0.00039094183,0.00017678371,0.00032298508,0.00015051076],"domain_scores_gemma":[0.99901533,0.00012532996,0.0003061154,0.00010649687,0.00029690677,0.00014982105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023309632,0.00013187903,0.00028226525,0.00041762865,0.00005691108,0.000045022098,0.000036437083,0.000039376464,0.0000062381873],"category_scores_gemma":[0.00019551438,0.00010139129,0.00007161299,0.0003836232,0.00005312322,0.0005726862,0.000022272423,0.0003788769,4.850974e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012540346,0.00040599608,0.98172736,0.000025530553,0.00004793542,0.0003563512,0.0007396056,0.00060591154,0.012315441,0.0000066800076,0.00042287936,0.0020922597],"study_design_scores_gemma":[0.0018517573,0.0006716328,0.9936062,0.00034489812,0.00007483254,0.00077468785,0.00024962466,0.00018439612,0.0017478429,0.000050920444,0.00031029538,0.00013292186],"about_ca_topic_score_codex":0.000006243438,"about_ca_topic_score_gemma":0.0000011590766,"teacher_disagreement_score":0.0118788155,"about_ca_system_score_codex":0.000055109715,"about_ca_system_score_gemma":0.00010914332,"threshold_uncertainty_score":0.41346171},"labels":[],"label_agreement":null},{"id":"W2198859253","doi":"10.1371/journal.pone.0138122","title":"Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Maastricht Universitair Medisch Centrum; Universiteit Maastricht","keywords":"Tractography; Deconvolution; Imaging phantom; Human Connectome Project; Computer science; Voxel; Artificial intelligence; Diffusion MRI; Probabilistic logic; Pattern recognition (psychology); Algorithm; Magnetic resonance imaging; Physics; Optics; Functional connectivity","score_opus":0.09028309085164263,"score_gpt":0.2916264425202657,"score_spread":0.20134335166862308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2198859253","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9198872,0.00015472253,0.07227465,0.0029779072,0.000012076221,0.0011240247,0.000023550238,0.00037639405,0.003169494],"genre_scores_gemma":[0.8523232,0.000007158157,0.14648812,0.0004533061,0.000028608547,0.00011666742,0.000034704764,0.000021816468,0.0005264301],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99917567,0.000018055416,0.00017705852,0.00022413288,0.0002144918,0.00019056865],"domain_scores_gemma":[0.9995024,0.000035830442,0.000059874754,0.00019370475,0.000067318615,0.00014085262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000094051924,0.000103666716,0.00022674089,0.000025002926,0.000029526343,0.000010085991,0.000048643375,0.000038846803,0.00003755704],"category_scores_gemma":[0.000069474896,0.00009277767,0.000018215096,0.00010490559,0.000090440626,0.00006142598,0.000029227826,0.00016819595,0.00002102684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014580509,0.010750101,0.0674092,0.00030142465,0.00036928602,0.00019854715,0.00107411,0.00014376418,0.86636084,0.0011732425,0.019667162,0.03109425],"study_design_scores_gemma":[0.044464994,0.00845176,0.009747393,0.003544266,0.0013537585,0.00031288076,0.002443946,0.21272945,0.69147146,0.002530456,0.020492839,0.0024567775],"about_ca_topic_score_codex":0.000040737374,"about_ca_topic_score_gemma":0.0000032645814,"teacher_disagreement_score":0.2125857,"about_ca_system_score_codex":0.000123051,"about_ca_system_score_gemma":0.00006554993,"threshold_uncertainty_score":0.37833634},"labels":[],"label_agreement":null},{"id":"W2206916168","doi":"10.1159/000439045","title":"Cognitive Function and 3-Tesla Magnetic Resonance Imaging Tractography of White Matter Hyperintensities in Elderly Persons","year":2015,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of Toronto; Kingston General Hospital","funders":"","keywords":"Hyperintensity; Magnetic resonance imaging; White matter; Cognition; Tractography; Psychology; Diffusion MRI; Medicine; Neuroscience; Radiology","score_opus":0.020355807171047888,"score_gpt":0.2756507647423577,"score_spread":0.2552949575713098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2206916168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691779,0.017042123,0.009691402,0.0008277239,0.00003259558,0.0006456368,0.000054430428,0.00004631008,0.0024818762],"genre_scores_gemma":[0.9979803,0.000654985,0.000687173,0.0004277081,0.00001693351,0.00009019206,0.00003205844,0.000019933303,0.000090730886],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991146,0.000032429376,0.00021556987,0.00032738026,0.0001172089,0.00019281465],"domain_scores_gemma":[0.99953735,0.00007545022,0.00007635494,0.000076961216,0.00015040777,0.00008348075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009122599,0.00016099078,0.00022200483,0.00024882826,0.00007578346,0.000015643604,0.00002484826,0.0000347891,0.000036995476],"category_scores_gemma":[0.000036898942,0.00015890857,0.000050542436,0.000313571,0.00021874208,0.000123537,0.00004325156,0.00014103201,0.0000016609908],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031700777,0.000153779,0.91489726,0.000050442475,0.000019785912,0.000006503543,0.0009939541,1.0036765e-7,0.0003639729,0.000062184896,0.0002118288,0.082923174],"study_design_scores_gemma":[0.0025919802,0.00037906785,0.98639834,0.00013170042,0.00038579863,0.000037671496,0.0069193374,0.00013160978,0.000066803215,0.0019663076,0.0008142438,0.00017713475],"about_ca_topic_score_codex":0.000049693917,"about_ca_topic_score_gemma":0.000013651207,"teacher_disagreement_score":0.08274604,"about_ca_system_score_codex":0.0000052052255,"about_ca_system_score_gemma":0.00002243382,"threshold_uncertainty_score":0.6480103},"labels":[],"label_agreement":null},{"id":"W2218066725","doi":"10.1161/strokeaha.115.011229","title":"Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects","year":2015,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Medical Research Council","keywords":"Medicine; Brain size; Hyperintensity; Magnetic resonance imaging; White matter; Longitudinal study; Cross-sectional study; Cardiology; Pathology; Radiology","score_opus":0.0683254785697802,"score_gpt":0.3635266156793527,"score_spread":0.29520113710957246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2218066725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99611497,0.00008716082,0.0009424091,0.001977565,0.000011440885,0.0002640868,0.0000073474343,0.00006208643,0.0005329284],"genre_scores_gemma":[0.9942815,0.000010066773,0.0051883245,0.00030293362,0.000009003907,0.00001830369,0.000011607074,0.000013278826,0.00016499366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999469,0.000052955555,0.00016017006,0.00010279444,0.000110662826,0.00010446121],"domain_scores_gemma":[0.9994984,0.000044932738,0.000064350264,0.00023001028,0.000043505635,0.00011875864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014936528,0.00006521464,0.00013209764,0.000055974473,0.0000656677,0.000004394903,0.000044044704,0.000030945444,0.000007417787],"category_scores_gemma":[0.0000707765,0.0000554803,0.000018071247,0.00008471509,0.00007944946,0.000043101165,0.00008169123,0.00039057908,0.000002306197],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010992153,0.00014835488,0.9950038,0.00007496659,0.0000034776378,0.00002166278,0.0006989813,0.0000129463515,0.0033191675,0.0001257061,0.00018874838,0.00029223767],"study_design_scores_gemma":[0.0008577763,0.000085873886,0.9918594,0.00062940206,0.00003775592,0.000016174901,0.0003519731,0.0015798752,0.0035671312,0.00076232874,0.0001684246,0.000083886516],"about_ca_topic_score_codex":0.000007179565,"about_ca_topic_score_gemma":0.0000011435538,"teacher_disagreement_score":0.004245915,"about_ca_system_score_codex":0.000014871604,"about_ca_system_score_gemma":0.000018306644,"threshold_uncertainty_score":0.22624211},"labels":[],"label_agreement":null},{"id":"W2220266781","doi":"10.1007/978-3-319-24574-4_3","title":"Multimodal Cortical Parcellation Based on Anatomical and Functional Brain Connectivity","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Artificial intelligence; Human Connectome Project; Functional magnetic resonance imaging; Spurious relationship; Robustness (evolution); Pattern recognition (psychology); Cluster analysis; Connectome; Weighting; Functional connectivity; Machine learning; Neuroscience; Psychology","score_opus":0.06352721780385819,"score_gpt":0.330669639901175,"score_spread":0.2671424220973168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2220266781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025082198,0.000025715479,0.9919305,0.0037353663,0.00010632079,0.00037458126,0.0000076675105,0.00010454763,0.0012071164],"genre_scores_gemma":[0.91045964,0.0000027588167,0.086602785,0.0025942684,0.00020252944,0.00000830981,0.0000200016,0.000020340514,0.00008937519],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985282,0.000015851556,0.00017628903,0.00066757656,0.00042518612,0.00018694282],"domain_scores_gemma":[0.99866796,0.0006235252,0.000068741865,0.00036016168,0.00012627768,0.00015335505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030115276,0.00019863062,0.0002503918,0.00022828112,0.000100596255,0.00003137998,0.0000984862,0.00014697605,0.00002389719],"category_scores_gemma":[0.00022308635,0.00017382379,0.000040237308,0.00011933038,0.00058193225,0.00004767762,0.00009565907,0.0006309025,0.0000056145213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075871794,0.00040923155,0.007514211,0.00014488121,0.000021150418,0.00019963259,0.00017819289,0.086536154,0.006675704,0.058526944,0.0010895643,0.83794564],"study_design_scores_gemma":[0.0005649864,0.00028152144,0.0058380384,0.00013858265,0.000012071514,0.000058093614,4.8334854e-8,0.9348786,0.0006101721,0.055424783,0.0019847644,0.0002083431],"about_ca_topic_score_codex":0.0000037497618,"about_ca_topic_score_gemma":0.0000037010886,"teacher_disagreement_score":0.9079514,"about_ca_system_score_codex":0.00016947745,"about_ca_system_score_gemma":0.00022785534,"threshold_uncertainty_score":0.7088328},"labels":[],"label_agreement":null},{"id":"W2222869326","doi":"10.1016/j.media.2015.10.011","title":"Strengths and weaknesses of state of the art fiber tractography pipelines – A comprehensive in-vivo and phantom evaluation study using Tractometer","year":2015,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; Deutsche Forschungsgemeinschaft","keywords":"Tractography; Metric (unit); Imaging phantom; Computer science; Consistency (knowledge bases); Artificial intelligence; Machine learning; Data mining; Diffusion MRI; Magnetic resonance imaging; Engineering; Medicine; Nuclear medicine; Radiology","score_opus":0.0852731398949972,"score_gpt":0.4298637285706721,"score_spread":0.34459058867567494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222869326","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958,0.00024612053,0.0031301845,0.00036929862,0.000006920985,0.00036905025,0.0000116921165,0.000010681387,0.000056026965],"genre_scores_gemma":[0.99674183,0.00010908898,0.003021753,0.0000656675,0.000010478733,0.000015491167,0.000004586363,0.000007024459,0.000024052708],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99869126,0.000107450316,0.00035078096,0.00019570936,0.00056660676,0.00008820912],"domain_scores_gemma":[0.9989288,0.00024601028,0.0001587675,0.00023785607,0.00033152965,0.000097026954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003916479,0.000092179085,0.00037340462,0.0002940606,0.000020060077,0.00000705835,0.00006225934,0.000026450456,0.000054617736],"category_scores_gemma":[0.0005491016,0.00006056178,0.00007951073,0.0011238385,0.00023959797,0.00007687042,0.000051462695,0.00012124522,1.4276472e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029339312,0.00375003,0.75980914,0.00024871997,0.0016268961,0.00005430455,0.0038067074,0.00029168584,0.08371328,0.0000064543,0.0006714133,0.14572796],"study_design_scores_gemma":[0.007877582,0.0006452349,0.7544301,0.0004009869,0.013929143,0.00008478909,0.0038481625,0.17936678,0.03537626,0.0013784738,0.0022049085,0.00045756943],"about_ca_topic_score_codex":0.00011152607,"about_ca_topic_score_gemma":0.00006243259,"teacher_disagreement_score":0.17907509,"about_ca_system_score_codex":0.000009499494,"about_ca_system_score_gemma":0.0000523053,"threshold_uncertainty_score":0.24696375},"labels":[],"label_agreement":null},{"id":"W2229909148","doi":"10.6084/m9.figshare.1216667.v1","title":"CST Mask in ICBM152 space","year":2014,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Space (punctuation); Computer science; Mathematics","score_opus":0.11457397241012524,"score_gpt":0.3683917273883437,"score_spread":0.25381775497821846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2229909148","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036259525,0.0010013015,0.005895409,0.087083824,0.00018591927,0.006931547,0.15570946,0.006370329,0.70056266],"genre_scores_gemma":[0.97426265,0.000004999655,0.0066219224,0.0019312217,0.00013712129,0.00031956442,0.014780535,0.000031648528,0.0019103126],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996282,0.0000061818328,0.00006873096,0.0001345606,0.000058028087,0.000104328996],"domain_scores_gemma":[0.99964684,0.000031323176,0.000022880486,0.00023574369,0.000018725917,0.000044507604],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000015131805,0.000054088374,0.00008087722,0.00003782012,0.000017355025,0.000005478395,0.000056063363,0.0000272118,0.010941138],"category_scores_gemma":[0.00028590256,0.000050411694,0.000023250463,0.00011947803,0.0000025186434,0.000027972226,0.000034608885,0.000115026436,0.0008475408],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011961788,0.000094069306,0.001922812,0.00014821555,0.0000024268977,0.000024889452,0.000046935176,0.000012493659,0.0025159894,0.0012201911,0.97703403,0.016965983],"study_design_scores_gemma":[0.00022521683,0.000033564032,0.015694316,0.0005542167,0.0000023705863,0.000017965318,0.0000058569,0.0007281052,0.0035401224,0.00067707256,0.9784475,0.000073704185],"about_ca_topic_score_codex":0.000002162343,"about_ca_topic_score_gemma":0.0000017410895,"teacher_disagreement_score":0.9380031,"about_ca_system_score_codex":0.000016038197,"about_ca_system_score_gemma":0.000010450249,"threshold_uncertainty_score":0.99993044},"labels":[],"label_agreement":null},{"id":"W2231927503","doi":"10.1155/2016/6029241","title":"Simultaneous Assessment of White Matter Changes in Microstructure and Connectedness in the Blind Brain","year":2016,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"H. Lundbeck A/S; Danmarks Frie Forskningsfond; Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"White matter; Corpus callosum; Diffusion MRI; Fractional anisotropy; Neuroscience; Voxel; Social connectedness; Psychology; Magnetic resonance imaging; Blindness; Medicine; Radiology","score_opus":0.03530728386644837,"score_gpt":0.34566196415317535,"score_spread":0.31035468028672697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2231927503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9812426,0.0000065429253,0.0010998506,0.017217496,0.000013641147,0.00031475775,0.000029680048,0.000015572286,0.000059883576],"genre_scores_gemma":[0.9975434,0.000008049794,0.00074799184,0.0016121108,0.000018409335,0.000019586876,0.0000024940448,0.000007139654,0.000040844745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948776,0.000031181313,0.00012290757,0.0001600456,0.00008106929,0.00011702374],"domain_scores_gemma":[0.9991512,0.00063777366,0.000047328682,0.000117192285,0.000023374112,0.000023171215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047640307,0.00007914251,0.00014071008,0.000056444787,0.000025709283,0.000004573422,0.000064389,0.00003541347,0.00002786213],"category_scores_gemma":[0.00011218219,0.000042418167,0.000011514711,0.00011983913,0.000090242924,0.000025601697,0.000042373027,0.0001380496,5.1003906e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017358265,0.00012471358,0.650249,0.000087982684,0.0000036282024,0.00007996113,0.0003555838,0.0000871637,0.34560725,0.00030260524,0.00057340984,0.0023550887],"study_design_scores_gemma":[0.0012378438,0.0001422174,0.9905767,0.00010485831,0.0000103575485,0.00011557087,0.00004073683,0.0027130723,0.0040477794,0.00042903828,0.0005034057,0.000078410274],"about_ca_topic_score_codex":0.000010421573,"about_ca_topic_score_gemma":0.00007983985,"teacher_disagreement_score":0.34155947,"about_ca_system_score_codex":0.000015551523,"about_ca_system_score_gemma":0.000009361697,"threshold_uncertainty_score":0.17297627},"labels":[],"label_agreement":null},{"id":"W2236225132","doi":"10.1002/mrm.26071","title":"Q‐space truncation and sampling in diffusion spectrum imaging","year":2016,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Consortia for Improving Medicine with Innovation and Technology","keywords":"Sampling (signal processing); Truncation (statistics); Spectrum (functional analysis); Diffusion; Nuclear magnetic resonance; Diffusion MRI; k-space; Space (punctuation); Physics; Statistical physics; Computer science; Mathematics; Mathematical analysis; Statistics; Medicine; Magnetic resonance imaging; Optics; Radiology; Fourier transform; Quantum mechanics","score_opus":0.04134616623408731,"score_gpt":0.34313900023516963,"score_spread":0.3017928340010823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2236225132","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8380789,0.010181666,0.01930781,0.1293247,0.00006704975,0.0007943423,0.000002262,0.00013217868,0.0021110594],"genre_scores_gemma":[0.9860224,0.0045496756,0.007702845,0.000792724,0.00010924308,0.00007560217,0.0000026687685,0.000021849346,0.00072298927],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989404,0.000021511372,0.0002879793,0.0003482171,0.00016660814,0.0002352856],"domain_scores_gemma":[0.9994062,0.0001589321,0.000051324834,0.00029435684,0.00002029336,0.00006887769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002247864,0.00012344941,0.00023886135,0.00021227109,0.000028973984,0.0000038636626,0.00006734738,0.000031714153,0.00007105958],"category_scores_gemma":[0.00026378603,0.00008194859,0.000013035736,0.00032637926,0.00018747906,0.00005857151,0.000043409607,0.00014732622,0.000003700356],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007356382,0.00005980988,0.35988227,0.00003375889,3.2465766e-7,0.00004092591,0.00019808457,4.61591e-7,0.08159758,0.002248718,0.0003607198,0.5555038],"study_design_scores_gemma":[0.00255301,0.00018485062,0.93119043,0.0014819097,0.000008582671,0.00008597385,0.0000761084,0.00080596586,0.0009867105,0.011829951,0.05067249,0.0001240042],"about_ca_topic_score_codex":0.00011685334,"about_ca_topic_score_gemma":0.00003416144,"teacher_disagreement_score":0.5713082,"about_ca_system_score_codex":0.000078462035,"about_ca_system_score_gemma":0.00001757777,"threshold_uncertainty_score":0.33417663},"labels":[],"label_agreement":null},{"id":"W2253627718","doi":"10.1016/j.mri.2015.12.032","title":"Importance of extended spatial coverage for quantitative susceptibility mapping of iron-rich deep gray matter","year":2015,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Quantitative susceptibility mapping; Globus pallidus; Computer science; Neuroscience; Gray (unit); Physics; Psychology; Magnetic resonance imaging; Basal ganglia; Medicine; Nuclear medicine","score_opus":0.0532588597182677,"score_gpt":0.3459175589204995,"score_spread":0.2926586992022318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2253627718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6056538,0.003830603,0.38531396,0.0016010687,0.000069940565,0.0014523217,0.00006631001,0.00008794661,0.0019240552],"genre_scores_gemma":[0.86649257,0.000042449676,0.13273749,0.00031180706,0.000031793268,0.000112116526,0.00001793841,0.000029787554,0.00022405501],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854404,0.000030269572,0.00052662205,0.0003988571,0.0002384023,0.00026179312],"domain_scores_gemma":[0.99860936,0.00013511599,0.00027096254,0.00055236643,0.000345883,0.000086329084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028367978,0.00016529733,0.00038596484,0.000088598674,0.00003909328,0.000007977765,0.00014780388,0.000026649133,0.000049748956],"category_scores_gemma":[0.00025404568,0.00015714881,0.000092870105,0.000229476,0.0002455816,0.000093997085,0.0000643326,0.00012366424,0.0000040771797],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003732615,0.00031227883,0.859687,0.0004085687,0.0000056502104,0.000012406369,0.00067909725,0.000028967688,0.043786574,0.0013366583,0.0020546298,0.09131492],"study_design_scores_gemma":[0.002795292,0.00060010824,0.9370912,0.00029767156,0.0000770312,0.00004666824,0.00043492796,0.015668854,0.015519644,0.015995802,0.0111268805,0.00034595706],"about_ca_topic_score_codex":0.000076250064,"about_ca_topic_score_gemma":0.000012328301,"teacher_disagreement_score":0.26083875,"about_ca_system_score_codex":0.000054838172,"about_ca_system_score_gemma":0.00006925211,"threshold_uncertainty_score":0.6408342},"labels":[],"label_agreement":null},{"id":"W2257429363","doi":"","title":"Novel Decomposition of Tensor Distance into Shape and Orientation Distances","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Orientation (vector space); Anisotropy; Tensor (intrinsic definition); Scalar (mathematics); Interpolation (computer graphics); Mathematics; Fractional anisotropy; Geometry; Measure (data warehouse); White noise; Mathematical analysis; Physics; White matter; Computer science; Artificial intelligence; Optics; Image (mathematics); Statistics","score_opus":0.03504798679884674,"score_gpt":0.38034551748719764,"score_spread":0.3452975306883509,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2257429363","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34271893,0.00010793794,0.6507353,0.0042133825,0.000008579137,0.00022855749,0.0000048337683,0.00010477373,0.0018777116],"genre_scores_gemma":[0.8653999,0.00005947211,0.13394305,0.0004663453,0.000012192268,0.000006762464,0.000013163132,0.000003080163,0.00009605466],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999658,0.0000015293612,0.00011089982,0.00011938161,0.00006164442,0.00004855819],"domain_scores_gemma":[0.9997684,0.000012299087,0.000043110624,0.00010163828,0.000044875786,0.00002970339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000019567718,0.000045313725,0.000080300335,0.00002308706,0.000032493932,0.0000040056793,0.000020760564,0.000012871892,0.00001106128],"category_scores_gemma":[0.0000081828575,0.00003725382,0.000014225004,0.000089394176,0.000040220013,0.00008141052,0.0000048605866,0.000032391657,4.865416e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010563608,0.00024218595,0.006699763,0.000043159187,0.0000040299356,0.0000013947966,0.0001288286,0.0000030494955,0.8157065,0.11248029,0.00036361124,0.064221576],"study_design_scores_gemma":[0.0021042312,0.0009702626,0.6521227,0.00026141247,0.00009848324,0.000102226106,0.00024328355,0.00915834,0.24005155,0.075173356,0.019385483,0.00032870605],"about_ca_topic_score_codex":0.000005083787,"about_ca_topic_score_gemma":0.000002353384,"teacher_disagreement_score":0.6454229,"about_ca_system_score_codex":0.000011272696,"about_ca_system_score_gemma":0.000004692664,"threshold_uncertainty_score":0.15191667},"labels":[],"label_agreement":null},{"id":"W2259452444","doi":"10.1089/brain.2014.0237","title":"Structure, Integrity, and Function of the Hypoplastic Corpus Callosum in Spina Bifida Myelomeningocele","year":2014,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health","keywords":"Corpus callosum; Dichotic listening; Spina bifida; Fractional anisotropy; Diffusion MRI; Psychology; Anatomy; Neuroscience; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.037596026441725376,"score_gpt":0.3017971270643748,"score_spread":0.2642011006226494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2259452444","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97182584,0.000021306123,0.024724582,0.0026135875,0.000060918086,0.0002905437,0.000007166432,0.000052284242,0.0004037741],"genre_scores_gemma":[0.9984409,0.000003518006,0.0009544982,0.00046909743,0.000035413235,0.000015328487,0.0000019980498,0.000010800377,0.000068411304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994066,0.00005821896,0.00012817407,0.00020547993,0.000093398514,0.00010815072],"domain_scores_gemma":[0.99921876,0.0003678653,0.000076718075,0.0002638289,0.000037494472,0.000035332767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016126219,0.00008600905,0.00016816462,0.000056272427,0.000050179246,0.0000055758724,0.000057686593,0.000049977505,0.0000062583345],"category_scores_gemma":[0.00081202295,0.00006294182,0.00002943418,0.0002153802,0.00011268145,0.000048525137,0.000070500995,0.00030590803,4.495712e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024080307,0.00023031633,0.4514697,0.00020971241,0.000019740259,0.0000026559987,0.0001275682,0.00003579521,0.37403548,0.06784089,0.00087264413,0.10491471],"study_design_scores_gemma":[0.0007111842,0.00021832917,0.9267781,0.00008110127,0.000021221407,0.000043197928,0.000014061182,0.002155669,0.02072884,0.045382176,0.0037731037,0.00009301386],"about_ca_topic_score_codex":0.00011925579,"about_ca_topic_score_gemma":0.00013967772,"teacher_disagreement_score":0.47530842,"about_ca_system_score_codex":0.000028705525,"about_ca_system_score_gemma":0.000028915116,"threshold_uncertainty_score":0.2566693},"labels":[],"label_agreement":null},{"id":"W2261986951","doi":"10.1007/978-3-319-15090-1_10","title":"Visualization of Diffusion Propagator and Multiple Parameter Diffusion Signal","year":2015,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Visualization; Diffusion MRI; Voxel; Computer science; Glyph (data visualization); Tractography; Diffusion; Diffusion imaging; Artificial intelligence; Diffusion map; Computer vision; Dimensionality reduction; Physics; Magnetic resonance imaging; Nonlinear dimensionality reduction","score_opus":0.09585173528790579,"score_gpt":0.3656442987827219,"score_spread":0.2697925634948161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2261986951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053812526,0.0013761586,0.91660666,0.00020337375,0.00007842879,0.004226729,0.0001153545,0.00046720522,0.023113573],"genre_scores_gemma":[0.755667,0.008914264,0.10961171,0.000580404,0.0005280426,0.000181226,0.0027605416,0.0008680455,0.12088881],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882394,0.000008793711,0.000463233,0.00030042953,0.00029935717,0.00010423642],"domain_scores_gemma":[0.9988994,0.000087173605,0.00041190838,0.00024140353,0.0002490551,0.00011106766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001320067,0.0002457071,0.00044306228,0.00016642912,0.000070566064,0.00002223587,0.000042277825,0.00019908322,0.000038664926],"category_scores_gemma":[0.00010474158,0.00020673232,0.000048353028,0.00005308632,0.00011324505,0.000055302437,0.00010421741,0.00010050787,0.0000022555912],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013780646,0.0008168819,0.0022064855,0.0046576005,0.0000875841,0.000009741894,0.0013756888,0.0000058292076,0.03962005,0.9301706,0.002124688,0.018787045],"study_design_scores_gemma":[0.004815584,0.002267505,0.00081338617,0.007297529,0.0015124945,0.0002731831,0.00016730465,0.5119274,0.012286728,0.36260766,0.09435082,0.0016803956],"about_ca_topic_score_codex":0.000002678528,"about_ca_topic_score_gemma":6.834034e-7,"teacher_disagreement_score":0.8069949,"about_ca_system_score_codex":0.000028969876,"about_ca_system_score_gemma":0.00003020219,"threshold_uncertainty_score":0.84303},"labels":[],"label_agreement":null},{"id":"W2262750511","doi":"10.1161/str.43.suppl_1.a4033","title":"Abstract 4033: Structural Integrity of the Corticospinal Tract Correlated with the Degree of Hand Recovery in Pediatric Patients Following Stroke","year":2012,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network","funders":"","keywords":"Cerebral peduncle; Corticospinal tract; Diffusion MRI; Medicine; Fractional anisotropy; Tractography; Stroke (engine); Pyramidal tracts; Region of interest; Pediatric stroke; Nuclear medicine; Internal capsule; Ischemic stroke; Magnetic resonance imaging; Radiology; Anatomy; White matter; Cardiology; Ischemia","score_opus":0.05015838496368698,"score_gpt":0.30796162488125134,"score_spread":0.2578032399175644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2262750511","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983446,0.00012025172,0.00028651464,0.00015896355,0.000105409206,0.00046832042,0.000052146526,0.000017539773,0.0004462253],"genre_scores_gemma":[0.99890625,0.000013967675,0.000894772,0.000037474547,0.00003879136,0.000014744164,0.00000773978,0.000013848856,0.000072414616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991191,0.00002354661,0.0002812742,0.00012394381,0.00025077807,0.00020133541],"domain_scores_gemma":[0.9992119,0.00009656232,0.00025564226,0.00032123234,0.00006884417,0.00004582163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011805555,0.00011537749,0.00020614384,0.00005527974,0.00006564395,0.000005479572,0.00013432238,0.000052529307,0.000010530249],"category_scores_gemma":[0.00009129669,0.00006080373,0.00011381352,0.0002104526,0.000100591926,0.00011064145,0.000040113504,0.00047122108,6.5118456e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115283634,0.00013770873,0.99304146,0.000026764179,0.000014549306,0.0000010213088,0.000098499266,0.000012781293,0.0034852037,0.000035612808,0.00003700043,0.0029941257],"study_design_scores_gemma":[0.0007324319,0.00017928582,0.99475443,0.000052762825,0.0001118022,0.000005569662,0.00005944069,0.000033709784,0.0039255004,0.000036890662,0.000048280366,0.0000599079],"about_ca_topic_score_codex":0.000062986306,"about_ca_topic_score_gemma":0.000016435391,"teacher_disagreement_score":0.0029342177,"about_ca_system_score_codex":0.000037794332,"about_ca_system_score_gemma":0.000053804953,"threshold_uncertainty_score":0.24795042},"labels":[],"label_agreement":null},{"id":"W2263537162","doi":"10.1161/str.45.suppl_1.tmp118","title":"Abstract T MP118: Microinfarct Disruption of Cerebral White Matter: A Longitudinal Diffusion Tractography Analysis","year":2014,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Titan Medical (Canada)","funders":"","keywords":"Medicine; Diffusion MRI; Lesion; Fractional anisotropy; Region of interest; White matter; Nuclear medicine; Effective diffusion coefficient; Magnetic resonance imaging; Hyperintensity; Radiology; Pathology","score_opus":0.02616798143469206,"score_gpt":0.31649176128136297,"score_spread":0.2903237798466709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2263537162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9449051,0.000021673353,0.050328553,0.00096378964,0.000018329727,0.00019348093,0.000057794263,0.00009172062,0.003419577],"genre_scores_gemma":[0.98903567,0.000022194432,0.010377818,0.0001379795,0.000052497264,0.00001820069,0.00007927291,0.000016160639,0.0002601939],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911106,0.000012980098,0.00026674013,0.0002684221,0.00016967926,0.00017113265],"domain_scores_gemma":[0.9992448,0.000030173353,0.00015531453,0.00043125357,0.000056573524,0.00008189038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000832056,0.0001257901,0.00028565983,0.0003011993,0.000054842076,0.00001092349,0.000086047,0.00004612584,0.0002674477],"category_scores_gemma":[0.000010035059,0.00010946722,0.00030452694,0.0004212939,0.000075720156,0.000063298845,0.000030222864,0.00016085563,0.000016437527],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044562825,0.00015997188,0.9309063,0.00003921577,0.000079238125,0.0000018968368,0.000026637641,0.0000128317215,0.06572896,0.00016268072,0.00031138078,0.0025263573],"study_design_scores_gemma":[0.00033552095,0.0000813827,0.99237853,0.000027412885,0.00040250566,0.000014532841,0.000013056475,0.0003823047,0.00421803,0.00021968006,0.0018338264,0.00009319084],"about_ca_topic_score_codex":0.000043443564,"about_ca_topic_score_gemma":0.000010101496,"teacher_disagreement_score":0.061510928,"about_ca_system_score_codex":0.000014106814,"about_ca_system_score_gemma":0.000008065542,"threshold_uncertainty_score":0.44639435},"labels":[],"label_agreement":null},{"id":"W2266699239","doi":"10.1093/cercor/bhv308","title":"The Corticocortical Structural Connectivity of the Human Insula","year":2015,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":312,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Hôpital Notre-Dame; Institut Universitaire de Gériatrie de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"","keywords":"Insula; Neuroscience; Tractography; Posterior cingulate; Precuneus; Cytoarchitecture; Psychology; Supramarginal gyrus; Entorhinal cortex; Human brain; Functional magnetic resonance imaging; Diffusion MRI; Hippocampus; Magnetic resonance imaging; Medicine","score_opus":0.09143753737255118,"score_gpt":0.37280994357773595,"score_spread":0.2813724062051848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2266699239","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949924,0.00003911879,0.0004067878,0.0020089925,0.00008362919,0.00038080334,0.0000047106514,0.000075727236,0.0020078572],"genre_scores_gemma":[0.9989179,0.0000022429424,0.00038736753,0.00026903694,0.000059413574,0.000019245219,0.0000027675062,0.000011966905,0.0003300951],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992917,0.000030175128,0.00019360417,0.00014603151,0.00018871331,0.00014976338],"domain_scores_gemma":[0.99911433,0.000055708526,0.000095738455,0.00052584265,0.000116556585,0.00009182722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007861741,0.0000818667,0.00013481306,0.0000114206505,0.00018066433,0.000010842535,0.00017235886,0.000031385036,0.000010795911],"category_scores_gemma":[0.00018933046,0.00004212238,0.00007251609,0.00014554862,0.00033462883,0.00003435784,0.00011114775,0.0002048688,0.000003525387],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010062217,0.00012829622,0.68682426,0.00002781349,0.000041527048,0.0000072678154,0.0001796911,0.000006268119,0.06144381,0.23704295,0.0043358095,0.00986169],"study_design_scores_gemma":[0.0005075292,0.00012308075,0.9575353,0.000016438455,0.000042958567,0.00006693366,0.00005406459,0.0005967399,0.008636314,0.028835382,0.0035151953,0.00007003415],"about_ca_topic_score_codex":0.000028425779,"about_ca_topic_score_gemma":0.0000100092675,"teacher_disagreement_score":0.27071106,"about_ca_system_score_codex":0.00003528878,"about_ca_system_score_gemma":0.00006469602,"threshold_uncertainty_score":0.17177008},"labels":[],"label_agreement":null},{"id":"W2271674807","doi":"","title":"Microstructural white matter changes mediated age- related cognitive decline in the Montreal Cognitive Assessment (MoCA)","year":2016,"lang":"en","type":"article","venue":"Scientific Repository (Petra Christian University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Cognitive decline; White matter; Cognition; Diffusion MRI; Psychology; Effects of sleep deprivation on cognitive performance; Gerontology; Medicine; Cardiology; Internal medicine; Magnetic resonance imaging; Psychiatry; Cognitive impairment; Disease; Radiology; Dementia","score_opus":0.02178047862863062,"score_gpt":0.2782523756910521,"score_spread":0.25647189706242146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2271674807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96962196,0.000047415644,0.0024676162,0.0064704013,0.00034486342,0.00093563803,0.00015464013,0.00018137797,0.019776072],"genre_scores_gemma":[0.9849381,0.000018440249,0.00046599744,0.00037163426,0.00004592871,0.00000849406,0.00013489209,0.00001868644,0.013997846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982916,0.00015230193,0.00024384836,0.0006461293,0.00033676365,0.00032935763],"domain_scores_gemma":[0.9988444,0.00023974598,0.0001850938,0.0003801447,0.00022125532,0.00012938764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024014259,0.00019909992,0.00022508089,0.0004087082,0.00041529268,0.000085074564,0.0002858441,0.00009560111,0.00007998126],"category_scores_gemma":[0.00005211741,0.00013517593,0.00008704265,0.0009545915,0.0008778106,0.00015626679,0.000113858594,0.00029750814,0.00003931664],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009473482,0.0009889051,0.6957881,0.0001297468,0.0002326843,0.011167551,0.004861364,0.0000026110724,0.26262072,0.0008209834,0.0148334745,0.0076065166],"study_design_scores_gemma":[0.002603707,0.00016741428,0.9767991,0.0004264302,0.00019028333,0.00039245002,0.0022351153,0.000056929828,0.0058949874,0.00023053786,0.010706597,0.00029648095],"about_ca_topic_score_codex":0.000073979456,"about_ca_topic_score_gemma":0.00012787867,"teacher_disagreement_score":0.28101096,"about_ca_system_score_codex":0.00015467296,"about_ca_system_score_gemma":0.000112173075,"threshold_uncertainty_score":0.5512314},"labels":[],"label_agreement":null},{"id":"W2273155963","doi":"10.1007/978-3-642-38868-2_31","title":"Group-Wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Spherical harmonics; Correspondence problem; Computer science; Entropy (arrow of time); Minification; Algorithm; Artificial intelligence; Mathematics; Pattern recognition (psychology); Mathematical analysis; Mathematical optimization; Physics","score_opus":0.025309178946464592,"score_gpt":0.3097011722853255,"score_spread":0.2843919933388609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273155963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1466035,0.000016540724,0.85029805,0.002332528,0.00013761513,0.00045084892,0.000001006213,0.00014775898,0.000012151692],"genre_scores_gemma":[0.6831568,0.0000046418263,0.31531727,0.0013976144,0.000078166064,0.00003155556,0.000004305433,0.000007471589,0.0000021930862],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854326,0.000034453034,0.00024305674,0.0005145344,0.00031698827,0.00034772625],"domain_scores_gemma":[0.9989458,0.00027401594,0.000060599785,0.00041978515,0.00014192636,0.0001579159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016828113,0.00014165507,0.00017595041,0.0001709344,0.00013102178,0.00007144868,0.00029779476,0.000056042903,0.00007478728],"category_scores_gemma":[0.00028031913,0.00011915734,0.000036518933,0.0009752707,0.0006340209,0.00024229742,0.0001288845,0.0003044365,0.00003573554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008359068,0.00042857227,0.058015686,0.00004038583,0.000005482137,0.00007590895,0.0005310513,0.0047389255,0.31247285,0.0028974053,0.00017054322,0.6205396],"study_design_scores_gemma":[0.0004898323,0.00023788436,0.052962344,0.000066800814,0.000007933274,0.00021311511,7.907156e-7,0.90965885,0.019814204,0.016231757,0.0001246899,0.00019179659],"about_ca_topic_score_codex":0.000023005252,"about_ca_topic_score_gemma":0.0000029551054,"teacher_disagreement_score":0.9049199,"about_ca_system_score_codex":0.00007606177,"about_ca_system_score_gemma":0.00008921481,"threshold_uncertainty_score":0.48590952},"labels":[],"label_agreement":null},{"id":"W2273771579","doi":"10.1089/brain.2015.0387","title":"Plasticity of Interhemispheric Temporal Lobe White Matter Pathways Due to Early Disruption of Corpus Callosum Development in Spina Bifida","year":2015,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Corpus callosum; Anterior commissure; White matter; Diffusion MRI; Neuroscience; Psychology; Anatomy; Fractional anisotropy; Cingulum (brain); Decussation; Temporal lobe; Commissure; Tractography; Biology; Epilepsy; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.07007561285151678,"score_gpt":0.3199479911161679,"score_spread":0.2498723782646511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273771579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89434445,0.000006984243,0.103900604,0.00086195616,0.000055385455,0.00044503727,0.000013743172,0.000049625334,0.00032220955],"genre_scores_gemma":[0.9843031,5.3669226e-7,0.015217775,0.00027050736,0.000033227254,0.00006926928,0.0000071598956,0.000017464154,0.00008091782],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990241,0.000038748545,0.00032135862,0.0002669014,0.00018635375,0.00016251772],"domain_scores_gemma":[0.9992729,0.00010066923,0.0001393722,0.00022997863,0.00013589457,0.00012118555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023259225,0.00012614933,0.0003211951,0.00008672274,0.000016760581,0.000004537219,0.00008883142,0.0000561638,0.000015038361],"category_scores_gemma":[0.00029467,0.00012091185,0.000039203234,0.00030350796,0.00005955428,0.00006727264,0.00010170488,0.00014405779,0.000010611726],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040107605,0.00058095355,0.9015983,0.00015765146,0.00001234047,0.000022941023,0.00094846805,0.000048739326,0.08720588,0.00029833108,0.0020908627,0.0066344794],"study_design_scores_gemma":[0.0008465936,0.00034352098,0.9301503,0.0002280237,0.000008971243,0.00003214058,0.00005895524,0.00022209517,0.06515271,0.0007043589,0.002092628,0.00015972261],"about_ca_topic_score_codex":0.00020710513,"about_ca_topic_score_gemma":0.00010992059,"teacher_disagreement_score":0.08995869,"about_ca_system_score_codex":0.00011570584,"about_ca_system_score_gemma":0.0001101534,"threshold_uncertainty_score":0.4930642},"labels":[],"label_agreement":null},{"id":"W2274502676","doi":"10.1038/tp.2015.216","title":"Conduct disorder in females is associated with reduced corpus callosum structural integrity independent of comorbid disorders and exposure to maltreatment","year":2016,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"VINNOVA; Vetenskapsrådet; Stockholms Läns Landsting; Karolinska Institutet; Stiftelsen för Strategisk Forskning","keywords":"Fractional anisotropy; Corpus callosum; White matter; Psychology; Diffusion MRI; Psychiatry; Internal medicine; Clinical psychology; Physiology; Medicine; Magnetic resonance imaging; Neuroscience","score_opus":0.05934138757850891,"score_gpt":0.3486620478158702,"score_spread":0.28932066023736125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274502676","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96866906,0.00020570833,0.0022668864,0.027997455,0.00003418608,0.00053963927,0.00014501708,0.00004011956,0.00010193635],"genre_scores_gemma":[0.98732036,0.000051337007,0.012223078,0.0002270139,0.000013585083,0.0000421332,0.00003797965,0.000016535712,0.00006797083],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999177,0.000021403317,0.00022791533,0.000253585,0.00018942486,0.00013067688],"domain_scores_gemma":[0.99959815,0.00005266573,0.00006940926,0.00015802556,0.00004954104,0.00007223158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049247596,0.0001328042,0.0002034001,0.0000814909,0.00003754125,0.000003590474,0.00005220911,0.000057016132,0.00004736643],"category_scores_gemma":[0.000010602418,0.00008591457,0.00003785965,0.00015796068,0.00009200332,0.00005701613,0.000008525348,0.0001287785,8.2626576e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024337566,0.00017793418,0.9882361,0.000021947477,0.000039374212,0.0000010122848,0.00016030154,0.000013637456,0.0036177817,0.0038628762,0.00004915363,0.0035764526],"study_design_scores_gemma":[0.0024001147,0.000351789,0.9853537,0.00020537106,0.000038208538,0.000014861965,0.0000502033,0.00002537362,0.00046218908,0.0108692385,0.00010970989,0.000119236895],"about_ca_topic_score_codex":0.000060900355,"about_ca_topic_score_gemma":0.0005799832,"teacher_disagreement_score":0.027770441,"about_ca_system_score_codex":0.000027029178,"about_ca_system_score_gemma":0.000080890204,"threshold_uncertainty_score":0.35034946},"labels":[],"label_agreement":null},{"id":"W2274948889","doi":"10.1001/jamapsychiatry.2015.3375","title":"Mediation of Developmental Risk Factors for Psychosis by White Matter Microstructure in Young Adults With Psychotic Experiences","year":2016,"lang":"en","type":"article","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Medical Research Council; Cardiff University; Wellcome Trust","keywords":"Psychosis; Psychology; Young adult; White matter; Mediation; Developmental psychology; Psychiatry; Clinical psychology; Medicine; Magnetic resonance imaging; Sociology","score_opus":0.009802066465755217,"score_gpt":0.2799803194094808,"score_spread":0.2701782529437256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274948889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98388237,0.00006074716,0.011091543,0.003828324,0.00017095939,0.0006325992,0.00012806458,0.000046088182,0.00015929998],"genre_scores_gemma":[0.93231946,0.00006723234,0.06681523,0.0003272194,0.00005146106,0.0002662396,0.000035790126,0.00002552057,0.00009182834],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990909,0.000011223321,0.00027322152,0.00031461407,0.00013526801,0.00017477186],"domain_scores_gemma":[0.9994687,0.000036910238,0.00018883208,0.0001999413,0.000047424888,0.00005821318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042940403,0.00014527379,0.00017810058,0.00008914397,0.00004596691,0.000008206926,0.0001030592,0.000077293815,0.00007942472],"category_scores_gemma":[0.000015954036,0.000088546505,0.000045950288,0.00018198023,0.00007479669,0.00012194474,0.0000091606735,0.000096117925,0.0000028989753],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003670485,0.00009431433,0.978711,0.000045581684,0.000010302121,8.518644e-8,0.0016186011,2.2126382e-7,0.0025628388,0.00001846263,0.015375421,0.0011960865],"study_design_scores_gemma":[0.0036552101,0.00023957457,0.9832291,0.00039945508,0.00002633356,0.000020811,0.0030831634,0.000011401279,0.007098912,0.00072573655,0.0013032499,0.00020703647],"about_ca_topic_score_codex":0.000023449897,"about_ca_topic_score_gemma":0.00004305029,"teacher_disagreement_score":0.055723682,"about_ca_system_score_codex":0.00003457303,"about_ca_system_score_gemma":0.00003105852,"threshold_uncertainty_score":0.36108217},"labels":[],"label_agreement":null},{"id":"W2278001415","doi":"10.3389/fnana.2016.00012","title":"A Digital Atlas of Middle to Large Brain Vessels and Their Relation to Cortical and Subcortical Structures","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Universität Ulm; Bundesministerium für Bildung und Forschung","keywords":"Neuroscience; Cortex (anatomy); Temporal lobe; Cytoarchitecture; Anatomy; Cerebral cortex; Neuroimaging; Lobe; Psychology; Medicine","score_opus":0.021203535322260755,"score_gpt":0.2903973633769404,"score_spread":0.2691938280546796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278001415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87957937,0.00006315576,0.11481095,0.0048179342,0.000036088437,0.0003961868,0.00003260693,0.000044637854,0.00021907156],"genre_scores_gemma":[0.99088293,0.000024686531,0.008210029,0.0006918934,0.000017791062,0.000022456374,0.0000026354096,0.000017066031,0.0001305062],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925184,0.000016978654,0.00019253943,0.0002777236,0.00008728172,0.00017362752],"domain_scores_gemma":[0.9994699,0.00010505805,0.000028706881,0.00019797248,0.000028695425,0.00016970834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004985413,0.00010080495,0.00020123145,0.0001344438,0.000027977288,0.000010886264,0.000052828353,0.000040211155,0.0000036045094],"category_scores_gemma":[0.00035550498,0.00006894454,0.00002132881,0.00018800255,0.00008281511,0.00008796266,0.00008032487,0.00010403072,9.877521e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005199264,0.00020126541,0.82530725,0.000085416425,0.00002613517,0.000048231297,0.0005004005,0.0000024319468,0.04458725,0.02034397,0.018809874,0.08956786],"study_design_scores_gemma":[0.0015226695,0.0004724185,0.92155623,0.00016830681,0.000021452895,0.00007685048,0.00013048462,0.0005658204,0.009327448,0.016806893,0.04912035,0.00023107944],"about_ca_topic_score_codex":8.999933e-7,"about_ca_topic_score_gemma":5.841288e-7,"teacher_disagreement_score":0.11130357,"about_ca_system_score_codex":0.000017918766,"about_ca_system_score_gemma":0.000013966034,"threshold_uncertainty_score":0.28114766},"labels":[],"label_agreement":null},{"id":"W2278559975","doi":"10.3389/fnana.2016.00009","title":"Maturation Along White Matter Tracts in Human Brain Using a Diffusion Tensor Surface Model Tract-Specific Analysis","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"White matter; Fasciculus; Diffusion MRI; Corpus callosum; Corticospinal tract; Superior longitudinal fasciculus; Fractional anisotropy; Uncinate fasciculus; Anatomy; Neuroscience; Pyramidal tracts; Inferior longitudinal fasciculus; Biology; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.03785058414571119,"score_gpt":0.3192626039099383,"score_spread":0.28141201976422714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278559975","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7770997,0.000057097022,0.21817386,0.003891763,0.000042774016,0.00042536313,0.000011283492,0.00008257889,0.00021556536],"genre_scores_gemma":[0.9502011,0.00006506979,0.04824737,0.00069370604,0.000025922998,0.000023466182,0.00001839697,0.000045453846,0.00067953474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99839276,0.000063980915,0.00045042703,0.00054903777,0.00022173495,0.00032208735],"domain_scores_gemma":[0.9991744,0.000041855466,0.00014152983,0.00050380686,0.00004535833,0.000093036506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013753303,0.00020741619,0.00040561173,0.00063088967,0.00007353892,0.000025187946,0.00014150781,0.000094971154,0.000032869128],"category_scores_gemma":[0.00002243761,0.00016721778,0.000121560646,0.0009706936,0.00007051155,0.00027843507,0.000040293366,0.00028020816,0.0000044852604],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007922565,0.00024919823,0.9144148,0.000016107242,0.000016527789,0.000090516754,0.00012283828,0.0038946439,0.07320876,0.00007535963,0.006749844,0.0010821667],"study_design_scores_gemma":[0.0013891471,0.000030341016,0.824041,0.00011525892,0.000106284366,0.000033493623,0.000041683375,0.16921704,0.0015091947,0.0013488521,0.0018750032,0.0002926822],"about_ca_topic_score_codex":0.000020237829,"about_ca_topic_score_gemma":0.000009508871,"teacher_disagreement_score":0.17310137,"about_ca_system_score_codex":0.00018214493,"about_ca_system_score_gemma":0.000022962098,"threshold_uncertainty_score":0.6818943},"labels":[],"label_agreement":null},{"id":"W2279592394","doi":"10.1371/journal.pone.0113081.t005","title":"Tract-based spatial statistics results showing regions of white matter integrity decrease in each of the patient groups compared with Controls&lt;sup&gt;a&lt;/sup&gt;","year":2015,"lang":"en","type":"paratext","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Statistics; Medicine; Biology; Mathematics; Magnetic resonance imaging","score_opus":0.08369833103386917,"score_gpt":0.32193233914679176,"score_spread":0.23823400811292259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2279592394","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004782052,0.00031839294,0.0046367324,0.0016432025,0.00008225855,0.00408519,0.97650445,0.00009804104,0.007849679],"genre_scores_gemma":[0.76225305,0.000008607328,0.007286076,0.00076444156,0.000120396384,0.0007870102,0.22727235,0.000120811,0.001387263],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99728066,0.00017114288,0.00097514223,0.00058151316,0.00063275854,0.0003588014],"domain_scores_gemma":[0.9963594,0.00042343308,0.000976755,0.001219494,0.00078555534,0.00023537835],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00011213521,0.00045462107,0.00097614946,0.00020433715,0.00009792232,0.000018872757,0.00042626832,0.00026425658,0.006411712],"category_scores_gemma":[0.001003956,0.00033008197,0.00016518618,0.00038076082,0.000097079566,0.00006357882,0.00018124981,0.0010833389,0.00013307284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008657109,0.0006191087,0.0005858352,0.00061647274,0.00003565401,0.00003337225,0.00035976933,0.001046634,0.00010671871,0.000018434155,0.995433,0.00027933408],"study_design_scores_gemma":[0.014938104,0.001855942,0.034074783,0.045818135,0.00068306393,0.00014193682,0.00021761731,0.030161634,0.0025512653,0.00026791927,0.8676002,0.001689419],"about_ca_topic_score_codex":0.00014015788,"about_ca_topic_score_gemma":0.00016948838,"teacher_disagreement_score":0.75747097,"about_ca_system_score_codex":0.00018600596,"about_ca_system_score_gemma":0.0007120262,"threshold_uncertainty_score":0.9999151},"labels":[],"label_agreement":null},{"id":"W2283128416","doi":"10.1093/cercor/bhv180","title":"Altered Human Memory Modification in the Presence of Normal Consolidation","year":2015,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Center for Neuroscience and Regenerative Medicine; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Israel National Road Safety Authority","keywords":"Memory consolidation; Neuroscience; Consolidation (business); Engram; Dissociation (chemistry); Human memory; Psychology; Human brain; Cognition; Hippocampus; Chemistry","score_opus":0.16406319875743555,"score_gpt":0.39272486988972,"score_spread":0.22866167113228444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283128416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98442304,0.000027415326,0.005009993,0.0014561083,0.000025253263,0.0005162363,0.0000045952866,0.000053335363,0.008484051],"genre_scores_gemma":[0.9977288,0.0000037097766,0.001724279,0.00024509343,0.000045780536,0.000050062677,0.000044568977,0.0000062752965,0.00015140562],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994543,0.000025746278,0.00017606563,0.00012313109,0.00013695657,0.000083760904],"domain_scores_gemma":[0.9994552,0.000025580279,0.00008199062,0.0003253217,0.00007625611,0.00003561871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014313303,0.000052768235,0.000090954425,0.000045188153,0.000027604447,0.000005532635,0.00011548458,0.000023663717,0.000011628428],"category_scores_gemma":[0.00005374151,0.00003989796,0.000021447162,0.00014936943,0.000072920964,0.00007915551,0.000020981483,0.00010638474,0.0000058230257],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000405878,0.0016267747,0.14552931,0.0002649878,0.000031633615,0.000026198119,0.006593359,0.00031467387,0.62013507,0.15702482,0.03811465,0.029932681],"study_design_scores_gemma":[0.0029575129,0.00061519793,0.86879814,0.00013553689,0.00007808988,0.00014553929,0.0015480117,0.0088778995,0.08704414,0.022880673,0.0066229226,0.00029631742],"about_ca_topic_score_codex":0.000048193408,"about_ca_topic_score_gemma":0.000006065687,"teacher_disagreement_score":0.72326887,"about_ca_system_score_codex":0.000018924105,"about_ca_system_score_gemma":0.000031448035,"threshold_uncertainty_score":0.16269916},"labels":[],"label_agreement":null},{"id":"W2284206694","doi":"10.1016/j.media.2016.01.002","title":"The application of a new sampling theorem for non-bandlimited signals on the sphere: Improving the recovery of crossing fibers for low b-value acquisitions","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; Washington University in St. Louis","keywords":"Deconvolution; Bandlimiting; Sampling (signal processing); Mathematics; Algorithm; Convolution (computer science); Kernel (algebra); Nonuniform sampling; Computer science; Mathematical analysis; Fourier transform; Artificial intelligence; Computer vision; Discrete mathematics; Artificial neural network","score_opus":0.038154558591240596,"score_gpt":0.36350859537872743,"score_spread":0.3253540367874868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284206694","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021766348,0.00006004883,0.95439214,0.022583995,0.00001312686,0.0010271528,0.00005617983,0.000033908786,0.000067132605],"genre_scores_gemma":[0.9607711,0.000094788025,0.036149792,0.0017744424,0.00020661889,0.00058464386,0.000035384095,0.000032696487,0.00035053006],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986862,0.00004293729,0.00046363278,0.00026480693,0.0003314679,0.0002109356],"domain_scores_gemma":[0.9940516,0.004551613,0.000353474,0.0007207791,0.00023624486,0.000086293534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010212504,0.00012274593,0.00030082752,0.00006559465,0.00046296025,0.000036989695,0.0003232405,0.000062381056,0.000043274067],"category_scores_gemma":[0.0020370898,0.00005012915,0.0004577596,0.00061103073,0.0005308779,0.00005090407,0.000044062523,0.00011522839,0.0000011596705],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005332922,0.00022978331,0.0002953919,0.000118884745,0.0009126409,6.126217e-7,0.0002485304,0.00023871369,0.42256376,0.009077343,0.0042364555,0.5615446],"study_design_scores_gemma":[0.004012251,0.0009207069,0.0034519676,0.0011335433,0.007882067,0.000012215367,0.00090933417,0.30472824,0.5510997,0.10664139,0.018647103,0.000561436],"about_ca_topic_score_codex":0.000054870976,"about_ca_topic_score_gemma":0.000011492864,"teacher_disagreement_score":0.9390048,"about_ca_system_score_codex":0.000037529993,"about_ca_system_score_gemma":0.00016243187,"threshold_uncertainty_score":0.35607627},"labels":[],"label_agreement":null},{"id":"W2284226518","doi":"10.1007/s10803-016-2744-2","title":"Widespread White Matter Differences in Children and Adolescents with Autism Spectrum Disorder","year":2016,"lang":"en","type":"article","venue":"Journal of Autism and Developmental Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Institute for Christian Studies; University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Sick Kids Foundation","keywords":"Corpus callosum; Fractional anisotropy; Autism spectrum disorder; Psychology; Autism; White matter; Diffusion MRI; Neurodevelopmental disorder; Audiology; Developmental psychology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.009518566486734784,"score_gpt":0.24509901106574214,"score_spread":0.23558044457900734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284226518","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9820374,0.00023381044,0.0038470782,0.013509657,0.00001736879,0.00019753084,0.0000045226916,0.000014279617,0.00013829849],"genre_scores_gemma":[0.9937799,0.0013156664,0.0044257795,0.00030433343,0.00000571221,0.000004946128,0.0000011124774,0.000014078266,0.00014845269],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992848,0.000011585257,0.00023912027,0.00016220007,0.00013723242,0.00016508024],"domain_scores_gemma":[0.9997079,0.000014495956,0.000111408815,0.000063283434,0.000005702355,0.00009724257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004898012,0.000131252,0.00021068049,0.00013576167,0.000051309366,0.000015660797,0.000057954767,0.000033093427,0.000029938486],"category_scores_gemma":[0.000005391882,0.00007609639,0.000021579257,0.00009688839,0.00014116576,0.00016902143,0.000045998026,0.0001200229,0.0000029526118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078074314,0.000086774126,0.9914437,0.000014481465,0.000014869674,0.0000064203573,0.00009577872,6.469012e-8,0.00017520721,0.000112305075,0.00015142869,0.00782089],"study_design_scores_gemma":[0.0018919375,0.00014538014,0.99258804,0.0006288623,0.000018307552,0.0006137213,0.00005494664,0.0000017791065,0.000047044537,0.0036786618,0.0002106108,0.00012072068],"about_ca_topic_score_codex":0.000014228978,"about_ca_topic_score_gemma":0.000017544471,"teacher_disagreement_score":0.013205324,"about_ca_system_score_codex":0.000027914073,"about_ca_system_score_gemma":0.00003756666,"threshold_uncertainty_score":0.31031206},"labels":[],"label_agreement":null},{"id":"W2288592143","doi":"10.1007/s11682-015-9495-0","title":"Correlating quantitative tractography at 3T MRI and cognitive tests in healthy older adults","year":2015,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; Queen's University; University of Toronto","funders":"","keywords":"Fractional anisotropy; Stroop effect; Corpus callosum; Psychology; White matter; Tractography; Diffusion MRI; Wechsler Adult Intelligence Scale; Cerebral peduncle; Neuroscience; Audiology; Cognition; Medicine; Magnetic resonance imaging; Internal capsule; Radiology","score_opus":0.0685035506087787,"score_gpt":0.3993114726856923,"score_spread":0.33080792207691356,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288592143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917582,0.0014242432,0.002053863,0.003708232,0.000028702283,0.00067756104,0.000020701695,0.0001276141,0.00020086057],"genre_scores_gemma":[0.985584,0.00007139964,0.012888735,0.0011803526,0.000018435625,0.00014545296,0.000028493709,0.000023574472,0.000059511676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999103,0.00003179481,0.00019531773,0.00035343788,0.0001102383,0.00020622049],"domain_scores_gemma":[0.99932164,0.00022345083,0.00007794308,0.00011033264,0.00008564837,0.00018100432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001527133,0.00013458004,0.00018582198,0.0001515741,0.00009021684,0.000017860646,0.000027086764,0.00003280952,0.0000032980602],"category_scores_gemma":[0.00015579608,0.00012681022,0.000025850986,0.00020978069,0.00016618271,0.000107874825,0.00004868664,0.00022571784,0.000002354038],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023296174,0.00030653164,0.93886507,0.000041557298,0.0000031729269,0.00008475281,0.001806618,1.8276833e-7,0.00093366124,0.00014533784,0.0008463814,0.056733795],"study_design_scores_gemma":[0.0035550348,0.00031153994,0.99087334,0.00065479364,0.0000921477,0.00038427938,0.0022757843,0.000712487,0.00026718254,0.00019647938,0.0004680783,0.00020887866],"about_ca_topic_score_codex":0.0000976817,"about_ca_topic_score_gemma":0.000022752542,"teacher_disagreement_score":0.056524914,"about_ca_system_score_codex":0.000026580034,"about_ca_system_score_gemma":0.000027252316,"threshold_uncertainty_score":0.5171171},"labels":[],"label_agreement":null},{"id":"W2290984633","doi":"10.1093/schbul/sbv180","title":"Limited Evidence for Association of Genome-Wide Schizophrenia Risk Variants on Cortical Neuroimaging Phenotypes","year":2015,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Corpus callosum; White matter; Neuroimaging; Splenium; Schizophrenia (object-oriented programming); Fractional anisotropy; Genome-wide association study; Neuroscience; Genetic association; Diffusion MRI; Single-nucleotide polymorphism; Psychology; Biology; Genetics; Medicine; Magnetic resonance imaging; Psychiatry; Genotype; Gene","score_opus":0.08618003780891856,"score_gpt":0.3389441491555898,"score_spread":0.2527641113466712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290984633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8967194,0.00058247644,0.061010923,0.036317524,0.00035466137,0.0027607528,0.00019113511,0.00084674224,0.0012163905],"genre_scores_gemma":[0.90903646,0.00015822361,0.08860156,0.0011495507,0.0002842291,0.00015569688,0.000043450294,0.00007186511,0.0004989902],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99789864,0.00013755391,0.00053779315,0.00056312676,0.00047328626,0.0003896097],"domain_scores_gemma":[0.9968246,0.0012955476,0.00045082826,0.0006472576,0.0005181397,0.00026363254],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0007347991,0.00025338645,0.0004471323,0.00017135976,0.00016589566,0.000033081284,0.00023231287,0.00011286816,0.000051816034],"category_scores_gemma":[0.0089730965,0.00024060698,0.00016339643,0.00033036055,0.00008660006,0.00006815745,0.00008869166,0.0005297271,0.000120757584],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.103880666,0.005373828,0.3782893,0.0010972262,0.0010356106,0.00017189905,0.0011261585,0.0027245118,0.12134551,0.047226764,0.25823015,0.07949837],"study_design_scores_gemma":[0.022744773,0.0042564385,0.7380107,0.0013945886,0.0016336578,0.00008199036,0.00011018652,0.009553161,0.014673893,0.02382884,0.18215275,0.0015590168],"about_ca_topic_score_codex":0.000024627094,"about_ca_topic_score_gemma":0.0000027394703,"teacher_disagreement_score":0.3597214,"about_ca_system_score_codex":0.00015982256,"about_ca_system_score_gemma":0.00019799771,"threshold_uncertainty_score":0.99937475},"labels":[],"label_agreement":null},{"id":"W2295505655","doi":"10.1007/978-3-319-27929-9_6","title":"A Graph Based Classification Method for Multiple Sclerosis Clinical Forms Using Support Vector Machine","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Agence Nationale de la Recherche","keywords":"Support vector machine; Computer science; Diffusion MRI; Pattern recognition (psychology); Artificial intelligence; Multiple sclerosis; Graph theory; Graph; Artificial neural network; Kernel (algebra); Machine learning; Data mining; Theoretical computer science; Magnetic resonance imaging; Mathematics; Medicine","score_opus":0.3312701000338951,"score_gpt":0.4433715667412938,"score_spread":0.11210146670739868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295505655","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008592401,0.00007642583,0.9966221,0.001232204,0.00024963022,0.0013097815,0.000060021575,0.00017225149,0.00019168807],"genre_scores_gemma":[0.0696489,0.000019743587,0.92808396,0.001712565,0.0002703633,0.00005468396,0.00008180146,0.000055352473,0.00007263463],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99764043,0.000019593026,0.0005812522,0.0009951555,0.00042704854,0.000336523],"domain_scores_gemma":[0.99758756,0.0006527271,0.00032461135,0.0008606633,0.0003739587,0.00020049627],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0011543095,0.00030999572,0.0005366919,0.00039391834,0.00015225247,0.000049751387,0.00044050315,0.0002487891,0.000011425542],"category_scores_gemma":[0.00032886263,0.00025808843,0.00021327166,0.0003007796,0.00042275843,0.000105779094,0.00014057927,0.0005672394,0.0000028990378],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023617821,0.00022242367,0.0021851042,0.00018368856,0.00002666001,0.00001516819,0.00008127469,0.0065602544,0.008740041,0.0052334494,0.00028585043,0.9762299],"study_design_scores_gemma":[0.0009552622,0.0004141062,0.0006610492,0.0002929502,0.000069256304,0.00003522207,1.117233e-7,0.94276845,0.0018369195,0.045556396,0.0070872214,0.00032304268],"about_ca_topic_score_codex":0.000010653544,"about_ca_topic_score_gemma":0.0000132602145,"teacher_disagreement_score":0.97590685,"about_ca_system_score_codex":0.00021589524,"about_ca_system_score_gemma":0.0005247511,"threshold_uncertainty_score":0.9999871},"labels":[],"label_agreement":null},{"id":"W2296626252","doi":"10.14288/1.0066854","title":"Myelin water imaging : development at 3.0T, application to the study of multiple sclerosis, and comparison to diffusion tensor imaging","year":2008,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffusion MRI; Multiple sclerosis; Diffusion imaging; Myelin; Neuroscience; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Psychology; Physics; Radiology; Central nervous system","score_opus":0.03655666054394428,"score_gpt":0.24008213335775522,"score_spread":0.20352547281381095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2296626252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790758,0.000039207996,0.018670328,0.00089182815,0.000011327099,0.0011921001,0.000013545944,0.00007008972,0.00003575981],"genre_scores_gemma":[0.9923652,0.000027960306,0.0072590946,0.00016345415,0.000010687996,0.000011031583,0.000013993913,0.0000133931435,0.00013520556],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99912715,0.00001965049,0.00016276426,0.00033746203,0.00019268923,0.00016026564],"domain_scores_gemma":[0.9993415,0.00002506746,0.00006918029,0.00030779664,0.00014786703,0.00010861688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000095347394,0.000047316935,0.00021475082,0.0000506352,0.0004462638,0.000012179502,0.00015261454,0.000016265803,0.0000070163287],"category_scores_gemma":[0.000013446829,0.00009349698,0.000030247273,0.0001714964,0.00009480711,0.00006356488,0.00033488992,0.00007896444,0.000008510118],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029689823,0.0003685218,0.6906621,0.000021965074,0.000008252707,0.000011443162,0.0022316037,0.000029721929,0.025625268,1.0710961e-7,0.0015756609,0.2794357],"study_design_scores_gemma":[0.00089369016,0.00005796479,0.99234515,0.00008872363,0.000027790213,0.000053486106,0.0019457268,0.0012145624,0.00026165912,0.000004459278,0.0030047994,0.00010196841],"about_ca_topic_score_codex":0.010452281,"about_ca_topic_score_gemma":0.014245368,"teacher_disagreement_score":0.3016831,"about_ca_system_score_codex":0.00007072513,"about_ca_system_score_gemma":0.000014986354,"threshold_uncertainty_score":0.9961372},"labels":[],"label_agreement":null},{"id":"W2298552625","doi":"10.1016/j.media.2016.02.010","title":"Non Local Spatial and Angular Matching: Enabling higher spatial resolution diffusion MRI datasets through adaptive denoising","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Noise reduction; Noise (video); Computer science; Artificial intelligence; Rician fading; Spatial analysis; Pattern recognition (psychology); Gaussian noise; Noise measurement; Algorithm; Computer vision; Mathematics; Statistics","score_opus":0.029768578420550303,"score_gpt":0.3345688220668706,"score_spread":0.3048002436463203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2298552625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038562447,0.00013262266,0.95467556,0.0060771387,0.000028625725,0.00019683459,0.00005942595,0.00013053838,0.0001368304],"genre_scores_gemma":[0.9720399,0.00038779085,0.025942193,0.0008719285,0.00029672164,0.000023708066,0.00027082863,0.000028032295,0.00013890705],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980815,0.000057520574,0.0003580455,0.0005737226,0.00062494143,0.00030427836],"domain_scores_gemma":[0.99890804,0.000119856064,0.00012543709,0.0005064473,0.00007862969,0.00026157216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025733918,0.0001953707,0.00041825426,0.00017325404,0.00018672376,0.000026163745,0.00013669662,0.00012853161,0.00046118448],"category_scores_gemma":[0.00012588366,0.00013112245,0.00014213246,0.00046707946,0.00036243632,0.00022112092,0.00022089624,0.00025324296,0.000017882097],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011075214,0.0014574942,0.019036882,0.00017875477,0.0016895212,0.0020315053,0.00072569144,0.000055093835,0.3113664,0.0013573173,0.01217444,0.6488194],"study_design_scores_gemma":[0.019413082,0.0021334342,0.23089385,0.0035557442,0.023501985,0.0006370422,0.00080993935,0.38984546,0.15379141,0.028349353,0.1432526,0.003816118],"about_ca_topic_score_codex":0.0016874439,"about_ca_topic_score_gemma":0.00013761983,"teacher_disagreement_score":0.93347746,"about_ca_system_score_codex":0.00008372081,"about_ca_system_score_gemma":0.00004252993,"threshold_uncertainty_score":0.5347018},"labels":[],"label_agreement":null},{"id":"W2303032580","doi":"10.3389/fnint.2016.00015","title":"Pre-Surgical Integration of fMRI and DTI of the Sensorimotor System in Transcortical Resection of a High-Grade Insular Astrocytoma","year":2016,"lang":"en","type":"article","venue":"Frontiers in Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Saskatchewan Health Research Foundation","keywords":"Astrocytoma; Internal capsule; Functional magnetic resonance imaging; Diffusion MRI; Middle frontal gyrus; Magnetic resonance imaging; Psychology; Medicine; Neuroscience; White matter; Radiology; Glioma","score_opus":0.03135172242304888,"score_gpt":0.31621968094846553,"score_spread":0.28486795852541663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2303032580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8382616,0.000031482523,0.16068491,0.0003390577,0.0001282155,0.00047405233,0.000019297324,0.000014488044,0.000046907568],"genre_scores_gemma":[0.9910575,0.000070762515,0.008768159,0.000012738325,0.000008500507,0.000040504205,3.733909e-7,0.000006854426,0.000034586745],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998832,0.00011550265,0.0004148403,0.00027770238,0.00023571958,0.000124222],"domain_scores_gemma":[0.9993728,0.0000881646,0.0001708671,0.0002457319,0.00008570364,0.00003672818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016090236,0.0001038282,0.00030576892,0.0001803113,0.000023285305,0.00000267408,0.00014103034,0.000050215887,6.358469e-7],"category_scores_gemma":[0.0003201043,0.000055675864,0.000052885596,0.00062179076,0.00073404965,0.00010552071,0.000031248073,0.00019059515,2.9550757e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067741773,0.0002137354,0.08627391,0.00008864239,0.0000024751637,0.000007854109,0.00041857705,0.000015356656,0.89855623,0.009448143,0.000042522726,0.004255141],"study_design_scores_gemma":[0.0011465779,0.0010086071,0.30238506,0.0010349557,0.000016731568,0.000053920776,0.0004096975,0.0041028955,0.68868804,0.0009855608,0.000096979405,0.00007101061],"about_ca_topic_score_codex":0.000048585694,"about_ca_topic_score_gemma":0.000012966056,"teacher_disagreement_score":0.21611114,"about_ca_system_score_codex":0.00007968133,"about_ca_system_score_gemma":0.00004916093,"threshold_uncertainty_score":0.27046365},"labels":[],"label_agreement":null},{"id":"W2308601713","doi":"10.1016/j.neuroimage.2016.03.042","title":"Complex interplay between brain function and structure during cerebral amyloidosis in APP transgenic mouse strains revealed by multi-parametric MRI comparison","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Genetically modified mouse; Cerebral amyloid angiopathy; Pathology; Amyloid (mycology); Neuroscience; Parenchyma; Population; Perivascular space; Amyloidosis; Intracellular; Neuroimaging; Amyloid precursor protein; Biology; Transgene; Alzheimer's disease; Medicine; Cell biology; Disease; Gene; Biochemistry","score_opus":0.05762622994255563,"score_gpt":0.3560699535394426,"score_spread":0.298443723596887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2308601713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95448476,0.00003585725,0.04015002,0.003936347,0.000021757314,0.00071935705,0.00031437963,0.0003067863,0.000030728304],"genre_scores_gemma":[0.9929138,0.000040882947,0.006074795,0.00040911994,0.000052788975,0.00003216425,0.00006882991,0.000059337293,0.00034830533],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99836046,0.00007721659,0.00042826543,0.0006083125,0.00017874813,0.00034702584],"domain_scores_gemma":[0.99912244,0.00013767777,0.00012501699,0.00041935334,0.000031789605,0.0001636934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007626106,0.00025670478,0.00042846275,0.00027996133,0.000098865654,0.000027864648,0.00014160748,0.00009698016,0.000057766312],"category_scores_gemma":[0.00008132923,0.00020764062,0.000074252486,0.00043898015,0.00013613453,0.00016270205,0.00006045488,0.0004022946,0.0000058518694],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007537339,0.000114114024,0.21911559,0.00006119768,0.000012659088,0.000003747808,0.00007271846,0.000002801303,0.7722257,0.000015779673,0.0014337427,0.006866576],"study_design_scores_gemma":[0.003729935,0.00024593165,0.95636433,0.00006973157,0.000057144112,0.000020019424,0.000033159424,0.00043913387,0.03722451,0.00013547667,0.0014256154,0.000255014],"about_ca_topic_score_codex":0.000022399228,"about_ca_topic_score_gemma":0.000021394479,"teacher_disagreement_score":0.7372487,"about_ca_system_score_codex":0.0000728063,"about_ca_system_score_gemma":0.00001371004,"threshold_uncertainty_score":0.8467339},"labels":[],"label_agreement":null},{"id":"W2309119811","doi":"10.3171/2016.1.peds15580","title":"Vulnerability of white matter to insult during childhood: evidence from patients treated for medulloblastoma","year":2016,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research; Pediatric Oncology Group","funders":"Brain Tumour Research; Hospital for Sick Children; Garron Family Cancer Centre; Genome British Columbia; Fondation Brain Canada; Pediatric Oncology Group of Ontario; Children's Hospital Foundation; Canadian Institutes of Health Research; Genome Canada","keywords":"Medicine; Fractional anisotropy; Medulloblastoma; White matter; Nuclear medicine; Diffusion MRI; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.04148133429304946,"score_gpt":0.3146477158787259,"score_spread":0.27316638158567647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2309119811","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926955,0.00003519604,0.0036994652,0.0028640877,0.00016644357,0.00038501716,0.00012025527,0.000027867089,0.0000061578335],"genre_scores_gemma":[0.9947691,0.00019277622,0.0042073196,0.00040641802,0.00030415773,0.000016737866,0.0000020410523,0.00003148539,0.00006994154],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984193,0.000042371856,0.0007886824,0.00023080966,0.00032576715,0.00019308043],"domain_scores_gemma":[0.9974806,0.00076891715,0.0006246598,0.00033304893,0.00059064775,0.00020214634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018398005,0.00014425805,0.00039353658,0.00031568875,0.000068810165,0.0000075379644,0.00014657405,0.000050997212,0.000027813476],"category_scores_gemma":[0.0015946301,0.00009749413,0.0002090809,0.00042485568,0.00003270293,0.00020471613,0.00007309865,0.00015029545,0.0000045384013],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039976227,0.00029223107,0.96463394,0.0000438634,0.0000070495157,0.00000821677,0.000050007347,0.000007698825,0.030545488,4.6474523e-7,0.0029427232,0.0010685234],"study_design_scores_gemma":[0.00076646,0.0003726481,0.97701627,0.00018236165,0.000093450624,0.000027611659,0.0000019733093,0.000002447373,0.020791264,0.00008548147,0.0005666979,0.00009333341],"about_ca_topic_score_codex":0.0000021234882,"about_ca_topic_score_gemma":2.1243875e-7,"teacher_disagreement_score":0.012382301,"about_ca_system_score_codex":0.000060190596,"about_ca_system_score_gemma":0.000060718572,"threshold_uncertainty_score":0.3975695},"labels":[],"label_agreement":null},{"id":"W2314099791","doi":"10.1177/0271678x15606718","title":"Exploring the use of shape and texture descriptors of positron emission tomography tracer distribution in imaging studies of neurodegenerative disease","year":2015,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Positron emission tomography; Artificial intelligence; Pattern recognition (psychology); Nuclear medicine; Raclopride; Parkinson's disease; Mathematics; Computer science; Biological system; Medicine; Striatum; Disease; Pathology; Dopamine; Internal medicine; Biology","score_opus":0.23844535160093902,"score_gpt":0.34282599972479105,"score_spread":0.10438064812385203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314099791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98922443,0.008100151,0.0010769716,0.0012473073,0.00009282053,0.00020536596,0.000043478736,0.00000748431,0.0000020147781],"genre_scores_gemma":[0.9929691,0.0012033297,0.005648443,0.00005770811,0.000090555295,0.000007745524,0.000004531658,0.00001269632,0.0000058672927],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988253,0.00009157963,0.000555708,0.00012402172,0.0002869975,0.00011639907],"domain_scores_gemma":[0.9987108,0.000075325486,0.00046084402,0.0001742257,0.00044761784,0.00013115922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002452256,0.0001287191,0.00045117608,0.00015082893,0.00003334469,0.00000783663,0.000086957814,0.000017638946,0.0000010873232],"category_scores_gemma":[0.00033965823,0.0000806786,0.00013686239,0.00032163964,0.00015931812,0.00042337584,0.000053654076,0.00024701163,1.7111397e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002158914,0.0017899155,0.3210498,0.00047824075,0.00051174045,0.00007599108,0.0062459405,0.001141211,0.61170053,0.0016150707,0.0021368999,0.051095743],"study_design_scores_gemma":[0.004241458,0.00042003163,0.60384005,0.0011551478,0.002076451,0.00015876866,0.0011617308,0.004121455,0.37800604,0.0020754598,0.0025019683,0.00024141387],"about_ca_topic_score_codex":0.00000827062,"about_ca_topic_score_gemma":6.7913254e-7,"teacher_disagreement_score":0.28279027,"about_ca_system_score_codex":0.000011832773,"about_ca_system_score_gemma":0.000052058524,"threshold_uncertainty_score":0.32899776},"labels":[],"label_agreement":null},{"id":"W2314151980","doi":"10.1038/srep22161","title":"Multimodal Image Analysis in Alzheimer’s Disease via Statistical Modelling of Non-local Intensity Correlations","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Information and Communication Technologies; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Southern California; University College London; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University College London Hospitals NHS Foundation Trust; Eli Lilly and Company; U.S. Department of Defense; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Magnetic resonance imaging; Positron emission tomography; Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; Cerebral atrophy; Posterior cortical atrophy; Partial least squares regression; Fluorodeoxyglucose; Pathology; Disease; Artificial intelligence; Alzheimer's disease; Neuroscience; Computer science; Pattern recognition (psychology); Medicine; Psychology; Dementia; Radiology; Machine learning","score_opus":0.058192720159185266,"score_gpt":0.348394349798752,"score_spread":0.29020162963956675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314151980","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1249163,0.000017309158,0.87413555,0.00034673052,0.00014900572,0.0002676171,0.000019328956,0.000047546884,0.00010061156],"genre_scores_gemma":[0.93351024,0.0000028450038,0.06622231,0.000016901959,0.000010288507,0.000022959526,0.000069077,0.0000092477,0.00013611923],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856126,0.000013396551,0.0004704641,0.0005132676,0.00026833138,0.00017328365],"domain_scores_gemma":[0.998638,0.000064253705,0.00016691803,0.0007200319,0.00023526186,0.00017558558],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032416306,0.00009069778,0.00024749173,0.0002928875,0.000077248646,0.0000128614965,0.00005144481,0.000027897802,0.0000590988],"category_scores_gemma":[0.00010801409,0.000066655964,0.00010456103,0.0007177105,0.00047747936,0.00010061037,0.000051438205,0.00008853253,0.0000070145124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043552488,0.0022103062,0.74864244,0.00007817465,0.00043663522,0.0032314346,0.00038742655,0.04458332,0.13950235,0.0016250389,0.0060477774,0.052819565],"study_design_scores_gemma":[0.00027132974,0.000023845298,0.10630043,0.00008230563,0.0008168883,0.000058078593,0.000016602382,0.86415815,0.008217285,0.019494245,0.00039725995,0.00016358418],"about_ca_topic_score_codex":0.0000640549,"about_ca_topic_score_gemma":0.000007458816,"teacher_disagreement_score":0.81957483,"about_ca_system_score_codex":0.00003906346,"about_ca_system_score_gemma":0.00008697451,"threshold_uncertainty_score":0.27181512},"labels":[],"label_agreement":null},{"id":"W2314790700","doi":"10.1136/archdischild-2014-307384.1078","title":"PO-0436 Postnatal Development Of The Auditory Thalamocortical Connexions","year":2014,"lang":"en","type":"article","venue":"Archives of Disease in Childhood","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Temporal lobe; Thalamus; White matter; Temporal cortex; Tractography; Neuroscience; Cortex (anatomy); Medicine; Fractional anisotropy; Auditory cortex; Diffusion MRI; Anatomy; Audiology; Magnetic resonance imaging; Psychology; Epilepsy; Radiology","score_opus":0.01942967463543542,"score_gpt":0.29409045366156633,"score_spread":0.2746607790261309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2314790700","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99011844,0.000040336916,0.0049282177,0.0014987353,0.000030846837,0.00040107704,0.000025354102,0.000037730897,0.0029192504],"genre_scores_gemma":[0.98952985,0.00000629136,0.010173315,0.00016093734,0.000040291045,0.000023970846,0.00001290793,0.00001211604,0.00004031402],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928427,0.000029550712,0.00026309327,0.00016270457,0.00013672546,0.00012367804],"domain_scores_gemma":[0.99925256,0.0001508111,0.000080966,0.00039416226,0.000013910523,0.000107599924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037627393,0.000083691906,0.00014801786,0.000061548286,0.000046874182,0.0000015297137,0.0001671665,0.000013762872,0.000014568102],"category_scores_gemma":[0.00015831001,0.000060892395,0.00009026717,0.00007518465,0.00021236845,0.000021532875,0.000121741155,0.00013016228,0.0000022636234],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005904845,0.006853566,0.8236367,0.00055546174,0.00013356551,0.00001592946,0.0050879717,0.00014685094,0.030530322,0.05418021,0.0007060018,0.07756293],"study_design_scores_gemma":[0.00045169904,0.000035647106,0.9782204,0.00020699033,0.00002680022,0.0000038886,0.000022350354,0.00013685507,0.011722425,0.00860812,0.0005039312,0.000060894523],"about_ca_topic_score_codex":0.0000015590796,"about_ca_topic_score_gemma":0.000001266221,"teacher_disagreement_score":0.1545837,"about_ca_system_score_codex":0.000005993115,"about_ca_system_score_gemma":0.00015821529,"threshold_uncertainty_score":0.24831198},"labels":[],"label_agreement":null},{"id":"W2315856334","doi":"10.1515/ins-2014-0012","title":"Part II: an evaluation of an integrated systems approach using diffusion-weighted, image-guided, exoscopic-assisted, transulcal radial corridors","year":2015,"lang":"en","type":"article","venue":"Innovative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Diffusion; Image (mathematics); Computer science; Computer vision; Artificial intelligence; Physics","score_opus":0.285184818469056,"score_gpt":0.40616575064967037,"score_spread":0.12098093218061434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315856334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96822447,0.0000462653,0.028692883,0.00012778425,0.0005410499,0.0013239573,0.000106569554,0.00029323838,0.0006437868],"genre_scores_gemma":[0.9798948,0.00000784208,0.018810563,0.00026774482,0.00026176564,0.0001955275,0.00043182552,0.00007958122,0.00005034946],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99662685,0.00054555625,0.00094319874,0.0006616795,0.00089320197,0.00032948537],"domain_scores_gemma":[0.9957355,0.00009388785,0.00045760008,0.00072527025,0.0027305398,0.00025715728],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0014526334,0.00032488687,0.0006133939,0.0004349944,0.00016597894,0.000041980646,0.00018180862,0.00013875343,0.0000147286855],"category_scores_gemma":[0.0004857703,0.00028679354,0.00007715344,0.002057197,0.00030361774,0.0004656969,0.000052750795,0.00042620627,0.0000015497391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023652862,0.0082899975,0.031020893,0.00040370418,0.00015781053,0.00017199629,0.0014649528,0.0025566746,0.8775241,0.0035951568,0.011129559,0.061319903],"study_design_scores_gemma":[0.0055622584,0.0012366797,0.008527212,0.00039808912,0.00036200133,0.0011340387,0.00074645795,0.9475882,0.024888488,0.0004981219,0.008304205,0.00075422466],"about_ca_topic_score_codex":0.00008417119,"about_ca_topic_score_gemma":8.9555704e-7,"teacher_disagreement_score":0.9450315,"about_ca_system_score_codex":0.0001581738,"about_ca_system_score_gemma":0.000741233,"threshold_uncertainty_score":0.9999584},"labels":[],"label_agreement":null},{"id":"W2315964472","doi":"10.1016/j.jpain.2012.01.385","title":"White matter alterations in long-term yoga practitioners: a diffusion-tensor imaging study","year":2012,"lang":"en","type":"article","venue":"Journal of Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Anterior cingulate cortex; Medicine; Insula; Internal capsule; Psychology; Cingulum (brain); Cingulate cortex; Neuroscience; Magnetic resonance imaging; Radiology; Central nervous system; Cognition","score_opus":0.04234693114602367,"score_gpt":0.371311472149703,"score_spread":0.32896454100367933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2315964472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93491864,0.000121995516,0.053534057,0.0105320085,0.000075357915,0.00040625522,0.00000215204,0.000026139698,0.00038342082],"genre_scores_gemma":[0.98961204,0.00001797414,0.007992074,0.0017690224,0.00027843183,0.000036211557,0.0000031211848,0.0000166552,0.0002744579],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99910665,0.00011504968,0.00036157746,0.000083664985,0.00017108457,0.00016200177],"domain_scores_gemma":[0.9993002,0.00009092927,0.00023058345,0.00017369317,0.00009786372,0.00010675927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007136758,0.00008432963,0.0001715094,0.00020627293,0.000056504552,0.000020976397,0.00006245914,0.000016898664,0.00021699947],"category_scores_gemma":[0.00010139608,0.00006788436,0.0000621509,0.00015861978,0.000020818265,0.0003429416,0.000023979497,0.00029184905,0.000016505566],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031368265,0.0010232462,0.99243027,0.000011134444,0.000008503144,0.00007112988,0.00052194856,0.0000034756563,0.0009092784,0.000016275148,0.0041956115,0.0007777624],"study_design_scores_gemma":[0.0006976045,0.00010330226,0.99673486,0.00012780886,0.000046176865,0.00048035072,0.00036103095,0.00010030579,0.000048461112,0.00007933715,0.0011549919,0.000065775705],"about_ca_topic_score_codex":0.0000032769744,"about_ca_topic_score_gemma":0.000002450561,"teacher_disagreement_score":0.054693438,"about_ca_system_score_codex":0.00006879133,"about_ca_system_score_gemma":0.000024004474,"threshold_uncertainty_score":0.27682438},"labels":[],"label_agreement":null},{"id":"W2316328502","doi":"10.1097/rct.0b013e3182ab60ea","title":"Diffusion Tensor Imaging of the Normal Foot at 3 T","year":2014,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Foot (prosody); Anatomy; Effective diffusion coefficient; Magnetic resonance imaging; Nuclear magnetic resonance; Nuclear medicine; Asymptomatic; Thigh; Radiology; Pathology; Physics","score_opus":0.02167771018270286,"score_gpt":0.2837120542004462,"score_spread":0.26203434401774334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2316328502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79541117,0.00012874336,0.19916888,0.003946898,0.00026220645,0.0001759796,0.0000027797332,0.000045543726,0.00085783587],"genre_scores_gemma":[0.95275784,0.00001559934,0.046218015,0.00073678716,0.00021886376,0.000001695353,8.2451436e-7,0.000013537497,0.00003682783],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990433,0.000046821755,0.00040669477,0.00010148029,0.00027773337,0.00012398291],"domain_scores_gemma":[0.9988353,0.00007586003,0.0004566596,0.0003145085,0.00023652898,0.000081103106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015217956,0.00009999265,0.0002490523,0.00019471822,0.00008875612,0.000010094527,0.00020595918,0.0000259649,0.000008234681],"category_scores_gemma":[0.00001619404,0.00006116576,0.00038447135,0.00034635083,0.000102036334,0.000057876332,0.00011437268,0.00022794316,5.7815333e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012826012,0.00036309788,0.8955325,0.00006339234,0.00006735264,0.000013580055,0.00008809192,0.000043856955,0.02984984,0.00033096268,0.0071148328,0.06640424],"study_design_scores_gemma":[0.0008620456,0.00020581178,0.95637214,0.0002453044,0.00010716109,0.0009345277,0.000003964566,0.002552115,0.0052326405,0.00039266632,0.033015296,0.00007632248],"about_ca_topic_score_codex":0.0000011644516,"about_ca_topic_score_gemma":2.6263058e-7,"teacher_disagreement_score":0.15734671,"about_ca_system_score_codex":0.000019056197,"about_ca_system_score_gemma":0.000016017513,"threshold_uncertainty_score":0.24942674},"labels":[],"label_agreement":null},{"id":"W2318362526","doi":"10.1227/neu.0000000000000271","title":"Anatomic Study of the Central Core of the Cerebrum Correlating 7-T Magnetic Resonance Imaging and Fiber Dissection With the Aid of a Neuronavigation System","year":2013,"lang":"en","type":"article","venue":"Operative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Neuronavigation; Medicine; Magnetic resonance imaging; White matter; Dissection (medical); Anatomy; Tractography; Radiology","score_opus":0.02083046362942726,"score_gpt":0.27779662753778067,"score_spread":0.2569661639083534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2318362526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99738634,0.00011943279,0.000056835317,0.0008401205,0.00005924467,0.0013915168,0.0000066603357,0.00001941276,0.00012045366],"genre_scores_gemma":[0.9995962,0.000008346988,0.000049674363,0.00010090413,0.0000137870275,0.00008130614,8.3219936e-7,0.000017593467,0.00013139371],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99909335,0.00012905002,0.00027604363,0.00019560153,0.00019092015,0.00011501991],"domain_scores_gemma":[0.99901825,0.00017299391,0.0002532137,0.0003918863,0.00014128147,0.000022345785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008008381,0.00010902616,0.00019082254,0.000023339706,0.00016692911,0.000011255237,0.00010099327,0.000014293527,0.000005685724],"category_scores_gemma":[0.00005189156,0.00005157405,0.000043679596,0.0003154722,0.00024376698,0.0000806409,0.00007580027,0.00019515342,2.2491797e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006113486,0.00014589806,0.92025864,0.00006840862,0.0000057049047,0.0000017176003,0.0009876683,0.00016624513,0.07443175,0.00023367662,0.00023530069,0.0034038865],"study_design_scores_gemma":[0.00035387353,0.00018066533,0.98279524,0.00027451717,0.00004867801,0.000071411276,0.0013194082,0.0049690777,0.009839357,0.000011890483,0.00008427549,0.00005160614],"about_ca_topic_score_codex":0.00012669175,"about_ca_topic_score_gemma":0.00000822891,"teacher_disagreement_score":0.064592384,"about_ca_system_score_codex":0.000017150012,"about_ca_system_score_gemma":0.000031511372,"threshold_uncertainty_score":0.21031287},"labels":[],"label_agreement":null},{"id":"W2319216091","doi":"10.1177/1545968315584004","title":"Dynamic Changes in White Matter Abnormalities Correlate With Late Improvement and Deterioration Following TBI","year":2015,"lang":"en","type":"article","venue":"Neurorehabilitation and neural repair","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Academy of Medical Sciences; National Institute for Health and Care Research","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Traumatic brain injury; Magnetic resonance imaging; Corpus callosum; Medicine; Corticospinal tract; Neuroimaging; Tractography; Neuroscience; Psychology; Physical medicine and rehabilitation; Radiology; Psychiatry","score_opus":0.027938809501586406,"score_gpt":0.3095742834121778,"score_spread":0.2816354739105914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2319216091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928845,0.000059026595,0.00016760423,0.0060054357,0.000036928886,0.0005411351,0.000002511083,0.00016837384,0.00013448558],"genre_scores_gemma":[0.99391866,0.000030963496,0.004130308,0.0014607792,0.0000066745483,0.00008530259,0.000009332577,0.000018969191,0.00033901527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925524,0.000033710523,0.00017211732,0.00028264374,0.00012057485,0.00013570907],"domain_scores_gemma":[0.99959916,0.00005598014,0.00005512345,0.00015569213,0.00004423191,0.000089791436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011691914,0.0001192609,0.00014830468,0.00009799571,0.00004236388,0.000020535044,0.000020644591,0.00002983119,0.0000037004718],"category_scores_gemma":[0.00004249406,0.00009624291,0.000026284712,0.00012231387,0.00007037292,0.00016699643,0.000029089932,0.00011960019,0.0000014582282],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003396566,0.000085116946,0.9661063,0.00016855118,0.00000943288,0.000048398233,0.0021884067,0.00006746304,0.019780159,0.000096978896,0.00011503283,0.010994517],"study_design_scores_gemma":[0.0010878776,0.0014698176,0.9749159,0.000072203555,0.000030308935,0.000057768397,0.00038017204,0.020802915,0.00017195797,0.00043954872,0.0004333437,0.00013818523],"about_ca_topic_score_codex":0.000015832238,"about_ca_topic_score_gemma":0.000050421015,"teacher_disagreement_score":0.020735454,"about_ca_system_score_codex":0.000030885807,"about_ca_system_score_gemma":0.000013426993,"threshold_uncertainty_score":0.3924672},"labels":[],"label_agreement":null},{"id":"W2320710418","doi":"10.1097/rct.0b013e3182772d66","title":"Quantitative DTI Assessment in Human Lumbar Stabilization Muscles at 3 T","year":2013,"lang":"en","type":"article","venue":"Journal of Computer Assisted Tomography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; McMaster University Medical Centre","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; Medicine; Diffusion MRI; Lumbar; Magnetic resonance imaging; Low back pain; Body mass index; Oswestry Disability Index; Nuclear medicine; Anatomy; Radiology; Pathology","score_opus":0.06766996994943697,"score_gpt":0.380726403764135,"score_spread":0.31305643381469805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2320710418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84865767,0.0000861723,0.14923726,0.0012016275,0.00006424603,0.00033961187,0.0000018102513,0.00004428044,0.00036731214],"genre_scores_gemma":[0.814717,0.00003891589,0.1848829,0.00024793763,0.000060644194,0.000016744641,0.0000070281317,0.000014471194,0.000014375743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99886286,0.00006293501,0.0005298272,0.00014851923,0.0002529292,0.00014295647],"domain_scores_gemma":[0.99897,0.000044275297,0.00036254703,0.00019451996,0.00032649128,0.00010218279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015052447,0.00011710916,0.0002867107,0.00049016654,0.000069472466,0.000031172276,0.0001143924,0.00004317306,0.00005269658],"category_scores_gemma":[0.000007735763,0.00009823397,0.00017758168,0.0005098908,0.000067973575,0.00019940504,0.000047137066,0.00028181897,0.0000020447083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007885054,0.0029018729,0.60587466,0.00022985402,0.00028932322,0.00017599855,0.000858375,0.0006067059,0.30792144,0.0076996586,0.0152523825,0.05811091],"study_design_scores_gemma":[0.0008757698,0.000661533,0.9913969,0.00019258373,0.000037076014,0.000120741235,0.00003921309,0.0024725017,0.00076678384,0.0019447105,0.0013890872,0.000103093655],"about_ca_topic_score_codex":0.000008389641,"about_ca_topic_score_gemma":0.0000040539803,"teacher_disagreement_score":0.38552228,"about_ca_system_score_codex":0.000090079404,"about_ca_system_score_gemma":0.00003292381,"threshold_uncertainty_score":0.4005865},"labels":[],"label_agreement":null},{"id":"W2321691898","doi":"10.3174/ajnr.a2844","title":"A Validation Study of Multicenter Diffusion Tensor Imaging: Reliability of Fractional Anisotropy and Diffusivity Values","year":2011,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":149,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Neurological Disorders and Stroke; Genentech; National Institutes of Health; Teva Pharmaceutical Industries; Biogen; National Multiple Sclerosis Society","keywords":"Fractional anisotropy; Concordance; Diffusion MRI; White matter; Medicine; Corpus callosum; Nuclear medicine; Magnetic resonance imaging; Intraclass correlation; Nuclear magnetic resonance; Pulse sequence; Concordance correlation coefficient; Radiology; Physics; Pathology; Statistics; Mathematics; Internal medicine","score_opus":0.0484040084854849,"score_gpt":0.3402699345200311,"score_spread":0.2918659260345462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2321691898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99085325,0.00001330255,0.008438199,0.00038333086,0.00004412518,0.00022351067,0.00000405813,0.000012781598,0.000027460203],"genre_scores_gemma":[0.98728395,0.0000909818,0.012448818,0.00012502263,0.000031206087,0.0000039510624,9.102903e-7,0.000011489678,0.0000036759038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99893856,0.00017414715,0.00048229517,0.00016985855,0.00013829353,0.00009687236],"domain_scores_gemma":[0.9983489,0.00021993702,0.0008298885,0.00023146777,0.00029655092,0.0000732505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015509537,0.00009605447,0.00044343894,0.00013226672,0.000031587762,0.000001477343,0.00008678256,0.000015577974,0.000012924442],"category_scores_gemma":[0.0002986093,0.00007438441,0.00006810706,0.00013443039,0.0004470693,0.00008045976,0.000044648823,0.00020619962,1.8389755e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059900223,0.0014833448,0.92712784,0.000012196237,0.000018748542,0.000016660457,0.0004798744,0.000005586245,0.066761665,0.00003102319,0.000025547848,0.0034384856],"study_design_scores_gemma":[0.0010306267,0.0042364215,0.989662,0.0000184911,0.00012243714,0.00039324787,0.0005445224,0.0003200477,0.0030395652,0.00051606854,0.00006421886,0.000052354764],"about_ca_topic_score_codex":0.000058089452,"about_ca_topic_score_gemma":2.5342723e-7,"teacher_disagreement_score":0.063722104,"about_ca_system_score_codex":0.000016341031,"about_ca_system_score_gemma":0.000024430914,"threshold_uncertainty_score":0.3033308},"labels":[],"label_agreement":null},{"id":"W2322861895","doi":"10.1002/hbm.23139","title":"Effects of change in FreeSurfer version on classification accuracy of patients with Alzheimer's disease and mild cognitive impairment","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroRx Research (Canada)","funders":"DoD Alzheimer's Disease Neuroimaging Initiative; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; National Institutes of Health; Foundation for the National Institutes of Health; Norges Forskningsråd; Northern California Institute for Research and Education; University of California, San Diego; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Bristol-Myers Squibb; Eli Lilly and Company; Biogen; Eisai; National Institute on Aging; Alzheimer's Association","keywords":"Neuroimaging; Cognition; Alzheimer's Disease Neuroimaging Initiative; Cognitive impairment; Entorhinal cortex; Disease; Psychology; Alzheimer's disease; Dementia; Audiology; Magnetic resonance imaging; Neuroscience; Medicine; Pathology; Radiology; Hippocampus","score_opus":0.10049862533979845,"score_gpt":0.34839473308590335,"score_spread":0.2478961077461049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2322861895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997104,0.00004851625,0.0006762882,0.000916228,0.000004644719,0.0011609157,0.000019844436,0.00002443842,0.0000451158],"genre_scores_gemma":[0.9992985,0.000019491112,0.00025265483,0.00026037134,0.000012475127,0.00011347765,0.000025134994,0.000010605621,0.0000072896914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994747,0.000025354682,0.00012937991,0.00017311184,0.00011314911,0.000084312924],"domain_scores_gemma":[0.9993923,0.00024709327,0.000121974175,0.00013163587,0.000056491106,0.000050544586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005134445,0.0000760031,0.00012182329,0.00011075134,0.00003299428,0.0000015587252,0.000031016396,0.000018234576,0.000006881753],"category_scores_gemma":[0.00007059062,0.00005251499,0.000018347895,0.000085700165,0.00007535157,0.00006382219,0.00002475672,0.000044608463,0.0000010820818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010461953,0.0012097786,0.8846663,0.00048365002,0.000054948618,0.000007576473,0.0007154634,2.3553716e-7,0.095739305,0.0016230401,0.00045033748,0.01400316],"study_design_scores_gemma":[0.002301513,0.00030868428,0.9925422,0.0017950335,0.000041034713,1.11886635e-7,0.000017833441,0.000018239016,0.002554909,0.00026086555,0.00010055816,0.00005899216],"about_ca_topic_score_codex":0.0000072148023,"about_ca_topic_score_gemma":9.0109916e-7,"teacher_disagreement_score":0.10787592,"about_ca_system_score_codex":0.000020788566,"about_ca_system_score_gemma":0.000008054976,"threshold_uncertainty_score":0.21414992},"labels":[],"label_agreement":null},{"id":"W2324703134","doi":"10.1109/embc.2014.6944098","title":"Optimized methodology for neonatal diffusion tensor imaging processing and study-specific template construction","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Template; Computer science; White matter; Modular design; Population; Pipeline (software); Artificial intelligence; Medicine; Magnetic resonance imaging; Programming language","score_opus":0.12621877826627628,"score_gpt":0.39593935126441127,"score_spread":0.269720572998135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2324703134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07386886,0.0001331455,0.9231196,0.0013015146,0.00003226953,0.0008944319,0.0000019076895,0.00026638346,0.00038185646],"genre_scores_gemma":[0.26235923,0.00004824067,0.7370704,0.00021845632,0.000059425438,0.00010943086,0.000007254943,0.000018342651,0.000109236316],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992639,0.000038748505,0.00018326809,0.00031125636,0.00006402689,0.0001388176],"domain_scores_gemma":[0.99944246,0.00017230744,0.00007210259,0.00017091887,0.00008546147,0.000056728142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024152033,0.00010289916,0.00021731597,0.0000770069,0.00016913799,0.00001943028,0.000037295482,0.000025499061,0.00001209615],"category_scores_gemma":[0.00007718279,0.000081758044,0.00002984546,0.00007800036,0.00010009355,0.00008303894,0.00003961573,0.00009344616,8.142699e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031877356,0.000105134604,0.01703786,0.00006723143,0.0000073854526,0.0000031288964,0.00016553527,0.0000076277697,0.02176529,0.0030826104,0.0002698551,0.9571696],"study_design_scores_gemma":[0.042114194,0.0026385996,0.08975402,0.00043220035,0.0008299985,0.005833427,0.007478461,0.25100264,0.045871653,0.072588556,0.4795237,0.0019325393],"about_ca_topic_score_codex":0.000003504571,"about_ca_topic_score_gemma":2.8133863e-7,"teacher_disagreement_score":0.95523703,"about_ca_system_score_codex":0.000012695623,"about_ca_system_score_gemma":0.0000080945165,"threshold_uncertainty_score":0.33339962},"labels":[],"label_agreement":null},{"id":"W2328218730","doi":"10.1017/s0317167100000627","title":"MRI Techniques: Bilateral Findings and “Normal Findings”","year":2000,"lang":"en","type":"review","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre","funders":"","keywords":"Magnetic resonance imaging; Fluid-attenuated inversion recovery; Coronal plane; Temporal lobe; Hippocampal sclerosis; Medicine; Nuclear medicine; Radiology; Creatine; Magnetic resonance spectroscopic imaging; Epilepsy; Internal medicine","score_opus":0.08788210174650572,"score_gpt":0.3591172914560427,"score_spread":0.271235189709537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328218730","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13514107,0.8566886,0.000049553637,0.003141975,0.00044236763,0.00091406045,0.00005740507,0.00011532107,0.0034496428],"genre_scores_gemma":[0.008609085,0.9795173,0.008982207,0.0023484777,0.00039141293,0.000017510443,0.0000019522433,0.000043717973,0.000088333734],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9946768,0.0005480214,0.0015650985,0.00092160905,0.00072271144,0.0015657184],"domain_scores_gemma":[0.9956792,0.00052152865,0.0008322688,0.0002766207,0.00026521485,0.0024251835],"candidate_categories":["metaepi_narrow","sts","research_integrity"],"consensus_categories":["sts"],"category_scores_codex":[0.0026394874,0.00071057497,0.0018133313,0.002062085,0.0025805146,0.0007695971,0.0018909223,0.0005084607,0.00022071313],"category_scores_gemma":[0.0007474924,0.00045946045,0.00064096774,0.0018134154,0.007630019,0.0008045616,0.000121858066,0.0030198104,0.0000054395487],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008643299,0.00008664526,0.038586754,0.0006628739,0.00006764725,0.017659472,0.00019475161,0.000034616012,0.0000033499255,0.001135115,0.0043720584,0.9371103],"study_design_scores_gemma":[0.00014146938,0.027502365,0.0009231364,0.0014396405,0.00031740128,0.15549877,0.000016390974,0.00004217835,0.000010239674,0.0036631075,0.8099684,0.0004768653],"about_ca_topic_score_codex":0.00024423903,"about_ca_topic_score_gemma":0.0013553269,"teacher_disagreement_score":0.9366334,"about_ca_system_score_codex":0.00031797943,"about_ca_system_score_gemma":0.0044266097,"threshold_uncertainty_score":0.9997857},"labels":[],"label_agreement":null},{"id":"W2328558547","doi":"10.1097/wnr.0000000000000044","title":"Functional reorganization of the corticospinal tract in a pediatric patient with an arteriovenous malformation","year":2013,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McMaster University; Hospital for Sick Children","funders":"","keywords":"Corticospinal tract; Magnetoencephalography; Precentral gyrus; White matter; Neuroscience; Tractography; Lateralization of brain function; Diffusion MRI; Psychology; Anatomy; Motor system; Medicine; Magnetic resonance imaging; Electroencephalography; Radiology","score_opus":0.028410600197774163,"score_gpt":0.26388390662875194,"score_spread":0.23547330643097777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328558547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99584746,0.000003038851,0.002597698,0.0005193596,0.000026772379,0.0005335487,8.43443e-7,0.000046041994,0.00042520487],"genre_scores_gemma":[0.9981944,0.0000066143634,0.0013506374,0.00030617908,0.000024463288,0.000059163496,0.00001594951,0.000012200777,0.000030372174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935555,0.000010847205,0.00025559985,0.00012629516,0.00017613733,0.00007557267],"domain_scores_gemma":[0.99940205,0.0000067051,0.00019734951,0.00024943077,0.00011243136,0.00003201194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002653836,0.000059568047,0.000081506754,0.000049117643,0.00003163552,0.0000060976995,0.00003286856,0.000018691431,0.000028035247],"category_scores_gemma":[0.000028254222,0.000039336814,0.000018364928,0.00028306834,0.000023176912,0.00015639512,0.000012484655,0.0001020438,0.0000028065313],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006723501,0.00094771985,0.97372836,0.000052112217,0.0000027702165,0.000047875725,0.00017648935,0.00023922067,0.016897233,0.0003201818,0.00023221943,0.0072885584],"study_design_scores_gemma":[0.00016852713,0.0004381942,0.99547654,0.000009264215,0.00001705471,0.0008720732,0.000012708645,0.00045954995,0.002152231,0.0002112376,0.00014378766,0.000038855596],"about_ca_topic_score_codex":0.000013498028,"about_ca_topic_score_gemma":0.0000013611863,"teacher_disagreement_score":0.021748131,"about_ca_system_score_codex":0.000018660941,"about_ca_system_score_gemma":0.000060220165,"threshold_uncertainty_score":0.16041087},"labels":[],"label_agreement":null},{"id":"W2330281932","doi":"10.1017/s0317167100006120","title":"Wallerian-Like Degeneration After Ischemic Stroke Revealed by Diffusion - Weighted Imaging","year":2007,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Magnetic resonance imaging; Middle cerebral artery; Radiology; Anterior cerebral artery; Dysarthria; Wallerian degeneration; Effective diffusion coefficient; Cardiology; Ischemia; Anatomy","score_opus":0.03063846124426548,"score_gpt":0.29841350257407073,"score_spread":0.26777504132980523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330281932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98671705,0.0018518639,0.0018219326,0.006902894,0.0004191333,0.00022895246,0.00001718624,0.00004412336,0.0019968916],"genre_scores_gemma":[0.9802803,0.00041900817,0.011538969,0.0073008067,0.0002760982,0.0000047205353,0.0000012927023,0.000017371973,0.00016145238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996409,0.0002278347,0.0009090265,0.00055499387,0.0006969319,0.0012022409],"domain_scores_gemma":[0.99668455,0.00023646803,0.00062627334,0.00019307641,0.00043577686,0.0018238805],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0026624205,0.00031375806,0.0004267027,0.0007738736,0.0017631946,0.00033883104,0.0009317031,0.00014363672,0.00016473027],"category_scores_gemma":[0.0005897201,0.00021929457,0.00021733352,0.0010086441,0.0033001893,0.00074602617,0.000060482373,0.0011614114,0.00000298653],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027915227,0.000067062334,0.9684039,0.0000091107895,0.000011152948,0.004353482,0.00013454437,0.00006869373,0.00908944,0.00021145336,0.007718596,0.009653444],"study_design_scores_gemma":[0.002451284,0.06356776,0.47596988,0.00025504574,0.00034443947,0.13443314,0.00042316783,0.007236317,0.00942949,0.01088111,0.29344374,0.0015646415],"about_ca_topic_score_codex":0.00032493268,"about_ca_topic_score_gemma":0.004697824,"teacher_disagreement_score":0.492434,"about_ca_system_score_codex":0.00021156554,"about_ca_system_score_gemma":0.0011925634,"threshold_uncertainty_score":0.9995364},"labels":[],"label_agreement":null},{"id":"W2332641582","doi":"10.1017/s0317167100000846","title":"Callosal Atrophy Correlates with Temporal Lobe Volume and Mental Status in Alzheimer's Disease","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Medical Research Council; Medical Research Council Canada","keywords":"Atrophy; Corpus callosum; Temporal lobe; Alzheimer's disease; Commissure; Neuroscience; Psychology; Dementia; Medicine; Pathology; Disease","score_opus":0.03592678515444098,"score_gpt":0.2942231187294774,"score_spread":0.2582963335750364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2332641582","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98906535,0.0017327031,0.000016631175,0.007840541,0.00009877096,0.00023738747,0.000017399907,0.000023244249,0.0009679786],"genre_scores_gemma":[0.99244183,0.00087122066,0.003954616,0.0025994375,0.00008768573,0.0000044130757,8.574399e-7,0.000012550226,0.00002736212],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972558,0.00024611517,0.00055923284,0.00048287484,0.00043826562,0.0010176824],"domain_scores_gemma":[0.99693096,0.00013145874,0.00028424693,0.000129827,0.00014439963,0.0023791308],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.000840007,0.0002648458,0.0003925839,0.00054221414,0.0011581045,0.00027379434,0.0005733757,0.00008410786,0.00023191205],"category_scores_gemma":[0.00023371584,0.00017148019,0.000101143894,0.0009207823,0.005609655,0.00064960064,0.000031649255,0.0009669877,0.0000023704433],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002566669,0.00003711194,0.9834892,0.0000028195984,0.0000069792227,0.006045184,0.00010799412,0.00095839147,0.000011968699,0.00021764541,0.00024500143,0.008620994],"study_design_scores_gemma":[0.00082477566,0.048301287,0.89442754,0.00009034821,0.00009064531,0.027949756,0.00012225071,0.005690168,0.000021356123,0.009048057,0.013053434,0.0003804],"about_ca_topic_score_codex":0.001324551,"about_ca_topic_score_gemma":0.014760066,"teacher_disagreement_score":0.08906172,"about_ca_system_score_codex":0.00012643056,"about_ca_system_score_gemma":0.0018972249,"threshold_uncertainty_score":0.9970965},"labels":[],"label_agreement":null},{"id":"W2337241400","doi":"10.1016/j.neuroimage.2016.04.048","title":"Dance and music training have different effects on white matter diffusivity in sensorimotor pathways","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; International Laboratory for Brain, Music and Sound Research; Cégep Marie-Victorin; Université de Montréal; Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dance; Psychology; Corpus callosum; White matter; Cognitive psychology; Diffusion MRI; Neuroscience; Visual arts; Medicine; Art","score_opus":0.07154916855905313,"score_gpt":0.3019285371522233,"score_spread":0.23037936859317015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2337241400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99162644,0.000010775402,0.0022793456,0.003691987,0.000050052997,0.0005356486,0.000016501794,0.00015111269,0.0016381468],"genre_scores_gemma":[0.9953683,0.00003326438,0.0009311859,0.0029749384,0.000091514965,0.00009256433,0.0000021546143,0.000041211722,0.00046484178],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989234,0.000048219095,0.00016241202,0.00046590544,0.00013387982,0.0002661461],"domain_scores_gemma":[0.99917066,0.00022231789,0.00005657192,0.000426641,0.000015659703,0.000108143315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047103385,0.0001883086,0.000257661,0.00009153575,0.000049033068,0.000013911508,0.00006488023,0.000040419418,0.000027662278],"category_scores_gemma":[0.000069884525,0.00012631585,0.000044765082,0.00006845361,0.00007569239,0.00006636315,0.000060304963,0.00021207299,0.000024211171],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008128014,0.00019030209,0.328667,0.00010485263,0.0000033762753,0.00024946348,0.00024258041,2.5138422e-7,0.6233678,0.00021990454,0.0009116834,0.04596148],"study_design_scores_gemma":[0.0011620516,0.00019174378,0.9720523,0.0002550252,0.000011872359,0.00005421904,0.000007043267,0.00007752503,0.024250537,0.00059556315,0.00120141,0.00014074612],"about_ca_topic_score_codex":0.0000018915993,"about_ca_topic_score_gemma":0.0000023984178,"teacher_disagreement_score":0.64338523,"about_ca_system_score_codex":0.000028588847,"about_ca_system_score_gemma":0.000007792419,"threshold_uncertainty_score":0.5151011},"labels":[],"label_agreement":null},{"id":"W2337594561","doi":"10.1037/neu0000258","title":"White matter and information processing speed following treatment with cranial-spinal radiation for pediatric brain tumor.","year":2016,"lang":"en","type":"article","venue":"Neuropsychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; Princess Margaret Cancer Centre; Hospital for Sick Children; University of British Columbia; Ontario Institute for Cancer Research; BC Children's Hospital; Children's Hospital of Eastern Ontario; University of Calgary","funders":"","keywords":"White matter; Optic radiation; Psychology; Diffusion MRI; Visual processing; Audiology; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.02670042228463997,"score_gpt":0.33940743535808293,"score_spread":0.31270701307344295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2337594561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8892049,0.00004186859,0.08471629,0.024101127,0.00006371358,0.0009023685,0.000010296783,0.00015689332,0.0008025139],"genre_scores_gemma":[0.9878622,0.000039671464,0.0068608425,0.004735809,0.00013302476,0.00010505179,0.0000110253995,0.00002255236,0.00022978833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942297,0.000013619909,0.0001569479,0.0001990713,0.00005816576,0.00014921447],"domain_scores_gemma":[0.9996293,0.000034399214,0.000095836695,0.00015192591,0.000036523594,0.00005197013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000039145565,0.00010425374,0.00013036396,0.00010457319,0.000072622184,0.000014752486,0.00003142691,0.000026647713,0.000008543187],"category_scores_gemma":[0.000018033716,0.000066470464,0.000030397487,0.00010853691,0.000029579594,0.00025425636,0.000007171628,0.000040943276,0.000013044072],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015188624,0.00022075094,0.6284475,0.0001408833,0.000020443253,0.000040257106,0.0002270128,0.0000022470886,0.017825516,0.00031669647,0.0042774826,0.34696236],"study_design_scores_gemma":[0.0059101684,0.0030694199,0.92715794,0.00004517549,0.00013228299,0.00057312293,0.00000939064,0.00013508892,0.0003853519,0.00034200848,0.06204824,0.00019180428],"about_ca_topic_score_codex":8.116771e-7,"about_ca_topic_score_gemma":1.9336343e-7,"teacher_disagreement_score":0.34677055,"about_ca_system_score_codex":0.00002664736,"about_ca_system_score_gemma":0.000021063968,"threshold_uncertainty_score":0.27105868},"labels":[],"label_agreement":null},{"id":"W2340818140","doi":"10.1016/j.neuroimage.2016.04.038","title":"Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Research and Development; National Institute of Nursing Research; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Biogen Idec; Genentech; National Institutes of Health; Servier; Eisai; Pfizer; BioClinica; Synarc; National Center for Complementary and Integrative Health; National Institute on Aging; Fonds Québécois de la Recherche sur la Nature et les Technologies; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; Medpace; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Research Resources; F. Hoffmann-La Roche; Ellison Medical Foundation; Alzheimer's Drug Discovery Foundation; Merck; NIH Blueprint for Neuroscience Research; Fujirebio Europe; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics","keywords":"Diffusion MRI; Univariate; Fractional anisotropy; Multivariate statistics; Population; White matter; Pattern recognition (psychology); Voxel; Artificial intelligence; Partial least squares regression; Multivariate analysis; Magnetic resonance imaging; Computer science; Statistics; Mathematics; Medicine; Radiology","score_opus":0.050328048339124805,"score_gpt":0.3634823989638484,"score_spread":0.3131543506247236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340818140","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21443191,0.000007564099,0.7815647,0.0030162635,0.00001943355,0.00060026586,0.0002267324,0.000072772535,0.00006032956],"genre_scores_gemma":[0.9462669,0.0000054562393,0.05277251,0.0007224054,0.000020553578,0.00011661279,0.00005035432,0.000032524185,0.000012677604],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99849826,0.0000729235,0.00043049236,0.0005222389,0.00021958226,0.00025649913],"domain_scores_gemma":[0.9987793,0.00016576702,0.0001389619,0.0006167226,0.00008062594,0.000218645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009809239,0.00016371622,0.00030967643,0.00046422996,0.00006120841,0.000016700189,0.00011544943,0.000024767438,0.000083308536],"category_scores_gemma":[0.00012136449,0.00013335634,0.00010107542,0.0008515572,0.000086921624,0.0001275799,0.00009027027,0.00010146361,0.000023916276],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019211535,0.0003751049,0.83323264,0.00001566497,0.000061723214,0.000022981782,0.00008806993,0.0010096825,0.15356012,0.001017253,0.000104092236,0.01032057],"study_design_scores_gemma":[0.0005175204,0.000025630508,0.9091855,0.000053481028,0.0009575312,0.0000035603973,0.000009401596,0.08754908,0.00094532163,0.0002946933,0.00030880398,0.00014945706],"about_ca_topic_score_codex":0.00011890976,"about_ca_topic_score_gemma":0.0000056750328,"teacher_disagreement_score":0.731835,"about_ca_system_score_codex":0.000052585605,"about_ca_system_score_gemma":0.00003462548,"threshold_uncertainty_score":0.5438114},"labels":[],"label_agreement":null},{"id":"W2342252618","doi":"10.3174/ajnr.a4772","title":"Gray Matter Growth Is Accompanied by Increasing Blood Flow and Decreasing Apparent Diffusion Coefficient during Childhood","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Globus pallidus; Putamen; Cerebral blood flow; Medicine; Effective diffusion coefficient; Thalamus; Caudate nucleus; Basal ganglia; Grey matter; Nuclear medicine; Cerebral cortex; Internal medicine; Cardiology; Magnetic resonance imaging; Central nervous system; Radiology; White matter","score_opus":0.011479287923401625,"score_gpt":0.26901416842542986,"score_spread":0.2575348805020282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342252618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848563,0.0001181891,0.008777314,0.005987565,0.000041005827,0.00013776925,0.000010418453,0.00003824001,0.000033166587],"genre_scores_gemma":[0.98904026,0.0005781213,0.00805032,0.0021818432,0.00009962126,0.000004126375,0.00000159083,0.000033873737,0.000010241411],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987699,0.00012719481,0.00040434737,0.00027460896,0.00015525564,0.00026872844],"domain_scores_gemma":[0.99883455,0.00019601482,0.00043173754,0.00021426685,0.000092479684,0.00023093585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011977156,0.00017551509,0.00047617272,0.00016157128,0.0001062912,0.000013555932,0.00014261226,0.000028707267,0.00002083149],"category_scores_gemma":[0.00010683555,0.00011536185,0.00008667356,0.00017136511,0.0003427592,0.00007102257,0.00007837731,0.00022890807,0.000002925776],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032740922,0.00044040452,0.39303303,0.000016606155,0.00006428167,0.00010419339,0.00023161664,0.0000019599206,0.5910595,0.00002399704,0.00073564914,0.013961357],"study_design_scores_gemma":[0.002685181,0.001375247,0.9384337,0.0002824859,0.0002347821,0.028128747,0.000071483875,0.000054133565,0.027224159,0.000338786,0.0009181026,0.00025317256],"about_ca_topic_score_codex":0.000011689405,"about_ca_topic_score_gemma":9.48521e-8,"teacher_disagreement_score":0.5638353,"about_ca_system_score_codex":0.000032390664,"about_ca_system_score_gemma":0.00002863966,"threshold_uncertainty_score":0.47043195},"labels":[],"label_agreement":null},{"id":"W2343783019","doi":"10.3174/ajnr.a4788","title":"Tractography at 3T MRI of Corpus Callosum Tracts Crossing White Matter Hyperintensities","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; University of Toronto; Queen's University","funders":"","keywords":"Corpus callosum; White matter; Hyperintensity; Diffusion MRI; Cingulum (brain); Fractional anisotropy; Tractography; Fluid-attenuated inversion recovery; Medicine; Magnetic resonance imaging; Anatomy; Radiology","score_opus":0.03429017887771286,"score_gpt":0.31555428671333197,"score_spread":0.2812641078356191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2343783019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9699268,0.000075607815,0.012766887,0.016826274,0.00010128231,0.00008376556,0.000011557346,0.000025992393,0.00018187835],"genre_scores_gemma":[0.9885971,0.00026191556,0.008202873,0.0026612612,0.00009257401,0.000002878349,7.216608e-7,0.000028770997,0.00015191434],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99892354,0.00007141144,0.00048552896,0.00017371547,0.0001230948,0.00022270597],"domain_scores_gemma":[0.9984938,0.00019828377,0.0007003743,0.00026522207,0.00020793275,0.00013441706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008486855,0.00013661842,0.00056336506,0.0002064174,0.000055995108,0.0000061614037,0.00013562567,0.00003166344,0.000039963434],"category_scores_gemma":[0.000050981696,0.00008878018,0.00020050415,0.00018417591,0.00133568,0.00007946019,0.000031728207,0.00020822162,0.000005676131],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005409351,0.00011490664,0.49791712,0.000015409927,0.000050379655,0.00022100586,0.00013570533,0.000006705441,0.48780987,0.00014764277,0.002414805,0.010625525],"study_design_scores_gemma":[0.0010419494,0.0031701494,0.9162328,0.00015491777,0.00012533901,0.022593059,0.0000809999,0.000008052824,0.01940795,0.00062230084,0.03637419,0.00018827019],"about_ca_topic_score_codex":0.0000060489924,"about_ca_topic_score_gemma":6.72709e-7,"teacher_disagreement_score":0.4684019,"about_ca_system_score_codex":0.000032388634,"about_ca_system_score_gemma":0.000048607653,"threshold_uncertainty_score":0.49213687},"labels":[],"label_agreement":null},{"id":"W2344067133","doi":"10.1016/j.pscychresns.2016.04.014","title":"White matter integrity in major depressive disorder: Implications of childhood trauma, 5-HTTLPR and BDNF polymorphisms","year":2016,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; University of Calgary; McMaster University","funders":"","keywords":"5-HTTLPR; White matter; Major depressive disorder; Medicine; Psychology; Internal medicine; Clinical psychology; Genetics; Biology; Polymorphism (computer science); Allele; Gene","score_opus":0.06373267162740659,"score_gpt":0.3913081380794589,"score_spread":0.3275754664520523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344067133","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8374585,0.0007057026,0.004925402,0.15263599,0.000055631128,0.0010393781,0.0000688671,0.000117391326,0.0029931357],"genre_scores_gemma":[0.9901258,0.00027278668,0.008336166,0.00064931344,0.00007288009,0.00021919135,0.0000069395055,0.000054931355,0.0002619986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979485,0.00013616061,0.00042310488,0.0006519328,0.0003160374,0.00052425696],"domain_scores_gemma":[0.9985128,0.00021569879,0.00010523674,0.00082815485,0.0001480246,0.0001901063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003443791,0.00018685425,0.00029267863,0.0005127165,0.00018141996,0.000027025535,0.00028425417,0.000056974444,0.00010396402],"category_scores_gemma":[0.00012248298,0.0001421016,0.00007885116,0.0006161502,0.0004296583,0.0002060955,0.00022155729,0.0007598849,0.000021741902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004549449,0.00036832428,0.9717768,0.000052305037,0.000008354567,0.0000040290274,0.000075710355,2.771493e-7,0.009471186,0.0021426638,0.0016640099,0.0143908365],"study_design_scores_gemma":[0.001323469,0.0000956693,0.97692525,0.00026111992,0.00001703165,0.00013558072,0.00005976614,0.000031258984,0.00082382467,0.019254906,0.00093636557,0.00013578111],"about_ca_topic_score_codex":0.00007823992,"about_ca_topic_score_gemma":0.000032136915,"teacher_disagreement_score":0.15266728,"about_ca_system_score_codex":0.000040978382,"about_ca_system_score_gemma":0.00010590984,"threshold_uncertainty_score":0.5794735},"labels":[],"label_agreement":null},{"id":"W2344337444","doi":"10.1016/j.neuroimage.2016.04.041","title":"Inter-site and inter-scanner diffusion MRI data harmonization","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":170,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vetenskapsrådet","keywords":"Diffusion MRI; Scanner; Spherical harmonics; Fractional anisotropy; Pattern recognition (psychology); Computer science; Artificial intelligence; Invariant (physics); Rotation (mathematics); SIGNAL (programming language); Computer vision; Algorithm; Mathematics; Magnetic resonance imaging; Mathematical analysis","score_opus":0.07737868940764157,"score_gpt":0.3476584246011658,"score_spread":0.2702797351935242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2344337444","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23810391,0.00007337042,0.7280688,0.029935807,0.00012879605,0.0006136379,0.00016403345,0.00053191866,0.0023796647],"genre_scores_gemma":[0.9824509,0.0005151974,0.0115125915,0.0018822163,0.000116824245,0.000018530087,0.00007997923,0.000048577178,0.0033752087],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99905914,0.000028001987,0.00016889311,0.0004927652,0.00009759382,0.00015362893],"domain_scores_gemma":[0.99875873,0.000063763284,0.00006146135,0.00096948864,0.000048894974,0.000097653334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000076772936,0.00012332313,0.0001361625,0.000070472255,0.00007578469,0.000024347893,0.00017384678,0.00003180713,0.00007910798],"category_scores_gemma":[0.00013813325,0.000083368446,0.000021760901,0.00011381965,0.00010153035,0.00025218693,0.0004588742,0.00014090777,0.000059133337],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069682865,0.00014368734,0.032931708,0.00003778856,0.0000065871595,0.00005643006,0.00004793833,7.891289e-8,0.7680442,0.00040776763,0.038666178,0.159588],"study_design_scores_gemma":[0.002303714,0.0003838732,0.108604625,0.00042663325,0.000118795,0.00047184076,0.000018213355,0.0046774927,0.03461845,0.0012790032,0.84667546,0.00042188592],"about_ca_topic_score_codex":0.000006466538,"about_ca_topic_score_gemma":0.0000021256444,"teacher_disagreement_score":0.8080093,"about_ca_system_score_codex":0.000016370537,"about_ca_system_score_gemma":0.000010978106,"threshold_uncertainty_score":0.33996665},"labels":[],"label_agreement":null},{"id":"W2345039138","doi":"10.1002/jmri.25269","title":"MRI in the evaluation of localization‐related epilepsy","year":2016,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; University Health Network; Hospital for Sick Children","funders":"","keywords":"Epilepsy; Diffusion MRI; Neuroimaging; Epilepsy surgery; Medicine; White matter; Magnetic resonance imaging; Radiology; Lesion; Medical physics; Pathology; Psychiatry","score_opus":0.09849419431217071,"score_gpt":0.42647568063472696,"score_spread":0.32798148632255625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345039138","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008001605,0.9929393,0.0038113906,0.0012599804,0.000073253934,0.0008539534,0.00000665421,0.000009919519,0.0010375242],"genre_scores_gemma":[0.00030701834,0.9970899,0.0022238493,0.00011606517,0.000104377934,0.00004648315,0.0000048391853,0.00003306017,0.000074385214],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99720275,0.0003382571,0.0013341027,0.00018538842,0.00077160634,0.00016788667],"domain_scores_gemma":[0.99746823,0.0002921169,0.0012222307,0.00044930624,0.0005265617,0.000041523675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021194452,0.00019823753,0.0008951943,0.00033870834,0.000033960987,0.000013778634,0.00034254696,0.00006928548,0.00009978667],"category_scores_gemma":[0.00039970514,0.000110393565,0.00029760046,0.0005893478,0.00013150653,0.000095701485,0.000033328557,0.00047524486,0.000005775673],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052146447,0.0000614215,0.00024757846,0.0005752524,0.000005107721,0.000019318355,0.000043077147,0.000005769246,0.0000029419277,0.00017370374,0.0015981259,0.9972625],"study_design_scores_gemma":[0.0006706153,0.00008166079,0.000757778,0.024897344,0.0006775009,0.0010889443,0.000018406783,0.00072549534,0.0000024625724,0.002105458,0.96887064,0.000103679944],"about_ca_topic_score_codex":0.0000018520252,"about_ca_topic_score_gemma":2.0765411e-7,"teacher_disagreement_score":0.9971588,"about_ca_system_score_codex":0.00014074586,"about_ca_system_score_gemma":0.00042135463,"threshold_uncertainty_score":0.4501719},"labels":[],"label_agreement":null},{"id":"W2345819060","doi":"10.1016/j.nicl.2016.04.013","title":"Integrity of the arcuate fasciculus in patients with schizophrenia with auditory verbal hallucinations: A DTI-tractography study","year":2016,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Canadian Institutes of Health Research; Brain and Behavior Research Foundation","keywords":"Arcuate fasciculus; Fasciculus; Fractional anisotropy; Schizophrenia (object-oriented programming); Tractography; White matter; Psychology; Diffusion MRI; Audiology; Psychosis; Neuroscience; Uncinate fasciculus; Medicine; Anatomy; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.06868667258836783,"score_gpt":0.37374370511709815,"score_spread":0.3050570325287303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345819060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99526,0.000004588516,0.0011940243,0.0018683753,0.000087220884,0.001302783,0.000020016741,0.000089594876,0.00017342549],"genre_scores_gemma":[0.9970104,0.00001298232,0.002487978,0.00026309802,0.00006439176,0.00007860465,0.0000023860416,0.000029451894,0.00005070573],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981802,0.0001803318,0.0005347455,0.0005100713,0.00040019653,0.00019444553],"domain_scores_gemma":[0.9981547,0.00035824493,0.00025372588,0.0009090984,0.00023201409,0.00009224277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028737495,0.0001739272,0.00034582315,0.00010592341,0.00006348518,0.000008833909,0.0002613775,0.000059254573,0.000012267846],"category_scores_gemma":[0.00041852848,0.00008119215,0.00011113127,0.0005056411,0.0004966949,0.0001235184,0.00010588946,0.0006620861,0.0000058230326],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009684718,0.0028886495,0.98986197,0.0000092192895,0.000019670193,0.000016788192,0.000022711076,7.70589e-7,0.00023147215,0.000070997936,0.00019360158,0.0057157106],"study_design_scores_gemma":[0.006028611,0.0020041366,0.9907759,0.00016820883,0.000071475944,0.0000057285743,0.000017926495,0.000010581092,0.00013971255,0.00018260688,0.00049140543,0.0001037096],"about_ca_topic_score_codex":0.000011293855,"about_ca_topic_score_gemma":0.000032993157,"teacher_disagreement_score":0.0056120013,"about_ca_system_score_codex":0.000025469639,"about_ca_system_score_gemma":0.00010619997,"threshold_uncertainty_score":0.33109197},"labels":[],"label_agreement":null},{"id":"W2346434957","doi":"10.1111/adb.12363","title":"Characterization of white matter integrity deficits in cocaine‐dependent individuals with substance‐induced psychosis compared with non‐psychotic cocaine users","year":2016,"lang":"en","type":"article","venue":"Addiction Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; AstraZeneca","keywords":"White matter; Psychosis; Fractional anisotropy; Diffusion MRI; Psychology; Corpus callosum; Schizophrenia (object-oriented programming); Neuroscience; Corona radiata (embryology); Voxel; Internal medicine; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04531289078426361,"score_gpt":0.31965017137040164,"score_spread":0.27433728058613804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346434957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92588913,0.000006027279,0.06993963,0.0031059405,0.00004529534,0.0006272176,0.000088253655,0.00008219224,0.00021632058],"genre_scores_gemma":[0.9959993,0.000078739235,0.002747745,0.0006011851,0.000027566806,0.00018700633,0.00023569805,0.000025676458,0.00009709147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99890846,0.000052926185,0.00034171692,0.00037631253,0.000110607456,0.00021000065],"domain_scores_gemma":[0.9991266,0.00005426465,0.00025462903,0.0003527836,0.000149191,0.00006249017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114207236,0.0001700767,0.00033675312,0.00021459616,0.000051192794,0.0000037281118,0.00009331021,0.000105660074,0.00012422689],"category_scores_gemma":[0.000009690095,0.000104469655,0.000027028056,0.00037680822,0.00013424292,0.00009592888,0.000015542693,0.00018694447,0.00001293437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003660755,0.00015497487,0.6492657,0.00001057562,0.00002887336,0.0000019950924,0.00010391896,0.0000016771331,0.3493883,0.00015772574,0.00006822582,0.0004519404],"study_design_scores_gemma":[0.0029808576,0.0007602932,0.9602272,0.00040853248,0.0000593311,0.00007888553,0.000035202207,0.00004803921,0.034014124,0.00013855765,0.0010760867,0.00017288185],"about_ca_topic_score_codex":0.000027910815,"about_ca_topic_score_gemma":0.00007543073,"teacher_disagreement_score":0.31537417,"about_ca_system_score_codex":0.00006382379,"about_ca_system_score_gemma":0.000027390428,"threshold_uncertainty_score":0.42601487},"labels":[],"label_agreement":null},{"id":"W2347466196","doi":"10.1371/journal.pone.0155557","title":"ZOOM or Non-ZOOM? Assessing Spinal Cord Diffusion Tensor Imaging Protocols for Multi-Centre Studies","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Université de Montréal","funders":"National Institute of Neurological Disorders and Stroke; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Fonds de recherche du Québec – Nature et technologies; International Spinal Research Trust; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Multiple Sclerosis Society; Wings for Life","keywords":"Diffusion MRI; Scanner; Echo-planar imaging; Reproducibility; Spinal cord; White matter; Computer science; Zoom; Biomedical engineering; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Mathematics; Radiology; Optics","score_opus":0.4180598378084749,"score_gpt":0.4811919151031335,"score_spread":0.06313207729465864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2347466196","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52165335,0.00022077006,0.37342608,0.03282867,0.000074010226,0.06995678,0.00008152077,0.0015410236,0.00021777413],"genre_scores_gemma":[0.22021821,0.00016693921,0.7484935,0.0010301375,0.00038633123,0.023239965,0.000011164113,0.00011144455,0.006342317],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988409,0.000013340646,0.0002655322,0.00038062714,0.00020363709,0.00029595493],"domain_scores_gemma":[0.9989836,0.00011384877,0.00014202537,0.0003717954,0.00029436947,0.00009435823],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008949058,0.00017457968,0.00035252,0.000067557994,0.00018695199,0.000024221992,0.000104008956,0.000031664084,0.00001800283],"category_scores_gemma":[0.00042547318,0.00010441832,0.000063575826,0.000110245506,0.00009946397,0.00014954127,0.000093557275,0.00010554186,0.000015243508],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011550245,0.0038093154,0.05351364,0.0009296488,0.00013729792,0.000034646207,0.00006841356,5.2509318e-8,0.8492903,0.0001110417,0.0016054474,0.08934519],"study_design_scores_gemma":[0.030779265,0.0050028753,0.0811597,0.049787,0.0020265626,0.00013153974,0.001307537,0.01577735,0.76763684,0.0027456637,0.041651465,0.001994198],"about_ca_topic_score_codex":0.0000017853099,"about_ca_topic_score_gemma":0.0000012138486,"teacher_disagreement_score":0.3750674,"about_ca_system_score_codex":0.00008999297,"about_ca_system_score_gemma":0.000044830555,"threshold_uncertainty_score":0.42580554},"labels":[],"label_agreement":null},{"id":"W2350722100","doi":"","title":"Change of MR diffusion tensor imaging and its correlation with cognitive impairment in patients with cerebral small vessel disease","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Caudate nucleus; Dementia; Frontal lobe; White matter; Medicine; Neuropsychology; Internal medicine; Cardiology; Psychology; Cognition; Correlation; Magnetic resonance imaging; Neuroscience; Radiology; Disease","score_opus":0.024709243266931583,"score_gpt":0.2699094831966479,"score_spread":0.24520023992971635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2350722100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98750126,0.000016747974,0.010756792,0.00055820507,0.0000042814045,0.00094617106,0.000010263954,0.000051040985,0.00015524743],"genre_scores_gemma":[0.99733704,0.00000836945,0.002105962,0.00034131453,0.000011904614,0.000084815125,0.000048443668,0.000014885741,0.00004724726],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949574,0.00001206589,0.00010200138,0.00018664046,0.0001012448,0.00010232639],"domain_scores_gemma":[0.99962395,0.000028848517,0.00006726598,0.00009659094,0.000100232406,0.00008308412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029721114,0.00008845725,0.00011782326,0.00005473638,0.000028122688,0.00000365868,0.00001962936,0.000011066763,0.000006609402],"category_scores_gemma":[0.000017133278,0.000058538208,0.00000941727,0.00009802101,0.000038306694,0.00007497676,0.000025580885,0.00006625059,7.338288e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045966715,0.00028021235,0.9960159,0.000044575994,0.0000024990736,0.0000014842616,0.00008458223,0.0000014357429,0.00004364387,0.00024870224,0.000006826874,0.002810445],"study_design_scores_gemma":[0.0027315489,0.0003771079,0.98826253,0.0003395146,0.00004471815,0.0000014923227,0.00003790006,0.007862267,0.00016867602,0.00007068963,0.000026167027,0.000077379045],"about_ca_topic_score_codex":0.000016867287,"about_ca_topic_score_gemma":0.000003580324,"teacher_disagreement_score":0.009835807,"about_ca_system_score_codex":0.000014979144,"about_ca_system_score_gemma":0.000009084217,"threshold_uncertainty_score":0.23871188},"labels":[],"label_agreement":null},{"id":"W2351131966","doi":"","title":"The Changes of Cerebral White Matter MR Diffusion Tensor Imaging of Brain on Patients of Mild Cognitive Impairment and Its Relationship with Cognitive Dysfunction","year":2015,"lang":"en","type":"article","venue":"Medical Innovation of China","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Montreal Cognitive Assessment; Diffusion MRI; Internal medicine; Cognition; Ischemia; Parahippocampal gyrus; Magnetic resonance imaging; Cardiology; Cognitive impairment; Radiology; Psychiatry; Temporal lobe","score_opus":0.04715136043640825,"score_gpt":0.32559953937687075,"score_spread":0.2784481789404625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2351131966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9847253,0.000024482062,0.0039217197,0.010183343,0.000022376007,0.00057681155,0.00003717256,0.000014946951,0.0004938754],"genre_scores_gemma":[0.998858,0.000008951572,0.0002864454,0.00060369214,0.000019839461,0.000032540025,0.00008701617,0.000012010925,0.00009150561],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988483,0.000046603407,0.0003819663,0.00014244606,0.00049313874,0.000087548346],"domain_scores_gemma":[0.99828887,0.00025599555,0.00044709007,0.00010329516,0.0008566242,0.00004811717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033343764,0.00009254214,0.00019693367,0.0001645957,0.00004318228,0.0000020427135,0.000043640393,0.00004257599,0.000018695324],"category_scores_gemma":[0.0008480949,0.00005901406,0.000017193683,0.00046174903,0.0002493469,0.000051866322,0.000038439448,0.00016549297,5.96627e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008818167,0.00043840424,0.9899877,0.00013629781,0.000021216792,5.4914346e-7,0.00056124595,7.4118884e-7,0.0004045731,0.002103087,0.00085487677,0.00460954],"study_design_scores_gemma":[0.0027087003,0.0010049515,0.98401,0.0009872902,0.00004480629,0.0000048558522,0.00028398196,0.0004425228,0.009651907,0.0007619688,0.000042475385,0.000056537454],"about_ca_topic_score_codex":0.000007637679,"about_ca_topic_score_gemma":0.0000014856357,"teacher_disagreement_score":0.014132726,"about_ca_system_score_codex":0.000016437141,"about_ca_system_score_gemma":0.000047385503,"threshold_uncertainty_score":0.24065234},"labels":[],"label_agreement":null},{"id":"W2358442394","doi":"","title":"A magnetic resonance diffusion tensor imaging analysis of the hippocampus in patients with mild cognitive impairment","year":2012,"lang":"en","type":"article","venue":"Journal of Shandong University","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Montreal Cognitive Assessment; Cognitive impairment; Magnetic resonance imaging; Correlation; Medicine; Hippocampus; Effective diffusion coefficient; Internal medicine; Nuclear medicine; Cognition; Psychology; Audiology; Radiology; Psychiatry; Geometry; Mathematics","score_opus":0.013895819982988614,"score_gpt":0.25166539471123855,"score_spread":0.23776957472824994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2358442394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9988537,0.00017866895,0.00045898635,0.00022207512,0.0000123423,0.00017485014,0.000010384481,0.0000045667225,0.00008444793],"genre_scores_gemma":[0.99889296,0.000051486546,0.00092841353,0.00007046731,0.000009185489,1.9357722e-7,0.000001420904,0.000003797078,0.00004207074],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949867,0.00003052577,0.00012980012,0.00006324896,0.00017456786,0.0001032216],"domain_scores_gemma":[0.9994069,0.000041763764,0.00021231241,0.00010131824,0.00018220494,0.00005550554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008972024,0.000057120134,0.0001861432,0.0002156701,0.000045321558,0.0000018191232,0.0000749749,0.000013762927,0.000010777566],"category_scores_gemma":[0.000018090663,0.000036876023,0.0000914579,0.00060160423,0.00006752146,0.00010272683,0.000042713968,0.0001421565,1.4543326e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000577015,0.00034285404,0.9954929,0.0000057657176,0.000029935223,0.0000059065255,0.0001626461,0.000005302869,0.000072844035,0.000011223473,0.00002775082,0.0032658998],"study_design_scores_gemma":[0.0024574674,0.00014700489,0.9958499,0.00020995087,0.00066593714,0.000006289798,0.0002014641,0.00012072791,0.000108516804,0.000018861549,0.00017601438,0.000037852158],"about_ca_topic_score_codex":0.000014349297,"about_ca_topic_score_gemma":0.0000036479003,"teacher_disagreement_score":0.0032280476,"about_ca_system_score_codex":0.00008723483,"about_ca_system_score_gemma":0.000024275967,"threshold_uncertainty_score":0.15037605},"labels":[],"label_agreement":null},{"id":"W2359665709","doi":"10.1155/2016/7526135","title":"Motor Skill Acquisition Promotes Human Brain Myelin Plasticity","year":2016,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Child and Family Research Institute; University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Natural Sciences and Engineering Research Council of Canada; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"Myelin; White matter; Neuroplasticity; Neuroscience; Psychology; Diffusion MRI; Intraparietal sulcus; Motor skill; Central sulcus; Human brain; Motor learning; Coactivation; Dreyfus model of skill acquisition; Motor cortex; Medicine; Magnetic resonance imaging; Functional magnetic resonance imaging; Central nervous system; Electromyography; Stimulation","score_opus":0.04988203912802484,"score_gpt":0.34109551376306313,"score_spread":0.29121347463503827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2359665709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93665093,0.0000053690014,0.055304762,0.006365231,0.000052638472,0.0005506543,0.00009525876,0.0006093361,0.00036579746],"genre_scores_gemma":[0.9939641,0.0000040968794,0.0038231444,0.0011057975,0.0002764372,0.000070959,0.000014550486,0.00003423542,0.0007066812],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986719,0.00003279436,0.00028458674,0.00044141218,0.0002386726,0.00033065813],"domain_scores_gemma":[0.9989145,0.0004550616,0.00010663669,0.00022672054,0.00010631181,0.00019077047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054858712,0.00020820127,0.00025197584,0.00008522832,0.00018931407,0.000020791997,0.00012862252,0.00008495337,0.0002115343],"category_scores_gemma":[0.0004898224,0.00014164126,0.00009426829,0.00013816889,0.00016672918,0.00017110244,0.00008049259,0.00020213629,0.00008386828],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115433206,0.00020319919,0.0040096673,0.000033512344,0.00000914948,0.00002617277,0.000016590999,0.0000044030303,0.9867616,0.001769884,0.0048383637,0.002212021],"study_design_scores_gemma":[0.003344484,0.00202367,0.6090642,0.00046825403,0.00015525206,0.00029492046,0.000011876612,0.0038359282,0.36194757,0.011775485,0.0063679535,0.000710415],"about_ca_topic_score_codex":0.000011552222,"about_ca_topic_score_gemma":0.0000033533763,"teacher_disagreement_score":0.62481403,"about_ca_system_score_codex":0.000074931,"about_ca_system_score_gemma":0.000022606537,"threshold_uncertainty_score":0.5775963},"labels":[],"label_agreement":null},{"id":"W2369402140","doi":"","title":"Correlation Between Deep Brain White Matter Ischemia and MR Diffusion Tensor Imaging of Mild Cognitive Impairment","year":2013,"lang":"en","type":"article","venue":"Zhongguo yixue yingxiangxue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Montreal Cognitive Assessment; White matter; Fractional anisotropy; Medicine; Cognitive impairment; Magnetic resonance imaging; Nuclear medicine; Internal medicine; Cognition; Cardiology; Radiology; Psychiatry","score_opus":0.021722185593413632,"score_gpt":0.29931712714328856,"score_spread":0.2775949415498749,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2369402140","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9538955,0.00017371414,0.03547781,0.0071362145,0.000039517043,0.0013479972,0.000035706646,0.00018534179,0.0017081924],"genre_scores_gemma":[0.9876074,0.00002614428,0.009168469,0.0015694574,0.000118440614,0.00014214477,0.00011127149,0.00005994751,0.001196697],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99855924,0.000035255005,0.0004186822,0.00044207327,0.0002248071,0.00031993468],"domain_scores_gemma":[0.9989039,0.00018321874,0.00023913046,0.00033623588,0.00016153528,0.00017600766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012130965,0.0002443616,0.00037054947,0.00017472114,0.00013970178,0.000034545672,0.00008159273,0.000087047716,0.00026245438],"category_scores_gemma":[0.000072192786,0.00022417768,0.00009343498,0.00024547798,0.00016022801,0.0002414308,0.0001342668,0.00030799175,0.00009906889],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027752907,0.00009050975,0.979878,0.00010806077,0.000022740009,0.0000071504824,0.000439923,0.0000028020963,0.008304156,0.000031816,0.0058436347,0.00524344],"study_design_scores_gemma":[0.0013431391,0.00010363978,0.9864154,0.0004547252,0.0001401489,0.00008457405,0.00035650612,0.003253071,0.006138319,0.00061929977,0.0008221713,0.000269026],"about_ca_topic_score_codex":0.00006640697,"about_ca_topic_score_gemma":0.0000014528619,"teacher_disagreement_score":0.03371192,"about_ca_system_score_codex":0.00004895383,"about_ca_system_score_gemma":0.000021841412,"threshold_uncertainty_score":0.9141701},"labels":[],"label_agreement":null},{"id":"W2370336172","doi":"","title":"The Observation of Water Compartmentalization In-Vivo in the Feline Lumbar Spinal Cord","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Grey matter; White matter; Spinal cord; Compartmentalization (fire protection); In vivo; Myelin; Anatomy; Pathology; Neuroscience; Chemistry; Nuclear medicine; Medicine; Nuclear magnetic resonance; Biology; Central nervous system; Magnetic resonance imaging; Physics; Radiology","score_opus":0.12227924569488281,"score_gpt":0.3881954848884261,"score_spread":0.2659162391935433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2370336172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.977358,0.000044383003,0.012743358,0.0055441717,0.0000200433,0.0006637136,0.0000010554668,0.000028646235,0.003596638],"genre_scores_gemma":[0.9957536,0.000071748254,0.0030817383,0.00077685824,0.000008323669,0.00004966456,0.000010289953,0.0000044083395,0.00024336627],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9995558,0.000029542602,0.00017599048,0.00007444097,0.00008511926,0.00007907824],"domain_scores_gemma":[0.9997459,0.00001657365,0.000027523585,0.0001744474,0.00002703948,0.000008482679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018139239,0.00004164232,0.00006381673,0.000022556964,0.000036948906,0.000004688852,0.00005349998,0.0000124427,0.00002104657],"category_scores_gemma":[0.000019972473,0.000019756548,0.000014947199,0.0001439188,0.000035664212,0.000030065676,0.000007299101,0.00005659044,0.0000016967756],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033122342,0.0010690121,0.3311239,0.00007796819,0.000011279107,0.000010944409,0.0004824106,0.00017045908,0.26283953,0.3858269,0.008513445,0.009542956],"study_design_scores_gemma":[0.0020928583,0.0009183141,0.38123134,0.000119328855,0.000034162502,0.0000589584,0.00082170346,0.0038995894,0.37133983,0.023611376,0.2156806,0.00019193105],"about_ca_topic_score_codex":0.000020738302,"about_ca_topic_score_gemma":0.00004023531,"teacher_disagreement_score":0.36221552,"about_ca_system_score_codex":0.000017065024,"about_ca_system_score_gemma":0.000007110118,"threshold_uncertainty_score":0.080564864},"labels":[],"label_agreement":null},{"id":"W2375759623","doi":"","title":"Quantitative research of diffusion tensor imaging in cognitive impairment of Parkinson's disease","year":2015,"lang":"en","type":"article","venue":"Chinese Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Putamen; White matter; Caudate nucleus; Diffusion MRI; Substantia nigra; Medicine; Globus pallidus; Parkinson's disease; Striatum; Neuroscience; Magnetic resonance imaging; Internal medicine; Psychology; Basal ganglia; Dopamine; Radiology; Central nervous system; Disease","score_opus":0.10400253968027091,"score_gpt":0.4360482739120871,"score_spread":0.3320457342318162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2375759623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97244,0.021921154,0.0018460926,0.0028061664,0.00004953858,0.00048513137,0.000018055893,0.000013100525,0.00042073068],"genre_scores_gemma":[0.9864821,0.0008210807,0.012434686,0.00009337353,0.000059647176,0.000018035727,0.0000026288446,0.000026662712,0.000061778155],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99780315,0.00015437709,0.00077865075,0.0002323454,0.00074839755,0.0002830984],"domain_scores_gemma":[0.99718565,0.00041010857,0.00044834169,0.00026798472,0.0014323627,0.00025555267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001219172,0.00017074984,0.0004900039,0.00058005936,0.00004038456,0.0000118478965,0.00020566597,0.000018131796,0.000016455393],"category_scores_gemma":[0.00185707,0.0001253477,0.00013072467,0.0007368907,0.00042273564,0.00020035414,0.00012488014,0.00045224366,0.0000011507941],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017583102,0.0006158386,0.9514658,0.00009245154,0.0000034585205,0.00033147554,0.00080897013,0.000018184497,0.0072253835,0.00009846842,0.0005269166,0.03705473],"study_design_scores_gemma":[0.0032786434,0.0006216877,0.97760236,0.0020844592,0.000043533622,0.00018768046,0.0012249585,0.0065835635,0.00078860763,0.0059412597,0.001521403,0.00012182801],"about_ca_topic_score_codex":0.000038145663,"about_ca_topic_score_gemma":0.0000015419294,"teacher_disagreement_score":0.0369329,"about_ca_system_score_codex":0.00009917463,"about_ca_system_score_gemma":0.00029588147,"threshold_uncertainty_score":0.5111531},"labels":[],"label_agreement":null},{"id":"W2377901611","doi":"","title":"A diffusion tensor imaging study of white matter lesion in amnesic mild cognitive impairment","year":2010,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Fractional anisotropy; Audiology; Diffusion MRI; White matter; Psychology; Cognition; Verbal fluency test; Cognitive impairment; Neuropsychology; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.26431484410636186,"score_gpt":0.5768198277249041,"score_spread":0.3125049836185423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2377901611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99586546,0.0004169651,0.00046822385,0.0006080651,0.00009816728,0.0018007266,0.000019183137,0.00004234449,0.0006808521],"genre_scores_gemma":[0.99766177,0.0005858622,0.0008464613,0.00049439206,0.00006028338,0.0001471237,0.000008741126,0.00005220361,0.000143179],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979284,0.00010096442,0.00078654016,0.000442442,0.00046675355,0.0002749113],"domain_scores_gemma":[0.99830204,0.00015579381,0.0006154129,0.0004932918,0.00027216104,0.0001612916],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00050259306,0.0002510788,0.0006519822,0.0007699837,0.00016635841,0.00010712834,0.00071240315,0.000052569598,0.0018377029],"category_scores_gemma":[0.0000847071,0.00021007944,0.00011120805,0.0007166764,0.0001144063,0.0006293481,0.0008381514,0.0006274482,0.000006613494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002827128,0.0019142404,0.86571527,0.00005710604,0.000020965892,0.00004266723,0.00037951075,0.0000039438883,0.1259001,0.0000036135048,0.0025728645,0.0031069834],"study_design_scores_gemma":[0.001776122,0.000042979093,0.98346096,0.0006796312,0.00009956627,0.000037801252,0.00037774295,0.0001148878,0.012222206,0.0007209905,0.00026849934,0.00019862695],"about_ca_topic_score_codex":0.00039491706,"about_ca_topic_score_gemma":0.000042424927,"teacher_disagreement_score":0.11774566,"about_ca_system_score_codex":0.00004609789,"about_ca_system_score_gemma":0.000050035298,"threshold_uncertainty_score":0.99907476},"labels":[],"label_agreement":null},{"id":"W2386694087","doi":"","title":"The application of diffusion tensor imaging on 3.0T MR in amnestic mild cognitive impairment","year":2012,"lang":"en","type":"article","venue":"Journal of China Clinic Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Splenium; Medicine; Fractional anisotropy; Cognitive impairment; White matter; Montreal Cognitive Assessment; Parahippocampal gyrus; Cognition; Magnetic resonance imaging; Audiology; Nuclear medicine; Radiology; Temporal lobe; Psychiatry; Epilepsy","score_opus":0.04121147298681041,"score_gpt":0.4130964285146729,"score_spread":0.3718849555278625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2386694087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8937461,0.0018309415,0.06974169,0.03250971,0.0003426979,0.00078556244,0.000004026447,0.00004976252,0.0009895291],"genre_scores_gemma":[0.995442,0.0007944592,0.0016533843,0.0016179205,0.0004023438,0.000022852977,0.000003273487,0.00002453451,0.000039241186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976078,0.00010567349,0.0010694857,0.0001634527,0.00073423726,0.00031933526],"domain_scores_gemma":[0.9973649,0.0011442833,0.0007476689,0.00026104675,0.00017044898,0.0003116886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019199449,0.00015261828,0.0003901917,0.00016723412,0.000107722626,0.00001047103,0.0002158241,0.000043145174,0.000039733008],"category_scores_gemma":[0.0018913758,0.00009495428,0.00016738831,0.0002485455,0.00026713323,0.0001365267,0.00007363508,0.00087332405,0.000009272442],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005839841,0.00174607,0.7493031,0.00008892766,0.00003140164,0.000064573374,0.00040204462,0.0000030979397,0.0013807212,0.00048661078,0.0017968133,0.24411266],"study_design_scores_gemma":[0.003947958,0.00027964482,0.97132754,0.0023245427,0.00019364363,0.0008696236,0.00048443975,0.011102403,0.0012026198,0.003454438,0.0046209996,0.00019212012],"about_ca_topic_score_codex":0.000011856263,"about_ca_topic_score_gemma":6.288032e-7,"teacher_disagreement_score":0.24392053,"about_ca_system_score_codex":0.00008832425,"about_ca_system_score_gemma":0.00012866475,"threshold_uncertainty_score":0.3872123},"labels":[],"label_agreement":null},{"id":"W2388595031","doi":"","title":"Study of microstructural white matter lesions in patients with mild cognitive impairment and mild and moderate Alzheimer disease","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Splenium; Fractional anisotropy; Corpus callosum; White matter; Internal capsule; Diffusion MRI; Cognitive impairment; Internal medicine; Parietal lobe; Medicine; Psychology; Audiology; Cardiology; Pathology; Disease; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.03113333164979861,"score_gpt":0.32048516422925916,"score_spread":0.28935183257946057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2388595031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998249,0.00001499079,0.0000557672,0.0004544519,0.0000053848194,0.00112158,0.000029582709,0.000019110228,0.000050118277],"genre_scores_gemma":[0.99676114,0.000003532754,0.002711935,0.00039867603,0.0000042561746,0.000052696883,0.000014447736,0.000011716604,0.000041593903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995135,0.000008019705,0.00011584572,0.00019945294,0.0000719871,0.00009119454],"domain_scores_gemma":[0.9996718,0.0000142529,0.000034814107,0.00013193344,0.000055199213,0.00009195597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000016777147,0.00009115443,0.00012625227,0.00005014452,0.000039539216,0.000006959749,0.00001997864,0.0000146323655,0.00002290517],"category_scores_gemma":[0.0000024721721,0.00006175737,0.000008284671,0.00005665086,0.0000790968,0.00005003404,0.00004509978,0.00011793314,5.598022e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037062122,0.00039829087,0.99847555,0.0000072034277,0.000011935485,0.0000022853123,0.00021430044,4.849396e-7,0.00014510185,0.000010076521,0.00007391752,0.00029025],"study_design_scores_gemma":[0.00275371,0.00027967407,0.9959742,0.000034177745,0.00009824738,0.0000024604865,0.00014962649,0.000057423254,0.00049165805,0.00008266802,0.000004407409,0.00007178961],"about_ca_topic_score_codex":0.000023513136,"about_ca_topic_score_gemma":0.000023177123,"teacher_disagreement_score":0.0026561678,"about_ca_system_score_codex":0.0000025590914,"about_ca_system_score_gemma":0.000008493974,"threshold_uncertainty_score":0.25183925},"labels":[],"label_agreement":null},{"id":"W2389283394","doi":"","title":"Diffusion Tensor Imaging in Acute Ischemic Stroke: Usefulness of Fractional Anisotropy","year":2006,"lang":"en","type":"article","venue":"Journal of the Korean Neurological Association","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; Modified Rankin Scale; Cardiology; Stroke (engine); Internal medicine; Penumbra; Magnetic resonance imaging; Infarction; Ischemic stroke; Anesthesia; Ischemia; Radiology; Myocardial infarction","score_opus":0.02168075310410963,"score_gpt":0.2859440296971228,"score_spread":0.2642632765930132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2389283394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9837808,0.000017858276,0.0027261958,0.012930603,0.00007775375,0.00013372973,0.000011041514,0.000019165607,0.00030284794],"genre_scores_gemma":[0.9970135,0.000031803724,0.0019734828,0.000586071,0.00013991017,0.0000033773401,0.0000031422182,0.000008962764,0.00023975004],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988833,0.000072310926,0.00044215113,0.000108472275,0.00036204973,0.00013167958],"domain_scores_gemma":[0.998662,0.00016691294,0.0008422072,0.00012598239,0.00017440619,0.00002850485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023374188,0.00008393474,0.00022392825,0.000078643694,0.000051266114,0.000008291037,0.00013452057,0.000061976956,0.000012936121],"category_scores_gemma":[0.000266706,0.00005238089,0.0001646152,0.0001839391,0.00003740488,0.00009581764,0.000049249786,0.0004551337,8.162697e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013883396,0.0002774467,0.87172717,0.0000034217915,0.000008732519,0.000019426896,0.0000061285637,0.00011890702,0.1238704,0.00023489063,0.003025017,0.000569651],"study_design_scores_gemma":[0.00076294475,0.000119094,0.98363096,0.000022167273,0.000076564575,0.00016220419,0.0000043397936,0.00097447855,0.009418209,0.0029852858,0.0017973279,0.00004644085],"about_ca_topic_score_codex":0.000007740912,"about_ca_topic_score_gemma":9.3988336e-7,"teacher_disagreement_score":0.11445219,"about_ca_system_score_codex":0.00011531602,"about_ca_system_score_gemma":0.000026044228,"threshold_uncertainty_score":0.21360306},"labels":[],"label_agreement":null},{"id":"W2397498493","doi":"10.1111/jon.12359","title":"Neurite Orientation Dispersion and Density Imaging Color Maps to Characterize Brain Diffusion in Neurologic Disorders","year":2016,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"White matter; Diffusion MRI; Medicine; Diffusion imaging; Orientation (vector space); Multiple sclerosis; Pathology; Neurite; Artificial intelligence; Magnetic resonance imaging; Radiology; Computer science; Biology","score_opus":0.028421646163467092,"score_gpt":0.3131157431984131,"score_spread":0.284694097034946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397498493","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8985442,0.000030228684,0.009640527,0.09132382,0.00010870263,0.00027505765,0.0000036928707,0.00004173535,0.000032069704],"genre_scores_gemma":[0.9917566,0.0002669097,0.0024609866,0.0053660073,0.00007405244,0.0000056384542,0.0000016194524,0.00002553245,0.000042634616],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988229,0.00006838376,0.00039231963,0.00028539388,0.00020488842,0.00022607506],"domain_scores_gemma":[0.9991571,0.00017362407,0.00023278147,0.00018749559,0.00008282265,0.00016618986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022024536,0.00014630616,0.0002505941,0.00033260003,0.00007891632,0.000027790855,0.00010033693,0.000021058844,0.000005315429],"category_scores_gemma":[0.00035306782,0.00010393915,0.000065502165,0.00025651386,0.000068309775,0.00033792134,0.000110789115,0.00024854334,0.0000024904107],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002252772,0.0000844978,0.3005771,0.000013837319,0.0000014698579,0.00016056091,0.0000816613,0.0000019533657,0.6368159,0.0000567507,0.0002808391,0.06170017],"study_design_scores_gemma":[0.0014681041,0.00030011544,0.984518,0.00017443292,0.000024499928,0.0009763159,0.000027661243,0.00054216385,0.002234247,0.0009365767,0.008668442,0.00012942852],"about_ca_topic_score_codex":0.0000075553694,"about_ca_topic_score_gemma":0.0000024205315,"teacher_disagreement_score":0.6839409,"about_ca_system_score_codex":0.000050833634,"about_ca_system_score_gemma":0.000020959686,"threshold_uncertainty_score":0.42385155},"labels":[],"label_agreement":null},{"id":"W2399008936","doi":"10.1002/nbm.3549","title":"Differences in iron and manganese concentration may confound the measurement of myelin from <i>R</i><sub>1</sub> and <i>R</i><sub>2</sub> relaxation rates in studies of dysmyelination","year":2016,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre; University of Toronto; McMaster University; Sunnybrook Hospital; Sunnybrook Health Science Centre","funders":"Diamond Light Source","keywords":"White matter; Chemistry; Myelin; Manganese; Analytical Chemistry (journal); Nuclear magnetic resonance; Relaxation (psychology); Magnetic resonance imaging; Biology; Physics; Chromatography; Central nervous system","score_opus":0.07151617025963065,"score_gpt":0.3341724110686814,"score_spread":0.26265624080905076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399008936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98989564,0.0022463421,0.00047535816,0.0065442026,0.000039614963,0.0007398919,0.000016261589,0.000019178979,0.000023519642],"genre_scores_gemma":[0.99046844,0.009005563,0.00021807615,0.00015033034,0.000044089862,0.00008077096,0.000019522666,0.00001108039,0.0000021100564],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985311,0.00008026628,0.0006134083,0.00029132154,0.00033416174,0.00014975917],"domain_scores_gemma":[0.9989145,0.0003731229,0.0002908138,0.00020198053,0.00017565087,0.00004392803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060869934,0.00015230734,0.00039314202,0.00019322985,0.000029381688,0.0000041917715,0.00006329757,0.000071502356,0.0000015849347],"category_scores_gemma":[0.00043339198,0.00009136164,0.00001744223,0.00036112062,0.00051630125,0.00010241734,0.000040380954,0.00012533514,4.1870857e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015062747,0.000090626214,0.08271244,0.00010559342,0.000010703206,0.0000035098385,0.00081859564,9.1359135e-7,0.88832295,0.00022779623,0.000043951106,0.02751231],"study_design_scores_gemma":[0.002459231,0.00024473437,0.4364516,0.001283934,0.000037893005,0.000004068386,0.000641724,0.0002336618,0.55584466,0.0026589783,0.000049343682,0.00009014454],"about_ca_topic_score_codex":0.00010217463,"about_ca_topic_score_gemma":0.0002605439,"teacher_disagreement_score":0.35373917,"about_ca_system_score_codex":0.00011078705,"about_ca_system_score_gemma":0.000042362983,"threshold_uncertainty_score":0.37256193},"labels":[],"label_agreement":null},{"id":"W2399294503","doi":"10.1007/978-3-319-19992-4_63","title":"Functional Nonlinear Mixed Effects Models for Longitudinal Image Data","year":2015,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Center for Research Resources; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Covariance operator; Computer science; Nonlinear system; Covariance; Functional data analysis; Artificial intelligence; Random effects model; Covariate; Algorithm; Machine learning; Data mining; Statistics; Mathematics","score_opus":0.1640109882639426,"score_gpt":0.38354205146568476,"score_spread":0.21953106320174218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399294503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006965359,0.000052383693,0.99010944,0.0020321272,0.00024553962,0.00045517427,0.000013212707,0.000114181,0.000012560198],"genre_scores_gemma":[0.3844934,0.0000016561585,0.6147105,0.0005355299,0.00019781372,0.000020978485,0.000031745403,0.000007008501,0.0000013554873],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998788,0.0000092668,0.00012781726,0.0005800319,0.00026135042,0.00023351065],"domain_scores_gemma":[0.9986854,0.00021082732,0.000038580663,0.0007688206,0.00017721594,0.00011915431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003441288,0.000105032625,0.00014304835,0.00011031142,0.000085302265,0.00004308373,0.00042629705,0.000030919196,9.313554e-7],"category_scores_gemma":[0.0002670164,0.000087155706,0.000023264998,0.00049400533,0.00022888587,0.00032657385,0.00033368418,0.00014981651,0.0000036525514],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038140436,0.00082393613,0.0077885343,0.0002923879,0.00002416895,0.000110387846,0.00041007152,0.18287332,0.0345249,0.0035251565,0.0060214982,0.76322424],"study_design_scores_gemma":[0.00056395953,0.00014241668,0.0013927935,0.000039476785,0.000009438396,0.00007070957,1.8718428e-7,0.94981813,0.013882409,0.033675093,0.00031139684,0.00009399661],"about_ca_topic_score_codex":0.0000065854033,"about_ca_topic_score_gemma":0.0000031664674,"teacher_disagreement_score":0.7669448,"about_ca_system_score_codex":0.0000587685,"about_ca_system_score_gemma":0.00016695532,"threshold_uncertainty_score":0.35541067},"labels":[],"label_agreement":null},{"id":"W2404527239","doi":"10.3389/fnins.2016.00247","title":"Microstructure Informed Tractography: Pitfalls and Open Challenges","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Diffusion MRI; Data science; Artificial intelligence; Medicine; Magnetic resonance imaging","score_opus":0.07275986416428372,"score_gpt":0.3553850544133283,"score_spread":0.2826251902490446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404527239","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7598005,0.0043487786,0.13652688,0.07912044,0.0016545567,0.0045898184,0.00008915017,0.0006615846,0.013208276],"genre_scores_gemma":[0.9302122,0.00845506,0.058878068,0.0020436947,0.000018982168,0.00005342913,6.4298837e-7,0.000014505758,0.0003234139],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992218,0.00001024587,0.00012541862,0.0003482349,0.000097938195,0.00019635909],"domain_scores_gemma":[0.99954504,0.000025079818,0.000047007976,0.00027630478,0.000015932601,0.000090621346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006959233,0.00009236106,0.00015179199,0.00012553742,0.00005926177,0.000028193843,0.00029465763,0.000033467375,0.000001990398],"category_scores_gemma":[0.00011305849,0.00006112899,0.000019597848,0.00022913971,0.0003049343,0.00029256177,0.00014285032,0.00009892432,4.6022896e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016602356,0.00017540764,0.47404265,0.00008580852,0.000003535336,0.00006872975,0.00037867358,0.0000013686134,0.22120357,0.008534312,0.011785183,0.28355473],"study_design_scores_gemma":[0.00084910775,0.00015973717,0.78502345,0.00011318202,0.0000061922156,0.0001130405,0.000047204816,0.000055084358,0.003745961,0.0090400465,0.20068781,0.00015915588],"about_ca_topic_score_codex":0.0000028888176,"about_ca_topic_score_gemma":0.0000020580344,"teacher_disagreement_score":0.3109808,"about_ca_system_score_codex":0.00001871747,"about_ca_system_score_gemma":0.000039258142,"threshold_uncertainty_score":0.24927679},"labels":[],"label_agreement":null},{"id":"W2406164791","doi":"10.1503/jpn.150030","title":"Frontal fasciculi and psychotic symptoms in antipsychotic-naive patients with schizophrenia before and after 6 weeks of selective dopamine D2/3 receptor blockade","year":2016,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Lundbeckfonden","keywords":"Dopamine receptor D2; Schizophrenia (object-oriented programming); Dopamine; Antipsychotic; Blockade; Psychology; Psychosis; Medicine; Psychiatry; Neuroscience; Receptor; Internal medicine","score_opus":0.00842308945023912,"score_gpt":0.26742311113302825,"score_spread":0.2590000216827891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406164791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960279,0.00019085914,0.0011318845,0.0022274142,0.0001603319,0.00022408037,0.000013934957,0.000008516913,0.000015064028],"genre_scores_gemma":[0.991812,0.00031520773,0.007577139,0.00020393582,0.000052101586,0.0000044645803,2.2352113e-7,0.000011007581,0.000023927956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990426,0.000023886501,0.00030184296,0.0002737476,0.0002003993,0.00015757866],"domain_scores_gemma":[0.99935377,0.000029985074,0.00025552468,0.00012922217,0.000088473214,0.00014305433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009195243,0.00013306411,0.00024509223,0.00016614966,0.000054561682,0.000012381673,0.00007789297,0.000036493533,0.0000026671364],"category_scores_gemma":[0.000034214503,0.00007804505,0.000028040653,0.00025289602,0.000368042,0.00023653088,0.000026554404,0.00019285515,1.4728035e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001428002,0.00028362052,0.9808819,0.000031386353,0.0000052494547,0.000005453449,0.0000538094,2.9739522e-7,0.013420624,0.00010542215,0.000048084374,0.003736125],"study_design_scores_gemma":[0.0030996157,0.0026232738,0.99154747,0.0004717463,0.000035607532,0.00025645323,0.000015634649,0.00001579288,0.0009564569,0.000764163,0.00012415698,0.00008960891],"about_ca_topic_score_codex":0.0000010925048,"about_ca_topic_score_gemma":0.000007665834,"teacher_disagreement_score":0.012464167,"about_ca_system_score_codex":0.000011120982,"about_ca_system_score_gemma":0.00004529244,"threshold_uncertainty_score":0.31825846},"labels":[],"label_agreement":null},{"id":"W2410277926","doi":"10.1017/cjn.2015.398","title":"Nε-(carboxymethyl)-lysine, White Matter, and Cognitive Function in Diabetes Patients","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Montreal Cognitive Assessment; Fractional anisotropy; Internal medicine; White matter; Fasciculus; Corpus callosum; Medicine; Cognition; Psychology; Cognitive impairment; Cardiology; Psychiatry; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.038058508760774545,"score_gpt":0.29062967376360704,"score_spread":0.2525711650028325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2410277926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894613,0.0004295299,0.00015504844,0.008540172,0.00020493347,0.00019585702,0.000012251259,0.000016748558,0.0009841361],"genre_scores_gemma":[0.9936454,0.00023277997,0.0014007358,0.004578335,0.00009604309,0.000005492933,2.966431e-7,0.000010811662,0.000030047788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973397,0.00032742386,0.0006139245,0.00046293304,0.00041204292,0.0008439716],"domain_scores_gemma":[0.997545,0.00046009474,0.00044477877,0.00009681143,0.00037468845,0.0010785968],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0013827374,0.00023263987,0.0003922663,0.0009030117,0.0008040382,0.00018161639,0.00048549977,0.000110794856,0.00010431467],"category_scores_gemma":[0.0012842567,0.00013432468,0.0001084012,0.0009532215,0.0040147332,0.00074265717,0.000051593295,0.00055611576,0.0000026845714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060528877,0.000031402848,0.99130946,0.0000042197244,0.0000053644976,0.00033968984,0.00004034977,0.000017189554,0.00007447619,0.00016098806,0.00024885565,0.0077074654],"study_design_scores_gemma":[0.0005467227,0.023332406,0.96354634,0.00010615246,0.000047519014,0.0018272789,0.000035234974,0.000114312854,0.0000839982,0.009470966,0.00072545395,0.0001636354],"about_ca_topic_score_codex":0.00011299995,"about_ca_topic_score_gemma":0.004481061,"teacher_disagreement_score":0.027763149,"about_ca_system_score_codex":0.00010520684,"about_ca_system_score_gemma":0.00070400443,"threshold_uncertainty_score":0.9986958},"labels":[],"label_agreement":null},{"id":"W2410342480","doi":"10.1007/s00406-016-0702-9","title":"The 5-HTTLPR and BDNF polymorphisms moderate the association between uncinate fasciculus connectivity and antidepressants treatment response in major depression","year":2016,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McMaster University","funders":"Mathison Centre for Mental Health Research and Education","keywords":"Uncinate fasciculus; Fractional anisotropy; 5-HTTLPR; Citalopram; Psychology; Internal medicine; Superior longitudinal fasciculus; Serotonin transporter; White matter; Sertraline; Antidepressant; Medicine; Fasciculus; Oncology; Psychiatry; Magnetic resonance imaging; Hippocampus; Serotonin","score_opus":0.05212781065193478,"score_gpt":0.36329858358076667,"score_spread":0.3111707729288319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2410342480","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834864,0.00022877307,0.001860307,0.013715221,0.00007550752,0.00029486284,0.000019715028,0.000027964414,0.0002912593],"genre_scores_gemma":[0.99619126,0.0025967457,0.0005830329,0.00030606188,0.00004418649,0.0000056502477,2.946637e-7,0.000010416225,0.00026234344],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99825186,0.0007096763,0.00032901246,0.00041134167,0.000121756486,0.00017635572],"domain_scores_gemma":[0.9970165,0.002374745,0.00019575482,0.00030111385,0.000010887474,0.00010099886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093535,0.00011092735,0.00018367526,0.00003458823,0.00031257008,0.000028300334,0.00012998091,0.0000188735,3.0012197e-7],"category_scores_gemma":[0.00068718527,0.000051432373,0.00004495447,0.00008707331,0.0006627508,0.00007530837,0.00016044517,0.00015529766,4.3974617e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006984869,0.00010414432,0.9332413,0.000004483553,0.0000051654647,0.0000042328597,0.000039612347,6.3299655e-7,0.013465613,0.0004205869,0.000013459205,0.052002247],"study_design_scores_gemma":[0.0011078345,0.00053184706,0.9941289,0.00008828729,0.000030622938,0.000014242485,0.000011622219,0.00030634887,0.00063709915,0.002508309,0.0005725192,0.00006238703],"about_ca_topic_score_codex":0.0000056763265,"about_ca_topic_score_gemma":0.0000059170093,"teacher_disagreement_score":0.06088755,"about_ca_system_score_codex":0.0000064594237,"about_ca_system_score_gemma":0.000029648303,"threshold_uncertainty_score":0.24419329},"labels":[],"label_agreement":null},{"id":"W2411482138","doi":"10.1016/j.bandl.2016.05.008","title":"Treatment of dysphasia with rTMS and language therapy after childhood stroke: Multimodal imaging of plastic change","year":2016,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Alberta Children's Hospital","funders":"Alberta Children's Hospital Foundation; Health Research Board; Heart and Stroke Foundation of Canada","keywords":"Aphasia; Psychology; Stroke (engine); Neuroimaging; Inferior frontal gyrus; Neuroplasticity; White matter; Neuroscience; Audiology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.018115668307559663,"score_gpt":0.3040748849272598,"score_spread":0.28595921661970014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2411482138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994654,0.0028463742,0.0009606699,0.0009271089,0.000005139696,0.00036282337,0.0000835034,0.000042761,0.000117597265],"genre_scores_gemma":[0.99688286,0.00033161932,0.002293821,0.00017638782,0.000041143754,0.000071850685,0.00000575165,0.000016387718,0.0001801557],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99957883,0.000009670677,0.00009145835,0.00015419476,0.0000640319,0.00010180523],"domain_scores_gemma":[0.9996358,0.00008412331,0.000049570255,0.00016637584,0.000013061553,0.000051056213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000019664336,0.00009839219,0.00016637864,0.00004958049,0.000015243632,0.000002854416,0.000021915339,0.000017446591,0.000028978584],"category_scores_gemma":[0.000012260803,0.000053291227,0.000026595113,0.00004014558,0.000099576544,0.000038814505,0.000011694877,0.000024596291,3.651595e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004989999,0.00051620376,0.14679034,0.00007151484,0.000072565,0.00012515397,0.010592253,4.672839e-8,0.27353093,0.00017107543,0.00003056535,0.5676003],"study_design_scores_gemma":[0.007251907,0.0013363883,0.9208491,0.0002769629,0.000071920236,0.0001749499,0.001057475,0.00006257442,0.06760223,0.000025123036,0.001108621,0.00018273959],"about_ca_topic_score_codex":0.000058090634,"about_ca_topic_score_gemma":0.0000056397107,"teacher_disagreement_score":0.77405876,"about_ca_system_score_codex":0.00000782737,"about_ca_system_score_gemma":0.000008095867,"threshold_uncertainty_score":0.21731532},"labels":[],"label_agreement":null},{"id":"W2413345301","doi":"","title":"Pulse: The brain drain: a statistical snapshot","year":2000,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Snapshot (computer storage); Brain drain; Computer science; Data science; Operating system","score_opus":0.021846170528829558,"score_gpt":0.32110566153287556,"score_spread":0.29925949100404603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2413345301","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025127754,0.00012557422,0.0037833685,0.9143636,0.00017303618,0.00035200667,0.00007193029,0.0000732798,0.055929404],"genre_scores_gemma":[0.7184522,0.00036658606,0.0040934533,0.26408073,0.0028999767,0.000053946977,0.00010072425,0.00004919264,0.009903193],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99831796,0.000093011935,0.00028409064,0.00013391789,0.00079161767,0.00037939515],"domain_scores_gemma":[0.99816215,0.00030137794,0.00006708693,0.00015371214,0.00013290913,0.0011827494],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008342761,0.000088382236,0.00014513885,0.00005774583,0.00036095214,0.00005748628,0.00016920465,0.00014249812,0.045653068],"category_scores_gemma":[0.0013393986,0.000062687526,0.000065324726,0.00020918706,0.00007592131,0.0000503888,0.0000066941843,0.0010532661,0.00018412805],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000875941,0.00002771133,0.0037129568,0.000002624361,0.000027642249,0.00033814652,0.00007492732,0.000001615145,0.000017841157,0.0030355998,0.77353156,0.2192206],"study_design_scores_gemma":[0.00039489745,0.00004292183,0.023334362,0.000023902414,0.000019651216,0.0014321436,0.00003348579,0.00042723058,0.000006095611,0.0022478052,0.9719683,0.00006919712],"about_ca_topic_score_codex":0.00048435616,"about_ca_topic_score_gemma":0.0012350322,"teacher_disagreement_score":0.69332445,"about_ca_system_score_codex":0.00041477996,"about_ca_system_score_gemma":0.0012264526,"threshold_uncertainty_score":0.9552193},"labels":[],"label_agreement":null},{"id":"W2415288600","doi":"10.1016/j.schres.2016.05.025","title":"Corrigendum to “abnormal white matter integrity in antipsychotic-naïve first-episode psychosis patients assessed by a DTI principal component analysis” [Schizophr. Res. 162 (1–3) (march 2015) 14–21]","year":2016,"lang":"en","type":"erratum","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychosis; White matter; Antipsychotic; Schizophrenia (object-oriented programming); Psychology; Psychiatry; Principal component analysis; Medicine; Magnetic resonance imaging; Computer science; Radiology","score_opus":0.09695297960127922,"score_gpt":0.4141474399166557,"score_spread":0.31719446031537646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2415288600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52065617,0.005047603,0.03152829,0.25386292,0.03926206,0.053633172,0.020692851,0.0034581914,0.07185871],"genre_scores_gemma":[0.53550303,0.00391958,0.03835192,0.003504707,0.0041040857,0.008337106,0.013833092,0.0013475772,0.39109895],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9883755,0.0008341102,0.0018106088,0.0030083198,0.0034495615,0.0025218902],"domain_scores_gemma":[0.9924411,0.00035244055,0.0004973775,0.0037463086,0.001660939,0.0013018152],"candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0021878334,0.0011764488,0.0021215235,0.0041016517,0.00062167196,0.0002772849,0.0020956306,0.0011692987,0.0012180426],"category_scores_gemma":[0.0005376393,0.0010015763,0.0006994665,0.0052720592,0.0005698637,0.00030750994,0.0012257725,0.008529237,0.0011891513],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037882267,0.0014080517,0.22720547,0.00026637135,0.00028624304,0.00004502119,0.000055450033,0.0000021891608,0.00012347988,0.000065412205,0.7656976,0.0010564909],"study_design_scores_gemma":[0.003861843,0.00061811705,0.4691647,0.0013110618,0.00028636202,0.000014457182,0.000017796165,0.00035830322,0.00013226322,0.0004972335,0.52274877,0.0009890845],"about_ca_topic_score_codex":0.0011911909,"about_ca_topic_score_gemma":0.0023086115,"teacher_disagreement_score":0.3192402,"about_ca_system_score_codex":0.001217269,"about_ca_system_score_gemma":0.00046541772,"threshold_uncertainty_score":0.999695},"labels":[],"label_agreement":null},{"id":"W241994552","doi":"10.1016/j.neuroimage.2015.05.016","title":"Robust and efficient linear registration of white-matter fascicles in the space of streamlines","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":93,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Max-Planck-Institut für Kognitions- und Neurowissenschaften","keywords":"Streamlines, streaklines, and pathlines; Artificial intelligence; Computer science; Diffusion MRI; Tractography; Jaccard index; Arcuate fasciculus; White matter; Computer vision; Pattern recognition (psychology); Physics","score_opus":0.11651302412537339,"score_gpt":0.34401294845725133,"score_spread":0.22749992433187793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W241994552","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98784626,0.000046795714,0.003373564,0.0064783506,0.000013045272,0.00028171472,0.000008413934,0.000021208105,0.0019306814],"genre_scores_gemma":[0.99137855,0.000019330562,0.008206885,0.00026124495,0.00002222328,0.0000083719,0.000004759614,0.000008294798,0.00009034763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994491,0.00002729432,0.00017872982,0.00013555455,0.00014072684,0.000068628004],"domain_scores_gemma":[0.9994787,0.000049576007,0.00009184561,0.00028300667,0.00006905912,0.000027823107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001422791,0.000061108905,0.00011821386,0.000051591724,0.00001792988,0.0000033899553,0.00006400822,0.000018171768,0.0000028554643],"category_scores_gemma":[0.00008723344,0.000042799857,0.000020506748,0.00016783943,0.00010612819,0.00003699901,0.00003392717,0.00009094363,0.0000010091791],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004586904,0.0018930678,0.7158035,0.0006097618,0.000013219466,0.00009612478,0.004172513,0.0083842045,0.23988493,0.007193899,0.018476915,0.0030131573],"study_design_scores_gemma":[0.0024277165,0.0008032253,0.8917023,0.00023007265,0.000095392585,0.00023607141,0.0009760061,0.026577204,0.06634491,0.0010009577,0.009356191,0.00024997626],"about_ca_topic_score_codex":0.000019963087,"about_ca_topic_score_gemma":0.000003052067,"teacher_disagreement_score":0.17589875,"about_ca_system_score_codex":0.0000045623988,"about_ca_system_score_gemma":0.000017490203,"threshold_uncertainty_score":0.17453276},"labels":[],"label_agreement":null},{"id":"W2423712451","doi":"10.18632/oncotarget.10091","title":"White matter degeneration in subjective cognitive decline: a diffusion tensor imaging study","year":2016,"lang":"en","type":"article","venue":"Oncotarget","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Medicine; Beijing; Cognitive decline; Neurology; Montreal Cognitive Assessment; China; Cognitive impairment; Disease; Internal medicine; Dementia; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.030354010026129082,"score_gpt":0.34816708322534795,"score_spread":0.31781307319921887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2423712451","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9719994,0.00002472956,0.02002228,0.005689012,0.000031135893,0.00088636763,0.000014616144,0.00010849988,0.0012239576],"genre_scores_gemma":[0.9932662,0.00001842609,0.003845546,0.001522657,0.00008811448,0.0002148659,0.00001482167,0.000028586874,0.0010007838],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990855,0.000042731743,0.00021038414,0.00033674028,0.00014237824,0.00018228487],"domain_scores_gemma":[0.9994906,0.00007236449,0.00006495616,0.00020391295,0.000108544795,0.00005958407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010997863,0.00012595668,0.00017532804,0.00011846049,0.000058351336,0.00001100979,0.000053090385,0.000025067719,0.00014306932],"category_scores_gemma":[0.000063090694,0.00008582179,0.00003768542,0.0001808134,0.00004028989,0.00011560415,0.000069061745,0.00010920064,0.00010239961],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096573414,0.00041726473,0.9866538,0.00000368384,0.000003320559,0.000031031454,0.00017244022,3.8154607e-7,0.010807978,0.000018333416,0.00047141503,0.001323767],"study_design_scores_gemma":[0.0018140529,0.000121140634,0.994343,0.00009887738,0.00002530861,0.000023359995,0.00016816042,0.00010493006,0.0019337812,0.0005027882,0.0007490171,0.000115572766],"about_ca_topic_score_codex":0.000021105452,"about_ca_topic_score_gemma":0.000028067234,"teacher_disagreement_score":0.021266798,"about_ca_system_score_codex":0.00008494146,"about_ca_system_score_gemma":0.0000267924,"threshold_uncertainty_score":0.34997112},"labels":[],"label_agreement":null},{"id":"W2423914761","doi":"10.1002/ana.24111","title":"Reply","year":2014,"lang":"en","type":"letter","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Annals; Biostatistics; Citation; Medicine; Library science; Psychology; Humanities; Classics; Art; Computer science; Public health; Pathology","score_opus":0.2168970704524688,"score_gpt":0.4189773543611998,"score_spread":0.202080283908731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2423914761","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0005052427,0.00007686866,0.00061435776,0.99305326,0.000060432296,0.00022546035,0.0000116230485,0.00014682725,0.0053059063],"genre_scores_gemma":[0.0021605103,0.00024286557,0.00067820423,0.99453264,0.0011131124,0.000034779805,0.000088606495,0.0000505017,0.0010987566],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989463,0.0000489533,0.00027523245,0.00036896422,0.00012474647,0.00023581299],"domain_scores_gemma":[0.99865246,0.00014264752,0.00022210352,0.00081746455,0.00012977993,0.000035571564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006526145,0.0001543663,0.0004364823,0.00012751309,0.000019884426,0.0000021083351,0.00016782238,0.00030589395,0.000043687705],"category_scores_gemma":[0.000092646704,0.00014311497,0.00015276023,0.00008341977,0.0001465635,0.000012599885,0.000053963213,0.0012144378,0.00003487479],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026018459,0.000018058596,0.00011903955,0.000075496515,0.000011686662,0.00023602757,0.0000017792272,3.562134e-7,0.00021470293,0.00024367568,0.99825984,0.00079333613],"study_design_scores_gemma":[0.0000885739,0.00061268115,0.00041251304,0.0000176621,0.000029084866,0.0004611892,4.945528e-8,0.0000138802225,0.0010304858,0.004153037,0.993099,0.000081896294],"about_ca_topic_score_codex":0.000009229781,"about_ca_topic_score_gemma":5.9509226e-8,"teacher_disagreement_score":0.0051608756,"about_ca_system_score_codex":0.000001052898,"about_ca_system_score_gemma":0.000024480469,"threshold_uncertainty_score":0.58360595},"labels":[],"label_agreement":null},{"id":"W2428473372","doi":"10.1371/journal.pone.0157218","title":"Progression of Microstructural Degeneration in Progressive Supranuclear Palsy and Corticobasal Syndrome: A Longitudinal Diffusion Tensor Imaging Study","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; Tau Consortium; National Institute on Aging; National Institutes of Health; U.S. Department of Veterans Affairs","keywords":"Progressive supranuclear palsy; Fractional anisotropy; Diffusion MRI; Corticobasal degeneration; Medicine; Tauopathy; Pathology; White matter; Magnetic resonance imaging; Radiology; Neurodegeneration; Disease","score_opus":0.06790541763405622,"score_gpt":0.3297950096081705,"score_spread":0.26188959197411427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2428473372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99729675,0.00014750767,0.00016151858,0.0010291659,0.0000062960326,0.0012685026,0.0000080639065,0.000075035605,0.0000071717786],"genre_scores_gemma":[0.9856222,0.00004810094,0.014123748,0.000029297733,0.000019003288,0.00010968591,0.000005589958,0.000020741134,0.000021625616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990391,0.00003021406,0.00026302252,0.00028527473,0.00022788727,0.00015449291],"domain_scores_gemma":[0.9994572,0.00003490384,0.00012675358,0.00021555192,0.00010672187,0.00005889387],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070973816,0.00011223068,0.00026139742,0.00009497942,0.00005436339,0.000009970412,0.00004798744,0.000025286594,0.000015700472],"category_scores_gemma":[0.000080161946,0.00007316895,0.00002017006,0.00012957293,0.000112480615,0.00010064185,0.00007424397,0.00009151861,0.0000014553993],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092097165,0.0012032025,0.5976717,0.000042388634,0.000007401045,0.00004727984,0.000058131267,2.9231446e-8,0.3971155,0.000016107473,0.0000035573773,0.0037426413],"study_design_scores_gemma":[0.0016712853,0.00073132536,0.92539436,0.0009213964,0.000099819794,0.00012927363,0.000050111394,0.0002142886,0.070547126,0.00014094956,0.0000029211562,0.00009712683],"about_ca_topic_score_codex":0.000005874805,"about_ca_topic_score_gemma":0.0000024371361,"teacher_disagreement_score":0.3277227,"about_ca_system_score_codex":0.00003157788,"about_ca_system_score_gemma":0.000015749381,"threshold_uncertainty_score":0.29837433},"labels":[],"label_agreement":null},{"id":"W2429763096","doi":"10.1097/wnr.0000000000000488","title":"A study of brain white matter plasticity in early blinds using tract-based spatial statistics and tract statistical analysis","year":2015,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"White matter; Diffusion MRI; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11209336524505895,"score_gpt":0.3995146119130394,"score_spread":0.2874212466679804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2429763096","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74849236,9.60461e-7,0.25087845,0.00012482921,0.000011082585,0.00032829595,0.00007370886,0.000027029313,0.000063272455],"genre_scores_gemma":[0.97272176,3.176641e-7,0.026940595,0.0002305568,0.000017250115,0.000018284516,0.000030127201,0.00002165603,0.000019441075],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99860215,0.00005575264,0.0005219443,0.0003428125,0.00031781994,0.00015951769],"domain_scores_gemma":[0.99907327,0.00019050745,0.00021152248,0.00026405015,0.000107615,0.00015306404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014820557,0.00013365044,0.00039447003,0.00027700386,0.00002373996,0.000013807725,0.000046951645,0.00003831581,0.000019368115],"category_scores_gemma":[0.00025673382,0.00012653426,0.000030518077,0.00042460067,0.0000790495,0.00004925755,0.00002771339,0.00023077273,8.418745e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009891251,0.0012020747,0.99627113,0.00001598356,0.00001962313,0.0008089993,0.00020337779,0.00063597644,0.0003689385,0.00001618256,0.0001477172,0.00021109497],"study_design_scores_gemma":[0.0010858758,0.00067176356,0.9762957,0.000009081827,0.0004192316,0.000102446495,0.000049265698,0.020981925,0.00014851839,0.00010494707,0.000036810492,0.000094424],"about_ca_topic_score_codex":0.00055135123,"about_ca_topic_score_gemma":0.00007445959,"teacher_disagreement_score":0.2242294,"about_ca_system_score_codex":0.000027807337,"about_ca_system_score_gemma":0.00010864381,"threshold_uncertainty_score":0.51599175},"labels":[],"label_agreement":null},{"id":"W2438513049","doi":"10.1109/isbi.2016.7493414","title":"A sparse coding approach for the efficient representation and segmentation of white matter fibers","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Embedding; Computer science; Neural coding; Segmentation; Artificial intelligence; Pattern recognition (psychology); Sparse approximation; Pairwise comparison; Centroid; Representation (politics); Fiber bundle; Coding (social sciences); Fiber; Mathematics","score_opus":0.08784135663455689,"score_gpt":0.36222850187348543,"score_spread":0.27438714523892854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2438513049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048570845,0.000009171535,0.9455219,0.004148927,0.0000073613023,0.00066676486,0.000004846573,0.000028597724,0.0010416012],"genre_scores_gemma":[0.87814116,0.0000170194,0.12038556,0.00029043562,0.0000131259385,0.00014160798,0.0000050643057,0.000006501525,0.0009995318],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996867,0.0000048013812,0.000091866335,0.00011222464,0.00005260935,0.00005178609],"domain_scores_gemma":[0.99968463,0.000085503176,0.000044715045,0.00013863157,0.00003083388,0.000015706115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057667497,0.000035437268,0.000054480268,0.000021738704,0.000055207183,0.0000028008778,0.0000214247,0.000009856245,0.000018902441],"category_scores_gemma":[0.000012023534,0.000017607876,0.000020785725,0.000048442016,0.00004529114,0.00002118918,0.000019391848,0.000014886231,7.770819e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036367608,0.00029111333,0.17234899,0.00026711173,0.00006421438,7.008265e-7,0.0013459182,0.0005403399,0.7418979,0.013530732,0.017283749,0.052065592],"study_design_scores_gemma":[0.005578003,0.00033660713,0.23174906,0.00021371729,0.00040480238,0.0001307588,0.0018377269,0.09642717,0.6563743,0.0023748882,0.0042302683,0.0003427182],"about_ca_topic_score_codex":0.0000028053844,"about_ca_topic_score_gemma":7.720863e-8,"teacher_disagreement_score":0.8295703,"about_ca_system_score_codex":0.000008974975,"about_ca_system_score_gemma":0.0000035037945,"threshold_uncertainty_score":0.07180283},"labels":[],"label_agreement":null},{"id":"W2444358503","doi":"10.1017/s0954579416000444","title":"Anxious/depressed symptoms are related to microstructural maturation of white matter in typically developing youths","year":2016,"lang":"en","type":"article","venue":"Development and Psychopathology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Psychology; Typically developing; White matter; Depression (economics); Developing country; Clinical psychology; Developmental psychology; Anxiety; White (mutation); Psychiatry; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.024052250900980475,"score_gpt":0.31504260550905033,"score_spread":0.2909903546080699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2444358503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849806,0.000028530694,0.007365081,0.0069420645,0.000065646316,0.00029806414,0.0000035082796,0.00004585936,0.00027065675],"genre_scores_gemma":[0.9401182,0.000019767824,0.058065988,0.0012227279,0.000008674284,0.0000414407,0.000011303294,0.000013225796,0.0004986923],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920356,0.000018059549,0.000305688,0.00026260904,0.000056437442,0.00015364146],"domain_scores_gemma":[0.99964195,0.000019122868,0.00008564194,0.0001520489,0.000055603963,0.000045625573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006967011,0.00010368865,0.00019048825,0.00014373506,0.000042942145,0.000003841545,0.000056290028,0.0000738775,0.000028322018],"category_scores_gemma":[0.000017356318,0.00007399334,0.000014739632,0.00016087768,0.00004711083,0.000041540992,0.00004989433,0.000073308234,0.000017928762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019609583,0.000020726795,0.9016157,0.0000259743,0.0000059810754,0.000014975361,0.0010917126,2.74043e-7,0.074312136,0.0004219404,0.0003015655,0.021992924],"study_design_scores_gemma":[0.00068611314,0.000029637325,0.9857838,0.00019556851,0.0000047875346,0.00013321992,0.000025376368,0.00000141823,0.00794887,0.00088731805,0.004191329,0.00011254877],"about_ca_topic_score_codex":5.810734e-7,"about_ca_topic_score_gemma":0.0000033667693,"teacher_disagreement_score":0.08416812,"about_ca_system_score_codex":0.000027433045,"about_ca_system_score_gemma":0.000024395473,"threshold_uncertainty_score":0.3017361},"labels":[],"label_agreement":null},{"id":"W2460472596","doi":"10.1016/b978-0-12-396460-1.00014-7","title":"Individual Differences in White Matter Microstructure in the Healthy Brain","year":2014,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Neuroscience; Human brain; Psychology; Cognition; Neuroimaging; Relevance (law); Medicine; Magnetic resonance imaging; Political science","score_opus":0.043391977386875495,"score_gpt":0.31279904332294567,"score_spread":0.26940706593607017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460472596","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027810258,0.00038811463,0.000056894718,0.019214818,0.00009242887,0.0018383036,0.00007584612,0.00007783551,0.9754747],"genre_scores_gemma":[0.046393618,0.000081875885,0.0019030401,0.051020227,0.00041380076,0.00023711842,0.00011492348,0.00010952661,0.89972585],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985574,0.00004594066,0.0004282392,0.0004411077,0.00025344422,0.00027389088],"domain_scores_gemma":[0.9989771,0.00011128609,0.0001765083,0.00065039453,0.00002408187,0.00006060818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023933573,0.0003193425,0.00051075785,0.00021084942,0.000054771102,0.000029939289,0.00034443283,0.00023553439,0.00012039534],"category_scores_gemma":[0.000011262755,0.00021935851,0.000101967096,0.00002869183,0.00015891221,0.000013414554,0.000090093126,0.0011313884,0.000044876324],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000822034,0.00003527192,0.035686813,0.00034594783,0.000026394866,0.000065707405,0.0016862823,2.1876544e-7,0.00006328998,0.009511083,0.01045272,0.9420441],"study_design_scores_gemma":[0.0004409668,0.000096923,0.059927404,0.00051591796,0.00003540349,0.00011662741,0.0000140265265,0.0000019718416,0.000004478933,0.022252252,0.9163533,0.00024072471],"about_ca_topic_score_codex":0.0000011953016,"about_ca_topic_score_gemma":0.000045727218,"teacher_disagreement_score":0.94180334,"about_ca_system_score_codex":0.000046729274,"about_ca_system_score_gemma":0.000058629048,"threshold_uncertainty_score":0.8945181},"labels":[],"label_agreement":null},{"id":"W2460496408","doi":"10.18632/oncotarget.10601","title":"Abnormal organization of white matter networks in patients with subjective cognitive decline and mild cognitive impairment","year":2016,"lang":"en","type":"article","venue":"Oncotarget","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Diffusion MRI; Medicine; Beijing; Montreal Cognitive Assessment; White matter; Cognitive impairment; Dementia; China; Cognition; Neurology; Disease; Internal medicine; Psychiatry; Magnetic resonance imaging; Political science; Radiology","score_opus":0.010186497445157245,"score_gpt":0.27076311483646104,"score_spread":0.2605766173913038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460496408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96407056,0.0000124380185,0.03446002,0.00052666693,0.000008901913,0.0006468833,0.000049555973,0.000029473626,0.00019548353],"genre_scores_gemma":[0.9973709,0.00003064056,0.0017728903,0.0005888051,0.000020727051,0.00003162905,0.0000824522,0.000023609933,0.00007832639],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999376,0.00001887287,0.00016296594,0.00020148586,0.00010533626,0.00013531302],"domain_scores_gemma":[0.999412,0.000071192924,0.00009848876,0.000081302016,0.0002839536,0.000053041167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046897734,0.00010356946,0.00016919133,0.000064912834,0.000038512415,0.000002762186,0.000025258389,0.00003735808,0.0000766847],"category_scores_gemma":[0.000027402293,0.000067943336,0.000012394796,0.00021977912,0.00009226566,0.00009088899,0.00006288826,0.000076883734,0.000004278367],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038396238,0.00024886752,0.9987692,0.000010456905,0.000012629453,0.0000022849658,0.00012513978,0.0000015633753,0.000036593603,0.0000138165515,0.00006977306,0.00032568208],"study_design_scores_gemma":[0.0036632866,0.00044100077,0.9941753,0.000348647,0.000039690218,0.0000039459874,0.000034964873,0.00002722112,0.0010868931,0.00006569903,0.000024434186,0.000088895955],"about_ca_topic_score_codex":0.0000073526985,"about_ca_topic_score_gemma":0.0000043326127,"teacher_disagreement_score":0.033300344,"about_ca_system_score_codex":0.00003489094,"about_ca_system_score_gemma":0.000021530463,"threshold_uncertainty_score":0.2770649},"labels":[],"label_agreement":null},{"id":"W2460521385","doi":"10.1002/ana.24712","title":"Development of White Matter Hyperintensity Is Preceded by Reduced Cerebrovascular Reactivity","year":2016,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Health Sciences Centre; University Health Network","funders":"Canadian Stroke Network; Campbell Foundation","keywords":"Fractional anisotropy; White matter; Hyperintensity; Diffusion MRI; Cardiology; Magnetic resonance imaging; Medicine; Internal medicine; Neuroimaging; Radiology; Psychiatry","score_opus":0.11353973132076414,"score_gpt":0.36128746957404045,"score_spread":0.2477477382532763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2460521385","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.961003,0.000011583257,0.002718419,0.035467833,0.000018736328,0.00018691804,0.000013939415,0.000040934665,0.00053862855],"genre_scores_gemma":[0.9898136,0.00006440952,0.004318293,0.00548816,0.000010737024,0.00001952403,0.000003530726,0.00001610491,0.00026563316],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991877,0.000027663616,0.00025789652,0.00026364863,0.000100897625,0.00016221432],"domain_scores_gemma":[0.9991689,0.000040453073,0.00014644607,0.00042817835,0.00016082825,0.000055235454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008949883,0.00009669422,0.00027649474,0.000052138086,0.00003327307,6.8650064e-7,0.00009042693,0.000060359765,0.00009342431],"category_scores_gemma":[0.000040384966,0.00007123102,0.00007728955,0.000073440184,0.00011227781,0.000039557308,0.00009802722,0.00008824706,0.000013644598],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015335219,0.0001671359,0.044515472,0.000026339416,0.000025398182,0.0000016135452,0.00008259954,6.9858025e-8,0.9341067,0.00002617444,0.016014345,0.004880768],"study_design_scores_gemma":[0.00021876127,0.00013253315,0.22502548,0.000015697393,0.000010551551,0.0000386751,0.0000013771921,0.000002275675,0.70718616,0.0002309326,0.067083366,0.00005420325],"about_ca_topic_score_codex":0.000005205191,"about_ca_topic_score_gemma":5.6372795e-7,"teacher_disagreement_score":0.22692057,"about_ca_system_score_codex":0.0000030818933,"about_ca_system_score_gemma":0.000026062376,"threshold_uncertainty_score":0.29047167},"labels":[],"label_agreement":null},{"id":"W2462313590","doi":"10.3174/ajnr.a4870","title":"DTI Analysis of Presbycusis Using Voxel-Based Analysis","year":2016,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Presbycusis; Fractional anisotropy; Diffusion MRI; Medicine; Voxel; Thermal diffusivity; White matter; Audiology; Magnetic resonance imaging; Radiology; Physics; Hearing loss","score_opus":0.08403468295634334,"score_gpt":0.3970112409590346,"score_spread":0.3129765580026913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2462313590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.741254,0.000031148244,0.2567972,0.0017865449,0.000017851744,0.000051122097,0.000014963145,0.000015917085,0.000031284446],"genre_scores_gemma":[0.9729091,0.00006361049,0.026310802,0.0006411628,0.00004164825,0.0000018929319,0.000002166694,0.000014404279,0.000015248273],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987406,0.00013715186,0.0005805501,0.00020247554,0.00016000839,0.00017919025],"domain_scores_gemma":[0.9977914,0.00036587458,0.0010192284,0.00042203304,0.00026936075,0.00013208666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016147253,0.000119556236,0.0010327331,0.0013800851,0.000027937207,0.0000025499687,0.0001834454,0.000027319735,0.00005500207],"category_scores_gemma":[0.00017717612,0.0000776643,0.0006217102,0.0029848826,0.00049395266,0.00004704159,0.00002287949,0.00013266684,5.60671e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003921339,0.00023636974,0.6737484,0.000008321211,0.00494051,0.000095996125,0.00003730121,0.0058653154,0.28560197,0.00015294385,0.0001040786,0.028816717],"study_design_scores_gemma":[0.001488245,0.0038326299,0.9105888,0.00006689711,0.04287237,0.0005893631,0.000059628983,0.018762065,0.016221642,0.00025244034,0.004943221,0.00032266762],"about_ca_topic_score_codex":0.00002257593,"about_ca_topic_score_gemma":0.0000015950552,"teacher_disagreement_score":0.26938033,"about_ca_system_score_codex":0.000043816042,"about_ca_system_score_gemma":0.00008626053,"threshold_uncertainty_score":0.31670582},"labels":[],"label_agreement":null},{"id":"W2466746677","doi":"10.1159/000446770","title":"Altered Superficial White Matter on Tractography MRI in Alzheimer's Disease","year":2016,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Kingston General Hospital; Queen's University; University of Toronto","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Tractography; Hyperintensity; Psychology; Stroop effect; Magnetic resonance imaging; Cognitive decline; Alzheimer's disease; Frontal lobe; Pathology; Neuroscience; Medicine; Cognition; Disease; Dementia; Radiology","score_opus":0.02363189521748272,"score_gpt":0.30127741748287973,"score_spread":0.277645522265397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2466746677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95780987,0.0015569502,0.02227822,0.013335185,0.00009412922,0.001492062,0.00017114209,0.00013387029,0.00312858],"genre_scores_gemma":[0.9969601,0.001369726,0.00031263166,0.001012116,0.00006586825,0.00017678805,0.000039137965,0.000025417414,0.000038231534],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989849,0.00002997926,0.00020631886,0.00040857474,0.00012405872,0.00024621573],"domain_scores_gemma":[0.9995519,0.00007451215,0.000051434254,0.00014984071,0.000036669833,0.00013567062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052971962,0.00017155037,0.00016825668,0.00023244199,0.00007073996,0.000015344704,0.000047643603,0.000036762474,0.00032636753],"category_scores_gemma":[0.0000138565065,0.00013066146,0.00008805987,0.00025776963,0.00009302505,0.00008972187,0.000026744616,0.00009979144,0.00003023414],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042459348,0.00048252344,0.93179333,0.000016248012,0.00007463404,0.000010652095,0.00006905079,2.4248553e-7,0.00046313804,0.00026870013,0.0015916494,0.06480526],"study_design_scores_gemma":[0.0020125457,0.00013467354,0.990786,0.00008500583,0.00035582233,0.0000025471927,0.00006238302,0.000015348238,0.00016195679,0.002109538,0.004072613,0.00020152405],"about_ca_topic_score_codex":0.000008122038,"about_ca_topic_score_gemma":0.000007896305,"teacher_disagreement_score":0.06460374,"about_ca_system_score_codex":0.0000062714726,"about_ca_system_score_gemma":0.000019530213,"threshold_uncertainty_score":0.53282195},"labels":[],"label_agreement":null},{"id":"W2467810590","doi":"10.1007/s10334-016-0575-y","title":"Assessing the accuracy of using oscillating gradient spin echo sequences with AxCaliber to infer micron-sized axon diameters","year":2016,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Canadian Institute for Theoretical Astrophysics; University of Toronto; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Echo (communications protocol); Axon; Physics; Spin (aerodynamics); Nuclear magnetic resonance; Acoustics; Computer science; Neuroscience; Biology","score_opus":0.07362427929021703,"score_gpt":0.4014896194416566,"score_spread":0.3278653401514396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2467810590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9884854,0.00055476575,0.0068284716,0.0033958904,0.000068718844,0.0005297977,0.000009726243,0.00002332333,0.00010393071],"genre_scores_gemma":[0.9842085,0.0004019916,0.014502281,0.00065993133,0.00013774622,0.000052462754,0.0000034066304,0.000013877623,0.000019781053],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900866,0.000083125524,0.00033240512,0.0002825244,0.000081287,0.00021201406],"domain_scores_gemma":[0.9991521,0.0003195821,0.00015984845,0.00026851817,0.000053036263,0.00004688217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029883534,0.00014466066,0.0003781286,0.000051403968,0.00006284449,0.00000791088,0.00009015451,0.00004559311,0.000021065653],"category_scores_gemma":[0.00021359976,0.000067393616,0.000014697032,0.00019637059,0.00061879714,0.00006149735,0.000063283354,0.00006962347,5.2165353e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007220391,0.000018767932,0.01793594,0.000032945412,0.000003052789,0.0000030427077,0.00016058447,0.0000014771944,0.90552706,0.0008203071,0.000013792306,0.07541085],"study_design_scores_gemma":[0.0041765324,0.0018614595,0.18650115,0.0049489667,0.00014003349,0.00012970572,0.00033040065,0.00012628094,0.77222216,0.022960825,0.006169506,0.0004329818],"about_ca_topic_score_codex":0.00011856164,"about_ca_topic_score_gemma":0.0000029083508,"teacher_disagreement_score":0.1685652,"about_ca_system_score_codex":0.00002530054,"about_ca_system_score_gemma":0.00003717529,"threshold_uncertainty_score":0.2748232},"labels":[],"label_agreement":null},{"id":"W2470264972","doi":"10.1109/tip.2016.2588328","title":"Multi-Tissue Decomposition of Diffusion MRI Signals via L0 Sparse-Group Estimation","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Aging; University of North Carolina at Chapel Hill; National Institutes of Health; Simon Fraser University","keywords":"Deconvolution; Algorithm; Voxel; Diffusion MRI; Robustness (evolution); Matrix decomposition; Computer science; Mathematics; Mathematical optimization; Artificial intelligence; Magnetic resonance imaging","score_opus":0.04059078803748986,"score_gpt":0.3646835081929801,"score_spread":0.3240927201554903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2470264972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019179402,0.000037318445,0.9788823,0.0009772348,0.000043304542,0.0004722619,0.000020154557,0.0003108217,0.000077170196],"genre_scores_gemma":[0.6742855,0.00005378597,0.3253281,0.00008773972,0.000016938859,0.00007882391,0.0000048269426,0.00002797631,0.00011630454],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99892974,0.00002457506,0.00034220956,0.00032144727,0.00020112873,0.00018090417],"domain_scores_gemma":[0.9992602,0.00006521957,0.00016935007,0.00026577094,0.00015252443,0.00008692396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008822884,0.00016570745,0.00021945155,0.00018648953,0.00019833588,0.000019192908,0.00007855981,0.000068344605,0.000061479426],"category_scores_gemma":[0.000007832815,0.00012801611,0.00007409337,0.00025611074,0.00012320006,0.00036779876,0.0000016838237,0.00014206333,0.000024170155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051330087,0.000325594,0.0000073433516,0.000072147224,0.000004257729,0.0000026152695,0.000031618656,0.0001316673,0.65783924,0.0000025936965,0.000010603304,0.341521],"study_design_scores_gemma":[0.00096846354,0.00024012353,0.00033790592,0.0006951185,0.000089851106,0.00006705611,0.000010173262,0.03808189,0.95874333,0.0004150507,0.00020057205,0.00015045844],"about_ca_topic_score_codex":0.000007891798,"about_ca_topic_score_gemma":0.0000016678289,"teacher_disagreement_score":0.65510607,"about_ca_system_score_codex":0.00007320286,"about_ca_system_score_gemma":0.000029305711,"threshold_uncertainty_score":0.5220345},"labels":[],"label_agreement":null},{"id":"W2471565160","doi":"10.1093/brain/aww167","title":"The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions","year":2016,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":119,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Savoy Foundation","keywords":"White matter; Temporal lobe; Magnetic resonance imaging; Fractional anisotropy; Neuroscience; Diffusion MRI; Grey matter; Epilepsy; Cortex (anatomy); Frontal lobe; Psychology; Anatomy; Medicine; Radiology","score_opus":0.03960624551264561,"score_gpt":0.31723039288946575,"score_spread":0.2776241473768201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2471565160","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7392839,0.00009241908,0.025605595,0.23378883,0.00008502624,0.0004894063,0.00005189794,0.00011948567,0.00048339352],"genre_scores_gemma":[0.99278414,0.000018186214,0.0033714722,0.0012286606,0.0010014281,0.000054625878,0.000027117985,0.000017629156,0.0014967079],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993112,0.000029514891,0.00017458815,0.0001938353,0.00009031262,0.00020051184],"domain_scores_gemma":[0.9994651,0.00020766057,0.000035067496,0.00020813191,0.00002224352,0.00006178695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001208876,0.00008971826,0.000114831295,0.00003039457,0.00016389723,0.000017694194,0.000051308984,0.000042331125,0.00007525855],"category_scores_gemma":[0.00003892835,0.00005082442,0.00003309739,0.00012422305,0.00013429928,0.00006095539,0.00005200306,0.00013748977,0.000017202563],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029127563,0.000003827482,0.9717779,0.0000031615814,0.0000049477626,0.0000025713223,0.000024728717,0.0000021960232,0.00038439964,0.0026654603,0.01320849,0.0118932035],"study_design_scores_gemma":[0.00037677243,0.000030165484,0.9237679,0.0000369703,0.00000895228,0.000026351598,0.000007659539,0.00005824486,0.000017089118,0.010643988,0.06495636,0.00006949057],"about_ca_topic_score_codex":0.000008641109,"about_ca_topic_score_gemma":0.000024926445,"teacher_disagreement_score":0.25350022,"about_ca_system_score_codex":0.000026217187,"about_ca_system_score_gemma":0.000023040853,"threshold_uncertainty_score":0.20725596},"labels":[],"label_agreement":null},{"id":"W2472551679","doi":"10.1088/0031-9155/61/15/5768","title":"Automated PET-only quantification of amyloid deposition with adaptive template and empirically pre-defined ROI","year":2016,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Spatial normalization; Voxel; Region of interest; Artificial intelligence; Normalization (sociology); Nuclear medicine; Computer science; Pittsburgh compound B; Segmentation; Pattern recognition (psychology); Positron emission tomography; Medicine; Alzheimer's disease; Pathology; Disease","score_opus":0.21797642221013058,"score_gpt":0.4287588403691964,"score_spread":0.21078241815906584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2472551679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84519994,0.00012813068,0.14855087,0.005358174,0.000010974761,0.00034450486,0.000014786315,0.00012443382,0.00026820318],"genre_scores_gemma":[0.9894765,0.00040912768,0.009764588,0.00022676653,0.000038714516,0.000025641122,0.000032553547,0.000008607127,0.000017492315],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994314,0.00002635186,0.00018290209,0.00021731616,0.00004415046,0.00009788655],"domain_scores_gemma":[0.9995068,0.0001369166,0.00010521235,0.0001419383,0.00007115008,0.00003804057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007614007,0.000088331406,0.0002321341,0.00005469186,0.000025637677,0.000001013028,0.000030222123,0.0000310895,0.0000030238054],"category_scores_gemma":[0.000034298813,0.00004796819,0.000009392852,0.00014297367,0.00033244357,0.000035717127,0.000018833396,0.00007076947,5.258839e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056053634,0.00016350414,0.07155972,0.00007224921,0.000030470597,0.00000838561,0.00015133455,0.000002380008,0.8373892,0.026646348,0.0002582211,0.06315766],"study_design_scores_gemma":[0.012543731,0.012638798,0.78415036,0.002882151,0.00044742582,0.0011941164,0.00028636772,0.013210359,0.08063045,0.088196084,0.0030797,0.00074043626],"about_ca_topic_score_codex":0.000048838654,"about_ca_topic_score_gemma":0.000007627377,"teacher_disagreement_score":0.75675875,"about_ca_system_score_codex":0.000010947486,"about_ca_system_score_gemma":0.000022956294,"threshold_uncertainty_score":0.19560862},"labels":[],"label_agreement":null},{"id":"W2483278632","doi":"10.1007/s00429-016-1274-1","title":"Transcallosal connectivity of the human cortical motor network","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Department of Education and Learning, Northern Ireland; Atlantic Philanthropies","keywords":"Neuroscience; Corpus callosum; White matter; Diffusion MRI; Tractography; Premotor cortex; Human brain; Motor cortex; Primary motor cortex; Supplementary motor area; Cortex (anatomy); Psychology; Biology; Anatomy; Dorsum; Magnetic resonance imaging; Functional magnetic resonance imaging; Medicine","score_opus":0.02681806880911118,"score_gpt":0.2955183435411584,"score_spread":0.2687002747320472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2483278632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95093834,0.00002227942,0.04365311,0.00483056,0.00006434301,0.00023124112,0.000010957334,0.000048940143,0.00020019794],"genre_scores_gemma":[0.9987071,0.0000038246676,0.00041819914,0.00056034606,0.00015018282,0.0000064449137,0.0000018847624,0.0000066628145,0.00014531624],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99963486,0.000020433907,0.00008653576,0.000118510776,0.00006471878,0.00007493866],"domain_scores_gemma":[0.99969417,0.00006370407,0.000034643148,0.0001548214,0.000022688148,0.000029998644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038418293,0.0000537798,0.00008867263,0.000009915265,0.000088580025,0.0000021572453,0.000025092852,0.00004160925,0.000028393919],"category_scores_gemma":[0.00003506493,0.00002681921,0.00003801316,0.00006222054,0.00008740054,0.000024569023,0.000012018535,0.000083337254,1.9751675e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100308156,0.000018305396,0.050789956,0.000017239967,0.000013890588,4.079761e-7,0.00001501979,0.0000012096614,0.8900644,0.03753464,0.0019378227,0.019506758],"study_design_scores_gemma":[0.00052044855,0.00017693939,0.93872124,0.000039619375,0.0000507716,0.00003133497,0.0000043437103,0.00002117551,0.01010124,0.0407735,0.009509128,0.000050232567],"about_ca_topic_score_codex":0.0000025424201,"about_ca_topic_score_gemma":0.0000031154652,"teacher_disagreement_score":0.8879313,"about_ca_system_score_codex":0.000007046147,"about_ca_system_score_gemma":0.000008066938,"threshold_uncertainty_score":0.10936557},"labels":[],"label_agreement":null},{"id":"W2485969200","doi":"10.1093/brain/aww195","title":"Healthy brain connectivity predicts atrophy progression in non-fluent variant of primary progressive aphasia","year":2016,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":139,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Canadian Centre for Applied Research in Cancer Control; Larry L. Hillblom Foundation","keywords":"Primary progressive aphasia; Frontotemporal dementia; Aphasia; Psychology; Neuroscience; Semantic dementia; Dementia; Atrophy; Frontal lobe; Middle frontal gyrus; Grey matter; White matter; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Pathology","score_opus":0.03239517832150831,"score_gpt":0.357791396281009,"score_spread":0.3253962179595007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2485969200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85229236,0.0003305475,0.0634589,0.077660106,0.00010422591,0.0041028457,0.00007641098,0.00036218716,0.0016124502],"genre_scores_gemma":[0.97466904,0.000026877307,0.02270615,0.0019702201,0.00011171314,0.0003702671,0.000015334495,0.000032893116,0.00009748234],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986499,0.00008044894,0.00034524774,0.00039734002,0.00024203402,0.0002850491],"domain_scores_gemma":[0.99885726,0.0002686965,0.00021534784,0.00045395823,0.00007403093,0.0001307128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003205529,0.00015377655,0.00033888826,0.00013823953,0.000039393955,0.000004684248,0.00011785095,0.00007880399,0.000019333695],"category_scores_gemma":[0.00031696717,0.00010398539,0.000068974136,0.00028669107,0.00016930206,0.000095633244,0.00009209586,0.00015627807,0.000004655949],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014894091,0.002256638,0.0303552,0.0005996101,0.000034712844,0.00043500075,0.0003191815,0.0000022324655,0.4601773,0.0067761196,0.014048401,0.48350617],"study_design_scores_gemma":[0.022854647,0.0069866045,0.7851039,0.007574962,0.000099282006,0.0013760121,0.00007764494,0.0009763369,0.09915518,0.018440155,0.05626419,0.0010910647],"about_ca_topic_score_codex":0.000011770737,"about_ca_topic_score_gemma":0.0000019484407,"teacher_disagreement_score":0.7547487,"about_ca_system_score_codex":0.00014217645,"about_ca_system_score_gemma":0.00014733152,"threshold_uncertainty_score":0.4240401},"labels":[],"label_agreement":null},{"id":"W2487395641","doi":"10.1016/j.neuroimage.2016.07.048","title":"Optimal DSI reconstruction parameter recommendations: Better ODFs and better connectivity","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Computation; Diffusion MRI; Software; Algorithm; Data mining; Orientation (vector space); Artificial intelligence; Mathematics","score_opus":0.05842319150817775,"score_gpt":0.3335125303600374,"score_spread":0.27508933885185965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2487395641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8929376,0.000017583494,0.04892984,0.05636757,0.00010117591,0.00039725294,0.000029982863,0.0002968688,0.00092212117],"genre_scores_gemma":[0.8682109,0.00018635011,0.124041334,0.006670853,0.00017726426,0.00011624185,0.000009921593,0.000047083588,0.0005400259],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99900895,0.00004765349,0.00020434946,0.00044077958,0.000095276955,0.00020296629],"domain_scores_gemma":[0.9991008,0.00025631476,0.000080813195,0.0004089808,0.00005661723,0.00009648156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000088576846,0.0001473677,0.00018703095,0.000088202396,0.00010514369,0.000027115522,0.00005816522,0.00005269868,0.00017192571],"category_scores_gemma":[0.00016770713,0.000108243774,0.00005695214,0.00010192752,0.00017038056,0.00027524758,0.000063619555,0.00018772572,0.00003911432],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007103271,0.00010247606,0.041876514,0.00002234882,0.000017237238,0.00002857067,0.000024533674,1.9753342e-7,0.21069506,0.00026636547,0.009886177,0.73700947],"study_design_scores_gemma":[0.005679984,0.0009877771,0.36663383,0.0004748573,0.00027786588,0.004126273,0.000037670205,0.0010005544,0.2130435,0.018538155,0.38809657,0.0011029752],"about_ca_topic_score_codex":0.0000033428482,"about_ca_topic_score_gemma":6.119146e-7,"teacher_disagreement_score":0.73590654,"about_ca_system_score_codex":0.000028075621,"about_ca_system_score_gemma":0.000012308293,"threshold_uncertainty_score":0.4414053},"labels":[],"label_agreement":null},{"id":"W2496475229","doi":"10.1007/978-1-4939-3995-4_20","title":"Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-oncology and Neurotraumatology","year":2016,"lang":"en","type":"book-chapter","venue":"Springer series in computational neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; St. Michael's Hospital","funders":"","keywords":"Susceptibility weighted imaging; Neuroimaging; Magnetic resonance imaging; Medicine; Biomarker; Radiology; Glioma; Diffusion MRI; Fractal analysis; Fractal dimension; Pathology; Fractal; Biology; Cancer research","score_opus":0.042439371411067725,"score_gpt":0.3441250715068095,"score_spread":0.30168570009574175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2496475229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4684852,0.0005853399,0.44398516,0.043315824,0.0011790884,0.00547115,0.0009149486,0.00090976636,0.03515352],"genre_scores_gemma":[0.97052616,0.000071821516,0.026700016,0.0020738344,0.00002417657,0.000038473936,0.00006518345,0.000052251507,0.00044806025],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99735445,0.000060659873,0.0008396819,0.0010161508,0.00043322518,0.00029583526],"domain_scores_gemma":[0.9979483,0.0009135605,0.00043765662,0.00038018354,0.00020869442,0.00011160142],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001947237,0.00032928347,0.0008109194,0.0014526913,0.00008088377,0.000020062724,0.0002568418,0.00012250339,0.000039641738],"category_scores_gemma":[0.00017359268,0.00032574954,0.00014392693,0.00059851474,0.0012348588,0.00017742538,0.00019729411,0.0005029406,0.000001945094],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006472721,0.00064187805,0.432358,0.0003367901,0.00007054578,0.00092506484,0.0001856341,0.12209397,0.007054889,0.4204491,0.00006776185,0.015169068],"study_design_scores_gemma":[0.0016779273,0.00048000875,0.47610477,0.00031609752,0.00027255417,0.00032003803,0.000010509275,0.37952313,0.00022457355,0.13136317,0.009023354,0.0006838636],"about_ca_topic_score_codex":0.0000066088514,"about_ca_topic_score_gemma":0.000020484771,"teacher_disagreement_score":0.502041,"about_ca_system_score_codex":0.000118294134,"about_ca_system_score_gemma":0.00032783148,"threshold_uncertainty_score":0.9999195},"labels":[],"label_agreement":null},{"id":"W2499587845","doi":"10.1016/j.neuroimage.2016.07.053","title":"Corrigendum to “A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging”","year":2016,"lang":"en","type":"erratum","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Compressed sensing; Joint (building); Resolution (logic); High resolution; Diffusion; Computer science; Diffusion imaging; Diffusion MRI; Artificial intelligence; Remote sensing; Geology; Medicine; Physics; Radiology; Engineering; Magnetic resonance imaging","score_opus":0.07265784918326551,"score_gpt":0.3106696367758546,"score_spread":0.23801178759258906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2499587845","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00079300936,0.0008024215,0.9737366,0.0059684394,0.0067578927,0.0041621025,0.0006535557,0.00100118,0.006124798],"genre_scores_gemma":[0.06241765,0.004731538,0.57430494,0.016960388,0.014424387,0.0015760505,0.009710988,0.0018613337,0.3140127],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968742,0.00007081783,0.0005568961,0.0013874527,0.00042811554,0.0006825285],"domain_scores_gemma":[0.9979431,0.00006399417,0.00026079532,0.0011027459,0.00028721883,0.00034214274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017149874,0.00059595,0.0007883365,0.00039383952,0.00040574523,0.00009103522,0.00020344042,0.00027511813,0.000012287088],"category_scores_gemma":[0.00023182384,0.00052315695,0.00021697386,0.00022666404,0.00022026629,0.00015346114,0.000362502,0.0008257378,0.000016073496],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015485454,0.00014296426,0.000032411383,0.00034826898,0.000012357139,0.00002968565,0.000025413578,0.0000042171973,0.11334542,0.00023253316,0.87403005,0.011641832],"study_design_scores_gemma":[0.0015475955,0.00036579216,0.0035061392,0.00069867383,0.0002853982,0.00033774303,0.0000147508335,0.042341206,0.0028716144,0.0007606412,0.9465399,0.00073054584],"about_ca_topic_score_codex":0.00009760665,"about_ca_topic_score_gemma":0.0000027422327,"teacher_disagreement_score":0.39943165,"about_ca_system_score_codex":0.0001907882,"about_ca_system_score_gemma":0.0001128208,"threshold_uncertainty_score":0.999722},"labels":[],"label_agreement":null},{"id":"W2502730944","doi":"10.1002/hbm.23339","title":"New insights in the homotopic and heterotopic connectivity of the frontal portion of the human corpus callosum revealed by microdissection and diffusion tractography","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Superior frontal gyrus; Neuroscience; Frontal lobe; Corpus callosum; Middle frontal gyrus; Diffusion MRI; Anatomy; Inferior frontal gyrus; Psychology; Medial frontal gyrus; Biology; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.03283729647112223,"score_gpt":0.2918627210989834,"score_spread":0.2590254246278612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2502730944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99449617,0.00011347196,0.0020672698,0.002480579,0.000016363445,0.0007128565,0.0000030590538,0.00001593373,0.000094329655],"genre_scores_gemma":[0.9995396,0.0000191759,0.0000756752,0.0001763412,0.00002268645,0.00002311933,0.0000016263267,0.0000062985127,0.00013546739],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993983,0.00007824537,0.00019632276,0.00015793878,0.000093293886,0.00007591865],"domain_scores_gemma":[0.99945986,0.00007264238,0.00016240023,0.00026941777,0.000016863192,0.000018808623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000107136766,0.00007750853,0.00013198107,0.000048062382,0.00017374285,0.000006107136,0.00008675666,0.000038437334,0.0000033696929],"category_scores_gemma":[0.000030458774,0.000036809997,0.000048169695,0.00011973676,0.00014358915,0.000043667682,0.00004710449,0.00011963611,3.209953e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035201194,0.000037717924,0.19007601,0.000025963032,0.0000033089354,2.7606734e-7,0.00039834168,2.2571635e-8,0.80723864,0.0006768559,0.00029584506,0.0012435239],"study_design_scores_gemma":[0.00060879835,0.00005149751,0.9821163,0.00024888976,0.000012812787,0.000016844038,0.00005925342,0.0000038296666,0.010142306,0.005329474,0.0013662085,0.000043801592],"about_ca_topic_score_codex":0.00014887057,"about_ca_topic_score_gemma":0.00011120065,"teacher_disagreement_score":0.7970963,"about_ca_system_score_codex":0.000015093935,"about_ca_system_score_gemma":0.0000068523896,"threshold_uncertainty_score":0.15010682},"labels":[],"label_agreement":null},{"id":"W2504994530","doi":"10.1101/066647","title":"The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Striatum; Addiction; Thalamus; Nucleus accumbens; Kurtosis; Psychology; Cocaine dependence; Neuroscience; Ventral striatum; Dopamine; Mathematics","score_opus":0.015220829807030028,"score_gpt":0.2683196317622078,"score_spread":0.25309880195517775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2504994530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99653476,0.0010456388,0.00058998185,0.0007665706,0.00004912136,0.00082351133,0.0001456549,0.000042686985,0.0000020694924],"genre_scores_gemma":[0.9985097,0.0006906185,0.00058856857,0.0000759585,0.000056561465,0.000040418414,3.7516412e-7,0.000036068825,0.0000017354791],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986742,0.00016286131,0.0003158749,0.00050632283,0.00015640691,0.00018429325],"domain_scores_gemma":[0.9982563,0.00031478665,0.00047327197,0.00077649625,0.0001113392,0.00006776592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038497034,0.0002853739,0.00049365783,0.00014267885,0.00038567558,0.00005212334,0.0001537621,0.0001409507,0.0000030307738],"category_scores_gemma":[0.00014883501,0.0001451273,0.000084068044,0.0002943347,0.0007256952,0.000033407345,0.0004852158,0.00043318962,4.219711e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003833837,0.000011217812,0.15262291,0.00008596738,0.0001229039,0.0000030194326,0.000007730601,9.81321e-7,0.8468593,0.00016788898,0.000012429727,0.00006731322],"study_design_scores_gemma":[0.00052476185,0.000079177655,0.7772207,0.00042152588,0.001030989,4.7210006e-7,0.0000032556375,0.0012027336,0.21926755,0.000023685705,0.000085197564,0.00013992802],"about_ca_topic_score_codex":0.000032316737,"about_ca_topic_score_gemma":0.0000015474778,"teacher_disagreement_score":0.6275917,"about_ca_system_score_codex":0.00003528688,"about_ca_system_score_gemma":0.000026170495,"threshold_uncertainty_score":0.59181195},"labels":[],"label_agreement":null},{"id":"W2505695543","doi":"10.1016/j.jad.2016.07.026","title":"Corpus callosum integrity is affected by mood disorders and also by the suicide attempt history: A diffusion tensor imaging study","year":2016,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Major depressive disorder; Suicide attempt; Bipolar disorder; Psychology; Mood disorders; Diffusion MRI; Poison control; Mood; Psychiatry; Clinical psychology; Internal medicine; Medicine; Injury prevention; Magnetic resonance imaging; Neuroscience; Anxiety","score_opus":0.021605041082241174,"score_gpt":0.3131748482433767,"score_spread":0.29156980716113556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2505695543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95814925,0.0017583215,0.016570933,0.021904211,0.00010994248,0.0011620551,0.000029584566,0.00007216023,0.0002435631],"genre_scores_gemma":[0.997574,0.00116721,0.00017913665,0.00066498516,0.00003741696,0.000047784186,0.00000265823,0.000045064804,0.0002817787],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856734,0.00017675525,0.00032806664,0.00032693232,0.00033672978,0.0002641487],"domain_scores_gemma":[0.9985797,0.00039616544,0.00039274208,0.00031284592,0.00017248048,0.00014607617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003170092,0.00025721604,0.0003948466,0.00012012445,0.0001617716,0.00001685833,0.00018796438,0.00005115183,0.000030292591],"category_scores_gemma":[0.0003656033,0.00014081324,0.00014797055,0.00018122715,0.00032167713,0.0001885893,0.000079794496,0.00052715826,0.0000018261079],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025690676,0.001487183,0.79521596,0.000018968592,0.00012110668,0.0000051671477,0.00066113466,2.0943676e-7,0.06384721,0.00002354191,0.06956536,0.06879725],"study_design_scores_gemma":[0.010771986,0.0032156962,0.9178219,0.00039887332,0.0006192128,0.0002388132,0.0025908048,0.00020088286,0.0024099478,0.0027708933,0.058357373,0.0006036094],"about_ca_topic_score_codex":0.00034310436,"about_ca_topic_score_gemma":0.00017296283,"teacher_disagreement_score":0.12260595,"about_ca_system_score_codex":0.0002885215,"about_ca_system_score_gemma":0.000057822323,"threshold_uncertainty_score":0.57421976},"labels":[],"label_agreement":null},{"id":"W2508153689","doi":"10.1016/j.media.2016.09.001","title":"Conformal invariants for multiply connected surfaces: Application to landmark curve-based brain morphometry analysis","year":2016,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; U.S. Department of Defense; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"Brain morphometry; Landmark; Invariant (physics); Conformal map; Neuroimaging; Computation; Mathematics; Artificial intelligence; Shape analysis (program analysis); Pattern recognition (psychology); Surface (topology); Geometry; Computer science; Algorithm; Neuroscience; Magnetic resonance imaging; Psychology; Medicine","score_opus":0.03491847557675011,"score_gpt":0.37055534472712737,"score_spread":0.33563686915037727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2508153689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06294575,0.000016843645,0.91107464,0.024589477,0.000010963549,0.00074412726,0.00021779678,0.00026278972,0.00013760549],"genre_scores_gemma":[0.9218044,0.000017510074,0.07023414,0.0062453635,0.00007135484,0.00049167924,0.00063731923,0.000029740406,0.00046844475],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977363,0.00006406009,0.0005751403,0.00063086057,0.0005985401,0.00039510755],"domain_scores_gemma":[0.99697506,0.0010239558,0.0001847906,0.0008396506,0.00039404674,0.00058249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007413275,0.00022487565,0.00075337425,0.001009742,0.00012285376,0.00003123422,0.00030221065,0.00013836502,0.00073692965],"category_scores_gemma":[0.002687167,0.00015468306,0.00055296766,0.004753823,0.00015096938,0.00011810279,0.00006620366,0.00014291759,0.00005662263],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015647023,0.0021684265,0.55677086,0.00027003407,0.014865126,0.00012383267,0.00018151292,0.0010395198,0.24661702,0.0014000437,0.036100604,0.13889834],"study_design_scores_gemma":[0.007562759,0.00045073865,0.21497719,0.00012767746,0.018858405,0.0000122648635,0.00007232304,0.6581739,0.032516934,0.00038856734,0.06586293,0.0009962975],"about_ca_topic_score_codex":0.00016906523,"about_ca_topic_score_gemma":0.00014769823,"teacher_disagreement_score":0.8588587,"about_ca_system_score_codex":0.00008082159,"about_ca_system_score_gemma":0.00011227907,"threshold_uncertainty_score":0.8068863},"labels":[],"label_agreement":null},{"id":"W2509368961","doi":"10.7717/peerj.2632","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model","year":2016,"lang":"en","type":"article","venue":"PeerJ","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"Medical Research Council","keywords":"Corpus callosum; Ex vivo; Magnetic resonance imaging; Diffusion MRI; Myelin; Relaxometry; Pathology; White matter; Neuroscience; Hippocampus; Central nervous system; Biology; Medicine; In vivo; Spin echo; Radiology","score_opus":0.09114219249002782,"score_gpt":0.37491447792262694,"score_spread":0.28377228543259914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2509368961","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25160307,0.00005398179,0.578628,0.16473901,0.000029238665,0.0005920156,0.00015556042,0.00022631587,0.0039727995],"genre_scores_gemma":[0.8759642,0.000028512697,0.06370813,0.0012171316,0.000028237679,0.000049345355,0.0000025716865,0.00002961208,0.058972243],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999445,0.000013217795,0.00013412055,0.00015597488,0.00014070648,0.00011098585],"domain_scores_gemma":[0.9992598,0.000095444426,0.00007110291,0.00045183397,0.00008179582,0.000040013812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000073478936,0.00007302854,0.0001302639,0.000026644724,0.00003802932,0.0000023571374,0.0001240196,0.000025068997,0.000022433509],"category_scores_gemma":[0.00014773902,0.000038581056,0.00006719206,0.00008668599,0.00012628172,0.000036435904,0.000060737715,0.00007434337,0.000019801064],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025465617,0.00007341709,0.0005466678,0.000013392609,0.0000072329854,5.2252074e-7,0.00010462805,0.00004173113,0.9282901,0.034286484,0.035421237,0.0011891214],"study_design_scores_gemma":[0.001292209,0.00018862767,0.0023322525,0.00018058813,0.000057513673,0.000013865614,0.00006730868,0.007709297,0.85329723,0.038142633,0.09652698,0.00019147524],"about_ca_topic_score_codex":0.000007534483,"about_ca_topic_score_gemma":0.0000020691323,"teacher_disagreement_score":0.62436116,"about_ca_system_score_codex":0.000020186377,"about_ca_system_score_gemma":0.00003030218,"threshold_uncertainty_score":0.15732898},"labels":[],"label_agreement":null},{"id":"W2510336237","doi":"10.1016/j.neuroimage.2016.08.053","title":"Functional activity and white matter microstructure reveal the independent effects of age of acquisition and proficiency on second-language learning","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Age of Acquisition; Diffusion MRI; Functional magnetic resonance imaging; White matter; Superior temporal gyrus; Parahippocampal gyrus; Inferior frontal gyrus; Language proficiency; Mandarin Chinese; Cognitive psychology; Cognition; Linguistics; Neuroscience; Temporal lobe; Magnetic resonance imaging; Medicine","score_opus":0.0134870159044191,"score_gpt":0.27883595711147147,"score_spread":0.2653489412070524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510336237","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961964,0.000033106255,0.0018968737,0.0011121344,0.000021453101,0.00034912134,0.000013461375,0.000027307266,0.00035013637],"genre_scores_gemma":[0.99842405,0.000014449117,0.00026331074,0.00037873877,0.000025252932,0.000014826146,0.0000033101533,0.0000128902475,0.0008631705],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99943566,0.00004438861,0.000101594465,0.00020926844,0.00011803955,0.000091026166],"domain_scores_gemma":[0.9995292,0.00012238215,0.00009951281,0.00019253763,0.000026317066,0.000030077901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060977844,0.000087687906,0.00012964441,0.000045946814,0.00005607919,0.0000060561765,0.000036910802,0.000032254917,0.000044303266],"category_scores_gemma":[0.00003167644,0.000050704217,0.000027378517,0.00006091556,0.00015341728,0.00005557052,0.000053162683,0.00017198485,0.0000015972117],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007680352,0.00003192002,0.036123224,0.0001259383,0.0000031518896,0.0000116789915,0.0001010583,3.116789e-7,0.9604837,0.000045062246,0.00019457514,0.0028026174],"study_design_scores_gemma":[0.00039062634,0.0001926233,0.76431465,0.000067411485,0.00001594431,0.00006676463,0.000009007178,0.000004583312,0.23469007,0.00011863877,0.000092596274,0.00003708793],"about_ca_topic_score_codex":0.0000019418023,"about_ca_topic_score_gemma":3.5531443e-7,"teacher_disagreement_score":0.72819144,"about_ca_system_score_codex":0.000008098162,"about_ca_system_score_gemma":0.000007614328,"threshold_uncertainty_score":0.2067658},"labels":[],"label_agreement":null},{"id":"W2511678394","doi":"10.1093/cercor/bhw221","title":"Longitudinal Study of White Matter Development and Outcomes in Children Born Very Preterm","year":2016,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Gestational age; Internal capsule; Pediatrics; Psychology; Medicine; Magnetic resonance imaging; Biology; Pregnancy; Radiology; Genetics","score_opus":0.03852160220448467,"score_gpt":0.31879269295294693,"score_spread":0.28027109074846224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2511678394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9984447,0.000010859658,0.00041333825,0.00041554167,0.000009362406,0.0004982748,0.000003952727,0.000036161917,0.00016785187],"genre_scores_gemma":[0.99686104,0.0000037340665,0.0024920078,0.00012012557,0.000008971394,0.00004396623,0.0000026290945,0.000012020598,0.00045547792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993755,0.000008341476,0.0001985407,0.00021278237,0.00008957235,0.00011523987],"domain_scores_gemma":[0.99965334,0.000015264684,0.000053909884,0.00021635785,0.000019368725,0.000041776435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003507814,0.000090170615,0.0001880614,0.00006606606,0.000032778153,0.0000031224786,0.00005507156,0.000020490177,0.000044257322],"category_scores_gemma":[0.0000068003856,0.000058249952,0.00001730475,0.00006122892,0.000037003585,0.00005402661,0.00009641419,0.000057537807,0.0000068720137],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019547158,0.00017243948,0.99667406,0.0000074328645,0.000014556388,0.0000027712608,0.00012531935,3.0577045e-8,0.00029584992,0.000018761037,0.00007884641,0.002590404],"study_design_scores_gemma":[0.0009861883,0.00012073849,0.9979972,0.00004540004,0.000016339864,0.000021410726,0.000017246972,0.0000011076081,0.0005699622,0.00008867472,0.0000642452,0.00007144788],"about_ca_topic_score_codex":0.00001146433,"about_ca_topic_score_gemma":0.000011743788,"teacher_disagreement_score":0.002518956,"about_ca_system_score_codex":0.000022317277,"about_ca_system_score_gemma":0.0000148891295,"threshold_uncertainty_score":0.23753642},"labels":[],"label_agreement":null},{"id":"W2515079814","doi":"10.1016/j.neurobiolaging.2016.08.006","title":"Age-related white-matter correlates of motor sequence learning and consolidation","year":2016,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Western University; Hôpital du Sacré-Cœur de Montréal; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Corpus callosum; Psychology; Consolidation (business); Young adult; Memory consolidation; Corticospinal tract; Motor learning; Developmental psychology; Audiology; Neuroscience; Physical medicine and rehabilitation; Magnetic resonance imaging; Medicine","score_opus":0.033700747211780055,"score_gpt":0.3210379763784704,"score_spread":0.28733722916669036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515079814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99560726,0.000040288924,0.0015205021,0.0020707115,0.000025845313,0.0001477081,0.000005135598,0.000067939734,0.0005146369],"genre_scores_gemma":[0.9971953,0.00012765519,0.0020023354,0.0001261991,0.0000062909976,0.0000062177323,0.0000064081305,0.000010572426,0.00051902875],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99946576,0.000034045577,0.00020264919,0.00017180218,0.00002861961,0.00009712528],"domain_scores_gemma":[0.99951357,0.00014762195,0.00014952324,0.00011617789,0.00004777237,0.000025322317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000570247,0.00006892992,0.00017145541,0.00007166206,0.000029055134,0.0000012464583,0.00003901958,0.00004582145,0.000048284204],"category_scores_gemma":[0.000050351926,0.000049918424,0.00002633455,0.00006571583,0.00032451763,0.000038695413,0.000038324513,0.00011375813,0.0000053323506],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010266846,0.000010787449,0.53195995,0.000020958045,0.0000056406666,0.0000024481992,0.000035490062,0.0000028130037,0.46677157,0.00023600298,0.00003705974,0.00090700336],"study_design_scores_gemma":[0.0013341705,0.0006203418,0.7831573,0.0005804356,0.00009971157,0.0003322252,0.000038497164,0.0002026167,0.20957969,0.0023924934,0.0014603337,0.0002021866],"about_ca_topic_score_codex":0.0000022240397,"about_ca_topic_score_gemma":1.0359569e-7,"teacher_disagreement_score":0.25719187,"about_ca_system_score_codex":0.000006071083,"about_ca_system_score_gemma":0.000009298272,"threshold_uncertainty_score":0.20356143},"labels":[],"label_agreement":null},{"id":"W2515350692","doi":"10.1007/s00429-016-1298-6","title":"Revisiting the human uncinate fasciculus, its subcomponents and asymmetries with stem-based tractography and microdissection validation","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":127,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Agence Nationale de la Recherche","keywords":"Tractography; Microdissection; Uncinate fasciculus; Psychology; Neuroscience; Diffusion MRI; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.029715552549711397,"score_gpt":0.28316871332772997,"score_spread":0.25345316077801855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515350692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97556657,0.00020338339,0.017626446,0.0061183632,0.000019774878,0.00033238658,0.000010788966,0.000080001795,0.000042290278],"genre_scores_gemma":[0.9988963,0.000051497926,0.00044923657,0.00039604705,0.00008902827,0.0000132255245,0.000020458752,0.000012223702,0.00007198963],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99945086,0.000028940261,0.000106941436,0.00023255558,0.00009047936,0.00009022908],"domain_scores_gemma":[0.9996157,0.0000815048,0.00008398044,0.000118092874,0.000058701266,0.00004201357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009539774,0.00010610289,0.00010415467,0.00008518518,0.00028523526,0.00003562104,0.000017585826,0.000042330877,0.0000041848716],"category_scores_gemma":[0.000017186385,0.000055111323,0.000015728003,0.00016189487,0.00008590746,0.000117434196,0.000011124393,0.00008843982,1.17376445e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018367436,0.0000104632045,0.10922852,0.00010709665,0.000025843668,0.000001696733,0.000060306174,0.0000012314815,0.716913,0.002287167,0.00011940337,0.17106158],"study_design_scores_gemma":[0.0016473217,0.00035702504,0.88907593,0.00021615466,0.00016385746,0.00017247233,0.00009340089,0.000066875255,0.095602,0.0022736203,0.01013947,0.00019186776],"about_ca_topic_score_codex":0.000006149222,"about_ca_topic_score_gemma":0.0000017317176,"teacher_disagreement_score":0.77984744,"about_ca_system_score_codex":0.000010313916,"about_ca_system_score_gemma":0.000006248661,"threshold_uncertainty_score":0.22473745},"labels":[],"label_agreement":null},{"id":"W2515401228","doi":"10.3791/53759","title":"Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography","year":2016,"lang":"en","type":"article","venue":"Journal of Visualized Experiments","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lateral geniculate nucleus; Tractography; Diffusion MRI; Optic radiation; Neuroscience; Visual cortex; Decussation; Albinism; Optic chiasm; Retinotopy; White matter; Biology; Artificial intelligence; Physics; Computer science; Optic nerve; Magnetic resonance imaging; Medicine","score_opus":0.10341913999359678,"score_gpt":0.452052485913231,"score_spread":0.34863334591963424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2515401228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938802,0.00039106552,0.00487268,0.00041991984,0.000030379651,0.00028085092,0.0000010467639,0.000015795147,0.00010803115],"genre_scores_gemma":[0.99668664,0.00008971288,0.0027720253,0.00036005725,0.000055601045,0.000012025822,5.0965787e-7,0.000019260386,0.000004160705],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987795,0.00012514014,0.00045284771,0.00016835278,0.0002893382,0.00018486546],"domain_scores_gemma":[0.99935156,0.000119924116,0.00027002598,0.00013792614,0.00005487509,0.00006568976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004987903,0.00013215232,0.00030862892,0.00030986973,0.0000810828,0.000020734988,0.0000958411,0.00003417119,0.000005755877],"category_scores_gemma":[0.000058396938,0.00007645328,0.0000835821,0.00018513697,0.00007995186,0.0002227871,0.000044662793,0.00020983107,1.8208904e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000123871,0.00051399204,0.099946536,0.000010731263,0.0000068503673,0.000077832774,0.0004951166,2.7720242e-7,0.89497113,0.000090468246,0.000008576711,0.0037545904],"study_design_scores_gemma":[0.011135205,0.00047316222,0.5416127,0.0015195197,0.00004118801,0.00084515556,0.0010207718,0.00023196143,0.44005153,0.0017397602,0.0010246166,0.00030445607],"about_ca_topic_score_codex":0.000019745987,"about_ca_topic_score_gemma":7.2506464e-7,"teacher_disagreement_score":0.45491964,"about_ca_system_score_codex":0.00010309953,"about_ca_system_score_gemma":0.000030697018,"threshold_uncertainty_score":0.31176743},"labels":[],"label_agreement":null},{"id":"W2517974079","doi":"10.1093/cercor/bhw250","title":"Impaired Frontal-Limbic White Matter Maturation in Children at Risk for Major Depression","year":2016,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health; Canadian Institutes of Health Research; Tommy Fuss Fund","keywords":"Depression (economics); Fractional anisotropy; White matter; Psychology; Corpus callosum; Cingulum (brain); Anterior cingulate cortex; Pathological; Limbic system; Risk factor; Neuroscience; Mood disorders; Clinical psychology; Anxiety; Internal medicine; Medicine; Psychiatry; Central nervous system; Magnetic resonance imaging; Cognition","score_opus":0.017751103400360176,"score_gpt":0.28944592070922104,"score_spread":0.27169481730886086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2517974079","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97861534,0.00004657622,0.017885655,0.0018049763,0.00003601373,0.0010933111,0.00007934057,0.0001514559,0.00028731354],"genre_scores_gemma":[0.9889017,0.000022333179,0.007328116,0.00046589374,0.00008738991,0.00021206886,0.00009719803,0.000033656008,0.002851658],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991791,0.00001534713,0.00020037651,0.00031799823,0.00008515673,0.00020199805],"domain_scores_gemma":[0.9994358,0.000026947308,0.00010203058,0.0003354454,0.000029730376,0.00007007637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047983332,0.00012182519,0.00015904887,0.00006487703,0.000081489394,0.000008410702,0.000075129356,0.00006442494,0.0002486145],"category_scores_gemma":[0.0000195388,0.00008127666,0.0000713969,0.00007269634,0.000033451848,0.00011142659,0.000056882236,0.00008343207,0.00010291705],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002694421,0.000042858355,0.96351707,0.000009195034,0.0000064164396,8.75969e-7,0.000014830757,2.9560152e-7,0.021919103,0.000023969345,0.009215726,0.00498019],"study_design_scores_gemma":[0.0016073985,0.00006675629,0.98938465,0.000076165554,0.00003457806,0.00005101363,0.0000028514817,0.000118560005,0.006310883,0.001364036,0.0008694537,0.000113679605],"about_ca_topic_score_codex":0.000019238136,"about_ca_topic_score_gemma":0.000018660463,"teacher_disagreement_score":0.025867525,"about_ca_system_score_codex":0.00010443255,"about_ca_system_score_gemma":0.000012322017,"threshold_uncertainty_score":0.3314366},"labels":[],"label_agreement":null},{"id":"W2518385205","doi":"10.3389/fnhum.2016.00410","title":"Identification of Reliable Sulcal Patterns of the Human Rolandic Region","year":2016,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital de l'Enfant-Jésus","funders":"","keywords":"Concordance; Lateralization of brain function; Segmentation; Magnetic resonance imaging; Human brain; Nuclear medicine; Anatomy; Medicine; Cartography; Psychology; Computer science; Radiology; Neuroscience; Artificial intelligence; Audiology; Geography","score_opus":0.04754164539441399,"score_gpt":0.3288227069448095,"score_spread":0.2812810615503955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2518385205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.871703,0.000012779153,0.12694219,0.00070882414,0.00016365481,0.0003075135,0.0000063283132,0.00003130173,0.00012439983],"genre_scores_gemma":[0.9986112,0.00003417754,0.0002795007,0.00009804469,0.000013239458,0.000019108023,5.050773e-7,0.0000086225,0.0009355712],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99906886,0.00002234461,0.0003020111,0.00024452034,0.00023840382,0.00012383438],"domain_scores_gemma":[0.99914694,0.000010398386,0.0002173178,0.0005429439,0.000054639706,0.000027770455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015109233,0.0000635711,0.00013189869,0.00010461508,0.00008738435,0.0000043101677,0.00029471848,0.000025069521,0.0000018445261],"category_scores_gemma":[0.000096448486,0.000039467384,0.000045094646,0.00026258346,0.0003036273,0.00008747032,0.00006291701,0.0000840901,9.886542e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004030981,0.000053137006,0.4837265,0.000017843005,2.9572567e-7,0.0000012060756,0.000022772341,0.0000055461837,0.51305693,0.0017374626,0.001073809,0.00030045383],"study_design_scores_gemma":[0.0004089294,0.00009680325,0.73613656,0.0001981485,0.000011501586,0.000012716936,0.000014469886,0.00020645262,0.25378132,0.0076562995,0.0014075392,0.00006927158],"about_ca_topic_score_codex":0.000010639689,"about_ca_topic_score_gemma":0.0000012337308,"teacher_disagreement_score":0.25927562,"about_ca_system_score_codex":0.000040262545,"about_ca_system_score_gemma":0.000019998342,"threshold_uncertainty_score":0.16094333},"labels":[],"label_agreement":null},{"id":"W2520118764","doi":"10.1007/s00406-016-0730-5","title":"Altered intracortical myelin staining in the dorsolateral prefrontal cortex in severe mental illness","year":2016,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Sunnybrook Health Science Centre","funders":"Stanley Medical Research Institute; Brain and Behavior Research Foundation","keywords":"White matter; Myelin; Luxol fast blue stain; Dorsolateral prefrontal cortex; Neuroscience; Major depressive disorder; Cortex (anatomy); Anterior cingulate cortex; Prefrontal cortex; Schizophrenia (object-oriented programming); Psychology; Medicine; Central nervous system; Psychiatry; Magnetic resonance imaging; Cognition","score_opus":0.048367836148668214,"score_gpt":0.3728467860560255,"score_spread":0.32447894990735726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2520118764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9887277,0.00002526893,0.0022186665,0.0064680986,0.00021293927,0.0003076591,0.000013327242,0.000028654968,0.0019976937],"genre_scores_gemma":[0.9940652,0.00032717906,0.0037867227,0.0016509147,0.00009274297,0.0000049986916,0.000001307748,0.000011970834,0.000058937112],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983531,0.00029878132,0.00055199023,0.0004330854,0.00014127675,0.0002217394],"domain_scores_gemma":[0.99920124,0.0002917765,0.00010548861,0.0003009348,0.0000055602636,0.000094973264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040146144,0.00011205423,0.00018688885,0.00006396379,0.000067174595,0.000012670802,0.00029168933,0.000016214844,0.0000052932933],"category_scores_gemma":[0.00017367845,0.00006462439,0.00006718639,0.00014969315,0.00072523183,0.000095703945,0.00014120669,0.00031239446,0.00000199588],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055849756,0.0010187528,0.8793952,0.00003090475,0.0000025741294,0.000057972546,0.00051730056,0.0000018639753,0.026862184,0.003910604,0.00010042981,0.087543726],"study_design_scores_gemma":[0.0011293844,0.00055828295,0.9943027,0.00018762755,0.000006866218,0.00009611726,0.00010354178,0.00047462282,0.000030431016,0.0020522282,0.00096429134,0.00009390119],"about_ca_topic_score_codex":0.0000026252299,"about_ca_topic_score_gemma":0.0000084467,"teacher_disagreement_score":0.11490752,"about_ca_system_score_codex":0.0000036455356,"about_ca_system_score_gemma":0.00003455109,"threshold_uncertainty_score":0.2672147},"labels":[],"label_agreement":null},{"id":"W2520475080","doi":"10.82308/26415","title":"Perceptual organisation in diffusion MRI: curves and streamline flows","year":2009,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Tangent; Artificial intelligence; Inference; Orientation (vector space); Computer science; Computer vision; Diffusion MRI; Algorithm; Geometry; Mathematics","score_opus":0.07893361469951948,"score_gpt":0.38806300680384137,"score_spread":0.3091293921043219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2520475080","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9884441,0.000081785365,0.00094364444,0.007001597,0.000005100011,0.00051306176,0.000005008412,0.0000060044003,0.0029996862],"genre_scores_gemma":[0.9530465,0.00043850005,0.045244567,0.0006048665,0.000024355828,0.000008053088,0.00004928052,0.000006209499,0.0005776487],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995828,0.00000832487,0.000108150474,0.00017197985,0.000056906832,0.000071784314],"domain_scores_gemma":[0.9997622,0.000012553677,0.000023867287,0.00014732855,0.00001383315,0.00004026127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005710793,0.00005715065,0.00010223235,0.000031513166,0.000030757867,0.000014859585,0.00005878422,0.000022735023,0.00041049454],"category_scores_gemma":[0.00002088499,0.00004944442,0.000008452266,0.00008080202,0.000016093214,0.00008309955,0.000041640753,0.00007856329,0.000018792816],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000645732,0.0004427753,0.012541994,0.000014470242,0.0000022731444,0.000021759946,0.000717199,0.0000035230871,0.17972767,0.00009725607,0.0015137428,0.8048528],"study_design_scores_gemma":[0.004550788,0.0012579522,0.78598964,0.001171395,0.00010587895,0.00025367204,0.0008749912,0.007023602,0.04481739,0.0033707668,0.14999531,0.00058860454],"about_ca_topic_score_codex":0.000011753644,"about_ca_topic_score_gemma":0.0000141729915,"teacher_disagreement_score":0.8042642,"about_ca_system_score_codex":0.00001631113,"about_ca_system_score_gemma":0.00001583807,"threshold_uncertainty_score":0.44946274},"labels":[],"label_agreement":null},{"id":"W2521607924","doi":"10.1016/j.neuroimage.2016.08.027","title":"Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Fujirebio Europe; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; Lundbeckfonden; Alzheimer's Drug Discovery Foundation; Chinese Academy of Sciences; National Natural Science Foundation of China; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Wellcome Trust; Roche; Merck; Takeda Pharmaceutical Company; AbbVie; National Institute on Aging; Queen Mary University of London; Wellcome; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Covariate; Overfitting; Nonparametric statistics; Neuroimaging; Computer science; Artificial intelligence; Imaging genetics; Interpretability; Dimensionality reduction; Curse of dimensionality; Machine learning; Mathematics; Econometrics; Psychology","score_opus":0.056628162743357746,"score_gpt":0.33561193653538707,"score_spread":0.2789837737920293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521607924","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9099994,0.00021017894,0.06003637,0.02630492,0.00011826412,0.002528559,0.00018738922,0.0005366571,0.00007827768],"genre_scores_gemma":[0.94446003,0.00032832875,0.04994655,0.0022906105,0.00020155936,0.00072308135,0.000032352633,0.000077817145,0.0019396544],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985037,0.000033105032,0.00031144355,0.00066600763,0.00018439691,0.0003013352],"domain_scores_gemma":[0.998733,0.00019234362,0.00012299845,0.00062667415,0.00013663853,0.00018837291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043770026,0.0002356924,0.0002863528,0.00009979922,0.0001883341,0.000023780338,0.00012374447,0.0000681629,0.000048894253],"category_scores_gemma":[0.000092065806,0.000156255,0.0000965136,0.00012657241,0.00013320976,0.000085278654,0.000092949376,0.00014667386,0.000013959594],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002353093,0.00014027924,0.0027407883,0.000055423945,0.0000122424835,0.000021515156,0.0000123299915,0.000002256271,0.9387988,0.0015475742,0.0053226445,0.051110834],"study_design_scores_gemma":[0.011077172,0.0012772656,0.58154994,0.00037305933,0.0003573217,0.00082061026,0.0000036090187,0.0017658006,0.2603018,0.015032745,0.12630427,0.0011364309],"about_ca_topic_score_codex":0.000007163705,"about_ca_topic_score_gemma":5.3349515e-7,"teacher_disagreement_score":0.678497,"about_ca_system_score_codex":0.000022728958,"about_ca_system_score_gemma":0.00003417483,"threshold_uncertainty_score":0.6371894},"labels":[],"label_agreement":null},{"id":"W2523274259","doi":"10.1002/hbm.23399","title":"Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET)","year":2016,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Tractography; Voxel; Diffusion MRI; Prior probability; Optic radiation; Artificial intelligence; Computer science; Loop (graph theory); White matter; Pattern recognition (psychology); Magnetic resonance imaging; Bayesian probability; Mathematics; Radiology; Medicine","score_opus":0.11054802625502137,"score_gpt":0.37362930450917187,"score_spread":0.2630812782541505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523274259","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6389398,0.00006637254,0.35841036,0.0012255047,0.000018488034,0.00047233523,0.00000875909,0.00016380362,0.00069462],"genre_scores_gemma":[0.95294464,0.000030604253,0.04602113,0.0004962575,0.000086201784,0.00003358833,0.000016613145,0.000034696353,0.00033628542],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989578,0.00003212311,0.00033435435,0.00029801947,0.00017476371,0.0002029532],"domain_scores_gemma":[0.99914575,0.00010296842,0.00019064161,0.00035384455,0.00015284921,0.000053964734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009635576,0.00014249934,0.00022165709,0.00016992743,0.00013625858,0.000006195899,0.00008470871,0.000056592253,0.00011749679],"category_scores_gemma":[0.00009869493,0.00011330853,0.00009962161,0.00037050238,0.0001533522,0.00015855144,0.000037959064,0.00011186392,0.0000031787745],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023720577,0.00009470331,0.0020333794,0.00004226636,0.000013782707,0.000003753447,0.00033273513,0.000003675182,0.98207563,0.0041113724,0.00038408418,0.0108809145],"study_design_scores_gemma":[0.010816774,0.0021335147,0.4578504,0.0045707203,0.00056075904,0.00027314047,0.0025871631,0.0033481366,0.2906771,0.038873907,0.1865011,0.001807281],"about_ca_topic_score_codex":0.000025019554,"about_ca_topic_score_gemma":0.0000019763904,"teacher_disagreement_score":0.6913985,"about_ca_system_score_codex":0.00005080084,"about_ca_system_score_gemma":0.000028122551,"threshold_uncertainty_score":0.46205878},"labels":[],"label_agreement":null},{"id":"W2523445319","doi":"10.1016/j.neuroimage.2016.09.018","title":"g-Ratio weighted imaging of the human spinal cord in vivo","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada","keywords":"Myelin; White matter; Axon; Spinal cord; Anatomy; Surface-area-to-volume ratio; Chemistry; Biology; Magnetic resonance imaging; Central nervous system; Medicine; Neuroscience; Radiology","score_opus":0.0545877705470188,"score_gpt":0.3621916563437483,"score_spread":0.3076038857967295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2523445319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9761121,0.00002753083,0.0060789585,0.009743882,0.0000563914,0.0005063532,0.000015150897,0.00014377554,0.0073158345],"genre_scores_gemma":[0.9969825,0.000014168818,0.0013908828,0.000693967,0.000037614533,0.000023659833,5.458449e-7,0.000020632595,0.0008359851],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992441,0.000026454501,0.00021960879,0.00022228896,0.00013771578,0.00014984893],"domain_scores_gemma":[0.99928004,0.000034159748,0.0000904914,0.00051379914,0.000045462126,0.00003605671],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005703227,0.00009246996,0.00013694733,0.000066763714,0.000054067383,0.000005219723,0.00015615414,0.000016411312,0.000068417816],"category_scores_gemma":[0.000055302276,0.000053717213,0.000060936894,0.00021556045,0.00015140825,0.00007249798,0.00007645694,0.00012723984,0.000005348062],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036057725,0.00006664996,0.047717765,0.000012930897,0.0000010807711,0.000016915477,0.000006921811,5.9094575e-8,0.9413536,0.0034193639,0.0012347086,0.00613392],"study_design_scores_gemma":[0.0011469725,0.00022703527,0.44359633,0.0002830506,0.00002416712,0.00010009596,0.000008480409,0.000102683276,0.5288949,0.0049355044,0.020543963,0.00013679781],"about_ca_topic_score_codex":0.000012331647,"about_ca_topic_score_gemma":0.0000026015482,"teacher_disagreement_score":0.41245872,"about_ca_system_score_codex":0.000024768508,"about_ca_system_score_gemma":0.000022795697,"threshold_uncertainty_score":0.21905243},"labels":[],"label_agreement":null},{"id":"W2526156408","doi":"10.3389/fnana.2016.00092","title":"An In vivo Multi-Modal Structural Template for Neonatal Piglets Using High Angular Resolution and Population-Based Whole-Brain Tractography","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Hospital for Sick Children; Toronto Rehabilitation Institute; SickKids Foundation; University Health Network; University of Toronto; Ontario Brain Institute","funders":"Fondation Brain Canada","keywords":"White matter; Diffusion MRI; Neuroimaging; Population; Metric (unit); Tractography; Segmentation; Artificial intelligence; Computer science; Pattern recognition (psychology); Neuroscience; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.028897425410416795,"score_gpt":0.33080834011038973,"score_spread":0.30191091469997294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526156408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7368017,0.00007067192,0.26062655,0.001550108,0.00010060747,0.00067615754,0.00009015272,0.000082764884,0.0000012831733],"genre_scores_gemma":[0.8115523,0.000004006142,0.18797544,0.0002978271,0.000032660962,0.00005483966,0.000039136183,0.000032603624,0.000011193466],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988423,0.000047836962,0.00027392295,0.00044254228,0.00012295633,0.0002704424],"domain_scores_gemma":[0.9994225,0.00006708292,0.00009267797,0.00028559208,0.000034895103,0.000097281365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009758652,0.00016742482,0.00023959148,0.00044476497,0.00008383237,0.0000155663,0.000091385555,0.00008267011,0.0000031595423],"category_scores_gemma":[0.00006333268,0.00014257141,0.000053268082,0.00029637973,0.00008527486,0.0002463097,0.000015522217,0.00014211003,8.89346e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004673007,0.00011859052,0.8877318,0.00007301524,0.000011088539,0.00007103613,0.00007709938,0.0005916144,0.086494,0.00042868208,0.00096695335,0.022968838],"study_design_scores_gemma":[0.007845153,0.00028022903,0.70420825,0.00022241939,0.000044173736,0.00005546624,0.00004943164,0.2657155,0.0074762627,0.0066767624,0.0069607836,0.00046557604],"about_ca_topic_score_codex":0.00016310364,"about_ca_topic_score_gemma":0.000033579865,"teacher_disagreement_score":0.26512387,"about_ca_system_score_codex":0.000083645646,"about_ca_system_score_gemma":0.000030178435,"threshold_uncertainty_score":0.58138937},"labels":[],"label_agreement":null},{"id":"W2526742587","doi":"10.1007/978-3-319-46720-7_21","title":"Predictive Subnetwork Extraction with Structural Priors for Infant Connectomes","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hospital for Sick Children; University of Toronto; Child and Family Research Institute; Simon Fraser University","funders":"","keywords":"Connectome; Subnetwork; Computer science; Prior probability; Artificial intelligence; Constraint (computer-aided design); Diffusion MRI; Pattern recognition (psychology); Machine learning; Functional connectivity; Neuroscience; Mathematics; Psychology; Bayesian probability","score_opus":0.029243037323431285,"score_gpt":0.3256026376107184,"score_spread":0.2963596002872871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526742587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009769029,0.000106357285,0.9955152,0.0009408837,0.00022276134,0.0012572313,0.000024086014,0.00017814728,0.00077838387],"genre_scores_gemma":[0.5893197,0.00005865719,0.40815127,0.00083915965,0.0008581748,0.00009597019,0.000019373749,0.00006449316,0.00059318176],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99842936,0.00000461068,0.00022242978,0.0007296639,0.0003089971,0.00030494347],"domain_scores_gemma":[0.99865156,0.0003533888,0.00019008924,0.00049391465,0.00021711133,0.000093944334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012483059,0.00027448247,0.00033087863,0.000235481,0.00014955616,0.000038538696,0.00025490165,0.00013169147,0.000011853288],"category_scores_gemma":[0.00004492976,0.00017832186,0.0000629153,0.00014979664,0.000564563,0.00014249946,0.000088250345,0.00036141174,0.0000017632525],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074691727,0.000035276957,0.0031306338,0.0002014935,0.00006755368,0.00008112208,0.0005171505,0.00743426,0.0026931467,0.030960567,0.00012315258,0.9540087],"study_design_scores_gemma":[0.0041688317,0.004769688,0.010048312,0.00580499,0.0003114433,0.0017772667,0.0000013577993,0.20136017,0.023308279,0.7118715,0.034270395,0.0023077475],"about_ca_topic_score_codex":0.0000022350675,"about_ca_topic_score_gemma":0.000008496571,"teacher_disagreement_score":0.951701,"about_ca_system_score_codex":0.0001820658,"about_ca_system_score_gemma":0.0002161168,"threshold_uncertainty_score":0.7271754},"labels":[],"label_agreement":null},{"id":"W2527824541","doi":"","title":"Group sparse kernelized dictionary learning for the clustering of white matter fibers","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Kernel (algebra); Cluster analysis; Outlier; Fiber bundle; Feature (linguistics); Sparse approximation; Dictionary learning; Feature learning; Fiber; Mathematics","score_opus":0.04612359615896681,"score_gpt":0.32267024458182375,"score_spread":0.2765466484228569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2527824541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01051397,0.000014786319,0.9792261,0.0048857257,0.000028555813,0.0003709705,0.000001065468,0.000126289,0.004832533],"genre_scores_gemma":[0.91176057,0.000025595995,0.08160819,0.0014444747,0.000071430884,0.00011908595,0.000010435263,0.000020347505,0.004939889],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996096,0.000009034487,0.000122040066,0.000113999806,0.000059116006,0.00008621088],"domain_scores_gemma":[0.9995783,0.00013035854,0.000050049242,0.00018896062,0.000028731965,0.000023595849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009371155,0.000054795462,0.00009447552,0.000023543702,0.00011790022,0.0000032154965,0.000051987892,0.000017951574,0.00011864778],"category_scores_gemma":[0.000021888942,0.00003600706,0.000055785957,0.00005146902,0.00003865438,0.000026851088,0.000049331713,0.00008403265,0.000006693134],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015131196,0.00060825335,0.6033394,0.0009603191,0.0002561601,0.0000036621784,0.001472988,0.0144981835,0.13130821,0.032320052,0.1063781,0.107341595],"study_design_scores_gemma":[0.002106548,0.0003791524,0.1346354,0.00013504473,0.00016759199,0.0000765381,0.00018930134,0.31790867,0.003116475,0.003594215,0.5374691,0.00022193881],"about_ca_topic_score_codex":0.000007244972,"about_ca_topic_score_gemma":8.981303e-7,"teacher_disagreement_score":0.9012466,"about_ca_system_score_codex":0.0000076941915,"about_ca_system_score_gemma":0.0000029919104,"threshold_uncertainty_score":0.14683253},"labels":[],"label_agreement":null},{"id":"W2528727157","doi":"10.1016/j.neuroimage.2016.10.009","title":"SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":628,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Spinal cord; Computer science; Software; Neuroimaging; Standardization; Medicine; Toolbox","score_opus":0.21217250137722327,"score_gpt":0.44659657430929695,"score_spread":0.23442407293207368,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528727157","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024300534,0.000121702,0.9625774,0.0085768765,0.00010617814,0.002214607,0.0003195719,0.0010505226,0.0007325937],"genre_scores_gemma":[0.50115097,0.00010174829,0.486278,0.0062460224,0.0007304639,0.00042677374,0.00032614789,0.00028353053,0.004456362],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978075,0.000030641644,0.000356219,0.0011026192,0.00025050397,0.00045249186],"domain_scores_gemma":[0.9973196,0.000063535,0.00019580554,0.001954282,0.00022343973,0.0002433769],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021931906,0.00026920295,0.00034240916,0.00008557503,0.0003093094,0.00015758805,0.0012924966,0.00006320913,0.000041272564],"category_scores_gemma":[0.0004470703,0.00020649403,0.00004617948,0.0002694307,0.00019439335,0.0009832532,0.00063477823,0.00022909741,0.000029577172],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033357025,0.00031540284,0.00089129905,0.00014786403,0.0000060362304,0.00005443521,0.0000054287293,3.7271695e-7,0.05471877,0.00034073275,0.01469207,0.92549187],"study_design_scores_gemma":[0.0030393451,0.010984346,0.01775786,0.0007550306,0.00016267537,0.0006685414,0.000024603269,0.0010841786,0.0075287945,0.0018185971,0.95555764,0.00061840186],"about_ca_topic_score_codex":0.000012303156,"about_ca_topic_score_gemma":0.0000032025062,"teacher_disagreement_score":0.9408656,"about_ca_system_score_codex":0.0000419523,"about_ca_system_score_gemma":0.00016982507,"threshold_uncertainty_score":0.84205824},"labels":[],"label_agreement":null},{"id":"W2528967587","doi":"10.1016/j.artmed.2016.09.003","title":"Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm","year":2016,"lang":"en","type":"article","venue":"Artificial Intelligence in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Computer science; Artificial intelligence; Segmentation; Pattern recognition (psychology); Diffusion MRI; Spectral clustering; DBSCAN; Fiber bundle; Fuzzy clustering; Algorithm; CURE data clustering algorithm; Bundle","score_opus":0.15710639887640207,"score_gpt":0.4112737736595068,"score_spread":0.2541673747831047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528967587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21706405,0.000048495214,0.7758928,0.006491852,0.000040023482,0.00031431884,0.000010483696,0.000110446716,0.000027509303],"genre_scores_gemma":[0.76899064,0.000048512524,0.23009016,0.00063786854,0.00010843655,0.0000062886666,0.000028999884,0.000023267745,0.00006581753],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878186,0.000030574432,0.00046636548,0.00036246865,0.000183121,0.00017561537],"domain_scores_gemma":[0.99910957,0.00013157199,0.00013870296,0.00045318226,0.0000772364,0.0000897109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024196517,0.00013047563,0.00025462278,0.00018161804,0.00007021142,0.000006232343,0.00012249772,0.000034540135,0.0001899067],"category_scores_gemma":[0.00013204322,0.00009078233,0.000016158887,0.0002491184,0.00021901685,0.0001520649,0.00017006192,0.00009006641,0.0000075510366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011555021,0.00012288587,0.14227459,0.0000777146,0.000008096715,0.00003130893,0.00042635255,0.0000902076,0.30245474,0.000032444947,0.00048432592,0.5538818],"study_design_scores_gemma":[0.0002825835,0.00008115085,0.025295768,0.0012748119,0.00006952586,0.00007491701,0.00029081426,0.9332759,0.037411105,0.0016205709,0.00017537115,0.00014748871],"about_ca_topic_score_codex":0.00036274476,"about_ca_topic_score_gemma":0.000029503597,"teacher_disagreement_score":0.9331857,"about_ca_system_score_codex":0.00004820738,"about_ca_system_score_gemma":0.000037048238,"threshold_uncertainty_score":0.3701996},"labels":[],"label_agreement":null},{"id":"W2528977329","doi":"10.1038/srep32833","title":"In-vivo Dynamics of the Human Hippocampus across the Menstrual Cycle","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":167,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; Douglas Mental Health University Institute","funders":"Max-Planck-Gesellschaft","keywords":"Hippocampal formation; Menstrual cycle; Estrogen; Hippocampus; Neuroimaging; Hormone; Neuroscience; Neuroplasticity; Fractional anisotropy; Sexual dimorphism; Ovulation; Physiology; Human brain; Biology; Medicine; Endocrinology; Internal medicine; Psychology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.027306205042633737,"score_gpt":0.3493622372302128,"score_spread":0.32205603218757906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2528977329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.991699,0.00001086364,0.0004775418,0.005300826,0.0006946159,0.00033831652,0.000007230504,0.00003829079,0.0014333467],"genre_scores_gemma":[0.9946783,0.0000018888935,0.0002954527,0.0000876484,0.000022754233,0.000025096077,0.0000014693754,0.0000088210145,0.004878533],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989838,0.000015787597,0.00029045268,0.00029387552,0.00024458172,0.00017148242],"domain_scores_gemma":[0.9985263,0.000028881645,0.00019776331,0.0011441401,0.00007134267,0.000031597694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005115697,0.00006401417,0.000100385834,0.00002584918,0.00023597802,0.000018781315,0.00014616645,0.000025111696,0.000038715538],"category_scores_gemma":[0.00008627837,0.00002810483,0.00006406643,0.00030518923,0.00064814015,0.0000560293,0.0001210102,0.00008285235,0.0000018084028],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008939257,0.0002512173,0.18349592,0.000037461934,0.00001307155,0.00015106346,0.0006387383,0.000015641544,0.7591312,0.011700094,0.026541494,0.018015169],"study_design_scores_gemma":[0.0004115218,0.000037639602,0.035285905,0.00024213183,0.000027653383,0.0010505994,0.00020343077,0.0001739317,0.311707,0.585791,0.06489923,0.00016999316],"about_ca_topic_score_codex":0.000016991002,"about_ca_topic_score_gemma":0.000047254696,"teacher_disagreement_score":0.5740909,"about_ca_system_score_codex":0.00005175566,"about_ca_system_score_gemma":0.000045003613,"threshold_uncertainty_score":0.23880994},"labels":[],"label_agreement":null},{"id":"W2529768151","doi":"10.7759/cureus.817","title":"Interhemispheric Difference Images from Postoperative Diffusion Tensor Imaging of Gliomas","year":2016,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"Organisation Canadienne des Physiciens Médicaux; Canadian Association of Radiation Oncology; American Association of Physicists in Medicine","keywords":"Medicine; Diffusion MRI; Nuclear medicine; Fractional anisotropy; Magnetic resonance imaging; Voxel; Glioma; Nuclear magnetic resonance; Radiology; Physics","score_opus":0.036998995925060334,"score_gpt":0.3273018284625544,"score_spread":0.29030283253749406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2529768151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91312635,0.00048364387,0.080395915,0.004137539,0.000041831834,0.00023281093,0.000060591043,0.00017068587,0.0013506552],"genre_scores_gemma":[0.9839625,0.00019466534,0.014702522,0.0002696709,0.000039877956,0.000026449468,0.000007467962,0.000017828817,0.00077904726],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993753,0.000011572951,0.00016376273,0.0002324768,0.00009718565,0.00011973684],"domain_scores_gemma":[0.99932086,0.00008279853,0.00007500767,0.0003605736,0.000100369216,0.000060357128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000019367337,0.000106953186,0.00017588264,0.000020837235,0.000034016324,0.0000052199753,0.00011037492,0.000022559618,0.00017348166],"category_scores_gemma":[0.00009630292,0.000064537606,0.000050214767,0.000083506406,0.00012036574,0.00006246409,0.00008666098,0.000063988475,0.000010518162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029145718,0.00008067521,0.04772109,0.000004933516,0.0000054981456,0.000008619932,0.000070890754,3.2485495e-8,0.92847645,0.0001999125,0.000702645,0.022700123],"study_design_scores_gemma":[0.000911474,0.00012688064,0.26064005,0.00040648872,0.000051362793,0.000040339888,0.00011357015,0.00015439338,0.73053354,0.003310797,0.0035314646,0.00017964878],"about_ca_topic_score_codex":0.000056009892,"about_ca_topic_score_gemma":0.0000012630074,"teacher_disagreement_score":0.21291895,"about_ca_system_score_codex":0.000036555917,"about_ca_system_score_gemma":0.000015667323,"threshold_uncertainty_score":0.26317674},"labels":[],"label_agreement":null},{"id":"W2531143546","doi":"10.3389/fnana.2016.00096","title":"Merged Group Tractography Evaluation with Selective Automated Group Integrated Tractography","year":2016,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; Krembil Foundation; University of Toronto","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; European Genomic Institute for Diabetes","keywords":"Tractography; Decussation; Artificial intelligence; Diffusion MRI; Computer science; Human Connectome Project; Neuroanatomy; Pattern recognition (psychology); Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.022463696182611948,"score_gpt":0.3081746143063434,"score_spread":0.28571091812373145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531143546","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7310872,0.00051323365,0.2544924,0.0027043177,0.00042206506,0.004245611,0.000058502046,0.0034737552,0.003002906],"genre_scores_gemma":[0.9587345,0.00019908971,0.039951522,0.00036612106,0.000030126497,0.00055371097,0.00006181923,0.000072349874,0.00003073262],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997904,0.00016021729,0.00037485064,0.0006849332,0.00046729925,0.00040872098],"domain_scores_gemma":[0.9988862,0.00007236957,0.00017725867,0.0004811172,0.00022547247,0.00015753832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027537846,0.00030909144,0.0004009795,0.0008806059,0.00009131854,0.000019324245,0.0001787814,0.00011301093,0.00002919926],"category_scores_gemma":[0.00009044547,0.0002056824,0.00013568011,0.0022853897,0.0002119402,0.00030711922,0.0000195105,0.00039867783,0.0000033852866],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018989601,0.0019176954,0.6673615,0.000076024124,0.00033858273,0.00018299304,0.00024919008,0.000021749278,0.065800786,0.0012352617,0.061458122,0.1994591],"study_design_scores_gemma":[0.011947312,0.0018662296,0.8907966,0.000650976,0.00060172525,0.00023678668,0.00026848895,0.020069154,0.010830294,0.0068733804,0.054758295,0.0011007529],"about_ca_topic_score_codex":0.000026718644,"about_ca_topic_score_gemma":0.000015834186,"teacher_disagreement_score":0.22764732,"about_ca_system_score_codex":0.00013925738,"about_ca_system_score_gemma":0.000068469155,"threshold_uncertainty_score":0.83874846},"labels":[],"label_agreement":null},{"id":"W2531371400","doi":"10.1111/adb.12466","title":"Progressive white matter impairment as a predictor of outcome in a cohort of opioid‐dependent patient's post‐detoxification","year":2016,"lang":"en","type":"article","venue":"Addiction Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"Trinity College Dublin","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Grey matter; Psychology; Internal medicine; Opioid; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.020075453226041734,"score_gpt":0.3270657382763677,"score_spread":0.306990285050326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2531371400","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935823,0.000056076748,0.0025631422,0.0021929326,0.000055978788,0.0009549735,0.00012424882,0.000056666082,0.00041365158],"genre_scores_gemma":[0.9977541,0.00004514803,0.0014010306,0.00024280965,0.000018305764,0.00032424871,0.000060307484,0.0000107066035,0.00014333012],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990913,0.00003597638,0.00043447188,0.00022826431,0.00008543152,0.00012450329],"domain_scores_gemma":[0.9992233,0.000036111487,0.00027539628,0.0002849636,0.00013912008,0.000041146097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007296065,0.000087061904,0.00021303538,0.00014379897,0.000013988198,9.695915e-7,0.000059423928,0.00007729861,0.0004111669],"category_scores_gemma":[0.000044657623,0.000058502552,0.00004942523,0.00011200191,0.00011469181,0.000042396365,0.00003789604,0.00006802936,0.000020130788],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010707462,0.0002228713,0.932524,0.000016517428,0.00001888402,0.0000019502459,0.000065072876,3.9430208e-7,0.06329795,0.00044357995,0.00021099663,0.0030906964],"study_design_scores_gemma":[0.00071594416,0.00093484105,0.9664194,0.00009904009,0.000033821227,0.000047883404,0.000025425814,0.000012611744,0.029681064,0.0007383677,0.0012292077,0.00006237631],"about_ca_topic_score_codex":0.000029854755,"about_ca_topic_score_gemma":0.000001310219,"teacher_disagreement_score":0.033895403,"about_ca_system_score_codex":0.00006242728,"about_ca_system_score_gemma":0.00003094187,"threshold_uncertainty_score":0.45019892},"labels":[],"label_agreement":null},{"id":"W2534746602","doi":"10.1016/j.jalz.2016.06.1901","title":"P3‐239: Asymmetrically Low White Matter Integrity in Seniors with Mci and POOR GAIT","year":2016,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials; Parkwood Institute","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Corticospinal tract; Gait; Population; Tractography; Medicine; Neuroscience; Radiology","score_opus":0.03327758752587061,"score_gpt":0.3056207425326355,"score_spread":0.27234315500676487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2534746602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75699764,0.010546467,0.10334962,0.11329353,0.00015198808,0.0031726493,0.000081856524,0.0007904606,0.011615756],"genre_scores_gemma":[0.9603663,0.00008541392,0.037171144,0.0021444703,0.000029671051,0.00006991441,0.0000069609896,0.000029568995,0.000096520685],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990178,0.000020999732,0.00020962115,0.00035082825,0.0001596491,0.0002411402],"domain_scores_gemma":[0.9994143,0.00004551022,0.00006503695,0.0003107145,0.00005443009,0.00010998852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009912326,0.00015071499,0.00019004948,0.00014303582,0.00004018359,0.00001679559,0.00009563894,0.00005074871,0.00019540005],"category_scores_gemma":[0.000013176095,0.000094444265,0.00003134423,0.00027570536,0.00010199097,0.000115476236,0.00007802113,0.00018301386,0.00008659895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016652037,0.0002896032,0.89251703,0.000013952372,0.0008042998,0.000055749326,0.000052641626,3.0736692e-7,0.009447221,0.00053412636,0.015737731,0.08038084],"study_design_scores_gemma":[0.0036156005,0.000551819,0.88795245,0.0003795041,0.004558235,0.00023890495,0.00004624896,0.00011387112,0.04277668,0.0014838075,0.05762217,0.0006607184],"about_ca_topic_score_codex":0.00003093578,"about_ca_topic_score_gemma":0.000013143969,"teacher_disagreement_score":0.20336866,"about_ca_system_score_codex":0.000007666971,"about_ca_system_score_gemma":0.000023506287,"threshold_uncertainty_score":0.38513252},"labels":[],"label_agreement":null},{"id":"W2537773907","doi":"10.1088/0031-9155/61/21/7765","title":"On the averaging of cardiac diffusion tensor MRI data: the effect of distance function selection","year":2016,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Biological and Environmental Research; National Institute of Biomedical Imaging and Bioengineering; Imperial College London; Office of Science; National Institutes of Health; National Institute for Health and Care Research; U.S. Department of Energy","keywords":"Diffusion MRI; Tensor (intrinsic definition); Euclidean distance; Context (archaeology); Mathematics; Voxel; Function (biology); Mathematical analysis; Computer science; Magnetic resonance imaging; Algorithm; Artificial intelligence; Geometry; Medicine; Radiology","score_opus":0.16060116566896776,"score_gpt":0.405546470237325,"score_spread":0.24494530456835722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2537773907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8825008,0.0003455958,0.102478504,0.01352871,0.00010278732,0.00058206235,0.000021109416,0.000027010168,0.00041336138],"genre_scores_gemma":[0.9988934,0.0006480773,0.00006044576,0.0002056592,0.00013418403,0.000020114523,0.000012289959,0.000004392333,0.000021453216],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995522,0.000070063186,0.00011851977,0.0001453529,0.000047697486,0.00006616053],"domain_scores_gemma":[0.9988461,0.000756819,0.00007832949,0.00028397687,0.0000246797,0.0000100997995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000261942,0.000059875576,0.00018208033,0.000019576393,0.000035678153,4.3643547e-7,0.00006815638,0.000020510726,0.000003050256],"category_scores_gemma":[0.00013356961,0.00002079695,0.000016247272,0.000125484,0.0002436729,0.000017177754,0.000039998406,0.0000948911,2.8980025e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004465047,0.00005825492,0.15985784,0.00008144563,0.00003590994,2.3575488e-7,0.00008684372,0.0000027282717,0.5700432,0.055548787,0.0028452405,0.21099299],"study_design_scores_gemma":[0.008108339,0.016587658,0.29783198,0.0038776058,0.0010563405,0.000033527514,0.00035405692,0.0070315194,0.26915172,0.25766674,0.13773063,0.0005698537],"about_ca_topic_score_codex":0.000020697491,"about_ca_topic_score_gemma":0.0000010219308,"teacher_disagreement_score":0.3008915,"about_ca_system_score_codex":0.000008054035,"about_ca_system_score_gemma":0.0000046300147,"threshold_uncertainty_score":0.0897823},"labels":[],"label_agreement":null},{"id":"W2538167484","doi":"","title":"Loss of callosal fibre integrity in healthy elderly with age-related white matter changes Martin GriebeAlex ForsterMichele WessaChristina RossmanithHansjorg Bazner • Tamara SauerKathrin ZohselChristian BlahakAndrea V. KingJulia Linke • Michael G. HennericiAchim GassKristina Szabo","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Corpus callosum; Magnetic resonance imaging; Psychology; Fractional anisotropy; Cognition; Diffusion MRI; Atrophy; Cognitive impairment; Audiology; Medicine; Cardiology; Neuroscience; Internal medicine; Radiology","score_opus":0.05316479166702132,"score_gpt":0.30253032504803157,"score_spread":0.24936553338101025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2538167484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9689719,0.00017683479,0.013247926,0.007026622,0.00009079249,0.0019248839,0.00010403514,0.0005458776,0.0079111],"genre_scores_gemma":[0.9568279,0.000097555654,0.038586423,0.0014048096,0.00008660657,0.00024410235,0.00016847272,0.00013450657,0.0024496543],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99672997,0.00011865133,0.0009814193,0.000928855,0.00041457274,0.0008265223],"domain_scores_gemma":[0.99788517,0.00007484132,0.00052631303,0.00095082243,0.00023954976,0.00032330528],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036271746,0.00058413326,0.00095412025,0.00034742555,0.0001452325,0.000030420824,0.0004305121,0.0003021198,0.00037175108],"category_scores_gemma":[0.000037721424,0.0004720431,0.00014107309,0.0007493482,0.00060430204,0.00016336689,0.00018873852,0.0012158491,0.000042076816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022437489,0.0014545519,0.98205227,0.0007313733,0.000074095544,0.00064159563,0.0022620377,0.000005683806,0.0023549884,0.0010108405,0.0046633505,0.002505487],"study_design_scores_gemma":[0.006283852,0.005281572,0.96678454,0.0017219593,0.00030743965,0.0011278492,0.0006400083,0.0009063447,0.0067804325,0.0020344772,0.006737747,0.0013937687],"about_ca_topic_score_codex":0.0023001076,"about_ca_topic_score_gemma":0.0024467616,"teacher_disagreement_score":0.025338497,"about_ca_system_score_codex":0.0001238987,"about_ca_system_score_gemma":0.00012943594,"threshold_uncertainty_score":0.99977314},"labels":[],"label_agreement":null},{"id":"W2539797428","doi":"10.1212/wnl.0000000000003373","title":"Cerebrovascular reactivity and white matter integrity","year":2016,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; Sunnybrook Health Science Centre","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Cerebral blood flow; Medicine; Leukoaraiosis; Bonferroni correction; Perfusion; Cardiology; Magnetic resonance imaging; Internal medicine; Nuclear medicine; Radiology; Mathematics","score_opus":0.03989864370391906,"score_gpt":0.3173514247816232,"score_spread":0.27745278107770416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2539797428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9240762,0.00000920179,0.011699856,0.061767038,0.000026562751,0.00014633132,0.0000031492375,0.00012292154,0.0021487433],"genre_scores_gemma":[0.9910276,0.00005602008,0.0017697688,0.006778348,0.000041099956,0.000023445298,8.738738e-7,0.000012783403,0.00029007863],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99950665,0.000026045464,0.000071708724,0.0002350223,0.000042585798,0.00011800763],"domain_scores_gemma":[0.9995592,0.000050821167,0.000024574558,0.00029335677,0.000020880543,0.000051143077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004468042,0.000065318716,0.00011649585,0.00003288969,0.000026071733,0.0000024173426,0.00003698301,0.000053520613,0.0001032785],"category_scores_gemma":[0.00002606851,0.00004197644,0.000028721892,0.000038753125,0.000103282706,0.000039382172,0.000050596467,0.00018081897,0.000056247336],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008612497,0.000055597735,0.9420958,0.000009687117,0.0000060286498,0.000016010703,0.000008308518,2.8378505e-8,0.042591054,0.0008086977,0.003294962,0.011027664],"study_design_scores_gemma":[0.00037789546,0.00021050154,0.89470434,0.0000058842684,0.000017167324,0.00048996846,2.681758e-7,0.000009487249,0.0028122533,0.0032414393,0.09807745,0.00005333603],"about_ca_topic_score_codex":0.000009098511,"about_ca_topic_score_gemma":0.0000020913217,"teacher_disagreement_score":0.094782494,"about_ca_system_score_codex":0.0000046739424,"about_ca_system_score_gemma":0.0000071034647,"threshold_uncertainty_score":0.17117496},"labels":[],"label_agreement":null},{"id":"W2541603500","doi":"10.1016/b978-0-12-801942-9.00003-3","title":"Imaging Approaches to Cerebral Cortex Pathology","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Centre; Western University","funders":"","keywords":"Positron emission tomography; Neurodegeneration; Disease; Magnetic resonance imaging; Neuroscience; Neuroimaging; Medicine; Drug development; Drug trial; Pathology; Clinical trial; Psychology; Drug; Radiology; Pharmacology","score_opus":0.1395140268724563,"score_gpt":0.3275713256474919,"score_spread":0.18805729877503563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2541603500","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024540665,0.00028124382,0.00076486997,0.0021293492,0.00011298418,0.0012135815,0.000044230554,0.0003174026,0.9951118],"genre_scores_gemma":[0.0025150618,0.000035787973,0.018413378,0.002151119,0.00041870543,0.00017341784,0.000060527804,0.00015856675,0.97607344],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984242,0.000008486005,0.00032904075,0.00072307617,0.00019438153,0.00032085186],"domain_scores_gemma":[0.99789333,0.000023102477,0.00024787756,0.0015453415,0.000061048806,0.00022930719],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010688966,0.0003941815,0.000606168,0.0001633009,0.00019898162,0.000036774312,0.000327892,0.00016848359,0.000066339606],"category_scores_gemma":[0.000025261876,0.0003720021,0.00022065533,0.000005451102,0.00023381412,0.000029181625,0.00026777518,0.0006195527,0.00021893512],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017306007,0.000011237948,0.000070251685,0.000055214055,0.00002177314,0.00021407308,0.00005324147,1.0818077e-7,0.00015715632,0.022548812,0.000785488,0.97606534],"study_design_scores_gemma":[0.00022525464,0.000060678904,0.00034420553,0.00032896132,0.0001535109,0.00051708485,0.0000024243548,0.000016593334,0.00010253538,0.03169816,0.9662143,0.0003363092],"about_ca_topic_score_codex":2.7936863e-7,"about_ca_topic_score_gemma":0.0000020974765,"teacher_disagreement_score":0.97572905,"about_ca_system_score_codex":0.00007195325,"about_ca_system_score_gemma":0.00008838118,"threshold_uncertainty_score":0.9998732},"labels":[],"label_agreement":null},{"id":"W2542536236","doi":"10.1503/jpn.150341","title":"Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging","year":2017,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":154,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Yale University","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Superior longitudinal fasciculus; Major depressive disorder; Medicine; Internal medicine; Cardiology; Meta-analysis; Neuroscience; Audiology; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Magnetic resonance imaging","score_opus":0.05634473385502789,"score_gpt":0.37672600299123216,"score_spread":0.32038126913620424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2542536236","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00036337884,0.9958405,0.00022341406,0.002387029,0.000040654297,0.0010415305,0.00009252344,0.0000056332074,0.0000053449116],"genre_scores_gemma":[0.0007108383,0.9967768,0.0016406309,0.0007519007,0.000010690283,0.00004443709,0.0000061389433,0.000015152231,0.000043373762],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99798256,0.00013568286,0.0010897041,0.00030492115,0.0003483707,0.00013873065],"domain_scores_gemma":[0.99618113,0.00015924474,0.0027826529,0.0006271576,0.00014492986,0.00010488533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003766687,0.00024962562,0.0032028737,0.0004249503,0.00013792251,0.000035631125,0.00042438722,0.00003982035,0.0000034129678],"category_scores_gemma":[0.0005265138,0.00013356145,0.0004691136,0.0004251474,0.00031676947,0.00021008054,0.000112807946,0.00032856085,3.908471e-8],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003858488,0.0004053499,0.051825415,0.9371396,0.0052017304,0.000033525575,0.0000794664,0.0000011057998,0.000007185716,0.0003176081,0.00026558392,0.004684855],"study_design_scores_gemma":[0.00114089,0.00034326394,0.026707182,0.099555984,0.8635742,0.0013482014,0.000034054487,0.00003369544,8.523252e-7,0.00033305114,0.0064971293,0.0004314708],"about_ca_topic_score_codex":0.0000069896228,"about_ca_topic_score_gemma":0.0000062047843,"teacher_disagreement_score":0.8583725,"about_ca_system_score_codex":0.000011798631,"about_ca_system_score_gemma":0.00011510922,"threshold_uncertainty_score":0.5446478},"labels":[],"label_agreement":null},{"id":"W2543407163","doi":"10.1089/neu.2016.4591","title":"Microstructural Integrity of Hippocampal Subregions Is Impaired after Mild Traumatic Brain Injury","year":2016,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hôpital du Sacré-Cœur de Montréal; Western University; McGill University; Douglas Mental Health University Institute; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Traumatic brain injury; Hippocampal formation; Neuroscience; Psychology; Structural integrity; Medicine; Psychiatry","score_opus":0.14861186423520872,"score_gpt":0.39846187009210043,"score_spread":0.2498500058568917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2543407163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96954024,0.000077522935,0.0030043626,0.026933387,0.000082308885,0.00024240887,0.000044441324,0.000033617413,0.000041726846],"genre_scores_gemma":[0.9921918,0.00007869408,0.005741918,0.001702519,0.00012926232,0.000009033745,5.312005e-7,0.000028160022,0.00011808698],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986668,0.00005113117,0.0006615449,0.0001639572,0.0002542689,0.00020228652],"domain_scores_gemma":[0.99867165,0.00014625773,0.00043756416,0.00035198175,0.00022420319,0.0001683703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013848204,0.00016342317,0.00039853243,0.00018383711,0.000036335085,0.000009300241,0.00018982694,0.000067352295,0.00011043065],"category_scores_gemma":[0.00015130124,0.00010051938,0.0003043053,0.00019385632,0.00023672053,0.00016616314,0.00003522889,0.00039569856,0.0000046361597],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015471802,0.00042883368,0.025402492,0.00015074677,0.00008483154,0.0001392432,0.0007462213,2.5630297e-7,0.86753124,0.00027499846,0.027806537,0.075887434],"study_design_scores_gemma":[0.0035708188,0.002630443,0.65329605,0.0014126231,0.00024299062,0.0039189574,0.00011286304,0.00003213398,0.31036332,0.013846382,0.010210259,0.00036315914],"about_ca_topic_score_codex":0.0000045006677,"about_ca_topic_score_gemma":9.725186e-7,"teacher_disagreement_score":0.62789357,"about_ca_system_score_codex":0.000047323563,"about_ca_system_score_gemma":0.000075448675,"threshold_uncertainty_score":0.40990615},"labels":[],"label_agreement":null},{"id":"W2544700523","doi":"10.1109/iembs.1996.652733","title":"Improved T/sub 2/ and diffusion maps from wavelet de-noised magnetic resonance imaging data","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital","funders":"","keywords":"Wavelet; Noise (video); Diffusion; Magnetic resonance imaging; Relaxation (psychology); Artificial intelligence; Image (mathematics); Base (topology); Computer science; Wavelet transform; Nuclear magnetic resonance; Diffusion MRI; Computer vision; Algorithm; Pattern recognition (psychology); Mathematics; Physics; Mathematical analysis","score_opus":0.053766825350059805,"score_gpt":0.30204886396288044,"score_spread":0.24828203861282064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2544700523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7169469,0.025426976,0.17821519,0.05172828,0.00012841176,0.002804805,0.000818358,0.0025783284,0.02135274],"genre_scores_gemma":[0.78484184,0.0025955662,0.2052837,0.004373786,0.00014485893,0.000047865215,0.00020663333,0.00005219854,0.0024535505],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991429,0.000011475789,0.00014826313,0.00042117474,0.00008521402,0.00019099147],"domain_scores_gemma":[0.9989067,0.00005385615,0.000033409866,0.00087867555,0.000022826272,0.00010457768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049701997,0.00011172144,0.00013543153,0.000034467073,0.00007596312,0.000021126129,0.0001607609,0.000027714857,0.00017015696],"category_scores_gemma":[0.00005087871,0.000096846416,0.000016294753,0.000092186165,0.00006966321,0.0000944839,0.0002315472,0.00014404915,0.000011199669],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022927405,0.00012232654,0.007341051,0.000013397249,0.0000018151932,0.000030080355,0.00004976221,2.8828405e-8,0.38405898,0.00027253773,0.025366727,0.5827204],"study_design_scores_gemma":[0.0031459178,0.00014932317,0.080955304,0.00016721255,0.00011577125,0.00019759744,0.000067120665,0.5259294,0.024229702,0.0060912003,0.35847273,0.00047874707],"about_ca_topic_score_codex":0.00009082283,"about_ca_topic_score_gemma":0.0000049211967,"teacher_disagreement_score":0.58224165,"about_ca_system_score_codex":0.000019006697,"about_ca_system_score_gemma":0.0000071487348,"threshold_uncertainty_score":0.39492822},"labels":[],"label_agreement":null},{"id":"W254543832","doi":"10.1016/j.neuroimage.2015.05.034","title":"A reliable spatially normalized template of the human spinal cord — Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Agence Nationale de la Recherche; Centre National de la Recherche Scientifique; Aix-Marseille Université","keywords":"White matter; Gray (unit); Grey matter; Segmentation; Spinal cord; Artificial intelligence; Cartography; Neuroscience; Pattern recognition (psychology); Computer science; Psychology; Medicine; Nuclear medicine; Magnetic resonance imaging; Radiology; Geography","score_opus":0.06169969129582981,"score_gpt":0.3493579809373288,"score_spread":0.287658289641499,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W254543832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89964014,0.000011378304,0.09411309,0.0025052188,0.000028006225,0.0021394477,0.00009593083,0.00023136102,0.0012354144],"genre_scores_gemma":[0.92854977,0.0000012582885,0.06703816,0.0036727418,0.000023831564,0.0003464297,0.000056937235,0.000055365545,0.00025550154],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998482,0.000051525254,0.00051164685,0.0004150215,0.00030050013,0.00023930696],"domain_scores_gemma":[0.99853855,0.000028500639,0.00033311278,0.00073246896,0.00022568456,0.00014170149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012715944,0.00022777302,0.00033915514,0.00027263295,0.00017099801,0.000046088226,0.00019146787,0.000043219305,0.000073105],"category_scores_gemma":[0.00001185124,0.00017726577,0.000063611864,0.0006785311,0.00017750887,0.00014097408,0.000100536345,0.00020354286,0.00003588691],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017351778,0.00017383216,0.6273895,0.0002709113,0.00001754972,0.000011025988,0.000110162386,0.00044299604,0.36529827,0.000033450866,0.005988606,0.00009016799],"study_design_scores_gemma":[0.0021808967,0.00059256755,0.93654835,0.0004693344,0.00017263187,0.00014973627,0.0000705882,0.0014523593,0.054725595,0.00012170973,0.0031886536,0.00032757607],"about_ca_topic_score_codex":0.000094738716,"about_ca_topic_score_gemma":0.000007677106,"teacher_disagreement_score":0.31057268,"about_ca_system_score_codex":0.000039927945,"about_ca_system_score_gemma":0.00004945614,"threshold_uncertainty_score":0.7228688},"labels":[],"label_agreement":null},{"id":"W2550828940","doi":"10.1101/084137","title":"Tractography-based connectomes are dominated by false-positive connections","year":2016,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sleep & Circadian Network; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; China Scholarship Council; Deutsche Forschungsgemeinschaft; Université de Sherbrooke","keywords":"Tractography; Human Connectome Project; Ground truth; Diffusion MRI; Connectome; White matter; Computer science; Human brain; Artificial intelligence; Connectomics; Pattern recognition (psychology); Neuroscience; Functional connectivity; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.024448664433080247,"score_gpt":0.280448739986918,"score_spread":0.25600007555383775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550828940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75844485,0.0032212166,0.20589785,0.013992193,0.0008732761,0.0050746333,0.0068045855,0.0056108,0.00008061025],"genre_scores_gemma":[0.98734015,0.00026955848,0.00992678,0.001097886,0.00020542953,0.00093889557,0.000004021877,0.00020289942,0.0000143675925],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972499,0.00010174177,0.00053231796,0.0012267226,0.00033527796,0.00055403693],"domain_scores_gemma":[0.9964478,0.00025556746,0.00059378135,0.0015068242,0.00080528675,0.0003907283],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022590367,0.0006421878,0.00080161996,0.0004367394,0.00025152805,0.0000901609,0.00034457966,0.0005072538,0.00005737977],"category_scores_gemma":[0.00025605425,0.0005941198,0.0003359744,0.0006356039,0.00030362335,0.00009794238,0.00015543247,0.00093304104,0.00004086878],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000102151374,0.00055012427,0.011155163,0.00026950712,0.00020286455,0.00008178071,0.0000025878762,0.0000040831414,0.98028684,0.0014832398,0.005851676,0.000009976691],"study_design_scores_gemma":[0.001717368,0.00013026476,0.062786356,0.001689336,0.00041416974,1.332506e-7,0.0000027372703,0.00018663524,0.8931011,0.000037794307,0.038947254,0.000986827],"about_ca_topic_score_codex":0.000019797557,"about_ca_topic_score_gemma":6.312621e-7,"teacher_disagreement_score":0.22889534,"about_ca_system_score_codex":0.00024879666,"about_ca_system_score_gemma":0.00034185604,"threshold_uncertainty_score":0.999651},"labels":[],"label_agreement":null},{"id":"W2551579479","doi":"10.1016/j.jpeds.2016.10.034","title":"Cerebellar Microstructural Organization is Altered by Complications of Premature Birth: A Case-Control Study","year":2016,"lang":"en","type":"article","venue":"The Journal of Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Canadian Institutes of Health Research","keywords":"Splenium; Fractional anisotropy; Medicine; Corpus callosum; Diffusion MRI; Cerebellum; Cerebellar vermis; Anatomy; Cardiology; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.023529074554977183,"score_gpt":0.3055935792693921,"score_spread":0.28206450471441497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551579479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94740474,0.00036699945,0.045709573,0.0057269144,0.00004957402,0.00051764434,0.00018576044,0.000025648353,0.000013129573],"genre_scores_gemma":[0.9969027,0.00031896602,0.002209668,0.00027528865,0.00019187851,0.0000015804632,0.0000013171809,0.000019524694,0.00007907772],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991967,0.000052904397,0.00039214976,0.000079007856,0.00018412014,0.000095133124],"domain_scores_gemma":[0.99834377,0.00020273963,0.00053288566,0.00030992078,0.00054923,0.00006147987],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019099769,0.000088584464,0.00019251704,0.00007701169,0.000089573194,0.0000063842763,0.0001637593,0.0000352109,0.000029189116],"category_scores_gemma":[0.00015214294,0.000045746863,0.000045602956,0.0003540387,0.000048507776,0.00006552529,0.000027805392,0.00016042826,0.0000022077743],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033364218,0.0009617253,0.31070435,0.00018157046,0.00009893845,0.00006785777,0.0025840073,0.000020654286,0.5966676,0.00015704407,0.08163883,0.0065837977],"study_design_scores_gemma":[0.029277572,0.0065112743,0.68750274,0.00032255572,0.009602061,0.060621347,0.003395887,0.00018645891,0.17963284,0.007940317,0.013747105,0.001259852],"about_ca_topic_score_codex":0.0000042711467,"about_ca_topic_score_gemma":5.923435e-7,"teacher_disagreement_score":0.41703475,"about_ca_system_score_codex":0.000033818225,"about_ca_system_score_gemma":0.000049991188,"threshold_uncertainty_score":0.18655029},"labels":[],"label_agreement":null},{"id":"W2551844768","doi":"10.1007/s00429-016-1336-4","title":"Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties","year":2016,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Thalamus; Segmentation; Voxel; Neuroscience; Anatomy; Diffusion MRI; Cluster analysis; Robustness (evolution); Magnetic resonance imaging; Pattern recognition (psychology); Computer science; Artificial intelligence; Biology; Medicine","score_opus":0.03718634432736501,"score_gpt":0.2825612260279025,"score_spread":0.2453748817005375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551844768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19393215,0.00023078657,0.7979545,0.006767694,0.000079066114,0.0005286612,0.000016088905,0.00019993927,0.00029110428],"genre_scores_gemma":[0.971867,0.00004241674,0.024533717,0.0026391444,0.00009612141,0.000036403337,0.000016342758,0.000022320553,0.00074650487],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99932843,0.00003461453,0.00011535436,0.00028001747,0.00013014674,0.00011144729],"domain_scores_gemma":[0.9996208,0.000059691418,0.000041897558,0.00019727203,0.000035489767,0.00004488255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053305717,0.00011428136,0.000107990745,0.000062152816,0.00010061446,0.000010718053,0.000027395714,0.000060530034,0.00007272591],"category_scores_gemma":[0.00003139119,0.00006751053,0.000026237343,0.00009660566,0.00006830306,0.00006279122,0.000014233773,0.00008874309,0.0000029990597],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034311504,0.000025493753,0.0017385945,0.000026650556,0.0000018197984,0.0000017787024,0.000021935997,0.000071031965,0.3156053,0.0006362054,0.0011461318,0.68038195],"study_design_scores_gemma":[0.008167022,0.004206298,0.5693909,0.0010710759,0.00024149913,0.0002333493,0.00019830842,0.08619302,0.17628995,0.014381692,0.13881074,0.00081615243],"about_ca_topic_score_codex":0.0000059674817,"about_ca_topic_score_gemma":0.0000018269313,"teacher_disagreement_score":0.7779349,"about_ca_system_score_codex":0.00004250784,"about_ca_system_score_gemma":0.000014541451,"threshold_uncertainty_score":0.27529997},"labels":[],"label_agreement":null},{"id":"W2553481210","doi":"10.1007/s10237-020-01346-z","title":"La metafisica di trascendenza come saturazione dell'orizzonte fenomenologico","year":2014,"lang":"en","type":"article","venue":"Biomechanics and Modeling in Mechanobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Humanities; Philosophy","score_opus":0.11141502329864984,"score_gpt":0.34253917770151515,"score_spread":0.23112415440286532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2553481210","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24698511,0.00046620105,0.7501879,0.0012520599,0.00010784438,0.0003973874,0.0000151652375,0.000228087,0.00036028455],"genre_scores_gemma":[0.9757401,0.00137558,0.02195361,0.00068494194,0.000052137504,0.00007843301,0.000042252428,0.000028994593,0.000043951193],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986833,0.00008934242,0.00031686985,0.00050263706,0.0000764009,0.0003314944],"domain_scores_gemma":[0.99934113,0.000089640664,0.00007508725,0.00034310768,0.00004807304,0.00010295599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046084024,0.00020467474,0.00041499967,0.0002432212,0.000082721206,0.000012780849,0.00013440882,0.00024606494,0.0000063762377],"category_scores_gemma":[0.00006611017,0.00017269498,0.00006412032,0.00021695503,0.00005216289,0.000030823674,0.000120674005,0.00033531932,0.000005279437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001323997,0.00026017617,0.00008088244,0.00006590936,0.000037500122,0.000018796256,0.00010404017,0.00012323073,0.6806814,0.25867566,0.000040678926,0.059779327],"study_design_scores_gemma":[0.0013668552,0.0006501693,0.000023772242,0.00007054953,0.00006812548,0.00025576394,0.00007588601,0.8402572,0.007144625,0.12713224,0.0226074,0.00034738053],"about_ca_topic_score_codex":0.000022989603,"about_ca_topic_score_gemma":0.0000049639357,"teacher_disagreement_score":0.840134,"about_ca_system_score_codex":0.000038394868,"about_ca_system_score_gemma":0.000020005235,"threshold_uncertainty_score":0.7042297},"labels":[],"label_agreement":null},{"id":"W2554475177","doi":"10.1371/journal.pone.0165637","title":"A Novel Approach for Studying the Physiology and Pathophysiology of Myelinated and Non-Myelinated Axons in the CNS White Matter","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"Ontario Brain Institute","keywords":"White matter; Connectomics; Corpus callosum; Neuroscience; Axon; Electrophysiology; Optic nerve; Population; Anatomy; Biology; Central nervous system; Chemistry; Medicine; Magnetic resonance imaging; Functional connectivity; Connectome","score_opus":0.10019311582913289,"score_gpt":0.30288387083637935,"score_spread":0.20269075500724648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2554475177","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97641397,0.00004298161,0.014849967,0.0073016905,0.0000031085192,0.0012312848,0.00003235752,0.000024257406,0.00010036369],"genre_scores_gemma":[0.97937185,0.00009891972,0.018987583,0.000979403,0.000031301606,0.0004502714,0.000009303441,0.000013992401,0.000057355275],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993903,0.000029767063,0.00016350807,0.00021726036,0.000057962163,0.00014120714],"domain_scores_gemma":[0.99933535,0.00023104476,0.00007281665,0.00027726035,0.00006445293,0.000019084826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012791604,0.000088829765,0.00022642012,0.00004300706,0.00006151093,0.0000029282505,0.0000917822,0.000042349646,0.000004176619],"category_scores_gemma":[0.000045125358,0.000041781735,0.00002117057,0.00011049764,0.00019099208,0.000024488707,0.00006521742,0.000107741595,6.902296e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008103066,0.0006997341,0.008011765,0.00010327855,0.000029232928,3.639822e-7,0.0003276058,6.97361e-7,0.9897836,0.00013395383,0.00008460758,0.0007441573],"study_design_scores_gemma":[0.0043114247,0.0008527405,0.94607055,0.00036558296,0.00034326233,0.00003076947,0.0005277658,0.005852774,0.033683125,0.0076042856,0.00010209149,0.0002555955],"about_ca_topic_score_codex":0.0000045746438,"about_ca_topic_score_gemma":6.1509746e-7,"teacher_disagreement_score":0.95610046,"about_ca_system_score_codex":0.00000617346,"about_ca_system_score_gemma":0.000008487996,"threshold_uncertainty_score":0.17038096},"labels":[],"label_agreement":null},{"id":"W2555769692","doi":"10.15353/vsnl.v1i1.63","title":"Superpixel-based Prostate Cancer Detection from Diffusion Magnetic Resonance Imaging","year":2015,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Magnetic resonance imaging; Prostate cancer; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion MRI; Cancer; Cancer detection; Prostate; Computer science; Computation; Medicine; Artificial intelligence; Radiology; Internal medicine; Algorithm","score_opus":0.028822922260031043,"score_gpt":0.33677633269411783,"score_spread":0.3079534104340868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2555769692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70472455,0.028531011,0.25847185,0.006879825,0.0006205313,0.0004990016,0.00003143265,0.00011350618,0.0001283044],"genre_scores_gemma":[0.9907044,0.000105089624,0.008348636,0.00051470567,0.00022115612,0.00001158627,0.000009680717,0.000022133929,0.0000626088],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987666,0.000057979185,0.0004581542,0.00016377818,0.00042812122,0.000125366],"domain_scores_gemma":[0.9987141,0.000105798485,0.00027058064,0.000111017456,0.00061292027,0.00018562094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024849363,0.00013019818,0.0002507535,0.00017900096,0.00009487033,0.00008355146,0.00006593073,0.00001966819,0.0000054780917],"category_scores_gemma":[0.000060019738,0.00010289734,0.000059522554,0.00016091212,0.00006961824,0.00021985217,0.000026353762,0.00019502336,0.0000023305647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011235911,0.00046797658,0.27457398,0.00015744251,0.000022379549,0.00018254387,0.00087549177,0.022110485,0.04898458,0.00025227954,0.008988659,0.6422606],"study_design_scores_gemma":[0.0038174898,0.00028310754,0.14449705,0.0012488471,0.000078307545,0.00074861816,0.0003560601,0.7901037,0.0007217892,0.00297821,0.054950416,0.00021641859],"about_ca_topic_score_codex":0.00008155901,"about_ca_topic_score_gemma":6.611957e-7,"teacher_disagreement_score":0.7679932,"about_ca_system_score_codex":0.00010233388,"about_ca_system_score_gemma":0.00014275381,"threshold_uncertainty_score":0.41960317},"labels":[],"label_agreement":null},{"id":"W2556879144","doi":"10.1016/j.neuroimage.2016.11.003","title":"CERES: A new cerebellum lobule segmentation method","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":197,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Centre for Addiction and Mental Health; Western University; Montreal Neurological Institute and Hospital","funders":"Engineering and Physical Sciences Research Council; Centre National de la Recherche Scientifique; Ministerio de Economía y Competitividad; Agence Nationale de la Recherche","keywords":"Cerebellum; Segmentation; Computer science; Neuroscience; Artificial intelligence; Anatomy; Medicine; Psychology","score_opus":0.0907674934808323,"score_gpt":0.39978312090164203,"score_spread":0.30901562742080974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2556879144","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01430459,0.00003725191,0.95520777,0.019511297,0.00007441775,0.0006050761,0.000017273309,0.00065871037,0.009583607],"genre_scores_gemma":[0.22705318,0.00026531194,0.72437245,0.0073359855,0.00049171905,0.000106286505,0.000020518371,0.00013238777,0.040222194],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99905735,0.000031583724,0.000180292,0.00036463403,0.00016054294,0.00020561497],"domain_scores_gemma":[0.9991584,0.00009752845,0.0000690668,0.00047408338,0.00004220872,0.00015874508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000063179454,0.00012799428,0.00015171558,0.000070349975,0.000059750015,0.000014427661,0.000098880264,0.000034272725,0.0003117277],"category_scores_gemma":[0.0000846982,0.000089679,0.00007247786,0.0001691119,0.00004075582,0.00012905168,0.000052120744,0.000105096515,0.00019233489],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038944792,0.00006762044,0.0015353065,0.000014474069,0.0000060378834,0.000030270108,0.000028516934,7.1235024e-7,0.82346934,0.0012885854,0.03453265,0.13898754],"study_design_scores_gemma":[0.0026456502,0.00039427364,0.021105172,0.00011403509,0.00010336771,0.00037833588,0.000021935512,0.00019932404,0.5442295,0.01082864,0.41965276,0.0003269844],"about_ca_topic_score_codex":0.000016290383,"about_ca_topic_score_gemma":0.0000010853778,"teacher_disagreement_score":0.3851201,"about_ca_system_score_codex":0.0000388767,"about_ca_system_score_gemma":0.00005205563,"threshold_uncertainty_score":0.36570033},"labels":[],"label_agreement":null},{"id":"W2556951263","doi":"10.3233/bpl-160033","title":"Magnetic Resonance of Myelin Water: An <i>in vivo</i> Marker for Myelin","year":2016,"lang":"en","type":"review","venue":"Brain Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":298,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Multiple Sclerosis Society of Canada","keywords":"Myelin; Magnetic resonance imaging; Multiple sclerosis; Relaxometry; White matter; Diffusion MRI; Neuroscience; Magnetization transfer; Medicine; Pathology; Chemistry; Biology; Central nervous system; Radiology; Spin echo; Immunology","score_opus":0.07084405338574562,"score_gpt":0.3746824336317408,"score_spread":0.3038383802459952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2556951263","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008072389,0.9625099,0.030993918,0.0005445125,0.0000906813,0.0037432215,0.0012310318,0.00020332186,0.00060270116],"genre_scores_gemma":[0.00006262254,0.9796688,0.017608134,0.00026736327,0.00020637496,0.00077232276,0.000082023595,0.00010317838,0.0012291793],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980027,0.00008226299,0.00076372165,0.00059694296,0.00017060191,0.00038375647],"domain_scores_gemma":[0.9981115,0.0009662796,0.00018841117,0.0005244657,0.00008747982,0.00012189755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027492506,0.00034633424,0.001289804,0.0001747634,0.000041974603,0.000006893472,0.00025954001,0.0002173411,0.00011451203],"category_scores_gemma":[0.00044297046,0.00022352533,0.0002637405,0.00016671569,0.00014739684,0.000048756712,0.0000829063,0.00025828453,0.00001816432],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009074294,0.00018066465,0.000020928937,0.0071015754,0.000008410835,0.000011951459,0.00000901363,2.7214188e-7,0.0007129786,0.0009807053,0.0038665037,0.98701626],"study_design_scores_gemma":[0.0005037241,0.00026159504,0.00004674905,0.010177094,0.00014383324,0.00004139459,9.668123e-7,0.000090591,0.0004007696,0.0006746579,0.987418,0.00024061669],"about_ca_topic_score_codex":0.0000057617103,"about_ca_topic_score_gemma":0.000006151848,"teacher_disagreement_score":0.98677564,"about_ca_system_score_codex":0.000071408445,"about_ca_system_score_gemma":0.00012749706,"threshold_uncertainty_score":0.9115099},"labels":[],"label_agreement":null},{"id":"W2558110624","doi":"10.1371/journal.pone.0167274","title":"Assessing White Matter Microstructure in Brain Regions with Different Myelin Architecture Using MRI","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Deutsche Forschungsgemeinschaft","keywords":"White matter; Myelin; Diffusion MRI; Fractional anisotropy; Magnetization transfer; Nuclear magnetic resonance; Relaxometry; Magnetic resonance imaging; Materials science; Biomedical engineering; Nuclear medicine; Neuroscience; Biology; Medicine; Physics; Radiology; Central nervous system; Spin echo","score_opus":0.08225228573317421,"score_gpt":0.3212132745469855,"score_spread":0.23896098881381128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558110624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8580774,0.000022406075,0.09652856,0.044688735,0.000004709589,0.00039428065,0.000010553941,0.000108805594,0.0001645688],"genre_scores_gemma":[0.8808276,0.000013126532,0.116445675,0.0019577066,0.00008350519,0.000035494813,0.000008891381,0.00004541656,0.0005825688],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99913734,0.000024613591,0.00016024217,0.00029801665,0.00015675538,0.00022302539],"domain_scores_gemma":[0.9993662,0.000056153625,0.00007093539,0.00039338568,0.000039677972,0.000073635034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030729883,0.00014866283,0.00023652421,0.00011239395,0.000058300688,0.000023890025,0.00007694348,0.00005440921,0.0000645028],"category_scores_gemma":[0.000019768717,0.00008719658,0.000030040408,0.00015696576,0.00008473777,0.00007899579,0.000042310574,0.00024203502,0.000005221009],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046947764,0.00032160387,0.22222635,0.00007546199,0.000024960967,0.000022910739,0.000097384334,0.00000758193,0.7760362,0.00006785741,0.00032647932,0.0007462777],"study_design_scores_gemma":[0.0033704261,0.00024652787,0.77661324,0.0079475,0.0003228716,0.00040197777,0.000093130075,0.00049653806,0.19967788,0.008741359,0.0013568914,0.0007316807],"about_ca_topic_score_codex":0.000004603719,"about_ca_topic_score_gemma":0.000009641805,"teacher_disagreement_score":0.5763583,"about_ca_system_score_codex":0.00006909741,"about_ca_system_score_gemma":0.000024819215,"threshold_uncertainty_score":0.35557735},"labels":[],"label_agreement":null},{"id":"W2559255072","doi":"10.1089/brain.2016.0451","title":"Using CForest to Analyze Diffusion Tensor Imaging Data: A Study of White Matter Integrity in Healthy Aging","year":2016,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton; Saint Mary's University; Dalhousie University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Cognitive decline; Psychology; Tractography; Neuroimaging; Neuroscience; Developmental psychology; Internal medicine; Medicine; Magnetic resonance imaging; Disease; Dementia","score_opus":0.1458535999089755,"score_gpt":0.4289856862583005,"score_spread":0.283132086349325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559255072","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89184,0.000009669334,0.08699668,0.020086998,0.000027106555,0.00087401125,0.000032990687,0.000076437645,0.00005610146],"genre_scores_gemma":[0.9902454,0.0000028210327,0.007871411,0.0017326484,0.000049742917,0.000033025914,0.000004416176,0.000025461326,0.00003506254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998572,0.000115715105,0.0003110961,0.000581975,0.00016811519,0.0002511136],"domain_scores_gemma":[0.99831384,0.000367089,0.000120113946,0.0010163933,0.00007863262,0.000103923136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005433509,0.00014385408,0.00034041837,0.0002489022,0.00010480663,0.000008711459,0.00019968825,0.000027478509,0.000022964941],"category_scores_gemma":[0.00047888342,0.000106159234,0.00003179655,0.00043316258,0.000049989216,0.00020225513,0.00051972707,0.00021473184,0.0000041937546],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011634076,0.00061383145,0.9756138,0.000028608385,0.000005569483,0.000016294565,0.00027198563,0.000005855154,0.01844922,0.000036888574,0.00040317912,0.0044384436],"study_design_scores_gemma":[0.0014995112,0.00017717802,0.9936046,0.0002777351,0.000023580822,0.00003638321,0.00026674694,0.0026679712,0.0003777378,0.00033934042,0.00058321387,0.00014601184],"about_ca_topic_score_codex":0.00074636907,"about_ca_topic_score_gemma":0.0005190382,"teacher_disagreement_score":0.098405406,"about_ca_system_score_codex":0.00012448958,"about_ca_system_score_gemma":0.00005120557,"threshold_uncertainty_score":0.43290478},"labels":[],"label_agreement":null},{"id":"W2559740506","doi":"10.1007/s11682-016-9657-8","title":"Age and gender interactions in white matter of schizophrenia and obsessive compulsive disorder compared to non-psychiatric controls: commonalities across disorders","year":2016,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Temerty Family Foundation; Canadian HIV Trials Network, Canadian Institutes of Health Research; BrainsWay; Campbell Institute; Eli Lilly and Company","keywords":"White matter; Fractional anisotropy; Psychology; Schizophrenia (object-oriented programming); Corpus callosum; Diffusion MRI; Comorbidity; Psychiatry; Clinical psychology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.03721346790613547,"score_gpt":0.36441410040761807,"score_spread":0.32720063250148257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559740506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9847212,0.00022971469,0.005773319,0.008378447,0.000025584592,0.00053972064,0.00007888244,0.000041965446,0.00021119356],"genre_scores_gemma":[0.99306846,0.000054231776,0.0056102704,0.0005995132,0.000016474918,0.00013838122,0.000007783879,0.000027287502,0.00047761793],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992665,0.00002207238,0.00020700012,0.00026615773,0.000065769185,0.00017250863],"domain_scores_gemma":[0.9995251,0.00011539965,0.00007212125,0.00016869008,0.000029942514,0.00008874299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048763886,0.00013465867,0.00024512605,0.000121015444,0.00007758916,0.000023897515,0.0000445293,0.000015613994,0.000019471014],"category_scores_gemma":[0.000017178716,0.00010324849,0.000026261967,0.00011245153,0.00022847299,0.00008690764,0.000086231834,0.00009650689,0.000001917075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067718414,0.00013886207,0.9746725,0.000035247536,0.0000057973316,0.000007657537,0.0006002405,4.1091704e-7,0.005409141,0.0000852256,0.00084975926,0.018127445],"study_design_scores_gemma":[0.0020846967,0.000026013247,0.99499005,0.00012592325,0.000047190453,0.00005388542,0.0006038806,0.000053080625,0.00005037947,0.00047769566,0.00135652,0.00013068304],"about_ca_topic_score_codex":0.00009703999,"about_ca_topic_score_gemma":0.00011314836,"teacher_disagreement_score":0.020317556,"about_ca_system_score_codex":0.0000117366735,"about_ca_system_score_gemma":0.000007945952,"threshold_uncertainty_score":0.4210351},"labels":[],"label_agreement":null},{"id":"W2559779481","doi":"10.1016/j.biopsych.2016.12.005","title":"Gray Matter Neuritic Microstructure Deficits in Schizophrenia and Bipolar Disorder","year":2016,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":131,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Bipolar disorder; Magnetic resonance imaging; Schizophrenia (object-oriented programming); Parahippocampal gyrus; Psychology; Neuroscience; Functional magnetic resonance imaging; White matter; Neuroimaging; Neurocognitive; Medicine; Cardiology; Psychiatry; Radiology; Cognition; Temporal lobe","score_opus":0.02652682464387103,"score_gpt":0.30247878792194444,"score_spread":0.2759519632780734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2559779481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852,0.0019997382,0.0013944469,0.0105464365,0.000056250876,0.00024921895,0.000014547988,0.00012131659,0.00041805915],"genre_scores_gemma":[0.9822099,0.00031094253,0.015218358,0.0019155223,0.000063453816,0.00002374097,0.0000034467826,0.000018746465,0.00023585482],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993924,0.000016345071,0.00012650262,0.00027514863,0.000033502103,0.0001561156],"domain_scores_gemma":[0.9996988,0.000023974897,0.000026623653,0.000181111,0.000007933546,0.0000615463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000024322804,0.00010528063,0.00013298511,0.00004998103,0.000030083529,0.0000047306085,0.000055271674,0.000086804095,0.00016967148],"category_scores_gemma":[0.000019136212,0.000055457054,0.00003063935,0.0000965503,0.00011712966,0.00001897284,0.000037424717,0.000110113775,0.00005470894],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005018536,0.00005802459,0.9612309,0.000010927616,0.0000018624984,0.000002233978,0.000001622501,1.8956369e-8,0.026969321,0.0038097731,0.0011026001,0.0067625674],"study_design_scores_gemma":[0.00074415206,0.000088500085,0.94800913,0.00005991164,0.0000054006123,0.00007585454,0.0000031248326,0.0000011378872,0.00011573497,0.015651079,0.03514696,0.00009900542],"about_ca_topic_score_codex":0.0000033829526,"about_ca_topic_score_gemma":0.000004237232,"teacher_disagreement_score":0.03404436,"about_ca_system_score_codex":0.000006123992,"about_ca_system_score_gemma":0.000007959992,"threshold_uncertainty_score":0.22614731},"labels":[],"label_agreement":null},{"id":"W2561965437","doi":"10.1503/jpn.150291","title":"Shape analysis of the cingulum, uncinate and arcuate fasciculi in patients with bipolar disorder","year":2016,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Agence Nationale de la Recherche","keywords":"Cingulum (brain); Tractography; Uncinate fasciculus; White matter; Inferior longitudinal fasciculus; Arcuate fasciculus; Temporal lobe; Diffusion MRI; Superior longitudinal fasciculus; Anatomy; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Fractional anisotropy; Radiology","score_opus":0.016301129963002592,"score_gpt":0.28771793684706753,"score_spread":0.27141680688406494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561965437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949027,0.00014484953,0.0011577982,0.0036438624,0.000052537765,0.00008161292,0.000004153598,0.0000032292726,0.000009280719],"genre_scores_gemma":[0.9984416,0.00019221441,0.00093556364,0.0003961718,0.000008633494,7.2628234e-7,5.0097583e-8,0.0000035248825,0.000021519983],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99940807,0.000018983255,0.00019358165,0.00012366388,0.00017354557,0.00008214746],"domain_scores_gemma":[0.9995091,0.000022843553,0.00021552334,0.00013374245,0.000058134032,0.000060672526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011216726,0.000057855745,0.0001514442,0.00015218405,0.000051976072,0.000005844143,0.000090947986,0.000012487574,0.0000026012985],"category_scores_gemma":[0.000055588713,0.000025724477,0.00003930174,0.0006686607,0.00020120046,0.00010161654,0.00003178571,0.000095708965,3.1153697e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042850745,0.00009449228,0.99320567,0.000007132915,0.0000055818496,6.706438e-7,0.000011781958,0.000008592703,0.003925698,0.0001661791,0.000009245699,0.0025221067],"study_design_scores_gemma":[0.0005553499,0.00030549066,0.99779904,0.0000878901,0.00011622558,0.0000143807,0.000008011464,0.00015565834,0.00020804496,0.000303679,0.00041198856,0.000034251607],"about_ca_topic_score_codex":0.0000024333217,"about_ca_topic_score_gemma":0.0000086943555,"teacher_disagreement_score":0.004593361,"about_ca_system_score_codex":0.000005661859,"about_ca_system_score_gemma":0.000037742906,"threshold_uncertainty_score":0.10490137},"labels":[],"label_agreement":null},{"id":"W2565838431","doi":"10.1016/j.neuroimage.2016.12.017","title":"Multivariate dynamical modelling of structural change during development","year":2016,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Mental Health; Medical Research Council; Deutscher Akademischer Austauschdienst; Jacobs Foundation; Wellcome Trust; McGill University","keywords":"Multivariate statistics; Bayesian probability; Bayesian inference; Neuroscience; Neuroimaging; Computer science; Psychology; Artificial intelligence; Machine learning","score_opus":0.14419327794513073,"score_gpt":0.3499756302418245,"score_spread":0.20578235229669375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2565838431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9114567,0.000016641636,0.0871088,0.0007370761,0.000028046268,0.00029901174,0.000009319738,0.00016666151,0.0001777664],"genre_scores_gemma":[0.9433635,0.000016136704,0.056231104,0.000092172,0.000044788892,0.000037451893,0.0000031330137,0.000025336938,0.0001863601],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992192,0.000010922649,0.00020988852,0.00024921933,0.00013292379,0.00017787727],"domain_scores_gemma":[0.9995038,0.000030390216,0.00007127058,0.00027509348,0.000049177757,0.00007026305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029868119,0.000107055406,0.00015777779,0.00006366725,0.00005352765,0.0000034278453,0.00008079911,0.000028211425,0.000023871447],"category_scores_gemma":[0.000021330045,0.00007327746,0.00004406156,0.00008515786,0.000056254445,0.000091042995,0.00007161268,0.00009052509,0.000008846852],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011261481,0.00006888803,0.01575659,0.00009812788,0.000011244711,0.000047558166,0.00015120933,0.000026323347,0.9635217,0.00088042323,0.000012830105,0.019312479],"study_design_scores_gemma":[0.002125221,0.000105734536,0.61671335,0.00030312623,0.00003745231,0.00016942548,0.000006222003,0.017391577,0.36003432,0.0009609905,0.0018345277,0.00031808022],"about_ca_topic_score_codex":0.0000060294674,"about_ca_topic_score_gemma":3.0821303e-7,"teacher_disagreement_score":0.6034874,"about_ca_system_score_codex":0.00003309358,"about_ca_system_score_gemma":0.000016188622,"threshold_uncertainty_score":0.29881677},"labels":[],"label_agreement":null},{"id":"W2566061819","doi":"10.1016/j.nicl.2016.12.012","title":"Longitudinal changes in microstructural white matter metrics in Alzheimer's disease","year":2016,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; University of Manitoba; University of Calgary; University of Victoria","funders":"National Institute on Aging; National Institutes of Health; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Defense","keywords":"White matter; Alzheimer's disease; Neuroscience; Disease; Psychology; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.16508872100979347,"score_gpt":0.433411103769093,"score_spread":0.26832238275929954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2566061819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9533622,0.00017992588,0.00071364,0.044496033,0.00016104704,0.0005810082,0.000040514966,0.00012790402,0.00033769914],"genre_scores_gemma":[0.9912601,0.0002693579,0.0037574915,0.0042079864,0.0001620217,0.00005307315,0.000008404089,0.00003965693,0.00024192032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982761,0.00008414905,0.000508494,0.0006348602,0.00016427533,0.00033212488],"domain_scores_gemma":[0.9986906,0.00033639168,0.000099832,0.0006022366,0.00004652783,0.0002244204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022962119,0.00017519614,0.0003428434,0.00024330258,0.0000251903,0.000015070826,0.00017218312,0.0000713339,0.00018343554],"category_scores_gemma":[0.0004233102,0.0001247801,0.00010786231,0.00044283678,0.00021959568,0.000102165875,0.00013926212,0.0003867698,0.000107562024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016930423,0.00016378629,0.9854181,0.000008308267,0.0000036162332,0.00036724063,0.0000046373693,2.64885e-7,0.0012780563,0.00003733584,0.0020339198,0.010515437],"study_design_scores_gemma":[0.0012660248,0.0001083886,0.99209607,0.0000790772,0.00004184355,0.000047361347,0.0000017852213,0.00005261518,0.00036230878,0.0005022392,0.0053027826,0.00013947922],"about_ca_topic_score_codex":0.0000052000128,"about_ca_topic_score_gemma":0.000016183287,"teacher_disagreement_score":0.040288046,"about_ca_system_score_codex":0.000030443962,"about_ca_system_score_gemma":0.00003997838,"threshold_uncertainty_score":0.5088385},"labels":[],"label_agreement":null},{"id":"W2568307873","doi":"10.1016/j.jneumeth.2016.12.020","title":"Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; BioClinica; Biogen; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Roche; Merck; Alzheimer's Drug Discovery Foundation; Takeda Pharmaceutical Company; AbbVie; Fujirebio Europe; Alzheimer's Association","keywords":"Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; White matter; Diffusion MRI; Context (archaeology); Voxel; Dementia; Computer science; Artificial intelligence; Psychology; Neuroscience; Disease; Magnetic resonance imaging; Medicine; Pathology; Radiology","score_opus":0.25053591682464693,"score_gpt":0.5517588206324406,"score_spread":0.3012229038077937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2568307873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9275365,0.000048600916,0.07085255,0.0013079677,0.00005411199,0.0001584896,0.0000021213302,0.0000100141815,0.000029639012],"genre_scores_gemma":[0.84304345,0.00016479795,0.15656543,0.00018763165,0.00002064501,0.0000029648293,1.4147112e-7,0.000004975672,0.000009998187],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985536,0.0002726047,0.00047422678,0.0002798392,0.0002668693,0.00015288564],"domain_scores_gemma":[0.9984182,0.00015972354,0.0006441879,0.00048713703,0.0001325258,0.00015822814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016421615,0.00009699571,0.00050886243,0.0004785123,0.00018932304,0.000043636537,0.00033156105,0.00002640615,0.000002974726],"category_scores_gemma":[0.00093836343,0.000067478395,0.000088840054,0.00051830255,0.00033165203,0.00025759364,0.00013532538,0.00031407995,2.7667339e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012542267,0.00081548194,0.7786602,0.000006821832,0.0000065033482,0.00020599696,0.00012149014,0.000010109432,0.19932105,0.000034869365,0.0000028922345,0.020689199],"study_design_scores_gemma":[0.0005342695,0.0018111388,0.99190307,0.000017519145,0.00020663599,0.00019436676,0.0000742128,0.0029151074,0.0018519715,0.0003707236,0.0000674061,0.000053555876],"about_ca_topic_score_codex":0.000012371903,"about_ca_topic_score_gemma":0.0000024837445,"teacher_disagreement_score":0.21324293,"about_ca_system_score_codex":0.000016782273,"about_ca_system_score_gemma":0.000040064584,"threshold_uncertainty_score":0.27516893},"labels":[],"label_agreement":null},{"id":"W2571211835","doi":"10.1016/b978-0-12-800756-3.00041-7","title":"Neuroimaging Findings in Adolescent Cannabis Use and Early Phase Psychosis","year":2017,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Psychosis; Cannabis; Neuroimaging; Psychology; Psychiatry; Effects of cannabis; Neuroscience; Mechanism (biology); Clinical psychology; Cannabidiol","score_opus":0.08783188676811546,"score_gpt":0.3627047429250566,"score_spread":0.2748728561569411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2571211835","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019309374,0.0009702667,0.00010272387,0.0037998671,0.00019300167,0.0032096857,0.000111511574,0.0004009187,0.97190267],"genre_scores_gemma":[0.025325019,0.0007517507,0.0021730503,0.0015469097,0.00015975161,0.00014076979,0.000017637847,0.00018460474,0.9697005],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99837744,0.000009559948,0.00040010505,0.00069702906,0.00021117392,0.00030467517],"domain_scores_gemma":[0.9984567,0.000022557588,0.00022199922,0.0010177902,0.00007960358,0.00020135814],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009938116,0.00040199445,0.00057086465,0.0002796563,0.00014824896,0.00010794307,0.0001938263,0.00016135695,0.000015679761],"category_scores_gemma":[0.000044475888,0.00040439493,0.00013889528,0.000010407312,0.00023479685,0.00010450849,0.00014099776,0.0008672927,0.00001202819],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006258339,0.000052916846,0.0031698046,0.00014609548,0.000019628917,0.00020552737,0.00011046203,3.3744467e-8,0.0004969292,0.001026062,0.0011606211,0.99354935],"study_design_scores_gemma":[0.0011330086,0.00011393752,0.008029974,0.0016941291,0.00012787887,0.00010740426,0.0000011062408,0.000010735163,0.00014556471,0.0027390805,0.9855412,0.00035598216],"about_ca_topic_score_codex":0.000008507986,"about_ca_topic_score_gemma":0.000012676306,"teacher_disagreement_score":0.9931933,"about_ca_system_score_codex":0.000080931306,"about_ca_system_score_gemma":0.000049887527,"threshold_uncertainty_score":0.9998408},"labels":[],"label_agreement":null},{"id":"W2576872718","doi":"10.1016/j.nicl.2017.01.009","title":"Hemispheric asymmetry in myelin after stroke is related to motor impairment and function","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Health and Medical Research Council; Medical Research Council; Canadian Institutes of Health Research; Michael Smith Health Research BC; Canada Research Chairs; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Stroke (engine); Myelin; Physical medicine and rehabilitation; Magnetic resonance imaging; Motor impairment; Chronic stroke; Psychology; Neuroscience; Medicine; Cardiology; Rehabilitation; Radiology; Central nervous system","score_opus":0.06965723557771637,"score_gpt":0.42084157966511526,"score_spread":0.3511843440873989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2576872718","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98667747,0.00006068501,0.0010738821,0.01014353,0.0001493498,0.0006509928,0.000017981185,0.00012800668,0.0010980819],"genre_scores_gemma":[0.9833531,0.00019271414,0.007940166,0.0062122825,0.00009750775,0.000100919424,0.0000031416182,0.000034727895,0.00206547],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99850667,0.000038388498,0.00049130764,0.00059459417,0.00014897443,0.00022004373],"domain_scores_gemma":[0.99853796,0.000105922954,0.0001249403,0.0009553674,0.000047016114,0.00022880132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027831583,0.00014792949,0.0002904058,0.000056185203,0.00009823603,0.000046853453,0.00013426722,0.00010808334,0.000077549405],"category_scores_gemma":[0.0005099529,0.00013798435,0.0001039762,0.000080911166,0.0001368811,0.0001065274,0.00020373089,0.00052083214,0.00006232019],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012023222,0.0006660141,0.8963582,0.000043504006,0.000019191124,0.00026795763,0.000040105555,7.7051703e-7,0.012502214,0.00005854564,0.0056960317,0.08314514],"study_design_scores_gemma":[0.0012007765,0.000799589,0.9731801,0.000050261966,0.000038664806,0.000034785386,0.000006985772,0.00048834295,0.00044536157,0.00037130638,0.023264304,0.000119535754],"about_ca_topic_score_codex":0.000009839011,"about_ca_topic_score_gemma":0.0000018022924,"teacher_disagreement_score":0.083025604,"about_ca_system_score_codex":0.00002379986,"about_ca_system_score_gemma":0.000026850079,"threshold_uncertainty_score":0.5626838},"labels":[],"label_agreement":null},{"id":"W2577018854","doi":"10.1016/j.dadm.2016.12.011","title":"Peripheral inflammatory markers indicate microstructural damage within periventricular white matter hyperintensities in Alzheimer's disease: A preliminary report","year":2017,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia; McMaster University; Health Sciences Centre; Centre for Addiction and Mental Health; Sunnybrook Health Science Centre; Heart and Stroke Foundation; Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Cognoptix; Canadian Institutes of Health Research; Alzheimer Society; Sunnybrook Research Institute; University of Toronto; Biogen; Heart and Stroke Foundation of Canada; Pfizer; Eli Lilly and Company","keywords":"Hyperintensity; White matter; Diffusion MRI; Pathology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Peripheral; Inflammation; Disease; Lesion; Dementia; Internal medicine; Radiology","score_opus":0.04145832636965725,"score_gpt":0.34864103449007655,"score_spread":0.3071827081204193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577018854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834722,0.009867774,0.00013501936,0.0037768765,0.00059565966,0.0017151242,0.00006222736,0.00023093057,0.00014418105],"genre_scores_gemma":[0.98859936,0.00036056392,0.0077518704,0.00031625354,0.00032567396,0.0023223248,0.00017311233,0.00012088703,0.000029953493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967268,0.000095944335,0.00082995597,0.0010370706,0.00063605886,0.00067417126],"domain_scores_gemma":[0.9965961,0.00004900767,0.00066473475,0.0018443624,0.00016195518,0.00068387133],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026142248,0.00055688387,0.00051538757,0.00023167019,0.00073605386,0.0003930645,0.00054199167,0.00008358602,0.00018785134],"category_scores_gemma":[0.000059023558,0.00056204543,0.00030847683,0.00013556739,0.00034190435,0.00079142797,0.0006217089,0.00048218723,0.000015998112],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002762857,0.00032286902,0.9917356,0.00005580644,0.0012782448,0.0036475807,0.000095746225,0.00011659745,0.00034350643,0.000033107633,0.000825112,0.0012695363],"study_design_scores_gemma":[0.0008795141,0.00006599429,0.9888487,0.00053426047,0.0054779416,0.000054304888,0.00017684384,0.0005174145,0.0017336915,0.0001136065,0.0010467557,0.000551013],"about_ca_topic_score_codex":0.00007923293,"about_ca_topic_score_gemma":0.0000020620948,"teacher_disagreement_score":0.00950721,"about_ca_system_score_codex":0.0001169094,"about_ca_system_score_gemma":0.00023845765,"threshold_uncertainty_score":0.9996831},"labels":[],"label_agreement":null},{"id":"W2580611812","doi":"10.1016/j.compbiomed.2017.01.016","title":"3D-SSF: A bio-inspired approach for dynamic multi-subject clustering of white matter tracts","year":2017,"lang":"en","type":"review","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Outlier; Computer science; Flocking (texture); Cluster analysis; Artificial intelligence; Pattern recognition (psychology); Population; Data mining","score_opus":0.20114477447282839,"score_gpt":0.47394949576067724,"score_spread":0.27280472128784883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2580611812","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017490316,0.5922945,0.4054249,0.0003022049,0.00015700945,0.0015578356,0.000029694336,0.00004515127,0.00017118896],"genre_scores_gemma":[0.00032082185,0.7937353,0.20473462,0.0002945715,0.000114596645,0.00024855146,0.0003954168,0.000035749665,0.00012037303],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985326,0.000051321396,0.00059039483,0.0005335453,0.00004367037,0.00024847154],"domain_scores_gemma":[0.9986949,0.00017934147,0.00044523587,0.00056017516,0.000038969567,0.00008138979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002579371,0.00031582522,0.0018260895,0.00031893526,0.00010512421,0.000002816762,0.00024129076,0.0003041865,0.0000033465108],"category_scores_gemma":[0.00006250419,0.00022179255,0.00013547711,0.00010128218,0.00049146346,0.00002368626,0.00016762227,0.00035231165,6.3283545e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042306216,0.00013167728,0.0011702849,0.014664882,0.00007997376,0.000009666096,0.0001056699,0.0000013164175,0.000023386145,0.00007065169,0.00034052925,0.98335963],"study_design_scores_gemma":[0.0036234432,0.0008136677,0.002475175,0.026292505,0.00097098894,0.0006809144,0.000015130428,0.01421915,0.0000018163727,0.00023327081,0.9501796,0.0004943485],"about_ca_topic_score_codex":0.0000064711867,"about_ca_topic_score_gemma":0.0000021683634,"teacher_disagreement_score":0.98286533,"about_ca_system_score_codex":0.00004284096,"about_ca_system_score_gemma":0.000050120718,"threshold_uncertainty_score":0.9044438},"labels":[],"label_agreement":null},{"id":"W2581789148","doi":"10.3389/fninf.2017.00005","title":"AxonPacking: An Open-Source Software to Simulate Arrangements of Axons in White Matter","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Open source; Open source software; Computer science; White matter; White (mutation); Software; Programming language; Biology; Medicine","score_opus":0.0682076722942466,"score_gpt":0.3653725144846666,"score_spread":0.29716484219042005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2581789148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68470937,0.000012142781,0.3025734,0.0026444923,0.00027221165,0.0024778133,0.000041972453,0.00012831793,0.0071402653],"genre_scores_gemma":[0.6333538,0.000026817774,0.36375806,0.0021345536,0.000018846638,0.00005813747,0.000018276267,0.00004368925,0.0005878005],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988912,0.00001502507,0.0004778145,0.0001865081,0.00017131484,0.00025814548],"domain_scores_gemma":[0.9983863,0.000015399008,0.00024664233,0.0011863384,0.000045754958,0.00011955079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014425321,0.00014749677,0.00034292057,0.00024195701,0.00010104677,0.00008354491,0.0007149258,0.000046051355,0.000013429613],"category_scores_gemma":[0.00014038682,0.00014863233,0.000031925258,0.00015311548,0.00007399561,0.0005899784,0.00039865376,0.0002288213,0.0000127433905],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008318942,0.00016705914,0.975851,0.00010391903,0.0000054902757,0.000013132198,0.00070717017,0.002246934,0.000100967794,0.000025491257,0.012503851,0.008191792],"study_design_scores_gemma":[0.0034014457,0.0005152974,0.8658223,0.00071577565,0.000045982346,0.000024022014,0.00057311734,0.05397832,0.0010106527,0.0015999698,0.07179402,0.00051906187],"about_ca_topic_score_codex":0.000012603815,"about_ca_topic_score_gemma":0.000007699416,"teacher_disagreement_score":0.11002867,"about_ca_system_score_codex":0.000044423025,"about_ca_system_score_gemma":0.000027722772,"threshold_uncertainty_score":0.6061051},"labels":[],"label_agreement":null},{"id":"W2582496673","doi":"10.1016/j.nicl.2017.01.026","title":"Independent value added by diffusion MRI for prediction of cognitive function in older adults","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Canadian Institutes of Health Research; California Department of Public Health; National Institute on Aging; Alzheimer's Association","keywords":"Dementia; White matter; Alzheimer's Disease Neuroimaging Initiative; Cognitive decline; Psychology; Neuroimaging; Diffusion MRI; Magnetic resonance imaging; Brain size; Internal medicine; Cognition; Medicine; Cardiology; Neuroscience; Disease; Radiology","score_opus":0.08883776844937022,"score_gpt":0.41924321603563136,"score_spread":0.3304054475862611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582496673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9350404,0.000030195024,0.05985138,0.0015684075,0.0002934948,0.0021115902,0.00031559417,0.00012533084,0.0006636145],"genre_scores_gemma":[0.9969978,0.00019248761,0.0014847941,0.0005565731,0.00015591999,0.0001863687,0.00016499855,0.000031809563,0.00022925899],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984684,0.00005334264,0.0005955393,0.0005220931,0.00018878626,0.00017186643],"domain_scores_gemma":[0.99839187,0.00042625534,0.0003602902,0.00056424475,0.00016004877,0.00009727244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031136203,0.000130119,0.00031672363,0.00006106034,0.00012665166,0.00001605747,0.00013643914,0.000135794,0.000017962218],"category_scores_gemma":[0.0016031652,0.00012205768,0.00015122762,0.00005277696,0.0001879044,0.00013627144,0.00009663407,0.00038654846,0.000004175005],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008594128,0.007683286,0.78640515,0.00033963562,0.000063525076,0.00004947425,0.0002133031,0.0000033602068,0.03539095,0.0005918678,0.023876911,0.13678843],"study_design_scores_gemma":[0.0069765383,0.001191763,0.9835607,0.00039247106,0.00011834546,0.000010837195,0.000031841024,0.00329122,0.0024562317,0.00050482404,0.0013762324,0.00008901793],"about_ca_topic_score_codex":0.0000143524685,"about_ca_topic_score_gemma":0.0000026436617,"teacher_disagreement_score":0.19715555,"about_ca_system_score_codex":0.000014682944,"about_ca_system_score_gemma":0.000034289653,"threshold_uncertainty_score":0.49773678},"labels":[],"label_agreement":null},{"id":"W2584408557","doi":"10.1101/104190","title":"Fiber tractography using machine learning","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Deutsche Forschungsgemeinschaft","keywords":"Tractography; Computer science; Random forest; Artificial intelligence; Imaging phantom; Fiber; Diffusion MRI; Machine learning; Pattern recognition (psychology); Physics; Medicine; Chemistry","score_opus":0.0603398396589757,"score_gpt":0.3155699989317103,"score_spread":0.25523015927273457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584408557","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9703223,0.0027307656,0.019876575,0.0012077462,0.0005308563,0.0021367008,0.00028297692,0.002746679,0.00016539943],"genre_scores_gemma":[0.8990395,0.0005082791,0.09941419,0.00020981168,0.00042626972,0.00014746175,0.0000010373714,0.00021526327,0.000038147115],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976982,0.000054985725,0.00043136388,0.0009936496,0.0003323889,0.00048944145],"domain_scores_gemma":[0.9967111,0.000041621566,0.00060771365,0.0019996588,0.00033754,0.0003023643],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002839959,0.00053279364,0.0006636895,0.0003285399,0.00045318762,0.0001753961,0.00045583,0.00040613723,0.00008000617],"category_scores_gemma":[0.00020914529,0.00056086795,0.00030703846,0.0002423002,0.00019023604,0.00013004322,0.00046571862,0.0018233983,0.00004228776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005968996,0.00032781722,0.051941697,0.0006309163,0.00020543342,0.00021548285,0.0000052166097,0.00012864567,0.9458125,0.0003739513,0.0002696606,0.000028978402],"study_design_scores_gemma":[0.0019476156,0.00023636268,0.17412777,0.003042247,0.0014046816,8.613865e-7,0.0000016388025,0.015131716,0.48538938,0.000044654575,0.3159949,0.0026781897],"about_ca_topic_score_codex":0.00008342008,"about_ca_topic_score_gemma":4.3733473e-7,"teacher_disagreement_score":0.46042314,"about_ca_system_score_codex":0.00014389666,"about_ca_system_score_gemma":0.0002885184,"threshold_uncertainty_score":0.9996843},"labels":[],"label_agreement":null},{"id":"W2584704508","doi":"10.1101/105270","title":"Group-level progressive alterations in brain connectivity patterns revealed by diffusion-tensor brain networks across severity stages in Alzheimer’s disease","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Ikerbasque, Basque Foundation for Science; Eisai; National Institute on Aging; Eusko Jaurlaritza; AstraZeneca; Bristol-Myers Squibb; Amorfix Life Sciences; European Commission; Alzheimer's Disease Neuroimaging Initiative; Biogen","keywords":"Parahippocampal gyrus; Neuroscience; Diffusion MRI; Entorhinal cortex; Middle temporal gyrus; Hippocampus; Neuroimaging; Psychology; Hippocampal formation; Cognition; Dementia; Disease; Temporal lobe; Medicine; Internal medicine; Epilepsy; Magnetic resonance imaging","score_opus":0.05181560930956387,"score_gpt":0.3354240008034575,"score_spread":0.28360839149389366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584704508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9651885,0.0012982178,0.018350918,0.007691664,0.00021906705,0.003620086,0.0031445425,0.0004851187,0.0000018638817],"genre_scores_gemma":[0.9916315,0.00030652384,0.0040683537,0.0013271644,0.00026576564,0.0022006507,0.000021468673,0.00016426602,0.000014315126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961261,0.00027711198,0.0007574955,0.0016151754,0.00037853944,0.00084555993],"domain_scores_gemma":[0.99587363,0.0003030757,0.000706502,0.0023209744,0.00029375928,0.00050206133],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00072340097,0.00070798665,0.00093712285,0.00021132623,0.00037654475,0.0002534211,0.00061438075,0.00045614337,0.000020998146],"category_scores_gemma":[0.0009591034,0.0007638678,0.00018506327,0.0003413855,0.0002705829,0.00027288162,0.00084648904,0.0017215533,0.000004680666],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030511006,0.0017529597,0.951957,0.00045356073,0.00011110203,0.0008032504,0.000050033057,0.00009468498,0.0412728,0.00028900194,0.0028101674,0.00010033656],"study_design_scores_gemma":[0.0015528972,0.00005824327,0.98732966,0.0017132293,0.00009676682,1.4623372e-7,0.0000054781735,0.0044822907,0.002668224,0.000025032925,0.0012516448,0.00081640726],"about_ca_topic_score_codex":0.00023064682,"about_ca_topic_score_gemma":0.00007778789,"teacher_disagreement_score":0.038604576,"about_ca_system_score_codex":0.0003506264,"about_ca_system_score_gemma":0.00032837674,"threshold_uncertainty_score":0.9994812},"labels":[],"label_agreement":null},{"id":"W2586729820","doi":"10.1016/j.pscychresns.2017.02.002","title":"Corpus callosum volumes in bipolar disorders and suicidal vulnerability","year":2017,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Corpus callosum; Bipolar disorder; Psychology; Bipolar I disorder; Psychiatry; Magnetic resonance imaging; Internal medicine; Suicide attempt; Audiology; Medicine; Clinical psychology; Poison control; Neuroscience; Injury prevention; Lithium (medication); Radiology; Mania","score_opus":0.1409115750582966,"score_gpt":0.46194309760321134,"score_spread":0.32103152254491474,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2586729820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9341303,0.001669399,0.00053111237,0.05976277,0.0001790076,0.00085884525,0.000011046159,0.00017209767,0.0026853944],"genre_scores_gemma":[0.99324363,0.0011092516,0.0047864295,0.00033149347,0.00012702479,0.0000899976,0.0000043963205,0.000045608464,0.0002621398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99790084,0.00013325013,0.0002637561,0.0006918856,0.00040401527,0.0006062556],"domain_scores_gemma":[0.9981665,0.00014044404,0.00007907257,0.0012909012,0.00009839261,0.00022468615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008078875,0.00016887193,0.00024582096,0.00027537122,0.0008792068,0.00017264216,0.0003819432,0.000048931168,0.000015108636],"category_scores_gemma":[0.0007031381,0.00016574987,0.00006044814,0.00022341456,0.0007887455,0.0002748289,0.0003720797,0.0011894621,0.00001043885],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057738504,0.0001867973,0.9615762,0.000084001,0.000003887963,0.000017132183,0.000029103196,0.0000011344723,0.0032515398,0.001455372,0.00065963174,0.032677423],"study_design_scores_gemma":[0.0007803386,0.00012338764,0.9527124,0.00006515338,0.000008886425,0.00005963343,0.00004156504,0.0025069534,0.0001529717,0.0207618,0.022633027,0.00015388563],"about_ca_topic_score_codex":0.00076846854,"about_ca_topic_score_gemma":0.00043209223,"teacher_disagreement_score":0.059431277,"about_ca_system_score_codex":0.000047685582,"about_ca_system_score_gemma":0.00012741185,"threshold_uncertainty_score":0.67622364},"labels":[],"label_agreement":null},{"id":"W2587656219","doi":"10.1007/s11682-016-9670-y","title":"Multi-site harmonization of diffusion MRI data in a registration framework","year":2017,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; University of Cincinnati","keywords":"Fractional anisotropy; Diffusion MRI; Computer science; Harmonization; Artificial intelligence; Pattern recognition (psychology); Image registration; Data mining; Statistics; Mathematics; Radiology; Medicine; Magnetic resonance imaging; Image (mathematics); Physics","score_opus":0.1189248562493965,"score_gpt":0.42021924601030924,"score_spread":0.3012943897609127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587656219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8252896,0.0001494527,0.1638833,0.009959365,0.000040260424,0.00047712997,0.000044332945,0.00008327092,0.000073291834],"genre_scores_gemma":[0.87396353,0.00011970895,0.12543234,0.00017032563,0.00002729429,0.000024116822,0.000096792384,0.000012035342,0.00015382585],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993817,0.000010520961,0.00016591874,0.00026738414,0.000086224376,0.00008825403],"domain_scores_gemma":[0.9987971,0.000029207282,0.0001458154,0.0009538936,0.00003704046,0.00003692585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013587766,0.000071011265,0.00011543735,0.000057857967,0.00012560606,0.000038699058,0.00014653022,0.000031320822,0.0000038276257],"category_scores_gemma":[0.00027975492,0.00006773138,0.00001364699,0.000049868297,0.00010791316,0.00019013917,0.00014480429,0.00013118381,8.081308e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013861386,0.00027569843,0.8176345,0.000034765075,9.4859416e-7,0.00001948005,0.00010648648,3.2701317e-7,0.13286789,0.00017189991,0.0004624214,0.048411727],"study_design_scores_gemma":[0.0005882113,0.000017132632,0.98726815,0.00028935677,0.00004526796,0.0000352561,0.000029366875,0.0077718715,0.0025074393,0.00018482048,0.001182629,0.00008052319],"about_ca_topic_score_codex":0.00014179238,"about_ca_topic_score_gemma":0.000014174967,"teacher_disagreement_score":0.16963363,"about_ca_system_score_codex":0.000010213504,"about_ca_system_score_gemma":0.000015551157,"threshold_uncertainty_score":0.27620053},"labels":[],"label_agreement":null},{"id":"W2589870402","doi":"10.1038/nn.4501","title":"Studying neuroanatomy using MRI","year":2017,"lang":"en","type":"review","venue":"Nature Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":335,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Hospital for Sick Children; University of Toronto","funders":"Engineering and Physical Sciences Research Council; Wellcome Trust","keywords":"Neuroanatomy; Neuroscience; Key (lock); Computer science; Neuroimaging; Brain function; Artificial intelligence; Cognitive science; Psychology","score_opus":0.334178582928508,"score_gpt":0.5299279926264469,"score_spread":0.19574940969793886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2589870402","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000037449893,0.99467295,0.0015663119,0.00019282631,0.00060298917,0.0013542573,0.000022582348,0.00030065948,0.0012836807],"genre_scores_gemma":[0.00009744318,0.9936899,0.004267825,0.0010596527,0.00022036828,0.000059873022,0.0000069682096,0.000080876096,0.00051710726],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99768573,0.000049479455,0.0003685566,0.0010484293,0.00045535262,0.00039244164],"domain_scores_gemma":[0.9975391,0.000078515106,0.0004994258,0.001616814,0.00008551095,0.00018061492],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0001596989,0.00040759245,0.0011082208,0.0002655192,0.0005510857,0.00012730519,0.00094293203,0.00035377467,0.000003571436],"category_scores_gemma":[0.00056346727,0.0003173081,0.00035439504,0.0005551592,0.0002791243,0.00017669944,0.00035374917,0.0024381527,0.000009084234],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000024946833,0.0001022746,0.000034427398,0.0032155772,0.00000531085,0.0003862149,0.000004019028,0.0000020763468,0.000072837574,0.000682969,0.0010243553,0.99446744],"study_design_scores_gemma":[0.000071459166,0.000040097784,0.000031535907,0.003159621,0.00030059915,0.0011655386,4.7655837e-7,0.00017491996,0.000007813051,0.00005696965,0.994758,0.00023294995],"about_ca_topic_score_codex":0.0000018054849,"about_ca_topic_score_gemma":1.327371e-7,"teacher_disagreement_score":0.9942345,"about_ca_system_score_codex":0.00007927427,"about_ca_system_score_gemma":0.00036407914,"threshold_uncertainty_score":0.9999279},"labels":[{"model":"gpt","categories":[],"domain":null,"study_design":"design_other","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"grok","categories":[],"domain":null,"study_design":"not_applicable","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"opus","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W2590116164","doi":"10.1088/1361-6560/aa5dbe","title":"DTI measurements for Alzheimer’s classification","year":2017,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Engineering and Physical Sciences Research Council; University of California, San Francisco; National Institute on Aging; Alzheimer's Disease Neuroimaging Initiative","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Neuroimaging; Feature selection; Alzheimer's Disease Neuroimaging Initiative; Artificial intelligence; Computer science; Alzheimer's disease; Psychology; Pattern recognition (psychology); Medicine; Disease; Neuroscience; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.8816298606038262,"score_gpt":0.5812535583468126,"score_spread":0.3003763022570136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590116164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35374668,0.0028731609,0.3969737,0.20282142,0.0007566397,0.0053781746,0.000060834605,0.0003763375,0.037013058],"genre_scores_gemma":[0.9923832,0.00024459526,0.006163523,0.0007468557,0.0002885177,0.00010684387,0.000037437738,0.000007226638,0.000021808357],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995742,0.000007313171,0.000112598864,0.00017560303,0.00003109578,0.00009919456],"domain_scores_gemma":[0.99950707,0.000039357103,0.000084354826,0.000285607,0.00005149653,0.000032117325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012783092,0.00006215826,0.00016021013,0.000023616261,0.000107777036,0.0000031873517,0.00007383474,0.000034055272,0.0000024033513],"category_scores_gemma":[0.00011932126,0.00004567266,0.000015832702,0.000023525763,0.00021363083,0.00002929426,0.000023436245,0.000074855016,7.258287e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012591694,0.00019062034,0.18721218,0.000063113155,0.000055374738,0.0000012143856,0.0001202582,4.7624397e-7,0.25229043,0.11884148,0.003916731,0.43718222],"study_design_scores_gemma":[0.007143254,0.0011546768,0.33617425,0.00035469685,0.00040142357,0.000026698614,0.0001396315,0.0032147227,0.018898048,0.5130452,0.11907113,0.00037626352],"about_ca_topic_score_codex":0.00001906441,"about_ca_topic_score_gemma":0.0000023869045,"teacher_disagreement_score":0.6386365,"about_ca_system_score_codex":0.000007952816,"about_ca_system_score_gemma":0.000010965498,"threshold_uncertainty_score":0.1862477},"labels":[],"label_agreement":null},{"id":"W2590185774","doi":"10.1016/j.neuroimage.2017.02.056","title":"Structural properties of the human corpus callosum: Multimodal assessment and sex differences","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital; University of Calgary","funders":"National Institute of Mental Health; Medical Research Council; National Institutes of Health; European Commission; Wellcome Trust","keywords":"Corpus callosum; Psychology; Natural language processing; Artificial intelligence; Computer science; Neuroscience","score_opus":0.13050249486350834,"score_gpt":0.3855794944059545,"score_spread":0.25507699954244617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590185774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970131,0.000023302928,0.000062782376,0.0013739989,0.000038156806,0.00034853947,0.000008365068,0.000050072194,0.0010817056],"genre_scores_gemma":[0.9980296,0.00001723101,0.0012027819,0.00014527226,0.000031263597,0.000019532528,8.7236197e-7,0.000012477694,0.0005409512],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994073,0.000019312443,0.00013119914,0.00019599695,0.0001398414,0.00010632955],"domain_scores_gemma":[0.9991336,0.000011162762,0.00013736163,0.00064426754,0.00003383497,0.000039763592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003158516,0.00009601895,0.00015719784,0.000015986923,0.00041974694,0.000040547744,0.00021602931,0.000021656373,0.000005791098],"category_scores_gemma":[0.00003207574,0.000056174737,0.000040429844,0.000018258557,0.00043267108,0.00006962647,0.00019568298,0.0001802769,2.6035906e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004427066,0.00002697325,0.4856502,0.000040179802,0.0000045238426,0.000004687849,0.00004521098,2.7782698e-7,0.5106396,0.0007396468,0.000046082354,0.0027981377],"study_design_scores_gemma":[0.0003043856,0.00006286596,0.9600753,0.000044496097,0.00002378994,0.00003217228,0.000010281276,0.0008226752,0.03787164,0.0005321842,0.00016243216,0.000057758527],"about_ca_topic_score_codex":0.000075015196,"about_ca_topic_score_gemma":0.0000037095863,"teacher_disagreement_score":0.4744251,"about_ca_system_score_codex":0.000009242803,"about_ca_system_score_gemma":0.00001791838,"threshold_uncertainty_score":0.32283965},"labels":[],"label_agreement":null},{"id":"W2590918729","doi":"","title":"Cleaning output of tractography via fiber to bundle coherence, a new open source implementation","year":2016,"lang":"en","type":"article","venue":"TU/e Research Portal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Coherence (philosophical gambling strategy); Tractography; Bundle; Computer science; Open source; Physics; Medicine; Materials science; Diffusion MRI; Radiology; Programming language; Software","score_opus":0.23658491046603872,"score_gpt":0.5110103378283268,"score_spread":0.27442542736228814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2590918729","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79283035,0.00006325921,0.14781842,0.015247131,0.00003479837,0.005737949,0.000085014246,0.00034130458,0.037841767],"genre_scores_gemma":[0.9748243,0.00001795933,0.01641154,0.0001333338,0.00007406286,0.00014243883,0.000017791446,0.000029956478,0.008348601],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99864614,0.000038312784,0.00025880607,0.00028976784,0.00043238324,0.00033459032],"domain_scores_gemma":[0.99897593,0.00011027543,0.000070202965,0.0003906813,0.0001852033,0.00026769895],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00044047096,0.00008623552,0.0001733433,0.00022828937,0.00008665641,0.00002506571,0.00027559165,0.000031110743,0.0012673989],"category_scores_gemma":[0.00007287316,0.00006350197,0.000056750698,0.00051215256,0.000086564745,0.00014860477,0.00022421645,0.00016042586,0.000080280326],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022022912,0.000331229,0.023512905,0.00003730518,0.000042731815,0.000020060232,0.00034749636,0.0000014304541,0.1789991,0.0020040767,0.12322272,0.6712607],"study_design_scores_gemma":[0.0035862913,0.0030205105,0.08961241,0.00051250344,0.00005459027,0.00011592539,0.0009457821,0.00003068428,0.21567313,0.009523067,0.67650443,0.00042065996],"about_ca_topic_score_codex":0.00063344446,"about_ca_topic_score_gemma":0.000037502898,"teacher_disagreement_score":0.6708401,"about_ca_system_score_codex":0.000023561839,"about_ca_system_score_gemma":0.00015417891,"threshold_uncertainty_score":0.9996456},"labels":[],"label_agreement":null},{"id":"W2592582590","doi":"10.1159/000456710","title":"White Matter Disruption and Connected Speech in Non-Fluent and Semantic Variants of Primary Progressive Aphasia","year":2017,"lang":"en","type":"article","venue":"Dementia and Geriatric Cognitive Disorders Extra","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; Sunnybrook Health Science Centre; Mount Sinai Hospital; Toronto Western Hospital; Hôpital du Sacré-Cœur de Montréal; University of Ottawa; Sinai Health System; Baycrest Hospital; Université de Montréal; Health Sciences Centre; University Health Network; University of Toronto; Heart and Stroke Foundation; Toronto Rehabilitation Institute","funders":"University of Toronto; Eli Lilly Canada; Morris Kerzner Memorial Fund; Canadian Institutes of Health Research; Toronto Rehabilitation Institute; Sunnybrook Research Institute","keywords":"Primary progressive aphasia; Diffusion MRI; White matter; Psychology; Natural language processing; Aphasia; Artificial intelligence; Computer science; Audiology; Medicine; Cognitive psychology; Pathology; Frontotemporal dementia","score_opus":0.017182474040084075,"score_gpt":0.30963321771317864,"score_spread":0.2924507436730946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592582590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919531,0.00095796835,0.004232111,0.0008040526,0.00001777039,0.0009751106,0.000024698167,0.000017330325,0.0010179112],"genre_scores_gemma":[0.99699694,0.0011981488,0.0014980367,0.0001267316,0.000015032856,0.000078146775,0.00003660118,0.0000143332145,0.000036050882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992247,0.000019112782,0.00020051726,0.0003155961,0.00008681942,0.00015322976],"domain_scores_gemma":[0.99951446,0.00003814798,0.00017657888,0.0001528229,0.000060755232,0.00005724682],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008340085,0.0001323194,0.00023504256,0.00011149159,0.00013454366,0.000037647253,0.000040094998,0.00004461653,0.000032678472],"category_scores_gemma":[0.00003164995,0.0001240838,0.000024099425,0.00007992933,0.00020429784,0.00012990778,0.00008867103,0.00009703149,8.798023e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011989656,0.00018963062,0.9422902,0.00024657795,0.000046132434,0.00002716304,0.00021806647,3.802952e-8,0.0018370006,0.000041674713,0.000037427533,0.0549462],"study_design_scores_gemma":[0.0022182036,0.00011544937,0.9954677,0.00016870695,0.00023866698,0.00005619585,0.00015719992,0.0001530015,0.00015603806,0.0011054962,0.00003941485,0.00012392558],"about_ca_topic_score_codex":0.000033088025,"about_ca_topic_score_gemma":0.00001185117,"teacher_disagreement_score":0.054822274,"about_ca_system_score_codex":0.000005604337,"about_ca_system_score_gemma":0.000012922725,"threshold_uncertainty_score":0.5059991},"labels":[],"label_agreement":null},{"id":"W2592815600","doi":"10.1117/12.2254418","title":"Automatic classification of patients with idiopathic Parkinson's disease and progressive supranuclear palsy using diffusion MRI datasets","year":2017,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Calgary","funders":"","keywords":"Progressive supranuclear palsy; Diffusion MRI; Support vector machine; Effective diffusion coefficient; Magnetic resonance imaging; Computer science; Parkinson's disease; Context (archaeology); Artificial intelligence; Pattern recognition (psychology); Medicine; Disease; Radiology; Pathology","score_opus":0.024586228229855636,"score_gpt":0.28678156296573015,"score_spread":0.26219533473587453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592815600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970613,0.00008811824,0.00009580715,0.0015161226,0.000028837816,0.0009372964,0.00015314504,0.000059973852,0.000059397335],"genre_scores_gemma":[0.9086881,0.00008499648,0.090949915,0.00003564993,0.00007239029,0.000094365845,0.000028197823,0.00004035665,0.0000059864483],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99853724,1.9574534e-8,0.00043094865,0.00033616932,0.00049482967,0.00020080253],"domain_scores_gemma":[0.99802643,0.000033390632,0.00071327743,0.0001400954,0.0009499636,0.00013684618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022162066,0.00020900072,0.00033957156,0.00006276463,0.00016772225,0.00007081293,0.00044405065,0.00007874708,0.0000028561847],"category_scores_gemma":[0.00043765918,0.00015701007,0.00017196716,0.00009965092,0.00041555878,0.00043181758,0.00017874797,0.0001929446,1.6271414e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009135623,0.0010749088,0.14755225,0.004343982,0.00048863643,7.3337026e-7,0.00021725161,0.000020975125,0.6535182,0.18781108,0.00083589857,0.0032225458],"study_design_scores_gemma":[0.0040037185,0.00088347,0.76200193,0.004019768,0.0010494445,0.000022709834,0.00040218423,0.18793331,0.03519734,0.0017532433,0.002168244,0.00056464365],"about_ca_topic_score_codex":0.000003672721,"about_ca_topic_score_gemma":2.977357e-8,"teacher_disagreement_score":0.6183208,"about_ca_system_score_codex":0.00006213281,"about_ca_system_score_gemma":0.000030771767,"threshold_uncertainty_score":0.6402685},"labels":[],"label_agreement":null},{"id":"W2593343929","doi":"10.1016/j.neuroimage.2017.08.038","title":"Promise and pitfalls of g-ratio estimation with MRI","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; McGill University; University of Calgary; Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec","keywords":"Estimation; Computer science; Medicine; Economics","score_opus":0.20888363962043036,"score_gpt":0.4534811352873786,"score_spread":0.24459749566694824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593343929","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009666308,0.9794197,0.012505051,0.00021354333,0.000022370108,0.0026179682,0.000054769258,0.00017923002,0.004977703],"genre_scores_gemma":[0.000059911665,0.9646399,0.034350168,0.000029671352,0.00003688445,0.0001684903,0.00006013027,0.00006286926,0.0005919948],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99898446,0.000026697895,0.00032154226,0.00039428478,0.00014632472,0.00012667078],"domain_scores_gemma":[0.9984089,0.00007754281,0.00049068185,0.0008802164,0.000064958775,0.00007769275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065993496,0.00024630857,0.0009273421,0.00010541783,0.00009629758,0.00003026881,0.00014126416,0.00007961921,0.0000069943158],"category_scores_gemma":[0.0001087387,0.00017778533,0.00009986082,0.000085869266,0.00018080759,0.00009691332,0.00006700102,0.00028823988,0.000006710329],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000115962275,0.00006750306,0.000011974736,0.012026878,0.000019816789,0.000046979807,0.000009258104,3.75354e-7,0.000037450427,0.0004202428,0.00037395986,0.98697394],"study_design_scores_gemma":[0.00028395414,0.00024940417,0.00010362808,0.00786079,0.00074607955,0.0004903618,7.982589e-7,0.00016978706,0.000051096576,0.000107296255,0.98974985,0.00018695595],"about_ca_topic_score_codex":0.000003211066,"about_ca_topic_score_gemma":6.67977e-7,"teacher_disagreement_score":0.9893759,"about_ca_system_score_codex":0.000015257824,"about_ca_system_score_gemma":0.00013226255,"threshold_uncertainty_score":0.7249875},"labels":[],"label_agreement":null},{"id":"W2593832538","doi":"10.17975/sfj-2017-006","title":"Comparison of Tractography in Mouse Models of Multiple Sclerosis and Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"STEM Fellowship Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Tractography; Corpus callosum; Neuroscience; Multiple sclerosis; Magnetic resonance imaging; Biology; Diffusion MRI; Artificial intelligence; Pathology; Psychology; Computer science; Medicine; Radiology","score_opus":0.3294660013029526,"score_gpt":0.407705977781786,"score_spread":0.0782399764788334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593832538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937765,0.0011586047,0.0041128662,0.00044554874,0.000019340581,0.00022649961,0.000021308782,0.000015009693,0.00022432503],"genre_scores_gemma":[0.99461573,0.00040384222,0.004896026,0.000021825572,0.000020775724,0.000007606209,0.0000013348296,0.000013978175,0.000018876719],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99921596,0.00002145438,0.00035735406,0.00012449572,0.0001582122,0.0001225199],"domain_scores_gemma":[0.9989692,0.000046629284,0.00038882162,0.00035731008,0.0000750713,0.00016297422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014892842,0.000087910375,0.0002925026,0.00012923242,0.000114611285,0.00001940044,0.00014491961,0.00003182895,0.0000031263994],"category_scores_gemma":[0.000028878487,0.00007660275,0.00009250408,0.00005222266,0.00016976304,0.00016484865,0.00003973796,0.00023548152,1.9107186e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025182316,0.0004182814,0.95453393,0.000058219088,0.00003069677,0.0000079180245,0.00030123032,0.00016852374,0.03357462,0.0003842317,0.00010729064,0.010163246],"study_design_scores_gemma":[0.003214998,0.0002815705,0.8695341,0.0009039629,0.00028635497,0.000038637678,0.0004852254,0.02237867,0.09714932,0.0052827336,0.00020806509,0.00023640307],"about_ca_topic_score_codex":0.00001974196,"about_ca_topic_score_gemma":0.0000051140933,"teacher_disagreement_score":0.08499986,"about_ca_system_score_codex":0.000007667708,"about_ca_system_score_gemma":0.000028807492,"threshold_uncertainty_score":0.31237695},"labels":[],"label_agreement":null},{"id":"W2594251290","doi":"10.1007/s00429-016-1356-0","title":"Magnetic resonance diffusion tensor imaging for the pedunculopontine nucleus: proof of concept and histological correlation","year":2017,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute on Aging; Sociedade Beneficente Israelita Brasileira Albert Einstein; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Pedunculopontine nucleus; Fractional anisotropy; Medial lemniscus; Diffusion MRI; White matter; Anatomy; Magnetic resonance imaging; Brainstem; Lateral lemniscus; Neuroscience; Nuclear magnetic resonance; Nucleus; Chemistry; Inferior colliculus; Medicine; Pathology; Physics; Psychology; Deep brain stimulation; Parkinson's disease; Radiology","score_opus":0.02637555752708965,"score_gpt":0.29535414324876114,"score_spread":0.2689785857216715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594251290","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61357266,0.009838363,0.3436334,0.029406514,0.00032037083,0.0025556854,0.000083481675,0.00013123342,0.00045829083],"genre_scores_gemma":[0.994677,0.000055356908,0.004220547,0.00044713347,0.000098540906,0.000025988604,0.0000138162995,0.000008885844,0.0004527267],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99956536,0.000007976376,0.00011252439,0.00017714298,0.00006196248,0.00007502138],"domain_scores_gemma":[0.9994667,0.000098182376,0.00012031994,0.00022806122,0.00006197032,0.000024773597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005015962,0.00007406692,0.000114046954,0.000017959403,0.00034073213,0.000017283197,0.000041106778,0.000038673872,0.000011270396],"category_scores_gemma":[0.00020886109,0.00004641648,0.000022957045,0.000022155795,0.00022959556,0.000057923815,0.000033491957,0.000089115034,4.2812665e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042992755,0.000028096034,0.066452816,0.000057782483,0.000005918854,0.0000014301405,0.00017384223,0.0000058983883,0.01805631,0.0059000924,0.0048737833,0.9040141],"study_design_scores_gemma":[0.0010643484,0.0002818192,0.8795985,0.000046844554,0.000095517964,0.00008378496,0.000047767513,0.010409625,0.00077211164,0.0076680547,0.09985432,0.000077276134],"about_ca_topic_score_codex":0.000008107807,"about_ca_topic_score_gemma":0.0000018563398,"teacher_disagreement_score":0.9039368,"about_ca_system_score_codex":0.0000068868544,"about_ca_system_score_gemma":0.000007284152,"threshold_uncertainty_score":0.26206705},"labels":[],"label_agreement":null},{"id":"W2594651183","doi":"10.1016/j.jagp.2017.02.021","title":"Stage-Dependent Significance of Subjective Memory Complaints: Responding to the Worried Well … and to the Unworried Unwell","year":2017,"lang":"en","type":"letter","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Dementia; Neuropsychology; Psychology; Fractional anisotropy; Neurocognitive; Cognitive decline; Psychiatry; Cognition; Clinical psychology; Disease; Montreal Cognitive Assessment; Medicine; Cognitive impairment; White matter; Internal medicine","score_opus":0.027396020033645097,"score_gpt":0.32928781890592185,"score_spread":0.30189179887227674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594651183","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036669273,0.0008586906,0.01759448,0.93935585,0.0014896404,0.0019852712,0.00016960828,0.000050699997,0.0018265009],"genre_scores_gemma":[0.37816775,0.001106788,0.055067085,0.5430633,0.013211411,0.00020629073,0.000022709739,0.00034034502,0.008814313],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997217,0.00028146605,0.00089294545,0.0004917639,0.0006919558,0.0004248446],"domain_scores_gemma":[0.9951401,0.00047181864,0.002411796,0.0014035729,0.00034883234,0.00022389476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008784264,0.00039629932,0.000986267,0.00060222665,0.00039321228,0.00007027175,0.0011575213,0.00011752793,0.00003362985],"category_scores_gemma":[0.0002333541,0.0002446171,0.00027525544,0.0010543443,0.000441509,0.000071794486,0.00019814199,0.002076034,0.0000135980135],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015893534,0.000115066214,0.0028011352,0.00013859694,0.00029780253,0.00015800558,0.000694257,0.0001515742,0.0005440493,0.00016168227,0.98401594,0.009332555],"study_design_scores_gemma":[0.00082888664,0.0018217646,0.007484597,0.00051709387,0.00056943105,0.0007779656,0.0015288179,0.000011667842,0.00026337215,0.00044842125,0.9853221,0.00042584183],"about_ca_topic_score_codex":0.00008615153,"about_ca_topic_score_gemma":0.00001080573,"teacher_disagreement_score":0.39629254,"about_ca_system_score_codex":0.00014213975,"about_ca_system_score_gemma":0.000492299,"threshold_uncertainty_score":0.9975196},"labels":[],"label_agreement":null},{"id":"W2597202272","doi":"10.1155/2017/9807512","title":"Thalamocortical Connectivity and Microstructural Changes in Congenital and Late Blindness","year":2017,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"H. Lundbeck A/S; Danmarks Frie Forskningsfond; Lundbeckfonden; Sundhed og Sygdom, Det Frie Forskningsråd","keywords":"Tractography; Neuroscience; Diffusion MRI; Thalamus; Cortex (anatomy); White matter; Fractional anisotropy; Connectomics; Visual cortex; Psychology; Magnetic resonance imaging; Connectome; Functional connectivity; Medicine","score_opus":0.06990996027466524,"score_gpt":0.35359893949321963,"score_spread":0.2836889792185544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597202272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99733764,0.000017559729,0.00011665037,0.0020650611,0.000035921414,0.00024682103,0.000018297103,0.000050402556,0.000111636204],"genre_scores_gemma":[0.9992037,0.000018739283,0.000505785,0.00016716839,0.00004126427,0.000014985774,0.000002167181,0.000008749085,0.00003745322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945134,0.000009867527,0.00008338217,0.00023992299,0.00005900553,0.00015646956],"domain_scores_gemma":[0.99958396,0.00010036387,0.000048665075,0.00015277472,0.00002324574,0.000090999456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029341385,0.00009993369,0.00017262736,0.00003168366,0.00016645266,0.000049722235,0.000052613963,0.000045025827,0.0000061423293],"category_scores_gemma":[0.0002296781,0.00008375193,0.00001262548,0.00002314719,0.00031188884,0.00009841277,0.00011668884,0.00020365845,7.0181346e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020127207,0.00006102548,0.8417218,0.000046557463,0.000007444041,0.00009568278,0.000065643864,0.0000014353129,0.14896512,0.0006083828,0.000021756005,0.0082039],"study_design_scores_gemma":[0.0006942058,0.000107358625,0.98164356,0.000017482493,0.000020409749,0.00017852294,0.000006709112,0.00407,0.012408858,0.0007190875,0.00005088283,0.00008293265],"about_ca_topic_score_codex":0.000048803253,"about_ca_topic_score_gemma":0.000108537606,"teacher_disagreement_score":0.13992177,"about_ca_system_score_codex":0.000009665789,"about_ca_system_score_gemma":0.000007388855,"threshold_uncertainty_score":0.34153047},"labels":[],"label_agreement":null},{"id":"W2598029772","doi":"10.3389/fneur.2017.00097","title":"Investigating Microstructural Abnormalities and Neurocognition in Sub-Acute and Chronic Traumatic Brain Injury Patients with Normal-Appearing White Matter: A Preliminary Diffusion Tensor Imaging Study","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; Ontario Neurotrauma Foundation","keywords":"Fractional anisotropy; Diffusion MRI; Traumatic brain injury; White matter; Neuropsychology; Neurocognitive; Neuroimaging; Medicine; Psychology; Physical medicine and rehabilitation; Cardiology; Audiology; Internal medicine; Cognition; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.01456521141226421,"score_gpt":0.2795929995735592,"score_spread":0.265027788161295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598029772","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960433,0.00006186395,0.0002804671,0.0023128898,0.00006754912,0.0011359841,0.000013020363,0.000048596346,0.00003632071],"genre_scores_gemma":[0.99587107,0.000039472965,0.0026975435,0.0011890256,0.000021488713,0.00011200206,0.000017822525,0.00003415197,0.0000174299],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99881756,0.00007777997,0.0002838948,0.0004326145,0.00009287001,0.00029526546],"domain_scores_gemma":[0.9993634,0.000030160301,0.00018640564,0.00032424257,0.000026541753,0.00006921425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008818548,0.00019359552,0.0003066931,0.00022449889,0.00023139577,0.000055653833,0.000111804366,0.000044555385,0.0000016082101],"category_scores_gemma":[0.000043704495,0.00017895659,0.000015275189,0.0000729454,0.00034716798,0.00030753016,0.00021141996,0.00040622137,3.8759856e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026724386,0.000076030716,0.99232656,0.00008359217,0.000006125985,0.00005782986,0.0005934213,0.000003938405,0.0008444543,0.000001414282,0.00014481986,0.0055945753],"study_design_scores_gemma":[0.0023731883,0.0009916296,0.9929028,0.00011350872,0.000038714286,0.0001512976,0.00012334979,0.0028314749,0.00008728276,0.00021242088,0.00002686732,0.00014746262],"about_ca_topic_score_codex":0.000046261986,"about_ca_topic_score_gemma":0.00002510665,"teacher_disagreement_score":0.005447113,"about_ca_system_score_codex":0.000026109612,"about_ca_system_score_gemma":0.000016576465,"threshold_uncertainty_score":0.72976375},"labels":[],"label_agreement":null},{"id":"W2598260296","doi":"","title":"Structural connectivity reproducibility through multiple acquisitions","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Reproducibility; Tractography; Probabilistic logic; Computer science; Artificial intelligence; Pattern recognition (psychology); Diffusion MRI; Mathematics; Statistics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.08295902571810543,"score_gpt":0.33597663976552244,"score_spread":0.253017614047417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598260296","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64940315,0.00087981264,0.27035946,0.04024268,0.00022410513,0.0020313035,0.0003798577,0.0014887062,0.03499091],"genre_scores_gemma":[0.8338534,0.00014498913,0.16237287,0.00025954322,0.000052803123,0.00019466145,0.0008865908,0.000054573917,0.0021805437],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951639,0.0017929078,0.0005259717,0.0018004201,0.0003846464,0.0003321351],"domain_scores_gemma":[0.9888922,0.00089750625,0.0004385679,0.006486135,0.0030583988,0.00022718159],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003869794,0.0003558004,0.0005210746,0.00009238952,0.0003555656,0.00012603728,0.0006173916,0.00025610632,0.00009798894],"category_scores_gemma":[0.0061929002,0.0003636086,0.00025214112,0.00033926952,0.00039328958,0.00015216791,0.0013710685,0.000986385,0.000023970972],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005624011,0.008937048,0.20568934,0.0030045577,0.0009001982,0.00012210052,0.039697327,0.0011755102,0.06640976,0.4642367,0.06224809,0.14701697],"study_design_scores_gemma":[0.0040386915,0.0000051372162,0.11866575,0.004649031,0.0006051603,0.00035644948,0.0003463052,0.06651424,0.293698,0.42730442,0.08147843,0.0023383694],"about_ca_topic_score_codex":0.0009507752,"about_ca_topic_score_gemma":0.00026917987,"teacher_disagreement_score":0.22728825,"about_ca_system_score_codex":0.00025026052,"about_ca_system_score_gemma":0.00039854422,"threshold_uncertainty_score":0.99988157},"labels":[],"label_agreement":null},{"id":"W2598379557","doi":"10.15353/vsnl.v2i1.107","title":"Sparse Correlated Diffusion Imaging: A New Computational Diffusion MRI Modality for Prostate Cancer Detection","year":2016,"lang":"en","type":"article","venue":"Journal of Computational Vision and Imaging Systems","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Toronto; Sunnybrook Health Science Centre","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Diffusion MRI; Modality (human–computer interaction); Prostate cancer; Magnetic resonance imaging; Diffusion; Computer science; Radiology; Artificial intelligence; Medicine; Cancer; Physics; Internal medicine","score_opus":0.028915644810776697,"score_gpt":0.34722755198007604,"score_spread":0.31831190716929936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598379557","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15649793,0.0006869321,0.8287923,0.012926774,0.0003602427,0.00061176176,0.000029220533,0.00007385321,0.000021003827],"genre_scores_gemma":[0.9848684,0.00017689564,0.013917316,0.00035334702,0.00027069228,0.000021551055,0.000016822813,0.00003218001,0.00034280546],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99834627,0.00005450208,0.00071950635,0.00024413959,0.0004486529,0.00018695425],"domain_scores_gemma":[0.99789304,0.00030421422,0.0006523582,0.00011477183,0.0008057509,0.00022984605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031231056,0.00019043392,0.0003527476,0.00025286147,0.00020238709,0.00007600601,0.0000795499,0.000037334856,0.000009425605],"category_scores_gemma":[0.000083400984,0.00012510816,0.00013205253,0.00017128771,0.00008599274,0.00033094792,0.000043170792,0.0001584538,0.0000022142224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029156434,0.00092106126,0.106816284,0.0004749002,0.00017494532,0.00006575063,0.0007680294,0.05272993,0.122606166,0.00341374,0.02571442,0.68339914],"study_design_scores_gemma":[0.0077807936,0.00036004584,0.10799236,0.0019574894,0.00015150617,0.002006422,0.00011860402,0.8297665,0.0004318979,0.029087506,0.020027941,0.00031893273],"about_ca_topic_score_codex":0.000039708273,"about_ca_topic_score_gemma":6.150124e-7,"teacher_disagreement_score":0.82837045,"about_ca_system_score_codex":0.00014963654,"about_ca_system_score_gemma":0.00018168372,"threshold_uncertainty_score":0.5101763},"labels":[],"label_agreement":null},{"id":"W2599979438","doi":"10.1093/schbul/sbx024.081","title":"SU85. The Behavioral and Neural Correlates of Social Cognition in Youth With Mental Illness","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Psychology; Neurocognitive; Social cognition; Cognition; Schizophrenia (object-oriented programming); Autism spectrum disorder; Bipolar disorder; Fractional anisotropy; Autism; White matter; Psychiatry; Clinical psychology; Medicine; Magnetic resonance imaging","score_opus":0.04380205161097011,"score_gpt":0.3247954440957202,"score_spread":0.2809933924847501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2599979438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99324834,0.000027964528,0.000058902893,0.0059069586,0.000023359647,0.00034966122,0.000042399843,0.000033587643,0.00030883495],"genre_scores_gemma":[0.9987364,0.000015746731,0.0010039821,0.00007188241,0.000035973324,0.000031168427,0.00003143237,0.000013756749,0.000059673734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995084,0.000015130796,0.000119435485,0.00014997699,0.00010047405,0.00010661604],"domain_scores_gemma":[0.99961215,0.00001410689,0.00011629912,0.00020043182,0.000029873827,0.000027155604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006208531,0.000086347776,0.00013532884,0.000028320981,0.0002919156,0.000022205495,0.00009247164,0.000032926197,0.000028859604],"category_scores_gemma":[0.000012285101,0.00005818306,0.00002452286,0.000030503594,0.00033730292,0.000028882028,0.0000607004,0.00018419388,0.0000023051045],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021454372,0.0028769313,0.6470744,0.0002688076,0.00013510908,0.00024690278,0.018113349,0.000010295679,0.03300468,0.020153766,0.005400207,0.25126114],"study_design_scores_gemma":[0.009658848,0.00075113046,0.97152674,0.00029425058,0.00037801114,0.00023290813,0.0024083236,0.00025669107,0.008937447,0.0013736296,0.003721336,0.00046067566],"about_ca_topic_score_codex":0.0000677798,"about_ca_topic_score_gemma":0.000018675204,"teacher_disagreement_score":0.32445234,"about_ca_system_score_codex":0.000008176144,"about_ca_system_score_gemma":0.000011966321,"threshold_uncertainty_score":0.23726363},"labels":[],"label_agreement":null},{"id":"W2599999445","doi":"10.1093/schbul/sbx021.111","title":"72. Behavioral and Neurobiological Correlates of Attention in Schizophrenia in a Virtual Environment","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Fractional anisotropy; Cognition; Neurocognitive; Schizophrenia (object-oriented programming); Effects of sleep deprivation on cognitive performance; Diffusion MRI; Cognitive psychology; Audiology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04149820874313977,"score_gpt":0.3130314617268467,"score_spread":0.27153325298370695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2599999445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971244,0.000101678655,0.00018131372,0.0019470078,0.00003742794,0.0004253518,0.00001298314,0.00004084302,0.00012903681],"genre_scores_gemma":[0.9930396,0.00021423795,0.0064243264,0.000043897428,0.000025384268,0.00006602336,0.000016674043,0.000017585115,0.00015227735],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891704,0.00003702001,0.00033817254,0.00037969372,0.00011158634,0.00021646211],"domain_scores_gemma":[0.9992255,0.000036323236,0.00017005867,0.00048471804,0.000012948377,0.00007046765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015919571,0.00015485546,0.00030026626,0.00011780919,0.00009516,0.000018864974,0.00015646937,0.0001010795,0.00008086672],"category_scores_gemma":[0.00006746753,0.00014075666,0.00005387739,0.00004666507,0.00029459386,0.000041447583,0.00020902973,0.000365542,0.000025096713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043593724,0.0017074568,0.82483405,0.000060533614,0.000013263612,0.00025245987,0.000096668045,0.00005137137,0.10855574,0.008750639,0.00043567145,0.050882764],"study_design_scores_gemma":[0.00349391,0.00047035806,0.9919708,0.00015672763,0.000024346225,0.000058994458,0.000020360903,0.00019273146,0.0009969213,0.0011625506,0.0012949721,0.00015733407],"about_ca_topic_score_codex":0.00005548231,"about_ca_topic_score_gemma":0.000010113222,"teacher_disagreement_score":0.16713673,"about_ca_system_score_codex":0.00002729021,"about_ca_system_score_gemma":0.000015121961,"threshold_uncertainty_score":0.573989},"labels":[],"label_agreement":null},{"id":"W2600405717","doi":"10.1101/120857","title":"Anatomical and functional organization of the human substantia nigra and its connections","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Substantia nigra; Salience (neuroscience); Human brain; Impulsivity; Striatum; Psychology; Human Connectome Project; Functional connectivity; Ventral striatum; Functional organization; Dopamine; Dopaminergic; Developmental psychology","score_opus":0.041946824727498215,"score_gpt":0.2840982228182877,"score_spread":0.2421513980907895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2600405717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99544895,0.00052992225,0.0018549535,0.0011941779,0.00013090421,0.00056865235,0.00009535002,0.00017147452,0.0000056445942],"genre_scores_gemma":[0.9980513,0.00041214432,0.001240509,0.00009033634,0.00010637073,0.000040153478,5.894994e-7,0.000050062623,0.000008521845],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990144,0.000026605103,0.00023561572,0.00043529243,0.00015365388,0.00013447525],"domain_scores_gemma":[0.99840224,0.00002782373,0.0002898409,0.00073170965,0.00044884646,0.00009956047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113780785,0.00019156125,0.000269177,0.00009913521,0.0003734225,0.00005008568,0.00013470568,0.00018357532,0.000013367989],"category_scores_gemma":[0.00021248277,0.00016733384,0.00004405263,0.00019621705,0.00019966102,0.000061034636,0.00030967305,0.00042232865,0.0000012080288],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004984265,0.00006763434,0.1066566,0.0001780113,0.000042174164,0.0000027323244,0.0000033929955,0.0000021264339,0.87772596,0.015119634,0.00019517101,0.0000015833799],"study_design_scores_gemma":[0.00028914766,0.00001510772,0.71106124,0.00020833335,0.00014748357,2.0887079e-7,8.0324105e-7,0.00016950969,0.2863587,0.00003435518,0.001555928,0.00015918486],"about_ca_topic_score_codex":0.000010845623,"about_ca_topic_score_gemma":8.78573e-7,"teacher_disagreement_score":0.6044046,"about_ca_system_score_codex":0.000045214503,"about_ca_system_score_gemma":0.0001502495,"threshold_uncertainty_score":0.68236756},"labels":[],"label_agreement":null},{"id":"W2602101619","doi":"10.1016/j.neuroimage.2017.03.065","title":"Validating myelin water imaging with transmission electron microscopy in a rat spinal cord injury model","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Myelin; Spinal cord; Spinal cord injury; White matter; Chemistry; Electron microscope; Pathology; Biophysics; Anatomy; Neuroscience; Biology; Central nervous system; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.05049683749905037,"score_gpt":0.3986401592412709,"score_spread":0.3481433217422205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2602101619","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9241254,0.00003550646,0.06769668,0.0058967527,0.000025056206,0.00062180066,0.0000048840343,0.00022577873,0.0013681552],"genre_scores_gemma":[0.95044196,0.000056458175,0.048091494,0.00088973664,0.000044648652,0.000055708377,0.000012851403,0.00006117027,0.00034596105],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986732,0.000020994707,0.00023629286,0.00049160013,0.00016833146,0.0004095672],"domain_scores_gemma":[0.9989934,0.000009057829,0.00009216957,0.0007555902,0.00004997533,0.0000997998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011919215,0.00020364954,0.00023636612,0.00010102954,0.0003020802,0.00009408391,0.00023530106,0.000033100656,0.000010704004],"category_scores_gemma":[0.000021810007,0.00014916845,0.00005291616,0.000058523437,0.00012009691,0.0002718079,0.00007390093,0.00046259016,0.000009878349],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009988244,0.000078120196,0.002879015,0.00003823925,0.0000014637171,0.000098294644,0.000026788466,0.000018569363,0.978315,0.00004852839,0.00019798361,0.017299162],"study_design_scores_gemma":[0.0010795824,0.00063533743,0.0026763552,0.00024817727,0.000033673212,0.00014620696,0.000005860978,0.021611417,0.96847147,0.0008647885,0.003996137,0.0002309914],"about_ca_topic_score_codex":0.000022673083,"about_ca_topic_score_gemma":0.0000015214257,"teacher_disagreement_score":0.02631659,"about_ca_system_score_codex":0.000044035743,"about_ca_system_score_gemma":0.00004661624,"threshold_uncertainty_score":0.60829127},"labels":[],"label_agreement":null},{"id":"W2604506905","doi":"10.3390/brainsci7040037","title":"Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Meso Scale Diagnostics; F. Hoffmann-La Roche; University of Southern California; Biogen; BioClinica; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Tractography; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Psychology; Fractional anisotropy; Artificial intelligence; Cognitive impairment; Computer science; Cognition; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.14223717141486394,"score_gpt":0.42844495725609366,"score_spread":0.28620778584122974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604506905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8236048,0.00045411446,0.0047803847,0.17014481,0.000027938046,0.000676408,0.000030692532,0.00012778882,0.00015303741],"genre_scores_gemma":[0.979486,0.0000071354693,0.018015493,0.002201823,0.00017094464,0.000028171515,0.000024273393,0.000010513574,0.000055682467],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99876416,0.000036354355,0.00017313489,0.00038096125,0.0003278064,0.00031756132],"domain_scores_gemma":[0.998739,0.00019736265,0.0002299301,0.00044568724,0.000051678595,0.0003363444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042635776,0.00013364307,0.00020533893,0.000057243054,0.00128639,0.00024200552,0.00032846123,0.000029909439,0.0000031628354],"category_scores_gemma":[0.00019646097,0.000096678836,0.00002081153,0.00021270278,0.000906599,0.00032046062,0.00009767121,0.00013950418,0.0000026825658],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002517584,0.000012144917,0.9867065,0.0000128055735,0.0000105480585,0.0000023533282,0.00007065018,0.000040060306,0.000053305324,0.0010736162,0.007155969,0.004836856],"study_design_scores_gemma":[0.00043497837,0.0003723146,0.98769075,0.000105223844,0.00005328316,0.000012783913,0.000040203733,0.00051547366,0.0000444856,0.0029891997,0.00761682,0.00012446509],"about_ca_topic_score_codex":0.00006384001,"about_ca_topic_score_gemma":0.000019127458,"teacher_disagreement_score":0.16794299,"about_ca_system_score_codex":0.000012869568,"about_ca_system_score_gemma":0.00018334613,"threshold_uncertainty_score":0.9894002},"labels":[],"label_agreement":null},{"id":"W2604855401","doi":"10.1007/s00234-017-1816-0","title":"Diffusion tensor imaging as a prognostic biomarker for motor recovery and rehabilitation after stroke","year":2017,"lang":"en","type":"review","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":146,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Diffusion MRI; Medicine; Stroke recovery; Corticospinal tract; Stroke (engine); Physical medicine and rehabilitation; Rehabilitation; Neurology; Neuroradiology; White matter; Biomarker; Neuroplasticity; Clinical trial; Physical therapy; Magnetic resonance imaging; Radiology; Internal medicine","score_opus":0.11026459000338917,"score_gpt":0.42646614135719596,"score_spread":0.3162015513538068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604855401","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00099838,0.98922706,0.0016259005,0.0014681411,0.00024618904,0.005701895,0.00027522558,0.0002275277,0.00022969782],"genre_scores_gemma":[0.00028745036,0.983881,0.010765608,0.00038849603,0.00016856103,0.0034035558,0.00013389424,0.000103974366,0.000867462],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983582,0.00010230761,0.00043153844,0.00075010676,0.000075606185,0.0002822233],"domain_scores_gemma":[0.9975549,0.0011608137,0.0003523948,0.0007367814,0.00008587449,0.00010926117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013545422,0.00033445886,0.0011446617,0.00026052957,0.00013843348,0.000029731817,0.00014100736,0.00018694281,0.000008841544],"category_scores_gemma":[0.0018093848,0.00026715166,0.00035569322,0.00005708672,0.00026328344,0.00007052907,0.000102023274,0.00030451763,0.00001089879],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001479302,0.000061588325,0.001665058,0.004926116,0.000029005112,0.000039844814,0.0000062209147,9.819564e-9,0.00006577919,0.00009230839,0.0010220781,0.9919441],"study_design_scores_gemma":[0.0003278472,0.00073974923,0.0048292326,0.0023313384,0.00068283256,0.0010763989,0.0000016096261,0.00005789215,4.041048e-7,0.00060329237,0.9891456,0.00020381082],"about_ca_topic_score_codex":0.000003511068,"about_ca_topic_score_gemma":3.8210277e-7,"teacher_disagreement_score":0.9917402,"about_ca_system_score_codex":0.00004967168,"about_ca_system_score_gemma":0.00009626407,"threshold_uncertainty_score":0.99997807},"labels":[],"label_agreement":null},{"id":"W2605823361","doi":"10.1002/hbm.23622","title":"Contributions of imprecision in<scp>PET</scp>‐<scp>MRI</scp>rigid registration to imprecision in amyloid<scp>PET</scp><scp>SUVR</scp>measurements","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Genentech; IXICO; Elsie and Marvin Dekelboum Family Foundation; Canadian Institutes of Health Research; GHR Foundation; F. Hoffmann-La Roche; Biogen; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Hum; White matter; Orientation (vector space); Artificial intelligence; Positron emission tomography; Image registration; Pattern recognition (psychology); Nuclear medicine; Computer science; Magnetic resonance imaging; Mathematics; Medicine; Radiology; Image (mathematics)","score_opus":0.10033635084873678,"score_gpt":0.38027108839224305,"score_spread":0.2799347375435063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605823361","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9254271,0.00040607018,0.051112752,0.0013396939,0.00037681294,0.0041242233,0.00019993747,0.0005697442,0.016443666],"genre_scores_gemma":[0.97816473,0.00027666663,0.012957199,0.00113097,0.0004927169,0.00068196683,0.00039158188,0.0001937265,0.005710454],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99259704,0.00033080473,0.0022102906,0.0018215785,0.0014763955,0.0015638924],"domain_scores_gemma":[0.99044144,0.003305132,0.0016472116,0.0030709354,0.0008906305,0.0006446545],"candidate_categories":["metaresearch","metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0028471819,0.00090783945,0.0014175569,0.0013313304,0.0013621106,0.00037262426,0.0014549352,0.00039486858,0.0000111784375],"category_scores_gemma":[0.022393955,0.0009752177,0.00042112492,0.0011427775,0.00040829123,0.00091368327,0.0007035342,0.0014274868,0.00010892835],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015783948,0.00095514685,0.023247292,0.0002991547,0.00009011665,0.0001909928,0.0022500912,0.0003387275,0.8699277,0.0039886227,0.09585778,0.0028385848],"study_design_scores_gemma":[0.009646388,0.001233255,0.5063393,0.005198015,0.00022922739,0.0003369483,0.004324798,0.0030499934,0.09177017,0.03309836,0.344411,0.00036253396],"about_ca_topic_score_codex":0.000317775,"about_ca_topic_score_gemma":0.00030224732,"teacher_disagreement_score":0.77815753,"about_ca_system_score_codex":0.0007385065,"about_ca_system_score_gemma":0.00028966402,"threshold_uncertainty_score":0.99993795},"labels":[],"label_agreement":null},{"id":"W2605983219","doi":"10.2214/ajr.17.18064","title":"Hallway Conversations in Physics","year":2017,"lang":"en","type":"article","venue":"American Journal of Roentgenology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Medicine; Tractography; White matter; Radiology; Magnetic resonance imaging","score_opus":0.07514372012561657,"score_gpt":0.39176554367246197,"score_spread":0.3166218235468454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2605983219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.940904,0.000056005796,0.034436528,0.0224616,0.000091755115,0.00012600282,0.000002663166,0.000020221514,0.0019012011],"genre_scores_gemma":[0.98263603,0.00018990159,0.01649598,0.0005207024,0.000094639145,0.0000028462698,5.4600525e-7,0.00000818947,0.00005118416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99953455,0.000015676036,0.00019428329,0.00007472407,0.00006678712,0.00011398395],"domain_scores_gemma":[0.99906117,0.000030721174,0.00046803014,0.00029705066,0.00008875875,0.000054260163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006279591,0.000051910985,0.00022410708,0.000066942695,0.00006424183,0.000006855015,0.00016447295,0.000012953234,0.000013508225],"category_scores_gemma":[0.000111230234,0.000045806795,0.000055037875,0.00005697058,0.0003620213,0.000070362694,0.000031813597,0.00019854707,0.000005145028],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000245123,0.0005176939,0.5940436,0.0000125697425,0.000096750584,0.00039545103,0.00043119403,0.00010216967,0.01581031,0.011147036,0.0014840538,0.37571403],"study_design_scores_gemma":[0.0027776766,0.0033846814,0.9092197,0.00017247391,0.00016775636,0.002551032,0.0007773155,0.00042923182,0.008152607,0.0146482345,0.057469606,0.0002497206],"about_ca_topic_score_codex":0.000030970576,"about_ca_topic_score_gemma":0.0000040027508,"teacher_disagreement_score":0.37546432,"about_ca_system_score_codex":0.000037165526,"about_ca_system_score_gemma":0.00005682792,"threshold_uncertainty_score":0.18679468},"labels":[],"label_agreement":null},{"id":"W2606128815","doi":"10.3174/ajnr.a5162","title":"A Novel MRI Biomarker of Spinal Cord White Matter Injury: T2*-Weighted White Matter to Gray Matter Signal Intensity Ratio","year":2017,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; AOSpine; Rick Hansen Institute; Christopher and Dana Reeve Foundation","keywords":"Medicine; Nuclear medicine; White matter; Fractional anisotropy; Magnetic resonance imaging; Magnetization transfer; Radiology","score_opus":0.046102369390599654,"score_gpt":0.35636721979096503,"score_spread":0.3102648504003654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606128815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.846044,0.000008770144,0.0905207,0.06230723,0.00020269546,0.00032933566,0.00003673934,0.000024109366,0.00052644045],"genre_scores_gemma":[0.9463857,0.000015039466,0.031221664,0.021861043,0.00017585722,0.000013510391,0.0000045216843,0.00005208707,0.00027062398],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981676,0.00008906081,0.0007718043,0.00038395528,0.00021518939,0.00037240065],"domain_scores_gemma":[0.9970278,0.000048320773,0.0013553597,0.00085593027,0.00043775214,0.00027482864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019382496,0.00027806364,0.0009504616,0.00034950773,0.00014100119,0.00003336858,0.00053519977,0.000058822447,0.00043967253],"category_scores_gemma":[0.000036981422,0.0002258214,0.00022200376,0.00021733384,0.0008378446,0.00016674044,0.00018023992,0.0005173141,0.00011594432],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003357595,0.00018431114,0.8167371,0.000022584229,0.00008018446,0.00009824805,0.00005746888,0.0000039509873,0.12158589,0.00002060179,0.055515457,0.0023365733],"study_design_scores_gemma":[0.00059625396,0.0038034802,0.9818747,0.00010650195,0.00012160312,0.0047268784,0.000032267235,0.00006165128,0.0022053004,0.00013622137,0.0061296206,0.00020553506],"about_ca_topic_score_codex":0.000027884249,"about_ca_topic_score_gemma":0.0000011194215,"teacher_disagreement_score":0.16513756,"about_ca_system_score_codex":0.00004440375,"about_ca_system_score_gemma":0.000066270644,"threshold_uncertainty_score":0.9208729},"labels":[],"label_agreement":null},{"id":"W2606631943","doi":"10.3174/ajnr.a5163","title":"Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability","year":2017,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; Université de Montréal; Toronto Western Hospital; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; AOSpine; Rick Hansen Institute; Christopher and Dana Reeve Foundation","keywords":"Magnetization transfer; Fractional anisotropy; Medicine; Magnetic resonance imaging; Nuclear medicine; Coefficient of variation; Reliability (semiconductor); Radiology; Diffusion MRI; Statistics; Mathematics; Physics","score_opus":0.12360889887312501,"score_gpt":0.50474400880697,"score_spread":0.38113510993384503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606631943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96539897,0.000039275386,0.024546029,0.009583608,0.00009290531,0.0002379129,0.000059802554,0.0000130173685,0.000028483619],"genre_scores_gemma":[0.80672985,0.00019330846,0.19213948,0.00083084655,0.00008524791,0.0000012638731,0.0000041664503,0.0000140658885,0.0000017976239],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984416,0.00015158484,0.00070993596,0.00036045525,0.00013482365,0.00020165091],"domain_scores_gemma":[0.99730384,0.00017415988,0.0011493511,0.00088905054,0.00024614876,0.00023743628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039225395,0.00015640589,0.0007100945,0.000110358764,0.00015217716,0.000028424305,0.00046129737,0.000031852956,0.0000045475067],"category_scores_gemma":[0.00039576087,0.00012734339,0.000043973017,0.000103236314,0.0013005409,0.00020227418,0.0004536699,0.00047439232,2.3311708e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020963328,0.00013260523,0.79152876,0.0000547077,0.00003966574,0.00010793856,0.000055750137,0.0000039723286,0.13335223,0.00015185484,0.0004335347,0.07204266],"study_design_scores_gemma":[0.0006570569,0.0067060813,0.98114395,0.00009468881,0.00013193526,0.0037756534,0.000073859956,0.0029950275,0.0009868353,0.00062821683,0.0026605534,0.00014616648],"about_ca_topic_score_codex":0.00005372943,"about_ca_topic_score_gemma":7.107626e-7,"teacher_disagreement_score":0.18961518,"about_ca_system_score_codex":0.000029778626,"about_ca_system_score_gemma":0.00013291609,"threshold_uncertainty_score":0.5192913},"labels":[],"label_agreement":null},{"id":"W2607432848","doi":"10.1016/j.neuroimage.2017.03.027","title":"Multi-center machine learning in imaging psychiatry: A meta-model approach","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Central European Institute of Technology; Ministry of Health, British Columbia; Ministry of Education, Youth and Science; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Generalizability theory; Support vector machine; Artificial intelligence; Machine learning; Computer science; Raw data; Similarity (geometry); Data sharing; Sample (material); Schizophrenia (object-oriented programming); Sample size determination; Data mining; Image (mathematics); Medicine; Mathematics; Statistics","score_opus":0.16009223452309757,"score_gpt":0.3899819900185808,"score_spread":0.22988975549548324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2607432848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14090843,0.0016969624,0.72060686,0.061339654,0.00039744517,0.0041101146,0.00014842438,0.0029653395,0.06782673],"genre_scores_gemma":[0.75268775,0.00006852448,0.2438771,0.0016615908,0.00004603735,0.00012284885,0.000026166983,0.00006739701,0.0014425581],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986832,0.0000333115,0.0002525521,0.0005539924,0.00016285764,0.00031404707],"domain_scores_gemma":[0.99866116,0.00001481656,0.00016843356,0.0010135353,0.00003799658,0.000104047125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001572223,0.00022071038,0.00036532516,0.00012563218,0.00030045654,0.000082050756,0.0003172908,0.000033800377,0.000013620203],"category_scores_gemma":[0.00013244947,0.00019163082,0.00017947622,0.00007949062,0.00011634157,0.00023463958,0.00019722663,0.0006751551,0.000014515984],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020653442,0.0044588326,0.91603255,0.000319735,0.00015736656,0.0002808784,0.00021692035,0.0010887207,0.061253957,0.0018832238,0.002783968,0.011317306],"study_design_scores_gemma":[0.0038453033,0.00005198748,0.08268324,0.000038320642,0.0003294937,0.00024553286,0.000012295634,0.89682186,0.00044425565,0.0006019211,0.01459418,0.0003316266],"about_ca_topic_score_codex":0.000044102664,"about_ca_topic_score_gemma":0.0000075590833,"teacher_disagreement_score":0.8957331,"about_ca_system_score_codex":0.000022229058,"about_ca_system_score_gemma":0.000036493013,"threshold_uncertainty_score":0.7814478},"labels":[],"label_agreement":null},{"id":"W2608502883","doi":"10.1016/j.neuroimage.2017.04.057","title":"A tract-specific approach to assessing white matter in preterm infants","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Programme Grants for Applied Research; Biotechnology and Biological Sciences Research Council; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Medical Research Council; Directorate for Biological Sciences; Medical Research Council Canada","keywords":"Tractography; Diffusion MRI; White matter; Population; Computer science; Artificial intelligence; Cartography; Medicine; Geography; Magnetic resonance imaging; Radiology","score_opus":0.11095673463104096,"score_gpt":0.3848755421898771,"score_spread":0.27391880755883613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608502883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8217525,0.000018664998,0.015779035,0.0050970516,0.00007221749,0.0009669539,0.000010223132,0.0001937689,0.15610959],"genre_scores_gemma":[0.95645833,0.000015795607,0.040303756,0.0020685324,0.000079927275,0.00010463834,0.0000064958585,0.000046835623,0.00091566035],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988349,0.00001998485,0.00021917805,0.0004912945,0.00015847372,0.0002761343],"domain_scores_gemma":[0.9984554,0.000020228419,0.00010240385,0.0012669506,0.000031993895,0.00012303861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009485553,0.00015378141,0.00022415993,0.00012716562,0.00017489253,0.0002063275,0.00029358338,0.00004469515,0.000035473273],"category_scores_gemma":[0.00005055112,0.00014732897,0.000054355933,0.00010057088,0.00007215043,0.00034127917,0.00013860165,0.00033862802,0.00009310515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008209534,0.0007220229,0.8825677,0.00009783421,0.0000037984262,0.0002483098,0.00032469397,0.00001561825,0.08664246,0.00026776554,0.013000223,0.016027464],"study_design_scores_gemma":[0.00042555964,0.000033999873,0.9767813,0.00006546855,0.0000070551573,0.00013186934,0.000008975135,0.00028778464,0.001460021,0.00014306256,0.020516925,0.0001379789],"about_ca_topic_score_codex":0.0000057115485,"about_ca_topic_score_gemma":4.0945957e-7,"teacher_disagreement_score":0.15519392,"about_ca_system_score_codex":0.000028979664,"about_ca_system_score_gemma":0.000016873524,"threshold_uncertainty_score":0.60079014},"labels":[],"label_agreement":null},{"id":"W2608872009","doi":"10.1093/schbul/sbx049","title":"Sex and Diffusion Tensor Imaging of White Matter in Schizophrenia: A Systematic Review Plus Meta-analysis of the Corpus Callosum","year":2017,"lang":"en","type":"review","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Centre of Excellence for Child and Youth Mental Health; University of Toronto; Western University; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; Health Canada; National Institutes of Health","keywords":"Corpus callosum; Splenium; Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Meta-analysis; Diffusion MRI; Psychology; Neuropathology; Clinical psychology; Medicine; Psychiatry; Disease; Neuroscience; Pathology; Magnetic resonance imaging","score_opus":0.11040003168301936,"score_gpt":0.37133684010968426,"score_spread":0.2609368084266649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608872009","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000028857457,0.9923956,0.00009769459,0.00253283,0.000027434902,0.0044983933,0.00020911764,0.000042062602,0.00016805221],"genre_scores_gemma":[0.00035224104,0.9934893,0.0031799423,0.00044368266,0.00002319118,0.0009299121,0.00005886275,0.000088768174,0.001434072],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99580824,0.00047702895,0.00213772,0.0007815173,0.00049681106,0.00029868528],"domain_scores_gemma":[0.9938748,0.0003013774,0.0027090178,0.002842111,0.00016436474,0.000108349064],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000846618,0.0006464316,0.009939379,0.00057646865,0.00017043599,0.000024863779,0.00075607514,0.0001665644,0.00023286094],"category_scores_gemma":[0.00040690738,0.00036616827,0.0028890264,0.00082437665,0.00031530389,0.000030133573,0.0006694271,0.00074967806,0.000018611536],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063317544,0.00013921282,0.00040573662,0.97688425,0.015264189,0.00003245973,0.000035120844,0.0000010982151,0.0000041790636,0.00016061646,0.0013621652,0.005647658],"study_design_scores_gemma":[0.00073096796,0.000025354535,0.00039842163,0.26259115,0.66068834,0.00026102396,0.00000558634,0.0000567253,0.0000025227737,0.00006888762,0.07469416,0.00047684828],"about_ca_topic_score_codex":0.00005622947,"about_ca_topic_score_gemma":0.000010501558,"teacher_disagreement_score":0.7142931,"about_ca_system_score_codex":0.00007744795,"about_ca_system_score_gemma":0.0001568751,"threshold_uncertainty_score":0.999879},"labels":[],"label_agreement":null},{"id":"W2609432052","doi":"10.1002/sim.7300","title":"Constructing longitudinal disease progression curves using sparse, short‐term individual data with an application to Alzheimer's disease","year":2017,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Department of Health, Government of Western Australia; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; University of Southern California; F. Hoffmann-La Roche; Australian Government; Novartis Pharmaceuticals Corporation; Government of Western Australia; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Australian Institute of Health and Welfare, Australian Government; Foundation for the National Institutes of Health","keywords":"Term (time); Trajectory; Construct (python library); Regression; Computer science; Longitudinal data; Disease; Regression analysis; Statistics; Algorithm; Mathematics; Applied mathematics; Machine learning; Medicine; Data mining; Pathology","score_opus":0.2365476554198065,"score_gpt":0.48871271654198184,"score_spread":0.25216506112217535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2609432052","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07206267,0.000829499,0.91580254,0.0058798054,0.000097426295,0.0027859479,0.0021437574,0.00018307658,0.00021529829],"genre_scores_gemma":[0.7396867,0.00010528943,0.2573706,0.0003424516,0.00021441076,0.000097316,0.002142973,0.000035248373,0.000004970158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982585,0.000028506402,0.0003242892,0.0006441359,0.00048455698,0.0002600353],"domain_scores_gemma":[0.99703056,0.00006896299,0.00019808022,0.00198858,0.00013218289,0.00058163976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003015567,0.00019783502,0.0003014004,0.00010977865,0.00029075262,0.00003617883,0.0005288349,0.000024603536,0.000017162043],"category_scores_gemma":[0.0005398644,0.00015595065,0.000009189654,0.00012809121,0.00052196026,0.00022877492,0.0002978724,0.00024060177,0.0000013792652],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038555358,0.00020034431,0.8899533,0.00022309466,0.000028240504,0.0003396603,0.000045043464,0.000016006366,0.00012246717,0.004200578,0.0009883085,0.1034974],"study_design_scores_gemma":[0.0010311397,0.00034868193,0.96578485,0.0036758394,0.0010704044,0.00006846707,0.0000840089,0.024218358,0.000053881995,0.0028384505,0.0005052366,0.00032069045],"about_ca_topic_score_codex":0.000055152992,"about_ca_topic_score_gemma":0.000055460263,"teacher_disagreement_score":0.66762406,"about_ca_system_score_codex":0.000042325286,"about_ca_system_score_gemma":0.00014658805,"threshold_uncertainty_score":0.6359483},"labels":[],"label_agreement":null},{"id":"W2609585001","doi":"10.1097/md.0000000000006703","title":"Correlation between prefrontal-striatal pathway impairment and cognitive impairment in patients with leukoaraiosis","year":2017,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Leukoaraiosis; Fractional anisotropy; Diffusion MRI; Medicine; Corpus callosum; Hyperintensity; Montreal Cognitive Assessment; Internal capsule; Neuropsychology; Magnetic resonance imaging; Cardiology; Internal medicine; Pathology; Cognition; Cognitive impairment; Radiology; Psychiatry","score_opus":0.03408362052617913,"score_gpt":0.3183947547624304,"score_spread":0.28431113423625126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2609585001","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915741,0.00004087671,0.0035778093,0.0027084823,0.000034322424,0.001332949,0.000033230648,0.000060895498,0.00063732127],"genre_scores_gemma":[0.9986088,0.000020201982,0.0007034309,0.00017488173,0.00009475364,0.00008799681,0.00015796821,0.000018693258,0.00013324777],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990594,0.000014986921,0.00022170966,0.00029076566,0.00023502645,0.00017814965],"domain_scores_gemma":[0.9992593,0.000045902743,0.00017560052,0.00032810163,0.00006815361,0.00012294066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012873876,0.00014685749,0.00028037615,0.00008920538,0.00015403028,0.000010531414,0.00005835326,0.000043701348,0.00002047959],"category_scores_gemma":[0.00008439604,0.0001024912,0.000017556858,0.000065392924,0.00021982047,0.00012013565,0.00006596591,0.00017877217,0.0000033969845],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023508984,0.00015503082,0.9836234,0.000024489334,0.000018378054,0.000008538699,0.00020194857,3.425608e-7,0.000032155767,0.000030692645,0.00017312675,0.015496818],"study_design_scores_gemma":[0.0072496063,0.0020313929,0.9889785,0.00059774134,0.000106330466,0.000005030115,0.00006205346,0.00007243165,0.00023088242,0.00013859622,0.00042535295,0.00010207126],"about_ca_topic_score_codex":0.00009537313,"about_ca_topic_score_gemma":0.000010138647,"teacher_disagreement_score":0.015394747,"about_ca_system_score_codex":0.00007705488,"about_ca_system_score_gemma":0.000028192848,"threshold_uncertainty_score":0.41794696},"labels":[],"label_agreement":null},{"id":"W2610161052","doi":"10.1002/hbm.23624","title":"Age‐related mapping of intracortical myelin from late adolescence to middle adulthood using T<sub>1</sub>‐weighted MRI","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McGill University; Douglas Mental Health University Institute; McMaster University","funders":"","keywords":"White matter; Neuroscience; Premotor cortex; Psychology; Magnetic resonance imaging; Cortex (anatomy); Myelin; Trajectory; Ventromedial prefrontal cortex; Prefrontal cortex; Medicine; Physics; Central nervous system; Anatomy; Cognition; Radiology","score_opus":0.1049593143279976,"score_gpt":0.34335855877965493,"score_spread":0.23839924445165733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610161052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8778331,0.000039183233,0.11799883,0.002782029,0.000058609065,0.0006482533,0.000016721693,0.0002527735,0.000370481],"genre_scores_gemma":[0.9444854,0.000018289436,0.05427263,0.0008895071,0.00015786705,0.00002691744,0.00003820506,0.00005495164,0.000056220724],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980439,0.000049758477,0.00064408046,0.0005923411,0.0002594923,0.00041045024],"domain_scores_gemma":[0.99805474,0.00009049632,0.00037999908,0.0011109847,0.00013636221,0.00022739703],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022948792,0.00024998945,0.00047138834,0.00020929833,0.000607908,0.00006563872,0.00039099352,0.00013330877,0.000028499197],"category_scores_gemma":[0.00029511313,0.00026509174,0.00012921884,0.00022055938,0.00023719741,0.0001495436,0.0002735773,0.00045934855,0.000029315863],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019637508,0.00009620446,0.003907915,0.00008469355,0.000033751217,0.00007737352,0.0006657764,0.0000264379,0.989998,0.0013216654,0.0002570119,0.0035115234],"study_design_scores_gemma":[0.0026047216,0.0001969733,0.78068304,0.007540266,0.0001744625,0.00006468343,0.00035060343,0.022627287,0.15053968,0.030978745,0.0032352014,0.001004337],"about_ca_topic_score_codex":0.00005163073,"about_ca_topic_score_gemma":0.0000069399343,"teacher_disagreement_score":0.83945835,"about_ca_system_score_codex":0.00007874995,"about_ca_system_score_gemma":0.000043333577,"threshold_uncertainty_score":0.99998015},"labels":[],"label_agreement":null},{"id":"W2610383986","doi":"10.1111/bdi.12489","title":"Longitudinal differences in white matter integrity in youth at high familial risk for bipolar disorder","year":2017,"lang":"en","type":"article","venue":"Bipolar Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Seventh Framework Programme; University of Edinburgh; Scottish Funding Council; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Royal College of Physicians; Health Foundation; Fonds de Recherche du Québec-Société et Culture; Dr Mortimer and Theresa Sackler Foundation; Brain and Behavior Research Foundation; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Bipolar disorder; Psychology; White matter; Clinical psychology; Psychiatry; Medicine; Mood; Magnetic resonance imaging","score_opus":0.05621888127931756,"score_gpt":0.3247170914896752,"score_spread":0.26849821021035764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610383986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9852749,0.0017993797,0.008164124,0.0031821658,0.00009389225,0.0010345719,0.0002855267,0.00007941577,0.00008601306],"genre_scores_gemma":[0.9918583,0.0041262703,0.003211075,0.00013698895,0.000049326765,0.00019000284,0.00007847976,0.00003978749,0.00030976612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986158,0.000037359343,0.00030322693,0.00050710374,0.00015504882,0.00038148407],"domain_scores_gemma":[0.9989066,0.000058992304,0.00018284607,0.00073706877,0.000033681532,0.000080785416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001745218,0.00023065502,0.00035441725,0.00017557961,0.000325751,0.00004019592,0.00032317376,0.00011933878,0.000051297822],"category_scores_gemma":[0.00016015272,0.00020136544,0.000114777904,0.000119821765,0.00022744093,0.00016046909,0.00016753389,0.00045693514,0.000021288473],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012724234,0.00021840497,0.98334116,0.000032625692,0.000008853064,0.0000014035268,0.00021336664,0.0000024638778,0.000070103495,0.00015215176,0.00015646714,0.015675774],"study_design_scores_gemma":[0.001513221,0.000102125574,0.97670805,0.000070636874,0.000044619253,0.0000020853925,0.00010937368,0.0003541089,0.000056127246,0.0024298336,0.018390866,0.00021894525],"about_ca_topic_score_codex":0.0036296519,"about_ca_topic_score_gemma":0.007948093,"teacher_disagreement_score":0.018234398,"about_ca_system_score_codex":0.00008085663,"about_ca_system_score_gemma":0.000030283607,"threshold_uncertainty_score":0.82114446},"labels":[],"label_agreement":null},{"id":"W2611301338","doi":"10.1002/mrm.26711","title":"Choice of reference measurements affects quantification of long diffusion time behaviour using stimulated echoes","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; University of Toronto; Sunnybrook Health Science Centre","funders":"Medical Research Council; Cancer Research UK; Wellcome Trust; Wellcome","keywords":"Diffusion; Nuclear magnetic resonance; Diffusion MRI; Effective diffusion coefficient; Chemistry; Magnetic resonance imaging; Physics; Thermodynamics; Radiology; Medicine","score_opus":0.2281639196815763,"score_gpt":0.4299483690553256,"score_spread":0.2017844493737493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611301338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949816,0.0012898251,0.0016449541,0.0004946481,0.00003210612,0.00066871004,0.0000053334434,0.00003494067,0.0008478981],"genre_scores_gemma":[0.9940106,0.00025622742,0.005325154,0.000033851342,0.000027832193,0.00001975567,0.00001499521,0.000019007044,0.00029255025],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99866784,0.00003836874,0.00043108626,0.00029824759,0.0003956151,0.00016884886],"domain_scores_gemma":[0.9983397,0.000085596155,0.00041728799,0.0009117894,0.00018669684,0.00005890487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031559978,0.00013819433,0.00042040413,0.00014129022,0.00008088287,0.0000047709837,0.0002554277,0.000073013674,0.000072651725],"category_scores_gemma":[0.0006659292,0.00011492935,0.000028773244,0.00017282246,0.00033260728,0.000069097776,0.00006620976,0.00017371918,0.0000019419997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072994066,0.0001632288,0.49868768,0.000104105275,0.0000018549141,0.000008280628,0.000040367253,0.000017410259,0.45783702,0.000026895561,0.00005921881,0.042980965],"study_design_scores_gemma":[0.0014544629,0.00039398024,0.9635583,0.0019223496,0.000068216825,0.0000073917718,0.000008488825,0.0068078116,0.025295518,0.00009015357,0.00030609092,0.00008723533],"about_ca_topic_score_codex":0.00052737276,"about_ca_topic_score_gemma":0.000018681565,"teacher_disagreement_score":0.46487063,"about_ca_system_score_codex":0.00004213092,"about_ca_system_score_gemma":0.000034040884,"threshold_uncertainty_score":0.4686683},"labels":[],"label_agreement":null},{"id":"W2611398135","doi":"","title":"Reducing Invalid Connections with Microstructure-Driven Tractography","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; Streamlines, streaklines, and pathlines; White matter; Computer science; Artificial intelligence; Neuroscience; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Psychology; Physics; Radiology; Medicine","score_opus":0.030784716112358022,"score_gpt":0.2849209317116451,"score_spread":0.2541362155992871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611398135","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18487325,0.00051562575,0.70950055,0.05372767,0.00015910463,0.0018098162,0.00027074487,0.001381645,0.047761615],"genre_scores_gemma":[0.82651657,0.0004402247,0.16950558,0.00023993322,0.000043371245,0.00021429455,0.0003531669,0.00008595822,0.002600899],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9973231,0.0007698091,0.00041477228,0.00088180567,0.00028725684,0.00032325386],"domain_scores_gemma":[0.9949627,0.00057108875,0.00045184448,0.0023120232,0.001480589,0.00022178145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007533968,0.000351593,0.00042078376,0.00026878034,0.00035540087,0.00014285672,0.0005302162,0.00023032217,0.00009419714],"category_scores_gemma":[0.00037745855,0.00029078624,0.00022658703,0.00039315104,0.00039065766,0.00009067335,0.00047663378,0.0008314982,0.0000127974035],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029642586,0.0031018234,0.045154218,0.0014010062,0.00093185855,0.00009755029,0.010610574,0.00024130593,0.49721718,0.29292122,0.015911488,0.13211533],"study_design_scores_gemma":[0.0037465785,0.0000073830356,0.046236973,0.018558925,0.0008112459,0.0008655324,0.00020130421,0.0034092122,0.70915335,0.047505822,0.16729364,0.0022100501],"about_ca_topic_score_codex":0.00021142758,"about_ca_topic_score_gemma":0.0001144166,"teacher_disagreement_score":0.64164335,"about_ca_system_score_codex":0.000098894714,"about_ca_system_score_gemma":0.00026385445,"threshold_uncertainty_score":0.9999544},"labels":[],"label_agreement":null},{"id":"W2612184340","doi":"10.1007/s11538-017-0271-8","title":"A Patient-Specific Anisotropic Diffusion Model for Brain Tumour Spread","year":2017,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures; Alberta Cancer Foundation; American Brain Tumor Association","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Anisotropy; Magnetic resonance imaging; Fiber tract; Tractography; Anisotropic diffusion; Grey matter; Physics; Glioma; Neuroscience; Nuclear magnetic resonance; Pathology; Medicine; Biology; Radiology; Optics","score_opus":0.07374728929369659,"score_gpt":0.3533821802579183,"score_spread":0.27963489096422167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612184340","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.171506,0.000063169,0.7818865,0.040478215,0.000029029667,0.0011874144,0.00005588172,0.00011421985,0.0046795667],"genre_scores_gemma":[0.74069977,0.000037456964,0.2577912,0.0005517455,0.00003776606,0.00014373312,0.000013865746,0.000019055902,0.00070541154],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999294,0.000011769075,0.0002555703,0.00021905197,0.000054619235,0.00016499542],"domain_scores_gemma":[0.9989758,0.00019584263,0.00017238375,0.0005327395,0.00006293634,0.0000602969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007799744,0.000099879966,0.00028546253,0.00002664527,0.000119860924,0.0000069693765,0.00015351172,0.000075213575,0.00013070658],"category_scores_gemma":[0.00045065544,0.000075966556,0.000094478404,0.000010767047,0.00021428359,0.0000062427234,0.00011138339,0.00008185063,0.000035174107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002553566,0.0009380858,0.00048863475,0.00032965018,0.000020096986,0.0000049175756,0.00011795772,0.0000036938302,0.23641309,0.6868347,0.051258877,0.023334956],"study_design_scores_gemma":[0.0024524794,0.001355111,0.0015176914,0.00032798265,0.000064180924,0.000084302505,0.000034127013,0.024474366,0.026000699,0.6307846,0.31258333,0.00032117267],"about_ca_topic_score_codex":0.0000019138429,"about_ca_topic_score_gemma":1.0627131e-7,"teacher_disagreement_score":0.5691938,"about_ca_system_score_codex":0.000010439432,"about_ca_system_score_gemma":0.000010292448,"threshold_uncertainty_score":0.30978265},"labels":[],"label_agreement":null},{"id":"W2612583120","doi":"10.1042/cs20170146","title":"Using DTI to assess white matter microstructure in cerebral small vessel disease (SVD) in multicentre studies","year":2017,"lang":"en","type":"article","venue":"Clinical Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NIHR Newcastle Biomedical Research Centre; University of Cambridge; Cambridge University Hospitals; Stroke Association; British Heart Foundation; National Institute for Health and Care Research","keywords":"Hyperintensity; Fractional anisotropy; White matter; Diffusion MRI; Neuropsychology; Montreal Cognitive Assessment; Cognition; Medicine; Psychology; Internal medicine; Magnetic resonance imaging; Radiology; Cognitive impairment; Neuroscience","score_opus":0.4690996578450013,"score_gpt":0.5580194649050302,"score_spread":0.08891980706002889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612583120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98892576,0.000027844391,0.0008469573,0.009490193,0.00013602324,0.0004075023,0.0000058292003,0.000025394915,0.00013448454],"genre_scores_gemma":[0.96237105,0.00002106089,0.0349086,0.0024781264,0.00006610368,0.000014236197,6.7736704e-7,0.000008225253,0.00013192117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871445,0.000022510136,0.0003211762,0.0005082249,0.00014006913,0.00029354735],"domain_scores_gemma":[0.9987874,0.00009043269,0.000108026325,0.0006796722,0.00008193553,0.00025252756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041624616,0.00009824853,0.00022864519,0.000058643996,0.00020606791,0.00006571554,0.0004420316,0.000032816748,0.000010899052],"category_scores_gemma":[0.0014114155,0.00007861536,0.000039996696,0.00022407553,0.0007064172,0.0001673587,0.00040114202,0.00026015838,0.000014022128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032778556,0.00007026598,0.99617994,0.000018158955,9.1260796e-7,0.00003207023,0.000089467154,0.000043478798,0.0023047137,0.000057163597,0.00014900348,0.0010220493],"study_design_scores_gemma":[0.00043690283,0.000018900051,0.995855,0.00020407858,0.000009531957,0.0000035914702,0.00007353747,0.0016977263,0.00023611508,0.000840435,0.00053050544,0.00009372073],"about_ca_topic_score_codex":0.00002394298,"about_ca_topic_score_gemma":0.000034263943,"teacher_disagreement_score":0.03406164,"about_ca_system_score_codex":0.00007292228,"about_ca_system_score_gemma":0.000107840715,"threshold_uncertainty_score":0.32058412},"labels":[],"label_agreement":null},{"id":"W2613834872","doi":"10.1016/j.neuroimage.2017.05.012","title":"Concurrent white matter bundles and grey matter networks using independent component analysis","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; McDonnell Center for Systems Neuroscience; NIH Blueprint for Neuroscience Research; Sackler Institute for Translational Neurodevelopment, King's College London; Medical Research Council Canada; National Institutes of Health; King's College London","keywords":"White matter; Tractography; Grey matter; Diffusion MRI; Neuroscience; Artificial intelligence; Pattern recognition (psychology); Computer science; Component (thermodynamics); Independent component analysis; Brain mapping; Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.20894823415073066,"score_gpt":0.43722122718067336,"score_spread":0.2282729930299427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613834872","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001573378,0.96955144,0.026618576,0.00039287793,0.00019796628,0.0017002762,0.00012812669,0.00016495385,0.001088459],"genre_scores_gemma":[0.0013396484,0.99457467,0.0016169604,0.0007799538,0.00022663827,0.00011664411,0.0002733787,0.00014220568,0.0009298999],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99751776,0.00012406356,0.0006912226,0.0009797018,0.00027435442,0.00041290693],"domain_scores_gemma":[0.99745536,0.00007330041,0.0006981565,0.0014677172,0.00007853593,0.00022693475],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014568139,0.0005890004,0.00208038,0.00041604138,0.00026075673,0.00021501986,0.0003433262,0.00020112419,0.00025569738],"category_scores_gemma":[0.0000128943375,0.00049327005,0.000661039,0.00028261152,0.00022238225,0.0001197594,0.00042877643,0.0009308977,0.00009601921],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021961032,0.0006701753,0.08088706,0.01832039,0.0020205143,0.0008599667,0.0000523518,0.00008735944,0.000030244555,0.00008927892,0.015445248,0.88151544],"study_design_scores_gemma":[0.00025340376,0.00003604409,0.018137194,0.0026851092,0.009385781,0.00067768566,0.0000015152938,0.0015570456,8.357355e-7,0.000012843103,0.96673703,0.00051553926],"about_ca_topic_score_codex":0.000019589015,"about_ca_topic_score_gemma":0.0000019870424,"teacher_disagreement_score":0.95129174,"about_ca_system_score_codex":0.00008148897,"about_ca_system_score_gemma":0.00005104625,"threshold_uncertainty_score":0.99975187},"labels":[],"label_agreement":null},{"id":"W2614686673","doi":"10.1007/s11060-017-2462-4","title":"Analysis of surgical and MRI factors associated with cerebellar mutism","year":2017,"lang":"en","type":"article","venue":"Journal of Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster Children's Hospital; Impact; McMaster University","funders":"","keywords":"Medicine; Calcification; Odds ratio; Medulloblastoma; Pathological; Pilocytic astrocytoma; Magnetic resonance imaging; Ventricle; Hemosiderin; Cohort; Fourth ventricle; Radiology; Astrocytoma; Surgery; Internal medicine; Pathology; Glioma","score_opus":0.08692544639285024,"score_gpt":0.39442740323993564,"score_spread":0.30750195684708537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2614686673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927765,0.000061112645,0.000651642,0.00562761,0.000037474823,0.00009148512,0.000008961415,0.000012866369,0.00073234376],"genre_scores_gemma":[0.9982846,0.0004412476,0.0010656103,0.00011970568,0.000029409703,0.0000011152694,0.0000026784678,0.000011179556,0.000044475833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991982,0.000053898002,0.0003379421,0.00012553061,0.00016448213,0.00011993673],"domain_scores_gemma":[0.9980862,0.0003585485,0.0009795704,0.00026548872,0.00018618153,0.00012401049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017611388,0.00009007222,0.0006065129,0.00020638944,0.000102201026,0.0000103036555,0.00013869123,0.00007914154,0.000018417799],"category_scores_gemma":[0.00022651536,0.0000619249,0.00013053685,0.00015531425,0.00021892098,0.00007171887,0.0000511174,0.00031910892,1.5153755e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037674227,0.00065608864,0.94769305,0.000015485783,0.0012321412,0.0014894787,0.00020954834,0.00008427259,0.041814152,0.00047595796,0.0011033413,0.0048497682],"study_design_scores_gemma":[0.0028390593,0.0032338714,0.91360945,0.00005842975,0.0034401221,0.0009492112,0.00006231171,0.00083393004,0.0047949892,0.00026709665,0.06978355,0.00012798567],"about_ca_topic_score_codex":0.000006656992,"about_ca_topic_score_gemma":0.000008561157,"teacher_disagreement_score":0.06868021,"about_ca_system_score_codex":0.00004965903,"about_ca_system_score_gemma":0.00008630911,"threshold_uncertainty_score":0.2525224},"labels":[],"label_agreement":null},{"id":"W2615056316","doi":"10.1371/journal.pone.0177466","title":"Exploring the role of white matter connectivity in cortex maturation","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Connectomics; White matter; Neuroscience; Diffusion MRI; Connectome; Biology; Cerebral cortex; Sensory system; Brain development; Functional connectivity; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.20100170113064128,"score_gpt":0.3231630553389885,"score_spread":0.1221613542083472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615056316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99268216,0.0000120162185,0.00021211745,0.0038745643,0.0000055606038,0.00025903058,0.000002539494,0.00002779183,0.0029242043],"genre_scores_gemma":[0.99717385,0.00003453069,0.002441798,0.00011018677,0.000030615156,0.0001041704,0.0000020095997,0.0000065399795,0.000096316864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996759,0.0000071729055,0.0000842145,0.00008946523,0.00008150806,0.00006169276],"domain_scores_gemma":[0.99943304,0.000021950023,0.000072832976,0.0004269751,0.00003113003,0.00001408465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005008635,0.00003863809,0.000098374556,0.000021357158,0.00010475615,0.000007683448,0.000076516626,0.000010126098,0.000016398602],"category_scores_gemma":[0.000043588756,0.00002909018,0.00001488029,0.000027522321,0.000040791947,0.00012329209,0.000051218107,0.00009920877,0.000008898783],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046798887,0.0004655526,0.6612823,0.000042030046,0.000013565609,0.0000016138562,0.00025051547,8.2866035e-7,0.33484694,0.000925103,0.00002455741,0.002100178],"study_design_scores_gemma":[0.000118623015,0.000018786408,0.8663095,0.00010740446,0.000020382786,0.0000015650132,0.000026521995,0.00038086495,0.13117823,0.001687354,0.00012212525,0.000028623575],"about_ca_topic_score_codex":0.000025982397,"about_ca_topic_score_gemma":0.000007967786,"teacher_disagreement_score":0.2050272,"about_ca_system_score_codex":0.0000111623895,"about_ca_system_score_gemma":0.000005304805,"threshold_uncertainty_score":0.11862631},"labels":[],"label_agreement":null},{"id":"W2615393412","doi":"10.1097/wnr.0000000000000813","title":"Radiation-induced cerebellar–cerebral functional connectivity alterations in nasopharyngeal carcinoma patients","year":2017,"lang":"en","type":"article","venue":"Neuroreport","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Task-positive network; Cerebellum; Neuroscience; Superior frontal gyrus; Middle frontal gyrus; Nasopharyngeal carcinoma; Cognition; Medicine; Montreal Cognitive Assessment; Default mode network; Psychology; Radiation therapy; Cognitive impairment; Internal medicine","score_opus":0.08435529029233034,"score_gpt":0.3428243763137724,"score_spread":0.25846908602144203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615393412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901969,0.000005153922,0.00038720333,0.0018868191,0.0002560896,0.0005800932,0.000014238168,0.000116255025,0.006557244],"genre_scores_gemma":[0.99818474,0.0000036290337,0.00046518768,0.00063779525,0.00017106497,0.00010851086,0.00010434897,0.000026514577,0.0002982281],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988249,0.000020378015,0.00030726328,0.00041998224,0.00023075553,0.00019673668],"domain_scores_gemma":[0.99868363,0.00004044451,0.0002444998,0.0008028716,0.000117590935,0.00011094079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000836333,0.00013969229,0.0001996856,0.000096871205,0.00037575702,0.000047426067,0.00010931054,0.000055688444,0.000051583265],"category_scores_gemma":[0.00033159388,0.00014245065,0.00007366398,0.00008077382,0.000055958477,0.00026656946,0.00007279417,0.00027248482,0.000015309144],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043464708,0.00023846432,0.99250734,0.000007944495,0.000004480052,0.00007365937,0.000019069363,0.0000055478326,0.0023543737,0.0007043103,0.0010544786,0.0029868418],"study_design_scores_gemma":[0.0011150423,0.00011406558,0.98994416,0.000009492053,0.000017517945,0.00007983337,0.0000020778996,0.00048615693,0.0059328107,0.0005672223,0.0016216855,0.000109946464],"about_ca_topic_score_codex":0.00013089915,"about_ca_topic_score_gemma":0.000022583743,"teacher_disagreement_score":0.007987817,"about_ca_system_score_codex":0.000071251845,"about_ca_system_score_gemma":0.00012376404,"threshold_uncertainty_score":0.58089685},"labels":[],"label_agreement":null},{"id":"W2615453098","doi":"10.1161/str.47.suppl_1.wmp40","title":"Abstract WMP40: Intra-arterial Mesenchymal Stem Cells in a Large Animal Endovascular Canine Stroke Model: Findings on Serial Diffusion Tensor Imaging","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Adidas (Canada)","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; White matter; Effective diffusion coefficient; Stroke (engine); Stroke recovery; Magnetic resonance imaging; Pathology; Nuclear medicine; Radiology","score_opus":0.025339264564449158,"score_gpt":0.28994046482040026,"score_spread":0.2646012002559511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615453098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98707175,0.000016561551,0.008685449,0.0018089826,0.00016170208,0.0007208057,0.00059631554,0.00026880964,0.00066962506],"genre_scores_gemma":[0.9951084,0.000051668747,0.0032118175,0.00029311018,0.00035168065,0.00013492118,0.000016748025,0.00006587606,0.00076578086],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979463,0.00002740542,0.00042727252,0.00061277667,0.00037759906,0.00060862856],"domain_scores_gemma":[0.9990546,0.00006751035,0.0001069156,0.0005266434,0.000063866704,0.00018046715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001987133,0.0003009548,0.0004089842,0.00020764394,0.000109353474,0.00003068558,0.00018261002,0.0000950028,0.00015850531],"category_scores_gemma":[0.000030056048,0.00022453548,0.00017378187,0.00012008408,0.00007297715,0.00016986302,0.000102673686,0.00032820692,0.00003622336],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006696816,0.00026121663,0.0068742414,0.000023087101,0.000014718068,0.00008332677,0.00006694825,0.000026361124,0.98739094,0.0008658078,0.0006408896,0.003082804],"study_design_scores_gemma":[0.020668965,0.0009480586,0.07641206,0.0007941647,0.00018310356,0.00015085729,0.00023035158,0.013500157,0.87153053,0.0005903851,0.013828161,0.0011632177],"about_ca_topic_score_codex":0.0000352004,"about_ca_topic_score_gemma":0.000012513672,"teacher_disagreement_score":0.1158604,"about_ca_system_score_codex":0.00017276498,"about_ca_system_score_gemma":0.00007388121,"threshold_uncertainty_score":0.91562915},"labels":[],"label_agreement":null},{"id":"W2619324736","doi":"10.1007/978-3-319-59448-4_4","title":"Cartan Frames for Heart Wall Fiber Motion","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Motion (physics); Frame (networking); Fiber; Artificial intelligence; Mechanics; Computer vision; Physics; Materials science; Telecommunications","score_opus":0.05562735939141506,"score_gpt":0.3494575874783898,"score_spread":0.29383022808697473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619324736","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009626406,0.00011505166,0.991493,0.0049864748,0.00018314969,0.00080706767,0.00001081965,0.00013366064,0.0021745048],"genre_scores_gemma":[0.09738907,0.00004832805,0.89029,0.0046491763,0.000794574,0.00007794429,0.00003467607,0.000073676965,0.0066425274],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99865097,0.0000029841228,0.00018720627,0.0006576446,0.00024815468,0.000253062],"domain_scores_gemma":[0.9985663,0.0001622672,0.00012479202,0.0009101965,0.00015175143,0.000084654785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001570842,0.00021386363,0.0003059635,0.00018070557,0.00021945593,0.00007435481,0.0003806671,0.00015708289,0.000021395685],"category_scores_gemma":[0.00010045273,0.00018774536,0.00010115969,0.000041558887,0.0004018865,0.00009175526,0.00013494899,0.00038655696,0.000014723016],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002711711,0.00004466768,0.0003055817,0.00014699886,0.000010265497,0.000021822725,0.00017866545,0.0010641163,0.001473499,0.009409097,0.0009357361,0.9863824],"study_design_scores_gemma":[0.0006403439,0.0004943201,0.0014290127,0.001152794,0.00006561877,0.00021748408,7.6826545e-8,0.05433775,0.008226618,0.48918816,0.4435139,0.0007339069],"about_ca_topic_score_codex":0.000007916983,"about_ca_topic_score_gemma":0.0000065350955,"teacher_disagreement_score":0.9856485,"about_ca_system_score_codex":0.000102317,"about_ca_system_score_gemma":0.000118757016,"threshold_uncertainty_score":0.76560336},"labels":[],"label_agreement":null},{"id":"W2619834707","doi":"10.1016/j.neuroimage.2017.05.052","title":"Brain grey and white matter predictors of verbal ability traits in older age: The Lothian Birth Cohort 1936","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Medical Research Council; Directorate for Biological Sciences; Centre for Cognitive Ageing and Cognitive Epidemiology; University of Edinburgh; Scottish Funding Council; Age UK; Medical Research Council Canada; Wellcome Trust","keywords":"Psychology; Grey matter; Fractional anisotropy; White matter; Cognition; Developmental psychology; Cognitive psychology; Semantic memory; Brain size; Arcuate fasciculus; Audiology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.029191684035404775,"score_gpt":0.3194922356273708,"score_spread":0.290300551591966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619834707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9787575,0.000021250813,0.00029400672,0.014751478,0.000042989937,0.0008349989,0.000041014868,0.000070212445,0.0051865648],"genre_scores_gemma":[0.996754,0.000023940764,0.000526479,0.0018656278,0.00004640742,0.000048165293,0.0000048814886,0.000027307178,0.0007032154],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990008,0.000045027104,0.00024139887,0.00036081416,0.00016179675,0.00019017713],"domain_scores_gemma":[0.9988363,0.0000752657,0.00012856025,0.00085962965,0.0000381646,0.00006212067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020056506,0.0001362443,0.0002310423,0.0000478589,0.0001352672,0.000040899213,0.00023338136,0.000044684286,0.000050071787],"category_scores_gemma":[0.00016610579,0.00010091291,0.000052017425,0.00007459014,0.00047019342,0.00013303795,0.00012259286,0.00030952788,0.000005065191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003082328,0.00009502706,0.98552597,0.000065255,0.0000049038954,0.000037448877,0.0001631927,8.1039815e-7,0.009230879,0.00007111207,0.0030920678,0.001682526],"study_design_scores_gemma":[0.0005502729,0.000057250196,0.99098784,0.00003868169,0.000020221507,0.000040677452,0.000007877098,0.00007113897,0.0008174496,0.00039444794,0.0069388407,0.000075313284],"about_ca_topic_score_codex":0.00003962449,"about_ca_topic_score_gemma":0.000015281808,"teacher_disagreement_score":0.017996492,"about_ca_system_score_codex":0.0000137094385,"about_ca_system_score_gemma":0.00002173257,"threshold_uncertainty_score":0.41151088},"labels":[],"label_agreement":null},{"id":"W2619945508","doi":"","title":"Microstructure driven tractography in the human brain","year":2016,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Human brain; Fascicle; Magnetic resonance imaging; Axon; Neocortex; Neuroimaging; Neuroscience; Nuclear magnetic resonance; Computer science; Anatomy; Physics; Psychology; Biology; Medicine; Radiology","score_opus":0.030523102029129626,"score_gpt":0.3074304985296007,"score_spread":0.2769073965004711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2619945508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44795194,0.0008806181,0.17092083,0.3015793,0.00012531837,0.0029522732,0.0002601337,0.0007903644,0.0745392],"genre_scores_gemma":[0.96831185,0.00022265023,0.027722148,0.0011008,0.000037324768,0.00020887615,0.00038454545,0.000050331637,0.0019614496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99688923,0.0015319724,0.0003974943,0.00062836905,0.00027872904,0.00027421003],"domain_scores_gemma":[0.99589676,0.000816999,0.00030504723,0.002351409,0.0005379507,0.00009181496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016616243,0.0002684234,0.0003110077,0.00021218126,0.00023554746,0.00012203499,0.0009675294,0.00022301721,0.000056030894],"category_scores_gemma":[0.00041119495,0.00019686884,0.00022906685,0.0003464921,0.00029787698,0.000053605036,0.0004774741,0.000974828,0.00000820462],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000398071,0.0022218688,0.06950834,0.0006114916,0.0001443847,0.00007406528,0.017886374,0.000014056514,0.36441982,0.44507793,0.03383777,0.0661641],"study_design_scores_gemma":[0.0028430738,0.0000026182151,0.3696751,0.008587308,0.00019983794,0.00023306982,0.00026717756,0.00087284675,0.08338556,0.23056987,0.30200902,0.0013545278],"about_ca_topic_score_codex":0.00014765891,"about_ca_topic_score_gemma":0.00021110504,"teacher_disagreement_score":0.52035993,"about_ca_system_score_codex":0.000059449296,"about_ca_system_score_gemma":0.000097574404,"threshold_uncertainty_score":0.80280787},"labels":[],"label_agreement":null},{"id":"W2620158492","doi":"10.1136/bjsports-2016-097270.86","title":"Eye movement and white matter integrity in patients with post-concussion syndrome","year":2017,"lang":"en","type":"article","venue":"British Journal of Sports Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University Health Network; Toronto Western Hospital; Hospital for Sick Children; Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"White matter; Uncinate fasciculus; Superior longitudinal fasciculus; Fractional anisotropy; Diffusion MRI; Tractography; Psychology; Cingulum (brain); Physical medicine and rehabilitation; Medicine; Audiology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.015165644709323564,"score_gpt":0.29299318400881375,"score_spread":0.27782753929949017,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620158492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98912513,0.00025210954,0.00021690871,0.009604145,0.000056571072,0.00025301284,0.000004527373,0.000009357361,0.00047823682],"genre_scores_gemma":[0.9954666,0.00049882353,0.0022297017,0.0014582849,0.00005563236,0.0000030914762,0.000007337695,0.000015886073,0.00026467475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99901104,0.0000069363587,0.00037706265,0.00014454927,0.00033117493,0.00012924758],"domain_scores_gemma":[0.9989896,0.0000069213247,0.0004219786,0.00022356313,0.00021524481,0.00014271411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002323421,0.000095603566,0.00033510217,0.00010144754,0.00009035417,0.000018960067,0.000100184174,0.000036052083,0.00013782733],"category_scores_gemma":[0.00005887929,0.00007020893,0.000023894068,0.00004163558,0.00017618637,0.00015585817,0.000040581726,0.00041364046,5.9861964e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012501706,0.000112306494,0.94818884,0.000030677405,0.00000690527,0.0013451112,0.000030752042,1.9956178e-7,0.000030767736,0.000007712778,0.0010912037,0.04903049],"study_design_scores_gemma":[0.002711701,0.00041687777,0.98837924,0.00591188,0.000042941716,0.0015719621,0.000036032587,0.0000017639361,0.000019173212,0.00037904276,0.00045974765,0.00006961575],"about_ca_topic_score_codex":0.000068534566,"about_ca_topic_score_gemma":0.0000031087227,"teacher_disagreement_score":0.048960872,"about_ca_system_score_codex":0.000033917786,"about_ca_system_score_gemma":0.000026197522,"threshold_uncertainty_score":0.2863037},"labels":[],"label_agreement":null},{"id":"W2620311529","doi":"10.1002/hbm.23658","title":"White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI)","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; St. Michael's Hospital","funders":"Canadian Institutes of Health Research; Siemens Canada; Canadian Institute for Military and Veteran Health Research; Defence Research and Development Canada","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Concussion; Athletes; Magnetic resonance imaging; Psychology; Neurite; Neuroscience; Medicine; Chemistry; Physical therapy; Poison control; Radiology; Injury prevention","score_opus":0.03303363302585623,"score_gpt":0.2934358046874379,"score_spread":0.2604021716615817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620311529","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935207,0.00020953138,0.0021661464,0.003192718,0.00002293961,0.0003281813,0.0000018144632,0.000047445155,0.0005105195],"genre_scores_gemma":[0.995249,0.000018814768,0.0036028556,0.0007525517,0.000031819392,0.000009593914,0.0000135437385,0.00001960515,0.00030225632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991616,0.000022309705,0.00020141325,0.00035279384,0.00010323788,0.00015866266],"domain_scores_gemma":[0.9992964,0.000028639266,0.00022076868,0.00034389,0.000049771927,0.000060480448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000098874676,0.00014433009,0.0002460589,0.00013174566,0.00031098037,0.00004032899,0.00007413615,0.00002359756,0.000010873978],"category_scores_gemma":[0.000024555411,0.00012320427,0.00002272334,0.000036350335,0.00032624428,0.00020525865,0.00015525501,0.00019606702,3.9467454e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027476666,0.00001257869,0.7813764,0.00011099087,0.0000019989766,0.00001834308,0.0008137375,7.495999e-7,0.21621099,0.000092810544,0.0005299458,0.000803976],"study_design_scores_gemma":[0.0010719636,0.00001586513,0.9931833,0.0007389618,0.000018093211,0.00012775292,0.00020782085,0.0025866874,0.00017053446,0.00026458927,0.0014818882,0.00013254539],"about_ca_topic_score_codex":0.00007385843,"about_ca_topic_score_gemma":0.000011249998,"teacher_disagreement_score":0.21604045,"about_ca_system_score_codex":0.000083175044,"about_ca_system_score_gemma":0.000012980305,"threshold_uncertainty_score":0.50241244},"labels":[],"label_agreement":null},{"id":"W2620852117","doi":"","title":"Human Statistical Atlas of Cardiac Fiber Architecture from DT-MRI","year":2011,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Atlas (anatomy); Diffusion MRI; Segmentation; Human heart; Population; Orientation (vector space); Computer science; Artificial intelligence; Computer vision; Anatomy; Mathematics; Biology; Medicine; Geometry; Cardiology; Radiology; Magnetic resonance imaging","score_opus":0.03629853074752196,"score_gpt":0.28755465957508936,"score_spread":0.25125612882756737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620852117","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34753335,0.00045207376,0.4653841,0.0053960104,0.000055035147,0.0008994668,0.00041624202,0.00055481325,0.17930892],"genre_scores_gemma":[0.6321892,0.0000635109,0.36325395,0.00008206584,0.000014844807,0.000038964437,0.00026142542,0.000030446306,0.0040655895],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983845,0.0005907205,0.00029262382,0.0003504638,0.00020199601,0.00017971337],"domain_scores_gemma":[0.9976371,0.00039838228,0.00015672101,0.0011579404,0.0005128344,0.00013700667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005463667,0.00013899972,0.0002556296,0.00007054955,0.00012860713,0.000016624144,0.00028269048,0.00007033814,0.0005735962],"category_scores_gemma":[0.0002525448,0.00013280973,0.00010305673,0.00019380671,0.00026170185,0.00004199651,0.00016055853,0.00025705117,0.000032040687],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011900904,0.0027410537,0.026205579,0.00020859562,0.00025107735,0.00002251245,0.014773309,0.0000057281904,0.22812922,0.5054126,0.015818408,0.2063129],"study_design_scores_gemma":[0.0008729121,0.000004520718,0.15138003,0.0008537291,0.00021481591,0.000018568664,0.00008938499,0.0005141854,0.66503,0.054905634,0.12565005,0.0004661444],"about_ca_topic_score_codex":0.0007971576,"about_ca_topic_score_gemma":0.00006054377,"teacher_disagreement_score":0.45050696,"about_ca_system_score_codex":0.000024484787,"about_ca_system_score_gemma":0.00004719326,"threshold_uncertainty_score":0.62804765},"labels":[],"label_agreement":null},{"id":"W2621188631","doi":"10.1017/cjn.2017.166","title":"P.082 Neural Reorganization Following Compression of the Motor Cortex: An fMRI and DTI Case Report","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Saskatoon Medical Imaging","funders":"","keywords":"Functional magnetic resonance imaging; Motor cortex; Diffusion MRI; Psychology; Supplementary motor area; Magnetic resonance imaging; Neuroscience; Cortex (anatomy); White matter; Subthalamic nucleus; Medicine; Anatomy; Deep brain stimulation; Radiology; Parkinson's disease; Pathology","score_opus":0.08188633804923962,"score_gpt":0.35428019309251807,"score_spread":0.27239385504327845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621188631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.992012,0.00023561984,0.000091736154,0.0065709343,0.00044297017,0.00020921102,0.000005990427,0.000015450687,0.00041608998],"genre_scores_gemma":[0.99500024,0.00008116089,0.0036159176,0.0011423716,0.00012782337,0.0000015830641,2.1078402e-7,0.000010104419,0.000020583173],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99763703,0.00029598363,0.0006620462,0.00039890278,0.00048029248,0.00052572537],"domain_scores_gemma":[0.99684596,0.00016643747,0.0012436071,0.00037579218,0.00035814565,0.001010063],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0017755083,0.0001937728,0.00036933366,0.00028024492,0.0046666185,0.00042200892,0.0012377688,0.00010313436,0.000017431108],"category_scores_gemma":[0.0026091482,0.0001131289,0.00016397065,0.00038729102,0.0050092437,0.0009357998,0.0001229573,0.0007646439,1.3325239e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039116232,0.000028417371,0.95000726,0.0000064773926,0.0000064754718,0.045219246,0.0001480707,0.00015479363,0.0015522878,0.00038941068,0.00013344041,0.0023149801],"study_design_scores_gemma":[0.00025073765,0.013235717,0.521698,0.00005716431,0.00006387013,0.45531383,0.00011870689,0.0029043832,0.00042561855,0.005319083,0.00046896585,0.00014389688],"about_ca_topic_score_codex":0.00093998126,"about_ca_topic_score_gemma":0.0088915415,"teacher_disagreement_score":0.42830926,"about_ca_system_score_codex":0.00006573965,"about_ca_system_score_gemma":0.0010029149,"threshold_uncertainty_score":0.99769855},"labels":[],"label_agreement":null},{"id":"W2621380256","doi":"10.1017/cjn.2017.167","title":"P.083 Characterization of an arteriovenous malformation using 7T structural and functional imaging: A case report","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Arteriovenous malformation; Digital subtraction angiography; Neuroimaging; Radiology; Abnormality; Intracranial Arteriovenous Malformations; Functional imaging; Magnetic resonance imaging; Angiography; Cerebral angiography","score_opus":0.08718711268704743,"score_gpt":0.33898033115505327,"score_spread":0.25179321846800584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621380256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963898,0.000069023685,0.000654532,0.00225069,0.00026773586,0.00014674317,0.000013924728,0.000012875008,0.00019467293],"genre_scores_gemma":[0.992262,0.00004031562,0.006829747,0.0006891297,0.00016267152,0.0000016602208,0.0000011356137,0.000007511022,0.000005828715],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.99804556,0.00015109994,0.0006507567,0.0003190696,0.00036546862,0.00046806858],"domain_scores_gemma":[0.99711335,0.000061607854,0.0013129961,0.00021275143,0.00043921723,0.00086007454],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.001364504,0.00017454934,0.0003193589,0.00044598867,0.0031919144,0.0004702531,0.00046952072,0.00007075563,0.00003384044],"category_scores_gemma":[0.0007690256,0.00012506638,0.00009203607,0.00024113028,0.0041514346,0.0017516739,0.00004977792,0.0004903123,1.3288285e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010888854,0.000031049596,0.90376484,0.000016032509,0.000009524121,0.07940893,0.00023290009,0.00039140394,0.005101222,0.0006865073,0.000019297717,0.010229386],"study_design_scores_gemma":[0.00016215211,0.006400019,0.3539633,0.00002440581,0.000031969994,0.6239851,0.000051824813,0.010981038,0.00030946938,0.0038151797,0.0001736856,0.00010187738],"about_ca_topic_score_codex":0.0007880428,"about_ca_topic_score_gemma":0.0026311344,"teacher_disagreement_score":0.5498016,"about_ca_system_score_codex":0.00008550018,"about_ca_system_score_gemma":0.0011336576,"threshold_uncertainty_score":0.9985587},"labels":[],"label_agreement":null},{"id":"W2621699596","doi":"10.1101/146878","title":"Unfolding the hippocampus: an intrinsic coordinate system for subfield segmentations and quantitative mapping","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Fondation Brain Canada; Ontario Brain Institute","keywords":"Hippocampal formation; Central sulcus; Neuroscience; Hippocampus; Grey matter; Neocortex; Computer science; Coordinate system; Anatomy; Artificial intelligence; Biology; Magnetic resonance imaging; White matter; Medicine; Radiology; Motor cortex","score_opus":0.07299884844012966,"score_gpt":0.331262584607385,"score_spread":0.25826373616725534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621699596","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8916484,0.0011688931,0.09870808,0.0028808569,0.00050790346,0.0038281132,0.00030202078,0.0009335026,0.000022245764],"genre_scores_gemma":[0.9298858,0.00023757816,0.068205945,0.00023525662,0.00021487367,0.0011221502,0.0000014001073,0.00009230785,0.0000047076965],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982493,0.00006385964,0.00039862844,0.00077082263,0.00017436137,0.00034305587],"domain_scores_gemma":[0.997223,0.00019899753,0.000521389,0.001426389,0.00044667977,0.00018350163],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000490695,0.00036209257,0.00048333505,0.00014602758,0.00076224236,0.0002530408,0.0003827667,0.00021351341,0.0000020590637],"category_scores_gemma":[0.00025236083,0.00031514416,0.00011004944,0.00016024862,0.00020915052,0.00017506663,0.00030372996,0.00057751534,0.0000035745352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019070094,0.00029495507,0.012519183,0.0047038365,0.00053962384,0.00008213363,0.00019678408,0.000051114712,0.91412765,0.06588626,0.001046937,0.00036084012],"study_design_scores_gemma":[0.007569477,0.0014081234,0.2550332,0.015474913,0.0034666592,0.0000032981698,0.0011426912,0.025329009,0.65583384,0.0017327461,0.028015077,0.00499095],"about_ca_topic_score_codex":0.000033596407,"about_ca_topic_score_gemma":0.0000015190324,"teacher_disagreement_score":0.25829375,"about_ca_system_score_codex":0.0001693501,"about_ca_system_score_gemma":0.00022499998,"threshold_uncertainty_score":0.9999301},"labels":[],"label_agreement":null},{"id":"W2621911999","doi":"10.1101/146688","title":"Learn to Track: Deep Learning for Tractography","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Ground truth; Artificial intelligence; Deep learning; Diffusion MRI; Trajectory; Track (disk drive); Imaging phantom; Tracking (education); Process (computing); Artificial neural network; Deep neural networks; White matter; Fiber tract; Machine learning; Magnetic resonance imaging; Psychology; Physics","score_opus":0.04752977220672326,"score_gpt":0.31785915994131053,"score_spread":0.27032938773458726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621911999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5551961,0.0013368708,0.425313,0.0056263194,0.00086503435,0.0074243727,0.0002318096,0.0038755771,0.00013089152],"genre_scores_gemma":[0.89097536,0.00028723525,0.10597111,0.00053678895,0.0005427657,0.0014195492,0.000001112462,0.00022385524,0.000042214917],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99742293,0.000036337693,0.00044278288,0.0011719244,0.00028297698,0.00064307405],"domain_scores_gemma":[0.9965966,0.00008823459,0.00043634957,0.0018684195,0.0005249584,0.0004854633],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038465788,0.00050832867,0.00068747083,0.0003677452,0.00045006935,0.0001921432,0.0005559633,0.00039976533,0.000017049204],"category_scores_gemma":[0.0006327979,0.00055252574,0.00036769014,0.0002524244,0.00011303235,0.00010266585,0.00029558933,0.0012413339,0.00003709277],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022223515,0.0004890185,0.017976403,0.001117569,0.000229986,0.00007222505,0.000023286138,0.00025439012,0.97566694,0.0017861648,0.0018085814,0.0003531745],"study_design_scores_gemma":[0.0014285095,0.00049660634,0.19558434,0.0012405835,0.00060963485,1.3090295e-7,0.0000048551415,0.0014592812,0.27731922,0.000055131786,0.52019435,0.0016073767],"about_ca_topic_score_codex":0.000013093291,"about_ca_topic_score_gemma":8.421671e-7,"teacher_disagreement_score":0.69834775,"about_ca_system_score_codex":0.00013179649,"about_ca_system_score_gemma":0.0002265001,"threshold_uncertainty_score":0.9996926},"labels":[],"label_agreement":null},{"id":"W2622626023","doi":"10.1002/mrm.26689","title":"The effect of realistic geometries on the susceptibility‐weighted MR signal in white matter","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; University of Toronto","keywords":"White matter; SIGNAL (programming language); Magnetic resonance imaging; Diffusion MRI; Nuclear magnetic resonance; Physics; Geometry; Diffusion; Work (physics); Mathematics; Computer science; Medicine; Radiology","score_opus":0.03430550830802002,"score_gpt":0.3434914899147198,"score_spread":0.30918598160669974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622626023","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9285964,0.002100154,0.00011929647,0.059696753,0.000063857384,0.0013750495,0.00000711946,0.00002932473,0.00801208],"genre_scores_gemma":[0.99703413,0.0004894175,0.00017437684,0.00060050446,0.00008190672,0.00018542724,0.0000037455964,0.000017688608,0.0014127987],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859387,0.000103285565,0.00041958125,0.0002918766,0.00033285652,0.00025854353],"domain_scores_gemma":[0.9970657,0.0013568149,0.00016777319,0.001316468,0.000049542155,0.00004365224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010808352,0.00016049983,0.00037394132,0.0001154138,0.0001816748,0.000015191551,0.00043356954,0.000049257265,0.0002346004],"category_scores_gemma":[0.0011931112,0.00007612479,0.00004020532,0.00029341676,0.0010877153,0.00002766561,0.00007725347,0.00039560307,0.000011166299],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005121348,0.000050987026,0.9395202,0.00008494016,0.0000022662355,0.00003896959,0.00012404537,0.000002970695,0.0016459896,0.0010362592,0.007386309,0.049594924],"study_design_scores_gemma":[0.0013101088,0.0015246859,0.97592914,0.0007342599,0.000021639455,0.000012459009,0.000034560882,0.00046948937,0.0016706184,0.0029583955,0.0152588,0.00007586308],"about_ca_topic_score_codex":0.00019773928,"about_ca_topic_score_gemma":0.00008797018,"teacher_disagreement_score":0.06843777,"about_ca_system_score_codex":0.00004331263,"about_ca_system_score_gemma":0.00001794087,"threshold_uncertainty_score":0.40077323},"labels":[],"label_agreement":null},{"id":"W2622868629","doi":"10.1101/148502","title":"Harmonization of cortical thickness measurements across scanners and sites","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health","keywords":"Scanner; Spurious relationship; Neuroimaging; Computer science; Statistical power; Artificial intelligence; Variance (accounting); Modalities; Reproducibility; Diffusion MRI; Data set; Set (abstract data type); Computer vision; Pattern recognition (psychology); Data mining; Magnetic resonance imaging; Machine learning; Statistics; Mathematics; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.09371964326403137,"score_gpt":0.3415614789768183,"score_spread":0.24784183571278695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622868629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788285,0.0005646361,0.01836904,0.0006941217,0.00015167631,0.00089772575,0.00015090905,0.00032815716,0.000015227381],"genre_scores_gemma":[0.9723717,0.00032956086,0.026862592,0.00013518026,0.00010758013,0.00011399598,7.979935e-7,0.00007354408,0.0000050217604],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983414,0.00003934696,0.0003716168,0.0006281766,0.00033249785,0.00028696156],"domain_scores_gemma":[0.9974712,0.00003230622,0.00043388025,0.0012063206,0.00066466915,0.00019163582],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003636356,0.00028302206,0.00047763847,0.0000843362,0.00023362241,0.000085139574,0.00025894548,0.00026273148,0.0000060839575],"category_scores_gemma":[0.00048288703,0.00029560074,0.000075645105,0.00013180594,0.0003252425,0.00009356498,0.0003990298,0.00054686563,0.0000037868303],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036426947,0.00012409342,0.13518547,0.00049783004,0.00006285971,0.000011225112,0.000009593183,0.000006302932,0.8636782,0.00025033596,0.00012958249,0.000008075398],"study_design_scores_gemma":[0.00057757646,0.000054058793,0.49886551,0.0007508646,0.00020801048,9.023691e-8,0.0000022940403,0.00057389535,0.497782,0.000013953559,0.0008165742,0.00035520192],"about_ca_topic_score_codex":0.000018097418,"about_ca_topic_score_gemma":6.136124e-7,"teacher_disagreement_score":0.36589622,"about_ca_system_score_codex":0.00008446198,"about_ca_system_score_gemma":0.00020788737,"threshold_uncertainty_score":0.99994963},"labels":[],"label_agreement":null},{"id":"W2624422566","doi":"10.1016/j.neurobiolaging.2017.05.023","title":"Long-term changes in time spent walking and subsequent cognitive and structural brain changes in older adults","year":2017,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health Research Institute; University of British Columbia; Vancouver Coastal Health","funders":"National Institute of Nursing Research; National Institute on Aging; Canadian Institutes of Health Research","keywords":"Cognition; Cognitive decline; White matter; Brain size; Effects of sleep deprivation on cognitive performance; Diffusion MRI; Psychology; Neuroimaging; Gerontology; Physical medicine and rehabilitation; Demographics; Medicine; Magnetic resonance imaging; Physical therapy; Dementia; Demography; Internal medicine; Psychiatry","score_opus":0.03544485928355749,"score_gpt":0.3413519391574788,"score_spread":0.3059070798739213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624422566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99302304,0.0001525882,0.000010912625,0.0062852274,0.000024726785,0.00043588562,0.000008512009,0.00002555632,0.000033561977],"genre_scores_gemma":[0.99886894,0.0002579405,0.00020109629,0.00055309373,0.000036300593,0.000023034154,0.000014252232,0.000012115646,0.000033243938],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993321,0.000031806958,0.00011791682,0.00030074306,0.000037612175,0.00017987394],"domain_scores_gemma":[0.9995467,0.00010105492,0.0001196656,0.0001727351,0.00002306977,0.000036797723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008826216,0.00011129173,0.00023353456,0.00012567164,0.0000640723,0.0000110779065,0.00008075918,0.000046798767,0.000008483094],"category_scores_gemma":[0.00006204262,0.00010107934,0.000011665447,0.00003443749,0.000243803,0.000044688,0.0001496035,0.00017435233,4.2727802e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006104095,0.000025096737,0.9504475,0.000094179195,0.000004810831,0.000056906327,0.0004903105,1.2601411e-7,0.030486232,0.00001962008,0.0000054665365,0.018308684],"study_design_scores_gemma":[0.0010877613,0.00012246212,0.972263,0.0006195001,0.000010781995,0.000105512394,0.000026552445,0.00005711583,0.02553478,0.00008799262,0.0000053841427,0.00007915375],"about_ca_topic_score_codex":0.000034996818,"about_ca_topic_score_gemma":0.00023563058,"teacher_disagreement_score":0.021815477,"about_ca_system_score_codex":0.0000117278105,"about_ca_system_score_gemma":0.0000058815435,"threshold_uncertainty_score":0.4121896},"labels":[],"label_agreement":null},{"id":"W2624604555","doi":"10.1007/978-3-319-46293-6_10","title":"Spinal Cord Imaging","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Magnetic resonance imaging; Spinal cord; Diffusion MRI; Medicine; White matter; Spinal cord injury; Radiology; Functional magnetic resonance imaging; Neuroscience; Psychology","score_opus":0.13466672986164469,"score_gpt":0.4122790765283925,"score_spread":0.27761234666674783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624604555","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000015620117,0.0002418059,0.01091834,0.0032464212,0.000048666654,0.00031128424,0.000008673116,0.00037683925,0.9848464],"genre_scores_gemma":[0.0021920688,0.00028919877,0.018490328,0.0012601904,0.0002576146,0.00001542114,0.00003044232,0.000066289176,0.97739846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99930197,7.059714e-7,0.00014504133,0.00030400665,0.00012534467,0.00012291469],"domain_scores_gemma":[0.99883944,0.0000067362375,0.0001341015,0.00086790527,0.000067311135,0.00008452299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027647435,0.00018125832,0.00024386731,0.00006520974,0.000108150656,0.000020809062,0.00014232194,0.0000642727,0.0005237247],"category_scores_gemma":[0.00001112186,0.00015964676,0.00011592483,0.0000029712917,0.000119965545,0.00003431547,0.000084749874,0.00032831746,0.00023457214],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010018628,0.000015750747,0.00007146696,0.000058422138,0.000018592213,0.00019421573,0.0000011018308,1.5091866e-8,0.00031983887,0.5836483,0.05800492,0.3575672],"study_design_scores_gemma":[0.00012248184,0.00010297274,0.00014285828,0.000263746,0.00006930592,0.0002491505,3.760347e-7,0.000014441309,0.00012482483,0.06094234,0.9378168,0.00015068593],"about_ca_topic_score_codex":0.000004823793,"about_ca_topic_score_gemma":5.91924e-7,"teacher_disagreement_score":0.8798119,"about_ca_system_score_codex":0.00003305746,"about_ca_system_score_gemma":0.00004255581,"threshold_uncertainty_score":0.65102065},"labels":[],"label_agreement":null},{"id":"W2624760699","doi":"10.1152/jn.00259.2017","title":"Diffusion-weighted tractography in the common marmoset monkey at 9.4T","year":2017,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Government of Canada","keywords":"Marmoset; Callithrix; White matter; Diffusion MRI; Neuroscience; Tractography; Fiber tract; Biology; Primate; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.06347437753438777,"score_gpt":0.3643572958683328,"score_spread":0.30088291833394504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624760699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901623,0.000028662247,0.000069542555,0.00893941,0.0000921448,0.00015379328,0.0000038137564,0.000012186184,0.00053816254],"genre_scores_gemma":[0.9959488,0.00048922666,0.00077395217,0.0025818031,0.0001426613,0.0000059250383,0.0000025932316,0.000013374023,0.0000416579],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99922055,0.00007397589,0.00030482866,0.00012344915,0.00013176605,0.00014543862],"domain_scores_gemma":[0.99875104,0.00013578817,0.00042283986,0.00057807623,0.000057840087,0.000054426066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047388196,0.000099133744,0.00028019756,0.0001031231,0.00020590759,0.000014504761,0.00042826706,0.0000439206,0.000015991987],"category_scores_gemma":[0.00006128265,0.000058650476,0.00014399947,0.00007983986,0.0001683385,0.00006747337,0.00009053169,0.00047583636,0.00000506426],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007952245,0.0007110292,0.019499673,0.000022753655,0.000021589278,0.0011585674,0.0001367844,0.000010409575,0.9628018,0.00056852197,0.0037563168,0.010517315],"study_design_scores_gemma":[0.00087644876,0.00066307763,0.9585416,0.000033541422,0.000035648693,0.0010543099,0.000012255518,0.00017500903,0.0011343161,0.004841359,0.032567654,0.000064781365],"about_ca_topic_score_codex":0.000008645026,"about_ca_topic_score_gemma":0.0000015152297,"teacher_disagreement_score":0.9616675,"about_ca_system_score_codex":0.000014158216,"about_ca_system_score_gemma":0.000013759363,"threshold_uncertainty_score":0.2391697},"labels":[],"label_agreement":null},{"id":"W2625813974","doi":"10.1016/j.nicl.2017.06.017","title":"Predicting pain relief: Use of pre-surgical trigeminal nerve diffusion metrics in trigeminal neuralgia","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; Toronto Western Hospital; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Trigeminal Neuralgia Association of Canada","keywords":"Trigeminal neuralgia; Diffusion MRI; Medicine; Fractional anisotropy; Trigeminal nerve; Anesthesia; Radiology; Magnetic resonance imaging","score_opus":0.21252290911907837,"score_gpt":0.45670683316170824,"score_spread":0.24418392404262987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625813974","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932807,0.00005971271,0.0027155557,0.0021214855,0.00018784424,0.0008139998,0.00002820985,0.00018424304,0.0006082679],"genre_scores_gemma":[0.9838762,0.00063482905,0.013966439,0.00039765806,0.00031177432,0.000043384232,0.000022987306,0.0000601087,0.00068661],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99642515,0.0003681055,0.0014693602,0.0008480104,0.00047225796,0.0004171196],"domain_scores_gemma":[0.9943328,0.0027111652,0.0007865124,0.0017129758,0.00017149822,0.00028507007],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0018207155,0.00027414723,0.0007939976,0.00023057849,0.00022323936,0.00007649849,0.00049709174,0.0002309637,0.000033545166],"category_scores_gemma":[0.014464731,0.00024231254,0.00036617467,0.0003357079,0.0005226298,0.00028888826,0.00040805465,0.0013397697,0.0000056973136],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013393555,0.0013756562,0.9379121,0.00009822423,0.000010507841,0.0013347141,0.000028030745,0.000005706816,0.0028614313,0.00023316742,0.001468593,0.05333251],"study_design_scores_gemma":[0.0035547672,0.0016922461,0.9501081,0.00033302297,0.00013034327,0.00030402731,0.000010442445,0.023037171,0.0010795569,0.00039064133,0.019089008,0.0002706671],"about_ca_topic_score_codex":0.00008151675,"about_ca_topic_score_gemma":0.000004530247,"teacher_disagreement_score":0.053061843,"about_ca_system_score_codex":0.000035857644,"about_ca_system_score_gemma":0.00008631141,"threshold_uncertainty_score":0.9938369},"labels":[],"label_agreement":null},{"id":"W2627002953","doi":"10.1016/j.bandc.2017.05.001","title":"Diffusion tensor MRI tractography reveals increased fractional anisotropy (FA) in arcuate fasciculus following music-cued motor training","year":2017,"lang":"en","type":"article","venue":"Brain and Cognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"FP7 People: Marie-Curie Actions; Wellcome Trust","keywords":"Arcuate fasciculus; Fractional anisotropy; Psychology; Diffusion MRI; Superior longitudinal fasciculus; Neuroscience; Audiology; White matter; Tractography; Motor learning; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.07908599173559543,"score_gpt":0.3464124446228678,"score_spread":0.26732645288727236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2627002953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98205155,0.000035675523,0.011498918,0.004081986,0.000046323843,0.00060130376,0.000029044117,0.00013796473,0.0015172242],"genre_scores_gemma":[0.98924154,0.00007620696,0.008620762,0.0015851165,0.00011488342,0.00013053881,0.00009388015,0.00002151886,0.00011554575],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99907166,0.000034534758,0.00020714215,0.00032130972,0.0001715147,0.00019385882],"domain_scores_gemma":[0.9993471,0.00011238627,0.00014095478,0.00024278737,0.000047128513,0.00010963711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018411413,0.00013683103,0.00021466627,0.00015407687,0.00039513863,0.000059432507,0.00006664568,0.00007431174,0.000025783691],"category_scores_gemma":[0.00026125283,0.00013091047,0.00010626888,0.00009043593,0.00008165098,0.00021491444,0.000031968902,0.00021446454,0.0000037456052],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004609411,0.0005226393,0.04821533,0.00008391979,0.00004919375,0.00018677635,0.00046164,8.248374e-7,0.85285664,0.0016301315,0.00084849255,0.094683446],"study_design_scores_gemma":[0.0034314487,0.00019126514,0.9738189,0.0004512007,0.00009538171,0.000094796414,0.00032817444,0.0012013679,0.0016289763,0.015033747,0.0034657628,0.00025895354],"about_ca_topic_score_codex":0.000049077793,"about_ca_topic_score_gemma":0.0000110274605,"teacher_disagreement_score":0.92560357,"about_ca_system_score_codex":0.000018611765,"about_ca_system_score_gemma":0.000022073566,"threshold_uncertainty_score":0.53383744},"labels":[],"label_agreement":null},{"id":"W2633513078","doi":"10.1101/153924","title":"Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; University College London; Alberta Children's Hospital Foundation; Norges Forskningsråd; Universitetet i Oslo; Children's Hospital Foundation","keywords":"Diffusion MRI; Neuroimaging; White matter; Brain development; Psychology; Popularity; Data science; Computer science; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.02907968211941895,"score_gpt":0.30838032152459577,"score_spread":0.2793006394051768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2633513078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98230755,0.012298853,0.0018446014,0.0020018101,0.000086249485,0.001290462,0.00003532017,0.00012865463,0.0000065109293],"genre_scores_gemma":[0.71838194,0.0043383306,0.27695426,0.000087620494,0.000046933365,0.00013703156,2.7166212e-7,0.000051275092,0.0000023334117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99843323,0.000051427687,0.00036661516,0.00075231795,0.0001485204,0.00024785794],"domain_scores_gemma":[0.998426,0.000018587893,0.0003715912,0.00090172846,0.00014682258,0.0001352583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002807274,0.00033879647,0.0005543957,0.0001819202,0.00013110293,0.000035590554,0.00020915204,0.00028469093,0.000003525507],"category_scores_gemma":[0.000041372256,0.00031591914,0.00003742455,0.00006912132,0.00023339712,0.00005756305,0.0008031189,0.0005975371,7.994612e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005759473,0.00036067123,0.70300907,0.0034003467,0.00006462172,0.00003815138,0.00028601923,6.436094e-7,0.29160282,0.00027919124,0.000047024303,0.0008538141],"study_design_scores_gemma":[0.00042401833,0.000021507403,0.92821085,0.0018726558,0.00004329829,2.3295168e-7,0.0000030164035,0.000023028708,0.06729873,0.000017600754,0.0018169702,0.00026808114],"about_ca_topic_score_codex":0.000003070039,"about_ca_topic_score_gemma":7.2110834e-7,"teacher_disagreement_score":0.27510968,"about_ca_system_score_codex":0.000048421694,"about_ca_system_score_gemma":0.00014796552,"threshold_uncertainty_score":0.9999293},"labels":[],"label_agreement":null},{"id":"W2638045955","doi":"10.3389/fnhum.2017.00306","title":"Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks","year":2017,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Boniface Hospital; Health Sciences Centre; University of Manitoba","funders":"Canadian Institutes of Health Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"White matter; Diffusion MRI; Precuneus; Tractography; Artificial intelligence; Computer science; Region of interest; Fractional anisotropy; Spatial normalization; Pattern recognition (psychology); Brain mapping; Neuroscience; Psychology; Functional magnetic resonance imaging; Magnetic resonance imaging; Voxel; Medicine","score_opus":0.028165057815306205,"score_gpt":0.35485452185098354,"score_spread":0.32668946403567733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2638045955","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9744837,0.00003536809,0.023212742,0.00035910387,0.0005035859,0.00067902217,0.000010676789,0.000077637465,0.0006381464],"genre_scores_gemma":[0.9959678,0.000013453703,0.0026572475,0.00038354433,0.00019122675,0.000046143454,0.000004799277,0.000025751777,0.0007100469],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987127,0.00003489511,0.00026986495,0.0005007834,0.00020642375,0.0002752871],"domain_scores_gemma":[0.9989874,0.000018312425,0.00023361358,0.00061648764,0.000042412223,0.00010181243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011734955,0.00016284801,0.00028104772,0.000115913914,0.00040220137,0.00006416083,0.0003108279,0.00005491799,0.000011795457],"category_scores_gemma":[0.00011872866,0.00015765431,0.000043222135,0.00009402255,0.00092193705,0.00017458688,0.00017825293,0.00024331317,3.5849382e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038061098,0.00023431239,0.947945,0.00010290648,0.0000022410316,0.00006657529,0.00015495915,0.00019496854,0.036015227,0.00013275088,0.014504921,0.00060805987],"study_design_scores_gemma":[0.00058237824,0.00040837677,0.979313,0.00013747437,0.000028445844,0.000011439472,0.000030880336,0.013709035,0.0040427656,0.0012306613,0.0002903262,0.00021520015],"about_ca_topic_score_codex":0.00003931864,"about_ca_topic_score_gemma":0.000008373773,"teacher_disagreement_score":0.03197246,"about_ca_system_score_codex":0.000032350603,"about_ca_system_score_gemma":0.000020574105,"threshold_uncertainty_score":0.64289564},"labels":[],"label_agreement":null},{"id":"W266018641","doi":"10.1093/oxfordhb/9780199764228.013.5","title":"White Matter Connectivity","year":2014,"lang":"en","type":"book","venue":"Oxford University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Psychology; Frontotemporal dementia; Dementia; White matter; Diffusion MRI; Aphasia; Schizophrenia (object-oriented programming); Agnosia; Neuropsychology; Depression (economics); Psychiatry; Neuroscience; Disease; Clinical psychology; Cognition; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.042216648225983325,"score_gpt":0.26783251262986846,"score_spread":0.22561586440388515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W266018641","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00008538276,0.000008690298,0.013610262,0.00020853899,0.0000390921,0.0005528688,0.00006704493,0.00033938795,0.9850887],"genre_scores_gemma":[0.00056540937,0.000030296826,0.0026470688,0.00060087733,0.000115313036,0.00000317385,0.00007143814,0.000052615393,0.9959138],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99908584,0.000023294475,0.0001103565,0.00042785902,0.00014904024,0.00020360488],"domain_scores_gemma":[0.9988922,0.000045517405,0.00014441891,0.00070322386,0.000084744264,0.0001299177],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000042811298,0.00024047129,0.00037051804,0.00010588494,0.00011524668,0.000012655967,0.0002150479,0.0002239394,0.000059369937],"category_scores_gemma":[0.000003487074,0.00026637857,0.00016712489,0.000010444561,0.0001490382,0.000035871253,0.00021368937,0.00050160225,0.0000063936736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025645652,0.00008104877,0.0018719207,0.0005090212,0.00014545226,0.0002095742,0.00007581342,0.0000041842195,0.000063188076,0.266032,0.72603005,0.0047212616],"study_design_scores_gemma":[0.00041032443,0.00005850208,0.00057068485,0.0001429654,0.00021336613,0.000042367494,0.0000024395808,0.00003785187,0.0000898078,0.0008579435,0.99733824,0.00023551944],"about_ca_topic_score_codex":0.00000478107,"about_ca_topic_score_gemma":0.0000016097174,"teacher_disagreement_score":0.27130815,"about_ca_system_score_codex":0.00017190169,"about_ca_system_score_gemma":0.00009518255,"threshold_uncertainty_score":0.99997884},"labels":[],"label_agreement":null},{"id":"W2666006491","doi":"10.1503/jpn.160090","title":"Hemispheric lateralization abnormalities of the white matter microstructure in patients with schizophrenia and bipolar disorder","year":2017,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Biomedical Research Council; National Medical Research Council; Medical Research Council; National Healthcare Group; Duke-NUS Medical School","keywords":"Lateralization of brain function; Bipolar disorder; Schizophrenia (object-oriented programming); Laterality; Psychology; White matter; Fractional anisotropy; Psychosis; Neuroscience; Audiology; Psychiatry; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.009839823075723788,"score_gpt":0.26573112413209254,"score_spread":0.25589130105636876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2666006491","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99728835,0.00010625767,0.00027405957,0.002145325,0.00006946275,0.00007410229,0.00000231973,0.0000019637512,0.00003815996],"genre_scores_gemma":[0.99680763,0.00005474818,0.0026840037,0.00032534075,0.000011909859,4.6205608e-7,7.736259e-8,0.000005532246,0.000110280555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99967265,0.000008040673,0.00011471029,0.00007185247,0.00008077509,0.000051986808],"domain_scores_gemma":[0.9995711,0.0000023357811,0.00023387479,0.00014101485,0.000026626392,0.000025090314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032159056,0.000046367684,0.00007776969,0.000024763081,0.00010441866,0.000021770542,0.00009091784,0.000012892714,0.0000037631955],"category_scores_gemma":[0.000010668375,0.000026064363,0.000012408114,0.00005904071,0.00018207819,0.00013779731,0.000031133535,0.000090823545,3.4345184e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005240742,0.000026672278,0.9983318,0.000020739466,4.870982e-7,2.746699e-7,0.000023677714,0.000004648189,0.0012626632,0.00008053848,0.000042048025,0.0001540857],"study_design_scores_gemma":[0.0005397677,0.0000942799,0.99813104,0.000093069706,0.0000081854,0.00005005095,0.0000065020463,0.000017715056,0.000194348,0.00030025048,0.0005372462,0.000027549422],"about_ca_topic_score_codex":0.0000021764845,"about_ca_topic_score_gemma":0.0000032594814,"teacher_disagreement_score":0.002409944,"about_ca_system_score_codex":0.0000017452062,"about_ca_system_score_gemma":0.000016101421,"threshold_uncertainty_score":0.10628739},"labels":[],"label_agreement":null},{"id":"W2679766784","doi":"10.3389/fninf.2017.00042","title":"Visualization, Interaction and Tractometry: Dealing with Millions of Streamlines from Diffusion MRI Tractography","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Hospitalier Universitaire de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Visualization; Streamlines, streaklines, and pathlines; Diffusion MRI; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Medicine; Radiology; Mechanics","score_opus":0.035425939507643625,"score_gpt":0.3413802033523625,"score_spread":0.3059542638447189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2679766784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7680302,0.000056536326,0.23052512,0.00034123764,0.00008653392,0.00030917462,0.000029874815,0.00005504804,0.0005662666],"genre_scores_gemma":[0.88079274,0.0012199035,0.117821075,0.00007341952,0.000018141745,0.000008240208,0.000042154017,0.000015717116,0.00000860263],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99932367,0.000006585816,0.00031637526,0.00012085934,0.00013148392,0.000101021695],"domain_scores_gemma":[0.9991063,0.000041621966,0.00034086246,0.00039291626,0.000059926635,0.000058397123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043412736,0.00011059561,0.00022271466,0.00027100736,0.00013067648,0.000036068577,0.00009688266,0.00004216506,0.0000023955042],"category_scores_gemma":[0.000076678436,0.0000925314,0.00003224529,0.00013786778,0.000117853844,0.00035950527,0.00003575373,0.00015383855,2.0728739e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017933028,0.0002073838,0.968427,0.00012609227,0.000029240035,0.000008936259,0.00060079986,0.00013509709,0.0015024449,0.00061110454,0.00060662493,0.027565971],"study_design_scores_gemma":[0.0028566301,0.000522746,0.82145536,0.00090052467,0.00021724755,0.000059564267,0.0018232128,0.14838529,0.0101981275,0.0026383183,0.010554414,0.00038859522],"about_ca_topic_score_codex":0.000029818548,"about_ca_topic_score_gemma":0.0000054528864,"teacher_disagreement_score":0.14825019,"about_ca_system_score_codex":0.00001024343,"about_ca_system_score_gemma":0.000011913434,"threshold_uncertainty_score":0.37733212},"labels":[],"label_agreement":null},{"id":"W2704183690","doi":"10.1007/s00415-017-8550-8","title":"Higher blood–brain barrier permeability is associated with higher white matter hyperintensities burden","year":2017,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; National Natural Science Foundation of China","keywords":"Hyperintensity; Medicine; White matter; Neurology; Leukoaraiosis; Magnetic resonance imaging; Montreal Cognitive Assessment; Internal medicine; Cardiology; Cognitive impairment; Psychiatry; Radiology; Disease","score_opus":0.04596272256702478,"score_gpt":0.3219293559223865,"score_spread":0.2759666333553617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2704183690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8299465,0.000022480686,0.000104858074,0.16713648,0.00014925977,0.00011343652,0.000009024415,0.000031965985,0.0024860145],"genre_scores_gemma":[0.9698231,0.0000123451555,0.000685144,0.022812257,0.00030168507,0.000006079282,0.0000011760176,0.000032105356,0.006326104],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990432,0.00005437076,0.00029829395,0.00020698436,0.00018240046,0.00021472835],"domain_scores_gemma":[0.99842995,0.00008642956,0.00047684836,0.0005684593,0.00031732876,0.00012098403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014942086,0.00014308337,0.0003878315,0.0000694212,0.00015775074,0.00003253072,0.0002296256,0.00009654487,0.0007544872],"category_scores_gemma":[0.00011268991,0.00010251467,0.00011233045,0.000037323927,0.00030937576,0.00013119722,0.00007313543,0.00055073015,0.000012370119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080924,0.00024520213,0.91041595,0.000025548865,0.00020323881,0.0013243135,0.00018382355,0.000010414931,0.023616735,0.00019973479,0.0627083,0.00025749116],"study_design_scores_gemma":[0.0011882161,0.0009755217,0.92603797,0.00003218062,0.00016545526,0.0015784075,0.0000049701775,0.000019716923,0.0005900878,0.0010922508,0.06821204,0.00010317376],"about_ca_topic_score_codex":0.0000068950635,"about_ca_topic_score_gemma":0.0000010662001,"teacher_disagreement_score":0.14432421,"about_ca_system_score_codex":0.00001536747,"about_ca_system_score_gemma":0.000038893977,"threshold_uncertainty_score":0.82611054},"labels":[],"label_agreement":null},{"id":"W2727983075","doi":"10.1016/j.neuroimage.2017.06.083","title":"Fiberprint: A subject fingerprint based on sparse code pooling for white matter fiber analysis","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Eastern Washington University","keywords":"Fiber bundle; Artificial intelligence; Pattern recognition (psychology); Pooling; Computer science; Feature vector; Diffusion MRI; Fingerprint (computing); Human Connectome Project; Bundle; Biology; Magnetic resonance imaging","score_opus":0.0788378342822814,"score_gpt":0.3710360669902838,"score_spread":0.2921982327080024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2727983075","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46848002,0.000021916547,0.3949525,0.055401616,0.00021916747,0.0038564226,0.00048682134,0.0011599179,0.07542162],"genre_scores_gemma":[0.9470874,0.0000050419853,0.043928694,0.004936254,0.000102881895,0.0002053707,0.000039600698,0.000066670276,0.0036280777],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985983,0.000021255963,0.00025294124,0.0006165166,0.00018959322,0.00032144028],"domain_scores_gemma":[0.99760306,0.00013067965,0.00020539403,0.0018412563,0.00009086925,0.00012876875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014446622,0.00021687723,0.00036001127,0.00021264511,0.0003831292,0.0001152119,0.00029890894,0.00005520585,0.00034580825],"category_scores_gemma":[0.00017307237,0.000202863,0.00034365535,0.00015189509,0.000095877076,0.00008575154,0.00009503353,0.00026055373,0.00014712533],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032453332,0.002145944,0.8499509,0.0006967278,0.000601077,0.0006318898,0.00023324236,0.012810803,0.049868017,0.0012196725,0.048969936,0.029626442],"study_design_scores_gemma":[0.001267069,0.00022000624,0.87076265,0.000090890404,0.00078825507,0.000019920071,0.0000028970821,0.067259364,0.009969291,0.0005461448,0.048721135,0.0003523664],"about_ca_topic_score_codex":0.000013848196,"about_ca_topic_score_gemma":0.0000053156755,"teacher_disagreement_score":0.4786074,"about_ca_system_score_codex":0.000036385427,"about_ca_system_score_gemma":0.000031084048,"threshold_uncertainty_score":0.82725126},"labels":[],"label_agreement":null},{"id":"W2732416206","doi":"10.1016/j.neuroimage.2017.06.047","title":"Thalamus segmentation using multi-modal feature classification: Validation and pilot study of an age-matched cohort","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Thalamus; Voxel; Fractional anisotropy; Pattern recognition (psychology); Diffusion MRI; Artificial intelligence; Segmentation; Feature (linguistics); Computer science; Neuroscience; Medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.2382049101604581,"score_gpt":0.43425491782629133,"score_spread":0.19605000766583322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2732416206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99165547,0.0000072884636,0.00632538,0.00037927827,0.000041548737,0.0012685127,0.000009724431,0.00011200661,0.00020080768],"genre_scores_gemma":[0.96358776,0.000021300884,0.03604006,0.00007147433,0.000048283753,0.000052038176,0.00003804042,0.00002894939,0.00011211485],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99905956,0.000050602037,0.00019800078,0.00038674733,0.00019244972,0.00011265499],"domain_scores_gemma":[0.998681,0.00002113074,0.0002792144,0.0008437025,0.000099975296,0.000074977026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000097430035,0.0001313369,0.00020447832,0.000064978696,0.0003065566,0.00007384806,0.00013508782,0.000029359671,0.000004339589],"category_scores_gemma":[0.000069118105,0.00012702351,0.00001995989,0.00006156936,0.000113209295,0.0003275132,0.000066198685,0.00017133755,9.675101e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007798348,0.0010468372,0.25087422,0.000031605072,0.000011479792,0.000028208522,0.00016831077,0.000009889267,0.745553,0.000041516032,0.000018811676,0.0021380936],"study_design_scores_gemma":[0.0013935269,0.00089636137,0.97209615,0.000018372872,0.00011788735,0.000054819116,0.00016739333,0.005237125,0.019825255,0.00006494674,0.000030546667,0.00009761257],"about_ca_topic_score_codex":0.00007259413,"about_ca_topic_score_gemma":0.000007375944,"teacher_disagreement_score":0.7257278,"about_ca_system_score_codex":0.00002322083,"about_ca_system_score_gemma":0.00001837398,"threshold_uncertainty_score":0.51798683},"labels":[],"label_agreement":null},{"id":"W2733738172","doi":"10.1016/j.eurpsy.2017.01.2122","title":"Classification of first-episode schizophrenia spectrum disorders and controls from whole brain white matter fractional anisotropy using machine learning","year":2017,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fractional anisotropy; Support vector machine; White matter; Schizophrenia (object-oriented programming); Artificial intelligence; Psychology; Machine learning; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Computer science","score_opus":0.029833558692052956,"score_gpt":0.31109454678328896,"score_spread":0.281260988091236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2733738172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8410281,0.00046917557,0.074335754,0.07948418,0.00021028139,0.00040562218,0.0000937902,0.000161224,0.0038118956],"genre_scores_gemma":[0.949094,0.00003746516,0.04959006,0.00048248642,0.00027466644,0.0000051511197,0.000062665706,0.000055445722,0.0003980358],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990613,0.000059652666,0.0002735294,0.00033641132,0.00012437865,0.00014472812],"domain_scores_gemma":[0.9989268,0.000035930167,0.00038949694,0.0005521901,0.000020107234,0.000075461656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001162438,0.00014712117,0.00019371691,0.000062466985,0.0004480124,0.00005348155,0.00015089371,0.000031082927,0.0000925616],"category_scores_gemma":[0.000046603804,0.00014364693,0.00006679761,0.000042645766,0.0001409302,0.0001454004,0.000078676996,0.0003119808,0.000035718676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013603384,0.00008715477,0.99106735,0.000021529138,0.000021938162,0.0000013934151,0.0000351246,0.000026890333,0.006003213,0.0009640923,0.0012188825,0.00041638402],"study_design_scores_gemma":[0.0013777443,0.000076254386,0.9610262,0.00015089345,0.000056556928,0.000016943239,0.000029334891,0.008648088,0.000058141417,0.003811239,0.024607487,0.00014115032],"about_ca_topic_score_codex":0.00010809542,"about_ca_topic_score_gemma":0.00008613103,"teacher_disagreement_score":0.108065955,"about_ca_system_score_codex":0.000015882657,"about_ca_system_score_gemma":0.0000129855725,"threshold_uncertainty_score":0.5857752},"labels":[],"label_agreement":null},{"id":"W2735032522","doi":"10.1161/str.47.suppl_1.214","title":"Abstract 214: Corticospinal Tract Integrity is Acutely Maintained Within Perihematoma Edema","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Edema; Corticospinal tract; Fractional anisotropy; Hematoma; White matter; Intracerebral hemorrhage; Anesthesia; Diffusion MRI; Stroke (engine); Magnetic resonance imaging; Nuclear medicine; Glasgow Coma Scale; Radiology; Surgery","score_opus":0.06869884978146984,"score_gpt":0.3671000579202947,"score_spread":0.29840120813882487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735032522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9437507,0.000045298126,0.032055993,0.016764311,0.00008781771,0.00052318204,0.00015407646,0.0005683609,0.0060502677],"genre_scores_gemma":[0.97783196,0.000044618224,0.018375121,0.0011786829,0.00012556696,0.0000636849,0.0000073052506,0.000033227967,0.0023398334],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988251,0.000009881372,0.0003137096,0.00034865882,0.00022233765,0.0002803128],"domain_scores_gemma":[0.999053,0.00006347295,0.00013162458,0.00048329245,0.00009456236,0.00017403708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011363152,0.00017783618,0.00025295274,0.000062396015,0.00008596411,0.000017257913,0.00013618279,0.00008058149,0.00047888103],"category_scores_gemma":[0.00010516012,0.000117250485,0.0001282195,0.00008802803,0.00013433654,0.000115766285,0.00004182475,0.000293378,0.00012498467],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060177664,0.0010619673,0.039151616,0.00017693115,0.000114348724,0.0004948261,0.00029892765,3.6475367e-7,0.8421564,0.0337506,0.015295511,0.0668967],"study_design_scores_gemma":[0.0034497574,0.0011905452,0.5880687,0.0008183465,0.00022184875,0.0017098958,0.00028153334,0.00017725126,0.3231152,0.017036313,0.06315053,0.0007800454],"about_ca_topic_score_codex":0.000014076138,"about_ca_topic_score_gemma":0.0000015468567,"teacher_disagreement_score":0.5489171,"about_ca_system_score_codex":0.000078964586,"about_ca_system_score_gemma":0.00008422495,"threshold_uncertainty_score":0.52434117},"labels":[],"label_agreement":null},{"id":"W2735700022","doi":"10.1016/j.neuroimage.2017.07.015","title":"Recognition of white matter bundles using local and global streamline-based registration and clustering","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":317,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Indiana University; State Corporation Commission","keywords":"Computer science; Bundle; Artificial intelligence; Tractography; Cluster analysis; Diffusion MRI; Process (computing); White matter; Streamlines, streaklines, and pathlines; Pipeline (software); Pattern recognition (psychology)","score_opus":0.2521597257101989,"score_gpt":0.4376269879966907,"score_spread":0.1854672622864918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2735700022","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012057895,0.8108123,0.1831243,0.0004599107,0.0000815281,0.0020260387,0.0005142937,0.00018399418,0.001591831],"genre_scores_gemma":[0.00271046,0.968464,0.028187545,0.00017622949,0.00008493823,0.000039255556,0.00020364787,0.00006169415,0.00007224206],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989352,0.000039776056,0.00037554966,0.00040881184,0.00010985281,0.00013076505],"domain_scores_gemma":[0.99891627,0.000039246686,0.00045295712,0.00046247157,0.000057467398,0.000071603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007268986,0.00023709975,0.0006800597,0.00007279618,0.00013285581,0.000037941965,0.00007283492,0.00011242408,0.000007723176],"category_scores_gemma":[0.000037639264,0.00021670562,0.00009808812,0.000070568276,0.00022964888,0.00009233703,0.00010031245,0.00016529164,0.0000019798474],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018313478,0.000045839468,0.0005500049,0.010275682,0.000011121701,0.00003242772,0.0000033728984,0.0000015580856,0.000044775014,0.0000079220445,0.000096032505,0.98891294],"study_design_scores_gemma":[0.001992935,0.0006735477,0.005722586,0.05127309,0.00427674,0.004352817,0.000015459627,0.0077876747,0.00017032151,0.00085686933,0.921554,0.0013239157],"about_ca_topic_score_codex":0.000020390307,"about_ca_topic_score_gemma":0.0000043777977,"teacher_disagreement_score":0.98758906,"about_ca_system_score_codex":0.000037468366,"about_ca_system_score_gemma":0.000074694195,"threshold_uncertainty_score":0.8836999},"labels":[],"label_agreement":null},{"id":"W2736256711","doi":"10.1093/scan/nsx070","title":"White matter correlates of psychopathic traits in a female community sample","year":2017,"lang":"en","type":"article","venue":"Social Cognitive and Affective Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Stiftelsen för Strategisk Forskning","keywords":"Uncinate fasciculus; Psychology; Cingulum (brain); Psychopathy; White matter; Facet (psychology); Diffusion MRI; Fornix; Fractional anisotropy; Fasciculus; Big Five personality traits; Neuroscience; Personality; Medicine; Magnetic resonance imaging; Social psychology","score_opus":0.09969603128901235,"score_gpt":0.402511471614359,"score_spread":0.3028154403253467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736256711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929724,0.000010340548,0.0031612816,0.00047635855,0.000029308496,0.0003863536,0.00007317049,0.00002131965,0.0028695227],"genre_scores_gemma":[0.9990946,0.00002082833,0.000135632,0.0006406894,0.000017371216,0.000040307285,0.0000019404636,0.000008610061,0.000040034793],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993548,0.000097078424,0.00010187208,0.00020754497,0.000096042444,0.00014270388],"domain_scores_gemma":[0.99942696,0.00020551137,0.00012308969,0.00012270275,0.00008066077,0.000041067062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018262802,0.0000888588,0.00018163552,0.000055254597,0.0006619572,0.000025748901,0.0001146766,0.000035630354,0.000006026914],"category_scores_gemma":[0.00049333106,0.00008411702,0.000039780505,0.00012047052,0.0008609372,0.00014397333,0.00009625502,0.00036066287,0.0000014810435],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004822234,0.00015508063,0.98869485,0.000026285448,9.823667e-7,0.0000036279423,0.00092893915,6.667404e-8,0.005823927,0.0002356359,0.000014755082,0.004067657],"study_design_scores_gemma":[0.00051000714,0.00020276893,0.99398834,0.00010217132,0.000014246272,0.000009808318,0.0003856823,0.000028867265,0.0012817082,0.0033900172,0.000015515998,0.00007088466],"about_ca_topic_score_codex":0.000076627395,"about_ca_topic_score_gemma":0.000026737327,"teacher_disagreement_score":0.006122242,"about_ca_system_score_codex":0.000007975878,"about_ca_system_score_gemma":0.000020199575,"threshold_uncertainty_score":0.50913066},"labels":[],"label_agreement":null},{"id":"W2737094118","doi":"10.1002/hbm.23743","title":"Towards a unified analysis of brain maturation and aging across the entire lifespan: A MRI analysis","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":286,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Drug Abuse; Engineering and Physical Sciences Research Council; National Institutes of Health; Genentech; Dana Foundation; Agence Nationale de la Recherche; Canadian Institutes of Health Research; National Health and Medical Research Council; Leon Levy Foundation; GlaxoSmithKline; Alzheimer's Drug Discovery Foundation; Medical Research Council; Centre National de la Recherche Scientifique; National Institute on Aging; Alzheimer's Association","keywords":"Brain size; White matter; Neuroimaging; Encephalization; Neuroscience; Aging brain; Hum; Brain aging; Amygdala; Senescence; Psychology; Hippocampus; Magnetic resonance imaging; Cognition; Medicine; Internal medicine; History","score_opus":0.08566485548572217,"score_gpt":0.4056353312085949,"score_spread":0.31997047572287274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737094118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8465302,0.00008229236,0.107581876,0.044249084,0.000014099293,0.0004105786,0.00002545352,0.00012763476,0.0009787716],"genre_scores_gemma":[0.99522686,0.000020651556,0.0027756435,0.0010455023,0.000055371544,0.000031769858,0.00006164634,0.000012908631,0.00076965906],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989627,0.000046684243,0.0002947005,0.00032161697,0.0001824049,0.00019192041],"domain_scores_gemma":[0.9983906,0.00011635029,0.00035602073,0.0009890776,0.000089603935,0.000058334637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005167524,0.00012864744,0.00039404747,0.0002927429,0.0009913314,0.00013899316,0.0002358048,0.0000463252,0.000021622327],"category_scores_gemma":[0.00021628258,0.00010141549,0.00022648863,0.00072167284,0.00023266925,0.00011675557,0.00016875667,0.00017077287,6.260687e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010656971,0.0002821213,0.3007215,0.0004414515,0.011183291,0.000057574114,0.02076884,0.0008090822,0.5788466,0.04583605,0.0053929547,0.035554018],"study_design_scores_gemma":[0.00028754832,0.000020635964,0.97697324,0.000058001082,0.0015626509,0.000004637979,0.00055770605,0.013096982,0.00039168482,0.001212132,0.0057128607,0.000121951976],"about_ca_topic_score_codex":0.00016951107,"about_ca_topic_score_gemma":0.00013952593,"teacher_disagreement_score":0.6762517,"about_ca_system_score_codex":0.000024353643,"about_ca_system_score_gemma":0.000015053738,"threshold_uncertainty_score":0.762462},"labels":[],"label_agreement":null},{"id":"W2737984394","doi":"10.1523/jneurosci.0560-17.2017","title":"Changes in White Matter Microstructure Impact Cognition by Disrupting the Ability of Neural Assemblies to Synchronize","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; Hospital for Sick Children; Pediatric Oncology Group of Ontario; Garron Family Cancer Centre; Fondation Brain Canada","keywords":"White matter; Neuroscience; Cognition; Psychology; Cuneus; Diffusion MRI; Audiology; Visual cortex; Medicine; Magnetic resonance imaging; Precuneus","score_opus":0.05281792820267213,"score_gpt":0.39681723200265046,"score_spread":0.34399930379997834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2737984394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9805527,0.000019270874,0.0009655375,0.018145928,0.00007292385,0.00017256275,0.00001598827,0.0000051437623,0.000049946415],"genre_scores_gemma":[0.99788606,0.000022943923,0.0006796745,0.0013427391,0.000040594532,0.0000031052223,2.7176762e-7,0.0000063774137,0.0000182031],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99930847,0.000023866316,0.00021419674,0.00012832653,0.00018764462,0.00013750607],"domain_scores_gemma":[0.9990926,0.000045659184,0.00039004406,0.00030776134,0.00009976987,0.00006416623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002119299,0.00007512318,0.00015958381,0.00006217867,0.00014559587,0.000058798578,0.00031403452,0.000017782522,0.000006528344],"category_scores_gemma":[0.00036631693,0.00004455172,0.000053436757,0.00012550857,0.00020039841,0.00019029471,0.000078442616,0.00023290873,3.9949816e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002589958,0.000028404704,0.19447033,0.000010957977,4.82546e-7,0.0000067664173,0.00006686625,0.000021088326,0.8040145,0.0000013840549,0.00048247544,0.00087081274],"study_design_scores_gemma":[0.000157524,0.00021579102,0.9755746,0.00006789924,0.000010512723,0.00033568416,0.000021825843,0.00026382052,0.022943893,0.00012611762,0.00024320203,0.00003910941],"about_ca_topic_score_codex":0.000005912608,"about_ca_topic_score_gemma":0.0000032482278,"teacher_disagreement_score":0.78110427,"about_ca_system_score_codex":0.000026262847,"about_ca_system_score_gemma":0.000026399157,"threshold_uncertainty_score":0.18167664},"labels":[],"label_agreement":null},{"id":"W2738800716","doi":"10.1002/hbm.23741","title":"Ax<scp>T</scp>ract: Toward microstructure informed tractography","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"H2020 European Research Council; Horizon 2020; Natural Sciences and Engineering Research Council of Canada; Centre d'Imagerie BioMédicale","keywords":"Tractography; White matter; Diffusion MRI; Streamlines, streaklines, and pathlines; Computer science; Connectomics; Artificial intelligence; Magnetic resonance imaging; Neuroscience; Microstructure; Geology; Computer vision; Physics; Psychology; Connectome; Materials science; Medicine; Radiology; Functional connectivity","score_opus":0.11000815081223125,"score_gpt":0.3775074931784151,"score_spread":0.26749934236618383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2738800716","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9013649,0.00013988589,0.018271118,0.011759665,0.00014991882,0.0012728592,0.000034843153,0.0009917375,0.066015035],"genre_scores_gemma":[0.9807597,0.000032301763,0.013663932,0.0033282267,0.00026583424,0.000057748377,0.000059587524,0.0000434426,0.0017892442],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988654,0.000009940869,0.00026983657,0.00033508908,0.00017302173,0.0003466574],"domain_scores_gemma":[0.99838763,0.00013955862,0.00027916822,0.0009764377,0.00007147336,0.0001457114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011461517,0.00020346302,0.00026444282,0.00017061338,0.00091940566,0.00015487343,0.00036405746,0.000104061844,0.000030060626],"category_scores_gemma":[0.00054485165,0.0001936242,0.00016213086,0.00009396261,0.00022079604,0.00023831718,0.00012518914,0.00042519768,0.000020368594],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009279593,0.00011837069,0.04964347,0.00036624126,0.00007672441,0.000083748695,0.0027151213,0.000003792167,0.8175068,0.017471632,0.10580968,0.0061951196],"study_design_scores_gemma":[0.0005184551,0.000040327755,0.5168689,0.00013651281,0.000018829178,0.000071875234,0.00020390547,0.000021784774,0.0016669837,0.009277174,0.47109243,0.0000828489],"about_ca_topic_score_codex":0.000017654495,"about_ca_topic_score_gemma":0.0000037057428,"teacher_disagreement_score":0.8158398,"about_ca_system_score_codex":0.000033022097,"about_ca_system_score_gemma":0.000038412716,"threshold_uncertainty_score":0.7895766},"labels":[],"label_agreement":null},{"id":"W2739042028","doi":"10.1007/978-3-319-73839-0_4","title":"A Generalized SMT-Based Framework for Diffusion MRI Microstructural Model Estimation","year":2018,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Orientation (vector space); Biological system; Axial symmetry; Computer science; Estimation theory; Diffusion MRI; Spherical harmonics; Algorithm; Ellipsoid; Physics; Mathematics; Magnetic resonance imaging; Mathematical analysis; Geometry","score_opus":0.08106635121994765,"score_gpt":0.3953394343880638,"score_spread":0.31427308316811614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739042028","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012201843,0.00006277746,0.9956351,0.000264166,0.0000330113,0.0013211487,0.00008235685,0.0001923161,0.0011889674],"genre_scores_gemma":[0.0014336035,0.00015509126,0.9803615,0.0005361208,0.00012962348,0.00011393654,0.0009433327,0.00012855521,0.016198244],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901855,0.0000028647385,0.00036687538,0.00031705628,0.00016425754,0.00013040125],"domain_scores_gemma":[0.9990175,0.00006867423,0.00031990727,0.0003298334,0.00019417606,0.000069959395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000748635,0.00025952337,0.0003587026,0.00012080247,0.00015140524,0.0000451386,0.000057701698,0.00026176317,0.00005638778],"category_scores_gemma":[0.0000653547,0.00023007998,0.000097117685,0.000034312834,0.000083321895,0.000035907044,0.000035402678,0.00010791411,0.000004329445],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042138643,0.000052537267,0.0000028938186,0.00084108574,0.000017731933,5.040028e-7,0.00018589434,0.00016279725,0.001871146,0.9936215,0.001722037,0.001479684],"study_design_scores_gemma":[0.0003043193,0.000078027944,0.0000014030574,0.00047931127,0.00012977944,0.000006892173,0.0000022068539,0.5606724,0.00083645544,0.4344072,0.002942396,0.00013957621],"about_ca_topic_score_codex":4.96097e-7,"about_ca_topic_score_gemma":3.1580595e-7,"teacher_disagreement_score":0.5605096,"about_ca_system_score_codex":0.00004355664,"about_ca_system_score_gemma":0.000041159452,"threshold_uncertainty_score":0.938239},"labels":[],"label_agreement":null},{"id":"W2739464459","doi":"10.1016/j.nicl.2017.07.020","title":"A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":175,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Neuroscience; Putamen; Diffusion MRI; Thalamus; Tractography; Parkinson's disease; Basal ganglia; Psychology; Deep brain stimulation; Essential tremor; Neurology; Medicine; Magnetic resonance imaging; Pathology; Disease; Central nervous system; Radiology","score_opus":0.2194016638390161,"score_gpt":0.47843130508799625,"score_spread":0.25902964124898015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739464459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9124488,0.000017011955,0.0111110285,0.056642793,0.00053888705,0.004335758,0.005190316,0.00081407453,0.008901307],"genre_scores_gemma":[0.97833854,0.000054127893,0.010528435,0.009911631,0.00030945957,0.00012225394,0.00015990424,0.00007746059,0.0004981978],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99716586,0.00012909248,0.00076731096,0.0011192657,0.00041123366,0.0004072375],"domain_scores_gemma":[0.9946935,0.0013449758,0.00033343444,0.0031636737,0.00010384402,0.00036057227],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00053167733,0.0003024914,0.0005502371,0.00006816027,0.00041539574,0.00019768078,0.0006779752,0.0001040314,0.00022425794],"category_scores_gemma":[0.003392627,0.0002558572,0.00013678765,0.00007722839,0.0005530549,0.00020277387,0.0003658485,0.0009848629,0.00065690535],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017876574,0.002684212,0.88883054,0.000017823968,0.000016592137,0.00097241637,0.00001285992,5.434273e-7,0.0010154423,0.00010157565,0.10041865,0.0057505523],"study_design_scores_gemma":[0.0013602012,0.002304998,0.93140334,0.000054238255,0.00012774559,0.00004980791,0.000014905333,0.00019804918,0.00012860908,0.00036412812,0.06376375,0.00023023202],"about_ca_topic_score_codex":0.000008098647,"about_ca_topic_score_gemma":0.0000031056666,"teacher_disagreement_score":0.06588971,"about_ca_system_score_codex":0.000017506823,"about_ca_system_score_gemma":0.00006676513,"threshold_uncertainty_score":0.9999894},"labels":[],"label_agreement":null},{"id":"W2739790172","doi":"10.1055/b-0034-91424","title":"Diffusion Tensor Imaging","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Research Resources; National Institute of Child Health and Human Development; Michael Smith Health Research BC; U.S. Department of Energy","keywords":"Diffusion MRI; Diffusion; Tensor (intrinsic definition); Physics; Medicine; Mathematics; Geometry; Radiology; Magnetic resonance imaging","score_opus":0.05355543596820343,"score_gpt":0.3266532703954651,"score_spread":0.27309783442726165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2739790172","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000007692455,0.00008912333,0.067825526,0.0034739312,0.000031448173,0.00034482003,0.000005461014,0.00059145933,0.92763054],"genre_scores_gemma":[0.0018845554,0.00022926614,0.018719694,0.0034908163,0.00023736637,0.000016279502,0.00005470567,0.000087544155,0.97527975],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923664,0.0000015841564,0.0001788688,0.00031927423,0.0001406588,0.00012299269],"domain_scores_gemma":[0.9991945,0.000026310829,0.00008324496,0.0005407597,0.000067090754,0.00008811157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029901132,0.0001934256,0.00026325317,0.00008827523,0.000051960316,0.000008285511,0.00007490123,0.00007744757,0.00074852427],"category_scores_gemma":[0.000011153908,0.0001552251,0.000117649965,0.000011094197,0.00006326002,0.00001194228,0.000072695635,0.0002890165,0.00027343992],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016339633,0.00002289667,0.0004873784,0.00007551948,0.000013700539,0.000045529687,0.0000049967975,1.6431382e-7,0.0014649812,0.7925679,0.08945772,0.115842864],"study_design_scores_gemma":[0.0001632449,0.000025354084,0.00017666433,0.0001681101,0.00006677486,0.0001180804,6.192622e-7,0.00020855055,0.00011466927,0.026262702,0.97253424,0.00016096716],"about_ca_topic_score_codex":0.0000025332681,"about_ca_topic_score_gemma":2.6348985e-7,"teacher_disagreement_score":0.88307655,"about_ca_system_score_codex":0.00003182569,"about_ca_system_score_gemma":0.000016036542,"threshold_uncertainty_score":0.81958157},"labels":[],"label_agreement":null},{"id":"W2741653274","doi":"","title":"Effects of mid sagittal plane selection on corpus callosal area","year":2006,"lang":"en","type":"article","venue":"Multiple Sclerosis Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Sagittal plane; Corpus callosum; Selection (genetic algorithm); Medicine; Artificial intelligence; Anatomy; Computer science","score_opus":0.06509693910491117,"score_gpt":0.2850036577089702,"score_spread":0.21990671860405903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2741653274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838821,0.00009445934,0.014669451,0.00044324883,0.00010646201,0.00030916213,0.000010892039,0.00011863941,0.00036552746],"genre_scores_gemma":[0.9904281,0.000091261296,0.008894061,0.0001494898,0.00025498265,0.000018634566,0.00001295768,0.000024990748,0.00012553312],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99909025,0.000025874046,0.00027670932,0.0001657186,0.00024263555,0.00019879563],"domain_scores_gemma":[0.99935853,0.00014528201,0.00018066872,0.00012062996,0.00009904677,0.000095813644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007525903,0.00012858302,0.00021349956,0.00012185686,0.00013425859,0.000017578795,0.00007167294,0.00005705878,0.000017749928],"category_scores_gemma":[0.00008628249,0.000109376255,0.00010757114,0.00016586535,0.000054784232,0.00005640004,0.000015302934,0.00035347164,0.000007209568],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020969173,0.000483841,0.049357556,0.000034195964,0.000015977326,0.000017788027,0.000011935013,0.00018377286,0.9400552,0.00009535621,0.0035299137,0.0060047735],"study_design_scores_gemma":[0.0019120036,0.00044208296,0.38484958,0.00027641671,0.00005238864,0.00035147998,0.0000031877241,0.0007204881,0.60915715,0.00032141712,0.0018107209,0.000103090744],"about_ca_topic_score_codex":0.000048917213,"about_ca_topic_score_gemma":0.0000076222395,"teacher_disagreement_score":0.335492,"about_ca_system_score_codex":0.00007827452,"about_ca_system_score_gemma":0.000032404823,"threshold_uncertainty_score":0.44602343},"labels":[],"label_agreement":null},{"id":"W2742736294","doi":"10.1016/j.cortex.2017.07.021","title":"Processing speed and the relationship between Trail Making Test-B performance, cortical thinning and white matter microstructure in older adults","year":2017,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Montreal Neurological Institute and Hospital","funders":"Biotechnology and Biological Sciences Research Council; Centre for Cognitive Ageing and Cognitive Epidemiology; Medical Research Council; University of Edinburgh; Age UK; Scottish Funding Council","keywords":"White matter; Psychology; Insula; Diffusion MRI; Grey matter; Trail Making Test; Audiology; Superior longitudinal fasciculus; Neuroscience; Fractional anisotropy; Cognition; Magnetic resonance imaging; Medicine","score_opus":0.04840686680783762,"score_gpt":0.34533061655337793,"score_spread":0.2969237497455403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2742736294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99486816,0.00009041849,0.00047641608,0.0032728792,0.000008808582,0.00037030695,0.0000029576838,0.00003979175,0.00087027444],"genre_scores_gemma":[0.99662596,0.000012782799,0.0026637602,0.00043242602,0.000057482703,0.00001252271,0.0000043311516,0.000016094176,0.00017465172],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99940866,0.0000101914675,0.00016486195,0.00021033247,0.00007153054,0.00013441392],"domain_scores_gemma":[0.99942666,0.00014421222,0.000104471554,0.00026214143,0.000026040645,0.000036469246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011158686,0.00009290503,0.00015467501,0.000037467333,0.00041673973,0.0000817816,0.00007998238,0.000050862203,0.0000067403093],"category_scores_gemma":[0.00016358151,0.00006420145,0.000014934296,0.000050077757,0.000306951,0.0001349752,0.00006599397,0.00036847513,0.0000017640818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035698202,0.000006278266,0.9942544,0.00007646386,0.0000011370408,0.0000029213895,0.00048301386,1.4925405e-7,0.00017008914,0.00005469357,0.000041607986,0.0048735095],"study_design_scores_gemma":[0.0012624223,0.000014930387,0.9959946,0.00050710724,0.000031305397,0.00007995696,0.000055952874,0.001352418,0.00003605535,0.0005308347,0.00006097871,0.0000734264],"about_ca_topic_score_codex":0.0000032726543,"about_ca_topic_score_gemma":0.0000016422671,"teacher_disagreement_score":0.004800083,"about_ca_system_score_codex":0.000009767852,"about_ca_system_score_gemma":0.00001398533,"threshold_uncertainty_score":0.32052672},"labels":[],"label_agreement":null},{"id":"W2744387978","doi":"10.1049/htl.2017.0073","title":"Multimodal connectivity based eloquence score computation and visualisation for computer‐aided neurosurgical path planning","year":2017,"lang":"en","type":"article","venue":"Healthcare Technology Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Computer science; Modalities; Artificial intelligence; Heuristics; Neuroimaging; Visualization; Machine learning; Pattern recognition (psychology); Neuroscience","score_opus":0.1292244648341827,"score_gpt":0.42820420481652344,"score_spread":0.29897973998234073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2744387978","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.524676,0.000016091153,0.39109072,0.083152376,0.000044265504,0.0005971283,0.000010764636,0.00041065394,0.0000020001726],"genre_scores_gemma":[0.87692916,0.000006377884,0.11763702,0.0051423064,0.00005870749,0.0001674026,0.00003713713,0.000020988233,8.812588e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897635,0.000027527556,0.00021053737,0.00044624848,0.00009610719,0.00024324445],"domain_scores_gemma":[0.9990485,0.00014381816,0.00022353852,0.00041050927,0.00009498841,0.00007866189],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013604065,0.0001423161,0.00025290667,0.00015642194,0.00057565316,0.000032221757,0.000118808406,0.00013355799,4.4384942e-7],"category_scores_gemma":[0.00014990206,0.00014500991,0.00003961976,0.00007811916,0.00033981333,0.00009201064,0.000058359277,0.00029488662,6.202372e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038208446,0.00020143438,0.7950296,0.0007183973,0.000022757145,0.00018885125,0.00011660826,0.0007877768,0.07843792,0.009916912,0.0012058343,0.11299185],"study_design_scores_gemma":[0.0031835116,0.0007296056,0.58429426,0.0004972761,0.000041065057,0.00027666177,0.000025959354,0.3987947,0.0067171818,0.004037752,0.0010484088,0.00035359873],"about_ca_topic_score_codex":0.00003885452,"about_ca_topic_score_gemma":0.0000017840816,"teacher_disagreement_score":0.39800692,"about_ca_system_score_codex":0.00005649208,"about_ca_system_score_gemma":0.000037646732,"threshold_uncertainty_score":0.5913332},"labels":[],"label_agreement":null},{"id":"W2745760221","doi":"10.1371/journal.pone.0182340","title":"Detailing neuroanatomical development in late childhood and early adolescence using NODDI","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":134,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; University of Calgary","keywords":"White matter; Diffusion MRI; Neurite; Neuroscience; Fractional anisotropy; Grey matter; Brain mapping; Axon; Gray (unit); Biology; Psychology; Magnetic resonance imaging; Medicine; Nuclear medicine; Radiology","score_opus":0.12787531040316102,"score_gpt":0.3233294250417209,"score_spread":0.19545411463855988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2745760221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998311,0.000041606483,0.0006229374,0.00055386155,0.0000039255556,0.00026224868,6.356044e-7,0.00006199389,0.00014178304],"genre_scores_gemma":[0.922001,0.000046610858,0.07774378,0.00012987432,0.000020801897,0.000011434185,6.336147e-7,0.000014481468,0.00003139553],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994058,0.000005699584,0.00013623103,0.00020646192,0.00010652633,0.00013930137],"domain_scores_gemma":[0.9995455,0.0000111763275,0.00006159379,0.00029003693,0.000025199117,0.00006648331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051209572,0.00007410898,0.00015237904,0.00004571632,0.00015215734,0.000027738522,0.000087788285,0.000027179318,0.0000019043745],"category_scores_gemma":[0.00008452302,0.000074438096,0.000011425285,0.00003462935,0.000055352946,0.00007971006,0.00009857156,0.00018630039,0.0000032672128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021045462,0.0007698481,0.8364437,0.0000709067,0.000016673648,0.000044391574,0.00018555003,0.0000025124525,0.15643938,0.0001275655,0.000001193053,0.005877205],"study_design_scores_gemma":[0.00041726974,0.000020814532,0.9326232,0.0005466448,0.000030469837,0.000010747646,0.0000019845288,0.0025170576,0.063423395,0.0002819318,0.000031895026,0.00009460032],"about_ca_topic_score_codex":0.000011700631,"about_ca_topic_score_gemma":0.0000020011878,"teacher_disagreement_score":0.09617946,"about_ca_system_score_codex":0.00002279325,"about_ca_system_score_gemma":0.000031040097,"threshold_uncertainty_score":0.30354974},"labels":[],"label_agreement":null},{"id":"W2747350130","doi":"10.1503/jpn.170137","title":"The neurobiology of transition to psychosis: clearing the cache","year":2017,"lang":"en","type":"letter","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"","keywords":"Psychosis; Endophenotype; Psychology; Neuroscience; Schizophrenia (object-oriented programming); Prodrome; Psychiatry; Cognition","score_opus":0.05652825236951737,"score_gpt":0.35981618978687224,"score_spread":0.3032879374173549,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747350130","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015020174,0.0002670628,0.0019623062,0.98114854,0.0012162948,0.00023794612,0.0000068051036,0.000009711759,0.00013118591],"genre_scores_gemma":[0.14395449,0.0026499804,0.0031064341,0.84691536,0.0028817097,0.000019097812,0.0000010447483,0.00004073549,0.00043116434],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990017,0.0000642076,0.0003551195,0.00020268752,0.0002053653,0.00017096523],"domain_scores_gemma":[0.99869806,0.000105774816,0.0005663862,0.0004879195,0.000087300454,0.00005455407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031949882,0.00012213255,0.00022612928,0.000072616924,0.0004493718,0.000045954304,0.0005472537,0.0000901146,8.7514326e-7],"category_scores_gemma":[0.00009278793,0.0000631523,0.00012659967,0.00011731389,0.00039753213,0.000066918146,0.000042599575,0.0012449794,4.2519545e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018807907,0.00009882053,0.0015624872,0.00013997825,0.000015705215,0.000042699696,0.00012153119,0.000027914903,0.017640568,0.0005460129,0.97549206,0.004124133],"study_design_scores_gemma":[0.00026258355,0.0011364102,0.020022789,0.00033659022,0.00013841137,0.0019525219,0.000023103034,0.000041389085,0.00066744315,0.0023492342,0.9729529,0.00011664012],"about_ca_topic_score_codex":0.0000027603899,"about_ca_topic_score_gemma":0.0000012006909,"teacher_disagreement_score":0.13423318,"about_ca_system_score_codex":0.000005937156,"about_ca_system_score_gemma":0.00007487066,"threshold_uncertainty_score":0.54088855},"labels":[],"label_agreement":null},{"id":"W2748010953","doi":"10.1002/hbm.23768","title":"Changes to white matter microstructure in transient ischemic attack: A longitudinal diffusion tensor imaging study","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Campbell Scientific (Canada); Heart and Stroke Foundation; Sunnybrook Health Science Centre; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Cingulum (brain); Fractional anisotropy; Diffusion MRI; White matter; Corticospinal tract; Superior longitudinal fasciculus; Fasciculus; Medicine; Cardiology; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.08835072668025683,"score_gpt":0.3771940305671938,"score_spread":0.28884330388693696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748010953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9556703,0.000017061615,0.002456866,0.03932792,0.000030810414,0.0011244224,0.000006306729,0.00010839709,0.0012579323],"genre_scores_gemma":[0.99191606,0.0000019701117,0.002759571,0.0038355794,0.00012462618,0.00013178127,0.000010431721,0.000038816044,0.0011811584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987986,0.000018517349,0.00021376694,0.0005065469,0.00014867402,0.00031388545],"domain_scores_gemma":[0.99894226,0.000016516053,0.00010393204,0.0007965698,0.000044324875,0.00009642376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014127025,0.00019227173,0.00026336173,0.0001984008,0.00049530395,0.00008891189,0.00025201263,0.000032637698,0.00008291629],"category_scores_gemma":[0.000032041928,0.0001804258,0.000049434875,0.000096064985,0.00006692756,0.00008136263,0.00016966625,0.00027477014,0.000020179548],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014961994,0.00009392768,0.71792895,0.00003921322,0.0000046275404,0.00005866854,0.0015333779,0.0000021836322,0.26318267,0.0000061153823,0.016662188,0.00047311434],"study_design_scores_gemma":[0.00084022945,0.00005324322,0.97159886,0.00028401962,0.000014599121,0.00005809395,0.00046347416,0.00006302374,0.00020003431,0.000036414076,0.026206974,0.00018104598],"about_ca_topic_score_codex":0.00004112931,"about_ca_topic_score_gemma":0.0001281312,"teacher_disagreement_score":0.26298264,"about_ca_system_score_codex":0.00006145607,"about_ca_system_score_gemma":0.000008518454,"threshold_uncertainty_score":0.7357551},"labels":[],"label_agreement":null},{"id":"W2748088957","doi":"10.3233/jad-170341","title":"White Matter Degradation is Associated with Reduced Financial Capacity in Mild Cognitive Impairment and Alzheimer’s Disease","year":2017,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; McGill University","keywords":"Cognitive impairment; White matter; Disease; Medicine; Psychology; Internal medicine; Magnetic resonance imaging","score_opus":0.09728137444753973,"score_gpt":0.344950787508043,"score_spread":0.24766941306050325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748088957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9876552,0.0010235097,0.00018753037,0.010344619,0.00004020527,0.0005339146,0.00011316155,0.000018781082,0.000083062194],"genre_scores_gemma":[0.9972368,0.00008476931,0.0009080416,0.001580879,0.00008164063,0.000031805608,0.000018876264,0.000024657125,0.000032549488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99889797,0.00003905927,0.00034308745,0.00023157785,0.00028736508,0.00020091853],"domain_scores_gemma":[0.99835503,0.00002936113,0.00056221994,0.00029679586,0.00025060726,0.0005059626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014872818,0.00017605534,0.00029274184,0.00012631975,0.0001918608,0.00005657326,0.0001100354,0.00003798641,0.000052615913],"category_scores_gemma":[0.00014454559,0.00014055229,0.00009990991,0.00007837402,0.0001782779,0.00035111562,0.000046576046,0.0002778545,0.0000037595562],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020128826,0.00084196596,0.99027014,0.000017119495,0.0002419106,0.00037264178,0.00016420324,0.000003119888,0.00008007444,0.00002673945,0.0046766396,0.0012925476],"study_design_scores_gemma":[0.0022335695,0.0001760944,0.99334633,0.0005978157,0.0020244317,0.000027928289,0.000017256918,0.00012375653,0.00060472195,0.00061535364,0.00007715604,0.00015559897],"about_ca_topic_score_codex":0.000011490389,"about_ca_topic_score_gemma":0.000003448816,"teacher_disagreement_score":0.009581564,"about_ca_system_score_codex":0.000037995796,"about_ca_system_score_gemma":0.00022278834,"threshold_uncertainty_score":0.57315564},"labels":[],"label_agreement":null},{"id":"W2748573512","doi":"10.1007/s00247-017-3955-1","title":"Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children","year":2017,"lang":"en","type":"article","venue":"Pediatric Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Cancer Institute; Foundation for the National Institutes of Health","keywords":"Corpus callosum; Diffusion MRI; White matter; Medicine; Neuroradiology; Term (time); Neurology; Radiology; Magnetic resonance imaging; Pathology; Psychiatry; Physics; Astronomy","score_opus":0.0172452671509386,"score_gpt":0.3154845928209104,"score_spread":0.2982393256699718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2748573512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99723035,0.0002794195,0.00016087551,0.0007619696,0.00008271277,0.0013957238,0.0000039267175,0.000020816682,0.00006420286],"genre_scores_gemma":[0.9987982,0.00062376866,0.00008215127,0.00021439436,0.0001416959,0.00007540122,0.0000045052516,0.000016917382,0.00004299486],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919045,0.00008094082,0.00025198943,0.0002323293,0.000103047445,0.00014122181],"domain_scores_gemma":[0.9987726,0.00010190032,0.00034747415,0.0007220018,0.000028521828,0.000027478745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010039449,0.00011237709,0.00028672387,0.00012644459,0.00008121034,0.0000043929167,0.00024381523,0.000042423006,0.0000070324404],"category_scores_gemma":[0.00008464793,0.00007469564,0.00006593751,0.00009776178,0.00009465887,0.000032492982,0.000063444655,0.00017742006,0.0000023348566],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006465352,0.0003828305,0.9935246,0.000022971923,0.000008777201,0.000005577217,0.00009922297,0.0000034008415,0.00097122695,0.000010481454,0.00014003176,0.0047662044],"study_design_scores_gemma":[0.0020061666,0.00025762536,0.9968508,0.000015161463,0.000053363132,0.00004364915,0.0000014568263,0.000028438779,0.0006042208,0.00007480299,0.000004476646,0.000059868875],"about_ca_topic_score_codex":0.000049749928,"about_ca_topic_score_gemma":0.0000018557823,"teacher_disagreement_score":0.0047063357,"about_ca_system_score_codex":0.000025858462,"about_ca_system_score_gemma":0.000020054831,"threshold_uncertainty_score":0.3046},"labels":[],"label_agreement":null},{"id":"W2749066460","doi":"10.1016/j.neulet.2017.08.036","title":"A structural motor network correlates with motor function and not impairment post stroke","year":2017,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Michael Smith Health Research BC; Heart and Stroke Foundation of Canada","keywords":"Motor function; Physical medicine and rehabilitation; Motor impairment; Stroke (engine); Psychology; Neuroscience; Medicine; Physics","score_opus":0.03164887749764121,"score_gpt":0.2926759741412607,"score_spread":0.26102709664361945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749066460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97780454,0.000005871949,0.0035254364,0.01785704,0.00018799055,0.00044128418,0.000014899787,0.00012046925,0.00004245965],"genre_scores_gemma":[0.98095566,0.000009841022,0.0021813898,0.01652186,0.00011306749,0.00003589767,0.0000017533183,0.000014511775,0.00016600387],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99909264,0.0000085016345,0.00009741294,0.00036398822,0.0001906789,0.00024676515],"domain_scores_gemma":[0.9992811,0.000017498345,0.000113575115,0.00045352805,0.000026463036,0.00010784033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046468158,0.00012068052,0.00011588015,0.000036209025,0.0005926308,0.00011059446,0.00015352471,0.000020815845,0.000002921031],"category_scores_gemma":[0.000038990253,0.0000899503,0.000029772467,0.000047063568,0.00032388233,0.0002295972,0.00007599507,0.00018275487,0.0000017106643],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017923948,0.000011462573,0.16264975,0.000008905714,0.0000016464785,0.000022408483,0.000011562537,0.000048678055,0.835617,0.0001418632,0.00027486775,0.0010326123],"study_design_scores_gemma":[0.00046488145,0.0007948121,0.99186695,0.000031211293,0.000029342362,0.00015313098,0.0000055024752,0.003471247,0.0022676934,0.00006299964,0.0007383536,0.00011389618],"about_ca_topic_score_codex":0.000016631064,"about_ca_topic_score_gemma":0.0000010597046,"teacher_disagreement_score":0.8333493,"about_ca_system_score_codex":0.000019687193,"about_ca_system_score_gemma":0.000014800497,"threshold_uncertainty_score":0.4558097},"labels":[],"label_agreement":null},{"id":"W2749107595","doi":"10.3389/fninf.2017.00054","title":"Fiberweb: Diffusion Visualization and Processing in the Browser","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Visualization; Computer science; Diffusion; Computer graphics (images); World Wide Web; Data mining; Physics","score_opus":0.047445804040137055,"score_gpt":0.35520976726546644,"score_spread":0.3077639632253294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749107595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86386305,0.00016643477,0.12376859,0.0040504183,0.00013369128,0.0011399414,0.000003409065,0.00010275484,0.006771703],"genre_scores_gemma":[0.9700455,0.0004802276,0.028200306,0.0011158966,0.00002433353,0.000028973229,0.000008441479,0.000013345993,0.00008293934],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994673,0.000010580972,0.0002024744,0.000085463216,0.00011726663,0.00011691407],"domain_scores_gemma":[0.9994854,0.000011108879,0.00011969951,0.00034307851,0.000016679427,0.000024041761],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011445815,0.000073919626,0.000113458795,0.00008668622,0.0001779658,0.000078768164,0.00014479875,0.00003064507,5.9814715e-7],"category_scores_gemma":[0.000111780515,0.000054136694,0.000013656034,0.000085616986,0.00008153679,0.00029320084,0.000059824964,0.00015870458,6.215474e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008511223,0.0002598721,0.7924907,0.0005546277,0.000002758143,0.000050143175,0.0064055473,0.000050780745,0.00041660803,0.0031101545,0.014311722,0.18226194],"study_design_scores_gemma":[0.0014068333,0.00010722828,0.55354226,0.000344579,0.000024209558,0.00009475073,0.0011208201,0.4056474,0.00024871703,0.005091239,0.032175913,0.00019607677],"about_ca_topic_score_codex":0.0000035883086,"about_ca_topic_score_gemma":0.000002040924,"teacher_disagreement_score":0.4055966,"about_ca_system_score_codex":0.000015796892,"about_ca_system_score_gemma":0.000015293004,"threshold_uncertainty_score":0.22076303},"labels":[],"label_agreement":null},{"id":"W2749609967","doi":"10.1002/nbm.3793","title":"User‐independent diffusion tensor imaging analysis pipelines in a rat model presenting ventriculomegalia: A comparison study","year":2017,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal","funders":"Institute of Human Development, Child and Youth Health; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Tensor (intrinsic definition); Pipeline transport; Computer science; Geology; Magnetic resonance imaging; Mathematics; Chemistry; Medicine; Radiology; Geometry","score_opus":0.07894206902046202,"score_gpt":0.42113731132863275,"score_spread":0.3421952423081707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749609967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98149574,0.00017952597,0.010645163,0.006001028,0.00005546308,0.0012094933,0.000006114589,0.00011623008,0.0002912462],"genre_scores_gemma":[0.9957334,0.00006388608,0.0032110503,0.0001841617,0.00010896962,0.00013863618,0.000035290497,0.000025639145,0.0004990064],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791646,0.00003807167,0.000672209,0.0005732149,0.0004415313,0.00035853314],"domain_scores_gemma":[0.9983588,0.000053381063,0.0003170515,0.0010228341,0.00010044443,0.00014747922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004446981,0.00021942312,0.0006885692,0.0009778067,0.00019111666,0.00004617748,0.00033655012,0.000054150212,0.000018150724],"category_scores_gemma":[0.00032080652,0.0001761986,0.000101620564,0.00086709746,0.000121758574,0.00013998772,0.00026258166,0.00037999896,0.0000036715521],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006306214,0.0012401218,0.989829,0.000031420073,0.000030784722,0.00022318678,0.00035625751,0.0005398394,0.005294892,0.000021576776,0.00036875586,0.002001108],"study_design_scores_gemma":[0.0029766676,0.00007548185,0.6490976,0.00014056242,0.000347288,0.000016138822,0.0005519474,0.34549457,0.00031320294,0.00015908909,0.0006712869,0.00015616236],"about_ca_topic_score_codex":0.000803466,"about_ca_topic_score_gemma":0.0003251655,"teacher_disagreement_score":0.34495473,"about_ca_system_score_codex":0.00013337971,"about_ca_system_score_gemma":0.000037823993,"threshold_uncertainty_score":0.71851707},"labels":[],"label_agreement":null},{"id":"W2749934906","doi":"10.1007/s11682-017-9758-z","title":"Abnormal relationships between local and global brain measures in subjects at clinical high risk for psychosis: a pilot study","year":2017,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Gender and Health","funders":"National Center for Research Resources; National Institute of Mental Health; Harvard University","keywords":"Brain size; White matter; Psychology; Psychosis; Lateral ventricles; Grey matter; Magnetic resonance imaging; Temporal lobe; Amygdala; Neuropsychology; Lateralization of brain function; Neuroscience; Cardiology; Internal medicine; Medicine; Cognition; Radiology; Psychiatry","score_opus":0.197856411745396,"score_gpt":0.4484658028593476,"score_spread":0.25060939111395164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749934906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9821364,0.00013663722,0.008303435,0.007706798,0.000054371656,0.0014060733,0.00008815402,0.00012270898,0.00004541916],"genre_scores_gemma":[0.99380994,0.000040054387,0.0052617174,0.0002616927,0.00011444095,0.0003708151,0.000018057935,0.000024699488,0.000098596305],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985335,0.00012704248,0.00039845143,0.0005318697,0.00015013179,0.00025903626],"domain_scores_gemma":[0.9986366,0.00039847367,0.0001929593,0.0005365484,0.0000558868,0.00017951317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010768148,0.00017614536,0.0003268659,0.00006301271,0.0006777508,0.00007987828,0.00013390287,0.000049263166,0.0000015867674],"category_scores_gemma":[0.0007191855,0.00016369806,0.00004704815,0.000068475674,0.0003435852,0.00014306772,0.00013410999,0.0003659063,0.0000016245084],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013579334,0.00052217185,0.92530936,0.000011512302,0.000008995333,0.00001647949,0.000052137544,1.950219e-7,0.00006484045,0.00008135586,0.0012878855,0.072509274],"study_design_scores_gemma":[0.003628809,0.0007287214,0.99297404,0.000073333744,0.0002679293,0.000051348063,0.000121007266,0.00008339708,0.000033699813,0.0009190756,0.0009518649,0.00016679332],"about_ca_topic_score_codex":0.00052007963,"about_ca_topic_score_gemma":0.00040697376,"teacher_disagreement_score":0.072342485,"about_ca_system_score_codex":0.00005344197,"about_ca_system_score_gemma":0.000026041569,"threshold_uncertainty_score":0.6675413},"labels":[],"label_agreement":null},{"id":"W2750443165","doi":"10.1016/j.nicl.2017.08.020","title":"Emotion detection deficits and changes in personality traits linked to loss of white matter integrity in primary progressive aphasia","year":2017,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Occupational Cancer Research Centre; Toronto Western Hospital; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Deafness and Other Communication Disorders; National Institute on Aging; National Institutes of Health; Larry L. Hillblom Foundation","keywords":"White matter; Uncinate fasciculus; Inferior longitudinal fasciculus; Psychology; Diffusion MRI; Audiology; Inferior frontal gyrus; Frontotemporal lobar degeneration; Neuroscience; Frontotemporal dementia; Medicine; Fractional anisotropy; Cognition; Internal medicine; Dementia; Magnetic resonance imaging; Radiology","score_opus":0.13711604485848117,"score_gpt":0.4352336571927776,"score_spread":0.29811761233429646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750443165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98772734,0.00001961942,0.00102801,0.0099772755,0.000046580066,0.00082178373,0.000013315491,0.000043128664,0.00032296567],"genre_scores_gemma":[0.99446565,0.000055265577,0.0039763576,0.0012907606,0.00007798588,0.00006695123,0.0000045559,0.000019527877,0.000042965275],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99863726,0.000103801765,0.00044423083,0.00049522874,0.00013923272,0.00018027406],"domain_scores_gemma":[0.9990438,0.00011787625,0.0002256263,0.00042762453,0.00008258498,0.00010248102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044916218,0.00013213909,0.00038086888,0.00011218237,0.00008769576,0.00001967716,0.00013618772,0.00012266338,0.0000116828205],"category_scores_gemma":[0.00058740086,0.00012428597,0.00006044625,0.00011253106,0.0002557809,0.00011300987,0.00016960101,0.00067973527,0.000003989178],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033229575,0.00042384485,0.9475143,0.0001223108,0.0000028359839,0.00010823251,0.00017093406,5.478045e-7,0.0088262465,0.000010113052,0.000042713415,0.042445626],"study_design_scores_gemma":[0.0009774051,0.00035634168,0.99711156,0.00019023262,0.00001602104,0.00007316104,0.000012953682,0.0001889561,0.0006038847,0.00019273552,0.00018630829,0.00009045394],"about_ca_topic_score_codex":0.00002432755,"about_ca_topic_score_gemma":0.00007398556,"teacher_disagreement_score":0.049597245,"about_ca_system_score_codex":0.00003188873,"about_ca_system_score_gemma":0.000028190845,"threshold_uncertainty_score":0.5068235},"labels":[],"label_agreement":null},{"id":"W2750953308","doi":"10.1167/17.10.584","title":"Model-based functional segmentation of the human lateral geniculate nucleus","year":2017,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Lateral geniculate nucleus; Neuroscience; Parvocellular cell; Receptive field; Visual cortex; Thalamus; Geniculate; Functional magnetic resonance imaging; Psychology; Computer science; Nucleus","score_opus":0.08630416084600195,"score_gpt":0.40165920521147247,"score_spread":0.3153550443654705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2750953308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9727107,0.000010117903,0.024564812,0.0023692697,0.00005605396,0.00009218584,0.0000022950805,0.000006948224,0.00018758484],"genre_scores_gemma":[0.9871326,0.0000067637593,0.012492638,0.00017801205,0.00005946071,9.602458e-7,0.0000013307981,0.0000068097524,0.000121388446],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995032,0.000008603128,0.00020495598,0.000051385723,0.00018601547,0.000045827233],"domain_scores_gemma":[0.9991399,0.000007673302,0.00044972132,0.00024296842,0.00013011342,0.00002963196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009731055,0.000042678912,0.000092586684,0.000032902022,0.00018596428,0.000013358164,0.00010486901,0.000020722711,0.000014265806],"category_scores_gemma":[0.000019675632,0.000026032916,0.00010505106,0.00002079272,0.000049433267,0.00009937853,0.000027408852,0.00011951316,6.6449707e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068702866,0.000116240124,0.010070796,0.000013567024,0.000009178589,0.000003119105,0.000017014569,0.0026137226,0.9829797,0.0003062569,0.001105952,0.0026957544],"study_design_scores_gemma":[0.0014704675,0.00026563802,0.87377113,0.00022948996,0.00008376765,0.00006749446,0.0000041248645,0.03492663,0.08354731,0.004917758,0.00066304725,0.00005311849],"about_ca_topic_score_codex":0.0000020836276,"about_ca_topic_score_gemma":3.29153e-7,"teacher_disagreement_score":0.89943236,"about_ca_system_score_codex":0.000026523863,"about_ca_system_score_gemma":0.000030881627,"threshold_uncertainty_score":0.14303057},"labels":[],"label_agreement":null},{"id":"W2751461426","doi":"10.1101/184978","title":"Brain white matter structure and language ability in preschool-aged children","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Psychology; Tractography; Lateralization of brain function; Developmental psychology; Corticospinal tract; Cognitive psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.015150891212742457,"score_gpt":0.2788213697264617,"score_spread":0.2636704785137193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751461426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941017,0.0004435155,0.00054168707,0.002669092,0.00008109229,0.0014282371,0.00040184273,0.00032032482,0.000012481619],"genre_scores_gemma":[0.9829401,0.00006770686,0.015680648,0.0008324759,0.00020844847,0.00015368352,0.0000018183204,0.000097826785,0.000017288816],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99803674,0.000069058384,0.0003528114,0.0009918598,0.0001973016,0.00035221214],"domain_scores_gemma":[0.9972472,0.00003502472,0.00027812854,0.0021401418,0.000096778844,0.00020269946],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025059909,0.00040492232,0.0005333376,0.00017461441,0.00012532636,0.00013014888,0.0003633075,0.0003544244,0.00006770899],"category_scores_gemma":[0.00020728211,0.0004048199,0.000079785976,0.00012571858,0.00016972549,0.00011401471,0.00052186043,0.0012765762,0.000010452508],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022198288,0.00005741839,0.78522664,0.00022973011,0.000024179188,0.000028646498,0.000012365341,0.0000038580274,0.21358338,0.000028070821,0.000780277,0.0000032390747],"study_design_scores_gemma":[0.0005349678,0.000018411552,0.97497594,0.0003330397,0.00005515338,1.5400383e-7,7.2018213e-7,0.00005105891,0.023326067,0.000016886623,0.00033986854,0.0003477256],"about_ca_topic_score_codex":0.00007513633,"about_ca_topic_score_gemma":0.000005298393,"teacher_disagreement_score":0.19025731,"about_ca_system_score_codex":0.000118900076,"about_ca_system_score_gemma":0.0001505346,"threshold_uncertainty_score":0.9998404},"labels":[],"label_agreement":null},{"id":"W2752410508","doi":"10.1002/nbm.3778","title":"A review of diffusion MRI of typical white matter development from early childhood to young adulthood","year":2017,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":414,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Calgary","funders":"Canada Research Chairs; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Diffusion imaging; Brain development; Psychology; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.08690828425249522,"score_gpt":0.4145742153961112,"score_spread":0.327665931143616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752410508","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014676419,0.994461,0.0009122622,0.0014763856,0.00007143779,0.0023524591,0.000105274004,0.000038154263,0.0004362774],"genre_scores_gemma":[0.00008812583,0.9753794,0.022546954,0.0009573039,0.0001383455,0.0002695546,0.00040526013,0.00005564257,0.00015940204],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99748415,0.000046125933,0.0013643522,0.00051690463,0.00035599948,0.00023247462],"domain_scores_gemma":[0.997732,0.000060596118,0.0007349884,0.0011460853,0.0001237759,0.00020258845],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022592049,0.00035467133,0.0024650963,0.0003916501,0.000033010998,0.000003523268,0.0004158986,0.00018302971,0.00022145569],"category_scores_gemma":[0.00017912085,0.0002500467,0.00020957465,0.00045540938,0.000115428345,0.000027236814,0.00023158488,0.0004060157,0.000055578694],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022724289,0.0004109458,0.0027683836,0.06342778,0.0000615342,0.000018055798,0.00023423185,4.7494275e-9,0.00002988084,0.000009179744,0.0076510003,0.9253663],"study_design_scores_gemma":[0.00034139282,0.00011115075,0.026249312,0.3226089,0.00031492228,0.00003208274,0.0000030632414,1.6809997e-7,0.000010932353,0.000017355656,0.6501684,0.00014229151],"about_ca_topic_score_codex":0.000035070047,"about_ca_topic_score_gemma":0.0000025361367,"teacher_disagreement_score":0.925224,"about_ca_system_score_codex":0.000098416436,"about_ca_system_score_gemma":0.00027545643,"threshold_uncertainty_score":0.9999952},"labels":[],"label_agreement":null},{"id":"W2753002091","doi":"10.1007/978-3-319-66182-7_71","title":"q-Space Upsampling Using x-q Space Regularization","year":2017,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism","keywords":"Upsampling; Computer science; Interpolation (computer graphics); Regularization (linguistics); Algorithm; Space (punctuation); ENCODE; Diffusion MRI; Graph; Artificial intelligence; Pattern recognition (psychology); Theoretical computer science; Image (mathematics)","score_opus":0.07985640111280169,"score_gpt":0.3800472213559094,"score_spread":0.3001908202431077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753002091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062246583,0.000020772788,0.93232524,0.004950473,0.0001323857,0.00019720006,4.5953269e-7,0.00008724193,0.00003965321],"genre_scores_gemma":[0.5233749,0.000003980122,0.47627637,0.0002470878,0.0000873468,0.0000020998823,4.83703e-7,0.000005601344,0.000002121582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999081,0.0000067625288,0.000104520106,0.00038987192,0.0001979447,0.00021987187],"domain_scores_gemma":[0.99888694,0.00004472154,0.00010210848,0.000815597,0.0000867949,0.000063814296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019039806,0.000092893184,0.00012047828,0.00012255613,0.0005045954,0.00014236257,0.00035758264,0.000037237074,0.0000020025832],"category_scores_gemma":[0.00023110889,0.00008404317,0.000023548966,0.0003104458,0.0003405865,0.00023009875,0.00022018548,0.00016996502,0.0000015970239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003351777,0.00013808634,0.0662775,0.0000769128,0.0000062830004,0.00007259697,0.0008861218,0.37244797,0.32690167,0.01006282,0.000016994509,0.22307955],"study_design_scores_gemma":[0.00018467523,0.000034913875,0.009269853,0.00013151197,0.000005723006,0.000074373864,3.1317848e-7,0.8925055,0.07092636,0.02658918,0.00016390262,0.00011367495],"about_ca_topic_score_codex":0.00002649511,"about_ca_topic_score_gemma":0.0000033008964,"teacher_disagreement_score":0.52005756,"about_ca_system_score_codex":0.000074772746,"about_ca_system_score_gemma":0.00008361402,"threshold_uncertainty_score":0.3880991},"labels":[],"label_agreement":null},{"id":"W2753319834","doi":"10.7759/cureus.1637","title":"Ischemic Stroke of Midbrain and Cerebellum Involving Reticular Activating System&#x0D;","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Abbott (Canada)","funders":"","keywords":"Reticular activating system; Medicine; Midbrain; Midbrain reticular formation; Reticular connective tissue; Cerebellum; Stroke (engine); Neuroscience; Sleep (system call); Reticular formation; Central nervous system; Anatomy; Internal medicine; Psychology","score_opus":0.07133301111960438,"score_gpt":0.35184238681472607,"score_spread":0.2805093756951217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753319834","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98121864,0.0006543953,0.0049996893,0.00082748756,0.00004368985,0.0003129114,0.000010514276,0.00012841802,0.011804263],"genre_scores_gemma":[0.9837824,0.00007666391,0.015645195,0.00004241271,0.00008092883,0.00001699757,0.0000030178655,0.000016443983,0.0003359308],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994812,0.0000072951175,0.0001415341,0.00017366829,0.00008679152,0.00010952802],"domain_scores_gemma":[0.99909514,0.000031974418,0.00017839903,0.0005891873,0.000050318176,0.000054967735],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008298263,0.00007718441,0.00016477848,0.000019287685,0.00016262024,0.000016920481,0.000112137124,0.000042027543,0.000005345494],"category_scores_gemma":[0.00020439037,0.00007054348,0.000032823606,0.00002060685,0.00010547648,0.00008473141,0.00010363568,0.00011703933,9.700145e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001029346,0.000029979386,0.01915669,0.0003033388,0.000019099758,0.000009400652,0.0001082397,3.667445e-7,0.9734287,0.003923499,0.001069863,0.0019405236],"study_design_scores_gemma":[0.001192694,0.00017286839,0.036746845,0.0016218709,0.0001335812,0.0002048525,0.0010013853,0.003809591,0.924803,0.00039201954,0.029602855,0.00031839556],"about_ca_topic_score_codex":0.00004356789,"about_ca_topic_score_gemma":0.000001221497,"teacher_disagreement_score":0.048625663,"about_ca_system_score_codex":0.000027482522,"about_ca_system_score_gemma":0.000015902828,"threshold_uncertainty_score":0.28766796},"labels":[],"label_agreement":null},{"id":"W2753663815","doi":"10.1523/eneuro.0164-17.2017","title":"Defining an Analytic Framework to Evaluate Quantitative MRI Markers of Traumatic Axonal Injury: Preliminary Results in a Mouse Closed Head Injury Model","year":2017,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; Center for Neuroscience and Regenerative Medicine; National Institutes of Health; W. Garfield Weston Foundation; Weston Brain Institute","keywords":"Diffusion MRI; Gliosis; Fractional anisotropy; Diffuse axonal injury; Magnetic resonance imaging; Traumatic brain injury; Pathology; White matter; Histology; Neuroscience; Medicine; Radiology; Biology","score_opus":0.13491145599568424,"score_gpt":0.45354494014850644,"score_spread":0.3186334841528222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753663815","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9771846,0.00001901968,0.018018657,0.0029705924,0.000026772632,0.0007260779,0.00014631964,0.00010284675,0.0008051383],"genre_scores_gemma":[0.8356358,0.000026458238,0.16349097,0.0005614801,0.000012600785,0.000090378024,0.000016987178,0.00003708303,0.00012827454],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984265,0.00008154445,0.000478275,0.00047750314,0.00028189737,0.00025429454],"domain_scores_gemma":[0.9980783,0.0002259166,0.0002688369,0.0011820956,0.00009163953,0.000153241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004216195,0.0001841715,0.0003700177,0.0002284129,0.00012991243,0.000024185114,0.0003161651,0.00007197041,0.000005038179],"category_scores_gemma":[0.0014537582,0.00018174476,0.00007480276,0.00019311064,0.00011683366,0.00016680168,0.00011895591,0.00037458865,0.000008517093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.17185086,0.009292924,0.04191939,0.0018010935,0.000450711,0.0005481072,0.022117114,0.11940848,0.32170108,0.13058853,0.01689744,0.16342427],"study_design_scores_gemma":[0.002862774,0.011251269,0.15059094,0.0017025414,0.00021830067,0.00002350436,0.00033912415,0.768191,0.03430032,0.029489206,0.00030356215,0.000727499],"about_ca_topic_score_codex":0.0000459832,"about_ca_topic_score_gemma":0.000013214219,"teacher_disagreement_score":0.6487825,"about_ca_system_score_codex":0.00004743608,"about_ca_system_score_gemma":0.00009656903,"threshold_uncertainty_score":0.74113363},"labels":[],"label_agreement":null},{"id":"W2753814260","doi":"10.1007/978-3-319-67159-8_5","title":"Interactive Computation and Visualization of Structural Connectomes in Real-Time","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Medical Research Council","keywords":"Visualization; Computer science; Graph drawing; Connectome; GRASP; Connectomics; Computation; Theoretical computer science; Graph; Node (physics); Enhanced Data Rates for GSM Evolution; On the fly; Graph theory; Perspective (graphical); Artificial intelligence; Algorithm; Functional connectivity; Mathematics; Engineering","score_opus":0.03936564957441193,"score_gpt":0.37807853417676957,"score_spread":0.33871288460235766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753814260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015453178,0.00006142747,0.981709,0.00026122888,0.00008856608,0.00053252635,0.0000070733463,0.000060336362,0.0018266551],"genre_scores_gemma":[0.91813016,0.00006395661,0.08151284,0.000108326814,0.00005570604,0.0000042880733,0.000020248921,0.000017687069,0.00008681361],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999011,0.000008610537,0.00023962725,0.00042626204,0.00019139514,0.00012311217],"domain_scores_gemma":[0.9991126,0.00018849516,0.00024518764,0.00027995708,0.00013491153,0.0000388137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000117912976,0.00015807069,0.00031959088,0.0003788831,0.00006235861,0.000034085802,0.00016718563,0.00008545485,0.000006411973],"category_scores_gemma":[0.000076504664,0.00014295483,0.000026066713,0.000081870174,0.00046540142,0.00014272862,0.00014781422,0.00020876195,9.256647e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017557196,0.00006229009,0.010986157,0.0003780746,0.00002587165,0.00009388081,0.0028629955,0.010236109,0.023006886,0.019365571,0.00002264395,0.93278396],"study_design_scores_gemma":[0.0009151061,0.00041650064,0.026984412,0.001967358,0.000030980063,0.00016320703,7.022095e-7,0.6935934,0.00982803,0.2655351,0.000115696086,0.0004495578],"about_ca_topic_score_codex":0.00002995828,"about_ca_topic_score_gemma":0.000012828688,"teacher_disagreement_score":0.93233436,"about_ca_system_score_codex":0.00008600462,"about_ca_system_score_gemma":0.00008573214,"threshold_uncertainty_score":0.58295286},"labels":[],"label_agreement":null},{"id":"W2754530470","doi":"10.1017/cjn.2017.221","title":"Corpus Callosum Impingement Syndrome: A Callosal or Colossal Problem?","year":2017,"lang":"fr","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Content (measure theory); Computer science; Medicine; Psychology; Neuroscience; Mathematics","score_opus":0.10535488708823874,"score_gpt":0.35991612036807624,"score_spread":0.2545612332798375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754530470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9243923,0.0053965272,0.0002530392,0.06106948,0.0036589094,0.0006357197,0.00007225604,0.000046051933,0.0044757244],"genre_scores_gemma":[0.97473294,0.0035550618,0.01436831,0.0052829445,0.0010086879,0.000016391099,6.493121e-7,0.00004039015,0.0009946005],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.9920952,0.0008755029,0.0016840477,0.0010561753,0.0012853863,0.0030037086],"domain_scores_gemma":[0.99077827,0.0007216503,0.0024910101,0.00061118393,0.0008785621,0.0045193373],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":["sts"],"category_scores_codex":[0.005502083,0.0006925339,0.0011247759,0.00095375435,0.010299333,0.002357966,0.005041879,0.0004369194,0.0005457685],"category_scores_gemma":[0.0048503284,0.00047627685,0.00047657022,0.0009766809,0.02481379,0.0019564661,0.00033822053,0.0029813342,0.000019759082],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003462722,0.00022103763,0.86413866,0.000082766725,0.000072243114,0.09918129,0.0002715206,0.0009986165,0.00010164136,0.008403449,0.0075652306,0.0186173],"study_design_scores_gemma":[0.0013391508,0.18133053,0.29773873,0.00085426774,0.00039055667,0.35557178,0.00022779372,0.0023639137,0.00015745305,0.04800393,0.111025885,0.0009959927],"about_ca_topic_score_codex":0.00449479,"about_ca_topic_score_gemma":0.06578631,"teacher_disagreement_score":0.56639993,"about_ca_system_score_codex":0.0008065049,"about_ca_system_score_gemma":0.010694087,"threshold_uncertainty_score":0.9997689},"labels":[],"label_agreement":null},{"id":"W2755098915","doi":"10.1007/978-3-319-67675-3_9","title":"White Matter Fiber Segmentation Using Functional Varifolds","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Fiber; Computer science; Artificial intelligence; Materials science; Composite material","score_opus":0.06946542090999351,"score_gpt":0.33812976724214705,"score_spread":0.2686643463321535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755098915","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002160519,0.00003951626,0.989189,0.0011305091,0.00025979785,0.00035992893,0.000007086211,0.00007413191,0.008723945],"genre_scores_gemma":[0.046432726,0.000019446674,0.9343859,0.0045216195,0.0008929546,0.000021018725,0.00004889154,0.00007198918,0.013605435],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99855655,0.0000046942628,0.0002121175,0.000634762,0.00037025474,0.00022161427],"domain_scores_gemma":[0.9988498,0.00004722313,0.00018473766,0.0007175547,0.00012689985,0.00007380185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013141465,0.00022678338,0.00023608946,0.00026123857,0.00024804854,0.00010026819,0.00027567506,0.00013388666,0.0004233635],"category_scores_gemma":[0.000011334827,0.00020623629,0.00006760027,0.000065702596,0.00037526852,0.00016760865,0.0002016724,0.0004182902,0.00007441261],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015635153,0.00022125695,0.039154742,0.00047011208,0.00008890397,0.00035805782,0.0007548217,0.07072322,0.011576799,0.005338048,0.0038290855,0.8673286],"study_design_scores_gemma":[0.0026779256,0.00062369055,0.07833787,0.0041703884,0.0004322427,0.0031108565,5.385511e-7,0.36640105,0.011552204,0.45869562,0.07071389,0.0032837107],"about_ca_topic_score_codex":0.0000057632533,"about_ca_topic_score_gemma":0.0000020444465,"teacher_disagreement_score":0.8640449,"about_ca_system_score_codex":0.00018230085,"about_ca_system_score_gemma":0.00016887202,"threshold_uncertainty_score":0.84100723},"labels":[],"label_agreement":null},{"id":"W2755475577","doi":"10.1016/j.neuroimage.2017.09.019","title":"A comparison of inhomogeneous magnetization transfer, myelin volume fraction, and diffusion tensor imaging measures in healthy children","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arkansas Children’s Hospital Research Institute; University of Calgary","keywords":"Magnetization transfer; Diffusion MRI; Nuclear magnetic resonance; Tensor (intrinsic definition); Diffusion; Magnetization; Physics; Volume fraction; Myelin; Condensed matter physics; Materials science; Medicine; Psychology; Mathematics; Magnetic resonance imaging; Neuroscience; Radiology; Magnetic field; Thermodynamics; Quantum mechanics; Geometry","score_opus":0.05793730415032883,"score_gpt":0.3752019245705948,"score_spread":0.317264620420266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755475577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9769701,0.00032976948,0.01794375,0.0037014836,0.000030172208,0.0006200014,0.000016172138,0.000098707664,0.00028984254],"genre_scores_gemma":[0.9963287,0.00048634023,0.0026602068,0.00035423477,0.000046186004,0.000024503915,0.00001815046,0.000030277117,0.00005138052],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989333,0.000035644003,0.00033715446,0.00034585086,0.00017755662,0.00017044968],"domain_scores_gemma":[0.9991646,0.000025011776,0.0001287018,0.00051573064,0.00008566778,0.00008027722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009559462,0.00013338834,0.00029762698,0.00012598876,0.00021352952,0.000032920147,0.00011961644,0.00004052894,0.000012485479],"category_scores_gemma":[0.00014835314,0.00013283633,0.000040484614,0.00008113535,0.0001474703,0.00013373696,0.000049018316,0.00024792837,0.000002456014],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014192685,0.00020893599,0.8950875,0.00003560768,0.0000019427002,0.000009644253,0.0000621526,0.000008102771,0.06076871,0.000035161498,0.00016847446,0.04347187],"study_design_scores_gemma":[0.0010008125,0.00020890846,0.98744065,0.000057268026,0.000028451444,0.000083286955,0.000013381196,0.005642656,0.0038594387,0.00014928197,0.0014151527,0.00010068753],"about_ca_topic_score_codex":0.0001731976,"about_ca_topic_score_gemma":0.000020142961,"teacher_disagreement_score":0.0923532,"about_ca_system_score_codex":0.000021238742,"about_ca_system_score_gemma":0.000025004865,"threshold_uncertainty_score":0.5416908},"labels":[],"label_agreement":null},{"id":"W2755700757","doi":"10.1007/978-3-319-73839-0_17","title":"Multi-Modal Analysis of Genetically-Related Subjects Using SIFT Descriptors in Brain MRI","year":2018,"lang":"en","type":"preprint","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Human Connectome Project; Scale-invariant feature transform; Similarity measure; Artificial intelligence; Computer science; Similarity (geometry); Diffusion MRI; Pattern recognition (psychology); Modality (human–computer interaction); Connectome; Modal; Measure (data warehouse); Modalities; Data mining; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Feature extraction; Radiology; Functional connectivity; Image (mathematics)","score_opus":0.1152558743178228,"score_gpt":0.4248246109812118,"score_spread":0.309568736663389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2755700757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48690757,0.000061903236,0.51247585,0.000052930976,0.000016748541,0.00039264828,0.000012289706,0.000042095176,0.000037987036],"genre_scores_gemma":[0.7203341,0.00018350387,0.27911884,0.00006645896,0.000016655551,0.000024555504,0.00017509349,0.000040420986,0.000040384883],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998789,0.000033130385,0.00057074253,0.00031803918,0.00016074895,0.0001283146],"domain_scores_gemma":[0.99905646,0.00006674734,0.00032002793,0.00035301695,0.00014735929,0.000056382465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027839153,0.00017270992,0.0005249907,0.00053746375,0.000034346365,0.000019557541,0.00007278383,0.0001865118,0.000020888823],"category_scores_gemma":[0.0001773336,0.00016626678,0.000096433134,0.0006787563,0.00009995672,0.000021852227,0.00016159461,0.00014378008,4.9683825e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019510875,0.010658807,0.27953467,0.016707242,0.0049532116,0.000059688595,0.025550423,0.037198626,0.51111174,0.108036496,0.00076874375,0.0052252393],"study_design_scores_gemma":[0.00029570336,0.000044092416,0.00756998,0.00047350797,0.0008834346,0.0000040328705,0.000047283196,0.9829636,0.0029940864,0.0045510954,0.000026557298,0.00014662759],"about_ca_topic_score_codex":0.000032437285,"about_ca_topic_score_gemma":0.000011065238,"teacher_disagreement_score":0.94576496,"about_ca_system_score_codex":0.000045703277,"about_ca_system_score_gemma":0.000045057484,"threshold_uncertainty_score":0.67801625},"labels":[],"label_agreement":null},{"id":"W2756068656","doi":"10.1117/1.jmi.4.3.036001","title":"Ex vivo tissue imaging for radiology–pathology correlation: a pilot study with a small bore 7-T MRI in a rare pigmented ganglioglioma exhibiting complex MR signal characteristics associated with melanin and hemosiderin","year":2017,"lang":"en","type":"article","venue":"Journal of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Manitoba Medical Service Foundation","keywords":"Hemosiderin; Medicine; Ex vivo; Magnetic resonance imaging; Pathology; Diffusion MRI; In vivo; Melanin; Radiology; Biology","score_opus":0.07248924691438242,"score_gpt":0.35460723132288585,"score_spread":0.28211798440850344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756068656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7446953,0.00012430453,0.2376088,0.016521556,0.00004846361,0.00086508255,0.000015862388,0.00005669165,0.00006389376],"genre_scores_gemma":[0.9824569,0.000035744626,0.01646212,0.00075312454,0.00017163609,0.00003984481,0.000017309796,0.000045226596,0.000018090284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981353,0.0001034641,0.00065722177,0.00031823886,0.00043722047,0.0003485152],"domain_scores_gemma":[0.9978711,0.00033677815,0.0009654569,0.0002604992,0.00032062212,0.00024553778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010094404,0.00022633527,0.0006576057,0.00024675264,0.00027894165,0.00008215413,0.0002560746,0.00004501097,0.000029196926],"category_scores_gemma":[0.00078824704,0.00017182805,0.00003519416,0.00014318574,0.0003554629,0.00018461263,0.00010882153,0.00067353883,2.5585177e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017007063,0.0013712146,0.93849015,0.000102385464,0.00011605885,0.01457855,0.00075772224,0.000011614933,0.017797783,0.0000875643,0.0012341115,0.023752108],"study_design_scores_gemma":[0.03207563,0.0065964954,0.8144746,0.0047883694,0.00072044274,0.040155146,0.0029087698,0.094316624,0.0013173159,0.0005139825,0.0013836714,0.00074898114],"about_ca_topic_score_codex":0.000027030115,"about_ca_topic_score_gemma":0.000040129882,"teacher_disagreement_score":0.23776157,"about_ca_system_score_codex":0.00009138705,"about_ca_system_score_gemma":0.00014838857,"threshold_uncertainty_score":0.7006945},"labels":[],"label_agreement":null},{"id":"W2756259711","doi":"10.1016/j.neuroscience.2017.09.011","title":"Pathways of the inferior frontal occipital fasciculus in overt speech and reading","year":2017,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Uncinate fasciculus; Psychology; Inferior longitudinal fasciculus; Diffusion MRI; Rapid automatized naming; Reading (process); Fractional anisotropy; Superior longitudinal fasciculus; Fasciculus; White matter; Context (archaeology); Tractography; Corticospinal tract; Cognitive psychology; Neuroscience; Phonological awareness; Linguistics; Magnetic resonance imaging; Medicine","score_opus":0.07105586257299687,"score_gpt":0.34937235447152787,"score_spread":0.278316491898531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756259711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965776,0.000006853341,0.0002860592,0.0008568714,0.000078221754,0.00018861944,0.000006102853,0.000021249996,0.0019783725],"genre_scores_gemma":[0.998555,0.000023256562,0.0009288013,0.0003440271,0.000011963006,0.000006460689,9.764208e-8,0.000004615639,0.0001257855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948484,0.0000062764407,0.00009297409,0.00018875072,0.000121406854,0.0001057361],"domain_scores_gemma":[0.9994161,0.000013248211,0.00007621567,0.00044609315,0.000013736099,0.000034586545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006281559,0.00005142078,0.000086548374,0.000024266157,0.00016676591,0.00002331065,0.00021241892,0.00001567295,0.000001562333],"category_scores_gemma":[0.00026684813,0.000035831123,0.000020834399,0.00006810364,0.00030633959,0.00012002329,0.00019480789,0.00011099455,5.64183e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000056137233,0.00003396214,0.5322178,0.0000079891015,1.2836995e-7,0.000013650166,0.000048394344,8.796103e-7,0.4614232,0.0011241315,0.00004343031,0.0050808396],"study_design_scores_gemma":[0.00015034273,0.000042303764,0.96232194,0.000038028913,0.00000244229,0.00006576629,0.0000080355785,0.00063857296,0.035430655,0.0005112429,0.0007558333,0.000034822075],"about_ca_topic_score_codex":0.000030896175,"about_ca_topic_score_gemma":0.00000585686,"teacher_disagreement_score":0.43010417,"about_ca_system_score_codex":0.00001150227,"about_ca_system_score_gemma":0.00002600616,"threshold_uncertainty_score":0.14611508},"labels":[],"label_agreement":null},{"id":"W2756436797","doi":"10.1002/hbm.23799","title":"A pediatric structural MRI analysis of healthy brain development from newborns to young adults","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Canada Foundation for Innovation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"White matter; Magnetic resonance imaging; Brain development; Brain morphometry; Neuroimaging; Hum; Medicine; Brain size; Pathological; Neuroscience; Psychology; Pathology; Radiology","score_opus":0.07595107030098333,"score_gpt":0.38110838037630673,"score_spread":0.30515731007532343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2756436797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94667614,0.000033086235,0.043607444,0.008580223,0.000039978837,0.0004937641,0.000029072764,0.00012572427,0.0004145533],"genre_scores_gemma":[0.9288938,0.000006164685,0.06864708,0.0018632673,0.00021435088,0.000048778707,0.00010728593,0.000021152067,0.00019808393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986799,0.000021361897,0.00040912084,0.00042198776,0.00021556039,0.00025206854],"domain_scores_gemma":[0.9984987,0.00008585668,0.00030832106,0.0008518627,0.00008967304,0.00016562601],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015779868,0.00015343419,0.0003888381,0.00040164162,0.0005754235,0.000037888123,0.0002987619,0.00004657164,0.00006014159],"category_scores_gemma":[0.00018969899,0.00015302977,0.00011155832,0.0003584704,0.00004370474,0.00007448397,0.00016240253,0.00015609618,0.000006405418],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013263774,0.000119314325,0.9266881,0.00021079314,0.00047775955,0.000024637382,0.0071840524,0.0001372643,0.037751615,0.0024273752,0.013333395,0.011513062],"study_design_scores_gemma":[0.0004659328,0.000047575802,0.99080366,0.00006289967,0.00013028865,0.0000020001214,0.00009639371,0.0006719283,0.00011617427,0.0005107076,0.0069435206,0.00014889475],"about_ca_topic_score_codex":0.00036436378,"about_ca_topic_score_gemma":0.00025508337,"teacher_disagreement_score":0.06411559,"about_ca_system_score_codex":0.00007464229,"about_ca_system_score_gemma":0.000059605907,"threshold_uncertainty_score":0.6240373},"labels":[],"label_agreement":null},{"id":"W2757204155","doi":"10.1007/978-3-319-73839-0_15","title":"Fiber-Flux Diffusion Density for White Matter Tracts Analysis: Application to Mild Anomalies Localization in Contact Sports Players","year":2018,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fiber bundle; Diffusion MRI; Fiber; Diffusion; Anisotropy; Mathematics; Physics; Optics; Materials science","score_opus":0.03743149619188727,"score_gpt":0.34174117214212896,"score_spread":0.30430967595024166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2757204155","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01068872,0.000030698004,0.98012507,0.0002629008,0.000019237368,0.0024804133,0.000060167444,0.00011449185,0.0062182737],"genre_scores_gemma":[0.6828309,0.0005098025,0.11408068,0.004664234,0.00051998155,0.0012197758,0.00930094,0.0005726018,0.18630105],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99854255,0.0000057920297,0.0005665404,0.000483955,0.00023718468,0.00016397872],"domain_scores_gemma":[0.99886215,0.000047430323,0.00036842393,0.0003973167,0.00022219193,0.000102484315],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016491079,0.00028688117,0.00054845086,0.00050659187,0.00010352422,0.00004075236,0.00006372166,0.00022339445,0.00019721249],"category_scores_gemma":[0.00002339024,0.00027988816,0.00010753622,0.00020788066,0.00003711207,0.00006654337,0.00004605738,0.000088709065,0.000019794712],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019187611,0.0035147462,0.108153544,0.013612256,0.0015973945,0.000042401814,0.0150083285,0.0025853505,0.0062763146,0.7646538,0.06566441,0.016972704],"study_design_scores_gemma":[0.0033727863,0.0011916255,0.07144321,0.0044980873,0.006907145,0.000078091885,0.0003242855,0.58396655,0.0034616487,0.09538692,0.22658576,0.0027838598],"about_ca_topic_score_codex":0.000004454583,"about_ca_topic_score_gemma":0.000021402031,"teacher_disagreement_score":0.8660444,"about_ca_system_score_codex":0.00008081505,"about_ca_system_score_gemma":0.00002125684,"threshold_uncertainty_score":0.9999653},"labels":[],"label_agreement":null},{"id":"W2758054168","doi":"10.7759/cureus.1722","title":"Tractography for Optic Radiation Preservation in Transcortical Approaches to Intracerebral Lesions","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Tractography; Optic radiation; Neuroscience; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.4468942478928639,"score_gpt":0.41873300207780717,"score_spread":0.028161245815056746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758054168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6954513,0.00008300552,0.2792812,0.022180503,0.00004978219,0.0018825837,0.000014360193,0.00011836712,0.0009388676],"genre_scores_gemma":[0.9319916,0.000024721714,0.067201525,0.00014258854,0.00007799077,0.0004714214,0.000022987555,0.000014376489,0.000052804353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99942917,0.0000061826127,0.00015211126,0.00019982512,0.000070489055,0.0001422209],"domain_scores_gemma":[0.9994042,0.000038619513,0.000046964153,0.00040773582,0.000020849764,0.000081620514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007851062,0.000071763076,0.0001169463,0.0000564758,0.00013008382,0.000029084387,0.00012355122,0.000048384467,0.0000060335888],"category_scores_gemma":[0.00017413936,0.00006769171,0.000056539167,0.000066427216,0.000036649395,0.00020398517,0.0000145411,0.00009660693,0.000001895336],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085275166,0.00275408,0.19808699,0.0004406453,0.000082462895,0.00001814802,0.0021158783,0.0005170955,0.04997083,0.404514,0.0041994187,0.3364477],"study_design_scores_gemma":[0.001432724,0.00038895608,0.9441476,0.000098121,0.000077114775,0.000012490187,0.00006402002,0.014971351,0.009604369,0.016460832,0.012529099,0.0002133542],"about_ca_topic_score_codex":0.000021656619,"about_ca_topic_score_gemma":0.000024063416,"teacher_disagreement_score":0.74606055,"about_ca_system_score_codex":0.000026673479,"about_ca_system_score_gemma":0.000019769039,"threshold_uncertainty_score":0.2760388},"labels":[],"label_agreement":null},{"id":"W2758085132","doi":"","title":"Studying white matter tractography reproducibility through connectivity matrices","year":2015,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; Reproducibility; White matter; Computer science; Grey matter; Connectome; Artificial intelligence; Pattern recognition (psychology); Functional connectivity; Neuroscience; Magnetic resonance imaging; Mathematics; Psychology; Medicine; Radiology; Statistics","score_opus":0.07567469515517751,"score_gpt":0.3302137052561688,"score_spread":0.2545390101009913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758085132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36948717,0.0023081882,0.39890543,0.071985446,0.00023547234,0.0027442814,0.00018138712,0.0015298559,0.15262279],"genre_scores_gemma":[0.8496409,0.000493639,0.14641389,0.00044392492,0.000048234633,0.00026673617,0.00032310965,0.000075630385,0.002293931],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99455225,0.0020313207,0.0006162459,0.0019893348,0.0004562748,0.00035457796],"domain_scores_gemma":[0.98996216,0.0005830164,0.00060260773,0.006281536,0.002371944,0.00019876116],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0062057115,0.00039637083,0.00060150813,0.0001766519,0.0003191521,0.00018939734,0.00071063713,0.0002471241,0.00013532021],"category_scores_gemma":[0.0015869905,0.0003989038,0.0003069814,0.0005701881,0.00030027836,0.00018563391,0.0012272864,0.001184263,0.00004323493],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019099507,0.0077721723,0.8653353,0.0022382298,0.0004391107,0.00004838143,0.022265704,0.00013656255,0.00412433,0.024897961,0.035596214,0.036955032],"study_design_scores_gemma":[0.0036615161,0.000006148773,0.5611377,0.009983421,0.0011459261,0.00037639673,0.000946492,0.0060349707,0.09290851,0.14539444,0.1752924,0.003112123],"about_ca_topic_score_codex":0.0005281344,"about_ca_topic_score_gemma":0.0001000574,"teacher_disagreement_score":0.48015374,"about_ca_system_score_codex":0.00014392231,"about_ca_system_score_gemma":0.00019761844,"threshold_uncertainty_score":0.9998463},"labels":[],"label_agreement":null},{"id":"W2758113150","doi":"10.1002/nbm.3785","title":"Diffusion MRI fiber tractography of the brain","year":2017,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":600,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Fonds Wetenschappelijk Onderzoek; McDonnell Center for Systems Neuroscience; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Tractography; Connectomics; Diffusion MRI; White matter; Neuroscience; Computer science; Fiber tract; Human Connectome Project; Tracking (education); Data science; Artificial intelligence; Psychology; Connectome; Medicine; Magnetic resonance imaging; Functional connectivity; Radiology","score_opus":0.17918645848264028,"score_gpt":0.4685740191986128,"score_spread":0.2893875607159725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758113150","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000013823397,0.9905611,0.00010326127,0.0041234856,0.000096616786,0.0015909114,0.000049804115,0.000059126574,0.0034018387],"genre_scores_gemma":[0.000047432335,0.9961851,0.0010319893,0.00034967437,0.00018029053,0.00012711926,0.00008281666,0.000045432822,0.0019501373],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99850804,0.00004754275,0.00061682373,0.0003503425,0.00028139076,0.0001958359],"domain_scores_gemma":[0.99771625,0.00017132242,0.00056994124,0.0014071013,0.000042802985,0.00009258736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024085636,0.00026805664,0.0012992902,0.0003844233,0.00006844173,0.0000047139233,0.00045754717,0.00021290516,0.000094836476],"category_scores_gemma":[0.00021681059,0.00014407739,0.00040936877,0.0006185354,0.00042501083,0.000023530947,0.00013814696,0.0005742401,0.000008974896],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046515233,0.00013582388,0.00008541516,0.0046932735,0.000019239787,0.000011286932,0.000015284464,1.4027907e-8,0.00004871684,0.00007814753,0.009209783,0.98569834],"study_design_scores_gemma":[0.0003686967,0.00007442694,0.00059107016,0.02234555,0.00028283746,0.00008893327,0.000002439804,0.0000021077392,0.000008816829,0.00018587212,0.9759392,0.00011000632],"about_ca_topic_score_codex":0.000028169274,"about_ca_topic_score_gemma":0.0000023355126,"teacher_disagreement_score":0.9855884,"about_ca_system_score_codex":0.000048910562,"about_ca_system_score_gemma":0.00013563703,"threshold_uncertainty_score":0.58753055},"labels":[],"label_agreement":null},{"id":"W2758471796","doi":"10.1161/str.47.suppl_1.tp373","title":"Abstract TP373: Tracts Enfolded by Small Hematomas Remain Intact in Acute Intracerebral Hemorrhage","year":2016,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Basal ganglia; Hematoma; Intracerebral hemorrhage; White matter; Corticospinal tract; Tractography; Diffusion MRI; Magnetic resonance imaging; Pyramidal tracts; Lesion; Nuclear medicine; Surgery; Radiology; Anatomy; Glasgow Coma Scale; Internal medicine; Central nervous system","score_opus":0.0342844207898849,"score_gpt":0.31662762216759693,"score_spread":0.282343201377712,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2758471796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9788247,0.00007137456,0.0081644915,0.006177354,0.000048496182,0.00056682236,0.00013125538,0.00035632876,0.0056592175],"genre_scores_gemma":[0.9777179,0.000088233755,0.01878747,0.00055676524,0.00006962113,0.000081484985,0.000027262407,0.00004290839,0.0026283502],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987386,0.000015165501,0.00033527167,0.00037918004,0.00015816618,0.00037362883],"domain_scores_gemma":[0.99910843,0.00009941277,0.000110836074,0.00048599293,0.000032347918,0.0001629495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012667898,0.00019636384,0.00028920968,0.00010877029,0.000041580704,0.000014757594,0.0001563288,0.00009677871,0.00015922092],"category_scores_gemma":[0.00007516402,0.00014367128,0.000089494315,0.00014213953,0.00006662891,0.00013012653,0.00004740124,0.00028265573,0.000070891285],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012259714,0.00027763264,0.007524984,0.00004753149,0.000022139548,0.00027480646,0.00004623309,2.3408309e-7,0.9499809,0.001457073,0.005113808,0.03513205],"study_design_scores_gemma":[0.00514206,0.00039991495,0.0889704,0.00050155155,0.00011633065,0.00063579273,0.00008142012,0.000101331585,0.85852957,0.0042040534,0.04061504,0.00070255954],"about_ca_topic_score_codex":0.000022023232,"about_ca_topic_score_gemma":0.000014807,"teacher_disagreement_score":0.09145136,"about_ca_system_score_codex":0.00010973125,"about_ca_system_score_gemma":0.00004703337,"threshold_uncertainty_score":0.58587444},"labels":[],"label_agreement":null},{"id":"W2759664261","doi":"10.1002/hbm.23831","title":"Altered white matter structure in the visual system following early monocular enucleation","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Enucleation; Lateral geniculate nucleus; Fractional anisotropy; White matter; Monocular; Diffusion MRI; Visual cortex; Optic tract; Psychology; Visual system; Tractography; Eye Enucleation; Anatomy; Optic radiation; Neuroscience; Ophthalmology; Optic nerve; Biology; Magnetic resonance imaging; Medicine; Optics; Surgery; Physics","score_opus":0.06478154638342154,"score_gpt":0.36307098968075013,"score_spread":0.2982894432973286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2759664261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9830775,0.0000133657,0.00848468,0.0053844806,0.00004277352,0.0005400426,0.0000023840332,0.00010722182,0.0023475394],"genre_scores_gemma":[0.99586874,4.095469e-7,0.002421133,0.0012353027,0.00019205103,0.00004102569,0.000014488364,0.000023835775,0.00020302743],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99922144,0.000041072406,0.00018697535,0.00023299869,0.00014642965,0.00017107],"domain_scores_gemma":[0.9991536,0.000023651704,0.00012446394,0.00065153325,0.000017899798,0.000028818045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017830473,0.000109228946,0.0001614243,0.000078052755,0.000586635,0.00014492925,0.0002463758,0.00004569387,0.00001533723],"category_scores_gemma":[0.000027040189,0.000087340755,0.00007246478,0.000056431836,0.000036641246,0.00014381151,0.000057639172,0.0002183239,0.000013402335],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017975017,0.000059588427,0.6333557,0.0002777982,0.000041212705,0.00013230578,0.0042623477,0.000017518392,0.34692514,0.007698196,0.005433552,0.0017786929],"study_design_scores_gemma":[0.00043466553,0.000024907622,0.9932937,0.00029154163,0.000015805284,0.000027407927,0.00030854536,0.00070494134,0.00011506065,0.0011264536,0.0035566182,0.000100346864],"about_ca_topic_score_codex":0.000028431981,"about_ca_topic_score_gemma":0.000004672359,"teacher_disagreement_score":0.35993806,"about_ca_system_score_codex":0.000047015914,"about_ca_system_score_gemma":0.000006345417,"threshold_uncertainty_score":0.4511982},"labels":[],"label_agreement":null},{"id":"W2760517586","doi":"10.7759/cureus.1721","title":"Diffusion Tensor Imaging for Ruptured Cerebral Arteriovenous Malformation","year":2017,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Neuroradiologist; Diffusion MRI; White matter; Tractography; Arteriovenous malformation; Fractional anisotropy; Radiology; Neurological deficit; Neuronavigation; Intracranial Arteriovenous Malformations; Nuclear medicine; Magnetic resonance imaging; Surgery; Cerebral angiography; Angiography","score_opus":0.0809561197386152,"score_gpt":0.3817563610082013,"score_spread":0.3008002412695861,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760517586","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54411423,0.00033039058,0.4085102,0.027643843,0.0005147219,0.0031028178,0.00011104138,0.0009789397,0.0146937845],"genre_scores_gemma":[0.96568584,0.000031164218,0.03255178,0.0007067326,0.0002003875,0.00012167525,0.00004816117,0.000022837145,0.0006314296],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99947995,0.0000028724771,0.00012488633,0.00016185167,0.00007302485,0.00015738867],"domain_scores_gemma":[0.9991589,0.00001180856,0.00012052459,0.00058369245,0.000067117944,0.000057956284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000044190176,0.00008657847,0.00012076868,0.000021280002,0.0003934178,0.000051039617,0.00012984166,0.000028712715,0.000018752666],"category_scores_gemma":[0.000080635924,0.00007438385,0.0000642181,0.000014831776,0.00004866445,0.00019111198,0.00004900086,0.000074127885,0.000010743905],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062615174,0.0013312605,0.22045924,0.00054000004,0.000080503676,0.00006663254,0.0014245997,0.000008691687,0.27910417,0.035393383,0.06478403,0.39618134],"study_design_scores_gemma":[0.0038988122,0.0003422013,0.5328423,0.00022656655,0.00017840645,0.0003877074,0.00016051721,0.022636782,0.014240122,0.018264744,0.4063187,0.0005031674],"about_ca_topic_score_codex":0.0000125835895,"about_ca_topic_score_gemma":0.0000017584199,"teacher_disagreement_score":0.42157158,"about_ca_system_score_codex":0.000035958725,"about_ca_system_score_gemma":0.0000137334155,"threshold_uncertainty_score":0.3033285},"labels":[],"label_agreement":null},{"id":"W2760605084","doi":"10.1016/j.schres.2017.09.030","title":"The influence of MIR137 on white matter fractional anisotropy and cortical surface area in individuals with familial risk for psychosis","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Rheinische Friedrich-Wilhelms-Universität Bonn; Deutsche Forschungsgemeinschaft","keywords":"Schizophrenia (object-oriented programming); Genotype; Psychosis; Allele; Medicine; Internal medicine; Biology; Genetics; Psychiatry; Gene","score_opus":0.08393412983607419,"score_gpt":0.42153832978966566,"score_spread":0.3376041999535915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2760605084","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9908406,0.000019840274,0.00066165946,0.007461766,0.000008910284,0.0007724497,0.000069737216,0.000014185324,0.00015085262],"genre_scores_gemma":[0.9829981,0.00019352324,0.016362427,0.00006827306,0.000029321443,0.00016397858,0.0000041706735,0.000016112735,0.00016410302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988371,0.00006372561,0.00016862362,0.00027954098,0.00039777896,0.00025324602],"domain_scores_gemma":[0.99828535,0.00073538756,0.00009391396,0.0006108404,0.00019465898,0.000079870195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005799509,0.00008687309,0.00014676338,0.00007166285,0.0006220506,0.000059420123,0.00022250699,0.000048638158,0.000009124683],"category_scores_gemma":[0.00045104377,0.000055900135,0.000025431618,0.000107235806,0.0005989083,0.00008260478,0.0000833083,0.00058103196,0.0000069964126],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023725457,0.0001086756,0.9906883,0.000020318324,0.000014785768,0.0000019805118,0.00003331256,0.000068645066,0.0023341218,0.0021355608,0.0012030005,0.0010187323],"study_design_scores_gemma":[0.0014731622,0.0003810357,0.98919934,0.00009702303,0.000010355025,0.0000060357443,0.000023798513,0.00034620642,0.00091769866,0.005957507,0.001530009,0.00005785348],"about_ca_topic_score_codex":0.000073908,"about_ca_topic_score_gemma":0.000042928226,"teacher_disagreement_score":0.015700767,"about_ca_system_score_codex":0.000025505436,"about_ca_system_score_gemma":0.000063781285,"threshold_uncertainty_score":0.47843733},"labels":[],"label_agreement":null},{"id":"W2761140693","doi":"10.3389/fnins.2017.00554","title":"Comparison of Diffusion-Weighted MRI Reconstruction Methods for Visualization of Cranial Nerves in Posterior Fossa Surgery","year":2017,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Western Hospital; University Health Network","funders":"Mitacs","keywords":"Tractography; Diffusion MRI; Visualization; Deconvolution; Artificial intelligence; Computer science; Computer vision; Medicine; Radiology; Magnetic resonance imaging; Algorithm","score_opus":0.10952893873970326,"score_gpt":0.4683709639523552,"score_spread":0.35884202521265196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761140693","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45258743,0.0000390089,0.5462022,0.00024142014,0.00048783157,0.0003784937,0.0000057315033,0.000017071021,0.00004084623],"genre_scores_gemma":[0.738702,0.000083420775,0.26109767,0.000039011655,0.000013509524,0.000034277946,0.0000027800736,0.000008716405,0.000018606326],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902165,0.00005134581,0.0004223799,0.00026738184,0.00010296843,0.000134301],"domain_scores_gemma":[0.9990483,0.00010045419,0.00040435581,0.000351021,0.00006254223,0.00003330759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031219784,0.000078522455,0.00035967128,0.00025683802,0.00009486026,0.000012885208,0.00017856184,0.00004319854,9.4534744e-7],"category_scores_gemma":[0.0005557328,0.00007583834,0.000057542107,0.00024313468,0.00033090106,0.00017958952,0.000053708394,0.000074289106,2.3784104e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001124698,0.00013256047,0.6958845,0.000063803,5.166183e-7,6.7028947e-7,0.000059887017,0.0000071582845,0.2111354,0.00012183104,0.00016063226,0.09232052],"study_design_scores_gemma":[0.0007883897,0.00019684012,0.69288,0.00028831835,0.000017219008,0.000018274764,0.000062408544,0.12807284,0.17335366,0.003024822,0.0011642193,0.0001330442],"about_ca_topic_score_codex":0.00001963345,"about_ca_topic_score_gemma":0.0000027952985,"teacher_disagreement_score":0.28611457,"about_ca_system_score_codex":0.000023870503,"about_ca_system_score_gemma":0.00004475949,"threshold_uncertainty_score":0.30925977},"labels":[],"label_agreement":null},{"id":"W2762036029","doi":"10.1002/hbm.23836","title":"Development of short‐range white matter in healthy children and adolescents","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Centre for Addiction and Mental Health; Hospital for Sick Children; University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Cohort; Psychology; Lateralization of brain function; Neuroscience; Hum; Tractography; Magnetic resonance imaging; Medicine; Pathology","score_opus":0.0854100442372943,"score_gpt":0.36677229395114175,"score_spread":0.28136224971384743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762036029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99384737,0.000022859022,0.002262871,0.0027434381,0.0000063213806,0.0003673478,0.000001910427,0.000031525768,0.0007163294],"genre_scores_gemma":[0.9835015,0.0000054010043,0.015304058,0.0010352103,0.000024615072,0.000022058593,0.000008304574,0.000012814958,0.00008604115],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993938,0.000007286225,0.00020290093,0.00019003336,0.000073971,0.00013200303],"domain_scores_gemma":[0.999533,0.000004664774,0.00007671457,0.0003243738,0.000014642705,0.00004660423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011601183,0.00007438519,0.00014733244,0.00008162671,0.00021116436,0.000013346654,0.00009511206,0.000025506522,0.000012648571],"category_scores_gemma":[0.000010679491,0.00007510235,0.000016103448,0.000027800706,0.00006162936,0.000047790225,0.00009098456,0.00011341781,0.000003349445],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007727401,0.000043183732,0.9884201,0.00008474051,0.0000030291123,0.0000018766921,0.00034806604,9.5919674e-8,0.008071404,0.00010039547,0.0005219198,0.002397455],"study_design_scores_gemma":[0.00038280347,0.000012008808,0.99762356,0.00040923804,0.000002454505,0.000008739694,0.000015940474,0.00000854693,0.00008349222,0.00019320933,0.0011947602,0.00006526669],"about_ca_topic_score_codex":0.000009397305,"about_ca_topic_score_gemma":0.000014408833,"teacher_disagreement_score":0.013041187,"about_ca_system_score_codex":0.000022154418,"about_ca_system_score_gemma":0.000013286967,"threshold_uncertainty_score":0.3062585},"labels":[],"label_agreement":null},{"id":"W2762896436","doi":"10.1016/j.neuroimage.2017.10.013","title":"Imaging microstructure in the living human brain: A viewpoint","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"National Institutes of Health; University of Toronto; Canadian Institutes of Health Research; Child Mind Institute","keywords":"Human brain; Neuroscience; Magnetic resonance imaging; White matter; Bridge (graph theory); Neuroimaging; Grey matter; Computer science; Ex vivo; Microstructure; In vivo; Psychology; Medicine; Materials science; Biology; Anatomy; Radiology","score_opus":0.06539384090682576,"score_gpt":0.38726362304611056,"score_spread":0.3218697821392848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762896436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7928306,0.00017950159,0.0022400005,0.17078266,0.00012223123,0.0014158651,0.000015551266,0.0003822774,0.032031298],"genre_scores_gemma":[0.9835663,0.000018577992,0.0017108661,0.014191076,0.00011956875,0.000041157946,0.000003636401,0.000029408426,0.0003194442],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99910367,0.000038865404,0.00017470247,0.00031650718,0.00013807659,0.00022819062],"domain_scores_gemma":[0.998459,0.00008692737,0.00011658839,0.001266205,0.00002807587,0.000043220978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019280003,0.00013288468,0.00015544497,0.000056163954,0.00051502505,0.00014471717,0.00045235775,0.000023187951,0.000028939874],"category_scores_gemma":[0.00031316868,0.000097197015,0.00007274534,0.000067194625,0.00016960978,0.00014432546,0.00015660681,0.0004506093,0.000012001172],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013834397,0.00017667862,0.105900146,0.00008355075,0.0000043219134,0.00070702535,0.00075456523,0.0000012411725,0.84940296,0.005256362,0.023665179,0.014034104],"study_design_scores_gemma":[0.0003069298,0.000035924386,0.9442562,0.00012047515,0.000014662949,0.0005033169,0.000045581746,0.00013263017,0.0015005476,0.0029670896,0.04999573,0.000120903256],"about_ca_topic_score_codex":0.00003818047,"about_ca_topic_score_gemma":0.000008971647,"teacher_disagreement_score":0.8479024,"about_ca_system_score_codex":0.000017837174,"about_ca_system_score_gemma":0.0000147429755,"threshold_uncertainty_score":0.39635792},"labels":[],"label_agreement":null},{"id":"W2763277880","doi":"10.5281/zenodo.1007149","title":"Tractography Challenge ISMRM 2015 b=3000s/mm² Data.","year":2017,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.20731157691122631,"score_gpt":0.40304209479875874,"score_spread":0.19573051788753243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763277880","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010625271,0.00036547784,0.0010294572,0.003779323,0.00010677452,0.0009812538,0.97805053,0.0010855504,0.014590998],"genre_scores_gemma":[0.00045495163,0.0034456544,0.00069995073,0.00030895552,0.0004682094,2.179395e-7,0.9926314,0.0014695599,0.00052110315],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975506,0.00012644485,0.00035377248,0.0009930993,0.0005257551,0.00045031882],"domain_scores_gemma":[0.9944568,0.000025619935,0.00034644175,0.0043864828,0.0004685874,0.00031604257],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00050889776,0.00031708463,0.0003920586,0.0003953659,0.002256296,0.0005737349,0.003221203,0.00021141487,0.0060174917],"category_scores_gemma":[0.0006493077,0.0003264126,0.00010674777,0.00028580223,0.00034417107,0.000299541,0.0030921733,0.0010524238,0.007849117],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004322964,0.00032295485,3.26056e-7,0.00018332068,0.000055221637,0.00006274097,0.000022412536,3.5166082e-7,0.00008386627,0.000098567645,0.97575337,0.023373654],"study_design_scores_gemma":[0.00045603415,0.000280131,0.000099821016,0.00014834391,0.00013105555,0.0002994209,0.000016925795,0.00003070307,0.000017847808,0.00016473833,0.99806714,0.0002878608],"about_ca_topic_score_codex":0.000036148216,"about_ca_topic_score_gemma":7.8626056e-7,"teacher_disagreement_score":0.023085793,"about_ca_system_score_codex":0.00008645787,"about_ca_system_score_gemma":0.000011702418,"threshold_uncertainty_score":0.9999188},"labels":[],"label_agreement":null},{"id":"W2763631887","doi":"10.1002/jnr.24142","title":"Age‐ and sex‐related effects in children with mild traumatic brain injury on diffusion magnetic resonance imaging properties: A comparison of voxelwise and tractography methods","year":2017,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health","keywords":"Uncinate fasciculus; Tractography; Fractional anisotropy; Corticospinal tract; Corpus callosum; White matter; Diffusion MRI; Superior longitudinal fasciculus; Cingulum (brain); Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Radiology","score_opus":0.17543774200190432,"score_gpt":0.49676812004678206,"score_spread":0.32133037804487774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763631887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99573267,0.0011185227,0.0004837161,0.0020157208,0.000012008434,0.00058256194,0.0000010200218,0.00000853752,0.000045218818],"genre_scores_gemma":[0.9924903,0.00045329548,0.00690183,0.00008939049,0.0000092703085,0.000011712615,8.6881485e-8,0.000013199874,0.00003092178],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984135,0.0002494767,0.0003310083,0.00025477735,0.0005075311,0.00024367376],"domain_scores_gemma":[0.9989347,0.00026906686,0.00023574306,0.00033487653,0.00008554128,0.00014011502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001262742,0.00010422895,0.00032435745,0.00049644936,0.00025868908,0.00007625323,0.00026425015,0.00002851903,4.8204646e-7],"category_scores_gemma":[0.00086832675,0.00006892973,0.00003184779,0.0003858625,0.0010153675,0.00019768432,0.00009834656,0.0007574183,5.8630903e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001874412,0.0003481173,0.34117094,0.000078203855,0.0000014212604,0.00005318275,0.00046264488,0.0000027411388,0.47597498,0.000038399103,0.00003140442,0.18165053],"study_design_scores_gemma":[0.0009767965,0.0022600687,0.9782108,0.00095815834,0.000011101282,0.000271653,0.000060465405,0.0041233664,0.012522501,0.00041615864,0.00012281032,0.000066111614],"about_ca_topic_score_codex":0.000021216982,"about_ca_topic_score_gemma":0.0000011319529,"teacher_disagreement_score":0.6370399,"about_ca_system_score_codex":0.000018352659,"about_ca_system_score_gemma":0.000050673025,"threshold_uncertainty_score":0.37411636},"labels":[],"label_agreement":null},{"id":"W2763784867","doi":"10.1002/mrm.26945","title":"Scan–rescan of axcaliber, macromolecular tissue volume, and g‐ratio in the spinal cord","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec; Canadian Institutes of Health Research; National Institutes of Health; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada; Canada Foundation for Innovation","keywords":"Intraclass correlation; Magnetic resonance imaging; White matter; Spinal cord; Repeatability; Artifact (error); Medicine; Nuclear medicine; Relaxometry; Partial volume; Radiology; Chemistry; Biology; Neuroscience; Spin echo","score_opus":0.0554028314702005,"score_gpt":0.389358564859911,"score_spread":0.3339557333897105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763784867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9234653,0.019715806,0.0017523248,0.04570143,0.00007008218,0.0014366545,0.000007188286,0.000036830897,0.007814358],"genre_scores_gemma":[0.9935479,0.0013969956,0.0033932016,0.0008392997,0.00007510953,0.00008912706,0.0000033259346,0.000013942448,0.0006411037],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989241,0.000038595066,0.0003313792,0.0002649697,0.00025285548,0.00018812511],"domain_scores_gemma":[0.9989614,0.00003457094,0.00012082761,0.0007916253,0.000041240004,0.000050356826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034994632,0.00012057924,0.00031246833,0.000087824075,0.000076443874,0.00001152381,0.000291992,0.000043808028,0.000046042496],"category_scores_gemma":[0.00030669148,0.000084781524,0.000016341433,0.00015411025,0.0006607575,0.00003964726,0.00006384714,0.00024287973,0.0000015763104],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043682416,0.00018095973,0.14749251,0.00018271053,0.000002253783,0.00044839506,0.00035758145,0.0000010261274,0.022036467,0.004249487,0.004361813,0.82025],"study_design_scores_gemma":[0.0013376131,0.0017997458,0.9052255,0.00075089245,0.000021443402,0.0001427421,0.00007790677,0.0005349325,0.0009803452,0.002895741,0.08614465,0.00008846196],"about_ca_topic_score_codex":0.00072124635,"about_ca_topic_score_gemma":0.00010832187,"teacher_disagreement_score":0.8201615,"about_ca_system_score_codex":0.000017852159,"about_ca_system_score_gemma":0.000027682918,"threshold_uncertainty_score":0.34572902},"labels":[],"label_agreement":null},{"id":"W2763963518","doi":"10.1016/j.neuropsychologia.2017.09.032","title":"Erratum to “A watershed model of individual differences in fluid intelligence” [Neuropsychologia 91 (2016) 186–198]","year":2017,"lang":"en","type":"erratum","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"Biotechnology and Biological Sciences Research Council; Wellcome Trust","keywords":"Psychology; Watershed; Fluid intelligence; Neuroscience; Cognition; Computer science; Machine learning","score_opus":0.16385716162347208,"score_gpt":0.3883942908832086,"score_spread":0.2245371292597365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763963518","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4342167,0.0016570444,0.049535763,0.021847762,0.038757756,0.015375279,0.0026789207,0.003944529,0.43198624],"genre_scores_gemma":[0.8470902,0.0031744465,0.01781945,0.0078833895,0.0009911837,0.00069979293,0.00068070466,0.00044392486,0.12121692],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9948616,0.0001660329,0.0012703341,0.0019802134,0.00078831014,0.0009334969],"domain_scores_gemma":[0.9952293,0.00009249651,0.00074908475,0.0033021015,0.00026867597,0.00035835558],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00036799014,0.00090109085,0.0015383681,0.000893241,0.00017004902,0.00010339645,0.0024451744,0.00083839265,0.000083240426],"category_scores_gemma":[0.00061287737,0.00076216226,0.00031922376,0.00057325966,0.0005926688,0.00013922816,0.0006497685,0.002878417,0.00012716337],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039715314,0.0008790576,0.0030559637,0.00020658752,0.000052512252,0.00025140503,0.00025855974,0.00004290906,0.025816983,0.00033224074,0.9562887,0.012417946],"study_design_scores_gemma":[0.0043081525,0.010649072,0.7178856,0.0062286602,0.0009861918,0.0008785991,0.00022163741,0.004121619,0.008575179,0.024837648,0.21540391,0.00590371],"about_ca_topic_score_codex":0.000020649402,"about_ca_topic_score_gemma":0.000004450106,"teacher_disagreement_score":0.7408848,"about_ca_system_score_codex":0.00006434329,"about_ca_system_score_gemma":0.00018929353,"threshold_uncertainty_score":0.9994829},"labels":[],"label_agreement":null},{"id":"W2764143201","doi":"10.1161/str.48.suppl_1.14","title":"Abstract 14: Effects of Lesion Laterality on Post-Stroke Motor Performance: An ENIGMA Stroke Recovery Analysis","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Laterality; Stroke (engine); Lesion; Lateralization of brain function; Physical medicine and rehabilitation; Stroke recovery; Physical therapy; Audiology; Pathology; Rehabilitation","score_opus":0.04431299141442506,"score_gpt":0.3541423515475729,"score_spread":0.3098293601331478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764143201","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950796,0.00002480246,0.0006880177,0.00035096184,0.00009831442,0.000501881,0.000353378,0.00013386933,0.0027691748],"genre_scores_gemma":[0.99134076,0.00017828653,0.004239102,0.00017503796,0.000115498544,0.0000482515,0.0000783078,0.000027147065,0.003797596],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99862057,0.000026063357,0.0003236676,0.00042485658,0.00033040126,0.00027441827],"domain_scores_gemma":[0.9977601,0.00008789292,0.00034424002,0.0014992431,0.00014940505,0.00015909945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017440612,0.00021222289,0.0004550155,0.00023180853,0.00028961615,0.000044003576,0.00030161816,0.00011045105,0.000043681855],"category_scores_gemma":[0.00013281156,0.00018391424,0.00031064329,0.000069699825,0.000119165634,0.00028209883,0.0000763799,0.0003311812,0.00001394186],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007122536,0.00051238446,0.13319075,0.00028181347,0.00027622448,0.00003628988,0.000050065173,0.00004785061,0.82170916,0.00013732574,0.00009011116,0.042955756],"study_design_scores_gemma":[0.00064317405,0.0010033177,0.7533986,0.00008440301,0.0003504653,0.000004617595,0.000008032185,0.00038789515,0.24319296,0.000045760113,0.000736255,0.00014452051],"about_ca_topic_score_codex":0.00010305947,"about_ca_topic_score_gemma":0.000012369669,"teacher_disagreement_score":0.62020785,"about_ca_system_score_codex":0.000056375688,"about_ca_system_score_gemma":0.00004161308,"threshold_uncertainty_score":0.74998045},"labels":[],"label_agreement":null},{"id":"W2764303658","doi":"10.1109/access.2017.2761701","title":"Data-Driven Corpus Callosum Parcellation Method Through Diffusion Tensor Imaging","year":2017,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Diffusion MRI; Artificial intelligence; Corpus callosum; Pattern recognition (psychology); Computer science; Tractography; Sørensen–Dice coefficient; Data set; Computer vision; Image segmentation; Segmentation; Psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.2846180431202832,"score_gpt":0.5028456206158834,"score_spread":0.21822757749560023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2764303658","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.083724715,0.00007359482,0.897504,0.009221683,0.00029846348,0.0007637437,0.000104602324,0.00044369776,0.007865525],"genre_scores_gemma":[0.8705587,0.000217659,0.12695035,0.0011752225,0.00034112734,0.00004208032,0.00012697955,0.000042683478,0.00054521137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99890715,0.00002347677,0.00020659491,0.00047362104,0.00018743626,0.00020173125],"domain_scores_gemma":[0.99742496,0.000064738866,0.0002397198,0.0021069911,0.00009226984,0.00007129854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011166062,0.00013630287,0.00021026924,0.00003745699,0.00045411204,0.00016271524,0.00089731754,0.000039578004,0.000030126774],"category_scores_gemma":[0.00010752393,0.00011667634,0.000042862022,0.000059786886,0.000096259726,0.0007841576,0.0004527978,0.0001957654,0.000018865067],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016342865,0.00044167257,0.5905061,0.00017282227,0.00005445124,0.00020599808,0.00015544356,0.00016931535,0.14797491,0.0022198148,0.042776637,0.21515943],"study_design_scores_gemma":[0.0023496326,0.00007015353,0.4004745,0.00032369193,0.00035578528,0.00028093884,0.00002537168,0.15764056,0.044600412,0.018473044,0.3747389,0.0006670074],"about_ca_topic_score_codex":0.00023327384,"about_ca_topic_score_gemma":0.0000120201885,"teacher_disagreement_score":0.78683394,"about_ca_system_score_codex":0.000030282115,"about_ca_system_score_gemma":0.000028783314,"threshold_uncertainty_score":0.4757923},"labels":[],"label_agreement":null},{"id":"W2765232463","doi":"10.1038/s41598-018-22181-4","title":"AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":164,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Compute Canada; McGill University; Nvidia","keywords":"Convolutional neural network; Segmentation; Computer science; Artificial intelligence; Axon; Myelin; Pattern recognition (psychology); Image segmentation; Deep learning; Pixel; Magnetic resonance imaging; Artificial neural network; Computer vision; Neuroscience; Anatomy; Biology; Central nervous system; Medicine; Radiology","score_opus":0.11562764753880364,"score_gpt":0.3972882005873601,"score_spread":0.2816605530485564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765232463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84242916,0.00022302399,0.15515101,0.00029066793,0.0012319606,0.00043776256,0.000016063033,0.00017523933,0.000045119865],"genre_scores_gemma":[0.86596,0.000006810096,0.13265191,0.00020038268,0.00024872992,0.000011596815,0.0007527297,0.000015691816,0.00015217622],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99851424,0.000019467645,0.00034231442,0.0007101845,0.00023068835,0.00018313278],"domain_scores_gemma":[0.99849457,0.000029157454,0.00020992455,0.0010490598,0.000118863594,0.00009841782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003380429,0.00010489684,0.0001403608,0.00007080918,0.00035275362,0.00011662749,0.000094915515,0.000041147505,0.000085507],"category_scores_gemma":[0.00006521481,0.0000977452,0.000021894324,0.00024213256,0.000399385,0.0002299399,0.00017845294,0.000101645004,0.0000041859535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034143777,0.00018613176,0.07102031,0.00004725956,0.00004144931,0.00019852899,0.00022459083,0.00016262583,0.87488914,0.00008117722,0.030108457,0.023006184],"study_design_scores_gemma":[0.00025825136,0.00004131522,0.0097089335,0.00010705579,0.00010585835,0.00073732,0.000042559655,0.9583696,0.01889218,0.0043742177,0.007192418,0.00017030393],"about_ca_topic_score_codex":0.000038252216,"about_ca_topic_score_gemma":0.0000070077695,"teacher_disagreement_score":0.95820695,"about_ca_system_score_codex":0.00003990476,"about_ca_system_score_gemma":0.00006626273,"threshold_uncertainty_score":0.39859337},"labels":[],"label_agreement":null},{"id":"W2765503737","doi":"10.3171/2017.7.peds17137","title":"Corticospinal tract atrophy and motor fMRI predict motor preservation after functional cerebral hemispherectomy","year":2017,"lang":"en","type":"article","venue":"Journal of Neurosurgery Pediatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; SickKids Foundation; Hospital for Sick Children; Toronto Western Hospital","funders":"University of California, Los Angeles; National Institutes of Health; Seattle Children's Research Institute","keywords":"Corticospinal tract; Medicine; Hemispherectomy; Neuroscience; Fractional anisotropy; Pyramidal tracts; Diffusion MRI; Atrophy; Motor cortex; Functional magnetic resonance imaging; Magnetic resonance imaging; Epilepsy; Physical medicine and rehabilitation; Psychology; Pathology; Radiology; Anatomy; Internal medicine; Stimulation","score_opus":0.056140547754351684,"score_gpt":0.3090965300936073,"score_spread":0.25295598233925565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765503737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924866,0.0003099556,0.004250545,0.0020652756,0.00046383712,0.00024158174,0.000029797253,0.000045142428,0.00010727385],"genre_scores_gemma":[0.99299115,0.00070861453,0.0037389903,0.00043702064,0.0016051304,0.00002096884,0.0000036978222,0.00003510604,0.0004593173],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99852407,0.000025566535,0.00055931095,0.00022746647,0.00045265458,0.00021093427],"domain_scores_gemma":[0.9980529,0.00015927786,0.0008472734,0.00039922283,0.0002942014,0.00024710776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019378327,0.0001701896,0.00031448636,0.00018374049,0.00021136996,0.000110727146,0.00014064854,0.000079091995,0.000050849023],"category_scores_gemma":[0.0006881172,0.00014724587,0.00021312962,0.00011641261,0.00009727068,0.000639128,0.0000741808,0.00046824588,0.0000025914044],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012408163,0.00032298212,0.9778424,0.00011106459,0.000016487285,0.00034822727,0.000009838249,0.000010356419,0.012111831,0.000023168575,0.004725362,0.0032374589],"study_design_scores_gemma":[0.0006868863,0.0005858172,0.98514396,0.000034069035,0.00017344549,0.0010763321,0.0000029454343,0.00037572236,0.00026575758,0.0002720665,0.011265039,0.0001179719],"about_ca_topic_score_codex":0.000002630982,"about_ca_topic_score_gemma":1.3877553e-7,"teacher_disagreement_score":0.011846074,"about_ca_system_score_codex":0.000040336832,"about_ca_system_score_gemma":0.00013251502,"threshold_uncertainty_score":0.60045123},"labels":[],"label_agreement":null},{"id":"W2766009055","doi":"10.1007/s11011-017-0135-9","title":"Prenatal methamphetamine exposure is associated with corticostriatal white matter changes in neonates","year":2017,"lang":"en","type":"article","venue":"Metabolic Brain Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health; University of Cape Town; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"White matter; Methamphetamine; Diffusion MRI; Fractional anisotropy; Orbitofrontal cortex; Tractography; Striatum; Neuroscience; Psychology; Medicine; Psychiatry; Dopamine; Magnetic resonance imaging; Prefrontal cortex; Cognition","score_opus":0.03816196029757842,"score_gpt":0.3215380286692689,"score_spread":0.2833760683716905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766009055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9495269,0.000722728,0.00053585495,0.047295786,0.000043373944,0.0008582305,0.0003531869,0.00016943277,0.00049452414],"genre_scores_gemma":[0.9899863,0.000060484672,0.001261341,0.005525803,0.00009017173,0.00026357893,0.00014152397,0.000046949473,0.0026238216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879783,0.000039317983,0.00018969152,0.00041935613,0.00023775251,0.0003160369],"domain_scores_gemma":[0.99843997,0.00005982037,0.00019669424,0.0009657321,0.00006931263,0.00026848266],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013511413,0.00020901264,0.00035574724,0.00010842002,0.00015014151,0.00006291786,0.00023875403,0.00004883684,0.00027029563],"category_scores_gemma":[0.00042679775,0.00016658321,0.000070979535,0.0001401937,0.00015194176,0.00016575523,0.000112545466,0.00019565294,0.000021815975],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002697271,0.0003587971,0.9883974,0.000054066724,0.000067192974,0.00020266492,0.00014812002,0.0000027357073,0.0006043436,0.00018248167,0.0033086557,0.0064038164],"study_design_scores_gemma":[0.0019559169,0.0000469614,0.98749423,0.00016940328,0.0001541631,0.000013377543,0.000013332791,0.000167553,0.002163433,0.00037690668,0.0072542895,0.00019040519],"about_ca_topic_score_codex":0.000032033055,"about_ca_topic_score_gemma":0.000037349426,"teacher_disagreement_score":0.04176998,"about_ca_system_score_codex":0.000022317112,"about_ca_system_score_gemma":0.0000589501,"threshold_uncertainty_score":0.6793066},"labels":[],"label_agreement":null},{"id":"W2766181796","doi":"10.1016/j.cortex.2017.10.022","title":"Short parietal lobe connections of the human and monkey brain","year":2017,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":113,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; King's College London; Wellcome Trust","keywords":"Supramarginal gyrus; Postcentral gyrus; Angular gyrus; Inferior parietal lobule; Superior parietal lobule; Neuroscience; Parietal lobe; Human brain; Psychology; Posterior parietal cortex; Middle temporal gyrus; Anatomy; Inferior temporal gyrus; Limbic lobe; Cortex (anatomy); Macaque; Superior temporal gyrus; Middle frontal gyrus; Temporal lobe; Cognition; Biology; Functional magnetic resonance imaging","score_opus":0.08919821177536608,"score_gpt":0.3927691679658896,"score_spread":0.30357095619052354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766181796","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98418254,0.00002794774,0.0016894133,0.0057361084,0.00003279712,0.00025155192,0.000007988358,0.000051460487,0.008020215],"genre_scores_gemma":[0.9981887,0.000012459978,0.0003968887,0.00022652184,0.00002897001,0.000015355312,0.0000021021801,0.0000069917673,0.0011220343],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997054,0.0000039787737,0.00007719236,0.00010676182,0.00004988308,0.00005680946],"domain_scores_gemma":[0.9993469,0.00001588214,0.000046968722,0.0005325015,0.000027409722,0.00003030725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028852592,0.000042226904,0.00007997427,0.000010238155,0.00030792525,0.00001020355,0.0000922147,0.000019449015,0.000009255714],"category_scores_gemma":[0.00006332642,0.000030294614,0.0000318613,0.000020688338,0.00021058088,0.000028871124,0.00007443045,0.000083728315,8.739386e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010830401,0.00015174471,0.5678903,0.00004093594,0.000027712882,0.0000069781026,0.000102715625,7.2396136e-7,0.33100322,0.06692142,0.012755396,0.021088015],"study_design_scores_gemma":[0.00013715166,0.00003164618,0.97051686,0.000024066401,0.000027838516,0.00003199435,0.000013075146,0.000070653434,0.0073817945,0.0038462295,0.017880796,0.000037907637],"about_ca_topic_score_codex":0.000021080134,"about_ca_topic_score_gemma":0.000007990602,"teacher_disagreement_score":0.40262654,"about_ca_system_score_codex":0.0000049897535,"about_ca_system_score_gemma":0.000008748378,"threshold_uncertainty_score":0.23683432},"labels":[],"label_agreement":null},{"id":"W2766426594","doi":"10.1016/j.neuroimage.2017.10.041","title":"PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":254,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Centre National de la Recherche Scientifique","keywords":"Spinal cord; Brainstem; Medicine; Computer science; White matter; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Radiology; Internal medicine","score_opus":0.07279584564477942,"score_gpt":0.3629979640391347,"score_spread":0.2902021183943553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766426594","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95751417,0.000025498932,0.0021499577,0.03661614,0.000036625177,0.0008069486,0.000018339164,0.000090859605,0.0027414574],"genre_scores_gemma":[0.99551857,0.0000198874,0.002647798,0.0011151251,0.000039270348,0.0000263063,0.0000011468355,0.000026935713,0.00060494634],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99923843,0.000033371,0.00012764569,0.0002635432,0.0001784711,0.00015854828],"domain_scores_gemma":[0.99840254,0.000052769396,0.00022361975,0.0012048963,0.000058584093,0.000057622034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092363916,0.00013299864,0.00017437128,0.000020067326,0.00044330893,0.000043563454,0.00030194467,0.000027012118,0.000004019029],"category_scores_gemma":[0.000091347734,0.000069065296,0.000052331772,0.00006846332,0.00047993354,0.0000796781,0.00015440953,0.00017207974,0.0000021049811],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023528587,0.0003169352,0.06607078,0.00023719654,0.000058867838,0.00021362178,0.00020344196,0.000010515777,0.8792185,0.0049011246,0.008471317,0.03794483],"study_design_scores_gemma":[0.0017707279,0.00095434405,0.90451634,0.00018222794,0.00011884635,0.00035084647,0.00006275858,0.0006821378,0.06599422,0.00027916138,0.02490743,0.00018096025],"about_ca_topic_score_codex":0.00005018009,"about_ca_topic_score_gemma":0.000010466273,"teacher_disagreement_score":0.83844554,"about_ca_system_score_codex":0.000007620652,"about_ca_system_score_gemma":0.0000307788,"threshold_uncertainty_score":0.34096187},"labels":[],"label_agreement":null},{"id":"W2766639217","doi":"10.1038/s41467-017-01285-x","title":"The challenge of mapping the human connectome based on diffusion tractography","year":2017,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1432,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MaRS; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Centre d'Imagerie BioMédicale; National Natural Science Foundation of China; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; École Polytechnique Fédérale de Lausanne; Deutsche Forschungsgemeinschaft; China Scholarship Council; National Institute for Health and Care Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; National Cancer Institute; Université de Sherbrooke; National Science Foundation","keywords":"Connectome; Tractography; Diffusion MRI; Human Connectome Project; Connectomics; Computer science; Neuroscience; Diffusion; Computational biology; Functional connectivity; Medicine; Biology; Magnetic resonance imaging; Physics; Radiology","score_opus":0.1387769546426739,"score_gpt":0.4102983062435371,"score_spread":0.2715213516008632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766639217","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0653861,0.005956077,0.002717606,0.79667103,0.0001548466,0.0026738907,0.00006419569,0.00044073744,0.12593552],"genre_scores_gemma":[0.9960823,0.0008761317,0.002151172,0.0006546135,0.000028607717,0.0001131162,0.00002133574,0.000013667063,0.000059063026],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994062,0.000056027257,0.00016790767,0.00012171453,0.00014637785,0.0001017603],"domain_scores_gemma":[0.99382937,0.0005493364,0.00023557877,0.005236179,0.00011826422,0.00003127078],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00024901424,0.0000835449,0.000113185924,0.00005404491,0.002390673,0.000032537995,0.0014124484,0.00008781349,0.0000043714726],"category_scores_gemma":[0.00024831994,0.000046520436,0.00010793171,0.00010754726,0.0004893618,0.000032031647,0.0001997667,0.00094321027,0.0000015751406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052004296,0.0014275758,0.028238887,0.00004770941,0.000070377435,0.0000018857751,0.00045986325,0.0000059384042,0.03148122,0.894073,0.0064001856,0.03774134],"study_design_scores_gemma":[0.0007058074,0.00013026434,0.47232676,0.00022288937,0.00006205128,0.000004096245,0.00010295908,0.0022951048,0.0013908999,0.011682824,0.51093954,0.00013679163],"about_ca_topic_score_codex":0.000010335136,"about_ca_topic_score_gemma":0.00004551691,"teacher_disagreement_score":0.9306962,"about_ca_system_score_codex":0.00001297047,"about_ca_system_score_gemma":0.000017699324,"threshold_uncertainty_score":0.9989081},"labels":[],"label_agreement":null},{"id":"W2766986295","doi":"10.1016/j.mri.2017.07.027","title":"A novel DTI-QA tool: Automated metric extraction exploiting the sphericity of an agar filled phantom","year":2017,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Sphericity; Imaging phantom; Metric (unit); Extraction (chemistry); Computer science; Biomedical engineering; Mathematics; Chromatography; Nuclear medicine; Chemistry; Medicine; Engineering; Geometry","score_opus":0.06488995868777386,"score_gpt":0.3745805827896747,"score_spread":0.30969062410190085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766986295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93772453,0.0034227064,0.045732636,0.0032685983,0.00017065316,0.0013884739,0.000032441247,0.0012591063,0.0070008705],"genre_scores_gemma":[0.916806,0.00016385023,0.08189741,0.00028530063,0.00010413764,0.00010355423,0.0000069915623,0.000040405663,0.0005923764],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99867475,0.000027544706,0.00035205,0.00038216411,0.00027819088,0.00028529484],"domain_scores_gemma":[0.99816275,0.00010387027,0.00035994363,0.0011717399,0.00013964735,0.00006204599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029010192,0.0001708659,0.00025813057,0.00007625214,0.0004646441,0.00009214923,0.00037431865,0.000032317414,0.00007673073],"category_scores_gemma":[0.00047556925,0.00013478541,0.00008036095,0.00026760664,0.00023315416,0.0003365529,0.00011505864,0.00023716953,0.00000827759],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008290035,0.00030977168,0.0129602235,0.00006174272,0.0000046272885,0.000040517385,0.00013160656,0.000022130846,0.2852484,0.00032351038,0.0009749854,0.6998396],"study_design_scores_gemma":[0.0022230856,0.00021328888,0.61567354,0.000355445,0.0001347327,0.00046552988,0.00020500139,0.28588918,0.044688378,0.0005098093,0.049251966,0.0003900553],"about_ca_topic_score_codex":0.0002674784,"about_ca_topic_score_gemma":0.000004078125,"teacher_disagreement_score":0.69944954,"about_ca_system_score_codex":0.000041458236,"about_ca_system_score_gemma":0.000043845514,"threshold_uncertainty_score":0.5496389},"labels":[],"label_agreement":null},{"id":"W2767050687","doi":"10.1038/mp.2017.170","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":736,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Norges Forskningsråd; National Health and Medical Research Council; Helse Sør-Øst RHF; Medical Research Council; NSW Ministry of Health; National Institute of Mental Health; Ministero della Salute; Office of Health and Medical Research; Hunter Medical Research Institute; Wellcome Trust; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Schizophrenia (object-oriented programming); Corpus callosum; White matter; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04207327760869915,"score_gpt":0.3272838972083747,"score_spread":0.28521061959967553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767050687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97391564,0.00066633284,0.0015013556,0.02194036,0.00052500557,0.0006106771,0.00021578553,0.0001417396,0.0004831141],"genre_scores_gemma":[0.9408622,0.000041317315,0.055920277,0.0025164075,0.00031456098,0.00007896226,0.00012147729,0.000060289956,0.00008452656],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977694,0.00008420725,0.00053025724,0.0007863486,0.0003223767,0.0005073781],"domain_scores_gemma":[0.9973295,0.00008824316,0.00039720404,0.002028562,0.000035515706,0.00012101783],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022369136,0.00035538056,0.00039432055,0.000064240914,0.0007019007,0.0003630423,0.0009717953,0.00013994524,0.000029671268],"category_scores_gemma":[0.00011333998,0.0002653756,0.0001742588,0.00017219214,0.00033997535,0.00014637908,0.00039788592,0.00077107496,0.000043515563],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065790873,0.0000921759,0.97870785,0.000014904095,0.00005157715,0.00003848027,0.00032490146,0.0000020273305,0.011334341,0.0006982869,0.0023254885,0.0057520694],"study_design_scores_gemma":[0.0033157787,0.000046203644,0.98113143,0.0004996819,0.0000553257,0.000054392196,0.00010107266,0.00004220386,0.0015028825,0.01154219,0.0014004603,0.000308355],"about_ca_topic_score_codex":0.00023160322,"about_ca_topic_score_gemma":0.0002283658,"teacher_disagreement_score":0.05441892,"about_ca_system_score_codex":0.000034171757,"about_ca_system_score_gemma":0.000053642114,"threshold_uncertainty_score":0.99997985},"labels":[],"label_agreement":null},{"id":"W2767073388","doi":"10.1016/j.neuroimage.2017.10.033","title":"Associations between prenatal, childhood, and adolescent stress and variations in white-matter properties in young men","year":2017,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; Economic and Social Research Council; National Institute of Mental Health; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; University of Bristol; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Prenatal stress; Psychology; Developmental psychology; White matter; Stress (linguistics); Clinical psychology; Medicine; Pregnancy; Biology; Genetics; Gestation; Philosophy; Magnetic resonance imaging","score_opus":0.12000149264979423,"score_gpt":0.3781422829021788,"score_spread":0.25814079025238457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767073388","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011052723,0.9832229,0.00020181146,0.0023112707,0.00006125232,0.005771501,0.0015010221,0.00022044098,0.0056045223],"genre_scores_gemma":[0.009668583,0.9882132,0.0006796103,0.000099008925,0.00010329266,0.00031896037,0.000321927,0.00008104282,0.00051439664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99837196,0.00009675164,0.000543908,0.0005764763,0.00015249432,0.00025841445],"domain_scores_gemma":[0.9988788,0.000068979585,0.00033114981,0.00059696677,0.000034156004,0.00008996592],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001327941,0.0003111974,0.0010448308,0.0002934024,0.00013916452,0.00010489044,0.00017848243,0.00015056529,0.0000061113947],"category_scores_gemma":[0.00014596501,0.0002684514,0.000079326564,0.00015883309,0.00010280418,0.00017993021,0.00022456383,0.0007568629,0.0000070190868],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000501146,0.00061926804,0.74145633,0.010190064,0.00005754865,0.00006988732,0.00035166493,5.771307e-7,0.000004185748,0.00007988157,0.0013935743,0.245772],"study_design_scores_gemma":[0.0004621418,0.000035505727,0.92868036,0.012224186,0.00034891866,0.000051267903,0.000005595679,0.000018003626,0.0000031680509,0.00009847175,0.057762776,0.0003096078],"about_ca_topic_score_codex":0.000039652612,"about_ca_topic_score_gemma":0.00002642278,"teacher_disagreement_score":0.2454624,"about_ca_system_score_codex":0.000082033424,"about_ca_system_score_gemma":0.00009043534,"threshold_uncertainty_score":0.99997675},"labels":[],"label_agreement":null},{"id":"W2767236431","doi":"10.1016/j.neuroscience.2017.10.050","title":"White Matter Changes Correlates of Peripheral Neuroinflammation in Patients with Parkinson’s Disease","year":2017,"lang":"en","type":"article","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael J. Fox Foundation for Parkinson's Research","keywords":"White matter; Corpus callosum; Splenium; Fornix; Cingulum (brain); Neuroinflammation; Diffusion MRI; Pathology; Neuroscience; Parkinson's disease; Neurodegeneration; Corticospinal tract; Psychology; Medicine; Disease; Magnetic resonance imaging; Fractional anisotropy; Hippocampus; Radiology","score_opus":0.029635594694023246,"score_gpt":0.29967394629913907,"score_spread":0.2700383516051158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2767236431","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99637425,0.0000027201847,0.00044109442,0.0024884103,0.000048220307,0.00031783918,0.00000724479,0.00002966356,0.00029056135],"genre_scores_gemma":[0.99869376,0.000010018228,0.00058973435,0.00044813813,0.000010112003,0.000026765792,0.0000026135929,0.000010281583,0.00020855175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999363,0.000008396615,0.00009522021,0.00023833184,0.00017028475,0.00012475868],"domain_scores_gemma":[0.9992768,0.0000066609614,0.00013051616,0.0004774366,0.000041304254,0.00006726424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030081113,0.00007336983,0.00009445891,0.000050051694,0.00010959732,0.000026508467,0.00016598911,0.000011512272,0.000009885397],"category_scores_gemma":[0.000056279554,0.000058225327,0.000014306667,0.00007605426,0.00019599764,0.00016762898,0.0000546787,0.00008422208,0.0000022111465],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000063817344,0.0000659428,0.9986665,0.000014278127,1.2572644e-7,0.000005568976,0.000019951185,0.000026697833,0.00057289336,0.000040022296,0.000045726003,0.00047844637],"study_design_scores_gemma":[0.00036304456,0.00012117791,0.99724185,0.00004778551,0.000005611838,0.0000017450942,0.0000011709539,0.0010373273,0.00021455435,0.000055225155,0.00085680163,0.00005367209],"about_ca_topic_score_codex":0.000003624709,"about_ca_topic_score_gemma":0.0000030662127,"teacher_disagreement_score":0.0023195387,"about_ca_system_score_codex":0.000011224295,"about_ca_system_score_gemma":0.000017774744,"threshold_uncertainty_score":0.237436},"labels":[],"label_agreement":null},{"id":"W2768007735","doi":"10.1177/0271678x17740501","title":"Lesion location matters: The relationships between white matter hyperintensities on cognition in the healthy elderly","year":2017,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":182,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Hyperintensity; Cognition; Lesion; Psychology; White matter; Cognitive aging; Medicine; Cognitive psychology; Audiology; Neuroscience; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.1131383849703217,"score_gpt":0.35109328363517933,"score_spread":0.23795489866485764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768007735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80934733,0.00018085293,0.0032392072,0.18616597,0.00014049307,0.00043880637,0.000010816636,0.000018772427,0.00045774857],"genre_scores_gemma":[0.98807305,0.000096114294,0.0036731306,0.0073276814,0.00068343285,0.000019938678,0.000009559344,0.000020264368,0.00009682989],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99866486,0.00017632222,0.0004685857,0.00013793317,0.0003830153,0.00016931487],"domain_scores_gemma":[0.99849874,0.00014808927,0.0005260185,0.00054566126,0.00021876955,0.00006269727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082536263,0.00013432365,0.00028004227,0.00013183286,0.0004771885,0.00012895005,0.00036609525,0.000065489075,0.000021604606],"category_scores_gemma":[0.00014381885,0.000075470925,0.000111873145,0.00010351916,0.00011658576,0.00030539968,0.000034714707,0.00086525263,0.000026369069],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015383681,0.0016655056,0.8781166,0.0002997109,0.000355449,0.00014034074,0.0064293523,0.00022196771,0.003373133,0.0067565115,0.060886737,0.040216323],"study_design_scores_gemma":[0.0012350719,0.00020807657,0.98479134,0.00023322314,0.00034877082,0.00034547583,0.00029952877,0.000045783472,0.0007023443,0.004866244,0.0068370514,0.00008709932],"about_ca_topic_score_codex":0.000011548334,"about_ca_topic_score_gemma":0.0000034642449,"teacher_disagreement_score":0.1788383,"about_ca_system_score_codex":0.000017071277,"about_ca_system_score_gemma":0.000042240914,"threshold_uncertainty_score":0.375914},"labels":[],"label_agreement":null},{"id":"W2768161353","doi":"10.1002/hbm.23900","title":"Integration of routine QA data into mega‐analysis may improve quality and sensitivity of multisite diffusion tensor imaging studies","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Fractional anisotropy; Diffusion MRI; Principal component analysis; Multivariate statistics; Statistics; Explained variation; White matter; Mathematics; Regression; Variance (accounting); Nuclear medicine; Artificial intelligence; Psychology; Pattern recognition (psychology); Computer science; Medicine; Magnetic resonance imaging","score_opus":0.2754570418686222,"score_gpt":0.4852983870692898,"score_spread":0.2098413452006676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768161353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86032456,0.00016857545,0.13547443,0.0035368896,0.000013108032,0.00030731078,0.000036052425,0.000056234072,0.00008281379],"genre_scores_gemma":[0.97685534,0.000060429633,0.022685997,0.0001596308,0.000039442817,0.000008098504,0.0000851763,0.000011267352,0.00009459268],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99883324,0.0000912403,0.0004154013,0.00039698384,0.00015377735,0.00010938131],"domain_scores_gemma":[0.9975629,0.00025459306,0.000571444,0.0013573921,0.0002133573,0.00004030635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096204795,0.000127672,0.00049341924,0.00016062375,0.00037042127,0.000021481592,0.00013100842,0.00002751469,0.000002383832],"category_scores_gemma":[0.001374806,0.00011042453,0.00007058039,0.000113852744,0.00032510367,0.0002013031,0.0005538984,0.00013553511,1.8853505e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013117063,0.000051533334,0.10376044,0.00016554997,0.00014258997,0.0000040614586,0.0007066731,0.0000012930544,0.88642526,0.0010356677,0.0000583578,0.0076354593],"study_design_scores_gemma":[0.0005052527,0.000022738708,0.969586,0.00027962038,0.00036262986,0.0000046076752,0.00097554765,0.01737237,0.008504184,0.0020969738,0.00016484747,0.00012520942],"about_ca_topic_score_codex":0.00065071124,"about_ca_topic_score_gemma":0.0001650851,"teacher_disagreement_score":0.87792104,"about_ca_system_score_codex":0.000025144429,"about_ca_system_score_gemma":0.000007285982,"threshold_uncertainty_score":0.4502982},"labels":[],"label_agreement":null},{"id":"W2768632892","doi":"10.1016/j.eplepsyres.2017.11.010","title":"Histological and MRI markers of white matter damage in focal epilepsy","year":2017,"lang":"en","type":"review","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"White matter; Epilepsy; Diffusion MRI; Cortical dysplasia; Neuroscience; Neuroimaging; Magnetic resonance imaging; Pathology; Medicine; Temporal lobe; Psychology; Radiology","score_opus":0.3585299072192049,"score_gpt":0.5228600838039462,"score_spread":0.1643301765847413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2768632892","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00018049395,0.9731505,0.00023158865,0.0018636632,0.000042892087,0.0024072418,0.00006500672,0.00005717145,0.022001443],"genre_scores_gemma":[0.00040763995,0.9892925,0.0043250355,0.000055078595,0.0000882291,0.00046854664,0.0000675651,0.00006531841,0.0052300813],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972039,0.00038528675,0.00067105936,0.0007325114,0.00046753173,0.00053969846],"domain_scores_gemma":[0.99753916,0.00050003367,0.00024551962,0.0013810231,0.00013178667,0.00020248075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014385591,0.0002901112,0.0016372006,0.0006049594,0.00020982047,0.000025800928,0.0005278058,0.00034675005,0.00038907753],"category_scores_gemma":[0.0003583324,0.00022559558,0.00023061335,0.0003561069,0.00096064544,0.00006349178,0.0007307287,0.0019018496,0.00008410289],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016161206,0.0003709862,0.05215214,0.01760848,0.00005757861,0.00047595194,0.00005530165,9.706332e-8,0.000007785548,0.0009912244,0.06406219,0.86405665],"study_design_scores_gemma":[0.00025945445,0.00022560271,0.01543775,0.006245086,0.00007341513,0.00015258644,0.000008708834,0.000014715212,0.0000011999962,0.00054177427,0.9768646,0.00017511084],"about_ca_topic_score_codex":0.00003120639,"about_ca_topic_score_gemma":0.0000054617626,"teacher_disagreement_score":0.9128024,"about_ca_system_score_codex":0.00015265211,"about_ca_system_score_gemma":0.00022798691,"threshold_uncertainty_score":0.91995203},"labels":[],"label_agreement":null},{"id":"W2769873747","doi":"10.1016/j.neuropsychologia.2017.11.017","title":"More than blindsight: Case report of a child with extraordinary visual capacity following perinatal bilateral occipital lobe injury","year":2017,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; State Government of Victoria; Australian Government","keywords":"Blindsight; Psychology; Occipital lobe; Visual cortex; Neuroscience; Visual field; Cortical blindness; N2pc; Cortex (anatomy); Temporal lobe; Visual perception; Extrastriate cortex; Audiology; Perception; Blindness; Medicine; Epilepsy; Optometry","score_opus":0.05564976656072537,"score_gpt":0.39066700030885576,"score_spread":0.3350172337481304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2769873747","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99329007,0.000012416649,0.0007783582,0.0018839559,0.00015719688,0.0004776123,0.000027488839,0.00023274489,0.0031401387],"genre_scores_gemma":[0.9948119,0.0000054597353,0.0044307616,0.00033603268,0.00010284831,0.000044266868,0.000013110606,0.0000490872,0.00020651636],"study_design_codex":"case_report","study_design_gemma":"observational","domain_scores_codex":[0.9985585,0.000023145243,0.00032305514,0.000599047,0.0002202576,0.0002759707],"domain_scores_gemma":[0.9981377,0.000017977041,0.00032194212,0.0013132882,0.000075919386,0.00013316634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010836588,0.00023640739,0.00033575503,0.00010099042,0.00038731826,0.00003772141,0.00023972052,0.00008828507,0.0000148958125],"category_scores_gemma":[0.00010199649,0.00018286634,0.0001605256,0.00012343178,0.0003570399,0.00021306964,0.00013537916,0.00048341477,0.0000036926278],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012507304,0.0013770619,0.36407694,0.00011028849,0.00012835472,0.55314463,0.00037956084,0.000003332658,0.07050816,0.00032408835,0.0010952977,0.007601537],"study_design_scores_gemma":[0.0015376252,0.0024035533,0.61394227,0.00017733073,0.00013404847,0.3665983,0.00006023819,0.00008522033,0.012686424,0.00010125959,0.0018936519,0.0003800795],"about_ca_topic_score_codex":0.000036018966,"about_ca_topic_score_gemma":0.0000015460209,"teacher_disagreement_score":0.24986532,"about_ca_system_score_codex":0.000019412168,"about_ca_system_score_gemma":0.000023188099,"threshold_uncertainty_score":0.74570733},"labels":[],"label_agreement":null},{"id":"W276996006","doi":"10.1007/978-3-319-10443-0_22","title":"Automatic Method for Thalamus Parcellation Using Multi-modal Feature Classification","year":2014,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Computer science; Modal; Artificial intelligence; Pattern recognition (psychology); Feature (linguistics)","score_opus":0.1041728978129066,"score_gpt":0.4138508495461696,"score_spread":0.30967795173326296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W276996006","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043029573,0.000013357924,0.95412225,0.0020389173,0.00009594434,0.00054790324,0.0000010635699,0.00014477891,0.000006230512],"genre_scores_gemma":[0.47929674,8.589274e-7,0.5202047,0.0004022288,0.00006979181,0.000015737565,0.000002765969,0.000006385601,7.7692994e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999025,0.0000301362,0.00014639004,0.0004216117,0.0001686949,0.00020820231],"domain_scores_gemma":[0.9991031,0.00027240827,0.00008696541,0.00037615927,0.00010492389,0.000056415538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035138434,0.00010610992,0.00014866657,0.00015137137,0.00015392227,0.000041827414,0.00017444137,0.0000580555,0.0000014913514],"category_scores_gemma":[0.0002007013,0.0000896333,0.00003774884,0.0005601907,0.000112679074,0.00009909145,0.00004841652,0.00015453188,8.8132015e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070749793,0.00005265428,0.004364376,0.000049081274,0.0000016334345,6.198023e-7,0.00021413907,0.01824661,0.12419381,0.00050210283,0.0000059133085,0.852362],"study_design_scores_gemma":[0.00029715407,0.000056773104,0.023017326,0.000053937772,0.000009533239,0.000033544296,4.1800746e-7,0.9494071,0.020330248,0.0065508783,0.00015485789,0.000088229885],"about_ca_topic_score_codex":0.0000063114076,"about_ca_topic_score_gemma":0.0000021752037,"teacher_disagreement_score":0.9311605,"about_ca_system_score_codex":0.00008826255,"about_ca_system_score_gemma":0.000061605344,"threshold_uncertainty_score":0.36551398},"labels":[],"label_agreement":null},{"id":"W2770851226","doi":"10.1016/j.neuroimage.2017.11.038","title":"Effects of bilingualism on white matter integrity in older adults","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto; York University","funders":"National Institute on Aging; National Institutes of Health","keywords":"Fractional anisotropy; Neuroscience of multilingualism; White matter; Psychology; Cognitive reserve; Diffusion MRI; Dementia; Mechanism (biology); Cognition; Audiology; Neuroscience; Medicine; Cognitive impairment; Physics; Magnetic resonance imaging; Pathology","score_opus":0.03388399414908069,"score_gpt":0.35974322054175445,"score_spread":0.32585922639267373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770851226","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99028265,0.000013771921,0.00033693598,0.0032474203,0.00006555168,0.0006199614,0.0000057809584,0.00007021593,0.005357683],"genre_scores_gemma":[0.99569947,0.000023472037,0.0021704056,0.0015213107,0.000042081843,0.000041593295,0.0000029281823,0.00002584446,0.00047292086],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992235,0.00002245154,0.00017926234,0.00030157302,0.0001225671,0.000150695],"domain_scores_gemma":[0.9988834,0.00007613039,0.0001238012,0.00082260027,0.00004247359,0.000051596722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060707236,0.00011605572,0.00020966481,0.00008784219,0.000058551603,0.000015233436,0.00018633349,0.00004592981,0.00003018678],"category_scores_gemma":[0.0002223276,0.00009977451,0.000060232735,0.0000544973,0.000102980506,0.00006967474,0.00007881613,0.00039231768,0.00003872619],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064826745,0.0022628536,0.8403899,0.0014663136,0.0000114775075,0.00087559206,0.0007762549,0.0000024769831,0.12146654,0.0011448117,0.009151797,0.02180368],"study_design_scores_gemma":[0.0010796166,0.00011187432,0.9387594,0.00040235367,0.000011497254,0.00001706283,0.0000044647,0.00007425197,0.058516175,0.00032269183,0.0006240842,0.00007652528],"about_ca_topic_score_codex":0.00003397992,"about_ca_topic_score_gemma":0.0000024474987,"teacher_disagreement_score":0.09836947,"about_ca_system_score_codex":0.0000136699,"about_ca_system_score_gemma":0.000013717157,"threshold_uncertainty_score":0.40686864},"labels":[],"label_agreement":null},{"id":"W2771176174","doi":"10.2967/jnumed.117.200006","title":"Flortaucipir F 18 Quantitation Using Parametric Estimation of Reference Signal Intensity","year":2017,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Avid Radiopharmaceuticals; Eli Lilly and Company","keywords":"White matter; Partial volume; Nuclear medicine; Voxel; Spatial normalization; Alzheimer's disease; Medicine; Magnetic resonance imaging; Pathology; Radiology; Disease","score_opus":0.3348029175542141,"score_gpt":0.4658599099119657,"score_spread":0.1310569923577516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771176174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9628245,0.00008860494,0.03205304,0.0038919582,0.000114693474,0.00013505133,0.0000014337594,0.000020538386,0.00087014417],"genre_scores_gemma":[0.94060206,0.00010946338,0.058885995,0.0002387589,0.00013374515,2.7781329e-7,0.0000015263323,0.000013124456,0.000015061674],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99905145,0.000014351413,0.00045711166,0.00009155348,0.00030065252,0.00008485617],"domain_scores_gemma":[0.99802375,0.0000557397,0.001031301,0.00030379434,0.0004985823,0.000086839056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033713167,0.000077483775,0.00034450623,0.00022382803,0.00012083323,0.000008953033,0.00015055544,0.0000429632,0.00008150671],"category_scores_gemma":[0.0009498974,0.00005793814,0.000055101315,0.0001267524,0.0002034146,0.00018611185,0.000031305855,0.00025817187,0.0000024076962],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029324635,0.0010916292,0.035351854,0.0007257736,0.0003138124,0.0003900415,0.0012798826,0.00317608,0.7833275,0.012271536,0.03119488,0.1279445],"study_design_scores_gemma":[0.0060630245,0.0061438037,0.6930306,0.0049953405,0.0013808633,0.0032744643,0.0008355554,0.24655688,0.011292799,0.012629649,0.013389356,0.0004076922],"about_ca_topic_score_codex":0.00003446158,"about_ca_topic_score_gemma":2.8455355e-7,"teacher_disagreement_score":0.77203476,"about_ca_system_score_codex":0.000044309087,"about_ca_system_score_gemma":0.000041211715,"threshold_uncertainty_score":0.23626488},"labels":[],"label_agreement":null},{"id":"W2771290777","doi":"10.1002/hbm.23908","title":"Cerebral sex dimorphism and sexual orientation","year":2017,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Vetenskapsrådet; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; Alberta Foundation for the Arts","keywords":"Sexual dimorphism; Sexual orientation; Psychology; Precuneus; Sex characteristics; Fractional anisotropy; Cerebral cortex; Developmental psychology; Heterosexuality; Sexual differentiation; Homosexuality; White matter; Neuroscience; Biology; Cognition; Zoology; Genetics; Social psychology; Medicine; Magnetic resonance imaging; Psychoanalysis","score_opus":0.13840602051202386,"score_gpt":0.3929665288813349,"score_spread":0.254560508369311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771290777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96466875,0.0000159677,0.019728644,0.0092862295,0.000027294434,0.000309605,0.0000030132508,0.00020940044,0.005751069],"genre_scores_gemma":[0.9886967,0.0000024238761,0.006594927,0.0010316147,0.00015471417,0.000027007687,0.000017999877,0.000015691627,0.003458951],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994572,0.000008126688,0.00010594456,0.00022988743,0.00007756195,0.000121277975],"domain_scores_gemma":[0.9993843,0.000021217236,0.00008587201,0.0004283664,0.00002099674,0.000059263242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008992342,0.000075444375,0.00010344503,0.000044931112,0.00078267185,0.00005853761,0.00007775317,0.00002730619,0.000024862962],"category_scores_gemma":[0.00006478772,0.00007564759,0.000016236443,0.000022062914,0.00011507781,0.000113971306,0.00007763887,0.000112355316,0.0000060694665],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013160386,0.000096327996,0.2267681,0.00015342071,0.00002797812,0.000049183483,0.0016089671,0.0000012595528,0.6524242,0.06896562,0.021906232,0.027985524],"study_design_scores_gemma":[0.00074039696,0.00007334655,0.93749595,0.00006309411,0.000015122478,0.00006482741,0.00022042428,0.00033421293,0.00068171206,0.014287404,0.045873966,0.00014952013],"about_ca_topic_score_codex":0.000021825204,"about_ca_topic_score_gemma":0.000002699401,"teacher_disagreement_score":0.7107279,"about_ca_system_score_codex":0.000016320826,"about_ca_system_score_gemma":0.000007652031,"threshold_uncertainty_score":0.6019758},"labels":[],"label_agreement":null},{"id":"W2771937409","doi":"10.1089/neu.2017.5274","title":"Decreased Number of Self-Paced Saccades in Post-Concussion Syndrome Associated with Higher Symptom Burden and Reduced White Matter Integrity","year":2017,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network; Toronto Western Hospital; Hospital for Sick Children; Occupational Cancer Research Centre","funders":"","keywords":"Post-concussion syndrome; Concussion; Traumatic brain injury; White matter; Medicine; Psychology; Physical medicine and rehabilitation; Poison control; Injury prevention; Psychiatry; Audiology; Medical emergency; Magnetic resonance imaging","score_opus":0.05738284679522208,"score_gpt":0.3627935700725841,"score_spread":0.305410723277362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771937409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896634,0.000013946698,0.000026526706,0.009340996,0.000032377313,0.00023910511,0.000007180128,0.00002713319,0.0006493402],"genre_scores_gemma":[0.9965545,0.000033928663,0.0028450324,0.00028003825,0.000043843822,0.0000058209257,0.0000018183812,0.000028434728,0.00020658488],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989934,0.000054760043,0.0003930629,0.00017014657,0.00023189248,0.00015673226],"domain_scores_gemma":[0.9985499,0.00007309099,0.0006934929,0.00032829843,0.00022027218,0.00013495245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001672545,0.0001445207,0.00040978278,0.00011161283,0.0000765911,0.000034918918,0.0001748654,0.00008153526,0.00006400165],"category_scores_gemma":[0.00013476041,0.000099958794,0.000069308975,0.000087946486,0.00009786418,0.00022179977,0.000046008157,0.0005645469,0.0000020548482],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073410035,0.00041904024,0.90265363,0.000087570166,0.000110596324,0.0007623587,0.00028614877,0.00000336169,0.09313526,0.00006692755,0.0006079397,0.0011330468],"study_design_scores_gemma":[0.0018721148,0.0003938095,0.9917165,0.0006848888,0.00009957506,0.0018491222,0.000020866291,0.000031975393,0.002839756,0.00022238238,0.00017235246,0.0000966301],"about_ca_topic_score_codex":0.000029825771,"about_ca_topic_score_gemma":0.0000022777406,"teacher_disagreement_score":0.09029551,"about_ca_system_score_codex":0.000046988825,"about_ca_system_score_gemma":0.0000636523,"threshold_uncertainty_score":0.40762013},"labels":[],"label_agreement":null},{"id":"W2775461784","doi":"10.1016/j.neuroimage.2017.12.036","title":"Surface-enhanced tractography (SET)","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Streamlines, streaklines, and pathlines; Connectomics; Artificial intelligence; Computer science; Diffusion MRI; Human Connectome Project; Pattern recognition (psychology); Computer vision; Neuroscience; Connectome; Magnetic resonance imaging; Physics; Psychology; Radiology; Medicine; Functional connectivity","score_opus":0.11706797726663845,"score_gpt":0.40060523113589525,"score_spread":0.28353725386925677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775461784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9042189,0.000039391438,0.011957021,0.006069147,0.00012124008,0.00055796327,0.000020274189,0.00063950545,0.076376535],"genre_scores_gemma":[0.98680884,0.000118100914,0.010642033,0.0009448094,0.000079381454,0.000019434172,0.000007943589,0.000038084338,0.0013414022],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991013,0.00001109239,0.0001522653,0.00035756058,0.00015257121,0.00022520572],"domain_scores_gemma":[0.99830973,0.000029600033,0.000128331,0.0013508893,0.000059360165,0.00012206015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055156168,0.00013739281,0.00018701132,0.00004217506,0.00037104602,0.00007865635,0.00026730137,0.00004063695,0.00006431319],"category_scores_gemma":[0.00010642602,0.00012768879,0.00012089768,0.00006934589,0.00017693742,0.0001820078,0.00008072427,0.0002713743,0.000073886986],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007497134,0.00021070785,0.017692877,0.000042433865,0.000013436073,0.00015022821,0.00004901179,0.00000410305,0.9536028,0.0014246819,0.00923989,0.017494846],"study_design_scores_gemma":[0.0013586989,0.00026830618,0.5897628,0.000063920415,0.00007698712,0.00013170432,0.000013500941,0.00028312084,0.2659123,0.0028523211,0.13893922,0.00033707835],"about_ca_topic_score_codex":0.000011117744,"about_ca_topic_score_gemma":9.967126e-7,"teacher_disagreement_score":0.6876905,"about_ca_system_score_codex":0.000009147682,"about_ca_system_score_gemma":0.00001949113,"threshold_uncertainty_score":0.5206998},"labels":[],"label_agreement":null},{"id":"W2776173315","doi":"10.3389/fnana.2017.00129","title":"Axon and Myelin Morphology in Animal and Human Spinal Cord","year":2017,"lang":"en","type":"review","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation","keywords":"Axon; Neuroscience; Spinal cord; White matter; Myelin; Segmentation; Myelin sheath; Biology; Computer science; Anatomy; Artificial intelligence; Magnetic resonance imaging; Central nervous system; Medicine","score_opus":0.1548428791220594,"score_gpt":0.4555201286528816,"score_spread":0.3006772495308222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2776173315","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0016098189,0.99589384,0.0002109918,0.00027523414,0.00011401397,0.0011959963,0.00001542721,0.00006681319,0.0006178948],"genre_scores_gemma":[0.0014373923,0.9914002,0.006519127,0.00013167027,0.00006844344,0.00018329978,0.000026990498,0.000059651982,0.0001732716],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984302,0.00006775888,0.00045036656,0.0006740541,0.000095160416,0.00028245122],"domain_scores_gemma":[0.99905163,0.000023021477,0.00024509858,0.00055766985,0.000017052833,0.000105549945],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013335829,0.00031714933,0.001349319,0.00049906503,0.00008437803,0.000025797992,0.00020593875,0.00020723527,0.0000037663435],"category_scores_gemma":[0.00006531308,0.00029925685,0.00008369345,0.00016107387,0.00030014516,0.000065453234,0.0001791703,0.0008663106,0.0000015875582],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057572604,0.00005419603,0.0040999027,0.002541628,0.000010852614,0.0006810647,0.0000038983508,1.1037722e-8,0.0000043234904,0.00050065323,0.0030280503,0.98901784],"study_design_scores_gemma":[0.00047813394,0.00039012745,0.0043403083,0.002909946,0.00013673327,0.0006313971,0.000004440437,0.000015842441,0.0000011926936,0.0006307904,0.9902361,0.00022499745],"about_ca_topic_score_codex":0.000028262784,"about_ca_topic_score_gemma":0.0000041940116,"teacher_disagreement_score":0.98879284,"about_ca_system_score_codex":0.00006144009,"about_ca_system_score_gemma":0.00006063721,"threshold_uncertainty_score":0.99994594},"labels":[],"label_agreement":null},{"id":"W2779764073","doi":"10.1016/j.schres.2017.11.038","title":"Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Alzheimer's Society; Consejo Nacional de Ciencia y Tecnología; Weston Brain Institute; Centre for Addiction and Mental Health Foundation; Canadian Institutes of Health Research; National Alliance for Research on Schizophrenia and Depression; Alzheimer Society; Natural Sciences and Engineering Research Council of Canada; Ontario Mental Health Foundation; Sistema Nacional de Investigadores; Michael J. Fox Foundation for Parkinson's Research","keywords":"Support vector machine; Artificial intelligence; Machine learning; Linear discriminant analysis; Pattern recognition (psychology); Computer science; Logistic regression; Cross-validation; Data set; Regression; Magnetic resonance imaging; Feature (linguistics); Mathematics; Statistics; Medicine; Radiology","score_opus":0.24079170290325963,"score_gpt":0.47929969308049564,"score_spread":0.238507990177236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779764073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778983,0.0065676873,0.0034004876,0.006246496,0.00006851684,0.0033738897,0.0022488097,0.00018345506,0.000012359976],"genre_scores_gemma":[0.84873503,0.0008805704,0.14945419,0.00017599303,0.00011262848,0.00019199963,0.00027070974,0.0000851747,0.000093696646],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962427,0.00061146636,0.00050652155,0.0012092419,0.00065915426,0.00077089685],"domain_scores_gemma":[0.9970323,0.0004919783,0.0002562896,0.0013582711,0.0003438388,0.0005173155],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0010720458,0.00037161756,0.0006053291,0.00032599518,0.0020681038,0.0004135612,0.00048707187,0.00010428662,0.000022130536],"category_scores_gemma":[0.0013577738,0.00033646286,0.00004978449,0.00023873622,0.0006124438,0.00028626338,0.0009474356,0.0017712822,0.0000093134495],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0060133226,0.0011606734,0.63035405,0.00007962812,0.00003171526,0.00016561085,0.00032344143,0.0000033452498,0.008023971,0.000086613254,0.0003230009,0.35343462],"study_design_scores_gemma":[0.029520579,0.0011090528,0.85884774,0.00028031543,0.000106089596,0.000049557668,0.00020556903,0.10228358,0.00028823855,0.0009811384,0.0058576246,0.0004705361],"about_ca_topic_score_codex":0.0036867063,"about_ca_topic_score_gemma":0.00068346085,"teacher_disagreement_score":0.35296407,"about_ca_system_score_codex":0.000115560186,"about_ca_system_score_gemma":0.00020891342,"threshold_uncertainty_score":0.99990875},"labels":[],"label_agreement":null},{"id":"W2780737922","doi":"10.1038/s41596-021-00588-0","title":"Generic acquisition protocol for quantitative MRI of the spinal cord","year":2021,"lang":"en","type":"article","venue":"Nature Protocols","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Centre Hospitalier Universitaire de Sherbrooke; International Collaboration On Repair Discoveries; University of British Columbia; Université de Montréal; Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute","funders":"National Institute of Neurological Disorders and Stroke; Staatssekretariat für Bildung, Forschung und Innovation; Economic and Social Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; CRIS Cancer Foundation; Regione Puglia; University College London Hospitals NHS Foundation Trust; Ministero dell’Istruzione, dell’Università e della Ricerca; Ministero della Salute; Concordia University; Agentura Pro Zdravotnický Výzkum České Republiky; National Institutes of Health; Rosetrees Trust; European Commission; Multiple Sclerosis Society; Bundesministerium für Bildung und Forschung; National Imaging Facility; National Institute for Health and Care Research; University of Pennsylvania; SpinalCure Australia; University of Minnesota; National Science Foundation; Compute Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Polytechnique Montréal; Wellcome Trust; Institut de Valorisation des Données; AstraZeneca; National Center for Advancing Translational Sciences; Craig H. Neilsen Foundation; McGill University; Canada First Research Excellence Fund; Max-Planck-Gesellschaft","keywords":"Protocol (science); Magnetic resonance imaging; Computer science; Diffusion MRI; Medicine; Spinal cord; Neuroimaging; Medical physics; Nuclear medicine; Radiology; Pathology","score_opus":0.14861896995219095,"score_gpt":0.51340233755156,"score_spread":0.364783367599369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2780737922","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00015587622,0.000008530147,0.04181874,0.0031929035,0.000012326285,0.9541259,0.000020986468,0.00006727872,0.0005974711],"genre_scores_gemma":[0.0030012268,2.0282489e-7,0.11970275,0.00087843434,0.000058667592,0.876139,0.000005484393,0.000015597541,0.00019865621],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99927425,0.000027178736,0.00019152078,0.00022372796,0.0001668129,0.00011648026],"domain_scores_gemma":[0.9989818,0.00002738567,0.00015522457,0.00039891282,0.000405418,0.00003130962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008222414,0.00009300987,0.0001603677,0.00002415319,0.00007765172,0.000008912241,0.000112988135,0.000108025604,0.00001714621],"category_scores_gemma":[0.00011523107,0.00006249284,0.000114626506,0.0003016126,0.000060350143,0.00003814953,0.00005191398,0.00029317147,0.0000011781901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008820774,0.0015993287,0.0044536954,0.0039466647,0.0000731443,0.000019071133,0.00006458973,0.000017816263,0.7083971,0.20780075,0.035174526,0.029632539],"study_design_scores_gemma":[0.0018000606,0.0013892516,0.007415569,0.000917482,0.000023600964,0.00005411696,0.000013316655,0.00018955313,0.5932174,0.013307397,0.3815684,0.00010387998],"about_ca_topic_score_codex":4.7572607e-7,"about_ca_topic_score_gemma":4.998781e-7,"teacher_disagreement_score":0.34639385,"about_ca_system_score_codex":0.000029307865,"about_ca_system_score_gemma":0.00013725566,"threshold_uncertainty_score":0.2548384},"labels":[],"label_agreement":null},{"id":"W2781188568","doi":"10.1186/s12880-017-0236-2","title":"Improving the evaluation of cardiac function in rats at 7T with denoising filters: a comparison study","year":2017,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Hôpital Fleurimont","funders":"Fonds de Recherche du Québec - Santé","keywords":"Noise reduction; Ejection fraction; Segmentation; Computer science; Ventricle; Filter (signal processing); Cardiac function curve; Pattern recognition (psychology); Medicine; Biomedical engineering; Artificial intelligence; Cardiology; Computer vision; Heart failure","score_opus":0.15102675773463192,"score_gpt":0.43331228315720466,"score_spread":0.28228552542257274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781188568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96353096,0.00026256414,0.03350349,0.0010404807,0.00007685655,0.0011106933,9.2445123e-7,0.000054967753,0.00041908876],"genre_scores_gemma":[0.9975274,0.000006910717,0.0020951387,0.00010606549,0.00008841607,0.00013197049,0.000005578685,0.000016877502,0.000021613481],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99830383,0.00013567631,0.00028248373,0.0002647156,0.00085049286,0.0001627923],"domain_scores_gemma":[0.9987073,0.00017476754,0.0002500104,0.00068124,0.00011163924,0.00007504291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015433143,0.000102652266,0.000238891,0.000059802904,0.00026807567,0.000032978594,0.00017729467,0.000023826002,0.000021080396],"category_scores_gemma":[0.0009338242,0.00006720362,0.00004179648,0.00008766915,0.00018297508,0.00012927133,0.00013850193,0.00023724818,0.0000022577165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001111341,0.00019382405,0.85095215,0.000037790418,0.000013610307,0.000003821389,0.0003057662,0.00003007883,0.006956428,0.000021295571,0.00016504269,0.14120904],"study_design_scores_gemma":[0.0018685068,0.0001402932,0.88046587,0.00044215933,0.00039278966,0.00002339585,0.001336532,0.11074181,0.003979761,0.000115310635,0.00036352105,0.00013006762],"about_ca_topic_score_codex":0.00026234367,"about_ca_topic_score_gemma":0.00018838688,"teacher_disagreement_score":0.14107896,"about_ca_system_score_codex":0.00010929105,"about_ca_system_score_gemma":0.00018149556,"threshold_uncertainty_score":0.27404842},"labels":[],"label_agreement":null},{"id":"W2781983970","doi":"10.1016/j.eplepsyres.2018.01.008","title":"Longitudinal hippocampal and extra-hippocampal microstructural and macrostructural changes following temporal lobe epilepsy surgery","year":2018,"lang":"en","type":"article","venue":"Epilepsy Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; University of Alberta","keywords":"Fornix; Mammillary body; Temporal lobe; Fractional anisotropy; Diffusion MRI; Epilepsy surgery; Hippocampus; Hippocampal formation; Epilepsy; Hippocampal sclerosis; Medicine; Psychology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.16147041313139757,"score_gpt":0.4221222310652415,"score_spread":0.26065181793384395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781983970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932763,0.0008367406,0.00024556174,0.004064328,0.00021240464,0.00076288125,0.000040544004,0.00020549784,0.0003557221],"genre_scores_gemma":[0.9899394,0.00025588938,0.008004681,0.00029586858,0.00082588673,0.00008846452,0.000063062704,0.00006663604,0.00046010714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969695,0.0001628173,0.00036714593,0.0008885579,0.0006188648,0.0009930938],"domain_scores_gemma":[0.9981018,0.0004758352,0.00008831895,0.00059596525,0.00027520515,0.0004629062],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010253607,0.00032115987,0.00053877424,0.00038124042,0.0007720456,0.00016668533,0.00019101986,0.00015758428,0.00014248995],"category_scores_gemma":[0.00034898636,0.00027898457,0.00012005293,0.0006120749,0.0014340425,0.00020413913,0.0003559872,0.0008087924,0.000024589988],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034322398,0.00003735581,0.90656495,0.0001158354,0.00004324874,0.00019271833,0.00031202743,4.010854e-8,0.046567153,0.00037186503,0.00538971,0.040061876],"study_design_scores_gemma":[0.0011551366,0.0007918854,0.9555589,0.00028952505,0.000058062044,0.0018030434,0.00035432758,0.00023286647,0.01846171,0.0073941527,0.0133737875,0.0005266354],"about_ca_topic_score_codex":0.00013624952,"about_ca_topic_score_gemma":0.000059118818,"teacher_disagreement_score":0.048993923,"about_ca_system_score_codex":0.0000815178,"about_ca_system_score_gemma":0.00012179167,"threshold_uncertainty_score":0.9999662},"labels":[],"label_agreement":null},{"id":"W2782258118","doi":"10.1007/s11548-017-1699-x","title":"Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection","year":2018,"lang":"en","type":"article","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Tractography; Diffusion MRI; Medicine; Brain tumor; Craniotomy; Radiology; Neuronavigation; Surgical planning; Intraoperative MRI; Magnetic resonance imaging; Pathology; Interventional magnetic resonance imaging","score_opus":0.051637209771576036,"score_gpt":0.35072452097686196,"score_spread":0.2990873112052859,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782258118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95654714,0.000103564285,0.041618414,0.0011407415,0.00044572118,0.00006239033,0.0000029324901,0.000014046597,0.00006506218],"genre_scores_gemma":[0.98275596,0.00027695435,0.016157607,0.0003144645,0.0004695482,0.0000018993537,0.000014636327,0.000005874519,0.000003034048],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990523,0.00004569594,0.0005722671,0.00009249642,0.00015261062,0.00008463998],"domain_scores_gemma":[0.9988117,0.00029606483,0.00036412934,0.000080413374,0.00040332228,0.000044360135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035143743,0.0000726105,0.0002552455,0.00066860113,0.000024811552,0.000008463564,0.000083653715,0.00007021566,0.000007483715],"category_scores_gemma":[0.000062887884,0.000060790753,0.000118683194,0.00020325083,0.0001591453,0.00014155713,0.000014129049,0.0001846826,4.4562626e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014214931,0.0009522368,0.90705794,0.000068201545,0.0004147472,0.00024372374,0.0004664284,0.00008124584,0.047938228,0.00062745664,0.00689064,0.03383763],"study_design_scores_gemma":[0.0010290988,0.0003821883,0.9589948,0.00033754794,0.000032602602,0.018651154,0.000021981004,0.0027807707,0.013772002,0.0011792214,0.002716258,0.00010239302],"about_ca_topic_score_codex":0.0000054908737,"about_ca_topic_score_gemma":0.0000022691688,"teacher_disagreement_score":0.051936813,"about_ca_system_score_codex":0.000030336536,"about_ca_system_score_gemma":0.00004840691,"threshold_uncertainty_score":0.2478975},"labels":[],"label_agreement":null},{"id":"W2782477562","doi":"10.1016/j.neuroimage.2017.12.097","title":"The development of brain white matter microstructure","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":637,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; National Institute of Mental Health; Alberta Children's Hospital Research Institute; National Institutes of Health; Bill and Melinda Gates Foundation","keywords":"White matter; Microstructure; Brain development; Neuroscience; Psychology; Medicine; Materials science; Metallurgy; Magnetic resonance imaging; Radiology","score_opus":0.08773591416304627,"score_gpt":0.39908749152442524,"score_spread":0.311351577361379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782477562","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017025952,0.99195504,0.001322651,0.0011669139,0.0001290725,0.0014316107,0.00005366879,0.0001319058,0.0037921031],"genre_scores_gemma":[0.00000407274,0.9679067,0.02508192,0.00079195335,0.00015701716,0.000138536,0.000076388766,0.00011371438,0.005729657],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985278,0.00004996745,0.00061127817,0.00040544098,0.00017034,0.00023512621],"domain_scores_gemma":[0.9984208,0.00014078313,0.00035778026,0.0009367546,0.000078506586,0.00006541561],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012626727,0.00029454406,0.00071534945,0.00007550603,0.00017296185,0.000024727435,0.00034277944,0.00010873847,0.00006907514],"category_scores_gemma":[0.000051452993,0.00017732332,0.00025113916,0.0002371145,0.00021481977,0.000023535726,0.00017875877,0.0004340794,0.00015778233],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009893043,0.000044886474,0.00007914095,0.0074761515,0.00004811085,0.000014398411,0.00006548114,1.0947842e-8,0.00017813608,0.00006619719,0.14893433,0.84308326],"study_design_scores_gemma":[0.00006875582,0.000024732519,0.00040193115,0.0017648631,0.00013419105,0.00017378561,0.0000016224208,4.188459e-7,0.00007749234,0.000061960935,0.99715686,0.00013339275],"about_ca_topic_score_codex":2.1472422e-7,"about_ca_topic_score_gemma":5.812503e-7,"teacher_disagreement_score":0.8482225,"about_ca_system_score_codex":0.000033521133,"about_ca_system_score_gemma":0.0001922736,"threshold_uncertainty_score":0.7231035},"labels":[],"label_agreement":null},{"id":"W2782642508","doi":"10.1159/000480766","title":"Diffusion Tensor Imaging of the Basal Ganglia for Functional Neurosurgery Applications","year":2018,"lang":"en","type":"review","venue":"Progress in neurological surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Medicine; Tractography; Neuroscience; Deep brain stimulation; Neurosurgery; White matter; Basal ganglia; Medical physics; Radiology; Magnetic resonance imaging; Pathology; Psychology; Central nervous system; Internal medicine","score_opus":0.1638321474368537,"score_gpt":0.3919044344635699,"score_spread":0.22807228702671617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782642508","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00052678736,0.9906608,0.0018038317,0.0017280682,0.00039017474,0.0044560554,0.00012181556,0.000254335,0.0000581263],"genre_scores_gemma":[0.0015141804,0.9863016,0.0013568039,0.0013943354,0.000766017,0.008292208,0.00016863423,0.00012310065,0.00008313021],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99735916,0.00015812571,0.0010236144,0.00076727866,0.0002884622,0.0004033341],"domain_scores_gemma":[0.9963079,0.0020199723,0.00066846446,0.000772899,0.00015180554,0.000078961195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003680419,0.00037619736,0.0013428897,0.00023903011,0.00014456519,0.000018948229,0.00027775968,0.0002041868,0.000023348244],"category_scores_gemma":[0.00038107258,0.0002293282,0.0010162803,0.0007626291,0.000595354,0.00003867328,0.000249785,0.00055662234,0.0000049015066],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101642676,0.0007562077,0.24565239,0.0050363084,0.000016014728,0.000025053123,0.0000010814647,3.7721875e-7,0.0000021957073,0.00067061477,0.0077334223,0.7400047],"study_design_scores_gemma":[0.00012339883,0.00004062482,0.027606543,0.0016701475,0.0002569459,0.000083935665,3.7005327e-7,0.00010450748,0.0000067306205,0.0031629119,0.96670765,0.00023626447],"about_ca_topic_score_codex":7.5041277e-7,"about_ca_topic_score_gemma":1.8096004e-7,"teacher_disagreement_score":0.9589742,"about_ca_system_score_codex":0.000023873974,"about_ca_system_score_gemma":0.00012605077,"threshold_uncertainty_score":0.9351733},"labels":[],"label_agreement":null},{"id":"W2783800543","doi":"10.1002/nbm.3868","title":"Can <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratio be used as a myelin‐specific measure in subcortical structures? Comparisons between FSE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios, GRASE‐based <i>T</i><sub>1</sub>w/<i>T</i><sub>2</sub>w ratios and multi‐echo GRASE‐based myelin water fractions","year":2018,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":83,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Manitoba Health; Health Sciences Centre","funders":"Canadian Institutes of Health Research","keywords":"White matter; Nuclear medicine; Nuclear magnetic resonance; Linear regression; Magnetic resonance imaging; Physics; Mathematics; Medicine; Statistics; Radiology","score_opus":0.06212933630555088,"score_gpt":0.32809298493096456,"score_spread":0.26596364862541366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783800543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8851681,0.0014900869,0.07050947,0.021438243,0.0020548855,0.013043618,0.00289597,0.0032643226,0.0001353037],"genre_scores_gemma":[0.9511559,0.002828922,0.0062015457,0.017853202,0.004498701,0.00425731,0.011424097,0.0017646797,0.000015629308],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9646063,0.0028614092,0.009531062,0.008763811,0.0068294373,0.007407982],"domain_scores_gemma":[0.9760512,0.0038686728,0.0035914958,0.0073914477,0.003654515,0.005442663],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity"],"consensus_categories":["metaepi_narrow","sts","research_integrity"],"category_scores_codex":[0.0053458763,0.0066013113,0.007771584,0.006578996,0.0034104711,0.0010661441,0.0031220913,0.003946176,0.000107049236],"category_scores_gemma":[0.0028841381,0.006405827,0.002135009,0.010054746,0.0064671305,0.0021935364,0.0011899822,0.0091232415,0.00059774594],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031048828,0.004443395,0.01152788,0.0010231241,0.00058544613,0.0010681747,0.0011086825,0.00088136876,0.93707794,0.00025612133,0.024573259,0.014349747],"study_design_scores_gemma":[0.029252961,0.0035249798,0.01378646,0.0028538508,0.002223653,0.0004996618,0.0007208639,0.011347928,0.91886556,0.0014538685,0.009639669,0.005830523],"about_ca_topic_score_codex":0.0004995481,"about_ca_topic_score_gemma":0.0046909535,"teacher_disagreement_score":0.06598782,"about_ca_system_score_codex":0.003452674,"about_ca_system_score_gemma":0.0042287563,"threshold_uncertainty_score":0.99997085},"labels":[],"label_agreement":null},{"id":"W2784595116","doi":"10.1177/1759091417753802","title":"Stuck in a State of Inattention? Functional Hyperconnectivity as an Indicator of Disturbed Intrinsic Brain Dynamics in Adolescents with Concussion: A Pilot Study","year":2018,"lang":"en","type":"article","venue":"ASN NEURO","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Concussion; Functional magnetic resonance imaging; Resting state fMRI; Psychology; Diffusion MRI; Neuroscience; Brain activity and meditation; Poison control; Brain Structure and Function; Physical medicine and rehabilitation; Neuroimaging; Medicine; Magnetic resonance imaging; Electroencephalography; Injury prevention","score_opus":0.03877808274899654,"score_gpt":0.334348101531653,"score_spread":0.2955700187826565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2784595116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971298,0.000003913931,0.0011726945,0.00057636003,0.000024134488,0.0009690301,0.000013031195,0.000044344153,0.00006666993],"genre_scores_gemma":[0.999294,0.0000026793023,0.00022548283,0.00034645974,0.000017695213,0.00006364067,0.000009655255,0.000021938642,0.000018484427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887085,0.00010292123,0.0003094675,0.00034661003,0.00022864419,0.00014152867],"domain_scores_gemma":[0.99926615,0.000059866954,0.00016078274,0.00035790022,0.000088820605,0.000066459535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016377069,0.000121988945,0.0002711234,0.00023243963,0.000029041998,0.000004017649,0.00009745748,0.000017252478,0.0000071298],"category_scores_gemma":[0.00012630904,0.00010116247,0.000019203215,0.0005129575,0.00017942104,0.00010551859,0.000069453956,0.00023723127,0.000002133437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014777604,0.005213049,0.9829539,0.000049437764,0.000008568328,0.00003720372,0.00015540175,0.000004129707,0.0060199965,0.00034908517,0.00001816281,0.0037133025],"study_design_scores_gemma":[0.00277767,0.0072544944,0.9872141,0.00016419399,0.000016880347,0.000026033904,0.00016927291,0.00039353032,0.0011292815,0.00075248204,0.000015771377,0.00008628059],"about_ca_topic_score_codex":0.0001866535,"about_ca_topic_score_gemma":0.0008207331,"teacher_disagreement_score":0.0048907152,"about_ca_system_score_codex":0.00007463426,"about_ca_system_score_gemma":0.00007542274,"threshold_uncertainty_score":0.41252857},"labels":[],"label_agreement":null},{"id":"W2785040294","doi":"","title":"Relevance of exosomes with structural changes of white matter and cognitive impairment in patients with PD","year":2017,"lang":"en","type":"article","venue":"Biomedical Research-tokyo","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; White matter; Fractional anisotropy; Diffusion MRI; Internal medicine; Montreal Cognitive Assessment; Medicine; Parkinson's disease; Exacerbation; Rating scale; Atrophy; Cognition; Psychology; Cardiology; Dementia; Gastroenterology; Pathology; Magnetic resonance imaging; Disease; Psychiatry; Radiology; Developmental psychology","score_opus":0.06808585921757733,"score_gpt":0.4094118734857848,"score_spread":0.34132601426820747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2785040294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99496645,0.000048456375,0.00014016876,0.0038581386,0.0000061823953,0.00067685085,0.000054734053,0.000011417168,0.00023762444],"genre_scores_gemma":[0.9969721,0.00005324038,0.0026644417,0.000059200964,0.000019439196,0.000059002392,0.000018945153,0.000014815816,0.00013881315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99869823,0.000031107615,0.00015255717,0.0002478021,0.00061829074,0.00025199374],"domain_scores_gemma":[0.9990228,0.00011690125,0.00011561226,0.00034543793,0.00025256374,0.00014671945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018787387,0.000092594484,0.00023079943,0.00016927479,0.000116524745,0.0000087305725,0.00013820024,0.00004291034,0.000045889097],"category_scores_gemma":[0.00018780479,0.000057527108,0.0000128788215,0.00015615142,0.0016448871,0.00006652511,0.00019549143,0.00023507625,0.0000012096918],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012257597,0.00023427064,0.988106,0.00023868705,0.000021602427,0.000021728612,0.00021605521,4.412462e-8,0.0006655011,0.00008479339,0.0002820194,0.008903539],"study_design_scores_gemma":[0.002142293,0.0017616411,0.9927305,0.0007786516,0.000012892013,0.000005311651,0.000059550184,0.000025139363,0.001746071,0.00032652807,0.00034809273,0.00006333021],"about_ca_topic_score_codex":0.000053734333,"about_ca_topic_score_gemma":0.00001753015,"teacher_disagreement_score":0.008840209,"about_ca_system_score_codex":0.000023484445,"about_ca_system_score_gemma":0.000056048662,"threshold_uncertainty_score":0.6060655},"labels":[],"label_agreement":null},{"id":"W2787874265","doi":"10.1007/s11548-018-1706-x","title":"Correction to: Nonlinear deformation of tractography in ultrasound-guided low-grade gliomas resection","year":2018,"lang":"en","type":"erratum","venue":"International Journal of Computer Assisted Radiology and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Acknowledgement; Tractography; Computer science; Medical physics; Medicine; Diffusion MRI; Radiology; Computer security; Magnetic resonance imaging","score_opus":0.041925504605143826,"score_gpt":0.3450086749760189,"score_spread":0.30308317037087507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2787874265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70313996,0.0015469197,0.17287022,0.0061087618,0.11359508,0.000915167,0.00007526665,0.00014236801,0.0016062228],"genre_scores_gemma":[0.93374205,0.0065231347,0.041767646,0.0023267732,0.012947445,0.00003869547,0.0010354156,0.00010386525,0.0015149533],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99817353,0.000090775895,0.0010628209,0.00020848273,0.00031860924,0.00014580527],"domain_scores_gemma":[0.9975356,0.00050879753,0.0009162577,0.00015590858,0.0007912228,0.00009221623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005261187,0.0001838721,0.00062763086,0.0018044709,0.00003710453,0.000020682539,0.00016833296,0.00026728294,0.000011181765],"category_scores_gemma":[0.00021670172,0.00016375592,0.00028007902,0.00037748922,0.00013115011,0.00015063591,0.000032623146,0.0007757186,0.0000010518751],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007149914,0.0003898514,0.032318622,0.00009143303,0.00033447985,0.0001456795,0.0001607782,0.000089430156,0.0015241025,0.000020830277,0.953515,0.010694803],"study_design_scores_gemma":[0.0016817498,0.0012607535,0.75443786,0.005243443,0.00021935932,0.05172605,0.000045130993,0.0072778687,0.0027142796,0.000681989,0.17419696,0.00051454216],"about_ca_topic_score_codex":0.00001888926,"about_ca_topic_score_gemma":0.0000118104645,"teacher_disagreement_score":0.77931803,"about_ca_system_score_codex":0.00011879542,"about_ca_system_score_gemma":0.00019161768,"threshold_uncertainty_score":0.66777724},"labels":[],"label_agreement":null},{"id":"W2788141036","doi":"10.1016/j.nicl.2018.01.033","title":"Telomere length and advanced diffusion MRI as biomarkers for repetitive mild traumatic brain injury in adolescent rats","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"National Health and Medical Research Council; Medical Research Council; Alberta Children's Hospital Foundation; National Imaging Facility; Children's Hospital Foundation","keywords":"Traumatic brain injury; Medicine; Diffusion MRI; Corpus callosum; Pathology; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.14806788697070153,"score_gpt":0.4690715258704526,"score_spread":0.32100363889975103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788141036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9784847,0.00005482967,0.0036285138,0.014286492,0.00015912036,0.0020582404,0.000032250955,0.00022127986,0.0010745818],"genre_scores_gemma":[0.9669266,0.0005963775,0.022488134,0.00922976,0.00024537707,0.00017332872,0.00002113526,0.0000687087,0.0002506156],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99792457,0.000113805974,0.0006926239,0.00079790415,0.00015880443,0.00031228675],"domain_scores_gemma":[0.9982647,0.000679133,0.00016962798,0.0005701243,0.00011064466,0.0002057745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044520228,0.00021459121,0.00043559753,0.00012570697,0.00011154747,0.00001840941,0.00012676798,0.000116386065,0.000021806505],"category_scores_gemma":[0.0016735941,0.00019550645,0.00013450396,0.00024548077,0.0004962988,0.00010217278,0.000114100265,0.00042114384,0.000016624754],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009054159,0.0046992614,0.1020997,0.00072471035,0.000077296725,0.00021040808,0.00048520055,8.213958e-7,0.19651166,0.003132847,0.04029523,0.6427087],"study_design_scores_gemma":[0.009488858,0.0074905087,0.83622485,0.0013872733,0.00016136657,0.00014706816,0.00025113608,0.0036985122,0.01860205,0.007005483,0.11475847,0.0007844029],"about_ca_topic_score_codex":0.0000044111684,"about_ca_topic_score_gemma":0.000005695771,"teacher_disagreement_score":0.7341252,"about_ca_system_score_codex":0.000031583048,"about_ca_system_score_gemma":0.000058379843,"threshold_uncertainty_score":0.7972522},"labels":[],"label_agreement":null},{"id":"W2788415044","doi":"10.1101/251108","title":"A population-based atlas of the human pyramidal tract in 410 healthy participants","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Pyramidal tracts; Atlas (anatomy); Diffusion MRI; Fiber tract; Corticospinal tract; Brain atlas","score_opus":0.07034661507362043,"score_gpt":0.3413616496605835,"score_spread":0.2710150345869631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788415044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99637604,0.00008615702,0.0006258229,0.0011017992,0.00016772063,0.0013033743,0.0000914984,0.00024049317,0.0000071234826],"genre_scores_gemma":[0.99328995,0.000013720112,0.005613987,0.0005040056,0.00017709362,0.0003145657,7.536122e-7,0.00008347898,0.0000024698136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99789673,0.00008759073,0.00066042424,0.00062333164,0.0003185493,0.000413346],"domain_scores_gemma":[0.997484,0.000056753353,0.00051213603,0.0015462729,0.00023819803,0.00016263434],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035054772,0.00030667105,0.00053395046,0.00019066254,0.00012524746,0.000024038482,0.00033199083,0.00026000565,0.000023042165],"category_scores_gemma":[0.00020012193,0.0002648128,0.00015504746,0.0005006859,0.0001726116,0.000042707245,0.00018432998,0.0007275882,0.0000063174166],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048529902,0.0006273374,0.81295204,0.00046759288,0.000021425856,0.000011575839,0.00000620639,0.000096088115,0.18491039,0.0007254208,0.00013106255,0.0000023298091],"study_design_scores_gemma":[0.0005407441,0.00008183258,0.917433,0.00066002953,0.00007210443,1.2520745e-8,5.126179e-7,0.00084007316,0.07957163,0.000025483829,0.00055302324,0.00022152616],"about_ca_topic_score_codex":0.00024415457,"about_ca_topic_score_gemma":0.000010366133,"teacher_disagreement_score":0.10533877,"about_ca_system_score_codex":0.0002502577,"about_ca_system_score_gemma":0.00048375368,"threshold_uncertainty_score":0.9999804},"labels":[],"label_agreement":null},{"id":"W2789296617","doi":"10.1101/282434","title":"Axons morphometry in the human spinal cord","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Axon; Spinal cord; Anatomy; Myelin; Neuroscience; Magnetic resonance imaging; Biology; Central nervous system; Medicine; Radiology","score_opus":0.071882110216865,"score_gpt":0.3414459069492006,"score_spread":0.26956379673233555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789296617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9819261,0.00040886865,0.011508485,0.00288709,0.00030409027,0.0019530809,0.00010972663,0.00075320975,0.00014934852],"genre_scores_gemma":[0.97803986,0.00012659274,0.019322649,0.0012681364,0.000587526,0.0005483688,6.064924e-7,0.00009962354,0.0000066276857],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99782073,0.00007692867,0.00046164045,0.00083086925,0.00036768592,0.00044215878],"domain_scores_gemma":[0.99728334,0.00004156098,0.00026893133,0.0020525132,0.00020506249,0.00014859842],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048744227,0.0004047474,0.00046846364,0.0003522643,0.00019910783,0.00009188986,0.0006682401,0.00028993562,0.00004604032],"category_scores_gemma":[0.00012954336,0.00034552408,0.00014810417,0.00076060614,0.00028097795,0.000058558726,0.0003831723,0.0012949558,0.00005653751],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023609262,0.0014605504,0.06684047,0.000988313,0.00013731504,0.00059307483,0.0000145913,0.0000040759355,0.8888607,0.02348246,0.017362712,0.000019616677],"study_design_scores_gemma":[0.0010687548,0.00080051983,0.8513224,0.0015648227,0.00030951566,5.548392e-7,0.000008726152,0.00015152062,0.083516695,0.00031225616,0.059810117,0.0011340792],"about_ca_topic_score_codex":0.000037486294,"about_ca_topic_score_gemma":0.0000012616707,"teacher_disagreement_score":0.80534405,"about_ca_system_score_codex":0.00024714382,"about_ca_system_score_gemma":0.00022074403,"threshold_uncertainty_score":0.9998997},"labels":[],"label_agreement":null},{"id":"W2789780381","doi":"10.1002/dev.21610","title":"Auditory structural connectivity in preterm and healthy term infants during the first postnatal year","year":2018,"lang":"en","type":"article","venue":"Developmental Psychobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children’s Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Canada Excellence Research Chairs, Government of Canada; Health Research Board; Natural Sciences and Engineering Research Council of Canada; Children's Health Research Institute","keywords":"Magnetic resonance imaging; Gestational age; White matter; Fractional anisotropy; Diffusion MRI; Brainstem; Tractography; Psychology; Audiology; Language development; Auditory pathways; Medicine; Pediatrics; Developmental psychology; Neuroscience; Pregnancy; Biology; Radiology","score_opus":0.029052862095500377,"score_gpt":0.34578539565578503,"score_spread":0.31673253356028463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789780381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976136,0.000027893413,0.000019548519,0.0011281306,0.00016911155,0.0003631905,0.000013831163,0.000055963203,0.0006086966],"genre_scores_gemma":[0.9970925,0.00002726773,0.0017081139,0.0009468148,0.00013474729,0.00003439211,0.000011724207,0.000009926569,0.00003453107],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993719,0.000015292442,0.00014210462,0.00024971325,0.000037947706,0.00018302641],"domain_scores_gemma":[0.99972296,0.000037547867,0.00004378896,0.00013827688,0.000016084306,0.000041317562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000552674,0.00009318303,0.000119931356,0.000049575163,0.00015068562,0.0000052767396,0.00007494293,0.000051522107,0.000037828268],"category_scores_gemma":[0.000018573353,0.000068149966,0.000013650446,0.000081902865,0.00026847937,0.000040978994,0.00007622061,0.00015854542,0.000011570573],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004155057,0.000028180282,0.9820789,0.0000264299,0.000013696668,0.000013064968,0.00050155737,3.1879768e-8,0.013787659,0.00013752953,0.00070757244,0.002289843],"study_design_scores_gemma":[0.00073377485,0.00011660601,0.9941086,0.000024318444,0.0000022931454,0.0004769871,0.000030350198,0.000006320878,0.0014740891,0.00016963201,0.0027779094,0.00007910388],"about_ca_topic_score_codex":0.000015758316,"about_ca_topic_score_gemma":0.00006873262,"teacher_disagreement_score":0.01231357,"about_ca_system_score_codex":0.00007190556,"about_ca_system_score_gemma":0.00002762463,"threshold_uncertainty_score":0.2779075},"labels":[],"label_agreement":null},{"id":"W2789795746","doi":"10.3389/fmed.2018.00031","title":"Quantitative Ex Vivo MRI Changes due to Progressive Formalin Fixation in Whole Human Brain Specimens: Longitudinal Characterization of Diffusion, Relaxometry, and Myelin Water Fraction Measurements at 3T","year":2018,"lang":"en","type":"article","venue":"Frontiers in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"Siemens Healthineers; University of Memphis; University of Manitoba; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Health Sciences Centre Foundation","keywords":"Relaxometry; Myelin; Ex vivo; Nuclear magnetic resonance; Diffusion MRI; Fixation (population genetics); Characterization (materials science); Pathology; Magnetic resonance imaging; In vivo; Chemistry; Medicine; Materials science; Biology; Central nervous system; Radiology; Internal medicine; Spin echo; Biochemistry","score_opus":0.07882573708557716,"score_gpt":0.3678608864943389,"score_spread":0.28903514940876174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2789795746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89049745,0.000116477444,0.09104714,0.016944444,0.00015101301,0.0010993471,0.00000973576,0.000035551573,0.0000988241],"genre_scores_gemma":[0.9777002,0.00007438144,0.020396823,0.0007594304,0.00022966006,0.00013597946,0.00022900525,0.00002832469,0.00044622822],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986679,0.000055926932,0.00039973366,0.00034438158,0.00031584216,0.00021622205],"domain_scores_gemma":[0.999303,0.000021675749,0.00019413503,0.0002101392,0.0001912555,0.0000798386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004468881,0.00015502666,0.00041058767,0.00058233,0.00008585918,0.0000047717194,0.0000682665,0.000076198994,0.00006154213],"category_scores_gemma":[0.00016482975,0.00011913844,0.000016548156,0.00041592272,0.00020220058,0.00013035715,0.00006518098,0.0001479293,0.0000039689194],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040356102,0.00012766563,0.10276099,0.000079050544,0.000014656272,0.000012485232,0.0018300054,8.1683294e-7,0.8882048,0.000067762136,0.0046135886,0.0018845818],"study_design_scores_gemma":[0.003248885,0.0026977516,0.692449,0.0015840518,0.0000692193,0.00003334488,0.00070615206,0.0011765683,0.2863757,0.0014921168,0.009907407,0.0002598106],"about_ca_topic_score_codex":0.00004204013,"about_ca_topic_score_gemma":0.00007464156,"teacher_disagreement_score":0.6018291,"about_ca_system_score_codex":0.00018571067,"about_ca_system_score_gemma":0.000008914678,"threshold_uncertainty_score":0.48583248},"labels":[],"label_agreement":null},{"id":"W2790018820","doi":"10.1101/256933","title":"Relationships between Human Brain Structural Connectomes and Traits","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Connectome; Human Connectome Project; Human brain; Computer science; Artificial intelligence; Neuroscience; Psychology; Resting state fMRI; Pattern recognition (psychology); Cognitive psychology; Functional connectivity","score_opus":0.07574890596280866,"score_gpt":0.3235845401569406,"score_spread":0.24783563419413196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790018820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926789,0.00026753807,0.002661417,0.0021501125,0.0000862143,0.000999771,0.00023964324,0.00089078315,0.000025624424],"genre_scores_gemma":[0.9717868,0.00004100069,0.027003605,0.00025028907,0.0006500394,0.00013751398,0.0000025047298,0.00011663516,0.0000116250685],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980038,0.00009335125,0.0004427069,0.0008727724,0.00023343378,0.0003539414],"domain_scores_gemma":[0.9980775,0.00014974116,0.0002916646,0.0008705538,0.00028725804,0.000323294],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00034328736,0.00041195037,0.0005502839,0.00023345671,0.00037934427,0.000091161906,0.00023468034,0.000413271,0.00002633019],"category_scores_gemma":[0.00033116384,0.00042402805,0.00009679128,0.00028379902,0.0003064568,0.000116993106,0.00031279254,0.001169474,0.000012088782],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027743492,0.00007213139,0.30560043,0.00072657433,0.00022609049,0.000044389955,0.00003475758,0.0000022066947,0.676735,0.013683664,0.002833478,0.000013540403],"study_design_scores_gemma":[0.0004989125,0.00008462184,0.95358837,0.00035411617,0.00019584797,1.08719625e-7,0.0000017593972,0.00007305353,0.038789332,0.00019349306,0.0057366644,0.0004837175],"about_ca_topic_score_codex":0.000009595882,"about_ca_topic_score_gemma":6.8048786e-7,"teacher_disagreement_score":0.64798796,"about_ca_system_score_codex":0.0001124938,"about_ca_system_score_gemma":0.00015757597,"threshold_uncertainty_score":0.9998211},"labels":[],"label_agreement":null},{"id":"W2790175756","doi":"10.1111/ejn.13841","title":"White matter microstructural organisation of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults","year":2018,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek","keywords":"White matter; Motor learning; Psychology; Premotor cortex; Fractional anisotropy; Primary motor cortex; Neuroscience; Tractography; Motor cortex; Diffusion MRI; Dorsum; Cortex (anatomy); Young adult; Physical medicine and rehabilitation; Developmental psychology; Medicine; Magnetic resonance imaging; Anatomy","score_opus":0.020959953705917047,"score_gpt":0.276564203888547,"score_spread":0.25560425018263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790175756","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99145985,0.000016915934,0.007993209,0.00022667562,0.00006832875,0.00009917432,0.0000021750977,0.000010577845,0.00012307541],"genre_scores_gemma":[0.9979751,0.000030830248,0.0018138795,0.000081348684,0.000032161337,3.544633e-7,6.744976e-7,0.000012392823,0.00005325121],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99918383,0.00007832626,0.000361102,0.00013718454,0.00014789986,0.00009167388],"domain_scores_gemma":[0.99928975,0.00001945106,0.0004079711,0.00009417961,0.00014184757,0.000046826244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016843466,0.00007617151,0.0001464799,0.00009898096,0.000034415865,0.0000112787775,0.000111955174,0.000008537225,0.000010471259],"category_scores_gemma":[0.00009916994,0.000059597765,0.000023890401,0.00016661223,0.00022546022,0.00013632666,0.000065702945,0.0001635387,4.7323152e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047044632,0.000035089415,0.32831907,0.00003139495,6.3496e-7,0.000008702786,0.0009324749,0.000004754828,0.6684179,0.000004117798,0.000027698885,0.0021711246],"study_design_scores_gemma":[0.0005241187,0.0006177402,0.94962156,0.00025173902,0.000007715365,0.00028841847,0.00012014313,0.0005386544,0.0479503,0.000011962181,0.000026544803,0.00004108291],"about_ca_topic_score_codex":8.6624306e-7,"about_ca_topic_score_gemma":2.7486328e-7,"teacher_disagreement_score":0.6213025,"about_ca_system_score_codex":0.0000144632295,"about_ca_system_score_gemma":0.00001368155,"threshold_uncertainty_score":0.24303263},"labels":[],"label_agreement":null},{"id":"W2790520416","doi":"10.1007/s10334-018-0680-1","title":"Toward faster inference of micron-scale axon diameters using Monte Carlo simulations","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Monte Carlo method; Scale (ratio); Cylinder; Axon; Materials science; Diffusion; Physics; Geometry; Mathematics; Statistics; Anatomy","score_opus":0.08719405476780663,"score_gpt":0.38342536726532556,"score_spread":0.29623131249751894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790520416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941887,0.00075136847,0.0039219344,0.0004695677,0.000108856875,0.00033026596,0.000042352483,0.000023408003,0.00016354659],"genre_scores_gemma":[0.99064994,0.00034056656,0.008341857,0.00033708615,0.00024812567,0.000018689898,0.000011870531,0.0000119097485,0.000039932424],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991649,0.000040986,0.0003150814,0.00025213658,0.00005379369,0.00017314317],"domain_scores_gemma":[0.9994544,0.00008341547,0.000099457524,0.00024471912,0.000076721444,0.00004129512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000954776,0.00012566005,0.00037084418,0.000059377682,0.000038131977,0.0000026660412,0.000068300455,0.00006804127,0.000054209842],"category_scores_gemma":[0.00004559589,0.000099051256,0.000015490843,0.00014940198,0.0008113969,0.00003149944,0.000059811762,0.00007500826,0.0000010098795],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009903398,0.00004864351,0.017556297,0.00006172282,0.000002924439,0.000001822191,0.000427275,0.0000035670726,0.9577059,0.0008682952,0.000025837868,0.02319868],"study_design_scores_gemma":[0.00425479,0.0033603865,0.15545096,0.0015327234,0.00018335939,0.00005685717,0.00023642053,0.003949103,0.78742146,0.034975022,0.008094215,0.0004847227],"about_ca_topic_score_codex":0.00015279364,"about_ca_topic_score_gemma":0.0000065877834,"teacher_disagreement_score":0.17028445,"about_ca_system_score_codex":0.000013959406,"about_ca_system_score_gemma":0.00002043866,"threshold_uncertainty_score":0.4039193},"labels":[],"label_agreement":null},{"id":"W2790987263","doi":"10.3389/fnana.2018.00021","title":"Alterations of White Matter Integrity and Hippocampal Functional Connectivity in Type 2 Diabetes Without Mild Cognitive Impairment","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Corpus callosum; White matter; Splenium; Hippocampal formation; Diffusion MRI; Psychology; Montreal Cognitive Assessment; Neuroscience; Audiology; Resting state fMRI; Medicine; Cognition; Magnetic resonance imaging; Internal medicine; Cognitive impairment; Radiology","score_opus":0.030012893694276697,"score_gpt":0.3125346215064711,"score_spread":0.2825217278121944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790987263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906537,0.000082362014,0.006842768,0.0012318218,0.00015411893,0.0004812568,0.000017266457,0.000032373984,0.0005043258],"genre_scores_gemma":[0.99139667,0.000029493487,0.007524779,0.00085062545,0.000042306376,0.000059512244,0.000015757745,0.000014269083,0.00006659017],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992306,0.000048766204,0.00019659933,0.00026958014,0.00009899843,0.0001554532],"domain_scores_gemma":[0.99958503,0.00004621271,0.000060166298,0.00014738427,0.000108657194,0.000052575084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000101934034,0.0001077083,0.00022189613,0.00020085087,0.000055058983,0.000006108937,0.00003982645,0.000042808115,0.000045507542],"category_scores_gemma":[0.000058168054,0.0001028005,0.000024995308,0.00030336078,0.0002376108,0.00009165988,0.000056786288,0.00030158975,0.0000030672743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012692153,0.00014888599,0.99459946,0.000024659248,0.000008553342,0.0000026500772,0.00013097035,0.000001069913,0.00020222968,0.00006932373,0.0041338545,0.00055142917],"study_design_scores_gemma":[0.00093912886,0.00022898044,0.9911,0.00010860723,0.000022765684,0.000008658151,0.00008310095,0.0024563158,0.0021709073,0.002285419,0.00050304836,0.00009305759],"about_ca_topic_score_codex":0.000011876895,"about_ca_topic_score_gemma":0.000012832157,"teacher_disagreement_score":0.003630806,"about_ca_system_score_codex":0.00003944779,"about_ca_system_score_gemma":0.000043078464,"threshold_uncertainty_score":0.41920826},"labels":[],"label_agreement":null},{"id":"W2791053909","doi":"10.1016/j.jneumeth.2018.03.001","title":"Extraction of corticospinal tract microstructural properties in chronic stroke","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Corticospinal tract; Motor impairment; Diffusion MRI; Stroke (engine); Fractional anisotropy; Physical medicine and rehabilitation; Medicine; Structural integrity; Chronic stroke; Magnetic resonance imaging; Physical therapy; Rehabilitation; Radiology","score_opus":0.197772134622818,"score_gpt":0.5022585865306397,"score_spread":0.3044864519078217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791053909","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90341,0.00011984867,0.095595576,0.00046081148,0.00021138725,0.00012246393,0.0000010066561,0.000010510613,0.00006836521],"genre_scores_gemma":[0.81323636,0.00007192728,0.18638326,0.00012665546,0.000106011554,0.0000016481231,4.3819835e-8,0.000006414978,0.000067655004],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990116,0.00008089678,0.00043610265,0.00012984817,0.00019828248,0.00014327992],"domain_scores_gemma":[0.9991668,0.000043647113,0.00039869687,0.00015245042,0.00017657988,0.000061859704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046722914,0.000074360585,0.00021649073,0.00017767117,0.000045263252,0.00001124533,0.0001436991,0.000025725942,0.0000062969534],"category_scores_gemma":[0.00039536462,0.000053299158,0.00007066448,0.00030269317,0.0003495496,0.00022696344,0.000023268649,0.00028207115,2.6051336e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006233193,0.00006707663,0.001205582,0.000015087121,6.549943e-7,0.00001424582,0.000034595774,0.000020208814,0.9691072,0.000020684696,0.000006231772,0.02944609],"study_design_scores_gemma":[0.00027795922,0.001441744,0.33935323,0.00008501274,0.00001679602,0.0019343587,0.00001708946,0.0015740503,0.65230787,0.00022905522,0.0027174377,0.00004541189],"about_ca_topic_score_codex":0.0000037465932,"about_ca_topic_score_gemma":3.1780203e-7,"teacher_disagreement_score":0.33814764,"about_ca_system_score_codex":0.0000828007,"about_ca_system_score_gemma":0.00017861092,"threshold_uncertainty_score":0.21734765},"labels":[],"label_agreement":null},{"id":"W2791224996","doi":"10.1016/j.neuroimage.2018.01.034","title":"High resolution in-vivo diffusion imaging of the human hippocampus","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Hippocampus; Hippocampal formation; Diffusion; Diffusion imaging; Nuclear magnetic resonance; Neuroscience; Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.03556724292426493,"score_gpt":0.33003583117118174,"score_spread":0.2944685882469168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791224996","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911814,0.000018940247,0.0012257985,0.0026141223,0.0000929668,0.0003551876,0.0000063953507,0.00011340877,0.0043917936],"genre_scores_gemma":[0.99626565,0.000012532234,0.0023938026,0.00083441054,0.000103831626,0.00001533942,0.0000020906107,0.000022083312,0.00035027956],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991821,0.000035349196,0.00021766328,0.00024345708,0.0001571232,0.00016430794],"domain_scores_gemma":[0.9991864,0.00002531263,0.00010038394,0.0005864499,0.00006639631,0.00003503172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007933157,0.00009412794,0.00013602317,0.00007813047,0.000121135025,0.00000652346,0.0001517638,0.000023622582,0.000047748013],"category_scores_gemma":[0.00006581878,0.000071177565,0.000056357636,0.00029564285,0.00026038522,0.00005816621,0.00013006286,0.00019407542,0.000005458616],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017320763,0.00011769053,0.052612443,0.000019203158,9.984715e-7,0.000009705526,0.000045479126,0.0000013963221,0.93977875,0.0023782186,0.002719797,0.0022989896],"study_design_scores_gemma":[0.0009903358,0.00014582108,0.7259138,0.00018010475,0.00003100983,0.00008142525,0.000016707136,0.0009650314,0.24759673,0.013417329,0.010525135,0.00013653195],"about_ca_topic_score_codex":0.00006724979,"about_ca_topic_score_gemma":0.000008231871,"teacher_disagreement_score":0.69218206,"about_ca_system_score_codex":0.000029576722,"about_ca_system_score_gemma":0.000017099705,"threshold_uncertainty_score":0.2902537},"labels":[],"label_agreement":null},{"id":"W2791409461","doi":"10.1016/j.neuroimage.2017.12.064","title":"Mapping population-based structural connectomes","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; National Science Foundation; National Institutes of Health; Cancer Prevention and Research Institute of Texas","keywords":"Connectome; Human Connectome Project; Connectomics; Tractography; Computer science; Population; Artificial intelligence; Outlier; Robustness (evolution); Pattern recognition (psychology); Diffusion MRI; Neuroscience; Functional connectivity; Biology; Magnetic resonance imaging","score_opus":0.06870418740974009,"score_gpt":0.367364929209922,"score_spread":0.2986607418001819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791409461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9783037,0.000013461313,0.013764363,0.0030855353,0.00009768035,0.00035603152,0.000011307819,0.000635878,0.003732053],"genre_scores_gemma":[0.9743473,0.0000016156326,0.02192547,0.003198399,0.0002079244,0.00001665804,0.00003321091,0.000027276483,0.0002421474],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992663,0.00001455552,0.0001504817,0.00026890854,0.00012627298,0.00017343681],"domain_scores_gemma":[0.999356,0.000050222374,0.00005492395,0.00038459583,0.00007960718,0.00007466828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032901447,0.0001064776,0.00013382998,0.00009468389,0.00013884471,0.00001845805,0.00007952131,0.000027080288,0.00017119238],"category_scores_gemma":[0.00008905009,0.00009682099,0.000053979642,0.00023615798,0.000080963524,0.000062106024,0.000026024347,0.00012721919,0.000049575632],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014121205,0.00012200904,0.6595881,0.00013230255,0.000020081448,0.00012153523,0.00014384245,0.00001983177,0.2967681,0.00619876,0.008223895,0.028520314],"study_design_scores_gemma":[0.00063638313,0.00017372389,0.94837934,0.000036126832,0.000016160997,0.00007914031,0.000009440792,0.00747325,0.01771793,0.0020813465,0.023226222,0.00017095992],"about_ca_topic_score_codex":0.000018964645,"about_ca_topic_score_gemma":0.0000013821651,"teacher_disagreement_score":0.2887912,"about_ca_system_score_codex":0.000022402364,"about_ca_system_score_gemma":0.000022499384,"threshold_uncertainty_score":0.39482456},"labels":[],"label_agreement":null},{"id":"W2791545517","doi":"10.1117/12.2293566","title":"Design and evaluation of a diffusion MRI fibre phantom using 3D printing","year":2018,"lang":"en","type":"article","venue":"Medical Imaging 2018: Physics of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Imaging phantom; 3D printing; Diffusion; Computer science; Biomedical engineering; Materials science; Engineering; Optics; Physics; Composite material","score_opus":0.09184233710314892,"score_gpt":0.4189484282336127,"score_spread":0.3271060911304638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791545517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14133225,0.0005494766,0.8510073,0.0058593126,0.00015053374,0.00060487224,0.00000289153,0.00014006827,0.0003533104],"genre_scores_gemma":[0.88976943,0.0002020026,0.108392134,0.00087881426,0.0006480087,0.000026403037,0.0000127897165,0.00006059735,0.000009797059],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9948555,0.00019808217,0.00074550096,0.00055862643,0.0032090084,0.00043323278],"domain_scores_gemma":[0.9975991,0.00034363515,0.00039446232,0.0005410291,0.00065814954,0.0004636254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030233802,0.00026697892,0.00055611145,0.00014967292,0.00016297767,0.000022914806,0.00035433364,0.0000985483,0.00020470921],"category_scores_gemma":[0.0014835307,0.00023451653,0.00009995949,0.0004196306,0.0015334598,0.000256133,0.0004433443,0.0005243641,0.000004139894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006510853,0.00053681113,0.014588543,0.00034720078,0.000051839354,0.000032345477,0.00053546677,0.000025458025,0.0802704,0.0005186013,0.0013061892,0.901722],"study_design_scores_gemma":[0.0018638341,0.00004573105,0.001074386,0.0021468576,0.00028311368,0.0002111065,0.000089930465,0.9623891,0.02682339,0.0041533182,0.0007134126,0.00020583835],"about_ca_topic_score_codex":0.000100153935,"about_ca_topic_score_gemma":5.278529e-7,"teacher_disagreement_score":0.9623636,"about_ca_system_score_codex":0.000077161196,"about_ca_system_score_gemma":0.0005207501,"threshold_uncertainty_score":0.95633066},"labels":[],"label_agreement":null},{"id":"W2791687065","doi":"10.1016/j.media.2018.03.004","title":"Riemannian metric optimization on surfaces (RMOS) for intrinsic brain mapping in the Laplace–Beltrami embedding space","year":2018,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; Foundation of the American Society of Neuroradiology; National Institutes of Health; BioClinica; National Eye Institute; National Institute on Aging; Alzheimer's Association; AbbVie; Biogen; American Society of Neuroradiology; Northern California Institute for Research and Education; Alzheimer's Drug Discovery Foundation; U.S. Department of Defense","keywords":"Embedding; Mathematics; Surface (topology); Riemannian geometry; Metric (unit); Polygon mesh; Artificial intelligence; Mathematical analysis; Topology (electrical circuits); Computer science; Algorithm; Geometry; Combinatorics","score_opus":0.04481816951865586,"score_gpt":0.39064356498760916,"score_spread":0.3458253954689533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791687065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029464848,0.000046320667,0.92806625,0.04079919,0.00002068398,0.000501301,0.000007019113,0.00011532663,0.0009790343],"genre_scores_gemma":[0.8735954,0.00008656274,0.11900537,0.006399411,0.0002470413,0.0001388042,0.00009977508,0.00002786607,0.0003997606],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984362,0.0000919804,0.00032210982,0.00038322745,0.0004916364,0.0002748175],"domain_scores_gemma":[0.99844813,0.0007316454,0.000110629946,0.00045832962,0.00013159338,0.00011965613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009907931,0.00014684266,0.0003460532,0.00063625124,0.00018654551,0.000044314176,0.00024186492,0.00008219315,0.0001919019],"category_scores_gemma":[0.0022900852,0.00010355937,0.00017623347,0.0037099712,0.00019086515,0.00008540247,0.0000405819,0.00027312967,0.000012743237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00167313,0.009503272,0.13222064,0.001480782,0.007102303,0.001509689,0.016666116,0.08589549,0.028837796,0.032306124,0.30182648,0.38097817],"study_design_scores_gemma":[0.0012598844,0.00030438456,0.009269896,0.00014143609,0.0008850341,0.000022910886,0.0006600511,0.96275324,0.0015118124,0.0007747775,0.022134796,0.00028179423],"about_ca_topic_score_codex":0.000052331827,"about_ca_topic_score_gemma":0.000029521709,"teacher_disagreement_score":0.87685776,"about_ca_system_score_codex":0.000057277608,"about_ca_system_score_gemma":0.000040498384,"threshold_uncertainty_score":0.42230284},"labels":[],"label_agreement":null},{"id":"W2791791346","doi":"10.4103/0366-6999.226060","title":"Brain Impairment in Chronic Schizophrenia Patients with Depressive Symptoms Differs from Brain Impairment in Chronic Depression Patients with Psychotic Symptoms","year":2018,"lang":"en","type":"article","venue":"Chinese Medical Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Depression (economics); Schizophrenia (object-oriented programming); Depressive symptoms; Psychiatry; Medicine; Psychosis; Chronic depression; Psychology; Internal medicine; Clinical psychology; Anxiety; Cognition","score_opus":0.007124780128962359,"score_gpt":0.2965348584193956,"score_spread":0.28941007829043325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791791346","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99091476,0.00024103817,0.004764592,0.0023493152,0.00015936815,0.001390105,0.00002923605,0.000107543354,0.000044057255],"genre_scores_gemma":[0.9965397,0.000052728465,0.0009939962,0.0013272705,0.0006634174,0.00014932388,0.00016384266,0.00009136601,0.000018338184],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99601054,0.00016249041,0.0008080312,0.0007497236,0.0014903883,0.000778854],"domain_scores_gemma":[0.997746,0.00022652828,0.00039643282,0.0006380103,0.00017700902,0.00081601884],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027501295,0.0005249699,0.00066880154,0.00038126128,0.00021008927,0.000052539704,0.00047686108,0.00020155641,0.00034921846],"category_scores_gemma":[0.00021788377,0.000311691,0.00010190459,0.0006412869,0.0004220274,0.00025260836,0.0001698224,0.0014279322,0.000016667864],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019279699,0.0014053045,0.9679473,0.00004159949,0.00007815713,0.0001424976,0.0001813644,0.00004931156,0.00024105328,0.0000047938192,0.0009441661,0.027036458],"study_design_scores_gemma":[0.028349897,0.003818433,0.9615087,0.0026538954,0.000052933497,0.000077177145,0.00000634278,0.0023848698,0.00008699379,0.00046146638,0.00024274648,0.00035657073],"about_ca_topic_score_codex":0.000065755674,"about_ca_topic_score_gemma":0.00017978264,"teacher_disagreement_score":0.026679888,"about_ca_system_score_codex":0.001588793,"about_ca_system_score_gemma":0.00073085097,"threshold_uncertainty_score":0.99993354},"labels":[],"label_agreement":null},{"id":"W2791995825","doi":"10.1111/jcpp.12879","title":"Diffusion tensor imaging correlates of early markers of depression in youth at high‐familial risk for bipolar disorder","year":2018,"lang":"en","type":"article","venue":"Journal of Child Psychology and Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"Medical Research Council; Fonds de Recherche du Québec - Santé; University of Edinburgh; European Commission; Seventh Framework Programme; Alzheimer Society; Wellcome Trust","keywords":"Fractional anisotropy; Major depressive disorder; Psychology; Bipolar disorder; Mood disorders; Depression (economics); Mood; Psychiatry; Diffusion MRI; Clinical psychology; White matter; Internal medicine; Medicine; Magnetic resonance imaging; Anxiety","score_opus":0.01354712241150179,"score_gpt":0.31979865715293326,"score_spread":0.30625153474143146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791995825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871872,0.0044891615,0.005317756,0.0021091977,0.0004583876,0.00023491516,0.00004150059,0.00000886142,0.0001530266],"genre_scores_gemma":[0.9874514,0.0023972183,0.009496533,0.0004196174,0.00019395746,0.000002707163,0.0000046094833,0.000016955828,0.000017050304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990753,0.00004208923,0.0004942097,0.0001673156,0.00009194592,0.00012914871],"domain_scores_gemma":[0.9989885,0.00006165369,0.0005844163,0.00020281602,0.000103367885,0.000059223104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022350771,0.00010633491,0.00030174645,0.00020081851,0.000082834704,0.0000017481128,0.00009118853,0.00009010449,0.000014373278],"category_scores_gemma":[0.000039034614,0.000081076934,0.00010387604,0.00012650338,0.00021801327,0.000051342748,0.000026004202,0.00029480207,3.6517233e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003059632,0.00029052125,0.98532087,0.000029292882,0.000025350384,8.4620444e-7,0.00017917065,0.0000011192011,0.0010777081,0.000083528175,0.00086593046,0.00906603],"study_design_scores_gemma":[0.0032877324,0.0009903654,0.9895391,0.00037683232,0.00013516971,0.00013237678,0.000061383456,0.000048621358,0.00020124036,0.003348789,0.0018066401,0.00007173385],"about_ca_topic_score_codex":0.000015649179,"about_ca_topic_score_gemma":0.000005541111,"teacher_disagreement_score":0.008994297,"about_ca_system_score_codex":0.0000061560136,"about_ca_system_score_gemma":0.000016591626,"threshold_uncertainty_score":0.33062214},"labels":[],"label_agreement":null},{"id":"W2792160103","doi":"10.1016/j.mri.2018.03.010","title":"T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; University of Alberta; Western University; University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Wellcome Trust; Canada Foundation for Innovation; Research Manitoba","keywords":"Diffusion MRI; Magnetization transfer; White matter; Hippocampus; Hippocampal formation; Magnetic resonance imaging; Pathology; Nuclear magnetic resonance; Neuroscience; Medicine; Biology; Radiology; Physics","score_opus":0.03846721745761758,"score_gpt":0.32534317293207915,"score_spread":0.28687595547446154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792160103","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97380066,0.0056127845,0.016329836,0.003103023,0.000026187827,0.000757966,0.000026897542,0.00009184816,0.00025078695],"genre_scores_gemma":[0.983259,0.00024582655,0.015465542,0.00077569124,0.000028118573,0.000062212894,0.0000061423398,0.00003911191,0.0001183518],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99875575,0.00005503314,0.00030676677,0.00042183977,0.00021344454,0.00024716338],"domain_scores_gemma":[0.99914104,0.00003842073,0.00005540876,0.0005050001,0.00015115608,0.00010896602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000114514805,0.00017466868,0.00019737075,0.00011308236,0.00012601793,0.000024027237,0.00015327301,0.000020582163,0.00001639446],"category_scores_gemma":[0.00006140035,0.00013975737,0.000045474026,0.00029114797,0.0005260977,0.00019763832,0.000073418276,0.00016264513,0.0000012731801],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030912293,0.00029640325,0.62874275,0.00005420302,0.0000019498602,0.000011963716,0.00096764124,0.00011613576,0.087529935,0.0033493275,0.00011846614,0.2785021],"study_design_scores_gemma":[0.0008927272,0.000099058816,0.47482622,0.00020532035,0.0000725134,0.000010808865,0.00010696724,0.5121459,0.0028648544,0.008175766,0.0004249588,0.00017490619],"about_ca_topic_score_codex":0.000038812268,"about_ca_topic_score_gemma":0.000013593813,"teacher_disagreement_score":0.51202977,"about_ca_system_score_codex":0.000022394792,"about_ca_system_score_gemma":0.00005034695,"threshold_uncertainty_score":0.569914},"labels":[],"label_agreement":null},{"id":"W2792230481","doi":"10.1101/282145","title":"Topographic diversity of structural connectivity in schizophrenia","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Taipei Veterans General Hospital; National Health Research Institutes; Janssen Canada; Academia Sinica; National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Schizophrenia (object-oriented programming); Diffusion MRI; Neuroscience; Similarity (geometry); Psychology; Biology; Medicine; Magnetic resonance imaging; Artificial intelligence; Computer science; Psychiatry","score_opus":0.03556129631042174,"score_gpt":0.2820594888935082,"score_spread":0.24649819258308645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792230481","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966199,0.00020300513,0.0015470088,0.0002049966,0.00019349939,0.00077108986,0.00013663358,0.00031354575,0.000010322809],"genre_scores_gemma":[0.97780657,0.000086259904,0.021764088,0.000091332266,0.00014878358,0.00005481803,3.0586537e-7,0.000046880574,9.585428e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99834085,0.00005337456,0.00035819775,0.00070060114,0.00025657337,0.00029039406],"domain_scores_gemma":[0.99799865,0.000045375218,0.00031475807,0.0011553653,0.00034133517,0.0001445046],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023253751,0.00031325174,0.00057305064,0.0003583602,0.00012217177,0.000017920927,0.00033559633,0.00027959945,0.000025719686],"category_scores_gemma":[0.00014246226,0.0003325243,0.00015322493,0.0005661494,0.00029222,0.0000770484,0.0010651314,0.00072340155,0.00000448719],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023865626,0.0002132335,0.67179185,0.00060195534,0.000088290704,0.000054840144,0.000011108237,0.000009117373,0.32437038,0.0024734023,0.00013922912,0.000007899492],"study_design_scores_gemma":[0.0007035355,0.00007479468,0.8699093,0.00038133157,0.000089869296,3.7316557e-8,7.8066887e-7,0.0002795753,0.127965,0.000108885084,0.00018348129,0.00030340173],"about_ca_topic_score_codex":0.00012783232,"about_ca_topic_score_gemma":0.000004733823,"teacher_disagreement_score":0.19811742,"about_ca_system_score_codex":0.00012896932,"about_ca_system_score_gemma":0.00019833216,"threshold_uncertainty_score":0.9999127},"labels":[],"label_agreement":null},{"id":"W2792269733","doi":"10.1101/253443","title":"A structural equation model for imaging genetics using spatial transcriptomics","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Stichting voor de Technische Wetenschappen; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; European Commission; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Imaging genetics; Interpretability; Neuroimaging; Context (archaeology); Structural equation modeling; Artificial intelligence; Computer science; Machine learning; Computational biology; Biology; Neuroscience","score_opus":0.09471566155556396,"score_gpt":0.32280967976409014,"score_spread":0.22809401820852618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792269733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39277717,0.00018284345,0.6046995,0.00021555627,0.00024470958,0.0012506999,0.00026785393,0.00036049893,0.0000011856574],"genre_scores_gemma":[0.6595267,0.000053399912,0.33929566,0.0002798947,0.000518575,0.00018408778,0.0000017548517,0.00013836514,0.0000015450273],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978419,0.000024263729,0.00051862624,0.00089189346,0.00026463415,0.00045868545],"domain_scores_gemma":[0.9976602,0.00002855644,0.0003526866,0.0010729019,0.00068761664,0.00019802974],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019736451,0.00045502328,0.00048180204,0.00020081406,0.00022123479,0.00010020635,0.0002865832,0.0002579206,0.0000063378943],"category_scores_gemma":[0.00008487951,0.00050838076,0.00020763271,0.0001775046,0.00015360625,0.0000951246,0.00017237406,0.00047625275,0.0000024881383],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009887496,0.00006606689,0.005816339,0.00048611872,0.0000617705,0.0000065919235,0.000016513812,0.0035320567,0.9892025,0.00055915857,0.00013252314,0.000021473074],"study_design_scores_gemma":[0.00056003826,0.000031453284,0.0028150093,0.00022798977,0.00030495969,7.803709e-8,6.069592e-7,0.86950445,0.1256817,0.00011583574,0.0003284262,0.00042946165],"about_ca_topic_score_codex":0.000022530656,"about_ca_topic_score_gemma":7.262618e-7,"teacher_disagreement_score":0.8659724,"about_ca_system_score_codex":0.00032475262,"about_ca_system_score_gemma":0.0005650274,"threshold_uncertainty_score":0.9997368},"labels":[],"label_agreement":null},{"id":"W2792428439","doi":"10.1002/mrm.27112","title":"Diffusion MRI monitoring of specific structures in the irradiated rat brain","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Astrogliosis; Corpus callosum; Hippocampus; Nuclear medicine; Medicine; Pathology; Magnetic resonance imaging; Internal medicine; Central nervous system; Radiology","score_opus":0.055476362538311105,"score_gpt":0.35731721185641563,"score_spread":0.3018408493181045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792428439","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97449684,0.0072464417,0.00035309384,0.015136653,0.00014876465,0.0007052839,0.0000017293885,0.00004364809,0.0018675172],"genre_scores_gemma":[0.99102926,0.0017539131,0.005787104,0.00069346215,0.0004244714,0.00005124889,0.0000046203077,0.000017007429,0.00023893215],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987927,0.00005921207,0.0003832893,0.0002599276,0.00029454276,0.00021034035],"domain_scores_gemma":[0.9991268,0.00019980149,0.00007496805,0.00050624274,0.00005311271,0.00003906714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031329494,0.00012704999,0.0002763517,0.00016721853,0.00003812366,0.0000036198628,0.00021676531,0.00005032939,0.00010901632],"category_scores_gemma":[0.00018218135,0.00008060863,0.000022533713,0.00070836494,0.0004236533,0.000025492947,0.000032908127,0.00027493617,0.0000028184882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040708776,0.00028046034,0.4534033,0.00011341836,0.0000021138949,0.00016674031,0.004179891,0.0000069162807,0.19107477,0.0037530786,0.024769237,0.32184297],"study_design_scores_gemma":[0.0013359688,0.00063530187,0.8793123,0.0004745066,0.0000066309276,0.000039590424,0.00035559142,0.00023906426,0.002358869,0.0035878127,0.111580245,0.00007412178],"about_ca_topic_score_codex":0.000086750726,"about_ca_topic_score_gemma":0.000011173666,"teacher_disagreement_score":0.42590898,"about_ca_system_score_codex":0.000032863376,"about_ca_system_score_gemma":0.000016640624,"threshold_uncertainty_score":0.32871246},"labels":[],"label_agreement":null},{"id":"W2792811499","doi":"10.1002/jmri.26013","title":"Novel connectivity map normalization procedure for improved quantitative investigation of structural thalamic connectivity in temporal lobe epilepsy patients","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Temporal lobe; Diffusion MRI; Tractography; Parahippocampal gyrus; Thalamus; Epilepsy; Normalization (sociology); Neuroscience; Medicine; Nuclear medicine; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.034724177122954225,"score_gpt":0.3304289340590972,"score_spread":0.29570475693614295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2792811499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93918735,0.00047462218,0.05808988,0.0012316362,0.000109494875,0.00082802813,0.00003462914,0.000018937362,0.00002543036],"genre_scores_gemma":[0.92718786,0.000015158624,0.0724568,0.00018926284,0.000082502505,0.000021398995,0.0000125286115,0.000021248305,0.000013242441],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874085,0.000039817405,0.0006167168,0.00021800485,0.00018952295,0.0001950755],"domain_scores_gemma":[0.99789894,0.00016547348,0.00073918054,0.00016496492,0.00096837885,0.0000630606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035514828,0.00014851382,0.00035296674,0.00019060375,0.00006790737,0.000014897227,0.000113336515,0.000041065676,0.0000064065403],"category_scores_gemma":[0.00066451525,0.00013195787,0.000080460035,0.0002889874,0.00024575027,0.000372565,0.0000311487,0.00020311041,2.829136e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051485596,0.000118878335,0.8835357,0.00013722118,0.0000046236446,0.0000016080656,0.00038884958,0.000010952547,0.10326717,0.000606334,0.00017438027,0.011239461],"study_design_scores_gemma":[0.003101714,0.0011656781,0.9327217,0.00044287828,0.00003880821,0.00006051609,0.00010029954,0.035930075,0.020860625,0.005096038,0.0003448229,0.00013685517],"about_ca_topic_score_codex":0.0000394865,"about_ca_topic_score_gemma":0.000023584516,"teacher_disagreement_score":0.08240655,"about_ca_system_score_codex":0.00009948832,"about_ca_system_score_gemma":0.00015667794,"threshold_uncertainty_score":0.5381086},"labels":[],"label_agreement":null},{"id":"W2793249164","doi":"10.1093/cercor/bhx363","title":"Diversity of Cortico-descending Projections: Histological and Diffusion MRI Characterization in the Monkey","year":2017,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Tractography; Neuroscience; Somatosensory system; Diffusion MRI; Anatomy; White matter; SMA*; Spinal cord; Internal capsule; Axon; Electrophysiology; Biology; Magnetic resonance imaging; Medicine; Computer science","score_opus":0.09689226681129072,"score_gpt":0.34613012875158367,"score_spread":0.24923786194029296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793249164","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948322,0.000010278533,0.0028584984,0.0014378503,0.000023935618,0.00035219057,0.0000054413695,0.000032182805,0.0004473976],"genre_scores_gemma":[0.9990173,0.00009698787,0.0006060507,0.00013826457,0.000019652285,0.000013594989,0.000014134858,0.000003704915,0.000090285896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99958795,0.000014030874,0.000107107575,0.00013724131,0.00007965989,0.00007398386],"domain_scores_gemma":[0.9995482,0.000016663986,0.00012256848,0.00026706635,0.000023820114,0.000021664819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005485752,0.00005266478,0.00010536841,0.000035273057,0.0005137906,0.000010433789,0.0001032796,0.00003101296,0.000007897489],"category_scores_gemma":[0.000062651394,0.000036530215,0.000021787648,0.000044820288,0.0001235421,0.000083926985,0.00021028679,0.00011018158,6.0132857e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000341357,0.00010962256,0.95058453,0.000022208771,0.0000022186189,0.0000074873274,0.00027648386,6.472671e-8,0.042685747,0.0021552662,0.00004209488,0.004080136],"study_design_scores_gemma":[0.00025422784,0.000068212576,0.99745876,0.000033530097,0.000019244022,0.000031091186,0.00004381525,0.00066216046,0.00038621336,0.0005236632,0.00048158472,0.00003751493],"about_ca_topic_score_codex":0.000049253846,"about_ca_topic_score_gemma":0.00000597832,"teacher_disagreement_score":0.046874207,"about_ca_system_score_codex":0.000019759902,"about_ca_system_score_gemma":0.000007854454,"threshold_uncertainty_score":0.39517134},"labels":[],"label_agreement":null},{"id":"W2793560073","doi":"10.1093/cercor/bhy031","title":"Global White Matter Diffusion Characteristics Predict Longitudinal Cognitive Change Independently of Amyloid Status in Clinically Normal Older Adults","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Research Resources; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institutes of Health; Canadian Institutes of Health Research; Centre d'Imagerie BioMédicale; Massachusetts General Hospital","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Cognitive decline; Cognition; Episodic memory; Psychology; Effects of sleep deprivation on cognitive performance; Neuroscience; Internal medicine; Medicine; Dementia; Magnetic resonance imaging; Radiology","score_opus":0.03980957992377172,"score_gpt":0.341549975888084,"score_spread":0.3017403959643123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793560073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945006,0.0000176175,0.0022335635,0.000281869,0.00011384403,0.0008480665,0.0003318331,0.00008334019,0.0015892639],"genre_scores_gemma":[0.9970179,0.000048638478,0.001113809,0.0011046503,0.00029860844,0.0000749976,0.00018826325,0.000024797426,0.0001283287],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983837,0.000028873752,0.00054090965,0.00042182542,0.00025735918,0.00036734447],"domain_scores_gemma":[0.9989886,0.000033869772,0.00025044015,0.00030010153,0.00025859545,0.00016835585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008608659,0.00018684099,0.0003465994,0.0000800524,0.00004951744,0.00001111429,0.00011774468,0.000115177514,0.0005271309],"category_scores_gemma":[0.000052576233,0.00017103877,0.00007880334,0.00023985091,0.00023753212,0.00013197835,0.0001655804,0.00024203322,0.000073778974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007428723,0.00036236274,0.9896841,0.000063769054,0.000010481093,0.000024236455,0.0001911656,1.1364908e-8,0.000111479225,0.000028030558,0.00025247125,0.008528995],"study_design_scores_gemma":[0.0017855308,0.0006670093,0.99616367,0.0004789085,0.00005659896,0.000049933853,0.000070601855,0.0002596271,0.00012616259,0.000075243755,0.00011775547,0.00014897769],"about_ca_topic_score_codex":0.00008265362,"about_ca_topic_score_gemma":0.00005277266,"teacher_disagreement_score":0.008380018,"about_ca_system_score_codex":0.00006115711,"about_ca_system_score_gemma":0.0000513368,"threshold_uncertainty_score":0.6974759},"labels":[],"label_agreement":null},{"id":"W2794587673","doi":"10.1002/jmri.26016","title":"Myocardial fibrosis evaluated by diffusion‐weighted imaging and its relationship to 3D contractile function in patients with hypertrophic cardiomyopathy","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Circle Cardiovascular Imaging","funders":"National Natural Science Foundation of China","keywords":"Medicine; Hypertrophic cardiomyopathy; Myocardial fibrosis; Cardiology; Internal medicine; Effective diffusion coefficient; Intraclass correlation; Diffusion MRI; Fibrosis; Cardiomyopathy; Magnetic resonance imaging; Population; Ventricle; Nuclear medicine; Heart failure; Radiology","score_opus":0.015548300847582927,"score_gpt":0.2734621996068646,"score_spread":0.25791389875928167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794587673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865068,0.0043578893,0.0058633187,0.0023242964,0.00010296656,0.00056336296,0.000012600577,0.000040246996,0.00022847342],"genre_scores_gemma":[0.99279505,0.00009376655,0.0061343554,0.0006891066,0.00016334033,0.000022660222,0.000006320325,0.000035177865,0.000060226863],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985008,0.00007124214,0.00045767057,0.00027996034,0.00043113847,0.00025916813],"domain_scores_gemma":[0.99869525,0.00010568529,0.00022995444,0.00021487885,0.0005913405,0.00016291256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026574853,0.0001754081,0.00033322777,0.00026989967,0.00013400162,0.000041857984,0.0000858278,0.000030182327,0.000023958144],"category_scores_gemma":[0.00022721589,0.00014286458,0.00005154806,0.0004474828,0.00008717456,0.0002901691,0.000043433076,0.00033027018,0.0000048165225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012248685,0.00012499712,0.9070725,0.000012487039,0.0000054344723,0.000020835116,0.00008936438,0.0000071938352,0.007064102,0.000013568327,0.0018694699,0.082495205],"study_design_scores_gemma":[0.0033017863,0.0007097869,0.9740468,0.0003426414,0.000119141696,0.00013091203,0.000027477967,0.0047228597,0.00024697854,0.0001403232,0.016052417,0.0001588576],"about_ca_topic_score_codex":0.000010203217,"about_ca_topic_score_gemma":6.862582e-7,"teacher_disagreement_score":0.082336344,"about_ca_system_score_codex":0.000100364035,"about_ca_system_score_gemma":0.000060750346,"threshold_uncertainty_score":0.58258486},"labels":[],"label_agreement":null},{"id":"W2794660696","doi":"10.3389/fpsyg.2018.00330","title":"Openness to Changing Religious Views Is Related to Radial Diffusivity in the Genu of the Corpus Callosum in an Initial Study of Healthy Young Adults","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"National Institute on Drug Abuse; National Institutes of Health; National Center for Responsible Gaming","keywords":"Corpus callosum; Psychology; White matter; Splenium; Diffusion MRI; Superior longitudinal fasciculus; Openness to experience; Inferior longitudinal fasciculus; Neuroscience; Social psychology; Fractional anisotropy; Medicine","score_opus":0.06200635574306377,"score_gpt":0.42748605235321224,"score_spread":0.36547969661014845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794660696","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99079245,0.000076424505,0.0021458797,0.0038249427,0.0005740192,0.002338839,0.000009653903,0.000015518552,0.00022225289],"genre_scores_gemma":[0.9925296,0.00004910586,0.003079319,0.0040575117,0.000047498535,0.00021074136,0.0000026799582,0.000016833234,0.000006739213],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99852365,0.00024916398,0.0004728247,0.0003624718,0.00012838889,0.0002634913],"domain_scores_gemma":[0.99901474,0.000025466321,0.000128575,0.00072943774,0.000049847156,0.000051964238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044988803,0.000111389105,0.00034985758,0.00036066325,0.000041524607,0.0000025278796,0.00040084965,0.000080250014,0.0000030286706],"category_scores_gemma":[0.00006972851,0.00008083206,0.00003061677,0.0011880352,0.000117434785,0.000029967923,0.00008889918,0.00030132566,0.0000012608446],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029841524,0.0029362855,0.8475272,0.000033201697,0.000013966806,0.000049234106,0.08372484,0.0000071872264,0.0021602176,0.00006691834,0.010228995,0.050267786],"study_design_scores_gemma":[0.007103213,0.0048945025,0.97526926,0.00023704607,0.000029300987,0.00007720415,0.0054207994,0.00032190958,0.0006020964,0.0028486266,0.0029723528,0.00022372046],"about_ca_topic_score_codex":0.0003835844,"about_ca_topic_score_gemma":0.00107511,"teacher_disagreement_score":0.12774202,"about_ca_system_score_codex":0.000050874143,"about_ca_system_score_gemma":0.000023980487,"threshold_uncertainty_score":0.32962358},"labels":[],"label_agreement":null},{"id":"W2794674174","doi":"10.1093/schbul/sby016.443","title":"T167. ABERRANT MYELINATION OF THE CINGULUM BUNDLE IN PATIENTS WITH SCHIZOPHRENIA: A 7T MTI/DTI STUDY","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Fractional anisotropy; Cingulum (brain); Diffusion MRI; White matter; Schizophrenia (object-oriented programming); Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Radiology; Psychiatry","score_opus":0.019380576258406425,"score_gpt":0.2791227404122939,"score_spread":0.25974216415388746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794674174","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9939719,0.00002354494,0.00040853425,0.0027329738,0.0000875337,0.0017494923,0.000014313878,0.00012141809,0.0008902873],"genre_scores_gemma":[0.9882891,0.0000037467387,0.0108580785,0.00021264494,0.00012739863,0.000121898636,0.000011308739,0.00004647121,0.0003293393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982577,0.00007839663,0.0004787743,0.00045546118,0.0004555331,0.00027413925],"domain_scores_gemma":[0.9984662,0.000046083263,0.00025549738,0.00084219803,0.0003145997,0.00007544904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023451801,0.00022498023,0.00033792722,0.00016118804,0.00016199311,0.000015688905,0.00027864377,0.00006648959,0.00013318591],"category_scores_gemma":[0.00014665718,0.00015201123,0.00007239817,0.0006290246,0.00024975612,0.000039796207,0.00014841602,0.00037178607,0.000048545287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011202312,0.009677779,0.95163625,0.00012151629,0.00012245495,0.000012867681,0.001169381,0.000027086713,0.002538538,0.0025383611,0.0057932325,0.015160212],"study_design_scores_gemma":[0.009368384,0.0019238048,0.9796926,0.00027028937,0.00009313195,0.000007779416,0.0000961637,0.00006769841,0.00250564,0.0008323891,0.0049113026,0.00023085208],"about_ca_topic_score_codex":0.000092248694,"about_ca_topic_score_gemma":0.00009351278,"teacher_disagreement_score":0.028056307,"about_ca_system_score_codex":0.00006368554,"about_ca_system_score_gemma":0.000083693565,"threshold_uncertainty_score":0.6198838},"labels":[],"label_agreement":null},{"id":"W2794907560","doi":"10.3897/rio.4.e25312","title":"FIIND: Ferret Interactive Integrated Neurodevelopment Atlas","year":2018,"lang":"en","type":"article","venue":"Research Ideas and Outcomes","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; European Commission","keywords":"Neocortex; Neuroscience; Brain development; Neuroimaging; Regionalisation; Diffusion MRI; Human Connectome Project; Brain size; Fiber tract; Biology; Brain atlas; Human brain; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Geography","score_opus":0.17726212184635556,"score_gpt":0.4973078213687,"score_spread":0.3200456995223444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794907560","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9624427,0.00012404758,0.0026840428,0.022991486,0.000080018115,0.00089251256,0.000013496275,0.00025373077,0.010517972],"genre_scores_gemma":[0.986305,0.00019178896,0.008053008,0.00077242847,0.00006372862,0.000066725726,0.000011568223,0.000019739016,0.004516034],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989341,0.000050882638,0.00014931489,0.00029159838,0.00027928132,0.00029481994],"domain_scores_gemma":[0.9990351,0.00019044269,0.000025639782,0.00026734654,0.00031272808,0.0001687088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027170542,0.00010336815,0.00017874446,0.00013106872,0.00019897612,0.000039784303,0.00009706107,0.00003442562,0.00010429257],"category_scores_gemma":[0.00042352048,0.000072785115,0.000034851146,0.00027392557,0.0002625709,0.00007200493,0.00016505794,0.00038914604,0.0000706057],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078652625,0.0006403444,0.6214747,0.00015010711,0.00019621225,0.00025077042,0.0013912034,4.445631e-7,0.019869544,0.03235593,0.10820178,0.21468244],"study_design_scores_gemma":[0.00084516045,0.0005856281,0.59002775,0.00014099911,0.000016554795,0.00009498822,0.00027998356,0.0004885844,0.010860686,0.01255716,0.3839044,0.00019808426],"about_ca_topic_score_codex":0.0000736537,"about_ca_topic_score_gemma":0.000011209974,"teacher_disagreement_score":0.27570263,"about_ca_system_score_codex":0.00006177904,"about_ca_system_score_gemma":0.00009009093,"threshold_uncertainty_score":0.29680908},"labels":[],"label_agreement":null},{"id":"W2794971544","doi":"10.1093/schbul/sby016.454","title":"T178. PRIOR SUB-THRESHOLD PSYCHOTIC SYMPTOMS ASSOCIATED WITH THICKER RIGHT INFERIOR FRONTAL GYRUS AMONG PATIENTS IN A FIRST EPISODE OF PSYCHOSIS","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"","keywords":"Psychosis; Psychology; Psychiatry; Schizophrenia (object-oriented programming); Neuroimaging; Recall; Clinical psychology","score_opus":0.013774802396196429,"score_gpt":0.26684695601873193,"score_spread":0.2530721536225355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794971544","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99534345,0.000034734203,0.00046222628,0.0017455859,0.000085992,0.0010932414,0.000043653912,0.00021087793,0.0009802255],"genre_scores_gemma":[0.99422365,0.000032679272,0.0047514564,0.00038173964,0.000076713164,0.00023348352,0.000061565595,0.00007210049,0.0001666044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980664,0.000038939554,0.00053428055,0.00056853256,0.00037897873,0.00041286973],"domain_scores_gemma":[0.9985671,0.0000897148,0.0003057572,0.00065074477,0.00022844136,0.00015821501],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015492327,0.00030380176,0.0004902905,0.00021610521,0.00014291628,0.000018815737,0.00023357746,0.0001662402,0.00030957008],"category_scores_gemma":[0.00014919147,0.00025164822,0.0001036033,0.00050766993,0.0004419807,0.00006079128,0.00006538144,0.00044345297,0.00007934856],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015304754,0.0011584751,0.98718685,0.000047735877,0.00006792746,0.000014402159,0.00014267617,0.0000035516127,0.0004537565,0.00027908137,0.00797773,0.0011373619],"study_design_scores_gemma":[0.0058293617,0.00091432186,0.98199785,0.00095789984,0.00009598323,0.000006700085,0.000006115292,0.00019108296,0.0041095503,0.00037014345,0.005195311,0.00032570487],"about_ca_topic_score_codex":0.00016790716,"about_ca_topic_score_gemma":0.00088226114,"teacher_disagreement_score":0.0051890016,"about_ca_system_score_codex":0.00010766423,"about_ca_system_score_gemma":0.000035069705,"threshold_uncertainty_score":0.99999356},"labels":[],"label_agreement":null},{"id":"W2795037714","doi":"10.1093/schbul/sby018.797","title":"S10. ASTROGLIAL PATHOLOGY IN SCHIZOPHRENIA: A META-ANALYSIS OF MRS STUDIES OF ANTERIOR CINGULATE MYOINOSITOL","year":2018,"lang":"es","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Care; London Health Sciences Centre; Western University","funders":"","keywords":"Schizophrenia (object-oriented programming); Anterior cingulate cortex; Meta-analysis; Inositol; Psychosis; Psychiatry; Medicine; Neuroscience; Internal medicine; Psychology; Cognition","score_opus":0.09390195899340781,"score_gpt":0.3813231331694894,"score_spread":0.2874211741760816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795037714","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98076594,0.010969549,0.0012977412,0.004837826,0.00020054496,0.0010684009,0.00048723945,0.00013387046,0.00023888964],"genre_scores_gemma":[0.9512634,0.0009871953,0.04680075,0.00024802715,0.00026346016,0.00015840796,0.000027005046,0.00007070145,0.00018099515],"study_design_codex":"bench_or_experimental","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9955129,0.0003629124,0.001936447,0.0010565926,0.00049644744,0.0006346983],"domain_scores_gemma":[0.9961474,0.00037923973,0.001211675,0.0014399942,0.00066121394,0.0001604666],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00077782385,0.00061571907,0.0039313585,0.0011441123,0.00013559732,0.000020852052,0.00053199916,0.0002490305,0.0007896924],"category_scores_gemma":[0.00053182914,0.00053429825,0.0015601916,0.002099952,0.0015855376,0.000053340587,0.00044108887,0.0005852164,0.00006928282],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.032210026,0.005287073,0.04140551,0.0027351382,0.3442669,0.0010690611,0.004373386,0.00045317743,0.5125297,0.02631868,0.0067930985,0.02255831],"study_design_scores_gemma":[0.01518752,0.005804924,0.15600425,0.0013632303,0.6114864,0.0002015717,0.0010071493,0.0012760669,0.18988515,0.004015434,0.011572733,0.002195576],"about_ca_topic_score_codex":0.00011606994,"about_ca_topic_score_gemma":0.000058252554,"teacher_disagreement_score":0.3226445,"about_ca_system_score_codex":0.0000664723,"about_ca_system_score_gemma":0.00012615013,"threshold_uncertainty_score":0.99971086},"labels":[],"label_agreement":null},{"id":"W2795150941","doi":"10.1016/j.nicl.2018.03.029","title":"Postmortem diffusion MRI of the entire human spinal cord at microscopic resolution","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Spinal cord; Magnetic resonance imaging; Diffusion MRI; Cord; Medicine; Magnetic resonance microscopy; Anatomy; Ex vivo; Biomedical engineering; Pathology; Neuroscience; Radiology; In vivo; Biology; Spin echo; Surgery","score_opus":0.16271483131394815,"score_gpt":0.47911206556944236,"score_spread":0.3163972342554942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795150941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993306,0.000030266323,0.0009907945,0.0032601373,0.0002704507,0.00051324716,0.000010727128,0.00012769298,0.0014907187],"genre_scores_gemma":[0.99282426,0.000059651687,0.0032782692,0.0017495715,0.00036364928,0.000012000798,0.000008230565,0.000028867136,0.0016754946],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984552,0.00009485569,0.0005836461,0.00044696475,0.00021823125,0.00020106211],"domain_scores_gemma":[0.99845004,0.00006963186,0.00025221234,0.0009926627,0.00013850162,0.00009697036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019758487,0.00013084612,0.0002653002,0.000034575005,0.0002719629,0.0000080520595,0.0002449723,0.000088459565,0.0000669944],"category_scores_gemma":[0.0002273356,0.00009543734,0.00020989082,0.00018925089,0.0008327874,0.000037345733,0.00037056583,0.00037649626,0.0000391841],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071449566,0.0006297401,0.18802293,0.000050701845,0.000009102816,0.000020653062,0.000013668899,8.532945e-8,0.7890259,0.0005519671,0.015087719,0.0058730133],"study_design_scores_gemma":[0.00087546057,0.0026217147,0.91840756,0.0001415617,0.00007547007,0.00009749187,0.0000034587104,0.00013912513,0.034227554,0.0003797945,0.042933267,0.000097533324],"about_ca_topic_score_codex":0.0000070930946,"about_ca_topic_score_gemma":0.0000059285417,"teacher_disagreement_score":0.75479835,"about_ca_system_score_codex":0.00003068333,"about_ca_system_score_gemma":0.00003539799,"threshold_uncertainty_score":0.38918218},"labels":[],"label_agreement":null},{"id":"W2795442880","doi":"10.1016/j.neuroimage.2018.04.009","title":"Microstructural imaging in the spinal cord and validation strategies","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Canada Foundation for Innovation; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec","keywords":"Magnetic resonance imaging; Spinal cord; Myelin; Medicine; Neuroscience; Biomedical engineering; Pathology; Computer science; Radiology; Psychology; Central nervous system","score_opus":0.14215483030592915,"score_gpt":0.447487751245612,"score_spread":0.3053329209396829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795442880","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054776506,0.99593186,0.0003736698,0.0005073673,0.00007197454,0.0012802307,0.000021960677,0.00012941577,0.0011357487],"genre_scores_gemma":[0.0015329873,0.99573016,0.0018835122,0.00041020036,0.00019127446,0.000098618824,0.00006155874,0.000047533882,0.000044175325],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99879235,0.00009006668,0.00033281205,0.00044539178,0.00013516708,0.00020422602],"domain_scores_gemma":[0.9991944,0.000054653374,0.00016805435,0.00051016756,0.000035276247,0.00003749278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013459692,0.00026499823,0.0004976121,0.00013040043,0.00009055576,0.00013053618,0.00020562044,0.000053961117,0.000006842952],"category_scores_gemma":[0.000041841424,0.00017420476,0.000113420705,0.0002583792,0.00021487659,0.00013484739,0.000079246165,0.00048023488,0.0000119443575],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021662992,0.000023767128,0.000044397384,0.0027795315,0.0000037652903,0.000115996154,0.00002115972,1.3417338e-8,0.00012711086,0.0006505424,0.0011146922,0.99509734],"study_design_scores_gemma":[0.0001402831,0.00016859213,0.00095535786,0.0024955776,0.00020338065,0.0021455407,0.000028467037,0.0000065868076,0.000014435645,0.00083652494,0.99283224,0.00017302627],"about_ca_topic_score_codex":0.000008171819,"about_ca_topic_score_gemma":6.882228e-7,"teacher_disagreement_score":0.9949243,"about_ca_system_score_codex":0.000025326155,"about_ca_system_score_gemma":0.00007934216,"threshold_uncertainty_score":0.7103864},"labels":[],"label_agreement":null},{"id":"W2795505299","doi":"10.1101/277087","title":"Comparison of different methods for average anatomical templates creation: do we really gain anything from a diffeomorphic framework?","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Diffeomorphism; Computer science; Computation; Population; Template; Artificial intelligence; Mathematics; Algorithm; Pure mathematics; Medicine; Programming language","score_opus":0.06948087597698725,"score_gpt":0.39353280889160874,"score_spread":0.3240519329146215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795505299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3334472,0.001262244,0.6615143,0.0010490118,0.0002604805,0.0015988398,0.00038257038,0.00048057645,0.0000048091547],"genre_scores_gemma":[0.58043844,0.0003785853,0.41821158,0.00010453939,0.00034552498,0.00041017978,0.0000033465908,0.00010581694,0.0000019908407],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99687916,0.00018339152,0.000997493,0.0011786504,0.0003210013,0.0004403155],"domain_scores_gemma":[0.9955944,0.0008738479,0.00085616956,0.0017954978,0.0005873549,0.00029275625],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045321495,0.0006030823,0.0014073118,0.00025709154,0.00017905237,0.000098002674,0.0004893194,0.0007119424,0.00008162013],"category_scores_gemma":[0.0006948837,0.00057692634,0.000311719,0.00028077635,0.00027050162,0.00006737425,0.0004483734,0.0011428376,0.00000451811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003831048,0.0010991134,0.04448428,0.0012751641,0.00043457546,0.000014260581,0.00009957553,0.00004019256,0.94287735,0.008249294,0.00086171256,0.00018135828],"study_design_scores_gemma":[0.0011981104,0.0003564926,0.049705714,0.004645209,0.00076784,8.007267e-8,0.000008722056,0.028109398,0.9036845,0.0031039955,0.0074042697,0.0010156989],"about_ca_topic_score_codex":0.00002430206,"about_ca_topic_score_gemma":3.514694e-7,"teacher_disagreement_score":0.24699125,"about_ca_system_score_codex":0.00023485823,"about_ca_system_score_gemma":0.0002110551,"threshold_uncertainty_score":0.99966824},"labels":[],"label_agreement":null},{"id":"W2795722583","doi":"10.1007/s00415-018-8846-3","title":"Alterations in white matter network topology contribute to freezing of gait in Parkinson’s disease","year":2018,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Western Sydney University; National Health and Medical Research Council; Parkinson Canada","keywords":"Connectome; White matter; Diffusion MRI; Neuroscience; Parkinson's disease; Modularity (biology); Psychology; Neuroradiology; Neurology; Gait; Disease; Medicine; Physical medicine and rehabilitation; Biology; Functional connectivity; Magnetic resonance imaging; Pathology","score_opus":0.030902479770605187,"score_gpt":0.3386517814299037,"score_spread":0.30774930165929854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795722583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9279738,0.00006005131,0.011427234,0.059973948,0.00014056097,0.00020568921,0.000005265837,0.000007838664,0.00020560432],"genre_scores_gemma":[0.98273695,0.000030658837,0.0039751446,0.012895559,0.00030029757,0.000010645805,0.0000012163257,0.000010285438,0.000039239727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990838,0.00007113867,0.0004577864,0.00012526715,0.00006908594,0.00019290969],"domain_scores_gemma":[0.99933535,0.00008717386,0.00018500387,0.00017684275,0.000109561595,0.00010605148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001608916,0.00006932937,0.00027336503,0.00021603308,0.000020535854,0.000002974759,0.00010035987,0.00004033311,0.0000658588],"category_scores_gemma":[0.00010147591,0.0000628682,0.000046277237,0.00022584327,0.00008032893,0.000044811717,0.000042981817,0.00027377452,0.0000066690955],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079035806,0.0001198887,0.9864484,0.000008155915,0.000005011807,0.00022807294,0.00008132905,0.0006451656,0.002760579,0.00044524955,0.008233164,0.0002346421],"study_design_scores_gemma":[0.00077655126,0.0008012697,0.95255977,0.00005031246,0.000019642144,0.00028902083,0.0000034437123,0.0004204956,0.00023510423,0.0037234519,0.0410699,0.000051052713],"about_ca_topic_score_codex":0.0000072445714,"about_ca_topic_score_gemma":0.000047711826,"teacher_disagreement_score":0.054763146,"about_ca_system_score_codex":0.00001664029,"about_ca_system_score_gemma":0.000043138058,"threshold_uncertainty_score":0.25636908},"labels":[],"label_agreement":null},{"id":"W2797006568","doi":"","title":"Effects of Formalin Fixation on Myelin Water Fraction MRI Measurements in Human White Matter: a Novel Ex Vivo Study","year":2017,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Ex vivo; White matter; Fixation (population genetics); Myelin; Chemistry; Fraction (chemistry); Pathology; Biomedical engineering; Magnetic resonance imaging; Medicine; Chromatography; Internal medicine; Biochemistry; Central nervous system; In vitro; Radiology","score_opus":0.07328939495328274,"score_gpt":0.3671232300828864,"score_spread":0.29383383512960365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797006568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99472404,0.0000030614133,0.00094744423,0.00091760064,0.000029333401,0.0012912876,0.0000011918753,0.00006689495,0.0020191786],"genre_scores_gemma":[0.9979745,0.00000411271,0.0012721231,0.00019757732,0.000059615548,0.00019712817,0.000004100664,0.000024356188,0.00026646437],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907374,0.0000032041316,0.00025434038,0.00026239158,0.00023892369,0.00016737524],"domain_scores_gemma":[0.99939495,0.000007887705,0.00019794298,0.00021062145,0.00014755667,0.00004100954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019665065,0.0001290437,0.00020808162,0.00013282895,0.00016982398,0.000036410165,0.0001381095,0.000048532875,0.000013579967],"category_scores_gemma":[0.00004981323,0.00010216663,0.00003827635,0.000050141134,0.000037173773,0.00027916892,0.00006138016,0.00016666525,0.000014611606],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007406778,0.0006889876,0.40921837,0.00017944678,0.000008796506,8.7623954e-7,0.00044143508,0.0000012386653,0.5887122,0.000066896326,0.0004125177,0.00019514607],"study_design_scores_gemma":[0.0014393298,0.00038523867,0.48219895,0.0002549634,0.00003986322,0.000003517699,0.00007290722,0.00008764326,0.5148024,0.00027721605,0.00034686163,0.00009107948],"about_ca_topic_score_codex":0.00003824986,"about_ca_topic_score_gemma":0.0000035360672,"teacher_disagreement_score":0.07390979,"about_ca_system_score_codex":0.000064600434,"about_ca_system_score_gemma":0.00000517737,"threshold_uncertainty_score":0.4166234},"labels":[],"label_agreement":null},{"id":"W2797202872","doi":"10.1016/j.biopsych.2018.02.679","title":"F66. The Effect of Traumatic Brain Injury on Superficial White Matter in Youth: Towards a Personalized Injury Profile","year":2018,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; SickKids Foundation; Hospital for Sick Children; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"White matter; Traumatic brain injury; Diffusion MRI; Medicine; Cortex (anatomy); Neuroscience; Cerebral cortex; Psychology; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.06872475749452366,"score_gpt":0.3769164492771213,"score_spread":0.30819169178259764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797202872","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9827625,0.000045654775,0.00021410806,0.012664838,0.00015107753,0.00094656367,0.00009235275,0.000093485454,0.003029425],"genre_scores_gemma":[0.99330086,0.000007909675,0.0020817379,0.0040257038,0.00030374533,0.000115135364,0.000030053287,0.000016328111,0.000118505115],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988832,0.00015645399,0.00030008247,0.00031109178,0.00013178147,0.00021741529],"domain_scores_gemma":[0.99938613,0.000089954934,0.00008128186,0.0003653542,0.000025622972,0.000051656258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030192538,0.0001731113,0.00032218904,0.00007128664,0.00006561463,0.0000064147152,0.0001792251,0.0001255666,0.00033557793],"category_scores_gemma":[0.00009889663,0.00008972694,0.00013081756,0.00027094726,0.0003696091,0.000019466803,0.00004668609,0.0002941168,0.00007314738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005878277,0.0008407297,0.9193973,0.00018741102,0.000041039268,0.0000025958786,0.00095568714,3.072493e-7,0.0110324435,0.0033013532,0.04247933,0.015883548],"study_design_scores_gemma":[0.0024653617,0.0147043625,0.96586204,0.00052781805,0.00008473625,0.000024053612,0.00038027528,0.00010678491,0.0074392823,0.0038213818,0.0041599157,0.00042400995],"about_ca_topic_score_codex":0.000012812599,"about_ca_topic_score_gemma":0.0000020051532,"teacher_disagreement_score":0.04646474,"about_ca_system_score_codex":0.000022892025,"about_ca_system_score_gemma":0.000030122312,"threshold_uncertainty_score":0.3674343},"labels":[],"label_agreement":null},{"id":"W2797379939","doi":"10.1016/j.biopsych.2018.02.845","title":"F231. Microstructural Changes in White Matter Associated With Alcohol Use in Early Phase Psychosis: A Diffusion Tensor Imaging (DTI) and Relaxometry Study","year":2018,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Psychosis; Relaxometry; Psychology; Medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.07058778630286348,"score_gpt":0.36415259528452115,"score_spread":0.29356480898165765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797379939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951793,0.000111893816,0.000066302884,0.0034440756,0.00006589136,0.00093433476,0.000021226262,0.00012524621,0.000051720504],"genre_scores_gemma":[0.9926733,0.00002906382,0.00457629,0.0024387108,0.00008807107,0.000101645,0.000015623327,0.000022324144,0.000055021323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870646,0.0000704182,0.0002590019,0.0005547112,0.00010363849,0.00030578565],"domain_scores_gemma":[0.99946004,0.000044976197,0.00010740008,0.0002541212,0.00004663075,0.00008684294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012724537,0.00020811823,0.00030189118,0.00020682314,0.00007739687,0.000031763655,0.00009683531,0.00009480919,0.00002998632],"category_scores_gemma":[0.000051296018,0.00013544135,0.000029189638,0.00050036155,0.0002044194,0.00007761523,0.00006969473,0.0003344202,0.0000063935386],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041643553,0.0009094491,0.9933597,0.000005494726,0.000009633271,0.000012229757,0.00012553182,2.8366323e-8,0.0041461717,0.000010609927,0.00039333757,0.00061139936],"study_design_scores_gemma":[0.0041185734,0.0013134881,0.9934536,0.00017642985,0.000023257222,0.000038355258,0.00019169964,0.000040977964,0.00003616581,0.00029930248,0.00012661588,0.00018153648],"about_ca_topic_score_codex":0.000046473324,"about_ca_topic_score_gemma":0.00015557912,"teacher_disagreement_score":0.0045099873,"about_ca_system_score_codex":0.00003706819,"about_ca_system_score_gemma":0.000007809366,"threshold_uncertainty_score":0.55231386},"labels":[],"label_agreement":null},{"id":"W2797747717","doi":"10.1101/300806","title":"The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in <i>Nrxn2</i> deletion mice","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Biotechnology and Biological Sciences Research Council; National Institutes of Health; Innovative Medicines Initiative; European Commission; University of Leeds; Alzheimer's Society; Medical Research Council; European Federation of Pharmaceutical Industries and Associations; British Pharmacological Society; International Seafood Sustainability Foundation; Wellcome Trust","keywords":"Orbitofrontal cortex; Diffusion MRI; Anterior cingulate cortex; Amygdala; Fractional anisotropy; Thalamus; Cortex (anatomy); Hippocampus; Cingulate cortex","score_opus":0.02203914396760065,"score_gpt":0.2819932292458216,"score_spread":0.25995408527822095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797747717","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98671633,0.00053802464,0.0063818623,0.0040955283,0.00011825883,0.0018316607,0.00009170409,0.00022275532,0.00000388194],"genre_scores_gemma":[0.9776335,0.00069824513,0.020508714,0.00049430726,0.0002171065,0.00037750552,0.0000013579586,0.0000648092,0.000004468809],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981326,0.000105723535,0.0004894777,0.00072684925,0.00025974453,0.0002856242],"domain_scores_gemma":[0.99772257,0.00014370843,0.0005747985,0.0010637317,0.00038152345,0.00011368542],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006428369,0.00032089654,0.00044684,0.00015656283,0.00016192312,0.000045460114,0.0002717265,0.0003176873,0.0000019573001],"category_scores_gemma":[0.000247624,0.00026345425,0.00005981768,0.00037861537,0.0002978531,0.000055062425,0.00033280448,0.00068120775,0.0000019792533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089044304,0.00005318553,0.04668697,0.00035927625,0.000019840372,0.0000034449324,0.000017706343,0.0000035607907,0.95130587,0.0012254977,0.00020148257,0.00003413236],"study_design_scores_gemma":[0.0007368448,0.00015336256,0.72165185,0.000717647,0.0001209438,3.2709787e-7,0.000006396861,0.003527095,0.2671995,0.00025785126,0.0051525803,0.000475625],"about_ca_topic_score_codex":0.0000917064,"about_ca_topic_score_gemma":0.000026213449,"teacher_disagreement_score":0.68410635,"about_ca_system_score_codex":0.000130666,"about_ca_system_score_gemma":0.00010656975,"threshold_uncertainty_score":0.99998176},"labels":[],"label_agreement":null},{"id":"W2797939012","doi":"10.1016/j.patcog.2019.06.002","title":"White matter fiber analysis using kernel dictionary learning and sparsity priors","year":2019,"lang":"en","type":"preprint","venue":"Pattern Recognition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Prior probability; occam; Streamlines, streaklines, and pathlines; Tractography; Human Connectome Project; Artificial intelligence; Computer science; Regularization (linguistics); Fiber bundle; Pattern recognition (psychology); Kernel (algebra); Set (abstract data type); Parallelizable manifold; Bundle; Machine learning; Diffusion MRI; Mathematics; Algorithm; Bayesian probability; Magnetic resonance imaging; Physics","score_opus":0.0824439340404125,"score_gpt":0.34516872211839905,"score_spread":0.26272478807798655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797939012","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85013515,0.00007010537,0.14716224,0.0005292659,0.000066632056,0.0005984323,0.00011019876,0.00019877763,0.0011292178],"genre_scores_gemma":[0.98295844,0.00021685514,0.01341882,0.0005556019,0.00015096589,0.00005890475,0.0014894672,0.000051195846,0.0010997457],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99873376,0.000053162872,0.00026263762,0.0006041169,0.00017124118,0.00017509227],"domain_scores_gemma":[0.99922276,0.000035512396,0.00025108637,0.0002994568,0.000113316746,0.00007790116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010067036,0.00022387315,0.00038311182,0.00031303917,0.00010143612,0.00004124709,0.000053295247,0.0001776196,0.00085941295],"category_scores_gemma":[0.0000103831035,0.00023745268,0.00018210389,0.00018403654,0.00004362476,0.00006602402,0.00027920742,0.0007374897,0.00018868157],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017783072,0.00005352217,0.97994375,0.00023601469,0.00021186892,0.0000086314685,0.000076534285,0.00049489696,0.0001500191,9.5704834e-8,0.00015915175,0.018647715],"study_design_scores_gemma":[0.00039210636,0.000046987614,0.95479465,0.000602328,0.003345591,0.00011274215,0.000046960144,0.037967566,0.00031784675,0.0006889059,0.0012048688,0.0004794494],"about_ca_topic_score_codex":0.00005605105,"about_ca_topic_score_gemma":0.0000019482663,"teacher_disagreement_score":0.13374342,"about_ca_system_score_codex":0.00008131092,"about_ca_system_score_gemma":0.000023088583,"threshold_uncertainty_score":0.9683039},"labels":[],"label_agreement":null},{"id":"W2798240981","doi":"10.1016/j.mri.2018.04.001","title":"Effect of cardiac-related translational motion in diffusion MRI of the spinal cord","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Institut de Valorisation des Données; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation","keywords":"Diffusion MRI; Spinal cord; Imaging phantom; SIGNAL (programming language); Cord; Diffusion; Medicine; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Nuclear medicine; Computer science; Radiology; Surgery","score_opus":0.014704282529158853,"score_gpt":0.3213850486417121,"score_spread":0.30668076611255324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798240981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99246264,0.0024032013,0.0017750001,0.0013586704,0.00007605326,0.0006475614,0.000006990143,0.000035734545,0.0012341596],"genre_scores_gemma":[0.99788624,0.00007351097,0.0018260602,0.00004091816,0.000029255461,0.00002502368,0.0000025782745,0.000012166566,0.00010422133],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99917376,0.00006239802,0.00027205225,0.0001796219,0.00018941643,0.00012272876],"domain_scores_gemma":[0.9994884,0.000043548203,0.000091840535,0.00029079645,0.000064352294,0.000021031954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001979239,0.00008848445,0.00019278556,0.00006743995,0.00003917334,0.000002647741,0.00009529994,0.00002400111,0.000025779926],"category_scores_gemma":[0.00005017666,0.000064494874,0.00008054885,0.00035042065,0.0002685562,0.000036396923,0.000031979445,0.00012963983,0.000001720388],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030320033,0.000048648344,0.2991008,0.00006695833,0.0000010972543,0.0000011106408,0.00004948401,0.0000028433715,0.08151378,0.0004531248,0.000059808503,0.61839914],"study_design_scores_gemma":[0.00072107185,0.0006764976,0.932128,0.00049417163,0.000033750784,0.000015973861,0.0000054417605,0.0053652846,0.056349494,0.00073442445,0.0034105459,0.00006531341],"about_ca_topic_score_codex":0.00003893088,"about_ca_topic_score_gemma":9.830146e-7,"teacher_disagreement_score":0.63302726,"about_ca_system_score_codex":0.000017000155,"about_ca_system_score_gemma":0.000018701414,"threshold_uncertainty_score":0.26300246},"labels":[],"label_agreement":null},{"id":"W2798489997","doi":"10.1101/311050","title":"Physical activity predicts population-level age-related differences in frontal white matter","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Brock University","funders":"Medical Research Council; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; European Commission; Wellcome Trust","keywords":"Fractional anisotropy; Internal capsule; White matter; Diffusion MRI; Corpus callosum; Uncinate fasciculus; Population; Psychology; Superior longitudinal fasciculus; Disconnection; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.04906034224454509,"score_gpt":0.29188653369696754,"score_spread":0.24282619145242246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2798489997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99417806,0.00003544349,0.0028267906,0.00074832694,0.00026489675,0.0011141526,0.00023659818,0.0005548147,0.0000409231],"genre_scores_gemma":[0.98943144,0.000027617565,0.009528257,0.00016747644,0.0003522279,0.00034198735,0.0000024239455,0.00011265674,0.00003592576],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99775237,0.000075000025,0.0003723419,0.0010204194,0.00034657266,0.0004333149],"domain_scores_gemma":[0.9981174,0.000042095653,0.0003173074,0.0011572836,0.00015889156,0.00020703208],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014086394,0.0004838249,0.00071950053,0.00025421786,0.00010162804,0.00007205835,0.00031456677,0.00037379604,0.0000653656],"category_scores_gemma":[0.00006537787,0.0004783856,0.00015149255,0.00038145273,0.00019903913,0.00014036236,0.0003884366,0.0010734018,0.00008435415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008172415,0.0009521216,0.8754514,0.00032322007,0.000088002154,0.000102481405,0.000026925158,0.000009377986,0.12169743,0.00024964262,0.0010085518,0.000009143424],"study_design_scores_gemma":[0.0004917599,0.000053664477,0.9799496,0.00053603004,0.00009570686,6.3096486e-8,5.8874105e-7,0.0017701527,0.016490387,0.000044230957,0.00014471852,0.0004230776],"about_ca_topic_score_codex":0.000106248044,"about_ca_topic_score_gemma":0.000002976342,"teacher_disagreement_score":0.10520705,"about_ca_system_score_codex":0.00026777465,"about_ca_system_score_gemma":0.0001458812,"threshold_uncertainty_score":0.99976677},"labels":[],"label_agreement":null},{"id":"W2800290738","doi":"10.2316/j.2010.216.680-0051","title":"Extraction of Human Heart Conduction Network from Diffusion Tensor MRI","year":2010,"lang":"en","type":"article","venue":"Mechatronic systems and control","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Human heart; Diffusion; Extraction (chemistry); Tensor (intrinsic definition); Nuclear magnetic resonance; Thermal conduction; Computer science; Physics; Medicine; Cardiology; Mathematics; Chemistry; Radiology; Magnetic resonance imaging; Geometry; Chromatography; Thermodynamics","score_opus":0.027360868665930637,"score_gpt":0.32170254667316617,"score_spread":0.29434167800723554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800290738","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93723637,0.0007603633,0.059537493,0.0009038807,0.0003778323,0.00085096096,0.000015889236,0.00014427467,0.00017292723],"genre_scores_gemma":[0.99789804,0.000038423794,0.0010920133,0.00008406144,0.0005348907,0.00009298851,0.000014840581,0.000016068187,0.00022864774],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926364,0.000024602195,0.00024426126,0.00021499544,0.00010999867,0.00014246914],"domain_scores_gemma":[0.99940234,0.000047493206,0.00013659165,0.00028688062,0.000062964325,0.000063709034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013847425,0.00009652954,0.00027435418,0.000033209275,0.000109387285,0.000012336953,0.00003502856,0.000085898064,0.00002732516],"category_scores_gemma":[0.000011548184,0.00008002965,0.000053865668,0.000052964908,0.000039399027,0.00005569669,0.00001159022,0.00022653362,0.0000026283278],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004097348,0.000055456014,0.009037256,0.000023871164,0.000019206043,0.000001144932,0.000013508559,0.000015947518,0.9795614,0.009674005,0.0005106336,0.0010465985],"study_design_scores_gemma":[0.0230959,0.00296131,0.32982805,0.0012927388,0.0016984137,0.0013536162,0.0010969313,0.0832481,0.05968136,0.031635158,0.46262264,0.0014857715],"about_ca_topic_score_codex":0.00039607918,"about_ca_topic_score_gemma":0.000014129381,"teacher_disagreement_score":0.91988003,"about_ca_system_score_codex":0.000014976314,"about_ca_system_score_gemma":0.000015525316,"threshold_uncertainty_score":0.32635143},"labels":[],"label_agreement":null},{"id":"W2800823087","doi":"10.1101/319863","title":"Superoanterior Fasciculus (SAF): Novel fiber tract revealed by diffusion MRI fiber tractography","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Arcuate fasciculus; Fractional anisotropy; White matter; Diffusion MRI; Fiber tract; Superior longitudinal fasciculus; Neuroscience; Inferior longitudinal fasciculus; Uncinate fasciculus; Artificial intelligence; Computer science; Anatomy; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.025978256114191342,"score_gpt":0.2760881515939531,"score_spread":0.25010989547976176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2800823087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.976748,0.00084272353,0.013296508,0.0022089372,0.00047163994,0.0030607367,0.0013344588,0.001931487,0.00010549448],"genre_scores_gemma":[0.91374606,0.00080296275,0.08194198,0.0011088978,0.0008427373,0.0008550777,0.000008968945,0.00041753126,0.0002757647],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99601054,0.000065178305,0.0008616067,0.001707705,0.0005752228,0.0007797721],"domain_scores_gemma":[0.9959433,0.00007919213,0.0005263074,0.0023688932,0.000553291,0.0005290244],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003501874,0.00088437647,0.0010036522,0.00037737653,0.00027198074,0.00015418672,0.0006079105,0.0007101603,0.000418454],"category_scores_gemma":[0.00011790736,0.0008612212,0.000479472,0.00069788704,0.00033238722,0.00018519303,0.00048888806,0.0013896587,0.00020556702],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008517074,0.0011443222,0.004455871,0.00041013566,0.000106004976,0.00005205164,0.000007594028,0.0000015159865,0.97835535,0.000036482124,0.015321126,0.000024353185],"study_design_scores_gemma":[0.0025546174,0.00040057252,0.18383354,0.002075518,0.00076743425,0.0000012551308,0.0000028057204,0.00045231337,0.3438501,0.000008309675,0.46394777,0.00210574],"about_ca_topic_score_codex":0.000038074486,"about_ca_topic_score_gemma":4.0673922e-7,"teacher_disagreement_score":0.6345053,"about_ca_system_score_codex":0.00021060661,"about_ca_system_score_gemma":0.00025688714,"threshold_uncertainty_score":0.99938387},"labels":[],"label_agreement":null},{"id":"W2801233903","doi":"10.1016/j.nicl.2018.04.029","title":"Connectome-derived diffusion characteristics of the fornix in Alzheimer's disease","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Health Canada; University of Oxford; Canadian Institutes of Health Research; National Institute for Health and Care Research; Massachusetts General Hospital; National Institutes of Health; Pfizer","keywords":"Fornix; Diffusion MRI; Hippocampus; Alzheimer's disease; Neuroscience; White matter; Temporal lobe; Psychology; Medicine; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.14411964394659818,"score_gpt":0.4306195358969989,"score_spread":0.2864998919504007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801233903","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937624,0.000025821168,0.00077046896,0.0041869446,0.00019243444,0.0005474464,0.000028382612,0.0000858312,0.00040028873],"genre_scores_gemma":[0.99577004,0.000096746524,0.0011555345,0.002648681,0.0002245047,0.000022047523,0.000008049764,0.000026832942,0.000047590445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99867135,0.000091734226,0.0005655495,0.0003419149,0.00015959788,0.00016987966],"domain_scores_gemma":[0.9984949,0.00027571202,0.00019030718,0.0007939397,0.00010726145,0.00013788382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018032765,0.00011465523,0.00028950808,0.000040850005,0.00005985778,0.0000064896553,0.00020404314,0.00005224251,0.00004684475],"category_scores_gemma":[0.0010951225,0.00008142474,0.00015627075,0.00021263173,0.0005715107,0.000037359725,0.00019285039,0.00034301632,0.000019753517],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005414044,0.0010609189,0.94185513,0.000026793285,0.000012769874,0.000060669838,0.00003415366,1.4797513e-7,0.0307561,0.00056731445,0.0014060518,0.02367852],"study_design_scores_gemma":[0.00075086247,0.00021070366,0.98691356,0.00007245103,0.00008087346,0.000009652699,0.0000031618433,0.0007002616,0.0022295048,0.0005554065,0.008398601,0.000074931864],"about_ca_topic_score_codex":0.0000032163773,"about_ca_topic_score_gemma":0.0000014825356,"teacher_disagreement_score":0.045058433,"about_ca_system_score_codex":0.000007889667,"about_ca_system_score_gemma":0.000065395834,"threshold_uncertainty_score":0.33204046},"labels":[],"label_agreement":null},{"id":"W2801394998","doi":"10.1093/cercor/bhy074","title":"Mapping Cortical Laminar Structure in the 3D BigBrain","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Wellcome Trust","keywords":"Cytoarchitecture; Laminar flow; Laminar organization; Neuroimaging; White matter; Anatomy; Neuroscience; Cerebral cortex; Cortex (anatomy); Geology; Computer science; Biology; Physics; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.05488904631452847,"score_gpt":0.34345049515007975,"score_spread":0.2885614488355513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2801394998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98233616,0.0000314056,0.006519908,0.005083677,0.000054510398,0.00043444047,0.000009180443,0.00013985416,0.005390865],"genre_scores_gemma":[0.98688585,0.0000055332866,0.008777712,0.003772064,0.00024685802,0.00001827472,0.000015517886,0.000014300923,0.00026388664],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992786,0.000030180518,0.00015345233,0.00021354594,0.00012799048,0.00019623552],"domain_scores_gemma":[0.99946135,0.00004836793,0.000034628854,0.00037342936,0.00003708742,0.000045108325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007984943,0.00009318909,0.00012246927,0.00005612364,0.00009666772,0.000013583523,0.00014254868,0.000047329704,0.00015970804],"category_scores_gemma":[0.00006449431,0.00006222612,0.000032694075,0.00031027466,0.00017345214,0.000038598904,0.000040860425,0.00030103003,0.00003049068],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029650354,0.000724512,0.32454503,0.0002108993,0.000057911315,0.00042991067,0.006316305,0.0000020004084,0.35646597,0.10155262,0.058732215,0.15066612],"study_design_scores_gemma":[0.00061565154,0.000289474,0.8970312,0.00006961537,0.000020059171,0.00032098926,0.00036449084,0.0016352747,0.0020843104,0.008982411,0.08841471,0.0001718464],"about_ca_topic_score_codex":0.000010812521,"about_ca_topic_score_gemma":0.000013190284,"teacher_disagreement_score":0.57248616,"about_ca_system_score_codex":0.000022717999,"about_ca_system_score_gemma":0.000023886261,"threshold_uncertainty_score":0.25375077},"labels":[],"label_agreement":null},{"id":"W2802026893","doi":"10.1007/s11682-018-9873-5","title":"DTI-derived indexes of brain WM correlate with cognitive performance in vascular MCI and small-vessel disease. A TBSS study","year":2018,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Regione Toscana","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Psychology; Corpus callosum; Cognition; Audiology; Cardiology; Neuroscience; Medicine; Magnetic resonance imaging; Cognitive impairment; Radiology","score_opus":0.036890063358661566,"score_gpt":0.3254143038895997,"score_spread":0.2885242405309381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802026893","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962448,0.00021016787,0.0015621387,0.0008639295,0.000012561278,0.00097058236,0.000013686759,0.00008072353,0.00004140618],"genre_scores_gemma":[0.9976234,0.00006654473,0.0015414425,0.00041454105,0.000024682953,0.00020098887,0.00001131106,0.000027586364,0.000089506066],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990942,0.000035044668,0.0001916041,0.00036543023,0.00012643704,0.00018731884],"domain_scores_gemma":[0.99941105,0.000080423684,0.00007881458,0.00021796461,0.00009835987,0.000113419876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015607958,0.00015909798,0.00023494105,0.00013355765,0.000101874895,0.000018600264,0.000055178527,0.000021530137,0.0000050982085],"category_scores_gemma":[0.000057270125,0.00013217938,0.000023217774,0.00020635399,0.00040656578,0.00009535892,0.00006904314,0.00017420633,8.278808e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015414016,0.0005987149,0.96872544,0.00006573183,0.000011817687,0.000052623047,0.00075581943,2.982652e-7,0.0060628364,0.0000144185215,0.00003423336,0.023523942],"study_design_scores_gemma":[0.0023460886,0.00041398755,0.9942269,0.00050091906,0.00023219535,0.000047155925,0.00057741307,0.00037097902,0.00097433187,0.000027669084,0.00012146224,0.00016089891],"about_ca_topic_score_codex":0.00004779614,"about_ca_topic_score_gemma":0.000010590209,"teacher_disagreement_score":0.025501475,"about_ca_system_score_codex":0.0000120971945,"about_ca_system_score_gemma":0.000037846647,"threshold_uncertainty_score":0.5390119},"labels":[],"label_agreement":null},{"id":"W2802608235","doi":"10.1002/hbm.24186","title":"Effects of<i>SYN1<sub>Q555X</sub></i>mutation on cortical gray matter microstructure","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Université du Québec à Trois-Rivières; Philips (Canada); Université de Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Savoy Foundation; Réseau en Bio-Imagerie du Quebec","keywords":"Fractional anisotropy; Diffusion MRI; Autism spectrum disorder; Psychology; Epilepsy; Nuclear magnetic resonance; Dyslexia; Autism; Connectome; Neuroscience; Medicine; Magnetic resonance imaging; Developmental psychology; Functional connectivity; Physics; Radiology","score_opus":0.02709015434167398,"score_gpt":0.32038294578242515,"score_spread":0.29329279144075115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802608235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9505066,0.000018221584,0.04499334,0.0023678425,0.000058528865,0.0005703933,0.0000049962455,0.00018447805,0.0012955873],"genre_scores_gemma":[0.99038523,0.0000031782104,0.003382951,0.0057849395,0.00023127998,0.000040549665,0.000042799875,0.000035193916,0.0000938662],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907535,0.00003776754,0.0002349593,0.00029608293,0.0001504918,0.0002053622],"domain_scores_gemma":[0.9992774,0.00015162563,0.00010659905,0.00031591937,0.000078272344,0.00007015976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008345486,0.00014509901,0.00020530174,0.00011630516,0.00019716722,0.00001456291,0.00008770573,0.000069925634,0.000048641832],"category_scores_gemma":[0.00009104956,0.00013475034,0.000072370414,0.00017179214,0.00020662675,0.000042089283,0.000039509832,0.00024471205,0.00008051685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021023097,0.000048526956,0.0013930214,0.00015401088,0.000010713898,0.000014767861,0.00015517668,7.597629e-7,0.9838532,0.0019317197,0.011603328,0.00081370876],"study_design_scores_gemma":[0.00070617953,0.00028083063,0.45114172,0.00035123102,0.000041916068,0.000060620274,0.000015283302,0.00006148036,0.52901053,0.010493983,0.007653239,0.0001829965],"about_ca_topic_score_codex":0.0000018066595,"about_ca_topic_score_gemma":8.7627626e-7,"teacher_disagreement_score":0.45484272,"about_ca_system_score_codex":0.00003244153,"about_ca_system_score_gemma":0.00001256442,"threshold_uncertainty_score":0.54949594},"labels":[],"label_agreement":null},{"id":"W2802754793","doi":"10.1161/str.49.suppl_1.wmp16","title":"Abstract WMP16: Elevated Cerebral Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Values Are Associated With Poor Neurologic Outcome in Comatose Cardiac Arrest Patients","year":2018,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Kurtosis; Coma (optics); Cardiology; Anesthesia; Internal medicine; Nuclear medicine; Magnetic resonance imaging; Radiology; Physics","score_opus":0.02124783518267544,"score_gpt":0.2911026425681579,"score_spread":0.26985480738548245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802754793","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9982471,0.000017361908,0.00011499262,0.00086908415,0.00006819,0.0004552967,0.000051660307,0.00013678215,0.00003956225],"genre_scores_gemma":[0.9988507,0.000028767026,0.000504717,0.00044694234,0.00003132893,0.000014992714,0.00008100414,0.000020334322,0.000021234326],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990464,0.000038958107,0.0001966213,0.0003509883,0.00016657374,0.00020044824],"domain_scores_gemma":[0.99944025,0.00005373254,0.00014825753,0.00017009178,0.00010496182,0.00008271101],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007891,0.00015304759,0.00023378969,0.00009179383,0.00013378783,0.000025703574,0.00004024103,0.00004404337,0.0000027129367],"category_scores_gemma":[0.000103937455,0.00012371846,0.000027002588,0.00015058645,0.00015354424,0.00012784853,0.00006843291,0.00018690678,0.000001351922],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010230442,0.00009817965,0.9885955,0.00001796012,0.000004828439,0.000009721189,0.00006665712,2.8192738e-7,0.010230828,0.000015950227,0.000037720096,0.0008200825],"study_design_scores_gemma":[0.00114236,0.00018179357,0.9956668,0.000061028015,0.000050646082,0.0000029594694,0.000060065413,0.0006741479,0.0018951899,0.0000963174,0.000051949894,0.00011673764],"about_ca_topic_score_codex":0.00006048275,"about_ca_topic_score_gemma":0.000016245664,"teacher_disagreement_score":0.008335638,"about_ca_system_score_codex":0.00004195995,"about_ca_system_score_gemma":0.00000752526,"threshold_uncertainty_score":0.50450927},"labels":[],"label_agreement":null},{"id":"W2803132175","doi":"10.1097/md.0000000000010858","title":"Cortical thickness contributes to cognitive heterogeneity in patients with type 2 diabetes mellitus","year":2018,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Medicine; Parahippocampal gyrus; Gyrus; Posterior cingulate; Middle frontal gyrus; Magnetic resonance imaging; Cardiology; Internal medicine; Temporal lobe; Cognition; Radiology; Psychiatry","score_opus":0.03729879803978029,"score_gpt":0.3477954183252305,"score_spread":0.31049662028545016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803132175","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98855436,0.00011952587,0.0059793177,0.0040678345,0.000059748996,0.0007133541,0.000007140399,0.00009061596,0.00040812592],"genre_scores_gemma":[0.9940021,0.00001284058,0.0010678892,0.004673359,0.00010338814,0.000048686503,0.00004538194,0.000017390634,0.0000289791],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99912363,0.000024593117,0.00018445135,0.0002601819,0.00017887831,0.00022827947],"domain_scores_gemma":[0.9991057,0.00012382184,0.00003577517,0.00021527077,0.00039011522,0.00012929643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121776335,0.00011530355,0.00027595388,0.00010188358,0.000052646086,0.0000032279615,0.000060490285,0.000038295228,0.00004750765],"category_scores_gemma":[0.00046774422,0.0000767899,0.000011994504,0.00047528534,0.00032116097,0.000026309122,0.000035890884,0.00016554416,0.000031860356],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053170027,0.00023643623,0.99032354,0.000020440426,0.000022876395,0.000006508195,0.00009548314,1.9327766e-7,0.0019190637,0.00028494478,0.0009954162,0.005563403],"study_design_scores_gemma":[0.0026147347,0.0023263183,0.98000073,0.0004940611,0.00007790081,0.0000018734132,0.000025505225,0.000041329025,0.00888221,0.0002748146,0.0051634167,0.000097116084],"about_ca_topic_score_codex":0.000009891433,"about_ca_topic_score_gemma":0.0000119302085,"teacher_disagreement_score":0.010322815,"about_ca_system_score_codex":0.00003629124,"about_ca_system_score_gemma":0.00002291123,"threshold_uncertainty_score":0.31314012},"labels":[],"label_agreement":null},{"id":"W2803143819","doi":"10.1186/s12888-018-1678-y","title":"Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy","year":2018,"lang":"en","type":"article","venue":"BMC Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Institute of Mental Health; National Institutes of Health; Otto von Guericke University Magdeburg; Grantová Agentura České Republiky; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Fractional anisotropy; Support vector machine; White matter; Artificial intelligence; Diffusion MRI; Machine learning; Voxel; Psychology; Medicine; Internal medicine; Psychiatry; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.031311570315625106,"score_gpt":0.32043863614544926,"score_spread":0.28912706582982417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803143819","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44674245,0.0003421092,0.506245,0.044599187,0.00019824054,0.0006073809,0.000036835234,0.00018779168,0.0010409874],"genre_scores_gemma":[0.8654381,0.0000233146,0.13331506,0.0005304042,0.00028610294,0.000020911795,0.00003197102,0.000033170414,0.00032094656],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911743,0.000029438404,0.00026718088,0.000293542,0.00013060802,0.00016176747],"domain_scores_gemma":[0.9993898,0.00003671605,0.00020484866,0.00026856572,0.000033645356,0.00006638108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008807388,0.0001326275,0.00018674856,0.00009977755,0.00020102206,0.000014835257,0.00006362174,0.000059509854,0.00012270246],"category_scores_gemma":[0.000029253428,0.00012728196,0.000061076,0.00016043248,0.00016184397,0.00009484921,0.000030763815,0.00021690495,0.000020109397],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002219885,0.00010034127,0.9907092,0.000052022435,0.000011657723,5.1100173e-8,0.00001639274,0.000029619978,0.0036278984,0.0036505533,0.0014193382,0.00016097969],"study_design_scores_gemma":[0.0017668215,0.00023755932,0.90869427,0.00010592825,0.000065945984,0.00005169724,0.000037918388,0.0461447,0.00014883351,0.013826424,0.028744342,0.00017556683],"about_ca_topic_score_codex":0.00005126757,"about_ca_topic_score_gemma":0.00019515019,"teacher_disagreement_score":0.41869566,"about_ca_system_score_codex":0.00002386784,"about_ca_system_score_gemma":0.000032484568,"threshold_uncertainty_score":0.51904076},"labels":[],"label_agreement":null},{"id":"W2803268487","doi":"10.1002/brb3.1010","title":"Altered white matter connectivity associated with visual hallucinations following occipital stroke","year":2018,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"White matter; Neuroscience; Visual cortex; Diffusion MRI; Tractography; Psychology; Visual system; Occipital lobe; Visual Hallucination; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.040264455028883525,"score_gpt":0.3596213435639656,"score_spread":0.31935688853508204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803268487","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918548,0.000005728075,0.0040919753,0.0025890134,0.000035009067,0.00038403444,0.00002809485,0.00015865361,0.0008526847],"genre_scores_gemma":[0.99404496,5.540596e-7,0.0024364328,0.00094529917,0.0000695519,0.000099571975,0.00003511003,0.0000214042,0.0023471126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993814,0.000017526378,0.00010106643,0.00023367415,0.00010942837,0.00015685285],"domain_scores_gemma":[0.99962175,0.00004760957,0.000045510344,0.00014738496,0.000060190632,0.00007757932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070377886,0.00010171342,0.00014062112,0.00005484024,0.00015496426,0.000024639336,0.000034314642,0.000042414482,0.00007585844],"category_scores_gemma":[0.000037451206,0.000084751446,0.000042346754,0.00010592877,0.00009372217,0.00008587656,0.000030257419,0.00011198959,0.000011590015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002982109,0.0005864709,0.9637379,0.0000064260553,0.000025065736,0.000028336233,0.00015991188,6.1606116e-8,0.029601999,0.00012891657,0.0028455213,0.0028495784],"study_design_scores_gemma":[0.00085557374,0.00039557196,0.99529517,0.00004488295,0.00014781462,0.000037277863,0.000044474575,0.000072212686,0.0022843434,0.000035709516,0.00066828047,0.00011867837],"about_ca_topic_score_codex":0.0000061386636,"about_ca_topic_score_gemma":0.000020719428,"teacher_disagreement_score":0.031557288,"about_ca_system_score_codex":0.000025907657,"about_ca_system_score_gemma":0.000018428216,"threshold_uncertainty_score":0.34560636},"labels":[],"label_agreement":null},{"id":"W2803916235","doi":"10.1016/j.neuroimage.2018.05.047","title":"Microstructural imaging of the human brain with a ‘super-scanner’: 10 key advantages of ultra-strong gradients for diffusion MRI","year":2018,"lang":"en","type":"review","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":206,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Medical Research Council Canada; Wellcome Trust; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Cancer Research UK","keywords":"Diffusion MRI; Scanner; Diffusion; Tractography; Materials science; Anisotropic diffusion; Computer science; Biomedical engineering; Nuclear magnetic resonance; Anisotropy; Magnetic resonance imaging; Artificial intelligence; Optics; Physics; Radiology; Medicine","score_opus":0.051943621094670954,"score_gpt":0.3765746836947506,"score_spread":0.3246310626000797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803916235","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023034014,0.94155264,0.0067885313,0.0020587833,0.00055030436,0.018911878,0.0034252438,0.00065880566,0.0030197802],"genre_scores_gemma":[0.013268555,0.9522686,0.02548437,0.0006981096,0.00062581187,0.00081706827,0.0009087449,0.000732401,0.005196309],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99797565,0.00007711647,0.00068446767,0.00064399745,0.00027058908,0.0003481913],"domain_scores_gemma":[0.99765086,0.00017678241,0.0007375898,0.0011555322,0.00019361981,0.000085621155],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010814421,0.00045780075,0.0012089354,0.00015577517,0.00018684696,0.000016797465,0.0005204182,0.000081189915,0.000021629081],"category_scores_gemma":[0.00010599471,0.00027875404,0.0005384625,0.00032892398,0.00058953057,0.000082996,0.00014000911,0.00038698135,0.0000015435988],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044867786,0.0014367598,0.0066574994,0.098588675,0.00045162486,0.0001061639,0.0006433548,0.0000023600194,0.33823213,0.0025655234,0.051204126,0.49966308],"study_design_scores_gemma":[0.0010232736,0.0004535016,0.0009892322,0.009198537,0.0010009672,0.0005090346,0.000016404942,0.000016492977,0.004875242,0.00014412632,0.98139554,0.00037765873],"about_ca_topic_score_codex":0.000010079239,"about_ca_topic_score_gemma":0.0000019652177,"teacher_disagreement_score":0.9301914,"about_ca_system_score_codex":0.00004599222,"about_ca_system_score_gemma":0.0000927157,"threshold_uncertainty_score":0.99996644},"labels":[],"label_agreement":null},{"id":"W2804787479","doi":"10.1038/s41593-019-0379-2","title":"The spatial correspondence and genetic influence of interhemispheric connectivity with white matter microstructure","year":2019,"lang":"en","type":"article","venue":"Nature Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; Wellcome Trust","keywords":"White matter; Functional connectivity; Neuroscience; Diffusion MRI; Genome-wide association study; Multivariate statistics; Biobank; Microstructure; Biology; Psychology; Magnetic resonance imaging; Genetics; Computer science; Medicine; Gene; Single-nucleotide polymorphism; Genotype","score_opus":0.006549790310904288,"score_gpt":0.2794167238913519,"score_spread":0.2728669335804476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804787479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963617,0.00008116986,0.0019015693,0.0010913901,0.000060349725,0.0003447084,0.0000048474503,0.000029020448,0.00012527696],"genre_scores_gemma":[0.99600786,0.000032082567,0.0014886633,0.0021294842,0.0000095241685,0.000009526881,2.7152694e-7,0.000009370533,0.00031321147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99923146,0.00001573526,0.00010087979,0.0003222074,0.00018557945,0.00014414462],"domain_scores_gemma":[0.99930114,0.000089285524,0.000092939445,0.00038628886,0.00008237728,0.000047961425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040246203,0.00009762145,0.00011381853,0.000020552885,0.00008504811,0.000023640489,0.00019199813,0.000053719406,0.000007620472],"category_scores_gemma":[0.00008108163,0.000058081736,0.000016506547,0.0002648848,0.0003953084,0.00007181748,0.000083863815,0.00042139663,0.0000022518477],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089571484,0.000010054994,0.53237414,0.000020676176,5.3672073e-7,0.000005572005,0.000021856522,0.00008386253,0.46664754,0.000047097015,0.00009343069,0.0006056751],"study_design_scores_gemma":[0.00016743559,0.00016663167,0.97612876,0.00004423972,0.0000069204557,0.00041218803,0.000006321191,0.0005119182,0.020532783,0.000107513806,0.0018506628,0.000064639185],"about_ca_topic_score_codex":0.000004939734,"about_ca_topic_score_gemma":0.0000027889905,"teacher_disagreement_score":0.44611475,"about_ca_system_score_codex":0.000009055725,"about_ca_system_score_gemma":0.000038446025,"threshold_uncertainty_score":0.23685044},"labels":[],"label_agreement":null},{"id":"W2805168298","doi":"10.1101/342436","title":"Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer’s Disease","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; University of Cape Town; Alzheimer's Disease Neuroimaging Initiative; Organization for Women in Science for the Developing World; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; University of Southern California; F. Hoffmann-La Roche; Styrelsen för Internationellt Utvecklingssamarbete; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Genome-wide association study; Neuroimaging; Disease; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Genetic association; Single-nucleotide polymorphism; Imaging genetics; Neuroscience; Biology; Computational biology; Medicine; Gene; Genetics; Genotype; Pathology","score_opus":0.06245420533810141,"score_gpt":0.31945832743342933,"score_spread":0.2570041220953279,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805168298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9814744,0.00036253006,0.008204491,0.0039061576,0.00022853221,0.0047590067,0.0005407693,0.00052035396,0.0000037694876],"genre_scores_gemma":[0.99026763,0.00007109183,0.006735693,0.00065765483,0.00044716705,0.0016902324,0.0000017931534,0.00012044612,0.000008293995],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979689,0.00008841231,0.0003970615,0.0008532403,0.0003387312,0.00035366538],"domain_scores_gemma":[0.9964675,0.0003968395,0.0007246725,0.001285164,0.0008798433,0.00024598936],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005941952,0.0003612692,0.0006319776,0.00020563522,0.0001346834,0.000036307818,0.0002698646,0.00021633675,0.000012348962],"category_scores_gemma":[0.0014698731,0.00039166238,0.00014117725,0.0002831397,0.00006743299,0.000055459124,0.00029323064,0.0003699673,0.000005510547],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044786037,0.0035853256,0.72615767,0.0010287804,0.0009763348,0.000028729679,0.000055337598,0.000022225006,0.26322573,0.00029247778,0.004170848,0.000008661977],"study_design_scores_gemma":[0.0011925653,0.00049121905,0.93715274,0.00021544554,0.0010317044,3.0879674e-9,0.000005065883,0.00018921398,0.048436206,0.000027894843,0.010793843,0.00046410234],"about_ca_topic_score_codex":0.000018858665,"about_ca_topic_score_gemma":0.0000036866466,"teacher_disagreement_score":0.21478952,"about_ca_system_score_codex":0.00028087507,"about_ca_system_score_gemma":0.00029829258,"threshold_uncertainty_score":0.99985355},"labels":[],"label_agreement":null},{"id":"W2805311321","doi":"10.1016/j.neuroimage.2018.05.077","title":"A supervised learning approach for diffusion MRI quality control with minimal training data","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; EPSRC Centre for Doctoral Training in Medical Imaging; NIH Blueprint for Neuroscience Research; Medical Research Council; Seventh Framework Programme; Medical Research Council Canada; McDonnell Center for Systems Neuroscience; Leverhulme Trust; European Research Council; National Institutes of Health; Royal Academy of Engineering; Engineering and Physical Sciences Research Council; University of Washington","keywords":"Computer science; Artificial intelligence; Classifier (UML); Machine learning; Convolutional neural network; Calibration; Process (computing); Pattern recognition (psychology); Data mining; Mathematics","score_opus":0.2173156371708592,"score_gpt":0.4026729381350168,"score_spread":0.18535730096415762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805311321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16393533,0.000016544165,0.82843083,0.0018560113,0.0000255215,0.0013365449,0.00010239955,0.0005171783,0.0037796625],"genre_scores_gemma":[0.7936756,0.000008157324,0.2041333,0.0011764829,0.0002566779,0.00011511386,0.00024507818,0.000054732354,0.00033483483],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984795,0.0000617937,0.00024824645,0.0006934797,0.00020240094,0.00031456686],"domain_scores_gemma":[0.99852043,0.00018102859,0.00010721288,0.0009441469,0.0001261379,0.000121064404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029982824,0.00017606925,0.0003094586,0.000056973116,0.0002516217,0.000032885193,0.00028351866,0.00004515676,0.000018207293],"category_scores_gemma":[0.00028176617,0.00014201482,0.000051830702,0.00016880082,0.00021098001,0.00015088666,0.000109423265,0.00028153928,0.000004316791],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0052310214,0.001415348,0.029471736,0.00050946436,0.00009736127,0.00006060485,0.0016267763,0.000052934538,0.8778321,0.0022892554,0.008736992,0.0726764],"study_design_scores_gemma":[0.02269013,0.0064544035,0.08141084,0.00021511831,0.0006290309,0.00057123177,0.0009868355,0.6319165,0.009783053,0.0004432761,0.24363616,0.0012634161],"about_ca_topic_score_codex":0.000008587524,"about_ca_topic_score_gemma":0.0000013142885,"teacher_disagreement_score":0.868049,"about_ca_system_score_codex":0.0000134453685,"about_ca_system_score_gemma":0.000054568543,"threshold_uncertainty_score":0.5791196},"labels":[],"label_agreement":null},{"id":"W2805625726","doi":"10.1109/isbi.2018.8363534","title":"Connectome priors in deep neural networks to predict autism","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Connectome; Computer science; Prior probability; Regularization (linguistics); Artificial intelligence; Connectomics; Autism; Artificial neural network; Human Connectome Project; Deep learning; Machine learning; Pattern recognition (psychology); Functional connectivity; Neuroscience; Psychology; Bayesian probability","score_opus":0.040013126448416224,"score_gpt":0.35073741450536466,"score_spread":0.31072428805694846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805625726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5132455,0.000027994993,0.46244124,0.012551788,0.00010170885,0.0009639447,0.0000015831806,0.0006919644,0.009974235],"genre_scores_gemma":[0.9783815,0.0000067620754,0.016613437,0.004316975,0.0001148458,0.00006087105,0.0000041557755,0.000016810849,0.00048462872],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993436,0.000008308748,0.00014717877,0.00021889812,0.00007489662,0.00020711923],"domain_scores_gemma":[0.9995206,0.000029329367,0.000019576573,0.00028539967,0.000026513893,0.0001185939],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005394241,0.00008070148,0.00012393859,0.00007960721,0.000036090845,0.0000071330965,0.00008016046,0.0000367707,0.00012295166],"category_scores_gemma":[0.00003439492,0.00006844917,0.000024561516,0.0003074397,0.000055252727,0.000038456543,0.000056762845,0.00013131279,0.000029517594],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012745213,0.0014307024,0.41788042,0.000107345026,0.000070393624,0.00039526538,0.0018083183,0.0035760808,0.028213536,0.1383039,0.044889748,0.36204976],"study_design_scores_gemma":[0.0015153445,0.0011612928,0.37097222,0.000083124716,0.000032080286,0.0001836209,0.00005634593,0.56744885,0.004512517,0.0030097056,0.050651036,0.00037384586],"about_ca_topic_score_codex":0.000022035043,"about_ca_topic_score_gemma":0.000028427108,"teacher_disagreement_score":0.5638728,"about_ca_system_score_codex":0.000029251938,"about_ca_system_score_gemma":0.000008132437,"threshold_uncertainty_score":0.2791276},"labels":[],"label_agreement":null},{"id":"W2805700032","doi":"10.1038/s41598-018-26627-7","title":"Alcohol use effects on adolescent brain development revealed by simultaneously removing confounding factors, identifying morphometric patterns, and classifying individuals","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Office of AIDS Research; National Institute of Allergy and Infectious Diseases; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; University of Alabama; Center for AIDS Research, University of Washington; National Institutes of Health; International AIDS Society; University of Alabama at Birmingham","keywords":"Confounding; Artificial intelligence; Functional magnetic resonance imaging; Machine learning; Cohort; Diffusion MRI; Magnetic resonance imaging; Psychology; Computer science; Medicine; Neuroscience; Pathology","score_opus":0.09894950361852398,"score_gpt":0.36577180731774067,"score_spread":0.26682230369921667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805700032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98613364,0.00009137743,0.011072099,0.00024256909,0.0009780033,0.0010856834,0.0000060829807,0.00031112495,0.000079414815],"genre_scores_gemma":[0.9891448,0.000014451588,0.008249773,0.0005172342,0.00008743037,0.000036900583,0.00012706536,0.000049594895,0.0017727469],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99691373,0.000059979986,0.0006563203,0.0011558689,0.000729232,0.00048484956],"domain_scores_gemma":[0.9978196,0.000424215,0.00046821326,0.000814148,0.0001880157,0.0002857963],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010192381,0.00028620768,0.00035619817,0.0005814242,0.0008097978,0.000496353,0.00011890558,0.00009155274,0.000022358412],"category_scores_gemma":[0.0015301418,0.00025637937,0.00006440432,0.0008349038,0.0002032508,0.00023692181,0.00017660129,0.00029599515,0.000008912346],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014122343,0.00014909873,0.7593997,0.0003198844,0.000036448626,0.00048443288,0.00050696364,0.000001073143,0.19408289,0.000018813138,0.023133943,0.021852642],"study_design_scores_gemma":[0.00083177106,0.00018516621,0.38268742,0.0030099005,0.000108686385,0.0011643133,0.00015302881,0.0003003784,0.4050367,0.00035736992,0.20539477,0.00077050587],"about_ca_topic_score_codex":0.000018464712,"about_ca_topic_score_gemma":0.0000034154828,"teacher_disagreement_score":0.37671226,"about_ca_system_score_codex":0.00018152675,"about_ca_system_score_gemma":0.00009174698,"threshold_uncertainty_score":0.99998885},"labels":[],"label_agreement":null},{"id":"W2806680184","doi":"10.1038/s41598-018-22985-4","title":"Altered Insulin/Insulin-Like Growth Factor Signaling in a Comorbid Rat model of Ischemia and β-Amyloid Toxicity","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research","keywords":"Insulin receptor; Internal medicine; Endocrinology; Basal forebrain; Insulin; Medicine; Striatum; Neuroscience; Psychology; Biology; Insulin resistance; Central nervous system; Dopamine","score_opus":0.06719222394954029,"score_gpt":0.32899416086149297,"score_spread":0.2618019369119527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806680184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98958737,0.000081356484,0.008752501,0.00023266766,0.0003567037,0.00042469462,0.000007736966,0.00008896332,0.00046802254],"genre_scores_gemma":[0.97879237,0.000019419824,0.020555742,0.0001265431,0.000048394322,0.000022123912,0.00001874839,0.000016872013,0.0003997938],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983933,0.0000143317175,0.00050607696,0.00060102623,0.0002720323,0.00021324385],"domain_scores_gemma":[0.9987499,0.000026369054,0.00024925306,0.00061330147,0.00024136157,0.00011982659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038790068,0.00012946925,0.0002612903,0.00016422893,0.00011513688,0.000033374057,0.00008046909,0.000056736917,0.000023628554],"category_scores_gemma":[0.00015669703,0.00011660351,0.000049457016,0.00041033956,0.00043782248,0.00011357843,0.00009973088,0.00015838239,0.0000018501354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025027306,0.000110799694,0.005448083,0.00004709637,0.0000033606625,0.00002833418,0.00027317385,0.000018200444,0.99223924,0.00008156991,0.0012008531,0.0005242602],"study_design_scores_gemma":[0.00029905775,0.000062038176,0.000662272,0.00011083425,0.000015211263,0.0001384954,0.000021662105,0.008429126,0.9780441,0.010660893,0.0014257726,0.00013051521],"about_ca_topic_score_codex":0.00001600999,"about_ca_topic_score_gemma":0.0000060680395,"teacher_disagreement_score":0.014195119,"about_ca_system_score_codex":0.000037603204,"about_ca_system_score_gemma":0.00011240593,"threshold_uncertainty_score":0.4754953},"labels":[],"label_agreement":null},{"id":"W2807651809","doi":"10.1007/s10334-018-0685-9","title":"Inferring diameters of spheres and cylinders using interstitial water","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba; Canadian Institutes of Health Research; University of Winnipeg; Canada Foundation for Innovation; Research Manitoba","keywords":"Diffusion; Volume (thermodynamics); Analytical Chemistry (journal); SPHERES; Materials science; Bead; Tube (container); Surface-area-to-volume ratio; RADIUS; Chemistry; Nuclear magnetic resonance; Composite material; Chromatography; Physics; Thermodynamics","score_opus":0.06763640712481932,"score_gpt":0.37534931229469465,"score_spread":0.3077129051698753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807651809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964343,0.00062211655,0.0020267444,0.00033036494,0.00010315389,0.00020385445,0.000005672686,0.000017842993,0.00025598714],"genre_scores_gemma":[0.99475664,0.00038129327,0.004250986,0.00030318112,0.00026401025,0.0000117068885,0.000007434199,0.00000996819,0.000014768214],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993399,0.000029125502,0.00023061482,0.00020634684,0.000037853122,0.00015619023],"domain_scores_gemma":[0.9997087,0.00003624398,0.000046065055,0.00014171994,0.00003197338,0.000035286655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010516487,0.000102239035,0.00029858557,0.000043109958,0.000033373326,0.000002486792,0.000039986986,0.000052248924,0.000068817484],"category_scores_gemma":[0.000035316163,0.00006887484,0.00000918393,0.00005507941,0.0010761368,0.000025327963,0.000069896894,0.00006207826,5.284732e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001498551,0.000021440968,0.012668226,0.00006397098,0.0000031606364,0.000003225387,0.00030842534,2.0632774e-7,0.9516946,0.0017642153,0.00001579604,0.033306863],"study_design_scores_gemma":[0.0025064996,0.0021381697,0.032836158,0.00080462225,0.00007417867,0.00007494467,0.00022545228,0.00034167324,0.9215914,0.036015525,0.0031863707,0.00020497438],"about_ca_topic_score_codex":0.00013564262,"about_ca_topic_score_gemma":0.00000548772,"teacher_disagreement_score":0.03425131,"about_ca_system_score_codex":0.000008185491,"about_ca_system_score_gemma":0.00000818697,"threshold_uncertainty_score":0.39650708},"labels":[],"label_agreement":null},{"id":"W2807820258","doi":"10.1038/sdata.2018.107","title":"Warping an atlas derived from serial histology to 5 high-resolution MRIs","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Western University; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Atlas (anatomy); Image warping; Histology; Computer science; High resolution; Artificial intelligence; Computer vision; Medicine; Anatomy; Pathology; Remote sensing; Geology","score_opus":0.1620349504297906,"score_gpt":0.3946804462657199,"score_spread":0.2326454958359293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807820258","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7839587,0.000029680621,0.2058075,0.0049767415,0.0018042388,0.00052049255,0.0021361636,0.0004308882,0.0003355959],"genre_scores_gemma":[0.7363564,0.0000036329955,0.252576,0.0006999499,0.0006648335,0.000024582903,0.008710485,0.00002230805,0.0009418495],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99863464,0.000024820172,0.00016622758,0.0008039621,0.00015460349,0.00021572968],"domain_scores_gemma":[0.99739236,0.000018934212,0.000053216452,0.002283815,0.000101067584,0.00015060126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002168848,0.00008439528,0.00013689372,0.00008972595,0.00030389984,0.00005919685,0.00058982475,0.000039738705,0.00019708881],"category_scores_gemma":[0.00015077594,0.0000805628,0.000014568854,0.0002905109,0.00031002198,0.00022857219,0.0005130089,0.000083393374,0.0003232016],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008624437,0.000107001346,0.00026808618,0.000005402574,0.000007437238,0.0000069354564,0.00016710752,0.0000021435021,0.7680967,0.0006693399,0.21905887,0.011524719],"study_design_scores_gemma":[0.0005192665,0.00020424974,0.009879001,0.00004750924,0.00006373487,0.000019415787,0.0000442912,0.0054478166,0.06893549,0.0035226564,0.9111119,0.00020468977],"about_ca_topic_score_codex":0.00034708806,"about_ca_topic_score_gemma":0.00020428516,"teacher_disagreement_score":0.69916123,"about_ca_system_score_codex":0.000046038524,"about_ca_system_score_gemma":0.00006259534,"threshold_uncertainty_score":0.41542104},"labels":[],"label_agreement":null},{"id":"W2808538832","doi":"10.1111/jon.12531","title":"Yakovlev's Basolateral Limbic Circuit in Multiple Sclerosis Related Cognitive Impairment","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; John S. Dunn Foundation","keywords":"Fractional anisotropy; Medicine; Diffusion MRI; Neuroscience; Cognition; Montreal Cognitive Assessment; Audiology; Magnetic resonance imaging; Cognitive impairment; Psychology; Psychiatry; Radiology","score_opus":0.13577067389362377,"score_gpt":0.3400989525921899,"score_spread":0.20432827869856615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808538832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99230427,0.000094497285,0.0031831914,0.0030608075,0.00015585801,0.0003172586,0.0000038390062,0.00007460226,0.00080570334],"genre_scores_gemma":[0.9955077,0.00010389704,0.00266075,0.0014280628,0.00017464052,0.0000069227563,0.0000019777337,0.000040072406,0.00007595014],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985773,0.000053618496,0.00060610974,0.00023090567,0.00024613025,0.00028596265],"domain_scores_gemma":[0.9988851,0.00013475346,0.00033990198,0.00019609508,0.0002966903,0.00014745668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002535697,0.00015571597,0.00031290235,0.0003495964,0.00009119668,0.000030542386,0.0001300706,0.00003822649,0.00005791844],"category_scores_gemma":[0.00022279989,0.00014081788,0.00013796301,0.00041937135,0.00014189155,0.00025302917,0.00005917407,0.0005697213,0.000018103165],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084429514,0.0014180411,0.53035104,0.00008348522,0.00009040627,0.0013698592,0.0016910486,0.000025974143,0.42384756,0.000165576,0.002128496,0.037984237],"study_design_scores_gemma":[0.005771296,0.0016844312,0.9519945,0.0016570766,0.00015332566,0.0037290715,0.00018326931,0.00428621,0.025801491,0.002197073,0.0022412364,0.00030103233],"about_ca_topic_score_codex":0.000009485446,"about_ca_topic_score_gemma":0.000001453072,"teacher_disagreement_score":0.42164344,"about_ca_system_score_codex":0.000092707356,"about_ca_system_score_gemma":0.00006746334,"threshold_uncertainty_score":0.5742386},"labels":[],"label_agreement":null},{"id":"W2809233735","doi":"10.1016/j.mri.2018.06.009","title":"Voxel-Wise Logistic Regression and Leave-One-Source-Out Cross Validation for white matter hyperintensity segmentation","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Vector Institute; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Segmentation; Computer science; Voxel; Fluid-attenuated inversion recovery; Pattern recognition (psychology); Hyperintensity; Logistic regression; Artificial intelligence; Similarity (geometry); Algorithm; Magnetic resonance imaging; Machine learning; Image (mathematics); Medicine","score_opus":0.07407320815730728,"score_gpt":0.3759359318396396,"score_spread":0.3018627236823323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809233735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5966039,0.0010650168,0.39177796,0.0072179176,0.00014737576,0.0014792954,0.000026258036,0.00031110618,0.0013712018],"genre_scores_gemma":[0.894713,0.000087760265,0.09737736,0.0015686144,0.00025397606,0.00018396888,0.000041318228,0.000049771334,0.0057242233],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883693,0.000020227959,0.00026031933,0.00046109752,0.0001562334,0.00026520644],"domain_scores_gemma":[0.999136,0.00005488531,0.00010894744,0.00037054162,0.00024814604,0.00008153427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014136046,0.00016652314,0.00019618873,0.00007273694,0.00024147228,0.00008109715,0.00007810007,0.000036367648,0.00008950336],"category_scores_gemma":[0.000102194164,0.00015422249,0.000044499244,0.000101061254,0.00033499618,0.00014628375,0.000076474505,0.00011726318,0.000036705063],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039835955,0.000094899435,0.65906316,0.00015715377,0.0000030007945,0.0000070212623,0.00046505014,0.000003898736,0.078170404,0.00008655859,0.0058041587,0.25574633],"study_design_scores_gemma":[0.0018525688,0.00031331004,0.8549567,0.00040998083,0.00009721301,0.00018843485,0.000117344236,0.01551383,0.046398487,0.0024939398,0.077287026,0.00037118408],"about_ca_topic_score_codex":0.000012592476,"about_ca_topic_score_gemma":0.0000011009913,"teacher_disagreement_score":0.29810914,"about_ca_system_score_codex":0.000046578913,"about_ca_system_score_gemma":0.000016188507,"threshold_uncertainty_score":0.62890106},"labels":[],"label_agreement":null},{"id":"W2810277203","doi":"10.1093/schbul/sby091","title":"Classification of First-Episode Schizophrenia Using Multimodal Brain Features: A Combined Structural and Diffusion Imaging Study","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Neuroimaging; Gyrification; Diffusion MRI; Artificial intelligence; Discriminative model; Fractional anisotropy; Pattern recognition (psychology); Parahippocampal gyrus; Psychology; Magnetic resonance imaging; Neuroscience; Computer science; Medicine; Radiology; Temporal lobe; Cerebral cortex","score_opus":0.030564212612422904,"score_gpt":0.32534361633564535,"score_spread":0.2947794037232224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810277203","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894177,0.000108491695,0.0022783244,0.00651963,0.00008124412,0.0012336757,0.00002104226,0.0002396338,0.00010031387],"genre_scores_gemma":[0.93981934,0.000009342065,0.05955805,0.00020451895,0.00020056692,0.000047758982,0.000024622024,0.00005270757,0.000083071995],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982877,0.00007429131,0.00044876555,0.0006005175,0.0002972315,0.00029152966],"domain_scores_gemma":[0.9985998,0.00012310527,0.0002617925,0.00064769556,0.00021689426,0.00015067043],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019127462,0.00028594455,0.0004041567,0.00020562,0.0003924888,0.00003885985,0.00018009756,0.0000755146,0.00008291823],"category_scores_gemma":[0.00021520065,0.0002555815,0.00007971052,0.00030496946,0.00037884834,0.000065047,0.0001900865,0.00033116023,0.000009268818],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010957375,0.0013783742,0.64661956,0.0002751449,0.00013561315,0.000050259772,0.0013488457,0.0000119467495,0.29238212,0.0047472464,0.0064788978,0.035614613],"study_design_scores_gemma":[0.00914571,0.0007904804,0.95808285,0.0002793506,0.00018514109,0.00020465883,0.0003941897,0.022792246,0.0034408993,0.0014576333,0.0027827942,0.00044406945],"about_ca_topic_score_codex":0.00026269807,"about_ca_topic_score_gemma":0.000073277035,"teacher_disagreement_score":0.31146327,"about_ca_system_score_codex":0.000054028438,"about_ca_system_score_gemma":0.00003013423,"threshold_uncertainty_score":0.9999896},"labels":[],"label_agreement":null},{"id":"W2810325419","doi":"10.1016/j.neuroimage.2018.06.045","title":"High-resolution 3D diffusion tensor MRI of anesthetized rhesus macaque brain at 3T","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Association Nationale de la Recherche et de la Technologie; Agence Nationale de la Recherche","keywords":"Diffusion MRI; White matter; Human Connectome Project; Macaque; Neuroscience; Magnetic resonance imaging; Connectome; Human brain; Computer science; Psychology; Medicine; Functional connectivity; Radiology","score_opus":0.03682248071453918,"score_gpt":0.3237640249850234,"score_spread":0.2869415442704842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810325419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9632509,0.000034561555,0.020795003,0.0115827145,0.0001104936,0.00083625,0.000038009006,0.00052412733,0.0028279787],"genre_scores_gemma":[0.9530821,0.00009878269,0.03974957,0.0026527669,0.00022844566,0.000049940718,0.00005071918,0.00006920776,0.0040185065],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987232,0.000051297517,0.00030599284,0.00042560007,0.00023604374,0.00025786884],"domain_scores_gemma":[0.99879086,0.00008980413,0.00016141697,0.00070363603,0.00014467744,0.00010957621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008035973,0.00017585399,0.00028799073,0.000110769586,0.00014355201,0.000007926922,0.00014128118,0.0000726063,0.00016308135],"category_scores_gemma":[0.00013571413,0.00015583017,0.000091208305,0.0002581052,0.00030606744,0.00006209718,0.00013394805,0.00018893865,0.000088854766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037037698,0.00023968506,0.002477648,0.00004953952,0.0000055494634,0.00006454612,0.000052761792,0.0000035273454,0.97084767,0.0016819305,0.020596553,0.003610218],"study_design_scores_gemma":[0.005481608,0.00225757,0.18106438,0.00024042018,0.00017554699,0.0011939507,0.000016860591,0.00676793,0.43881968,0.0031362893,0.36023656,0.0006092126],"about_ca_topic_score_codex":0.00004246878,"about_ca_topic_score_gemma":0.000004018073,"teacher_disagreement_score":0.53202796,"about_ca_system_score_codex":0.0000474354,"about_ca_system_score_gemma":0.00002265267,"threshold_uncertainty_score":0.63545704},"labels":[],"label_agreement":null},{"id":"W2810948267","doi":"10.1016/j.neuroimage.2018.06.072","title":"In vivo manganese tract tracing of frontal eye fields in rhesus macaques with ultra-high field MRI: Comparison with DWI tractography","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Neuroscience; Tracing; Diffusion MRI; In vivo; Saccadic masking; Tractography; Computer science; Magnetic resonance imaging; Biology; Eye movement; Medicine; Radiology","score_opus":0.02671317543621853,"score_gpt":0.33373560398211854,"score_spread":0.3070224285459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810948267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849931,0.000031384283,0.008192348,0.0017803503,0.000030209283,0.0005677155,0.000013923821,0.000108597,0.004282368],"genre_scores_gemma":[0.9885254,0.000040314673,0.010420526,0.0007763289,0.0000624089,0.000046576133,0.000005906236,0.00003703176,0.00008552686],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99870646,0.000036061057,0.00035623982,0.00040805462,0.00021067269,0.00028251382],"domain_scores_gemma":[0.9991748,0.00013369699,0.00013812211,0.00042145248,0.000055519533,0.00007646436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007463143,0.00020946653,0.00041090517,0.00025693842,0.00003989226,0.000014009499,0.00014269228,0.000084940744,0.000079959835],"category_scores_gemma":[0.000024945777,0.00016696047,0.00005618091,0.00047615598,0.00016588639,0.00019358008,0.000013984962,0.00053161004,0.000001930428],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025867594,0.0024906322,0.7657626,0.00029347368,0.00003024439,0.0011590421,0.0021464382,0.000083503975,0.21820165,0.0004244587,0.002545715,0.0042754803],"study_design_scores_gemma":[0.0030437624,0.0041211224,0.45996663,0.00047891168,0.000070867296,0.00025280856,0.00029827058,0.00053818483,0.52818125,0.0003113393,0.0023424276,0.00039442972],"about_ca_topic_score_codex":0.00046587278,"about_ca_topic_score_gemma":0.00053854863,"teacher_disagreement_score":0.30997962,"about_ca_system_score_codex":0.000018097622,"about_ca_system_score_gemma":0.00002725934,"threshold_uncertainty_score":0.680845},"labels":[],"label_agreement":null},{"id":"W2811003555","doi":"10.1159/000489491","title":"The Relationship between White Matter and Reading Acquisition, Refinement and Maintenance","year":2018,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"National Institute on Drug Abuse","keywords":"White matter; Neuroscience; Reading (process); Psychology; White (mutation); Cognitive psychology; Biology; Medicine; Linguistics; Genetics; Philosophy; Magnetic resonance imaging","score_opus":0.07529957441823172,"score_gpt":0.342031578114362,"score_spread":0.2667320036961303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811003555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9740786,0.000016461121,0.0072507,0.015473022,0.000051169554,0.00028955858,0.0000048591623,0.00007919681,0.0027564368],"genre_scores_gemma":[0.9823652,0.000026528527,0.012406897,0.0035215174,0.000030062316,0.000023916098,0.000002036489,0.000007578674,0.0016162995],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993254,0.0000109516295,0.00013180615,0.00025903602,0.00011454921,0.00015828005],"domain_scores_gemma":[0.9996484,0.00008516709,0.000042321975,0.00012445204,0.000030094452,0.000069597794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013506564,0.000071371884,0.000060181923,0.000032580356,0.0006291487,0.000047464877,0.000070333655,0.0000138940295,0.0000047658295],"category_scores_gemma":[0.00008372993,0.00005096638,0.0000071490995,0.000188893,0.00046842603,0.00009063969,0.000111145535,0.00008180967,0.000012048424],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046511836,0.0000039562055,0.9935014,0.000004042181,3.253661e-7,0.0000014607151,0.00005798282,1.4317988e-8,0.0023688474,0.0013582916,0.0018203624,0.00087861373],"study_design_scores_gemma":[0.00010232347,0.00003775172,0.97668374,0.00003181803,0.0000036907752,0.00012059406,0.000025673797,0.000019140143,0.0008712851,0.0012480069,0.020797627,0.000058342088],"about_ca_topic_score_codex":0.0000014542429,"about_ca_topic_score_gemma":5.0413695e-7,"teacher_disagreement_score":0.018977264,"about_ca_system_score_codex":0.000024584284,"about_ca_system_score_gemma":0.000018312589,"threshold_uncertainty_score":0.48389667},"labels":[],"label_agreement":null},{"id":"W2811045425","doi":"10.1101/356576","title":"Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; James S. McDonnell Foundation","keywords":"Connectome; Tractography; Macaque; Betweenness centrality; Human Connectome Project; Diffusion MRI; Modularity (biology); Connectomics; Computer science; Neuroscience; Network topology; Artificial intelligence; Topology (electrical circuits); Centrality; Pattern recognition (psychology); Psychology; Functional connectivity; Biology; Mathematics; Medicine; Magnetic resonance imaging; Evolutionary biology","score_opus":0.18416910244361595,"score_gpt":0.35850793081213295,"score_spread":0.174338828368517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811045425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98602337,0.000996627,0.01039855,0.0010867451,0.00023352802,0.0011211922,0.000019271436,0.00011813188,0.000002598798],"genre_scores_gemma":[0.96846724,0.0010166586,0.029411849,0.00042167006,0.00023500579,0.00040055878,2.5191787e-7,0.000046510326,2.3800759e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984741,0.00013126816,0.00043992983,0.0004730532,0.00020695201,0.0002746905],"domain_scores_gemma":[0.99814886,0.00035831792,0.00035387557,0.00085028,0.00023503201,0.0000536375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045930597,0.00028411002,0.00044887827,0.00017550706,0.00019175562,0.000027166137,0.00024068632,0.00013174488,0.0000024803003],"category_scores_gemma":[0.00018754542,0.00019401427,0.0000931169,0.0005615289,0.0005292487,0.000069985486,0.00012734986,0.00060983386,5.1128177e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004658217,0.0013675826,0.19092654,0.003475,0.00057733944,0.00018305176,0.0007563984,0.004634058,0.7899297,0.00679313,0.00060045155,0.00029092442],"study_design_scores_gemma":[0.0010167002,0.00024581573,0.9027293,0.0028121525,0.00065659935,6.3327076e-7,0.00007917453,0.029486423,0.061075896,0.00020528198,0.0010451273,0.00064691604],"about_ca_topic_score_codex":0.0000297766,"about_ca_topic_score_gemma":0.0000027589563,"teacher_disagreement_score":0.7288538,"about_ca_system_score_codex":0.00006010679,"about_ca_system_score_gemma":0.000118710115,"threshold_uncertainty_score":0.7911672},"labels":[],"label_agreement":null},{"id":"W2811225418","doi":"10.1017/cjn.2018.166","title":"P.064 Preoperative mapping using fMRI and DTI: a multimodal approach to assessing language dominance","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Saskatoon Medical Imaging","funders":"","keywords":"Arcuate fasciculus; Lateralization of brain function; Diffusion MRI; Precentral gyrus; Psychology; Wada test; Medicine; Neuroscience; Tractography; Radiology; Epilepsy surgery; Magnetic resonance imaging; Epilepsy","score_opus":0.1050975204146551,"score_gpt":0.3665366888966896,"score_spread":0.2614391684820345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811225418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890128,0.00044455894,0.005133847,0.0027476235,0.00018292443,0.00028100263,0.000005523902,0.000026557944,0.0021652037],"genre_scores_gemma":[0.86988103,0.00005659081,0.12596607,0.0037639497,0.0002999546,0.0000036114207,1.7102677e-7,0.00001125533,0.000017367149],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99718136,0.00032082226,0.000579189,0.0005631331,0.00043990815,0.0009156123],"domain_scores_gemma":[0.99725336,0.00020734969,0.0004163741,0.00015352806,0.00044171695,0.0015276747],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0018647353,0.000260372,0.000437631,0.0007444336,0.0025046146,0.0005618838,0.00077301654,0.000107568776,0.000019591478],"category_scores_gemma":[0.0013330297,0.00017975882,0.00010714086,0.0013082948,0.0053001163,0.0008125279,0.00009018899,0.0008317377,0.0000013504479],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014399998,0.00011499134,0.9683179,0.000028253637,0.000023119117,0.003284893,0.004127786,0.0018870871,0.006888382,0.0016359595,0.00064589555,0.012901692],"study_design_scores_gemma":[0.0013376895,0.082027175,0.64388806,0.00046620966,0.00016837993,0.17858665,0.0037702986,0.068367116,0.003284121,0.010527616,0.0063065505,0.0012701596],"about_ca_topic_score_codex":0.00060049264,"about_ca_topic_score_gemma":0.0020047463,"teacher_disagreement_score":0.3244299,"about_ca_system_score_codex":0.00016969819,"about_ca_system_score_gemma":0.0015116612,"threshold_uncertainty_score":0.99879396},"labels":[],"label_agreement":null},{"id":"W2811480054","doi":"10.1016/j.neuroimage.2018.08.012","title":"A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology","year":2018,"lang":"en","type":"preprint","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Universidad de Castilla-La Mancha; NIH Blueprint for Neuroscience Research; Fujirebio Europe; Eisai; Bristol-Myers Squibb; Ministerio de Economía y Competitividad; Lundbeckfonden; U.S. Department of Defense; Eli Lilly and Company; Eusko Jaurlaritza; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; National Center for Research Resources; F. Hoffmann-La Roche; National Institute of Neurological Disorders and Stroke; IXICO; Takeda Pharmaceutical Company; European Commission; AbbVie; European Research Council; Northern California Institute for Research and Education; Massachusetts General Hospital; Novartis Pharmaceuticals Corporation; University of Southern California; Roche; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics","keywords":"Thalamus; Ex vivo; Neuroimaging; Putamen; Atlas (anatomy); Segmentation; Neuroscience; Brain atlas; Human brain; Magnetic resonance imaging; Diffusion MRI; Computer science; In vivo; Artificial intelligence; Medicine; Anatomy; Biology; Radiology","score_opus":0.06383799917899072,"score_gpt":0.34536827674136117,"score_spread":0.2815302775623705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811480054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842282,0.00010624349,0.0008976397,0.003955787,0.00021384841,0.0015512707,0.000051260653,0.00027035896,0.008725369],"genre_scores_gemma":[0.9940383,0.0000656241,0.004195165,0.00052794727,0.00009513749,0.00008196134,0.000014962952,0.000071786126,0.00090916053],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985458,0.000077477416,0.0003390314,0.00064156344,0.00017721942,0.00021888918],"domain_scores_gemma":[0.9980664,0.00008790462,0.00035445573,0.0013102839,0.000114107665,0.00006681836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010264959,0.000256754,0.0004713784,0.000081077,0.00013611381,0.000016429638,0.00035284174,0.00014577228,0.000036486475],"category_scores_gemma":[0.000141747,0.00020237964,0.00013194385,0.000108058965,0.0008428526,0.000023608089,0.001022991,0.0008004541,0.000004841761],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001690232,0.0014565783,0.060287025,0.004619337,0.00014901707,0.0002224986,0.0011948412,0.000062379644,0.8199918,0.039221626,0.07040991,0.0022159617],"study_design_scores_gemma":[0.004985557,0.0021650328,0.47512275,0.0037560605,0.0021130836,0.0024006527,0.00008043024,0.007831373,0.07042111,0.26159248,0.16739951,0.002131949],"about_ca_topic_score_codex":0.00002655597,"about_ca_topic_score_gemma":0.0000036321017,"teacher_disagreement_score":0.74957067,"about_ca_system_score_codex":0.000045954035,"about_ca_system_score_gemma":0.00007016663,"threshold_uncertainty_score":0.82528025},"labels":[],"label_agreement":null},{"id":"W2847223726","doi":"10.1002/acn3.601","title":"Presymptomatic white matter integrity loss in familial frontotemporal dementia in the <scp>GENFI</scp> cohort: A cross‐sectional diffusion tensor imaging study","year":2018,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Occupational Cancer Research Centre; University of Toronto; Western University; Sunnybrook Health Science Centre","funders":"Medical Research Council; Stichting Dioraphte; Ministero della Salute; Erasmus Medisch Centrum; Alzheimer’s Research UK; Brain Research Trust; Wolfson Foundation; National Institute for Health and Care Research; Alzheimer Nederland; EU Joint Programme – Neurodegenerative Disease Research; ZonMw; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Canadian Institutes of Health Research; Wellcome","keywords":"C9orf72; Splenium; Corpus callosum; Medicine; White matter; Diffusion MRI; Internal capsule; Uncinate fasciculus; Fractional anisotropy; Frontotemporal dementia; Pathology; Dementia; Radiology; Magnetic resonance imaging; Disease","score_opus":0.1382471159744504,"score_gpt":0.4537488345202032,"score_spread":0.3155017185457528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2847223726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889255,0.0000648882,0.00072520407,0.009046204,0.00006959816,0.00071415177,0.000021276754,0.000022243068,0.00041090127],"genre_scores_gemma":[0.99407816,0.000043354736,0.00048748462,0.005121232,0.00015790688,0.00005853931,0.00001831095,0.000011276372,0.000023709963],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99796593,0.00027772537,0.00090396317,0.00040700813,0.00024437893,0.00020101997],"domain_scores_gemma":[0.9986824,0.0007577912,0.00015528375,0.0002186803,0.00012880407,0.000057033918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091517786,0.00013349575,0.0003420507,0.00010515898,0.000072680006,0.0000128885285,0.0001395772,0.00009185429,0.000033534317],"category_scores_gemma":[0.00016891344,0.000097593824,0.00010215246,0.00014857088,0.00055639783,0.000097470496,0.00003910625,0.0005417462,0.000006117028],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020521505,0.0009549798,0.997755,0.000015026166,0.000020882488,0.00002007398,0.00018360233,0.000006842054,0.0000097697775,0.00016863548,0.00019985021,0.00046011267],"study_design_scores_gemma":[0.0015866241,0.0004464608,0.98778445,0.000012570872,0.00002757631,0.000043881915,0.000013450639,0.0018750596,0.0000040413543,0.00759738,0.0005736849,0.00003483531],"about_ca_topic_score_codex":0.00007610588,"about_ca_topic_score_gemma":0.000099149045,"teacher_disagreement_score":0.009970576,"about_ca_system_score_codex":5.4435577e-7,"about_ca_system_score_gemma":0.00003675756,"threshold_uncertainty_score":0.39797604},"labels":[],"label_agreement":null},{"id":"W28615604","doi":"10.1007/978-3-642-38868-2_44","title":"Moving Frames for Heart Fiber Geometry","year":2013,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Geometry; Computer graphics (images); Fiber; Computer vision; Engineering drawing; Artificial intelligence; Mathematics; Engineering; Composite material; Materials science","score_opus":0.031902053099422636,"score_gpt":0.33720562827644507,"score_spread":0.30530357517702245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28615604","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09437327,0.000037978527,0.8991277,0.0058188825,0.00006166447,0.00045608144,7.6219874e-7,0.000104934305,0.000018675813],"genre_scores_gemma":[0.5100816,0.0000012657164,0.48711547,0.0026745978,0.00007110135,0.000045177803,6.717805e-7,0.0000051354723,0.0000049949595],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991765,0.000004243652,0.000112626425,0.00032749656,0.00013733369,0.0002417688],"domain_scores_gemma":[0.9992909,0.00020440161,0.000025703015,0.00032313573,0.00009017331,0.0000657303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011287935,0.00007995715,0.00011820097,0.00014610958,0.00009818586,0.00005217107,0.00017940969,0.000032528347,0.00003037097],"category_scores_gemma":[0.00014005891,0.00006503671,0.000033029373,0.00060608616,0.00016491298,0.00013952873,0.00009389237,0.00014365923,0.000017709637],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006123042,0.00008126574,0.012356667,0.00004908702,0.0000024914805,0.0000024671933,0.00017175252,0.0049438747,0.039153248,0.00027165233,0.00072008,0.9422413],"study_design_scores_gemma":[0.0006365486,0.0003735217,0.060301732,0.00020583584,0.000010523352,0.00014108712,0.0000012488614,0.6706234,0.15416464,0.10264385,0.010502302,0.0003952542],"about_ca_topic_score_codex":0.000016601132,"about_ca_topic_score_gemma":5.680039e-7,"teacher_disagreement_score":0.941846,"about_ca_system_score_codex":0.000036992424,"about_ca_system_score_gemma":0.000044682136,"threshold_uncertainty_score":0.265212},"labels":[],"label_agreement":null},{"id":"W286640797","doi":"10.1007/978-3-319-11182-7_13","title":"Diffusion Propagator Estimation Using Gaussians Scattered in q-Space","year":2014,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Propagator; Gaussian; Basis (linear algebra); Diffusion; Basis function; Diffusion MRI; Radial basis function; Statistical physics; Orientation (vector space); Mathematics; Mathematical analysis; Physics; Computer science; Geometry; Artificial intelligence","score_opus":0.08375704491233274,"score_gpt":0.37670314711074593,"score_spread":0.2929461021984132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W286640797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036990882,0.00006955812,0.9777248,0.0003073541,0.000023384871,0.0010677997,0.000007915298,0.00014679691,0.016953323],"genre_scores_gemma":[0.25686213,0.0014982714,0.6013577,0.0011112812,0.0004436542,0.000191707,0.0010187408,0.000737953,0.1367786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99911404,0.000005719539,0.0003462325,0.00025909225,0.00016678822,0.0001081428],"domain_scores_gemma":[0.99933666,0.000028244158,0.00026107754,0.00025963972,0.000056973753,0.00005741109],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001005759,0.00020280492,0.00032906706,0.0002002633,0.00006507919,0.000028635135,0.000039279304,0.00015189932,0.00002637937],"category_scores_gemma":[0.000036491427,0.0001849502,0.00003845325,0.000053188392,0.00004830634,0.00003564849,0.000043611075,0.00012780029,0.000006667809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013532098,0.00012488602,0.00016030313,0.0015556463,0.0000126676605,0.0000068035374,0.0003314663,0.000051267514,0.0055757784,0.9857159,0.0002925241,0.006159212],"study_design_scores_gemma":[0.00074149814,0.00014415146,0.0001562289,0.0038945752,0.00020882834,0.000115084695,0.000018573666,0.86524314,0.0009796497,0.11807268,0.009976929,0.00044868022],"about_ca_topic_score_codex":0.0000032703595,"about_ca_topic_score_gemma":0.0000011745357,"teacher_disagreement_score":0.86764324,"about_ca_system_score_codex":0.000064411506,"about_ca_system_score_gemma":0.000025662197,"threshold_uncertainty_score":0.75420505},"labels":[],"label_agreement":null},{"id":"W28703433","doi":"10.1002/chem.201703215","title":"22 DWI volume color-coded mapとDTI tractographyによる白質神経線維走行可視化結果の比較(北日本脳神経外科連合会第30回学術集会)","year":2007,"lang":"en","type":"article","venue":"新潟医学会雑誌","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Volume (thermodynamics); Artificial intelligence; Computer vision; Computer science; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging; Physics","score_opus":0.05908910226020175,"score_gpt":0.37028104855537053,"score_spread":0.3111919462951688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28703433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6561528,0.00053819094,0.22164552,0.008654549,0.00036155345,0.0022396257,0.00006153029,0.002813421,0.107532814],"genre_scores_gemma":[0.9205891,0.00009658917,0.07235138,0.0019439155,0.00027144788,0.00007485481,0.00005640331,0.00007016016,0.004546126],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99834484,0.000014922895,0.0003820606,0.00045867692,0.0002853307,0.00051419094],"domain_scores_gemma":[0.9986839,0.000080406666,0.00011873613,0.0006862508,0.00015721521,0.00027343506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028735603,0.00022995695,0.00031046124,0.00022039903,0.0001522253,0.00002194143,0.00018961389,0.00012940122,0.00030850247],"category_scores_gemma":[0.00007433126,0.00021830227,0.00017195338,0.00073382206,0.00012663168,0.00010312298,0.00005600711,0.0003885663,0.0002123311],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090884743,0.0023430723,0.12521651,0.0002353912,0.00018884847,0.0005926876,0.00043310437,0.000025268237,0.56438416,0.028954154,0.16877587,0.10794209],"study_design_scores_gemma":[0.0012183985,0.0003896399,0.13461508,0.00006729002,0.00012024433,0.00036730297,0.00008736737,0.00036085202,0.03131221,0.0028406882,0.82820815,0.00041279185],"about_ca_topic_score_codex":0.000029238867,"about_ca_topic_score_gemma":0.000013854631,"teacher_disagreement_score":0.6594323,"about_ca_system_score_codex":0.00006528481,"about_ca_system_score_gemma":0.00004600436,"threshold_uncertainty_score":0.8902108},"labels":[],"label_agreement":null},{"id":"W2883037454","doi":"10.1016/j.mri.2018.07.011","title":"Scan-rescan repeatability and cross-scanner comparability of DTI metrics in healthy subjects in the SPRINT-MS multicenter trial","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroRx Research (Canada); Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Repeatability; Scanner; Siemens; Nuclear medicine; Diffusion MRI; Fractional anisotropy; Medicine; Mathematics; Physics; Magnetic resonance imaging; Artificial intelligence; Computer science; Statistics; Radiology","score_opus":0.07056010756874385,"score_gpt":0.3980813807907984,"score_spread":0.32752127322205454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883037454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924124,0.0019316165,0.00034928293,0.0026616524,0.00006090049,0.0015469424,0.000011198041,0.000039212377,0.0009867777],"genre_scores_gemma":[0.9929951,0.000105862055,0.0060272883,0.0006313119,0.00007511961,0.00011556382,0.000003012335,0.000015107692,0.000031645643],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981188,0.00014609747,0.0006086697,0.00052300334,0.0002642953,0.0003390921],"domain_scores_gemma":[0.9985483,0.00030143993,0.00012643737,0.00082692696,0.00012817027,0.00006871553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011013767,0.00015523467,0.0003425263,0.00016554336,0.000072715,0.000030040976,0.00021404364,0.000033900546,0.000026095237],"category_scores_gemma":[0.00065935415,0.00012093141,0.000051083403,0.00072516256,0.00078224775,0.00009561052,0.00010677082,0.0003236739,0.0000015687551],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004435143,0.00037454977,0.9325597,0.000072170595,5.9208685e-7,0.000008888526,0.00032476248,0.0000013876781,0.00044882402,0.00021841945,0.00006631935,0.061489217],"study_design_scores_gemma":[0.010673143,0.00039991387,0.9747282,0.00008717477,0.000008948872,0.000016067785,0.00007655968,0.0041040275,0.0006848564,0.00060147676,0.008515151,0.000104458384],"about_ca_topic_score_codex":0.0014172627,"about_ca_topic_score_gemma":0.00027374405,"teacher_disagreement_score":0.06138476,"about_ca_system_score_codex":0.00009775976,"about_ca_system_score_gemma":0.00008216534,"threshold_uncertainty_score":0.49314395},"labels":[],"label_agreement":null},{"id":"W2883215471","doi":"10.3389/fninf.2018.00057","title":"Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Aging; National Institutes of Health; National Natural Science Foundation of China","keywords":"Upsampling; Diffusion MRI; Spherical harmonics; Diffusion; Regularization (linguistics); Interpolation (computer graphics); Computer science; Algorithm; Matching (statistics); Scanner; Mathematics; Artificial intelligence; Mathematical analysis; Physics; Magnetic resonance imaging; Statistics","score_opus":0.03758903992502172,"score_gpt":0.3275924135135114,"score_spread":0.2900033735884897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883215471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60220534,0.000050282935,0.395668,0.0004033969,0.00017014772,0.00050445227,0.0000031278448,0.0000779537,0.0009172925],"genre_scores_gemma":[0.6255834,0.00018022823,0.37358755,0.00052563223,0.000056215005,0.000013237074,0.0000083530085,0.00003027732,0.000015098526],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864256,0.000021421307,0.00057005964,0.00020238884,0.00019789963,0.00036569146],"domain_scores_gemma":[0.9992997,0.000032824762,0.00014383353,0.00041679395,0.000031911062,0.000074903604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019819244,0.00017618404,0.00032725374,0.00061190536,0.00006096889,0.000025000347,0.0001501347,0.00007744767,0.0000036977367],"category_scores_gemma":[0.000095235526,0.00017841178,0.00004196594,0.00077822263,0.000080451,0.00029536145,0.0001271002,0.00045586244,0.0000032161722],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023395925,0.00046853215,0.956607,0.0004075446,0.000010644039,0.0002107157,0.008264487,0.013824323,0.0072544017,0.003460409,0.0013164523,0.007941553],"study_design_scores_gemma":[0.0015700088,0.00012474612,0.033785168,0.0006719237,0.000015057468,0.00007795884,0.0011344656,0.94842833,0.0010461481,0.01003164,0.002818984,0.00029559014],"about_ca_topic_score_codex":0.00005148419,"about_ca_topic_score_gemma":0.000014181763,"teacher_disagreement_score":0.934604,"about_ca_system_score_codex":0.0001544097,"about_ca_system_score_gemma":0.000051462914,"threshold_uncertainty_score":0.7275421},"labels":[],"label_agreement":null},{"id":"W2883730994","doi":"10.1007/s00234-018-2053-x","title":"Impact of white matter hyperintensities on surrounding white matter tracts","year":2018,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Hyperintensity; White matter; Neuroradiology; Medicine; Neurology; White (mutation); Magnetic resonance imaging; Neurosurgery; Pathology; Radiology; Biology; Psychiatry","score_opus":0.06462821543391545,"score_gpt":0.3667525050291711,"score_spread":0.30212428959525567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883730994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.984507,0.0000059798044,0.0011210947,0.0038175131,0.0001280572,0.0002139941,0.000015541795,0.00009585252,0.01009494],"genre_scores_gemma":[0.99142104,0.000009039905,0.0015606715,0.0055259513,0.0002016812,0.000017552695,0.000010907284,0.000039960516,0.0012131621],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907583,0.00004409515,0.00022989718,0.00030648042,0.000077074714,0.00026661844],"domain_scores_gemma":[0.9991612,0.00006609373,0.00010476873,0.00048399574,0.00010608589,0.00007784277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052791514,0.00015965138,0.00033347023,0.00014490799,0.00007861361,0.0000057076595,0.0001022075,0.00006802072,0.0006354897],"category_scores_gemma":[0.000027476282,0.0001275461,0.00011998371,0.00012774234,0.0002781847,0.000052966774,0.00004993447,0.00022463626,0.00026238523],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015889408,0.00007462763,0.9524303,0.000017235086,0.000015574376,0.00001954396,0.0001390833,0.000008637128,0.024861833,0.00014437133,0.022020133,0.00010972995],"study_design_scores_gemma":[0.0002793132,0.0010918567,0.99172264,0.000029781006,0.000024065372,0.0008145039,0.000010975692,0.00006278112,0.0018438542,0.00023319354,0.0037863725,0.000100640646],"about_ca_topic_score_codex":0.000009280622,"about_ca_topic_score_gemma":5.860079e-7,"teacher_disagreement_score":0.039292328,"about_ca_system_score_codex":0.000036606943,"about_ca_system_score_gemma":0.000022514387,"threshold_uncertainty_score":0.6958167},"labels":[],"label_agreement":null},{"id":"W2885277692","doi":"10.2147/ndt.s169583","title":"Abnormal white matter integrity in Chinese young adults with first-episode medication-free anxious depression: a possible neurological biomarker of subtype major depressive disorder","year":2018,"lang":"en","type":"article","venue":"Neuropsychiatric Disease and Treatment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Uncinate fasciculus; Fractional anisotropy; Major depressive disorder; White matter; Medicine; Diffusion MRI; Depression (economics); Anxiety; Superior longitudinal fasciculus; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology; Mood","score_opus":0.01220636934380843,"score_gpt":0.2826764052142453,"score_spread":0.2704700358704369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885277692","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9932064,0.00068985,0.00049443345,0.003966055,0.000053289164,0.00090079993,0.000057194466,0.00008495434,0.00054702885],"genre_scores_gemma":[0.9963661,0.0004765725,0.002156582,0.00044760638,0.00007804881,0.00030580637,0.00004580356,0.000030009407,0.0000934618],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865884,0.000045461722,0.0002938017,0.0005579315,0.00020566414,0.00023830934],"domain_scores_gemma":[0.9987656,0.0000615808,0.0001463598,0.0006903495,0.00007875797,0.00025733598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029942237,0.00025838308,0.00027926435,0.00015850838,0.00012760203,0.000013788825,0.00014028186,0.000053535612,0.00008294394],"category_scores_gemma":[0.00004244079,0.0001571364,0.00006980129,0.0004271845,0.00019929197,0.000089122805,0.00009193863,0.00014455966,0.000007734212],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024409934,0.0012657463,0.9933064,0.00005486939,0.000027730965,0.00011156564,0.0000769792,0.0000025271206,0.000007207666,0.000021859361,0.00043493672,0.0022491757],"study_design_scores_gemma":[0.0043174606,0.00087753806,0.99295235,0.00007530813,0.00021210185,0.000114988194,0.000008076009,0.0007765301,0.000012053478,0.00033907,0.00017953239,0.00013499775],"about_ca_topic_score_codex":0.00026245866,"about_ca_topic_score_gemma":0.0005675671,"teacher_disagreement_score":0.0035184487,"about_ca_system_score_codex":0.000016592947,"about_ca_system_score_gemma":0.0000523552,"threshold_uncertainty_score":0.64078367},"labels":[],"label_agreement":null},{"id":"W2885417691","doi":"10.1016/j.nicl.2018.08.021","title":"Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Tractography; Diffusion MRI; Siemens; Protocol (science); Variance (accounting); Epilepsy surgery; Temporal lobe; Nuclear medicine; Computer science; Artificial intelligence; Psychology; Medicine; Radiology; Physics; Magnetic resonance imaging; Neuroscience; Electroencephalography; Epilepsy; Pathology","score_opus":0.23602589910635866,"score_gpt":0.5001529943187989,"score_spread":0.26412709521244027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885417691","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44326666,0.0000717255,0.17266288,0.061932757,0.001478229,0.29082593,0.00042720523,0.005779722,0.023554875],"genre_scores_gemma":[0.59683675,0.0001567567,0.20077401,0.04700447,0.004932668,0.14746678,0.00015650789,0.00066890474,0.002003159],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975131,0.00009158359,0.00081286405,0.0009391021,0.00023089082,0.00041242433],"domain_scores_gemma":[0.99706495,0.0012642603,0.00023730118,0.0008208744,0.00031611955,0.00029652595],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006492107,0.00027935894,0.0005364394,0.00018967506,0.0002186813,0.000069661866,0.0001559222,0.00009390349,0.00004512524],"category_scores_gemma":[0.001585908,0.00024662822,0.00038418703,0.0002596771,0.00063540816,0.00017059341,0.00009146711,0.00049447134,0.000027050142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029918235,0.002732011,0.2160801,0.000563785,0.00008507449,0.0005363482,0.00004300829,2.8807924e-7,0.03521029,0.0010342037,0.3978571,0.34286597],"study_design_scores_gemma":[0.005752989,0.0021861657,0.22948994,0.0003506394,0.00024155201,0.0007478203,0.00001855605,0.0020520869,0.02885736,0.0032853603,0.72623795,0.000779583],"about_ca_topic_score_codex":0.000002977578,"about_ca_topic_score_gemma":6.2249995e-7,"teacher_disagreement_score":0.3420864,"about_ca_system_score_codex":0.000013209039,"about_ca_system_score_gemma":0.000079399084,"threshold_uncertainty_score":0.99999857},"labels":[],"label_agreement":null},{"id":"W2885904423","doi":"10.3389/fneur.2018.00575","title":"Pathological Insights From Quantitative Susceptibility Mapping and Diffusion Tensor Imaging in Ice Hockey Players Pre and Post-concussion","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Vertex Pharmaceuticals; Canadian Institutes of Health Research; Teva Pharmaceutical Industries; Biogen; Celgene; Sanofi","keywords":"Myelin; Diffusion MRI; White matter; Fractional anisotropy; Concussion; Voxel; Chemistry; Biophysics; Neuroscience; Magnetic resonance imaging; Medicine; Psychology; Biology; Radiology; Poison control; Central nervous system","score_opus":0.027008619643349708,"score_gpt":0.30872483542783874,"score_spread":0.281716215784489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885904423","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98422563,0.0004086236,0.011596337,0.0030012813,0.00011857505,0.00047207467,0.0000097164075,0.0000777802,0.00008998713],"genre_scores_gemma":[0.9683716,0.00020256017,0.02888724,0.002432026,0.000036334328,0.000028245528,0.000014681833,0.000014931465,0.0000123651025],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99873006,0.00012870571,0.00024832357,0.00060682686,0.00007239266,0.00021368406],"domain_scores_gemma":[0.99946994,0.00011155742,0.000075028765,0.00023413877,0.000043128144,0.000066228495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085043146,0.00014897528,0.00029904334,0.00020317035,0.00007911213,0.0000088229235,0.00007183501,0.00010804189,0.000003965119],"category_scores_gemma":[0.0002177647,0.00012190039,0.000020479243,0.0001635166,0.0004965468,0.00009091064,0.00014713872,0.00038231688,9.45492e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006576,0.00008375337,0.93109995,0.000011893534,0.000002105612,0.00011592708,0.00100872,0.0000010122741,0.058645796,0.00014870909,0.00026544847,0.007959095],"study_design_scores_gemma":[0.0010269393,0.00048000691,0.9824804,0.000038539947,0.000009397057,0.000049816048,0.00033265838,0.009804408,0.0002887709,0.0044212397,0.00095631287,0.00011150947],"about_ca_topic_score_codex":0.00011799306,"about_ca_topic_score_gemma":0.000037750826,"teacher_disagreement_score":0.058357026,"about_ca_system_score_codex":0.000022810274,"about_ca_system_score_gemma":0.000012816224,"threshold_uncertainty_score":0.49709535},"labels":[],"label_agreement":null},{"id":"W2885963010","doi":"10.1016/j.nicl.2018.101650","title":"Girls' internalizing symptoms and white matter tracts in Cortico-Limbic circuitry","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Western University; Canada Foundation for Innovation; Fondation Brain Canada; Children's Health Research Institute","keywords":"Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); White matter; Psychology; Diffusion MRI; Limbic system; Fasciculus; Psychopathology; Neuroscience; Audiology; Developmental psychology; Medicine; Clinical psychology; Magnetic resonance imaging; Central nervous system","score_opus":0.12614242268611708,"score_gpt":0.4423561381816067,"score_spread":0.3162137154954896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2885963010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875116,0.000032315485,0.0026687155,0.00397241,0.0001755855,0.00035162875,0.0000040095747,0.00016854994,0.005115231],"genre_scores_gemma":[0.9856522,0.000083664214,0.0026594629,0.010581623,0.00033516152,0.00002328056,0.000004264807,0.00004550964,0.0006148352],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998276,0.0000690127,0.00063840393,0.00059023954,0.00014279627,0.00028357303],"domain_scores_gemma":[0.99886763,0.00021113282,0.00012746928,0.0005414958,0.00006296852,0.00018931308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024306895,0.0001607578,0.0003424476,0.00009989197,0.00005185745,0.000034330205,0.00013280024,0.00009532697,0.00014881467],"category_scores_gemma":[0.00026575272,0.00015136805,0.00008948211,0.00017283918,0.00043028887,0.00011680234,0.00012409389,0.00062282884,0.00015552457],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000684685,0.00024463618,0.98431623,0.000024109797,0.0000057496486,0.00015658067,0.000038296625,9.939893e-8,0.003345523,0.00006901343,0.0024756638,0.009255625],"study_design_scores_gemma":[0.00093966204,0.0004077958,0.9869915,0.00011466288,0.00003711469,0.00037228284,0.000006572138,0.00033654153,0.0005000191,0.0005678311,0.009590542,0.00013544403],"about_ca_topic_score_codex":0.0000045907027,"about_ca_topic_score_gemma":0.000003093602,"teacher_disagreement_score":0.009120181,"about_ca_system_score_codex":0.00001843094,"about_ca_system_score_gemma":0.000029635521,"threshold_uncertainty_score":0.61726093},"labels":[],"label_agreement":null},{"id":"W2886571235","doi":"10.1097/md.0000000000011803","title":"Cognitive decline and white matter changes in mesial temporal lobe epilepsy","year":2018,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Fractional anisotropy; Fasciculus; Uncinate fasciculus; Superior longitudinal fasciculus; Diffusion MRI; Hippocampal sclerosis; Corpus callosum; Epilepsy; Voxel-based morphometry; Temporal lobe; Cardiology; Magnetic resonance imaging; Anatomy; Radiology; Psychiatry","score_opus":0.060242372306823694,"score_gpt":0.38086392421319853,"score_spread":0.32062155190637487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886571235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8415935,0.00020776925,0.008930877,0.14083034,0.000090136135,0.0006975868,0.000011166573,0.00014676875,0.007491879],"genre_scores_gemma":[0.9834711,0.00009489637,0.0030523646,0.011875039,0.0006665074,0.000050287174,0.000034418703,0.000020424366,0.00073497003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924344,0.000016962285,0.00017408408,0.0002591054,0.00013152999,0.00017489081],"domain_scores_gemma":[0.9995509,0.000050200808,0.000053166514,0.00017018353,0.00007778755,0.00009780826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015317004,0.00011702299,0.00024803705,0.000134788,0.000040169416,0.00000326157,0.000047025147,0.000043066437,0.0005394979],"category_scores_gemma":[0.000076061035,0.00008783576,0.000012226545,0.00021394658,0.00039723978,0.000030606534,0.000059965856,0.00015124465,0.000037001068],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014022927,0.000056372843,0.9827228,0.0000311474,0.0000051069824,0.000041323136,0.00032320732,1.205408e-8,0.0020151888,0.00008847609,0.008372566,0.006203575],"study_design_scores_gemma":[0.0021368766,0.00073351734,0.969609,0.00040471702,0.000049887032,0.00015317823,0.00015262133,0.000105572624,0.0019020829,0.0012941957,0.023346376,0.000111947375],"about_ca_topic_score_codex":0.000066577835,"about_ca_topic_score_gemma":0.00011647794,"teacher_disagreement_score":0.14187762,"about_ca_system_score_codex":0.000015151571,"about_ca_system_score_gemma":0.000012435472,"threshold_uncertainty_score":0.59071237},"labels":[],"label_agreement":null},{"id":"W2886832730","doi":"10.1093/schbul/sby016.418","title":"T142. PARIETAL CONNECTIVITY IN SCHIZOPHRENIA AND PSYCHOTIC BIPOLAR DISORDER: A COMBINED STRUCTURAL AND DYNAMIC FUNCTIONAL CONNECTIVITY STUDY","year":2018,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Supramarginal gyrus; Parietal lobe; Psychology; Schizophrenia (object-oriented programming); Resting state fMRI; Bipolar disorder; Neuroscience; Psychosis; Temporal lobe; Fractional anisotropy; Middle frontal gyrus; Superior temporal gyrus; Angular gyrus; Diffusion MRI; Functional magnetic resonance imaging; Psychiatry; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.021794763789255628,"score_gpt":0.3014564537811058,"score_spread":0.27966168999185015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886832730","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99360067,0.0004174231,0.0016966285,0.0024559177,0.00009292649,0.0012676595,0.000021537195,0.0002829626,0.00016428935],"genre_scores_gemma":[0.99391,0.00004530307,0.005428161,0.00015702665,0.00008122252,0.00011107559,0.000015386293,0.00006332149,0.00018846647],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99831283,0.00011435509,0.00029825186,0.0007508692,0.0002067113,0.00031695233],"domain_scores_gemma":[0.9990495,0.00014764715,0.00011238491,0.00044314086,0.000072541785,0.00017481961],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022986934,0.0003060799,0.0004296678,0.00020510731,0.00027406338,0.000046792353,0.00008809724,0.00009396651,0.00024317876],"category_scores_gemma":[0.00016881389,0.0002854141,0.00004741155,0.00032266206,0.00046882205,0.000066158755,0.00014083652,0.0004507061,0.00003300716],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.013810059,0.002029791,0.88486123,0.00013329583,0.00018221674,0.000082591134,0.0004620636,0.000005848266,0.008284317,0.013070388,0.0011261082,0.075952105],"study_design_scores_gemma":[0.009223239,0.0012715451,0.9771436,0.000055276898,0.00007704312,0.00018154441,0.000103295206,0.0020335107,0.00009690461,0.0052823466,0.004194475,0.00033720932],"about_ca_topic_score_codex":0.00013501245,"about_ca_topic_score_gemma":0.00051285035,"teacher_disagreement_score":0.09228239,"about_ca_system_score_codex":0.000041823412,"about_ca_system_score_gemma":0.00004404337,"threshold_uncertainty_score":0.9999598},"labels":[],"label_agreement":null},{"id":"W2887072805","doi":"10.1016/j.neuroimage.2018.10.029","title":"Limits to anatomical accuracy of diffusion tractography using modern approaches","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":282,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; Vanderbilt Institute for Clinical and Translational Research; National Institute on Aging; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University","keywords":"Tractography; Diffusion MRI; Computer science; White matter; Artificial intelligence; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.220788248719264,"score_gpt":0.3910391396846636,"score_spread":0.17025089096539958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887072805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92188066,0.000017892266,0.07512215,0.0008640106,0.000029143965,0.0004620169,0.000011432236,0.00016103224,0.0014516711],"genre_scores_gemma":[0.9375687,0.000011014392,0.061480895,0.0007575267,0.000100521305,0.000013769163,0.0000047636677,0.00003465374,0.000028134087],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990248,0.000020327963,0.00022675515,0.00035407874,0.00017618753,0.00019784854],"domain_scores_gemma":[0.99911356,0.000064716056,0.00008725278,0.0005124595,0.00008267909,0.00013931407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005339597,0.00013184315,0.00021373597,0.00017126973,0.000074177544,0.000011187821,0.00013689745,0.00004505631,0.000014838369],"category_scores_gemma":[0.000136425,0.00011956303,0.00009602694,0.00041239415,0.00014654876,0.000087064655,0.00007604634,0.00016912774,0.0000074710783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009555801,0.00028563224,0.0049003274,0.00002997819,0.0000051333086,0.0000090870035,0.00011522585,0.0000048120146,0.9686915,0.0003720115,0.00032542343,0.025165312],"study_design_scores_gemma":[0.0014260983,0.0011361432,0.16454458,0.0001976194,0.00017717818,0.00025754576,0.0000484904,0.06768314,0.745492,0.003857429,0.014671823,0.0005079485],"about_ca_topic_score_codex":0.000008807201,"about_ca_topic_score_gemma":6.83341e-7,"teacher_disagreement_score":0.2231995,"about_ca_system_score_codex":0.000012701185,"about_ca_system_score_gemma":0.00002392961,"threshold_uncertainty_score":0.48756388},"labels":[],"label_agreement":null},{"id":"W2887719417","doi":"10.1016/j.neurobiolaging.2018.07.018","title":"Re-examining age-related differences in white matter microstructure with free-water corrected diffusion tensor imaging","year":2018,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":124,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Nursing Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"White matter; Diffusion MRI; Free water; Myelin; Cohort; Neuroscience; Medicine; Psychology; Magnetic resonance imaging; Pathology; Radiology; Geology; Central nervous system","score_opus":0.024024038761350237,"score_gpt":0.2752394576277168,"score_spread":0.25121541886636656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2887719417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99504817,0.000015713087,0.0003692164,0.003033618,0.000091614114,0.00028014428,0.0000068255154,0.00015133622,0.00100337],"genre_scores_gemma":[0.9935653,0.000008747406,0.0045388914,0.0014558312,0.000042369124,0.000013507981,0.000035474128,0.000034174158,0.00030565722],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988089,0.000056346777,0.00030865314,0.00043714995,0.000066540815,0.00032239777],"domain_scores_gemma":[0.9992612,0.000054892065,0.0001199583,0.00043881318,0.00008004147,0.00004510872],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000617499,0.00019353912,0.00034733838,0.00020399672,0.000088390705,0.00000962791,0.0001762258,0.00007069463,0.00012548575],"category_scores_gemma":[0.00001759061,0.00012683461,0.000031663672,0.0002080334,0.0005271347,0.000055177192,0.00014673134,0.0003621512,0.000009749753],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005258208,0.000028736293,0.82646716,0.00001894095,0.0000061400374,0.00003187986,0.0004689114,0.0000014619561,0.17242157,0.000005095858,0.00031784287,0.00017967695],"study_design_scores_gemma":[0.0009299157,0.00022491638,0.96394837,0.00023762307,0.000032650038,0.0001809349,0.000114197166,0.00012734652,0.033625163,0.00028773214,0.00014097289,0.00015016143],"about_ca_topic_score_codex":0.00002367609,"about_ca_topic_score_gemma":0.0000139213225,"teacher_disagreement_score":0.13879642,"about_ca_system_score_codex":0.000016744973,"about_ca_system_score_gemma":0.000011305893,"threshold_uncertainty_score":0.5172165},"labels":[],"label_agreement":null},{"id":"W2888278728","doi":"10.1186/s13742-016-0147-0-w","title":"DIPY: Brain tissue classification","year":2016,"lang":"en","type":"article","venue":"GigaScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Brain tissue; Computer science; Computational biology; Artificial intelligence; Neuroscience; Biology","score_opus":0.11838140739627466,"score_gpt":0.4176493103567173,"score_spread":0.29926790296044264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888278728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09954938,0.00003392893,0.755183,0.13191551,0.00008797674,0.0004185106,0.0000068253153,0.00051240553,0.01229246],"genre_scores_gemma":[0.97453845,0.000025160405,0.019150885,0.0015087416,0.000054951048,0.00003942437,0.0000010314396,0.000006775412,0.0046745823],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99944216,0.0000060867605,0.00008253261,0.0002175413,0.00012653795,0.00012513161],"domain_scores_gemma":[0.9994872,0.00004803807,0.000032200576,0.00032453882,0.000037896098,0.00007008923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009242929,0.000046470166,0.00005602464,0.000035696947,0.000064927975,0.000007350168,0.00011116214,0.000016824957,0.000042313073],"category_scores_gemma":[0.00014191985,0.000028906665,0.000015424912,0.0002026995,0.00015643837,0.00009715597,0.000026530704,0.000035768462,0.00012159728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025580919,0.000020820673,0.001959257,0.0000022013855,3.6249452e-7,0.0000018908725,0.000011269555,5.9016536e-8,0.86144173,0.016326262,0.005861917,0.11437169],"study_design_scores_gemma":[0.00030707673,0.00013248401,0.13246985,0.000068224086,0.00000716281,0.00008430981,0.000011785922,0.00016054773,0.19430685,0.0112696225,0.66105735,0.0001247335],"about_ca_topic_score_codex":0.0000015312162,"about_ca_topic_score_gemma":3.0992112e-7,"teacher_disagreement_score":0.8749891,"about_ca_system_score_codex":0.000027969143,"about_ca_system_score_gemma":0.000030217061,"threshold_uncertainty_score":0.15629275},"labels":[],"label_agreement":null},{"id":"W2889179699","doi":"10.1093/cercor/bhy204","title":"Maturation of the Human Cerebral Cortex During Adolescence: Myelin or Dendritic Arbor?","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; Medical Research Council; National Institutes of Health; Vetenskapsrådet; Svenska Forskningsrådet Formas; Fondation pour la Recherche Médicale; EU Joint Programme – Neurodegenerative Disease Research; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; Deutsche Forschungsgemeinschaft; National Institute for Health and Care Research; Mission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives; European Commission","keywords":"Myelin; Neuroscience; Cortex (anatomy); Biology; Cerebral cortex; White matter; Human brain; Oligodendrocyte; Central nervous system; Magnetic resonance imaging; Medicine","score_opus":0.04529827670135839,"score_gpt":0.3405659199363404,"score_spread":0.295267643234982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889179699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99552673,0.00002434127,0.0008737339,0.0008857492,0.00014706417,0.0006207636,0.0000145723425,0.0002102691,0.0016967603],"genre_scores_gemma":[0.9950063,0.000008058568,0.0020668278,0.0005852511,0.00037973438,0.000030429712,0.000014600953,0.0000357613,0.0018730023],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99877065,0.00002803215,0.0003612916,0.00033521466,0.000243818,0.00026100743],"domain_scores_gemma":[0.9988677,0.00001795341,0.00017953053,0.00067312934,0.00017108288,0.00009059776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056021716,0.00016759761,0.00023260036,0.000063206055,0.00027793905,0.000018210145,0.00024071474,0.000076850185,0.00030949517],"category_scores_gemma":[0.000057514342,0.00011472565,0.00010501437,0.00032083437,0.0003348645,0.00010248498,0.00011452444,0.00028257412,0.00002992836],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027597116,0.0002620766,0.08861303,0.00029892748,0.000031768042,0.000018205077,0.00022404868,9.369199e-7,0.896276,0.008614779,0.0026562088,0.0027280399],"study_design_scores_gemma":[0.00071032805,0.0001855153,0.90266854,0.00029898607,0.000067840614,0.00014023726,0.00006589486,0.0002861958,0.09353366,0.0012140516,0.00067323016,0.00015553816],"about_ca_topic_score_codex":0.000018577277,"about_ca_topic_score_gemma":0.000026443395,"teacher_disagreement_score":0.8140555,"about_ca_system_score_codex":0.000058597307,"about_ca_system_score_gemma":0.00007016316,"threshold_uncertainty_score":0.4678376},"labels":[],"label_agreement":null},{"id":"W2889302022","doi":"10.3389/fpsyt.2018.00391","title":"Associations Among Suicidal Ideation, White Matter Integrity and Cognitive Deficit in First-Episode Schizophrenia","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Xiangya Hospital, Central South University; Natural Science Foundation of Hunan Province; Hunan Provincial Science and Technology Department; National Natural Science Foundation of China","keywords":"Psychology; Working memory; Cognitive deficit; Fractional anisotropy; Cognition; Corona radiata (embryology); Suicidal ideation; Schizophrenia (object-oriented programming); Precuneus; Clinical psychology; Wechsler Adult Intelligence Scale; White matter; Psychiatry; Poison control; Medicine; Injury prevention; Internal medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.019359267026921596,"score_gpt":0.30792116874827413,"score_spread":0.28856190172135254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889302022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92162436,0.00028332422,0.06640928,0.0077132196,0.0007740475,0.0006296322,0.000060739174,0.00010692604,0.0023984672],"genre_scores_gemma":[0.89780736,0.00002992893,0.10069353,0.0009861909,0.00015342944,0.0000889743,0.000050071216,0.000024429153,0.00016609386],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989899,0.00003082767,0.00030609552,0.0003350269,0.00011329936,0.00022488898],"domain_scores_gemma":[0.9995186,0.000030358186,0.00010320398,0.00019903669,0.00008156083,0.00006726696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014048735,0.00014052955,0.00024034853,0.0002660847,0.00010785767,0.000020006357,0.000075198375,0.00011617183,0.000034636625],"category_scores_gemma":[0.0000767233,0.00014541984,0.000039242914,0.00042823472,0.00019007757,0.00013519217,0.000038204777,0.00049064803,0.000013689439],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006652674,0.00010439633,0.9672403,0.000016368409,0.000010795876,0.0000012606989,0.00011359625,9.165435e-7,0.0000034842449,0.00042177585,0.03156347,0.00045713162],"study_design_scores_gemma":[0.0010414757,0.000055074343,0.9828543,0.00016739509,0.00003811592,0.000006664022,0.00017948073,0.0006634681,0.000025759035,0.014589653,0.00024180493,0.00013682808],"about_ca_topic_score_codex":0.00022406183,"about_ca_topic_score_gemma":0.0018933348,"teacher_disagreement_score":0.034284253,"about_ca_system_score_codex":0.00007941349,"about_ca_system_score_gemma":0.00003940379,"threshold_uncertainty_score":0.5930049},"labels":[],"label_agreement":null},{"id":"W2889789314","doi":"10.1002/jmri.26269","title":"Evaluation of Intra‐ and Interscanner Reliability of MRI Protocols for Spinal Cord Gray Matter and Total Cross‐Sectional Area Measurements","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"School of Medicine, University of California, San Francisco; University of California, San Francisco; Polytechnique Montréal","keywords":"Gray (unit); Medicine; Spinal cord; Reliability (semiconductor); Cross-sectional study; Nuclear medicine; Radiology; Pathology; Physics","score_opus":0.12262668503511116,"score_gpt":0.4348650783346461,"score_spread":0.31223839329953496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889789314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834317,0.00070269365,0.011199686,0.0009668719,0.000049617738,0.003442789,0.000009730556,0.0000062526506,0.00019063786],"genre_scores_gemma":[0.96457654,0.0000143556035,0.0348912,0.000082670434,0.000090564616,0.00030593207,6.0273254e-7,0.000010656122,0.000027494705],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99867886,0.000041328145,0.00052920455,0.00016526738,0.00047597426,0.000109347464],"domain_scores_gemma":[0.9975897,0.000037707352,0.0004031915,0.00015523245,0.0017607992,0.0000533573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001355041,0.00009004544,0.00021693228,0.000086836655,0.000045586938,0.000016409958,0.00006165844,0.000022053384,0.00004309909],"category_scores_gemma":[0.0003142561,0.000073378185,0.00005554644,0.000073959076,0.00035705962,0.00013789622,0.000031514875,0.00011256701,1.7554751e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018752097,0.00015200995,0.8190361,0.0001826465,0.000008809742,8.9317166e-7,0.00007416431,0.0000060389084,0.04515664,0.000016614276,0.00077781605,0.13271305],"study_design_scores_gemma":[0.0020117871,0.0018592613,0.97540456,0.0005569855,0.00009426339,0.00033011707,0.000022629816,0.0029080198,0.012504055,0.0028580257,0.0013820184,0.00006827028],"about_ca_topic_score_codex":0.0000046540313,"about_ca_topic_score_gemma":5.6523623e-7,"teacher_disagreement_score":0.15636846,"about_ca_system_score_codex":0.000053112974,"about_ca_system_score_gemma":0.00008617045,"threshold_uncertainty_score":0.29922757},"labels":[],"label_agreement":null},{"id":"W2889989509","doi":"10.1111/jon.12559","title":"Multicenter Measurements of T<sub>1</sub> Relaxation and Diffusion Tensor Imaging: Intra and Intersite Reproducibility","year":2018,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Fractional anisotropy; Reproducibility; Diffusion MRI; Intraclass correlation; Medicine; White matter; Nuclear medicine; Corpus callosum; Magnetic resonance imaging; Pathology; Radiology; Mathematics; Statistics","score_opus":0.07068274961811168,"score_gpt":0.3370152020516118,"score_spread":0.2663324524335001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2889989509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9895594,0.00017767031,0.0058227316,0.004037499,0.00007645822,0.00020770369,0.0000014132663,0.000026984077,0.00009015443],"genre_scores_gemma":[0.99029684,0.00015769538,0.008871895,0.0005252035,0.00012277401,0.0000012220985,7.0451387e-7,0.000018405573,0.000005255676],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987722,0.000049387567,0.00046563387,0.0003559221,0.00022791408,0.00012891907],"domain_scores_gemma":[0.99850076,0.000049567836,0.0004846818,0.00039593276,0.0004671928,0.000101847785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005572022,0.00011445093,0.0002380709,0.00017030026,0.00007494825,0.000019485116,0.000067913126,0.000017899398,0.0000021102076],"category_scores_gemma":[0.0006768665,0.00009624887,0.000053973414,0.00012194805,0.0002304237,0.00024932856,0.00009752652,0.00024388792,5.498662e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000105441264,0.000075928576,0.35593504,0.000043136584,0.000007513731,0.000010152195,0.00015338158,2.7047918e-7,0.62374085,0.0000033494348,0.00014909737,0.019775847],"study_design_scores_gemma":[0.0011849087,0.00023982124,0.68614066,0.00046862673,0.00011425257,0.000772647,0.000057207155,0.0015323156,0.3087067,0.00027305883,0.00041795732,0.000091823415],"about_ca_topic_score_codex":0.0000023914795,"about_ca_topic_score_gemma":3.1181057e-7,"teacher_disagreement_score":0.33020562,"about_ca_system_score_codex":0.000031711537,"about_ca_system_score_gemma":0.000019050214,"threshold_uncertainty_score":0.3924915},"labels":[],"label_agreement":null},{"id":"W2890034454","doi":"10.1016/j.neuroimage.2018.09.004","title":"Corpus callosum microstructure is associated with motor function in preschool children","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Alberta Children's Hospital Foundation; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Corticospinal tract; Motor skill; White matter; Psychology; Motor function; Physical medicine and rehabilitation; Audiology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.021710149441484045,"score_gpt":0.28807220158875935,"score_spread":0.2663620521472753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890034454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99478126,0.000025912912,0.0014785598,0.0010240764,0.000060118535,0.0007694352,0.000064303655,0.00032461018,0.0014717324],"genre_scores_gemma":[0.9935036,0.000014056394,0.0015510572,0.0035790822,0.00013260519,0.000040859053,0.00004966726,0.000047909067,0.0010811662],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990216,0.0000232302,0.0001651234,0.00039665218,0.00015999805,0.00023340948],"domain_scores_gemma":[0.9992981,0.000021279528,0.00008398705,0.0004130736,0.00010025641,0.00008333392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041147425,0.00015608167,0.0001824785,0.00009038898,0.00007935843,0.000021214219,0.00009610316,0.00006841598,0.00008566441],"category_scores_gemma":[0.00007038105,0.0001308809,0.000039895494,0.00031457076,0.00013198266,0.00009276389,0.00004026492,0.00034388062,0.000027582097],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005170754,0.0002610136,0.4578971,0.000015242386,0.000032652693,0.00007606295,0.00006945522,0.0000012670297,0.52103287,0.00008240626,0.017480085,0.0025347695],"study_design_scores_gemma":[0.0011316834,0.00067553384,0.9749772,0.000053161963,0.000048262253,0.00012827644,0.0000018516545,0.00013475325,0.017654771,0.00032341614,0.0047349497,0.00013612033],"about_ca_topic_score_codex":0.000028239236,"about_ca_topic_score_gemma":0.000010265795,"teacher_disagreement_score":0.5170801,"about_ca_system_score_codex":0.000044530658,"about_ca_system_score_gemma":0.00003533097,"threshold_uncertainty_score":0.53371686},"labels":[],"label_agreement":null},{"id":"W2890400814","doi":"10.1038/s41393-018-0191-y","title":"Decreased white matter fractional anisotropy is associated with poorer functional motor skills following spinal cord injury: a pilot study","year":2018,"lang":"en","type":"article","venue":"Spinal Cord","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"GF Strong Rehabilitation Centre; University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries; University of New Brunswick","funders":"International Collaboration on Repair Discoveries","keywords":"Fractional anisotropy; White matter; Corpus callosum; Corticospinal tract; Diffusion MRI; Medicine; Superior longitudinal fasciculus; Spinal cord injury; Physical medicine and rehabilitation; Grip strength; Spinal cord; Physical therapy; Neuroscience; Anatomy; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.06935069524829889,"score_gpt":0.378778178087942,"score_spread":0.3094274828396431,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890400814","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97190464,0.000013609759,0.023629496,0.0020412905,0.00016804315,0.0010684382,0.000048711612,0.0003083853,0.0008173784],"genre_scores_gemma":[0.98320186,0.0000018650258,0.009040849,0.0052797454,0.00041556812,0.00022417417,0.00005810632,0.00006725272,0.0017106053],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980393,0.00004361942,0.00032596174,0.0006094554,0.00059909816,0.00038254025],"domain_scores_gemma":[0.9987801,0.00002671948,0.00019699971,0.0004470506,0.00033690798,0.00021225968],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014265745,0.0002994782,0.00035233644,0.00016191797,0.00035874645,0.000047458107,0.00014074262,0.00005216717,0.0010063008],"category_scores_gemma":[0.00006402737,0.00025674587,0.000113949514,0.00044845286,0.00014754344,0.0001714947,0.00007015971,0.00037154453,0.00025150902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.08166022,0.0060549206,0.8680802,0.000026209687,0.0004762363,0.00019404685,0.000028036073,4.8809136e-7,0.015255059,0.00038427286,0.024089983,0.0037503054],"study_design_scores_gemma":[0.0019282682,0.08876261,0.903364,0.00017633646,0.00026583075,0.00009090275,0.000057476573,0.00003835,0.00039419194,0.0007094668,0.00391919,0.0002933638],"about_ca_topic_score_codex":0.000069900336,"about_ca_topic_score_gemma":0.000011904865,"teacher_disagreement_score":0.08270769,"about_ca_system_score_codex":0.00018401732,"about_ca_system_score_gemma":0.00015057319,"threshold_uncertainty_score":0.9999885},"labels":[],"label_agreement":null},{"id":"W2890509943","doi":"10.1017/s0033291718002647","title":"Aberrant myelination of the cingulum and Schneiderian delusions in schizophrenia: a 7T magnetization transfer study","year":2018,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Wellcome Trust","keywords":"Cingulum (brain); Schizophrenia (object-oriented programming); Psychology; Neuroscience; Audiology; White matter; Medicine; Psychiatry; Magnetic resonance imaging; Fractional anisotropy; Radiology","score_opus":0.09328243376669865,"score_gpt":0.40815789258830815,"score_spread":0.3148754588216095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890509943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97500074,0.000087645894,0.00943969,0.012969955,0.00007946705,0.0010055677,0.000001789807,0.000062420244,0.0013527455],"genre_scores_gemma":[0.9967698,0.000077610224,0.0020651626,0.00083843846,0.00012659177,0.000056976103,0.0000027705776,0.000009604304,0.00005304253],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990082,0.000059598588,0.000349925,0.00027959154,0.00018268636,0.000120001074],"domain_scores_gemma":[0.99942607,0.000052003168,0.00004804369,0.0003197158,0.00009679329,0.000057361332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002554059,0.00010079645,0.00022028192,0.00009823093,0.00008022053,0.000002321784,0.000097453034,0.000057072164,0.00010787421],"category_scores_gemma":[0.0002829629,0.00005664078,0.000022935694,0.00052322855,0.000413602,0.000026289374,0.000035282854,0.00020254179,0.0000016636121],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021320214,0.0067891437,0.22044303,0.00014336173,0.000048887545,0.00005108337,0.0063224076,0.0000061984842,0.40946296,0.015528112,0.0018874168,0.33718538],"study_design_scores_gemma":[0.0031766146,0.002121951,0.98865604,0.00018301452,0.000053337255,0.000050217015,0.00024668168,0.00027323942,0.0006467073,0.00411496,0.00040791434,0.00006934661],"about_ca_topic_score_codex":0.000024954916,"about_ca_topic_score_gemma":0.000032289692,"teacher_disagreement_score":0.768213,"about_ca_system_score_codex":0.000012512916,"about_ca_system_score_gemma":0.000004629744,"threshold_uncertainty_score":0.2309744},"labels":[],"label_agreement":null},{"id":"W2891370352","doi":"10.1016/j.nicl.2018.09.005","title":"Early changes in white matter predict intellectual outcome in children treated for posterior fossa tumors","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children's & Women's Health Centre of British Columbia; SickKids Foundation; Alberta Children's Hospital; Hospital for Sick Children","funders":"Canadian Cancer Society Research Institute; Canadian Cancer Society","keywords":"White matter; Diffusion MRI; Medicine; Tractography; Voxel; Optic radiation; Neuroimaging; Magnetic resonance imaging; Radiology; Nuclear medicine; Psychology; Psychiatry","score_opus":0.11640286118457063,"score_gpt":0.4216149981999025,"score_spread":0.3052121370153319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891370352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923874,0.000007936176,0.00059272366,0.0047010863,0.00006338427,0.0015826799,0.000052535936,0.00018767439,0.00042459182],"genre_scores_gemma":[0.99014515,0.000016909598,0.003516123,0.004929889,0.00033960247,0.00021283014,0.000035868772,0.00006836764,0.0007352345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979181,0.00008470793,0.00078790286,0.0006877426,0.00012954295,0.00039194705],"domain_scores_gemma":[0.998713,0.0003793023,0.00012405674,0.00057061744,0.00007886089,0.00013412365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003224922,0.00021782881,0.00051418866,0.00022802189,0.000045306584,0.000024504465,0.00020954684,0.00012026776,0.00013130989],"category_scores_gemma":[0.000723458,0.00019634022,0.00013461927,0.00033387783,0.00030576732,0.000078277415,0.00012687029,0.00044843607,0.00008509594],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037989297,0.0002733868,0.99363434,0.000012995095,0.0000053211247,0.000024580291,0.000062567975,1.2127687e-7,0.00083831087,0.000003911192,0.0022088985,0.002555697],"study_design_scores_gemma":[0.0020874413,0.001598391,0.9936681,0.0000743387,0.000029258132,0.000105029874,0.0000063674465,0.00027388657,0.0006030364,0.00008738473,0.0013091709,0.00015761645],"about_ca_topic_score_codex":0.000017430539,"about_ca_topic_score_gemma":0.000026477024,"teacher_disagreement_score":0.0029233992,"about_ca_system_score_codex":0.000031946623,"about_ca_system_score_gemma":0.000028361032,"threshold_uncertainty_score":0.80065215},"labels":[],"label_agreement":null},{"id":"W2891372289","doi":"10.1101/415158","title":"Uncovering a role for the dorsal hippocampal commissure in episodic memory","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut du Savoir Montfort; Montreal Neurological Institute and Hospital","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Medical Research Council; Centre d'Imagerie BioMédicale; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Wellcome Trust; University of California, Los Angeles; University of Minnesota; Massachusetts General Hospital","keywords":"Diffusion MRI; White matter; Neuroscience; Anterior commissure; Episodic memory; Tractography; Corpus callosum; Hippocampal formation; Fractional anisotropy; Commissure; Psychology; Human Connectome Project; Temporal lobe; Hippocampus; Cingulum (brain); Anatomy; Biology; Medicine; Functional connectivity; Magnetic resonance imaging; Cognition; Epilepsy","score_opus":0.03211149104441389,"score_gpt":0.2911100686521923,"score_spread":0.2589985776077784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891372289","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9367905,0.0051061288,0.043752793,0.0047361176,0.0009917988,0.0066519934,0.00041707128,0.0014860921,0.00006749169],"genre_scores_gemma":[0.97249186,0.00027534715,0.024232889,0.0007065988,0.0006274717,0.0014953538,7.1214146e-7,0.0001572247,0.000012536366],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978587,0.00005029066,0.00048598277,0.00082518277,0.0002717997,0.00050801836],"domain_scores_gemma":[0.9973406,0.00021092444,0.00028114306,0.0017182678,0.00030219185,0.00014685282],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00056875404,0.00043892796,0.0005524663,0.00018649892,0.00020349731,0.00008044662,0.0005440656,0.00033106914,0.000024368846],"category_scores_gemma":[0.00028015013,0.00037736056,0.00019536182,0.00039107524,0.00021286822,0.000069718524,0.00043643417,0.00096085103,0.000019302666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078003283,0.0011916785,0.049863353,0.0027202012,0.000511663,0.0001591886,0.0001111083,0.0009006514,0.93221325,0.0025018237,0.008725566,0.0003214809],"study_design_scores_gemma":[0.0042479807,0.00047929195,0.20769396,0.0028994374,0.00095564517,5.027354e-7,0.0000327145,0.01228816,0.46484482,0.0006108602,0.30366507,0.0022815627],"about_ca_topic_score_codex":0.00006944152,"about_ca_topic_score_gemma":0.000003873538,"teacher_disagreement_score":0.46736842,"about_ca_system_score_codex":0.00024349919,"about_ca_system_score_gemma":0.00038508006,"threshold_uncertainty_score":0.99986786},"labels":[],"label_agreement":null},{"id":"W2891444336","doi":"10.3389/fpsyt.2018.00438","title":"Putative Astroglial Dysfunction in Schizophrenia: A Meta-Analysis of 1H-MRS Studies of Medial Prefrontal Myo-Inositol","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"Instituto de Salud Carlos III; Canadian Institutes of Health Research","keywords":"Schizophrenia (object-oriented programming); Inositol; Prefrontal cortex; Meta-analysis; DISC1; Internal medicine; Psychosis; Psychology; Sample size determination; Psychiatry; Medicine; Chemistry; Cognition; Biochemistry; Receptor","score_opus":0.09004497261632373,"score_gpt":0.38765712489573645,"score_spread":0.29761215227941273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891444336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8757334,0.005771464,0.109393016,0.0035579922,0.003310029,0.0013663936,0.00020933166,0.0001107334,0.0005476604],"genre_scores_gemma":[0.726679,0.00007132509,0.27283835,0.00010073005,0.00012778626,0.0001026473,0.000023287015,0.000015237231,0.000041626827],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985512,0.00006863841,0.0005915646,0.00035512703,0.0002518183,0.00018166857],"domain_scores_gemma":[0.9991279,0.000038454342,0.00029409898,0.00034535918,0.00014715691,0.000047033678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020261206,0.00017117905,0.0011108535,0.00076273736,0.00003439178,0.0000026069442,0.00012288828,0.00008142734,0.000020806618],"category_scores_gemma":[0.000073975076,0.00014575748,0.0004159102,0.0012142387,0.0003928384,0.00008693565,0.000048796566,0.0002316844,7.8979235e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005826299,0.0023653214,0.83702767,0.00038008156,0.08394956,0.000013029177,0.004560748,0.00037996107,0.0053515728,0.0035819293,0.050664186,0.0058996393],"study_design_scores_gemma":[0.014826119,0.0046407306,0.6119371,0.00029935472,0.26276428,0.000023646218,0.01327819,0.009572217,0.02417288,0.055776093,0.0015133573,0.0011960288],"about_ca_topic_score_codex":0.000042189895,"about_ca_topic_score_gemma":0.00016581538,"teacher_disagreement_score":0.22509056,"about_ca_system_score_codex":0.00007287898,"about_ca_system_score_gemma":0.00008308631,"threshold_uncertainty_score":0.5943818},"labels":[],"label_agreement":null},{"id":"W2891919159","doi":"10.1002/jmri.26328","title":"Characterizing Structural Changes With Evolving Remyelination Following Experimental Demyelination Using High Angular Resolution Diffusion MRI and Texture Analysis","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; University of Calgary","funders":"Alberta Innovates; Health Research Board; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Remyelination; Diffusion imaging; Diffusion MRI; Texture (cosmology); High resolution; Diffusion; Medicine; Computer science; Magnetic resonance imaging; Physics; Radiology; Artificial intelligence; Geology; Myelin; Internal medicine","score_opus":0.01985293469802128,"score_gpt":0.3191306368759522,"score_spread":0.2992777021779309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2891919159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94262606,0.0068978304,0.04791575,0.0021859526,0.000082453465,0.00021830831,0.0000024082708,0.000039041337,0.00003220669],"genre_scores_gemma":[0.9022072,0.00013032011,0.097035915,0.00021308326,0.0003528757,0.0000042302686,0.0000064306982,0.000023807444,0.000026149028],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99875027,0.00004555568,0.00032546328,0.00026683687,0.00039663236,0.00021525503],"domain_scores_gemma":[0.99894464,0.000033739667,0.00041714084,0.00019032838,0.0003259424,0.00008823505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002669556,0.00017070849,0.0003229616,0.00042429994,0.00027796178,0.0000713992,0.00008528134,0.000042089636,0.000020956042],"category_scores_gemma":[0.00006258755,0.00013889876,0.000089058514,0.0005606188,0.0001162586,0.0004105577,0.000053964162,0.00021746075,2.3942647e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002457491,0.00005375421,0.08307592,0.000028845141,0.000049441434,0.00010166574,0.00091683434,0.00003527986,0.818574,0.0000864587,0.000045864588,0.0967862],"study_design_scores_gemma":[0.0018901437,0.00085838727,0.67343795,0.0008748677,0.0010435047,0.0011139939,0.00063736393,0.28396353,0.03353335,0.0002742711,0.0020288813,0.00034375445],"about_ca_topic_score_codex":0.000024062656,"about_ca_topic_score_gemma":0.0000048880934,"teacher_disagreement_score":0.7850406,"about_ca_system_score_codex":0.00014696587,"about_ca_system_score_gemma":0.000032908676,"threshold_uncertainty_score":0.5664127},"labels":[],"label_agreement":null},{"id":"W2892140621","doi":"10.1101/423459","title":"Bundle-specific fornix reconstruction for dual-tracer PET-tractometry","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Fornix; Tractography; Diffusion MRI; Positron emission tomography; Neuroscience; Partial volume; Voxel; Human Connectome Project; White matter; Medicine; Nuclear medicine; Psychology; Hippocampus; Radiology; Magnetic resonance imaging","score_opus":0.05268890752959248,"score_gpt":0.30640840972062744,"score_spread":0.25371950219103495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2892140621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8623567,0.0010635698,0.124990225,0.001611681,0.002155585,0.00445406,0.0008548383,0.0024252664,0.00008805059],"genre_scores_gemma":[0.7462237,0.0007599208,0.24971421,0.000285111,0.0016868048,0.001050148,0.000002553464,0.0002443207,0.000033245375],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970501,0.000036912457,0.0006707152,0.0013287785,0.00032562696,0.00058786746],"domain_scores_gemma":[0.9963136,0.00011319845,0.0005431121,0.0018130968,0.00089890294,0.00031810257],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040241127,0.00057437125,0.0006898569,0.0004460327,0.0002635412,0.00013089711,0.00028851946,0.00041283917,0.00010452783],"category_scores_gemma":[0.00021016443,0.00061556365,0.00031313338,0.0005299278,0.0002669658,0.0001594205,0.00024529902,0.00093960355,0.000081144106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025308828,0.00072893535,0.0074440055,0.00118515,0.00022143881,0.000057287736,0.000005866194,0.0000065666686,0.97504,0.0026363754,0.012315408,0.00010583993],"study_design_scores_gemma":[0.0017671009,0.0004884763,0.05747441,0.0014391006,0.0004957661,0.000003209149,0.0000056832237,0.00075711077,0.61181754,0.00018426655,0.32392302,0.0016443378],"about_ca_topic_score_codex":0.000004899399,"about_ca_topic_score_gemma":2.940842e-7,"teacher_disagreement_score":0.3632225,"about_ca_system_score_codex":0.0003479552,"about_ca_system_score_gemma":0.0003377492,"threshold_uncertainty_score":0.99962956},"labels":[],"label_agreement":null},{"id":"W2893406291","doi":"10.1007/s00429-018-1759-1","title":"Topological principles and developmental algorithms might refine diffusion tractography","year":2018,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Tractography; Computer science; Diffusion; Topology (electrical circuits); Diffusion MRI; Cognitive science; Artificial intelligence; Algorithm; Psychology; Mathematics; Physics; Medicine; Combinatorics; Magnetic resonance imaging","score_opus":0.10554750883450897,"score_gpt":0.36201536571622606,"score_spread":0.2564678568817171,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893406291","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001359611,0.9934103,0.003122304,0.00035974817,0.00013166145,0.00087514136,0.000066613924,0.00019647263,0.00047816167],"genre_scores_gemma":[0.00014652948,0.9807561,0.01744247,0.00038597354,0.00037139127,0.00005039877,0.00035436417,0.00003095006,0.00046180564],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989466,0.000029144296,0.00028244124,0.0004822524,0.000110775,0.00014877356],"domain_scores_gemma":[0.9994831,0.00008304202,0.0001357557,0.0001680878,0.000030002624,0.00010001132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005912751,0.000278313,0.00057801284,0.00013706695,0.00016499146,0.000022944878,0.000044418914,0.0002800076,0.00006022468],"category_scores_gemma":[0.000043359854,0.00018154285,0.00010020726,0.00019198946,0.00016896361,0.000041298583,0.0000770473,0.0003249358,0.0000018685757],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019381503,0.000020648853,0.00010329373,0.0011192497,0.00003384918,0.0000057203656,0.000015560609,3.53795e-9,0.000054214586,0.0006790648,0.0013227678,0.99662626],"study_design_scores_gemma":[0.0001972359,0.00019436597,0.0020714481,0.0008864112,0.00028221155,0.00082162576,0.000008222017,0.0000043540103,0.000007837498,0.000993217,0.9943505,0.00018255164],"about_ca_topic_score_codex":0.0000026375815,"about_ca_topic_score_gemma":0.0000017023029,"teacher_disagreement_score":0.9964437,"about_ca_system_score_codex":0.000024883142,"about_ca_system_score_gemma":0.00003302262,"threshold_uncertainty_score":0.7403103},"labels":[],"label_agreement":null},{"id":"W2893628403","doi":"10.1115/1.4041541","title":"Diffusion-Tensor Imaging Versus Digitization in Reconstructing the Masseter Architecture","year":2018,"lang":"en","type":"article","venue":"Journal of Biomechanical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Sunnybrook Research Institute","keywords":"Diffusion MRI; Voxel; Tractography; Biomedical engineering; Orientation (vector space); Magnetic resonance imaging; Anatomy; Materials science; Computer science; Nuclear magnetic resonance; Artificial intelligence; Physics; Mathematics; Geometry; Medicine; Radiology","score_opus":0.03342880551342237,"score_gpt":0.3108715339195204,"score_spread":0.277442728406098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2893628403","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42557582,0.00006756796,0.5692682,0.004283757,0.00040767298,0.00016369282,0.000001844822,0.000068924935,0.00016248679],"genre_scores_gemma":[0.96033484,0.000021581893,0.03909919,0.00013796617,0.00037630476,0.0000028287766,7.995739e-7,0.00001756972,0.000008942747],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993279,0.000008546503,0.00029795224,0.000093709576,0.00013066326,0.00014120844],"domain_scores_gemma":[0.9994922,0.00011704263,0.000112457514,0.00013588747,0.00008180713,0.0000605613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015372339,0.00008123568,0.00014315388,0.00016169097,0.000037314137,0.00001822618,0.000098442004,0.000029310102,0.000011478262],"category_scores_gemma":[0.00026301478,0.000054275646,0.00006754855,0.00029082142,0.000031911164,0.00006760571,0.00003926415,0.00030582966,0.0000014580762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037668456,0.00010603427,0.0027735857,0.00005577027,0.000043185235,0.0001176195,0.00018238637,0.00049040903,0.7768358,0.002333678,0.00015476684,0.21653007],"study_design_scores_gemma":[0.013560195,0.0024938397,0.016682003,0.0035790394,0.00039511334,0.013428938,0.0006929096,0.5616613,0.27155283,0.012489345,0.1021348,0.0013296524],"about_ca_topic_score_codex":0.0000013782901,"about_ca_topic_score_gemma":4.063511e-7,"teacher_disagreement_score":0.56117094,"about_ca_system_score_codex":0.00004983742,"about_ca_system_score_gemma":0.000017369042,"threshold_uncertainty_score":0.22132966},"labels":[],"label_agreement":null},{"id":"W2894095668","doi":"10.1111/acps.12964","title":"Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity","year":2018,"lang":"en","type":"article","venue":"Acta Psychiatrica Scandinavica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministerstvo Zdravotnictví Ceské Republiky; Agence Nationale de la Recherche","keywords":"Schizophrenia (object-oriented programming); Machine learning; Artificial intelligence; Signature (topology); Psychosis; Psychology; Computer science; Pattern recognition (psychology); Psychiatry; Mathematics","score_opus":0.05515447275850306,"score_gpt":0.3596134905246516,"score_spread":0.30445901776614853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894095668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9957608,0.000552882,0.0020377531,0.0008889233,0.000047465488,0.00042002165,0.00003691252,0.00018028099,0.00007498429],"genre_scores_gemma":[0.9188567,0.00011122827,0.080592945,0.00011452076,0.00017361133,0.0000055523537,0.00002460634,0.000042272386,0.00007860951],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99838614,0.000041378047,0.00027842086,0.0007164767,0.0002512645,0.00032631302],"domain_scores_gemma":[0.9987677,0.000046442656,0.0002657714,0.00062348024,0.00014266216,0.00015394854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014794928,0.00022151772,0.00036819058,0.00013816796,0.00038122715,0.00004002151,0.00015789006,0.00009461237,0.000026061261],"category_scores_gemma":[0.00008060973,0.00018182611,0.000060898274,0.0007357992,0.0003108965,0.00013229065,0.00015351358,0.0005601082,8.502737e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019018588,0.00022599325,0.74639237,0.00021998968,0.0000889997,0.000026493337,0.0004901218,0.000009178028,0.24707383,0.00047147775,0.00050663284,0.0025930647],"study_design_scores_gemma":[0.011616502,0.004549331,0.8288406,0.00079769833,0.0013556882,0.0027768058,0.0004876101,0.013700111,0.1118272,0.0062008263,0.015994532,0.0018530787],"about_ca_topic_score_codex":0.00010361942,"about_ca_topic_score_gemma":0.000025934449,"teacher_disagreement_score":0.13524663,"about_ca_system_score_codex":0.000032510976,"about_ca_system_score_gemma":0.000050041974,"threshold_uncertainty_score":0.74146533},"labels":[],"label_agreement":null},{"id":"W2894333093","doi":"10.1016/j.neuroimage.2018.09.076","title":"Towards microstructure fingerprinting: Estimation of tissue properties from a dictionary of Monte Carlo diffusion MRI simulations","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Foulkes Foundation; Natural Sciences and Engineering Research Council of Canada; Royal College of Psychiatrists","keywords":"Monte Carlo method; Human Connectome Project; Diffusion MRI; Computer science; Ground truth; Voxel; Algorithm; Diffusion; Statistical physics; Artificial intelligence; Biological system; Magnetic resonance imaging; Physics; Mathematics; Statistics; Radiology; Neuroscience; Biology","score_opus":0.04307607797040159,"score_gpt":0.3293704997543542,"score_spread":0.2862944217839526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894333093","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.968458,0.000060763265,0.02951151,0.0007582327,0.0000635022,0.00046495226,0.000113675356,0.00014044583,0.00042890268],"genre_scores_gemma":[0.95947665,0.000019856532,0.04006508,0.00013511088,0.000086498316,0.0000116582,0.000027260336,0.000025658393,0.00015221932],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912095,0.000020800995,0.00031045487,0.00025801698,0.00017952244,0.00011028187],"domain_scores_gemma":[0.9991087,0.000037260634,0.00017711948,0.00043019094,0.00020255244,0.000044195418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029082259,0.000121273166,0.00021797471,0.000089029345,0.00008637384,0.0000074091267,0.00009836879,0.000052375017,0.000051463616],"category_scores_gemma":[0.00013130893,0.00010540954,0.000053688673,0.00019568123,0.00021762165,0.00009448586,0.00009068479,0.00013707293,0.0000031889822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000065917615,0.000096764146,0.0030620468,0.000053607357,0.000007488526,0.000002699721,0.00025753456,0.0006311326,0.9869533,0.00006146305,0.00024316389,0.00856486],"study_design_scores_gemma":[0.0005079415,0.0003214816,0.1602652,0.00019025446,0.00008858743,0.00002357626,0.00002108007,0.078320414,0.7547544,0.0009838893,0.0043930607,0.00013005912],"about_ca_topic_score_codex":0.00014931631,"about_ca_topic_score_gemma":0.000003203987,"teacher_disagreement_score":0.23219888,"about_ca_system_score_codex":0.000016277494,"about_ca_system_score_gemma":0.000037405272,"threshold_uncertainty_score":0.42984763},"labels":[],"label_agreement":null},{"id":"W2894533856","doi":"10.3389/fphar.2018.01172","title":"Confused Connections? Targeting White Matter to Address Treatment Resistant Schizophrenia","year":2018,"lang":"en","type":"review","venue":"Frontiers in Pharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Nova Scotia Health Authority","funders":"Canadian Institutes of Health Research","keywords":"Psychosis; Schizophrenia (object-oriented programming); Antipsychotic; Medicine; Pharmacotherapy; Serotonergic; Psychiatry; Psychology; Internal medicine; Serotonin; Receptor","score_opus":0.08410181325738236,"score_gpt":0.4174358491086453,"score_spread":0.3333340358512629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894533856","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000045679673,0.9855246,0.005085795,0.0015787167,0.0018277296,0.0040729535,0.00017559846,0.0002580729,0.0014308863],"genre_scores_gemma":[0.000023634542,0.93870366,0.054118548,0.0013859726,0.0006437643,0.002421783,0.00019610788,0.00011239535,0.0023941577],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99781483,0.00017392749,0.0006785154,0.0007629319,0.00010513602,0.00046464207],"domain_scores_gemma":[0.9989752,0.00007503855,0.00025325938,0.00041480557,0.00007503467,0.00020665246],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013970568,0.00044452815,0.0015786552,0.0005923645,0.0001188972,0.000015651613,0.00023088565,0.00023152216,0.0005047254],"category_scores_gemma":[0.00002324622,0.00038092697,0.00026317185,0.00052969664,0.00014262725,0.0000366885,0.00009556938,0.00043723462,0.00018707036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030760773,0.0002500369,0.00025058768,0.0015843504,0.0002299323,0.000108429784,0.000054638505,0.0000016421648,0.00006190525,0.000024628609,0.90942425,0.08770197],"study_design_scores_gemma":[0.001080998,0.0002807477,0.00002388853,0.0012857192,0.00092510507,0.00005714832,0.000013305251,0.0000193067,0.000079588885,0.000061791274,0.9958729,0.00029945734],"about_ca_topic_score_codex":0.00000872826,"about_ca_topic_score_gemma":0.0000019294616,"teacher_disagreement_score":0.087402515,"about_ca_system_score_codex":0.0006436444,"about_ca_system_score_gemma":0.00021913866,"threshold_uncertainty_score":0.9998643},"labels":[],"label_agreement":null},{"id":"W2894670374","doi":"10.1093/cercor/bhy231","title":"Altered White Matter Organization in the TUBB3 E410K Syndrome","year":2018,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hamilton Health Sciences","funders":"Boston Children's Hospital; Intellectual and Developmental Disabilities Research Center; National Institutes of Health; National Eye Institute; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Howard Hughes Medical Institute","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Corticospinal tract; Neuroimaging; Psychology; Endophenotype; Neuroscience; Magnetic resonance imaging; Pyramidal tracts; Medicine; Cognition; Radiology","score_opus":0.03665468334787248,"score_gpt":0.3163464266729352,"score_spread":0.27969174332506275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894670374","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9779287,0.000010024686,0.0060119177,0.00930814,0.0000667384,0.00046723912,0.0000047163976,0.00014094712,0.0060615623],"genre_scores_gemma":[0.991067,0.000003952433,0.0020156417,0.005781289,0.0001219397,0.00002148706,0.00003806644,0.000022953152,0.0009276632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939966,0.000018406781,0.00014275288,0.00019229656,0.000101947335,0.0001449079],"domain_scores_gemma":[0.9994488,0.000012768385,0.000040069965,0.00038086987,0.00008379963,0.00003374033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005301343,0.00008271051,0.00010390057,0.00005146861,0.000069067064,0.00001847348,0.00013027611,0.000033169476,0.00073196663],"category_scores_gemma":[0.00002214981,0.00005869271,0.000018521525,0.00049965875,0.00007482993,0.00006684377,0.00003599092,0.00013341737,0.00043070415],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018136994,0.00013952088,0.9466053,0.000028159226,0.000007208891,0.000034984925,0.00047022043,5.2645163e-7,0.00542168,0.0017367945,0.044512406,0.0010250431],"study_design_scores_gemma":[0.000256697,0.000101601225,0.99090177,0.000028071398,0.000015258313,0.0004559262,0.000039568276,0.000095367155,0.0006715563,0.0011769328,0.006181201,0.00007604935],"about_ca_topic_score_codex":0.000007761411,"about_ca_topic_score_gemma":0.0000041920903,"teacher_disagreement_score":0.044296455,"about_ca_system_score_codex":0.000023496612,"about_ca_system_score_gemma":0.000018008157,"threshold_uncertainty_score":0.80145216},"labels":[],"label_agreement":null},{"id":"W2894959679","doi":"10.1016/j.nicl.2018.09.028","title":"Widespread diffusion changes differentiate Parkinson's disease and progressive supranuclear palsy","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Calgary","funders":"","keywords":"Progressive supranuclear palsy; Diffusion MRI; Fractional anisotropy; Parkinson's disease; Artificial intelligence; Psychology; Nuclear medicine; Medicine; Pathology; Computer science; Disease; Magnetic resonance imaging; Radiology","score_opus":0.1195562695030688,"score_gpt":0.42324322796270725,"score_spread":0.30368695845963845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894959679","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98573023,0.00019814233,0.0009475656,0.011371427,0.00018055143,0.0007493015,0.000026542535,0.00044436418,0.00035186185],"genre_scores_gemma":[0.9888836,0.0011551599,0.0041068676,0.004649608,0.0006819596,0.00007091415,0.000021422291,0.00006056634,0.00036987284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99833924,0.000104487306,0.00033500255,0.00072705053,0.00020256714,0.00029167623],"domain_scores_gemma":[0.99834836,0.00026184256,0.0001454822,0.00067778444,0.00011384132,0.00045272324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015508257,0.00020518684,0.00034116284,0.00006112227,0.00017905765,0.000042652522,0.0001333785,0.0000756122,0.000102116166],"category_scores_gemma":[0.0006753451,0.00016718429,0.00010656321,0.00012879171,0.00076987466,0.000070316484,0.00025085144,0.0003713324,0.00005171803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026641241,0.0025116263,0.70959306,0.00025282474,0.00006780301,0.0010320563,0.00013192913,5.8309684e-8,0.033649836,0.0012009997,0.021594169,0.22730152],"study_design_scores_gemma":[0.0012471193,0.0010230552,0.8364654,0.00015980151,0.00017796073,0.00006525623,0.000006357054,0.00076513895,0.0010022942,0.0010991477,0.15778667,0.00020176716],"about_ca_topic_score_codex":0.000001895014,"about_ca_topic_score_gemma":0.0000015497104,"teacher_disagreement_score":0.22709976,"about_ca_system_score_codex":0.000008215489,"about_ca_system_score_gemma":0.00002624397,"threshold_uncertainty_score":0.68175775},"labels":[],"label_agreement":null},{"id":"W2896133725","doi":"10.1002/acn3.667","title":"Diffusion <scp>MRI</scp> abnormalities in adolescent rats given repeated mild traumatic brain injury","year":2018,"lang":"en","type":"article","venue":"Annals of Clinical and Translational Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Cummings Foundation","keywords":"Medicine; Traumatic brain injury; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Concussion; Population; Neuroscience; Radiology; Poison control; Injury prevention; Psychiatry; Psychology; Emergency medicine","score_opus":0.26504683664408674,"score_gpt":0.46885978822287316,"score_spread":0.20381295157878643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896133725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9535967,0.000111366106,0.00094658934,0.044216566,0.000049725364,0.00031532857,0.00003484955,0.00005016772,0.00067867007],"genre_scores_gemma":[0.9858808,0.0005619466,0.00089333166,0.012372205,0.00013907996,0.00001547341,0.000032391414,0.000013448656,0.00009134146],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984119,0.00014689555,0.0007933997,0.00031429736,0.00014491274,0.00018861548],"domain_scores_gemma":[0.99854916,0.0008831644,0.00014874265,0.0001899345,0.00012273852,0.0001062662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003948354,0.00011916776,0.00039459858,0.000106657106,0.000048931837,0.0000038524754,0.00007626879,0.0001342341,0.000017137862],"category_scores_gemma":[0.00028064082,0.000103823,0.00011053769,0.0001529958,0.00053186395,0.000061451115,0.000024659841,0.00033328927,0.0000042869483],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011763234,0.0013440244,0.95534533,0.00017928105,0.00004165771,0.000031620988,0.00036883928,0.000011403473,0.0016198057,0.007997682,0.00834546,0.023538578],"study_design_scores_gemma":[0.00089446065,0.0009194249,0.95120215,0.00006709559,0.000016466918,0.00002329436,0.0000074298387,0.0010648904,0.0010550846,0.018945482,0.025760781,0.000043417425],"about_ca_topic_score_codex":0.000011823126,"about_ca_topic_score_gemma":0.000011751827,"teacher_disagreement_score":0.032284044,"about_ca_system_score_codex":2.766201e-7,"about_ca_system_score_gemma":0.000035617955,"threshold_uncertainty_score":0.4233779},"labels":[],"label_agreement":null},{"id":"W2896255880","doi":"10.1038/s41598-018-34219-8","title":"Allostatic load and disordered white matter microstructure in overweight adults","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Universitat de Barcelona; Generalitat de Catalunya","keywords":"Allostatic load; Overweight; White matter; Medicine; Gerontology; Psychology; Obesity; Endocrinology; Magnetic resonance imaging","score_opus":0.013815243343114505,"score_gpt":0.2955988558445625,"score_spread":0.281783612501448,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896255880","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944673,0.000080661826,0.000494637,0.0019163731,0.0004110145,0.00044759747,0.0000034486293,0.00006542228,0.0021135176],"genre_scores_gemma":[0.98770934,0.0000057823718,0.007765565,0.00038560582,0.00003558501,0.000021911917,0.000025035117,0.000014403389,0.0040367492],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883705,0.000007824639,0.00025216676,0.0005351022,0.00018481442,0.00018304134],"domain_scores_gemma":[0.99913657,0.000007610541,0.000100163714,0.0005739869,0.000108227585,0.00007344766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015672669,0.000094929885,0.00012961339,0.00008587085,0.00010625772,0.000055218527,0.000040527382,0.000034259894,0.00018500593],"category_scores_gemma":[0.000038454175,0.000078451245,0.00002416359,0.0002812827,0.0003322467,0.00007766217,0.00005538571,0.00009702172,0.00002083068],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082061015,0.00014658688,0.83722883,0.00012934633,0.0000072331677,0.00042819578,0.0019320532,7.8624834e-7,0.061428737,0.00007100993,0.09501388,0.0035313033],"study_design_scores_gemma":[0.0006979186,0.00011296726,0.7354483,0.00035305065,0.000030258214,0.002281217,0.0001364962,0.00028236047,0.018400585,0.03659486,0.20534424,0.0003177708],"about_ca_topic_score_codex":0.000016855207,"about_ca_topic_score_gemma":0.00003416779,"teacher_disagreement_score":0.110330366,"about_ca_system_score_codex":0.000030752497,"about_ca_system_score_gemma":0.00005238595,"threshold_uncertainty_score":0.3199149},"labels":[],"label_agreement":null},{"id":"W2896736741","doi":"10.1101/439836","title":"Novel use of Diffusion Tensor Imaging to Delineate the Rat Basolateral Amygdala","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Neuroscience; Diffusion MRI; Basolateral amygdala; Amygdala; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.052795566163076096,"score_gpt":0.29377080010411555,"score_spread":0.24097523394103945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2896736741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8669095,0.000113067326,0.12639554,0.0036738934,0.00041795906,0.001713448,0.0002286122,0.0005439108,0.0000040535833],"genre_scores_gemma":[0.85416424,0.00012029539,0.14277825,0.0020584846,0.00044704427,0.0002551665,7.7689066e-7,0.00015149883,0.000024262974],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976579,0.000046528778,0.00061214966,0.00088966463,0.00034926736,0.0004444688],"domain_scores_gemma":[0.99622655,0.000090785536,0.0003774047,0.0020950444,0.00095155375,0.0002586841],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028608966,0.00047033513,0.0005618204,0.00022980258,0.00017864793,0.000108844986,0.000461795,0.00017595082,0.000021713575],"category_scores_gemma":[0.00034348998,0.00036624947,0.00019052956,0.0004668502,0.00020823434,0.0001110774,0.00085823616,0.00066773937,0.000025256437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072508235,0.0001745102,0.027501712,0.00014069301,0.000034271434,0.000015354124,0.000007763618,0.00003446907,0.9701761,0.00015799169,0.0016747115,0.000009924169],"study_design_scores_gemma":[0.0009922844,0.00012688847,0.32714576,0.0017830234,0.0004268498,5.479582e-7,0.0000026233422,0.01153113,0.58781534,0.0000073148763,0.069206156,0.0009620926],"about_ca_topic_score_codex":0.00007644665,"about_ca_topic_score_gemma":6.5666654e-7,"teacher_disagreement_score":0.38236076,"about_ca_system_score_codex":0.00013113974,"about_ca_system_score_gemma":0.00020201798,"threshold_uncertainty_score":0.99987894},"labels":[],"label_agreement":null},{"id":"W2897068525","doi":"10.1016/j.mri.2018.10.003","title":"Fiber orientation distribution function from non-negative sparse recovery with quantitative analysis of local fiber orientations and tractography using DW-MRI datasets","year":2018,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"H2020 European Research Council; Horizon 2020","keywords":"Tractography; Voxel; Diffusion MRI; Computer science; Artificial intelligence; Orientation (vector space); Pattern recognition (psychology); Human Connectome Project; Population; Noise (video); Mathematics; Magnetic resonance imaging; Image (mathematics); Biology","score_opus":0.029898547542991143,"score_gpt":0.3302889309628341,"score_spread":0.300390383419843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897068525","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43301526,0.00030212902,0.5647665,0.00014761025,0.000023605526,0.00036340556,0.0012079203,0.00004211917,0.00013142421],"genre_scores_gemma":[0.83985883,0.00007318754,0.15756847,0.00013743064,0.00004198975,0.00005426788,0.0021782662,0.000023761992,0.00006380255],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99877,0.00003896396,0.00030953978,0.00047365983,0.00022570496,0.00018216224],"domain_scores_gemma":[0.9989378,0.0001611111,0.00021951844,0.0003438462,0.0002660904,0.00007163417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000090165166,0.00016595304,0.000280617,0.00022488563,0.00016309963,0.000029469196,0.0000527376,0.00003119474,0.00017159678],"category_scores_gemma":[0.000039376166,0.00015117101,0.000064544,0.0014316514,0.00054623804,0.00032585202,0.000032097316,0.00012561145,0.0000053519593],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004931476,0.0010500733,0.25523457,0.00013160912,0.0007872407,0.00006266464,0.002599466,0.0032556374,0.030544877,0.0014134413,0.004345361,0.6956436],"study_design_scores_gemma":[0.0014918074,0.0008463875,0.83750206,0.0002637777,0.0029118524,0.00001839914,0.0010337648,0.13819882,0.0065542567,0.0010449111,0.009804105,0.00032985065],"about_ca_topic_score_codex":0.00056929793,"about_ca_topic_score_gemma":0.000048121005,"teacher_disagreement_score":0.69531375,"about_ca_system_score_codex":0.000053823933,"about_ca_system_score_gemma":0.000040324685,"threshold_uncertainty_score":0.6164575},"labels":[],"label_agreement":null},{"id":"W2897519381","doi":"10.1016/j.jalz.2018.06.491","title":"P1‐481: DEFAULT MODE NETWORK CONNECTIVITY CHANGE DETECTED BY DIFFUSION TENSOR IMAGING CONTRIBUTES TO COGNITIVE IMPAIRMENTS IN VASCULAR COGNITIVE IMPAIRMENT, NO DEMENTIA","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Default mode network; Montreal Cognitive Assessment; Diffusion MRI; White matter; Cognition; Dementia; Psychology; Prefrontal cortex; Audiology; Posterior cingulate; Vascular dementia; Neuroscience; Cardiology; Medicine; Cognitive impairment; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.036583717660380266,"score_gpt":0.3328418265583878,"score_spread":0.2962581088980075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897519381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88317263,0.016400672,0.089343615,0.0013479555,0.00033584342,0.0078684995,0.00043114313,0.00071180135,0.00038784955],"genre_scores_gemma":[0.99016345,0.00019133305,0.003546689,0.0038011868,0.00026238113,0.0015173265,0.0004129691,0.00009684315,0.000007842762],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969436,0.00015419498,0.0005632768,0.0009838298,0.0003712383,0.0009838659],"domain_scores_gemma":[0.9982447,0.00018211652,0.00023114459,0.00044097268,0.00060135074,0.00029972786],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003399736,0.0004825897,0.00054801704,0.00022649334,0.00038175716,0.000056778827,0.0002054253,0.000111604466,0.00015515102],"category_scores_gemma":[0.00014023522,0.00048484,0.00016899664,0.0007427579,0.00022061272,0.00026864378,0.00035414813,0.00033191466,0.00019318948],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023345395,0.0030667444,0.8274058,0.000041197425,0.011700795,0.00016671538,0.0007340806,0.0000039388747,0.046555474,0.00005661201,0.023408005,0.08452609],"study_design_scores_gemma":[0.016088448,0.0022886368,0.85234886,0.0016380546,0.030767774,0.00007518936,0.00041353842,0.011418306,0.06748618,0.0013501425,0.014285721,0.0018391422],"about_ca_topic_score_codex":0.00059700396,"about_ca_topic_score_gemma":0.00014407163,"teacher_disagreement_score":0.10699081,"about_ca_system_score_codex":0.000048699567,"about_ca_system_score_gemma":0.000048790716,"threshold_uncertainty_score":0.9997603},"labels":[],"label_agreement":null},{"id":"W2897543276","doi":"10.1002/jmri.26290","title":"Diffusion tensor imaging of white matter in patients with prediabetes by trace‐based spatial statistics","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Prediabetes; Medicine; White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Superior longitudinal fasciculus; Internal medicine; Magnetic resonance imaging; Radiology; Type 2 diabetes; Diabetes mellitus; Pathology; Endocrinology","score_opus":0.009361816085818807,"score_gpt":0.2686683266081283,"score_spread":0.25930651052230946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897543276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9295016,0.0011421742,0.06637231,0.002237455,0.00006053966,0.0003954533,0.000079884245,0.000020127087,0.00019046635],"genre_scores_gemma":[0.91108364,0.00002623397,0.08818429,0.00050378504,0.00007306973,0.000006588301,0.000007228752,0.00003343206,0.00008171845],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99858063,0.00003277598,0.00056502485,0.00018873008,0.0003921898,0.0002406508],"domain_scores_gemma":[0.9986967,0.00007067914,0.0004319949,0.00024130105,0.00047565356,0.000083688574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001435897,0.00015304172,0.00032159325,0.00018343666,0.000058612073,0.00001512308,0.00013477755,0.000019107974,0.00012306386],"category_scores_gemma":[0.000068278234,0.0001192748,0.000042702828,0.00019090195,0.00024228354,0.00013221799,0.000038353126,0.00024610406,0.000002041536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002703965,0.00025225306,0.9440218,0.000035910623,0.0000014767422,0.0000141643595,0.000070779126,0.0000033010983,0.0017480055,0.0000024338663,0.0040557436,0.049523704],"study_design_scores_gemma":[0.0028626253,0.00056330743,0.9836201,0.00055389333,0.0000466672,0.000021081198,0.000017722296,0.0056706127,0.0015106637,0.000117104566,0.0048974557,0.0001187353],"about_ca_topic_score_codex":0.000013109567,"about_ca_topic_score_gemma":0.0000014502814,"teacher_disagreement_score":0.049404968,"about_ca_system_score_codex":0.00004909475,"about_ca_system_score_gemma":0.00005867376,"threshold_uncertainty_score":0.48638853},"labels":[],"label_agreement":null},{"id":"W2897772899","doi":"10.1016/j.jalz.2018.06.2057","title":"IC‐06‐04: ANTEMORTEM LONGITUDINAL MRI METRICS AS A BIOMARKER OF POSTMORTEM BRAAK NFT STAGING","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Temporal lobe; Atrophy; Pathology; Neuropathology; Medicine; Magnetic resonance imaging; Neurofibrillary tangle; Senile plaques; Alzheimer's disease; Psychology; Neuroscience; Radiology; Disease","score_opus":0.10347928492331174,"score_gpt":0.3790310302017456,"score_spread":0.27555174527843385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897772899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6988726,0.059547175,0.19351748,0.010421615,0.0008286661,0.0041693463,0.00019381205,0.0017834564,0.030665834],"genre_scores_gemma":[0.9655598,0.00016087365,0.03330498,0.00064424064,0.0001150607,0.000035039637,0.000050909006,0.00005252664,0.00007660072],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99823666,0.000029057452,0.00049099355,0.0004969838,0.00037573188,0.00037055867],"domain_scores_gemma":[0.99846685,0.0000613568,0.00025022076,0.0007499384,0.00030941673,0.00016224364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023027926,0.00023265427,0.0003408278,0.00027997862,0.00014555248,0.000022296497,0.00023040714,0.00006822509,0.0003354694],"category_scores_gemma":[0.00004536406,0.00021977759,0.0001417055,0.0008299511,0.00020530424,0.00015485816,0.0001713943,0.00016414358,0.00014569366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047612007,0.0018507313,0.4815617,0.00012188593,0.019340165,0.00029633165,0.00044753213,0.0000014120668,0.24542478,0.00863473,0.106949866,0.13489476],"study_design_scores_gemma":[0.0023816414,0.0011831294,0.18795225,0.00024094136,0.024393918,0.00042416187,0.00016207139,0.0020247893,0.58289254,0.0016741249,0.19576438,0.000906073],"about_ca_topic_score_codex":0.0000742912,"about_ca_topic_score_gemma":0.0000055939167,"teacher_disagreement_score":0.33746773,"about_ca_system_score_codex":0.000010175105,"about_ca_system_score_gemma":0.00007905111,"threshold_uncertainty_score":0.896227},"labels":[],"label_agreement":null},{"id":"W2897779915","doi":"10.1016/j.jalz.2018.06.1327","title":"P2‐631: JAZZERCISE AS AN INTERVENTION FOR SUBJECTIVE COGNITIVE DECLINE IN POSTMENOPAUSAL WOMEN: PILOT STUDY RATIONALE AND FEASIBILITY","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Guenther Dermatology Research Centre; Western University; Robarts Clinical Trials; Parkwood Institute","funders":"","keywords":"Cognition; Physical therapy; Psychology; Cognitive decline; Physical medicine and rehabilitation; Cardiovascular fitness; Gait; Neuropsychology; Diffusion MRI; Posterior cingulate; Medicine; Magnetic resonance imaging; Physical fitness; Dementia; Internal medicine; Psychiatry","score_opus":0.11880431243032989,"score_gpt":0.418394331533933,"score_spread":0.2995900191036031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897779915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99063504,0.0007227177,0.0042655705,0.00034619845,0.00004130494,0.0037410902,0.00004721804,0.0000847859,0.00011606569],"genre_scores_gemma":[0.9935442,0.000011840995,0.0045088297,0.00056112057,0.00007781606,0.0011306471,0.00012614283,0.000024663063,0.000014705254],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998815,0.0000649953,0.00030096812,0.0004742717,0.00013431416,0.00021043165],"domain_scores_gemma":[0.99922574,0.000081457394,0.000096380645,0.00023181655,0.0002620911,0.00010250204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038335414,0.00014590794,0.00019846015,0.00009376741,0.00012590323,0.000024211626,0.000069323585,0.00002432524,0.00008644871],"category_scores_gemma":[0.00008665087,0.00014426406,0.000023588484,0.00015759689,0.00012773713,0.00020550532,0.000088607165,0.00010072631,0.000012410153],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.018074952,0.03843558,0.7944382,0.00005614521,0.005133608,0.000040390612,0.0060418723,8.740982e-7,0.035309337,0.0030208454,0.0004156927,0.09903251],"study_design_scores_gemma":[0.010250273,0.044734396,0.90255505,0.00006948929,0.0039175106,0.00003179415,0.002415532,0.00028520022,0.016911555,0.017623153,0.00083899195,0.0003670736],"about_ca_topic_score_codex":0.00009623296,"about_ca_topic_score_gemma":0.00023812798,"teacher_disagreement_score":0.108116835,"about_ca_system_score_codex":0.000021667927,"about_ca_system_score_gemma":0.00003833911,"threshold_uncertainty_score":0.5882918},"labels":[],"label_agreement":null},{"id":"W2897798352","doi":"10.1016/j.jalz.2018.06.2291","title":"IC‐P‐224: HETEROGENEOUS TAU‐PET SIGNAL IN THE HIPPOCAMPUS HELPS RESOLVE DISCREPANCIES BETWEEN IMAGING AND PATHOLOGY","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; McGill University Health Centre","funders":"","keywords":"Hippocampus; Entorhinal cortex; Hippocampal formation; Neuroscience; Positron emission tomography; Neuroimaging; Alzheimer's disease; Psychology; Voxel; Pittsburgh compound B; Dementia; Medicine; Pathology; Disease; Cognitive impairment; Cognition; Radiology","score_opus":0.051867200182784026,"score_gpt":0.33499694428727145,"score_spread":0.28312974410448744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897798352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.941014,0.030603133,0.009331106,0.015434544,0.00011000955,0.0013978749,0.000051564442,0.00033836305,0.0017194219],"genre_scores_gemma":[0.98526216,0.000094620395,0.01191669,0.0023655777,0.00020492628,0.00009373118,0.000031186595,0.000026697879,0.000004414792],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987951,0.0000721842,0.00026460184,0.0003808832,0.00016477703,0.00032245],"domain_scores_gemma":[0.99925876,0.00008496513,0.0000836224,0.00044041264,0.00005503403,0.00007718966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024305667,0.00016677259,0.00020524452,0.00007899514,0.00017231346,0.00003139154,0.00017804092,0.000032284115,0.00005889633],"category_scores_gemma":[0.00001848966,0.00012637216,0.000050744275,0.00016480467,0.00037100434,0.00007824948,0.00013521848,0.00020768194,0.000025595513],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018789753,0.0005040325,0.33751374,0.000032987256,0.002476002,0.0015578464,0.0029662973,0.000002471966,0.058247726,0.00318992,0.014948093,0.578373],"study_design_scores_gemma":[0.005215121,0.0023399254,0.3696945,0.00029911665,0.02552839,0.009281814,0.0017272822,0.0012545759,0.1696649,0.075901404,0.33698907,0.0021038877],"about_ca_topic_score_codex":0.000040237817,"about_ca_topic_score_gemma":0.000026239013,"teacher_disagreement_score":0.5762691,"about_ca_system_score_codex":0.0000043570244,"about_ca_system_score_gemma":0.000023863333,"threshold_uncertainty_score":0.51533073},"labels":[],"label_agreement":null},{"id":"W2898273293","doi":"10.1002/hbm.24435","title":"Developmental origins of depression‐related white matter properties: Findings from a prenatal birth cohort","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Psychology; Young adult; White matter; Depression (economics); Cingulum (brain); Cohort; Prenatal stress; Longitudinal study; Diffusion MRI; Uncinate fasciculus; Cohort study; Pediatrics; Medicine; Pregnancy; Developmental psychology; Offspring; Internal medicine; Magnetic resonance imaging; Pathology","score_opus":0.053580519763796124,"score_gpt":0.30489348037053304,"score_spread":0.2513129606067369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898273293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901821,0.000021598935,0.0046201246,0.0006715026,0.000022878317,0.0005484581,0.00001740825,0.00022116586,0.0036947879],"genre_scores_gemma":[0.9806625,0.000001911718,0.01622623,0.00091061817,0.00006503513,0.000072147566,0.00005046905,0.00003496624,0.0019761196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99892485,0.000017052871,0.00033063174,0.00035356884,0.00017196243,0.00020194793],"domain_scores_gemma":[0.999489,0.000024692825,0.00010017887,0.00024559035,0.000070669994,0.00006986866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009221033,0.00014543837,0.00022016336,0.00012359906,0.0002083692,0.000015349158,0.00014086337,0.000060288985,0.0008712046],"category_scores_gemma":[0.000031544114,0.00012411902,0.00005059368,0.00018644078,0.0001948568,0.0000942176,0.000119945005,0.00017189678,0.00009861166],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018188779,0.00005955235,0.6080405,0.000057451067,0.000042075822,0.000006180873,0.0012149799,4.9392565e-7,0.38530365,0.00026524081,0.0047906507,0.00020100581],"study_design_scores_gemma":[0.00066944194,0.00006169092,0.94036293,0.0008681754,0.000024235356,0.00005021639,0.00014955494,0.00017056616,0.028157508,0.00082873,0.028451364,0.00020556911],"about_ca_topic_score_codex":0.000048962545,"about_ca_topic_score_gemma":0.0000032856724,"teacher_disagreement_score":0.35714614,"about_ca_system_score_codex":0.00010504231,"about_ca_system_score_gemma":0.0000395754,"threshold_uncertainty_score":0.95390797},"labels":[],"label_agreement":null},{"id":"W2898476585","doi":"10.1016/j.neuroimage.2018.10.067","title":"Diffusion tensor imaging shows mechanism-specific differences in injury pattern and progression in rat models of acute spinal cord injury","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; Wings for Life","keywords":"Diffusion MRI; White matter; Spinal cord injury; Spinal cord; Anatomy; Medicine; Corticospinal tract; Cord; Diffuse axonal injury; Superior longitudinal fasciculus; Magnetic resonance imaging; Traumatic brain injury; Radiology; Fractional anisotropy; Surgery","score_opus":0.06474475424370242,"score_gpt":0.3664488663145007,"score_spread":0.3017041120707983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898476585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9816135,0.00007271935,0.016372398,0.0008907392,0.00006611385,0.00070155924,0.00002738538,0.000103381775,0.00015221308],"genre_scores_gemma":[0.9935208,0.00047858173,0.0053822235,0.00041406858,0.000054398963,0.00006826868,0.000006897898,0.000034956545,0.000039783707],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99855226,0.000051662333,0.00038390292,0.0005174377,0.000221358,0.00027336067],"domain_scores_gemma":[0.99928117,0.00002549753,0.00013651352,0.00040411917,0.000070493006,0.00008218662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010946116,0.00020484303,0.00034772573,0.0002794504,0.00006026992,0.000021470589,0.0001463583,0.00005032113,0.000018321036],"category_scores_gemma":[0.000014790859,0.00017261614,0.000040846702,0.00029164806,0.00022697478,0.00019362487,0.00020263612,0.00032101534,0.0000024102849],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010671295,0.00030183804,0.082984015,0.000058046466,0.0000027151386,0.00010356512,0.0000887149,7.2293545e-8,0.7337733,0.0005212999,0.0001709363,0.18092838],"study_design_scores_gemma":[0.0037462218,0.007544647,0.46645176,0.0023073985,0.00010930324,0.00031973523,0.0001607537,0.045797624,0.4425135,0.028949015,0.0011378455,0.0009621901],"about_ca_topic_score_codex":0.000017590699,"about_ca_topic_score_gemma":0.0000037343136,"teacher_disagreement_score":0.38346773,"about_ca_system_score_codex":0.00002677201,"about_ca_system_score_gemma":0.000018997802,"threshold_uncertainty_score":0.7039082},"labels":[],"label_agreement":null},{"id":"W2898573652","doi":"10.1002/hbm.24437","title":"Corticospinal tract degeneration in ALS unmasked in T1‐weighted images using texture analysis","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Canadian Institutes of Health Research; Fondation Brain Canada; ALS Society of Canada; ALS Association","keywords":"Corticospinal tract; Medicine; Diffusion MRI; Voxel; Magnetic resonance imaging; Amyotrophic lateral sclerosis; Nuclear medicine; Internal capsule; Radiology; Pathology; White matter","score_opus":0.12037111040865021,"score_gpt":0.40619548992288373,"score_spread":0.2858243795142335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898573652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89320266,0.000045270095,0.10453593,0.0013334556,0.000011792194,0.000351483,0.0000030206777,0.00010277383,0.0004136053],"genre_scores_gemma":[0.97310615,0.000005486453,0.025674919,0.00082964194,0.0001399749,0.000028999351,0.00005178468,0.000019422761,0.00014364293],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99883676,0.00005447161,0.000383197,0.00035168134,0.00013598008,0.00023790765],"domain_scores_gemma":[0.99940175,0.000042411655,0.00012272973,0.00030993996,0.00007004328,0.00005313162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023462491,0.0001368233,0.00028820772,0.0006250761,0.00014651023,0.000029312896,0.00008305054,0.00006641198,0.00007925641],"category_scores_gemma":[0.00006483424,0.00013874855,0.00007567373,0.0012533562,0.00009073561,0.00011805197,0.0000301864,0.00021873208,0.0000042160623],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012229073,0.00013636258,0.0737291,0.000021440832,0.000021007363,0.000038175993,0.00031669965,0.00008592802,0.9234058,0.0009417138,0.00019905537,0.0010924523],"study_design_scores_gemma":[0.00071750546,0.00008355776,0.95761865,0.0001792083,0.00010708925,0.000026826978,0.000093524905,0.029304978,0.0070895534,0.0030329935,0.0015207613,0.00022535789],"about_ca_topic_score_codex":0.0000795923,"about_ca_topic_score_gemma":0.00009975063,"teacher_disagreement_score":0.9163163,"about_ca_system_score_codex":0.00011896832,"about_ca_system_score_gemma":0.000029410354,"threshold_uncertainty_score":0.5658002},"labels":[],"label_agreement":null},{"id":"W2899191342","doi":"10.1016/j.nicl.2018.10.026","title":"Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Ministry of Education; Ministry of Education - Singapore; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Alzheimer's Drug Discovery Foundation; AbbVie; Alzheimer's Association; Foundation for the National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Precuneus; Psychology; White matter; Neuroscience; Apolipoprotein E; Cognitive decline; Temporal lobe; Corpus callosum; Cognition; Dementia; Disease; Medicine; Pathology; Magnetic resonance imaging","score_opus":0.242862737418475,"score_gpt":0.4746921061407849,"score_spread":0.2318293687223099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899191342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905014,0.000032235683,0.0075602434,0.0006948349,0.00015440551,0.00062067993,0.000036630772,0.00015138443,0.00024820038],"genre_scores_gemma":[0.9740248,0.000013752754,0.024185892,0.001406055,0.0002669685,0.00001287407,0.000017384566,0.00004540391,0.000026913556],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99821407,0.00008461413,0.00069050066,0.0005396339,0.00021514746,0.00025604462],"domain_scores_gemma":[0.9983887,0.0000982375,0.00022624967,0.0008170807,0.00016070787,0.00030901222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020307093,0.00018236326,0.0003775283,0.00006631604,0.00008934841,0.0000118239495,0.00013992954,0.00006128265,0.00010609547],"category_scores_gemma":[0.0001778783,0.00015467123,0.000275429,0.00016004247,0.00046695588,0.000105815874,0.00015737742,0.0002833643,0.000033218257],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011794889,0.00047167361,0.9918725,0.000025098007,0.000020865618,0.00002181012,0.00000937993,0.0000032508335,0.0066994894,0.00002351361,0.00048239442,0.00025210582],"study_design_scores_gemma":[0.0005366728,0.00048240498,0.9723442,0.000056071498,0.00027941083,0.000021198395,0.0000070455017,0.0022324834,0.022933232,0.00014335947,0.0008079844,0.00015594135],"about_ca_topic_score_codex":0.0000029419427,"about_ca_topic_score_gemma":2.4993798e-7,"teacher_disagreement_score":0.019528273,"about_ca_system_score_codex":0.000015032969,"about_ca_system_score_gemma":0.0000798725,"threshold_uncertainty_score":0.630731},"labels":[],"label_agreement":null},{"id":"W2899606321","doi":"10.1371/journal.pone.0206607","title":"Data-driven, voxel-based analysis of brain PET images: Application of PCA and LASSO methods to visualize and quantify patterns of neurodegeneration","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Lasso (programming language); Voxel; Principal component analysis; Pattern recognition (psychology); Artificial intelligence; Functional principal component analysis; Positron emission tomography; Computer science; Covariate; Mathematics; Nuclear medicine; Medicine; Machine learning","score_opus":0.1882450430924438,"score_gpt":0.44988884250456906,"score_spread":0.26164379941212523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899606321","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5297574,0.000016321519,0.46881437,0.0008553927,0.0000015477286,0.00027335482,0.0002480455,0.00002169807,0.000011859759],"genre_scores_gemma":[0.7045843,0.000032690958,0.29490593,0.00021233302,0.000015307136,0.000026407832,0.00020031605,0.0000107349515,0.0000120030345],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990909,0.00006334401,0.0003138353,0.00030563673,0.0001521717,0.00007408713],"domain_scores_gemma":[0.9986562,0.0001737875,0.00021693874,0.00067114754,0.00022658927,0.00005532749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023793789,0.000084135114,0.00038161993,0.00022410571,0.000025084995,0.000004512646,0.00009825179,0.000023298355,0.000007199428],"category_scores_gemma":[0.00021044936,0.0000807104,0.000027840244,0.00045070215,0.00009679674,0.00005242881,0.00008251385,0.000050519073,3.021042e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041494084,0.00043575032,0.037827943,0.00018287974,0.00014075817,2.4282383e-7,0.000044961427,0.000012275092,0.9583703,0.0003632505,0.0000585102,0.0025216246],"study_design_scores_gemma":[0.00030540978,0.000329849,0.07730159,0.000081263606,0.0013050893,9.515723e-7,0.000012888549,0.12374192,0.7965651,0.00007517704,0.00020552,0.00007524735],"about_ca_topic_score_codex":0.00005759171,"about_ca_topic_score_gemma":0.000024243038,"teacher_disagreement_score":0.17482689,"about_ca_system_score_codex":0.000006251008,"about_ca_system_score_gemma":0.000015272462,"threshold_uncertainty_score":0.32912746},"labels":[],"label_agreement":null},{"id":"W2900068659","doi":"10.1007/s12035-018-1405-1","title":"Regional Amyloid-β Load and White Matter Abnormalities Contribute to Hypometabolism in Alzheimer’s Dementia","year":2018,"lang":"en","type":"article","venue":"Molecular Neurobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute","funders":"National Institute on Aging","keywords":"Fractional anisotropy; Precuneus; Diffusion MRI; White matter; Standardized uptake value; Dementia; Psychology; Positron emission tomography; Neuroscience; Posterior cingulate; Neuroimaging; Pathology; Magnetic resonance imaging; Internal medicine; Medicine; Disease; Cognition; Radiology","score_opus":0.038701346181607706,"score_gpt":0.31713659956393536,"score_spread":0.27843525338232766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900068659","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9659001,0.0008794347,0.009732436,0.020916052,0.00008939058,0.0006645666,0.000025625806,0.00011404779,0.0016783453],"genre_scores_gemma":[0.96287054,0.000054180575,0.005518578,0.0312678,0.000060503207,0.00007644211,0.000021544354,0.000023951381,0.000106435364],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990308,0.000052107207,0.00020304635,0.00036026805,0.00006785885,0.00028588096],"domain_scores_gemma":[0.9994492,0.000022609654,0.000043695127,0.00029631806,0.000090664216,0.000097520584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000811806,0.00013823796,0.00022470517,0.00012195164,0.000046385747,0.000009998411,0.00009144884,0.000059765203,0.00006377089],"category_scores_gemma":[0.000024798792,0.00013142922,0.000036276488,0.00016904701,0.00019192729,0.000031503194,0.00011873421,0.00013833956,0.00007163201],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005320283,0.00030083169,0.18696024,0.000036835638,0.00033205288,0.00034048906,0.0004274592,0.00001833623,0.73370606,0.01130268,0.062605545,0.0034374355],"study_design_scores_gemma":[0.0019512911,0.00070521096,0.39013898,0.000049663307,0.00029988444,0.0009155582,0.000021410488,0.0000599059,0.061945077,0.003506004,0.5399485,0.00045850076],"about_ca_topic_score_codex":0.000021599923,"about_ca_topic_score_gemma":0.000007943441,"teacher_disagreement_score":0.671761,"about_ca_system_score_codex":0.000010820002,"about_ca_system_score_gemma":0.000026275075,"threshold_uncertainty_score":0.5359528},"labels":[],"label_agreement":null},{"id":"W2900602020","doi":"10.3389/fncel.2018.00428","title":"White Matter Plasticity Keeps the Brain in Tune: Axons Conduct While Glia Wrap","year":2018,"lang":"en","type":"review","venue":"Frontiers in Cellular Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Neuroscience; Glutamatergic; Neuroplasticity; Context (archaeology); Biology; White matter; Oligodendrocyte; Myelin; Plasticity; Diffusion MRI; Psychology; Central nervous system; Glutamate receptor; Physics; Medicine","score_opus":0.1321283382690935,"score_gpt":0.36998595918111293,"score_spread":0.23785762091201942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900602020","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026692948,0.89806056,0.0872255,0.004059913,0.0026203676,0.0050386623,0.0001492241,0.00026537894,0.002313454],"genre_scores_gemma":[0.00056050654,0.9783305,0.011673639,0.0040655322,0.00024462424,0.0005565677,0.000043804142,0.0001410815,0.0043837773],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99697953,0.00022268294,0.0006911591,0.0011213727,0.00037634932,0.0006089002],"domain_scores_gemma":[0.99833465,0.00015471865,0.00030352283,0.0010285351,0.00003935522,0.00013924402],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004231556,0.0004511309,0.0010907387,0.0004191848,0.00017436875,0.00006844772,0.0009872257,0.00018484885,0.00004023719],"category_scores_gemma":[0.00025688333,0.00032513766,0.00023997053,0.0015969683,0.0009416985,0.00013131561,0.00028868948,0.001158147,0.000052434032],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059704395,0.0010284712,0.03354225,0.009175052,0.000025008509,0.0010179668,0.0003941672,0.000042198746,0.0008962379,0.00045526488,0.8520613,0.10130241],"study_design_scores_gemma":[0.00016921751,0.00006502332,0.00071286364,0.0020014348,0.000077344426,0.00010496617,0.0000122366155,0.0005324716,0.00004777347,0.00024827622,0.99572873,0.00029965155],"about_ca_topic_score_codex":0.000009096102,"about_ca_topic_score_gemma":0.0000035084347,"teacher_disagreement_score":0.14366747,"about_ca_system_score_codex":0.00015825137,"about_ca_system_score_gemma":0.00023353046,"threshold_uncertainty_score":0.99992007},"labels":[],"label_agreement":null},{"id":"W2900804267","doi":"10.1016/j.neuroimage.2018.11.015","title":"Arterial stiffness and white matter integrity in the elderly: A diffusion tensor and magnetization transfer imaging study","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Clinical Research Institute; Université de Montréal; Polytechnique Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Arterial stiffness; Corpus callosum; Internal capsule; Myelin; Corona radiata (embryology); External capsule; Pulse wave velocity; Internal medicine; Cardiology; Medicine; Anatomy; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.036469752460684284,"score_gpt":0.32324278488670943,"score_spread":0.28677303242602514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900804267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891288,0.0000112831995,0.003517092,0.0058730314,0.000035553796,0.0008857512,0.0000060122143,0.00006690409,0.00047553424],"genre_scores_gemma":[0.99753845,0.000015531888,0.00055593875,0.0016325014,0.000097719596,0.00005891688,0.0000041129633,0.00002043616,0.00007641377],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99916124,0.00007290884,0.00016559438,0.00033582334,0.00012042385,0.00014403486],"domain_scores_gemma":[0.99957347,0.00003938565,0.000019946152,0.00028276458,0.000044783614,0.000039672355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010706037,0.00012495577,0.00014001186,0.000075604206,0.0001108515,0.000063170424,0.0000713785,0.000022251383,0.000043181335],"category_scores_gemma":[0.00002226573,0.000087751,0.000015585316,0.0001562256,0.00016191704,0.0001042837,0.000043200504,0.00024391258,0.0000051308593],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035594503,0.00069616555,0.8483459,0.000054774217,0.0000032589433,0.0000969754,0.0029271941,1.04646524e-7,0.11773693,0.00009701636,0.0011002148,0.028585533],"study_design_scores_gemma":[0.0012564851,0.00024611293,0.9960221,0.000023912922,0.000031977,0.00011971201,0.00028629327,0.000470824,0.00010698603,0.00023194622,0.0011190783,0.00008454094],"about_ca_topic_score_codex":0.000019271707,"about_ca_topic_score_gemma":0.000014528063,"teacher_disagreement_score":0.14767624,"about_ca_system_score_codex":0.0000064711817,"about_ca_system_score_gemma":0.0000069451653,"threshold_uncertainty_score":0.3578382},"labels":[],"label_agreement":null},{"id":"W2900930986","doi":"10.1016/j.nicl.2018.11.006","title":"White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; Canada Research Chairs; SickKids Foundation; University of Toronto; Children's Hospital of Western Ontario; Hospital for Sick Children; Western University","funders":"Canadian Institutes of Health Research; Ontario Brain Institute","keywords":"White matter; Corpus callosum; Fractional anisotropy; Corona radiata (embryology); Diffusion MRI; Interquartile range; Fasciculus; Medicine; Magnetic resonance imaging; Connectome; Diffuse axonal injury; Anatomy; Neuroscience; Functional connectivity; Internal medicine; Psychology; Traumatic brain injury; Radiology","score_opus":0.060511695163842416,"score_gpt":0.3845515843053998,"score_spread":0.3240398891415574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900930986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929306,0.000027668772,0.0011917695,0.004173665,0.00022290697,0.0004662969,0.000060776594,0.00017361899,0.00075271394],"genre_scores_gemma":[0.9900358,0.000052414747,0.002968431,0.006110856,0.00040468693,0.00003202135,0.000030488647,0.00003761975,0.0003277036],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99841875,0.00008773243,0.00044162196,0.00066165684,0.00014170649,0.000248556],"domain_scores_gemma":[0.99889684,0.0002708996,0.00010388877,0.00048192855,0.000094562565,0.00015190203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019587173,0.00018420737,0.00031999144,0.0000836653,0.00008518634,0.00002978331,0.00008998103,0.00013796196,0.00016845156],"category_scores_gemma":[0.00031539527,0.00016516705,0.00008185815,0.00018260922,0.0006196953,0.00014023062,0.0001575079,0.00063840975,0.000038882343],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005066641,0.00014019651,0.97985137,0.000025192876,0.000006945558,0.000037572612,0.000026195772,2.3218895e-7,0.00686626,0.00003123061,0.00942549,0.0030826612],"study_design_scores_gemma":[0.0009904099,0.00045155545,0.98938805,0.00004886938,0.000030432382,0.00018518652,0.0000045598204,0.00040594058,0.0007546107,0.0009026411,0.0067049153,0.0001328203],"about_ca_topic_score_codex":0.000005063807,"about_ca_topic_score_gemma":0.000004443425,"teacher_disagreement_score":0.009536699,"about_ca_system_score_codex":0.000018283932,"about_ca_system_score_gemma":0.000044216373,"threshold_uncertainty_score":0.67353165},"labels":[],"label_agreement":null},{"id":"W2900990031","doi":"10.3389/fnins.2018.00854","title":"Inter-Vendor Reproducibility of Myelin Water Imaging Using a 3D Gradient and Spin Echo Sequence","year":2018,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; University of Manitoba; University of British Columbia","funders":"National Research Foundation of Korea; National Research Foundation","keywords":"White matter; Corpus callosum; Reproducibility; Myelin; Magnetic resonance imaging; Nuclear magnetic resonance; Nuclear medicine; Splenium; T2 relaxation; Coefficient of variation; Relaxometry; Spin echo; Chemistry; Medicine; Radiology; Physics; Pathology; Internal medicine; Central nervous system","score_opus":0.08428072625631944,"score_gpt":0.3744385856514024,"score_spread":0.290157859395083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2900990031","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81509393,0.00005234327,0.18302523,0.0008145216,0.00035499403,0.00042124497,0.000018036382,0.00007308042,0.00014661906],"genre_scores_gemma":[0.8739862,0.0000263479,0.1253781,0.00050617434,0.000032778476,0.0000131959505,0.0000013420432,0.000010307927,0.000045539273],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99838424,0.000030854393,0.0002652305,0.000934139,0.0001327561,0.0002527843],"domain_scores_gemma":[0.99889326,0.000011049764,0.00007077923,0.00089109264,0.000064162894,0.00006963932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043919455,0.00010326436,0.00018892063,0.00014682188,0.00008021731,0.0000130306125,0.00016567856,0.000017212458,0.000006170974],"category_scores_gemma":[0.00043725446,0.000082624894,0.000026904705,0.00031465304,0.0009453673,0.00015095623,0.0001641222,0.00014736336,5.1257007e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040325747,0.0000873865,0.19080687,0.000043389995,6.6965094e-7,0.00002487817,0.0003170291,0.000008222459,0.7927682,0.000032450942,0.00055430765,0.015316284],"study_design_scores_gemma":[0.0007511834,0.00046096332,0.06349742,0.000460927,0.000036070265,0.0004971154,0.00016444515,0.20638254,0.7067063,0.005876873,0.014765775,0.00040042723],"about_ca_topic_score_codex":0.000029807203,"about_ca_topic_score_gemma":8.3160177e-7,"teacher_disagreement_score":0.20637432,"about_ca_system_score_codex":0.00005610299,"about_ca_system_score_gemma":0.000030839154,"threshold_uncertainty_score":0.3483245},"labels":[],"label_agreement":null},{"id":"W2901083077","doi":"10.1002/jmri.26543","title":"White matter myelin profiles linked to clinical subtypes of Parkinson's disease","year":2018,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Myelin; Psychology; Medicine; Apathy; Population; Cingulum (brain); Internal medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.043332027507938325,"score_gpt":0.37115914392323757,"score_spread":0.32782711641529927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901083077","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9322209,0.0065455115,0.014245206,0.044043053,0.00036153154,0.00073275185,0.000022393977,0.000063384265,0.0017653122],"genre_scores_gemma":[0.89578325,0.00034514946,0.09932079,0.002936515,0.00082887325,0.00001174879,0.0000010772707,0.000031064406,0.00074153126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99842405,0.00005085316,0.0007932822,0.0002222111,0.0002975092,0.00021210691],"domain_scores_gemma":[0.99837905,0.00008585639,0.0003704649,0.00039036502,0.000504452,0.00026981274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041830738,0.0001299835,0.00035975804,0.0001493082,0.000046119163,0.000017748722,0.00021478465,0.000026554351,0.00022623251],"category_scores_gemma":[0.00027306707,0.00010514676,0.00016068023,0.00022681821,0.00024983348,0.000098870274,0.00007228327,0.00027361294,0.00004033479],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004057674,0.0001229297,0.88448715,0.000033045257,0.0000031938887,0.0000565761,0.000052477353,0.000001280096,0.0009070825,0.000030193733,0.021079388,0.09282088],"study_design_scores_gemma":[0.00046816643,0.0003127255,0.7555533,0.00036755067,0.000052401898,0.00007546628,0.000017474447,0.00028163084,0.00030963015,0.0004588256,0.24202369,0.00007915301],"about_ca_topic_score_codex":0.0000021279743,"about_ca_topic_score_gemma":3.3308342e-7,"teacher_disagreement_score":0.2209443,"about_ca_system_score_codex":0.000022078088,"about_ca_system_score_gemma":0.000116280826,"threshold_uncertainty_score":0.42877606},"labels":[],"label_agreement":null},{"id":"W2901161095","doi":"10.1089/brain.2018.0611","title":"Microstructural Findings in White Matter Associated with Cannabis and Alcohol Use in Early-Phase Psychosis: A Diffusion Tensor Imaging and Relaxometry Study","year":2018,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"International Business Machines Corporation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Cannabis; Psychosis; Psychology; Relaxometry; Inferior longitudinal fasciculus; Schizophrenia (object-oriented programming); Psychiatry; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.03454579141614181,"score_gpt":0.3432349715257514,"score_spread":0.30868918010960955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901161095","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9940483,0.000015642372,0.00017315334,0.0046685976,0.000014236108,0.00096348283,0.000018457873,0.00007345631,0.000024689904],"genre_scores_gemma":[0.99778694,0.0000027530116,0.00076205266,0.0011861665,0.000016261565,0.00008765549,0.000004211635,0.000027381702,0.0001266016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989248,0.00007469451,0.0001777559,0.00048104918,0.0001052352,0.00023647532],"domain_scores_gemma":[0.99940014,0.00015769876,0.000068956244,0.00024182526,0.000056620313,0.00007478866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002286838,0.00016366724,0.00026186177,0.00024671495,0.00009597632,0.000050104558,0.000045307926,0.000044492346,0.000008748258],"category_scores_gemma":[0.00033274465,0.00013891942,0.000015818987,0.00045659507,0.00016783443,0.00021764876,0.00007545815,0.0002666097,8.654076e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019763605,0.00033053942,0.9896756,0.000008326628,0.00000832442,0.000036476667,0.0008975766,6.290611e-8,0.0073927795,0.000004099524,0.00058963854,0.0008589758],"study_design_scores_gemma":[0.004659749,0.00036521352,0.9935838,0.00015896551,0.000020970932,0.00007079898,0.00017821169,0.00029133997,0.00032169805,0.00010787984,0.00008229073,0.00015906937],"about_ca_topic_score_codex":0.0005991863,"about_ca_topic_score_gemma":0.0009572015,"teacher_disagreement_score":0.007071081,"about_ca_system_score_codex":0.00007210789,"about_ca_system_score_gemma":0.000011910577,"threshold_uncertainty_score":0.56649697},"labels":[],"label_agreement":null},{"id":"W2901273401","doi":"10.1371/journal.pone.0203271","title":"Diffusion spectrum imaging in white matter microstructure in subjects with type 2 diabetes","year":2018,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Fractional anisotropy; Cingulum (brain); Uncinate fasciculus; White matter; Medicine; Diffusion MRI; Internal medicine; Tractography; Cardiology; Glycated hemoglobin; Type 2 diabetes; Fasciculus; Diabetes mellitus; Nuclear medicine; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.02455098010149183,"score_gpt":0.26337317626290463,"score_spread":0.23882219616141281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901273401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942072,0.000046728983,0.00006058591,0.0042678933,0.000007794926,0.00030497735,0.0000023566042,0.00007198261,0.0010304478],"genre_scores_gemma":[0.9877579,0.000018929144,0.010439646,0.0014091298,0.00007268714,0.000019407615,0.000011149876,0.00002615819,0.00024499232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937254,0.000008639284,0.000107779924,0.00021390253,0.00009750671,0.0001996517],"domain_scores_gemma":[0.9996382,0.000011064705,0.000032647356,0.00024982364,0.000032022475,0.000036245616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000292305,0.00009184209,0.0001540514,0.000113860195,0.000025681447,0.000009499831,0.0000569525,0.00002360612,0.00011811167],"category_scores_gemma":[0.000010850169,0.000074900956,0.000009468161,0.00029505423,0.00007072483,0.00005005281,0.000037984635,0.00017136722,0.000037022543],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003258191,0.00018054302,0.769055,0.00002731491,0.000002458167,0.000008494924,0.00007418996,1.2414782e-7,0.23040414,0.000009926598,0.0001280217,0.00007718571],"study_design_scores_gemma":[0.00050003215,0.00010707065,0.86731404,0.0004414226,0.000019071655,0.0000070487185,0.000012799112,0.0002500935,0.1303225,0.00080253853,0.00012332303,0.00010002908],"about_ca_topic_score_codex":0.000011183659,"about_ca_topic_score_gemma":0.000037162336,"teacher_disagreement_score":0.10008162,"about_ca_system_score_codex":0.00003823389,"about_ca_system_score_gemma":0.00001349366,"threshold_uncertainty_score":0.30543724},"labels":[],"label_agreement":null},{"id":"W2901408666","doi":"10.1159/000494134","title":"Repeated Pediatric Concussions Evoke Long-Term Oligodendrocyte and White Matter Microstructural Dysregulation Distant from the Injury","year":2018,"lang":"en","type":"article","venue":"Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"","keywords":"White matter; Concussion; Diffusion MRI; OLIG2; Traumatic brain injury; Medicine; Neuroscience; Anterior commissure; Neuropsychology; Psychology; Oligodendrocyte; Poison control; Myelin; Cognition; Injury prevention; Magnetic resonance imaging; Psychiatry; Central nervous system; Radiology","score_opus":0.031064054534084288,"score_gpt":0.31557673334302994,"score_spread":0.28451267880894565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901408666","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959981,0.000019530717,0.0018037492,0.0013932739,0.0001653667,0.00033368592,0.000040629042,0.00010320303,0.00014248364],"genre_scores_gemma":[0.9917875,0.00004740462,0.0044403505,0.0031852324,0.00009147372,0.000019976214,0.000028110717,0.000015430724,0.0003845381],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99894106,0.000018941944,0.0002070203,0.00044048906,0.00018569517,0.00020677107],"domain_scores_gemma":[0.9994999,0.000027786768,0.0000840088,0.0002473647,0.000043186374,0.00009772298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047336318,0.00013637105,0.000107805274,0.00004491852,0.00043046923,0.00006220523,0.00016644517,0.000028763261,0.000052635485],"category_scores_gemma":[0.00002976187,0.00009064081,0.000021938447,0.00034987653,0.0004194662,0.00014601221,0.0001911958,0.00012755768,0.000023243367],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024998206,0.000012060897,0.841216,0.0000036358442,7.7391826e-7,0.0000072176026,0.00012517702,7.5453706e-8,0.15696903,0.000017641969,0.00090805074,0.0007153092],"study_design_scores_gemma":[0.0001709483,0.000040405466,0.9682575,0.000019612946,0.000015037611,0.00016286335,0.000011407768,0.00008380582,0.03013559,0.000078301884,0.0009122441,0.00011228054],"about_ca_topic_score_codex":0.0000068947797,"about_ca_topic_score_gemma":0.000002950498,"teacher_disagreement_score":0.12704147,"about_ca_system_score_codex":0.0000412419,"about_ca_system_score_gemma":0.000049932663,"threshold_uncertainty_score":0.3696225},"labels":[],"label_agreement":null},{"id":"W2901469177","doi":"10.1016/j.arr.2018.11.004","title":"MRI-based evaluation of structural degeneration in the ageing brain: Pathophysiology and assessment","year":2018,"lang":"en","type":"review","venue":"Ageing Research Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Columbian Hospital; Surrey Memorial Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; China Scholarship Council","keywords":"Ageing; White matter; Neuroscience; Atrophy; Brain aging; Medicine; Magnetic resonance imaging; Degeneration (medical); Pathology; Physical medicine and rehabilitation; Psychology; Radiology; Disease; Internal medicine","score_opus":0.5339555385415052,"score_gpt":0.6172250369411001,"score_spread":0.08326949839959485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901469177","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044652304,0.99264896,0.0005547829,0.0006925678,0.000022321856,0.005344087,0.000006384459,0.000015851263,0.000268541],"genre_scores_gemma":[0.0005183023,0.98886555,0.008481546,0.00019168657,0.00016304999,0.0015679763,0.0001667909,0.000027296626,0.000017812677],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9944796,0.0033265946,0.00075719965,0.0004764799,0.00068921753,0.00027091324],"domain_scores_gemma":[0.99759644,0.0008566268,0.0003538287,0.00081442826,0.00033042982,0.00004822707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009369801,0.00021382,0.0010239476,0.0003017583,0.0001614039,0.00003086885,0.00025979834,0.00011891418,0.000020457403],"category_scores_gemma":[0.0013023658,0.00012590256,0.00018118776,0.0007512324,0.00022593811,0.000054949014,0.00009607262,0.00087438204,0.000005138859],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000019976924,0.000021401782,0.000010335525,0.0066966508,0.0000052922474,0.00001263188,0.000027350174,0.0000010490855,0.00011854223,0.00028424183,0.0011418138,0.9916787],"study_design_scores_gemma":[0.00022216691,0.00019829042,0.0004162185,0.013872289,0.00023769638,0.000019757066,0.000007511444,0.0017593475,0.000010311186,0.00197028,0.9811654,0.00012074049],"about_ca_topic_score_codex":0.000023809906,"about_ca_topic_score_gemma":0.0000149465095,"teacher_disagreement_score":0.99155796,"about_ca_system_score_codex":0.00018055453,"about_ca_system_score_gemma":0.00045677755,"threshold_uncertainty_score":0.5134157},"labels":[],"label_agreement":null},{"id":"W2901502594","doi":"10.1016/j.neuroimage.2018.11.018","title":"Bundle-specific tractography with incorporated anatomical and orientational priors","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Computer science; Artificial intelligence; Bundle; Diffusion MRI; Representation (politics); Prior probability; False positive paradox; Pattern recognition (psychology); Computer vision; Bayesian probability; Magnetic resonance imaging","score_opus":0.05679261682419582,"score_gpt":0.3304423075185419,"score_spread":0.2736496906943461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901502594","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97983754,0.000027634813,0.015628006,0.0014448152,0.000028459113,0.0003708716,0.000013961589,0.0002854536,0.0023632743],"genre_scores_gemma":[0.9586924,0.000043425676,0.04011322,0.0008848451,0.00009853369,0.000024109808,0.000024901788,0.000029619217,0.00008894355],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991907,0.000014376288,0.00013860741,0.00034834264,0.00015788116,0.00015012582],"domain_scores_gemma":[0.999397,0.000035704546,0.0000616391,0.00026240706,0.00012193275,0.0001213622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037503964,0.00011933525,0.00013133248,0.00011105129,0.00010948269,0.000025631247,0.00005343568,0.00003122964,0.000047412854],"category_scores_gemma":[0.000012876955,0.000097096374,0.000025933974,0.0004188514,0.00043057583,0.00010082682,0.000026921529,0.00018319,0.000014791371],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019502897,0.0018192456,0.3938571,0.00009530197,0.000066781766,0.00041504428,0.0004509462,0.000002607142,0.50940984,0.042037204,0.017059688,0.032835975],"study_design_scores_gemma":[0.0023196922,0.00201226,0.791554,0.00005636586,0.00006657593,0.0009478236,0.00005085021,0.0005168848,0.0315719,0.0028980267,0.16764188,0.00036375682],"about_ca_topic_score_codex":0.0000030840388,"about_ca_topic_score_gemma":0.0000011202354,"teacher_disagreement_score":0.47783792,"about_ca_system_score_codex":0.000010477717,"about_ca_system_score_gemma":0.000028479597,"threshold_uncertainty_score":0.39594752},"labels":[],"label_agreement":null},{"id":"W2901779940","doi":"10.1007/s00429-018-1798-7","title":"A population-based atlas of the human pyramidal tract in 410 healthy participants","year":2018,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Région Normandie","keywords":"Tractography; Pyramidal tracts; Diffusion MRI; Atlas (anatomy); Population; Corticospinal tract; Human brain; Artificial intelligence; Neuroscience; Psychology; Magnetic resonance imaging; Computer science; Anatomy; Medicine; Radiology","score_opus":0.0587474499733975,"score_gpt":0.3642715730419366,"score_spread":0.3055241230685391,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901779940","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99631,0.000015330816,0.0009930087,0.0022493317,0.000050015504,0.00026079497,0.0000069044,0.00003084785,0.00008377734],"genre_scores_gemma":[0.9979568,7.171343e-7,0.00042742738,0.0014459182,0.00009942514,0.000009829986,0.00001676575,0.0000075247826,0.000035579953],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99952614,0.000019330722,0.0001460135,0.00013214258,0.00007805691,0.00009832462],"domain_scores_gemma":[0.9996693,0.000029516552,0.00006915428,0.00017218686,0.000028363664,0.000031447926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005171823,0.000058973583,0.00010026938,0.000042130963,0.00008758345,0.0000039069896,0.000024411273,0.00004339263,0.000025657104],"category_scores_gemma":[0.00004005264,0.000040514118,0.00002276789,0.00015834944,0.00006923962,0.00002759919,0.000008837463,0.00010526438,2.9610712e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015421755,0.00006477975,0.9443717,0.00004747868,0.000004513426,5.6330424e-7,0.00009807145,0.000026104122,0.04204838,0.0027561823,0.0004870685,0.0099409595],"study_design_scores_gemma":[0.00046625565,0.00021576851,0.988808,0.00002770618,0.000015585212,0.000005051353,0.000009734262,0.00046097158,0.0026930622,0.0056194738,0.0016409388,0.00003748711],"about_ca_topic_score_codex":0.000099918456,"about_ca_topic_score_gemma":0.00008312543,"teacher_disagreement_score":0.044436283,"about_ca_system_score_codex":0.00001698269,"about_ca_system_score_gemma":0.000020562738,"threshold_uncertainty_score":0.16521178},"labels":[],"label_agreement":null},{"id":"W2901968891","doi":"10.3389/fncel.2018.00430","title":"Patterns of Cerebellar Gray Matter Atrophy Across Alzheimer’s Disease Progression","year":2018,"lang":"en","type":"article","venue":"Frontiers in Cellular Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministero della Salute","keywords":"Cerebellum; Voxel-based morphometry; Cerebellar vermis; Neuroscience; Atrophy; Dementia; Grey matter; Voxel; Psychology; Pathology; Cognition; Alzheimer's disease; Medicine; Anatomy; White matter; Disease; Magnetic resonance imaging; Radiology","score_opus":0.04246044604399141,"score_gpt":0.3516118511360751,"score_spread":0.3091514050920837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901968891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74943435,0.00033027033,0.24747775,0.0010423585,0.00063997286,0.00073735975,0.00004260678,0.00010213557,0.00019320997],"genre_scores_gemma":[0.98113483,0.00006239108,0.017655224,0.00083709246,0.000068375295,0.000034588484,0.0000068103454,0.000025756977,0.00017494189],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985689,0.00003089542,0.00025547095,0.00050841295,0.00029616125,0.00034016708],"domain_scores_gemma":[0.99903333,0.000008469336,0.000119433935,0.00061230856,0.000058719375,0.00016775653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108914355,0.00014374939,0.0002019976,0.00009566533,0.00011948376,0.000017169117,0.00028990276,0.000036619596,0.000015206687],"category_scores_gemma":[0.00003360829,0.00012519375,0.00007080784,0.00039591332,0.00042968412,0.00010744181,0.00014416892,0.00016230224,0.0000091161755],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006864203,0.00017842925,0.92115146,0.000038827475,0.0000013999269,0.000058547346,0.00007764706,0.0000054993357,0.07280297,0.0000379947,0.0018418388,0.0037367262],"study_design_scores_gemma":[0.0008907715,0.000488275,0.62393534,0.00031578017,0.000075203534,0.000027667207,0.000058442718,0.006272137,0.32291257,0.0013721706,0.04325084,0.0004008303],"about_ca_topic_score_codex":0.000006243832,"about_ca_topic_score_gemma":3.4364737e-7,"teacher_disagreement_score":0.29721615,"about_ca_system_score_codex":0.000020709644,"about_ca_system_score_gemma":0.000035191108,"threshold_uncertainty_score":0.5105253},"labels":[],"label_agreement":null},{"id":"W2901971624","doi":"10.1002/hbm.24463","title":"Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database","year":2018,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research; National Institute of Nursing Research; Alzheimer Society Research Program; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; Canadian Bee Research Fund; National Institutes of Health; Michael Smith Health Research BC","keywords":"Covariate; Database; Harmonization; Computer science; Goodness of fit; Confounding; Statistics; Data mining; Mathematics; Machine learning","score_opus":0.08452248102561821,"score_gpt":0.3890073806962967,"score_spread":0.3044848996706785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901971624","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6879127,0.00000811013,0.30895576,0.0020973668,0.000014794249,0.00069547776,0.000030714935,0.000023980318,0.0002610966],"genre_scores_gemma":[0.98825806,0.00000487187,0.010759996,0.00063795585,0.00006758621,0.00008169958,0.000047580146,0.000011182233,0.00013106584],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99925935,0.00007713532,0.00020557412,0.0002068993,0.00014940712,0.000101646765],"domain_scores_gemma":[0.99761075,0.0017432296,0.0001772457,0.00035041117,0.000094103205,0.000024276773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037391734,0.000094584466,0.00021571924,0.00019450497,0.000214744,0.00001360509,0.00009358393,0.000027462595,0.000023169057],"category_scores_gemma":[0.00063441583,0.00006243806,0.00006621414,0.00061544473,0.00011564845,0.00003370262,0.000043068034,0.00012691176,3.6417705e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029344714,0.0009246464,0.037930347,0.00083849556,0.0010619805,0.0000134425945,0.0026469768,0.00009571953,0.5933043,0.323061,0.014080272,0.025749382],"study_design_scores_gemma":[0.0020995743,0.0055744913,0.7579185,0.00080342375,0.0011516882,0.0000061847104,0.001593824,0.1729884,0.050163183,0.005487205,0.0017941069,0.00041946193],"about_ca_topic_score_codex":0.000021508322,"about_ca_topic_score_gemma":0.0000069323264,"teacher_disagreement_score":0.7199881,"about_ca_system_score_codex":0.000017214925,"about_ca_system_score_gemma":0.0000133094345,"threshold_uncertainty_score":0.25461504},"labels":[],"label_agreement":null},{"id":"W2902067632","doi":"10.1016/j.mri.2018.11.014","title":"Challenges in diffusion MRI tractography – Lessons learned from international benchmark competitions","year":2018,"lang":"en","type":"review","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; National Science Foundation","keywords":"Tractography; Diffusion MRI; Benchmark (surveying); Computer science; Neuroimaging; Perspective (graphical); Data science; Field (mathematics); Reliability (semiconductor); Medical physics; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology; Cartography; Geography; Mathematics; Physics","score_opus":0.20952158320229128,"score_gpt":0.4216562884691373,"score_spread":0.212134705266846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902067632","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000010169791,0.9770604,0.0004447978,0.008307832,0.00019768458,0.0008512297,0.00018574177,0.00021116647,0.012730986],"genre_scores_gemma":[0.000063356,0.9853741,0.012572135,0.00017742805,0.0003783822,0.00047375177,0.00050603464,0.000089885485,0.00036495327],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974308,0.000094576,0.00069079606,0.0010547611,0.00034058493,0.00038848986],"domain_scores_gemma":[0.99834186,0.00025318173,0.00026636405,0.0009244266,0.00009360381,0.00012056431],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016906601,0.00045155935,0.0010392497,0.00053123117,0.000107639324,0.000057975965,0.00048411053,0.00014213963,0.00033025863],"category_scores_gemma":[0.00008521902,0.0004199708,0.000383636,0.00046941562,0.0002546797,0.0001052146,0.00021135317,0.0007625088,0.000060394785],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007576875,0.00018799693,0.00019857577,0.00044867294,0.0000070482674,0.000059869868,0.000041272106,9.9868295e-8,0.000006351391,0.0006138074,0.0012052042,0.9972235],"study_design_scores_gemma":[0.00039410108,0.000040594554,0.0034795296,0.014141878,0.00017028204,0.00009161956,0.000030720872,0.00022669534,0.0000012334172,0.0019155288,0.97917026,0.00033756933],"about_ca_topic_score_codex":0.000050634615,"about_ca_topic_score_gemma":0.000028312654,"teacher_disagreement_score":0.99688596,"about_ca_system_score_codex":0.0001224529,"about_ca_system_score_gemma":0.00009827946,"threshold_uncertainty_score":0.99982524},"labels":[],"label_agreement":null},{"id":"W2902151647","doi":"10.1016/j.nicl.2018.101627","title":"Linked MRI signatures of the brain's acute and persistent response to concussion in female varsity rugby players","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Fowler Kennedy Sport Medicine Clinic; Robarts Clinical Trials; Western University","funders":"Schulich School of Medicine and Dentistry; Schulich School of Medicine and Dentistry, Western University; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Concussion; Diffusion MRI; White matter; Athletes; Medicine; Resting state fMRI; Physical medicine and rehabilitation; Psychology; Brain Structure and Function; Functional connectivity; Neuroscience; Neuroimaging; Physical therapy; Poison control; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.09107329699219512,"score_gpt":0.42450009547508755,"score_spread":0.3334267984828924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902151647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9662028,0.000018225684,0.0005836437,0.032181967,0.000098398334,0.00063242385,0.000017348719,0.000060817754,0.00020440445],"genre_scores_gemma":[0.98570615,0.000037019654,0.0046836687,0.008894823,0.00008462279,0.000012372255,0.0000017428541,0.000018813862,0.0005607849],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985624,0.00023343881,0.00039893392,0.00044787463,0.00017824332,0.00017912553],"domain_scores_gemma":[0.99825853,0.00076958176,0.00011144086,0.00062220276,0.000087870925,0.00015037281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057513826,0.00012084718,0.00028629132,0.000070416725,0.00008851916,0.0000089746045,0.00019260928,0.00010365649,0.000013478249],"category_scores_gemma":[0.0014458823,0.00008398329,0.00015178704,0.0002599,0.0004893436,0.000039235456,0.00027342432,0.0004963785,0.000006513902],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.012751462,0.0010541765,0.174458,0.000064226304,0.00006351063,0.00021233223,0.0009980794,0.000017447268,0.768976,0.00040341716,0.03205546,0.008945898],"study_design_scores_gemma":[0.0017415456,0.0019045619,0.95845026,0.00013806905,0.000083425926,0.000058281472,0.00005529334,0.0007664989,0.009137357,0.0001349762,0.027390769,0.00013893568],"about_ca_topic_score_codex":0.0000041908474,"about_ca_topic_score_gemma":0.0000030079416,"teacher_disagreement_score":0.7839923,"about_ca_system_score_codex":0.000018636601,"about_ca_system_score_gemma":0.00006270505,"threshold_uncertainty_score":0.3424739},"labels":[],"label_agreement":null},{"id":"W2902209191","doi":"10.1038/sdata.2018.270","title":"In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging","year":2018,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Atlas (anatomy); Segmentation; Computer science; Magnetic resonance imaging; Artificial intelligence; Thalamus; Cluster analysis; Diffusion MRI; Diffusion-Weighted Magnetic Resonance Imaging; Pattern recognition (psychology); Probabilistic logic; Brain atlas; Functional magnetic resonance imaging; Neuroimaging; Neuroscience; Biology; Anatomy; Medicine; Radiology","score_opus":0.05710554135325454,"score_gpt":0.3492608401373721,"score_spread":0.29215529878411756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902209191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9669144,0.000385245,0.0025644545,0.0079955235,0.0008095491,0.002690176,0.0025721288,0.00047813242,0.015590385],"genre_scores_gemma":[0.98590297,0.000004001395,0.010134803,0.0003234769,0.000072930045,0.000027349355,0.00038895005,0.000026793756,0.0031187283],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99843377,0.000025457146,0.00025060243,0.00075632724,0.00030221237,0.00023162144],"domain_scores_gemma":[0.9971032,0.00005514406,0.0000872312,0.0025844646,0.00010658422,0.000063386346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033300673,0.00011695214,0.00016945582,0.00020817839,0.00017579945,0.000035792473,0.0006491856,0.000022952285,0.00037453294],"category_scores_gemma":[0.00014269867,0.00010175967,0.000025212863,0.000663199,0.00076762325,0.000124661,0.00030964357,0.00013116695,0.00004237207],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014834446,0.0016111458,0.019658078,0.00020413606,0.0000023806167,0.00006117199,0.00016447256,0.0000025024249,0.6433306,0.006934433,0.30616766,0.021715118],"study_design_scores_gemma":[0.0028892176,0.00058235624,0.053484477,0.0014316076,0.00008359838,0.000031001535,0.000047324655,0.24269366,0.0626092,0.017353518,0.61825985,0.0005341848],"about_ca_topic_score_codex":0.000023062157,"about_ca_topic_score_gemma":0.000016053044,"teacher_disagreement_score":0.5807214,"about_ca_system_score_codex":0.000036664725,"about_ca_system_score_gemma":0.00006697513,"threshold_uncertainty_score":0.4149639},"labels":[],"label_agreement":null},{"id":"W2903146653","doi":"10.1101/480905","title":"A macaque connectome for large-scale network simulations in TheVirtualBrain","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; McGill University; Montreal Neurological Institute and Hospital; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Horizon 2020 Framework Programme; Canada First Research Excellence Fund; Berlin Institute of Health; Deutsche Forschungsgemeinschaft","keywords":"Connectome; Macaque; Human Connectome Project; Tractography; Computer science; Connectomics; Tracing; Resting state fMRI; Diffusion MRI; Neuroscience; Scale (ratio); Functional connectivity; Cartography; Psychology; Geography; Magnetic resonance imaging","score_opus":0.03937587564426802,"score_gpt":0.31196897709648386,"score_spread":0.2725931014522158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903146653","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68750095,0.00049320876,0.29791263,0.003597017,0.00060852634,0.006642119,0.0016259889,0.0015796976,0.00003987634],"genre_scores_gemma":[0.8837826,0.000081328326,0.11284584,0.0011404573,0.0009023736,0.001062838,0.0000037418567,0.0001655223,0.000015253682],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.997548,0.00005993644,0.00056376774,0.00097439165,0.00020132562,0.0006525814],"domain_scores_gemma":[0.99746156,0.00023140905,0.0002959185,0.0014089127,0.00038989205,0.00021230105],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038635478,0.00043024367,0.00064514624,0.00024165447,0.00017510807,0.000059524788,0.00032565792,0.00040562823,0.00004825077],"category_scores_gemma":[0.0003073673,0.0004601504,0.00017804904,0.00058766943,0.00009872295,0.00007707931,0.00033073485,0.0006944245,0.00002092239],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000921462,0.0032902644,0.17879657,0.0034297593,0.00056901504,0.00016895859,0.00015005276,0.005660498,0.7356582,0.044985726,0.026347624,0.000021801707],"study_design_scores_gemma":[0.009339265,0.0008674353,0.25771317,0.005661233,0.00096175907,2.996283e-7,0.000014888095,0.16646412,0.14805609,0.0021034603,0.4045557,0.0042625763],"about_ca_topic_score_codex":0.000009660289,"about_ca_topic_score_gemma":0.000007091216,"teacher_disagreement_score":0.5876022,"about_ca_system_score_codex":0.00021807215,"about_ca_system_score_gemma":0.00030580646,"threshold_uncertainty_score":0.999785},"labels":[],"label_agreement":null},{"id":"W2903516807","doi":"10.1101/484543","title":"Tractography Reproducibility Challenge with Empirical Data (TraCED): The 2017 ISMRM Diffusion Study Group Challenge","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; China Scholarship Council; National Center for Research Resources; National Natural Science Foundation of China; National Institutes of Health; Vanderbilt University","keywords":"Reproducibility; Tractography; Diffusion MRI; Computer science; Outlier; Imaging phantom; Tracking (education); Ground truth; Diffusion; Artificial intelligence; Magnetic resonance imaging; Pattern recognition (psychology); Data mining; Nuclear medicine; Statistics; Mathematics; Psychology; Medicine; Physics; Radiology","score_opus":0.14012493138709564,"score_gpt":0.3588019647956082,"score_spread":0.21867703340851258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903516807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655643,0.002316778,0.006547647,0.014629012,0.00050048763,0.007898888,0.00048959546,0.0019293393,0.00012391525],"genre_scores_gemma":[0.9860044,0.0016070523,0.00981495,0.0003923247,0.001082229,0.00087992154,0.000004934412,0.00020994213,0.0000042224115],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99294233,0.00026231265,0.0007765733,0.0045437017,0.0008170229,0.0006580665],"domain_scores_gemma":[0.9802046,0.00013111018,0.0006304998,0.018128995,0.00055241334,0.0003523739],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0022882668,0.00082148064,0.0009309144,0.00023643734,0.00057576725,0.0001391212,0.0018713622,0.00041875464,0.000030439374],"category_scores_gemma":[0.00042017014,0.0005779641,0.00018155487,0.0006543523,0.0005825881,0.00022119567,0.0022318375,0.002168823,0.000026421547],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004482552,0.09726812,0.72156394,0.0065734093,0.004452614,0.002791059,0.0013820219,0.000017859169,0.12096361,0.002422287,0.037472293,0.0006102305],"study_design_scores_gemma":[0.002158004,0.0020528669,0.913389,0.0010172212,0.001209722,8.303462e-7,0.00005750456,0.00060863025,0.0031718747,0.000037852744,0.07478115,0.0015152863],"about_ca_topic_score_codex":0.000057882262,"about_ca_topic_score_gemma":0.000020037349,"teacher_disagreement_score":0.1918251,"about_ca_system_score_codex":0.00013789389,"about_ca_system_score_gemma":0.00025761797,"threshold_uncertainty_score":0.99966717},"labels":[],"label_agreement":null},{"id":"W2903623499","doi":"10.1007/s13253-018-00344-0","title":"Modeling and Prediction of Multiple Correlated Functional Outcomes","year":2018,"lang":"en","type":"article","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Cancer Institute; King Abdullah University of Science and Technology","keywords":"Copula (linguistics); Marginal distribution; Diffusion MRI; Skew; Multivariate statistics; Computer science; Mathematics; Algorithm; Statistics; Econometrics; Random variable","score_opus":0.060400101196526314,"score_gpt":0.2668792346862158,"score_spread":0.20647913348968952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2903623499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9555151,0.000077132834,0.044054642,0.00013025703,0.000026504393,0.00005820087,0.0001225933,0.000004762098,0.00001083436],"genre_scores_gemma":[0.97997093,0.0005303387,0.019338708,0.000042726115,0.000045186203,7.436976e-7,0.000045420275,0.0000015784675,0.000024338256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99959844,0.000007678886,0.00020413693,0.00006546964,0.00007299509,0.000051254818],"domain_scores_gemma":[0.9997701,0.000042252024,0.00008815164,0.000022859564,0.000021441992,0.000055201814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031554504,0.0000572317,0.0001285961,0.000012068003,0.000047867925,0.0000027700116,0.0000146885795,0.00003573511,0.000025904297],"category_scores_gemma":[0.000032436714,0.000027942113,0.000021811875,0.000019901621,0.00014622012,0.00003159078,0.000023652043,0.00008833953,6.3628823e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019669629,0.00024639667,0.7441105,0.000011200547,0.000057005152,0.000005647003,0.000057788504,0.00014687619,0.24683213,0.00026145615,0.0005156691,0.007558583],"study_design_scores_gemma":[0.0004159263,0.00067146646,0.9930945,0.0000138930545,0.000036684854,0.00026675043,0.00010568081,0.0041094013,0.000660856,0.0004565193,0.00013370224,0.0000345904],"about_ca_topic_score_codex":0.0000013248072,"about_ca_topic_score_gemma":1.4691675e-7,"teacher_disagreement_score":0.24898398,"about_ca_system_score_codex":0.0000134057445,"about_ca_system_score_gemma":0.0000015911864,"threshold_uncertainty_score":0.11394463},"labels":[],"label_agreement":null},{"id":"W2904087114","doi":"10.1016/j.nicl.2018.101642","title":"Spatial correlations exploitation based on nonlocal voxel-wise GWAS for biomarker detection of AD","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Science and Technology Planning Project of Guangdong Province; Canadian Institutes of Health Research; University of California, San Diego; GE Healthcare; National Institutes of Health; Genentech; National Natural Science Foundation of China; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Takeda Pharmaceutical Company; Eli Lilly and Company; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Johnson and Johnson Pharmaceutical Research and Development; Merck; Alzheimer's Drug Discovery Foundation; Eisai; National Institute on Aging; Fujirebio Europe; Alzheimer's Association","keywords":"Voxel; Computer science; Weighting; Artificial intelligence; Pattern recognition (psychology); Data set; Genome-wide association study; Biology; Medicine; Single-nucleotide polymorphism; Genetics","score_opus":0.1840363593501134,"score_gpt":0.451933414664985,"score_spread":0.2678970553148716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904087114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09208382,0.0000048120874,0.9034005,0.0022226267,0.0003753174,0.0010115408,0.000044886434,0.00022077534,0.000635732],"genre_scores_gemma":[0.9717145,0.0000103667,0.026043052,0.0015776826,0.0002934406,0.00013398526,0.000048024798,0.000043699336,0.000135236],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844193,0.00007759166,0.000628752,0.0004713949,0.00020110498,0.00017920967],"domain_scores_gemma":[0.99780864,0.0009332647,0.0002307007,0.0005624617,0.00034150705,0.00012343771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030183257,0.00014563485,0.00027431466,0.00013433336,0.00012372043,0.000009357883,0.00009371811,0.00011978604,0.00003915778],"category_scores_gemma":[0.0016717257,0.00013858412,0.0002297478,0.00023447737,0.00035743043,0.000070179034,0.000026216509,0.00025301953,0.00003472476],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0064401207,0.0043129986,0.02154513,0.00017707764,0.000054358778,0.000026681695,0.00007314056,0.00009121016,0.25546438,0.0005557376,0.009500915,0.70175827],"study_design_scores_gemma":[0.004705199,0.006872103,0.2789412,0.00013571956,0.00024176849,0.000023110344,0.000013956886,0.6288939,0.041990016,0.0009467028,0.036949813,0.00028648908],"about_ca_topic_score_codex":0.000005702547,"about_ca_topic_score_gemma":0.0000067110996,"teacher_disagreement_score":0.8796307,"about_ca_system_score_codex":0.000023655613,"about_ca_system_score_gemma":0.00007110578,"threshold_uncertainty_score":0.56512964},"labels":[],"label_agreement":null},{"id":"W2904338322","doi":"10.1038/s41386-018-0298-z","title":"Brain structure, cognition, and brain age in schizophrenia, bipolar disorder, and healthy controls","year":2018,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":176,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health; Western University","funders":"","keywords":"Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Bipolar disorder; Cognition; Psychosis; Age of onset; Psychiatry; Brain aging; Clinical psychology; Neuroscience; Audiology; Magnetic resonance imaging; Diffusion MRI; Medicine; Internal medicine","score_opus":0.028203336023498834,"score_gpt":0.37257286489913416,"score_spread":0.3443695288756353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904338322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9662974,0.00096481194,0.0006655737,0.03065514,0.00014573002,0.00088188663,0.000036233905,0.00014614048,0.00020712394],"genre_scores_gemma":[0.95151156,0.00068147125,0.0020945198,0.04527735,0.00022924846,0.00006725963,0.000017355549,0.00003687871,0.000084343024],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881667,0.000112854286,0.00025221787,0.00046435272,0.000077726014,0.00027616194],"domain_scores_gemma":[0.9992892,0.0002335939,0.00007580382,0.00018337887,0.000052473457,0.00016551909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009185965,0.00016480208,0.00026813423,0.0001807425,0.00011946714,0.000013790572,0.000069664464,0.00007609975,0.00006937781],"category_scores_gemma":[0.0001094839,0.00016109848,0.000021002767,0.00025852592,0.00042154602,0.00006116427,0.00005336598,0.0003755258,0.0000059258155],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022998333,0.0002269298,0.012383463,0.00006692841,0.00002045475,0.00015241279,0.00009338465,4.5114461e-7,0.8999878,0.001481168,0.010448802,0.07283838],"study_design_scores_gemma":[0.027069934,0.0029161407,0.34820813,0.000052551513,0.000105259045,0.0010267497,0.000020090145,0.0006192382,0.0036253817,0.013609535,0.60229844,0.00044856122],"about_ca_topic_score_codex":0.000012600591,"about_ca_topic_score_gemma":0.000040698756,"teacher_disagreement_score":0.8963624,"about_ca_system_score_codex":0.000011148672,"about_ca_system_score_gemma":0.000027925167,"threshold_uncertainty_score":0.6569405},"labels":[],"label_agreement":null},{"id":"W2904572182","doi":"10.1101/497669","title":"White matter microstructure in women with acute and remitted anorexia nervosa: an exploratory neuroimaging study","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Psychology; External capsule; Anorexia nervosa; Neuroimaging; Grey matter; Corona radiata (embryology); Psychiatry; Neuroscience; Internal medicine; Medicine; Eating disorders; Magnetic resonance imaging; Radiology","score_opus":0.020924928740851025,"score_gpt":0.2718497284903547,"score_spread":0.2509247997495037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2904572182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9957444,0.0001092738,0.00070350745,0.0006381561,0.00012184443,0.001992053,0.0000896501,0.0005948502,0.0000062357635],"genre_scores_gemma":[0.9776827,0.00008064808,0.019371444,0.0016251737,0.0002372104,0.0007428621,0.0000010063088,0.00025290836,0.000006037299],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99671346,0.00013454581,0.0005264317,0.0016449152,0.00031808089,0.0006625808],"domain_scores_gemma":[0.99685186,0.00002010886,0.00034124719,0.0020349412,0.00035695574,0.00039490734],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031952705,0.0006982999,0.00078858214,0.00043633132,0.00016051382,0.00018533166,0.000393537,0.00025643312,0.000033446468],"category_scores_gemma":[0.00002047152,0.00065377564,0.000041982952,0.00065391645,0.00028812312,0.00028916055,0.0005826972,0.0012712671,0.000012101944],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038290262,0.00039885374,0.76956075,0.00021274076,0.00010990994,0.00058600964,0.0002353614,0.0000053336394,0.22800754,0.0000072261764,0.0004896697,0.0000036661083],"study_design_scores_gemma":[0.0013812475,0.00045373934,0.98980474,0.0003809214,0.00019088412,0.0000012051385,0.000056619396,0.0001287063,0.0062342566,0.000008587694,0.0006319993,0.0007271105],"about_ca_topic_score_codex":0.000014355629,"about_ca_topic_score_gemma":0.0000037447603,"teacher_disagreement_score":0.22177328,"about_ca_system_score_codex":0.00025371823,"about_ca_system_score_gemma":0.000298487,"threshold_uncertainty_score":0.99959135},"labels":[],"label_agreement":null},{"id":"W2905156767","doi":"10.1503/jpn.170221","title":"Psychoradiologic abnormalities of white matter in patients with bipolar disorder: diffusion tensor imaging studies using tract-based spatial statistics","year":2018,"lang":"en","type":"review","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Diffusion MRI; White matter; Bipolar disorder; Fractional anisotropy; Cardiology; Medicine; Magnetic resonance imaging; Audiology; Psychology; Internal medicine; Pathology; Radiology; Lithium (medication)","score_opus":0.061533307337877895,"score_gpt":0.378008227620823,"score_spread":0.3164749202829451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905156767","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054011717,0.921848,0.022434352,0.000306059,0.0005910897,0.00065433345,0.00013603247,0.000013936018,0.0000044656763],"genre_scores_gemma":[0.006743365,0.95186454,0.04080625,0.0003848336,0.00013707297,0.0000070447036,0.0000057261536,0.000038346312,0.0000128171105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99838924,0.000089313995,0.00077644945,0.0002784096,0.00027672807,0.00018985175],"domain_scores_gemma":[0.9982863,0.000075392236,0.0011626036,0.00022026559,0.00018092428,0.000074522286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020470511,0.0002449205,0.0009166705,0.00034093985,0.0001451601,0.000014819841,0.00016902728,0.000047183,0.000003523811],"category_scores_gemma":[0.00005624862,0.00015255061,0.00010345246,0.00032694658,0.00046245588,0.0001299661,0.000048566533,0.00038522572,1.8823636e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078456134,0.00046390013,0.9815471,0.0033130262,0.0000069687185,0.000011097989,0.000030643674,0.000008235442,0.000003868438,0.00001585871,0.0001336579,0.014387178],"study_design_scores_gemma":[0.0029578682,0.004288552,0.8018148,0.035662353,0.0015198474,0.001164061,0.00010079353,0.0006855721,0.0000038077494,0.00054052356,0.15046507,0.00079678826],"about_ca_topic_score_codex":0.0000036962424,"about_ca_topic_score_gemma":0.0000016847757,"teacher_disagreement_score":0.17973234,"about_ca_system_score_codex":0.000027286822,"about_ca_system_score_gemma":0.00017228318,"threshold_uncertainty_score":0.6220833},"labels":[],"label_agreement":null},{"id":"W2905311230","doi":"10.1007/s11682-018-0012-0","title":"Dopamine receptor density and white mater integrity: 18F-fallypride positron emission tomography and diffusion tensor imaging study in healthy and schizophrenia subjects","year":2018,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Neuroscience; Corpus callosum; Internal capsule; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.024148494034705165,"score_gpt":0.32844904230493227,"score_spread":0.3043005482702271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905311230","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918979,0.00047628558,0.00019863954,0.006309981,0.000043562726,0.0008798033,0.00000903803,0.00016478602,0.000019993935],"genre_scores_gemma":[0.9898324,0.0001846086,0.008857555,0.0008639161,0.000074018266,0.00006137912,0.000013131705,0.000035122503,0.000077881436],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856347,0.00006706384,0.00027717592,0.0006517668,0.00014404909,0.000296455],"domain_scores_gemma":[0.9992918,0.000057707868,0.00008283295,0.0002708783,0.00007575032,0.0002210532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002907327,0.00024472518,0.00031540214,0.0002890446,0.00028001127,0.000092741735,0.000051161824,0.00003640164,0.0000049173013],"category_scores_gemma":[0.000054660886,0.00020753348,0.000023098304,0.00020400854,0.00030825232,0.0001465726,0.00020793227,0.00036122804,5.912072e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030529543,0.00026556812,0.86922485,0.000044244145,0.000002493651,0.000046327896,0.00028166184,2.0253745e-9,0.09289248,0.000006481567,0.00019488206,0.036735732],"study_design_scores_gemma":[0.0023357468,0.00035980574,0.9928002,0.00027019097,0.00009256791,0.0005232127,0.00043356704,0.00019350005,0.0023812037,0.00008088082,0.00030636435,0.00022280803],"about_ca_topic_score_codex":0.00018651597,"about_ca_topic_score_gemma":0.000039564708,"teacher_disagreement_score":0.12357532,"about_ca_system_score_codex":0.000026996051,"about_ca_system_score_gemma":0.000018650735,"threshold_uncertainty_score":0.84629697},"labels":[],"label_agreement":null},{"id":"W2907533374","doi":"10.1016/j.neubiorev.2018.12.030","title":"Variation in fourteen brain structure volumes in schizophrenia: A comprehensive meta-analysis of 246 studies","year":2019,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":153,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fogarty International Center; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Planum temporale; Caudate nucleus; Psychology; Brain size; Neuroscience; Brain morphometry; Lateral ventricles; Gray (unit); Magnetic resonance imaging; Medicine; Nuclear medicine; Radiology","score_opus":0.6347428318919834,"score_gpt":0.5433849932673688,"score_spread":0.09135783862461466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907533374","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045700508,0.99516225,0.00013597989,0.00005189599,0.0000886131,0.003855327,0.0002045583,0.000039154558,0.00000523347],"genre_scores_gemma":[0.00044511072,0.99484044,0.0035523395,0.00046012615,0.00001708076,0.0005001129,0.00006302373,0.00003801928,0.000083753825],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99598163,0.00033651444,0.0017731983,0.0011240101,0.00043444507,0.00035022653],"domain_scores_gemma":[0.99721646,0.00003699031,0.0012906166,0.0012293665,0.00014098585,0.00008556375],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045629768,0.000589332,0.007449065,0.0013760274,0.00004585714,0.000024843752,0.000508222,0.00019425736,0.000035191773],"category_scores_gemma":[0.00041984624,0.00040151333,0.001996364,0.0051184916,0.00024377381,0.00016627548,0.00021777548,0.0007430373,0.0000061948754],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000104965675,0.00024646462,0.00023350061,0.0059631597,0.00011742467,0.000032751504,0.00008419486,0.000014882823,0.00092964567,0.00015292232,0.00025748936,0.99195707],"study_design_scores_gemma":[0.00016280897,0.00012069206,0.0018827738,0.0011990465,0.10415789,0.000020272266,0.00000659807,0.00006194753,0.0000014382656,0.000043277658,0.89206195,0.00028133075],"about_ca_topic_score_codex":0.000051431947,"about_ca_topic_score_gemma":0.000052227257,"teacher_disagreement_score":0.99167573,"about_ca_system_score_codex":0.00015640135,"about_ca_system_score_gemma":0.00017856443,"threshold_uncertainty_score":0.99984366},"labels":[],"label_agreement":null},{"id":"W2907839286","doi":"","title":"In Vivo Assessment of Spinal Cord Integrity Using Magnetic Resonance Diffusion Tensor Imaging","year":2008,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Nuclear magnetic resonance; Spinal cord; Medicine; Neuroscience; Physics; Psychology; Radiology","score_opus":0.08826950733957728,"score_gpt":0.3983357910574297,"score_spread":0.31006628371785244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907839286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954456,0.00032493562,0.0010921998,0.00072031503,0.000025326486,0.00037348483,0.000003390306,0.00008791453,0.0019268262],"genre_scores_gemma":[0.93014663,0.00022573747,0.06904672,0.0002830853,0.00005073349,0.00003080579,6.5437666e-7,0.000020495292,0.00019512024],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990233,0.0000033456452,0.0002862336,0.00029104803,0.00019550187,0.00020057679],"domain_scores_gemma":[0.9995112,0.000010257383,0.00010512719,0.0001283006,0.00018494231,0.000060203787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008984829,0.00012854248,0.00024408202,0.00013673678,0.00008054386,0.000006428509,0.00010209005,0.000036900474,0.000026860716],"category_scores_gemma":[0.000062814426,0.000118874865,0.00004810297,0.000339431,0.00017600927,0.00014494888,0.000079262645,0.0003133567,7.8053387e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012490242,0.0002146043,0.67406654,0.00011381272,0.0000010255391,0.00003116108,0.00006397181,2.5298888e-7,0.3176141,0.0016150676,0.0007153482,0.00543921],"study_design_scores_gemma":[0.0010825081,0.0006620906,0.93605024,0.00090345734,0.000035566463,0.000946424,0.00017387257,0.019321622,0.026885387,0.0011625832,0.012520208,0.0002560497],"about_ca_topic_score_codex":0.000055756853,"about_ca_topic_score_gemma":4.785063e-7,"teacher_disagreement_score":0.29072872,"about_ca_system_score_codex":0.0000992406,"about_ca_system_score_gemma":0.000054511376,"threshold_uncertainty_score":0.48475763},"labels":[],"label_agreement":null},{"id":"W2909504075","doi":"10.1017/9781316257951.008","title":"Imaging White Matter Pathology in Epilepsy","year":2019,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Epilepsy; Pathology; Medicine; Neuroscience; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.03311763258857997,"score_gpt":0.25720206037748483,"score_spread":0.22408442778890486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909504075","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00035828387,0.00006511753,0.0021873878,0.000321434,0.00006885819,0.00070923794,0.00011030236,0.0001729358,0.9960064],"genre_scores_gemma":[0.0036930405,0.00008161063,0.0011712861,0.00088911306,0.000056089633,0.000002013518,0.000075744254,0.0000693311,0.99396175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99887025,0.00001625253,0.0001846423,0.0005566759,0.0001208086,0.00025139097],"domain_scores_gemma":[0.9989075,0.000029975114,0.00014713408,0.0007472709,0.000074687334,0.000093404466],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000048654238,0.00027692816,0.00043209238,0.00026601742,0.00004826909,0.000009960307,0.00022334169,0.00018201624,0.000021280874],"category_scores_gemma":[0.0000030462118,0.0003277569,0.00014679966,0.000009923468,0.0001692238,0.000048145765,0.0002658266,0.0006563906,0.00008729626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020544957,0.000043322452,0.009988031,0.00029000317,0.000042660286,0.0037355337,0.00004824807,0.0000033858341,0.00055205537,0.85946584,0.122971356,0.0026541236],"study_design_scores_gemma":[0.00074669626,0.000030281888,0.0036926665,0.0003083896,0.00012453955,0.0002821333,0.000010058991,0.00007769553,0.00012163893,0.000042393913,0.9942318,0.0003316621],"about_ca_topic_score_codex":0.000016360544,"about_ca_topic_score_gemma":3.8895587e-7,"teacher_disagreement_score":0.87126046,"about_ca_system_score_codex":0.00016397794,"about_ca_system_score_gemma":0.000071736446,"threshold_uncertainty_score":0.99991745},"labels":[],"label_agreement":null},{"id":"W2909531344","doi":"10.1101/524785","title":"Global and regional white matter development in early childhood","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Foundation; Children's Hospital Foundation","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Brain development; Early childhood; Developmental psychology; Tractography; Psychology; Pediatrics; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.023823727102381568,"score_gpt":0.2624490381423651,"score_spread":0.23862531103998352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909531344","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99327147,0.00037300773,0.0032881396,0.0015256553,0.00011027789,0.0010623033,0.00005285317,0.00027081897,0.000045457593],"genre_scores_gemma":[0.9455589,0.00010865593,0.052735705,0.0011870794,0.00010129133,0.00022910925,6.0056493e-7,0.000065159475,0.000013516925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99817544,0.00002521216,0.00038285018,0.00083112024,0.00024094207,0.00034445693],"domain_scores_gemma":[0.9986693,0.0000147347555,0.00017850907,0.0008295341,0.00013401812,0.00017389651],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014314665,0.0003543369,0.00042801662,0.00015545616,0.000055762444,0.0000599549,0.00020049128,0.00025532822,0.000019844985],"category_scores_gemma":[0.000019610468,0.0003736333,0.00005910909,0.00028790435,0.00007387712,0.00006880002,0.00039253788,0.00052568066,0.000072285686],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022064141,0.0001821698,0.9941852,0.00020860299,0.000037114303,0.000035466033,0.000016156038,0.000010296865,0.0039984086,0.00041127144,0.00088684657,0.000006381341],"study_design_scores_gemma":[0.00048835087,0.000021846967,0.9880217,0.0005460042,0.000032598426,1.5944825e-7,6.732837e-7,0.000029112161,0.0022860847,0.000010656802,0.008210604,0.00035226502],"about_ca_topic_score_codex":0.000014708511,"about_ca_topic_score_gemma":9.282689e-7,"teacher_disagreement_score":0.049447563,"about_ca_system_score_codex":0.00025681418,"about_ca_system_score_gemma":0.0004337071,"threshold_uncertainty_score":0.99987155},"labels":[],"label_agreement":null},{"id":"W2909661867","doi":"10.1016/j.dadm.2018.10.008","title":"White matter and its relationship with cognition in subjective cognitive decline","year":2018,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Merck; Alzheimer's Drug Discovery Foundation; AbbVie; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"White matter; Corpus callosum; Diffusion MRI; Cognition; Psychology; Neuroimaging; Neuropsychology; Cognitive decline; Neuroscience; Disease; Medicine; Dementia; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.07467865023449355,"score_gpt":0.3896330849859277,"score_spread":0.31495443475143414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909661867","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907079,0.002972082,0.0022385581,0.0018688065,0.00007165156,0.0012936079,0.00003861353,0.00012896644,0.00067984784],"genre_scores_gemma":[0.99206454,0.00025242945,0.005154907,0.00039644164,0.00022242637,0.0017771517,0.00007694358,0.000047273228,0.000007893204],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99858665,0.000058255628,0.00027838783,0.0005106009,0.00028302835,0.0002830549],"domain_scores_gemma":[0.99902064,0.00019921803,0.00012491528,0.00020415589,0.00022763973,0.000223462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012544308,0.00022253476,0.00020536674,0.00017456921,0.00020313784,0.000058284233,0.000063594416,0.000041395495,0.000090325906],"category_scores_gemma":[0.00003278163,0.00021203459,0.00004252661,0.0003074941,0.000100106205,0.00033378604,0.00010357901,0.00021457404,0.000028336372],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013016573,0.0003786613,0.9975544,0.000017950282,0.00034270826,0.000028466287,0.000058049605,0.0000018781056,0.000064628126,0.0001237583,0.000052795058,0.0012465235],"study_design_scores_gemma":[0.0011564195,0.00017648075,0.98939484,0.00052324234,0.0035310911,0.000005412779,0.00010524041,0.00015396326,0.0040595126,0.00056764507,0.000103626684,0.00022255135],"about_ca_topic_score_codex":0.000012787025,"about_ca_topic_score_gemma":0.0000063026205,"teacher_disagreement_score":0.008159601,"about_ca_system_score_codex":0.00003135581,"about_ca_system_score_gemma":0.000064562795,"threshold_uncertainty_score":0.864652},"labels":[],"label_agreement":null},{"id":"W2910571127","doi":"10.3389/fnagi.2018.00436","title":"Relationship Between DTI Metrics and Cognitive Function in Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":151,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University; University of Manitoba; University of Calgary; University of Victoria","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Alberta Innovates; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; University of California, San Diego; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Psychology; Executive dysfunction; Episodic memory; Neuropsychology; Neuroimaging; Cognition; Memory impairment; Neuroscience; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.10609777979272579,"score_gpt":0.3567329223139554,"score_spread":0.25063514252122965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910571127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89774036,0.0007214178,0.09880469,0.0012802602,0.00027667766,0.0007031306,0.000010151812,0.00010767269,0.0003556174],"genre_scores_gemma":[0.9951964,0.000026893804,0.003928356,0.0006761779,0.000016770582,0.00002567342,0.0000063582725,0.000011594112,0.000111757945],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99908334,0.00003130715,0.0001539205,0.00039174606,0.000159323,0.00018037272],"domain_scores_gemma":[0.99951756,0.00013717139,0.00005158195,0.00017295149,0.000019814895,0.000100908655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016250635,0.00008647123,0.00013484503,0.00042168223,0.00005486747,0.000019208217,0.00007298585,0.000024311415,0.0000010287679],"category_scores_gemma":[0.00040494854,0.00008917875,0.000018517772,0.0011116276,0.00011598158,0.00019854037,0.00005012624,0.00025921877,0.0000025022596],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018157552,0.000022670718,0.99605626,0.000010178482,4.9414774e-7,0.000007863457,0.000025551359,0.000012060378,0.000089357534,0.00023042821,0.00010240108,0.0034245746],"study_design_scores_gemma":[0.00036741258,0.0000441695,0.99262995,0.00006542663,0.000044145927,0.0000029024045,0.000033871776,0.0032701734,0.00007330751,0.0027540128,0.00063053024,0.00008412494],"about_ca_topic_score_codex":0.000005371281,"about_ca_topic_score_gemma":3.013568e-7,"teacher_disagreement_score":0.09745604,"about_ca_system_score_codex":0.000026081705,"about_ca_system_score_gemma":0.000035963418,"threshold_uncertainty_score":0.3636604},"labels":[],"label_agreement":null},{"id":"W2910624401","doi":"10.3389/fnins.2018.01055","title":"Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Réseau québécois de recherche sur le vieillissement; Canadian Institutes of Health Research; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Tractography; Diffusion MRI; Arcuate fasciculus; Fractional anisotropy; White matter; Inferior longitudinal fasciculus; Reliability (semiconductor); Computer science; Artificial intelligence; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.02681081110324444,"score_gpt":0.30219033126579137,"score_spread":0.2753795201625469,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910624401","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97018796,0.00005318898,0.028158588,0.00040255382,0.00017701054,0.00058009964,0.000024617058,0.00008978909,0.00032620493],"genre_scores_gemma":[0.93967265,0.000010342185,0.059516825,0.0005690464,0.00001168252,0.000015330133,0.000004259442,0.000021025422,0.00017884736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985964,0.00004007346,0.000301138,0.00049453764,0.0003169798,0.0002508782],"domain_scores_gemma":[0.99902064,0.00007916182,0.00014467933,0.0006124276,0.000066021275,0.000077050965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001853812,0.00014759792,0.00026971265,0.00024694685,0.00005473891,0.00001771688,0.0002152642,0.000055435703,0.000028108863],"category_scores_gemma":[0.0002272382,0.0001308169,0.00009363592,0.00073905993,0.000269164,0.00017360754,0.000044823464,0.00025494557,0.0000031326572],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020707379,0.00017047052,0.7485478,0.000039186176,3.1101942e-7,0.000005353364,0.000033308992,0.0001916044,0.25024128,0.0000010706715,0.00028514562,0.0004637752],"study_design_scores_gemma":[0.0003992938,0.000099759796,0.9665994,0.00012767107,0.000016707725,0.000012793921,0.00003100129,0.013838795,0.017101575,0.00005688728,0.0015793748,0.00013673973],"about_ca_topic_score_codex":0.000039514278,"about_ca_topic_score_gemma":0.0000010956782,"teacher_disagreement_score":0.23313971,"about_ca_system_score_codex":0.00003858445,"about_ca_system_score_gemma":0.000051442395,"threshold_uncertainty_score":0.53345585},"labels":[],"label_agreement":null},{"id":"W2911682836","doi":"10.1093/brain/awz021","title":"A probabilistic map of negative motor areas of the upper limb and face: a brain stimulation study","year":2019,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; National Institutes of Health","keywords":"Physical medicine and rehabilitation; Stimulation; Neuroscience; Upper limb; Psychology; Face (sociological concept); Medicine","score_opus":0.03587705274377593,"score_gpt":0.3381441764944299,"score_spread":0.30226712375065395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911682836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99123985,0.00001421091,0.00075780274,0.005576297,0.00001178886,0.0021881782,0.000015033073,0.000028314027,0.0001685564],"genre_scores_gemma":[0.99682075,5.9166507e-7,0.0014219165,0.00026024444,0.000009795172,0.000050547762,0.0000022252407,0.000010226517,0.0014237071],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994781,0.000038839014,0.0001533956,0.00014966389,0.00011536329,0.00006463765],"domain_scores_gemma":[0.99924916,0.00026978788,0.00009750555,0.00030245254,0.00005776709,0.000023304825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010090494,0.0000650815,0.0001471755,0.00003486351,0.000020429405,0.0000025646966,0.00005772957,0.00001865125,0.000015897134],"category_scores_gemma":[0.000311323,0.00004441462,0.000034762776,0.00010292157,0.00006871589,0.000026487322,0.000052980202,0.000075023614,0.0000022192974],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072261674,0.00225362,0.7298324,0.00074707635,0.00010353804,0.0000030674057,0.006349149,0.0003901278,0.23574884,0.009712433,0.0045421706,0.009594956],"study_design_scores_gemma":[0.0012064716,0.0008218272,0.9847525,0.000120388075,0.00003880139,0.0000057660027,0.0004203307,0.0036679627,0.0029135041,0.0050106295,0.00096889655,0.00007295835],"about_ca_topic_score_codex":0.000014874606,"about_ca_topic_score_gemma":0.0000023320563,"teacher_disagreement_score":0.25492007,"about_ca_system_score_codex":0.000013400901,"about_ca_system_score_gemma":0.00002481393,"threshold_uncertainty_score":0.18111756},"labels":[],"label_agreement":null},{"id":"W2911755615","doi":"10.1016/j.psychres.2019.02.028","title":"Mapping cortical surface features in treatment resistant schizophrenia with in vivo structural MRI","year":2019,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Research Council; National Institute for Health and Care Research; Maudsley Charity; Guy's and St Thomas' Charity; Wellcome Trust; South London and Maudsley NHS Foundation Trust; King's College London; King's University College; Health Research","keywords":"Schizophrenia (object-oriented programming); Cortex (anatomy); Neuroscience; Psychology; Temporal cortex; Temporal lobe; Neuroimaging; Posterior cingulate; Cingulate cortex; Anterior cingulate cortex; Psychosis; Gyrus; Occipital lobe; Cerebral cortex; Precentral gyrus; Medicine; Magnetic resonance imaging; Psychiatry; Cognition; Central nervous system; Epilepsy; Radiology","score_opus":0.06503372729228592,"score_gpt":0.4089443704777311,"score_spread":0.3439106431854452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911755615","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9875258,0.000410627,0.00005406239,0.008426886,0.000040434024,0.0010670287,0.000009144167,0.00006445243,0.0024015608],"genre_scores_gemma":[0.96385306,0.000088644236,0.03459148,0.00006614114,0.00005214253,0.00006133422,0.0000070316905,0.000027206586,0.0012529319],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998422,0.00009269768,0.00020872113,0.00044298818,0.000380526,0.00045305316],"domain_scores_gemma":[0.999177,0.00010455154,0.000027200036,0.0005192039,0.000061294224,0.000110773006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002463077,0.00013580544,0.0002378776,0.00024800564,0.000087354034,0.000023884138,0.00013128601,0.00006231842,0.00009169908],"category_scores_gemma":[0.000019740226,0.000098037955,0.000034671313,0.00082694576,0.00010070353,0.000052664105,0.000048195747,0.0006858262,0.000020822463],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002151299,0.00024062161,0.972696,0.00008970178,0.000014766693,0.00004990914,0.00019018886,0.00008392396,0.017790815,0.0052232854,0.0009738373,0.0004956225],"study_design_scores_gemma":[0.0036894463,0.0011113979,0.9850579,0.00039912778,0.0000065663753,0.00007513582,0.0006213568,0.0011176604,0.0010674064,0.0036206055,0.003040227,0.0001931757],"about_ca_topic_score_codex":0.00027962422,"about_ca_topic_score_gemma":0.0005764883,"teacher_disagreement_score":0.03453742,"about_ca_system_score_codex":0.00020514579,"about_ca_system_score_gemma":0.00022382368,"threshold_uncertainty_score":0.3997872},"labels":[],"label_agreement":null},{"id":"W2911790418","doi":"10.1161/str.50.suppl_1.wp454","title":"Abstract WP454: Multi-modal Neuroimaging Biomarkers of Aneurysmal Subarachnoid Hemorrhage","year":2019,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital","funders":"","keywords":"Medicine; Neuroimaging; Diffusion MRI; Corona radiata (embryology); White matter; Fractional anisotropy; Subarachnoid hemorrhage; Stroke (engine); Magnetic resonance imaging; Neuroscience; Cerebral amyloid angiopathy; Cardiology; Radiology; Pathology; Internal medicine; Psychology; Dementia; Psychiatry; Disease","score_opus":0.039012557082769676,"score_gpt":0.323920451514626,"score_spread":0.2849078944318563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911790418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898427,0.00007531531,0.0029164322,0.00079086266,0.00008758433,0.0005231138,0.00006208464,0.00025615882,0.0054457597],"genre_scores_gemma":[0.9665567,0.000003688015,0.032210477,0.00024782744,0.000036341306,0.000015567786,0.000022487186,0.000037310336,0.0008695675],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989457,0.00000951972,0.00026371423,0.00034040186,0.00018911251,0.00025153664],"domain_scores_gemma":[0.999119,0.000037575726,0.00012765115,0.0005613035,0.000061236264,0.00009323526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008200286,0.00015441114,0.0002362928,0.00012255265,0.000038817772,0.000009301144,0.00014718532,0.00004630741,0.00011034468],"category_scores_gemma":[0.000034372002,0.00014849102,0.00011576402,0.00015792364,0.000090573405,0.0000940142,0.000062608815,0.0002509738,0.000056756136],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008119431,0.00018179198,0.09009297,0.00027692184,0.0000072057173,0.00007055815,0.000020465828,0.000012475671,0.9005654,0.00018434445,0.00007134098,0.008435357],"study_design_scores_gemma":[0.0030743894,0.00033937657,0.65579456,0.000043046195,0.00013620163,0.00046930969,0.00013953255,0.01173435,0.3253719,0.00014358791,0.0023004154,0.00045331722],"about_ca_topic_score_codex":0.00002610169,"about_ca_topic_score_gemma":6.651153e-7,"teacher_disagreement_score":0.57519346,"about_ca_system_score_codex":0.000022770755,"about_ca_system_score_gemma":0.0000363863,"threshold_uncertainty_score":0.6055288},"labels":[],"label_agreement":null},{"id":"W2911926566","doi":"10.1016/j.mri.2019.04.013","title":"Tractography and machine learning: Current state and open challenges","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Artificial intelligence; Robustness (evolution); Tractography; Machine learning; False positive paradox; Prior probability; Bayesian probability; Diffusion MRI","score_opus":0.06153289244575866,"score_gpt":0.34137806627959294,"score_spread":0.2798451738338343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2911926566","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43362468,0.53983647,0.0008808117,0.013093015,0.000074308125,0.0019707128,0.000016077493,0.00025256196,0.010251381],"genre_scores_gemma":[0.9199715,0.06972498,0.008119356,0.00035537127,0.00002613146,0.00008791502,0.0000068415407,0.000041788626,0.0016660775],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991225,0.000022407734,0.00015072539,0.00039914128,0.00010496286,0.00020027728],"domain_scores_gemma":[0.99952143,0.000048345973,0.000054298827,0.00025116972,0.00003236416,0.000092386486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119654316,0.00013537728,0.00020821656,0.00007606151,0.00007000231,0.00006309203,0.00010814023,0.00001084057,0.000038495647],"category_scores_gemma":[0.000020812411,0.00012152663,0.00002260944,0.000103142556,0.00009677648,0.00012918573,0.00019319735,0.00026917667,0.000008970547],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023812203,0.00003482386,0.12583287,0.00005701195,9.3729153e-7,0.0000060145703,0.000096488046,2.9367465e-7,0.0009985465,0.0004004403,0.00006682567,0.87248194],"study_design_scores_gemma":[0.00076360995,0.00013885791,0.40432495,0.00015461646,0.0000144547585,0.00009485706,0.000026612259,0.0023813497,0.00017919489,0.0022244942,0.5895575,0.00013945876],"about_ca_topic_score_codex":0.000019555428,"about_ca_topic_score_gemma":0.0000017336333,"teacher_disagreement_score":0.87234247,"about_ca_system_score_codex":0.0000076089796,"about_ca_system_score_gemma":0.000012616104,"threshold_uncertainty_score":0.49557123},"labels":[],"label_agreement":null},{"id":"W2912265831","doi":"10.3389/fneur.2019.00081","title":"A Neuroimaging Marker Based on Diffusion Tensor Imaging and Cognitive Impairment Due to Cerebral White Matter Lesions","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; Ministry of Science and Technology of the People's Republic of China; Beijing Institute For Brain Disorders; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support; National Natural Science Foundation of China","keywords":"Hyperintensity; Montreal Cognitive Assessment; Diffusion MRI; Cognition; Magnetic resonance imaging; Neuropsychology; Neuroimaging; Medicine; Cardiology; White matter; Internal medicine; Psychology; Audiology; Cognitive impairment; Psychiatry; Radiology","score_opus":0.01172256914487974,"score_gpt":0.2741991326381511,"score_spread":0.26247656349327136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912265831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9292309,0.000027212083,0.0288174,0.03873847,0.00027632999,0.0013683367,0.00001760644,0.00012386744,0.0013998561],"genre_scores_gemma":[0.9412197,0.0000054452803,0.0128046125,0.045456782,0.000034682464,0.00011866596,0.000014075792,0.00005111932,0.000294932],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985489,0.00008661293,0.00021983056,0.00064033404,0.00012920193,0.00037508283],"domain_scores_gemma":[0.99931985,0.00009020052,0.000058877056,0.00035278016,0.000036230475,0.000142081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008680464,0.00020435386,0.0003210096,0.0003988693,0.00006549699,0.000015924728,0.00009041751,0.00004934008,0.00009072229],"category_scores_gemma":[0.00003729638,0.00019148196,0.00005269929,0.0002226722,0.00008409601,0.000057609766,0.00012153964,0.00042268308,0.00004381544],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064577756,0.00013975627,0.9870275,0.00002326333,0.0000030680028,0.00013504075,0.000046756228,0.000074439144,0.0003013,0.000010508211,0.009183876,0.0024086772],"study_design_scores_gemma":[0.0015436856,0.0003860943,0.9492065,0.00007898827,0.00002628748,0.00014591709,0.000034975303,0.0455104,0.000047593476,0.00019301458,0.0026720557,0.00015450678],"about_ca_topic_score_codex":0.000007490366,"about_ca_topic_score_gemma":7.02179e-7,"teacher_disagreement_score":0.04543596,"about_ca_system_score_codex":0.000024985711,"about_ca_system_score_gemma":0.000020959473,"threshold_uncertainty_score":0.78084075},"labels":[],"label_agreement":null},{"id":"W2912348536","doi":"10.1101/541631","title":"Formalin Tissue Fixation Biases Myelin-Sensitive MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; Vanderbilt University; University of British Columbia; Multiple Sclerosis Society; Icahn School of Medicine at Mount Sinai; National Institutes of Health","keywords":"Fixation (population genetics); Myelin; Chemistry; Nuclear magnetic resonance; Nuclear medicine; Medicine; Biochemistry; Internal medicine; Central nervous system; Physics","score_opus":0.046579405526018136,"score_gpt":0.30794883079322455,"score_spread":0.2613694252672064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912348536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7313335,0.0010467422,0.24796528,0.0075564464,0.0013107231,0.0061345804,0.0010403246,0.0034558417,0.00015659917],"genre_scores_gemma":[0.9340024,0.00066883833,0.063162595,0.0011003064,0.00054673175,0.00030554048,0.0000045246666,0.00016159762,0.000047492576],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99764866,0.000056091274,0.0005214022,0.00097052974,0.00035858853,0.00044472428],"domain_scores_gemma":[0.9969237,0.00012006618,0.00045644297,0.0016297841,0.00063888426,0.0002311388],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025338458,0.00049337646,0.00062549196,0.0002774428,0.00012733247,0.00008018721,0.00026027366,0.00041190197,0.000029939294],"category_scores_gemma":[0.00027943007,0.00051757495,0.00015793245,0.0003797586,0.00010630663,0.00013939351,0.00037667245,0.00088481116,0.000223267],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009568651,0.0002991867,0.0038566669,0.0006755747,0.00012100762,0.0001220295,0.000012166883,0.0002794016,0.9878678,0.0024306052,0.0042111096,0.000028800576],"study_design_scores_gemma":[0.00063598336,0.00014766782,0.0398511,0.0011631086,0.0002609965,1.9071106e-7,0.0000027129404,0.0025446704,0.9089512,0.000014686097,0.045682654,0.0007450103],"about_ca_topic_score_codex":0.000034007502,"about_ca_topic_score_gemma":5.9665246e-7,"teacher_disagreement_score":0.2026689,"about_ca_system_score_codex":0.00023396157,"about_ca_system_score_gemma":0.0003913473,"threshold_uncertainty_score":0.9997276},"labels":[],"label_agreement":null},{"id":"W2912379919","doi":"10.1109/bibm.2018.8621466","title":"Artificial Neural Networks Classification of Patients with Parkinsonism based on Gait","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Gait; Computer science; Artificial neural network; Artificial intelligence; Parkinsonism; Pattern recognition (psychology); Physical medicine and rehabilitation; Medicine","score_opus":0.05928719116410922,"score_gpt":0.3236009863481946,"score_spread":0.2643137951840854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912379919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5294263,0.0000015909877,0.4620391,0.0017512811,0.000041163035,0.00061238644,0.0000073067413,0.00021630518,0.0059046065],"genre_scores_gemma":[0.98887515,6.02093e-7,0.009956309,0.0009474328,0.00008318041,0.000027519198,0.00004124799,0.000014400287,0.000054177483],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994371,0.000010090482,0.00014241482,0.00017211863,0.00013484288,0.00010344863],"domain_scores_gemma":[0.9994102,0.000029433832,0.00007571819,0.00030376573,0.00013563517,0.00004526277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003406755,0.0000726189,0.000097055934,0.000045067132,0.000050293824,0.0000044040607,0.000046598852,0.000029736519,0.00005461032],"category_scores_gemma":[0.000013822068,0.000051950483,0.000023812909,0.00015229156,0.00011307949,0.00002479839,0.0000074860372,0.000080649865,0.0000046608106],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004292083,0.0042762416,0.6400777,0.000066836605,0.000037944865,0.000005304731,0.000077041455,0.0019999384,0.008812934,0.032344397,0.011141223,0.29686835],"study_design_scores_gemma":[0.0005232343,0.0013418449,0.54481864,0.00003185409,0.00003249318,6.7623586e-7,0.0000049049727,0.4391157,0.0077240006,0.00032050637,0.0059770383,0.000109097986],"about_ca_topic_score_codex":0.0000029557737,"about_ca_topic_score_gemma":0.0000017398935,"teacher_disagreement_score":0.45944887,"about_ca_system_score_codex":0.000014189925,"about_ca_system_score_gemma":0.000012665339,"threshold_uncertainty_score":0.21184792},"labels":[],"label_agreement":null},{"id":"W2912545990","doi":"10.1016/j.bpj.2018.11.1270","title":"High Resolution Imaging and Histopathological Characterization of Myocardial Infarction","year":2019,"lang":"en","type":"article","venue":"Biophysical Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Centre for Phenogenomics; University of Toronto","funders":"","keywords":"Histopathology; Sirius Red; Infarction; Medicine; Fractional anisotropy; Myocardial infarction; Fibrosis; Diffusion MRI; Pathology; Magnetic resonance imaging; CD31; Ex vivo; Artery; Cardiology; Immunohistochemistry; In vivo; Radiology; Biology","score_opus":0.022545619925701647,"score_gpt":0.28875458375245733,"score_spread":0.2662089638267557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912545990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836381,0.0000058504957,0.014600717,0.00142422,0.0000858922,0.00011945818,0.000003700322,0.000034770845,0.000087301014],"genre_scores_gemma":[0.9962943,0.000073982614,0.003174106,0.0001655742,0.0002323639,0.0000030585397,0.000011779395,0.0000070500296,0.000037756166],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999529,0.000018903453,0.0001489825,0.00011118022,0.00011097554,0.00008098248],"domain_scores_gemma":[0.99967295,0.000010593354,0.00010429326,0.00009364654,0.00006539358,0.000053115557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058032878,0.000056666293,0.00013660535,0.00004810206,0.000042884913,0.000008896645,0.000026989004,0.00002461158,0.000013278558],"category_scores_gemma":[0.000014880466,0.000046154168,0.000047704696,0.0000762265,0.000057510242,0.0000924816,0.000023035931,0.00016642234,0.0000056308554],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053487143,0.000049334914,0.009550034,0.0000071032946,0.0000027230676,0.0000036451584,0.000009077365,0.0000011974475,0.98303145,0.0018392887,0.000025041061,0.0054276185],"study_design_scores_gemma":[0.00058891607,0.00023763039,0.9542175,0.000050653645,0.000041141127,0.0005815073,0.0000075626263,0.0013599681,0.039011568,0.0009475699,0.0028726568,0.00008332954],"about_ca_topic_score_codex":0.0000014853864,"about_ca_topic_score_gemma":5.2225873e-9,"teacher_disagreement_score":0.94466746,"about_ca_system_score_codex":0.000030273686,"about_ca_system_score_gemma":0.000011976837,"threshold_uncertainty_score":0.18821123},"labels":[],"label_agreement":null},{"id":"W2912735102","doi":"10.1002/brb3.1233","title":"Diffusion tensor imaging of neurocognitive profiles in a community cohort living in marginal housing","year":2019,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Neurocognitive; White matter; Diffusion MRI; Psychology; Cohort; Neuropsychology; Cognition; Neuroscience; Medicine; Magnetic resonance imaging; Internal medicine","score_opus":0.036527671610566026,"score_gpt":0.3407798012256903,"score_spread":0.30425212961512427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912735102","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9983256,0.000024979945,0.000097224445,0.00037916293,0.000008962465,0.00083724625,0.0000059402964,0.000038122314,0.00028275617],"genre_scores_gemma":[0.99783033,0.00002102478,0.0016959086,0.00026681303,0.0000066133216,0.00008073613,0.00000715163,0.000014231221,0.00007720819],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994321,0.000060453745,0.00016608092,0.00014459956,0.00007515508,0.000121652905],"domain_scores_gemma":[0.99957085,0.00015335098,0.00005229581,0.00016349913,0.000029772855,0.000030223993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017559652,0.00008000335,0.000177067,0.00013386,0.000035658697,0.000006264123,0.000044600103,0.000023536159,0.0000135322625],"category_scores_gemma":[0.000071418704,0.000074810334,0.000021446887,0.00014832422,0.00006306153,0.00005700279,0.00008404719,0.00029455163,9.485898e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015858255,0.00034349697,0.92360485,0.00005100174,4.749945e-7,0.00001573998,0.00018900925,1.6900712e-7,0.06732183,0.000023357437,0.000008281599,0.008425953],"study_design_scores_gemma":[0.00043999555,0.00006200549,0.9964965,0.0004984153,0.000018536457,0.000040916926,0.00037638037,0.0002500833,0.0016738598,0.00003476406,0.000039470826,0.00006905398],"about_ca_topic_score_codex":0.0002115943,"about_ca_topic_score_gemma":0.00001978352,"teacher_disagreement_score":0.07289169,"about_ca_system_score_codex":0.000019935946,"about_ca_system_score_gemma":0.000015111056,"threshold_uncertainty_score":0.3050677},"labels":[],"label_agreement":null},{"id":"W2912783379","doi":"10.1101/541920","title":"Reducing variability in along-tract analysis with diffusion profile realignment","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; Fonds de recherche du Québec – Nature et technologies; McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Resampling; Fractional anisotropy; Diffusion MRI; Human Connectome Project; White matter; Anisotropy; Artificial intelligence; Computer science; Fiber tract; Pairwise comparison; Thermal diffusivity; Magnetic resonance imaging; Pattern recognition (psychology); Mathematics; Physics; Neuroscience; Biology; Functional connectivity; Medicine; Radiology; Optics","score_opus":0.024060956204398954,"score_gpt":0.28199231162539695,"score_spread":0.257931355420998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912783379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95503885,0.0000816095,0.041105893,0.0005936099,0.00009783142,0.0023574838,0.00014625811,0.00052140764,0.000057053094],"genre_scores_gemma":[0.9458738,0.00014149105,0.053031713,0.00014074187,0.000103608814,0.000596031,0.000003361244,0.00009814007,0.0000111152085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969012,0.00013769009,0.00062777865,0.0014408046,0.00043582323,0.00045666104],"domain_scores_gemma":[0.99643403,0.00011018028,0.00044147187,0.0025220201,0.0002774493,0.00021484704],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00085051433,0.00047847745,0.0009007291,0.00050120393,0.00008079999,0.000059375758,0.00029951017,0.00032517206,0.000046711797],"category_scores_gemma":[0.00016797654,0.0004328897,0.00019145317,0.0013269999,0.000093284456,0.00008754172,0.00034866834,0.0010195317,0.000015560714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013491206,0.0012854052,0.6602508,0.00077990704,0.00033279898,0.00012251477,0.00001499812,0.0010223965,0.33546686,0.00045480582,0.000122276,0.000012348549],"study_design_scores_gemma":[0.0006181918,0.00011149166,0.90673697,0.0008039511,0.0010201674,7.337352e-8,0.0000021951691,0.006363269,0.08291067,0.0000064533415,0.0008228404,0.0006037429],"about_ca_topic_score_codex":0.00026265896,"about_ca_topic_score_gemma":0.000002982833,"teacher_disagreement_score":0.25255617,"about_ca_system_score_codex":0.000584961,"about_ca_system_score_gemma":0.00047680954,"threshold_uncertainty_score":0.9998123},"labels":[],"label_agreement":null},{"id":"W2913104887","doi":"10.1016/j.schres.2019.01.041","title":"Progressive post-onset reorganisation of MRI-derived cortical thickness in adolescents with schizophrenia","year":2019,"lang":"en","type":"letter","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Schulich School of Medicine and Dentistry; Canadian Institutes of Health Research; Western University; Academic Medical Organization of Southwestern Ontario; Chrysalis","keywords":"Default mode network; Thalamus; Basal ganglia; Salience (neuroscience); Neuroscience; Grey matter; Psychology; Voxel; Schizophrenia (object-oriented programming); Functional connectivity; Medicine; Psychiatry; Magnetic resonance imaging; Central nervous system; White matter","score_opus":0.07153619351847491,"score_gpt":0.382296318182013,"score_spread":0.3107601246635381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913104887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5428763,0.00046101183,0.00070158823,0.44758683,0.0001345287,0.0073500876,0.00024315872,0.0003501939,0.00029629003],"genre_scores_gemma":[0.9560583,0.000105141386,0.015258957,0.025569364,0.0008894989,0.0006279873,0.00078440463,0.00028345062,0.0004228786],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99473417,0.0005585457,0.00071786746,0.0011507111,0.0018834714,0.00095521],"domain_scores_gemma":[0.9962364,0.0003083267,0.00031922507,0.0016262309,0.0013626638,0.00014719102],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00071363075,0.0004788243,0.0009123507,0.0010525485,0.00016727066,0.000060847295,0.0006530689,0.0007989741,0.00007683058],"category_scores_gemma":[0.0005331252,0.00039344846,0.00013592362,0.0013111788,0.0009087891,0.00014104815,0.00034672816,0.007775623,0.00012834281],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.09363731,0.0045531807,0.095556356,0.023134906,0.0005640452,0.014230242,0.0012993074,0.000029354951,0.18621998,0.0019755533,0.56521475,0.013585018],"study_design_scores_gemma":[0.06610977,0.016793568,0.6433957,0.07670257,0.001318984,0.007834972,0.0008960228,0.0015375764,0.10147498,0.014546582,0.06259948,0.006789809],"about_ca_topic_score_codex":0.00008399306,"about_ca_topic_score_gemma":0.000017515518,"teacher_disagreement_score":0.54783934,"about_ca_system_score_codex":0.00028980273,"about_ca_system_score_gemma":0.0014326534,"threshold_uncertainty_score":0.99985176},"labels":[],"label_agreement":null},{"id":"W2913496827","doi":"10.1017/s0033291718003951","title":"White matter microstructure of the extended limbic system in male and female youth with conduct disorder","year":2019,"lang":"en","type":"article","venue":"Psychological Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"Consejo Nacional de Ciencia y Tecnología; European Commission","keywords":"Cingulum (brain); Fornix; Uncinate fasciculus; Fractional anisotropy; Limbic system; White matter; Psychology; Tractography; Retrosplenial cortex; Neuroscience; Diffusion MRI; Magnetic resonance imaging; Medicine; Hippocampus; Central nervous system","score_opus":0.0557079454839565,"score_gpt":0.35129266129423364,"score_spread":0.2955847158102771,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913496827","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9891651,0.00020955021,0.00022047883,0.0046694307,0.000052589738,0.0007221192,0.000007940767,0.000037480266,0.004915305],"genre_scores_gemma":[0.99646205,0.000020606993,0.0013222765,0.0014646854,0.000028679427,0.000023038065,0.000005715137,0.000012786378,0.0006601481],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919564,0.000028479324,0.0002097955,0.00029507023,0.00012864331,0.00014235878],"domain_scores_gemma":[0.9993581,0.000030238678,0.00009081622,0.00043760866,0.000032812703,0.00005041477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008144554,0.000120074525,0.0003022214,0.00004310302,0.000021720363,0.0000022158545,0.00010382311,0.00006106756,0.00023105154],"category_scores_gemma":[0.000013881496,0.000054550987,0.000023264276,0.00022929284,0.00028266307,0.000019221197,0.00003729968,0.00025141783,0.0000070586443],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001898431,0.00010983388,0.9855511,0.00016765397,0.000007237864,0.000010567972,0.00034428414,0.0000017958346,0.012025974,0.0004946618,0.00029542542,0.000801598],"study_design_scores_gemma":[0.0017296176,0.0005019833,0.99515784,0.00047201166,0.000034607376,0.00044415,0.0009397383,0.000014095926,0.00018000291,0.00016579119,0.00028879705,0.00007135825],"about_ca_topic_score_codex":0.00000941385,"about_ca_topic_score_gemma":0.0000013256896,"teacher_disagreement_score":0.011845971,"about_ca_system_score_codex":0.000011785194,"about_ca_system_score_gemma":0.0000027023161,"threshold_uncertainty_score":0.25298524},"labels":[],"label_agreement":null},{"id":"W2913682618","doi":"10.1101/537092","title":"Free water in white matter differentiates MCI and AD from control subjects","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Q & T Research","funders":"","keywords":"White matter; Diffusion MRI; Hyperintensity; Fluid-attenuated inversion recovery; Partial volume; Neuroinflammation; Psychology; Cardiology; Neuroscience; Internal medicine; Pathology; Medicine; Nuclear medicine; Magnetic resonance imaging; Disease; Radiology","score_opus":0.018025699262401617,"score_gpt":0.24500930733610846,"score_spread":0.22698360807370685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913682618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896586,0.00064075645,0.0045158425,0.0027380842,0.00022008142,0.0013451243,0.00052465074,0.0003443222,0.000012564524],"genre_scores_gemma":[0.9916843,0.00022299109,0.0062781526,0.001196579,0.00013626865,0.00032593845,0.0000024522278,0.00013257342,0.000020729249],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978996,0.000054880024,0.00041781022,0.00097383227,0.00020784378,0.00044602697],"domain_scores_gemma":[0.9978037,0.000057053938,0.00015502701,0.0016756176,0.00013527994,0.00017330739],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012921548,0.0004529268,0.0006944241,0.00022350627,0.000052474985,0.00009182124,0.00031654452,0.00033180488,0.00012195965],"category_scores_gemma":[0.000038499955,0.00038316508,0.00009622809,0.00011708776,0.00009260016,0.00008419292,0.0005187697,0.00081976876,0.00008249597],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006533314,0.00012780256,0.5592428,0.0002541442,0.000060087797,0.000041310064,0.000011451028,0.0000057271336,0.43954235,0.00003428214,0.0006136978,0.0000010446586],"study_design_scores_gemma":[0.0016419495,0.000032471973,0.86882234,0.0005258877,0.00014865323,3.373511e-8,0.0000010360014,0.00040238988,0.12656052,0.0000493996,0.0013724833,0.0004428187],"about_ca_topic_score_codex":0.000057430138,"about_ca_topic_score_gemma":0.0000030642616,"teacher_disagreement_score":0.31298184,"about_ca_system_score_codex":0.00010252308,"about_ca_system_score_gemma":0.00007264835,"threshold_uncertainty_score":0.999862},"labels":[],"label_agreement":null},{"id":"W2913858605","doi":"10.1155/2019/7092496","title":"White Matter Biomarkers Associated with Motor Change in Individuals with Stroke: A Continuous Theta Burst Stimulation Study","year":2019,"lang":"en","type":"article","venue":"Neural Plasticity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Regina; BC Mental Health & Substance Use Services; University of British Columbia; Memorial University of Newfoundland","funders":"Medical Research Council; National Health and Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Michael Smith Health Research BC","keywords":"CTBS; Fractional anisotropy; White matter; Medicine; Stimulation; Motor cortex; Stroke (engine); Primary motor cortex; Neuroscience; Psychology; Diffusion MRI; Brain stimulation; Physical medicine and rehabilitation; Magnetic resonance imaging; Physics","score_opus":0.04277785402908888,"score_gpt":0.3107162946795218,"score_spread":0.2679384406504329,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913858605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99609333,0.0000034391364,0.00027705953,0.0005734422,0.000019897805,0.0025126056,0.00007595511,0.00015173151,0.00029256273],"genre_scores_gemma":[0.9985238,6.1894474e-7,0.00051136134,0.0003987762,0.00002267097,0.00017489177,0.000036248246,0.000033407432,0.00029822753],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988665,0.00004661067,0.00019151265,0.00035870768,0.00028707512,0.00024961424],"domain_scores_gemma":[0.99936014,0.0001368433,0.0001377283,0.00022306283,0.00007152587,0.00007068352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000080033984,0.00018498533,0.00030534057,0.0001330143,0.000044210872,0.000025951873,0.00008596191,0.00004438964,0.00006466396],"category_scores_gemma":[0.000031662188,0.00013023165,0.000025741281,0.00029096412,0.000049862814,0.00015214107,0.00003866286,0.0002523845,0.000019421761],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026675855,0.0004333722,0.99807763,0.000011131373,0.000041012554,0.000019812067,0.00015816062,0.00010123323,0.0007156501,0.0000028413926,0.00006533217,0.00010706928],"study_design_scores_gemma":[0.0025636402,0.0014857629,0.99072605,0.00010097102,0.00009132119,0.000015094383,0.00006981162,0.0046681305,0.00010325746,0.000006879811,0.000023043001,0.00014605679],"about_ca_topic_score_codex":0.00006562423,"about_ca_topic_score_gemma":0.00004507346,"teacher_disagreement_score":0.0073515954,"about_ca_system_score_codex":0.000058623016,"about_ca_system_score_gemma":0.000016137154,"threshold_uncertainty_score":0.5310693},"labels":[],"label_agreement":null},{"id":"W291418382","doi":"10.1016/j.neuroimage.2015.05.023","title":"In vivo histology of the myelin g-ratio with magnetic resonance imaging","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":316,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Polytechnique Montréal; Université Laval; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Research Council for Economics, Humanities and Social Science","keywords":"Myelin; White matter; Magnetic resonance imaging; Corpus callosum; Axon; Multiple sclerosis; Histology; Human brain; Nuclear magnetic resonance; Chemistry; Pathology; Anatomy; Medicine; Biology; Central nervous system; Neuroscience; Physics; Radiology","score_opus":0.044427088814174766,"score_gpt":0.3155453774144212,"score_spread":0.2711182886002464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W291418382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86772233,0.0039206464,0.01119664,0.066748366,0.00033771442,0.0026100003,0.00004218688,0.00042920592,0.04699291],"genre_scores_gemma":[0.9869191,0.000025001278,0.008264992,0.0027928543,0.000035626388,0.000045775367,8.194111e-7,0.000027669294,0.001888127],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992737,0.000035540474,0.00017912859,0.00022122992,0.00014585638,0.00014455248],"domain_scores_gemma":[0.99927914,0.000032534874,0.00006802181,0.000497589,0.00007381029,0.00004889366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007082261,0.000089728885,0.00015340582,0.000055127835,0.0000238644,0.0000038858993,0.0001378204,0.000017429405,0.00002150444],"category_scores_gemma":[0.00009126038,0.00006234908,0.00002678592,0.00028242072,0.0001973754,0.000063521686,0.00005618691,0.00019362447,0.000004018107],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006378888,0.0006828277,0.41984054,0.00010630639,0.0000033196106,0.000667675,0.00077846466,0.00009577605,0.47173998,0.011634667,0.07287336,0.020939192],"study_design_scores_gemma":[0.004094927,0.0007025293,0.280214,0.0002050347,0.00006724405,0.0013317752,0.00009875841,0.004794995,0.09240469,0.0047776615,0.6109592,0.00034918782],"about_ca_topic_score_codex":0.00003415548,"about_ca_topic_score_gemma":0.000011022664,"teacher_disagreement_score":0.5380858,"about_ca_system_score_codex":0.000032418702,"about_ca_system_score_gemma":0.00007716197,"threshold_uncertainty_score":0.25425214},"labels":[],"label_agreement":null},{"id":"W2914916753","doi":"10.3389/fnins.2019.00011","title":"Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Medical Research Council; Alzheimer Society Research Program; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Engineering and Physical Sciences Research Council; Alzheimer Society; National Institute for Health and Care Research; University College London; National Institute on Aging; Eli Lilly and Company","keywords":"Ex vivo; In vivo; Neuroimaging; Magnetic resonance imaging; Statistical power; Brain size; Biomedical engineering; Pathology; Neuroscience; Medicine; Biology; Mathematics; Radiology; Statistics","score_opus":0.0587991854399033,"score_gpt":0.38115759191798915,"score_spread":0.32235840647808583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914916753","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98875654,0.000019186351,0.009002132,0.00008243199,0.00007191066,0.0019858456,0.000032576536,0.000046237044,0.0000031546565],"genre_scores_gemma":[0.9966698,0.000009189916,0.003077601,0.000036068883,0.0000070448,0.00008199231,0.0000014978777,0.0000094164925,0.00010733553],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906474,0.000043326516,0.0001683739,0.00041193524,0.00016630904,0.00014532256],"domain_scores_gemma":[0.9995822,0.00006134021,0.00008503283,0.00019803768,0.000020307634,0.00005309429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012915551,0.00012035926,0.00016559832,0.000101799196,0.00010032898,0.000028241455,0.000072648036,0.000020837317,4.1813308e-7],"category_scores_gemma":[0.000058529822,0.00007841536,0.000022088016,0.00015721034,0.00018474211,0.000083104045,0.00004191299,0.00007481953,2.445486e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002922331,0.00009996745,0.93171567,0.000020168563,8.244891e-7,0.0000020167115,0.00008404171,0.0060085296,0.06126464,0.000014803459,0.0000072133066,0.0004898644],"study_design_scores_gemma":[0.0005936305,0.0005326657,0.47516066,0.00001733531,0.000005324943,0.0000024778221,0.000007588484,0.5218825,0.0016737529,0.00008382484,0.000002511977,0.000037744085],"about_ca_topic_score_codex":0.000008563749,"about_ca_topic_score_gemma":0.0000014973002,"teacher_disagreement_score":0.51587397,"about_ca_system_score_codex":0.000066865825,"about_ca_system_score_gemma":0.000030018193,"threshold_uncertainty_score":0.31976855},"labels":[],"label_agreement":null},{"id":"W2915476106","doi":"10.1073/pnas.1807983116","title":"Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain","year":2019,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":241,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Royal Ottawa Mental Health Centre; University of Ottawa","funders":"National Institute on Drug Abuse; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Alliance for Research on Schizophrenia and Depression; New York State Psychiatric Institute; Parkinson's Foundation; Parkinson's Disease Foundation; Ministero dell’Istruzione, dell’Università e della Ricerca; Dana Foundation","keywords":"Neuromelanin; Dopamine; Substantia nigra; Neurodegeneration; Neuroscience; Parkinson's disease; Human brain; Striatum; Medicine; Pathology; Dopaminergic; Psychology; Disease","score_opus":0.06439228242440746,"score_gpt":0.35239454207170023,"score_spread":0.28800225964729276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2915476106","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9745495,0.000017566555,0.000011161384,0.015165293,0.0000054717934,0.0006416941,0.000004543944,0.000012705081,0.009592091],"genre_scores_gemma":[0.9980796,0.000006861409,0.00066158926,0.0009882303,0.000028315784,0.0000198398,2.757266e-7,0.0000040601994,0.00021121002],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99869066,0.000008239544,0.00023596786,0.00019241181,0.00078301015,0.00008971469],"domain_scores_gemma":[0.9992099,0.00014521967,0.0003316061,0.000015880296,0.00028306406,0.000014334963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008166546,0.00006885437,0.00014205968,0.00013683154,0.00007283412,0.000005823875,0.0003154578,0.00003928387,0.0000052700525],"category_scores_gemma":[0.00034271795,0.000039778246,0.000053373806,0.00076693395,0.00040320327,0.0001552247,0.000057956997,0.00020921756,0.0000012198385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033240485,0.000084379724,0.017431963,0.000060444414,0.0000058470614,2.0075511e-8,0.00024495745,0.000024085137,0.9026126,0.07897456,0.0003766315,0.00015124204],"study_design_scores_gemma":[0.0005242654,0.000588544,0.37654638,0.00035666107,0.000030027031,0.00008891652,0.00072092435,0.0005346259,0.56525993,0.054418415,0.00083981035,0.00009149924],"about_ca_topic_score_codex":0.0000072953826,"about_ca_topic_score_gemma":5.990215e-8,"teacher_disagreement_score":0.3591144,"about_ca_system_score_codex":0.00001752969,"about_ca_system_score_gemma":0.000029153836,"threshold_uncertainty_score":0.16221099},"labels":[],"label_agreement":null},{"id":"W2916685372","doi":"10.1101/559351","title":"Dimensionality Reduction of Diffusion MRI Measures for Improved Tractometry of the Human Brain","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Diffusion imaging; White matter; Dimensionality reduction; Diffusion; Covariance; Computer science; Tractography; Neuroscience; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Psychology; Medicine; Mathematics; Physics; Statistics; Radiology","score_opus":0.042554195835598475,"score_gpt":0.3120515487837536,"score_spread":0.2694973529481551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916685372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9779174,0.00021680183,0.016420344,0.0019654531,0.00035227326,0.0026303476,0.00032380593,0.00016769841,0.000005883496],"genre_scores_gemma":[0.98408735,0.00005805192,0.015338896,0.00010682891,0.00013948473,0.00018179575,0.0000010309979,0.00007075848,0.000015829792],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998329,0.00005950981,0.0005591524,0.0005683048,0.00028164263,0.00020242867],"domain_scores_gemma":[0.9968566,0.00008578339,0.00076393166,0.0015462262,0.0006700227,0.000077493925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046855683,0.00026613526,0.00054950814,0.00015637562,0.000111310335,0.000011054078,0.0003040975,0.0002742262,0.000005796406],"category_scores_gemma":[0.00029441624,0.00021482924,0.0002868544,0.00033622741,0.00017238302,0.000043950167,0.00027602975,0.0004885007,5.8859126e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046512254,0.0002677918,0.0030344517,0.00061263586,0.00004711481,1.930712e-7,0.0000030082247,0.000012836215,0.9944921,0.0010202283,0.00045742522,0.0000056794906],"study_design_scores_gemma":[0.00053671637,0.00008087406,0.17631836,0.0005250061,0.000159584,2.983085e-8,0.0000015796379,0.0002595287,0.81926507,0.00005442442,0.002609284,0.00018955347],"about_ca_topic_score_codex":0.000027313365,"about_ca_topic_score_gemma":2.2701052e-7,"teacher_disagreement_score":0.17522708,"about_ca_system_score_codex":0.00011283744,"about_ca_system_score_gemma":0.00025121245,"threshold_uncertainty_score":0.8760482},"labels":[],"label_agreement":null},{"id":"W2916731520","doi":"10.3171/2018.9.jns182022","title":"Quantitative assessment of secondary white matter injury in the visual pathway by pituitary adenomas: a multimodal study at 7-Tesla MRI","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Francophone University Association","funders":"National Cancer Institute","keywords":"Optic chiasm; Medicine; White matter; Diffusion MRI; Visual field; Tractography; Fractional anisotropy; Optic tract; Optic radiation; Visual system; Optic nerve; Visual cortex; Ophthalmology; Radiology; Magnetic resonance imaging; Pathology; Nuclear medicine; Neuroscience; Psychology","score_opus":0.03209522537419985,"score_gpt":0.374945952573815,"score_spread":0.3428507271996152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916731520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99625176,0.00007800667,0.0003693377,0.0021121153,0.00013367897,0.000631131,0.00003354089,0.000012402793,0.00037802634],"genre_scores_gemma":[0.99648416,0.00004668244,0.0013365953,0.0017999157,0.000041294268,0.000020219577,0.0000053205713,0.000029089304,0.00023669862],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981577,0.00021979789,0.0007810335,0.0002142288,0.0004394967,0.00018773494],"domain_scores_gemma":[0.99849486,0.00041472158,0.0005944027,0.00031027268,0.000120641875,0.00006508355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061404635,0.00016272596,0.00048073463,0.0002771037,0.000041348943,0.000014257628,0.0001798182,0.000039190272,0.00013741132],"category_scores_gemma":[0.000035826062,0.00011224269,0.00017229813,0.00031571896,0.000060875816,0.0001835979,0.0000805322,0.0006331978,0.00000863301],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004253559,0.0016804927,0.88940156,0.000050074126,0.000030218192,0.00020858066,0.0003943446,0.000025943595,0.088393725,0.000013756873,0.018999869,0.00037608657],"study_design_scores_gemma":[0.0010451555,0.0031956225,0.98935354,0.0001204017,0.00004651625,0.00035059967,0.00066812296,0.0003464743,0.0015033731,0.000050583578,0.0031884331,0.00013117035],"about_ca_topic_score_codex":0.000004293788,"about_ca_topic_score_gemma":5.368471e-7,"teacher_disagreement_score":0.099952,"about_ca_system_score_codex":0.000059782906,"about_ca_system_score_gemma":0.000115140625,"threshold_uncertainty_score":0.4577124},"labels":[],"label_agreement":null},{"id":"W2916984470","doi":"10.1016/j.cortex.2019.02.010","title":"Organization of extrastriate and temporal cortex in chimpanzees compared to humans and macaques","year":2019,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute on Deafness and Other Communication Disorders; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; James S. McDonnell Foundation; National Institutes of Health; Yerkes National Primate Research Center, Emory University; John Templeton Foundation","keywords":"Extrastriate cortex; Neuroscience; Visual cortex; Primate; Cortex (anatomy); Macaque; Temporal cortex; Psychology; White matter; Association (psychology); Posterior parietal cortex; Medicine; Magnetic resonance imaging","score_opus":0.03511358491176709,"score_gpt":0.3282728182939709,"score_spread":0.29315923338220384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916984470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971461,0.0000401398,0.0017681932,0.00029408708,0.0000113565475,0.00043798424,0.000008811847,0.000050646704,0.00024263421],"genre_scores_gemma":[0.9962253,0.000063300686,0.0033432872,0.00015624306,0.000010263138,0.0000063456414,0.000023447736,0.000012913835,0.00015892285],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99954236,0.0000064754886,0.0001506948,0.0001694783,0.00005529659,0.00007568232],"domain_scores_gemma":[0.99970067,0.00001574613,0.000048055615,0.00014402425,0.000040626986,0.000050897033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031694773,0.00006446268,0.00016902304,0.000073760435,0.000015840733,0.0000060929065,0.00003210856,0.000022307699,0.000029041636],"category_scores_gemma":[0.00001823854,0.000060878578,0.000007538704,0.00017735055,0.00003193679,0.000037961272,0.000035648205,0.000057571255,0.000003323123],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016518406,0.00003776195,0.85504305,0.000034871857,0.0000026929026,0.000001665963,0.00015838892,9.923659e-7,0.14267512,0.00052769366,0.00014245448,0.0013588023],"study_design_scores_gemma":[0.00047981422,0.00008938053,0.9940393,0.000071212904,0.000010321379,0.00001210684,0.000061305785,0.00021877201,0.0039882916,0.00030822048,0.00066173,0.00005956194],"about_ca_topic_score_codex":0.000038160495,"about_ca_topic_score_gemma":0.000009797974,"teacher_disagreement_score":0.13899624,"about_ca_system_score_codex":0.000010026047,"about_ca_system_score_gemma":0.000013056823,"threshold_uncertainty_score":0.24825564},"labels":[],"label_agreement":null},{"id":"W2917580875","doi":"10.1192/bjp.2018.299","title":"Evaluation of functional connectivity in subdivisions of the thalamus in schizophrenia","year":2019,"lang":"en","type":"article","venue":"The British Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"University of Electronic Science and Technology of China; National Natural Science Foundation of China","keywords":"Thalamus; Neuroscience; Schizophrenia (object-oriented programming); Functional magnetic resonance imaging; Functional connectivity; Psychology; Psychiatry","score_opus":0.0527393387733216,"score_gpt":0.33633084107450534,"score_spread":0.28359150230118374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917580875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99516064,0.0009563895,0.00030074015,0.0023899816,0.00025521527,0.00032256756,0.000006040724,0.0000033489662,0.00060510123],"genre_scores_gemma":[0.99859565,0.00008928459,0.0011477716,0.00007939494,0.000058494876,0.000004580949,6.4220603e-7,0.0000069674106,0.00001723654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887115,0.00015074636,0.00037521133,0.000075546915,0.00045667376,0.000070682945],"domain_scores_gemma":[0.9991113,0.00008275321,0.00033614834,0.00020059104,0.00025078718,0.000018399149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014580622,0.000047716294,0.00017421498,0.00006576178,0.000040026418,0.0000060742314,0.00013587468,0.000029850264,0.000050446142],"category_scores_gemma":[0.00017461405,0.000034502304,0.00009855929,0.0002971404,0.00006645865,0.00006130044,0.000028413071,0.00036589164,7.7427524e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003883502,0.0010612905,0.9378753,0.0000705633,0.000047238544,0.0000034522727,0.00009308448,0.0023912631,0.011325003,0.0059399563,0.0013756325,0.039428886],"study_design_scores_gemma":[0.001842424,0.00007464825,0.96288735,0.0006634276,0.00006148085,0.00050961826,0.00008077458,0.0006152132,0.00044974586,0.032750778,0.000034021316,0.00003052551],"about_ca_topic_score_codex":0.0000681618,"about_ca_topic_score_gemma":0.00021133211,"teacher_disagreement_score":0.039398357,"about_ca_system_score_codex":0.000038188326,"about_ca_system_score_gemma":0.00029888327,"threshold_uncertainty_score":0.15896374},"labels":[],"label_agreement":null},{"id":"W2917789037","doi":"10.1002/nbm.4073","title":"VERDICT MRI validation in fresh and fixed prostate specimens using patient‐specific moulds for histological and MR alignment","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"Programme Grants for Applied Research; National Health and Medical Research Council; Cancer Research UK; Prostate Cancer UK; Medical Research Council; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; University College London","keywords":"Histology; Ex vivo; Diffusion MRI; Prostatectomy; Verdict; Fixation (population genetics); Prostate; Pathology; Anatomy; Medicine; Biomedical engineering; Chemistry; Materials science; Biology; Magnetic resonance imaging; In vivo; Radiology; Internal medicine","score_opus":0.06177218552594573,"score_gpt":0.34663223746614713,"score_spread":0.2848600519402014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2917789037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99208486,0.0005309037,0.002531767,0.0029664075,0.000053435,0.0015729158,0.000020080332,0.000043331936,0.00019627894],"genre_scores_gemma":[0.97833306,0.0004275688,0.02053968,0.000391392,0.00004335613,0.00008150993,0.00007759018,0.000016632093,0.00008923688],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99903464,0.000016606979,0.00028915028,0.000337758,0.00013487051,0.000186998],"domain_scores_gemma":[0.9995573,0.0000681057,0.00007622358,0.00018973186,0.000028532686,0.00008009081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013714614,0.00011852106,0.00025594115,0.00019757285,0.000028937819,0.000006127118,0.000033706507,0.00006324893,0.000031966163],"category_scores_gemma":[0.00002804587,0.000097072254,0.00001648569,0.0002122005,0.00011330394,0.00004740583,0.000043547072,0.00011677673,0.0000015241104],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007168378,0.0005611538,0.24566683,0.00033331334,0.000019024808,0.000071931194,0.00116278,0.00006200287,0.72377306,0.0018797839,0.005195244,0.020558016],"study_design_scores_gemma":[0.031220283,0.0072635375,0.3304142,0.002282454,0.00020083466,0.0005676962,0.0017231287,0.03198838,0.08248846,0.012149175,0.49838498,0.0013168624],"about_ca_topic_score_codex":0.000018541627,"about_ca_topic_score_gemma":0.0000018605775,"teacher_disagreement_score":0.6412846,"about_ca_system_score_codex":0.00014095921,"about_ca_system_score_gemma":0.00001738562,"threshold_uncertainty_score":0.39584917},"labels":[],"label_agreement":null},{"id":"W2919694754","doi":"10.3389/fnana.2019.00024","title":"The Superoanterior Fasciculus (SAF): A Novel White Matter Pathway in the Human Brain?","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institutes of Health; National Institute of Mental Health; Medical Research Council; University of Bristol; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Human Connectome Project; Tractography; White matter; Cingulum (brain); Human brain; Neuroscience; Uncinate fasciculus; Diffusion MRI; Computer science; Fiber tract; Fasciculus; Arcuate fasciculus; Brain mapping; Fractional anisotropy; Artificial intelligence; Psychology; Magnetic resonance imaging; Medicine; Functional connectivity; Radiology","score_opus":0.01904501160294042,"score_gpt":0.2936389971660267,"score_spread":0.2745939855630863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919694754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94644237,0.00016303577,0.0033776439,0.03989821,0.00033345958,0.001890623,0.0000124093,0.000105527455,0.007776752],"genre_scores_gemma":[0.9853008,0.000026386304,0.0021897387,0.009687755,0.00004861085,0.00021323033,0.000009009067,0.000041466756,0.002483031],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99867696,0.000065827124,0.0003045581,0.0003749979,0.00022671613,0.00035096137],"domain_scores_gemma":[0.9989742,0.00007691792,0.00006639315,0.0008119983,0.000025962161,0.0000445159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025887866,0.00017197433,0.0002304898,0.00013677278,0.00012263533,0.000050569543,0.00045201337,0.00005000141,0.000025299503],"category_scores_gemma":[0.000029507053,0.000105531,0.0000838678,0.00043531274,0.00012428091,0.00009627487,0.000089985566,0.0005209632,0.00003524232],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049085615,0.00023542398,0.90850264,0.000042064592,0.0000102055965,0.00008459097,0.00060131226,0.000008930603,0.0062118135,0.0019510178,0.079742245,0.0025606796],"study_design_scores_gemma":[0.0018281692,0.00012382392,0.6031619,0.000092647424,0.0000124109965,0.00015857608,0.00073502073,0.0011235283,0.00047397494,0.0018298096,0.39020663,0.00025355353],"about_ca_topic_score_codex":0.000018529165,"about_ca_topic_score_gemma":0.0000124348035,"teacher_disagreement_score":0.3104644,"about_ca_system_score_codex":0.000051723404,"about_ca_system_score_gemma":0.000027772878,"threshold_uncertainty_score":0.4303429},"labels":[],"label_agreement":null},{"id":"W2920455229","doi":"10.1038/s41598-019-39199-x","title":"Comparisons between multi-component myelin water fraction, T1w/T2w ratio, and diffusion tensor imaging measures in healthy human brain structures","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre; Canadian Institute for Advanced Research","funders":"National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Nuclear medicine; Region of interest; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Psychology; Physics; Radiology","score_opus":0.0669565510197751,"score_gpt":0.3679131003551871,"score_spread":0.300956549335412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920455229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850166,0.0000898266,0.009074688,0.0042371647,0.00038508233,0.0009562148,0.0000030789033,0.00015701119,0.00008037151],"genre_scores_gemma":[0.99340504,0.0000044900867,0.005453364,0.00028239615,0.000060632523,0.00003321848,0.00015862854,0.000023490798,0.0005787484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99794984,0.000048835493,0.00057617034,0.00076804607,0.00035181796,0.00030531164],"domain_scores_gemma":[0.99880964,0.000037478363,0.00019148513,0.0007023449,0.00011979575,0.00013923708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066957984,0.0001615503,0.00031629883,0.00026291606,0.00035959535,0.000105872314,0.00006872396,0.000046182533,0.000047411046],"category_scores_gemma":[0.00005667982,0.00012130269,0.000051030973,0.00018156825,0.00016735916,0.00013859742,0.000088961344,0.00028385554,0.000009074089],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012683726,0.00007731949,0.6096206,0.00003148104,0.0000037837526,0.000034855042,0.00015138688,0.000020115158,0.3856389,0.00003759937,0.0031700684,0.0012012448],"study_design_scores_gemma":[0.0008296048,0.00005578707,0.8854092,0.00010377587,0.000027238146,0.00023673614,0.00013888905,0.0016452871,0.035327226,0.0043593133,0.07161924,0.00024770107],"about_ca_topic_score_codex":0.0001476302,"about_ca_topic_score_gemma":0.000023681754,"teacher_disagreement_score":0.35031167,"about_ca_system_score_codex":0.00007461562,"about_ca_system_score_gemma":0.00003783219,"threshold_uncertainty_score":0.49465802},"labels":[],"label_agreement":null},{"id":"W2921139541","doi":"10.1038/s41598-019-40070-2","title":"Subtle white matter alterations in schizophrenia identified with a new measure of fiber density","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"McGill University; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Schizophrenia (object-oriented programming); Fasciculus; Neuroscience; Uncinate fasciculus; Superior longitudinal fasciculus; Arcuate fasciculus; Psychology; Medicine; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.029030859436621186,"score_gpt":0.29265932818484636,"score_spread":0.26362846874822515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2921139541","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99333954,0.000018666873,0.0020959377,0.00077245,0.00026292738,0.00060346286,0.0000014256232,0.00005549144,0.0028501218],"genre_scores_gemma":[0.9614724,4.3438473e-7,0.009920721,0.000068837704,0.000018041494,0.000015527774,0.000029788316,0.0000142416,0.028459989],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99877846,0.000010061352,0.00031269746,0.00045724268,0.0002975463,0.00014400968],"domain_scores_gemma":[0.99869764,0.000009626101,0.0001689363,0.0008961079,0.00015045065,0.00007725282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002531136,0.00008862104,0.00018482562,0.00015540839,0.000052761996,0.00004540258,0.000055175402,0.00003108021,0.00047234935],"category_scores_gemma":[0.000021122076,0.00007199458,0.000045347206,0.00048174761,0.00008446042,0.00012416841,0.000034469653,0.00012003542,0.00009778924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012349708,0.00017148467,0.82242244,0.00007111912,0.000013658476,0.00013149652,0.00027241366,0.000110072055,0.14050223,0.00014285221,0.035361536,0.0006772014],"study_design_scores_gemma":[0.0012682554,0.00009354835,0.8112823,0.00059607736,0.0000850269,0.0014645435,0.00005456958,0.0001941876,0.15841554,0.009626558,0.016571073,0.0003483518],"about_ca_topic_score_codex":0.000038934617,"about_ca_topic_score_gemma":0.00004601121,"teacher_disagreement_score":0.031867098,"about_ca_system_score_codex":0.000025184603,"about_ca_system_score_gemma":0.00016318864,"threshold_uncertainty_score":0.5171894},"labels":[],"label_agreement":null},{"id":"W2922001838","doi":"10.1117/12.2512870","title":"Constructing an average geometry and diffusion tensor magnetic resonance field from freshly explanted porcine hearts","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Tech University","funders":"","keywords":"Diffusion MRI; Atlas (anatomy); Tensor (intrinsic definition); Tensor field; Cardiac cycle; Diffusion; Magnetic resonance imaging; Structure tensor; Transformation (genetics); Physics; Computer science; Geometry; Nuclear magnetic resonance; Mathematics; Mathematical analysis; Artificial intelligence; Chemistry; Anatomy; Exact solutions in general relativity","score_opus":0.026086190324028775,"score_gpt":0.29552196630262056,"score_spread":0.2694357759785918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922001838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915272,0.00038113465,0.0028507772,0.0015945325,0.000036361547,0.00036451584,0.000023747063,0.00022309033,0.0029986475],"genre_scores_gemma":[0.9572341,0.00014180987,0.038323134,0.0019405882,0.000058805745,0.000011059335,0.000044155582,0.000017605891,0.0022287278],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992513,0.000011600948,0.0001593189,0.0003235755,0.00010556947,0.00014865512],"domain_scores_gemma":[0.99933636,0.00012414095,0.000037985348,0.00037096473,0.00003345167,0.00009707132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003633684,0.00010681059,0.00018749594,0.00006128172,0.000049479408,0.000014376108,0.000049617105,0.000052212734,0.000651205],"category_scores_gemma":[0.000043869437,0.00008841718,0.000021255113,0.00010757625,0.000034123022,0.000074960815,0.000056394038,0.00017093786,0.00001966446],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013012935,0.000098272656,0.7862424,0.000031033098,0.0000035615744,0.000046669848,0.00006477686,4.6727072e-7,0.12558079,0.0016079474,0.0016229535,0.08457096],"study_design_scores_gemma":[0.005139487,0.0021688498,0.81412166,0.0006851931,0.00008067236,0.0008966728,0.0007429473,0.020541443,0.08493523,0.0043843184,0.06552294,0.0007805601],"about_ca_topic_score_codex":0.00014345779,"about_ca_topic_score_gemma":0.000010033376,"teacher_disagreement_score":0.0837904,"about_ca_system_score_codex":0.000010674549,"about_ca_system_score_gemma":0.000008848945,"threshold_uncertainty_score":0.7130238},"labels":[],"label_agreement":null},{"id":"W2922076169","doi":"10.1007/s00429-019-01856-2","title":"Uncovering the inferior fronto-occipital fascicle and its topological organization in non-human primates: the missing connection for language evolution","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fascicle; Tractography; Fiber tract; Non-human; Human brain; Diffusion MRI; Neuroscience; Psychology; Computer science; Cognitive science; Biology; Philosophy; Anatomy; Medicine","score_opus":0.01409800587079065,"score_gpt":0.3024756631009879,"score_spread":0.28837765723019726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922076169","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730975,0.000116846575,0.02377585,0.0021510718,0.00006163462,0.00068487,0.000006151501,0.000049903665,0.000056189765],"genre_scores_gemma":[0.99894965,0.0000067213514,0.00031113514,0.00048989913,0.00009248293,0.00001596074,0.00003929849,0.0000096910035,0.00008516284],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99959815,0.000014310878,0.00009584239,0.00015752614,0.000050350554,0.00008384572],"domain_scores_gemma":[0.999727,0.00006757554,0.000046210906,0.000099744924,0.000042035666,0.000017437258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007646491,0.00006967931,0.00008163723,0.000027210875,0.00018303025,0.000027402108,0.000024294697,0.00005259801,0.000016067388],"category_scores_gemma":[0.00009367827,0.000041652802,0.000011579565,0.00013160416,0.000027491167,0.000096333475,0.000022227438,0.00010182602,4.6672486e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013747341,0.000025840713,0.06639879,0.00011629772,0.000013197015,8.1671647e-7,0.0010660449,0.00012240343,0.9106956,0.009764111,0.00026672083,0.011392685],"study_design_scores_gemma":[0.0012017689,0.00036477324,0.9708166,0.00005222334,0.00005096059,0.000091892136,0.0012002797,0.0053108134,0.008612178,0.010624495,0.0015405279,0.00013344611],"about_ca_topic_score_codex":0.000022703149,"about_ca_topic_score_gemma":0.00001379553,"teacher_disagreement_score":0.9044179,"about_ca_system_score_codex":0.000036822876,"about_ca_system_score_gemma":0.0000096352815,"threshold_uncertainty_score":0.16985519},"labels":[],"label_agreement":null},{"id":"W2922110169","doi":"10.1002/cjs.11601","title":"A spatial Bayesian semiparametric mixture model for positive definite matrices with applications in diffusion tensor imaging","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Centre for Advancing Health Outcomes","funders":"National Institute of Dental and Craniofacial Research; National Institute on Drug Abuse","keywords":"Diffusion MRI; Bayesian probability; Tensor (intrinsic definition); Semiparametric model; Mathematics; Positive-definite matrix; Semiparametric regression; Diffusion; Statistical physics; Computer science; Econometrics; Statistics; Physics; Medicine; Geometry; Eigenvalues and eigenvectors; Radiology; Nonparametric statistics; Thermodynamics","score_opus":0.02534461656232357,"score_gpt":0.291729914995808,"score_spread":0.26638529843348446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922110169","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038191588,0.0003556467,0.9930164,0.0015007108,0.000013063122,0.000325579,0.0008497744,0.0000073850288,0.00011228327],"genre_scores_gemma":[0.5166471,0.00006753977,0.48268875,0.0003649284,0.000037864873,0.000022491316,0.000080416474,0.000020197529,0.00007072014],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992824,0.000011132746,0.000263429,0.00013933129,0.00010672234,0.00019694182],"domain_scores_gemma":[0.9987112,0.00015847436,0.00017137847,0.0001377809,0.0005149277,0.00030622273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005620798,0.00010028306,0.00020474987,0.00033463212,0.00010284317,0.000029300083,0.00007084609,0.000031223677,0.0000073784486],"category_scores_gemma":[0.00014729092,0.00008741303,0.00003650031,0.00043838227,0.000067333196,0.000048447317,0.0000062558925,0.00022334588,3.582567e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049990654,0.0007546752,0.70037043,0.00074562774,0.00019250937,0.004617324,0.0025690221,0.009357765,0.0037814605,0.10565421,0.018500611,0.15295646],"study_design_scores_gemma":[0.005103201,0.0006175396,0.14443707,0.0011598251,0.0009650591,0.004263164,0.0009822869,0.7418754,0.0014710815,0.08255485,0.01571511,0.0008553916],"about_ca_topic_score_codex":0.00038378607,"about_ca_topic_score_gemma":0.0032955895,"teacher_disagreement_score":0.73251766,"about_ca_system_score_codex":0.00014253228,"about_ca_system_score_gemma":0.0010122826,"threshold_uncertainty_score":0.35645998},"labels":[],"label_agreement":null},{"id":"W2922746028","doi":"10.1111/acer.14024","title":"Myelin Water Fraction Imaging of the Brain in Children with Prenatal Alcohol Exposure","year":2019,"lang":"en","type":"article","venue":"Alcoholism Clinical and Experimental Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of British Columbia; University of Alberta; University of Guelph","funders":"Kids Brain Health Network; Canada Research Chairs; Australian Government; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute","keywords":"Splenium; Corpus callosum; White matter; Internal capsule; Putamen; Caudate nucleus; Myelin; Magnetic resonance imaging; Anatomy; Medicine; Brain size; Pathology; Internal medicine; Central nervous system; Radiology","score_opus":0.11943737111477723,"score_gpt":0.4770539394554527,"score_spread":0.35761656834067546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922746028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99459726,0.0001901414,0.000016694717,0.0035808752,0.000022983015,0.00090919266,0.0000038900366,0.000022568085,0.0006563887],"genre_scores_gemma":[0.99850196,0.000047046415,0.00049825216,0.00044007652,0.00006534389,0.00006866279,0.000011320292,0.000018361203,0.0003489574],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99860066,0.00012100158,0.00030558385,0.00035364184,0.00035561228,0.00026350465],"domain_scores_gemma":[0.99926627,0.00015403939,0.00003793585,0.00039863546,0.00005743044,0.00008567606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006386741,0.0000943662,0.00020748422,0.000074870106,0.00007319001,0.000014986756,0.00014045359,0.00005627421,0.00006246323],"category_scores_gemma":[0.00006169978,0.000050800914,0.00006011611,0.00016480187,0.00042560694,0.0001030591,0.00024660153,0.0006050109,0.000017371156],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024889552,0.00030132924,0.91641814,0.0000115132325,0.000014073793,0.0000027765784,0.00011121253,0.0000017339247,0.078957684,0.00024888758,0.00023436878,0.0034493736],"study_design_scores_gemma":[0.0027505048,0.0004105912,0.5748924,0.00014338002,0.000007796808,0.00007927446,0.00027972917,0.00018381812,0.41972136,0.00044996603,0.0009811397,0.0001000543],"about_ca_topic_score_codex":0.000115373805,"about_ca_topic_score_gemma":0.0000014553952,"teacher_disagreement_score":0.34152576,"about_ca_system_score_codex":0.000021853002,"about_ca_system_score_gemma":0.000030968447,"threshold_uncertainty_score":0.2628505},"labels":[],"label_agreement":null},{"id":"W2922947702","doi":"10.1002/hbm.24574","title":"Proprioception and motor performance after stroke: An examination of diffusion properties in sensory and motor pathways","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Proprioception; Postcentral gyrus; Corticospinal tract; Psychology; Supramarginal gyrus; Sensory system; Physical medicine and rehabilitation; Gyrus; Neuroscience; Diffusion MRI; Pyramidal tracts; Medicine; Somatosensory system; Magnetic resonance imaging","score_opus":0.06381975238675555,"score_gpt":0.2805149586489354,"score_spread":0.21669520626217983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922947702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985802,0.00005325147,0.00025522689,0.00014722384,0.000006444994,0.00075075414,0.000003867801,0.0000555332,0.00014750572],"genre_scores_gemma":[0.99738723,0.000045393965,0.0016681191,0.00009934965,0.00002400397,0.00007290715,0.0000070177557,0.000013800656,0.00068219355],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99941045,0.000026219763,0.00016122781,0.00020882691,0.000096131414,0.00009716973],"domain_scores_gemma":[0.9996919,0.00001259233,0.00006194105,0.0001648632,0.000036689577,0.000032020715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014302901,0.00008392862,0.00013084771,0.00013491925,0.000050061124,0.000010019833,0.000026757863,0.000039776794,0.000010264763],"category_scores_gemma":[0.000015037324,0.0000735493,0.000012112975,0.000047992078,0.00006144673,0.00016371008,0.00003959497,0.00010406197,9.4793916e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002688115,0.000053184358,0.05240106,0.0002972514,0.000001363244,9.918153e-7,0.0009700861,7.7503586e-7,0.9368316,0.0001144268,0.0000016528284,0.009300743],"study_design_scores_gemma":[0.00045073737,0.00028291845,0.9899164,0.000312369,0.000004223974,0.000009724766,0.00027286037,0.0052238903,0.0031761995,0.00009397107,0.00017638975,0.00008033967],"about_ca_topic_score_codex":0.000004390692,"about_ca_topic_score_gemma":0.000002091613,"teacher_disagreement_score":0.9375153,"about_ca_system_score_codex":0.000024145747,"about_ca_system_score_gemma":0.000007323979,"threshold_uncertainty_score":0.29992536},"labels":[],"label_agreement":null},{"id":"W2924890706","doi":"10.1101/590521","title":"Improving spatial normalization of brain diffusion MRI to measure longitudinal changes of tissue microstructure in the cortex and white matter","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Universidad de Buenos Aires","keywords":"Reproducibility; White matter; Spatial normalization; Diffusion MRI; Fractional anisotropy; Normalization (sociology); Magnetic resonance imaging; Computer science; Artificial intelligence; Medicine; Nuclear medicine; Mathematics; Statistics; Radiology","score_opus":0.018899622846885046,"score_gpt":0.26397221897469425,"score_spread":0.2450725961278092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2924890706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94268596,0.00018909962,0.05208462,0.0029209426,0.00010782863,0.0017951552,0.00016007219,0.00005239176,0.000003906248],"genre_scores_gemma":[0.99022084,0.000055009707,0.008933499,0.0005495123,0.00009790429,0.0000884455,0.0000013236745,0.000049292077,0.000004184384],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99867976,0.00005343499,0.0003361605,0.000489434,0.00024751507,0.00019369315],"domain_scores_gemma":[0.99849373,0.000036411755,0.0003548335,0.0007891106,0.00026249955,0.0000634379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025850328,0.0002494226,0.00042139355,0.00021505925,0.000039434264,0.00002519087,0.00021965608,0.00020115622,0.000015967607],"category_scores_gemma":[0.00006971147,0.00020767038,0.000039221664,0.00030200943,0.00007413192,0.000039290004,0.0002768234,0.00037417334,0.0000016766606],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041787265,0.000046380836,0.18823521,0.0006801349,0.000009087633,0.0000047861126,0.000043336906,0.000017636028,0.81070524,0.000037959908,0.00016309983,0.000015346855],"study_design_scores_gemma":[0.00032432156,0.00009503742,0.8357212,0.0005694526,0.00006332883,1.7958654e-7,0.000004240362,0.0003015645,0.16203767,0.0000016999853,0.00070103403,0.00018027503],"about_ca_topic_score_codex":0.00015794551,"about_ca_topic_score_gemma":0.000022505856,"teacher_disagreement_score":0.6486676,"about_ca_system_score_codex":0.000047273927,"about_ca_system_score_gemma":0.00008583436,"threshold_uncertainty_score":0.8468552},"labels":[],"label_agreement":null},{"id":"W2929956211","doi":"10.1186/s13229-019-0261-9","title":"The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in Nrxn2 deletion mice","year":2019,"lang":"en","type":"article","venue":"Molecular Autism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Biotechnology and Biological Sciences Research Council; National Institute of General Medical Sciences; Royal Society; Medical Research Council; Alzheimer's Society; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Orbitofrontal cortex; Neuroscience; Anterior cingulate cortex; Diffusion MRI; Amygdala; Fractional anisotropy; Cortex (anatomy); Posterior cingulate; Psychology; Connectome; Thalamus; Biology; Prefrontal cortex; Medicine; Magnetic resonance imaging; Functional connectivity; Cognition","score_opus":0.013275047935143737,"score_gpt":0.29864701728910575,"score_spread":0.28537196935396203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2929956211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97166806,0.0002464658,0.014053327,0.012967142,0.000018488943,0.00090703677,0.0000051155744,0.000049804345,0.00008454476],"genre_scores_gemma":[0.99345946,0.00008371138,0.0055847047,0.0006691365,0.000004232683,0.000059499216,0.000018508073,0.0000150459755,0.000105684485],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99930054,0.00004379142,0.00017105187,0.00023097925,0.00013130881,0.00012230336],"domain_scores_gemma":[0.99943537,0.000055580036,0.0001134397,0.0003322934,0.00003008339,0.000033255685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001712208,0.0000913832,0.0001496438,0.000051411804,0.00004782042,0.000008290533,0.000076031094,0.00006409656,0.000002072466],"category_scores_gemma":[0.00003865427,0.00006893572,0.000027043141,0.00015582508,0.000065441105,0.000026054562,0.000053605698,0.00017700897,0.0000019097795],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029269517,0.00001542486,0.008292414,0.000041556686,0.000004097365,0.0000025819545,0.00009346268,0.000008496453,0.97173476,0.014112426,0.00003211545,0.0056333733],"study_design_scores_gemma":[0.00090194255,0.00018256344,0.909,0.00011839259,0.0000326427,0.00008563355,0.000040899362,0.0105987275,0.049192846,0.025696665,0.0039822455,0.0001674443],"about_ca_topic_score_codex":0.00006692824,"about_ca_topic_score_gemma":0.000024184723,"teacher_disagreement_score":0.9225419,"about_ca_system_score_codex":0.000027218213,"about_ca_system_score_gemma":0.000010904336,"threshold_uncertainty_score":0.28111172},"labels":[],"label_agreement":null},{"id":"W2936247364","doi":"10.1093/schbul/sbz019.297","title":"T17. ACUTE CONCEPTUAL DISORGANIZATION IN UNTREATED FIRST-EPISODE PSYCHOSIS: A 7T DTI STUDY OF CINGULUM TRAC","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Precuneus; Psychosis; Psychology; Diffusion MRI; Default mode network; Uncinate fasciculus; Medicine; Cardiology; Neuroscience; Audiology; Radiology; Psychiatry; Magnetic resonance imaging; Functional connectivity; Cognition","score_opus":0.023117003794150978,"score_gpt":0.29998956188496223,"score_spread":0.27687255809081124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936247364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936433,0.00008526391,0.00070680253,0.003169269,0.00005942933,0.0016605417,0.000018734143,0.00022188303,0.0004348163],"genre_scores_gemma":[0.9942853,0.00006879565,0.0046565877,0.00021094058,0.00004293795,0.00013437067,0.00004241745,0.000051859723,0.00050680904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99860215,0.000045911685,0.00044519975,0.00045676436,0.00022257495,0.00022740706],"domain_scores_gemma":[0.99902415,0.00005782067,0.00016876314,0.00057258754,0.00010117401,0.00007550951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009465169,0.00020021769,0.00040176348,0.00016278945,0.00005237021,0.000010359344,0.00016806628,0.000081093014,0.00049415353],"category_scores_gemma":[0.00005542473,0.0001879491,0.000055824163,0.00057846494,0.000068831476,0.000035632824,0.000058233596,0.00027363873,0.0001427387],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037896908,0.0058604237,0.9423828,0.00017423963,0.00024978255,0.00007774385,0.0034317223,0.00038569514,0.017865025,0.0024945145,0.01817337,0.005114984],"study_design_scores_gemma":[0.04865296,0.006950881,0.8343529,0.0013025252,0.0008907965,0.00016273084,0.003870033,0.0012816573,0.023798654,0.0019613723,0.07515188,0.001623602],"about_ca_topic_score_codex":0.00026021485,"about_ca_topic_score_gemma":0.00013141621,"teacher_disagreement_score":0.1080299,"about_ca_system_score_codex":0.00004429853,"about_ca_system_score_gemma":0.000016256847,"threshold_uncertainty_score":0.7664342},"labels":[],"label_agreement":null},{"id":"W2936261028","doi":"10.1093/schbul/sbz021.225","title":"O7.1. ABNORMAL DEVELOPMENT, FAULTY MATURATION OR ACCELERATED AGING? “WHITE MATTER AT THE CENTER STAGE OF SCHIZOPHRENIA” REVISITED","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Psychology; Neuroimaging; Human Connectome Project; Schizophrenia (object-oriented programming); Nuclear medicine; Medicine; Statistics; Neuroscience; Magnetic resonance imaging; Mathematics; Psychiatry; Radiology; Functional connectivity","score_opus":0.036109064608451945,"score_gpt":0.30834092205080255,"score_spread":0.2722318574423506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2936261028","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98358744,0.00010670952,0.0010862474,0.009881541,0.00010492138,0.0015718769,0.00011391232,0.00029162999,0.0032557382],"genre_scores_gemma":[0.8755566,0.00007087994,0.05667655,0.0031860329,0.0001551424,0.00014853293,0.00055275095,0.00010814625,0.063545346],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99803257,0.00007176657,0.00062787393,0.00052948296,0.00036186597,0.00037643392],"domain_scores_gemma":[0.9983794,0.00006944244,0.00034612484,0.00089833466,0.00019489748,0.00011178515],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00021818932,0.00031498392,0.00040471117,0.0001347208,0.00021084736,0.000047749316,0.00030600498,0.00010589435,0.009727696],"category_scores_gemma":[0.000036487105,0.00020603233,0.000112238275,0.00040122712,0.00010690706,0.00008654088,0.0002634019,0.0004356857,0.0018220611],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03347882,0.0010622889,0.5036768,0.0017659952,0.00039544547,0.00011371804,0.0008509803,0.000097610086,0.12901713,0.0019770644,0.3110088,0.016555356],"study_design_scores_gemma":[0.0046143006,0.00012901222,0.24433987,0.0004089027,0.000059096645,0.00018635164,0.000045346424,0.00013216633,0.039374124,0.00003493155,0.71023005,0.00044587566],"about_ca_topic_score_codex":0.0000081532735,"about_ca_topic_score_gemma":0.0000063455946,"teacher_disagreement_score":0.3992212,"about_ca_system_score_codex":0.000091304966,"about_ca_system_score_gemma":0.00009628389,"threshold_uncertainty_score":0.99895513},"labels":[],"label_agreement":null},{"id":"W2937654715","doi":"10.1101/614008","title":"The role of diffusion and perivascular spaces in dynamic susceptibility contrast MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"White matter; Diffusion MRI; Contrast (vision); Voxel; Isotropy; Nuclear magnetic resonance; Orientation (vector space); Anisotropy; Physics; Diffusion; Magnetic resonance imaging; Mathematics; Geometry; Medicine; Optics; Radiology","score_opus":0.011591502086148706,"score_gpt":0.25793157756593144,"score_spread":0.24634007547978273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937654715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99270535,0.0030802528,0.0019365607,0.00063603837,0.00007954905,0.0013561152,0.000054398653,0.00014273198,0.000008997622],"genre_scores_gemma":[0.9924952,0.0026131917,0.0046323603,0.000043125336,0.00003399916,0.0001252909,2.845224e-7,0.00005308776,0.0000034678033],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984517,0.00006372201,0.00037564017,0.00062722975,0.0002151972,0.00026652322],"domain_scores_gemma":[0.99802744,0.00009645031,0.00024593726,0.0013447752,0.00018667479,0.0000987092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037753367,0.00026929617,0.00046982535,0.00010308973,0.00008541402,0.00004487993,0.00023268852,0.00020293808,0.0000046558757],"category_scores_gemma":[0.00013255942,0.00021699858,0.000100296675,0.00019787459,0.00024422188,0.000042686683,0.00038260355,0.00058877363,0.0000028201864],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046585876,0.00014224085,0.15682621,0.00027220062,0.000029854382,0.0000053844255,0.000009909073,0.000015270634,0.841775,0.00084291806,0.000009954134,0.000024471336],"study_design_scores_gemma":[0.0007853045,0.000092404385,0.864934,0.00067928317,0.00011466834,5.966692e-8,0.00002126052,0.007871169,0.1181273,0.00007789547,0.006915678,0.00038097813],"about_ca_topic_score_codex":0.000059613587,"about_ca_topic_score_gemma":0.000007937133,"teacher_disagreement_score":0.7236477,"about_ca_system_score_codex":0.00011901184,"about_ca_system_score_gemma":0.00016613796,"threshold_uncertainty_score":0.88489455},"labels":[],"label_agreement":null},{"id":"W2939399262","doi":"10.1101/608349","title":"Reducing false positives in tractography with microstructural and anatomical priors","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"False positive paradox; Tractography; Prior probability; Regularization (linguistics); Synthetic data; Pattern recognition (psychology); Convex optimization; Magnetic resonance imaging; False positives and false negatives","score_opus":0.017685054265505165,"score_gpt":0.271381288056013,"score_spread":0.2536962337905079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2939399262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958531,0.0006997969,0.0011376267,0.00058084243,0.00007910985,0.0012468816,0.00008481767,0.00031142967,0.0000063412313],"genre_scores_gemma":[0.95560485,0.0002862644,0.043595582,0.00022405741,0.00007711941,0.00010989528,6.327592e-7,0.000099782206,0.000001791612],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980763,0.000040971645,0.00035576313,0.0009583009,0.00019030357,0.00037835777],"domain_scores_gemma":[0.99853665,0.00004960898,0.00022324706,0.00084390247,0.0001534899,0.00019309913],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013923571,0.0004146096,0.00057405245,0.00038592555,0.000065975444,0.000080610895,0.00017553131,0.0002732375,0.000004410858],"category_scores_gemma":[0.0000422316,0.00037919183,0.00008469064,0.00043171496,0.00022305585,0.00010792339,0.00020619389,0.0010440731,0.0000026545606],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001372342,0.00010556745,0.14854436,0.00035054403,0.00005521061,0.00009044704,0.000019063627,0.000017761198,0.85023946,0.0003978244,0.000030656356,0.00001188558],"study_design_scores_gemma":[0.00082828104,0.00010372626,0.800893,0.0010549001,0.00010758212,6.016407e-7,0.000005493499,0.00026759846,0.19569822,0.0000073397637,0.0005332075,0.0005000229],"about_ca_topic_score_codex":0.00004301368,"about_ca_topic_score_gemma":9.3821853e-7,"teacher_disagreement_score":0.65454125,"about_ca_system_score_codex":0.00011703632,"about_ca_system_score_gemma":0.00022730723,"threshold_uncertainty_score":0.999866},"labels":[],"label_agreement":null},{"id":"W2942142200","doi":"10.1016/j.neuroimage.2019.04.067","title":"Test-retest reliability of Diffusion Tensor Imaging metrics in neonates","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Turun Yliopistosäätiö; Emil Aaltosen Säätiö; Sigrid Juséliuksen Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Alfred Kordelinin Säätiö","keywords":"Diffusion MRI; Reliability (semiconductor); Fractional anisotropy; White matter; Repeatability; Intraclass correlation; Computer science; Pattern recognition (psychology); Artificial intelligence; Mathematics; Psychology; Statistics; Medicine; Reproducibility; Magnetic resonance imaging; Physics; Radiology","score_opus":0.0285276830363727,"score_gpt":0.3201254471056927,"score_spread":0.29159776406932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942142200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9922416,0.00007349636,0.00068909035,0.0020773124,0.000045556193,0.00068432477,0.000017308203,0.00017939275,0.003991895],"genre_scores_gemma":[0.98756576,0.00008101883,0.011309604,0.00057353615,0.000017029972,0.000018961398,0.0000087338285,0.000031981403,0.0003933782],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988375,0.000023250741,0.00032709292,0.00039916707,0.00020461009,0.00020842633],"domain_scores_gemma":[0.9985974,0.00043513125,0.00011030444,0.0006761129,0.000116986994,0.00006406065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014239863,0.00013486453,0.0002781493,0.00022373014,0.000023168468,0.000007991654,0.00013707523,0.00003294699,0.00005212014],"category_scores_gemma":[0.00094028754,0.000119920864,0.0000756137,0.0006895587,0.000082369406,0.000105831736,0.000106410414,0.00029611468,0.000028598271],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019120082,0.00021609981,0.8009005,0.000067260364,4.813926e-7,0.000018510898,0.0000146735165,0.0000065336326,0.19501302,0.000091573784,0.00018351796,0.00346868],"study_design_scores_gemma":[0.0008896693,0.00016886074,0.960321,0.00008458505,0.000018714618,0.000045551435,0.000018381914,0.007584239,0.022771914,0.0010973219,0.0068631843,0.00013658518],"about_ca_topic_score_codex":0.00003623292,"about_ca_topic_score_gemma":5.5777076e-7,"teacher_disagreement_score":0.1722411,"about_ca_system_score_codex":0.00003734207,"about_ca_system_score_gemma":0.000027056922,"threshold_uncertainty_score":0.4890231},"labels":[],"label_agreement":null},{"id":"W2942578351","doi":"10.1002/nbm.4092","title":"The role of iron and myelin in orientation dependent R<sub>2</sub><sup>*</sup> of white matter","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Myelin; White matter; Multiple sclerosis; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Pathology; Internal medicine; Biology; Medicine; Immunology; Central nervous system; Physics","score_opus":0.011263521046215098,"score_gpt":0.2897892733660687,"score_spread":0.2785257523198536,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942578351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99609166,0.00033044574,0.00023037533,0.002295493,0.00001668228,0.00050768495,0.000006733305,0.000013927648,0.0005069882],"genre_scores_gemma":[0.99854237,0.0003407114,0.00071685633,0.00024169579,0.000026384132,0.000031061696,0.000019571578,0.000012788554,0.00006855912],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991189,0.000020946643,0.00035811015,0.00018565691,0.00018486285,0.00013150518],"domain_scores_gemma":[0.9994464,0.000074837444,0.000110571535,0.00028203183,0.00004389659,0.000042277512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022182056,0.00008509979,0.00020710663,0.00017688176,0.000019425157,0.0000017792565,0.00006973303,0.00004555335,0.00002203716],"category_scores_gemma":[0.000029402678,0.0000599884,0.000018542642,0.00031166372,0.00012715213,0.00003786751,0.00005450441,0.00013503074,0.000006301763],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110590416,0.00009663589,0.60024583,0.00010164649,0.0000038855783,0.0000025609431,0.0006801795,0.00003429041,0.3837097,0.00025867106,0.00012807363,0.014627896],"study_design_scores_gemma":[0.0038655247,0.00059203396,0.7446804,0.0006474192,0.00004695886,0.00005111544,0.0020298292,0.004258969,0.23579094,0.0035103748,0.004353801,0.00017261821],"about_ca_topic_score_codex":0.000038210383,"about_ca_topic_score_gemma":0.000007998894,"teacher_disagreement_score":0.14791876,"about_ca_system_score_codex":0.000033326443,"about_ca_system_score_gemma":0.000021281568,"threshold_uncertainty_score":0.2446256},"labels":[],"label_agreement":null},{"id":"W2942629314","doi":"10.1101/624445","title":"Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; Université de Sherbrooke; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Working memory; Concussion; Tractography; Neuroscience; Neuropathology; Prefrontal cortex; Fractional anisotropy; Diffusion MRI; Psychology; Dorsolateral prefrontal cortex; Anterior cingulate cortex; Medicine; Poison control; Pathology; Cognition; Magnetic resonance imaging; Radiology; Injury prevention","score_opus":0.016228301816442928,"score_gpt":0.24782085475783042,"score_spread":0.23159255294138748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942629314","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99255824,0.0021784622,0.0013208099,0.00037749784,0.00034674755,0.0023552545,0.00028485793,0.00056201185,0.0000161303],"genre_scores_gemma":[0.9922234,0.00037191302,0.0064000506,0.00022232183,0.0002773707,0.00031745472,0.00001857501,0.0001550833,0.000013846551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9965905,0.00016491354,0.00086203247,0.0012338508,0.00045784394,0.0006908836],"domain_scores_gemma":[0.99782306,0.000069621005,0.00048497686,0.0013098958,0.0001344756,0.00017797246],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004464373,0.00062457623,0.00085830444,0.0005022345,0.00012167059,0.000098988385,0.00045553208,0.0003878884,0.000021239597],"category_scores_gemma":[0.00011600666,0.000652299,0.00014761707,0.00046580235,0.00019991341,0.00023287306,0.00048463533,0.0015309157,0.0000052235478],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001367107,0.00012675955,0.7151363,0.00027602713,0.000033063738,0.000080557336,0.00003745751,0.00019663676,0.2835286,0.000147339,0.00028154062,0.000019011539],"study_design_scores_gemma":[0.0018533346,0.000043430613,0.95567036,0.00212616,0.00008029514,4.830103e-7,0.000011044164,0.0038440889,0.035585325,0.00001803944,0.00013317147,0.0006342692],"about_ca_topic_score_codex":0.00071934145,"about_ca_topic_score_gemma":0.00001217995,"teacher_disagreement_score":0.24794328,"about_ca_system_score_codex":0.0006280161,"about_ca_system_score_gemma":0.00026443703,"threshold_uncertainty_score":0.99959284},"labels":[],"label_agreement":null},{"id":"W2942766429","doi":"10.3390/e21050475","title":"Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Entropy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; F. Hoffmann-La Roche; University of Southern California; Pfizer; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Foundation for the National Institutes of Health","keywords":"Connectome; Connectomics; Neuroscience; Diffusion MRI; Tractography; Human Connectome Project; Neuroimaging; Receiver operating characteristic; Cortex (anatomy); Functional connectivity; Computer science; Psychology; Medicine; Magnetic resonance imaging; Machine learning","score_opus":0.042057004459428775,"score_gpt":0.3420695597698176,"score_spread":0.30001255531038884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942766429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938219,0.0000693221,0.0046104137,0.00091376045,0.00003071973,0.00043510887,0.000007450014,0.00004920178,0.00006209261],"genre_scores_gemma":[0.99813217,0.000039061855,0.0015061675,0.00016958229,0.000023765873,0.000015439251,0.00009163482,0.000009085233,0.000013120153],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994876,0.000026043774,0.00018044957,0.00012559559,0.00007555019,0.00010479365],"domain_scores_gemma":[0.99940044,0.00002933558,0.000051568528,0.0004291468,0.00002632479,0.00006315904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003876647,0.000059382935,0.00014143577,0.00002480251,0.000013510644,0.0000028756197,0.00007210551,0.000023112658,0.00008562097],"category_scores_gemma":[0.00001970582,0.00005241441,0.000037862737,0.00010225843,0.000053067713,0.000044658154,0.000045082586,0.00013592577,0.0000047064054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018652648,0.00009628522,0.954066,0.000014723421,0.000006410228,0.0000026399387,0.000017617265,0.000048312762,0.032587707,0.011150485,0.000010823251,0.0018124718],"study_design_scores_gemma":[0.00036251114,0.00004026143,0.9676409,0.000026431875,0.000026159203,0.0000018132598,0.000002632131,0.02944329,0.0013373446,0.000701935,0.0003675874,0.000049128677],"about_ca_topic_score_codex":0.0000062306276,"about_ca_topic_score_gemma":3.6184085e-7,"teacher_disagreement_score":0.03125036,"about_ca_system_score_codex":0.000018274426,"about_ca_system_score_gemma":0.000015961292,"threshold_uncertainty_score":0.21373975},"labels":[],"label_agreement":null},{"id":"W2942862165","doi":"10.1371/journal.pone.0215974","title":"Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) in rats at 9.4 Tesla","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Reproducibility; Neurite; Biomedical engineering; Voxel; Nuclear medicine; Region of interest; Orientation (vector space); Coefficient of variation; Nuclear magnetic resonance; Materials science; Chemistry; Medicine; Physics; Chromatography; Mathematics; Radiology","score_opus":0.06374813235442438,"score_gpt":0.31174422065228036,"score_spread":0.24799608829785597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942862165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997595,0.00006518676,0.00009605274,0.0013497596,0.0000069764897,0.0005188685,0.0000032564299,0.000050192528,0.000314678],"genre_scores_gemma":[0.9934137,0.00007133164,0.0059562405,0.00015057056,0.000012416669,0.000010450866,0.000014032579,0.000008813635,0.0003624295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991426,0.000016690028,0.00015075719,0.00049127295,0.00011810843,0.000080603415],"domain_scores_gemma":[0.99911183,0.00003484002,0.000059285794,0.0007020345,0.000059859463,0.000032145737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019696004,0.000056065095,0.00015959586,0.000046646397,0.000022060973,0.00000255784,0.000027426404,0.000015256263,0.000017650347],"category_scores_gemma":[0.00016995035,0.000054124343,0.000016339121,0.00012432369,0.00004270008,0.00006696523,0.000069743095,0.00008783716,0.0000054483285],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038660477,0.00023167155,0.5437921,0.0000738264,0.000002068637,0.0000013484873,0.00004938099,3.2958667e-7,0.45513368,0.000039892544,0.00001966384,0.0006173375],"study_design_scores_gemma":[0.00032870925,0.000045259516,0.5632057,0.00014502041,0.000029388484,0.000005625407,0.000013182658,0.0011277578,0.43463242,0.00037542317,0.0000430787,0.000048405134],"about_ca_topic_score_codex":0.000023566483,"about_ca_topic_score_gemma":0.0000018835342,"teacher_disagreement_score":0.02050126,"about_ca_system_score_codex":0.00003986364,"about_ca_system_score_gemma":0.000008225775,"threshold_uncertainty_score":0.22071266},"labels":[],"label_agreement":null},{"id":"W2942962900","doi":"10.1038/s41537-019-0076-x","title":"Impaired illness awareness in schizophrenia and posterior corpus callosal white matter tract integrity","year":2019,"lang":"en","type":"article","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Krembil Foundation; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institutes of Health; Ontario Ministry of Health and Long-Term Care; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; Weston Brain Institute; Consejo Nacional de Ciencia y Tecnología; Government of Canada; Vancouver Coastal Health Research Institute; Centre for Addiction and Mental Health; National Institute of Mental Health; Pfizer; Fondation Brain Canada; National Alliance for Research on Schizophrenia and Depression; Eli Lilly and Company; Ontario Ministry of Research and Innovation; Patient-Centered Outcomes Research Institute","keywords":"Splenium; Corpus callosum; White matter; Psychology; Diffusion MRI; Fractional anisotropy; Disconnection; Schizophrenia (object-oriented programming); Cingulum (brain); Neuroscience; Audiology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.029134793893927573,"score_gpt":0.31299480591915074,"score_spread":0.28386001202522315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942962900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9951068,0.00011030353,0.000329867,0.0019089981,0.00011426612,0.0008344505,0.00003053078,0.00026798376,0.0012967922],"genre_scores_gemma":[0.9865139,0.000024293508,0.011080147,0.0004903772,0.00006848804,0.0000833424,0.000029776143,0.00008653748,0.001623136],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985687,0.000041986576,0.00032960175,0.0005576187,0.00017474391,0.00032734944],"domain_scores_gemma":[0.9990514,0.00004139802,0.000102298116,0.0005846673,0.00004890739,0.00017132847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011997323,0.0002682035,0.00043287716,0.00021372721,0.00006363616,0.000039957937,0.00015513091,0.00013472563,0.00041221452],"category_scores_gemma":[0.00002400319,0.00023784408,0.00007376994,0.0003015728,0.00010467479,0.00015390247,0.00012036223,0.0005426915,0.0002755241],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013435237,0.00022336758,0.9618403,0.00012136526,0.000012462087,0.000070994945,0.00011047008,0.0000020645232,0.02081763,0.00067334267,0.00044240206,0.014342134],"study_design_scores_gemma":[0.0033869469,0.00014164652,0.9901562,0.00023923375,0.000031684067,0.00049505394,0.000037499376,0.0003597224,0.0020591086,0.001099576,0.0016472616,0.0003461098],"about_ca_topic_score_codex":0.00009461343,"about_ca_topic_score_gemma":0.000041421405,"teacher_disagreement_score":0.028315915,"about_ca_system_score_codex":0.000052580715,"about_ca_system_score_gemma":0.00009346821,"threshold_uncertainty_score":0.9699},"labels":[],"label_agreement":null},{"id":"W2943048304","doi":"10.1109/ichi.2019.8904574","title":"CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke Lesion Segmentation","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Computer science; Artificial intelligence; Discriminator; Stroke (engine); Ground truth; Convolutional neural network; Magnetic resonance imaging; Pattern recognition (psychology); Medicine; Radiology; Physics","score_opus":0.08452751323886673,"score_gpt":0.3879938338791196,"score_spread":0.3034663206402529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943048304","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0103799,0.00002900646,0.9802456,0.002395047,0.00030117072,0.0035462705,0.0004328718,0.00023151455,0.0024386027],"genre_scores_gemma":[0.45086634,0.0001402503,0.5186784,0.004296257,0.001422018,0.0021482706,0.009803853,0.00008278854,0.01256178],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987811,0.000013987537,0.0002786079,0.0005545541,0.00018144178,0.00019032556],"domain_scores_gemma":[0.9990961,0.00008865067,0.00015232521,0.0003871628,0.00017367284,0.00010207439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007768576,0.00022456163,0.00030083247,0.00009210859,0.00008250403,0.0000237428,0.00011252543,0.00011351138,0.00009649609],"category_scores_gemma":[0.000028355278,0.00021161287,0.00015739883,0.00005586618,0.00003228152,0.000045405155,0.00020340162,0.00037696227,0.000023739116],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007251008,0.00037344018,0.0010104722,0.00034139268,0.00023910002,0.000009116561,0.000102446975,0.113838285,0.21417701,0.012680791,0.6460238,0.01047904],"study_design_scores_gemma":[0.00609956,0.00078038767,0.0013263951,0.0005332191,0.0007278226,0.000080399695,0.00015928871,0.39482728,0.37850752,0.006342772,0.20928061,0.0013347722],"about_ca_topic_score_codex":0.000009957056,"about_ca_topic_score_gemma":0.0000013550991,"teacher_disagreement_score":0.46156716,"about_ca_system_score_codex":0.00015092666,"about_ca_system_score_gemma":0.00012722115,"threshold_uncertainty_score":0.86293226},"labels":[],"label_agreement":null},{"id":"W2943572673","doi":"10.1101/623892","title":"Tractostorm: Rater reproducibility assessment in tractography dissection of the pyramidal tract","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Voxel; Diffusion MRI; Segmentation; Computer science; Bundle; Artificial intelligence; Dissection (medical); Magnetic resonance imaging; Radiology; Medicine","score_opus":0.03789750424890323,"score_gpt":0.3128440670341284,"score_spread":0.2749465627852252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2943572673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99230665,0.00016242889,0.0032680472,0.0010926566,0.0005135793,0.0022679912,0.000103141785,0.0002497241,0.00003576703],"genre_scores_gemma":[0.9936607,0.00012340683,0.0055580735,0.0001403305,0.00013394454,0.00029066426,6.2781737e-7,0.000086600616,0.0000056810627],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.996889,0.00012701526,0.0007481372,0.0015171198,0.0003898033,0.00032890998],"domain_scores_gemma":[0.9949089,0.0000656105,0.0005757108,0.0040601646,0.00028515293,0.00010440837],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009926616,0.00039367122,0.00063996436,0.0002524849,0.000068179594,0.000038016493,0.00038463305,0.00034609597,0.000020218007],"category_scores_gemma":[0.00022061687,0.0003189695,0.00032767505,0.0007016809,0.0002157167,0.0001202494,0.0002321533,0.001709041,0.0000031471545],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035416648,0.0007390314,0.36442682,0.00037011126,0.000022835095,0.000007556467,0.0000062556746,0.000058973885,0.6340819,0.0001872189,0.000058211535,0.0000056802096],"study_design_scores_gemma":[0.00032144797,0.000049025017,0.7660646,0.00034395186,0.00008458637,9.527335e-8,0.000001825515,0.00012210998,0.23207282,0.00001106609,0.00070593454,0.00022254817],"about_ca_topic_score_codex":0.00005574002,"about_ca_topic_score_gemma":0.0000025713937,"teacher_disagreement_score":0.40200907,"about_ca_system_score_codex":0.0003120723,"about_ca_system_score_gemma":0.0005145124,"threshold_uncertainty_score":0.9999262},"labels":[],"label_agreement":null},{"id":"W2944031440","doi":"10.1101/620419","title":"Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institutes of Health","keywords":"Cingulum (brain); White matter; Univariate; Grey matter; Corpus callosum; Fornix; Fractional anisotropy; Psychology; Neuroscience; Brain size; Anatomy; Multivariate statistics; Biology; Medicine; Mathematics; Magnetic resonance imaging; Hippocampus","score_opus":0.02039391204576375,"score_gpt":0.2898791029104136,"score_spread":0.26948519086464984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944031440","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91204,0.0003924659,0.08100038,0.0045748632,0.00014208506,0.0010788019,0.000631618,0.00013684217,0.0000029187677],"genre_scores_gemma":[0.9909912,0.00008163952,0.007870613,0.0007886928,0.00009898456,0.00010697337,0.0000063824527,0.00005125869,0.0000043022897],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978751,0.00010289688,0.00069564575,0.0007463413,0.00023348519,0.00034654854],"domain_scores_gemma":[0.9980511,0.00008915024,0.00043645894,0.00090356945,0.00032455532,0.00019513955],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031182828,0.00031981745,0.0008430431,0.0006817342,0.0000752707,0.000044314973,0.000125145,0.00033599648,0.000051102117],"category_scores_gemma":[0.00020098762,0.00033226368,0.00017220186,0.0010342845,0.00017676559,0.00006545804,0.00022794523,0.0010017639,0.000008684622],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010886301,0.00014495561,0.79556584,0.0003853741,0.00015031947,0.000010886423,0.000014413299,0.00044914507,0.2024121,0.0003330988,0.00042407436,9.0255577e-7],"study_design_scores_gemma":[0.00077541365,0.000075518736,0.97688425,0.00028281755,0.0005035332,1.3937664e-7,0.0000039740908,0.0056421934,0.015071632,0.000007098,0.0004738818,0.00027957445],"about_ca_topic_score_codex":0.000052426134,"about_ca_topic_score_gemma":0.0000022514394,"teacher_disagreement_score":0.18734047,"about_ca_system_score_codex":0.0001887122,"about_ca_system_score_gemma":0.00024843364,"threshold_uncertainty_score":0.9999129},"labels":[],"label_agreement":null},{"id":"W2944052887","doi":"10.1007/s00429-019-01864-2","title":"Diffusion weighted imaging evidence of extra-callosal pathways for interhemispheric communication after complete commissurotomy","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institute for Advanced Research; University of Miami","keywords":"Corpus callosum; Commissurotomy; White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Psychology; Tractography; Commissure; Cognition; Magnetic resonance imaging; Medicine; Cardiology; Radiology","score_opus":0.040573470213786086,"score_gpt":0.3049478365474945,"score_spread":0.2643743663337084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944052887","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.900799,0.0009113635,0.09485456,0.0017830809,0.0000623944,0.0012405023,0.000029753293,0.00010433947,0.00021500983],"genre_scores_gemma":[0.9819775,0.00005938946,0.016900074,0.0007699223,0.000034741122,0.00007594726,0.00006592744,0.00001782279,0.000098635086],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993708,0.000023717213,0.00019784819,0.00021204805,0.00009348736,0.000102092614],"domain_scores_gemma":[0.999193,0.00017735829,0.00011183231,0.00037571022,0.00009892342,0.000043164997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000069544905,0.000109738445,0.00017835769,0.00003923372,0.00005913537,0.000011784256,0.00006561238,0.00004427291,0.00007776371],"category_scores_gemma":[0.00003169571,0.000092796916,0.000050208357,0.00010074399,0.000068441,0.000111564696,0.00005027885,0.00013023142,0.000001035017],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012132488,0.000043412547,0.039804865,0.0004013208,0.000017090386,7.5542795e-7,0.0001811676,0.0000020831026,0.90366477,0.0020585016,0.0011142909,0.051498525],"study_design_scores_gemma":[0.0075339866,0.0017382938,0.6455217,0.0031982784,0.00047780256,0.00030713444,0.00044294167,0.045919314,0.04831186,0.06387213,0.18171075,0.0009658219],"about_ca_topic_score_codex":0.0000074915965,"about_ca_topic_score_gemma":0.0000013140987,"teacher_disagreement_score":0.8553529,"about_ca_system_score_codex":0.000017298618,"about_ca_system_score_gemma":0.000012745902,"threshold_uncertainty_score":0.37841484},"labels":[],"label_agreement":null},{"id":"W2944068640","doi":"10.1007/s12264-019-00381-w","title":"White Matter Abnormalities in Major Depression Biotypes Identified by Diffusion Tensor Imaging","year":2019,"lang":"en","type":"article","venue":"Neuroscience Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Neurocognitive; Major depressive disorder; Psychology; Subgroup analysis; Depression (economics); Medicine; Internal medicine; Oncology; Psychiatry; Magnetic resonance imaging; Neuroscience; Cognition; Radiology; Meta-analysis","score_opus":0.016822475210303944,"score_gpt":0.2899825822187401,"score_spread":0.2731601070084362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944068640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97927964,0.00007788062,0.0013945044,0.014599432,0.00017643397,0.00056402374,0.000011754845,0.00017814578,0.0037182153],"genre_scores_gemma":[0.9779768,0.000040589297,0.0012337622,0.007339623,0.000020108704,0.0000417252,0.0000070982396,0.000024062283,0.013316238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872094,0.00002769346,0.00021745607,0.0005024276,0.00023978374,0.0002916997],"domain_scores_gemma":[0.99938583,0.00003233172,0.00007395063,0.00040358226,0.000029770808,0.00007455806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000113739035,0.00013285471,0.00015843163,0.00012465961,0.00008878191,0.000051826402,0.00019325153,0.00003081832,0.0004409517],"category_scores_gemma":[0.000039495924,0.00011217316,0.00004074614,0.00023075359,0.0001127567,0.000091161586,0.00013660085,0.0002074028,0.00031918575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022343187,0.00006599093,0.7845778,0.000021041325,1.39229e-7,0.000011678603,0.00002428739,0.0000035055727,0.19555165,0.000024416348,0.01943268,0.000264462],"study_design_scores_gemma":[0.0006077696,0.000036734295,0.85023266,0.0001269046,0.0000066216585,0.00009998147,0.000048888316,0.00068215316,0.015225204,0.00009600251,0.13265978,0.00017729813],"about_ca_topic_score_codex":0.00003573561,"about_ca_topic_score_gemma":4.8721716e-7,"teacher_disagreement_score":0.18032643,"about_ca_system_score_codex":0.000024536555,"about_ca_system_score_gemma":0.000012065108,"threshold_uncertainty_score":0.4828112},"labels":[],"label_agreement":null},{"id":"W2944274429","doi":"10.1101/631952","title":"TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow &amp; Singularity","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Pipeline (software); Diffusion MRI; Tractography; Fractional anisotropy; Orientation (vector space); Artificial intelligence; Image processing; Computation; Data mining; Pattern recognition (psychology); Image (mathematics); Algorithm; Mathematics","score_opus":0.05343977480373192,"score_gpt":0.28627855693465654,"score_spread":0.23283878213092463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944274429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76965845,0.0014672944,0.22328322,0.0020787823,0.00043773738,0.001869094,0.000111409114,0.0010635207,0.000030496114],"genre_scores_gemma":[0.856278,0.0007417981,0.14160182,0.0005121887,0.00045877605,0.00016308244,0.0000029903717,0.00018285977,0.000058491947],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99609643,0.00007709202,0.0006497576,0.0021260206,0.00046368927,0.0005870137],"domain_scores_gemma":[0.99550986,0.00008070674,0.00042137824,0.0031303624,0.000509829,0.00034788295],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007022782,0.00063924334,0.00083850994,0.00033564132,0.00024450952,0.00017396495,0.00031863718,0.00042354193,0.00003131666],"category_scores_gemma":[0.00041208198,0.0006548911,0.00018749632,0.00048396917,0.00016426037,0.00009229159,0.00078886515,0.0014867331,0.00003590147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013670369,0.0010803058,0.018774984,0.0015496137,0.00008390719,0.00008993231,0.00003353591,0.0034710271,0.9717333,0.0005200321,0.0024766491,0.000050056686],"study_design_scores_gemma":[0.005497305,0.00028773796,0.25425538,0.0067863027,0.0016143295,0.0000035005426,0.000013522013,0.16245246,0.33843046,0.0000847741,0.22584133,0.004732875],"about_ca_topic_score_codex":0.000055096163,"about_ca_topic_score_gemma":6.70674e-7,"teacher_disagreement_score":0.6333028,"about_ca_system_score_codex":0.00025732216,"about_ca_system_score_gemma":0.00035432415,"threshold_uncertainty_score":0.9995902},"labels":[],"label_agreement":null},{"id":"W2944454351","doi":"10.1016/j.nicl.2019.101855","title":"White matter microstructural differences identified using multi-shell diffusion imaging in six-year-old children born very preterm","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; University of Toronto; Mental Health Research Canada; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Shell (structure); Diffusion imaging; Diffusion; Medicine; Psychology; Magnetic resonance imaging; Physics; Materials science; Radiology","score_opus":0.07307813547691652,"score_gpt":0.3862503993791584,"score_spread":0.31317226390224184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944454351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968283,0.00003199362,0.0006049244,0.0007686699,0.00036156806,0.000996828,0.000030071662,0.00018162285,0.00019600625],"genre_scores_gemma":[0.98522025,0.00005349749,0.011329996,0.0023640413,0.00016611438,0.000013956388,0.000041970936,0.00007188146,0.0007382676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99739254,0.00012752731,0.00083308236,0.0009654606,0.00024171133,0.00043967395],"domain_scores_gemma":[0.9984736,0.0001756,0.00023247683,0.0008974529,0.00006380161,0.00015707378],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002081237,0.00029928036,0.0005429063,0.00015042943,0.00008112021,0.00008758279,0.00030378526,0.000115244344,0.0002039276],"category_scores_gemma":[0.00011261387,0.0002665195,0.00023393384,0.00021556189,0.00022055034,0.00023912544,0.00032353395,0.0008300079,0.00016205346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108412234,0.00017805884,0.94777495,0.000026671689,0.000004833019,0.000037891365,0.000024999908,0.0000018767961,0.051013306,0.000005179163,0.00024306025,0.0005807681],"study_design_scores_gemma":[0.0021826548,0.00007273246,0.9927054,0.00014950028,0.00004543048,0.00015149865,0.000012546916,0.0035583014,0.0007100941,0.000071251096,0.00009062355,0.00024998546],"about_ca_topic_score_codex":0.000045933928,"about_ca_topic_score_gemma":0.0000040663913,"teacher_disagreement_score":0.050303213,"about_ca_system_score_codex":0.000040055715,"about_ca_system_score_gemma":0.000035687957,"threshold_uncertainty_score":0.9999787},"labels":[],"label_agreement":null},{"id":"W2944551460","doi":"10.1101/624171","title":"Early childhood development of white matter fiber density and morphology","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates; National Imaging Facility; Australian Government","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Corpus callosum; Corticospinal tract; Brain development; Tractography; Fiber bundle; Anatomy; Fiber; Biology; Neuroscience; Psychology; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.02070771686353873,"score_gpt":0.2536076822523065,"score_spread":0.23289996538876778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944551460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99302894,0.00016292783,0.0051607783,0.0004237207,0.00009590748,0.0008631567,0.000040357303,0.00019921616,0.000024991452],"genre_scores_gemma":[0.8793198,0.00004303987,0.11997909,0.0003898204,0.00006199882,0.00009954859,4.5628462e-7,0.000076036355,0.000030205225],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983717,0.000027995387,0.00042704403,0.000710956,0.00018258933,0.00027969998],"domain_scores_gemma":[0.99823153,0.000023338976,0.0003048066,0.0010474682,0.0002469235,0.00014593692],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001569072,0.00032348617,0.0005542339,0.00016735033,0.000097456934,0.00001916553,0.00018038417,0.00028029262,0.00007611061],"category_scores_gemma":[0.000026081467,0.0003309834,0.000073722294,0.00015369318,0.00011392003,0.000045543056,0.0006917573,0.0005646089,0.000093379735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045793204,0.00035061655,0.54525745,0.0007588431,0.00017107476,0.000038626906,0.000082494895,0.0000068239124,0.45233953,0.00015108206,0.0007828199,0.000014872094],"study_design_scores_gemma":[0.00031062926,0.000027555283,0.84656405,0.00026342622,0.00008146183,1.5042919e-7,5.381431e-7,0.000009884571,0.15004976,0.0000032962023,0.0024319247,0.00025731436],"about_ca_topic_score_codex":0.0000055867285,"about_ca_topic_score_gemma":9.837252e-8,"teacher_disagreement_score":0.30228975,"about_ca_system_score_codex":0.00007436773,"about_ca_system_score_gemma":0.000297959,"threshold_uncertainty_score":0.9999142},"labels":[],"label_agreement":null},{"id":"W2944724695","doi":"10.1136/bcr-2018-228971","title":"Spatial reorganisation of the somatosensory cortex in a patient with a low-grade glioma","year":2019,"lang":"en","type":"article","venue":"BMJ Case Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; St. Michael's Hospital","funders":"Canadian Cancer Society Research Institute","keywords":"Somatosensory system; Glioma; Neuroplasticity; Psychology; Neuroscience; Dissociation (chemistry); Medicine; Sensation","score_opus":0.022743683206585312,"score_gpt":0.3112501977776423,"score_spread":0.28850651457105697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944724695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9972904,0.000008617525,0.00037159154,0.000382814,0.000035510453,0.0013937636,0.0000017270922,0.000048272137,0.00046732926],"genre_scores_gemma":[0.9984472,0.0000015020196,0.0013055917,0.000097601194,0.000015215622,0.00005894642,0.000004166739,0.000016754524,0.000053055246],"study_design_codex":"bench_or_experimental","study_design_gemma":"case_report","domain_scores_codex":[0.99918747,0.00001786098,0.00032243217,0.0001944976,0.00018508815,0.000092672875],"domain_scores_gemma":[0.9990174,0.000021328526,0.00029892212,0.0005760763,0.00005405499,0.00003219955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006940335,0.00007602566,0.0001507002,0.000051791696,0.000022334163,0.0000029384719,0.000016471662,0.000030461366,0.00001802889],"category_scores_gemma":[0.00004248732,0.0000499744,0.000037739752,0.00019724743,0.000040282324,0.000027745331,0.000029589559,0.00009474036,0.000002072815],"study_design_candidate":"case_report","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017288144,0.0007053783,0.22258365,0.00025782263,0.000025871343,0.3581566,0.00069876725,0.00006815236,0.41136864,0.00033436005,0.00025392015,0.005373967],"study_design_scores_gemma":[0.00048873294,0.00019954894,0.063263476,0.00032006446,0.00003589102,0.7874157,0.0001361737,0.00039632132,0.14668497,0.00038005368,0.0005638336,0.00011528037],"about_ca_topic_score_codex":0.00017685052,"about_ca_topic_score_gemma":0.000029420855,"teacher_disagreement_score":0.42925906,"about_ca_system_score_codex":0.000038610204,"about_ca_system_score_gemma":0.00008813826,"threshold_uncertainty_score":0.20378968},"labels":[],"label_agreement":null},{"id":"W2944868864","doi":"10.1016/j.neuroimage.2019.05.042","title":"The influence of brain iron on myelin water imaging","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Austrian Science Fund; National Multiple Sclerosis Society","keywords":"Myelin; Neuroscience; Chemistry; Psychology","score_opus":0.020942089022172292,"score_gpt":0.3187720889944748,"score_spread":0.2978299999723025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944868864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791663,0.000015673102,0.000164412,0.016033992,0.00003413349,0.00040838128,0.0000035397247,0.00011860463,0.004054926],"genre_scores_gemma":[0.9938247,0.000029045877,0.000528009,0.003994538,0.00002735999,0.000018104085,0.0000039600377,0.000025315387,0.0015489495],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99921185,0.000023423327,0.00017732906,0.00023222448,0.00016212842,0.00019305598],"domain_scores_gemma":[0.999069,0.00014777097,0.000049526894,0.000641562,0.00005142909,0.00004072708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011206686,0.000096971366,0.00011909333,0.000039163395,0.00006881492,0.000012971406,0.00014977905,0.000015455726,0.000022489863],"category_scores_gemma":[0.00007375608,0.000056685152,0.00005364626,0.00007837019,0.000094967196,0.00006032612,0.00006660947,0.00021229246,0.00015797684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005583528,0.000045274497,0.0068760645,0.000027810904,0.0000016888469,0.000012459294,0.00003668996,0.00012611931,0.9847564,0.0012184914,0.0019218872,0.0049212463],"study_design_scores_gemma":[0.0011793291,0.00045965973,0.2515671,0.00014800837,0.000030519997,0.000114422815,0.000032830543,0.0013716597,0.4585756,0.0026999689,0.28355882,0.0002621018],"about_ca_topic_score_codex":0.0000053669064,"about_ca_topic_score_gemma":1.7865285e-7,"teacher_disagreement_score":0.52618086,"about_ca_system_score_codex":0.000011866862,"about_ca_system_score_gemma":0.000011011713,"threshold_uncertainty_score":0.23115534},"labels":[],"label_agreement":null},{"id":"W2944934343","doi":"10.1007/978-3-030-20351-1_14","title":"Minimizing Non-holonomicity: Finding Sheets in Fibrous Structures","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Computer science; Algorithm; Contraction (grammar); Field (mathematics); Exploit; Measure (data warehouse); Human heart; Theoretical computer science; Mathematics; Data mining; Pure mathematics","score_opus":0.049636773734566174,"score_gpt":0.32846047506756243,"score_spread":0.2788237013329963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944934343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008675584,0.0001557642,0.98403424,0.0009102455,0.00037411676,0.00085273926,0.000009714542,0.000115846684,0.004871754],"genre_scores_gemma":[0.71072775,0.000047291804,0.28696156,0.0016518066,0.00024909014,0.000008882565,0.000014203942,0.000052325307,0.00028708094],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980209,0.0000062977415,0.0003507652,0.0009402238,0.00028772213,0.00039408205],"domain_scores_gemma":[0.99874294,0.00020614619,0.00016491594,0.0007523786,0.000051932107,0.00008171055],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017996835,0.0003222468,0.00048867974,0.0006384253,0.000081444115,0.00006510736,0.00052272703,0.00020833108,0.000035884015],"category_scores_gemma":[0.00004730343,0.0003002083,0.00007846114,0.00024587734,0.00030682443,0.00011259377,0.00036372067,0.00085846684,0.000014577858],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008427219,0.000058187878,0.004686989,0.0003426302,0.000017584587,0.000394353,0.0010650149,0.04141342,0.009583981,0.0065364717,0.00014902715,0.93566805],"study_design_scores_gemma":[0.0038564797,0.0013805352,0.03392196,0.008557912,0.00012271704,0.0015206648,0.0000027378521,0.4702,0.044845622,0.4157215,0.015979486,0.0038903672],"about_ca_topic_score_codex":0.000015477262,"about_ca_topic_score_gemma":0.000011186514,"teacher_disagreement_score":0.9317777,"about_ca_system_score_codex":0.00027725505,"about_ca_system_score_gemma":0.0002674283,"threshold_uncertainty_score":0.999945},"labels":[],"label_agreement":null},{"id":"W2946033723","doi":"10.1002/hbm.24622","title":"The efficiency of the brain connectome is associated with cerebrovascular reactivity in persons with white matter hyperintensities","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"White matter; Hyperintensity; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Connectomics; Psychology; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.031500696721701804,"score_gpt":0.27386803603567733,"score_spread":0.24236733931397553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946033723","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97639596,0.000012543228,0.00083050114,0.019478751,0.000009428206,0.0006584221,0.0000049908967,0.00005930485,0.0025500935],"genre_scores_gemma":[0.9938147,0.0000010487739,0.00018747227,0.003150167,0.000010533501,0.00003589624,0.0000033800463,0.000025360077,0.0027714425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991012,0.00006616984,0.00015586396,0.00024735468,0.0002109588,0.00021840345],"domain_scores_gemma":[0.998933,0.00025111943,0.0001372081,0.00057721266,0.00007675576,0.000024702695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029766557,0.0001270204,0.00022642461,0.000062040046,0.00020460413,0.000019123376,0.0001540645,0.000033839755,0.000037599584],"category_scores_gemma":[0.000068693014,0.00006925178,0.00006656136,0.00032017767,0.0002293084,0.000050588995,0.000057617028,0.00028031252,0.0000047082763],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004815116,0.00015024927,0.84407,0.0000889969,0.000085369014,0.0000072607986,0.004139772,0.000039004426,0.14542432,0.0015852212,0.004293734,0.000067898465],"study_design_scores_gemma":[0.0008854958,0.000118517324,0.99075544,0.00056567614,0.000020644164,0.00005229134,0.0015943918,0.00030439495,0.0012081688,0.00025658595,0.0040968996,0.00014147274],"about_ca_topic_score_codex":0.000043039734,"about_ca_topic_score_gemma":0.000047673828,"teacher_disagreement_score":0.14668544,"about_ca_system_score_codex":0.000059303467,"about_ca_system_score_gemma":0.000033647953,"threshold_uncertainty_score":0.28240058},"labels":[],"label_agreement":null},{"id":"W2946440603","doi":"10.1016/j.neuroimage.2019.05.003","title":"Combining white matter diffusion and geometry for tract-specific alignment and variability analysis","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministry of Defense; Israel Science Foundation","keywords":"Diffusion MRI; Human Connectome Project; Tractography; Voxel; White matter; Fiber tract; Artificial intelligence; Computer science; Fractional anisotropy; Fiber bundle; Diffusion; Pattern recognition (psychology); Fiber; Mathematics; Physics; Magnetic resonance imaging; Neuroscience; Psychology; Chemistry; Medicine; Functional connectivity","score_opus":0.031622683434222795,"score_gpt":0.310384717275131,"score_spread":0.2787620338409082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946440603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96247953,0.00003479675,0.033205565,0.0023753329,0.00002755906,0.0007397634,0.00002689398,0.00008291979,0.0010276427],"genre_scores_gemma":[0.98666316,0.000084082116,0.011523027,0.0010423934,0.000020192107,0.00004681995,0.000027181297,0.00002165953,0.0005714742],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907047,0.000022620734,0.00018257918,0.00046004532,0.00010601737,0.00015824445],"domain_scores_gemma":[0.9992526,0.0001379679,0.00006387478,0.00042691056,0.000032771906,0.00008583958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015104955,0.000120980185,0.00026211704,0.00012841349,0.00006981755,0.00003137327,0.000046518282,0.000036799698,0.00010683875],"category_scores_gemma":[0.00001671818,0.00010858434,0.00006868376,0.00023832353,0.00006663899,0.000070607646,0.000071536466,0.00012788175,0.000007755913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043699234,0.00016624975,0.94173867,0.00007909527,0.000021429252,0.0000037940922,0.0000552674,0.0000031755603,0.05483197,0.000489804,0.00062620244,0.00194063],"study_design_scores_gemma":[0.00070831587,0.00013645997,0.9827186,0.000012891839,0.0002008163,0.000028676004,0.000017004,0.001876432,0.0009635547,0.0008179257,0.012403341,0.00011601124],"about_ca_topic_score_codex":0.000002042741,"about_ca_topic_score_gemma":1.0252958e-7,"teacher_disagreement_score":0.053868417,"about_ca_system_score_codex":0.000014988234,"about_ca_system_score_gemma":0.000004267473,"threshold_uncertainty_score":0.44279408},"labels":[],"label_agreement":null},{"id":"W2946716788","doi":"10.1016/j.neurobiolaging.2019.05.005","title":"Synergism between fornix microstructure and beta amyloid accelerates memory decline in clinically normal older adults","year":2019,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; Sunnybrook Health Science Centre","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council; National Institute on Aging; National Institutes of Health; Canadian Institutes of Health Research; Biogen","keywords":"Fornix; Episodic memory; Cognitive decline; Medicine; Hippocampus; Psychology; Cognition; Neuroscience; Internal medicine; Dementia; Disease","score_opus":0.023823285753759707,"score_gpt":0.3256395321655264,"score_spread":0.3018162464117667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946716788","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9966226,0.00008252127,0.00009890943,0.0023676043,0.00005129577,0.0004169066,0.000022732333,0.00006862307,0.00026876753],"genre_scores_gemma":[0.994051,0.00012732175,0.004224864,0.0013847523,0.00006498806,0.000009752535,0.00004108205,0.000022179669,0.000074055846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988735,0.000035795147,0.0004251856,0.0003851864,0.000057406865,0.00022295657],"domain_scores_gemma":[0.9991983,0.0002257971,0.00015510194,0.00029680974,0.00006687662,0.00005709074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014733875,0.0001438782,0.00039188558,0.00010543131,0.000030428311,0.000004922485,0.00013402589,0.00011672918,0.000025738977],"category_scores_gemma":[0.000035011086,0.00012570669,0.00005336513,0.00011851438,0.00014848229,0.000056323443,0.00017614769,0.0003959499,0.0000043598507],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000070382885,0.00003690576,0.9297699,0.00009186213,0.000009614954,0.0000043049818,0.000079991434,0.000009272911,0.06494788,0.000027407417,0.00007266326,0.0048798216],"study_design_scores_gemma":[0.0014990434,0.00024674597,0.95283955,0.00016036627,0.000027154934,0.000048023707,0.000025599098,0.000044570657,0.044340976,0.00017215188,0.00047869407,0.00011713683],"about_ca_topic_score_codex":0.00002454987,"about_ca_topic_score_gemma":0.0000041347403,"teacher_disagreement_score":0.023069646,"about_ca_system_score_codex":0.00000897055,"about_ca_system_score_gemma":0.000028907045,"threshold_uncertainty_score":0.512617},"labels":[],"label_agreement":null},{"id":"W2947056593","doi":"10.1016/j.dadm.2019.03.002","title":"Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Alzheimer's Disease Research Center, Emory University; Servier; Pfizer; BioClinica; Biogen; Eli Lilly and Company; U.S. Department of Defense; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Roche; Merck; Alzheimer's Drug Discovery Foundation; Takeda Pharmaceutical Company; AbbVie; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Perivascular space; Magnetic resonance imaging; Interstitial fluid; Diffusion MRI; Pathology; Parenchyma; Cognitive decline; Hyperintensity; Cerebrospinal fluid; Thermal diffusivity; Pathological; Pathophysiology; Medicine; Disease; Dementia; Radiology; Physics","score_opus":0.08263600615335222,"score_gpt":0.3967723127486974,"score_spread":0.3141363065953452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947056593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97886896,0.014442735,0.00046762728,0.003108334,0.00027480462,0.0024226827,0.000076302094,0.00017741456,0.00016112207],"genre_scores_gemma":[0.9942602,0.0009376684,0.002295778,0.00055129797,0.00023957752,0.0015686435,0.00006455067,0.00007467894,0.000007598238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967963,0.00018403798,0.0008269926,0.0008588082,0.00080003205,0.0005338083],"domain_scores_gemma":[0.996897,0.0005547424,0.0003370532,0.0014790361,0.0001433787,0.00058881],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004160162,0.00040430966,0.0005447333,0.00015450032,0.0001636895,0.00005956972,0.00047211646,0.000069233036,0.00022505157],"category_scores_gemma":[0.000077916586,0.00033829568,0.00037640904,0.00043046047,0.00015947902,0.00025810648,0.0003912223,0.00041495432,0.000026032832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000154321,0.0017270311,0.98669016,0.000038666625,0.00090146746,0.000020509415,0.00006479477,0.00008073606,0.0007541009,0.00016242314,0.00050145603,0.008904306],"study_design_scores_gemma":[0.0012534633,0.000109476736,0.97794795,0.00038485945,0.0073164334,9.1942076e-7,0.00006903633,0.0017997305,0.0072152447,0.00027302455,0.003298497,0.00033138943],"about_ca_topic_score_codex":0.0002571919,"about_ca_topic_score_gemma":0.000003323528,"teacher_disagreement_score":0.01539123,"about_ca_system_score_codex":0.000047627247,"about_ca_system_score_gemma":0.00025518096,"threshold_uncertainty_score":0.9999069},"labels":[],"label_agreement":null},{"id":"W2947357678","doi":"10.1016/j.nicl.2019.101883","title":"Automated fiber tract reconstruction for surgery planning: Extensive validation in language-related white matter tracts","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London Hospitals NHS Foundation Trust; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; University College London; Wellcome Trust","keywords":"Computer science; Segmentation; Tractography; Artificial intelligence; White matter; Diffusion MRI; Surgical planning; Pipeline (software); Task (project management); Perspective (graphical); Machine learning; Natural language processing; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.10703746224582505,"score_gpt":0.4296475374320574,"score_spread":0.32261007518623236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947357678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933757,0.000021161182,0.0003786733,0.0028001615,0.00030798817,0.0011335092,0.000017644239,0.00061018876,0.0013549682],"genre_scores_gemma":[0.989277,0.000019721328,0.0068390886,0.0017098108,0.0001076962,0.00007731834,0.00015900446,0.00006475075,0.0017455872],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980993,0.00010461807,0.00083008426,0.00057608,0.00012925448,0.00026061272],"domain_scores_gemma":[0.9980245,0.0010311168,0.00027114627,0.00046330024,0.00011103929,0.000098890814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042923517,0.0001704263,0.00046027495,0.00017584361,0.000036035657,0.000023737468,0.00007145536,0.00017350304,0.00031385338],"category_scores_gemma":[0.00055668334,0.00016499318,0.00022026317,0.00024212069,0.00007364261,0.00019899369,0.000022979666,0.00049436936,0.00028588445],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003364229,0.0005210584,0.9589468,0.000098267825,0.000017122731,0.00014782652,0.000101899655,0.00013202748,0.007202812,0.000013744209,0.019570911,0.012911095],"study_design_scores_gemma":[0.0013810071,0.00017702744,0.9858651,0.00019329847,0.000054731478,0.00049598614,0.000040353156,0.006535461,0.0015598192,0.00016667153,0.003332002,0.00019852801],"about_ca_topic_score_codex":0.0000026148032,"about_ca_topic_score_gemma":1.4544865e-7,"teacher_disagreement_score":0.026918301,"about_ca_system_score_codex":0.000029642177,"about_ca_system_score_gemma":0.00005719244,"threshold_uncertainty_score":0.67282265},"labels":[],"label_agreement":null},{"id":"W2947735528","doi":"10.1002/jmri.26807","title":"Increasing body mass index in an elderly cohort: Effects on the quantitative MR parameters of the brain","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Universität Duisburg-Essen","keywords":"Body mass index; Medicine; White matter; Nuclear medicine; Voxel-based morphometry; Bayesian multivariate linear regression; Magnetic resonance imaging; Internal medicine; Cardiology; Linear regression; Radiology; Statistics; Mathematics","score_opus":0.022895981403102793,"score_gpt":0.3249197381238344,"score_spread":0.3020237567207316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947735528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881045,0.0009145147,0.0007969843,0.009138603,0.00006769827,0.000621615,0.0000015471282,0.000010505397,0.00034398877],"genre_scores_gemma":[0.9883053,0.000064114654,0.010200617,0.0013181329,0.000026693178,0.000011858935,2.8554717e-7,0.000020245985,0.000052776537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99862677,0.00024889785,0.000416453,0.00016520373,0.00035867604,0.0001839942],"domain_scores_gemma":[0.9978934,0.0011132505,0.00039902082,0.00042264824,0.00012234738,0.000049326358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079549383,0.00012509093,0.00028846372,0.00012079568,0.000047276393,0.000023052171,0.0002812247,0.000025053205,0.000010786371],"category_scores_gemma":[0.00060736836,0.00007296463,0.00010040296,0.0003083529,0.00012842662,0.00013020581,0.00003362863,0.00052439334,0.0000017775989],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028563393,0.000086701504,0.8540711,0.000038331287,0.0000053576046,0.000033523695,0.0001571464,0.000066043736,0.101363465,0.0007915824,0.00023371409,0.042867407],"study_design_scores_gemma":[0.00096852053,0.0008207233,0.9770575,0.0012119851,0.000032831635,0.00017881577,0.00019904811,0.0059116255,0.009447638,0.0027606012,0.0013148964,0.00009579294],"about_ca_topic_score_codex":0.000030602252,"about_ca_topic_score_gemma":0.0000016821598,"teacher_disagreement_score":0.12298643,"about_ca_system_score_codex":0.000057868656,"about_ca_system_score_gemma":0.000068660025,"threshold_uncertainty_score":0.2975411},"labels":[],"label_agreement":null},{"id":"W2948371953","doi":"10.3389/fnagi.2019.00134","title":"Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson’s Disease","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Siemens Healthineers; Ministero della Salute; University of Southern California","keywords":"Fractional anisotropy; Putamen; Cerebral blood flow; Basal ganglia; Diffusion MRI; Caudate nucleus; Subthalamic nucleus; Medicine; Parkinson's disease; Nuclear medicine; Cardiology; Internal medicine; Pathology; Psychology; Magnetic resonance imaging; Radiology; Deep brain stimulation; Central nervous system; Disease","score_opus":0.021040234148796445,"score_gpt":0.29554198216451116,"score_spread":0.2745017480157147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2948371953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98841846,0.000022845039,0.009770918,0.00087158586,0.00028122682,0.0005273113,0.000007197986,0.000048138663,0.000052343472],"genre_scores_gemma":[0.93808866,0.00003298924,0.06103507,0.00072962855,0.0000046846067,0.00002717998,0.0000021815824,0.000013685316,0.00006594366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988102,0.000039803126,0.000242472,0.00045321518,0.00023381857,0.0002205192],"domain_scores_gemma":[0.99940944,0.000025949503,0.00009580111,0.0003337333,0.000015879068,0.000119186494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015967962,0.00011985407,0.00022927189,0.00021929682,0.00003443585,0.00001955358,0.00015390084,0.000023380526,9.961466e-7],"category_scores_gemma":[0.00007246367,0.00011367317,0.000029843657,0.00042175723,0.00015612692,0.00013834507,0.0000959889,0.00023242555,2.0668485e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034658395,0.00016593054,0.9899559,0.00004125475,6.6030134e-7,0.000030857318,0.00010196317,0.00023561779,0.008961282,0.000115845854,0.00007262421,0.0002834171],"study_design_scores_gemma":[0.00096539676,0.00015094334,0.8636931,0.00015183692,0.0000118337375,0.0000017623788,0.00003256108,0.1319708,0.0010811638,0.0018127467,0.00003061887,0.000097224736],"about_ca_topic_score_codex":0.000025349289,"about_ca_topic_score_gemma":0.0000010120556,"teacher_disagreement_score":0.13173518,"about_ca_system_score_codex":0.00003503173,"about_ca_system_score_gemma":0.000057180387,"threshold_uncertainty_score":0.46354577},"labels":[],"label_agreement":null},{"id":"W2949115936","doi":"10.1016/j.bandl.2017.10.008","title":"Brain white matter structure and language ability in preschool-aged children","year":2017,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; MediWound","keywords":"Fractional anisotropy; Psychology; White matter; Diffusion MRI; Corpus callosum; Lateralization of brain function; Tractography; Developmental psychology; Cognitive psychology; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.012146118882947981,"score_gpt":0.32078468978117297,"score_spread":0.308638570898225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949115936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98632586,0.00029130268,0.00010599215,0.011781082,0.000008679576,0.00041982016,0.000059908296,0.000066772096,0.00094059174],"genre_scores_gemma":[0.9925053,0.000010868886,0.0023918357,0.0036005033,0.00006812467,0.000014928522,0.00003462544,0.000017620463,0.0013561543],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993497,0.000027483648,0.00011408378,0.00028732358,0.00006834294,0.0001530658],"domain_scores_gemma":[0.9992436,0.000044130524,0.000055729717,0.00056641264,0.000007281548,0.000082839964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011132932,0.00011389267,0.00016591686,0.000044454213,0.00011619505,0.000054174572,0.00009740152,0.000058735517,0.00014422128],"category_scores_gemma":[0.00015474227,0.00009454526,0.000022569342,0.000032017804,0.00011627054,0.00008995483,0.000101035424,0.00023389365,0.0000027992498],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026179881,0.000028331242,0.95239365,0.00004980441,0.0000060783345,0.000035577847,0.0014943768,2.0322142e-7,0.035834067,0.00007666732,0.0042317063,0.0058233268],"study_design_scores_gemma":[0.0007374808,0.00002241903,0.9970984,0.000041270276,0.000008428038,0.00008175151,0.00012393498,0.000025605093,0.001061109,0.00025326462,0.00044727913,0.000099095785],"about_ca_topic_score_codex":0.00017743549,"about_ca_topic_score_gemma":0.00010497579,"teacher_disagreement_score":0.044704683,"about_ca_system_score_codex":0.000009817839,"about_ca_system_score_gemma":0.000008256927,"threshold_uncertainty_score":0.3855444},"labels":[],"label_agreement":null},{"id":"W2949343593","doi":"10.1016/j.nicl.2019.101896","title":"Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia Hospital; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multiple sclerosis; Spinal cord; Myelin; Medicine; Neuromyelitis optica; Diffusion MRI; White matter; Magnetic resonance imaging; Cord; Lesion; Nuclear medicine; Transverse myelitis; Radiology; Pathology; Central nervous system; Internal medicine; Surgery; Immunology","score_opus":0.1589229524372321,"score_gpt":0.4829302378793488,"score_spread":0.3240072854421167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949343593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8026259,0.00017948948,0.12979807,0.057820883,0.0010433722,0.004880519,0.000082097176,0.00048448678,0.0030852042],"genre_scores_gemma":[0.9484325,0.00023054123,0.04458943,0.0056067663,0.00043141955,0.00012549234,0.000033716296,0.00007044648,0.00047967545],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976409,0.000105777945,0.0009253127,0.00064710126,0.00030198693,0.00037890964],"domain_scores_gemma":[0.9973613,0.0008792336,0.00018776231,0.0012119173,0.00021969444,0.00014011185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009200366,0.00021485476,0.00051782833,0.00006183216,0.00010162545,0.00002734684,0.0003831641,0.000077305325,0.00024366433],"category_scores_gemma":[0.00026093697,0.0001324614,0.00041469262,0.0001232079,0.0003096669,0.00008880635,0.00023656934,0.0007139945,0.00005639936],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039512995,0.0024841845,0.32899296,0.0006837511,0.00014634489,0.00012832963,0.000035592275,0.00003877263,0.15794966,0.0061541214,0.020701228,0.47873378],"study_design_scores_gemma":[0.0036885103,0.0032081127,0.63535523,0.00012426746,0.00029843033,0.0001021974,0.00003842691,0.034959994,0.005487188,0.0014263913,0.31499523,0.00031601434],"about_ca_topic_score_codex":0.000004375731,"about_ca_topic_score_gemma":3.688614e-7,"teacher_disagreement_score":0.47841775,"about_ca_system_score_codex":0.000023062907,"about_ca_system_score_gemma":0.00009060265,"threshold_uncertainty_score":0.5401619},"labels":[],"label_agreement":null},{"id":"W2949992076","doi":"","title":"Variability of basal ganglia morphology after spatial normalization: Implications for group studies","year":2010,"lang":"en","type":"article","venue":"CMBES Proceedings","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Normalization (sociology); Morphology (biology); Basal ganglia; Biology; Zoology; Neuroscience; Central nervous system; Anthropology","score_opus":0.05948938173205512,"score_gpt":0.3802843787120086,"score_spread":0.3207949969799535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949992076","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92740166,0.000036602847,0.06452754,0.0058911936,0.000112101945,0.0010768931,0.000053245807,0.00018526032,0.0007155116],"genre_scores_gemma":[0.9399388,0.000023773204,0.05817393,0.0006528947,0.0001859421,0.00092291797,0.00001934994,0.00002068451,0.00006173498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924904,0.0000022811432,0.0002568486,0.00027660333,0.00006201724,0.00015320619],"domain_scores_gemma":[0.99893254,0.00007286675,0.000113146096,0.00019556396,0.0006283259,0.00005757838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001656506,0.000107876695,0.00021752928,0.000056476707,0.00007926363,0.000006558214,0.000093726274,0.00007241124,0.000023273087],"category_scores_gemma":[0.00042307185,0.00009649365,0.000066602086,0.00016281851,0.00023263195,0.00009177566,0.000060509956,0.00013672357,0.0000015937972],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017972267,0.00032100847,0.5073062,0.000419532,0.00003921413,5.476102e-7,0.00028962764,2.4589417e-7,0.3917631,0.0914458,0.006183315,0.0020516452],"study_design_scores_gemma":[0.0011343124,0.00049515633,0.7395653,0.00006804531,0.00025679346,0.000052561376,0.0001045106,0.0003447168,0.0610485,0.18179625,0.0148327695,0.0003010933],"about_ca_topic_score_codex":0.0000044074286,"about_ca_topic_score_gemma":0.0000029461917,"teacher_disagreement_score":0.33071458,"about_ca_system_score_codex":0.000017582948,"about_ca_system_score_gemma":0.000021365742,"threshold_uncertainty_score":0.3934897},"labels":[],"label_agreement":null},{"id":"W2950007767","doi":"10.1101/547588","title":"White matter changes in the perforant path in patients with amyotrophic lateral sclerosis","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Nederland; Alzheimer Society","keywords":"Amyotrophic lateral sclerosis; Fractional anisotropy; White matter; Frontotemporal dementia; Neuroscience; Psychology; Perforant path; Pathology; Hippocampal formation; Hippocampus; Diffusion MRI; Chemistry; Dementia; Medicine; Disease; Magnetic resonance imaging; Dentate gyrus; Radiology","score_opus":0.026160296775236836,"score_gpt":0.23843515976293797,"score_spread":0.21227486298770112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950007767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99500567,0.000073008116,0.0002143294,0.0024605694,0.000093878116,0.0019138171,0.00009795692,0.00013097377,0.00000979484],"genre_scores_gemma":[0.99339104,0.000113555274,0.0039576245,0.0017428375,0.00009129007,0.0005932015,0.00000159333,0.000103638464,0.000005251086],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99810725,0.00007498303,0.00031744313,0.0007350935,0.0003414357,0.00042380852],"domain_scores_gemma":[0.9981893,0.000024736408,0.00020730293,0.0013398835,0.00016088391,0.00007792586],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023553407,0.00038990323,0.00047211244,0.00028289694,0.000054585165,0.00007219796,0.0003683138,0.00020304724,0.00003210406],"category_scores_gemma":[0.000014663802,0.00028263123,0.000059174636,0.00047092847,0.000079636906,0.000074147836,0.00020986653,0.0009792399,0.00004041717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078592275,0.0002647949,0.9953342,0.00022590846,0.000013056172,0.00001901168,0.000022331746,0.000031861226,0.0038162058,0.00003069088,0.00016175635,0.0000015639174],"study_design_scores_gemma":[0.0010096926,0.00012619815,0.99542546,0.0011125637,0.000046558605,1.7233457e-8,0.0000016458063,0.0001590966,0.001318684,0.0000017027454,0.0004749967,0.0003233813],"about_ca_topic_score_codex":0.00003171382,"about_ca_topic_score_gemma":0.0000043575997,"teacher_disagreement_score":0.003743295,"about_ca_system_score_codex":0.00016738118,"about_ca_system_score_gemma":0.00011086917,"threshold_uncertainty_score":0.99996257},"labels":[],"label_agreement":null},{"id":"W2950133780","doi":"10.1016/j.bpsc.2019.05.016","title":"White Matter Indices of Medication Response in Major Depression: A Diffusion Tensor Imaging Study","year":2019,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network; St. Michael's Hospital; Queen's University; McMaster University; University of Alberta; Baycrest Hospital; University of Calgary; University of British Columbia; St. Joseph’s Healthcare Hamilton","funders":"Janssen Pharmaceuticals; Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; St. Jude Medical; Janssen Biotech; Johnson and Johnson; Sunovion; H. Lundbeck A/S; Servier; Leading Edge Endowment Fund; Otsuka America; Victoria General Hospital Foundation; Allergan; Canadian Psychiatric Association; Ontario Mental Health Foundation; Hamilton Health Sciences Foundation; Alkermes; Bristol-Myers Squibb; Government of Ontario; Canadian Network for Mood and Anxiety Treatments; AllerGen; Pfizer; Ontario Brain Institute; University Health Network; Fondation Brain Canada; Abbott Laboratories; Merck; Hamilton Health Sciences; Akili Interactive Labs; Shire","keywords":"Diffusion MRI; White matter; Depression (economics); Medicine; White (mutation); Psychiatry; Psychology; Magnetic resonance imaging; Radiology; Chemistry; Economics","score_opus":0.04691694577998693,"score_gpt":0.35836275280229446,"score_spread":0.3114458070223075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950133780","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99427104,0.00012266703,0.00048170032,0.0034393447,0.00015459333,0.001102709,0.000009643843,0.000077507415,0.00034079893],"genre_scores_gemma":[0.9948098,0.000058970963,0.00049358356,0.0044963723,0.000025518662,0.00005275862,0.0000035902344,0.000015615457,0.00004380861],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99807864,0.00020295377,0.00037760622,0.00082232826,0.00024217044,0.00027628976],"domain_scores_gemma":[0.9991485,0.00021732057,0.00019335159,0.00027039467,0.00006291162,0.00010752481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035607154,0.00019239912,0.00029570897,0.00027842447,0.00010905633,0.000024748942,0.00016296217,0.000037784615,0.00003711923],"category_scores_gemma":[0.00021307601,0.00014217816,0.000051245475,0.00051083614,0.00031210645,0.00018033978,0.00019392445,0.00032767362,0.000010320939],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075184315,0.00054831756,0.9575452,0.00001996514,9.174198e-7,0.000019962632,0.00008306189,4.3637573e-7,0.040035117,0.000008843416,0.000021130183,0.00096521474],"study_design_scores_gemma":[0.0014125942,0.00058425934,0.9960635,0.00017682172,0.000019406463,0.00012144583,0.00049252075,0.00047694042,0.0002652589,0.00017604965,0.0000707334,0.00014047293],"about_ca_topic_score_codex":0.000005915896,"about_ca_topic_score_gemma":5.0704057e-7,"teacher_disagreement_score":0.039769858,"about_ca_system_score_codex":0.000009679063,"about_ca_system_score_gemma":0.000040650364,"threshold_uncertainty_score":0.57978576},"labels":[],"label_agreement":null},{"id":"W2950351598","doi":"10.1101/661348","title":"A data-driven approach to optimising the encoding for multi-shell diffusion MRI with application to neonatal imaging","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"Centre For Medical Engineering, King’s College London; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; European Commission; King's College London; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Human Connectome Project; Diffusion MRI; Computer science; Data acquisition; Encoding (memory); Diffusion; Shell (structure); Protocol (science); Data mining; Diffusion imaging; Pattern recognition (psychology); Artificial intelligence; Algorithm; Magnetic resonance imaging; Physics; Radiology; Engineering; Pathology; Medicine","score_opus":0.06284205203733073,"score_gpt":0.3156799636398977,"score_spread":0.25283791160256697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950351598","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025542622,0.00014133031,0.9635745,0.002105439,0.0001186026,0.0072821304,0.00060251163,0.0006135003,0.00001930654],"genre_scores_gemma":[0.4586904,0.000035785273,0.53832215,0.0009561253,0.00023715131,0.0015873569,0.000011009612,0.00015161728,0.000008427924],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99685526,0.00003701876,0.00044131954,0.0017322319,0.00036267564,0.0005714807],"domain_scores_gemma":[0.9952697,0.00008907965,0.00030868273,0.0035955994,0.0004273139,0.00030958274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004595204,0.00051216787,0.00053128967,0.00024167131,0.00032914313,0.00017622962,0.0011239839,0.00015408003,0.0000016920421],"category_scores_gemma":[0.00012928685,0.00040891446,0.00009556531,0.00053416,0.00007694774,0.00015107438,0.0015226746,0.0006564159,0.000022110922],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036096468,0.00066118175,0.006659836,0.0012512918,0.0001519601,0.000014815328,0.000106519816,0.01729023,0.9692897,0.0016247708,0.0023685992,0.00022010667],"study_design_scores_gemma":[0.0019025436,0.00016286413,0.015944887,0.0015137544,0.0005926413,8.4841736e-7,0.00004194569,0.82707596,0.059846453,0.0000037397865,0.09134645,0.0015679096],"about_ca_topic_score_codex":0.000028288832,"about_ca_topic_score_gemma":0.0000011310663,"teacher_disagreement_score":0.90944326,"about_ca_system_score_codex":0.0002549436,"about_ca_system_score_gemma":0.00027800666,"threshold_uncertainty_score":0.99983627},"labels":[],"label_agreement":null},{"id":"W2950396589","doi":"10.1016/j.dcn.2017.12.002","title":"Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress","year":2017,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute for Health and Care Research","keywords":"Diffusion MRI; Neuroimaging; Psychology; White matter; Brain development; Popularity; Data science; Neuroscience; Cognitive psychology; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.1406222692049797,"score_gpt":0.4381496966508886,"score_spread":0.2975274274459089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950396589","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029632403,0.99403894,0.0004245012,0.000150821,0.00006159316,0.0020179302,0.000036701123,0.000040515355,0.00026578575],"genre_scores_gemma":[0.0022450276,0.94471663,0.05251504,0.00018848147,0.000010822728,0.00018950392,0.000022983739,0.000035747704,0.00007577197],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99805564,0.00008415119,0.00048182253,0.0008872731,0.00021101083,0.00028009457],"domain_scores_gemma":[0.999156,0.00006759883,0.0003915855,0.0001966443,0.0000650922,0.00012306303],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022404517,0.00038602928,0.0009446335,0.00025630317,0.00026939638,0.00003095215,0.00021962242,0.00012736785,0.00000300073],"category_scores_gemma":[0.000103680555,0.00030916533,0.000051740615,0.00017436863,0.0007221234,0.0001155074,0.0007179212,0.0004303052,0.0000016189432],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006938147,0.00008948877,0.009661344,0.0033052347,0.0000042008724,0.000022665035,0.00051157887,1.0622635e-9,0.00006832066,0.000009928456,0.0000034680288,0.98631686],"study_design_scores_gemma":[0.00042874814,0.00006498784,0.7563774,0.02334229,0.00008929925,0.0010926101,0.000072436604,0.0000015678012,0.00031643064,0.000053272273,0.21773376,0.00042720165],"about_ca_topic_score_codex":5.800102e-7,"about_ca_topic_score_gemma":0.0000011703444,"teacher_disagreement_score":0.9858896,"about_ca_system_score_codex":0.000043525302,"about_ca_system_score_gemma":0.00025294506,"threshold_uncertainty_score":0.99993604},"labels":[],"label_agreement":null},{"id":"W2951010418","doi":"10.1101/424150","title":"Structural connectivity analysis using Finsler geometry","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Geodesic; Tractography; Metric (unit); Finsler manifold; Computer science; Diffusion MRI; Connectome; Population; Riemannian geometry; Human Connectome Project; Mathematics; Artificial intelligence; Functional connectivity; Geometry; Psychology; Neuroscience; Magnetic resonance imaging; Engineering; Medicine","score_opus":0.0570971091719142,"score_gpt":0.31910423698519813,"score_spread":0.26200712781328395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951010418","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95309865,0.00024547055,0.04439102,0.00019307433,0.0002784743,0.00075093296,0.00024606375,0.0007862558,0.000010040997],"genre_scores_gemma":[0.91743535,0.00005222995,0.08146314,0.00032388058,0.0005247713,0.00008368426,0.0000010822026,0.00011133253,0.000004513134],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99740684,0.00006403091,0.00047122987,0.0011971928,0.0003696386,0.0004910593],"domain_scores_gemma":[0.99656093,0.00006225972,0.00043841833,0.0020370523,0.00060936733,0.00029197056],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027717455,0.00051684835,0.000884141,0.00071160856,0.0002298939,0.00010151688,0.0003483291,0.00040929834,0.00013096341],"category_scores_gemma":[0.00022065845,0.00052972935,0.00039077268,0.0017241876,0.00023542355,0.000110024266,0.0005417216,0.00088560267,0.000021409911],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008393284,0.00023149625,0.25417256,0.000533552,0.0018645312,0.00011284372,0.000007819884,0.00046525878,0.7412499,0.0007721616,0.0004984458,0.000007478142],"study_design_scores_gemma":[0.0006140011,0.000086284184,0.72955775,0.0003197862,0.0039049883,1.6540356e-7,0.000001451747,0.031068044,0.23089944,0.000032135355,0.0023405636,0.0011753715],"about_ca_topic_score_codex":0.000060750506,"about_ca_topic_score_gemma":9.965535e-7,"teacher_disagreement_score":0.51035047,"about_ca_system_score_codex":0.00034436226,"about_ca_system_score_gemma":0.0003249371,"threshold_uncertainty_score":0.99971545},"labels":[],"label_agreement":null},{"id":"W2951189597","doi":"10.1038/tp.2017.92","title":"The effect of crack cocaine addiction and age on the microstructure and morphology of the human striatum and thalamus using shape analysis and fast diffusion kurtosis imaging","year":2017,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"Striatum; Thalamus; Nucleus accumbens; Ventral striatum; Kurtosis; Neuroscience; Addiction; Magnetic resonance imaging; Psychology; Cocaine dependence; Brain morphometry; Medicine; Dopamine; Radiology; Mathematics","score_opus":0.022930719908856142,"score_gpt":0.3311533694720586,"score_spread":0.30822264956320244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951189597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921668,0.0006588447,0.0005324489,0.006169807,0.00003122155,0.0003285279,0.000047472204,0.000008834855,0.000056018114],"genre_scores_gemma":[0.9987454,0.00012915935,0.00097145495,0.00008540131,0.000036830435,0.0000055808673,0.000009064324,0.000008644179,0.000008486491],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994279,0.00004877226,0.00016374726,0.00017979756,0.00010469875,0.00007506245],"domain_scores_gemma":[0.999314,0.00016609055,0.00018510947,0.0002863553,0.000023815786,0.000024633515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014977054,0.000101574326,0.00017612355,0.00004701451,0.0006953385,0.00002568089,0.00007366202,0.0000371791,0.0000043514124],"category_scores_gemma":[0.000019249203,0.000052282638,0.000052834126,0.00008099335,0.00052278605,0.000038055427,0.00003431304,0.00015835524,1.5943112e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000100261605,0.000015321913,0.8711351,0.00003375556,0.00008458572,3.264935e-7,0.00007364627,0.000007750362,0.12155109,0.0016324164,0.00002608346,0.0053396528],"study_design_scores_gemma":[0.0006885892,0.00006567542,0.9902287,0.0000653128,0.0004986097,0.000025406729,0.000016951704,0.0041448413,0.0014022477,0.002782078,0.000035645193,0.00004591283],"about_ca_topic_score_codex":0.000030682288,"about_ca_topic_score_gemma":0.00002138115,"teacher_disagreement_score":0.12014884,"about_ca_system_score_codex":0.0000031279212,"about_ca_system_score_gemma":0.000008172569,"threshold_uncertainty_score":0.5348051},"labels":[],"label_agreement":null},{"id":"W2951290748","doi":"10.1016/j.neuroimage.2017.07.028","title":"Fiber tractography using machine learning","year":2017,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Deutsche Forschungsgemeinschaft","keywords":"Tractography; Computer science; Artificial intelligence; Random forest; Diffusion MRI; Imaging phantom; Fiber; Pattern recognition (psychology); Machine learning; Chemistry; Medicine; Nuclear medicine; Magnetic resonance imaging","score_opus":0.1365906204835527,"score_gpt":0.3990254124329575,"score_spread":0.26243479194940483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951290748","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94745016,0.00012551714,0.0075935195,0.0036453553,0.00009515308,0.0005758782,0.000017970597,0.00079320895,0.039703265],"genre_scores_gemma":[0.96858925,0.00006226675,0.02866706,0.00051038596,0.00010139753,0.0000112238295,0.000008944183,0.000048700447,0.0020007999],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99926907,0.000014955367,0.00012751113,0.00027852642,0.00012323889,0.00018668918],"domain_scores_gemma":[0.99899954,0.000023719582,0.00012734975,0.00071973115,0.000039364895,0.00009031991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000056926583,0.00011840239,0.00015468859,0.0000686363,0.0005137652,0.00007033753,0.00016287045,0.000032616037,0.00012442272],"category_scores_gemma":[0.000121856734,0.000110736044,0.000102222504,0.000059840873,0.00011851962,0.00015536012,0.00008611598,0.00038120453,0.000037741],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001023878,0.00033785155,0.22578153,0.00008467885,0.000027534952,0.0005048243,0.000052527117,0.000041948482,0.72194165,0.0006963029,0.0011282412,0.049300537],"study_design_scores_gemma":[0.0015183673,0.00029767345,0.36673164,0.00010520764,0.00017143776,0.0007449884,0.000007145674,0.015497478,0.04516471,0.001089999,0.5682225,0.00044880118],"about_ca_topic_score_codex":0.000041195068,"about_ca_topic_score_gemma":8.5373733e-7,"teacher_disagreement_score":0.67677695,"about_ca_system_score_codex":0.000009465392,"about_ca_system_score_gemma":0.000013163812,"threshold_uncertainty_score":0.45156848},"labels":[],"label_agreement":null},{"id":"W2951488689","doi":"10.3389/fninf.2019.00002","title":"Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; BioClinica; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Clinical Dementia Rating; Fornix; Neuroimaging; Cingulum (brain); Dementia; Psychology; Cognitive impairment; Medicine; Cognition; Neuroscience; Magnetic resonance imaging; Disease; Pathology; Radiology; Hippocampus","score_opus":0.02635451086619333,"score_gpt":0.31591104852532836,"score_spread":0.289556537659135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951488689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83916175,0.000013845311,0.091705725,0.0025616756,0.000061704224,0.06540576,0.000014776018,0.00010100538,0.00097375934],"genre_scores_gemma":[0.90079254,0.000043357937,0.081150815,0.003385513,0.000017967934,0.014326602,0.00008801344,0.00004313346,0.00015208306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989676,0.000051322702,0.0004304554,0.00019785686,0.0001298144,0.00022298403],"domain_scores_gemma":[0.9994531,0.000074673924,0.00013062003,0.00026099719,0.00002189572,0.00005871473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002755263,0.00015838328,0.00023392614,0.00035268898,0.000041340343,0.00002403011,0.00011950643,0.000059551196,0.0000023219245],"category_scores_gemma":[0.000056855915,0.00011189764,0.000024715931,0.00054096873,0.000049728427,0.00020574374,0.00012225677,0.0004213719,0.0000036489914],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003825402,0.00060961215,0.96320766,0.0003239137,0.000009819079,0.0000093224235,0.015246149,0.001477384,0.00044909146,0.00015899363,0.0034723843,0.014653105],"study_design_scores_gemma":[0.004241805,0.00025193839,0.51112497,0.00035527095,0.0000069773187,0.000020364363,0.0052064275,0.47364956,0.0003064428,0.00033985014,0.0042957272,0.00020065105],"about_ca_topic_score_codex":0.000010207654,"about_ca_topic_score_gemma":0.00000525724,"teacher_disagreement_score":0.4721722,"about_ca_system_score_codex":0.00007621343,"about_ca_system_score_gemma":0.000028156604,"threshold_uncertainty_score":0.45630535},"labels":[],"label_agreement":null},{"id":"W2951503675","doi":"10.1101/232439","title":"Shape-related characteristics of age-related differences in subcortical structures","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Sphericity; Curse of dimensionality; Fractal dimension; Fractal; Brain size; Measure (data warehouse); Curvature; Volume (thermodynamics); Mathematics; Psychology; Statistics; Computer science; Medicine; Geometry; Physics; Mathematical analysis; Magnetic resonance imaging","score_opus":0.044141022166421566,"score_gpt":0.2950998302017782,"score_spread":0.25095880803535664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951503675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99719185,0.00028271475,0.0003711601,0.00041808942,0.00030038986,0.00088325026,0.00016452733,0.00036191562,0.000026078971],"genre_scores_gemma":[0.99326,0.00049090805,0.005885162,0.000059905873,0.0000806077,0.00011798388,0.0000019071248,0.00009423396,0.000009276755],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9975266,0.00005740165,0.00090657955,0.00079598033,0.00031635156,0.00039708492],"domain_scores_gemma":[0.99707836,0.000065719294,0.0007658497,0.0016203442,0.00026509035,0.00020462715],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020453053,0.00045047974,0.0010220053,0.00028830813,0.00009835467,0.000049440936,0.0005382089,0.00058025686,0.000060553684],"category_scores_gemma":[0.00041636213,0.00043508914,0.00016703764,0.00024719644,0.0004549437,0.000067384804,0.00040912666,0.0013270584,0.000009010668],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010919688,0.00052619405,0.36916357,0.00093275,0.00021699128,0.0005604994,0.000022756254,0.0000033232986,0.6162148,0.012114241,0.000082022656,0.00005364175],"study_design_scores_gemma":[0.0005339882,0.00006510249,0.96927845,0.0008295954,0.00017099081,1.1173501e-7,7.678703e-7,0.000884258,0.02748406,0.00017325694,0.00018811543,0.0003913267],"about_ca_topic_score_codex":0.0000345294,"about_ca_topic_score_gemma":5.218578e-7,"teacher_disagreement_score":0.6001149,"about_ca_system_score_codex":0.00011387925,"about_ca_system_score_gemma":0.00030082284,"threshold_uncertainty_score":0.9998101},"labels":[],"label_agreement":null},{"id":"W2951540119","doi":"10.7554/elife.26653","title":"Anatomical and functional organization of the human substantia nigra and its connections","year":2017,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":150,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Neuroscience; Substantia nigra; Salience (neuroscience); Striatum; Psychology; Impulsivity; Human brain; Ventral striatum; Basal ganglia; Human Connectome Project; Putamen; Functional connectivity; Biology; Dopamine; Dopaminergic; Central nervous system; Developmental psychology","score_opus":0.06987130663645406,"score_gpt":0.34711368151375155,"score_spread":0.27724237487729747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951540119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952182,0.0000456795,0.0010354803,0.0032687543,0.00002109604,0.00011862827,0.000005789933,0.00003162652,0.00025474574],"genre_scores_gemma":[0.9993409,0.0000632074,0.0002501661,0.00014745054,0.00003356983,0.000003316886,0.000003965806,0.00000637157,0.00015104271],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997459,0.000004527547,0.0000654376,0.000085778316,0.000060723807,0.000037646932],"domain_scores_gemma":[0.99965537,0.000011877381,0.000054835375,0.00017775524,0.000073230694,0.000026912883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028201646,0.000033660355,0.000056478086,0.000015980939,0.0003352861,0.000010423556,0.000031868487,0.000019474082,0.000014470065],"category_scores_gemma":[0.00010719155,0.00002496079,0.000009563164,0.000044691536,0.00008507595,0.000037878668,0.00004351615,0.000059800273,6.563452e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052679716,0.00005432265,0.64256024,0.000021042219,0.000012634995,7.7283056e-7,0.000049263774,9.0797937e-7,0.26447132,0.090508446,0.0019428227,0.00037297278],"study_design_scores_gemma":[0.00023179447,0.000011961219,0.9265506,0.000016170734,0.000022475298,0.000029815308,0.000008929255,0.0001175593,0.07022388,0.0005945305,0.0021633576,0.000028888659],"about_ca_topic_score_codex":0.0000053345443,"about_ca_topic_score_gemma":0.0000030706224,"teacher_disagreement_score":0.2839904,"about_ca_system_score_codex":0.000004555636,"about_ca_system_score_gemma":0.000011118306,"threshold_uncertainty_score":0.25787836},"labels":[],"label_agreement":null},{"id":"W2951566176","doi":"10.1016/j.neuroimage.2018.10.033","title":"Axons morphometry in the human spinal cord","year":2018,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Trois-Rivières; Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Multiple Sclerosis Society of Canada; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Axon; Spinal cord; Anatomy; Myelin; Neuroscience; Magnetic resonance imaging; Central nervous system; Biology; Medicine; Radiology","score_opus":0.14608111365162862,"score_gpt":0.4319122923201034,"score_spread":0.2858311786684748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951566176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9345333,0.00002945361,0.0073989537,0.008924214,0.00006819046,0.000677864,0.000007896537,0.0002862765,0.048073877],"genre_scores_gemma":[0.99109596,0.000009495154,0.003054478,0.0052629793,0.00019923339,0.000045633744,0.000005331247,0.000019728826,0.00030713412],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99923027,0.000029635261,0.00014980951,0.0002472167,0.00015334642,0.00018972335],"domain_scores_gemma":[0.99928766,0.000030449783,0.000039837665,0.0005683496,0.00003069867,0.00004300324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010891729,0.0000959919,0.00011377329,0.000104634695,0.00013416652,0.0000200577,0.00019829583,0.000024889589,0.0000746715],"category_scores_gemma":[0.000053742613,0.00007063855,0.000045194512,0.00042818903,0.00021608811,0.00004962246,0.000049825445,0.00029413693,0.000076714976],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045847712,0.0014989224,0.07144811,0.000097813296,0.0000134202555,0.0010817951,0.0002441474,4.370049e-7,0.69913036,0.07710256,0.1186593,0.03026466],"study_design_scores_gemma":[0.00084678107,0.0024317931,0.7689084,0.00006233459,0.000038644226,0.00064983027,0.00007841945,0.00010272731,0.009796959,0.009017353,0.20785472,0.00021203766],"about_ca_topic_score_codex":0.000014944935,"about_ca_topic_score_gemma":0.0000040726645,"teacher_disagreement_score":0.6974603,"about_ca_system_score_codex":0.000020399984,"about_ca_system_score_gemma":0.000013306464,"threshold_uncertainty_score":0.28805563},"labels":[],"label_agreement":null},{"id":"W2951846649","doi":"10.1101/392571","title":"Limits to anatomical accuracy of diffusion tractography using modern approaches","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; Vanderbilt Institute for Clinical and Translational Research; National Institutes of Health; Vanderbilt University","keywords":"Tractography; Diffusion MRI; Computer science; Artificial intelligence; White matter; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.10965666558173885,"score_gpt":0.3205598659333588,"score_spread":0.2109032003516199,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951846649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9033651,0.00023169945,0.09392031,0.00037347263,0.00013885535,0.0013782026,0.0001307733,0.00045054074,0.00001109437],"genre_scores_gemma":[0.84267145,0.00009047717,0.15648073,0.00022572433,0.00026245601,0.00014096311,5.432826e-7,0.000126767,9.1426523e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975292,0.000049958344,0.0005986749,0.0010207198,0.00038069175,0.00042074273],"domain_scores_gemma":[0.9970046,0.00007604426,0.00045314874,0.0016758835,0.00041885444,0.00037146662],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023059404,0.00046934464,0.00071795104,0.0004889186,0.00011204966,0.00004788064,0.00043142648,0.00039890126,0.00001127884],"category_scores_gemma":[0.0002690436,0.00047548497,0.00025643434,0.0006967628,0.00019182928,0.00009224022,0.0004659804,0.000697956,0.000007228303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008337033,0.00045470646,0.010244031,0.00039369968,0.00006619876,0.000012271592,0.000012356321,0.00003727505,0.9881951,0.00033539307,0.00013663931,0.000028958151],"study_design_scores_gemma":[0.0006398472,0.00017253423,0.10634004,0.0013230286,0.0003886471,1.5429974e-7,0.0000026052173,0.017177474,0.8709561,0.00005805538,0.0021080177,0.0008334981],"about_ca_topic_score_codex":0.000021311978,"about_ca_topic_score_gemma":2.7397016e-7,"teacher_disagreement_score":0.117239006,"about_ca_system_score_codex":0.00013303569,"about_ca_system_score_gemma":0.00029636407,"threshold_uncertainty_score":0.9997697},"labels":[],"label_agreement":null},{"id":"W2951906816","doi":"10.1101/402255","title":"Deep Learning for Quality Control of Subcortical Brain 3D Shape Models","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Artificial intelligence; Computer science; Deep learning; Convolutional neural network; Residual neural network; Feature (linguistics); Grey matter; Pattern recognition (psychology); Human Connectome Project; Machine learning; Neuroscience; Functional connectivity; Magnetic resonance imaging; Psychology; White matter; Medicine","score_opus":0.062254647520927985,"score_gpt":0.3322475259131574,"score_spread":0.26999287839222946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951906816","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23068336,0.00032255374,0.7654902,0.00093606143,0.00013591285,0.0017214825,0.00011104437,0.00058549887,0.000013894109],"genre_scores_gemma":[0.89316154,0.0000916996,0.105120875,0.0005553123,0.00032988057,0.000604821,0.0000010339626,0.00012920484,0.0000056438344],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974208,0.00010453881,0.00078727445,0.0009012099,0.00032628977,0.0004598959],"domain_scores_gemma":[0.996708,0.00035558088,0.0005634171,0.0011861441,0.0009328413,0.00025403142],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00072052237,0.0004018104,0.0008737349,0.0001602493,0.00013057671,0.000035593283,0.0003214747,0.0003937624,0.000029527577],"category_scores_gemma":[0.001030266,0.00042065023,0.00026929227,0.00023351508,0.0002650173,0.000083357234,0.00022653394,0.0007581159,0.0000075021667],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006068413,0.00062954135,0.011946292,0.0019709808,0.00029444683,0.000016523836,0.000014638734,0.0009930646,0.96565515,0.017278276,0.0005319859,0.00006226659],"study_design_scores_gemma":[0.004664299,0.0007435893,0.073016144,0.0012428114,0.00087444927,1.1648323e-7,0.000004358052,0.71678615,0.1905676,0.0004529151,0.010106453,0.0015410882],"about_ca_topic_score_codex":0.000012340191,"about_ca_topic_score_gemma":3.274632e-7,"teacher_disagreement_score":0.77508754,"about_ca_system_score_codex":0.00013048429,"about_ca_system_score_gemma":0.00028593975,"threshold_uncertainty_score":0.9998245},"labels":[],"label_agreement":null},{"id":"W2951972782","doi":"10.1002/jmri.26794","title":"Tractography reproducibility challenge with empirical data (TraCED): The 2017 ISMRM diffusion study group challenge","year":2019,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; Vanderbilt University; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Reproducibility; Context (archaeology); Intraclass correlation; Computer science; Diffusion MRI; Tractography; Similarity (geometry); Artificial intelligence; Nuclear medicine; Statistics; Magnetic resonance imaging; Medicine; Mathematics; Radiology","score_opus":0.2806202968680405,"score_gpt":0.45689265641747934,"score_spread":0.17627235954943882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951972782","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012663715,0.9887651,0.0005042124,0.0063458025,0.00017935377,0.0031251612,0.000040550916,0.00007006395,0.00084308774],"genre_scores_gemma":[0.0012671283,0.99423873,0.0033169417,0.0001724551,0.0006466842,0.00008757003,0.000026066195,0.0001196219,0.00012479759],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9948288,0.00037758955,0.001589428,0.0017213575,0.0010100771,0.0004727231],"domain_scores_gemma":[0.99048615,0.00045671515,0.0016698117,0.0068985587,0.0002977298,0.00019101582],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0028508226,0.00063525763,0.0022183522,0.00031311082,0.00024074299,0.00008981135,0.001777583,0.00012245668,0.00003364381],"category_scores_gemma":[0.00039554847,0.0003450925,0.00050501403,0.0005837708,0.0003064924,0.00033280466,0.0005627073,0.0024995327,0.00000971927],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009206074,0.0016879772,0.0011636737,0.0019765852,0.000042581403,0.00037695648,0.00016900123,1.3697434e-7,8.4326985e-7,0.000011584143,0.00240156,0.99207705],"study_design_scores_gemma":[0.0009882671,0.0015241354,0.005852502,0.009730796,0.0018688587,0.003007138,0.00019111916,0.00006374654,1.3638663e-7,0.00008267291,0.9763513,0.0003393356],"about_ca_topic_score_codex":0.000010488529,"about_ca_topic_score_gemma":0.0000062548625,"teacher_disagreement_score":0.9917377,"about_ca_system_score_codex":0.00009778592,"about_ca_system_score_gemma":0.0002604117,"threshold_uncertainty_score":0.9999001},"labels":[],"label_agreement":null},{"id":"W2952148882","doi":"10.1016/j.neuroimage.2019.06.016","title":"Reducing variability in along-tract analysis with diffusion profile realignment","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; Fonds de recherche du Québec – Nature et technologies; McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Diffusion; Phase (matter); Computer science; Geology; Chemistry; Physics; Thermodynamics","score_opus":0.02698230986161734,"score_gpt":0.3208204024195131,"score_spread":0.2938380925578958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952148882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9827345,0.0000049811542,0.00704996,0.0010145232,0.00001706524,0.00092511356,0.000011078094,0.00017644791,0.008066301],"genre_scores_gemma":[0.98696035,0.000017288201,0.012014356,0.00031259222,0.000019230169,0.00007238697,0.000043826247,0.000024645322,0.0005353166],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987015,0.000064468695,0.00024644134,0.00055160787,0.00021934105,0.00021663748],"domain_scores_gemma":[0.99885285,0.00010027019,0.00008799556,0.00083895895,0.00004089784,0.00007901984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025234357,0.00013876482,0.0002947224,0.00017441295,0.00003609274,0.000014185658,0.00009204792,0.00003679766,0.00015318386],"category_scores_gemma":[0.000057424044,0.000110662884,0.000076538876,0.00081477006,0.000039421506,0.00008784718,0.000055295142,0.0002672733,0.000025821482],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011588026,0.0007100288,0.85563093,0.00006814977,0.000024716894,0.000093136536,0.0000752041,0.00019019721,0.139249,0.00031213468,0.00015505309,0.0033755873],"study_design_scores_gemma":[0.00062004547,0.00023943537,0.98130804,0.000052779982,0.00018597888,0.00004371253,0.000015678686,0.006374575,0.009489525,0.00016214668,0.0013592948,0.00014877277],"about_ca_topic_score_codex":0.00012206292,"about_ca_topic_score_gemma":0.0000051789257,"teacher_disagreement_score":0.12975948,"about_ca_system_score_codex":0.000070885464,"about_ca_system_score_gemma":0.000035758017,"threshold_uncertainty_score":0.45127013},"labels":[],"label_agreement":null},{"id":"W2952326196","doi":"10.1101/677153","title":"Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; Lawson Health Research Institute; Western University","funders":"National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Medical Research Council; Clinical Science Research and Development; National Institutes of Health; Congressionally Directed Medical Research Programs; Bill and Melinda Gates Foundation; ZonMw; National Alliance for Research on Schizophrenia and Depression; Canadian Institute for Military and Veteran Health Research; Chinese Academy of Sciences; Division of Research Capacity Development; Deutsche Forschungsgemeinschaft; National Research Foundation; Yale Center for Clinical Investigation, Yale School of Medicine; Institute for Clinical and Translational Research, University of Wisconsin, Madison; Medical Research and Materiel Command; National Natural Science Foundation of China; Georgia Clinical and Translational Science Alliance; Waisman Center; Yale University; U.S. Department of Veterans Affairs; Office of Research and Development; Michael J. Fox Foundation for Parkinson's Research; Traumatic Brain Injury Center of Excellence; South African Medical Research Council; U.S. Department of Defense; National Center for PTSD, U.S. Department of Veterans Affairs; Canadian Institutes of Health Research; National Science Foundation","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Neuroimaging; Psychology; Depression (economics); Brain Structure and Function; Tractography; Psychiatry; Traumatic stress; Confounding; Clinical psychology; Medicine; Neuroscience; Internal medicine; Magnetic resonance imaging","score_opus":0.01758380025829856,"score_gpt":0.26954051819305536,"score_spread":0.2519567179347568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952326196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98560774,0.00027101624,0.0017896941,0.004038016,0.0004904802,0.0022873406,0.0051031127,0.000408039,0.000004564819],"genre_scores_gemma":[0.9905422,0.00015711255,0.006916939,0.00162062,0.00030931467,0.00017102876,0.00006181185,0.00020439684,0.00001663085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99672794,0.00011923939,0.00096058,0.0012623008,0.00034243058,0.00058748067],"domain_scores_gemma":[0.9958187,0.00016244808,0.0006585337,0.0023609507,0.00084858807,0.00015082402],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022048931,0.0006055242,0.0006755819,0.000116304844,0.00018656958,0.00022393427,0.00066727016,0.00040961,0.00008517381],"category_scores_gemma":[0.0004266014,0.0005078495,0.00010377206,0.00072009175,0.00020393834,0.00016457964,0.00060920854,0.0011943927,0.00011908668],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000410524,0.00033899918,0.82626003,0.000583014,0.00013438659,0.00003870416,0.0008485569,0.00023695026,0.16946329,0.000040400882,0.0016335506,0.000011613287],"study_design_scores_gemma":[0.0018848778,0.00004224916,0.9631295,0.0013338713,0.000103947015,1.718136e-7,0.00013601422,0.00044360058,0.031686172,0.0000028799398,0.0006671961,0.0005694932],"about_ca_topic_score_codex":0.0007625106,"about_ca_topic_score_gemma":0.00008314421,"teacher_disagreement_score":0.13777712,"about_ca_system_score_codex":0.0002216428,"about_ca_system_score_gemma":0.000292001,"threshold_uncertainty_score":0.9997373},"labels":[],"label_agreement":null},{"id":"W2952355381","doi":"10.1016/j.neuroimage.2019.04.004","title":"Global and regional white matter development in early childhood","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":134,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Foundation; University of Calgary","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Brain development; Early childhood; Developmental psychology; Tractography; Psychology; Pediatrics; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.026618182018506444,"score_gpt":0.2961953305486827,"score_spread":0.2695771485301762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952355381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889117,0.000024937532,0.00035704,0.0030020336,0.000017952727,0.00035379588,0.0000031132809,0.00007885352,0.0072505684],"genre_scores_gemma":[0.9837423,0.000012138934,0.011644878,0.0037580575,0.000018023036,0.000023024279,0.000006824249,0.000015051886,0.00077970105],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99931574,0.000008969027,0.00013414164,0.00028194016,0.000107830594,0.0001513525],"domain_scores_gemma":[0.9996603,0.000009994921,0.000029231536,0.00022489956,0.000016395192,0.000059145772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031241463,0.00009335833,0.00012020279,0.00004374129,0.000022698956,0.000013477539,0.00005517977,0.00002557725,0.000059001],"category_scores_gemma":[0.000004730776,0.00008822993,0.000019237672,0.00013829602,0.00002902682,0.00006594951,0.000058898615,0.000119027834,0.00014895125],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013598368,0.000070171074,0.9956298,0.00001300243,0.0000017138954,0.000021107211,0.00008042355,8.9100445e-7,0.00072687917,0.00025181653,0.0014086965,0.0017818867],"study_design_scores_gemma":[0.0004751193,0.000038455648,0.9801291,0.00003087628,0.000003481733,0.00013188309,0.000004310562,0.000014026829,0.00013870554,0.000321986,0.018635374,0.000076667035],"about_ca_topic_score_codex":0.000004392945,"about_ca_topic_score_gemma":0.0000013641896,"teacher_disagreement_score":0.017226677,"about_ca_system_score_codex":0.000025369134,"about_ca_system_score_gemma":0.000028896367,"threshold_uncertainty_score":0.35979122},"labels":[],"label_agreement":null},{"id":"W2952547383","doi":"10.1016/j.nicl.2019.101886","title":"Facial emotion recognition in children treated for posterior fossa tumours and typically developing children: A divergence of predictors","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Pediatric Oncology Group","funders":"Canadian Institutes of Health Research; Pediatric Oncology Group of Ontario","keywords":"White matter; Neuroimaging; Cognition; Psychology; Fractional anisotropy; Audiology; Social cognition; Medicine; Developmental psychology; Neuroscience; Magnetic resonance imaging","score_opus":0.07999941178710104,"score_gpt":0.3779813293236043,"score_spread":0.29798191753650327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952547383","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995969,0.000013654883,0.0016603073,0.00049727,0.000049133985,0.0015852267,0.000091684604,0.00009383029,0.000039905048],"genre_scores_gemma":[0.9885184,0.00011962179,0.010708034,0.00035933175,0.00006943183,0.000038038168,0.00013051466,0.000024025467,0.000032606145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986532,0.000052715233,0.0005549778,0.00045887294,0.00010899423,0.00017128157],"domain_scores_gemma":[0.99928015,0.00014770892,0.00016782476,0.00022583152,0.00010287455,0.0000755842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019109566,0.0001310267,0.00033338266,0.00009163563,0.000034278353,0.000009531524,0.00008328603,0.0000944192,0.000012516143],"category_scores_gemma":[0.00041977307,0.00012477693,0.00009541767,0.00016377644,0.00011110021,0.00009750614,0.00007151411,0.0002303563,0.0000064931382],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026204385,0.00013267333,0.97403836,0.000021085913,0.000008580169,0.0000014696666,0.000011193905,4.544529e-7,0.0029280707,0.000015910507,0.000041296396,0.02253883],"study_design_scores_gemma":[0.0017906068,0.00071960513,0.9949489,0.000108314336,0.000049616276,0.00006534485,0.0000037163024,0.0001980369,0.0016850708,0.00028259473,0.000039329294,0.00010883702],"about_ca_topic_score_codex":0.000010758889,"about_ca_topic_score_gemma":0.0000012901237,"teacher_disagreement_score":0.022429993,"about_ca_system_score_codex":0.00001618247,"about_ca_system_score_gemma":0.000043351527,"threshold_uncertainty_score":0.50882554},"labels":[],"label_agreement":null},{"id":"W2952939467","doi":"10.1016/j.neuroimage.2019.06.020","title":"Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Dimensionality reduction; Diffusion MRI; Diffusion; Diffusion map; Reduction (mathematics); Human brain; Multifactor dimensionality reduction; Curse of dimensionality; Computer science; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Chemistry; Psychology; Mathematics; Magnetic resonance imaging; Medicine; Physics; Nonlinear dimensionality reduction; Radiology","score_opus":0.0538105318690795,"score_gpt":0.36017632451497034,"score_spread":0.3063657926458908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952939467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99156207,0.000018132088,0.002705596,0.0039676526,0.00008173097,0.0011023139,0.000033663124,0.0000537273,0.00047510522],"genre_scores_gemma":[0.99596864,0.000007734353,0.0030335428,0.00023665551,0.00003150249,0.000021928667,0.0000108498125,0.000019607023,0.0006695317],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99926716,0.000028671873,0.00024083465,0.00021674666,0.00014950958,0.000097053366],"domain_scores_gemma":[0.99903065,0.000083173305,0.00018903703,0.0005421109,0.00012656617,0.000028447255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014314477,0.000082570026,0.00019096257,0.00005273839,0.00005837776,0.0000025672693,0.00010669666,0.000036667003,0.000014249042],"category_scores_gemma":[0.00012377463,0.000058534744,0.00013609299,0.00018341816,0.000089015266,0.00004356327,0.00005131266,0.00013712118,6.955524e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045055207,0.00016180649,0.002380397,0.00007528072,0.0000039905976,9.50658e-8,0.000014580782,0.0000019850147,0.9942217,0.0008664938,0.00096287404,0.0012657811],"study_design_scores_gemma":[0.0009472201,0.00029356958,0.25438076,0.00006759406,0.000047347065,0.000020928583,0.000017246459,0.00033134574,0.7328081,0.002660756,0.008345671,0.00007945486],"about_ca_topic_score_codex":0.000010939008,"about_ca_topic_score_gemma":3.0727085e-7,"teacher_disagreement_score":0.26141357,"about_ca_system_score_codex":0.000013214464,"about_ca_system_score_gemma":0.000020984466,"threshold_uncertainty_score":0.23869775},"labels":[],"label_agreement":null},{"id":"W2953031404","doi":"10.1016/j.media.2019.06.010","title":"XQ-SR: Joint x-q space super-resolution with application to infant diffusion MRI","year":2019,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Huawei Technologies (Canada)","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Resolution (logic); Computer science; Image resolution; Focus (optics); Artificial intelligence; SIGNAL (programming language); Pattern recognition (psychology); Domain (mathematical analysis); Joint (building); Mathematics; Magnetic resonance imaging; Physics; Optics; Mathematical analysis; Medicine","score_opus":0.014259364138998113,"score_gpt":0.31385705844009204,"score_spread":0.29959769430109395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953031404","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20581351,0.0000312405,0.7678797,0.024121922,0.000010420617,0.0006438616,0.00000641263,0.00022479761,0.0012680915],"genre_scores_gemma":[0.94470686,0.0001256334,0.050842803,0.0026877103,0.00009683606,0.00019361901,0.00016424336,0.00003106317,0.001151253],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812645,0.000029786812,0.0003019419,0.00054038217,0.0007327164,0.00026874949],"domain_scores_gemma":[0.99846995,0.00004315573,0.000084552004,0.00083736744,0.00016162175,0.0004033748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023880268,0.00016914499,0.0004299619,0.00033917362,0.00007889891,0.000020926476,0.0001519345,0.000084625644,0.0006222449],"category_scores_gemma":[0.00012240701,0.00012398123,0.00016831922,0.0016141376,0.00008969244,0.00008900057,0.000111086425,0.0002764608,0.00028723208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006430201,0.0022802958,0.250247,0.00030021623,0.0013627891,0.00023553951,0.00067009294,0.001055635,0.64900106,0.00480333,0.023750754,0.06565023],"study_design_scores_gemma":[0.0037820921,0.0012376116,0.29436207,0.00041948076,0.0051574525,0.00019957384,0.00028984767,0.39630118,0.036368974,0.0007378271,0.25990838,0.0012355003],"about_ca_topic_score_codex":0.00020358368,"about_ca_topic_score_gemma":0.00005110065,"teacher_disagreement_score":0.73889333,"about_ca_system_score_codex":0.00008068686,"about_ca_system_score_gemma":0.000055426008,"threshold_uncertainty_score":0.6813145},"labels":[],"label_agreement":null},{"id":"W2953109071","doi":"10.1016/j.neuroimage.2019.02.018","title":"Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the macaque cortex","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; James S. McDonnell Foundation","keywords":"Connectome; Tractography; Macaque; Betweenness centrality; Diffusion MRI; Human Connectome Project; Connectomics; Modularity (biology); Computer science; Neuroscience; Network topology; Artificial intelligence; Pattern recognition (psychology); Centrality; Psychology; Biology; Functional connectivity; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.2828809455244366,"score_gpt":0.41036486000167766,"score_spread":0.12748391447724106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953109071","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9944025,0.00017477499,0.0022956168,0.0022458425,0.00006770497,0.0006213128,0.000002071945,0.000037958613,0.00015216312],"genre_scores_gemma":[0.9941525,0.00027327065,0.0044146595,0.001044869,0.00003514239,0.000055415094,0.0000022029578,0.000014162028,0.000007815934],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992983,0.000069579095,0.00019198975,0.0001887388,0.00011171032,0.00013971621],"domain_scores_gemma":[0.9990424,0.0004977603,0.000090446214,0.00031816209,0.00003378717,0.000017457209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001341971,0.0000971007,0.00018034132,0.000064964144,0.00007880216,0.000007475754,0.000086782056,0.000019275936,0.0000036240733],"category_scores_gemma":[0.000063294254,0.00005816514,0.000044891523,0.00030589142,0.00017829178,0.0000746115,0.000024040728,0.0002291716,6.9841906e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005372464,0.000980203,0.37180638,0.00086183596,0.00007793907,0.00017814906,0.005170126,0.010708893,0.5354375,0.0093371095,0.0007114145,0.064193174],"study_design_scores_gemma":[0.0011479919,0.000378753,0.9312183,0.00028608055,0.00013160809,0.00016127927,0.0007031169,0.056985404,0.005060259,0.0024765248,0.0012683901,0.00018227617],"about_ca_topic_score_codex":0.000013377276,"about_ca_topic_score_gemma":0.000003163435,"teacher_disagreement_score":0.55941194,"about_ca_system_score_codex":0.000008010563,"about_ca_system_score_gemma":0.000012138914,"threshold_uncertainty_score":0.23719056},"labels":[],"label_agreement":null},{"id":"W2953163966","doi":"10.1016/j.jagp.2019.06.006","title":"Molecular Senescence Is Associated With White Matter Microstructural Damage in Late-Life Depression","year":2019,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Depression (economics); Senescence; White matter; Psychology; Gerontology; Medicine; Internal medicine; Economics","score_opus":0.007345487743370153,"score_gpt":0.27497534413216923,"score_spread":0.2676298563887991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953163966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933485,0.00015812747,0.0015634884,0.0042583863,0.00013295194,0.00020846563,0.0000062973227,0.00002477804,0.0002990449],"genre_scores_gemma":[0.9759965,0.000042563646,0.01998789,0.0037756243,0.000059572318,0.000002985019,0.000003774128,0.000034028297,0.00009706789],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884623,0.000047200298,0.00040890367,0.00022235415,0.0002431514,0.00023217962],"domain_scores_gemma":[0.998753,0.00002500986,0.0006578498,0.00030737335,0.000110836525,0.00014593909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000105283296,0.000163164,0.00041946297,0.00021514123,0.000029003242,0.000016194766,0.00017110213,0.000039050257,0.00010072569],"category_scores_gemma":[0.000015665404,0.0001231612,0.00010143636,0.0007354289,0.00008232918,0.00011243785,0.00003231221,0.00040012377,0.000012316378],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023837999,0.00008158587,0.987864,0.000015611386,0.000028304843,0.000033096123,0.000072101924,0.000095537456,0.009805048,0.000005971824,0.0012537295,0.00050660706],"study_design_scores_gemma":[0.0014622268,0.00047427384,0.99593025,0.0002734012,0.00007472154,0.00029055413,0.00012250523,0.00013079641,0.0006799202,0.00019423511,0.00018957267,0.0001775392],"about_ca_topic_score_codex":0.000011714545,"about_ca_topic_score_gemma":0.0000011329876,"teacher_disagreement_score":0.018424401,"about_ca_system_score_codex":0.00005185873,"about_ca_system_score_gemma":0.00017167086,"threshold_uncertainty_score":0.5022368},"labels":[],"label_agreement":null},{"id":"W2953687313","doi":"10.1016/j.bbr.2019.112042","title":"Effect of aerobic exercise on white matter microstructure in the aging brain","year":2019,"lang":"en","type":"article","venue":"Behavioural Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Libin Cardiovascular Institute of Alberta; Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Fasciculus; White matter; Diffusion MRI; Aerobic exercise; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Uncinate fasciculus; Medicine; Psychology; Cardiology; Internal medicine; Magnetic resonance imaging","score_opus":0.07756362520729278,"score_gpt":0.4381327679662803,"score_spread":0.36056914275898755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953687313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691401,0.000040355513,0.000010792205,0.028366504,0.00001780461,0.0016805889,0.000008551434,0.000031281696,0.00070401025],"genre_scores_gemma":[0.995594,0.000006240868,0.00030362754,0.0012171693,0.00002060434,0.00013611933,0.00002643898,0.000027621474,0.0026681584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983966,0.0002962668,0.00019024414,0.0003055084,0.00045306218,0.00035833483],"domain_scores_gemma":[0.9984177,0.0007424531,0.000039610142,0.000686164,0.00006226519,0.00005182466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013297538,0.00012625649,0.00022787107,0.00023862948,0.00006648633,0.000024247382,0.0003081722,0.00006744769,0.0002004933],"category_scores_gemma":[0.00008472465,0.00007954421,0.000078520476,0.0005164758,0.00013097514,0.000045784556,0.000093168164,0.0008400577,0.00010797269],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025432973,0.00009077945,0.82903516,0.00015933893,0.0000024310514,0.00004151899,0.0003929073,0.000004993986,0.135597,0.00014634547,0.02942656,0.004848628],"study_design_scores_gemma":[0.001316671,0.00097200816,0.9349227,0.00056061085,0.000013624985,0.000075678305,0.000124192,0.000037139733,0.059774395,0.00021599545,0.0018550188,0.00013198913],"about_ca_topic_score_codex":0.00006817927,"about_ca_topic_score_gemma":0.0000033487183,"teacher_disagreement_score":0.10588751,"about_ca_system_score_codex":0.000050103576,"about_ca_system_score_gemma":0.000024002904,"threshold_uncertainty_score":0.36496794},"labels":[],"label_agreement":null},{"id":"W2953691333","doi":"10.1002/glia.23661","title":"White matter plasticity and maturation in human cognition","year":2019,"lang":"en","type":"review","venue":"Glia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; University of Toronto; University Health Network; SickKids Foundation; McGill University; Mental Health Research Canada; Hospital for Sick Children","funders":"Ontario Institute for Regenerative Medicine","keywords":"White matter; Cognition; Neuroscience; Psychology; Biology; Neuroplasticity; Cognitive psychology; Developmental psychology; Medicine; Magnetic resonance imaging","score_opus":0.13386162556062928,"score_gpt":0.42031177553835386,"score_spread":0.28645014997772456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953691333","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023774833,0.98862517,0.002288388,0.00028935695,0.000061001112,0.002470987,0.00008118639,0.00016179956,0.0057843537],"genre_scores_gemma":[0.0005174006,0.996387,0.0013781498,0.00019310055,0.00007114767,0.0001453796,0.0003355065,0.000030982406,0.0009413256],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99942476,0.000015179315,0.00020176865,0.0002160256,0.0000559614,0.000086326785],"domain_scores_gemma":[0.9997008,0.000022679635,0.00009434085,0.0001384976,0.00001739229,0.00002629556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002673535,0.00012580055,0.00042729478,0.000095593525,0.000023457766,0.000012189742,0.00003130025,0.000092944814,0.00006363164],"category_scores_gemma":[0.000007003246,0.00010541746,0.000046998815,0.00009175306,0.000022302285,0.00003600345,0.000027194546,0.00024244863,0.00010420667],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057189198,0.00030091635,0.003039077,0.07481407,0.000065693326,0.00006309468,0.000078928846,6.3796665e-7,0.00016251433,0.0017437926,0.02687393,0.89280015],"study_design_scores_gemma":[0.00021641953,0.000038758997,0.0052988017,0.009250899,0.00041260995,0.00010886632,0.000001837301,0.000012700656,0.000005599582,0.00056528376,0.9839116,0.00017666079],"about_ca_topic_score_codex":0.0000018415352,"about_ca_topic_score_gemma":9.41137e-7,"teacher_disagreement_score":0.9570376,"about_ca_system_score_codex":0.0000293001,"about_ca_system_score_gemma":0.0000158281,"threshold_uncertainty_score":0.42987993},"labels":[],"label_agreement":null},{"id":"W2953747591","doi":"10.1101/690701","title":"Early life maturation of human visual system white matter is altered by monocular enucleation","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; University of Waterloo","funders":"","keywords":"Enucleation; White matter; Monocular; Diffusion MRI; Eye Enucleation; Optic radiation; Visual system; Anatomy; Psychology; Optic tract; Ophthalmology; Neuroscience; Medicine; Optic nerve; Visual cortex; Magnetic resonance imaging; Surgery; Optics; Radiology; Physics","score_opus":0.023548082950263057,"score_gpt":0.280683093048121,"score_spread":0.25713501009785794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953747591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97570616,0.00021343211,0.020902729,0.0005539671,0.00020561114,0.0016213603,0.00025115008,0.0005156409,0.000029954104],"genre_scores_gemma":[0.9909821,0.000036200465,0.0077775973,0.0005589572,0.00024352375,0.00021417328,0.000004705339,0.00015367867,0.0000290496],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978747,0.00004749958,0.00065857964,0.0007791146,0.0003589085,0.0002812352],"domain_scores_gemma":[0.9974306,0.000015883368,0.0006736108,0.0012651558,0.0004369844,0.0001777321],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017265075,0.00039328833,0.00062134984,0.00021331839,0.000095591626,0.00007492868,0.0002500055,0.0003642534,0.000049287974],"category_scores_gemma":[0.000021286141,0.00042485117,0.00016303099,0.00024813684,0.000067297595,0.00013225549,0.00020593642,0.000543398,0.0001108761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004588765,0.00012950042,0.033893842,0.0012989077,0.00008376558,0.0000038350586,0.000014166007,0.000009254795,0.9592298,0.00031373012,0.004976316,9.792909e-7],"study_design_scores_gemma":[0.00089627394,0.00020846448,0.4549102,0.0016368763,0.00037477879,7.314573e-8,0.0000063075295,0.0031721275,0.53573966,0.0000043423593,0.00231986,0.0007310515],"about_ca_topic_score_codex":0.000033326556,"about_ca_topic_score_gemma":4.8756338e-8,"teacher_disagreement_score":0.42349014,"about_ca_system_score_codex":0.00020332576,"about_ca_system_score_gemma":0.00013394163,"threshold_uncertainty_score":0.99982035},"labels":[],"label_agreement":null},{"id":"W2953829863","doi":"10.1080/02699052.2019.1605620","title":"Impact of non-invasive brain stimulation on transcallosal modulation in mild traumatic brain injury: a multimodal pilot investigation","year":2019,"lang":"en","type":"article","venue":"Brain Injury","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; CHU Sainte-Justine Foundation","keywords":"Corpus callosum; Transcranial magnetic stimulation; Fractional anisotropy; Psychology; Traumatic brain injury; Concussion; Functional magnetic resonance imaging; White matter; Diffusion MRI; Physical medicine and rehabilitation; Neuroscience; Magnetic resonance imaging; Stimulation; Medicine; Poison control; Psychiatry; Injury prevention; Radiology","score_opus":0.07497996076537589,"score_gpt":0.3880042181379802,"score_spread":0.3130242573726043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953829863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98452115,0.00000509496,0.006575738,0.006103359,0.000042240645,0.0022744897,0.00008373154,0.00014918773,0.00024499831],"genre_scores_gemma":[0.99138385,0.0000042705497,0.0063882717,0.0015851668,0.000066062144,0.00012713781,0.00023608639,0.00006181517,0.00014731822],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99811715,0.00011744972,0.00063347083,0.0004890573,0.0003482191,0.00029467806],"domain_scores_gemma":[0.9983355,0.0006210713,0.00026173616,0.00054738385,0.00009844781,0.00013589358],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00036029975,0.00028437487,0.00045187116,0.00049824157,0.000048371134,0.000014665426,0.00013736561,0.00013656988,0.00006156319],"category_scores_gemma":[0.00043223315,0.00027192102,0.00017570454,0.0006490342,0.000097196884,0.0002452412,0.000023065058,0.00035621537,0.00003055667],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014539721,0.0006471043,0.0747403,0.00022176192,0.000039057315,0.0000027246897,0.0009913727,0.0056579574,0.90125793,0.000883458,0.003277041,0.01082734],"study_design_scores_gemma":[0.002884505,0.0040123104,0.8812745,0.00060866936,0.000024966266,0.000005863572,0.000037917936,0.087265946,0.01936226,0.0041684117,0.000046480804,0.00030817543],"about_ca_topic_score_codex":0.00020801502,"about_ca_topic_score_gemma":0.000019354678,"teacher_disagreement_score":0.88189566,"about_ca_system_score_codex":0.0002415856,"about_ca_system_score_gemma":0.00018026277,"threshold_uncertainty_score":0.9999733},"labels":[],"label_agreement":null},{"id":"W2954554842","doi":"10.1111/jon.12646","title":"Brain Amyloid PET Tracer Delivery is Related to White Matter Integrity in Patients with Mild Cognitive Impairment","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Sunnybrook Health Science Centre; Baycrest Hospital; Health Sciences Centre; University of Toronto; University Health Network; St. Michael's Hospital; Centre for Addiction and Mental Health","funders":"Health Canada; Fondation Brain Canada","keywords":"White matter; Fractional anisotropy; Medicine; Hyperintensity; Pittsburgh compound B; Cerebral blood flow; Positron emission tomography; Pathology; Magnetic resonance imaging; Neuroimaging; Alzheimer's disease; Nuclear medicine; Internal medicine; Disease; Radiology; Psychiatry","score_opus":0.021372388126418503,"score_gpt":0.3094134326514754,"score_spread":0.2880410445250569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2954554842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9807849,0.000014965993,0.00041571932,0.017713437,0.000056530847,0.0006186508,0.000011421976,0.000026140333,0.0003582427],"genre_scores_gemma":[0.9833364,0.000008713963,0.0044956324,0.011832811,0.000019552384,0.000006361661,0.000004041226,0.000038788756,0.00025770842],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986996,0.000045519006,0.00045018006,0.0002530664,0.0003188473,0.00023278713],"domain_scores_gemma":[0.99906224,0.00007865338,0.00025145707,0.00020421098,0.0002609213,0.000142521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016418853,0.00016646822,0.000313663,0.00031811415,0.000031344436,0.000024276966,0.000111783214,0.000020830037,0.00016311312],"category_scores_gemma":[0.000030122836,0.00013061627,0.0000878266,0.00033722026,0.000032606084,0.00024832148,0.000053277417,0.0007875488,0.000057494766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005769348,0.00031768964,0.99250674,0.000025490363,0.000017876468,0.000110238005,0.00035051166,0.00002496242,0.0019990187,0.0000028790414,0.0035536457,0.00051398104],"study_design_scores_gemma":[0.0029425127,0.0006360985,0.99389917,0.0006291201,0.000043598142,0.00030833652,0.00008899561,0.00013178469,0.0005550168,0.000056299312,0.0005709761,0.00013807566],"about_ca_topic_score_codex":0.000005158864,"about_ca_topic_score_gemma":5.046371e-7,"teacher_disagreement_score":0.005880625,"about_ca_system_score_codex":0.00009546345,"about_ca_system_score_gemma":0.000044774886,"threshold_uncertainty_score":0.5326377},"labels":[],"label_agreement":null},{"id":"W2955848820","doi":"10.7554/elife.44056","title":"Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age","year":2019,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"H2020 European Research Council; National Institute of Biomedical Imaging and Bioengineering; Seventh Framework Programme; Max-Planck-Gesellschaft; Horizon 2020 Framework Programme; Jacobs Foundation; National Institute of Mental Health; Medical Research Council; Bundesministerium für Bildung und Forschung","keywords":"Structural equation modeling; Voxel; Alcohol Use Disorders Identification Test; Voxel-based morphometry; Psychology; Neuroimaging; Grey matter; Alcohol use disorder; Developmental psychology; Clinical psychology; Alcohol; Neuroscience; Medicine; Artificial intelligence; Magnetic resonance imaging; Machine learning; Computer science; Poison control; Biology; Injury prevention; White matter; Environmental health; Radiology","score_opus":0.03187171842279533,"score_gpt":0.3125187406850376,"score_spread":0.28064702226224225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955848820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9981124,0.00004099043,0.0011820993,0.00018785361,0.00003656392,0.0002659673,0.00002887118,0.00005832384,0.00008693091],"genre_scores_gemma":[0.96353436,0.0000028416587,0.035888374,0.00021993667,0.0000325873,0.000004835096,0.000064278516,0.000016879327,0.00023592435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928355,0.0000075432995,0.00023369063,0.00016389064,0.00021283515,0.000098507524],"domain_scores_gemma":[0.99950486,0.000026624763,0.00013092092,0.0002593382,0.00003595561,0.000042298085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049381768,0.00006804863,0.00016908273,0.000036406902,0.000021977448,0.0000020704372,0.00007903441,0.000039507348,0.00004264627],"category_scores_gemma":[0.000026478621,0.000068521156,0.000034709738,0.000069647016,0.000023311966,0.00001960827,0.000098142,0.000121843084,0.0000057832563],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016291051,0.000046174824,0.55559874,0.00003392363,0.000009899442,0.0000041931544,0.0005240174,0.000011380551,0.4386206,0.000028611725,0.00057502015,0.0045311507],"study_design_scores_gemma":[0.00038904522,0.00002764602,0.7305902,0.00027752106,0.000017053313,0.0000030729213,0.00004594761,0.000056406832,0.2594523,0.000053026615,0.009024396,0.00006333396],"about_ca_topic_score_codex":0.000010227983,"about_ca_topic_score_gemma":0.000009891608,"teacher_disagreement_score":0.17916828,"about_ca_system_score_codex":0.00004389474,"about_ca_system_score_gemma":0.000034319102,"threshold_uncertainty_score":0.27942118},"labels":[],"label_agreement":null},{"id":"W2955883382","doi":"10.1136/gutjnl-2019-318308","title":"Role of brain imaging in disorders of brain–gut interaction: a Rome Working Team Report","year":2019,"lang":"en","type":"review","venue":"Gut","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Neuroimaging; Neuroscience; Vulvodynia; Medicine; Brain activity and meditation; Cognition; Identification (biology); Psychology; Bioinformatics; Pelvic pain; Electroencephalography; Biology","score_opus":0.0846703725919825,"score_gpt":0.4276850734605936,"score_spread":0.3430147008686111,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955883382","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00007199515,0.97671795,0.0012771115,0.001318366,0.00011766159,0.0017691144,0.0000151723525,0.00013386816,0.01857874],"genre_scores_gemma":[0.00445824,0.9890843,0.004078295,0.00020718249,0.0001303012,0.00022611511,0.00017114812,0.000108933404,0.0015354881],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982688,0.000044156604,0.0008946294,0.0004203559,0.00017942855,0.00019264016],"domain_scores_gemma":[0.9980267,0.00026925202,0.00082403934,0.0007919386,0.000043729262,0.000044312805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024389845,0.00023837469,0.0011857252,0.00034141744,0.000018791334,0.0000063868993,0.00018352274,0.00009174461,0.000024694142],"category_scores_gemma":[0.00024120061,0.00021756871,0.00032654087,0.00044147982,0.000068123474,0.00006365681,0.00011771769,0.0004903609,0.000008831887],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006805682,0.00013504174,0.00070152816,0.0037096324,0.000024460993,0.000018029094,0.000060838902,0.0000019997512,0.00022201324,0.00028044634,0.0014240713,0.9934151],"study_design_scores_gemma":[0.00016089916,0.000034923087,0.00018749021,0.014799162,0.000139128,0.00041030362,0.000044441025,0.00004116149,0.000009736363,0.0007008959,0.9833196,0.00015228929],"about_ca_topic_score_codex":0.00005616269,"about_ca_topic_score_gemma":0.0000082993265,"teacher_disagreement_score":0.9932628,"about_ca_system_score_codex":0.00009970323,"about_ca_system_score_gemma":0.00015665127,"threshold_uncertainty_score":0.8872195},"labels":[],"label_agreement":null},{"id":"W2955905284","doi":"10.1101/689778","title":"Effects of unilateral cortical resection of the visual cortex on bilateral human white matter","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institutes of Health","keywords":"White matter; Psychology; Cortex (anatomy); Resection; Visual cortex; Neuroscience; Inferior longitudinal fasciculus; Lateralization of brain function; Tractography; Anatomy; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.01951688567825972,"score_gpt":0.2928760603138892,"score_spread":0.2733591746356295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955905284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996899,0.000028910441,0.00078454026,0.00031191905,0.00034720433,0.0014299243,0.000036326714,0.00013744508,0.000024693001],"genre_scores_gemma":[0.9982298,0.000019088779,0.0010444771,0.000337225,0.00013027928,0.00010957434,4.449051e-7,0.00008875612,0.0000403522],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99820834,0.00010214626,0.0005104619,0.0005711127,0.00034090946,0.0002670216],"domain_scores_gemma":[0.9979646,0.00006547511,0.00044779386,0.0011532046,0.00027323622,0.000095698],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015179628,0.00031721278,0.00054514705,0.00017574492,0.000082527185,0.000020358571,0.00028141608,0.00027574305,0.000026880334],"category_scores_gemma":[0.000054237018,0.00024964786,0.00020364513,0.00029391708,0.00019509708,0.00004170368,0.0003335941,0.0009022957,0.000016965902],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000897746,0.00027414368,0.12553202,0.0009595642,0.00004831904,0.0000075368457,0.000004263828,0.000019007346,0.8723707,0.00045827823,0.0002360431,3.5035688e-7],"study_design_scores_gemma":[0.00034003914,0.00020503199,0.56935203,0.00077382074,0.0001066113,3.7998976e-8,1.7807353e-7,0.00014746193,0.42877263,0.0000047972508,0.0001620293,0.0001353346],"about_ca_topic_score_codex":0.000015063915,"about_ca_topic_score_gemma":2.3278788e-7,"teacher_disagreement_score":0.44382,"about_ca_system_score_codex":0.00011441004,"about_ca_system_score_gemma":0.0001278591,"threshold_uncertainty_score":0.9999956},"labels":[],"label_agreement":null},{"id":"W2955932350","doi":"10.1016/j.media.2020.101758","title":"Automated characterization of noise distributions in diffusion MRI data","year":2020,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Noise (video); Scanner; Computer science; Imaging phantom; Artificial intelligence; Noise reduction; Algorithm; Sensitivity (control systems); Pattern recognition (psychology); Physics; Optics","score_opus":0.05534162756861639,"score_gpt":0.3762756233350233,"score_spread":0.3209339957664069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955932350","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24474996,0.000012959977,0.7251977,0.029155742,0.0000055774976,0.00018106222,0.00029213433,0.00031197668,0.00009288543],"genre_scores_gemma":[0.98542434,0.00019898587,0.0074469806,0.0008233521,0.000038116217,0.000013849724,0.006026796,0.000009013706,0.000018562814],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989335,0.00002965799,0.0003387673,0.0002888539,0.00029974116,0.00010948443],"domain_scores_gemma":[0.9991163,0.0000328435,0.000091788366,0.0005119539,0.00006429985,0.000182802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000119234304,0.00007491807,0.0003026967,0.00011974136,0.000027112817,0.000006320927,0.0002274854,0.00004990086,0.00033576426],"category_scores_gemma":[0.000563625,0.00006428144,0.000070806636,0.0018268226,0.000090716894,0.000100451995,0.00019047441,0.00015707758,0.0000094246225],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069484835,0.0009679006,0.10293876,0.00012666619,0.0002686381,0.00016558524,0.00014258883,0.000008924214,0.8809283,0.00020758522,0.0031218047,0.011053783],"study_design_scores_gemma":[0.00044227316,0.00003219699,0.18050632,0.000040713217,0.000705141,0.0000038435464,0.000011457482,0.8079899,0.006845023,0.000022579414,0.0033189321,0.000081641076],"about_ca_topic_score_codex":0.00003170965,"about_ca_topic_score_gemma":0.000004666507,"teacher_disagreement_score":0.8740833,"about_ca_system_score_codex":0.00001544549,"about_ca_system_score_gemma":0.000042665382,"threshold_uncertainty_score":0.36763832},"labels":[],"label_agreement":null},{"id":"W2956022343","doi":"10.1503/jpn.170241","title":"Altered white matter connectivity in young people exposed to childhood abuse: a tract-based spatial statistics (TBSS) and tractography study","year":2019,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Institute of Psychiatry, Psychology and Neuroscience, King’s College London; Lee Kong Chian School of Medicine, Nanyang Technological University; King's College London; Imperial College London; Nanyang Technological University; National Institute for Health and Care Research; Wellcome Trust","keywords":"Fractional anisotropy; Uncinate fasciculus; Fasciculus; Inferior longitudinal fasciculus; White matter; Psychiatry; Psychology; Corpus callosum; Superior longitudinal fasciculus; Splenium; Tractography; Child abuse; Medicine; Clinical psychology; Poison control; Neuroscience; Magnetic resonance imaging; Injury prevention","score_opus":0.019118047283042033,"score_gpt":0.3101815627143095,"score_spread":0.2910635154312675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956022343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776426,0.000020087322,0.019590978,0.0018327433,0.00031337162,0.0005459939,0.00001597867,0.00001187213,0.000026403191],"genre_scores_gemma":[0.99008894,0.00002557325,0.008675105,0.0011317285,0.00005141801,0.0000071053532,3.992675e-7,0.000011444501,0.000008310652],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989921,0.00004704672,0.00031410184,0.00027000203,0.00021732743,0.00015944365],"domain_scores_gemma":[0.99936897,0.000058491307,0.00019346144,0.00018025216,0.000045793524,0.0001530194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021289464,0.00011858853,0.00025260035,0.00023344571,0.00006667037,0.000041141546,0.00009822747,0.000023306991,0.000009972005],"category_scores_gemma":[0.00003096136,0.000099786106,0.000035576493,0.00034890286,0.000044175657,0.00015393684,0.000017179498,0.00030362248,9.2206506e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011697123,0.0010961929,0.98958945,0.000022001692,0.0000013727649,0.000007469949,0.0004142459,0.00003065177,0.008440428,0.000017559863,0.000077858494,0.00018580566],"study_design_scores_gemma":[0.0015348785,0.0018899946,0.99518025,0.00006256894,0.000024700183,0.00029254664,0.00014968304,0.00034711257,0.00020947382,0.00016118372,0.00005197245,0.00009566572],"about_ca_topic_score_codex":0.000011047276,"about_ca_topic_score_gemma":0.00009665458,"teacher_disagreement_score":0.012446343,"about_ca_system_score_codex":0.000007836903,"about_ca_system_score_gemma":0.00005948011,"threshold_uncertainty_score":0.40691593},"labels":[],"label_agreement":null},{"id":"W2956846297","doi":"10.1007/s00062-019-00805-0","title":"Microstructural White Matter Alterations in Mild Cognitive Impairment and Alzheimer’s Disease","year":2019,"lang":"en","type":"article","venue":"Clinical Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Corpus callosum; Receiver operating characteristic; Area under the curve; Montreal Cognitive Assessment; White matter; Audiology; Splenium; Alzheimer's disease; Psychology; Medicine; Internal medicine; Dementia; Cardiology; Magnetic resonance imaging; Pathology; Disease; Radiology","score_opus":0.09006671855847243,"score_gpt":0.419373250352193,"score_spread":0.3293065317937206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956846297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9876086,0.00012298519,0.00012321013,0.010919174,0.00012444971,0.00078398694,0.00003183691,0.000051316623,0.00023442287],"genre_scores_gemma":[0.9849259,0.00010089257,0.0012904581,0.013300731,0.000075258875,0.000052620806,0.000052109925,0.000017598473,0.00018440756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888545,0.00009211482,0.00036417437,0.00042946945,0.000041208692,0.00018757237],"domain_scores_gemma":[0.9992188,0.0002675266,0.000064556654,0.00025043575,0.000030747677,0.00016790665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000077898905,0.000115626164,0.00028465656,0.00005702635,0.000030287396,0.0000078701705,0.00005569011,0.000059083675,0.00012692106],"category_scores_gemma":[0.000055438428,0.00009942452,0.000067294175,0.000080399164,0.0002136878,0.000044624554,0.00006839263,0.00032847948,0.00009925219],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023227902,0.00009327622,0.9976194,0.000008985916,0.00000863075,0.000027005042,0.000015910211,0.0000019114038,0.00019072341,0.00014718404,0.0012528881,0.000401823],"study_design_scores_gemma":[0.0011801207,0.00030966543,0.9959603,0.000032151984,0.00005704399,0.0000975694,0.000008351222,0.00034393516,0.00003271003,0.0007313299,0.0011554963,0.00009134842],"about_ca_topic_score_codex":0.0000022076101,"about_ca_topic_score_gemma":8.575947e-7,"teacher_disagreement_score":0.002682695,"about_ca_system_score_codex":0.0000073368733,"about_ca_system_score_gemma":0.000028506038,"threshold_uncertainty_score":0.4054414},"labels":[],"label_agreement":null},{"id":"W2957612371","doi":"10.1016/j.neuroimage.2019.116017","title":"White matter information flow mapping from diffusion MRI and EEG","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Université de Sherbrooke; École de Technologie Supérieure","funders":"H2020 European Research Council; European Research Council","keywords":"Diffusion MRI; Electroencephalography; White matter; Computer science; Tractography; Information flow; Artificial intelligence; Diffusion; Pattern recognition (psychology); Neuroscience; Computer vision; Magnetic resonance imaging; Psychology; Physics","score_opus":0.019871119711756677,"score_gpt":0.27120904374643257,"score_spread":0.25133792403467586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2957612371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9473449,0.000021095404,0.033446673,0.0062129353,0.00008418926,0.00059558573,0.000035955447,0.00026050513,0.011998183],"genre_scores_gemma":[0.9381382,0.00009682091,0.050332747,0.009824445,0.00005865174,0.00003059541,0.00013908249,0.000030198466,0.0013492883],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999387,0.00001052926,0.00016403882,0.00019386929,0.000116538395,0.00012801694],"domain_scores_gemma":[0.999464,0.000026740809,0.000059559126,0.00035648988,0.000031094594,0.00006211506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002950923,0.00010310156,0.00013290401,0.0000733225,0.000048294904,0.000036771427,0.000055994413,0.00003489221,0.0002967393],"category_scores_gemma":[0.000009786056,0.00009354066,0.000031057156,0.00009619114,0.000026024407,0.00031221964,0.000086324326,0.0001726776,0.0005230722],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008202987,0.00009704256,0.82153803,0.0001666843,0.000010542704,0.000019944227,0.0006179468,0.000021631071,0.12032588,0.0002004422,0.028453149,0.028466677],"study_design_scores_gemma":[0.0005768726,0.000041212083,0.8611311,0.00005395886,0.000013788741,0.00003247931,0.000027963282,0.007928952,0.0007326052,0.00043809213,0.12891144,0.0001115542],"about_ca_topic_score_codex":0.000009080723,"about_ca_topic_score_gemma":1.9229805e-7,"teacher_disagreement_score":0.11959327,"about_ca_system_score_codex":0.000011616384,"about_ca_system_score_gemma":0.0000070226592,"threshold_uncertainty_score":0.67232096},"labels":[],"label_agreement":null},{"id":"W2957869398","doi":"10.1038/s41597-019-0129-z","title":"A macaque connectome for large-scale network simulations in TheVirtualBrain","year":2019,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":91,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Western University; McGill University; Montreal Neurological Institute and Hospital; Baycrest Hospital","funders":"Deutsche Forschungsgemeinschaft; European Commission","keywords":"Connectome; Macaque; Connectomics; Tractography; Computer science; Human Connectome Project; Diffusion MRI; Resting state fMRI; Neuroscience; Scale (ratio); Tracing; Functional connectivity; Biology; Cartography; Magnetic resonance imaging; Geography; Medicine","score_opus":0.11977953947096279,"score_gpt":0.40320857664028026,"score_spread":0.28342903716931744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2957869398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46374643,0.00029813894,0.47080383,0.01952008,0.001873104,0.010949339,0.026295828,0.0009458935,0.0055673723],"genre_scores_gemma":[0.92846876,0.0000042135844,0.05539212,0.00075448223,0.00010824061,0.00006688171,0.007914145,0.000026034872,0.0072651347],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988854,0.000013232086,0.00017277809,0.00055447133,0.00011659417,0.00025750176],"domain_scores_gemma":[0.9979852,0.00015764807,0.00004584052,0.0017121789,0.00004497892,0.000054146603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042749848,0.00007236912,0.00013795464,0.00008157236,0.00011068147,0.000045565932,0.00038176423,0.000029833594,0.0001442161],"category_scores_gemma":[0.00012699228,0.00006555736,0.000025604335,0.00049575715,0.000047843638,0.00016051457,0.00025849932,0.000100921534,0.000071224305],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024326751,0.0013109051,0.089604825,0.000327893,0.000042292224,0.000011787442,0.00080626237,0.004495553,0.056058254,0.07724255,0.75785035,0.012006036],"study_design_scores_gemma":[0.0008664419,0.000034438955,0.0027927777,0.00007383483,0.000015779326,0.0000050971344,0.00005266476,0.1877115,0.0003119431,0.009766649,0.7982579,0.000110987035],"about_ca_topic_score_codex":0.0000031804746,"about_ca_topic_score_gemma":0.000044106502,"teacher_disagreement_score":0.4647223,"about_ca_system_score_codex":0.000019462834,"about_ca_system_score_gemma":0.00004922492,"threshold_uncertainty_score":0.26733515},"labels":[],"label_agreement":null},{"id":"W2961056674","doi":"10.3389/fcell.2019.00124","title":"Structural and Diffusion MRI Analyses With Histological Observations in Patients With Lissencephaly","year":2019,"lang":"en","type":"article","venue":"Frontiers in Cell and Developmental Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; St. Francis Xavier University; Montreal Neurological Institute and Hospital","funders":"National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"Lissencephaly; White matter; Magnetic resonance imaging; Diffusion MRI; Doublecortin; Biology; Anatomy; Medicine; Pathology; Neuroscience; Radiology; Central nervous system; Genetics","score_opus":0.03643628097830259,"score_gpt":0.28764108186933757,"score_spread":0.251204800891035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961056674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9979389,0.00010679435,0.001095419,0.00018873495,0.000022046808,0.00029305523,0.0000037172385,0.000017486645,0.00033387015],"genre_scores_gemma":[0.8733444,0.000050234088,0.12625223,0.0001668862,0.0000020950417,0.000013879378,0.00006394728,0.000004269998,0.00010205215],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99948347,0.000011394829,0.00011332671,0.00023646392,0.000038253736,0.00011707073],"domain_scores_gemma":[0.9998367,0.000016580718,0.000035224526,0.000059954335,0.000014890465,0.000036653593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001825384,0.00008919448,0.00017741525,0.000088885645,0.000031942884,0.0000035297214,0.00003106333,0.00004603524,0.000007973615],"category_scores_gemma":[0.0000040760315,0.00005584994,0.0000057505817,0.00014128129,0.00011645754,0.000040592953,0.00003652827,0.00009917959,4.0224816e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014442553,0.000037958223,0.99701244,0.000009604009,0.0000034622947,0.0000027394733,0.000066385466,0.0000013828272,0.0014704408,0.00005426849,0.000094198724,0.001102682],"study_design_scores_gemma":[0.0012537787,0.00024964742,0.9967051,0.000019190222,0.000006274594,0.000007815259,0.0001525386,0.00014740901,0.00025724905,0.00029939227,0.0008120715,0.00008950662],"about_ca_topic_score_codex":0.000017014363,"about_ca_topic_score_gemma":0.000008915385,"teacher_disagreement_score":0.12515682,"about_ca_system_score_codex":0.000040502033,"about_ca_system_score_gemma":0.00002040084,"threshold_uncertainty_score":0.22774945},"labels":[],"label_agreement":null},{"id":"W2961338082","doi":"10.1002/hbm.24706","title":"A multiparametric analysis of white matter maturation during late childhood and adolescence","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"White matter; Psychology; Developmental psychology; White (mutation); Medicine; Biology; Magnetic resonance imaging; Genetics","score_opus":0.02860885313794186,"score_gpt":0.3029596770906897,"score_spread":0.27435082395274785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2961338082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9933656,0.000028455248,0.004964404,0.00074092316,0.0000049428813,0.0003341878,0.0000032292426,0.00006998208,0.0004882934],"genre_scores_gemma":[0.99337435,0.000006733361,0.0054674563,0.00044246612,0.000014206577,0.000011628822,0.000015791758,0.00001189302,0.0006554686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935466,0.000013494768,0.00019488485,0.00023255563,0.000092836635,0.00011158066],"domain_scores_gemma":[0.99955153,0.000029462626,0.00011239913,0.00023769563,0.0000336399,0.000035293284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007088158,0.00008209465,0.00021713642,0.00046228262,0.00009840715,0.0000106802245,0.000049218754,0.000029322442,0.000066598026],"category_scores_gemma":[0.000018784895,0.00008011213,0.000061170205,0.000756801,0.000029430887,0.00006751578,0.00005829387,0.0001149913,0.000008662829],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007907853,0.000044282355,0.6658442,0.00012868679,0.000067946516,0.0000018427919,0.0005294661,0.00012817826,0.33290088,0.0001452954,0.000053366126,0.00014796405],"study_design_scores_gemma":[0.00029186552,0.000014457694,0.99637514,0.00012045588,0.00009372933,0.000008747032,0.000032840664,0.0023110274,0.00046676974,0.00013423995,0.000074868054,0.0000758264],"about_ca_topic_score_codex":0.000005415506,"about_ca_topic_score_gemma":7.394415e-7,"teacher_disagreement_score":0.3324341,"about_ca_system_score_codex":0.000015527785,"about_ca_system_score_gemma":0.0000038782578,"threshold_uncertainty_score":0.32668775},"labels":[],"label_agreement":null},{"id":"W2962033364","doi":"10.1101/703835","title":"Comparison of CPU and GPU Bayesian Estimates of Fibre Orientations from Diffusion MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"BC Children's Hospital","keywords":"Markov chain Monte Carlo; Computer science; Diffusion; Voxel; Central processing unit; Bayesian probability; Monte Carlo method; Markov chain; Algorithm; Fraction (chemistry); Diffusion MRI; Artificial intelligence; Mathematics; Statistics; Physics; Machine learning; Computer hardware","score_opus":0.03499608116880228,"score_gpt":0.3237638238203944,"score_spread":0.28876774265159216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962033364","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8924937,0.0007574146,0.10458801,0.00032134936,0.0001408997,0.0009378163,0.00052864826,0.00021988696,0.000012281149],"genre_scores_gemma":[0.85769135,0.00024389362,0.14185318,0.00003972623,0.000053967866,0.000054752712,0.0000035116288,0.00005761101,0.0000020030539],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984192,0.000027292013,0.0005586799,0.0005738329,0.00023555158,0.00018543948],"domain_scores_gemma":[0.99781835,0.00013926481,0.0005614398,0.0010459321,0.0003034866,0.00013154992],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008880222,0.0002861663,0.0007339449,0.00016775084,0.000060480455,0.000020441748,0.00019428447,0.00022407593,0.000024921954],"category_scores_gemma":[0.0001048669,0.00029015413,0.00009343386,0.000243972,0.00016698854,0.000058469144,0.00032943505,0.0004035551,0.0000036191025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031985,0.00024381909,0.27301753,0.0005328592,0.000051235147,0.0000027393464,0.000021485746,0.000043829423,0.72521037,0.0006064231,0.00022708879,0.000010646492],"study_design_scores_gemma":[0.0005417097,0.00013402253,0.36256287,0.0011190575,0.00028865042,1.8271779e-8,0.000008387996,0.007178535,0.62695724,0.000052863677,0.00087141007,0.0002852602],"about_ca_topic_score_codex":0.00007680257,"about_ca_topic_score_gemma":7.021328e-7,"teacher_disagreement_score":0.09825315,"about_ca_system_score_codex":0.000049943723,"about_ca_system_score_gemma":0.00016296387,"threshold_uncertainty_score":0.99995506},"labels":[],"label_agreement":null},{"id":"W2964269336","doi":"10.1090/tran/7641","title":"From dimers to webs","year":2018,"lang":"en","type":"article","venue":"Transactions of the American Mathematical Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Perimeter Institute","funders":"National Science Foundation","keywords":"Algorithm; Annotation; Computer science; Artificial intelligence; Type (biology); Mathematics; Biology","score_opus":0.041730274093232565,"score_gpt":0.3582147635843501,"score_spread":0.31648448949111757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964269336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24607427,0.000002677507,0.74358237,0.0088356715,0.000018420185,0.00026969353,0.000022219021,0.00010226403,0.0010924116],"genre_scores_gemma":[0.73678344,0.000006551429,0.26128742,0.0014803282,0.00004845722,0.000030498177,5.86017e-7,0.000013927847,0.00034875423],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99941176,0.0000109006805,0.0001606825,0.00014673232,0.0001490404,0.00012086264],"domain_scores_gemma":[0.9992181,0.000086153595,0.00006941202,0.00048901566,0.000053822994,0.00008351156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045465797,0.00007742082,0.00020073738,0.00001070472,0.0001036202,0.000003885595,0.00015348998,0.000016375418,0.00021937647],"category_scores_gemma":[0.000020814125,0.000052091153,0.00024297398,0.00038731235,0.000619949,0.000020560075,0.0000144187525,0.0001221345,0.000052686126],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004939417,0.0041554742,0.0029374822,0.00033355504,0.0011935367,0.0000019509687,0.016116787,0.0001356058,0.76181537,0.013025399,0.06942987,0.130361],"study_design_scores_gemma":[0.0019121756,0.002530581,0.03798232,0.00078497344,0.001973124,0.0000948474,0.0070603266,0.015628101,0.6270641,0.2320171,0.071806096,0.001146264],"about_ca_topic_score_codex":0.000047940586,"about_ca_topic_score_gemma":7.342981e-7,"teacher_disagreement_score":0.4907092,"about_ca_system_score_codex":0.000027627237,"about_ca_system_score_gemma":0.000020328489,"threshold_uncertainty_score":0.24020185},"labels":[],"label_agreement":null},{"id":"W2965216242","doi":"10.1101/730366","title":"Mapping the living mouse brain neural architecture: strain specific patterns of brain structural and functional connectivity","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Neuroscience; Corpus callosum; Splenium; Connectome; Diffusion MRI; Biology; Human Connectome Project; Brain mapping; Psychology; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.0428710507140658,"score_gpt":0.2623174863620694,"score_spread":0.21944643564800362,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965216242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93259877,0.0003605499,0.059905343,0.00479819,0.00023511302,0.0012569287,0.00054043403,0.0003014697,0.0000032154796],"genre_scores_gemma":[0.99351656,0.000056957735,0.00486076,0.0010044436,0.00033888285,0.0001045818,0.0000016112949,0.00010084678,0.000015335323],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99778175,0.00015494603,0.00045928798,0.00087266014,0.00034609044,0.00038524115],"domain_scores_gemma":[0.99735653,0.00060901773,0.00042475865,0.0012535513,0.00020434968,0.00015180619],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046400636,0.0004537316,0.00056295586,0.0002177707,0.00017086136,0.00008417729,0.0002731899,0.00022337619,0.000038873215],"category_scores_gemma":[0.0003221664,0.00038089484,0.00016605908,0.0002592045,0.00018027397,0.00008781548,0.0005249343,0.0012506192,0.0000025368836],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003977962,0.00006205384,0.053299144,0.00057590945,0.00009415712,0.00001315419,0.000043525375,0.00029761618,0.9433809,0.0018172453,0.0003219936,0.00005454877],"study_design_scores_gemma":[0.00047344062,0.00007801859,0.958924,0.0005556882,0.000046751127,8.9151195e-7,0.000016512764,0.0022673826,0.034865003,0.000032700296,0.0022452443,0.0004943528],"about_ca_topic_score_codex":0.000027890816,"about_ca_topic_score_gemma":0.0000019653705,"teacher_disagreement_score":0.9085159,"about_ca_system_score_codex":0.00010443072,"about_ca_system_score_gemma":0.00016355542,"threshold_uncertainty_score":0.9998643},"labels":[],"label_agreement":null},{"id":"W2965361043","doi":"10.1038/s41467-019-11244-3","title":"Brainstem and spinal cord MRI identifies altered sensorimotor pathways post-stroke","year":2019,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":111,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Corticospinal tract; Brainstem; Spinal cord; Pyramidal tracts; Neuroscience; Stroke (engine); Medicine; Magnetic resonance imaging; Anatomy; Psychology; Diffusion MRI; Radiology","score_opus":0.058971944821037674,"score_gpt":0.36943882185410293,"score_spread":0.31046687703306525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965361043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9357777,0.006714959,0.001101921,0.038457338,0.00029688966,0.0022110916,0.00032873754,0.00085967785,0.014251692],"genre_scores_gemma":[0.9614126,0.00092618336,0.03422893,0.001863965,0.00005617601,0.00006317119,0.00011337805,0.000025491054,0.0013100986],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.999221,0.000039586193,0.0002002049,0.0002493378,0.0001371969,0.00015266838],"domain_scores_gemma":[0.9975083,0.0001225154,0.00009597379,0.0019783124,0.00020470818,0.00009019676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092138034,0.00012872607,0.00018989471,0.00009988602,0.0001921146,0.000033276196,0.0003762894,0.00014262107,0.000015614338],"category_scores_gemma":[0.000081032864,0.00012114076,0.000069711205,0.0001466488,0.00013525765,0.00010411191,0.00029458993,0.0008510496,0.000047385478],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004249901,0.00051616895,0.041125666,0.00020334408,0.000107175074,0.000008964202,0.00024651142,0.0000010847758,0.8094534,0.10149442,0.008809271,0.037608985],"study_design_scores_gemma":[0.001789771,0.0011414295,0.2964602,0.00036659988,0.00018822112,0.00053093693,0.0004621328,0.0011033998,0.018540649,0.0020365084,0.67678267,0.0005974781],"about_ca_topic_score_codex":0.000007739598,"about_ca_topic_score_gemma":0.000011958496,"teacher_disagreement_score":0.79091275,"about_ca_system_score_codex":0.000034316305,"about_ca_system_score_gemma":0.00004131198,"threshold_uncertainty_score":0.4939977},"labels":[],"label_agreement":null},{"id":"W2965413344","doi":"10.3389/fnagi.2019.00211","title":"Topographical Heterogeneity of Alzheimer’s Disease Based on MR Imaging, Tau PET, and Amyloid PET","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Fondation Brain Canada; Ministry of Science and ICT, South Korea; Korea Health Industry Development Institute; College of Medicine, Seoul National University; National Research Foundation; Fonds de Recherche du Québec - Santé; Seoul National University","keywords":"Atrophy; Dementia; Magnetic resonance imaging; Pittsburgh compound B; Positron emission tomography; Pathology; Medicine; Clinical Dementia Rating; Alzheimer's disease; Nuclear medicine; Disease; Radiology","score_opus":0.029856257097428607,"score_gpt":0.31957953744253653,"score_spread":0.2897232803451079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965413344","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97391266,0.00020313676,0.021975655,0.0026959125,0.00030383872,0.00055941724,0.000019509502,0.00012496553,0.00020492784],"genre_scores_gemma":[0.9810479,0.00006668882,0.016350053,0.0024528005,0.000012192733,0.000023242557,0.000003522473,0.000017565004,0.000026003196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986828,0.000035354456,0.00019986996,0.00055682706,0.00027168362,0.0002534848],"domain_scores_gemma":[0.99917114,0.000028774475,0.00008423383,0.0005156287,0.000024514335,0.0001757033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014106755,0.00014297706,0.00022167659,0.0002718281,0.000060628226,0.000018494693,0.00017943128,0.000008778938,0.0000034382115],"category_scores_gemma":[0.00007858795,0.00013485095,0.00006517396,0.00044297377,0.00037306335,0.0000985128,0.00007131559,0.00021166498,8.2199125e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046273537,0.00014226219,0.97442496,0.000034478922,9.221122e-7,0.00008723446,0.000009520291,0.00023086382,0.023351302,0.00016117879,0.00056133186,0.0009496625],"study_design_scores_gemma":[0.0007204929,0.00011759605,0.8414572,0.00016196416,0.000037690246,0.00005518875,0.000012159563,0.14771332,0.0069167353,0.00043731957,0.0021605678,0.00020979096],"about_ca_topic_score_codex":0.0000070698725,"about_ca_topic_score_gemma":2.769903e-7,"teacher_disagreement_score":0.14748245,"about_ca_system_score_codex":0.000018230772,"about_ca_system_score_gemma":0.00004301754,"threshold_uncertainty_score":0.5499062},"labels":[],"label_agreement":null},{"id":"W2965430693","doi":"10.1016/j.nicl.2019.101975","title":"White matter integrity is associated with gait impairment and falls in mild cognitive impairment. Results from the gait and brain study","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkwood Institute; Lawson Health Research Institute; Western University","funders":"Ontario Ministry of Research and Innovation; Canadian Institutes of Health Research; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Gait; Cognitive impairment; Physical medicine and rehabilitation; White matter; Cognition; Psychology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.07902827855567719,"score_gpt":0.3935651748319158,"score_spread":0.3145368962762386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965430693","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97641367,0.000022031238,0.000053850756,0.020497648,0.00003277045,0.002312281,0.00025406168,0.000086447755,0.00032723098],"genre_scores_gemma":[0.980263,0.000058229583,0.00046893643,0.018471222,0.000049966926,0.000064205116,0.000052183088,0.000037197944,0.00053506286],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976289,0.00033003106,0.0006378582,0.00087927957,0.00025133285,0.00027257882],"domain_scores_gemma":[0.99663657,0.0023736332,0.00021160727,0.0005468835,0.000090738984,0.00014054877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008157012,0.00023756384,0.00047814252,0.000048721697,0.000070831884,0.000052442654,0.00012975988,0.000097060925,0.000060846745],"category_scores_gemma":[0.0005114871,0.00015674513,0.00006545091,0.00020055208,0.00025454635,0.000096336255,0.00021992804,0.0011034576,0.000031731706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001031017,0.0012530689,0.98908263,0.000006263267,0.00003989586,0.00008209647,0.0006934512,1.5565398e-7,0.00004945065,0.0000019506883,0.00736261,0.00039740096],"study_design_scores_gemma":[0.008292593,0.0022128632,0.98769677,0.00023520137,0.00010282447,0.000021589743,0.0005604785,0.00024938944,0.00002296851,0.00012840342,0.00031882664,0.00015812449],"about_ca_topic_score_codex":0.000095428135,"about_ca_topic_score_gemma":0.00005335999,"teacher_disagreement_score":0.0072615757,"about_ca_system_score_codex":0.000027610586,"about_ca_system_score_gemma":0.00004210059,"threshold_uncertainty_score":0.63918805},"labels":[],"label_agreement":null},{"id":"W2965493050","doi":"10.1093/cercor/bhz143","title":"Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory","year":2019,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Neurological Institute and Hospital","funders":"Medical Research Council; Wellcome Trust","keywords":"Diffusion MRI; White matter; Neuroscience; Anterior commissure; Tractography; Corpus callosum; Psychology; Commissure; Temporal lobe; Hippocampal formation; Cingulum (brain); Anatomy; Fractional anisotropy; Hippocampus; Magnetic resonance imaging; Biology; Medicine","score_opus":0.044399753488846117,"score_gpt":0.3165180994592483,"score_spread":0.2721183459704022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965493050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98984003,0.00022153927,0.0027375347,0.0019229036,0.00010000245,0.001474085,0.000021133466,0.00015120162,0.0035315636],"genre_scores_gemma":[0.99573344,0.000018376957,0.0025604581,0.0008128835,0.00007083739,0.00014389656,0.000039708935,0.000020535384,0.0005998414],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9994584,0.000009000085,0.00013024577,0.00017771877,0.000076595956,0.00014808081],"domain_scores_gemma":[0.9995304,0.00009921289,0.00004293996,0.00026312214,0.00003528955,0.000029068375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086597305,0.00008005494,0.0001249707,0.00003380384,0.000047483656,0.000010329815,0.00008036611,0.000038094557,0.00009679477],"category_scores_gemma":[0.000029326622,0.000059780792,0.000056498557,0.00011369324,0.000024339903,0.000056514684,0.000029431216,0.00017064472,0.000041809733],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011317673,0.00049015414,0.1372574,0.00041919638,0.000080362195,0.000017550185,0.00083337055,0.0002849316,0.101352945,0.0021131383,0.007620505,0.74839866],"study_design_scores_gemma":[0.009543281,0.0012870161,0.5594148,0.00065251085,0.00029539884,0.00025784606,0.0018685639,0.028798552,0.031516626,0.09839428,0.26699457,0.000976583],"about_ca_topic_score_codex":0.0000344837,"about_ca_topic_score_gemma":0.000011392628,"teacher_disagreement_score":0.7474221,"about_ca_system_score_codex":0.000033452117,"about_ca_system_score_gemma":0.000025185267,"threshold_uncertainty_score":0.24377899},"labels":[],"label_agreement":null},{"id":"W2965530185","doi":"","title":"Non-negative least squares fitting of multi-exponential T2 decay data: Are we able to accurately measure the fraction of myelin water?","year":2019,"lang":"en","type":"article","venue":"Lund University Publications (Lund University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Exponential function; Fraction (chemistry); Myelin; Measure (data warehouse); Exponential decay; Least-squares function approximation; Mathematics; Chemistry; Biological system; Statistics; Internal medicine; Biology; Mathematical analysis; Physics; Chromatography; Medicine; Computer science; Data mining; Central nervous system","score_opus":0.14249787062635028,"score_gpt":0.328629429196639,"score_spread":0.18613155857028874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965530185","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42573667,0.000048811806,0.36959648,0.029696248,0.00018035379,0.004123876,0.0009492565,0.0005121447,0.16915615],"genre_scores_gemma":[0.86698407,0.00020311648,0.020051017,0.00015011031,0.00007635441,0.0000025275758,0.00043111588,0.00004301403,0.11205865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876696,0.000066838285,0.00020189483,0.00047888927,0.00024826394,0.00023713715],"domain_scores_gemma":[0.9975635,0.00013860353,0.00029997277,0.001180354,0.0006831388,0.00013444123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001700552,0.00016177392,0.00029371493,0.00057662436,0.00040502666,0.000023343444,0.00081974786,0.000099108685,0.00008598487],"category_scores_gemma":[0.00005463938,0.00014589523,0.00010347201,0.0012623629,0.00016285588,0.00084888894,0.0005030696,0.00028175995,0.00002633138],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032586842,0.0059633115,0.074853025,0.0011326368,0.0016900727,0.0000716144,0.008894395,0.0054233978,0.34104347,0.5177906,0.02807439,0.01180441],"study_design_scores_gemma":[0.0014861018,0.00012050495,0.0080165705,0.0001604715,0.0002834536,0.000008147194,0.0109664295,0.0027309465,0.015453846,0.000066246954,0.9604823,0.00022497225],"about_ca_topic_score_codex":0.00038882293,"about_ca_topic_score_gemma":0.00010414532,"teacher_disagreement_score":0.9324079,"about_ca_system_score_codex":0.00018424484,"about_ca_system_score_gemma":0.000147678,"threshold_uncertainty_score":0.5949435},"labels":[],"label_agreement":null},{"id":"W2965761097","doi":"10.2967/jnumed.118.225508","title":"Multimodal <sup>18</sup>F-AV-1451 and MRI Findings in Nonfluent Variant of Primary Progressive Aphasia: Possible Insights on Nodal Propagation of Tau Protein Across the Syntactic Network","year":2019,"lang":"en","type":"article","venue":"Journal of Nuclear Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Fractional anisotropy; White matter; Primary progressive aphasia; Aphasia; Node (physics); Fasciculus; Neuroscience; Neuroimaging; Psychology; Medicine; Magnetic resonance imaging; Physics; Disease; Pathology; Dementia; Frontotemporal dementia; Radiology","score_opus":0.023955157340165182,"score_gpt":0.31416947141654633,"score_spread":0.29021431407638115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965761097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99120796,0.00031346496,0.00030229113,0.0062787966,0.00004180934,0.0014339818,0.0000028974068,0.000015955018,0.00040283974],"genre_scores_gemma":[0.99422127,0.00010654417,0.0049237134,0.0004743166,0.00019149619,0.000013642253,0.0000025972724,0.000031538293,0.000034865687],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99831116,0.000078623925,0.00072774163,0.00019344184,0.0004808041,0.00020820534],"domain_scores_gemma":[0.998479,0.00016013053,0.000739313,0.00028863453,0.0002384095,0.00009448311],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005996969,0.00016044363,0.00056434266,0.00014101404,0.00007419312,0.000007990065,0.0001644555,0.000080927,0.000038436363],"category_scores_gemma":[0.00018787038,0.00009361733,0.000067359084,0.00034188936,0.0002519293,0.00014395437,0.00006319404,0.00065638317,0.0000018671989],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016589265,0.0058674957,0.05322526,0.004577762,0.000736646,0.0022529657,0.037475497,0.007844649,0.8159689,0.012049365,0.0065598614,0.03685237],"study_design_scores_gemma":[0.044404518,0.03964777,0.7281989,0.047051087,0.0011577695,0.010504736,0.00861236,0.057831332,0.029672563,0.0069489693,0.024747975,0.0012220556],"about_ca_topic_score_codex":0.000014924413,"about_ca_topic_score_gemma":5.662408e-7,"teacher_disagreement_score":0.7862963,"about_ca_system_score_codex":0.0000929509,"about_ca_system_score_gemma":0.000081957274,"threshold_uncertainty_score":0.3817604},"labels":[],"label_agreement":null},{"id":"W2966311196","doi":"10.3389/fneur.2019.00884","title":"Microstructural White Matter Characteristics in Parkinson's Disease With Depression: A Diffusion Tensor Imaging Replication Study","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Sanofi Genzyme; Genentech; H. Lundbeck A/S; Teva Pharmaceutical Industries; Union Chimique Belge; Sanofi; Biogen; GlaxoSmithKline; Servier; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; Michael J. Fox Foundation for Parkinson's Research","keywords":"Diffusion MRI; White matter; Neuroimaging; Neuropathology; Depression (economics); Psychology; Clinical psychology; Fractional anisotropy; Replication (statistics); Parkinson's disease; Neuroscience; Medicine; Disease; Psychiatry; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.010471842581975623,"score_gpt":0.2728891978692175,"score_spread":0.26241735528724186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966311196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99227417,0.00004311011,0.0017552455,0.004289251,0.00014172538,0.0013402868,0.000008387084,0.00007139185,0.00007641343],"genre_scores_gemma":[0.99210054,0.000017072465,0.0044432795,0.003008912,0.000032907647,0.00017226454,0.000033178185,0.0000338937,0.00015793297],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987058,0.00006001927,0.00024884316,0.00064595987,0.00010176566,0.00023762832],"domain_scores_gemma":[0.9989787,0.000017559842,0.00011144091,0.0007875448,0.000029597959,0.0000751707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006722962,0.0001508602,0.00028126058,0.00019603343,0.00003245119,0.000011061355,0.00012472043,0.000036849106,0.000024451183],"category_scores_gemma":[0.000022374177,0.00012465769,0.000024707126,0.00020369406,0.00006223186,0.000073349,0.000079759986,0.00034022657,0.000008473976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009781427,0.00017686957,0.9951237,0.000020247657,0.0000022375043,0.00015750324,0.00008007623,0.0000068920663,0.0007673235,0.000002061976,0.00091734057,0.001767625],"study_design_scores_gemma":[0.0013628213,0.00013739322,0.99067307,0.000030217176,0.00001889115,0.000084188374,0.000033815053,0.0025809954,0.000025305715,0.000109583685,0.004829345,0.000114377195],"about_ca_topic_score_codex":0.0000089355235,"about_ca_topic_score_gemma":0.0000022471497,"teacher_disagreement_score":0.004450613,"about_ca_system_score_codex":0.000029330242,"about_ca_system_score_gemma":0.00002022997,"threshold_uncertainty_score":0.5083393},"labels":[],"label_agreement":null},{"id":"W2967310397","doi":"10.3171/2019.5.jns19890","title":"Intraoperative acquisition of DTI in cranial neurosurgery: readout-segmented DTI versus standard single-shot DTI","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Diffusion MRI; Artifact (error); Multislice; Nuclear medicine; Magnetic resonance imaging; Tractography; Intraoperative MRI; Radiology; Interventional magnetic resonance imaging; Neuroscience","score_opus":0.10298990287274894,"score_gpt":0.3542022665953433,"score_spread":0.25121236372259437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967310397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99507743,0.00007747874,0.0007761416,0.0020271789,0.0009548345,0.00041695678,0.00003970454,0.000047527075,0.00058273115],"genre_scores_gemma":[0.9976152,0.00023808244,0.0010091093,0.0007754236,0.0002109073,0.000006579587,0.000010862834,0.000051270723,0.000082558116],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975513,0.00013911701,0.0011313965,0.00030405735,0.0005652846,0.00030883044],"domain_scores_gemma":[0.9977463,0.000519292,0.0007899723,0.00038524627,0.0003997415,0.00015943481],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044899472,0.00023809326,0.00079769397,0.00062062585,0.00004361868,0.00003083019,0.00014449384,0.00009109139,0.00010198125],"category_scores_gemma":[0.00033946172,0.00021400752,0.00027969753,0.00071788055,0.00010890954,0.00032974276,0.00005403913,0.000593472,0.000006386537],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011257082,0.00075153686,0.044993695,0.00009614659,0.000041707153,0.0006534736,0.000120634046,0.00019243293,0.93549883,0.0001192919,0.0031078,0.0031673864],"study_design_scores_gemma":[0.021774663,0.018638533,0.28235382,0.0028517712,0.00048462558,0.0033465517,0.00041254464,0.0009716044,0.6282965,0.00082531205,0.038730584,0.00131351],"about_ca_topic_score_codex":0.0000043946884,"about_ca_topic_score_gemma":0.0000010355919,"teacher_disagreement_score":0.30720234,"about_ca_system_score_codex":0.00013873994,"about_ca_system_score_gemma":0.00017335029,"threshold_uncertainty_score":0.87269735},"labels":[],"label_agreement":null},{"id":"W2967480225","doi":"10.1016/j.neurobiolaging.2019.08.011","title":"Tracking white matter degeneration in asymptomatic and symptomatic MAPT mutation carriers","year":2019,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health","keywords":"Asymptomatic; Asymptomatic carrier; White matter; Fractional anisotropy; Medicine; Mutation; Internal medicine; Psychology; Pathology; Genetics; Magnetic resonance imaging; Biology; Radiology","score_opus":0.021201181684875284,"score_gpt":0.29957009963799514,"score_spread":0.27836891795311985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967480225","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99672824,0.000029314479,0.0010397444,0.0013437436,0.000037335918,0.00035320836,0.0000016159192,0.000053477692,0.00041328956],"genre_scores_gemma":[0.99451256,0.000009097763,0.004633595,0.00071830297,0.00001092678,0.000017779132,0.000015184565,0.000014181676,0.00006836937],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993781,0.000034640583,0.00022389123,0.00020014399,0.000043920296,0.0001193163],"domain_scores_gemma":[0.9996413,0.000055195513,0.00009207694,0.00016233353,0.000024546089,0.000024560293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079095094,0.00008304954,0.00018472203,0.00014061903,0.000022109245,0.000005936878,0.000040301788,0.000040532785,0.000026135902],"category_scores_gemma":[0.000011132047,0.00007974469,0.000022551882,0.0001123185,0.00004946761,0.00007545824,0.000017231097,0.00011090075,0.000009511819],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068463596,0.00002040355,0.90807074,0.00016168803,0.0000044792228,0.0000032738994,0.0003151445,0.00020106943,0.0903116,0.00017113138,0.000040447798,0.00069317996],"study_design_scores_gemma":[0.00075121294,0.00013508444,0.9529942,0.0002320057,0.000032938908,0.00018818158,0.000108165164,0.0042088684,0.04064809,0.00053804443,0.00004207345,0.00012109083],"about_ca_topic_score_codex":0.000003916357,"about_ca_topic_score_gemma":0.0000016287395,"teacher_disagreement_score":0.049663506,"about_ca_system_score_codex":0.000016461843,"about_ca_system_score_gemma":0.000011636254,"threshold_uncertainty_score":0.3251894},"labels":[],"label_agreement":null},{"id":"W2967676857","doi":"10.1111/jon.12659","title":"Myelin Water Fraction and Intra/Extracellular Water Geometric Mean T<sub>2</sub>Normative Atlases for the Cervical Spinal Cord from 3T MRI","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Simon Fraser University; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research; International Collaboration on Repair Discoveries; National Institute for Health and Care Research; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Medicine; Spinal cord; Multiple sclerosis; Myelin; Population; Anatomy; Nuclear medicine; Central nervous system; Internal medicine","score_opus":0.04186393742645254,"score_gpt":0.31857417548462164,"score_spread":0.2767102380581691,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967676857","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86114633,0.0004066864,0.12591094,0.011821517,0.00018175061,0.00046449836,0.0000074033296,0.000039188446,0.000021672695],"genre_scores_gemma":[0.993402,0.0004900034,0.004533791,0.0010859905,0.00040148152,0.00001241379,0.000011386473,0.000038546666,0.000024390942],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99863875,0.00004501409,0.00049704115,0.00024264857,0.00028949018,0.00028706106],"domain_scores_gemma":[0.99888086,0.000279403,0.00022242712,0.00026676292,0.00023223854,0.00011828219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030773162,0.00018190118,0.00032953755,0.00024305194,0.00015705597,0.00007450774,0.0001533111,0.000042838004,0.000032784694],"category_scores_gemma":[0.000059030597,0.000097845135,0.00015226372,0.00014291036,0.000076672586,0.00035106187,0.000081030164,0.0006046732,0.00002256473],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000872758,0.000104065635,0.0034770416,0.000060841616,0.00005597077,0.00006178973,0.00013399901,0.000071461836,0.9616445,0.000042175576,0.0007197459,0.032755654],"study_design_scores_gemma":[0.0018572033,0.0013423583,0.023670645,0.00019473469,0.000393606,0.0013226131,0.00021867604,0.0072912197,0.9195865,0.0037103544,0.040160093,0.00025201376],"about_ca_topic_score_codex":0.000008698003,"about_ca_topic_score_gemma":4.0778042e-7,"teacher_disagreement_score":0.13225566,"about_ca_system_score_codex":0.000049824688,"about_ca_system_score_gemma":0.000018696475,"threshold_uncertainty_score":0.39900088},"labels":[],"label_agreement":null},{"id":"W2967827238","doi":"10.1097/pr9.0000000000000755","title":"Trigeminal nerve and white matter brain abnormalities in chronic orofacial pain disorders","year":2019,"lang":"en","type":"review","venue":"PAIN Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Connaught Fund; University of Toronto","keywords":"Orofacial pain; Trigeminal neuralgia; Diffusion MRI; Trigeminal nerve; Medicine; Temporomandibular joint; Chronic pain; White matter; Neuroscience; TMJ disorders; Magnetic resonance imaging; Pathology; Psychology; Anatomy; Radiology; Anesthesia; Physical therapy","score_opus":0.06113211186667545,"score_gpt":0.37753809467731836,"score_spread":0.3164059828106429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2967827238","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000042757154,0.99120367,0.0036888944,0.0010909649,0.000069463626,0.0022052908,0.0000173015,0.0001419262,0.0015397595],"genre_scores_gemma":[0.000215464,0.99236554,0.00095323974,0.0007639238,0.00017064669,0.000605552,0.00027928947,0.000093429866,0.0045529036],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99763393,0.0003388437,0.0008554249,0.0006333029,0.0001877712,0.00035073253],"domain_scores_gemma":[0.9983423,0.00039758068,0.00046633274,0.0006784203,0.000023141889,0.00009225567],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0021381427,0.00037516258,0.0012090717,0.00022901644,0.000048861533,0.000026612744,0.000080844904,0.00020174813,0.0001363078],"category_scores_gemma":[0.0002718456,0.0003168499,0.00024184918,0.00024456222,0.00010149041,0.000059524304,0.00008503023,0.0005176716,0.000013961581],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044754206,0.000041329906,0.013135629,0.016900303,0.000023979894,0.0004281151,0.00004275714,8.7125073e-7,7.263403e-7,0.000036415062,0.013069406,0.956316],"study_design_scores_gemma":[0.0001108691,0.000086993954,0.0004703257,0.0062709227,0.0001502416,0.00075360324,0.000016272073,0.000032807362,2.9152073e-7,0.0004436255,0.99136657,0.00029748664],"about_ca_topic_score_codex":0.00004953018,"about_ca_topic_score_gemma":0.000018034398,"teacher_disagreement_score":0.9782972,"about_ca_system_score_codex":0.00022812425,"about_ca_system_score_gemma":0.00031202743,"threshold_uncertainty_score":0.99992836},"labels":[],"label_agreement":null},{"id":"W2968037752","doi":"10.1016/s1474-4422(19)30138-3","title":"MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers","year":2019,"lang":"en","type":"review","venue":"The Lancet Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":208,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"Horizon 2020; Canadian Institutes of Health Research; European Research Council; International Foundation for CDKL5 Research; H2020 European Research Council; Eisai; International Foundation for Research in Paraplegia; Siemens; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; F. Hoffmann-La Roche; Singapore Eye Research Institute; University College London Hospitals NHS Foundation Trust; European Commission; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Wings for Life; International Spinal Research Trust; University College London; Staatssekretariat für Bildung, Forschung und Innovation; Craig H. Neilsen Foundation; Wellcome Trust","keywords":"Medicine; Neuroimaging; Magnetic resonance imaging; Spinal cord; Spinal cord injury; Traumatic brain injury; Spinal cord compression; Radiology; Physical medicine and rehabilitation","score_opus":0.3661599137340523,"score_gpt":0.5518174254858047,"score_spread":0.18565751175175238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968037752","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030091107,0.8906628,0.005329103,0.0846977,0.001830922,0.010275141,0.00031893188,0.00082100736,0.0030552964],"genre_scores_gemma":[0.00038465112,0.97683924,0.005420632,0.016102592,0.0006309734,0.00039695564,0.000077000295,0.000106991196,0.000040947853],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99668515,0.00064347556,0.0010307471,0.00092228974,0.00019537313,0.00052298384],"domain_scores_gemma":[0.99692947,0.00075678894,0.00040467564,0.0017490216,0.000028184259,0.00013183594],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006082631,0.00042211486,0.002633098,0.00022235102,0.000053412656,0.00002483264,0.0007794885,0.00021240916,0.000035042463],"category_scores_gemma":[0.00011963004,0.0002926369,0.00035742347,0.0005124949,0.00016596486,0.000033138105,0.000340618,0.001989644,0.00017643064],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051076926,0.00013452307,0.0010621424,0.0013795574,0.00006848194,0.0000906864,0.0000053303515,0.0000010295029,0.00000545004,0.00039859407,0.00969539,0.986648],"study_design_scores_gemma":[0.00043969153,0.0014558353,0.008112506,0.0015104699,0.0005720119,0.00012512684,0.0000015764775,0.00013010789,2.4971862e-7,0.00052850234,0.986901,0.00022291971],"about_ca_topic_score_codex":0.000037314,"about_ca_topic_score_gemma":0.0000057544094,"teacher_disagreement_score":0.9864251,"about_ca_system_score_codex":0.000049329275,"about_ca_system_score_gemma":0.00019676931,"threshold_uncertainty_score":0.99995255},"labels":[],"label_agreement":null},{"id":"W2968327236","doi":"10.1002/hbm.24760","title":"Neurite orientation dispersion and density imaging (NODDI) and free‐water imaging in Parkinsonism","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":116,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"High Magnetic Field Laboratory, Chinese Academy of Sciences; Division of Materials Research; McKnight Foundation; National Institute of Neurological Disorders and Stroke; National High Magnetic Field Laboratory; National Institutes of Health; National Science Foundation","keywords":"Parkinsonism; Corpus callosum; Globus pallidus; Basal ganglia; Neuroscience; Cerebellum; Fractional anisotropy; Thalamus; Midbrain; Striatum; Substantia nigra; Diffusion MRI; Psychology; Chemistry; Pathology; Anatomy; Magnetic resonance imaging; Biology; Medicine; Dopaminergic; Central nervous system; Radiology; Dopamine","score_opus":0.027206375517248926,"score_gpt":0.3040667323848043,"score_spread":0.2768603568675554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968327236","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870586,0.000084822306,0.00472715,0.007054626,0.000025883035,0.0004036708,0.0000014352045,0.00012041932,0.0005234373],"genre_scores_gemma":[0.9950255,0.000025848676,0.002774363,0.0018716941,0.00003896752,0.0000146089815,0.000023444147,0.000021607864,0.00020392574],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991178,0.000027218935,0.00017319324,0.00037395587,0.00009855828,0.00020925514],"domain_scores_gemma":[0.9995527,0.000040408675,0.000042736778,0.00027836117,0.000025239662,0.00006052662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018717325,0.00011883801,0.00015184293,0.00015612585,0.00015960561,0.000044118147,0.000053018495,0.000020086633,0.000016920863],"category_scores_gemma":[0.000025983989,0.000108597524,0.000022242866,0.00007795128,0.00007194432,0.00018692219,0.00015092034,0.00017293615,0.0000048798356],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008732556,0.000019561206,0.46420383,0.00006288252,0.0000017039207,0.000024712916,0.0007591791,0.0000012595201,0.52872574,0.0011335488,0.00034009392,0.0047187423],"study_design_scores_gemma":[0.0014281236,0.000021711832,0.9645568,0.00026241902,0.000012534141,0.00014599462,0.0003237991,0.0041577066,0.0026341653,0.009467221,0.01677381,0.00021568795],"about_ca_topic_score_codex":0.000049982667,"about_ca_topic_score_gemma":0.000004230657,"teacher_disagreement_score":0.5260916,"about_ca_system_score_codex":0.000035695433,"about_ca_system_score_gemma":0.000004931414,"threshold_uncertainty_score":0.44284785},"labels":[],"label_agreement":null},{"id":"W2969721658","doi":"10.1038/s41386-019-0485-6","title":"Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals","year":2019,"lang":"en","type":"review","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":235,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"National Institute on Aging; National Center for Mental Health; European Regional Development Fund; Instituto de Salud Carlos III; Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Dalhousie University; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Norges Forskningsråd; Dainippon Sumitomo Pharma; National Institute of Mental Health; Fondation pour la Recherche Médicale; South African Medical Research Council; Departament d'Innovació, Universitats i Empresa, Generalitat de Catalunya; Generalitat de Catalunya; University of Edinburgh; Sanofi; European Commission; Nova Scotia Health Research Foundation; Deutsche Forschungsgemeinschaft; H. Lundbeck A/S; Centres de Recerca de Catalunya; Ministerio de Ciencia, Innovación y Universidades; Universitetet i Oslo; Allergan; Fundação de Amparo à Pesquisa do Estado de São Paulo; Royal College of Physicians of Edinburgh; NIH Clinical Center; Agence Nationale de la Recherche; Fondation de l'Avenir pour la Recherche Médicale Appliquée; Wellcome Trust; Biogen; Centro de Investigación Biomédica en Red de Salud Mental; National Alliance for Research on Schizophrenia and Depression","keywords":"Corpus callosum; Fractional anisotropy; White matter; Diffusion MRI; Cingulum (brain); Bipolar disorder; Medicine; Internal medicine; Psychology; Biomarker; Cardiology; Neuroscience; Magnetic resonance imaging; Lithium (medication); Biology; Radiology; Genetics","score_opus":0.2973544460892999,"score_gpt":0.513220610675638,"score_spread":0.21586616458633806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969721658","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0075062937,0.9876364,0.0000764733,0.001184748,0.0003328673,0.0020902483,0.0009919618,0.0001377344,0.000043314445],"genre_scores_gemma":[0.00066738686,0.9911601,0.0024782384,0.0035995438,0.00013739486,0.0006388878,0.00016520267,0.00014712191,0.0010061213],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99611783,0.0005586506,0.0011361232,0.0013057801,0.00025164883,0.000629966],"domain_scores_gemma":[0.99716085,0.0010596801,0.00062808907,0.00090593006,0.00007447324,0.00017094906],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002246207,0.0008116693,0.0034586017,0.00032682472,0.00011100715,0.00007953252,0.0005362466,0.00032409624,0.0010094706],"category_scores_gemma":[0.00006991681,0.00060802413,0.00068005075,0.00053854054,0.00034204288,0.00024884986,0.00039862114,0.0013221592,0.00013975546],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051742996,0.0006406994,0.07701477,0.034385335,0.013495832,0.0011648424,0.0014983162,0.000025820134,0.011233448,0.000038838934,0.041531876,0.8184528],"study_design_scores_gemma":[0.00063042715,0.00010258776,0.006776119,0.00070327776,0.02233012,0.00051225885,0.000011461662,0.000005285303,0.000049082664,0.00007696539,0.96831274,0.00048966805],"about_ca_topic_score_codex":0.00012956925,"about_ca_topic_score_gemma":0.000009725855,"teacher_disagreement_score":0.9267809,"about_ca_system_score_codex":0.000058722566,"about_ca_system_score_gemma":0.00009212032,"threshold_uncertainty_score":0.99990374},"labels":[],"label_agreement":null},{"id":"W2970275262","doi":"10.1038/s41380-019-0477-2","title":"White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group","year":2019,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":373,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Instituto de Salud Carlos III; National Health and Medical Research Council; Rivierduinen; University of California, San Francisco; GGZ inGeest; National Institutes of Health; Vrije Universiteit Amsterdam; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Centro de Investigación Biomédica en Red de Salud Mental; National Alliance for Research on Schizophrenia and Depression; ZonMw; Medical Research Council; Leids Universitair Medisch Centrum; Universiteit Leiden; Universitair Medisch Centrum Groningen; University of Minnesota; Science Foundation Ireland; American Foundation for Suicide Prevention; European Commission; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Deutsche Forschungsgemeinschaft; GlaxoSmithKline; European Regional Development Fund; National Healthcare Group; Rappaport Foundation; Brain and Behavior Research Foundation","keywords":"Fractional anisotropy; Major depressive disorder; Corpus callosum; White matter; Psychology; Diffusion MRI; Depression (economics); Neuroimaging; Psychiatry; Clinical psychology; Internal medicine; Medicine; Neuroscience; Magnetic resonance imaging; Cognition","score_opus":0.009484764895849637,"score_gpt":0.3067051679151785,"score_spread":0.29722040301932884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970275262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9618977,0.0006845129,0.021297256,0.013110599,0.00015232773,0.00068750634,0.000016239199,0.000052895943,0.0021010027],"genre_scores_gemma":[0.9931863,0.000023050174,0.0034919037,0.0027307603,0.000032203043,0.00019245091,0.00013226848,0.00002239926,0.00018866187],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987993,0.000054015396,0.00027867424,0.0004126068,0.00021389732,0.00024146365],"domain_scores_gemma":[0.99930775,0.000024530096,0.000111204594,0.0004993422,0.000025024718,0.000032162327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013509353,0.00015288948,0.00025133148,0.00016898898,0.000049003047,0.00004437858,0.00029438297,0.00005205951,0.00007659282],"category_scores_gemma":[0.000007701501,0.000120171535,0.0001410307,0.0008872399,0.0000460724,0.000058671314,0.00007501428,0.00031445466,0.000016764756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048178335,0.00019385955,0.9977525,0.000014620835,0.0000765352,0.000034073866,0.00014355923,0.00024433606,0.00040505934,0.0004182442,0.000383334,0.00028571044],"study_design_scores_gemma":[0.0010706023,0.000026675432,0.99250275,0.00010230983,0.00010617438,0.000026084923,0.00021856549,0.0011560058,0.00005785972,0.0014402767,0.0031358756,0.00015682794],"about_ca_topic_score_codex":0.000066788234,"about_ca_topic_score_gemma":0.000359521,"teacher_disagreement_score":0.03128864,"about_ca_system_score_codex":0.00003408188,"about_ca_system_score_gemma":0.000012992655,"threshold_uncertainty_score":0.49004528},"labels":[],"label_agreement":null},{"id":"W2970385260","doi":"10.1016/j.jhevol.2019.102654","title":"Trabecular bone structure scales allometrically in the foot of four human groups","year":2019,"lang":"en","type":"article","venue":"Journal of Human Evolution","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"H2020 European Research Council; Biotechnology and Biological Sciences Research Council; Arts and Humanities Research Council; European Commission; Pennsylvania State University","keywords":"Allometry; Calcaneus; Biology; Anatomy; Scaling; Mathematics; Geometry; Ecology","score_opus":0.044660875609583095,"score_gpt":0.3403876264091231,"score_spread":0.29572675079954003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970385260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995189,0.00037070835,0.00320552,0.00072125776,0.000023555878,0.00024133571,0.0000024356511,0.0000108863305,0.00023529088],"genre_scores_gemma":[0.9967606,0.000020057909,0.002958366,0.000098767225,0.00010211839,0.0000019627648,0.000003428171,0.0000106996,0.00004397209],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99890804,0.000050495106,0.0004870345,0.00009506425,0.00034766464,0.00011169983],"domain_scores_gemma":[0.99914944,0.000043973003,0.0004119853,0.00023178838,0.00012759029,0.000035196113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034830786,0.0000830765,0.00030267364,0.00033601956,0.000050501927,0.000007309237,0.00015738285,0.000051578256,0.000025494517],"category_scores_gemma":[0.000058867772,0.000054115964,0.00014784608,0.00035005176,0.00005481475,0.000089143665,0.000017376886,0.00036706516,9.0446e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051213647,0.00031247703,0.06431602,0.000081339145,0.000030383586,0.00003531447,0.00019730492,0.00006741821,0.90659815,0.026285972,0.000961388,0.0010629995],"study_design_scores_gemma":[0.0011920929,0.0011906511,0.9474321,0.00019593588,0.00008983032,0.0005728394,0.0001760118,0.00010012759,0.0033299106,0.045036588,0.0005903084,0.000093611685],"about_ca_topic_score_codex":0.000007555637,"about_ca_topic_score_gemma":0.00000929498,"teacher_disagreement_score":0.9032683,"about_ca_system_score_codex":0.00008794899,"about_ca_system_score_gemma":0.000020899288,"threshold_uncertainty_score":0.22067851},"labels":[],"label_agreement":null},{"id":"W2970513362","doi":"10.1002/epi4.12357","title":"Regional hippocampal diffusion abnormalities associated with subfield‐specific pathology in temporal lobe epilepsy","year":2019,"lang":"en","type":"article","venue":"Epilepsia Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Temporal lobe; Hippocampal sclerosis; Fractional anisotropy; Hippocampus; Hippocampal formation; Pathology; Medicine; Epilepsy; Epilepsy surgery; Psychology; Radiology; Neuroscience; Magnetic resonance imaging; Internal medicine","score_opus":0.06874866591562907,"score_gpt":0.33065790928720207,"score_spread":0.261909243371573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970513362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97878736,0.000057813115,0.0006317491,0.004461694,0.000058643418,0.0014356764,0.000016228856,0.00013806646,0.014412765],"genre_scores_gemma":[0.989011,0.00010212022,0.004716142,0.0016099185,0.00005007027,0.00017135705,0.00023094367,0.000038124228,0.004070356],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986167,0.00008262851,0.00031900394,0.00045209168,0.00020547076,0.00032411976],"domain_scores_gemma":[0.9990128,0.00013173398,0.00014848876,0.00054459885,0.00007020517,0.00009216616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026637272,0.00018597832,0.00041312238,0.00010813007,0.00007281814,0.000039542603,0.00032807572,0.00011735368,0.0004651766],"category_scores_gemma":[0.00003226309,0.00015292157,0.00005308402,0.00029977295,0.00010692312,0.00019693251,0.00019932425,0.00039304295,0.00008080835],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045586991,0.0004064047,0.97580004,0.00001899936,0.000013453498,0.00022200697,0.00028058534,0.000009275553,0.0021147472,0.009711463,0.009528614,0.0014385277],"study_design_scores_gemma":[0.003330137,0.00070500764,0.9348596,0.0003404215,0.000017652726,0.00024062452,0.0002999397,0.00017569643,0.00044564987,0.0056976257,0.053551823,0.00033582863],"about_ca_topic_score_codex":0.00009684848,"about_ca_topic_score_gemma":0.000045708213,"teacher_disagreement_score":0.04402321,"about_ca_system_score_codex":0.00009354275,"about_ca_system_score_gemma":0.00008212029,"threshold_uncertainty_score":0.623596},"labels":[],"label_agreement":null},{"id":"W2971074351","doi":"10.1002/hbm.24774","title":"Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute on Aging; National Institutes of Health","keywords":"Cingulum (brain); White matter; Corpus callosum; Fornix; Univariate; Neuroscience; Fractional anisotropy; Psychology; Anatomy; Multivariate statistics; Biology; Medicine; Magnetic resonance imaging; Hippocampus","score_opus":0.03456366577798601,"score_gpt":0.3363201265224972,"score_spread":0.3017564607445112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971074351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91653347,0.000056498,0.06779667,0.014846111,0.00002140063,0.0005111928,0.000035287234,0.00005626531,0.00014310319],"genre_scores_gemma":[0.99532586,0.00000320306,0.0018780271,0.0024214138,0.000040964143,0.000021670709,0.000121959085,0.000014380416,0.00017252502],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988554,0.00006427371,0.0004173895,0.00031563107,0.00012822058,0.00021908643],"domain_scores_gemma":[0.99928236,0.000116783805,0.00015649183,0.0002960834,0.00006627357,0.00008199023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023070542,0.00012182576,0.00037882078,0.00045487893,0.00010563017,0.000017735367,0.000049365968,0.00007181133,0.0001931966],"category_scores_gemma":[0.00008942498,0.00012211049,0.000089121364,0.0006643946,0.00010459806,0.00006266312,0.00005291882,0.00032233688,0.0000078951925],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036878133,0.000056949826,0.8037332,0.000101325255,0.000043466316,0.0000032169678,0.00041622788,0.00018175192,0.1917591,0.0020166638,0.0015894081,0.000061768566],"study_design_scores_gemma":[0.00089347403,0.0000817829,0.9915498,0.00010830609,0.00006866847,0.000024094994,0.00017503329,0.004725235,0.00023817633,0.0007816666,0.001242803,0.00011094728],"about_ca_topic_score_codex":0.000033969947,"about_ca_topic_score_gemma":0.000010737312,"teacher_disagreement_score":0.19152091,"about_ca_system_score_codex":0.000059175356,"about_ca_system_score_gemma":0.000023170822,"threshold_uncertainty_score":0.4979521},"labels":[],"label_agreement":null},{"id":"W2971116709","doi":"10.1002/hbm.24771","title":"MR‐based age‐related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan","year":2019,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":76,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Weston Brain Institute; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Alzheimer's Society; Fonds de Recherche du Québec - Santé; Michael J. Fox Foundation for Parkinson's Research","keywords":"Globus pallidus; Striatum; Psychology; Putamen; Magnetic resonance imaging; Basal ganglia; Thalamus; Neuroscience; Central nervous system; Medicine; Radiology; Dopamine","score_opus":0.05756960529907895,"score_gpt":0.3559492060056729,"score_spread":0.298379600706594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971116709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95318586,0.00008640615,0.00020769497,0.043457706,0.00004050252,0.0019164787,0.000008743068,0.00017560976,0.00092099386],"genre_scores_gemma":[0.98195386,0.00002011445,0.0003635004,0.017171854,0.00006568026,0.00015420672,0.000026429934,0.000031543386,0.00021282733],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99857455,0.00017489104,0.00028792748,0.00037977792,0.00021960348,0.0003632354],"domain_scores_gemma":[0.99808556,0.0010430164,0.0001467417,0.0006212488,0.000031067666,0.000072352814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006165122,0.00018692095,0.00025353077,0.00007397917,0.00035847217,0.000056398007,0.00021060211,0.00008770513,0.000017147167],"category_scores_gemma":[0.00024277267,0.00011787112,0.0000578519,0.0003395421,0.00012320718,0.000038163787,0.00008837459,0.0006244327,0.000019815137],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003980308,0.00085019076,0.64711016,0.0014453166,0.00020476432,0.0002585424,0.012986813,0.00023450622,0.11313405,0.17943472,0.01735087,0.026592055],"study_design_scores_gemma":[0.002878197,0.00045737578,0.97231245,0.00087435305,0.000017033039,0.000018269982,0.00040807918,0.0005889374,0.00057904393,0.007865654,0.013765693,0.00023488587],"about_ca_topic_score_codex":0.000039310693,"about_ca_topic_score_gemma":0.000017090357,"teacher_disagreement_score":0.32520232,"about_ca_system_score_codex":0.000053375832,"about_ca_system_score_gemma":0.000029985153,"threshold_uncertainty_score":0.48066446},"labels":[],"label_agreement":null},{"id":"W2971514011","doi":"10.1016/j.neuroimage.2019.116156","title":"Construction of a rat spinal cord atlas of axon morphometry","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Fondation Institut de Cardiologie de Montréal; Canada First Research Excellence Fund; Canada Foundation for Innovation","keywords":"White matter; Spinal cord; Axon; Atlas (anatomy); Brain atlas; Neuroscience; Anatomy; Segmentation; Biology; Myelin; Central nervous system; Medicine; Magnetic resonance imaging; Computer science; Artificial intelligence; Radiology","score_opus":0.05231506742740956,"score_gpt":0.3515690291370087,"score_spread":0.29925396170959917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971514011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9923691,0.000042657575,0.0026993076,0.00032068425,0.00011716903,0.00039684895,0.000009219102,0.00007986215,0.0039651156],"genre_scores_gemma":[0.9748456,0.00006298247,0.024548864,0.00013903466,0.00002445661,0.0000078256935,0.0000067675805,0.000017775743,0.0003467045],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992789,0.000013525864,0.00023795693,0.00020704293,0.00015654032,0.00010602772],"domain_scores_gemma":[0.99925536,0.000029950497,0.00016124763,0.00041865092,0.00009193016,0.000042858526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004317779,0.00008759825,0.00023147585,0.00011746085,0.000014358197,0.0000026577193,0.00007674095,0.00003211965,0.000094318726],"category_scores_gemma":[0.000043296903,0.00008285696,0.00007774546,0.00027880442,0.00013065473,0.000055951936,0.000041673615,0.0001497151,0.000020979875],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003495337,0.00009596428,0.028052712,0.00015727065,0.0000050376443,0.0000080890295,0.0000036400372,9.729255e-7,0.9596714,0.0021855661,0.00070903165,0.00876079],"study_design_scores_gemma":[0.00166698,0.0033188958,0.1467099,0.00023328858,0.00009755293,0.00054023665,0.00004822983,0.0003206169,0.8230277,0.0011868504,0.02265085,0.00019895831],"about_ca_topic_score_codex":0.0000073896426,"about_ca_topic_score_gemma":8.658271e-8,"teacher_disagreement_score":0.13664375,"about_ca_system_score_codex":0.000010481794,"about_ca_system_score_gemma":0.000026751137,"threshold_uncertainty_score":0.33788088},"labels":[],"label_agreement":null},{"id":"W2971691110","doi":"10.1007/s11682-019-00183-8","title":"Verbal memory and hippocampal volume predict subsequent fornix microstructure in those at risk for Alzheimer’s disease","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Science and Technology Planning Project of Guangdong Province; Canadian Institutes of Health Research; National Institutes of Health; Genentech; University of Hong Kong; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fornix; Fractional anisotropy; Memory impairment; Psychology; Hippocampus; Hippocampal formation; Neuroscience; Diffusion MRI; Medicine; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.031838480286548794,"score_gpt":0.32795009339339315,"score_spread":0.29611161310684436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2971691110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99367434,0.0018833842,0.00035654675,0.0020632865,0.00006981488,0.0015053521,0.00029376027,0.0001230329,0.000030503532],"genre_scores_gemma":[0.99370414,0.00012584832,0.004461205,0.0006461153,0.00006521136,0.00029655767,0.000110763394,0.000038526934,0.000551623],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990022,0.00002062445,0.00018351708,0.00044139358,0.000097632226,0.0002546317],"domain_scores_gemma":[0.9993497,0.000058828322,0.0000720528,0.0003027487,0.000032020038,0.0001846274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011916095,0.00016961625,0.00020348902,0.00007363067,0.000107252425,0.000026577447,0.00006013489,0.000038688,0.00002113973],"category_scores_gemma":[0.000038498783,0.00015425895,0.000058823687,0.000069265916,0.00012593609,0.000084903586,0.00008500912,0.00017819933,0.0000032034598],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002082316,0.00009026945,0.94432527,0.00005807481,0.000005826013,0.000029027045,0.00012714868,0.0000012906373,0.010792549,0.00002650753,0.0028753283,0.041460488],"study_design_scores_gemma":[0.0022792635,0.00010295459,0.9837968,0.00012400796,0.00039274886,0.00014718351,0.00008239338,0.0015802643,0.0009881303,0.0005167044,0.009753594,0.00023599497],"about_ca_topic_score_codex":0.00003295356,"about_ca_topic_score_gemma":0.0000044975313,"teacher_disagreement_score":0.04122449,"about_ca_system_score_codex":0.00004286528,"about_ca_system_score_gemma":0.00003496711,"threshold_uncertainty_score":0.6290497},"labels":[],"label_agreement":null},{"id":"W2972389188","doi":"10.1038/s41380-019-0509-y","title":"White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study","year":2019,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":187,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Medical Research Council; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Neuroscience; Magnetic resonance imaging; Medicine; Psychiatry; Gerontology; Radiology","score_opus":0.02070048841522074,"score_gpt":0.32664578529911775,"score_spread":0.305945296883897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972389188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97810185,0.0002589426,0.014329337,0.0052551273,0.00016809467,0.0014191275,0.000024534258,0.00011929692,0.0003237056],"genre_scores_gemma":[0.9700186,0.000016596763,0.026485156,0.002086859,0.00004771854,0.000103795384,0.000014618657,0.000045782,0.0011808443],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987919,0.000063574815,0.00031556105,0.00033993213,0.00024540824,0.00024364644],"domain_scores_gemma":[0.99871033,0.000016723738,0.00014301502,0.0009946227,0.00007157979,0.00006373437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014861088,0.00018460142,0.00027856528,0.000052514213,0.00010678597,0.000023480525,0.00021489582,0.00004642837,0.00007249758],"category_scores_gemma":[0.0000065569066,0.00013065037,0.00015420804,0.00022593007,0.00007859665,0.000049106035,0.00016331839,0.0002915219,0.00010536663],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000221558,0.0007754576,0.9833022,0.00008656561,0.00004974348,0.000008619751,0.0008706633,0.000017348948,0.013442747,0.00024614943,0.0008334338,0.0001455558],"study_design_scores_gemma":[0.005789079,0.0004133628,0.98516405,0.00016333217,0.00016286985,0.00009355738,0.0016240982,0.00041966885,0.0028681958,0.00058673834,0.0024149304,0.00030012155],"about_ca_topic_score_codex":0.00003428465,"about_ca_topic_score_gemma":0.000009814173,"teacher_disagreement_score":0.012155821,"about_ca_system_score_codex":0.000012816476,"about_ca_system_score_gemma":0.000034814067,"threshold_uncertainty_score":0.5327767},"labels":[],"label_agreement":null},{"id":"W2972624218","doi":"10.1177/0891988719874132","title":"Clinical and Diffusion Tensor Imaging to Evaluate Falls, Balance and Gait Dysfunction in Leukoaraiosis: an Observational, Prospective Cohort Study","year":2019,"lang":"en","type":"article","venue":"Journal of Geriatric Psychiatry and Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Impact","funders":"Beijing Municipal Science and Technology Commission","keywords":"Fractional anisotropy; Medicine; Corpus callosum; Berg Balance Scale; Diffusion MRI; White matter; Leukoaraiosis; Physical therapy; Physical medicine and rehabilitation; Balance (ability); Poison control; Gait; Internal capsule; Magnetic resonance imaging; Internal medicine; Radiology; Pathology","score_opus":0.049511954185200914,"score_gpt":0.3782518935606128,"score_spread":0.32873993937541185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972624218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916864,0.00038939944,0.00027937544,0.006339544,0.00033916792,0.0009038849,0.0000016761655,0.000018722223,0.00004179711],"genre_scores_gemma":[0.9937253,0.0007658881,0.0027633428,0.0024538247,0.0002317331,0.000020449224,0.0000010755948,0.000014021108,0.000024381003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986893,0.00013546574,0.00052251504,0.00036861593,0.0001480308,0.00013610105],"domain_scores_gemma":[0.9992353,0.00009583383,0.00025244133,0.00017070641,0.000112439346,0.00013331715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006270352,0.00012403411,0.00038577104,0.00018956562,0.00006325588,0.000015942645,0.00005733532,0.00005429247,0.0000058693554],"category_scores_gemma":[0.00008204316,0.00010182718,0.000033152486,0.00022335828,0.000053597247,0.00016301732,0.00005410788,0.00040884592,9.370986e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009379726,0.00046670085,0.9962469,0.000017065327,0.000014334406,0.000012550687,0.00004769978,0.000006404951,0.0005978967,0.00011148929,0.00012503566,0.0014159948],"study_design_scores_gemma":[0.0028266117,0.003185773,0.9904694,0.00002307617,0.000094315896,0.0005684812,0.00006453279,0.0009498273,0.0000018897609,0.0014018215,0.0003306209,0.00008365657],"about_ca_topic_score_codex":0.0000066617035,"about_ca_topic_score_gemma":0.0000045472075,"teacher_disagreement_score":0.005777462,"about_ca_system_score_codex":0.000009876694,"about_ca_system_score_gemma":0.00005390381,"threshold_uncertainty_score":0.41523919},"labels":[],"label_agreement":null},{"id":"W2972685576","doi":"10.1016/b978-2-294-76430-1.00001-9","title":"Définition et interinfluence de ces trois cerveaux","year":2019,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Collège d'Études Ostéopathiques de Montréal","funders":"","keywords":"Humanities; Geography; Art","score_opus":0.0673091011149228,"score_gpt":0.35029645579318697,"score_spread":0.2829873546782642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972685576","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009461895,0.0013079667,0.0031491355,0.0015659305,0.0003821336,0.0013245415,0.0001553501,0.00033608038,0.9908327],"genre_scores_gemma":[0.056637436,0.0028124254,0.02248642,0.00551786,0.0007000789,0.00021811368,0.00011419563,0.0002397666,0.9112737],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977474,0.00006367118,0.00062539836,0.00073490915,0.0002872486,0.0005413243],"domain_scores_gemma":[0.9979564,0.00022289492,0.00038506053,0.0010406168,0.00015017427,0.00024486074],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00030050817,0.00056769024,0.0006684536,0.0001700084,0.00012916826,0.000049124203,0.0003735153,0.00033711386,0.0004945559],"category_scores_gemma":[0.00007093539,0.0005822413,0.00034187737,0.000026879497,0.0004206652,0.00009879312,0.0002298897,0.0010798307,0.00091493706],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035978155,0.00003168168,0.00018072865,0.00037826927,0.00005430663,0.00007427203,0.00013555393,0.0000065201034,0.004905843,0.21848011,0.000070475115,0.77564627],"study_design_scores_gemma":[0.00039879946,0.00029289591,0.0005595123,0.0029967674,0.00028084472,0.00034079168,0.000013839973,0.00011760977,0.0020611167,0.036309414,0.956117,0.0005114146],"about_ca_topic_score_codex":0.0000033450383,"about_ca_topic_score_gemma":0.000006969767,"teacher_disagreement_score":0.9560465,"about_ca_system_score_codex":0.00028475394,"about_ca_system_score_gemma":0.00029736833,"threshold_uncertainty_score":0.99986297},"labels":[],"label_agreement":null},{"id":"W2973102543","doi":"10.1101/766139","title":"Evaluation of six phase encoding based susceptibility distortion correction methods for diffusion MRI","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"ITEA3; Vetenskapsrådet; Linköpings Universitet; VINNOVA; ITEA","keywords":"Diffusion MRI; Encoding (memory); Ground truth; Preprocessor; Computer science; Diffusion; Phase (matter); Distortion (music); Standard deviation; Algorithm; Data mining; Artificial intelligence; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.0916819829983843,"score_gpt":0.40826539191435013,"score_spread":0.3165834089159658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973102543","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3066053,0.00018218295,0.6883116,0.000150138,0.0008984129,0.0034278089,0.000105707135,0.0003102811,0.000008587136],"genre_scores_gemma":[0.8222026,0.00005520048,0.17656156,0.000061243234,0.00016754573,0.00086384616,0.0000055163164,0.00007862671,0.000003838627],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972481,0.00031485016,0.0006694879,0.0009511064,0.000545327,0.00027111085],"domain_scores_gemma":[0.9953559,0.00024361233,0.0007775625,0.0014557245,0.002032874,0.00013434023],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0032963364,0.00035641756,0.00060788594,0.00027240926,0.00012330835,0.000028574317,0.0001878441,0.00034005052,0.000034312874],"category_scores_gemma":[0.0014345549,0.00037637912,0.00026573637,0.00034987152,0.00008985307,0.000094442934,0.00012743862,0.00047679513,0.0000030307808],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016510728,0.0006855939,0.0036690573,0.0006267243,0.00004173548,4.3449842e-7,0.0000049377827,0.000488873,0.99351627,0.00007769273,0.00021878685,0.0005048005],"study_design_scores_gemma":[0.0020382474,0.00025396576,0.017752402,0.0005622565,0.0009503809,1.5252496e-8,0.0000017342787,0.29405308,0.6819656,0.000025958827,0.0020665708,0.00032980595],"about_ca_topic_score_codex":0.000021201788,"about_ca_topic_score_gemma":9.4361405e-7,"teacher_disagreement_score":0.5155973,"about_ca_system_score_codex":0.00082700927,"about_ca_system_score_gemma":0.0007700478,"threshold_uncertainty_score":0.9998688},"labels":[],"label_agreement":null},{"id":"W2973683106","doi":"10.1002/mrm.28232","title":"High‐fidelity, accelerated whole‐brain submillimeter in vivo diffusion MRI using gSlider‐spherical ridgelets (gSlider‐SR)","year":2020,"lang":"en","type":"preprint","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Mental Health","keywords":"Scanner; Computer science; Diffusion MRI; Redundancy (engineering); Human Connectome Project; Noise (video); Data acquisition; Angular resolution (graph drawing); Image resolution; Signal-to-noise ratio (imaging); Monte Carlo method; SIGNAL (programming language); Artificial intelligence; Computer vision; Physics; Magnetic resonance imaging; Mathematics","score_opus":0.10801500256919347,"score_gpt":0.3738312845897153,"score_spread":0.2658162820205219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2973683106","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81547993,0.012476805,0.02265894,0.14290836,0.00057340943,0.004558324,0.00011035331,0.00058301917,0.0006508626],"genre_scores_gemma":[0.856676,0.0061235307,0.11369329,0.019058345,0.001466963,0.0008751307,0.0003705582,0.00035022534,0.0013859627],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99411225,0.00027300313,0.0018360892,0.0019475409,0.0009622076,0.0008689332],"domain_scores_gemma":[0.9969549,0.00039958744,0.00043641313,0.0016037144,0.00021634047,0.00038901885],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00065523625,0.0008439139,0.00195071,0.00044697057,0.000093207826,0.000044175573,0.00067345786,0.0005620064,0.00062025944],"category_scores_gemma":[0.0011062876,0.0007558784,0.0001710252,0.0013993374,0.00051564473,0.00008523938,0.0010738571,0.002733601,0.000019300753],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017437757,0.0018407367,0.066348344,0.00254674,0.000049835795,0.0075152023,0.0023012825,0.0011138375,0.6382739,0.0005729305,0.1275468,0.15014662],"study_design_scores_gemma":[0.01655925,0.0028730512,0.40744194,0.01777091,0.00048577355,0.0006688082,0.00037941552,0.12085952,0.00960631,0.040175565,0.38018516,0.002994302],"about_ca_topic_score_codex":0.0014596179,"about_ca_topic_score_gemma":0.00009532151,"teacher_disagreement_score":0.6286676,"about_ca_system_score_codex":0.00046158562,"about_ca_system_score_gemma":0.00025990733,"threshold_uncertainty_score":0.99956715},"labels":[],"label_agreement":null},{"id":"W2974984553","doi":"10.3171/2019.6.jns19612","title":"Tractography-based targeting of the ventral intermediate nucleus: accuracy and clinical utility in MRgFUS thalamotomy","year":2019,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Western Hospital; University Health Network; University of Toronto; Ontario Brain Institute; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Thalamotomy; Medicine; Tractography; Magnetic resonance imaging; Essential tremor; Radiology; Diffusion MRI; Physical medicine and rehabilitation; Pathology; Parkinson's disease; Deep brain stimulation","score_opus":0.05985985853866739,"score_gpt":0.3699382358241312,"score_spread":0.31007837728546384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2974984553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99816453,0.000065018816,0.00012678675,0.0010756161,0.00028020944,0.0002241627,0.00000487539,0.000011430578,0.000047353267],"genre_scores_gemma":[0.998556,0.00016746852,0.00063551374,0.00055802375,0.00006313109,0.0000015302055,5.429894e-7,0.000012933973,0.000004849646],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99863905,0.00010476544,0.00079447334,0.00013503204,0.00018858643,0.00013809428],"domain_scores_gemma":[0.9982024,0.0007535889,0.00065373775,0.0002342675,0.000078037,0.0000780035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006119805,0.000088296685,0.0003477319,0.00014087772,0.000019214054,0.000008278795,0.00012154995,0.000045660185,0.000014030719],"category_scores_gemma":[0.00057174696,0.000059288377,0.00029771743,0.0002629549,0.00012909196,0.0000979418,0.000039082297,0.00058725907,4.6696815e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019214331,0.00025444553,0.98489165,0.000044311535,0.0000068870954,0.000035006025,0.000020325475,0.0000045068655,0.010648579,0.0000059150993,0.00032896028,0.00356728],"study_design_scores_gemma":[0.0006877941,0.0001560606,0.99285084,0.00021714863,0.000027319145,0.000075952645,0.000016530143,0.0006006008,0.00258129,0.00015685007,0.0025834914,0.000046111327],"about_ca_topic_score_codex":0.0000023028665,"about_ca_topic_score_gemma":2.59711e-7,"teacher_disagreement_score":0.008067289,"about_ca_system_score_codex":0.000009151104,"about_ca_system_score_gemma":0.000083074476,"threshold_uncertainty_score":0.2551381},"labels":[],"label_agreement":null},{"id":"W2975235655","doi":"10.1038/s41598-019-49970-9","title":"Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St Joseph's Health Care; Sunnybrook Health Science Centre; St Joseph's Health Centre; McGill University; Jewish General Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; Genentech; IXICO; Eisai; University of Southern California; Agence Nationale de la Recherche; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Servier; Alzheimer's Disease Neuroimaging Initiative; Eli Lilly and Company; Foundation for the National Institutes of Health","keywords":"Subiculum; Computer science; Hippocampal formation; Diffusion MRI; Magnetic resonance imaging; Hippocampus; Artificial intelligence; Neuroimaging; Grading (engineering); Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Pattern recognition (psychology); Machine learning; Alzheimer's disease; Pathology; Medicine; Disease; Radiology; Biology; Dentate gyrus","score_opus":0.11005114133744558,"score_gpt":0.37743080638013005,"score_spread":0.26737966504268446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975235655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94454026,0.00023757048,0.03970411,0.0044722348,0.0036086864,0.0039351275,0.000012049651,0.00061322394,0.0028767588],"genre_scores_gemma":[0.9835068,0.0000028205925,0.013264578,0.00014461075,0.00007434385,0.00019753534,0.00016290965,0.000020178904,0.002626204],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867916,0.000007171372,0.00027517497,0.00061960187,0.00021552858,0.0002033919],"domain_scores_gemma":[0.99860066,0.00003913154,0.00015713848,0.0008984253,0.00013545384,0.00016920854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030860284,0.00009635194,0.00013208296,0.000095289564,0.00016948962,0.00006149086,0.000065446904,0.000033607557,0.000051215582],"category_scores_gemma":[0.000107288826,0.00008728517,0.00010925031,0.0002047313,0.000085602536,0.00010818623,0.000026165382,0.00008643467,0.000027300255],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026248916,0.0007637697,0.38335112,0.00026166247,0.000065487955,0.00020233389,0.00025623903,0.00009592368,0.43992472,0.013217971,0.108633086,0.052965183],"study_design_scores_gemma":[0.0011019055,0.00018718888,0.102054566,0.000231309,0.00043953792,0.00037587708,0.0001405092,0.04112806,0.07981958,0.11330711,0.6605109,0.00070345483],"about_ca_topic_score_codex":0.0000026694509,"about_ca_topic_score_gemma":2.776705e-7,"teacher_disagreement_score":0.5518778,"about_ca_system_score_codex":0.000027042004,"about_ca_system_score_gemma":0.00011769658,"threshold_uncertainty_score":0.35593858},"labels":[],"label_agreement":null},{"id":"W2976721110","doi":"10.1371/journal.pone.0223211","title":"Acute ex vivo changes in brain white matter diffusion tensor metrics","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Toronto Western Hospital; Hospital for Sick Children; University of Toronto; University Health Network","funders":"Mitacs; Fondation Brain Canada","keywords":"Ex vivo; Diffusion MRI; Fractional anisotropy; White matter; Tractography; In vivo; Magnetic resonance imaging; Biomedical engineering; Materials science; Pathology; Anatomy; Biology; Medicine; Radiology","score_opus":0.07238416628773542,"score_gpt":0.3080497953706954,"score_spread":0.23566562908295996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976721110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9620821,0.00003330198,0.0003972091,0.033524875,0.0000110049095,0.00069273845,0.000016303555,0.00014159831,0.0031008867],"genre_scores_gemma":[0.87755233,0.0003689691,0.06582649,0.01374021,0.00012802692,0.0001679773,0.00004131263,0.00007924613,0.042095426],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992914,0.000010631374,0.000115404655,0.00022918152,0.00018424439,0.00016909523],"domain_scores_gemma":[0.99944746,0.000049229773,0.000045458324,0.00036429326,0.00003986663,0.00005366848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050414896,0.000092809445,0.00021151213,0.00019610248,0.000017585478,0.000007582303,0.000078309415,0.000045861612,0.00047566797],"category_scores_gemma":[0.000028792474,0.00008126129,0.000024457095,0.0003687307,0.00001722274,0.000038897426,0.000065908534,0.00016880957,0.00029828743],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030366016,0.00072975695,0.5016401,0.00008150981,0.00002049232,0.000011883273,0.00006267359,1.6724356e-7,0.49377,0.00006997318,0.0033103204,0.00027277917],"study_design_scores_gemma":[0.003924301,0.0008718521,0.60961384,0.0012848711,0.00036980235,0.000055897584,0.00010445492,0.004917556,0.3510955,0.0014778838,0.025531938,0.00075214345],"about_ca_topic_score_codex":0.0000037573864,"about_ca_topic_score_gemma":0.0000028390666,"teacher_disagreement_score":0.1426745,"about_ca_system_score_codex":0.000034696735,"about_ca_system_score_gemma":0.000006339049,"threshold_uncertainty_score":0.52082306},"labels":[],"label_agreement":null},{"id":"W2977486527","doi":"10.3389/fnins.2019.01024","title":"White Matter fMRI Activation Cannot Be Treated as a Nuisance Regressor: Overcoming a Historical Blind Spot","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":107,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Fraser Health; Surrey Memorial Hospital; Simon Fraser University; University of Calgary","funders":"","keywords":"White matter; Neuroimaging; Blind spot; Functional magnetic resonance imaging; Psychology; White noise; Cognitive psychology; Magnetic resonance imaging; Neuroscience; Computer science; Medicine","score_opus":0.04601412287914873,"score_gpt":0.32175123125396277,"score_spread":0.275737108374814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977486527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95935464,0.000042161435,0.022144351,0.012684276,0.00061850727,0.00089565985,0.000005935361,0.00018037306,0.0040740957],"genre_scores_gemma":[0.9685866,0.000039670816,0.014919435,0.0052378397,0.000039242623,0.00006782273,0.0000046264304,0.000028838465,0.011075877],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859065,0.000027050792,0.00022234135,0.0005852076,0.00027582434,0.00029891328],"domain_scores_gemma":[0.999237,0.000023520532,0.000113578855,0.00049325696,0.000037105092,0.000095509924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008923376,0.00015084118,0.0002368655,0.00022271939,0.00007743681,0.000024661185,0.00021858353,0.000057050747,0.000027625367],"category_scores_gemma":[0.00009283154,0.0001437147,0.000047555634,0.00074669474,0.000094110015,0.0002490465,0.00005959914,0.0003070861,0.00001421133],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021429888,0.00014876458,0.891985,0.000032405507,0.0000010885918,0.000030900734,0.0001246528,0.000056043777,0.06494058,0.00013461584,0.04166277,0.0006689052],"study_design_scores_gemma":[0.0025902728,0.0004405079,0.6841869,0.0003196285,0.000029634237,0.00017630856,0.00006417539,0.013280574,0.030056706,0.0010241474,0.26725793,0.0005732695],"about_ca_topic_score_codex":0.000056244684,"about_ca_topic_score_gemma":9.649061e-7,"teacher_disagreement_score":0.22559516,"about_ca_system_score_codex":0.00041863092,"about_ca_system_score_gemma":0.00005555652,"threshold_uncertainty_score":0.5860516},"labels":[],"label_agreement":null},{"id":"W2977674931","doi":"10.1002/hbm.25117","title":"Harmonization of diffusion <scp>MRI</scp> data sets with adaptive dictionary learning","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Harmonization; Diffusion MRI; Diffusion; Computer science; Neuroscience; Artificial intelligence; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.1568266212760925,"score_gpt":0.3388444901377222,"score_spread":0.1820178688616297,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977674931","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14815302,0.00008542732,0.84181327,0.0059832796,0.000010968024,0.0006133015,0.000029954055,0.0005397834,0.0027710022],"genre_scores_gemma":[0.96364754,0.000030899682,0.033907775,0.0013256533,0.00010260218,0.00001970437,0.00060231495,0.000038376867,0.00032515512],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991072,0.000032912467,0.00019210417,0.00035644966,0.00018234695,0.00012898847],"domain_scores_gemma":[0.99923426,0.00011413868,0.0001562836,0.00033745676,0.00007631262,0.000081542894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008715836,0.0001095678,0.00017109183,0.00006620408,0.00021583459,0.0000099836325,0.00015493867,0.00003429447,0.0000132507375],"category_scores_gemma":[0.00018259148,0.000101620586,0.000022854912,0.00029413257,0.0000721496,0.00013550514,0.00019212616,0.00025429254,0.0000049316454],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045029064,0.0002145112,0.048953585,0.0002855877,0.00007941347,0.000050095667,0.0034971912,0.00097538944,0.90148586,0.005858906,0.034139417,0.0044150376],"study_design_scores_gemma":[0.003351168,0.0016504492,0.38263583,0.0014229518,0.00020543297,0.00013817775,0.004400215,0.22252318,0.00507686,0.002730312,0.37550852,0.0003568851],"about_ca_topic_score_codex":0.0000054818543,"about_ca_topic_score_gemma":5.465931e-7,"teacher_disagreement_score":0.896409,"about_ca_system_score_codex":0.000018586143,"about_ca_system_score_gemma":0.0000244914,"threshold_uncertainty_score":0.41439673},"labels":[],"label_agreement":null},{"id":"W2977742585","doi":"10.1016/j.neuroimage.2019.116226","title":"Brain status modeling with non-negative projective dictionary learning","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; École de Technologie Supérieure; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Aerospace Science Foundation of China; National Institutes of Health; Fonds de Recherche du Québec - Santé; National Natural Science Foundation of China; Fondation Brain Canada","keywords":"Discriminative model; Neuroimaging; Artificial intelligence; Computer science; Pattern recognition (psychology); Feature selection; Feature (linguistics); Psychology; Neuroscience","score_opus":0.03745440563170813,"score_gpt":0.32865332863927393,"score_spread":0.2911989230075658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977742585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.841359,0.000013808254,0.12521863,0.0018555574,0.000035790697,0.0013507123,0.0000098050805,0.0005730823,0.029583577],"genre_scores_gemma":[0.97777766,0.000024914514,0.018787157,0.001026403,0.000050963004,0.000091447866,0.00001983132,0.00005949155,0.0021621098],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989065,0.000029881065,0.00014142296,0.0004447459,0.00020397722,0.00027349006],"domain_scores_gemma":[0.9993087,0.00010260568,0.0000684723,0.00030969712,0.000117259915,0.00009323134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005591915,0.00015696265,0.00019061047,0.00009907892,0.00011206385,0.00001781789,0.00006198692,0.00003312604,0.00003821933],"category_scores_gemma":[0.0000750815,0.00013124497,0.00004755196,0.0002824896,0.00005335656,0.00017311248,0.000053420863,0.00053491,0.00006388853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031630206,0.0014411354,0.26774967,0.0005232131,0.00021803746,0.0006710538,0.0042923777,0.06168356,0.62473243,0.0047977,0.004964527,0.025763266],"study_design_scores_gemma":[0.0056431885,0.004212176,0.088911295,0.00042503688,0.00014984302,0.00063600077,0.001128257,0.85463583,0.017201297,0.0023658285,0.02378551,0.0009057179],"about_ca_topic_score_codex":0.00002879529,"about_ca_topic_score_gemma":7.6977545e-7,"teacher_disagreement_score":0.7929523,"about_ca_system_score_codex":0.000053074935,"about_ca_system_score_gemma":0.000081551225,"threshold_uncertainty_score":0.53520143},"labels":[],"label_agreement":null},{"id":"W2977932297","doi":"10.1093/schbul/sbz019.333","title":"T53. AN EFFECT-SIZE META-ANALYSIS OF WHITE MATTER DAMAGE RELATED TO CANNABIS USE: RELEVANCE TO THE ANATOMY OF PSYCHOSIS","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Cannabis; White matter; Fractional anisotropy; Psychosis; Meta-analysis; Schizophrenia (object-oriented programming); Psychology; Diffusion MRI; Effects of cannabis; Psychiatry; Clinical psychology; Medicine; Audiology; Internal medicine; Magnetic resonance imaging; Radiology; Cannabidiol","score_opus":0.029051361499693812,"score_gpt":0.3427579512224502,"score_spread":0.31370658972275633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977932297","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92758965,0.00009121726,0.00072486425,0.06913195,0.000038050912,0.0016237168,0.0001444499,0.00010365087,0.000552437],"genre_scores_gemma":[0.9551718,0.000011408296,0.034780834,0.0035760554,0.000013365619,0.00027575434,0.000026190593,0.000051390296,0.0060931854],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99817705,0.00014169975,0.00054003764,0.0005594936,0.00033710725,0.00024458944],"domain_scores_gemma":[0.9973593,0.00022543364,0.00023379811,0.0018120897,0.00020064582,0.00016873622],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00038692664,0.0002387653,0.00099885,0.0002826768,0.00007280924,0.000014701009,0.00037266334,0.000073531424,0.002752503],"category_scores_gemma":[0.0001808769,0.00016152574,0.00052999903,0.0017138592,0.000059492537,0.00004568711,0.00014201514,0.00026556037,0.0002626293],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00651153,0.0011459625,0.3163976,0.00049537566,0.04830249,0.000028740553,0.0020676602,0.0066279517,0.07929197,0.0042829034,0.5317868,0.0030609968],"study_design_scores_gemma":[0.001677075,0.0012396068,0.5129914,0.00008282316,0.06128532,0.000015839243,0.000044479188,0.00032548682,0.01637537,0.00029262019,0.40505686,0.00061309175],"about_ca_topic_score_codex":0.00016455846,"about_ca_topic_score_gemma":0.00004852683,"teacher_disagreement_score":0.19659382,"about_ca_system_score_codex":0.000024094361,"about_ca_system_score_gemma":0.000016976968,"threshold_uncertainty_score":0.9981591},"labels":[],"label_agreement":null},{"id":"W2978374216","doi":"10.3233/jad-190446","title":"Multicenter Tract-Based Analysis of Microstructural Lesions within the Alzheimer’s Disease Spectrum: Association with Amyloid Pathology and Diagnostic Usefulness","year":2019,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Diffusion MRI; Dementia; Fractional anisotropy; Biomarker; Medicine; Cognitive decline; Prospective cohort study; Internal medicine; Alzheimer's disease; White matter; Disease; Pathology; Oncology; Psychology; Radiology; Magnetic resonance imaging","score_opus":0.03281436635443027,"score_gpt":0.31216672371294624,"score_spread":0.279352357358516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978374216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99100024,0.0018585115,0.0007863702,0.005638671,0.00006774021,0.00050754135,0.0001129113,0.000020555659,0.000007444131],"genre_scores_gemma":[0.99763274,0.000060490518,0.0013802996,0.0007937446,0.000050865583,0.000016762873,0.00003125567,0.000023968569,0.000009872968],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865675,0.00009853008,0.00048613362,0.00022147261,0.00035737478,0.0001797206],"domain_scores_gemma":[0.99772614,0.00044175936,0.00086244725,0.0003964319,0.00023227712,0.0003409142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021414609,0.00017582935,0.00044186515,0.000238695,0.00008421621,0.000024597513,0.00013471831,0.000039786366,0.0000497287],"category_scores_gemma":[0.00023897765,0.00010746768,0.0002502853,0.00040209547,0.00013099011,0.00013905768,0.000030513049,0.00030035886,0.0000021609278],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008883352,0.00044679316,0.9929683,0.00002192452,0.0014319369,0.00021103851,0.00010641198,0.0017080059,0.001542621,0.000115544965,0.00015102449,0.0004080527],"study_design_scores_gemma":[0.0013203972,0.0001773157,0.96847856,0.0000943319,0.023851555,0.000031545133,0.000053660686,0.0028539025,0.0027748165,0.00014491504,0.00009336887,0.0001256523],"about_ca_topic_score_codex":0.0000086901655,"about_ca_topic_score_gemma":0.0000031378484,"teacher_disagreement_score":0.024489772,"about_ca_system_score_codex":0.000034861467,"about_ca_system_score_gemma":0.00018418576,"threshold_uncertainty_score":0.43824047},"labels":[],"label_agreement":null},{"id":"W2978497465","doi":"10.1017/s1041610219001418","title":"Glutamine + glutamate level predicts the magnitude of microstructural organization in the gray matter in the healthy elderly","year":2019,"lang":"en","type":"article","venue":"International Psychogeriatrics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"Japan Society for the Promotion of Science","keywords":"Glutamine; White matter; Diffusion MRI; Glutamate receptor; Neuroscience; Anterior cingulate cortex; Posterior cingulate; Prefrontal cortex; Magnetic resonance imaging; Cortex (anatomy); Internal medicine; Psychology; Chemistry; Medicine; Amino acid; Biochemistry","score_opus":0.03147723437835876,"score_gpt":0.3426619046844492,"score_spread":0.3111846703060904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978497465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9604241,0.000045442677,0.0011616393,0.036578853,0.0002421434,0.00081081706,0.000058659785,0.000019156172,0.000659173],"genre_scores_gemma":[0.9923304,0.00009010683,0.0014181825,0.005771752,0.000119399745,0.00003496002,0.00008302873,0.000016325572,0.00013588338],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99889106,0.00005916342,0.0003437258,0.00019599276,0.00037515606,0.00013487916],"domain_scores_gemma":[0.9991345,0.00014617117,0.00015682954,0.00038567142,0.00016185816,0.000014991442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003265654,0.00010551732,0.000116876865,0.00011773999,0.000036518697,0.00003628915,0.0006070168,0.000043528406,0.000083296974],"category_scores_gemma":[0.000073907846,0.000055243527,0.000035284436,0.00074022944,0.00004953086,0.000074011936,0.000039567065,0.0002652354,0.000031373464],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022550099,0.00038791215,0.9655786,0.0000679866,0.000019954836,0.0000091062675,0.0016245487,0.000090929745,0.013928334,0.0042025056,0.011461239,0.0024033815],"study_design_scores_gemma":[0.0009422039,0.00010140898,0.9891148,0.000030141258,0.000012585542,0.00013873875,0.00016473603,0.00012147663,0.00031533916,0.0019152095,0.007077584,0.00006572571],"about_ca_topic_score_codex":0.000062974366,"about_ca_topic_score_gemma":0.0000138355845,"teacher_disagreement_score":0.031906247,"about_ca_system_score_codex":0.000041510164,"about_ca_system_score_gemma":0.00003145459,"threshold_uncertainty_score":0.22527657},"labels":[],"label_agreement":null},{"id":"W2978584402","doi":"10.3389/fnagi.2019.00270","title":"Free Water in White Matter Differentiates MCI and AD From Control Subjects","year":2019,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Hyperintensity; Partial volume; Fluid-attenuated inversion recovery; Cardiology; Psychology; Neuroscience; Internal medicine; Magnetic resonance imaging; Pathology; Medicine; Nuclear medicine; Radiology","score_opus":0.015912025209341336,"score_gpt":0.2660259573467302,"score_spread":0.25011393213738886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978584402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97910374,0.00010544227,0.015665518,0.0041239117,0.00032348355,0.00041172243,0.000015765467,0.000068269306,0.00018216395],"genre_scores_gemma":[0.99133223,0.00005076317,0.0049898475,0.003160659,0.000012182183,0.00002941544,0.0000041907665,0.000017336348,0.000403394],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99886966,0.000027004005,0.00017197816,0.0004890559,0.00014014928,0.00030212992],"domain_scores_gemma":[0.9994537,0.000024324178,0.000025317082,0.0004226051,0.0000108712775,0.000063171945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007652605,0.00012523166,0.00022506123,0.00017966503,0.000036425954,0.000035292574,0.00020682676,0.000031160085,0.000018540359],"category_scores_gemma":[0.000025182213,0.00009840161,0.000023492123,0.00017612641,0.00011990255,0.00015047405,0.00011114594,0.00023077696,0.000007100789],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001746205,0.000032671815,0.9439967,0.000012434497,5.3702814e-7,0.000015561294,0.00012956986,0.0000139937765,0.054755904,0.0000060244206,0.0008123084,0.0002068101],"study_design_scores_gemma":[0.0011471614,0.000033164077,0.98181784,0.00008235113,0.0000070264355,0.000009573128,0.000028774402,0.0066151423,0.007174757,0.001958614,0.0010016167,0.00012395898],"about_ca_topic_score_codex":0.000025282863,"about_ca_topic_score_gemma":0.0000037318011,"teacher_disagreement_score":0.047581147,"about_ca_system_score_codex":0.000028725295,"about_ca_system_score_gemma":0.000009082374,"threshold_uncertainty_score":0.40127012},"labels":[],"label_agreement":null},{"id":"W2978944956","doi":"10.3389/fnins.2019.01053","title":"Quantifying Neurodegenerative Progression With DeepSymNet, an End-to-End Data-Driven Approach","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; Nvidia; F. Hoffmann-La Roche; National Center for Advancing Translational Sciences; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Neuroimaging; Computer science; Artificial intelligence; Voxel; Population; Deep learning; Preprocessor; Machine learning; Medicine; Neuroscience; Psychology","score_opus":0.12866102627308487,"score_gpt":0.38915079730854735,"score_spread":0.26048977103546245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978944956","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50488824,0.000048394646,0.49084523,0.00097063475,0.00033878788,0.0016961916,0.000029489309,0.0002461273,0.000936882],"genre_scores_gemma":[0.58985424,0.000015994767,0.40888733,0.00097553525,0.000021671667,0.00006056766,0.00003356038,0.00002481312,0.00012627298],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978814,0.000057337817,0.00019543763,0.0011440386,0.0003683986,0.0003533737],"domain_scores_gemma":[0.99840665,0.000016274584,0.000085024614,0.0012655314,0.00004086993,0.00018567541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016865003,0.00017712118,0.0002499358,0.0002075362,0.000120306104,0.00005024198,0.0006638334,0.00003535879,0.0000033838464],"category_scores_gemma":[0.00005902337,0.00013934443,0.000017820083,0.00086424535,0.0001970864,0.00048227384,0.00024877288,0.00031100612,0.0000036906863],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047229425,0.0010275168,0.75282085,0.00010767064,0.000004583671,0.00012728787,0.00048438425,0.010824893,0.19624156,0.002264819,0.0047060265,0.030918103],"study_design_scores_gemma":[0.0010263358,0.0017415973,0.1263869,0.00015548537,0.000030452267,0.00022031317,0.00020716178,0.83678865,0.006829937,0.00010195358,0.026006354,0.0005048534],"about_ca_topic_score_codex":0.0000061718974,"about_ca_topic_score_gemma":0.0000028817235,"teacher_disagreement_score":0.8259638,"about_ca_system_score_codex":0.000034836183,"about_ca_system_score_gemma":0.0000817499,"threshold_uncertainty_score":0.5682301},"labels":[],"label_agreement":null},{"id":"W2979488433","doi":"10.1007/s11682-019-00193-6","title":"White matter microstructure in women with acute and remitted anorexia nervosa: an exploratory neuroimaging study","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Diffusion MRI; Psychology; Neuroimaging; External capsule; Anorexia nervosa; Corona radiata (embryology); Internal capsule; Grey matter; Psychiatry; Internal medicine; Neuroscience; Medicine; Eating disorders; Magnetic resonance imaging; Radiology","score_opus":0.018105067132589463,"score_gpt":0.30612855027810437,"score_spread":0.2880234831455149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979488433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9962765,0.000057645273,0.00007169478,0.0024063555,0.00002432827,0.00094483944,0.000009390352,0.00015559376,0.00005368224],"genre_scores_gemma":[0.99331605,0.000011723722,0.003096398,0.0030227562,0.000025344294,0.00019213522,0.000013139069,0.00005631724,0.00026612962],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987532,0.000043997992,0.00019114946,0.00058413425,0.00012271076,0.00030480933],"domain_scores_gemma":[0.99928725,0.000018957053,0.000064342144,0.00044781083,0.00004041669,0.00014123086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001201386,0.00021644814,0.00026811627,0.00016554177,0.00007935826,0.00007542988,0.00008054547,0.00002727235,0.000026715907],"category_scores_gemma":[0.0000035058986,0.00018067232,0.000012998339,0.00021726714,0.00010800938,0.000288557,0.000088529865,0.0003193855,0.0000037581601],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010383586,0.00019275749,0.9431806,0.000020529993,0.0000050691992,0.0002180301,0.001611573,4.1062995e-7,0.050010927,0.0000019794868,0.00030927165,0.004344994],"study_design_scores_gemma":[0.0017050771,0.00024610735,0.99421084,0.000066549415,0.00007650251,0.0007148417,0.002139551,0.00007277258,0.00017174458,0.000034082444,0.00034241466,0.00021953491],"about_ca_topic_score_codex":0.0000155306,"about_ca_topic_score_gemma":0.0000048135685,"teacher_disagreement_score":0.0510302,"about_ca_system_score_codex":0.000033713037,"about_ca_system_score_gemma":0.00002510759,"threshold_uncertainty_score":0.7367603},"labels":[],"label_agreement":null},{"id":"W2979668791","doi":"10.1101/796615","title":"Freewater EstimatoR using iNtErpolated iniTialization (FERNET): Toward Accurate Estimation of Free Water in Peritumoral Region Using Single-Shell Diffusion MRI Data","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Initialization; Diffusion MRI; Tractography; Estimator; Computer science; Free water; Shell (structure); Magnetic resonance imaging; Diffusion; Biomedical engineering; Algorithm; Artificial intelligence; Medicine; Radiology; Materials science; Mathematics; Statistics; Physics; Geology","score_opus":0.127315405091424,"score_gpt":0.32864350684893223,"score_spread":0.20132810175750823,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979668791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.708038,0.00009732614,0.28961912,0.00022580074,0.00027946793,0.0012898395,0.00016647414,0.00028148122,0.0000025061702],"genre_scores_gemma":[0.8862736,0.000056302073,0.11320342,0.000097677264,0.0001258066,0.00003717478,0.000032690354,0.00017157818,0.0000017227792],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99668944,0.00012919526,0.0010640337,0.0012270687,0.00039164885,0.00049858756],"domain_scores_gemma":[0.9957668,0.000036717687,0.0006428155,0.0029833852,0.00041831587,0.00015197412],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035883498,0.0005748926,0.0008567342,0.0005782659,0.00010649501,0.00015029564,0.0008068216,0.0004668993,0.000017586055],"category_scores_gemma":[0.0002280115,0.0005348461,0.00010638317,0.00044626152,0.00018895607,0.000519385,0.0019463643,0.0007286923,0.0000072913817],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014887252,0.0003418885,0.0075428807,0.0010346931,0.000040776365,0.00007401008,0.000046745226,0.0078306375,0.9828035,0.000072634706,0.00005660369,0.000006722077],"study_design_scores_gemma":[0.000876226,0.00006980987,0.0036856763,0.0023800014,0.00020951137,8.1501287e-7,0.000003927055,0.62897974,0.36312002,0.00002477945,0.00016310476,0.00048638645],"about_ca_topic_score_codex":0.00027416807,"about_ca_topic_score_gemma":0.0000021026692,"teacher_disagreement_score":0.62114906,"about_ca_system_score_codex":0.00046781928,"about_ca_system_score_gemma":0.00035602011,"threshold_uncertainty_score":0.9997103},"labels":[],"label_agreement":null},{"id":"W2979919254","doi":"10.1016/j.neuroimage.2019.116255","title":"Quantification of apparent axon density and orientation dispersion in the white matter of youth born with congenital heart disease","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Montreal Children's Hospital; Université de Sherbrooke; McGill University Health Centre; McGill University","funders":"Canada First Research Excellence Fund; Canadian Institutes of Health Research; McGill University Health Centre; Faculty of Medicine, McGill University; McGill University; Institut de recherche, Centre universitaire de santé McGill","keywords":"White matter; Corpus callosum; Diffusion MRI; Fractional anisotropy; Axon; Magnetic resonance imaging; Psychology; Neuroscience; Anatomy; Cardiology; Medicine; Radiology","score_opus":0.03581453844897592,"score_gpt":0.301980156900281,"score_spread":0.2661656184513051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2979919254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959888,0.000015261992,0.0017787138,0.0014344999,0.000010936155,0.0005907361,0.00002179752,0.0000141328155,0.00014514105],"genre_scores_gemma":[0.9988547,0.00000769134,0.00070004485,0.00033089556,0.0000056388003,0.000011645073,0.00004851667,0.000008949267,0.00003194853],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994525,0.000025295407,0.00013761777,0.0001823426,0.0001370462,0.00006523878],"domain_scores_gemma":[0.999518,0.000020862995,0.000074629825,0.00030837348,0.000049473183,0.000028702298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006031587,0.000063521584,0.00010858114,0.000046334015,0.000017446107,0.000005545574,0.00004155444,0.00001163401,0.0000068997188],"category_scores_gemma":[0.000009160176,0.00004336793,0.000019671357,0.00012874023,0.00007215636,0.000067042434,0.000017872168,0.00007761855,0.0000036417737],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021390159,0.00011991883,0.95377594,0.00006223956,0.0000015712628,0.0000021622557,0.00030081964,0.000006976188,0.04525121,0.00011871163,0.00006147593,0.000085101805],"study_design_scores_gemma":[0.0003844633,0.000116662806,0.99312484,0.000032121843,0.000042169075,0.000009324011,0.000281565,0.00025823567,0.0056072697,0.000039282968,0.00006326282,0.000040810446],"about_ca_topic_score_codex":0.000012692423,"about_ca_topic_score_gemma":0.0000015052954,"teacher_disagreement_score":0.03964394,"about_ca_system_score_codex":0.0000059619433,"about_ca_system_score_gemma":0.0000112158405,"threshold_uncertainty_score":0.17684928},"labels":[],"label_agreement":null},{"id":"W2980279673","doi":"10.3389/conf.fnhum.2019.01.00114","title":"A DTI study of cognitive function post stroke","year":2019,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; Neurocognitive; Diffusion MRI; Stroke (engine); Superior longitudinal fasciculus; Medicine; Montreal Cognitive Assessment; Corpus callosum; Rehabilitation; Arcuate fasciculus; Psychology; Physical medicine and rehabilitation; Magnetic resonance imaging; Physical therapy; Pathology; Psychiatry; Cognitive impairment; Radiology","score_opus":0.04839063865320071,"score_gpt":0.34380756651479344,"score_spread":0.29541692786159274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980279673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9787223,0.000014589031,0.019084042,0.000045295157,0.00022739494,0.00092359213,0.000008299443,0.00005749721,0.00091702706],"genre_scores_gemma":[0.99806637,0.0000045381016,0.00061895815,0.00035666002,0.000010953302,0.000035680314,0.000002370566,0.000010199886,0.0008942902],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99913275,0.000022037048,0.00017377263,0.00033439492,0.00019827567,0.00013877559],"domain_scores_gemma":[0.9995439,0.000019483121,0.00008098709,0.00025550567,0.000060693837,0.000039421586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007607621,0.000078106415,0.00016463721,0.00019612454,0.000054268286,0.0000075446524,0.00011840533,0.000018521188,0.000008862459],"category_scores_gemma":[0.00007013225,0.00007475668,0.000028132152,0.00031174283,0.00011218756,0.00010328768,0.00005101992,0.00016267212,9.494205e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120469515,0.0009877811,0.83123666,0.000020355703,0.0000026270397,0.000012007105,0.00033822958,0.000057013585,0.16500181,0.0001958228,0.00028045877,0.0017467904],"study_design_scores_gemma":[0.0018634608,0.0039409217,0.9849384,0.00008800509,0.00004551136,0.000012073249,0.0017359615,0.0016487009,0.004630539,0.00045295575,0.000503407,0.00014010232],"about_ca_topic_score_codex":0.000012143003,"about_ca_topic_score_gemma":0.0000017375497,"teacher_disagreement_score":0.16037126,"about_ca_system_score_codex":0.000018155379,"about_ca_system_score_gemma":0.000019158704,"threshold_uncertainty_score":0.3048489},"labels":[],"label_agreement":null},{"id":"W2980535964","doi":"10.1007/s00429-019-01963-0","title":"The descending motor tracts are different in dancers and musicians","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cégep Marie-Victorin; Concordia University; McGill University; International Laboratory for Brain, Music and Sound Research","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Diffusion MRI; Tractography; Psychology; Dance; Corticospinal tract; White matter; Neuroscience; Pyramidal tracts; Motor cortex; Corpus callosum; Motor learning; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging","score_opus":0.023335629380980775,"score_gpt":0.27973532344128127,"score_spread":0.2563996940603005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980535964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99573797,0.00019068278,0.0011510083,0.0023222156,0.00008610692,0.00031482943,0.0000042929187,0.000036396505,0.00015647463],"genre_scores_gemma":[0.99850214,0.000098911245,0.00021237654,0.0008875715,0.00006249167,0.000010202426,0.000004942704,0.000008078228,0.00021330631],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996308,0.000008739322,0.00007240604,0.00014750456,0.00005151021,0.00008901401],"domain_scores_gemma":[0.9997535,0.000059677113,0.000037463513,0.000111365836,0.0000091302245,0.000028885046],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027061295,0.00006628232,0.0000838416,0.00003059978,0.0000750499,0.000015949647,0.000017413913,0.000033649685,0.000005737936],"category_scores_gemma":[0.000018379504,0.000042037038,0.000012356181,0.00005597614,0.000029985718,0.00003847188,0.000012725507,0.000130737,3.3779844e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046774303,0.000035149522,0.48501748,0.00014030766,0.000023105056,0.000006836502,0.00037758506,0.00001490098,0.25202292,0.0077972286,0.0020360851,0.25206062],"study_design_scores_gemma":[0.0004340573,0.00009265057,0.9745192,0.00005299771,0.000013295806,0.000026836602,0.00016807935,0.00036247142,0.00073350157,0.0034648294,0.020072687,0.00005938586],"about_ca_topic_score_codex":0.0000044457265,"about_ca_topic_score_gemma":0.00001674727,"teacher_disagreement_score":0.4895017,"about_ca_system_score_codex":0.000019173052,"about_ca_system_score_gemma":0.0000042167626,"threshold_uncertainty_score":0.17142206},"labels":[],"label_agreement":null},{"id":"W2980627049","doi":"10.3389/fnhum.2019.00352","title":"White Matter Integrity Is Associated With Intraindividual Variability in Neuropsychological Test Performance in Healthy Older Adults","year":2019,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Neuropsychology; White matter; Psychology; Neuropsychological test; Test (biology); Clinical psychology; Audiology; Medicine; Cognition; Psychiatry; Magnetic resonance imaging; Biology","score_opus":0.03180931399941534,"score_gpt":0.32035138698081667,"score_spread":0.28854207298140133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980627049","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99351996,0.000004597029,0.0025004942,0.0019280639,0.00014457731,0.0010113226,0.000013180287,0.00007442815,0.00080335565],"genre_scores_gemma":[0.9913564,0.000014961048,0.0025692384,0.0058044633,0.000010760323,0.00008197986,0.000006560529,0.000018540297,0.00013712555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99787605,0.00012059845,0.0003897058,0.0008701305,0.00027786713,0.00046563984],"domain_scores_gemma":[0.99916416,0.00007983233,0.000115047325,0.00051178323,0.000037452697,0.00009169237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005970496,0.0001880462,0.0003347274,0.00026482143,0.00006214271,0.000023241546,0.00033763674,0.00008898795,0.000041294174],"category_scores_gemma":[0.00022130544,0.00015957227,0.000027169379,0.0010601197,0.00031520985,0.00020954538,0.00008585775,0.0010888901,0.0000029084365],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012325839,0.0006110972,0.99790454,0.000029989209,2.868169e-7,0.000025723934,0.00024141638,0.000032045136,0.00013634138,0.000013202607,0.0005070743,0.00037503513],"study_design_scores_gemma":[0.0013413513,0.00061183184,0.9910856,0.00021250283,0.0000023695918,0.000021215807,0.00003255503,0.0062213424,0.00004227243,0.00015478044,0.00012152406,0.00015266323],"about_ca_topic_score_codex":0.000011532864,"about_ca_topic_score_gemma":0.0000102516415,"teacher_disagreement_score":0.0068189385,"about_ca_system_score_codex":0.0001555635,"about_ca_system_score_gemma":0.00005118261,"threshold_uncertainty_score":0.65071684},"labels":[],"label_agreement":null},{"id":"W2980921467","doi":"10.1016/j.neuroimage.2019.116274","title":"Adaptive phase correction of diffusion-weighted images","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; CARE Canada; Philips (Canada)","funders":"European Research Council; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Diffusion MRI; Regularization (linguistics); Preprocessor; Mathematics; Gaussian; Image quality; Algorithm; Gaussian noise; Artificial intelligence; Rician fading; Noise (video); Computer science; Pattern recognition (psychology); Magnetic resonance imaging; Image (mathematics); Physics","score_opus":0.04029410667227545,"score_gpt":0.3471191143887975,"score_spread":0.30682500771652205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980921467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95048606,0.000044671826,0.020745965,0.00063501194,0.0002723761,0.00092527235,0.000033390214,0.000375857,0.026481405],"genre_scores_gemma":[0.99014425,0.000056264515,0.00610379,0.0003698314,0.000041630872,0.00002236536,0.000019109786,0.000029823192,0.0032129318],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922043,0.000019573949,0.00019220368,0.00027812115,0.00015448144,0.00013520142],"domain_scores_gemma":[0.99922997,0.000069944974,0.000108611006,0.00042884744,0.0000999532,0.00006266211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000036590252,0.00011264392,0.00020993332,0.00009323159,0.000034744353,0.000005398072,0.00007526799,0.000032910295,0.00018648109],"category_scores_gemma":[0.00003607584,0.000100181795,0.000080026366,0.00023085235,0.00006570436,0.00008617765,0.000047986847,0.0001949663,0.000067483066],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028447981,0.00055148616,0.0024917126,0.000029029807,0.0000070146466,0.000020956277,0.000030427096,0.000002920755,0.964034,0.00027061062,0.0056085084,0.02666884],"study_design_scores_gemma":[0.0062919524,0.0027523586,0.04261215,0.000194054,0.00013858978,0.00023613936,0.00008718421,0.025484992,0.871393,0.001094198,0.0493433,0.00037207076],"about_ca_topic_score_codex":0.00000997225,"about_ca_topic_score_gemma":1.4392369e-7,"teacher_disagreement_score":0.092641,"about_ca_system_score_codex":0.00001667819,"about_ca_system_score_gemma":0.000022998036,"threshold_uncertainty_score":0.40852952},"labels":[],"label_agreement":null},{"id":"W2980937299","doi":"10.1016/j.jalz.2019.08.120","title":"P4‐572: NEURAL CORRELATES OF COGNITIVE PERFORMANCE IN ALZHEIMER'S DISEASE AND LEWY BODY DISEASE SPECTRA","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fractional anisotropy; White matter; Corpus callosum; Psychology; Executive dysfunction; Diffusion MRI; Audiology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Neuropsychology; Radiology","score_opus":0.032088284934262946,"score_gpt":0.3095251436414882,"score_spread":0.27743685870722523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980937299","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95230216,0.045437545,0.000097328106,0.00047480428,0.000059807157,0.0010368421,0.000042922424,0.0000853351,0.00046328024],"genre_scores_gemma":[0.99822986,0.0006776599,0.00057406625,0.00027794187,0.000029351455,0.00007879538,0.00008996892,0.000032054653,0.000010307238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988936,0.000021635109,0.00028326508,0.00037671512,0.00017401073,0.00025076946],"domain_scores_gemma":[0.99921566,0.00006649349,0.00011125914,0.00032048963,0.000058136753,0.00022796841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000062289844,0.00018393707,0.00023619636,0.00010263883,0.00004664151,0.000011208139,0.000092150236,0.000029491703,0.000114214825],"category_scores_gemma":[0.000020373236,0.00017563993,0.000064394684,0.00017766413,0.0001361444,0.00017933709,0.000090292546,0.00018614055,0.00003716859],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042252432,0.00029800367,0.9878621,0.00002857658,0.0009616676,0.000033214088,0.00005645571,0.0000144068645,0.0012884998,0.00056317804,0.00010353663,0.008367828],"study_design_scores_gemma":[0.0011848868,0.00018684384,0.9762591,0.0002269993,0.009618908,0.000009284406,0.00002704679,0.0059217433,0.005677494,0.00029280465,0.00036722884,0.00022763002],"about_ca_topic_score_codex":0.000014601854,"about_ca_topic_score_gemma":0.0000011065606,"teacher_disagreement_score":0.04592772,"about_ca_system_score_codex":0.0000032470393,"about_ca_system_score_gemma":0.000046441226,"threshold_uncertainty_score":0.71623886},"labels":[],"label_agreement":null},{"id":"W2980965008","doi":"10.1016/j.jalz.2019.06.1200","title":"P1‐595: HIGHER LITERACY ASSOCIATES WITH BETTER BRAIN STRUCTURE AND COGNITION IN MIDDLE‐AGED INDIVIDUALS","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; White matter; Psychology; Logistic regression; Literacy; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Clinical psychology; Medicine; Internal medicine; Gerontology; Magnetic resonance imaging; Neuroscience","score_opus":0.03496237975333192,"score_gpt":0.3097574231830202,"score_spread":0.27479504342968825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980965008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99094075,0.0035671284,0.00008824169,0.004108323,0.00003192045,0.000690842,0.000049508722,0.00009837323,0.00042491636],"genre_scores_gemma":[0.9821721,0.0000224415,0.013444987,0.003990535,0.00004138275,0.00004498925,0.0001984421,0.0000292133,0.000055958284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914217,0.00003094572,0.00017849483,0.00029797552,0.00015245417,0.0001979594],"domain_scores_gemma":[0.99954253,0.000066053646,0.000090559304,0.00021116134,0.000036561432,0.00005312281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007287278,0.00014382078,0.00018667917,0.00008469764,0.0000440057,0.000036772817,0.00005885145,0.00006298951,0.00028622244],"category_scores_gemma":[0.000006018747,0.00011991421,0.000023798495,0.00014862139,0.00004048192,0.00017969182,0.00004514936,0.00021802231,0.000017380686],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052213916,0.0001381105,0.9434151,0.000025635682,0.0017092264,0.000018613566,0.00033716636,8.923912e-7,0.03045317,0.00036645593,0.0036010228,0.01988236],"study_design_scores_gemma":[0.0023819867,0.00020986731,0.9419969,0.00020108715,0.0033186069,0.000028890066,0.000022651464,0.000021487389,0.02674952,0.0034971891,0.021265851,0.00030601362],"about_ca_topic_score_codex":0.000011284936,"about_ca_topic_score_gemma":0.000004578644,"teacher_disagreement_score":0.019576348,"about_ca_system_score_codex":0.0000044210783,"about_ca_system_score_gemma":0.000011921975,"threshold_uncertainty_score":0.48899597},"labels":[],"label_agreement":null},{"id":"W2980976190","doi":"10.1016/j.jalz.2019.06.4200","title":"IC‐P‐038: DIFFERENTIAL GREY AND WHITE MATTER MICROSTRUCTURAL ABNORMALITIES IN EARLY AND LATE‐ONSET ALZHEIMER'S DISEASE AND MILD COGNITIVE IMPAIRMENT","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Precuneus; Diffusion MRI; Grey matter; Fractional anisotropy; Dementia; Cardiology; Cognitive decline; Medicine; Internal medicine; Age of onset; Psychology; Audiology; Disease; Neuroscience; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.024555491158394695,"score_gpt":0.29118170939955274,"score_spread":0.26662621824115806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980976190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9830757,0.014565164,0.000032060172,0.001035446,0.000047147892,0.0009945995,0.00012795483,0.00005556729,0.00006635445],"genre_scores_gemma":[0.99778986,0.0002566416,0.00074720953,0.0009242916,0.00002321995,0.00008285547,0.000104448016,0.00003308069,0.000038396134],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988373,0.000034656212,0.00025342242,0.0004459796,0.00012734879,0.0003013039],"domain_scores_gemma":[0.9994627,0.00003679074,0.000078070676,0.00021117766,0.000041665484,0.00016958339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005010361,0.00024081844,0.0002584866,0.00010184418,0.00008721426,0.00007099799,0.000054040887,0.000049581005,0.00016104868],"category_scores_gemma":[0.0000025556417,0.00021731644,0.000038773436,0.000071515125,0.00019538276,0.00020277985,0.0001759361,0.00017387005,0.000019758862],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026271035,0.000054892447,0.9956766,0.000022337406,0.0008644199,0.000017046537,0.00040822828,1.0587276e-7,0.00083764794,0.000037885693,0.00023374538,0.0015843769],"study_design_scores_gemma":[0.0016040782,0.00012583449,0.9910121,0.00008769402,0.00415453,0.0000459427,0.00007514158,0.00006468137,0.0020030388,0.00034199024,0.00024804712,0.00023689697],"about_ca_topic_score_codex":0.00008416121,"about_ca_topic_score_gemma":0.000008148961,"teacher_disagreement_score":0.014714152,"about_ca_system_score_codex":0.000003454441,"about_ca_system_score_gemma":0.000017162145,"threshold_uncertainty_score":0.8861907},"labels":[],"label_agreement":null},{"id":"W2981131390","doi":"10.1016/j.jalz.2019.06.2813","title":"P2‐406: INVESTIGATING THE SENSITIVITY OF FREE‐WATER IMAGING IN DETECTING WHITE‐MATTER ABNORMALITIES WITHIN PATIENTS WITH ALZHEIMER'S DISEASE","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Corpus callosum; Splenium; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Nuclear magnetic resonance; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Audiology; Nuclear medicine; Physics; Radiology","score_opus":0.025644432178095398,"score_gpt":0.2713589953143164,"score_spread":0.245714563136221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981131390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99536777,0.0010384362,0.00048108154,0.0016196191,0.000056694957,0.0009521848,0.000021764283,0.00009077756,0.0003716831],"genre_scores_gemma":[0.99232846,0.0000021362596,0.0062519195,0.0012233972,0.000027988015,0.00006497114,0.000045871126,0.00004855904,0.000006711479],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847776,0.0001081181,0.00040853274,0.00036248565,0.00030246022,0.00034064174],"domain_scores_gemma":[0.99875075,0.00008807051,0.00020047865,0.0007349194,0.00012357785,0.00010218608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037325342,0.00022001131,0.00024611322,0.00009512763,0.00011652226,0.000028675735,0.0001527181,0.000026455398,0.00007532453],"category_scores_gemma":[0.000027792019,0.00014150314,0.00006262656,0.00017153018,0.00018084535,0.00026338318,0.00021158079,0.00026326263,0.00002784565],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004518482,0.00007369609,0.99518204,0.000013761794,0.00031982217,0.000007060471,0.00048938196,0.00010238793,0.0023566457,0.000058425034,0.00013252441,0.0012190667],"study_design_scores_gemma":[0.0012969327,0.000066234395,0.9178877,0.0002505944,0.004166053,0.000014486589,0.0002823643,0.001985743,0.072902836,0.0005612344,0.0002458582,0.0003399515],"about_ca_topic_score_codex":0.00016836841,"about_ca_topic_score_gemma":0.000025412568,"teacher_disagreement_score":0.07729433,"about_ca_system_score_codex":0.00000702579,"about_ca_system_score_gemma":0.000036340865,"threshold_uncertainty_score":0.5770331},"labels":[],"label_agreement":null},{"id":"W2981254264","doi":"10.1016/j.jalz.2019.06.2736","title":"P2‐329: TRACKING WHITE MATTER DEGENERATION IN ASYMPTOMATIC AND SYMPTOMATIC <i>MAPT</i> MUTATION CARRIERS WITH DTI","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Asymptomatic; Asymptomatic carrier; White matter; Fractional anisotropy; Diffusion MRI; Frontotemporal lobar degeneration; Medicine; Frontotemporal dementia; Pathology; Internal medicine; Dementia; Magnetic resonance imaging; Radiology; Disease","score_opus":0.02619467090158327,"score_gpt":0.2912314390830439,"score_spread":0.2650367681814606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981254264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98756546,0.0018701358,0.006536909,0.0013489097,0.000039094768,0.0010911972,0.000003872057,0.00013477872,0.0014096732],"genre_scores_gemma":[0.97840273,0.000014303227,0.020350497,0.0009743842,0.000020454816,0.000116681294,0.000054377677,0.000035843786,0.000030721905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990363,0.000026070484,0.00026306766,0.00030047604,0.00017855687,0.00019551134],"domain_scores_gemma":[0.99947745,0.000024806382,0.000106006155,0.00028125546,0.00004463711,0.00006582692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000977531,0.00015330664,0.00019251062,0.000113921844,0.000055300094,0.000042629315,0.000058875845,0.000044603403,0.000101923324],"category_scores_gemma":[0.0000037472219,0.00013592909,0.000025709884,0.00019413764,0.000039760303,0.00023511396,0.000020010672,0.00012140849,0.000077794524],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050061644,0.00011837032,0.9644215,0.00008911361,0.00079289195,0.000022305494,0.00079400116,0.00030830977,0.020610565,0.00045300747,0.001006266,0.011333577],"study_design_scores_gemma":[0.0071896254,0.00090634695,0.8090169,0.0010590366,0.014773717,0.00080784777,0.0006993865,0.028926829,0.13026005,0.0014562382,0.0034684523,0.0014355886],"about_ca_topic_score_codex":0.000011454458,"about_ca_topic_score_gemma":0.000014809775,"teacher_disagreement_score":0.15540466,"about_ca_system_score_codex":0.000010073582,"about_ca_system_score_gemma":0.000025218165,"threshold_uncertainty_score":0.55430275},"labels":[],"label_agreement":null},{"id":"W2981767205","doi":"10.1016/j.nicl.2019.102033","title":"Premature white matter aging in patients with right mesial temporal lobe epilepsy: A machine learning approach based on diffusion MRI data","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Ministry of Science and Technology, Taiwan","keywords":"White matter; Epilepsy; Mesial temporal lobe epilepsy; Diffusion MRI; Temporal lobe; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Radiology","score_opus":0.048352604006440265,"score_gpt":0.35092793752135176,"score_spread":0.3025753335149115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981767205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9664027,0.000014293822,0.017025849,0.007940276,0.00016505839,0.0026081337,0.00010526747,0.00044527603,0.005293109],"genre_scores_gemma":[0.95680165,0.000008792963,0.035329208,0.0057263565,0.00012284594,0.00002945848,0.0011969791,0.0000966746,0.0006880327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997181,0.00021722967,0.0006139549,0.0012011522,0.00044328242,0.00034339432],"domain_scores_gemma":[0.99756217,0.00021038862,0.00024163016,0.0017498553,0.00007689644,0.00015904052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043081568,0.00029067995,0.0005309947,0.00014506657,0.00007852431,0.000038915707,0.0004284057,0.00013589425,0.00020986468],"category_scores_gemma":[0.00016678062,0.00021601183,0.000093022296,0.00030137523,0.000107188454,0.00018420555,0.00030773573,0.0016760377,0.000087494],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007286811,0.0012739314,0.9945124,0.00006970359,0.0000043682912,0.00004648153,0.000009805833,0.00017210674,0.000038282982,0.000007903998,0.0026501887,0.0004861695],"study_design_scores_gemma":[0.0046035424,0.00077995064,0.8943827,0.00020807378,0.000044854172,0.000012860134,0.0000029437351,0.08837552,0.000014535452,0.00001735658,0.011322503,0.00023516665],"about_ca_topic_score_codex":0.0000073549936,"about_ca_topic_score_gemma":0.000001935223,"teacher_disagreement_score":0.10012969,"about_ca_system_score_codex":0.000027351769,"about_ca_system_score_gemma":0.000050777257,"threshold_uncertainty_score":0.8808707},"labels":[],"label_agreement":null},{"id":"W2982063848","doi":"10.1503/jpn.180243","title":"Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder","year":2019,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Superior longitudinal fasciculus; Major depressive disorder; Fractional anisotropy; White matter; Corpus callosum; Psychology; Cardiology; Internal medicine; Medicine; Psychiatry; Magnetic resonance imaging; Neuroscience; Radiology; Cognition","score_opus":0.027936833045804157,"score_gpt":0.3461763405610605,"score_spread":0.31823950751525637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982063848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99357957,0.0001780999,0.00050963194,0.005004237,0.00020640821,0.0003821775,0.0000016772007,0.000017162189,0.00012103691],"genre_scores_gemma":[0.9966877,0.00012495682,0.0020251188,0.00093244395,0.000060046194,0.00000445793,2.0626334e-7,0.000011330422,0.00015373284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989634,0.000035505658,0.00031558768,0.0002640359,0.0002421874,0.00017924006],"domain_scores_gemma":[0.99937916,0.0000362896,0.00022328066,0.00020077259,0.000052455405,0.00010801468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019841966,0.00010732088,0.00022518971,0.0001609946,0.00007737773,0.000029971925,0.00014653179,0.000018011453,0.000012774306],"category_scores_gemma":[0.00004881045,0.00008097762,0.00005095016,0.00025894988,0.00008393375,0.000226393,0.000065706416,0.00031173087,0.0000041768317],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011635745,0.0005814808,0.98540723,0.000015133105,0.0000016858528,0.000035792105,0.000049862072,0.000016566317,0.013240239,0.00006237307,0.00014151147,0.00033177307],"study_design_scores_gemma":[0.0018922637,0.00074360386,0.9940597,0.00011238174,0.00003226584,0.00068115897,0.00015337332,0.0008009651,0.00006013912,0.00053574896,0.00083788176,0.00009053949],"about_ca_topic_score_codex":0.000005396064,"about_ca_topic_score_gemma":0.0000026564098,"teacher_disagreement_score":0.013180099,"about_ca_system_score_codex":0.0000135198225,"about_ca_system_score_gemma":0.000055253775,"threshold_uncertainty_score":0.33021715},"labels":[],"label_agreement":null},{"id":"W2982389559","doi":"10.1101/824706","title":"Harmonization of diffusion MRI datasets with adaptive dictionary learning","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Engineering and Physical Sciences Research Council; Wolfson Foundation; Cardiff University; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Scanner; Pooling; Computer science; Artificial intelligence; Pattern recognition (psychology); Harmonization; Matching (statistics); Image registration; Diffusion MRI; Population; Data mining; Computer vision; Magnetic resonance imaging; Statistics; Mathematics; Image (mathematics); Radiology","score_opus":0.02812963206835971,"score_gpt":0.26737774111580564,"score_spread":0.23924810904744592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982389559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49594992,0.0006117418,0.49757448,0.00071045867,0.0002544737,0.002666526,0.0010363042,0.0011492622,0.000046829693],"genre_scores_gemma":[0.9373492,0.0005195173,0.061612353,0.00011216806,0.00011905451,0.00014574148,0.000016206226,0.00011341631,0.00001231655],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982565,0.000052863084,0.000359417,0.00074062234,0.00035210067,0.00023850604],"domain_scores_gemma":[0.9978279,0.000050157032,0.00049597374,0.0010834702,0.00041080153,0.00013170765],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001458173,0.00033580093,0.00046798185,0.00021683789,0.00010989325,0.0000242499,0.00020936602,0.00022251018,0.000021696385],"category_scores_gemma":[0.00006581696,0.00031440216,0.00007555426,0.00039453758,0.000116559575,0.000111147914,0.00035165646,0.0008321411,0.000016343245],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040155495,0.0006247144,0.095108174,0.00090182514,0.0002064597,0.00006761217,0.000013623986,0.0024663073,0.897135,0.0015483869,0.001510553,0.00001577197],"study_design_scores_gemma":[0.0023017363,0.0009891718,0.43108696,0.00394987,0.0008542237,4.5951754e-7,0.000012735264,0.026810057,0.50035995,0.000012813639,0.032256328,0.0013656893],"about_ca_topic_score_codex":0.000018872164,"about_ca_topic_score_gemma":1.6454072e-7,"teacher_disagreement_score":0.4413993,"about_ca_system_score_codex":0.00013407988,"about_ca_system_score_gemma":0.00029624772,"threshold_uncertainty_score":0.9999308},"labels":[],"label_agreement":null},{"id":"W2982576266","doi":"10.1016/j.mri.2019.09.012","title":"Inherent spatial structure in myelin water fraction maps","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Purdue Policy Research Institute, Purdue University; Vancouver Coastal Health Research Institute; Genzyme; Roche; University of British Columbia; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Voxel; Spatial distribution; Fiber bundle; Mathematics; Anisotropy; Anatomy; Bundle; Physics; Biology; Optics; Medicine; Materials science; Statistics; Magnetic resonance imaging; Radiology","score_opus":0.017132514992752538,"score_gpt":0.29561739947951193,"score_spread":0.2784848844867594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982576266","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9856947,0.0015723917,0.003726177,0.00489506,0.0001621212,0.0010754828,0.000013622096,0.00020655405,0.0026538637],"genre_scores_gemma":[0.99116945,0.00007984426,0.0065352283,0.00085504696,0.00009895231,0.000046202826,0.000035035777,0.000030319025,0.0011499322],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9989501,0.000018285951,0.00022944521,0.00034896782,0.0001731972,0.00027997774],"domain_scores_gemma":[0.9994756,0.000017165068,0.00003598052,0.00038302515,0.000039943414,0.00004830782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059763235,0.00013705753,0.00018624132,0.00010265494,0.00003237256,0.000021575584,0.00008634185,0.000035251356,0.000634781],"category_scores_gemma":[0.000014395523,0.00010833537,0.000038438404,0.00011980331,0.00003844818,0.000093214156,0.000056865625,0.00031002783,0.00010133275],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079648926,0.00006392425,0.38449648,0.000047011345,8.540916e-7,0.000041255007,0.00008649074,0.000024577643,0.14117011,0.00018975895,0.00085972593,0.47294015],"study_design_scores_gemma":[0.0015682132,0.00011204477,0.52988064,0.00020922044,0.00001511821,0.00011774475,0.000049996706,0.0070892065,0.03324746,0.0047458904,0.42269635,0.0002680973],"about_ca_topic_score_codex":0.000158895,"about_ca_topic_score_gemma":0.000010306196,"teacher_disagreement_score":0.47267205,"about_ca_system_score_codex":0.0000746378,"about_ca_system_score_gemma":0.000017866034,"threshold_uncertainty_score":0.6950407},"labels":[],"label_agreement":null},{"id":"W2982698399","doi":"10.1038/s41582-019-0270-5","title":"Traumatic and nontraumatic spinal cord injury: pathological insights from neuroimaging","year":2019,"lang":"en","type":"review","venue":"Nature Reviews Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":229,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; University of Toronto","funders":"","keywords":"Medicine; Spinal cord; Myelopathy; Spinal cord injury; Neuroimaging; Pathological; White matter; Neuroscience; Grey matter; Pathophysiology; Central nervous system disease; Pathology; Magnetic resonance imaging; Radiology; Surgery; Psychology","score_opus":0.18370922188088395,"score_gpt":0.46205088929619076,"score_spread":0.2783416674153068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982698399","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00021796573,0.9932469,0.00035947215,0.00075992267,0.00032396236,0.0044097695,0.000045465535,0.0002563059,0.00038021823],"genre_scores_gemma":[0.0001634478,0.98806524,0.0042383526,0.006429855,0.0002959324,0.00046975253,0.00016737198,0.0001247345,0.000045307734],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960182,0.00062011415,0.0012934358,0.001401335,0.000227364,0.00043956822],"domain_scores_gemma":[0.9970679,0.00041715652,0.0008550372,0.001388998,0.000053707263,0.0002171557],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00017814536,0.00084790733,0.004606036,0.00029305744,0.000101521204,0.000037597954,0.00043784047,0.00093417754,0.000031519456],"category_scores_gemma":[0.00041719197,0.0005770045,0.00065273565,0.00047947688,0.00021597017,0.00008050626,0.00025242695,0.004633803,0.00018348487],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073229334,0.00007900328,0.000007306498,0.011480221,0.00002477743,0.00017850638,0.0000044319518,8.59201e-9,0.000010515293,0.00046227738,0.0009605862,0.98671913],"study_design_scores_gemma":[0.00021559473,0.0013517602,0.00025757652,0.007640064,0.001738703,0.0013837247,4.4865385e-7,0.00002259813,4.98964e-7,0.00080703635,0.98619443,0.00038757068],"about_ca_topic_score_codex":0.0000026044154,"about_ca_topic_score_gemma":7.7613737e-7,"teacher_disagreement_score":0.9863316,"about_ca_system_score_codex":0.000035029178,"about_ca_system_score_gemma":0.00008995877,"threshold_uncertainty_score":0.9996681},"labels":[],"label_agreement":null},{"id":"W2983379126","doi":"10.1101/833095","title":"Assessing white matter pathway reproducibility from human whole-brain tractography clustering","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Compute Canada","keywords":"Human Connectome Project; Tractography; Connectome; Diffusion MRI; Cluster analysis; White matter; Human brain; Intraclass correlation; Computer science; Identification (biology); Artificial intelligence; Pattern recognition (psychology); Fractional anisotropy; Reproducibility; Cartography; Neuroscience; Biology; Magnetic resonance imaging; Mathematics; Statistics; Medicine; Geography; Functional connectivity; Radiology","score_opus":0.054635329108588065,"score_gpt":0.31618647453421356,"score_spread":0.2615511454256255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983379126","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94498855,0.0003038822,0.044792794,0.0055445083,0.0005214776,0.0019538119,0.00041067306,0.0013998699,0.000084447776],"genre_scores_gemma":[0.9439013,0.00001493532,0.05306216,0.0017482027,0.00063522346,0.0003281408,0.000007198296,0.000264905,0.000037909715],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9945117,0.00015207446,0.0009315492,0.0033236889,0.00045507203,0.00062590576],"domain_scores_gemma":[0.99183786,0.00010253575,0.00069744076,0.006679923,0.0003761772,0.00030605253],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009953837,0.0007407779,0.0009844659,0.00035347743,0.00024866592,0.00040358063,0.00056512875,0.00054256886,0.000109524204],"category_scores_gemma":[0.0002053496,0.00079168467,0.0003838236,0.00050170516,0.00018281635,0.00034480655,0.0007950075,0.0017934762,0.000119568635],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002022263,0.0002555169,0.25375572,0.00044996434,0.000078349745,0.000042250766,0.000011398453,0.00003874995,0.7436984,0.000032701842,0.0016086032,0.000008075713],"study_design_scores_gemma":[0.00059801136,0.00005014806,0.87130153,0.001207792,0.00017827157,8.611721e-8,0.000004839809,0.0003804663,0.110814,0.000031272906,0.014551197,0.0008823826],"about_ca_topic_score_codex":0.00008141151,"about_ca_topic_score_gemma":0.000001838064,"teacher_disagreement_score":0.63288444,"about_ca_system_score_codex":0.00025476437,"about_ca_system_score_gemma":0.00028645902,"threshold_uncertainty_score":0.9994534},"labels":[],"label_agreement":null},{"id":"W2983420661","doi":"10.1016/j.compbiomed.2019.103528","title":"Synthesizing diffusion tensor imaging from functional MRI using fully convolutional networks","year":2019,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Institute for Information and Communications Technology Promotion; Institute for Basic Science; National Research Foundation of Korea; Korea Institute for Advancement of Technology; Ministry of Science, ICT and Future Planning; Ministry of Trade, Industry and Energy","keywords":"Diffusion MRI; Computer science; Tensor (intrinsic definition); Diffusion; Convolutional neural network; Artificial intelligence; Magnetic resonance imaging; Nuclear magnetic resonance; Pattern recognition (psychology); Physics; Mathematics; Radiology; Medicine; Geometry","score_opus":0.04606733961215789,"score_gpt":0.3430287233218202,"score_spread":0.2969613837096623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983420661","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49522832,0.0013727621,0.49871576,0.003718011,0.0004215558,0.00025368092,0.0000034488837,0.000077997094,0.00020847566],"genre_scores_gemma":[0.9676758,0.00030404257,0.028706042,0.0027467133,0.00043087333,0.0000076935885,0.00008940298,0.000011108935,0.000028308103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99921095,0.000030264115,0.0002021678,0.0003259134,0.0000569359,0.00017375208],"domain_scores_gemma":[0.9993936,0.00027438015,0.00006428171,0.00016538678,0.000036157722,0.000066196095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011371698,0.00011632919,0.00026012937,0.00010741191,0.00007039897,0.0000025100085,0.000051841922,0.000066941415,0.000062719686],"category_scores_gemma":[0.000028065964,0.00009158364,0.000024145662,0.000102912665,0.00023989889,0.000033205495,0.00007275896,0.00022840273,0.0000025978136],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013363171,0.000051545823,0.9541917,0.000015377618,0.000017847326,0.000017084967,0.00003777627,0.00027348584,0.028032392,0.005595014,0.000911068,0.010723064],"study_design_scores_gemma":[0.0022620105,0.0001401391,0.5778281,0.00065106456,0.000052280302,0.00024713675,0.000067721725,0.40487805,0.000068730544,0.0065920204,0.0070331832,0.00017957516],"about_ca_topic_score_codex":0.000044522203,"about_ca_topic_score_gemma":7.2674396e-7,"teacher_disagreement_score":0.4724475,"about_ca_system_score_codex":0.000042812804,"about_ca_system_score_gemma":0.000019489082,"threshold_uncertainty_score":0.37346727},"labels":[],"label_agreement":null},{"id":"W2983699868","doi":"10.1007/s00429-019-01973-y","title":"Brain structure and internalizing and externalizing behavior in typically developing children and adolescents","year":2019,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute","keywords":"White matter; Cingulum (brain); Fractional anisotropy; Uncinate fasciculus; Psychology; Diffusion MRI; Limbic system; Prefrontal cortex; Clinical psychology; Neuroscience; Developmental psychology; Medicine; Cognition; Central nervous system; Magnetic resonance imaging","score_opus":0.016695107895879746,"score_gpt":0.29450722829315745,"score_spread":0.2778121203972777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983699868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99473935,0.00049190846,0.0032069127,0.0009775244,0.000049667186,0.00046111603,0.000013207868,0.000047896163,0.000012391651],"genre_scores_gemma":[0.99355245,0.00009932441,0.0043256762,0.0018410909,0.00007167462,0.0000058461023,0.000023320263,0.000019666744,0.00006096355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99922496,0.000019554613,0.00016433015,0.00036249653,0.000085548694,0.00014313807],"domain_scores_gemma":[0.9996894,0.000029669796,0.00006394045,0.00012223626,0.000022821272,0.000071939256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050359547,0.0001507174,0.00018568146,0.000105154984,0.0000654413,0.000047908863,0.000030428966,0.00009484575,0.000010708904],"category_scores_gemma":[0.000030265799,0.00013112661,0.000013038779,0.00008701222,0.000056834717,0.00012937537,0.00007989002,0.00025566324,2.0446633e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010613039,0.000005915551,0.8807875,0.00007749538,0.00000831587,0.0000039243123,0.00011019456,5.132686e-7,0.050252117,0.0006614049,0.00006709458,0.0679194],"study_design_scores_gemma":[0.0009616469,0.000098145494,0.99367553,0.0002768255,0.000030826603,0.0004594423,0.000026953581,0.00007322205,0.00074530987,0.0026005146,0.00091340207,0.00013819951],"about_ca_topic_score_codex":0.000030446328,"about_ca_topic_score_gemma":0.000017223554,"teacher_disagreement_score":0.11288802,"about_ca_system_score_codex":0.000019665787,"about_ca_system_score_gemma":0.000011432409,"threshold_uncertainty_score":0.5347188},"labels":[],"label_agreement":null},{"id":"W2983754438","doi":"10.1093/geroni/igz038.1343","title":"POOR SLEEP QUALITY IS RELATED TO DECREASED WHITE MATTER INTEGRITY IN BRAIN NOCICEPTIVE PATHWAYS IN OLDER ADULTS","year":2019,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fractional anisotropy; White matter; Insula; Precuneus; Medicine; Bonferroni correction; Diffusion MRI; Audiology; Psychology; Neuroscience; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.04339950372748718,"score_gpt":0.36636418589470415,"score_spread":0.32296468216721697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2983754438","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96745485,0.00000473746,0.0041166693,0.025553457,0.000038327704,0.0010469188,0.000010275023,0.00009373201,0.0016810468],"genre_scores_gemma":[0.9763284,0.0000011712748,0.0067495587,0.016452165,0.0000113384285,0.00014183085,0.0000620202,0.000023297243,0.00023024085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99838024,0.000062897125,0.00073927327,0.0004227243,0.00016472397,0.00023013657],"domain_scores_gemma":[0.9992258,0.00009868749,0.00015002508,0.0003302881,0.00015979253,0.00003543141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006339859,0.00013915962,0.00024666422,0.0007427722,0.000018528139,0.00001322559,0.000098178985,0.000092024915,0.00022916353],"category_scores_gemma":[0.00020421208,0.0001456207,0.000024344336,0.0027012601,0.000021366288,0.00015749295,0.000057409525,0.00061166706,0.00010201608],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084144835,0.00015565194,0.9787261,0.000057771293,0.0000022741935,0.000007989951,0.0045192717,0.000023806997,0.009635988,0.0023535911,0.00064099545,0.0037924089],"study_design_scores_gemma":[0.0017950973,0.000025976671,0.9895636,0.0007043464,0.0000015849195,0.000004904331,0.00085549743,0.0012472167,0.002546489,0.002719666,0.000367833,0.00016778844],"about_ca_topic_score_codex":0.00031549274,"about_ca_topic_score_gemma":0.000050079077,"teacher_disagreement_score":0.010837493,"about_ca_system_score_codex":0.00023318245,"about_ca_system_score_gemma":0.000039256596,"threshold_uncertainty_score":0.59382397},"labels":[],"label_agreement":null},{"id":"W2984354293","doi":"10.1016/j.schres.2019.10.034","title":"Topographic diversity of structural connectivity in schizophrenia","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lawson Health Research Institute; Western University","funders":"Higher Education Discipline Innovation Project; Taipei Veterans General Hospital; Janssen Canada; National Key Research and Development Program of China; Canadian Institutes of Health Research; Academia Sinica; Natural Science Foundation of Shanghai; National Natural Science Foundation of China; Health Research Foundation; National Health Research Institutes; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Diversity (politics); Geography; Economic geography; Psychology; Psychiatry; Sociology; Anthropology","score_opus":0.11330511247548293,"score_gpt":0.4080466097785989,"score_spread":0.294741497303116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984354293","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99650615,0.00011755066,0.000059826943,0.0007830956,0.000041150124,0.0008404963,0.000015292568,0.000080471116,0.0015559376],"genre_scores_gemma":[0.99470025,0.000039321847,0.0049666055,0.000029218407,0.000039093502,0.00002343639,0.000009583732,0.000017375016,0.00017512252],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982895,0.000118822376,0.00022153388,0.00041671196,0.0005768225,0.000376571],"domain_scores_gemma":[0.99872285,0.00021594216,0.000054241813,0.0006596017,0.00022895397,0.000118393385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005883566,0.00012074145,0.00030913544,0.0005820608,0.00014935009,0.000011114535,0.00028390414,0.00008537395,0.00016399563],"category_scores_gemma":[0.00015061538,0.000110778325,0.00009563284,0.0012660666,0.00026646187,0.00012008209,0.0005817665,0.00082896266,0.000041282146],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035661506,0.00019411398,0.88849217,0.00018792436,0.00002552296,0.000033021377,0.00013418503,0.000013733646,0.053898875,0.0408094,0.00020925593,0.012435621],"study_design_scores_gemma":[0.0033708438,0.0003383713,0.94916457,0.00012432675,0.000009638409,0.000027514607,0.00006892019,0.00065641693,0.011085827,0.03474673,0.00025812132,0.00014870008],"about_ca_topic_score_codex":0.0003017671,"about_ca_topic_score_gemma":0.000062190324,"teacher_disagreement_score":0.060672395,"about_ca_system_score_codex":0.00007297492,"about_ca_system_score_gemma":0.00011856996,"threshold_uncertainty_score":0.4517409},"labels":[],"label_agreement":null},{"id":"W2984423921","doi":"10.1016/j.brs.2019.11.003","title":"Interhemispheric pathways in agenesis of the corpus callosum and Parkinson’s disease","year":2019,"lang":"en","type":"letter","venue":"Brain stimulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Toronto Western Hospital; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Transcranial magnetic stimulation; Neuroscience; Motor cortex; Inhibitory postsynaptic potential; Agenesis of the corpus callosum; Excitatory postsynaptic potential; Pyramidal tracts; Psychology; Cortex (anatomy); Primary motor cortex; Medicine; Stimulation","score_opus":0.058007788290823446,"score_gpt":0.30852700349884815,"score_spread":0.2505192152080247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984423921","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17000026,0.00059428025,0.007264386,0.81836015,0.00019157228,0.0026312652,0.00011163567,0.00015441404,0.0006920504],"genre_scores_gemma":[0.7520551,0.000083101746,0.0016303147,0.24335241,0.0003661631,0.0001049037,0.00021953146,0.000065574306,0.0021228837],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913675,0.00004466432,0.00025108887,0.00028668906,0.00016487505,0.000115960254],"domain_scores_gemma":[0.99905056,0.00022855311,0.00018014044,0.00047523723,0.00004111805,0.000024410952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060446117,0.00014682893,0.00023891109,0.00005902361,0.000024635248,0.000005228307,0.000097521835,0.00013711504,0.000017762744],"category_scores_gemma":[0.00015824716,0.000109712804,0.00006260717,0.00016459593,0.00008757325,0.000028641078,0.0000695061,0.0003562882,0.0000018166515],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013297157,0.00008553881,0.16104166,0.0011501944,0.00002222431,0.000060170554,0.0001833886,0.0005288048,0.009557775,0.00018732791,0.80908185,0.017968105],"study_design_scores_gemma":[0.00056163454,0.000041980733,0.36869606,0.00058305217,0.00006605865,0.000008556594,0.0000031163397,0.0062543526,0.0001497782,0.0016821185,0.6217954,0.00015785768],"about_ca_topic_score_codex":0.000027650047,"about_ca_topic_score_gemma":0.0000015206031,"teacher_disagreement_score":0.58205485,"about_ca_system_score_codex":0.000053929678,"about_ca_system_score_gemma":0.000043939574,"threshold_uncertainty_score":0.44739583},"labels":[],"label_agreement":null},{"id":"W2984928487","doi":"10.1016/j.nic.2019.09.007","title":"Neuroimaging in Schizophrenia","year":2019,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":144,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"H2020 Marie Skłodowska-Curie Actions; National Institute of Mental Health; Harvard Catalyst","keywords":"Neuroimaging; Schizophrenia (object-oriented programming); Neurochemical; Medicine; Neuroscience; Functional neuroimaging; Cognition; Psychiatry; Psychology; Internal medicine","score_opus":0.14971513642966588,"score_gpt":0.4372400620032872,"score_spread":0.2875249255736213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2984928487","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0002577588,0.9943504,0.0007022995,0.0003433275,0.00033043284,0.0023022508,0.00014330832,0.00039864864,0.0011716286],"genre_scores_gemma":[0.00019540351,0.98739403,0.010519437,0.0009482477,0.00014298595,0.000115071685,0.00024596162,0.00026478237,0.00017409665],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954012,0.00016853723,0.0019948797,0.0013532059,0.00045192783,0.0006302448],"domain_scores_gemma":[0.99539113,0.0007949046,0.0014341741,0.002019946,0.00014873261,0.0002110909],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017301738,0.00075778173,0.0035402244,0.00089740974,0.000057705092,0.000029694227,0.00072743924,0.00013366471,0.000019679648],"category_scores_gemma":[0.00047680558,0.0007296295,0.0009792257,0.001815817,0.0003366461,0.00014911982,0.0003972479,0.0021685697,0.00014956067],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029493276,0.00022247976,0.0033228968,0.007069457,0.000028848663,0.000120268756,0.000008705795,0.000013351976,8.629977e-7,0.000018851491,0.00040825098,0.98875654],"study_design_scores_gemma":[0.00057930883,0.00017754127,0.0017058764,0.0058434587,0.00072304776,0.00019701062,0.0000020575121,0.00038200035,4.4122493e-7,0.000045163502,0.989862,0.0004820602],"about_ca_topic_score_codex":0.000020701927,"about_ca_topic_score_gemma":0.0000017159085,"teacher_disagreement_score":0.9894538,"about_ca_system_score_codex":0.000084238796,"about_ca_system_score_gemma":0.00062724494,"threshold_uncertainty_score":0.9995155},"labels":[],"label_agreement":null},{"id":"W2985279176","doi":"10.1016/j.cmpb.2019.105200","title":"Novel atlas of fiber directions built from ex-vivo diffusion tensor images of porcine hearts","year":2019,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of Ontario Institute of Technology","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Diffusion MRI; Atlas (anatomy); Ex vivo; Fractional anisotropy; Computer science; Artificial intelligence; Computer vision; Pattern recognition (psychology); Biomedical engineering; Anatomy; Medicine; In vivo; Biology; Magnetic resonance imaging; Radiology","score_opus":0.09102182885112914,"score_gpt":0.4095629576410048,"score_spread":0.31854112878987567,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985279176","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5798322,0.0016365227,0.41371068,0.002680448,0.00025437895,0.0013139554,0.000036761456,0.00013913673,0.0003958763],"genre_scores_gemma":[0.08892054,0.0003457872,0.91000414,0.00016630454,0.00012857324,0.00002466152,0.00004705798,0.000021067526,0.0003418886],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99885046,0.000051366198,0.00044140714,0.00034741734,0.000145835,0.00016351801],"domain_scores_gemma":[0.9989609,0.00023727065,0.000160883,0.00042449514,0.0001085157,0.000107908505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030880622,0.00015521915,0.00054956647,0.00020244543,0.000021844317,0.0000048614534,0.00008566608,0.00007258459,0.00007239222],"category_scores_gemma":[0.000035171644,0.00011512716,0.00006605932,0.00047107847,0.00023118609,0.000039245297,0.00012403405,0.00016667179,0.0000011674366],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006558715,0.00049748144,0.043631174,0.00017131548,0.000024611978,0.0000035740027,0.000129806,0.0000010983662,0.38510838,0.00008041688,0.00031069302,0.56997585],"study_design_scores_gemma":[0.008131171,0.0040292284,0.5799154,0.0031603787,0.00029741367,0.0002714489,0.00013175601,0.010814693,0.12054317,0.0038412805,0.26829842,0.00056566246],"about_ca_topic_score_codex":0.00030002304,"about_ca_topic_score_gemma":0.0000014903317,"teacher_disagreement_score":0.5694102,"about_ca_system_score_codex":0.000013478938,"about_ca_system_score_gemma":0.00001903316,"threshold_uncertainty_score":0.4694749},"labels":[],"label_agreement":null},{"id":"W2985804183","doi":"10.1038/s41467-019-12867-2","title":"Author Correction: The challenge of mapping the human connectome based on diffusion tractography","year":2019,"lang":"en","type":"erratum","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MaRS; Western University; Hôpital du Sacré-Cœur de Montréal; Synaptive (Canada); Institut Universitaire de Gériatrie de Montréal; University of Toronto; University Health Network; Université de Montréal; Université de Sherbrooke","funders":"Wellcome Trust","keywords":"Connectome; Tractography; Diffusion MRI; Computer science; Human Connectome Project; Diffusion; Connectomics; Neuroscience; Data science; Functional connectivity; Biology; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.10895082961789886,"score_gpt":0.3856030417001582,"score_spread":0.2766522120822593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985804183","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024059895,0.022150384,0.0031225758,0.53610855,0.010064035,0.007085897,0.00034862163,0.0010007127,0.4198786],"genre_scores_gemma":[0.945143,0.0029030642,0.0016745663,0.0040538395,0.0006013295,0.0006477083,0.001814363,0.00012476469,0.043037403],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99840236,0.00022362136,0.00042882873,0.00035030628,0.0004038223,0.0001910849],"domain_scores_gemma":[0.9917688,0.0010400664,0.00053372636,0.0062939296,0.0003120409,0.000051470677],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003777207,0.000288791,0.0004212674,0.00028311482,0.0008184646,0.000025181136,0.0017072633,0.0006703474,0.000044173456],"category_scores_gemma":[0.00023534568,0.00017130777,0.00036284328,0.0007801178,0.00041882714,0.000030231477,0.00028059215,0.006516657,0.000009240091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014046228,0.0005117104,0.00026124445,0.00008344432,0.00005046667,6.268112e-7,0.00019746518,0.0000062798294,0.00034794805,0.013822929,0.98256147,0.0021423928],"study_design_scores_gemma":[0.00024813836,0.00013402349,0.009722658,0.0006797145,0.00015525347,0.000008477159,0.00009607787,0.0032831416,0.000039397277,0.000636071,0.9848327,0.0001643511],"about_ca_topic_score_codex":0.000018490862,"about_ca_topic_score_gemma":0.00004942008,"teacher_disagreement_score":0.94490236,"about_ca_system_score_codex":0.00006564537,"about_ca_system_score_gemma":0.00013143275,"threshold_uncertainty_score":0.99577534},"labels":[],"label_agreement":null},{"id":"W2986314683","doi":"10.1016/j.neuroimage.2019.116345","title":"Effects of unilateral cortical resection of the visual cortex on bilateral human white matter","year":2019,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Eye Institute; National Institutes of Health","keywords":"White matter; Resection; Psychology; Visual cortex; Inferior longitudinal fasciculus; Cortex (anatomy); Neuroscience; Tractography; Anatomy; Medicine; Magnetic resonance imaging; Surgery; Radiology","score_opus":0.02010873190519451,"score_gpt":0.3333295160145337,"score_spread":0.3132207841093392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986314683","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961594,0.0000023239825,0.00010565567,0.00056021934,0.000094194016,0.0006405346,0.0000035508517,0.00004988543,0.0023842503],"genre_scores_gemma":[0.9971613,0.000002417903,0.00015740131,0.0008360406,0.000030799383,0.000013435494,0.000004182763,0.000026564807,0.0017678387],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991487,0.000055338012,0.00023075631,0.00023096772,0.00019416746,0.0001400623],"domain_scores_gemma":[0.9993217,0.00006393929,0.00011178564,0.00041361462,0.000050474773,0.000038484184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043705815,0.00010744508,0.0002015374,0.00006430786,0.000044129618,0.000005523302,0.00010451847,0.00004033505,0.000080327794],"category_scores_gemma":[0.00001986847,0.00007443765,0.0000985138,0.00016676722,0.00010791381,0.000042911906,0.000068500434,0.00028876818,0.000030682117],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000098124496,0.0001737976,0.1702256,0.00013512811,0.0000046164882,0.0000060183133,0.000022332333,0.000003404542,0.8284866,0.00032031038,0.00047102757,0.00005300109],"study_design_scores_gemma":[0.000489502,0.00069368636,0.77126634,0.00009500107,0.000027209247,0.000020993239,0.0000014590352,0.00015266566,0.22678629,0.00014156844,0.00027636296,0.00004890838],"about_ca_topic_score_codex":0.0000060271764,"about_ca_topic_score_gemma":3.3444613e-7,"teacher_disagreement_score":0.60170037,"about_ca_system_score_codex":0.00001477582,"about_ca_system_score_gemma":0.000011058613,"threshold_uncertainty_score":0.30354792},"labels":[],"label_agreement":null},{"id":"W2986892424","doi":"10.7554/elife.44056.011","title":"Author response: Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age","year":2019,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"","keywords":"Psychology; Alcohol Use Disorders Identification Test; Voxel; Structural equation modeling; Novelty; Alcohol consumption; Artificial intelligence; Developmental psychology; Computer science; Machine learning; Social psychology; Alcohol","score_opus":0.08138228622988378,"score_gpt":0.3876331510564533,"score_spread":0.3062508648265695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986892424","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7568882,0.018624164,0.027898418,0.17064625,0.0021618146,0.01378778,0.007034499,0.0013953021,0.0015635787],"genre_scores_gemma":[0.10772594,0.00029000387,0.3135011,0.004582553,0.0003176852,0.00015268607,0.0063031907,0.00030214773,0.5668247],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977095,0.00006922691,0.00085971336,0.00053676445,0.0005935797,0.00023121372],"domain_scores_gemma":[0.997959,0.00018839845,0.00066239806,0.0009000302,0.0001912234,0.00009895549],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035006594,0.0002874452,0.00088946556,0.00014693636,0.000047168644,0.0000055757855,0.00029529864,0.00024287286,0.000280406],"category_scores_gemma":[0.00028735894,0.00027033789,0.00017147497,0.00018953436,0.0000674584,0.000024154197,0.0003700485,0.00060306117,0.000008611367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018564449,0.00014317667,0.0059117987,0.0030548798,0.00008368867,0.000033672375,0.00033741092,0.000003015677,0.06309652,0.00001697471,0.9040855,0.023047723],"study_design_scores_gemma":[0.00039417,0.00006336655,0.060130596,0.013565769,0.00024215863,0.000014988804,0.00001830288,0.000011189868,0.012423435,0.000043470423,0.9128568,0.00023571416],"about_ca_topic_score_codex":0.000036293975,"about_ca_topic_score_gemma":0.000037686415,"teacher_disagreement_score":0.64916223,"about_ca_system_score_codex":0.0002071043,"about_ca_system_score_gemma":0.00031615858,"threshold_uncertainty_score":0.9999749},"labels":[],"label_agreement":null},{"id":"W2988205449","doi":"10.7554/elife.50482.024","title":"Author response: Shifts in myeloarchitecture characterise adolescent development of cortical gradients","year":2019,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroscience; Biology; Evolutionary biology; Computational biology; Cognitive science; Psychology","score_opus":0.11240874232942236,"score_gpt":0.4142457435658354,"score_spread":0.301837001236413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988205449","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1396422,0.014910243,0.030398577,0.78320706,0.002260491,0.023089007,0.0009403634,0.0012460166,0.0043060454],"genre_scores_gemma":[0.06789943,0.0032568716,0.18576844,0.027244737,0.00037893758,0.0015753427,0.00321325,0.0004440853,0.7102189],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976955,0.00009633937,0.00086668204,0.00055764324,0.0004601116,0.00032370188],"domain_scores_gemma":[0.9985351,0.00009938186,0.00026967545,0.0007957091,0.00014138989,0.00015872905],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046495153,0.0003322581,0.00093195617,0.0002708037,0.00003138611,0.000004999838,0.00024801557,0.0002022644,0.00020902576],"category_scores_gemma":[0.00030192625,0.0002666385,0.00014704482,0.0003154975,0.00007471368,0.000018426677,0.00017450552,0.0010298707,0.00005478179],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00155099,0.0015284776,0.0020073105,0.017087398,0.00007320423,0.000097031254,0.0003115733,6.032649e-7,0.008169966,0.00015830023,0.8723839,0.09663124],"study_design_scores_gemma":[0.00036554597,0.000086513275,0.12242377,0.010742549,0.00006864951,0.000020506715,0.0000036235438,0.000010793205,0.0007113212,0.000023615945,0.86531913,0.0002239548],"about_ca_topic_score_codex":0.0000042100337,"about_ca_topic_score_gemma":0.0000061747005,"teacher_disagreement_score":0.7559623,"about_ca_system_score_codex":0.00017693813,"about_ca_system_score_gemma":0.00050579925,"threshold_uncertainty_score":0.9999786},"labels":[],"label_agreement":null},{"id":"W2988570450","doi":"10.1016/j.schres.2019.10.014","title":"Amygdala subnucleus volumes in psychosis high-risk state and first-episode psychosis","year":2019,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Suomalainen Lääkäriseura Duodecim; Seventh Framework Programme; Orionin Tutkimussäätiö; Turun Yliopisto; Academy of Finland; Turun Yliopistollinen Keskussairaala; National Alliance for Research on Schizophrenia and Depression","keywords":"Psychosis; Amygdala; Schizophrenia (object-oriented programming); Psychology; Population; Basal ganglia; Nucleus; Psychiatry; Neuroscience; Medicine; Internal medicine; Central nervous system","score_opus":0.05799041123087315,"score_gpt":0.3859631769696918,"score_spread":0.3279727657388186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2988570450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901244,0.00035506499,0.00022485077,0.00693413,0.00005905971,0.0012044995,0.0000428085,0.00013631416,0.0009188467],"genre_scores_gemma":[0.9778308,0.0031239078,0.016002707,0.00014255462,0.00006659071,0.00030189476,0.000012698745,0.00006062113,0.002458196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99770236,0.000121965975,0.00031244374,0.0007183955,0.0005364964,0.0006083514],"domain_scores_gemma":[0.99836636,0.0002770897,0.000065669374,0.000897005,0.00015940377,0.00023446896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006847328,0.00018917996,0.00032709644,0.00049816666,0.00018852754,0.000064660475,0.0002569227,0.000093699666,0.00020262437],"category_scores_gemma":[0.00014218078,0.00017446604,0.00006109463,0.00078703754,0.0002299369,0.00013777711,0.00018003923,0.0010650037,0.00039884113],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012719686,0.0003181825,0.9104837,0.00013891696,0.000028461625,0.000021303364,0.0001496363,0.000014353506,0.0020135464,0.0017382654,0.012392539,0.071429126],"study_design_scores_gemma":[0.00446801,0.00068122096,0.90265137,0.0003231085,0.000022641352,0.000032334578,0.000053935677,0.0023724467,0.0026117773,0.025694283,0.060734857,0.0003540428],"about_ca_topic_score_codex":0.0021663548,"about_ca_topic_score_gemma":0.00097374915,"teacher_disagreement_score":0.07107508,"about_ca_system_score_codex":0.00010159201,"about_ca_system_score_gemma":0.000030274648,"threshold_uncertainty_score":0.7114518},"labels":[],"label_agreement":null},{"id":"W2989104806","doi":"10.1016/j.neuron.2019.09.030","title":"Holographic Reconstruction of Axonal Pathways in the Human Brain","year":2019,"lang":"en","type":"article","venue":"Neuron","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":145,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Center for Complementary and Integrative Health; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Neuroscience; Holography; Human brain; Psychology; Biology; Physics; Optics","score_opus":0.06744416312274708,"score_gpt":0.3318688984028369,"score_spread":0.2644247352800898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989104806","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99263406,0.00000917806,0.00013550854,0.0020984416,0.000024866997,0.00028396415,0.000002131871,0.000038882354,0.004772984],"genre_scores_gemma":[0.9982924,0.000010461687,0.00068848213,0.0009187938,0.00001833221,0.000017329961,0.000004579557,0.0000062781364,0.000043372213],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996075,0.000025343223,0.000108609886,0.00011898195,0.0000727544,0.000066823806],"domain_scores_gemma":[0.99964845,0.000044242217,0.000044463697,0.00023947038,0.000012677197,0.000010717515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000077531055,0.00004230593,0.000077157594,0.00006535724,0.000017711827,0.000002094712,0.00006420385,0.00002140818,0.000019917843],"category_scores_gemma":[0.000014624201,0.000031065327,0.000033449156,0.00016143851,0.000045655663,0.000024279572,0.000011239277,0.00015346015,0.0000043688788],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017098124,0.00012252544,0.19494289,0.000033317294,0.000001821979,0.000007894773,0.00007904234,0.000004287786,0.7716912,0.015916148,0.0006854898,0.01649828],"study_design_scores_gemma":[0.0005826439,0.00039347867,0.9724865,0.000050648123,0.000009261522,0.00022657891,0.00005385469,0.00007903274,0.007642244,0.008606978,0.009803459,0.000065305554],"about_ca_topic_score_codex":0.000005854897,"about_ca_topic_score_gemma":0.0000012704114,"teacher_disagreement_score":0.7775436,"about_ca_system_score_codex":0.000004221581,"about_ca_system_score_gemma":0.0000064833634,"threshold_uncertainty_score":0.12668073},"labels":[],"label_agreement":null},{"id":"W2989717595","doi":"10.1002/mrm.28083","title":"Diffusion dispersion imaging: Mapping oscillating gradient spin‐echo frequency dependence in the human brain","year":2019,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dispersion (optics); Nuclear magnetic resonance; Diffusion; White matter; Spin echo; Diffusion MRI; Isotropy; Effective diffusion coefficient; Human brain; Materials science; Physics; Magnetic resonance imaging; Optics; Medicine; Radiology","score_opus":0.0410082662047876,"score_gpt":0.340301888024965,"score_spread":0.29929362182017744,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2989717595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96193475,0.004406807,0.0006741576,0.023876727,0.000082169485,0.0013372875,0.0000014037847,0.00008452335,0.0076021883],"genre_scores_gemma":[0.99209356,0.00043870194,0.0034841062,0.0032527656,0.0001139794,0.00010088783,0.00001330911,0.000025961235,0.00047670785],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979379,0.000087490655,0.0005316398,0.00054082787,0.0005013577,0.00040078638],"domain_scores_gemma":[0.9988356,0.00021255689,0.00011670166,0.0007230605,0.000042309992,0.0000697363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007102565,0.00021179568,0.00035059635,0.0002547571,0.0001008665,0.000012650884,0.00033426928,0.000052457573,0.00015839956],"category_scores_gemma":[0.0002853724,0.00014501822,0.00004558258,0.00077516877,0.00019276267,0.00007933852,0.000087686574,0.000571167,0.000015968213],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001555399,0.00012315567,0.76358885,0.000089389134,6.005343e-7,0.00015425507,0.0017185675,0.0000048159286,0.16227631,0.0022371626,0.0008108323,0.0689805],"study_design_scores_gemma":[0.002010555,0.00039540482,0.95884323,0.0020713725,0.000010195425,0.00015844502,0.0013067155,0.0042307274,0.00014490966,0.006078889,0.024539692,0.00020986117],"about_ca_topic_score_codex":0.0005164616,"about_ca_topic_score_gemma":0.000054430293,"teacher_disagreement_score":0.19525439,"about_ca_system_score_codex":0.00012115263,"about_ca_system_score_gemma":0.000023716986,"threshold_uncertainty_score":0.5913671},"labels":[],"label_agreement":null},{"id":"W2990004766","doi":"10.1101/861880","title":"Use of multi-flip angle measurements to account for transmit inhomogeneity and non-Gaussian diffusion in DW-SSFP","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Steady-state free precession imaging; Flip angle; Diffusion; Gaussian; Diffusion MRI; Nuclear magnetic resonance; Computational physics; Physics; Statistical physics","score_opus":0.10267477529616657,"score_gpt":0.3162942403898048,"score_spread":0.21361946509363822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990004766","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93835616,0.00016493737,0.056663338,0.00043456428,0.00013869848,0.0037686531,0.00033217575,0.00013978446,0.0000017113413],"genre_scores_gemma":[0.8889623,0.00013345487,0.10983232,0.00034274856,0.00005947717,0.00056691957,0.0000010033687,0.00009627136,0.0000054890143],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9979658,0.000032004893,0.00051814347,0.0008544691,0.00027838582,0.00035120815],"domain_scores_gemma":[0.9980505,0.00004959497,0.00024845955,0.0010810315,0.00035543367,0.00021499449],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003149827,0.0003775341,0.00065097766,0.00032541453,0.00005919972,0.00004379552,0.00022383606,0.00028477635,0.0000038419735],"category_scores_gemma":[0.00016054355,0.00038384675,0.00011462856,0.00033276432,0.000063556705,0.000104222716,0.00024213137,0.00038791966,0.0000031380885],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011665658,0.0004031196,0.11780841,0.00065033126,0.000033372362,0.0000048259594,0.000014871127,0.00005792685,0.8807627,0.00003407737,0.00008266247,0.00003103188],"study_design_scores_gemma":[0.001376723,0.00015502464,0.62897664,0.0011185493,0.00011942185,2.4986972e-8,0.0000015076126,0.0021868714,0.3618138,0.0000019533911,0.0038243479,0.00042514203],"about_ca_topic_score_codex":0.000107904816,"about_ca_topic_score_gemma":0.000011320618,"teacher_disagreement_score":0.5189489,"about_ca_system_score_codex":0.00018823259,"about_ca_system_score_gemma":0.00021299414,"threshold_uncertainty_score":0.99986136},"labels":[],"label_agreement":null},{"id":"W2990322742","doi":"10.1101/859538","title":"Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute for Health and Care Research; National Institute of Neurological Disorders and Stroke; Canada First Research Excellence Fund; National Institutes of Health; Craig H. Neilsen Foundation; Natural Sciences and Engineering Research Council of Canada; Engineering and Physical Sciences Research Council; Institut de Valorisation des Données; European Commission; Multiple Sclerosis Society; Canadian Institutes of Health Research","keywords":"Noise reduction; Computer science; Parametric statistics; SIGNAL (programming language); Artificial intelligence; Noise (video); Principal component analysis; Diffusion MRI; Pattern recognition (psychology); Image quality; Algorithm; Mathematics; Magnetic resonance imaging; Image (mathematics); Medicine; Radiology","score_opus":0.06322021613638709,"score_gpt":0.33134311904228686,"score_spread":0.2681229029058998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990322742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5828617,0.0009132328,0.4127693,0.00059088954,0.00010928025,0.0019329009,0.00012476176,0.00068364636,0.000014280174],"genre_scores_gemma":[0.6242165,0.00025005933,0.3750656,0.0001653272,0.000063847154,0.00011167607,6.50735e-7,0.000113705086,0.000012635337],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9974471,0.000068220485,0.00044326045,0.0012200831,0.00035115273,0.00047021295],"domain_scores_gemma":[0.9973241,0.00010470264,0.00046595605,0.0012091686,0.00060816464,0.0002879202],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028179283,0.0005641557,0.0007457118,0.00048314105,0.00015552124,0.00015595049,0.00027435727,0.0002825579,0.00001122906],"category_scores_gemma":[0.00014609279,0.0005282859,0.00009626502,0.0007709712,0.0003165049,0.00015277312,0.00034182888,0.0011321399,0.00003360805],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011883436,0.00043458614,0.016931744,0.0011501143,0.00021228321,0.0002856816,0.000009466419,0.000059126985,0.9779452,0.0015103676,0.00024582644,0.000027229902],"study_design_scores_gemma":[0.0050707296,0.003806273,0.5187649,0.0054048467,0.0014107069,0.0000023939997,0.00003385526,0.0140033765,0.44077364,0.000022137843,0.007720726,0.0029863818],"about_ca_topic_score_codex":0.000045864148,"about_ca_topic_score_gemma":7.2666296e-7,"teacher_disagreement_score":0.5371716,"about_ca_system_score_codex":0.0001932805,"about_ca_system_score_gemma":0.00041930893,"threshold_uncertainty_score":0.9997169},"labels":[],"label_agreement":null},{"id":"W2990532819","doi":"10.1002/hipo.23177","title":"Curved multiplanar reformatting provides improved visualization of hippocampal anatomy","year":2019,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Hippocampal formation; Visualization; Anatomy; Coronal plane; Computer science; Neuroscience; Dentate gyrus; Biology; Artificial intelligence","score_opus":0.031107763402867576,"score_gpt":0.34284111682084806,"score_spread":0.3117333534179805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990532819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98433083,0.00010739434,0.011185747,0.00039174705,0.00008063431,0.0011714781,0.000010068525,0.00037557064,0.0023465469],"genre_scores_gemma":[0.9833664,0.000032035467,0.015787484,0.00034996367,0.00004080377,0.00004875202,0.00006929595,0.000034669953,0.00027061882],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99898237,0.00002523808,0.00035245216,0.0002651937,0.00016287097,0.00021187404],"domain_scores_gemma":[0.9990587,0.000052753458,0.00022341966,0.0004442901,0.00014051385,0.00008031004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015163817,0.00014127766,0.00026816345,0.00011940127,0.000049386505,0.000009332151,0.000105425206,0.000071462906,0.00004650543],"category_scores_gemma":[0.000079843754,0.00012374314,0.000080719736,0.0002728564,0.000053302483,0.00014173944,0.000048826045,0.00013865391,0.000035089375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039095577,0.0005353675,0.31612903,0.0011741059,0.00007607838,0.000011734559,0.0005897484,0.00004299571,0.5795031,0.007863225,0.0009603864,0.09272328],"study_design_scores_gemma":[0.015398472,0.0032192967,0.16548829,0.002212965,0.00048381588,0.0006376176,0.0014724634,0.19509293,0.48719347,0.029540304,0.09705805,0.0022023353],"about_ca_topic_score_codex":0.000023035382,"about_ca_topic_score_gemma":0.0000014910365,"teacher_disagreement_score":0.19504994,"about_ca_system_score_codex":0.000048859558,"about_ca_system_score_gemma":0.00005579797,"threshold_uncertainty_score":0.5046099},"labels":[],"label_agreement":null},{"id":"W2990740276","doi":"10.3389/fnana.2019.00096","title":"Internal Subdivisions of the Marmoset Claustrum Complex: Identification by Myeloarchitectural Features and High Field Strength Imaging","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"Claustrum; Marmoset; Identification (biology); Field (mathematics); Psychology; Neuroscience; Artificial intelligence; Computer science; Biology; Mathematics; Paleontology","score_opus":0.010110163181727572,"score_gpt":0.28268659783731115,"score_spread":0.27257643465558357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990740276","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841353,0.0001886655,0.005689163,0.00852159,0.00030006157,0.0005744987,0.00005366215,0.00005634232,0.00048068605],"genre_scores_gemma":[0.9946508,0.00005311604,0.004056427,0.0007142996,0.00001478634,0.000014309494,0.000023606812,0.000015273316,0.00045740698],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991936,0.00003598766,0.00021622148,0.0002578756,0.00014941196,0.000146922],"domain_scores_gemma":[0.9993851,0.00005525081,0.000109043416,0.00038019044,0.000027980015,0.0000423967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053835844,0.00010738595,0.0001743301,0.00009796606,0.000046252033,0.000016361966,0.0001944975,0.00002910567,0.000018157207],"category_scores_gemma":[0.000049957584,0.000082029095,0.000047113797,0.00019996878,0.00010616172,0.00005908466,0.00011667909,0.00033807333,8.1692923e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000080681304,0.0000745362,0.77400756,0.00006466358,0.000014622948,0.0000051417487,0.00008206346,0.000006489763,0.025592439,0.00088288944,0.15191333,0.04727558],"study_design_scores_gemma":[0.00090929156,0.00006478984,0.9492126,0.00011099906,0.000036312187,0.000092334536,0.00012868257,0.004044769,0.028211439,0.0038926103,0.013142629,0.00015355356],"about_ca_topic_score_codex":0.00007219898,"about_ca_topic_score_gemma":0.0000022827837,"teacher_disagreement_score":0.17520502,"about_ca_system_score_codex":0.000021090633,"about_ca_system_score_gemma":0.000012836265,"threshold_uncertainty_score":0.33450496},"labels":[],"label_agreement":null},{"id":"W2990802750","doi":"10.1016/j.exger.2019.110792","title":"Tractography of the external capsule and cognition: A diffusion MRI study of cholinergic fibers","year":2019,"lang":"en","type":"article","venue":"Experimental Gerontology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; Cégep de l'Abitibi Témiscamingue; Centre intégré de santé et de services sociaux de Chaudière-Appalaches","funders":"","keywords":"Tractography; Cholinergic; Diffusion MRI; Cognition; Capsule; Internal capsule; Medicine; Neuroscience; External capsule; Magnetic resonance imaging; Anatomy; Psychology; Pathology; Biology; Radiology; Fractional anisotropy","score_opus":0.05096605843489169,"score_gpt":0.36334770724545473,"score_spread":0.3123816488105631,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2990802750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976926,0.00039252188,0.0001056672,0.000113545044,0.00004647971,0.0005964659,0.0000030371864,0.000017583227,0.0010321402],"genre_scores_gemma":[0.9986717,0.000016821641,0.0010626735,0.00010237562,0.000011724324,0.00003909919,0.0000017559781,0.000007058079,0.00008679159],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995098,0.000022176153,0.00015860405,0.00014944146,0.00008684053,0.00007309826],"domain_scores_gemma":[0.9996306,0.000013781792,0.00009416504,0.00021585003,0.000019255378,0.000026388016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022839044,0.00006748458,0.00017013846,0.000033704786,0.000025583604,0.000001229127,0.000058454196,0.000027731061,0.00006421544],"category_scores_gemma":[0.000002318972,0.00004785994,0.000043082186,0.000066329936,0.00010695953,0.000023383609,0.000053275307,0.00007451887,7.447145e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094676514,0.001204525,0.048280783,0.000014622073,0.000015771777,0.0000022023105,0.0012915335,0.0000014584401,0.9482833,0.00028026878,0.000053930387,0.0004768863],"study_design_scores_gemma":[0.0041260733,0.0020323305,0.34101424,0.000069800466,0.0000666895,0.00016965477,0.0039675455,0.00012986944,0.6478016,0.00021217193,0.00029767066,0.00011240529],"about_ca_topic_score_codex":0.000046424157,"about_ca_topic_score_gemma":0.000002806083,"teacher_disagreement_score":0.30048177,"about_ca_system_score_codex":0.0000068931486,"about_ca_system_score_gemma":0.000005802021,"threshold_uncertainty_score":0.19516717},"labels":[],"label_agreement":null},{"id":"W2991015307","doi":"10.1016/j.nicl.2019.102102","title":"Microstructural abnormalities in deep and superficial white matter in youths with mild traumatic brain injury","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Centre for Addiction and Mental Health; Hospital for Sick Children; Toronto Rehabilitation Institute; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; Hospital for Sick Children","keywords":"White matter; Fractional anisotropy; Voxel; Diffusion MRI; Traumatic brain injury; Psychology; Audiology; Neuroscience; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.07875665709767951,"score_gpt":0.3932316182364547,"score_spread":0.31447496113877516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991015307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99287164,0.00002504437,0.00009436563,0.005522784,0.000057238412,0.00067522144,0.000014530023,0.00006610837,0.00067307],"genre_scores_gemma":[0.9883103,0.000027853597,0.004478206,0.006679261,0.000062492734,0.000026337731,0.000014190768,0.000039445844,0.00036194405],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998396,0.0000976786,0.00058886735,0.0004991977,0.0001323224,0.0002859507],"domain_scores_gemma":[0.999129,0.000254666,0.00007556654,0.00042024243,0.000027508033,0.0000929977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023591428,0.00018256008,0.00043172695,0.00013382573,0.000025149937,0.000028209688,0.00010964324,0.00009021995,0.000112731905],"category_scores_gemma":[0.00008386104,0.00015118402,0.00005753865,0.00020477922,0.00022711202,0.00014705674,0.00007462335,0.0006768924,0.000037637492],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003305811,0.00010118741,0.99632627,0.00006686703,0.0000027234878,0.00005381232,0.00029386504,0.0000025780262,0.0010709724,0.000055367433,0.00033827685,0.0013574819],"study_design_scores_gemma":[0.001721028,0.00040737627,0.9957996,0.000112000955,0.000014054819,0.00014214107,0.00017848598,0.00049859786,0.00015186917,0.00024684166,0.00056258374,0.0001654257],"about_ca_topic_score_codex":0.000025462798,"about_ca_topic_score_gemma":0.00004428448,"teacher_disagreement_score":0.0045613693,"about_ca_system_score_codex":0.000018921124,"about_ca_system_score_gemma":0.00003328989,"threshold_uncertainty_score":0.61651057},"labels":[],"label_agreement":null},{"id":"W2991457998","doi":"10.1101/852764","title":"Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Australian Government; National Imaging Facility; Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Diffusion MRI; White matter; Neurite; Tractography; Neuroscience; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.01361255381374003,"score_gpt":0.25412181501823183,"score_spread":0.24050926120449181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991457998","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959788,0.00040045328,0.002150461,0.000278926,0.00010833093,0.0009356076,0.000012369573,0.00013064862,0.0000044501858],"genre_scores_gemma":[0.98965895,0.00060452445,0.009389743,0.00016589816,0.000056364832,0.00007534799,9.0528744e-7,0.000046008496,0.0000022314548],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865514,0.00003308416,0.00030155614,0.0006770714,0.00013818836,0.00019497785],"domain_scores_gemma":[0.9991513,0.000032196098,0.00016088349,0.00047757727,0.000082958424,0.0000950772],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015236085,0.00024277209,0.00033181877,0.00020851943,0.00003699429,0.000060925493,0.00007951279,0.00017959258,0.0000019132228],"category_scores_gemma":[0.000079819205,0.0002617766,0.000031212367,0.0003427774,0.000054494914,0.00014430335,0.00023446971,0.0006467865,0.000003003002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008147394,0.00018077617,0.70163393,0.0003741922,0.000012280845,0.000035150948,0.000057511486,0.000009942129,0.2972855,0.0002420434,0.00002188318,0.00006533689],"study_design_scores_gemma":[0.0005830761,0.000051408915,0.96454954,0.0005536952,0.000028854625,1.3401682e-7,0.0000045544098,0.00089515414,0.033006843,0.00001035188,0.00009757196,0.0002187974],"about_ca_topic_score_codex":0.000050924216,"about_ca_topic_score_gemma":0.000002561099,"teacher_disagreement_score":0.26427865,"about_ca_system_score_codex":0.0001303295,"about_ca_system_score_gemma":0.000072843504,"threshold_uncertainty_score":0.99998343},"labels":[],"label_agreement":null},{"id":"W2991597154","doi":"10.1523/jneurosci.1650-18.2019","title":"Differences in Frontal Network Anatomy Across Primate Species","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Biotechnology and Biological Sciences Research Council; King's College London; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Primate; Anatomy; Biology; Evolutionary biology; Neuroscience","score_opus":0.11234750293543096,"score_gpt":0.3886606071373994,"score_spread":0.2763131042019685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991597154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9772194,0.000084781364,0.010911577,0.011273039,0.0001159681,0.000107892025,0.0000029953153,0.000028376695,0.00025596764],"genre_scores_gemma":[0.9917,0.000183892,0.0047555817,0.0031582077,0.00015311802,0.0000014070275,1.1214499e-7,0.0000057739744,0.000041917323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991737,0.000014252264,0.00026030745,0.00013938556,0.00022716579,0.00018519598],"domain_scores_gemma":[0.99953985,0.000029222707,0.00017211746,0.000089090354,0.000041461346,0.00012825379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009747517,0.0000687138,0.00019582763,0.000027420538,0.00005950194,0.000027119328,0.00020946976,0.000014971396,0.0000049001387],"category_scores_gemma":[0.0001383077,0.00005168421,0.0000507931,0.00039086075,0.0001335769,0.00015673331,0.000064038926,0.00026598736,0.000001272968],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018515892,0.00021043807,0.6529908,0.000038840746,0.0000025943907,0.0008063845,0.0006803199,0.00019740769,0.33705273,0.0010385285,0.0035346039,0.0032621832],"study_design_scores_gemma":[0.00042914972,0.00045106074,0.97120965,0.000069094756,0.000006751812,0.0003891223,0.00007808251,0.002193992,0.004498514,0.00039802914,0.020195128,0.00008142558],"about_ca_topic_score_codex":7.736827e-7,"about_ca_topic_score_gemma":4.302964e-7,"teacher_disagreement_score":0.33255422,"about_ca_system_score_codex":0.00001813287,"about_ca_system_score_gemma":0.00004068696,"threshold_uncertainty_score":0.21076208},"labels":[],"label_agreement":null},{"id":"W2994619082","doi":"10.1002/brb3.1514","title":"Diffusion tensor imaging tractography reveals altered fornix in all diagnostic subtypes of multiple sclerosis","year":2019,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Multiple Sclerosis Society; Canada Research Chairs; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Uncinate fasciculus; White matter; Inferior longitudinal fasciculus; Cingulum (brain); Medicine; Tractography; Multiple sclerosis; Psychology; Neuroscience; Magnetic resonance imaging; Pathology; Radiology; Internal medicine; Hippocampus; Psychiatry","score_opus":0.07964463984501635,"score_gpt":0.33372659288023976,"score_spread":0.2540819530352234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2994619082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997732,0.00015247267,0.00016283554,0.0010113763,0.000022843484,0.0007865344,0.000025783962,0.000056769775,0.00004942275],"genre_scores_gemma":[0.9955814,0.0001638694,0.0035176503,0.00048618444,0.000015586598,0.000106438776,0.000023913008,0.000018300796,0.00008667475],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99931866,0.000015312546,0.00020586679,0.0002261943,0.00008728488,0.00014665509],"domain_scores_gemma":[0.9993368,0.0002805234,0.0000699966,0.00022483701,0.00002878714,0.000059075475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000077490964,0.00009978579,0.0002064669,0.0001255563,0.000020383766,0.000006849617,0.000050959246,0.000032676835,0.000023334067],"category_scores_gemma":[0.000114711176,0.0000835624,0.000058495425,0.00013532574,0.00005046471,0.000053307343,0.000033442506,0.00010999864,0.000003030766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015400577,0.0002298195,0.6969806,0.00003223571,0.0000011777436,0.0000036619526,0.000042423217,1.4945354e-7,0.29217902,0.000022325115,0.0001746198,0.010318584],"study_design_scores_gemma":[0.0009852656,0.00007568514,0.9914078,0.00020986242,0.000047000343,0.000016696928,0.000038956896,0.00007868983,0.0060730963,0.00009309908,0.00088591897,0.00008790963],"about_ca_topic_score_codex":0.000053017113,"about_ca_topic_score_gemma":0.0000064439955,"teacher_disagreement_score":0.29442725,"about_ca_system_score_codex":0.000008967343,"about_ca_system_score_gemma":0.0000061211126,"threshold_uncertainty_score":0.3407576},"labels":[],"label_agreement":null},{"id":"W2995065313","doi":"10.1038/s41380-019-0631-x","title":"Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium","year":2019,"lang":"en","type":"review","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":117,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Lawson Health Research Institute; Western University","funders":"National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Center for Research Resources; National Institute of Allergy and Infectious Diseases; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute on Alcohol Abuse and Alcoholism; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Clinical Science Research and Development; National Institutes of Health; Congressionally Directed Medical Research Programs; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Bill and Melinda Gates Foundation; ZonMw; National Alliance for Research on Schizophrenia and Depression; Canadian Institute for Military and Veteran Health Research; Chinese Academy of Sciences; Division of Research Capacity Development; Deutsche Forschungsgemeinschaft; National Research Foundation; Yale Center for Clinical Investigation, Yale School of Medicine; Institute for Clinical and Translational Research, University of Wisconsin, Madison; Medical Research and Materiel Command; National Natural Science Foundation of China; Georgia Clinical and Translational Science Alliance; Waisman Center; U.S. Department of Veterans Affairs; Yale University; Office of Research and Development; National Center for PTSD, U.S. Department of Veterans Affairs; Michael J. Fox Foundation for Parkinson's Research; Traumatic Brain Injury Center of Excellence; South African Medical Research Council; U.S. Department of Defense","keywords":"Fractional anisotropy; White matter; Corpus callosum; Psychology; Neuroimaging; Psychiatry; Diffusion MRI; Brain Structure and Function; Depression (economics); Clinical psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.033739197866423314,"score_gpt":0.3567746116945881,"score_spread":0.32303541382816475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995065313","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023452554,0.9605115,0.002249676,0.004867,0.00083596376,0.0043669757,0.0033462315,0.0002225989,0.00014746873],"genre_scores_gemma":[0.0074734543,0.9589244,0.013256297,0.005172239,0.00048744655,0.00030047033,0.013448075,0.00051466754,0.00042292525],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971201,0.00016036081,0.001092016,0.0009181635,0.00026791845,0.00044144035],"domain_scores_gemma":[0.99736166,0.00009325966,0.00060232147,0.0017137764,0.00014062009,0.000088364446],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009872764,0.000571207,0.0011243949,0.00008398962,0.00012466896,0.00009413637,0.0005431471,0.00027417016,0.00007668283],"category_scores_gemma":[0.0000892423,0.00040887904,0.00027826283,0.00082370004,0.000121628145,0.000069660346,0.00018772462,0.0008467639,0.00016826642],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012635001,0.0037440984,0.2803925,0.08643335,0.0020932907,0.00035715272,0.007945785,0.00016641193,0.00046431963,0.001126004,0.08281407,0.53319955],"study_design_scores_gemma":[0.009919056,0.00032736268,0.06042309,0.087657556,0.0031953335,0.000942591,0.001322473,0.0001388851,0.00012364477,0.0009952814,0.83177525,0.0031794976],"about_ca_topic_score_codex":0.00014841641,"about_ca_topic_score_gemma":0.000084697196,"teacher_disagreement_score":0.74896115,"about_ca_system_score_codex":0.00008304999,"about_ca_system_score_gemma":0.00020077237,"threshold_uncertainty_score":0.9998363},"labels":[],"label_agreement":null},{"id":"W2995216162","doi":"10.3233/jad-191005","title":"Associations of White Matter Hyperintensities with Cognitive Decline: A Longitudinal Study","year":2019,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":92,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Hyperintensity; Cognition; Cognitive decline; Psychology; White matter; Longitudinal study; Medicine; Neuroscience; Dementia; Magnetic resonance imaging; Disease; Internal medicine; Pathology","score_opus":0.07958373307148219,"score_gpt":0.37107292871685926,"score_spread":0.29148919564537706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995216162","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996425,0.00024946564,0.0008827766,0.0016486632,0.00002894958,0.00041353077,0.000037936494,0.000013966012,0.00029973357],"genre_scores_gemma":[0.99723613,0.00000852457,0.002058795,0.0005295119,0.00005263296,0.0000079219235,0.0000054252887,0.000017571154,0.00008348952],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99917877,0.000021767422,0.00031541917,0.00010972505,0.00027801894,0.00009632174],"domain_scores_gemma":[0.9986241,0.00004896286,0.0003640471,0.00016326949,0.00065935607,0.00014030389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092581206,0.00009325007,0.0002898675,0.00010147168,0.00004142299,0.00000806868,0.00006079212,0.000013728705,0.00012961047],"category_scores_gemma":[0.000034695073,0.00006729273,0.00010611353,0.00012647142,0.0000506313,0.00011428878,0.000047195354,0.0001576303,0.000013604627],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004956939,0.0006867369,0.997751,0.000009181746,0.00033208754,0.00006869825,0.00015433632,0.000010742031,0.00007765975,0.000020083,0.00031109317,0.0000826882],"study_design_scores_gemma":[0.0012584473,0.0006185238,0.99535793,0.00012368572,0.0017232787,0.00007575362,0.00039630692,0.000021596543,0.00018414154,0.00011182789,0.00005975817,0.00006874601],"about_ca_topic_score_codex":0.00000417792,"about_ca_topic_score_gemma":8.0184424e-7,"teacher_disagreement_score":0.0023930655,"about_ca_system_score_codex":0.000013162058,"about_ca_system_score_gemma":0.00010569444,"threshold_uncertainty_score":0.2744118},"labels":[],"label_agreement":null},{"id":"W2995316596","doi":"10.1016/j.jmr.2019.106667","title":"Constant gradient FEXSY: A time-efficient method for measuring exchange","year":2019,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Raymond and Beverly Sackler Institute for Biological, Physical and Engineering Sciences, Yale University; Azrieli Foundation; Israel Science Foundation","keywords":"Mixing (physics); Chemistry; Diffusion; SIGNAL (programming language); Filter (signal processing); Constant (computer programming); Time constant; Weighting; Fick's laws of diffusion; Analytical Chemistry (journal); Residence time (fluid dynamics); Pulsed field gradient; Biological system; Chromatography; Thermodynamics; Physics; Computer science; Acoustics","score_opus":0.0584617030778875,"score_gpt":0.34395649548648843,"score_spread":0.28549479240860093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995316596","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38587743,0.03740776,0.54591465,0.013411371,0.0005917249,0.004574815,0.00005634476,0.0001803616,0.0119855385],"genre_scores_gemma":[0.16393998,0.0009951238,0.82605493,0.0012592634,0.00031594318,0.00008900456,0.000002102097,0.00006769578,0.0072759516],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99896723,0.000027132992,0.000370772,0.00016808124,0.00026761426,0.00019917585],"domain_scores_gemma":[0.9989969,0.00014891813,0.00024624582,0.00025549025,0.00024696338,0.000105459774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00048477846,0.00010694771,0.00031215168,0.000097825236,0.000038805974,0.000011068194,0.00012472032,0.000032881628,0.000104241524],"category_scores_gemma":[0.000110838606,0.00008442916,0.00014606092,0.00014017575,0.00003500308,0.000027809094,0.000029098639,0.00017482083,0.000015319085],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017837465,0.0011114891,0.004263291,0.00066051964,0.000040989667,0.00016824933,0.00057109864,0.00047999786,0.21614023,0.00848484,0.02681276,0.73948276],"study_design_scores_gemma":[0.0035417741,0.0024889063,0.01204922,0.00076452637,0.00013651648,0.0014691523,0.000041381303,0.027459491,0.011170215,0.0019599937,0.93868166,0.00023715035],"about_ca_topic_score_codex":0.0000012798987,"about_ca_topic_score_gemma":8.91842e-8,"teacher_disagreement_score":0.91186893,"about_ca_system_score_codex":0.00006669858,"about_ca_system_score_gemma":0.00006692085,"threshold_uncertainty_score":0.3442921},"labels":[],"label_agreement":null},{"id":"W2995329121","doi":"10.1101/661702","title":"Hippocampal subfields and limbic white matter jointly predict learning rate in older adults","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"College of Engineering, Michigan State University; National Institutes of Health; Deutsche Forschungsgemeinschaft; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Strategic Innovation Fund; Michigan State University","keywords":"Fractional anisotropy; White matter; Psychology; Limbic system; Magnetic resonance imaging; Diffusion MRI; Verbal learning; Hippocampal formation; Tractography; Hippocampus; Brain size; Limbic lobe; Audiology; Neuroscience; Cognition; Medicine; Radiology; Central nervous system","score_opus":0.016038070354299192,"score_gpt":0.2524127172686653,"score_spread":0.23637464691436613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995329121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914203,0.0006185553,0.0038493956,0.001589689,0.00023562655,0.0016659419,0.00003989997,0.0005273804,0.00005319833],"genre_scores_gemma":[0.99187917,0.00053643796,0.0058924155,0.0009270193,0.00020420818,0.0003445416,0.0000012630843,0.00015452968,0.000060399925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997527,0.000104588216,0.0005246052,0.001118716,0.00022526589,0.0004998164],"domain_scores_gemma":[0.99812186,0.000069423826,0.00030119246,0.0010762842,0.0002053775,0.00022584731],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037062776,0.00048732597,0.00065284513,0.00033456893,0.000082116574,0.00009433751,0.00022798186,0.0004649454,0.00008958167],"category_scores_gemma":[0.000106889194,0.0005116563,0.00010815334,0.00033283827,0.00010316066,0.00011447012,0.00044988166,0.0018336992,0.00008245452],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013725596,0.0002306333,0.95466805,0.0013990661,0.000055553624,0.00010608772,0.00004186198,0.000095763164,0.04199923,0.00008646549,0.0011683683,0.000011657631],"study_design_scores_gemma":[0.0012323916,0.00010849771,0.9807481,0.0021155968,0.000101476486,1.81812e-7,0.00000568764,0.001978838,0.011320096,0.0000062044537,0.0018354044,0.0005475166],"about_ca_topic_score_codex":0.00002338931,"about_ca_topic_score_gemma":0.0000010226171,"teacher_disagreement_score":0.030679133,"about_ca_system_score_codex":0.00012905661,"about_ca_system_score_gemma":0.00020107214,"threshold_uncertainty_score":0.9997335},"labels":[],"label_agreement":null},{"id":"W2995345211","doi":"10.1007/s11682-019-00211-7","title":"Differences in attentional control and white matter microstructure in adolescents with attentional, affective, and behavioral disorders","year":2019,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; Lotte and John Hecht Memorial Foundation","keywords":"Psychology; Fractional anisotropy; Psychopathology; Neuropsychology; White matter; Cognition; Association (psychology); Attentional control; Developmental psychology; Clinical psychology; Neuroscience; Medicine","score_opus":0.013776475550799572,"score_gpt":0.2962825678662885,"score_spread":0.2825060923154889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995345211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958475,0.0001716956,0.00019368289,0.0030572054,0.000016531358,0.00064997684,0.000022153441,0.000026663056,0.000014575933],"genre_scores_gemma":[0.9984691,0.000023045905,0.00073709444,0.0005115367,0.000009086711,0.000091572874,0.000013470042,0.000016323515,0.00012875673],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992336,0.000022194778,0.00012743642,0.0003552633,0.00009495635,0.00016655221],"domain_scores_gemma":[0.9997646,0.000014790403,0.000042187872,0.00010448757,0.000018553264,0.00005533892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050062696,0.00013948487,0.00018988838,0.00012613252,0.000043758428,0.000034552,0.000031277712,0.000031430918,0.000013822781],"category_scores_gemma":[0.0000024356957,0.00011457172,0.000018488663,0.00008634223,0.00016077107,0.00010581912,0.00003288239,0.00019607175,0.0000012247934],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004963749,0.00016911328,0.9894058,0.000049410723,0.0000014594498,0.000009988772,0.00004793361,1.3520057e-7,0.0074970666,0.00001124446,0.00004133537,0.002716849],"study_design_scores_gemma":[0.002665587,0.00006400849,0.99624985,0.00038149327,0.00004123979,0.00014525381,0.00011033338,0.000074054784,0.000017175673,0.000081497456,0.000036582285,0.00013291603],"about_ca_topic_score_codex":0.00006489891,"about_ca_topic_score_gemma":0.000058244943,"teacher_disagreement_score":0.0074798907,"about_ca_system_score_codex":0.000016173977,"about_ca_system_score_gemma":0.000010035901,"threshold_uncertainty_score":0.4672099},"labels":[],"label_agreement":null},{"id":"W2995639855","doi":"10.1371/journal.pone.0226715","title":"Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Parkwood Institute; Ottawa Hospital; Health Sciences Centre; Baycrest Hospital; University of Toronto; Sunnybrook Health Science Centre; Western University","funders":"Faculty of Health Sciences, Queen's University; London Health Sciences Foundation; Queen's University; Centre for Addiction and Mental Health Foundation; McMaster University; Fondation Brain Canada; Temerty Family Foundation; University of Ottawa; Ontario Brain Institute; Canada First Research Excellence Fund; Government of Ontario","keywords":"Diffusion MRI; Artifact (error); Fractional anisotropy; Computer science; Artificial intelligence; Ground truth; Standard deviation; White matter; Pattern recognition (psychology); Mathematics; Statistics; Magnetic resonance imaging; Medicine","score_opus":0.1955343761508801,"score_gpt":0.5016304248407035,"score_spread":0.30609604868982343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995639855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46582466,0.00012460805,0.5303087,0.0019908508,0.000009055362,0.0010356489,0.00003813709,0.00052592426,0.00014239165],"genre_scores_gemma":[0.60265523,0.000007587246,0.39687344,0.0002065558,0.00001565044,0.000058827165,0.00003856465,0.0000117718255,0.0001323854],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900806,0.00006136931,0.00041489213,0.00023593444,0.0001450499,0.000134678],"domain_scores_gemma":[0.99857134,0.00043058448,0.00023365801,0.00043076935,0.00028226263,0.000051393985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028666886,0.00009712893,0.00070485275,0.00013802193,0.00003673135,0.0000053258304,0.00007911582,0.000030870087,0.00003137886],"category_scores_gemma":[0.00028635983,0.00008280127,0.00015212274,0.00034561194,0.00003554389,0.000032928987,0.000024584973,0.0000857421,0.000003712695],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009069193,0.0010939545,0.36444184,0.00016410828,0.00024680604,9.174848e-8,0.000028102084,0.000017408107,0.6315176,0.00024184129,0.00007172049,0.0020858538],"study_design_scores_gemma":[0.0013653293,0.000099225086,0.120685644,0.00010049859,0.0024172636,4.618585e-7,0.000038974526,0.7388971,0.13555555,0.0004027201,0.00031754613,0.00011970497],"about_ca_topic_score_codex":0.000019415475,"about_ca_topic_score_gemma":6.3700094e-7,"teacher_disagreement_score":0.7388797,"about_ca_system_score_codex":0.000019639501,"about_ca_system_score_gemma":0.000012281224,"threshold_uncertainty_score":0.33765376},"labels":[],"label_agreement":null},{"id":"W2995803042","doi":"10.1002/nbm.4222","title":"Myelin water imaging and R<sub>2</sub><sup>*</sup> mapping in neonates: Investigating R<sub>2</sub><sup>*</sup> dependence on myelin and fibre orientation in whole brain white matter","year":2019,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"White matter; Myelin; Nuclear medicine; Nuclear magnetic resonance; Orientation (vector space); Magnetic resonance imaging; Medicine; Multiple sclerosis; T2 relaxation; Physics; Internal medicine; Radiology; Central nervous system; Mathematics","score_opus":0.01954663813922236,"score_gpt":0.2835762526544734,"score_spread":0.26402961451525103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995803042","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96546775,0.00029262752,0.00096630596,0.03146591,0.000047244204,0.0014461471,0.000024005472,0.0001515157,0.0001384912],"genre_scores_gemma":[0.98757684,0.00016485283,0.0032790513,0.008167044,0.00017780502,0.00018241761,0.00025943047,0.00009969231,0.000092865055],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9962448,0.00014739076,0.0010718519,0.0012040559,0.00051763223,0.00081428466],"domain_scores_gemma":[0.99847,0.00031711877,0.00019564768,0.00061256875,0.00009899852,0.00030564237],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00095632876,0.00051995605,0.00071872026,0.0012676922,0.000108050874,0.000061224455,0.00020798942,0.00020668983,0.000035121033],"category_scores_gemma":[0.00024449846,0.00045268683,0.000054699307,0.0011228255,0.0003673012,0.00044528968,0.00023351784,0.000962114,0.00009028456],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009589677,0.00010669402,0.37148973,0.00041398456,0.000009568557,0.000117760064,0.0049122567,0.0007927622,0.59840655,0.00003623944,0.0010517196,0.02256685],"study_design_scores_gemma":[0.016239172,0.0008371148,0.47946745,0.011588364,0.00009512126,0.0007811844,0.010197415,0.18315732,0.28426006,0.0062489253,0.005195977,0.0019318779],"about_ca_topic_score_codex":0.00010670826,"about_ca_topic_score_gemma":0.000018186352,"teacher_disagreement_score":0.31414646,"about_ca_system_score_codex":0.00024300457,"about_ca_system_score_gemma":0.00007686977,"threshold_uncertainty_score":0.9997925},"labels":[],"label_agreement":null},{"id":"W2995804543","doi":"10.1016/j.nicl.2019.102133","title":"Organization of the commissural fiber system in congenital and late-onset blindness","year":2019,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Western University","funders":"H. Lundbeck A/S; Natural Sciences and Engineering Research Council of Canada; Lundbeckfonden","keywords":"Corpus callosum; Tractography; Commissure; Anterior commissure; Posterior commissure; Diffusion MRI; Anatomy; Magnetic resonance imaging; Neuroscience; Optic chiasm; Psychology; Medicine; Radiology","score_opus":0.0692362285574352,"score_gpt":0.3780526058192199,"score_spread":0.3088163772617847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995804543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99748564,0.000011823919,0.000058944952,0.0009052031,0.000093464616,0.00050322723,0.0000116239435,0.00006682726,0.0008632404],"genre_scores_gemma":[0.9984351,0.0000138915175,0.0005214828,0.00034068036,0.000025557456,0.0000048759553,0.000007294721,0.000020873129,0.00063027296],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990868,0.00008142277,0.00039133584,0.00023500892,0.00010823427,0.000097219796],"domain_scores_gemma":[0.9990836,0.0002339906,0.00011143785,0.00043541542,0.00008744489,0.000048133028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017612372,0.000080236554,0.000238248,0.000031459043,0.000026030917,0.000008039304,0.00010529212,0.00006294525,0.00003501835],"category_scores_gemma":[0.00026685424,0.000058381032,0.000046807494,0.00026106078,0.00013909824,0.00004606626,0.000110519664,0.00029236998,0.00002510737],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029859384,0.00011949476,0.99694705,0.000060011065,0.000004096943,0.000009501117,0.000019202926,0.0000031531163,0.0016794918,0.00011244333,0.0002128409,0.0008028279],"study_design_scores_gemma":[0.00096648047,0.000103938786,0.994818,0.00007166964,0.000030202533,0.00010424226,0.000023356779,0.00084184494,0.0012294909,0.000029690418,0.00172028,0.00006080232],"about_ca_topic_score_codex":0.000006636091,"about_ca_topic_score_gemma":9.915789e-7,"teacher_disagreement_score":0.0021290758,"about_ca_system_score_codex":0.000010509664,"about_ca_system_score_gemma":0.00003395308,"threshold_uncertainty_score":0.23807094},"labels":[],"label_agreement":null},{"id":"W2995848445","doi":"10.1101/864108","title":"Diffusion Weighted Image Co-registration: Investigation of Best Practices","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Image registration; Diffusion MRI; Fractional anisotropy; Artificial intelligence; Scalar (mathematics); Computer science; Computer vision; Mathematics; Nuclear medicine; Image (mathematics); Pattern recognition (psychology); Medicine; Radiology; Magnetic resonance imaging; Geometry","score_opus":0.06417132458827192,"score_gpt":0.33094702908479406,"score_spread":0.26677570449652216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995848445","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9808706,0.00033262552,0.013686146,0.0021610076,0.00023963857,0.0018397059,0.0002017041,0.00052229146,0.00014626168],"genre_scores_gemma":[0.90055114,0.00049494166,0.098091274,0.00024721463,0.00027044723,0.00019897129,0.000005072088,0.00009910146,0.000041857802],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978581,0.00007055337,0.00061105745,0.00078388036,0.0004267648,0.00024965405],"domain_scores_gemma":[0.9956997,0.00009478643,0.0017657776,0.0015683243,0.00068816444,0.00018322298],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029074177,0.00037050463,0.0005350971,0.00022295315,0.0000956031,0.00006991345,0.0002891454,0.00034568945,0.000037563997],"category_scores_gemma":[0.00028265297,0.00037859136,0.0001279166,0.00037049325,0.00022008522,0.00022420318,0.00020072759,0.0007428244,0.00006103631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004855702,0.00017858371,0.028183918,0.0007972591,0.000042425876,0.000015013891,0.000005866077,0.0000023968846,0.96899915,0.0007895775,0.0009335306,0.0000037453758],"study_design_scores_gemma":[0.0008215087,0.00019654131,0.09470434,0.001285226,0.00037100294,1.4481668e-7,0.0000035331414,0.0018945151,0.8847062,0.00002967051,0.015434869,0.00055245135],"about_ca_topic_score_codex":0.00005728338,"about_ca_topic_score_gemma":5.348835e-7,"teacher_disagreement_score":0.084405124,"about_ca_system_score_codex":0.00010868062,"about_ca_system_score_gemma":0.0005764629,"threshold_uncertainty_score":0.9998666},"labels":[],"label_agreement":null},{"id":"W2995940953","doi":"10.3174/ajnr.a6357","title":"Diffusion Properties of Normal-Appearing White Matter Microstructure and Severity of Motor Impairment in Acute Ischemic Stroke","year":2019,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Movement Disorders","funders":"Agency for Healthcare Research and Quality; National Institutes of Health; Davee Foundation; Northwestern University","keywords":"Fractional anisotropy; Internal capsule; Medicine; Diffusion MRI; Splenium; White matter; Cingulum (brain); Corpus callosum; Stroke (engine); Cardiology; Fluid-attenuated inversion recovery; Internal medicine; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.011559684935330834,"score_gpt":0.2639780858234442,"score_spread":0.25241840088811335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995940953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99841136,0.00006565505,0.00011927899,0.0011496991,0.000026874322,0.00017398682,0.000008444309,0.0000048819466,0.000039821392],"genre_scores_gemma":[0.9957152,0.0001941405,0.003625118,0.0003821563,0.000015266492,0.0000019960237,6.744959e-7,0.000011522757,0.000053931282],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99929804,0.000037533337,0.00035474962,0.000118388016,0.000071325456,0.00011998931],"domain_scores_gemma":[0.99928766,0.000017956503,0.00042770724,0.00016069044,0.000058899244,0.00004710555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059191727,0.000089263194,0.0004434567,0.00012696032,0.000009395572,0.0000017423852,0.0000896038,0.000024369372,0.000010857986],"category_scores_gemma":[0.000008819945,0.00006685413,0.000057581816,0.000094325194,0.00022991622,0.000050627365,0.000061569575,0.00025447088,4.760452e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021958041,0.00002779309,0.45416552,0.000029825247,0.000010572401,0.000006530121,0.000089354806,0.0000049216533,0.5449305,0.0000011626953,0.000038755716,0.00047545315],"study_design_scores_gemma":[0.0006632128,0.0016637923,0.95364136,0.00011494528,0.00003858288,0.002113343,0.00011527998,0.000089001885,0.041157708,0.000012029157,0.0003278625,0.00006291751],"about_ca_topic_score_codex":0.000013377111,"about_ca_topic_score_gemma":2.7972717e-7,"teacher_disagreement_score":0.50377285,"about_ca_system_score_codex":0.000016715472,"about_ca_system_score_gemma":0.000026708383,"threshold_uncertainty_score":0.27262324},"labels":[],"label_agreement":null},{"id":"W2996631414","doi":"10.1159/000505077","title":"An Analysis of Clinical Outcome and Tractography following Bilateral Anterior Capsulotomy for Depression","year":2019,"lang":"en","type":"article","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"","keywords":"Internal capsule; Medicine; Neuropsychology; Beck Depression Inventory; Sham surgery; Depression (economics); Psychology; Internal medicine; Neuroscience; Psychiatry; Pathology; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.09817051744641327,"score_gpt":0.40837371373684556,"score_spread":0.3102031962904323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2996631414","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99373966,0.00005814526,0.005332232,0.00014490844,0.00023229897,0.0003658569,0.00002841784,0.000051465988,0.0000470127],"genre_scores_gemma":[0.9979635,0.000040574425,0.0012138386,0.00057360093,0.000048815567,0.00003121479,0.00003496505,0.000016928867,0.00007656762],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99881756,0.00003138227,0.00051390403,0.00038326814,0.00012707636,0.0001268247],"domain_scores_gemma":[0.9989829,0.0004182607,0.00018373635,0.0002489487,0.000048712398,0.00011742819],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023439125,0.00011682024,0.00051005563,0.00027038285,0.000059885988,0.000017679458,0.000025555799,0.000056114957,0.000018525525],"category_scores_gemma":[0.000061480074,0.000094728275,0.00033777033,0.00024220944,0.000053525255,0.00016420307,0.000020831589,0.00012738162,4.1913847e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041299086,0.000118324395,0.9870659,0.000038934268,0.0001439996,0.000004462487,0.000006588659,0.000003301033,0.009332404,0.000042326785,0.000015971784,0.0028147807],"study_design_scores_gemma":[0.00068656413,0.00023800124,0.9942171,0.00002865162,0.00067194283,0.00002853123,0.000012584491,0.0031818012,0.00011131625,0.000047854508,0.0006862459,0.00008938419],"about_ca_topic_score_codex":0.0000053733447,"about_ca_topic_score_gemma":3.8171584e-7,"teacher_disagreement_score":0.009221087,"about_ca_system_score_codex":0.0000032459116,"about_ca_system_score_gemma":0.000016034459,"threshold_uncertainty_score":0.38629067},"labels":[],"label_agreement":null},{"id":"W2998287850","doi":"10.1007/s00429-019-02002-8","title":"Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children","year":2020,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Children's Hospital; McGill University; Université de Sherbrooke; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Working memory; White matter; Concussion; Neuropathology; Tractography; Neuroscience; Prefrontal cortex; Fractional anisotropy; Diffusion MRI; Psychology; Dorsolateral prefrontal cortex; Medicine; Poison control; Pathology; Cognition; Magnetic resonance imaging; Radiology; Injury prevention","score_opus":0.01671676476347245,"score_gpt":0.24953331171933826,"score_spread":0.23281654695586582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998287850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99318933,0.00074696506,0.0023440802,0.002747456,0.00007322495,0.0006152961,0.000049689857,0.00015426025,0.000079708865],"genre_scores_gemma":[0.9967388,0.000047820296,0.0010102063,0.001482591,0.00022442934,0.000021460795,0.00041195264,0.000024927891,0.000037790767],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884415,0.00005770566,0.0002958439,0.00041118177,0.00016649856,0.00022459506],"domain_scores_gemma":[0.9995925,0.000040888666,0.00009969973,0.00015989029,0.000019760746,0.000087284985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007506773,0.00018919645,0.00025310714,0.00010634107,0.000100271056,0.000027252416,0.000061595536,0.00009184177,0.000028466413],"category_scores_gemma":[0.00005414019,0.00016790499,0.00003737053,0.00023830924,0.00009102213,0.00018711943,0.00004944813,0.00037972687,2.978377e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007575338,0.000024016545,0.8398553,0.00008262747,0.000016511707,0.000024854213,0.001060958,0.00013595192,0.12462948,0.00039841892,0.002523537,0.030490788],"study_design_scores_gemma":[0.0020113303,0.00012110392,0.98941463,0.00013018267,0.000031504987,0.000084391795,0.00021881121,0.003954004,0.0018406743,0.0015924054,0.00041816736,0.00018281944],"about_ca_topic_score_codex":0.00022174015,"about_ca_topic_score_gemma":0.000034517583,"teacher_disagreement_score":0.14955927,"about_ca_system_score_codex":0.00005668205,"about_ca_system_score_gemma":0.00001878721,"threshold_uncertainty_score":0.6846967},"labels":[],"label_agreement":null},{"id":"W2999007024","doi":"10.1088/1741-2552/ab6aad","title":"Common misconceptions, hidden biases and modern challenges of dMRI tractography","year":2020,"lang":"en","type":"review","venue":"Journal of Neural Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":123,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Computer science; Connectomics; Focus (optics); Connectome; Diffusion MRI; Data science; Field (mathematics); Artificial intelligence; Functional connectivity; Neuroscience; Psychology; Medicine; Mathematics; Magnetic resonance imaging; Physics","score_opus":0.20854267233809906,"score_gpt":0.3999560560535329,"score_spread":0.19141338371543384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999007024","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031027602,0.9979568,0.0008586184,0.0005416731,0.000042834672,0.00021178805,0.000014017435,0.00004322121,0.000020783424],"genre_scores_gemma":[0.0050792242,0.9889999,0.0056716013,0.000018000299,0.00017504997,0.000007951704,0.0000034752768,0.00004203305,0.0000027602787],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99902326,0.000015815867,0.00058502506,0.0001290062,0.00014397308,0.00010289795],"domain_scores_gemma":[0.99905795,0.00017377258,0.00043974296,0.00015454486,0.00004838383,0.00012561178],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052430678,0.0002042506,0.0011733315,0.00024182885,0.00001496205,0.000007647358,0.000117698684,0.00007689465,0.0000020508912],"category_scores_gemma":[0.00006578216,0.00015910967,0.00037088638,0.00015724746,0.000030199993,0.0000738344,0.00003338916,0.0005713631,2.0901848e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052190753,0.000033350272,0.0000037243306,0.00488162,0.00007653816,0.00007389547,0.000033634416,0.000045457145,0.00018862983,0.00010799179,0.000047113495,0.99450284],"study_design_scores_gemma":[0.0003722433,0.0005322111,0.00014294195,0.023733195,0.0014402268,0.004712671,0.000023622088,0.0023537397,0.00006130284,0.00013071697,0.9661923,0.00030483695],"about_ca_topic_score_codex":5.2784145e-7,"about_ca_topic_score_gemma":7.299539e-8,"teacher_disagreement_score":0.99419796,"about_ca_system_score_codex":0.000017450315,"about_ca_system_score_gemma":0.000029012615,"threshold_uncertainty_score":0.64883035},"labels":[],"label_agreement":null},{"id":"W2999285008","doi":"10.1016/j.neuroimage.2020.116533","title":"Diffusion time dependency along the human corpus callosum and exploration of age and sex differences as assessed by oscillating gradient spin-echo diffusion tensor imaging","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Corpus callosum; Diffusion MRI; Diffusion; Dependency (UML); Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Spin echo; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Computer science; Artificial intelligence; Mathematics; Quantum mechanics; Radiology; Geometry","score_opus":0.06032784273529428,"score_gpt":0.3258782284872872,"score_spread":0.2655503857519929,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999285008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99064946,0.0001692848,0.0035974083,0.00414803,0.000017611566,0.0006548982,0.000016090422,0.00018181722,0.00056537666],"genre_scores_gemma":[0.9973449,0.0002976319,0.0010897176,0.000957525,0.000049757356,0.000029424402,0.00003068904,0.000035850357,0.00016447571],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99863845,0.00006611952,0.0003364815,0.0004849272,0.00027557075,0.00019843041],"domain_scores_gemma":[0.99919975,0.00011191721,0.00020868964,0.00028678917,0.000049648035,0.00014321366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008659491,0.00020817656,0.00029770576,0.00005088767,0.0003126333,0.00006187162,0.00012020262,0.00003755433,0.000015161022],"category_scores_gemma":[0.00014861042,0.00015249115,0.00004603704,0.00016725663,0.00019853015,0.00020795461,0.00019848415,0.00028190433,0.000002256973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014483928,0.00007514766,0.07674207,0.00006205754,0.0000038918333,0.00005876177,0.00045017162,5.1297326e-7,0.9149665,0.00014359862,0.00022548091,0.0072572874],"study_design_scores_gemma":[0.0039359163,0.0016513594,0.84144765,0.0005260375,0.0003792157,0.0003808387,0.00096066267,0.045589115,0.09445582,0.0057662856,0.0039319745,0.00097513857],"about_ca_topic_score_codex":0.000095925025,"about_ca_topic_score_gemma":0.0000030749873,"teacher_disagreement_score":0.8205107,"about_ca_system_score_codex":0.000013000143,"about_ca_system_score_gemma":0.000013038023,"threshold_uncertainty_score":0.6218409},"labels":[],"label_agreement":null},{"id":"W2999340690","doi":"10.1101/2020.01.07.896951","title":"Age-related changes of Peak width Skeletonized Mean Diffusivity (PSMD) across the adult life span: a multi-cohort study","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; Fondation pour la Recherche Médicale; Bundesministerium für Bildung und Forschung; National Health and Medical Research Council; European Commission; Fondation Leducq; Agence Nationale de la Recherche; Canadian Institutes of Health Research; EU Joint Programme – Neurodegenerative Disease Research","keywords":"Life span; Cohort; Span (engineering); Thermal diffusivity; Cohort study; Longevity; Demography; Gerontology; Medicine; Statistics; Mathematics; Physics; Engineering; Structural engineering; Thermodynamics; Sociology","score_opus":0.04884314225868297,"score_gpt":0.31313215610129996,"score_spread":0.264289013842617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999340690","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9833653,0.0003211299,0.0039502704,0.0045769317,0.0002904514,0.005946587,0.0003269229,0.0012133467,0.000009069457],"genre_scores_gemma":[0.9856043,0.00037751804,0.011324639,0.0009062612,0.0002708087,0.0012787436,0.0000019216343,0.00022021671,0.000015605574],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9961536,0.00022382816,0.00086056767,0.0014740755,0.0006674646,0.00062044326],"domain_scores_gemma":[0.9950168,0.00012405627,0.0008993541,0.002722663,0.00079899846,0.00043810942],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006517143,0.0007405418,0.0013373586,0.00013476996,0.00028990494,0.00009398497,0.0008681903,0.0003794359,0.000019922702],"category_scores_gemma":[0.0008371778,0.0006107038,0.00029277586,0.0008523293,0.00041569734,0.000064804364,0.001205435,0.0016897277,0.000020088384],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037199032,0.0039519244,0.25716352,0.0012967112,0.0014181786,0.00040548676,0.00076974294,0.000029543009,0.7334109,0.000704306,0.0004482797,0.000029418832],"study_design_scores_gemma":[0.0029853112,0.00038173597,0.9414647,0.0005604578,0.00087568973,1.3136706e-7,0.000067847206,0.001542909,0.049854346,0.000009457898,0.0014126132,0.0008447646],"about_ca_topic_score_codex":0.00024738765,"about_ca_topic_score_gemma":0.00003203939,"teacher_disagreement_score":0.6843012,"about_ca_system_score_codex":0.00020692975,"about_ca_system_score_gemma":0.0004744002,"threshold_uncertainty_score":0.99963444},"labels":[],"label_agreement":null},{"id":"W2999483695","doi":"10.1101/2020.01.17.911032","title":"Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Health and Medical Research Council; Medical Research Council; National Institutes of Health; Ramsay Health Care; NSW Ministry of Health; Pratt Foundation; Australian Schizophrenia Research Bank; Sylvia and Charles Viertel Charitable Foundation","keywords":"White matter; Normative; Percentile; Schizophrenia (object-oriented programming); Cohort; Fractional anisotropy; Psychology; Magnetic resonance imaging; Medicine; Internal medicine; Psychiatry; Radiology; Statistics; Mathematics","score_opus":0.0449064795165414,"score_gpt":0.3063060764977635,"score_spread":0.26139959698122206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2999483695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93973154,0.00021343303,0.04933784,0.0006846973,0.00013736976,0.0013070822,0.008228891,0.00035011803,0.000009006327],"genre_scores_gemma":[0.9440182,0.000051683437,0.05478007,0.0005612854,0.00022247933,0.00025603597,0.000024786403,0.00008436698,0.0000011032752],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997492,0.0000732621,0.0007583802,0.000875327,0.0004779578,0.00032305656],"domain_scores_gemma":[0.9978727,0.0001107809,0.000518101,0.00087560597,0.00042314373,0.00019964752],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022417761,0.00040015473,0.0006519827,0.00029184856,0.00010535832,0.00007286021,0.0003996228,0.0004227251,0.00005705929],"category_scores_gemma":[0.00026980805,0.0004408665,0.0001502084,0.00062154955,0.000129278,0.00019168855,0.0005059009,0.001344305,0.0000069298794],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015609148,0.00029153598,0.7552838,0.00028931856,0.00027600874,0.00003282889,0.000048740174,0.0007268075,0.23298846,0.0095967995,0.00030808488,0.0000015624913],"study_design_scores_gemma":[0.0010267007,0.00003261632,0.9533207,0.00023721509,0.000096588206,3.9108514e-8,0.0000015545737,0.00466874,0.039209504,0.0007524568,0.0003057237,0.0003481683],"about_ca_topic_score_codex":0.00006655781,"about_ca_topic_score_gemma":0.000006516664,"teacher_disagreement_score":0.19803694,"about_ca_system_score_codex":0.00020139547,"about_ca_system_score_gemma":0.00062179426,"threshold_uncertainty_score":0.9998043},"labels":[],"label_agreement":null},{"id":"W3000068606","doi":"10.1101/2020.01.17.910851","title":"Elucidating the complex organization of neural micro-domains in the locust <i>Schistocerca gregaria</i> using dMRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Desert locust; Schistocerca; Kurtosis; Diffusion MRI; Fractional anisotropy; Locust; Neuroscience; Computer science; Magnetic resonance imaging; Diffusion imaging; Artificial intelligence; Biological system; Biology; Medicine; Mathematics; Ecology; Radiology","score_opus":0.06645331878895105,"score_gpt":0.29559273025199106,"score_spread":0.22913941146304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000068606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92699957,0.00027416885,0.060616687,0.0086199045,0.0001919608,0.0026815636,0.0001589348,0.0004331741,0.00002404546],"genre_scores_gemma":[0.9628337,0.00006126533,0.034826137,0.0018394298,0.0002545438,0.00006999555,0.0000021841984,0.00011206362,6.766269e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979683,0.00015161851,0.00061852153,0.00062429975,0.00033262774,0.00030463224],"domain_scores_gemma":[0.99756587,0.00011518512,0.0005628458,0.0013060983,0.0003637641,0.000086268585],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003637746,0.00035970978,0.00048614,0.00012548377,0.00022915554,0.00007564144,0.0006694297,0.00017347543,0.000014113812],"category_scores_gemma":[0.0003411676,0.00026931363,0.000106406056,0.0011797688,0.00022282773,0.00007268127,0.00043486935,0.0010283311,0.0000041605185],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015887172,0.00010740298,0.011364897,0.00024941904,0.000026755932,0.000026536507,0.000045654808,0.0001872754,0.9864235,0.001165394,0.00038439545,0.0000028849345],"study_design_scores_gemma":[0.001714078,0.00012970963,0.31920913,0.0011777707,0.0007402243,0.0000017913239,0.00006513039,0.021084346,0.6462352,0.00005129543,0.0084298495,0.0011614533],"about_ca_topic_score_codex":0.00008177685,"about_ca_topic_score_gemma":0.0000014749745,"teacher_disagreement_score":0.3401883,"about_ca_system_score_codex":0.00018172199,"about_ca_system_score_gemma":0.0002966691,"threshold_uncertainty_score":0.9999759},"labels":[],"label_agreement":null},{"id":"W3000134386","doi":"10.1002/hbm.24917","title":"Tractostorm: The what, why, and how of tractography dissection reproducibility","year":2020,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":98,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Tractography; Protocol (science); Diffusion MRI; Reproducibility; Standardization; Bundle; Computer science; Fractional anisotropy; Checklist; Segmentation; Medical physics; Data mining; Psychology; Artificial intelligence; Medicine; Radiology; Magnetic resonance imaging; Pathology; Cognitive psychology; Statistics; Mathematics","score_opus":0.22686246618368003,"score_gpt":0.4114473892578078,"score_spread":0.1845849230741278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000134386","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009590578,0.9850592,0.0024602134,0.0103063425,0.00005705366,0.0016801347,0.000010715061,0.00018330905,0.0001471378],"genre_scores_gemma":[0.0010252326,0.9973061,0.00066242,0.00041278996,0.00021568805,0.0001594492,0.00006253794,0.00004735196,0.00010840061],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99832726,0.00011953905,0.00036890508,0.00088465645,0.00015323315,0.00014643015],"domain_scores_gemma":[0.99793255,0.00023967768,0.0004174622,0.0012886142,0.000050039176,0.00007166893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060842116,0.00025466573,0.00090888987,0.00013422119,0.00019698695,0.0000647004,0.00015896598,0.00011040398,0.000008773922],"category_scores_gemma":[0.00032981584,0.00017645606,0.00034475743,0.00045627286,0.00020124791,0.0001479561,0.00007259513,0.00062136893,6.396616e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031752659,0.00006430353,0.000036880338,0.009934898,0.00007001187,0.0000074589993,0.00028500802,2.0939494e-8,0.00095604145,0.00066472986,0.00463312,0.9833444],"study_design_scores_gemma":[0.00007167472,0.000058527694,0.0009423632,0.0049511883,0.00027130745,0.00012221976,0.00012718057,0.0000020054322,0.0000065855575,0.00069215684,0.9926149,0.00013985962],"about_ca_topic_score_codex":0.0000046355444,"about_ca_topic_score_gemma":0.0000019658369,"teacher_disagreement_score":0.9879818,"about_ca_system_score_codex":0.0000301278,"about_ca_system_score_gemma":0.000036055328,"threshold_uncertainty_score":0.71956694},"labels":[],"label_agreement":null},{"id":"W3000146139","doi":"10.1016/j.pnpbp.2020.109871","title":"White matter microstructural organizations in patients with severe treatment-resistant schizophrenia: A diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"Progress in Neuro-Psychopharmacology and Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Douglas Mental Health University Institute; McGill University","funders":"Daiichi Sankyo Europe; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Novartis Pharma; National Institutes of Health; Japan Health Foundation; SENSHIN Medical Research Foundation; Mochida Memorial Foundation for Medical and Pharmaceutical Research; Ministero dello Sviluppo Economico; Meiji Seika Pharma; Shionogi; Eisai; Daiichi-Sankyo; Novartis; Ontario Mental Health Foundation; W. Garfield Weston Foundation; Otsuka Pharmaceutical; National Alliance for Research on Schizophrenia and Depression; Weston Brain Institute; Fujifilm Corporation; Michael J. Fox Foundation for Parkinson's Research; Takeda Science Foundation; Dainippon Sumitomo Pharma; Janssen Japan; Natural Sciences and Engineering Research Council of Canada; Pfizer; Japan Research Foundation for Clinical Pharmacology; Japan Agency for Medical Research and Development; Naito Foundation; McGill University; Consejo Nacional de Ciencia y Tecnología; Instituto de Ciencia y Tecnología del Distrito Federal; Uehara Memorial Foundation; Innovationsfonden; Tsumura and Company; Alzheimer's Association","keywords":"White matter; Uncinate fasciculus; Corpus callosum; Internal capsule; Fractional anisotropy; Fasciculus; Diffusion MRI; Superior longitudinal fasciculus; Medicine; Psychology; Positive and Negative Syndrome Scale; Cerebral peduncle; Corona radiata (embryology); Population; Internal medicine; Magnetic resonance imaging; Neuroscience; Psychiatry; Radiology; Psychosis","score_opus":0.01835313595439185,"score_gpt":0.31278221084865754,"score_spread":0.2944290748942657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000146139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9845658,0.00025367606,0.000016094622,0.013183832,0.00010583774,0.0016900186,0.000028557643,0.0001221989,0.000034016954],"genre_scores_gemma":[0.9912854,0.000056380362,0.0030254025,0.005329742,0.000072354,0.00016169265,0.000036488396,0.000025598067,0.0000069752905],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854076,0.00009420254,0.0003212187,0.0006740765,0.00008111916,0.00028865048],"domain_scores_gemma":[0.9995207,0.0000357875,0.00009803292,0.00015957074,0.000050888342,0.0001349815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029489343,0.00026115918,0.00033496082,0.000103416074,0.000113505295,0.000018291386,0.00011719722,0.00007487183,0.00009400189],"category_scores_gemma":[0.000011538794,0.00016759904,0.000030872612,0.00056528894,0.0002035455,0.000060435024,0.0000787504,0.0003655403,0.0000059739887],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004605743,0.0016312283,0.9919275,0.000018348894,0.000015079906,0.000043140546,0.00009289286,0.0000013926436,0.00008233241,0.000012504181,0.00023016997,0.0013396558],"study_design_scores_gemma":[0.011982046,0.001686413,0.98565274,0.000023462642,0.000048124206,0.0000279008,0.00005733142,0.000057642137,0.0000025366814,0.000091179056,0.00019027163,0.00018032208],"about_ca_topic_score_codex":0.0000015743537,"about_ca_topic_score_gemma":0.0000032889832,"teacher_disagreement_score":0.00785409,"about_ca_system_score_codex":0.000023941911,"about_ca_system_score_gemma":0.000025148045,"threshold_uncertainty_score":0.68344903},"labels":[],"label_agreement":null},{"id":"W3000797342","doi":"10.1016/j.jneumeth.2020.108593","title":"A framework for quality control of corpus callosum segmentation in large-scale studies","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Fundação de Amparo à Pesquisa do Estado de São Paulo; NYU Langone Medical Center","keywords":"Segmentation; Pattern recognition (psychology); Artificial intelligence; Computer science; Support vector machine; Ground truth; Classifier (UML); Metric (unit); Machine learning","score_opus":0.36441515726137436,"score_gpt":0.5804615676928803,"score_spread":0.2160464104315059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000797342","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06902089,0.00021813104,0.9215936,0.008722548,0.000118425785,0.00030008625,0.000009668051,0.0000114873665,0.000005170457],"genre_scores_gemma":[0.3034279,0.00015808374,0.69326186,0.00308286,0.000046446145,0.000011839848,1.2336076e-7,0.000005913086,0.000004973051],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988218,0.00017301297,0.00053620647,0.00014797627,0.00019560839,0.0001253854],"domain_scores_gemma":[0.9983445,0.00075812597,0.0004950269,0.00010962507,0.00020689139,0.0000858421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012126905,0.00006897794,0.00037941922,0.00007037183,0.000038084796,0.000005680227,0.00012443797,0.000025965668,9.191309e-7],"category_scores_gemma":[0.004419724,0.00005385523,0.00010251548,0.0003727629,0.000106526204,0.000095186886,0.000024991496,0.00022368543,5.820187e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024144934,0.0001452865,0.00996591,0.000092158916,0.0000044868852,0.000007209297,0.00053066976,0.00011047478,0.97872305,0.0016121718,0.000048584145,0.008518545],"study_design_scores_gemma":[0.008627434,0.0061334507,0.19452773,0.0006560538,0.0003250281,0.00026250415,0.0024560106,0.033384982,0.65673053,0.080930226,0.015540258,0.00042581095],"about_ca_topic_score_codex":5.0427235e-7,"about_ca_topic_score_gemma":1.9087776e-7,"teacher_disagreement_score":0.32199255,"about_ca_system_score_codex":0.000025657762,"about_ca_system_score_gemma":0.000051346855,"threshold_uncertainty_score":0.5291142},"labels":[],"label_agreement":null},{"id":"W3002121850","doi":"10.1016/j.neuroimage.2020.116552","title":"Early childhood development of white matter fiber density and morphology","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Institute of Neurosciences, Mental Health and Addiction; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Alberta Heritage Foundation for Medical Research; Hotchkiss Brain Institute","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Corpus callosum; Corticospinal tract; Brain development; Tractography; Fiber bundle; Anatomy; Fiber; Biology; Neuroscience; Psychology; Chemistry; Medicine; Magnetic resonance imaging","score_opus":0.0390138754629844,"score_gpt":0.2901391307683762,"score_spread":0.2511252553053918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002121850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894632,0.000013491577,0.0032961655,0.0056460346,0.000007106888,0.0002175661,0.0000039108368,0.00008743978,0.0012651039],"genre_scores_gemma":[0.9430581,0.0000057009365,0.05186142,0.0048119733,0.00002300041,0.000009948226,0.000005046691,0.000019345598,0.00020546859],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993939,0.000011006506,0.00016224645,0.00024595615,0.00007665514,0.00011026503],"domain_scores_gemma":[0.99963,0.000013655629,0.00005227411,0.00017978747,0.000031289408,0.00009300842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000021903148,0.0000871117,0.00016319162,0.000026395492,0.000059522208,0.0000039977504,0.000052408384,0.000025830313,0.00011618399],"category_scores_gemma":[0.000017662544,0.00008173921,0.000025405674,0.000087495006,0.000063482454,0.00003572679,0.00013195364,0.00014549943,0.00006585014],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012331184,0.0003136579,0.44878748,0.00017977742,0.000031336254,0.0001834931,0.0037893027,0.0000017999633,0.52151996,0.00014106453,0.010054,0.014874837],"study_design_scores_gemma":[0.00030607675,0.00007381066,0.9544171,0.000009832836,0.000017760825,0.00008376144,0.0000050693,0.000011400326,0.03717761,0.000055401335,0.0077758157,0.00006632519],"about_ca_topic_score_codex":8.8499326e-7,"about_ca_topic_score_gemma":6.383543e-8,"teacher_disagreement_score":0.50562966,"about_ca_system_score_codex":0.0000041642465,"about_ca_system_score_gemma":0.000019886498,"threshold_uncertainty_score":0.3333228},"labels":[],"label_agreement":null},{"id":"W3002904902","doi":"10.1038/s41598-020-58128-x","title":"Predicting change trajectories of neuroticism from baseline brain structure using whole brain analyses and latent growth curve models in adolescents","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Jacobs Foundation; Deutsche Forschungsgemeinschaft; European Commission","keywords":"Neuroticism; Psychopathology; Structural equation modeling; Psychology; Personality; Growth curve (statistics); Latent growth modeling; Voxel; Neuroimaging; Developmental psychology; Clinical psychology; Neuroscience; Statistics; Social psychology; Artificial intelligence; Computer science; Mathematics","score_opus":0.1774518183243011,"score_gpt":0.36909903682310813,"score_spread":0.19164721849880703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3002904902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841836,0.0001899467,0.011602391,0.0031511646,0.00019180079,0.00054060324,0.000053330747,0.00008114345,0.0000060372513],"genre_scores_gemma":[0.9938545,0.0000031849788,0.005388815,0.0005481813,0.000089362504,0.000008736542,0.00007460757,0.000020284371,0.0000122821475],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99837166,0.000047715075,0.00047085984,0.00063398335,0.00029769205,0.00017810865],"domain_scores_gemma":[0.9990902,0.0000385381,0.00026495315,0.0003493058,0.0001257327,0.00013126955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002564629,0.0001357864,0.00029589437,0.0001283661,0.000083056206,0.00004036084,0.00006307839,0.0000454313,0.000005340031],"category_scores_gemma":[0.00043901303,0.00012231512,0.00004986325,0.0005916133,0.00014578277,0.00021582162,0.00008642086,0.00018178069,1.0957586e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002578911,0.00006848498,0.31830347,0.00014940997,0.0000096932245,0.0002025337,0.0011143642,0.0006665611,0.6784984,0.000021430473,0.0003512284,0.0005886577],"study_design_scores_gemma":[0.001171121,0.00017950183,0.1825472,0.0016365423,0.00022230567,0.00028694354,0.00032186546,0.54548746,0.24123417,0.025891962,0.00049309107,0.00052786863],"about_ca_topic_score_codex":0.00023182046,"about_ca_topic_score_gemma":0.000025440853,"teacher_disagreement_score":0.5448209,"about_ca_system_score_codex":0.000019831694,"about_ca_system_score_gemma":0.00004510164,"threshold_uncertainty_score":0.4987866},"labels":[],"label_agreement":null},{"id":"W3003448798","doi":"10.1016/j.bpsc.2020.01.004","title":"Fully Automated Habenula Segmentation Provides Robust and Reliable Volume Estimation Across Large Magnetic Resonance Imaging Datasets, Suggesting Intriguing Developmental Trajectories in Psychiatric Disease","year":2020,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; McGill University; Douglas Mental Health University Institute; University Health Network","funders":"General Armaments Department, People's Liberation Army; Fundação de Amparo à Pesquisa do Estado de São Paulo; National Alliance for Research on Schizophrenia and Depression; Wellcome Trust; Fondation Brain Canada; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Compute Canada; Health Canada; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); Segmentation; Bipolar disorder; Magnetic resonance imaging; Habenula; Reliability (semiconductor); Neuroimaging; Computer science; Artificial intelligence; Neuroscience; Psychology; Medicine; Psychiatry; Radiology; Cognition; Physics","score_opus":0.055396165592117824,"score_gpt":0.34116374613976697,"score_spread":0.28576758054764917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003448798","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97703743,0.002122292,0.010653137,0.007996318,0.00013584943,0.0010694053,0.00031397646,0.0006419358,0.000029654995],"genre_scores_gemma":[0.97098476,0.00035657553,0.020413391,0.0079331845,0.0000623472,0.00007591308,0.00014279378,0.000025448986,0.0000055718615],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976256,0.0000818881,0.00043057642,0.0010872792,0.00020900398,0.00056564057],"domain_scores_gemma":[0.9992731,0.00010172145,0.00014669955,0.00012261608,0.00006934358,0.0002865141],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023242178,0.00028629415,0.00026401968,0.00010616603,0.00056381844,0.00016048494,0.00013141127,0.000038059494,0.000004405685],"category_scores_gemma":[0.0009817289,0.00026062512,0.000034874225,0.0008461846,0.00037493487,0.0005144825,0.00023449332,0.00037036298,0.0000026519585],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020919273,0.00014508281,0.9710019,0.0000999772,6.583819e-7,0.00007012693,0.00014362615,0.00002684737,0.00884315,0.00006849307,0.00029253497,0.019098362],"study_design_scores_gemma":[0.0011373793,0.00023116356,0.8344232,0.0001737678,0.000024487425,0.00012679462,0.00041785298,0.1623048,0.00014003148,0.00019952368,0.00054314354,0.00027786105],"about_ca_topic_score_codex":0.000010883155,"about_ca_topic_score_gemma":0.0000021199128,"teacher_disagreement_score":0.16227795,"about_ca_system_score_codex":0.000026972128,"about_ca_system_score_gemma":0.00010718464,"threshold_uncertainty_score":0.9999846},"labels":[],"label_agreement":null},{"id":"W3003557145","doi":"10.1016/j.ymgme.2019.11.297","title":"Intraspinal space restriction at the occipito-cervical junction alters cervical spinal cord diffusion MRI metrics in mucopolysacharidoses patients","year":2020,"lang":"en","type":"article","venue":"Molecular Genetics and Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Normalization (sociology); Generalization; Artificial neural network; Computer science; Context (archaeology); Artificial intelligence; Diffusion MRI; Inductive bias; Space (punctuation); Machine learning; Neuroscience; Task (project management); Psychology; Biology; Mathematics; Magnetic resonance imaging; Medicine","score_opus":0.033533848730522314,"score_gpt":0.30845885781807564,"score_spread":0.27492500908755335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003557145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9383534,0.0020966262,0.0494342,0.009322054,0.00013161958,0.0005305828,0.0000077074765,0.000056605943,0.00006719659],"genre_scores_gemma":[0.988631,0.0033542686,0.0050928476,0.0026795142,0.00012557938,0.000039341336,0.00003501795,0.000028327853,0.000014111456],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99873155,0.00005558986,0.00025721788,0.00040091207,0.0003114672,0.00024325225],"domain_scores_gemma":[0.9993633,0.000017526156,0.000087352346,0.0002577893,0.00007815906,0.00019587182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075492906,0.00017335005,0.00022151017,0.00010815311,0.00013326264,0.00002598294,0.00009980986,0.00008210319,0.000011835803],"category_scores_gemma":[0.00007491851,0.00013520254,0.00007012099,0.00058209006,0.000084376945,0.000027751417,0.00020553816,0.00028933992,0.000005390834],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036813794,0.001437419,0.14482,0.00028890473,0.000122025755,0.00016797651,0.00040425098,0.00037550367,0.5679575,0.014984901,0.0030277742,0.26273236],"study_design_scores_gemma":[0.002403013,0.0011659714,0.8249577,0.000039659484,0.00032245897,0.000032743956,0.00005319,0.0076537323,0.04059832,0.0010882634,0.12134432,0.00034056435],"about_ca_topic_score_codex":0.00004204317,"about_ca_topic_score_gemma":0.0000034511202,"teacher_disagreement_score":0.68013775,"about_ca_system_score_codex":0.00003961912,"about_ca_system_score_gemma":0.000023966371,"threshold_uncertainty_score":0.55134},"labels":[],"label_agreement":null},{"id":"W3003644065","doi":"10.3390/app10030934","title":"Machine Learning and DWI Brain Communicability Networks for Alzheimer’s Disease Detection","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Servier; University of Southern California; Eli Lilly and Company; Genentech; IXICO","keywords":"Computer science; Artificial intelligence; Machine learning; Brain disease; Feature (linguistics); Pattern recognition (psychology); Disease; Medicine; Pathology","score_opus":0.11891175296995896,"score_gpt":0.3755350759972443,"score_spread":0.2566233230272853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003644065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.096855015,0.0026648983,0.8154617,0.07779521,0.00004177324,0.0030217273,0.000016903683,0.0010514403,0.0030913327],"genre_scores_gemma":[0.9843688,0.000068876514,0.013053599,0.0023248377,0.000045660254,0.00011490973,0.000007782127,0.0000073164288,0.000008237169],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994118,0.000014457611,0.00010285466,0.00026168744,0.00008183248,0.00012734233],"domain_scores_gemma":[0.99948716,0.00019343261,0.000044368095,0.00011526533,0.000015660236,0.00014412627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020477912,0.000069884554,0.000104421466,0.000016753187,0.00038209185,0.000021961481,0.00009311508,0.000018369512,0.000004519982],"category_scores_gemma":[0.00009929903,0.000058857917,0.000026039193,0.00020003176,0.0002940074,0.000038080143,0.000073038245,0.00014747013,8.612123e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011654982,0.00033189275,0.06821449,0.00019208681,0.000056390098,0.0000040150103,0.00069897284,0.0048120986,0.09519912,0.05899499,0.0015759348,0.7687545],"study_design_scores_gemma":[0.0010162115,0.0005727051,0.0128426645,0.000022758499,0.00015169584,0.00000816854,0.00018757966,0.8484577,0.005739991,0.012285922,0.1183972,0.00031738897],"about_ca_topic_score_codex":0.000004602627,"about_ca_topic_score_gemma":0.000001898487,"teacher_disagreement_score":0.88751376,"about_ca_system_score_codex":0.000005450795,"about_ca_system_score_gemma":0.00001565841,"threshold_uncertainty_score":0.29387802},"labels":[],"label_agreement":null},{"id":"W3003733514","doi":"10.1038/s41598-020-58291-1","title":"Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Alzheimer's Disease Neuroimaging Initiative; Organization for Women in Science for the Developing World; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; University of Southern California; F. Hoffmann-La Roche; Styrelsen för Internationellt Utvecklingssamarbete; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; University of Cape Town; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Genome-wide association study; Neuroimaging; Disease; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Genetic association; Single-nucleotide polymorphism; Imaging genetics; Neuroscience; Computational biology; Biology; Bioinformatics; Medicine; Genetics; Gene; Genotype; Pathology","score_opus":0.11546791995508524,"score_gpt":0.3674257070247437,"score_spread":0.25195778706965843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003733514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9683277,0.000077355246,0.004462091,0.024379645,0.00027020177,0.0022120024,0.000014394836,0.00015763765,0.00009896385],"genre_scores_gemma":[0.9978947,0.0000013804735,0.0008381549,0.00061976357,0.00005767411,0.00018885771,0.000050611077,0.000012923519,0.00033595352],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989085,0.00001943757,0.00022457707,0.0004539512,0.0002637748,0.00012976851],"domain_scores_gemma":[0.9987932,0.00014501008,0.00031377657,0.00040681954,0.00019670202,0.00014450322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004766327,0.00007146907,0.0001731041,0.0000485565,0.000120759665,0.000022596556,0.00004799749,0.000018307474,0.000012475405],"category_scores_gemma":[0.0015849512,0.000067131194,0.000054632415,0.00027399953,0.00003717707,0.000045532626,0.000040846167,0.000055835542,0.0000012728104],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012617797,0.0013203387,0.8688655,0.00011930041,0.00010578008,0.00013886177,0.0015590528,0.000054644315,0.073681414,0.00007887849,0.051800266,0.0021498061],"study_design_scores_gemma":[0.0012907604,0.0010025529,0.62327325,0.00004566048,0.00073791575,0.000011671935,0.0005092288,0.0007965939,0.037140492,0.009948667,0.32488108,0.0003621319],"about_ca_topic_score_codex":0.000003882664,"about_ca_topic_score_gemma":0.0000050895214,"teacher_disagreement_score":0.2730808,"about_ca_system_score_codex":0.000031897413,"about_ca_system_score_gemma":0.00006242122,"threshold_uncertainty_score":0.27375308},"labels":[],"label_agreement":null},{"id":"W3005461968","doi":"10.1101/2020.02.05.934430","title":"Myelin water fraction decrease in mild traumatic brain injury","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Mitacs","keywords":"Splenium; Corpus callosum; White matter; Traumatic brain injury; Myelin; Corticospinal tract; Medicine; Superior longitudinal fasciculus; Cognition; Psychology; Fasciculus; Neuroscience; Internal medicine; Diffusion MRI; Audiology; Anesthesia; Cardiology; Magnetic resonance imaging; Pathology; Central nervous system; Psychiatry; Radiology","score_opus":0.06387169348619276,"score_gpt":0.3208510489758709,"score_spread":0.25697935548967815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005461968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9648482,0.00021561242,0.016841028,0.01459057,0.00021943757,0.0019680036,0.00011831005,0.0011795348,0.000019256604],"genre_scores_gemma":[0.9642604,0.0001759168,0.031117449,0.0033570125,0.00032802252,0.00059812784,0.00000232626,0.00015507647,0.0000056964104],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975728,0.00008477075,0.0006268683,0.0009722178,0.0002966024,0.0004467328],"domain_scores_gemma":[0.9979567,0.000059089587,0.00020480988,0.0011821832,0.00016689289,0.00043035834],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003058481,0.00045896877,0.0006450344,0.00031944134,0.00008173344,0.000065159074,0.00028445682,0.000365041,0.00008636023],"category_scores_gemma":[0.0003562085,0.00043112703,0.00015974147,0.00039357552,0.00008062475,0.00011470187,0.00029238185,0.0013600702,0.000117769625],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012622557,0.00033253417,0.004545415,0.00060527987,0.000046075893,0.00012718097,0.000016249582,0.000014409009,0.9916536,0.00032275796,0.0021913978,0.000018846904],"study_design_scores_gemma":[0.0012221574,0.00015846796,0.11536272,0.0015247711,0.00022621799,1.1667799e-7,0.000005235722,0.0027084656,0.843636,0.00014673699,0.03393928,0.0010698796],"about_ca_topic_score_codex":0.000060824805,"about_ca_topic_score_gemma":0.0000012355816,"teacher_disagreement_score":0.14801767,"about_ca_system_score_codex":0.00030988004,"about_ca_system_score_gemma":0.00029379816,"threshold_uncertainty_score":0.99981403},"labels":[],"label_agreement":null},{"id":"W3005837005","doi":"10.1002/jmri.27092","title":"Improving Spatial Normalization of Brain Diffusion MRI to Measure Longitudinal Changes of Tissue Microstructure in the Cortex and White Matter","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Agencia Nacional de Promoción Científica y Tecnológica; Ministry of Defense; Fondo para la Investigación Científica y Tecnológica; Universidad de Buenos Aires; Réseau en Bio-Imagerie du Quebec","keywords":"Reproducibility; White matter; Diffusion MRI; Fractional anisotropy; Spatial normalization; Normalization (sociology); Diffusion imaging; Medicine; Nuclear medicine; Computer science; Artificial intelligence; Mathematics; Magnetic resonance imaging; Radiology; Statistics","score_opus":0.02012599535054777,"score_gpt":0.2876542271717417,"score_spread":0.26752823182119395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005837005","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82757235,0.0039630034,0.079644136,0.088052034,0.0000417325,0.0006230084,0.000014635318,0.000009933143,0.00007915669],"genre_scores_gemma":[0.98549896,0.00011105152,0.012098421,0.0021640437,0.00009480099,0.0000036688984,0.000001244293,0.000012478527,0.000015301992],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991513,0.000034676807,0.00034272252,0.00012786672,0.00023498376,0.00010845233],"domain_scores_gemma":[0.9993418,0.000040634255,0.00028819207,0.00012702125,0.0001496039,0.000052788262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018125313,0.00009126622,0.00023154602,0.00009075763,0.000026233189,0.000012627418,0.00012070862,0.000020889895,0.000026652267],"category_scores_gemma":[0.00009967726,0.00006560469,0.000028678889,0.00022095644,0.00006189733,0.000063268795,0.000050064726,0.00018706707,2.2811457e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017679324,0.000031559764,0.40316287,0.00014865505,0.0000014128709,0.00003335235,0.0014485798,0.000014097311,0.48641574,0.0000099447525,0.0012042888,0.107352704],"study_design_scores_gemma":[0.00070868613,0.00039339624,0.982685,0.0003444823,0.000034516608,0.00038016288,0.000189241,0.0015267463,0.008968338,0.00005352702,0.0046457183,0.000070128044],"about_ca_topic_score_codex":0.00003441573,"about_ca_topic_score_gemma":0.000012402176,"teacher_disagreement_score":0.5795222,"about_ca_system_score_codex":0.000011816322,"about_ca_system_score_gemma":0.000023013677,"threshold_uncertainty_score":0.26752818},"labels":[],"label_agreement":null},{"id":"W3006287032","doi":"10.1002/nbm.4270","title":"Rapid acquisition diffusion MR spectroscopy of metabolites in human brain","year":2020,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Diffusion; Data acquisition; White matter; Nuclear magnetic resonance; Diffusion imaging; Spectroscopy; Computer science; Physics; Biological system; Magnetic resonance imaging; Medicine; Biology","score_opus":0.0527022688788116,"score_gpt":0.3695152712650518,"score_spread":0.3168130023862402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006287032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94738126,0.00072711625,0.0030193033,0.04710518,0.000019739717,0.0005629965,0.000012835577,0.00011302399,0.0010585459],"genre_scores_gemma":[0.987709,0.00026227615,0.0073785814,0.004329265,0.0001505711,0.000029082461,0.000089885536,0.000017583607,0.00003378796],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989898,0.000025428742,0.0003777875,0.0002573697,0.00018367701,0.00016592054],"domain_scores_gemma":[0.9994959,0.00005137034,0.000090127956,0.00022130055,0.00002978971,0.00011146245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014540394,0.00011226081,0.0003466364,0.00025618298,0.000019127647,0.0000021130088,0.000090430454,0.000050398885,0.00017980594],"category_scores_gemma":[0.000106033425,0.000095154806,0.000038397528,0.0008152275,0.00012478058,0.000041030886,0.000044305336,0.00018793636,0.000003382352],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006316766,0.00016247483,0.013321933,0.00008087216,0.000002826757,0.000018997005,0.00021253602,6.545313e-7,0.9820121,0.00084188755,0.0014349783,0.0018475977],"study_design_scores_gemma":[0.005641888,0.0014813858,0.24409954,0.0005861862,0.00005026769,0.000024294026,0.00021859634,0.0011265805,0.7097683,0.004369887,0.032400932,0.0002321653],"about_ca_topic_score_codex":0.000042476833,"about_ca_topic_score_gemma":0.0000022014426,"teacher_disagreement_score":0.2722438,"about_ca_system_score_codex":0.000039232706,"about_ca_system_score_gemma":0.000021434518,"threshold_uncertainty_score":0.38803002},"labels":[],"label_agreement":null},{"id":"W3006318419","doi":"10.1101/2020.02.14.949826","title":"Network efficiency predicts resilience to cognitive decline in elderly at risk for Alzheimer’s","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Servier; Eisai; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cognitive decline; White matter; Hyperintensity; Dementia; Cognition; Effects of sleep deprivation on cognitive performance; Neuropsychology; Psychology; Psychological resilience; Internal medicine; Cognitive reserve; Medicine; Gerontology; Cardiology; Neuroscience; Cognitive impairment; Magnetic resonance imaging; Disease; Radiology","score_opus":0.05382894729616882,"score_gpt":0.3177781001630959,"score_spread":0.26394915286692705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006318419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7147054,0.0020414495,0.26773518,0.004966669,0.00041197674,0.007884231,0.0010322975,0.0011980045,0.000024800738],"genre_scores_gemma":[0.9128586,0.00032452933,0.082026035,0.002290111,0.0005320043,0.001821508,0.0000021417834,0.00014042815,0.0000046367404],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99676394,0.00007271231,0.0006565363,0.0014790512,0.00035145678,0.00067631353],"domain_scores_gemma":[0.99738634,0.0002928486,0.0004013273,0.0009923894,0.00044752413,0.00047958168],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045409254,0.000498508,0.0007012535,0.0001898629,0.00020541501,0.00005091032,0.00045848044,0.0003102263,0.000012192862],"category_scores_gemma":[0.0011154887,0.00053936214,0.0001520249,0.00091083854,0.00012938598,0.000058366073,0.0008808671,0.00088535395,0.00004582535],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005572325,0.002635891,0.42167813,0.0023923966,0.000770662,0.0006974761,0.00016942126,0.007445303,0.5267724,0.003559998,0.027872559,0.0004334365],"study_design_scores_gemma":[0.0052848193,0.0023519557,0.68531704,0.0049073203,0.0018602252,2.6164045e-7,0.000008021564,0.014918816,0.22909607,0.00030850194,0.05330133,0.0026456707],"about_ca_topic_score_codex":0.000031146246,"about_ca_topic_score_gemma":0.00000698829,"teacher_disagreement_score":0.29767632,"about_ca_system_score_codex":0.0002056072,"about_ca_system_score_gemma":0.00040895148,"threshold_uncertainty_score":0.9997058},"labels":[],"label_agreement":null},{"id":"W3006482384","doi":"10.1111/jon.12689","title":"Brain Myelin Water Fraction and Diffusion Tensor Imaging Atlases for 9‐10 Year‐Old Children","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Heritage Foundation for Medical Research; Canadian Language and Literacy Research Network","keywords":"Medicine; Diffusion MRI; White matter; Fractional anisotropy; Corpus callosum; Neuroimaging; Magnetic resonance imaging; Nuclear medicine; Radiology; Pathology; Psychiatry","score_opus":0.045986652713089805,"score_gpt":0.33084603988391603,"score_spread":0.2848593871708262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006482384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8533232,0.00012059286,0.037047468,0.108902514,0.000049048806,0.00037774374,0.000008605359,0.00009459302,0.00007619627],"genre_scores_gemma":[0.97195995,0.000118024334,0.017152146,0.009921223,0.00064094434,0.0000064732826,0.00001083372,0.0000511628,0.0001392588],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99906904,0.000021492735,0.0003389219,0.00021761736,0.00016567895,0.00018726585],"domain_scores_gemma":[0.99927783,0.00010343042,0.00018168404,0.00012731005,0.00014455026,0.00016520078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012161427,0.00012995598,0.00025001992,0.00010355909,0.000110240944,0.00004760955,0.000081607184,0.000019781372,0.000026754502],"category_scores_gemma":[0.00027471024,0.00009562371,0.00011179042,0.00008005167,0.000047443657,0.00023578297,0.00005867091,0.0003043236,0.0000048482248],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000512776,0.00013062355,0.16836078,0.00008677777,0.000028750477,0.000102834,0.00019419556,0.000026536027,0.7772369,0.000069428395,0.026524685,0.026725741],"study_design_scores_gemma":[0.01073805,0.0016443545,0.52070713,0.0006144347,0.0007002084,0.007445508,0.00031080827,0.030226381,0.097022876,0.0031342052,0.3265854,0.0008706147],"about_ca_topic_score_codex":0.000002360226,"about_ca_topic_score_gemma":4.024136e-8,"teacher_disagreement_score":0.680214,"about_ca_system_score_codex":0.000020040503,"about_ca_system_score_gemma":0.000015884689,"threshold_uncertainty_score":0.38994217},"labels":[],"label_agreement":null},{"id":"W3006508673","doi":"","title":"PAM50 : multimodal template of the brainstem and spinal cord compatible with the ICBM152 space","year":2017,"lang":"en","type":"preprint","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"","keywords":"Spinal cord; Brainstem; Computer science; Template; Artificial intelligence; Medicine; Pattern recognition (psychology)","score_opus":0.041770262395684946,"score_gpt":0.31750391863496125,"score_spread":0.2757336562392763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006508673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55367327,0.0016710284,0.34277198,0.09336035,0.00012297153,0.005922257,0.00024466074,0.0008532045,0.0013802656],"genre_scores_gemma":[0.9269018,0.00033032295,0.069604404,0.0013210574,0.00010322854,0.0007812391,0.000019932002,0.000096718075,0.00084127294],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978743,0.00010155191,0.00043881664,0.0006643845,0.0004477949,0.00047315104],"domain_scores_gemma":[0.99564403,0.000097970624,0.00090903346,0.0029423193,0.00020862426,0.0001980192],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004146501,0.00049652276,0.0006997454,0.0001583045,0.0005819563,0.00013460395,0.0009538887,0.00030479467,0.0000047005256],"category_scores_gemma":[0.00011445933,0.0002964361,0.0002236264,0.00019901608,0.000642998,0.0000940494,0.0012718916,0.0015244127,0.0000013141312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008855189,0.0023528952,0.6040027,0.004289413,0.0012767982,0.00043188522,0.0014604433,0.0047929967,0.07674296,0.07572273,0.038688242,0.18138376],"study_design_scores_gemma":[0.0026225245,0.0018595732,0.84506667,0.0039201495,0.00089891686,0.0016746463,0.00030704145,0.054303516,0.04829486,0.009701403,0.029905714,0.0014450034],"about_ca_topic_score_codex":0.0046195965,"about_ca_topic_score_gemma":0.00084585155,"teacher_disagreement_score":0.37322855,"about_ca_system_score_codex":0.00016845268,"about_ca_system_score_gemma":0.0003868466,"threshold_uncertainty_score":0.9999488},"labels":[],"label_agreement":null},{"id":"W3007025644","doi":"10.1109/embc44109.2020.9176229","title":"Rapid Quantification of White Matter Disconnection in the Human Brain","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"Max-Planck-Institut für Kognitions- und Neurowissenschaften","keywords":"Disconnection; White matter; Diffusion MRI; Hyperintensity; Tractography; Neuroscience; Population; Cognition; Psychology; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.14886587824039635,"score_gpt":0.3980968119004431,"score_spread":0.24923093366004676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007025644","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19876242,0.00007921728,0.349191,0.42388323,0.00008611939,0.0031144326,0.00003823338,0.00031436418,0.024530966],"genre_scores_gemma":[0.9902709,0.000026360902,0.005819123,0.0029967043,0.000061480794,0.00019408266,0.00019119887,0.000017640106,0.00042250793],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999182,0.000046215766,0.0002905009,0.00029264856,0.00011541122,0.000073221665],"domain_scores_gemma":[0.99915975,0.00004437025,0.0001464595,0.0005976898,0.0000325595,0.000019192357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014974453,0.00010557837,0.00019139519,0.00007801957,0.000046647383,0.000009853268,0.00015914746,0.00006750483,0.00013298682],"category_scores_gemma":[0.000024868674,0.000073831565,0.000075216005,0.00014094419,0.000048122387,0.000021965652,0.00014187653,0.00040780727,0.000011498527],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012345158,0.0013782728,0.19265696,0.002317486,0.00007931064,0.000019396235,0.00567332,0.0002627948,0.477909,0.113809176,0.197947,0.0078238435],"study_design_scores_gemma":[0.0006565625,0.00017049721,0.87101316,0.00048254826,0.00012784032,0.000037053218,0.0005770072,0.0016262521,0.026609503,0.06604814,0.03226765,0.00038376983],"about_ca_topic_score_codex":0.000045870263,"about_ca_topic_score_gemma":0.000007471481,"teacher_disagreement_score":0.7915085,"about_ca_system_score_codex":0.000018717501,"about_ca_system_score_gemma":0.000017066412,"threshold_uncertainty_score":0.30107638},"labels":[],"label_agreement":null},{"id":"W3007327257","doi":"10.3389/fninf.2020.00007","title":"A Standardized Protocol for Efficient and Reliable Quality Control of Brain Registration in Functional MRI Studies","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Jewish General Hospital; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Protocol (science); Reliability (semiconductor); Computer science; Consistency (knowledge bases); Kappa; Quality (philosophy); Medical physics; Inter-rater reliability; Artificial intelligence; Data mining; Medicine; Statistics; Rating scale; Pathology; Mathematics","score_opus":0.11857537595006894,"score_gpt":0.4060679210469642,"score_spread":0.28749254509689526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007327257","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074293986,0.000024357762,0.92130524,0.008574052,0.000038020975,0.06234435,0.000043315504,0.000058349644,0.00018291768],"genre_scores_gemma":[0.16442837,0.000074522744,0.7040195,0.006011723,0.00008668884,0.12519155,0.000040390565,0.000050609895,0.000096660726],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990369,0.00001878184,0.00055642624,0.00012165024,0.00015385891,0.00011234657],"domain_scores_gemma":[0.99940515,0.00012466122,0.00020410467,0.00013356564,0.000089060406,0.000043444426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002937987,0.00008658068,0.0003144899,0.0000710708,0.00002951478,0.0000065703507,0.00003540741,0.000028830606,6.505342e-7],"category_scores_gemma":[0.0007171471,0.00007781603,0.000036142024,0.00017764895,0.000082518076,0.00006970021,0.000019619974,0.00012062894,1.0455701e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.030571662,0.0016025377,0.2577671,0.022571137,0.0002353891,0.000029084205,0.0113952495,0.06884821,0.008277009,0.03361042,0.54835546,0.016736744],"study_design_scores_gemma":[0.024663543,0.0013217558,0.013649663,0.0004874631,0.00004751058,0.0000115972325,0.0018572005,0.87519115,0.002787545,0.0064409007,0.07323801,0.00030367755],"about_ca_topic_score_codex":0.000001116154,"about_ca_topic_score_gemma":5.539786e-7,"teacher_disagreement_score":0.80634296,"about_ca_system_score_codex":0.000040508014,"about_ca_system_score_gemma":0.000059320402,"threshold_uncertainty_score":0.31732455},"labels":[],"label_agreement":null},{"id":"W3007568584","doi":"10.3233/adr-190149","title":"Identification of Superficial White Matter Abnormalities in Alzheimer’s Disease and Mild Cognitive Impairment Using Diffusion Tensor Imaging","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":34,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; University of Toronto; National Institute on Aging; National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Diffusion MRI; White matter; Cognitive impairment; Medicine; Identification (biology); Cognition; Disease; Psychology; Neuroscience; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.062459267255215146,"score_gpt":0.34403485168776377,"score_spread":0.2815755844325486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3007568584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873076,0.0061544883,0.0011521418,0.004678448,0.000058829923,0.00057394116,0.00003488231,0.00002263721,0.000016996413],"genre_scores_gemma":[0.9980821,0.00018689552,0.0007196609,0.0008036561,0.0001467387,0.000013035742,0.0000143102025,0.000030306503,0.0000032681098],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980728,0.000047357047,0.001065828,0.00026672563,0.0003722995,0.00017497486],"domain_scores_gemma":[0.9981998,0.00002810185,0.0008031025,0.00019343862,0.00029582423,0.00047973605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001981738,0.00017104592,0.00035420846,0.0001845773,0.000062485946,0.000026544927,0.000048302696,0.000023258377,0.000037708458],"category_scores_gemma":[0.00007941267,0.00015176075,0.00015781679,0.00017970413,0.00012479592,0.0003020006,0.00006896137,0.00018777561,8.4877996e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007088108,0.0003413384,0.9928229,0.00007953602,0.00012821166,0.0015413099,0.00034256704,0.000054384054,0.0031416086,0.000008429864,0.00029283282,0.00053805707],"study_design_scores_gemma":[0.00068139227,0.000060757895,0.9896913,0.0004904247,0.0027331563,0.00046899257,0.00028810612,0.0025735514,0.0024709194,0.00032774513,0.00005108345,0.00016256222],"about_ca_topic_score_codex":0.000010049202,"about_ca_topic_score_gemma":1.7525707e-7,"teacher_disagreement_score":0.010774493,"about_ca_system_score_codex":0.000024044619,"about_ca_system_score_gemma":0.00017836585,"threshold_uncertainty_score":0.6188624},"labels":[],"label_agreement":null},{"id":"W3008115946","doi":"10.1016/j.neuroimage.2020.116675","title":"Diffusion tensor imaging of the corpus callosum in healthy aging: Investigating higher order polynomial regression modelling","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Women and Children’s Health Research Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Corpus callosum; White matter; Fractional anisotropy; Linear regression; Mathematics; Polynomial; Regression; Voxel; Statistics; Psychology; Medicine; Neuroscience; Magnetic resonance imaging; Artificial intelligence; Computer science; Mathematical analysis; Radiology","score_opus":0.10637217483648236,"score_gpt":0.3423117426563857,"score_spread":0.23593956781990333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3008115946","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92693937,0.0001507508,0.0073304554,0.06393572,0.00011080533,0.00064750656,0.00000877467,0.00021555687,0.00066108594],"genre_scores_gemma":[0.97696257,0.00005238805,0.01272219,0.009970455,0.0001262904,0.000018807297,0.0000052644023,0.000051057978,0.00009095912],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986095,0.00006699122,0.00039809934,0.00041997206,0.00024796702,0.00025748645],"domain_scores_gemma":[0.9990931,0.00007038561,0.00020790505,0.00041101014,0.0000736482,0.00014395676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000732615,0.0001742716,0.00027087267,0.00006317416,0.000115525996,0.000013095411,0.00019408939,0.0000394004,0.000010527725],"category_scores_gemma":[0.00013429111,0.00012587382,0.00007593856,0.0005412103,0.00015166332,0.000087124616,0.00019852737,0.000553131,0.0000026100427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021720758,0.00020919158,0.3593164,0.00026877338,0.000004326482,0.00007400987,0.0005076252,0.0017062458,0.63104624,0.0003597819,0.0023344187,0.003955776],"study_design_scores_gemma":[0.0058719045,0.00048141475,0.2819148,0.0014397269,0.000118859265,0.00014206211,0.00012924527,0.62494755,0.051984157,0.001042964,0.03118177,0.00074553594],"about_ca_topic_score_codex":0.00007895167,"about_ca_topic_score_gemma":0.0000011457973,"teacher_disagreement_score":0.6232413,"about_ca_system_score_codex":0.000034408306,"about_ca_system_score_gemma":0.00007097233,"threshold_uncertainty_score":0.5132986},"labels":[],"label_agreement":null},{"id":"W3009055550","doi":"10.1101/2020.03.04.962191","title":"Increased Sensitivity and Signal-to-Noise Ratio in Diffusion-Weighted MRI using Multi-Echo Acquisitions","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère de l'Enseignement Supérieur et de la Recherche; Max-Planck-Gesellschaft; Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur et de la Recherche Scientifique; Deutsche Forschungsgemeinschaft","keywords":"Computer science; SIGNAL (programming language); Signal-to-noise ratio (imaging); Noise (video); Diffusion MRI; Monte Carlo method; Image quality; Echo (communications protocol); Sensitivity (control systems); Algorithm; Artificial intelligence; Encoding (memory); Contrast (vision); Pattern recognition (psychology); Computer vision; Mathematics; Image (mathematics); Magnetic resonance imaging; Statistics; Radiology; Telecommunications; Medicine","score_opus":0.044631809135098,"score_gpt":0.2969208412061476,"score_spread":0.2522890320710496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009055550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7772046,0.00013526,0.21784464,0.0019618266,0.000069679525,0.0018697678,0.00030155462,0.0006100602,0.0000026644525],"genre_scores_gemma":[0.7764111,0.000108256965,0.22174452,0.0012641115,0.00016139487,0.00020240141,0.0000018956936,0.00010520414,0.0000010908834],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974322,0.00015522548,0.000522883,0.0011951842,0.00027911045,0.00041545322],"domain_scores_gemma":[0.99752295,0.00012329657,0.00024402517,0.0012478838,0.0003174153,0.00054445653],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029240077,0.00050809904,0.0007171181,0.00040994998,0.00019066966,0.00009372594,0.00020288842,0.00031834652,0.000018250614],"category_scores_gemma":[0.00027236776,0.00056292705,0.00010943772,0.00081454456,0.00012059813,0.00010755054,0.0008418388,0.00093418884,0.000014525952],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006664516,0.00028890016,0.015106137,0.00019572864,0.000029799536,0.00022919619,0.000014389242,0.00006366899,0.9837539,0.00017220149,0.000076490054,0.0000029461237],"study_design_scores_gemma":[0.0022670657,0.00010406524,0.385468,0.0017152276,0.00034978107,6.062227e-7,0.0000075116945,0.13844754,0.46944904,0.000028616349,0.00091599766,0.0012465433],"about_ca_topic_score_codex":0.00018567775,"about_ca_topic_score_gemma":0.0000055416963,"teacher_disagreement_score":0.5143049,"about_ca_system_score_codex":0.00028540415,"about_ca_system_score_gemma":0.00039084323,"threshold_uncertainty_score":0.99968225},"labels":[],"label_agreement":null},{"id":"W3009380668","doi":"10.1007/s11682-019-00252-y","title":"Default mode network integrity changes contribute to cognitive deficits in subcortical vascular cognitive impairment, no dementia","year":2020,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Beijing Municipal Science and Technology Commission; National Natural Science Foundation of China","keywords":"Fractional anisotropy; White matter; Default mode network; Diffusion MRI; Psychology; Dementia; Executive dysfunction; Cognition; Montreal Cognitive Assessment; Neuropsychology; Neuroimaging; Vascular dementia; Neuroscience; Audiology; Medicine; Internal medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.05279933910206276,"score_gpt":0.36083473142062916,"score_spread":0.3080353923185664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009380668","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.921261,0.0005979554,0.060301807,0.015425091,0.00004173914,0.001844119,0.00014310643,0.00027970425,0.000105493236],"genre_scores_gemma":[0.98433495,0.000094069546,0.0041552396,0.010628886,0.00014120931,0.0004909368,0.000102690996,0.000033304223,0.000018698129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986201,0.000053959815,0.00023310282,0.00050967885,0.0001693252,0.00041382108],"domain_scores_gemma":[0.9991722,0.00015712905,0.000053457457,0.00012154231,0.00018455801,0.0003111099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001531644,0.00020560421,0.0003156813,0.0000663176,0.00010163257,0.000035204004,0.00006679242,0.000049200113,0.000020969519],"category_scores_gemma":[0.00035616665,0.00019850404,0.00006394805,0.00030557407,0.000098628225,0.00006301172,0.0001252843,0.0004015312,0.000022589205],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000663626,0.0010684028,0.88954705,0.00013325746,0.00008631898,0.0004969655,0.00081953104,0.000007171228,0.018578235,0.0002674115,0.0069926744,0.081339374],"study_design_scores_gemma":[0.007666109,0.0011735706,0.9650307,0.0016372256,0.0018980295,0.00017733451,0.0008809941,0.00813942,0.0073568965,0.0003046062,0.0047573005,0.0009778094],"about_ca_topic_score_codex":0.00009737714,"about_ca_topic_score_gemma":0.000030889838,"teacher_disagreement_score":0.08036157,"about_ca_system_score_codex":0.000030570263,"about_ca_system_score_gemma":0.000035964957,"threshold_uncertainty_score":0.80947596},"labels":[],"label_agreement":null},{"id":"W3009440750","doi":"10.1016/j.pscychresns.2020.111060","title":"Relationship between white matter glucose metabolism and fractional anisotropy in healthy and schizophrenia subjects","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Schizophrenia (object-oriented programming); Psychology; Voxel; Psychosis; Medicine; Neuroscience; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.1562425113989862,"score_gpt":0.4235886478819125,"score_spread":0.26734613648292627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3009440750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8124481,0.00091334566,0.0016372267,0.183879,0.00004140063,0.0005647418,0.000022465923,0.00012478132,0.00036896951],"genre_scores_gemma":[0.9708242,0.00016811973,0.024494296,0.0040089427,0.00035520937,0.000055071836,0.000021027992,0.00004776247,0.00002538613],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980539,0.00018299626,0.00030668796,0.00064383115,0.00038123335,0.0004313301],"domain_scores_gemma":[0.9988639,0.00032058527,0.00006130822,0.00028521902,0.00007858141,0.00039042233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034422523,0.00016372689,0.0002575834,0.00033133634,0.0002981456,0.00007903043,0.000110578876,0.00005113268,0.000022158636],"category_scores_gemma":[0.0002310275,0.0001677489,0.000035083664,0.00077359716,0.0001988934,0.00026269164,0.00016403719,0.0013700781,0.000023944353],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031312386,0.000043427433,0.99353915,0.00012304523,0.0000036766205,0.00001172666,0.000079238154,0.0000013553351,0.00057094696,0.0030916822,0.0018080268,0.00041462443],"study_design_scores_gemma":[0.001236531,0.00012862617,0.9839478,0.000041380204,0.00001691784,0.0000698649,0.00004635782,0.00044036462,0.00003396598,0.01078492,0.0031317722,0.000121458674],"about_ca_topic_score_codex":0.00002083911,"about_ca_topic_score_gemma":0.0000030352,"teacher_disagreement_score":0.17987005,"about_ca_system_score_codex":0.000026168218,"about_ca_system_score_gemma":0.00012905306,"threshold_uncertainty_score":0.6840602},"labels":[],"label_agreement":null},{"id":"W3010843466","doi":"10.1101/2020.03.17.994574","title":"Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Shanghai Jiao Tong University; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Precuneus; Mnemonic; Superior longitudinal fasciculus; Psychology; Arcuate fasciculus; Neuroscience; Inferior longitudinal fasciculus; Diffusion MRI; Cognitive psychology; Functional magnetic resonance imaging; Metacognition; Fractional anisotropy; Cognition; Human Connectome Project; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.08139070351100748,"score_gpt":0.2942308151786235,"score_spread":0.21284011166761602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010843466","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9674281,0.0002884976,0.029005762,0.001402827,0.00010639874,0.0011622562,0.00015349279,0.00043738933,0.000015316622],"genre_scores_gemma":[0.9903237,0.0001883767,0.0087843705,0.00018541672,0.00019839958,0.00023959816,0.0000023589782,0.00007219399,0.00000556749],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99815184,0.000059567214,0.00039394666,0.00086164393,0.0003067569,0.00022622981],"domain_scores_gemma":[0.9984865,0.000040486982,0.00026874655,0.00059429643,0.00039625174,0.00021367436],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017529642,0.00035019976,0.00059034745,0.00014758362,0.00017736378,0.00004375469,0.00011095843,0.00022069593,0.00003533656],"category_scores_gemma":[0.00014781131,0.00029165493,0.00013371072,0.0002735411,0.00022616843,0.00009696127,0.00040208639,0.00063751277,0.0000050250337],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006935373,0.0002473408,0.017878203,0.00055345346,0.000077843455,0.000022116556,0.0000035446908,0.000002269652,0.9798497,0.0011676705,0.00011748546,0.000010993682],"study_design_scores_gemma":[0.0008045427,0.00019031648,0.6332574,0.0006156114,0.00038884976,2.5023465e-7,0.0000026951113,0.0005896544,0.36289892,0.00006672808,0.0007899572,0.0003950758],"about_ca_topic_score_codex":0.000044187214,"about_ca_topic_score_gemma":0.000001256476,"teacher_disagreement_score":0.6169508,"about_ca_system_score_codex":0.000111426816,"about_ca_system_score_gemma":0.00020472491,"threshold_uncertainty_score":0.99995357},"labels":[],"label_agreement":null},{"id":"W3010895829","doi":"10.1017/s1355617720000223","title":"Microstructure of the Corpus Callosum Long after Pediatric Concussion","year":2020,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Université de Moncton; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Splenium; Corpus callosum; Fractional anisotropy; Diffusion MRI; Concussion; White matter; Psychology; Medicine; Physical therapy; Magnetic resonance imaging; Poison control; Neuroscience; Radiology; Injury prevention","score_opus":0.04375649190366941,"score_gpt":0.3331737599436393,"score_spread":0.28941726803996987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010895829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92567086,0.00009241065,0.0012656995,0.07221371,0.00043730438,0.0001401622,0.0000141052205,0.000013522403,0.00015222208],"genre_scores_gemma":[0.9788294,0.00016762552,0.0016658683,0.018765949,0.00044501448,0.0000019372944,4.3783191e-7,0.000009097681,0.00011471547],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99903744,0.00003515091,0.0003474526,0.00012403344,0.00037575728,0.00008014433],"domain_scores_gemma":[0.9991074,0.000053000884,0.0004276807,0.0001644702,0.00018083776,0.000066596105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007582313,0.00008480998,0.0001445062,0.000008328211,0.000047542777,0.000010796479,0.0005245569,0.000055671047,0.000068720816],"category_scores_gemma":[0.00019493613,0.00003735068,0.00049855956,0.00018371858,0.00012214965,0.000036900336,0.0001806805,0.00060256076,0.0000013753839],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089177437,0.0003102104,0.6847817,0.000038364924,0.000084716296,0.00005741926,0.0002145774,0.00010636244,0.25850728,0.00024061844,0.05337641,0.0013905948],"study_design_scores_gemma":[0.00056376297,0.00012949253,0.98114073,0.00002751687,0.00005850593,0.00042057745,0.000008246701,0.000095594434,0.002986171,0.000581279,0.01394232,0.00004580133],"about_ca_topic_score_codex":4.229515e-7,"about_ca_topic_score_gemma":4.1837463e-8,"teacher_disagreement_score":0.29635906,"about_ca_system_score_codex":0.00002515937,"about_ca_system_score_gemma":0.000029226803,"threshold_uncertainty_score":0.261786},"labels":[],"label_agreement":null},{"id":"W3010953972","doi":"10.1523/eneuro.0290-19.2020","title":"Resting State BOLD Variability of the Posterior Medial Temporal Lobe Correlates with Cognitive Performance in Older Adults with and without Risk for Cognitive Decline","year":2020,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Montreal Cognitive Assessment; Cognition; Temporal lobe; Psychology; Cognitive decline; Effects of sleep deprivation on cognitive performance; Parahippocampal gyrus; Audiology; Entorhinal cortex; Frontal lobe; Neuroscience; Dementia; Hippocampus; Internal medicine; Medicine; Disease; Cognitive impairment","score_opus":0.02380971415525295,"score_gpt":0.298112807450058,"score_spread":0.27430309329480507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3010953972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925678,0.000016189348,0.0048049088,0.00079090265,0.000010319124,0.0015878868,0.00011754578,0.000050651783,0.000053808388],"genre_scores_gemma":[0.995739,0.000031381696,0.0033325504,0.0006958921,0.000026237738,0.0001226108,0.000016605281,0.00002628795,0.000009454302],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991663,0.000047839396,0.00020612832,0.00031276286,0.00012715528,0.00013982608],"domain_scores_gemma":[0.9990751,0.00038613426,0.00018910592,0.00011722343,0.00016296793,0.00006947035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012184341,0.00012932002,0.0002167365,0.000021578633,0.00006367919,0.000006203933,0.000055129927,0.000024360721,0.0000019549693],"category_scores_gemma":[0.00059541303,0.00007979713,0.000019734302,0.00019278357,0.00021348176,0.000065229295,0.00006681181,0.00025412816,2.0647646e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029680005,0.00007126712,0.9930396,0.00013524131,0.000008446372,0.0000038207854,0.0008585473,0.000011283751,0.00038944322,0.0000030476015,0.0000024471474,0.0025088529],"study_design_scores_gemma":[0.0053543607,0.0014971776,0.9731346,0.0011385805,0.0001277394,0.00004782366,0.00023135573,0.005020854,0.013237734,0.000055821245,0.000024797086,0.00012920413],"about_ca_topic_score_codex":0.000021194819,"about_ca_topic_score_gemma":0.000026111144,"teacher_disagreement_score":0.01990505,"about_ca_system_score_codex":0.0000070125448,"about_ca_system_score_gemma":0.000058528534,"threshold_uncertainty_score":0.32540327},"labels":[],"label_agreement":null},{"id":"W3011265095","doi":"10.1007/s00429-020-02056-z","title":"The role of diffusion tractography in refining glial tumor resection","year":2020,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; White matter; Diffusion MRI; Magnetic resonance imaging; Computer science; Neuronavigation; Surgical planning; Diffusion imaging; Imaging phantom; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.03682589367444844,"score_gpt":0.33722179382944417,"score_spread":0.30039590015499573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011265095","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0004254727,0.99803585,0.00029808766,0.00024707156,0.00009922025,0.0004822969,0.000024906158,0.000061184415,0.00032591456],"genre_scores_gemma":[0.0028597917,0.9961984,0.00039993695,0.00009847461,0.00024424802,0.000053729345,0.00008182029,0.000028952569,0.000034607914],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99916786,0.00004804706,0.0003105638,0.00025917875,0.000112813796,0.000101517806],"domain_scores_gemma":[0.99937725,0.00014457524,0.00022080021,0.00019346582,0.000024335848,0.000039575632],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007358912,0.00015783029,0.00046191705,0.00012372677,0.00009817673,0.000012418226,0.000049774397,0.00011286647,0.0000044383146],"category_scores_gemma":[0.00008299691,0.00009948654,0.00012447382,0.000412345,0.0000555081,0.000031675147,0.000031456424,0.00046877924,3.2082983e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078445315,0.000007876691,0.000095932766,0.00065954856,0.000012193715,0.0000019110375,0.00001620443,9.8399184e-8,0.00044162493,0.00075832946,0.00013183591,0.997796],"study_design_scores_gemma":[0.00015619716,0.00017878064,0.0006371388,0.0011504709,0.00014979708,0.0000816548,0.000023426053,0.000017128761,0.000030116911,0.0023194633,0.9951783,0.0000775179],"about_ca_topic_score_codex":0.000013246601,"about_ca_topic_score_gemma":0.000010272807,"teacher_disagreement_score":0.99771845,"about_ca_system_score_codex":0.0000208709,"about_ca_system_score_gemma":0.000038236394,"threshold_uncertainty_score":0.40569434},"labels":[],"label_agreement":null},{"id":"W3011339117","doi":"10.1101/2020.03.11.987925","title":"Myelin water imaging depends on white matter fiber orientation in the human brain","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Canadian Institutes of Health Research; Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Multiple Sclerosis Society","keywords":"White matter; Diffusion MRI; Voxel; Nuclear magnetic resonance; Orientation (vector space); Magnetic resonance imaging; Myelin; Chemistry; Physics; Neuroscience; Psychology; Mathematics; Medicine; Artificial intelligence; Central nervous system; Computer science; Radiology; Geometry","score_opus":0.0336502951825454,"score_gpt":0.3011239643473336,"score_spread":0.26747366916478815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3011339117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92991114,0.000067837784,0.00449551,0.062136132,0.00020688702,0.002130132,0.00009911986,0.00067972246,0.00027350942],"genre_scores_gemma":[0.98143345,0.000012222062,0.006102552,0.0113948425,0.00035833206,0.0005342359,0.000004508609,0.00012791494,0.000031940286],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9977544,0.00011222516,0.00046623318,0.0009083614,0.0003532428,0.00040556095],"domain_scores_gemma":[0.99828017,0.00004957299,0.00016564305,0.0012470607,0.00013567827,0.000121903846],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003744636,0.00040151124,0.0003730693,0.00022369409,0.00014815702,0.00012737696,0.00040240472,0.00015525077,0.00019043215],"category_scores_gemma":[0.000048437156,0.0003013176,0.00012392153,0.00030794155,0.00008035681,0.00009027224,0.000261888,0.0011649926,0.0003170873],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006223153,0.0003229033,0.102184325,0.00040744458,0.000040972496,0.00030693132,0.00012986346,0.00005365971,0.881488,0.0011252019,0.013865028,0.000013425933],"study_design_scores_gemma":[0.0012326278,0.00009202515,0.72117794,0.00073507463,0.00016498,3.02851e-7,0.000013231066,0.00041163096,0.22461447,0.00010591311,0.05053972,0.0009120791],"about_ca_topic_score_codex":0.000019020248,"about_ca_topic_score_gemma":6.468926e-7,"teacher_disagreement_score":0.6568735,"about_ca_system_score_codex":0.000157789,"about_ca_system_score_gemma":0.00007026693,"threshold_uncertainty_score":0.9999439},"labels":[],"label_agreement":null},{"id":"W3013188727","doi":"10.1176/appi.ajp.2019.19030225","title":"The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium","year":2020,"lang":"en","type":"review","venue":"American Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Department of Psychiatry, University of Toronto; University of California, Irvine; National Institutes of Health; Centre for Cognitive Ageing and Cognitive Epidemiology; H. Lundbeck A/S; Servier; Cilag; University of Cape Town; Science Foundation Ireland; Regeneron Pharmaceuticals; Medical Research Council; Gedeon Richter; Biogen; Otsuka America; Campbell Family Mental Health Research Institute; Georgia State University; School of Medicine, University of California, Irvine; University of Toronto; Sunovion; Sanofi; Pfizer","keywords":"Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Cognition; Effects of sleep deprivation on cognitive performance; Psychology; Sample size determination; Psychosis; Medicine; Clinical psychology; Internal medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.05319407554041516,"score_gpt":0.37948415936031904,"score_spread":0.3262900838199039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013188727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5301007,0.4570643,0.00014486325,0.011173358,0.00004842644,0.0013530382,0.00006850513,0.000010352912,0.000036448197],"genre_scores_gemma":[0.61044824,0.37431934,0.012740163,0.002024501,0.00028590753,0.0000639742,0.000022385397,0.00008416752,0.00001130956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998679,0.00026157213,0.0005565288,0.00019608256,0.00013644031,0.00017037334],"domain_scores_gemma":[0.9985776,0.00040368678,0.0007057397,0.0001702581,0.00003899993,0.00010373437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021235642,0.00017490757,0.00068966445,0.000084606705,0.00007847579,0.000021530403,0.000105913416,0.00004085103,0.000002347191],"category_scores_gemma":[0.000074716845,0.00008842408,0.000059880997,0.00034724153,0.0004083954,0.000033282362,0.000024438668,0.0008660441,8.308835e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015828619,0.000027033164,0.9191295,0.00021588936,0.000021275888,0.0000021653482,0.000073490584,3.397981e-8,1.2977042e-8,0.00004494102,0.000104626546,0.080222756],"study_design_scores_gemma":[0.000744743,0.0004503004,0.9845985,0.0016989369,0.00028414303,0.00007017548,0.00011088838,2.982914e-7,1.2451535e-8,0.0003863047,0.011568629,0.000087064516],"about_ca_topic_score_codex":0.000005789315,"about_ca_topic_score_gemma":0.000014496068,"teacher_disagreement_score":0.082744956,"about_ca_system_score_codex":0.00002474353,"about_ca_system_score_gemma":0.00019512925,"threshold_uncertainty_score":0.37625787},"labels":[],"label_agreement":null},{"id":"W3013503384","doi":"10.1016/j.bpsc.2020.03.003","title":"In Vivo Imaging of Gray Matter Microstructure in Major Psychiatric Disorders: Opportunities for Clinical Translation","year":2020,"lang":"en","type":"review","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Canon Medical Systems USA; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression; Radiological Society of North America","keywords":"Gray (unit); Translation (biology); Psychiatry; Medicine; Psychology; Radiology; Chemistry","score_opus":0.26774318085976523,"score_gpt":0.45915613417016954,"score_spread":0.1914129533104043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013503384","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029093423,0.9796506,0.0027698863,0.00870336,0.000783663,0.004256888,0.0005001141,0.00010907194,0.0003170516],"genre_scores_gemma":[0.0067202123,0.9846277,0.002650605,0.005540566,0.00015707625,0.00020174662,0.00003523657,0.000053928696,0.000012889508],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9967223,0.00023292631,0.0012014634,0.0012779181,0.0001466008,0.00041883474],"domain_scores_gemma":[0.99859893,0.00050750695,0.00046897982,0.00022641465,0.00004697545,0.00015117088],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027840817,0.00048024248,0.0014258131,0.00046391945,0.00009700287,0.000035825167,0.00025151836,0.00016385442,0.000010656243],"category_scores_gemma":[0.00019548483,0.00037596622,0.00041785176,0.00082087825,0.00066023384,0.00018550697,0.00009957129,0.000813056,0.0000011197511],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026209097,0.0005900472,0.17415756,0.0053618723,0.000009768421,0.000065178705,0.00003990035,1.302814e-7,0.00028450883,0.00026609135,0.00089975185,0.8180631],"study_design_scores_gemma":[0.003463398,0.001033718,0.04753735,0.006533878,0.0006201943,0.00054591836,0.00021497473,0.0003010684,0.000013648984,0.005255871,0.9332949,0.0011851175],"about_ca_topic_score_codex":0.000004307327,"about_ca_topic_score_gemma":0.0000027458382,"teacher_disagreement_score":0.9323951,"about_ca_system_score_codex":0.000014684277,"about_ca_system_score_gemma":0.0001817865,"threshold_uncertainty_score":0.9998692},"labels":[],"label_agreement":null},{"id":"W3013886781","doi":"10.1002/hbm.24964","title":"Impact of <i>b</i> ‐value on estimates of apparent fibre density","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":105,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Wolfson Foundation; Engineering and Physical Sciences Research Council; International Society for Magnetic Resonance in Medicine; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Deconvolution; Robustness (evolution); Population; White matter; Magnetic resonance imaging; Statistics; Sampling (signal processing); Mathematics; Nuclear magnetic resonance; Nuclear medicine; Physics; Chemistry; Optics; Medicine; Radiology","score_opus":0.13521282274823745,"score_gpt":0.3948600916401611,"score_spread":0.2596472688919237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013886781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.965466,0.000023433646,0.029852657,0.0028768857,0.000005183057,0.00032881362,0.000013449675,0.00014554913,0.001288019],"genre_scores_gemma":[0.99064994,0.0000031274305,0.008440599,0.00081357453,0.00003867987,0.0000068556933,0.000018705405,0.000014832883,0.000013686338],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993818,0.000011474011,0.00020924369,0.00017596835,0.000113516246,0.00010803362],"domain_scores_gemma":[0.99943966,0.00007803392,0.00012338777,0.00023581872,0.00004897842,0.000074118376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052124273,0.00009470178,0.00024224135,0.000045310433,0.000050408165,0.0000030656488,0.000078149926,0.000024812785,0.000024176665],"category_scores_gemma":[0.00012280219,0.000083587736,0.000116402894,0.00014263354,0.00006566145,0.000021788426,0.000046591696,0.00011365358,0.0000032458595],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003298439,0.000099500496,0.024085194,0.00019238364,0.000027795279,0.0000056655435,0.0003231825,0.0002118419,0.9632421,0.00482967,0.0061794766,0.000770199],"study_design_scores_gemma":[0.0011589931,0.001485337,0.88851,0.00082286895,0.00006313106,0.00002571974,0.00009082312,0.0049635954,0.09048933,0.009709821,0.0024088875,0.00027149753],"about_ca_topic_score_codex":0.000016257427,"about_ca_topic_score_gemma":1.6324627e-7,"teacher_disagreement_score":0.8727528,"about_ca_system_score_codex":0.00002232369,"about_ca_system_score_gemma":0.000021413856,"threshold_uncertainty_score":0.3408609},"labels":[],"label_agreement":null},{"id":"W3014870269","doi":"10.1089/neu.2019.6886","title":"White Matter Abnormalities in Retired Professional Rugby League Players with a History of Concussion","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Concussion; Fractional anisotropy; White matter; Diffusion MRI; Corpus callosum; Psychology; Corticospinal tract; Medicine; Physical therapy; Poison control; Physical medicine and rehabilitation; Magnetic resonance imaging; Injury prevention; Neuroscience; Radiology","score_opus":0.12353809413654963,"score_gpt":0.34481904821830844,"score_spread":0.2212809540817588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014870269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9765556,0.00015445947,0.0005513825,0.019756796,0.00008764704,0.0002859942,0.0000050756985,0.000024916075,0.0025781717],"genre_scores_gemma":[0.99232787,0.000031145428,0.0028720223,0.0035272217,0.00008080376,0.0000069567122,0.0000013870327,0.00001853926,0.001134082],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990688,0.00003809018,0.00042169806,0.00011338894,0.00024881624,0.000109222194],"domain_scores_gemma":[0.99928486,0.000038138747,0.00035647798,0.00011478997,0.000097030075,0.00010867373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006648589,0.00009557551,0.00027757208,0.00010055232,0.000013405776,0.000002435121,0.000097745746,0.00003408595,0.00009157749],"category_scores_gemma":[0.000026640992,0.00006618965,0.00006633438,0.00011042683,0.00009394752,0.00011693563,0.000022436832,0.0004144127,0.0000022545858],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00802219,0.0008295831,0.6321023,0.0009677615,0.00006052323,0.0016057077,0.007386786,0.00032805357,0.12907514,0.0006725968,0.2166195,0.0023298645],"study_design_scores_gemma":[0.0059003113,0.0034200205,0.8793352,0.0016907438,0.00012492733,0.0022387472,0.0008139843,0.00089311175,0.012064864,0.00017886482,0.09300782,0.0003314055],"about_ca_topic_score_codex":0.0000027180545,"about_ca_topic_score_gemma":4.196882e-7,"teacher_disagreement_score":0.2472329,"about_ca_system_score_codex":0.00006984932,"about_ca_system_score_gemma":0.00015411578,"threshold_uncertainty_score":0.26991355},"labels":[],"label_agreement":null},{"id":"W3014906913","doi":"10.1089/neu.2020.6992","title":"White Matter Changes Caused by Mild Traumatic Brain Injury in Mice Evaluated Using Neurite Orientation Dispersion and Density Imaging","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto; Hospital for Sick Children","funders":"","keywords":"White matter; Traumatic brain injury; Fractional anisotropy; Diffusion MRI; Glial fibrillary acidic protein; Neuroscience; Pathology; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.14982499954835007,"score_gpt":0.399856576614741,"score_spread":0.2500315770663909,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3014906913","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95138884,0.00007290839,0.0024893782,0.04566806,0.000035417313,0.0003022395,0.0000063339394,0.000024526486,0.000012276572],"genre_scores_gemma":[0.98839813,0.00006815682,0.0019126798,0.009505599,0.000068341134,0.0000029835367,0.0000040343366,0.000027619091,0.000012444609],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99899983,0.00007970457,0.00035159267,0.00020036995,0.00021888633,0.00014962317],"domain_scores_gemma":[0.9993702,0.000043609714,0.00025687795,0.00009815382,0.00008956785,0.00014157055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014427117,0.00012956622,0.0002547643,0.00013870613,0.00005533389,0.000026994847,0.000068386995,0.000027842842,0.000016125945],"category_scores_gemma":[0.0000653242,0.00011902699,0.000045654753,0.000277556,0.000044329885,0.00019151626,0.0000308089,0.00034058362,0.0000015334364],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000309839,0.00012699427,0.16908398,0.00015395932,0.000010944914,0.00014163669,0.0012851612,0.00005024393,0.8184261,0.0000030004278,0.005814942,0.0045931996],"study_design_scores_gemma":[0.003685442,0.00077650516,0.89352024,0.0006423839,0.00024574195,0.0011826423,0.00035533347,0.053773727,0.04348968,0.00015326917,0.0018165914,0.00035845002],"about_ca_topic_score_codex":0.000008221706,"about_ca_topic_score_gemma":0.0000012538736,"teacher_disagreement_score":0.77493644,"about_ca_system_score_codex":0.000040467745,"about_ca_system_score_gemma":0.000018931638,"threshold_uncertainty_score":0.485378},"labels":[],"label_agreement":null},{"id":"W3015297905","doi":"10.1002/mrm.28268","title":"MAPL1:<i>q</i>‐space reconstruction using ‐regularized mean apparent propagator","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; National Institute of Mental Health","keywords":"Undersampling; Mathematics; Basis (linear algebra); Basis function; Diffusion MRI; Algorithm; Mathematical analysis; Artificial intelligence; Computer science; Geometry","score_opus":0.09644794645795542,"score_gpt":0.34335743818512676,"score_spread":0.24690949172717136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015297905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8508271,0.010717937,0.041665412,0.08785909,0.00029505457,0.0035293482,0.00001151973,0.0007364327,0.004358138],"genre_scores_gemma":[0.8320111,0.0009509923,0.15982775,0.005661863,0.00075091614,0.00018179895,0.000019104478,0.0000834684,0.00051302736],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99836344,0.000046459558,0.00045793876,0.00050921313,0.00032830468,0.0002946737],"domain_scores_gemma":[0.99915355,0.000042019234,0.000112570604,0.00039314877,0.000080414844,0.00021827169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016414252,0.00020355737,0.00045763678,0.000104321894,0.000058752375,0.000007765561,0.00013649609,0.00007058314,0.0002026787],"category_scores_gemma":[0.00024799834,0.00017116024,0.000047160767,0.00065025064,0.0002940295,0.000057523015,0.00005357518,0.0003579245,0.00001074004],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009164722,0.00026512478,0.05208789,0.00052442,0.000012459963,0.0003873669,0.0019226731,0.00007471585,0.45469704,0.002965282,0.0062863105,0.47986025],"study_design_scores_gemma":[0.022827523,0.0056178733,0.08481507,0.0059800236,0.00051258673,0.0025647762,0.0025036598,0.2306556,0.036284454,0.010463011,0.5960454,0.0017300548],"about_ca_topic_score_codex":0.00004618233,"about_ca_topic_score_gemma":0.000003440085,"teacher_disagreement_score":0.58975905,"about_ca_system_score_codex":0.00008341143,"about_ca_system_score_gemma":0.00006672215,"threshold_uncertainty_score":0.69797117},"labels":[],"label_agreement":null},{"id":"W3015883524","doi":"10.3389/fnins.2020.00269","title":"Microstructural Investigations of the Visual Pathways in Pediatric Epilepsy Neurosurgery: Insights From Multi-Shell Diffusion Magnetic Resonance Imaging","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"NIHR Great Ormond Street Hospital Biomedical Research Centre; Medical Research Council Canada; Fight for Sight UK; National Institute for Health and Care Research; Great Ormond Street Institute of Child Health; Medical Research Council","keywords":"Tractography; Optic radiation; Diffusion MRI; Epilepsy surgery; Magnetic resonance imaging; Fractional anisotropy; Medicine; Visual field; White matter; Neurosurgery; Epilepsy; Radiology; Ophthalmology; Psychiatry","score_opus":0.03560498313517041,"score_gpt":0.2768057979748006,"score_spread":0.24120081483963018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015883524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914178,0.0009916781,0.004562463,0.0019653428,0.00043430654,0.00050891005,0.000029691577,0.00006629123,0.000023465413],"genre_scores_gemma":[0.98138285,0.00028373272,0.014983196,0.0032413558,0.000044363,0.000026044929,0.0000040584414,0.000019842317,0.000014564348],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984707,0.00007906324,0.00039709418,0.0005651941,0.00024916703,0.0002387309],"domain_scores_gemma":[0.99932015,0.000056019104,0.00014376959,0.00033172802,0.000031073367,0.00011723652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000045523706,0.0001570918,0.00024308874,0.00015312979,0.000101197336,0.00001894617,0.0003698509,0.000034386223,0.0000017127849],"category_scores_gemma":[0.0004717872,0.00012752521,0.000061621904,0.0016194774,0.00039977994,0.00015187683,0.00020570212,0.00038448535,6.9697023e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014029013,0.00005471897,0.7797764,0.000011350971,5.653157e-8,0.000017622273,0.00025804347,0.000033345666,0.21806672,0.000028690427,0.00034086336,0.0013981843],"study_design_scores_gemma":[0.0004892476,0.000042891425,0.91887885,0.000041372958,0.0000079626425,0.000005963433,0.000039786293,0.07013324,0.008453889,0.0006565251,0.0011407153,0.00010952399],"about_ca_topic_score_codex":0.000030085079,"about_ca_topic_score_gemma":0.0000035897417,"teacher_disagreement_score":0.20961283,"about_ca_system_score_codex":0.000034015353,"about_ca_system_score_gemma":0.00009156354,"threshold_uncertainty_score":0.52003276},"labels":[],"label_agreement":null},{"id":"W3015921769","doi":"10.1101/2020.04.07.20057166","title":"Orbitofrontal-striatal structural alterations linked to negative symptoms at different stages of the schizophrenia spectrum","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"McGill University","keywords":"Apathy; Schizotypy; Anhedonia; Orbitofrontal cortex; Schizophrenia (object-oriented programming); Psychosis; Psychology; Ventral striatum; Striatum; Antipsychotic; Pathological; Cohort; Psychiatry; Medicine; Internal medicine; Neuroscience; Prefrontal cortex; Dopamine; Cognition","score_opus":0.0464635915880752,"score_gpt":0.3273896492387321,"score_spread":0.2809260576506569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3015921769","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97443473,0.00003958304,0.004619482,0.017885586,0.00033714375,0.0018381404,0.0005170561,0.0002100276,0.000118272204],"genre_scores_gemma":[0.9926629,0.000025900796,0.0058179875,0.00040104936,0.00034703407,0.00019890275,0.00012737155,0.00005226817,0.0003665745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826103,0.00006081337,0.00050255324,0.00061334186,0.00033050243,0.00023175543],"domain_scores_gemma":[0.99827254,0.00008397376,0.00031764878,0.0010606821,0.00007373491,0.00019142128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003850929,0.00034233424,0.0005381297,0.000081371596,0.00016194631,0.000026828513,0.0004587602,0.0001159035,0.000077513614],"category_scores_gemma":[0.00017666962,0.00023053518,0.00026229178,0.00020792967,0.00013957905,0.00002846866,0.0013787411,0.0007939348,0.000011642243],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014290733,0.00035800473,0.50551325,0.000937138,0.0006921306,0.00003673794,0.0033395716,0.0009312248,0.46482158,0.014005178,0.004783934,0.0031521786],"study_design_scores_gemma":[0.00092631136,0.00022451022,0.75805247,0.00041422417,0.00025350013,0.000021047414,0.000021377193,0.0009895078,0.22469787,0.013241444,0.00079115306,0.00036658047],"about_ca_topic_score_codex":0.000039210416,"about_ca_topic_score_gemma":0.000053008836,"teacher_disagreement_score":0.25253922,"about_ca_system_score_codex":0.00019223882,"about_ca_system_score_gemma":0.000083196406,"threshold_uncertainty_score":0.9400952},"labels":[],"label_agreement":null},{"id":"W3016018540","doi":"10.1101/2020.04.07.029850","title":"Diffusion MRI of the Unfolded Hippocampus","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Hippocampus; Diffusion MRI; Neuroscience; Hippocampal formation; Tractography; Computer science; Artificial intelligence; Magnetic resonance imaging; Biology; Medicine; Radiology","score_opus":0.03553262599891273,"score_gpt":0.2779900029114306,"score_spread":0.2424573769125179,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016018540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9734856,0.00053450797,0.012571842,0.009492592,0.00055184844,0.0021946535,0.00019056439,0.00092973944,0.000048656464],"genre_scores_gemma":[0.9742466,0.00031572988,0.02403911,0.0009028705,0.00021929163,0.0001679625,2.7085986e-7,0.0001020358,0.000006103516],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99816775,0.000054132415,0.0004605397,0.00069101487,0.0003580517,0.00026852268],"domain_scores_gemma":[0.997208,0.000043269847,0.00045509962,0.0018174715,0.00028407603,0.00019210285],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012957465,0.0003501473,0.00053170853,0.00009158797,0.00010855396,0.000026236681,0.00053102494,0.00026500653,0.000020127822],"category_scores_gemma":[0.00019019647,0.00028085907,0.0002479706,0.0005070856,0.0001758489,0.000035933575,0.00084887986,0.00089323416,0.000014670146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029236706,0.00015501534,0.009432216,0.00046508643,0.000046658344,0.000016164051,0.0000051623183,0.0000081446615,0.98690796,0.0015967418,0.0013285925,0.000008994313],"study_design_scores_gemma":[0.00076054304,0.00008667555,0.21310368,0.0012696007,0.0003764795,7.496437e-8,0.0000017747752,0.00097538484,0.7619276,0.00024771865,0.020714968,0.00053551595],"about_ca_topic_score_codex":0.000014160494,"about_ca_topic_score_gemma":2.07031e-7,"teacher_disagreement_score":0.2249804,"about_ca_system_score_codex":0.00011300692,"about_ca_system_score_gemma":0.00036196446,"threshold_uncertainty_score":0.99996436},"labels":[],"label_agreement":null},{"id":"W3016428943","doi":"10.1016/j.media.2021.101988","title":"Magic DIAMOND: Multi-fascicle diffusion compartment imaging with tensor distribution modeling and tensor-valued diffusion encoding","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Diffusion MRI; Voxel; Tractography; Tensor (intrinsic definition); Computer science; Fascicle; Algorithm; Artificial intelligence; Mathematics; Statistical physics; Physics; Geometry; Geology; Magnetic resonance imaging","score_opus":0.03966792182640934,"score_gpt":0.34059918555620194,"score_spread":0.3009312637297926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016428943","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43619683,0.00023900048,0.5596755,0.0034841653,0.000009083069,0.00016483034,0.000019518875,0.00014408091,0.000067008055],"genre_scores_gemma":[0.9565727,0.00045632053,0.041277647,0.00082715997,0.000057971516,0.00003659382,0.00053273834,0.000026860233,0.00021201995],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99784225,0.00007472805,0.00040253164,0.0006599391,0.00067044253,0.00035011],"domain_scores_gemma":[0.99864805,0.00007109737,0.000103851686,0.0004964858,0.00027312498,0.0004073787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023381693,0.00023206472,0.0005330235,0.00014791726,0.00027156458,0.00006554686,0.00010302332,0.00006037519,0.00018116325],"category_scores_gemma":[0.00029510676,0.00017481192,0.00017794165,0.0009601421,0.00019481328,0.00013784392,0.00019513149,0.0003462816,0.000008158474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025766465,0.0032199305,0.69859374,0.000257283,0.0009261071,0.002954797,0.000525648,0.00081620406,0.24935327,0.00048435928,0.0008762555,0.041734748],"study_design_scores_gemma":[0.0013931732,0.00003433046,0.029745506,0.0001367539,0.0015211025,0.00014600612,0.000262089,0.962957,0.0030569695,0.00007952298,0.00045120274,0.00021630678],"about_ca_topic_score_codex":0.0000833887,"about_ca_topic_score_gemma":0.000018139843,"teacher_disagreement_score":0.96214086,"about_ca_system_score_codex":0.00009032093,"about_ca_system_score_gemma":0.000055071618,"threshold_uncertainty_score":0.7128623},"labels":[],"label_agreement":null},{"id":"W3016720595","doi":"10.1371/journal.pone.0231669","title":"Neurological soft signs (NSS) and brain morphology in patients with chronic schizophrenia and healthy controls","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Parahippocampal gyrus; Schizophrenia (object-oriented programming); Motor coordination; Medicine; Cerebellum; Thalamus; Magnetic resonance imaging; Neuroscience; Neurological examination; Sensory system; Neuroimaging; Psychology; Audiology; Temporal lobe; Psychiatry; Radiology","score_opus":0.06185096783244322,"score_gpt":0.2826069056056145,"score_spread":0.22075593777317132,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016720595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96807534,0.00010269556,0.00085387233,0.030143926,0.0000010888683,0.00065024226,0.0000065828895,0.00010793237,0.000058334725],"genre_scores_gemma":[0.9850921,0.000037907295,0.006499733,0.00824482,0.000029056577,0.000052306408,0.000007181933,0.000019580983,0.000017302764],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993988,0.000021908058,0.000104702034,0.00025795176,0.0000785427,0.0001380433],"domain_scores_gemma":[0.9996545,0.00006315874,0.00003726754,0.00010572663,0.000016419244,0.00012297642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000024500974,0.00007935369,0.00021395822,0.000029907163,0.000026628257,0.00000462209,0.00003223381,0.00003535542,0.000020930423],"category_scores_gemma":[0.000083937826,0.0000634501,0.000006560877,0.00008755133,0.00009708976,0.000024144805,0.000040042218,0.00019093069,0.000003930454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030142893,0.0014085036,0.93373954,0.00015170491,0.00003478367,0.00005048112,0.000047124453,0.0000029136968,0.055989593,0.00091093936,0.00033385726,0.004316281],"study_design_scores_gemma":[0.011836395,0.011203186,0.9720407,0.00008749962,0.000078689205,0.000012706852,0.000002440462,0.002491769,0.0007389353,0.00054299744,0.00076923036,0.000195444],"about_ca_topic_score_codex":0.0000026375092,"about_ca_topic_score_gemma":0.0000023041614,"teacher_disagreement_score":0.055250656,"about_ca_system_score_codex":0.00000804995,"about_ca_system_score_gemma":0.00001783752,"threshold_uncertainty_score":0.258742},"labels":[],"label_agreement":null},{"id":"W3016882932","doi":"10.3233/jad-200022","title":"Plasma Neurofilament Light and Longitudinal Progression of White Matter Hyperintensity in Elderly Persons Without Dementia","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Hyperintensity; Dementia; Neurofilament; White matter; Medicine; Longitudinal study; Psychology; Gerontology; Neuroscience; Internal medicine; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.06558397709974662,"score_gpt":0.3395510494010985,"score_spread":0.27396707230135187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016882932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97492063,0.0010049106,0.00054716587,0.023214864,0.000021223928,0.00022308361,0.000004564202,0.000012467014,0.00005108083],"genre_scores_gemma":[0.9935623,0.000053862055,0.005592888,0.000719743,0.00004737833,0.000005097482,0.0000011353932,0.000013513535,0.0000041180924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992507,0.00001917976,0.0002989824,0.00014491208,0.00018173951,0.000104481805],"domain_scores_gemma":[0.9992811,0.000007478586,0.0002127819,0.00011474278,0.00009090094,0.00029300747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049949358,0.00009688188,0.00023256203,0.0000681874,0.00003580984,0.000007836792,0.000058206202,0.000017359824,0.000033805787],"category_scores_gemma":[0.000020017476,0.00007548726,0.000077109304,0.0000938062,0.000041811145,0.00009234241,0.00006479225,0.0001855219,0.00000160895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060429075,0.00020842586,0.9900064,0.000046634086,0.000071216775,0.00018464096,0.00018336656,0.000007640484,0.0063669365,0.000008574691,0.001347463,0.0009644402],"study_design_scores_gemma":[0.0010034979,0.00051748264,0.9902868,0.00020008678,0.00079104275,0.00013097632,0.000048548976,0.0005440996,0.005148494,0.000033397602,0.0012133504,0.000082176135],"about_ca_topic_score_codex":8.7803795e-7,"about_ca_topic_score_gemma":1.8220334e-7,"teacher_disagreement_score":0.02249512,"about_ca_system_score_codex":0.0000064169694,"about_ca_system_score_gemma":0.000042807253,"threshold_uncertainty_score":0.30782813},"labels":[],"label_agreement":null},{"id":"W3017144256","doi":"10.1002/brb3.1609","title":"Reliability of multimodal MRI brain measures in youth at risk for mental illness","year":2020,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Canadian Institutes of Health Research; Dalhousie University; Nova Scotia Health Research Foundation; Brain and Behavior Research Foundation; Canada Research Chairs; Fondation Brain Canada; Dalhousie Medical Research Foundation","keywords":"Mental illness; Reliability (semiconductor); Psychology; Neuroimaging; Mental health; Psychiatry; Medicine; Reliability engineering; Physical medicine and rehabilitation; Engineering","score_opus":0.07004747563812988,"score_gpt":0.3552865085876501,"score_spread":0.28523903294952024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017144256","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98806214,0.000041047973,0.0030008964,0.0073817046,0.0000148582385,0.0010620236,0.00035349667,0.000060886035,0.000022969132],"genre_scores_gemma":[0.99018747,0.000037113296,0.008663649,0.00082346326,0.000026849586,0.00013789651,0.000053618773,0.000014148387,0.000055813376],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993831,0.000021971577,0.00018148606,0.00021640694,0.0000891229,0.00010792354],"domain_scores_gemma":[0.99959874,0.0000778522,0.00005836728,0.00015063226,0.000031879128,0.00008250719],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012875095,0.000084237014,0.00017561454,0.000024472743,0.000053265732,0.0000030938095,0.000047429796,0.000040985342,0.000008969087],"category_scores_gemma":[0.00019505725,0.00007273135,0.00005371033,0.00008195967,0.00008762308,0.000029519355,0.00004734917,0.00009291235,5.358459e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010065619,0.0012581011,0.46701592,0.000200143,0.000009724822,0.000009629284,0.008895269,0.000008216526,0.41884312,0.00018319456,0.0069502178,0.09561991],"study_design_scores_gemma":[0.0067938934,0.00089102925,0.8450333,0.0001060347,0.00021909777,0.000020886066,0.0013886172,0.0015697111,0.1150338,0.0003337866,0.028176581,0.0004332643],"about_ca_topic_score_codex":0.00006748894,"about_ca_topic_score_gemma":0.0000113621645,"teacher_disagreement_score":0.37801737,"about_ca_system_score_codex":0.000024768213,"about_ca_system_score_gemma":0.000013189697,"threshold_uncertainty_score":0.29658985},"labels":[],"label_agreement":null},{"id":"W3017967689","doi":"10.1038/s41598-020-63965-x","title":"An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"CIHR Skin Research Training Centre; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Health Canada; Canadian Open Neuroscience Platform; Government of Canada; Fondation Brain Canada","keywords":"Atlas (anatomy); Brain atlas; Coefficient of variation; Standard deviation; Nuclear medicine; Medicine; Computer science; Anatomy; Artificial intelligence; Statistics; Mathematics","score_opus":0.05158695924931106,"score_gpt":0.3329099153176824,"score_spread":0.2813229560683713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017967689","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9615038,0.00002267278,0.0032729555,0.03298998,0.0005738826,0.00053139013,0.000002242023,0.00017252308,0.0009305613],"genre_scores_gemma":[0.99451566,0.0000013860663,0.0031199038,0.0015096419,0.00005382417,0.000014875962,0.000013309753,0.000016063437,0.0007553348],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99878204,0.00003121329,0.00029100862,0.00048558912,0.0002755663,0.00013460228],"domain_scores_gemma":[0.9986388,0.000020745112,0.00016849185,0.00094201637,0.000085585154,0.00014434975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019545112,0.0000820935,0.00014476314,0.000027060145,0.00012118279,0.000031766118,0.00014446829,0.000030061246,0.000062302126],"category_scores_gemma":[0.00022716998,0.000056126664,0.00009063259,0.00042803172,0.00029490748,0.000066967325,0.00008235254,0.00015703111,0.000005148766],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009045307,0.000062165775,0.00588261,0.000014810446,0.0000029261616,0.000069514164,0.00011308132,0.000020564437,0.9310837,0.00022023142,0.062013846,0.00050752074],"study_design_scores_gemma":[0.0001500834,0.000061275736,0.0057931305,0.000024541336,0.00002929341,0.00024857448,0.000030160221,0.0018128993,0.6821016,0.0028889002,0.30676046,0.00009906436],"about_ca_topic_score_codex":0.0000031937993,"about_ca_topic_score_gemma":7.205033e-7,"teacher_disagreement_score":0.24898209,"about_ca_system_score_codex":0.000009672972,"about_ca_system_score_gemma":0.00010425221,"threshold_uncertainty_score":0.2288779},"labels":[],"label_agreement":null},{"id":"W3018190643","doi":"10.1016/j.nicl.2020.102266","title":"Cingulum-Callosal white-matter microstructure associated with emotional dysregulation in children: A diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Massachusetts Institute of Technology; Canadian Institutes of Health Research; DuPont; Massachusetts General Hospital; Brain and Behavior Research Foundation","keywords":"Fractional anisotropy; Emotional dysregulation; Cingulum (brain); White matter; Diffusion MRI; Psychology; Anxiety; Mood disorders; Mood; Corpus callosum; Neuroimaging; Clinical psychology; Psychiatry; Magnetic resonance imaging; Medicine; Neuroscience","score_opus":0.053075270726928955,"score_gpt":0.3621189217190611,"score_spread":0.30904365099213216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018190643","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836296,0.000007959509,0.002220847,0.012391802,0.000038020884,0.0012628356,0.00002682053,0.00028230733,0.00013982084],"genre_scores_gemma":[0.9878961,0.000004085594,0.0028884658,0.008684382,0.00023009698,0.000029610857,0.00012476761,0.000067457666,0.00007504516],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976631,0.0001739834,0.00067929295,0.00085484417,0.0003390956,0.00028967796],"domain_scores_gemma":[0.99889684,0.00015169472,0.00021523624,0.00040972276,0.000121916404,0.00020461112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001911579,0.0002537225,0.00046192997,0.00008656815,0.00010115649,0.000041978597,0.00016238148,0.00008498607,0.000115272225],"category_scores_gemma":[0.0004808237,0.00021228846,0.00012023092,0.00043780365,0.00016698094,0.00012432484,0.00013522334,0.0009018196,0.000026590491],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019745018,0.0008406839,0.9949791,0.000006556443,0.000016070024,0.00010924843,0.00008072454,0.000025068424,0.0018760841,0.0000050989966,0.0012552362,0.00060867314],"study_design_scores_gemma":[0.0035128654,0.0005309932,0.9920795,0.000061957675,0.000081786005,0.0001131004,0.000031502594,0.0032407036,0.000018463967,0.00005227985,0.00008484432,0.00019202361],"about_ca_topic_score_codex":0.0000045537136,"about_ca_topic_score_gemma":0.0000021749918,"teacher_disagreement_score":0.0042665014,"about_ca_system_score_codex":0.000035706962,"about_ca_system_score_gemma":0.0000522998,"threshold_uncertainty_score":0.8656872},"labels":[],"label_agreement":null},{"id":"W3018777018","doi":"10.1016/j.maturitas.2020.04.012","title":"Prospective associations between physical activity levels and white matter integrity in older adults: results from the MAPT study","year":2020,"lang":"en","type":"article","venue":"Maturitas","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre Hospitalier Universitaire de Toulouse; Agence Nationale de la Recherche; Les Laboratories Pierre Fabre","keywords":"Medicine; Gerontology; Physical activity; Prospective cohort study; White matter; Internal medicine; Physical therapy; Magnetic resonance imaging","score_opus":0.07486253772604844,"score_gpt":0.35638171580147754,"score_spread":0.2815191780754291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018777018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9547934,0.000008927947,0.00027955865,0.042410996,0.000008054267,0.0011624797,0.0009015751,0.00009704113,0.00033799396],"genre_scores_gemma":[0.9978059,0.0000011770372,0.0010266737,0.00081081,0.0001720053,0.0000822907,0.00004465857,0.00001517807,0.000041333904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919003,0.000058460726,0.00013575451,0.0003538041,0.00013891516,0.00012304907],"domain_scores_gemma":[0.99934965,0.000232081,0.00007221211,0.0002474205,0.000041021103,0.00005763286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000081720325,0.000112765345,0.00022595869,0.000016269223,0.00007368078,0.000025740437,0.00008791782,0.000040933082,0.000009339297],"category_scores_gemma":[0.00014308856,0.00008031831,0.00003365489,0.00018959904,0.000043685297,0.000080737205,0.000102197206,0.00061888364,0.000016949305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011253886,0.00045449735,0.9875358,0.0000065388363,0.000025731119,0.0000059384665,0.007255032,2.0979252e-7,0.00013318897,0.00003452883,0.00356851,0.00086750666],"study_design_scores_gemma":[0.0012913451,0.00007321181,0.99648654,0.000040759867,0.000048948074,5.950966e-7,0.00047772462,0.00008701963,0.000327096,0.0009424195,0.00014506881,0.00007928886],"about_ca_topic_score_codex":0.00016109293,"about_ca_topic_score_gemma":0.000021425622,"teacher_disagreement_score":0.0430125,"about_ca_system_score_codex":0.0000457009,"about_ca_system_score_gemma":0.000014106644,"threshold_uncertainty_score":0.32752857},"labels":[],"label_agreement":null},{"id":"W3019621902","doi":"10.3171/2020.2.jns193177","title":"Dissecting the default mode network: direct structural evidence on the morphology and axonal connectivity of the fifth component of the cingulum bundle","year":2020,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Cingulum (brain); Default mode network; Precuneus; Neuroscience; Medicine; Anatomy; Functional connectivity; White matter; Magnetic resonance imaging; Biology; Functional magnetic resonance imaging; Fractional anisotropy; Radiology","score_opus":0.12761878272212182,"score_gpt":0.34515009010465486,"score_spread":0.21753130738253304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3019621902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776192,0.0002158744,0.00025628362,0.0213805,0.00024887294,0.00022777477,0.0000063927773,0.000010695594,0.00003443116],"genre_scores_gemma":[0.99757624,0.000106243046,0.00006603971,0.0020362227,0.00019206312,0.000003574513,1.10347344e-7,0.000012200002,0.0000072841854],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99892443,0.00019198666,0.00037293945,0.000115073366,0.0002622924,0.00013329452],"domain_scores_gemma":[0.99685556,0.0021292176,0.00055300945,0.00029829264,0.0001189279,0.000045002515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003398381,0.0001029533,0.00027447514,0.000018275805,0.0001944913,0.000009932192,0.00025281278,0.000024524265,0.0000045204542],"category_scores_gemma":[0.0011815605,0.000041501207,0.00018349876,0.00026268384,0.00027166918,0.000045657387,0.00012949339,0.00054937846,7.194565e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079679827,0.00016292861,0.45329034,0.00013730113,0.000112428796,0.000031932737,0.0007790465,0.019848656,0.5148182,0.0010873046,0.0073527154,0.0015823726],"study_design_scores_gemma":[0.00026265916,0.00036625325,0.9359172,0.00056041573,0.00013994573,0.0008978816,0.00008953388,0.013206715,0.045898404,0.0015696958,0.0009886409,0.00010267614],"about_ca_topic_score_codex":0.000009240442,"about_ca_topic_score_gemma":0.000001628396,"teacher_disagreement_score":0.48262683,"about_ca_system_score_codex":0.00001326824,"about_ca_system_score_gemma":0.00004071534,"threshold_uncertainty_score":0.23868065},"labels":[],"label_agreement":null},{"id":"W3020957360","doi":"10.1101/2020.05.01.064576","title":"Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"National Institutes of Health","keywords":"Semantic dementia; Frontotemporal lobar degeneration; Frontotemporal dementia; Primary progressive aphasia; White matter; Atrophy; Psychology; Neuroscience; Neuroimaging; Dementia; Diffusion MRI; Voxel-based morphometry; Cognitive decline; Cognition; Voxel; Pathology; Executive dysfunction; Disease; Medicine; Neuropsychology; Magnetic resonance imaging; Radiology","score_opus":0.05855679745492247,"score_gpt":0.3123917869707199,"score_spread":0.2538349895157974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3020957360","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9896781,0.0006298601,0.007273545,0.00043729244,0.000035221296,0.0013144814,0.00046808698,0.00014088042,0.000022555418],"genre_scores_gemma":[0.9954407,0.00022534365,0.003905845,0.00012705113,0.00007633231,0.00015353065,0.0000021154365,0.0000678081,0.0000012498309],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985634,0.000061088926,0.00040257073,0.0005197143,0.00025569473,0.00019751271],"domain_scores_gemma":[0.99846095,0.00010635741,0.00033454798,0.0006014054,0.0003669639,0.00012976867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017582734,0.00030693802,0.00049511675,0.00010421242,0.000057878842,0.000019400879,0.00016150305,0.00016761501,0.000046182824],"category_scores_gemma":[0.00017049945,0.00024072685,0.00017743216,0.00022549977,0.00017153464,0.000041692227,0.0002051272,0.00047989364,0.000005278023],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049521425,0.00058386463,0.6161366,0.00090715644,0.0008360079,0.000066466724,0.000028373248,0.000015940479,0.3793175,0.00077548175,0.00078495895,0.000052448497],"study_design_scores_gemma":[0.00044489856,0.0003511551,0.8940846,0.0009244111,0.00054867513,8.328608e-8,0.0000023158757,0.00031796214,0.10289617,0.000010549016,0.00015275204,0.00026644394],"about_ca_topic_score_codex":0.000054436554,"about_ca_topic_score_gemma":9.5245196e-7,"teacher_disagreement_score":0.277948,"about_ca_system_score_codex":0.00006520413,"about_ca_system_score_gemma":0.00018413836,"threshold_uncertainty_score":0.9816556},"labels":[],"label_agreement":null},{"id":"W3020977526","doi":"10.1101/2020.01.08.899583","title":"A cortical wiring space links cellular architecture, functional dynamics and hierarchies in humans","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Human brain; Tractography; Cortex (anatomy); Human Connectome Project; Cerebral cortex; Neuroimaging; Dynamics (music); Computational model; Nerve net","score_opus":0.03424715446565342,"score_gpt":0.26647884742329186,"score_spread":0.23223169295763846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3020977526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7285755,0.00053802715,0.26361254,0.00524131,0.00015544124,0.0010394608,0.00011176603,0.0006971114,0.000028785611],"genre_scores_gemma":[0.94474435,0.00023895167,0.05384919,0.00053580437,0.0002973311,0.0002100626,0.0000020723392,0.00011423431,0.0000080074315],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99787974,0.00005874551,0.00041779372,0.000979492,0.00028048974,0.00038373153],"domain_scores_gemma":[0.99857473,0.0000909103,0.00015949484,0.0007551679,0.000119464006,0.00030022376],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00017011305,0.0004159105,0.00054558,0.0002886588,0.0001276304,0.000072721064,0.00018259666,0.00040304763,0.000012064683],"category_scores_gemma":[0.00018975796,0.0004495701,0.00010523931,0.0003813722,0.00024776589,0.000047062633,0.0005002192,0.0028840192,0.0000074777063],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001904363,0.0003333694,0.06749282,0.0012307165,0.000103225626,0.00043338395,0.0000325985,0.00023847958,0.89350396,0.036223,0.0001894555,0.000028528502],"study_design_scores_gemma":[0.002190612,0.0003088993,0.83179265,0.0019508728,0.0004435451,6.037928e-7,0.000011575258,0.027750483,0.12381104,0.0007672423,0.009112739,0.0018597166],"about_ca_topic_score_codex":0.00001740796,"about_ca_topic_score_gemma":0.00000363734,"teacher_disagreement_score":0.76969296,"about_ca_system_score_codex":0.00019922225,"about_ca_system_score_gemma":0.00024633572,"threshold_uncertainty_score":0.9997956},"labels":[],"label_agreement":null},{"id":"W3021621901","doi":"10.3389/fpsyt.2020.00342","title":"Age-Related Changes of Peak Width Skeletonized Mean Diffusivity (PSMD) Across the Adult Lifespan: A Multi-Cohort Study","year":2020,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Holland Bloorview Kids Rehabilitation Hospital; Hospital for Sick Children; University of Toronto","funders":"Medical Research Council; Bundesministerium für Wissenschaft, Forschung und Wirtschaft; Bundesministerium für Bildung und Forschung; National Health and Medical Research Council; European Commission; Fondation Leducq; Agence Nationale de la Recherche; Canadian Institutes of Health Research; EU Joint Programme – Neurodegenerative Disease Research","keywords":"Cohort; Demography; Gerontology; Medicine; Psychology; Internal medicine; Sociology","score_opus":0.0323848196296587,"score_gpt":0.3353835566800775,"score_spread":0.3029987370504188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021621901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9510271,0.0006306172,0.016137242,0.027265582,0.0012337556,0.0030650909,0.00004092973,0.0003265239,0.00027317798],"genre_scores_gemma":[0.9341572,0.00020639626,0.06259886,0.0024170247,0.00014939443,0.00024264521,0.000018851493,0.000052864678,0.000156763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99841213,0.00009410532,0.00041427405,0.0004955778,0.000272813,0.00031108395],"domain_scores_gemma":[0.99888134,0.000025940451,0.00021625611,0.0006704144,0.00007620005,0.00012983456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021919938,0.00022476194,0.00051828957,0.00006452818,0.00012463106,0.000013212332,0.00033548698,0.00009015287,0.0000087871185],"category_scores_gemma":[0.00010816731,0.00017025696,0.00012054954,0.0006375491,0.0002134729,0.000045554876,0.00012744036,0.0005355113,0.0000033244723],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024270802,0.0011488016,0.9764649,0.00008390572,0.00011792283,0.000015520143,0.003824849,0.0000069325984,0.00042435105,0.00014428316,0.014394425,0.0031313796],"study_design_scores_gemma":[0.0065757404,0.00081262935,0.976939,0.0001537817,0.0002520838,0.000014239378,0.007017878,0.0035847633,0.0002351389,0.0011728002,0.0028918157,0.00035011297],"about_ca_topic_score_codex":0.00007514701,"about_ca_topic_score_gemma":0.00015686192,"teacher_disagreement_score":0.04646162,"about_ca_system_score_codex":0.000037735797,"about_ca_system_score_gemma":0.000051362887,"threshold_uncertainty_score":0.6942877},"labels":[],"label_agreement":null},{"id":"W3021820897","doi":"10.1016/j.neuroimage.2020.116884","title":"Multi-parametric quantitative in vivo spinal cord MRI with unified signal readout and image denoising","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Horizon 2020; Horizon 2020 Framework Programme; Engineering and Physical Sciences Research Council; Institut de Valorisation des Données; Spinal Research; Department of Health and Aged Care, Australian Government; Multiple Sclerosis Society; Fonds Wetenschappelijk Onderzoek; Department of Health and Social Care; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; National Multiple Sclerosis Society; Craig H. Neilsen Foundation; Natural Sciences and Engineering Research Council of Canada; Wings for Life; ASCRS Research Foundation","keywords":"Noise reduction; Singular value decomposition; Computer science; Parametric statistics; SIGNAL (programming language); Noise (video); Artificial intelligence; Pattern recognition (psychology); Image quality; Computer vision; Mathematics; Image (mathematics)","score_opus":0.1312747457715866,"score_gpt":0.3881293509769566,"score_spread":0.25685460520537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021820897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70126736,0.00014320808,0.28987053,0.0063563404,0.000013688985,0.0009965542,0.000026454865,0.00036324508,0.0009626283],"genre_scores_gemma":[0.7646878,0.00006948077,0.23347624,0.0015921751,0.000023717908,0.000022923863,0.0000044252165,0.00004225341,0.000081006365],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987811,0.000042580403,0.00023042852,0.0005283122,0.00017353156,0.00024407294],"domain_scores_gemma":[0.9993267,0.000094153525,0.00009507002,0.00023364845,0.00007304804,0.00017736896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000066025816,0.0001909293,0.0002888836,0.0001676404,0.00006897206,0.000041269395,0.00009923159,0.000036207308,0.000020061007],"category_scores_gemma":[0.00014195088,0.0001695577,0.00003361611,0.0008057301,0.00019244669,0.00016266755,0.00006950506,0.00041031238,0.000011126096],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029269184,0.00031857946,0.014151164,0.00019082446,0.000015049379,0.0014677404,0.0002370728,0.000030377947,0.9734085,0.00095040194,0.0007424549,0.0055609145],"study_design_scores_gemma":[0.018844679,0.027595252,0.4997336,0.0011084856,0.00051761226,0.0018799262,0.0013060188,0.106709786,0.31167793,0.00086501957,0.027393932,0.0023677421],"about_ca_topic_score_codex":0.000027814187,"about_ca_topic_score_gemma":0.000003870322,"teacher_disagreement_score":0.6617306,"about_ca_system_score_codex":0.00002365718,"about_ca_system_score_gemma":0.00004074362,"threshold_uncertainty_score":0.69143623},"labels":[],"label_agreement":null},{"id":"W3022230549","doi":"10.1111/gbb.12656","title":"Genetic risk for Alzheimer disease in children: Evidence from early‐life IQ and brain white‐matter microstructure","year":2020,"lang":"en","type":"article","venue":"Genes Brain & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministry of Health, British Columbia; Secretaría de Educación Superior, Ciencia, Tecnología e Innovación; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Erasmus Medisch Centrum; Erasmus Universiteit Rotterdam; ZonMw; Agence Nationale de la Recherche; Health Research","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Intelligence quotient; Medicine; Internal medicine; Physiology; Neuroscience; Cognition; Magnetic resonance imaging","score_opus":0.051463965432771715,"score_gpt":0.3338814669371,"score_spread":0.2824175015043283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022230549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9697937,0.0038154235,0.0046961354,0.019332038,0.000019014238,0.0017418194,0.00049586245,0.000105011575,0.0000010007071],"genre_scores_gemma":[0.9440389,0.0001464675,0.04384134,0.011006184,0.00023120287,0.0005446419,0.00009108487,0.00006349991,0.000036620793],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871045,0.00003867066,0.0002719779,0.00060864206,0.00012458621,0.00024568793],"domain_scores_gemma":[0.9989689,0.00014495637,0.00009270989,0.0004030957,0.000037413854,0.00035290467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047280748,0.00021095965,0.00025021503,0.000048958507,0.00008585991,0.00003408205,0.0001492273,0.0000714278,0.00009571424],"category_scores_gemma":[0.00016049681,0.00020106156,0.000084690066,0.00014529315,0.00009643133,0.000080500235,0.00007915948,0.00019981795,0.000015325275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009420303,0.000038506612,0.956308,0.000009705747,0.000011009669,0.000010559791,0.00023858123,0.000010422055,0.031724617,0.0000015754883,0.0044025662,0.007150223],"study_design_scores_gemma":[0.0007096344,0.00008264369,0.9955126,0.00004959029,0.00033920447,0.000009559715,0.000012201137,0.0001480026,0.0014572964,0.00007410836,0.001399204,0.00020595298],"about_ca_topic_score_codex":0.00009638764,"about_ca_topic_score_gemma":0.000004723721,"teacher_disagreement_score":0.03920457,"about_ca_system_score_codex":0.000012328172,"about_ca_system_score_gemma":0.00004569231,"threshold_uncertainty_score":0.8199052},"labels":[],"label_agreement":null},{"id":"W3022546824","doi":"10.1038/s41386-020-0691-2","title":"Multiparametric mapping of white matter microstructure in catatonia","year":2020,"lang":"en","type":"article","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":88,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"Catatonia; Fractional anisotropy; White matter; Psychology; Diffusion MRI; Orbitofrontal cortex; Corticospinal tract; Neuroscience; Corpus callosum; Putamen; Schizophrenia (object-oriented programming); Psychiatry; Magnetic resonance imaging; Medicine; Prefrontal cortex; Cognition; Radiology","score_opus":0.05974089286520401,"score_gpt":0.36466737453720777,"score_spread":0.30492648167200376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022546824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98408085,0.000087770626,0.0013815443,0.012849372,0.00008470891,0.0005105033,0.000015904188,0.00008407846,0.00090529164],"genre_scores_gemma":[0.97113055,0.000062099745,0.009200166,0.019427588,0.000059423197,0.000031700736,0.0000057196617,0.000026838192,0.000055907298],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991193,0.00003439895,0.00027686244,0.00031779884,0.00007027586,0.00018135335],"domain_scores_gemma":[0.99958277,0.0000420851,0.0000933642,0.00014279963,0.000039337134,0.000099647674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002582822,0.00011297232,0.00024583776,0.00017223164,0.000027263859,0.0000021806457,0.00012574601,0.00004954291,0.00024945143],"category_scores_gemma":[0.000026600364,0.00011124243,0.000050440496,0.0008135475,0.000074041825,0.00003000677,0.00007187034,0.00035129066,0.000040982773],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016158607,0.00007308704,0.20111336,0.00007566191,0.0000062096406,0.00008213259,0.00026262537,0.000045299596,0.79116315,0.0000126466675,0.006034668,0.0009695619],"study_design_scores_gemma":[0.0028177884,0.0001824053,0.9372927,0.000019069123,0.0000339441,0.00021549407,0.000022038364,0.0012110556,0.018768718,0.00007931521,0.039204527,0.00015296422],"about_ca_topic_score_codex":0.0000033489832,"about_ca_topic_score_gemma":1.2879849e-7,"teacher_disagreement_score":0.7723944,"about_ca_system_score_codex":0.000012787214,"about_ca_system_score_gemma":0.000018850935,"threshold_uncertainty_score":0.45363346},"labels":[],"label_agreement":null},{"id":"W3023084566","doi":"10.1016/j.biopsych.2020.02.379","title":"Assessing Intracortical Myelin and Neurocognitive Performance in Substance Use Disorder","year":2020,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Neurocognitive; Myelin; Schizophrenia (object-oriented programming); Neuroscience; Bipolar disorder; Psychology; Biomarker; Magnetic resonance imaging; Medicine; Cognition; Psychiatry; Central nervous system; Biology","score_opus":0.1649639880212219,"score_gpt":0.37374512140220173,"score_spread":0.20878113338097984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023084566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98153853,0.00022065618,0.0074675735,0.010123089,0.00003024018,0.00027283374,0.000003434775,0.00013603357,0.00020757984],"genre_scores_gemma":[0.96967924,0.00042628686,0.024289612,0.005466187,0.00008958396,0.000026925876,0.000008334301,0.000009434923,0.000004397223],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992404,0.000023975645,0.0001875462,0.00032757333,0.00005651377,0.00016397626],"domain_scores_gemma":[0.99966925,0.00006522645,0.00003670101,0.00009480584,0.000021751519,0.000112241134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000036077796,0.00010432085,0.00016170167,0.000021175425,0.00004536153,0.000021354996,0.000047998667,0.00006623075,0.000013298271],"category_scores_gemma":[0.00011141584,0.000077663695,0.000026633294,0.00019605996,0.000120922086,0.00013054007,0.000030969877,0.00031252508,0.000006405279],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091451824,0.00010691803,0.98714006,0.000019681562,0.0000018673708,0.0000069586536,0.000019304141,0.0000016392368,0.0014676339,0.0010771723,0.0000550077,0.010012292],"study_design_scores_gemma":[0.00041820225,0.00023483319,0.99503255,0.000047804813,0.0000076927545,0.000018977365,0.00005100412,0.0012719298,0.0000707075,0.00065025256,0.0020948756,0.00010117718],"about_ca_topic_score_codex":0.0000013349222,"about_ca_topic_score_gemma":0.0000014399599,"teacher_disagreement_score":0.01682204,"about_ca_system_score_codex":0.0000065804848,"about_ca_system_score_gemma":0.000016697999,"threshold_uncertainty_score":0.31670338},"labels":[],"label_agreement":null},{"id":"W3023831429","doi":"10.1101/2020.05.02.064840","title":"Structural alterations in the macaque frontoparietal white matter network after recovery from prefrontal cortex lesions","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Neuroscience; Lesion; Superior longitudinal fasciculus; Macaque; Prefrontal cortex; Fractional anisotropy; Psychology; Diffusion MRI; Tractography; Uncinate fasciculus; Saccade; Inferior longitudinal fasciculus; Cortex (anatomy); Posterior parietal cortex; Medicine; Magnetic resonance imaging; Cognition; Eye movement; Radiology","score_opus":0.029669665462461164,"score_gpt":0.26724888598683194,"score_spread":0.23757922052437078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023831429","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97100496,0.0006592105,0.016161151,0.0073855924,0.0005638194,0.0024876804,0.0012033826,0.0004609908,0.00007319653],"genre_scores_gemma":[0.9520118,0.00009189876,0.041292414,0.0044069146,0.0010032754,0.0010539644,0.0000125068855,0.00011297202,0.000014205787],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974906,0.0001296631,0.000586986,0.0010179082,0.000315172,0.00045968362],"domain_scores_gemma":[0.9979064,0.000078629855,0.00026251617,0.0014385572,0.000119820914,0.00019407758],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011335777,0.00050039316,0.00055804825,0.0000923773,0.000175987,0.00018921896,0.00047067172,0.00031357718,0.0002519973],"category_scores_gemma":[0.000045047833,0.0004279653,0.00020753102,0.0003239328,0.00012278954,0.00016190374,0.0004225283,0.0014980601,0.00008306242],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010518517,0.000527955,0.7469274,0.0004968594,0.00048569223,0.001076794,0.00028608937,0.0009267034,0.21423209,0.0013672903,0.03259616,0.000025114825],"study_design_scores_gemma":[0.00038156734,0.00004801379,0.9924901,0.00034022194,0.0001999102,1.8590642e-7,0.0000052051046,0.0015102096,0.0015155319,0.00013791454,0.0029094033,0.00046172593],"about_ca_topic_score_codex":0.00013740694,"about_ca_topic_score_gemma":0.000026502226,"teacher_disagreement_score":0.2455627,"about_ca_system_score_codex":0.00019267063,"about_ca_system_score_gemma":0.00026124282,"threshold_uncertainty_score":0.9998172},"labels":[],"label_agreement":null},{"id":"W3025004389","doi":"10.1038/s41598-020-64124-y","title":"Dissociating the white matter tracts connecting the temporo-parietal cortical region with frontal cortex using diffusion tractography","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Arcuate fasciculus; Neuroscience; Inferior parietal lobule; White matter; Tractography; Superior longitudinal fasciculus; Macaque; Superior parietal lobule; Anatomy; Premotor cortex; Posterior parietal cortex; Biology; Supramarginal gyrus; Diffusion MRI; Cortex (anatomy); Temporal cortex; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine; Dorsum; Fractional anisotropy","score_opus":0.05775910657762829,"score_gpt":0.31057148671502416,"score_spread":0.2528123801373959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3025004389","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9662649,0.000034330933,0.020752562,0.010962279,0.00029177265,0.00073365273,0.0000016304324,0.00016719243,0.000791672],"genre_scores_gemma":[0.9958182,0.0000012168921,0.002911365,0.0009473137,0.00011539823,0.00002073585,0.000023831692,0.00002980631,0.00013214603],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998245,0.000046749108,0.00040600836,0.000586335,0.00044505598,0.0002708254],"domain_scores_gemma":[0.99868065,0.000078345314,0.00042363777,0.0005841804,0.000097432894,0.00013575138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038071704,0.00015259173,0.00019622684,0.000034751003,0.0011404894,0.00019732925,0.00011124334,0.000043723732,0.00003341575],"category_scores_gemma":[0.00014590049,0.00008020014,0.000120178694,0.00051626336,0.0003521109,0.00013421514,0.00007072361,0.00044113855,0.0000035528085],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008474744,0.00018452946,0.8679047,0.000039977822,0.00003913747,0.00073613663,0.0034241427,0.000060361814,0.11939051,0.00009170271,0.006726518,0.0013175263],"study_design_scores_gemma":[0.0010054586,0.00034688824,0.8971746,0.00047844514,0.0007392675,0.01293289,0.0068866606,0.02220282,0.010154824,0.0022181454,0.045033917,0.0008260941],"about_ca_topic_score_codex":0.000014591335,"about_ca_topic_score_gemma":0.000005323792,"teacher_disagreement_score":0.10923568,"about_ca_system_score_codex":0.000029616582,"about_ca_system_score_gemma":0.000058328693,"threshold_uncertainty_score":0.87718374},"labels":[],"label_agreement":null},{"id":"W3026205139","doi":"10.1016/j.pscychresns.2020.111106","title":"White Matter Connectivity in Youth at Risk for Serious Mental Illness: A Longitudinal Analysis","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Ottawa; University Health Network; University of Toronto; Heart and Stroke Foundation; Sunnybrook Health Science Centre; Alberta Children's Hospital; Health Sciences Centre; Hotchkiss Brain Institute; Mental Health Research Canada; University of Calgary","funders":"National Institute of Mental Health; Fondation Brain Canada","keywords":"Fractional anisotropy; White matter; Fasciculus; Uncinate fasciculus; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Diffusion MRI; Psychology; Medicine; Internal medicine; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.13071774812324316,"score_gpt":0.4199659554645772,"score_spread":0.28924820734133405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026205139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9269371,0.00014926234,0.012290939,0.057579093,0.00007964826,0.0017442495,0.00028580063,0.00020035484,0.00073357497],"genre_scores_gemma":[0.9908599,0.00008374661,0.006796106,0.001600968,0.00017176519,0.00023075125,0.00008739164,0.000060788498,0.00010857974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99746907,0.00017341693,0.00033872193,0.00092998875,0.00044294744,0.00064585306],"domain_scores_gemma":[0.9987866,0.00014283218,0.000101995356,0.0005468378,0.00013155024,0.00029014077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049494754,0.00021075325,0.0004064775,0.00046241793,0.0004322439,0.00006277361,0.00024305182,0.00004197386,0.00010520594],"category_scores_gemma":[0.00014808078,0.00020823124,0.00024389394,0.0019929335,0.00016529535,0.0001506495,0.00027250257,0.00078163284,0.000045043405],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045068166,0.00016775099,0.9939423,0.000080744925,0.0000674149,0.000015393016,0.0006083061,0.0000710787,0.000648483,0.00005554448,0.0033507422,0.00054152095],"study_design_scores_gemma":[0.0017041129,0.00026822093,0.970343,0.000044960096,0.0003121538,0.00003850891,0.0005276352,0.022367192,0.00024370791,0.0008308604,0.0030293136,0.00029033158],"about_ca_topic_score_codex":0.00008722505,"about_ca_topic_score_gemma":0.00007434585,"teacher_disagreement_score":0.06392282,"about_ca_system_score_codex":0.0001221675,"about_ca_system_score_gemma":0.00007325679,"threshold_uncertainty_score":0.8491423},"labels":[],"label_agreement":null},{"id":"W3026323094","doi":"10.3389/fnagi.2020.00129","title":"Fitness Level Influences White Matter Microstructure in Postmenopausal Women","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Joseph’s Healthcare Hamilton; McMaster University","funders":"Canada Research Chairs; McMaster University","keywords":"Cingulum (brain); Cardiorespiratory fitness; White matter; Aerobic exercise; Diffusion MRI; Brain Structure and Function; Psychology; Neuroimaging; Transcranial magnetic stimulation; Neuroscience; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Fractional anisotropy; Physical medicine and rehabilitation; Internal medicine; Stimulation","score_opus":0.04494927487757623,"score_gpt":0.31467662526375023,"score_spread":0.269727350386174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026323094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9612001,0.00006055314,0.024705352,0.013058869,0.00024692246,0.00037849945,0.000020969823,0.00011868225,0.00021004629],"genre_scores_gemma":[0.9557243,0.000019564335,0.023462612,0.020518122,0.000030088695,0.000045783498,0.0000023650969,0.00001816313,0.0001789839],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986699,0.00002404311,0.00022316903,0.00052340014,0.0001795508,0.00037992056],"domain_scores_gemma":[0.9995427,0.000010683931,0.00006120024,0.00023243592,0.0000185655,0.00013440626],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007942886,0.00014271155,0.0002175218,0.00015716575,0.00006060421,0.00003707355,0.00030240568,0.00003544929,0.000011483031],"category_scores_gemma":[0.000057068693,0.00013534618,0.00001888526,0.0009055668,0.0002193827,0.00019339182,0.00010926552,0.00034898016,0.0000044822746],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023853523,0.000025600231,0.9561283,0.000030888303,4.0204827e-7,0.000067679255,0.0009034357,0.00026794022,0.039525278,0.000012425467,0.0023450952,0.0006690997],"study_design_scores_gemma":[0.00039512766,0.00008835587,0.9891981,0.00005017527,0.0000027782728,0.00004372893,0.00021370614,0.0024092763,0.0013725798,0.00058609375,0.0054768273,0.00016329173],"about_ca_topic_score_codex":0.000008519048,"about_ca_topic_score_gemma":6.8689974e-7,"teacher_disagreement_score":0.0381527,"about_ca_system_score_codex":0.00007642109,"about_ca_system_score_gemma":0.00005121439,"threshold_uncertainty_score":0.5519257},"labels":[],"label_agreement":null},{"id":"W3026522746","doi":"10.1016/j.neuroimage.2020.116889","title":"TractoFlow: A robust, efficient and reproducible diffusion MRI pipeline leveraging Nextflow &amp; Singularity","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":199,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs","keywords":"Tractography; Pipeline (software); Computer science; Diffusion MRI; Tensor (intrinsic definition); Diffusion; Singularity; Orientation (vector space); Data mining; Artificial intelligence; Algorithm; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.13229725443034684,"score_gpt":0.3335525059408864,"score_spread":0.20125525151053958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026522746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64759475,0.00025051454,0.3125039,0.03624686,0.00006129767,0.0007493046,0.00001873472,0.0008025763,0.0017720542],"genre_scores_gemma":[0.90408957,0.00021029274,0.08757233,0.0071771783,0.000309887,0.000026758269,0.00004701708,0.00007432145,0.0004926454],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99825597,0.000036919242,0.000282204,0.0009169908,0.00023440657,0.00027352327],"domain_scores_gemma":[0.99881446,0.000057175763,0.00008606446,0.00069853954,0.00008326653,0.00026046898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013823152,0.00020666722,0.00028461547,0.00006585453,0.00017569562,0.000053477255,0.00010960031,0.000048830967,0.000047480076],"category_scores_gemma":[0.00041231047,0.00019527542,0.00007820379,0.00033825252,0.00010057016,0.00008153347,0.00017093553,0.00047406502,0.00002358674],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029417462,0.0008221217,0.007573789,0.00032464098,0.000011789346,0.00030827703,0.00080560456,0.0015854614,0.9377271,0.00043747883,0.022234738,0.027874822],"study_design_scores_gemma":[0.0040476373,0.00049830705,0.04613135,0.0002467845,0.0002914398,0.0009719979,0.00008778968,0.30548978,0.041218657,0.00090820156,0.5991041,0.0010039393],"about_ca_topic_score_codex":0.000013318478,"about_ca_topic_score_gemma":5.851535e-7,"teacher_disagreement_score":0.89650846,"about_ca_system_score_codex":0.00002080117,"about_ca_system_score_gemma":0.000029532554,"threshold_uncertainty_score":0.79631007},"labels":[],"label_agreement":null},{"id":"W3026648707","doi":"10.1016/j.pscychresns.2020.111105","title":"White Matter Microstructural Properties Associated with Impaired Attention in Chronic Schizophrenia: A Multi-Center Study","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Splenium; Cingulum (brain); Fractional anisotropy; Schizophrenia (object-oriented programming); White matter; Medicine; Psychology; Neurocognitive; Audiology; Cardiology; Internal medicine; Neuroscience; Cognition; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.1547307103881278,"score_gpt":0.3952001869922741,"score_spread":0.2404694766041463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026648707","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9670251,0.00012746062,0.00026205098,0.03002991,0.000050035807,0.0021298847,0.0000123843065,0.00027224436,0.000090923226],"genre_scores_gemma":[0.9956881,0.000011408039,0.0026376927,0.0010543488,0.00013787315,0.00022091964,0.000025000587,0.00008656819,0.00013813748],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974018,0.00025995207,0.00037054854,0.00077971694,0.00052194914,0.0006660808],"domain_scores_gemma":[0.99903333,0.000026354066,0.000087337,0.000452187,0.00019376022,0.00020701415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027905765,0.00024759333,0.00031686676,0.00027295173,0.00024039719,0.00011338913,0.00026434602,0.00003910971,0.000033116885],"category_scores_gemma":[0.00008005944,0.0001972127,0.00007481092,0.0010537693,0.00019650412,0.00024411929,0.00020452551,0.0012097183,0.00005022264],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047820364,0.00072999625,0.97857577,0.00010008967,0.000025880405,0.000064515254,0.00030701532,0.000016762473,0.018530346,0.000003841842,0.0009608663,0.00020671212],"study_design_scores_gemma":[0.0067586787,0.0007814959,0.9859406,0.0003238172,0.000026264766,0.00007130158,0.00037370875,0.005261767,0.00012425786,0.0000342846,0.00009963218,0.00020418892],"about_ca_topic_score_codex":0.00003021826,"about_ca_topic_score_gemma":0.00006730696,"teacher_disagreement_score":0.028975561,"about_ca_system_score_codex":0.00020066505,"about_ca_system_score_gemma":0.00022918131,"threshold_uncertainty_score":0.80421007},"labels":[],"label_agreement":null},{"id":"W3026862239","doi":"10.1016/j.compbiomed.2020.103815","title":"Multi-scale segmentation in GBM treatment using diffusion tensor imaging","year":2020,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Institute for Health and Care Research; NIHR Imperial Biomedical Research Centre; University of Cambridge; Cancer Research UK; Nvidia","keywords":"Fluid-attenuated inversion recovery; Diffusion MRI; Segmentation; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine; Fractional anisotropy; Convolutional neural network; White matter; Radiation treatment planning; Image segmentation; Radiology; Pattern recognition (psychology); Radiation therapy","score_opus":0.11511095803964475,"score_gpt":0.42537756107860614,"score_spread":0.31026660303896136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026862239","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8149789,0.00053154724,0.16879204,0.015106123,0.000063650856,0.00042077803,0.000001931616,0.00006188599,0.000043157663],"genre_scores_gemma":[0.82941884,0.00057790504,0.16614205,0.0036953858,0.000100671095,0.00001736573,0.0000331216,0.0000081634735,0.0000064921333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994288,0.00002464645,0.00017034957,0.00023630638,0.000025326752,0.000114564646],"domain_scores_gemma":[0.9997355,0.000043955843,0.000037679376,0.000105598054,0.000010984217,0.00006630929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043264612,0.00009017975,0.00021036608,0.000085832835,0.000030382886,0.000001252302,0.000039335693,0.00003142403,0.0000044366507],"category_scores_gemma":[0.000023155219,0.000066579596,0.000012915059,0.00013117942,0.00012488595,0.000021140379,0.000043824777,0.000091479575,5.28501e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006380747,0.00010063785,0.74116904,0.00002168958,0.0000036615406,0.000036370995,0.00083961815,0.000017239423,0.22018878,0.000060282633,0.00007509206,0.037423767],"study_design_scores_gemma":[0.012978538,0.001168521,0.5894534,0.0005679516,0.00007269149,0.00020346182,0.00068054313,0.38641864,0.0039477525,0.0011492781,0.0030923237,0.00026693914],"about_ca_topic_score_codex":0.00005691992,"about_ca_topic_score_gemma":0.000004806352,"teacher_disagreement_score":0.38640139,"about_ca_system_score_codex":0.00005277286,"about_ca_system_score_gemma":0.0000095129335,"threshold_uncertainty_score":0.27150372},"labels":[],"label_agreement":null},{"id":"W3027797983","doi":"10.1093/schbul/sbaa030.335","title":"M23. ALTERATION OF REGIONAL CEREBRAL BLOOD FLOW MEASURED BY ARTERIAL SPIN LABELING IN PATIENTS WITH TREATMENT-RESISTANT SCHIZOPHRENIA","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Centre for Addiction and Mental Health","funders":"","keywords":"Cerebral blood flow; Antipsychotic; Positive and Negative Syndrome Scale; Schizophrenia (object-oriented programming); Putamen; Psychology; Internal medicine; Medicine; Magnetic resonance imaging; Cardiology; Nuclear medicine; Psychosis; Psychiatry; Radiology","score_opus":0.028374071167982698,"score_gpt":0.2605660444093958,"score_spread":0.2321919732414131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027797983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9886416,0.000118792064,0.0012051734,0.008673923,0.000030733372,0.0009442964,0.00015758524,0.00016428716,0.000063584244],"genre_scores_gemma":[0.9195636,0.000018604956,0.07921359,0.00046940416,0.00015530833,0.000094516,0.00040035718,0.000051261322,0.000033391614],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983712,0.000052546708,0.00046019384,0.000505393,0.00035267972,0.00025798578],"domain_scores_gemma":[0.99914956,0.000030345245,0.00019315977,0.00032932142,0.00012757386,0.0001700132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059345733,0.00026895048,0.00042144474,0.000085935615,0.000078335,0.000022904087,0.000118177864,0.000078144694,0.0001116663],"category_scores_gemma":[0.000060037437,0.00022580025,0.0000794807,0.00027943533,0.00008349864,0.00005171872,0.000030951407,0.00020281406,0.000018518636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.15811998,0.008792836,0.070485905,0.00051721133,0.0006682379,0.00012910187,0.001113917,0.00054090924,0.6952467,0.004246023,0.028970648,0.031168552],"study_design_scores_gemma":[0.30114913,0.02714761,0.23399632,0.002785821,0.0020880497,0.000082013634,0.00015827474,0.006921114,0.31755993,0.0018308378,0.102337785,0.0039431104],"about_ca_topic_score_codex":0.000035831796,"about_ca_topic_score_gemma":0.000010432161,"teacher_disagreement_score":0.37768674,"about_ca_system_score_codex":0.00005378721,"about_ca_system_score_gemma":0.00009710379,"threshold_uncertainty_score":0.9207867},"labels":[],"label_agreement":null},{"id":"W3027998805","doi":"10.1093/schbul/sbaa031.223","title":"S157. A MULTICENTER HARMONIZED DIFFUSION TENSOR IMAGING STUDY ON THE ASSOCIATION OF WHITE MATTER STRUCTURE AND CLINICAL FUNCTIONING","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Fasciculus; Fractional anisotropy; Uncinate fasciculus; Cingulum (brain); White matter; Diffusion MRI; Inferior longitudinal fasciculus; Psychology; Superior longitudinal fasciculus; Internal medicine; Neuroscience; Medicine; Audiology; Magnetic resonance imaging; Radiology","score_opus":0.03780438445684866,"score_gpt":0.3140589004211563,"score_spread":0.27625451596430767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027998805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90169364,0.00001684882,0.0008681807,0.09639685,0.000045250443,0.00075218314,0.0000144861,0.00008751828,0.00012506415],"genre_scores_gemma":[0.9883749,0.000011462398,0.0054134447,0.0058190925,0.0001480365,0.00002390608,0.0000074937243,0.000025062283,0.00017659231],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888617,0.00011302485,0.0003379519,0.00032104403,0.00021023254,0.00013156564],"domain_scores_gemma":[0.9991696,0.00020449031,0.00021790851,0.00024269709,0.00008878894,0.00007655199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018460925,0.00013023331,0.00024092456,0.0000316788,0.00017569386,0.000021244356,0.000078351615,0.000041391155,0.0002905427],"category_scores_gemma":[0.0002963328,0.000087403314,0.000072611176,0.0001100739,0.00004516326,0.000018115506,0.00012195966,0.00043363078,0.000035550365],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081553427,0.00015478142,0.98862606,0.00001228737,0.000029467545,0.0000038850817,0.00023708196,0.00000136579,0.002193486,0.000029856688,0.006803902,0.0010922712],"study_design_scores_gemma":[0.0031688232,0.00020518604,0.98629344,0.00005342077,0.00013916373,0.0000044637777,0.00022234104,0.00079416425,0.00025042615,0.000048978818,0.008724789,0.0000948322],"about_ca_topic_score_codex":0.0000041367334,"about_ca_topic_score_gemma":5.211626e-7,"teacher_disagreement_score":0.09057775,"about_ca_system_score_codex":0.000021970622,"about_ca_system_score_gemma":0.00001011894,"threshold_uncertainty_score":0.35642037},"labels":[],"label_agreement":null},{"id":"W3028002316","doi":"10.1093/schbul/sbaa028.029","title":"O5.6. ADVANCED DIFFUSION IMAGING IN PSYCHOSIS RISK: A CROSS-SECTIONAL AND LONGITUDINAL STUDY OF WHITE MATTER DEVELOPMENT","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Psychosis; Prodrome; Magnetic resonance imaging; Fractional anisotropy; Population; Diffusion MRI; Psychology; Neuroimaging; Brain size; Human Connectome Project; Medicine; Neuroscience; Physiology; Internal medicine; Psychiatry; Radiology","score_opus":0.04204082862059,"score_gpt":0.33206056112335847,"score_spread":0.29001973250276847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028002316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993736,0.000080241596,0.002159343,0.0031602327,0.000023896162,0.000601798,0.000007428692,0.000083795974,0.00014720928],"genre_scores_gemma":[0.96332794,0.000027087593,0.03604605,0.00036149836,0.000039483042,0.00011953652,0.000008038073,0.000025743242,0.000044607677],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998694,0.000029669589,0.00041199173,0.00048329466,0.0002071781,0.00017386493],"domain_scores_gemma":[0.999442,0.000032108444,0.00014723759,0.00020824386,0.00006175089,0.00010869398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009049468,0.00016084457,0.00023745878,0.000100961624,0.00015533017,0.000016722086,0.00009074569,0.000029905435,0.0002066105],"category_scores_gemma":[0.00004069136,0.0001514975,0.000035407345,0.00021369675,0.00006261294,0.00003611314,0.00016980145,0.00028056154,0.000034237673],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008000451,0.00031455228,0.99406344,0.00003170926,0.000007424973,0.0000103976045,0.0003957169,0.000017882618,0.0012381164,0.000011426973,0.0002556579,0.0028536413],"study_design_scores_gemma":[0.0031104258,0.00013468065,0.99237424,0.000051627103,0.000014717873,0.00002146153,0.00007336956,0.0001003021,0.00031732308,0.00008132781,0.003588371,0.00013217336],"about_ca_topic_score_codex":0.000024688128,"about_ca_topic_score_gemma":0.000009213497,"teacher_disagreement_score":0.03388671,"about_ca_system_score_codex":0.000028398108,"about_ca_system_score_gemma":0.00001928874,"threshold_uncertainty_score":0.6177889},"labels":[],"label_agreement":null},{"id":"W3028068931","doi":"10.1038/s41366-020-0582-y","title":"Inflammatory agents partially explain associations between cortical thickness, surface area, and body mass in adolescents and young adulthood","year":2020,"lang":"en","type":"article","venue":"International Journal of Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Internal medicine; Body mass index; Medicine; Endocrinology; Cerebral cortex; Body surface area; Precentral gyrus; Magnetic resonance imaging","score_opus":0.050980610371409024,"score_gpt":0.33661345225046235,"score_spread":0.28563284187905336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028068931","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98202586,0.000045554672,0.012263402,0.005398207,0.0000567223,0.00012743544,0.000027243857,0.000019061757,0.00003652993],"genre_scores_gemma":[0.99606264,0.0001468372,0.003146984,0.00047973756,0.000139613,0.0000013777777,0.000008226943,0.000008541288,0.000006072824],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990329,0.000044490112,0.0003737269,0.00012865514,0.0003226252,0.00009756379],"domain_scores_gemma":[0.9992975,0.0000477362,0.00022149792,0.000055257937,0.00022040456,0.00015758898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017906069,0.00008218045,0.00019862904,0.000049978382,0.000040512823,0.00002685632,0.00011177526,0.000048357466,0.0000064675787],"category_scores_gemma":[0.00031290497,0.00007892874,0.000039201706,0.00006210315,0.00004452553,0.00015766236,0.0000632796,0.00037012962,0.0000014213867],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055114226,0.0000785453,0.9951345,0.000011408252,0.000032691,0.000095226584,0.00016965269,0.000011834526,0.0038298855,0.00013882807,0.00015563486,0.0002866861],"study_design_scores_gemma":[0.0009361126,0.000063394255,0.9961822,0.00017327833,0.000038716345,0.000059768434,0.000045631605,0.0007988046,0.0008347482,0.0005797172,0.00022491199,0.00006271727],"about_ca_topic_score_codex":0.0000068222153,"about_ca_topic_score_gemma":0.0000040784653,"teacher_disagreement_score":0.014036766,"about_ca_system_score_codex":0.0000693524,"about_ca_system_score_gemma":0.00005529797,"threshold_uncertainty_score":0.32186207},"labels":[],"label_agreement":null},{"id":"W3028115645","doi":"10.1093/schbul/sbaa030.367","title":"M55. STRUCTURAL CHANGES RELEVANT TO MUSICAL DEFICITS IN SCHIZOPHRENIA","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Schizophrenia (object-oriented programming); Fractional anisotropy; Psychology; Gyrification; Audiology; Diffusion MRI; Cognition; Neuroscience; Positive and Negative Syndrome Scale; Tractography; Psychiatry; Psychosis; Medicine; Magnetic resonance imaging; Cerebral cortex","score_opus":0.0482970804247953,"score_gpt":0.3096000113988383,"score_spread":0.261302930974043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028115645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7843265,0.00014980401,0.0013132158,0.21189684,0.00007666119,0.0010202238,0.00003592585,0.00056500174,0.0006158374],"genre_scores_gemma":[0.8925315,0.000036357604,0.096004404,0.010610477,0.00044737416,0.00014260122,0.00003008293,0.000066725945,0.0001304597],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981339,0.0000415909,0.0003496471,0.0007231231,0.00030136437,0.00045039854],"domain_scores_gemma":[0.9988634,0.0000666184,0.00007625896,0.00046605538,0.00006845871,0.00045922966],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000905232,0.00029124253,0.00044036112,0.0001586313,0.00009606614,0.00003209354,0.0002590897,0.00010251596,0.00037514293],"category_scores_gemma":[0.00034085743,0.0002677105,0.00008862552,0.0006121543,0.00007158146,0.00002639043,0.00020771929,0.0005910854,0.0005775579],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.028298194,0.0006619054,0.0072991787,0.00070343097,0.00012313908,0.001660783,0.0026508681,0.0004274591,0.37471968,0.063978285,0.18358244,0.3358946],"study_design_scores_gemma":[0.012160408,0.0023669205,0.10283677,0.00067954126,0.00016015518,0.00045805788,0.00020553257,0.0024690465,0.02610255,0.005037653,0.84570295,0.0018204268],"about_ca_topic_score_codex":0.0000258975,"about_ca_topic_score_gemma":0.000025187433,"teacher_disagreement_score":0.6621205,"about_ca_system_score_codex":0.00005700027,"about_ca_system_score_gemma":0.00005910776,"threshold_uncertainty_score":0.9999775},"labels":[],"label_agreement":null},{"id":"W3028304957","doi":"10.1093/schbul/sbaa030.472","title":"M160. INVESTIGATING STRUCTURAL CONNECTIVITY CORRELATES OF VERBAL MEMORY DEFICITS AMONG FIRST-EPISODE PSYCHOSIS PATIENTS","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University","funders":"","keywords":"Tractography; Fractional anisotropy; Psychology; White matter; Verbal memory; Psychosis; Cognition; Schizophrenia (object-oriented programming); Wechsler Adult Intelligence Scale; Audiology; Cognitive psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.0334144047036408,"score_gpt":0.27990410711341634,"score_spread":0.24648970240977555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028304957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99326575,0.000075116935,0.0006283338,0.0045555243,0.00007458422,0.00059956533,0.000046409466,0.00028368493,0.00047105463],"genre_scores_gemma":[0.9807918,0.000012402048,0.018196307,0.0007403907,0.000088935405,0.000056216766,0.000046116536,0.000042079882,0.000025734864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998631,0.000038528837,0.00039193168,0.0004433846,0.00025409012,0.0002410749],"domain_scores_gemma":[0.9989336,0.00013881546,0.0002560909,0.00032388078,0.000117436524,0.00023016929],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006426166,0.00022111765,0.0003679465,0.00004981306,0.0001514784,0.000013500512,0.00016982073,0.00009078448,0.00021342961],"category_scores_gemma":[0.0004923174,0.00021038277,0.00011938668,0.00028028805,0.00021807101,0.00004994892,0.00011068645,0.00040156004,0.000033750603],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047647813,0.00009343493,0.98438853,0.00016636273,0.000035759484,0.000004838321,0.00026030026,0.00011735735,0.0010519644,0.00059662963,0.0067890463,0.006019315],"study_design_scores_gemma":[0.0043413565,0.00081392546,0.9650152,0.00042882853,0.00018144753,0.000015374695,0.000070200156,0.004323587,0.018386753,0.0017541517,0.004125079,0.00054412],"about_ca_topic_score_codex":0.00013185857,"about_ca_topic_score_gemma":0.0000144445585,"teacher_disagreement_score":0.019373337,"about_ca_system_score_codex":0.000029578205,"about_ca_system_score_gemma":0.000015022023,"threshold_uncertainty_score":0.85791606},"labels":[],"label_agreement":null},{"id":"W3028433604","doi":"10.1016/j.neuroimage.2020.116968","title":"Virtual histology of multi-modal magnetic resonance imaging of cerebral cortex in young men","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":66,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"National Institutes of Health; National Institute of Mental Health; Medical Research Council; University of Bristol; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"Fractional anisotropy; Magnetization transfer; Myelin; Magnetic resonance imaging; White matter; Neuroscience; Nuclear magnetic resonance; Psychology; Medicine; Central nervous system; Radiology; Physics","score_opus":0.04138358293079613,"score_gpt":0.3167914785572872,"score_spread":0.27540789562649104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028433604","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9623772,0.001281891,0.014142275,0.008574727,0.00009066999,0.0012415547,0.00009550747,0.0003144644,0.011881744],"genre_scores_gemma":[0.98788464,0.00006026531,0.011236892,0.0005863878,0.000024805551,0.00001902316,0.0000071187237,0.000030546318,0.00015031638],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998889,0.00003702902,0.00038744096,0.00035133178,0.00014158373,0.0001935856],"domain_scores_gemma":[0.99937105,0.000047772235,0.00012714643,0.00031717893,0.000058081165,0.00007876337],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004842967,0.00012715696,0.00033594854,0.000084867715,0.000018641786,0.00000249134,0.00016015673,0.000031062493,0.000046702025],"category_scores_gemma":[0.00013829388,0.00013385557,0.00006431991,0.00027486365,0.00021535595,0.00006365167,0.00009754307,0.0002563523,0.0000047185376],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022003741,0.00027300997,0.24224567,0.000080695914,0.0000019575266,0.00014036759,0.00039068554,0.000010047883,0.7383316,0.0010179994,0.0011607739,0.01612715],"study_design_scores_gemma":[0.002567329,0.0006058043,0.93710244,0.0000639615,0.00003661105,0.00013079452,0.000086193984,0.028988134,0.024807772,0.00011593647,0.0053172163,0.00017778053],"about_ca_topic_score_codex":0.00005886001,"about_ca_topic_score_gemma":0.0000037092082,"teacher_disagreement_score":0.7135238,"about_ca_system_score_codex":0.000021047399,"about_ca_system_score_gemma":0.000037264657,"threshold_uncertainty_score":0.5458472},"labels":[],"label_agreement":null},{"id":"W3028537570","doi":"10.1016/j.schres.2020.04.016","title":"Thalamic and striato-pallidal volumes in schizophrenia patients and individuals at risk for psychosis: A multi-atlas segmentation study","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"Japan Society for the Promotion of Science; Japan Agency for Medical Research and Development","keywords":"Globus pallidus; Putamen; Psychosis; Psychology; Thalamus; Neuroscience; Striatum; Schizophrenia (object-oriented programming); Basal ganglia; Caudate nucleus; Neuroimaging; Medicine; Psychiatry; Central nervous system; Dopamine","score_opus":0.13793972385796965,"score_gpt":0.4255632434515125,"score_spread":0.2876235195935428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028537570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9927256,0.00031395242,0.000598031,0.0016471077,0.000018216184,0.004425402,0.00016249873,0.00009884193,0.000010347829],"genre_scores_gemma":[0.9663001,0.00037969896,0.03199675,0.00009377542,0.000070463895,0.0009961587,0.000070978385,0.000045273267,0.00004680516],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977985,0.00020279404,0.0003698824,0.0007445888,0.00048802333,0.0003961993],"domain_scores_gemma":[0.9989165,0.0002699288,0.00010338511,0.00028157744,0.00016781503,0.0002607589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005587827,0.00019966159,0.00031957298,0.00027977923,0.0003274906,0.00007446199,0.00015480109,0.00008242966,0.00001051651],"category_scores_gemma":[0.0004706789,0.00018466718,0.000042756303,0.0005456496,0.0001514454,0.00013944866,0.0002869162,0.00057245407,0.0000102677795],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002953973,0.00066274015,0.9611058,0.000096314645,0.000045822188,0.0000047784224,0.0010265007,0.0000026486769,0.00261105,0.00007974261,0.00078226853,0.030628309],"study_design_scores_gemma":[0.02458779,0.0018840665,0.96586037,0.000078395424,0.000071618524,0.0000041277485,0.0006110317,0.0034824586,0.0015935869,0.0010721812,0.0005161644,0.00023818418],"about_ca_topic_score_codex":0.00007078624,"about_ca_topic_score_gemma":0.000098864846,"teacher_disagreement_score":0.03139872,"about_ca_system_score_codex":0.000079098136,"about_ca_system_score_gemma":0.000055706114,"threshold_uncertainty_score":0.75305086},"labels":[],"label_agreement":null},{"id":"W3029385835","doi":"10.1371/journal.pone.0233645","title":"Freewater estimatoR using iNtErpolated iniTialization (FERNET): Characterizing peritumoral edema using clinically feasible diffusion MRI data","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health","keywords":"Initialization; Diffusion MRI; Estimator; Tractography; Computer science; Magnetic resonance imaging; Edema; Compartment (ship); Medicine; Radiology; Biomedical engineering; Algorithm; Mathematics; Surgery; Statistics","score_opus":0.47849369363589145,"score_gpt":0.4139731804885342,"score_spread":0.06452051314735724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029385835","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8849809,0.000025887812,0.11030881,0.003467188,0.00002453454,0.00062064483,0.000060912113,0.0004331735,0.0000779084],"genre_scores_gemma":[0.7629177,0.000038209197,0.23410754,0.0021332982,0.00028352704,0.000008978882,0.00043646514,0.00005993851,0.00001435676],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846375,0.000039987386,0.00049199315,0.000522087,0.00025140672,0.00023076305],"domain_scores_gemma":[0.998846,0.000030932755,0.00019428431,0.0006219717,0.000113724374,0.00019311393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010351396,0.00017598197,0.00037692222,0.000060846873,0.0001740062,0.00007493933,0.00026339773,0.0000786762,0.00007803473],"category_scores_gemma":[0.00024681483,0.00017149227,0.00004179056,0.00024218074,0.00008224546,0.0003202856,0.0006222643,0.00027003224,0.000016902979],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015938103,0.0006346423,0.01965405,0.00016761143,0.000044165452,0.000031559965,0.00013396345,0.000008138789,0.97876865,0.000044181415,0.00007016968,0.0002834906],"study_design_scores_gemma":[0.0008430574,0.0002238916,0.001776902,0.0010525411,0.0004038985,0.000041645486,0.000026492526,0.9365157,0.058325905,0.00013876658,0.00038377105,0.00026743687],"about_ca_topic_score_codex":0.000023735518,"about_ca_topic_score_gemma":4.5761558e-7,"teacher_disagreement_score":0.9365076,"about_ca_system_score_codex":0.000048085978,"about_ca_system_score_gemma":0.00007882085,"threshold_uncertainty_score":0.6993252},"labels":[],"label_agreement":null},{"id":"W3029732117","doi":"10.1002/jmri.27203","title":"Longitudinal Structural <scp>MRI</scp> in Neurologically Healthy Adults","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University College London Hospitals NHS Foundation Trust; Canadian Institutes of Health Research; UK Dementia Research Institute; National Institute for Health and Care Research; Alzheimer's Society; Wellcome Trust; Medical Research Council; Canadian Institute for Advanced Research; CHDI Foundation; Auburn University; Cure Huntington's Disease Initiative","keywords":"Fractional anisotropy; Intraclass correlation; Diffusion MRI; Magnetic resonance imaging; Nuclear medicine; Medicine; Psychology; Mathematics; Radiology; Statistics; Reproducibility","score_opus":0.041494978350020285,"score_gpt":0.3272383641464254,"score_spread":0.28574338579640507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3029732117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94130224,0.012017089,0.003390199,0.04202135,0.00008832632,0.0003705792,0.000004839598,0.000073120376,0.0007322714],"genre_scores_gemma":[0.9624849,0.00089111814,0.029149048,0.007119072,0.00028810214,0.000007378733,0.000001172733,0.000024864432,0.000034375393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983698,0.000045910274,0.00064125704,0.0002830182,0.0003311996,0.0003287726],"domain_scores_gemma":[0.9989234,0.00015224598,0.00031132184,0.00018793148,0.00017179678,0.000253295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015444228,0.00016574783,0.00037931508,0.00011226424,0.000053131855,0.000026979356,0.00023549347,0.000033844626,0.000023861736],"category_scores_gemma":[0.00054651557,0.00013604031,0.000112583686,0.00036928413,0.000103225975,0.00015933231,0.00006942714,0.0007338807,0.000005124152],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010206426,0.00014475801,0.71876425,0.00013345211,0.000004226386,0.0025013306,0.00050776947,0.00013488544,0.0042443713,0.00031919128,0.006596388,0.26562873],"study_design_scores_gemma":[0.002680006,0.002029281,0.9092,0.00022459433,0.000029698736,0.0021655958,0.00010495784,0.01056237,0.00026186375,0.00091967726,0.07174065,0.00008130001],"about_ca_topic_score_codex":0.0000075587886,"about_ca_topic_score_gemma":0.0000010473085,"teacher_disagreement_score":0.26554742,"about_ca_system_score_codex":0.000040329454,"about_ca_system_score_gemma":0.00008650338,"threshold_uncertainty_score":0.5547563},"labels":[],"label_agreement":null},{"id":"W3030622902","doi":"10.3760/cma.j.issn.0254-1424.2014.04.006","title":"Diffusion tensor imaging and the Montreal cognitive assessment for assessing severe traumatic brain injury","year":2014,"lang":"en","type":"article","venue":"Zhonghua wuli yixue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Superior longitudinal fasciculus; White matter; Fasciculus; Psychology; Traumatic brain injury; Medicine; Internal capsule; Audiology; Neuroscience; Cognition; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.03697124716353998,"score_gpt":0.37579117782277427,"score_spread":0.33881993065923427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3030622902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41329768,0.00016928054,0.54226255,0.03273204,0.00010391443,0.002947467,0.00005477369,0.0004497861,0.007982531],"genre_scores_gemma":[0.97138107,0.00003796212,0.023924524,0.0035367378,0.00017778076,0.00034834337,0.00004440881,0.000049647326,0.0004995418],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99878204,0.00009305504,0.00028325868,0.0003840846,0.00018406963,0.00027348992],"domain_scores_gemma":[0.9982503,0.0010471481,0.00015676976,0.00032369627,0.000116825206,0.000105249164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041976265,0.00020412642,0.00034732372,0.00006982303,0.00037671498,0.00009544513,0.000101784855,0.00004538695,0.000011013778],"category_scores_gemma":[0.0003968723,0.00013965598,0.00010572418,0.00013200913,0.00024351655,0.00015390843,0.00008296821,0.00026481456,0.0000029604143],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061660353,0.00048406585,0.033237383,0.00042533717,0.000090714835,0.000014438744,0.0011529389,0.000009124203,0.010166488,0.013197808,0.010655919,0.92994916],"study_design_scores_gemma":[0.022782514,0.00054478686,0.61258394,0.0018885027,0.0010951696,0.00066201744,0.0032896935,0.25807863,0.0017428222,0.065004855,0.031159645,0.0011674416],"about_ca_topic_score_codex":0.00004662744,"about_ca_topic_score_gemma":0.000005161248,"teacher_disagreement_score":0.92878175,"about_ca_system_score_codex":0.000040067946,"about_ca_system_score_gemma":0.00003691214,"threshold_uncertainty_score":0.56950057},"labels":[],"label_agreement":null},{"id":"W3031362040","doi":"10.3760/cma.j.issn.1674-6554.2019.03.001","title":"Brain structural network changes in Parkinson's disease with mild cognitive impairment: a diffusion tensor imaging study","year":2019,"lang":"en","type":"article","venue":"Zhonghua xingwei yixue yu naokexue zazhi","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Cognition; Parkinson's disease; Cognitive impairment; Montreal Cognitive Assessment; Neurology; Psychology; Medicine; Internal medicine; Audiology; Neuroscience; Disease; Magnetic resonance imaging; Radiology","score_opus":0.021327565241089454,"score_gpt":0.30913904425309796,"score_spread":0.2878114790120085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031362040","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898526,0.00036920034,0.0004889696,0.0043724794,0.000117743504,0.0040501743,0.00004611951,0.0004167217,0.0002860085],"genre_scores_gemma":[0.99419904,0.00003811548,0.0017547528,0.0022353823,0.00030706296,0.00042941677,0.00008770033,0.000114296054,0.00083426404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973755,0.00010953661,0.0003571203,0.00095868984,0.0004561422,0.0007430334],"domain_scores_gemma":[0.9984101,0.00023099803,0.00021463643,0.0006891285,0.00012999293,0.00032512037],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002364504,0.00045355663,0.0005608504,0.0002690097,0.00021643988,0.0000679357,0.00022536587,0.00005789207,0.00010487652],"category_scores_gemma":[0.00007448947,0.00037184963,0.00009663959,0.00071388605,0.00012578286,0.00019996587,0.00020471099,0.000561764,0.000041202555],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011119078,0.0004409946,0.9928014,0.00008624025,0.000035271136,0.00034723157,0.0005263295,0.00008581672,0.0003702495,0.00007771711,0.00062619004,0.0034906114],"study_design_scores_gemma":[0.00585234,0.00078560563,0.97983074,0.0008885079,0.00015831242,0.000080890364,0.00093132065,0.004405617,0.00015769592,0.00040519985,0.005965145,0.0005385986],"about_ca_topic_score_codex":0.00010378796,"about_ca_topic_score_gemma":0.00010112624,"teacher_disagreement_score":0.012970673,"about_ca_system_score_codex":0.00013655535,"about_ca_system_score_gemma":0.00008554572,"threshold_uncertainty_score":0.99987334},"labels":[],"label_agreement":null},{"id":"W3031445639","doi":"10.1093/brain/awaa140","title":"Slow blood-to-brain transport underlies enduring barrier dysfunction in American football players","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Izaak Walton Killam Health Centre; Dalhousie University; McGill University","funders":"Canadian Institutes of Health Research; European Commission; National Institutes of Health; National Institute on Aging; Nova Scotia Health Research Foundation; Israel Science Foundation; School of Medicine, Boston University","keywords":"Blood–brain barrier; Football; Neuroscience; American football; Psychology; Football players; Medicine; History; Central nervous system","score_opus":0.053116205411711165,"score_gpt":0.3158144215079702,"score_spread":0.262698216096259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031445639","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8408758,0.000021082365,0.05522186,0.10109546,0.000023794015,0.0006386832,0.000018305134,0.0004496153,0.0016553993],"genre_scores_gemma":[0.96616966,0.000010462731,0.010678428,0.022279529,0.000093878836,0.00009398544,0.000019822537,0.000036465135,0.00061775564],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990385,0.000019434961,0.00020947134,0.00035856158,0.00014623058,0.00022777241],"domain_scores_gemma":[0.99942863,0.00007938125,0.000046810892,0.00021486913,0.000017689377,0.00021261383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008119587,0.00013524579,0.00022111431,0.00010221618,0.00004657738,0.000007127961,0.000090393,0.000032188054,0.00003180219],"category_scores_gemma":[0.0001384088,0.00013896855,0.00006268041,0.0004920246,0.00006334675,0.00005429618,0.00002141249,0.00022201489,0.000016259019],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005655614,0.000359903,0.12431955,0.00022849922,0.0000983163,0.0006940119,0.003657012,0.00104394,0.7778184,0.0052659065,0.027060265,0.058888625],"study_design_scores_gemma":[0.004995509,0.0019213437,0.45819673,0.00028770138,0.000175932,0.00021587509,0.001452953,0.0028417627,0.058823347,0.0014348519,0.46866402,0.0009899852],"about_ca_topic_score_codex":0.000054071355,"about_ca_topic_score_gemma":0.000031757776,"teacher_disagreement_score":0.71899503,"about_ca_system_score_codex":0.00003701617,"about_ca_system_score_gemma":0.00003948894,"threshold_uncertainty_score":0.5666973},"labels":[],"label_agreement":null},{"id":"W3031563897","doi":"10.3390/molecules25112472","title":"White Matter Brain Network Research in Alzheimer’s Disease Using Persistent Features","year":2020,"lang":"en","type":"article","venue":"Molecules","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Shanxi Provincial Key Research and Development Project; National Key Research and Development Program of China; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; H. Lundbeck A/S; Servier; Genentech; IXICO; North University of China; National Institutes of Health; Natural Science Foundation of Shanxi Province; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Persistent homology; Neuroscience; Connectome; Disease; Psychology; Cognition; Connectomics; Alzheimer's disease; Computer science; Medicine; Functional connectivity; Pathology; Magnetic resonance imaging","score_opus":0.2368974460481099,"score_gpt":0.4271473711546619,"score_spread":0.190249925106552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031563897","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32096666,0.0074698655,0.015347549,0.6446054,0.000058127724,0.0022089651,0.000033830725,0.00042284082,0.008886797],"genre_scores_gemma":[0.9687028,0.000018623763,0.0170452,0.013868112,0.000163319,0.000044638375,0.000016232567,0.000032860138,0.00010820366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911785,0.000055821994,0.00011172842,0.0002760681,0.0001822609,0.00025624994],"domain_scores_gemma":[0.99949217,0.000032859505,0.00001990373,0.00023083053,0.00003782034,0.00018644515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008397019,0.00008497393,0.000115029536,0.0000544976,0.00007696531,0.000019527031,0.000094037874,0.000026748394,0.00004049852],"category_scores_gemma":[0.000026250715,0.000079263795,0.000066822555,0.0003495901,0.00007285234,0.000028086846,0.00009723821,0.0002804489,0.000026238631],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008509787,0.00035726154,0.5705575,0.00024083134,0.00010646057,0.001279712,0.00090782315,0.013229388,0.017134832,0.00527139,0.3848925,0.0051713353],"study_design_scores_gemma":[0.0016240561,0.00036754893,0.861503,0.00075190107,0.00028237168,0.000102756,0.00031409165,0.042298235,0.0019030069,0.008171163,0.08196235,0.0007194927],"about_ca_topic_score_codex":0.000010900047,"about_ca_topic_score_gemma":0.0000010244421,"teacher_disagreement_score":0.64773613,"about_ca_system_score_codex":0.000025274416,"about_ca_system_score_gemma":0.000034719393,"threshold_uncertainty_score":0.3232284},"labels":[],"label_agreement":null},{"id":"W3032589417","doi":"10.1101/2020.05.26.116152","title":"Plis de passage in the Superior Temporal Sulcus: Morphology and local connectivity","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Agence Nationale de la Recherche; Aix-Marseille Université","keywords":"Human Connectome Project; Sulcus; Central sulcus; Morphology (biology); Anatomy; Biology; Functional connectivity; Neuroscience; Cartography; Geology; Geography; Paleontology","score_opus":0.04102571676518483,"score_gpt":0.2898513356119279,"score_spread":0.24882561884674306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032589417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9574673,0.00035126065,0.030273678,0.010169146,0.00007002623,0.0011459918,0.0001279639,0.00038449737,0.000010111503],"genre_scores_gemma":[0.9838952,0.0002119565,0.012903473,0.0022959877,0.00016661677,0.00045214174,6.424583e-7,0.00007293144,0.0000010868531],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981744,0.00015117374,0.00032403873,0.0007919748,0.00018188235,0.00037649684],"domain_scores_gemma":[0.99853104,0.00013303013,0.00014257008,0.0009139204,0.00009442403,0.00018498857],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00044485793,0.00033890127,0.0005139334,0.00011692329,0.00009504781,0.00005974165,0.0003096229,0.00030491236,0.000012427333],"category_scores_gemma":[0.0002283737,0.0002939919,0.000084656494,0.00034537847,0.00030598292,0.000056600365,0.0003531065,0.0012551951,0.0000058956357],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016509376,0.00046576056,0.25820315,0.0006696765,0.00007588083,0.0013763276,0.00008689123,0.000017973418,0.73168975,0.0057239565,0.0014948341,0.000030739822],"study_design_scores_gemma":[0.0013791304,0.00023880445,0.8841114,0.00039679903,0.00021440008,0.0000020215402,0.00003318825,0.002250633,0.09587532,0.00018019347,0.014525637,0.00079249655],"about_ca_topic_score_codex":0.00014675116,"about_ca_topic_score_gemma":0.0000045374904,"teacher_disagreement_score":0.6358144,"about_ca_system_score_codex":0.00016119449,"about_ca_system_score_gemma":0.00032579864,"threshold_uncertainty_score":0.99995124},"labels":[],"label_agreement":null},{"id":"W3032824173","doi":"10.1101/2020.05.29.118737","title":"Axon morphology is modulated by the local environment and impacts the non-invasive investigation of its structure-function relationship","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Vetenskapsrådet","keywords":"Axon; White matter; Soma; Corpus callosum; Magnetic resonance imaging; Diffusion MRI; Biophysics; Nuclear magnetic resonance; Neuroscience; Anatomy; Biology; Physics; Medicine","score_opus":0.035226373212578016,"score_gpt":0.25234472874585734,"score_spread":0.21711835553327932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3032824173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94565564,0.00061252277,0.043100502,0.008721039,0.00008092446,0.0014488343,0.00025173332,0.00012713532,0.0000016426535],"genre_scores_gemma":[0.9953462,0.00041415804,0.0023445748,0.0016073054,0.00008495181,0.00014038195,0.0000036444253,0.000056358454,0.0000024399887],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99854195,0.00009098253,0.00037468225,0.0005611461,0.00023666146,0.00019455233],"domain_scores_gemma":[0.99833244,0.00013256219,0.0004319962,0.0008237267,0.00013264932,0.00014662286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016741535,0.00028791738,0.0003068366,0.000064802356,0.00017352981,0.00002762177,0.00019317384,0.00027481865,0.000015124903],"category_scores_gemma":[0.00015655035,0.00020589531,0.00006504199,0.00025450482,0.000363461,0.00006117632,0.00022851312,0.0007809194,0.000006204723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003529033,0.000017651872,0.014119698,0.00014792924,0.00005929119,0.000003103833,0.000029097968,0.00010471394,0.98387265,0.00044370315,0.0011632045,0.0000036673948],"study_design_scores_gemma":[0.00030093474,0.00009869724,0.37653115,0.00013469497,0.00025598958,1.8737832e-7,0.0000046371215,0.0023772018,0.61946934,0.00014122996,0.0005040074,0.0001819358],"about_ca_topic_score_codex":0.000021892682,"about_ca_topic_score_gemma":3.0141118e-7,"teacher_disagreement_score":0.36440334,"about_ca_system_score_codex":0.00013009789,"about_ca_system_score_gemma":0.00017715506,"threshold_uncertainty_score":0.8396167},"labels":[],"label_agreement":null},{"id":"W3033410889","doi":"10.1007/s12021-020-09469-5","title":"Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer’s Disease","year":2020,"lang":"en","type":"review","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Chinese Government Scholarship; Canadian Institutes of Health Research; National Institute on Aging; Agence Nationale de la Recherche","keywords":"Computer science; Pattern recognition (psychology); Artificial intelligence; Preprocessor; Feature selection; Diffusion MRI; Voxel; Feature extraction; Smoothing; Feature (linguistics); Data mining; Magnetic resonance imaging; Computer vision; Medicine; Radiology","score_opus":0.19711400074071547,"score_gpt":0.42456733330900737,"score_spread":0.2274533325682919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033410889","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007768305,0.95946926,0.011069725,0.0006031183,0.00014660193,0.025745494,0.0010782139,0.00040953833,0.0007012102],"genre_scores_gemma":[0.0011080147,0.95487064,0.039865263,0.00008681183,0.00006653116,0.0010148127,0.0028444007,0.00011940503,0.000024138419],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99792415,0.000046851284,0.00094306207,0.00029219285,0.00066443253,0.00012928294],"domain_scores_gemma":[0.9967216,0.0001360556,0.0014200532,0.0010215136,0.00058860495,0.00011217084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022032962,0.0002615098,0.000952536,0.00016598288,0.00004816794,0.000009086775,0.00017225395,0.00007784746,0.0000061971755],"category_scores_gemma":[0.0005117783,0.00018831404,0.0002306239,0.00037622135,0.000069244175,0.000110691675,0.00005421583,0.00019539041,0.0000024063008],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050959396,0.0002619611,0.00011588566,0.024373826,0.000065674736,2.7522947e-7,0.000065491404,0.000012522329,0.0000026089608,0.0003161971,0.00155356,0.973181],"study_design_scores_gemma":[0.0022519135,0.0010155065,0.009981127,0.014793759,0.02131434,0.000014694075,0.000026816795,0.05051886,0.00006734351,0.00044000737,0.8990374,0.00053820934],"about_ca_topic_score_codex":3.809824e-7,"about_ca_topic_score_gemma":8.842273e-8,"teacher_disagreement_score":0.97264284,"about_ca_system_score_codex":0.000046713594,"about_ca_system_score_gemma":0.0004220356,"threshold_uncertainty_score":0.76792234},"labels":[],"label_agreement":null},{"id":"W3033502402","doi":"10.3389/fnins.2020.00806","title":"Corrigendum: Histological Correlates of Diffusion-Weighted Magnetic Resonance Microscopy in a Mouse Model of Mesial Temporal Lobe Epilepsy","year":2020,"lang":"en","type":"erratum","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"","keywords":"Temporal lobe; Epilepsy; Diffusion-Weighted Magnetic Resonance Imaging; Mesial temporal lobe epilepsy; Magnetic resonance imaging; Diffusion MRI; Nuclear magnetic resonance; Neuroscience; Diffusion; Psychology; Medicine; Physics; Radiology","score_opus":0.0432563520567713,"score_gpt":0.2994360851847402,"score_spread":0.2561797331279689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033502402","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3065781,0.04409971,0.53798497,0.007727096,0.07230617,0.015475045,0.0032269517,0.0014415316,0.011160406],"genre_scores_gemma":[0.3751724,0.02073697,0.4407186,0.003705942,0.00034329738,0.00056137965,0.00035895436,0.00035368427,0.1580488],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971294,0.00007127755,0.00089420954,0.000996165,0.0004867237,0.00042224364],"domain_scores_gemma":[0.9986036,0.000030182664,0.00047989693,0.00066131563,0.00007790925,0.00014708519],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012361007,0.00036004497,0.0010549506,0.00042347788,0.00005135674,0.000008555625,0.00074189017,0.00035224817,0.000006765436],"category_scores_gemma":[0.00033455458,0.00033785103,0.00014203334,0.0010361018,0.0010686797,0.000078249584,0.0002549166,0.0013867622,7.041214e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000814158,0.0011645518,0.17072563,0.0004636233,0.000002123557,0.00021320286,0.00033278618,0.00011483472,0.10123439,0.00038714017,0.7225531,0.0019944953],"study_design_scores_gemma":[0.0034255132,0.0023576547,0.032780774,0.0016540769,0.00011594635,0.00007723589,0.0000910294,0.78734684,0.010514609,0.00592978,0.15447067,0.0012358997],"about_ca_topic_score_codex":0.000039210907,"about_ca_topic_score_gemma":0.00000405118,"teacher_disagreement_score":0.787232,"about_ca_system_score_codex":0.00013712539,"about_ca_system_score_gemma":0.00041926382,"threshold_uncertainty_score":0.9999074},"labels":[],"label_agreement":null},{"id":"W3035270228","doi":"10.1111/jon.12741","title":"Learning‐Challenged Youth Show an Abnormal Relationship Between Fronto‐Parietal Myelination and Mathematical Ability","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"White matter; Myelin; Typically developing; Developmental psychology; Psychology; Audiology; Medicine; Cognitive psychology; Magnetic resonance imaging; Neuroscience; Central nervous system","score_opus":0.20074021644277756,"score_gpt":0.37663562283373336,"score_spread":0.1758954063909558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035270228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89891726,0.00006635202,0.08656027,0.0137365535,0.00002095914,0.0001849951,0.000005322626,0.000110290675,0.00039796933],"genre_scores_gemma":[0.9828971,0.000019550436,0.016334074,0.000367299,0.00033186708,0.0000027955925,0.000009130476,0.0000273783,0.000010814097],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987271,0.000103628445,0.0005029793,0.00022060318,0.00028964924,0.00015607919],"domain_scores_gemma":[0.9988291,0.00025351736,0.0003039022,0.0001560111,0.00016443008,0.00029300788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036098267,0.00013313194,0.00031429433,0.00008222163,0.00013801469,0.00004404826,0.00010497841,0.00004474254,0.000012926788],"category_scores_gemma":[0.0010515467,0.000119653574,0.0000877598,0.00013446357,0.000098943005,0.00044398766,0.000052803334,0.00088100974,0.0000030276367],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020527457,0.00023643278,0.97020346,0.00021336546,0.000029708559,0.00012291924,0.0050158347,0.00012355596,0.0068854014,0.0021561484,0.00011232946,0.014695579],"study_design_scores_gemma":[0.0014529305,0.0012457026,0.97059196,0.00011246821,0.0003356556,0.0006990648,0.0011845825,0.011844791,0.0004471959,0.010950185,0.0009035701,0.00023187086],"about_ca_topic_score_codex":8.622627e-7,"about_ca_topic_score_gemma":8.249593e-8,"teacher_disagreement_score":0.08397981,"about_ca_system_score_codex":0.000028606337,"about_ca_system_score_gemma":0.000041556068,"threshold_uncertainty_score":0.48793313},"labels":[],"label_agreement":null},{"id":"W3035680799","doi":"10.3389/fneur.2020.00561","title":"Altered White Matter Structural Network in Frontal and Temporal Lobe Epilepsy: A Graph-Theoretical Study","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Diffusion MRI; Temporal lobe; Epilepsy; Neuroscience; Psychology; Frontal lobe; Cognition; Connectome; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.020287890543845912,"score_gpt":0.2900120420111246,"score_spread":0.26972415146727874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035680799","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97059554,0.00009742644,0.008244068,0.019683791,0.00021283943,0.0008857043,0.0000065007816,0.00008150291,0.00019265607],"genre_scores_gemma":[0.9756661,0.000015866395,0.013937362,0.010121482,0.00014258207,0.00006641093,0.000011881163,0.000028515251,0.0000098142755],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998662,0.00012149321,0.0003019683,0.00050118624,0.000087410765,0.00032596564],"domain_scores_gemma":[0.9995576,0.000025454801,0.0000538106,0.00022682894,0.000010999299,0.00012530466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007432648,0.00016650729,0.00040343314,0.00010166372,0.00003713733,0.000009268903,0.00012029552,0.00008171499,0.00005449328],"category_scores_gemma":[0.000022368433,0.0001571336,0.000037281934,0.00026726667,0.00028737358,0.00004904424,0.000118328964,0.0005638202,0.0000033315275],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063894276,0.00005904381,0.98395395,0.000010375956,0.0000070381348,0.00019505131,0.00024013824,0.000038400758,0.000028425806,0.0003599341,0.014125067,0.0003436459],"study_design_scores_gemma":[0.0019355522,0.00091688026,0.9734236,0.000007650222,0.000023040877,0.00009737317,0.00007703263,0.0065911333,0.00000728003,0.015752144,0.0010271011,0.00014121743],"about_ca_topic_score_codex":0.000009530617,"about_ca_topic_score_gemma":0.000007535872,"teacher_disagreement_score":0.015392209,"about_ca_system_score_codex":0.000011726307,"about_ca_system_score_gemma":0.000012903939,"threshold_uncertainty_score":0.6407723},"labels":[],"label_agreement":null},{"id":"W3035690190","doi":"10.1101/2020.06.12.148999","title":"Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; Compute Canada; Vanderbilt Institute for Clinical and Translational Research; National Institutes of Health; Vanderbilt University; U.S. Department of Defense","keywords":"White matter; Tractography; Diffusion MRI; Human Connectome Project; Fiber tract; Population; Artificial intelligence; Computer science; Neuroscience; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine","score_opus":0.02904121661004588,"score_gpt":0.2664746249582702,"score_spread":0.2374334083482243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035690190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96148336,0.0002893119,0.02860169,0.005572596,0.00022359313,0.0015996578,0.0008159236,0.0013951871,0.000018681607],"genre_scores_gemma":[0.920104,0.000098351404,0.07641621,0.0023096448,0.00040096688,0.00043943076,0.000024759385,0.00019868168,0.000007949727],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972122,0.00007531503,0.0006060201,0.0012881733,0.0004018065,0.00041650957],"domain_scores_gemma":[0.99727154,0.000112863105,0.0004568603,0.001507528,0.00026420903,0.0003870129],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000086162436,0.00062076823,0.0007635492,0.00025585375,0.0001868546,0.0001320352,0.0003424774,0.00039995468,0.00046202252],"category_scores_gemma":[0.00007174065,0.00062994054,0.00034326845,0.0005160945,0.00009291437,0.00010202182,0.0002790176,0.0009363881,0.0001607224],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012946679,0.00050560664,0.62069786,0.0003170557,0.00010197218,0.000051046343,0.000005637293,0.00007864602,0.3758896,0.00003243392,0.0021860746,0.0000046193068],"study_design_scores_gemma":[0.00085132086,0.00006389759,0.92101055,0.0005790541,0.0003301691,2.2853724e-8,9.2190203e-7,0.000994116,0.06832076,0.00002045345,0.007159795,0.00066893315],"about_ca_topic_score_codex":0.00019329572,"about_ca_topic_score_gemma":0.0000019695012,"teacher_disagreement_score":0.30756882,"about_ca_system_score_codex":0.00014406926,"about_ca_system_score_gemma":0.00019587412,"threshold_uncertainty_score":0.9996152},"labels":[],"label_agreement":null},{"id":"W3035781430","doi":"10.1007/s10237-020-01346-z","title":"Fluorescence recovery after photobleaching: direct measurement of diffusion anisotropy","year":2020,"lang":"en","type":"article","venue":"Biomechanics and Modeling in Mechanobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fluorescence recovery after photobleaching; Anisotropy; Thermal diffusivity; Isotropy; Materials science; Diffusion; Anisotropic diffusion; Tensor (intrinsic definition); Photobleaching; Work (physics); Optics; Thermodynamics; Fluorescence; Physics; Geometry; Mathematics","score_opus":0.11660971423851212,"score_gpt":0.30834446034793317,"score_spread":0.19173474610942104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035781430","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.468794,0.0007022071,0.5281218,0.0015228497,0.0000734329,0.0005787444,0.000022843042,0.000112910726,0.00007122403],"genre_scores_gemma":[0.9692491,0.0012408441,0.02883925,0.0005633439,0.000025699752,0.00005253765,0.000008667289,0.00001754241,0.000003013656],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990422,0.000030390907,0.00027921033,0.00036297776,0.000108546126,0.00017666815],"domain_scores_gemma":[0.9995894,0.000013593368,0.00006717012,0.00017929375,0.00006709048,0.00008344995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019732903,0.00012852026,0.00029142585,0.00009992893,0.000029505694,0.0000038452504,0.00007318607,0.00009616788,0.0000074871496],"category_scores_gemma":[0.00007048448,0.000113091686,0.00005115717,0.0001617579,0.00001977527,0.000023338755,0.00010412422,0.00014327474,0.0000010780085],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003122218,0.00006994727,0.0000570412,0.0000663381,0.000007240803,0.0000064401793,0.000057801415,0.00003284671,0.9905898,0.0011910717,0.000010406797,0.0075988336],"study_design_scores_gemma":[0.00083362334,0.0010676029,0.000018771821,0.00020703803,0.000041927266,0.000016703812,0.000049218706,0.8360453,0.1521835,0.0084110955,0.0009183351,0.0002068534],"about_ca_topic_score_codex":0.000029958164,"about_ca_topic_score_gemma":0.000002290614,"teacher_disagreement_score":0.8384063,"about_ca_system_score_codex":0.000032600423,"about_ca_system_score_gemma":0.000030964762,"threshold_uncertainty_score":0.46117452},"labels":[],"label_agreement":null},{"id":"W3035809474","doi":"10.1002/jmri.27188","title":"Mapping Structural Connectivity Using Diffusion <scp>MRI</scp>: Challenges and Opportunities","year":2020,"lang":"en","type":"review","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":199,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Australian Research Council; Medical Research Council; State Government of Victoria; National Health and Medical Research Council; Wellcome Trust","keywords":"Connectome; Tractography; Diffusion MRI; Computer science; Connectomics; Human Connectome Project; Graph theory; Graph; Artificial intelligence; Data science; Complex network; Machine learning; Neuroscience; Functional connectivity; Theoretical computer science; Psychology; Magnetic resonance imaging; Mathematics; Medicine; World Wide Web","score_opus":0.18716514936947706,"score_gpt":0.37723593507207087,"score_spread":0.1900707857025938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035809474","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046512188,0.9959607,0.0013206443,0.0011904379,0.00011630487,0.00049048045,0.000016981618,0.000057240406,0.00038206522],"genre_scores_gemma":[0.0001616275,0.98398435,0.015044109,0.00018337772,0.00044701336,0.0000110764695,0.000003867153,0.0000744147,0.000090161855],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99790514,0.00012342999,0.00089484715,0.00039297636,0.00036873855,0.00031485112],"domain_scores_gemma":[0.99774647,0.0004363115,0.0010641761,0.00031138575,0.00019085052,0.00025082176],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002966702,0.00042714755,0.0017239565,0.00032712345,0.0001361891,0.000060175997,0.00022672204,0.000096777825,0.000007581455],"category_scores_gemma":[0.00032410902,0.00034187207,0.00033255198,0.00016482196,0.00020199272,0.00020999154,0.00020384481,0.0009485103,6.8359907e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035585626,0.000016479009,0.000041902666,0.002734119,0.000013052547,0.00046428177,0.00018827445,1.9139225e-7,0.000048849775,0.00012958182,0.0001858137,0.9961739],"study_design_scores_gemma":[0.00035052275,0.00012244994,0.00041544126,0.015693223,0.0004028387,0.009331841,0.00032450177,0.00082240364,0.0000034348034,0.0006144983,0.97178537,0.00013349642],"about_ca_topic_score_codex":0.0000025060544,"about_ca_topic_score_gemma":1.5711261e-7,"teacher_disagreement_score":0.9960404,"about_ca_system_score_codex":0.00012042601,"about_ca_system_score_gemma":0.00026982496,"threshold_uncertainty_score":0.9999033},"labels":[],"label_agreement":null},{"id":"W3035841897","doi":"10.1001/jamapsychiatry.2020.1495","title":"Assessment of Neurobiological Mechanisms of Cortical Thinning During Childhood and Adolescence and Their Implications for Psychiatric Disorders","year":2020,"lang":"en","type":"article","venue":"JAMA Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Hospital for Sick Children; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; University of Toronto","funders":"Medical Research Council","keywords":"Cohort; Psychology; Neuroimaging; Psychiatry; Neuroscience; Medicine; Pathology","score_opus":0.02741887362394515,"score_gpt":0.3249181216440192,"score_spread":0.29749924802007405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035841897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7063281,0.00029494887,0.25324428,0.038971826,0.000036519898,0.0008285663,0.00006664607,0.00010031818,0.0001287821],"genre_scores_gemma":[0.8808116,0.0001926592,0.11798016,0.0009004915,0.000044407767,0.00004775256,0.000007817343,0.00001397655,0.0000011530086],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999261,0.000016124717,0.0002703068,0.00029170216,0.00004010311,0.00012071476],"domain_scores_gemma":[0.9994827,0.0000620245,0.0001353702,0.00018725816,0.000035865804,0.00009681693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054580203,0.000110524044,0.0002279688,0.00003867826,0.00008901632,0.000006199123,0.00007911953,0.000056421737,0.0000015875237],"category_scores_gemma":[0.000048249785,0.00008725286,0.0000636968,0.00016750925,0.00009096041,0.000038825303,0.000060475242,0.00020556335,5.686028e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012833813,0.00063782645,0.6755118,0.0007218058,0.000038469563,1.0665038e-7,0.00015337822,0.000011984689,0.12566492,0.19281761,0.0001970442,0.0041167196],"study_design_scores_gemma":[0.0009488236,0.00045112515,0.9609262,0.00005244523,0.000046320034,0.000019081983,0.0000900612,0.0007532432,0.0006705697,0.035916913,0.00004502963,0.00008019342],"about_ca_topic_score_codex":0.0000010240001,"about_ca_topic_score_gemma":3.8592378e-7,"teacher_disagreement_score":0.2854144,"about_ca_system_score_codex":0.0000038494973,"about_ca_system_score_gemma":0.00003788828,"threshold_uncertainty_score":0.35580683},"labels":[],"label_agreement":null},{"id":"W3036457878","doi":"10.3233/jad-200213","title":"Fascicle- and Glucose-Specific Deterioration in White Matter Energy Supply in Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"White matter; Disease; Fascicle; Alzheimer's disease; Medicine; Neuroscience; Internal medicine; Psychology; Anatomy","score_opus":0.06738659874914049,"score_gpt":0.3170203315413269,"score_spread":0.24963373279218642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036457878","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90007484,0.033145342,0.002290008,0.06371805,0.000074300355,0.00050528656,0.000043049506,0.000053168456,0.00009593942],"genre_scores_gemma":[0.99236745,0.0009335786,0.0020470938,0.0044278065,0.00015217197,0.000022075956,0.000013965329,0.000031507854,0.000004354802],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99875385,0.000048930935,0.0005228591,0.00025335248,0.00023108552,0.00018992819],"domain_scores_gemma":[0.9988083,0.000021718166,0.0001958544,0.0002062852,0.00007449381,0.00069334503],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000081314436,0.00016248984,0.00028381703,0.00019026968,0.00003128633,0.000034665183,0.00010520802,0.000030686802,0.00010943403],"category_scores_gemma":[0.000023214103,0.00014648764,0.00009863914,0.0002809029,0.00006682383,0.00030331183,0.000052805226,0.00022534236,0.000008572903],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024459935,0.00058859005,0.962179,0.00003808273,0.000081783684,0.001545923,0.00028402836,0.0001280801,0.0058298,0.0003017854,0.008386944,0.018189989],"study_design_scores_gemma":[0.0014966057,0.00013208836,0.9865622,0.00015120642,0.00039142076,0.00003529373,0.00004053795,0.0011546973,0.0010106202,0.0009860663,0.007853179,0.00018606402],"about_ca_topic_score_codex":0.0000038122573,"about_ca_topic_score_gemma":0.000001658896,"teacher_disagreement_score":0.09229259,"about_ca_system_score_codex":0.000023474871,"about_ca_system_score_gemma":0.0000986534,"threshold_uncertainty_score":0.59735924},"labels":[],"label_agreement":null},{"id":"W3036999708","doi":"10.1002/hbm.24977","title":"Depth‐dependent abnormal cortical myelination in first‐episode treatment‐naïve schizophrenia","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Western University","funders":"West China Hospital, Sichuan University; National Key Research and Development Program of China; Sichuan University; National Natural Science Foundation of China","keywords":"Supramarginal gyrus; Neuroscience; Psychology; Superior temporal gyrus; Myelin; Schizophrenia (object-oriented programming); Posterior cingulate; Parietal lobe; Middle frontal gyrus; Superior frontal gyrus; Cortex (anatomy); Temporal lobe; Cognition; Central nervous system; Functional magnetic resonance imaging; Epilepsy; Psychiatry","score_opus":0.11093449547315763,"score_gpt":0.35089601582930047,"score_spread":0.23996152035614282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036999708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8469771,0.0001331262,0.08388332,0.061433226,0.000041937183,0.0015813014,0.0000151996555,0.0008508839,0.0050839144],"genre_scores_gemma":[0.98937607,0.000019625382,0.0077686934,0.0022249885,0.00020053978,0.00012365717,0.00006853507,0.000028954293,0.00018892801],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988741,0.000031903826,0.00031527516,0.00037125783,0.00016089133,0.00024656323],"domain_scores_gemma":[0.9994331,0.00008597329,0.00007039759,0.00023436874,0.0000316873,0.00014447975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000833814,0.00015914366,0.00023181252,0.000107374486,0.00019175683,0.000022884073,0.00009536203,0.000059750615,0.00008467759],"category_scores_gemma":[0.00012066935,0.00015758844,0.00007034701,0.00023296739,0.0000429084,0.00009064039,0.000053643158,0.0002606459,0.00004544798],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00072671846,0.0019812686,0.2631551,0.00057181425,0.00016108084,0.0011367295,0.00689558,0.0007091874,0.5243495,0.14412972,0.012957297,0.04322597],"study_design_scores_gemma":[0.0057020127,0.0007075058,0.91711754,0.0002601094,0.00006043616,0.00009809906,0.00027925862,0.015732529,0.0033781594,0.0045166938,0.051632844,0.00051484053],"about_ca_topic_score_codex":0.000043411324,"about_ca_topic_score_gemma":0.00011325925,"teacher_disagreement_score":0.65396243,"about_ca_system_score_codex":0.00013272863,"about_ca_system_score_gemma":0.000020336405,"threshold_uncertainty_score":0.642627},"labels":[],"label_agreement":null},{"id":"W3037018865","doi":"10.1186/s41824-020-00079-7","title":"18F-FDG PET-guided diffusion tractography reveals white matter abnormalities around the epileptic focus in medically refractory epilepsy: implications for epilepsy surgical evaluation","year":2020,"lang":"en","type":"article","venue":"European Journal of Hybrid Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; St. Michael's Hospital; Queen's University; Lawson Health Research Institute; Western University","funders":"Mitacs; Physicians' Services Incorporated Foundation; London Health Sciences Centre; Lawson Health Research Institute","keywords":"Diffusion MRI; White matter; Medicine; Fractional anisotropy; Epilepsy; Tractography; Nuclear medicine; Lateralization of brain function; Positron emission tomography; Radiology; Magnetic resonance imaging; Audiology","score_opus":0.06948927614457129,"score_gpt":0.3434076416982299,"score_spread":0.2739183655536586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037018865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7532071,0.0011018177,0.07507457,0.16398351,0.00017301938,0.0016345832,0.000056940436,0.00012381919,0.0046446216],"genre_scores_gemma":[0.9867418,0.0003144135,0.008042673,0.0040794327,0.0006174474,0.00004437664,0.000033764525,0.00008003182,0.000046060704],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9969426,0.00056165253,0.0012929137,0.00036118936,0.00047573698,0.0003659106],"domain_scores_gemma":[0.99760216,0.00043201583,0.0007587681,0.00044752943,0.00048030188,0.00027924124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024713431,0.00025167243,0.00045037438,0.0002398974,0.00021670468,0.00008444862,0.00042238322,0.00000616495,0.00011786943],"category_scores_gemma":[0.00048393002,0.00018579236,0.00033775673,0.00034155344,0.00020949681,0.00033825837,0.00008985598,0.00072302297,0.000018450586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008428923,0.0008557232,0.8066412,0.0002684817,0.00015460124,0.002990754,0.00120092,0.0002663057,0.01611101,0.00074467936,0.11161036,0.05831307],"study_design_scores_gemma":[0.006620897,0.0006386876,0.86801004,0.00085297617,0.00061842526,0.023000235,0.00064029614,0.0070208665,0.0004814086,0.0056989933,0.085817456,0.00059971167],"about_ca_topic_score_codex":0.0000024413253,"about_ca_topic_score_gemma":2.7562888e-7,"teacher_disagreement_score":0.23353468,"about_ca_system_score_codex":0.00009228357,"about_ca_system_score_gemma":0.000110941946,"threshold_uncertainty_score":0.7576392},"labels":[],"label_agreement":null},{"id":"W3037092022","doi":"10.1016/j.nicl.2020.102320","title":"Network reorganisation following anterior temporal lobe resection and relation with post-surgery seizure relapse: A longitudinal study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Temporal lobe; Anterior temporal lobectomy; Tractography; Epilepsy; Fractional anisotropy; White matter; Uncinate fasciculus; Epilepsy surgery; Medicine; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Neuroscience; Surgery; Magnetic resonance imaging; Radiology","score_opus":0.1658678099377777,"score_gpt":0.406680260432219,"score_spread":0.2408124504944413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037092022","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9712571,0.00007725329,0.013251192,0.013702732,0.00013308783,0.0010460594,0.0000037802254,0.00043798756,0.0000908083],"genre_scores_gemma":[0.98840326,0.00005892111,0.008359259,0.002468037,0.00053347304,0.000038211034,0.000028671328,0.000059369686,0.000050783303],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99785215,0.00019809399,0.0006663919,0.000773555,0.00028475,0.00022506496],"domain_scores_gemma":[0.99860686,0.00042147702,0.00024387277,0.00039601146,0.00011217911,0.00021959656],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004577767,0.00020011113,0.00046316764,0.000052279243,0.00021262388,0.000051310053,0.000069062786,0.00009848624,0.000012286989],"category_scores_gemma":[0.000933259,0.00017349528,0.00012969623,0.00043870558,0.00010141957,0.0002572972,0.00009187244,0.00070691254,0.000010405965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011658233,0.00025734238,0.99351317,0.00002704606,0.000030339597,0.0005551113,0.00009361544,0.0000062306044,0.00093436975,0.00001788192,0.0012690759,0.0021300078],"study_design_scores_gemma":[0.001331843,0.0034118758,0.9923733,0.000112784764,0.00021758497,0.00029026065,0.00007607356,0.0007288269,0.00003385821,0.00009236869,0.0011547749,0.0001764426],"about_ca_topic_score_codex":0.00001034291,"about_ca_topic_score_gemma":0.000005226926,"teacher_disagreement_score":0.017146176,"about_ca_system_score_codex":0.000021868527,"about_ca_system_score_gemma":0.0000779017,"threshold_uncertainty_score":0.7074932},"labels":[],"label_agreement":null},{"id":"W3037939475","doi":"10.3389/fnagi.2020.00202","title":"Volumetric and Diffusion Abnormalities in Subcortical Nuclei of Older Adults With Cognitive Frailty","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Fujian University of Traditional Chinese Medicine; National Natural Science Foundation of China","keywords":"Montreal Cognitive Assessment; Cognition; Caudate nucleus; Diffusion MRI; Thalamus; Psychology; Effects of sleep deprivation on cognitive performance; Medicine; Putamen; Nucleus accumbens; Cognitive decline; Neuroscience; Audiology; Internal medicine; Cognitive impairment; Magnetic resonance imaging; Dementia; Central nervous system; Radiology; Disease","score_opus":0.03367734249124475,"score_gpt":0.2976633712077241,"score_spread":0.26398602871647936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037939475","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9322527,0.00011220406,0.06617606,0.0009356206,0.000033612574,0.00031909705,0.0000055031833,0.000047210404,0.00011801695],"genre_scores_gemma":[0.9888164,0.00015033937,0.009821632,0.0011531216,0.000008604622,0.000016408398,0.00000130451,0.000010418719,0.000021783131],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911076,0.00001922633,0.00017315116,0.00034168866,0.00017678381,0.00017841301],"domain_scores_gemma":[0.99968404,0.000039097624,0.00005429033,0.00010187362,0.00002867735,0.00009202073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053231845,0.00008846824,0.00018817821,0.00017152553,0.000034281133,0.000009507785,0.000085509986,0.000021272657,0.0000015096831],"category_scores_gemma":[0.00022163356,0.00007678192,0.000014492264,0.0009551874,0.00033744267,0.00011737613,0.00006929852,0.00020282726,1.7231102e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012783048,0.00009212645,0.988741,0.000077831035,4.91079e-7,0.000050954986,0.0008467542,0.000005961047,0.0020930772,0.000059326263,0.000108856875,0.007795796],"study_design_scores_gemma":[0.0010946904,0.00023877647,0.9703297,0.00033539257,0.000009490531,0.000022168155,0.00052600587,0.025053997,0.0020761045,0.00006329384,0.00015145286,0.00009890536],"about_ca_topic_score_codex":0.000021401558,"about_ca_topic_score_gemma":0.0000011726859,"teacher_disagreement_score":0.05656371,"about_ca_system_score_codex":0.000014311622,"about_ca_system_score_gemma":0.000024482104,"threshold_uncertainty_score":0.3131076},"labels":[],"label_agreement":null},{"id":"W3038146172","doi":"10.1101/2020.07.07.191809","title":"Beware of White Matter Hyperintensities Causing Systematic Errors in Grey Matter Segmentations!","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; University of Alberta; Centres Intégré Universitaires de Santé et de Services Sociaux","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; Alzheimer Society; U.S. Department of Defense; Eli Lilly and Company; Consortium canadien en neurodégénérescence associée au vieillissement; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Sanofi; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Hyperintensity; Putamen; Grey matter; White matter; Fluid-attenuated inversion recovery; Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Cardiology; Internal medicine; Effects of sleep deprivation on cognitive performance; Psychology; Medicine; Magnetic resonance imaging; Neuroscience; Cognition; Disease; Cognitive impairment; Radiology","score_opus":0.04253700151309517,"score_gpt":0.28508521451069563,"score_spread":0.24254821299760046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038146172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9802548,0.00032484945,0.011530981,0.0044348235,0.00023400223,0.0025920612,0.00021315682,0.00038652404,0.000028799988],"genre_scores_gemma":[0.96306545,0.00004000318,0.034412775,0.001764629,0.00007879396,0.00048813797,0.0000012383787,0.00013302098,0.000015972315],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99777305,0.00007909625,0.00084708334,0.0006994912,0.0002888303,0.00031244702],"domain_scores_gemma":[0.9978181,0.00004521754,0.0004997586,0.0010936239,0.0003949023,0.00014840926],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001706261,0.00041316115,0.00095052854,0.00034000856,0.00008599586,0.000044584915,0.00020481388,0.00020169256,0.0000856454],"category_scores_gemma":[0.000079030186,0.0004271743,0.0001556092,0.00043567613,0.00012227622,0.00010435018,0.0004452962,0.00063604483,0.000070905764],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006276399,0.00024668156,0.44917032,0.05780393,0.00017828941,0.00024780096,0.00020656006,0.00014887501,0.49029735,0.00019219803,0.0014450785,1.7042692e-7],"study_design_scores_gemma":[0.0010019141,0.000083318184,0.79590964,0.030636039,0.00075206073,0.0000012403561,0.00012389373,0.0015181853,0.16855668,0.000023020984,0.00020758607,0.001186389],"about_ca_topic_score_codex":0.00004016441,"about_ca_topic_score_gemma":0.000001095497,"teacher_disagreement_score":0.34673935,"about_ca_system_score_codex":0.00021638919,"about_ca_system_score_gemma":0.00017476491,"threshold_uncertainty_score":0.999818},"labels":[],"label_agreement":null},{"id":"W3038220767","doi":"10.1016/j.neuroimage.2020.117129","title":"Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":313,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Canadian Institutes of Health Research; Johnson and Johnson; Janssen Research and Development; National Institutes of Health; H. Lundbeck A/S; IXICO; Genentech; GE Healthcare; Fujirebio US; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Southern California; Merck","keywords":"Scanner; Longitudinal data; Computer science; Artificial intelligence; Data science; Data mining","score_opus":0.46129922390750755,"score_gpt":0.4545831753150153,"score_spread":0.006716048592492252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038220767","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023029263,0.0002262466,0.9649882,0.03006422,0.000073892414,0.0010691317,0.00026957595,0.0006851743,0.0003206649],"genre_scores_gemma":[0.23741549,0.00004283829,0.75408113,0.0074217427,0.00036251903,0.000117273106,0.00026305256,0.00011932665,0.0001766486],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978069,0.000040666288,0.00035927352,0.0011370989,0.00022298645,0.0004330862],"domain_scores_gemma":[0.9980962,0.00017931423,0.00013794033,0.001151011,0.00013885376,0.00029664958],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020697163,0.0002770671,0.00039595473,0.00007363836,0.00021944294,0.000072525036,0.00054693734,0.00003741291,0.000036618552],"category_scores_gemma":[0.00046324453,0.0002701647,0.00013054491,0.0003205931,0.00009671147,0.00032028262,0.00049238757,0.00042567108,0.000027961776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084253406,0.0010289517,0.11897307,0.0008647179,0.00014012292,0.0012040884,0.000325678,0.00009936563,0.6095568,0.0022875392,0.15975316,0.104924],"study_design_scores_gemma":[0.004331119,0.00035897398,0.07336687,0.00011856594,0.00053660054,0.0007447555,0.000061863095,0.6382279,0.01913938,0.00035208627,0.2620367,0.00072521495],"about_ca_topic_score_codex":0.000020074687,"about_ca_topic_score_gemma":0.0000016542983,"teacher_disagreement_score":0.6381285,"about_ca_system_score_codex":0.000026417332,"about_ca_system_score_gemma":0.00005967979,"threshold_uncertainty_score":0.999975},"labels":[],"label_agreement":null},{"id":"W3038476824","doi":"10.1016/j.nicl.2020.102340","title":"Post-mortem 7 Tesla MRI detection of white matter hyperintensities: A multidisciplinary voxel-wise comparison of imaging and histological correlates","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Health Research","keywords":"Hyperintensity; White matter; Magnetic resonance imaging; Voxel; Medicine; Neuroimaging; Pathology; Neuroscience; Radiology; Psychology","score_opus":0.10254094753991623,"score_gpt":0.4015952357323905,"score_spread":0.29905428819247426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038476824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730104,0.00017986425,0.015238747,0.010587277,0.00008429921,0.00042610004,0.000026524047,0.00016307076,0.00028370979],"genre_scores_gemma":[0.9890758,0.000063454856,0.008608673,0.0020640825,0.00006847146,0.0000142967165,0.000010361718,0.00003302208,0.000061880906],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981451,0.000083023304,0.0009132523,0.00052490947,0.00015778116,0.00017591023],"domain_scores_gemma":[0.9985321,0.00036528552,0.00034371967,0.0003651788,0.00021358994,0.00018008523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001334626,0.0001795217,0.00066641055,0.00005983287,0.000083163235,0.0000062683957,0.00011407395,0.00008556306,0.00003077327],"category_scores_gemma":[0.00046861317,0.00015811522,0.00018259179,0.00014705224,0.00059871894,0.000079634825,0.00029770663,0.00057995203,0.000011011738],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004968628,0.00035060302,0.89725703,0.00013458221,0.000012375411,0.000058410962,0.00031613416,0.0000067929072,0.09829944,0.000013948287,0.00074163073,0.002312194],"study_design_scores_gemma":[0.0011257996,0.0012985955,0.954558,0.000093279064,0.0001738001,0.00024837098,0.00031418787,0.033898283,0.0070213294,0.000090360154,0.0009971962,0.00018078942],"about_ca_topic_score_codex":0.000004842742,"about_ca_topic_score_gemma":3.600629e-7,"teacher_disagreement_score":0.09127811,"about_ca_system_score_codex":0.000010838538,"about_ca_system_score_gemma":0.000025382598,"threshold_uncertainty_score":0.64477515},"labels":[],"label_agreement":null},{"id":"W3038661352","doi":"10.1101/2020.07.01.183038","title":"Surface-Based Connectivity Integration","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"White matter; Human Connectome Project; Diffusion MRI; Diffusion imaging; Computer science; Connectome; Functional connectivity; High resolution; Neuroscience; Pattern recognition (psychology); Artificial intelligence; Psychology; Magnetic resonance imaging; Geology; Medicine","score_opus":0.062445125858220006,"score_gpt":0.30318049289518945,"score_spread":0.24073536703696943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3038661352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.655931,0.00026014433,0.32957655,0.008861483,0.00035157104,0.002028026,0.0002773158,0.0026737875,0.00004009443],"genre_scores_gemma":[0.88399905,0.00006227905,0.11412341,0.0013034048,0.0001918284,0.00019400072,0.0000014206896,0.00012183523,0.000002745135],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979364,0.00006832719,0.00038572922,0.0009911603,0.0003009159,0.0003174454],"domain_scores_gemma":[0.99761415,0.00008017982,0.00030396978,0.0012873465,0.00041442012,0.00029996017],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020882774,0.0004447416,0.000576839,0.000113579445,0.00011827247,0.00008167722,0.00026541145,0.00032718127,0.000032053842],"category_scores_gemma":[0.00032394056,0.00046492385,0.00019184744,0.0004375947,0.000115284194,0.000075113734,0.00022216729,0.0011425976,0.000055613968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006409997,0.00020670632,0.0051453603,0.00030373372,0.000042182754,0.000053023665,0.0000022595877,0.00010349039,0.9910636,0.0019429893,0.0010671202,0.000005448322],"study_design_scores_gemma":[0.00070088264,0.0001311662,0.058516245,0.0005847891,0.0002215943,2.7465882e-8,9.211421e-7,0.014795648,0.91421074,0.00003541444,0.010155705,0.0006468791],"about_ca_topic_score_codex":0.00002545216,"about_ca_topic_score_gemma":5.3978096e-7,"teacher_disagreement_score":0.22806805,"about_ca_system_score_codex":0.00026414834,"about_ca_system_score_gemma":0.00058783457,"threshold_uncertainty_score":0.99978024},"labels":[],"label_agreement":null},{"id":"W3039504579","doi":"10.1016/j.cmpb.2020.105636","title":"VBM sensitivity to localization and extent of mouse brain lesions: A simulation approach","year":2020,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Agencia Nacional de Promoción Científica y Tecnológica","keywords":"Voxel; Computer science; Neuroimaging; Artificial intelligence; Workflow; Preprocessor; Voxel-based morphometry; Pattern recognition (psychology); Pipeline (software); Magnetic resonance imaging; Computer vision; Psychology; Neuroscience; Medicine; Radiology; White matter","score_opus":0.2049777215591546,"score_gpt":0.45221734157210725,"score_spread":0.24723962001295263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3039504579","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034148335,0.00017410572,0.9590655,0.005729019,0.000012150225,0.0007802091,0.0000020635446,0.00007646983,0.000012145229],"genre_scores_gemma":[0.2902299,0.000046091285,0.70736814,0.0022384094,0.000057635683,0.00002079767,0.000024357563,0.00000957717,0.000005093613],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914044,0.00012124892,0.00024285179,0.0002969103,0.00009339699,0.00010515366],"domain_scores_gemma":[0.99939054,0.00016647985,0.00005880988,0.00014310173,0.000057002275,0.00018404535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047385605,0.00010148137,0.0002755603,0.00010310314,0.000028518043,0.000007382832,0.000027402759,0.000044074117,8.2906223e-7],"category_scores_gemma":[0.00013084004,0.000082095925,0.000019102117,0.00047670281,0.00010454566,0.000031040126,0.00009025549,0.00009553885,1.2003424e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062500534,0.00013767656,0.0031023554,0.00023619179,0.0000069386087,0.000005036909,0.00064353796,0.0005231244,0.015405666,0.00033099775,0.00008019275,0.9794658],"study_design_scores_gemma":[0.0009047922,0.00093771634,0.0060232794,0.00017588674,0.000025983561,0.000031423737,0.000070788476,0.97723603,0.0017038323,0.00042882294,0.012343984,0.00011742982],"about_ca_topic_score_codex":0.000011332249,"about_ca_topic_score_gemma":2.564066e-7,"teacher_disagreement_score":0.97934836,"about_ca_system_score_codex":0.000010220248,"about_ca_system_score_gemma":0.000010413992,"threshold_uncertainty_score":0.33477747},"labels":[],"label_agreement":null},{"id":"W3040060243","doi":"10.1101/2020.07.02.185397","title":"Microstructural characterization and validation of a 3D printed axon-mimetic phantom for diffusion MRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Research Council Canada; Western Economic Diversification Canada; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Canada First Research Excellence Fund; University of Saskatchewan; Canadian Light Source","keywords":"Imaging phantom; Reproducibility; Characterization (materials science); Microscopy; Confocal microscopy; Anisotropy; Tortuosity; Kurtosis; Diffusion","score_opus":0.031108065820987178,"score_gpt":0.283938934636493,"score_spread":0.2528308688155058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040060243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79299027,0.00007446308,0.20341869,0.00088928756,0.00012226508,0.0018345244,0.00037036976,0.00029942076,7.3576433e-7],"genre_scores_gemma":[0.894927,0.0002543034,0.10409338,0.00018189468,0.00016206558,0.00028263347,0.000013601721,0.00008194122,0.0000031503325],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99846613,0.000029403061,0.00045500553,0.0006729147,0.00016842491,0.00020811998],"domain_scores_gemma":[0.9983467,0.000044527955,0.0004798553,0.00057558686,0.00041046552,0.00014285118],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011236347,0.00030555858,0.00048809114,0.0001561024,0.00008159256,0.000045975725,0.00014642983,0.00020726716,0.0000064697383],"category_scores_gemma":[0.0001710965,0.0003124689,0.0000871287,0.0002570986,0.00009535482,0.000078494406,0.00025111152,0.00030716177,0.0000013581497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081821905,0.000061731786,0.004076145,0.00080320705,0.000033410008,0.0000024928272,0.0000091443235,0.0000013802019,0.9946472,0.00023962703,0.000018878321,0.000024965335],"study_design_scores_gemma":[0.0006745311,0.00010345845,0.09735234,0.0004657988,0.00020907751,8.4354674e-8,7.694202e-7,0.0030266824,0.8958403,0.000011856659,0.0020458873,0.00026919722],"about_ca_topic_score_codex":0.000004872529,"about_ca_topic_score_gemma":4.5120714e-8,"teacher_disagreement_score":0.10193679,"about_ca_system_score_codex":0.00007128942,"about_ca_system_score_gemma":0.00013436184,"threshold_uncertainty_score":0.99993277},"labels":[],"label_agreement":null},{"id":"W3040109440","doi":"10.1038/s42003-020-1050-x","title":"A time-dependent diffusion MRI signature of axon caliber variations and beading","year":2020,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":109,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; U.S. Department of Health and Human Services; National Institutes of Health; Center for Advanced Imaging Innovation and Research; National Institute of Biomedical Imaging and Bioengineering; York University","keywords":"Caliber; Signature (topology); Diffusion MRI; Diffusion; Neuroscience; Medicine; Biology; Physics; Magnetic resonance imaging; Mathematics; Radiology; Materials science; Geometry","score_opus":0.07668858133215542,"score_gpt":0.36070362206639867,"score_spread":0.2840150407342432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040109440","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12917437,0.0064030723,0.50306505,0.33864176,0.000064305306,0.003079804,0.0003727702,0.0011959618,0.018002905],"genre_scores_gemma":[0.94661254,0.00090368016,0.050966088,0.001195485,0.000020040192,0.000050338935,0.00014107783,0.000011693266,0.00009907703],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994923,0.000055978566,0.00018303013,0.0001539694,0.00003384358,0.00008091926],"domain_scores_gemma":[0.9989389,0.00015663187,0.00008737711,0.0006808202,0.000068693604,0.000067530294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053835414,0.000070093556,0.00015799796,0.000045628225,0.000110932386,0.0000031600498,0.00021803462,0.000076865785,0.00003135355],"category_scores_gemma":[0.00009860126,0.00006290542,0.00003079612,0.0001616204,0.00020974728,0.000025809293,0.00031732995,0.00021718143,0.000009530866],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004386597,0.00032820404,0.009789263,0.00004988398,0.00005071246,0.0000010656101,0.0009798382,0.000010146101,0.89274013,0.082602754,0.0022757351,0.0111284265],"study_design_scores_gemma":[0.005202419,0.0019839767,0.03633681,0.000417255,0.00092344114,0.0002206861,0.0006400759,0.20026338,0.04054789,0.043616552,0.6686255,0.0012220668],"about_ca_topic_score_codex":0.00000738114,"about_ca_topic_score_gemma":0.0000010807299,"teacher_disagreement_score":0.8521922,"about_ca_system_score_codex":0.000012111519,"about_ca_system_score_gemma":0.000021544594,"threshold_uncertainty_score":0.25652084},"labels":[],"label_agreement":null},{"id":"W3040260334","doi":"10.1016/j.nicl.2020.102338","title":"Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; National Institutes of Health; H. Lundbeck A/S; Arizona Alzheimer’s Consortium; Genentech; Fujirebio US; GE Healthcare; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Canadian Institutes of Health Research; University of Southern California","keywords":"Magnetic resonance imaging; Cardiology; Medicine; Internal medicine; Biomarker; Cognitive decline; Cohort; Neuroimaging; Disease; Psychology; Radiology; Dementia; Psychiatry; Biology","score_opus":0.18913676788077588,"score_gpt":0.4249174092099615,"score_spread":0.23578064132918564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3040260334","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95317084,0.000016100064,0.03167041,0.008790938,0.000089249545,0.0055020354,0.00008765008,0.0004506889,0.00022206228],"genre_scores_gemma":[0.93108386,0.000015170359,0.04608108,0.022173788,0.0002396986,0.00026800676,0.000018729403,0.00008945482,0.000030234902],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99518585,0.00042860562,0.0019660417,0.0011464912,0.0008108297,0.00046219557],"domain_scores_gemma":[0.99451506,0.0025383772,0.0004134366,0.00088712724,0.0006398028,0.0010061911],"candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015645867,0.00035831868,0.0011085398,0.00015504564,0.000117717966,0.00003307378,0.00049603125,0.000119482116,0.0000770033],"category_scores_gemma":[0.009415472,0.00034067658,0.0003853477,0.0012830805,0.00020110494,0.000070908914,0.00046218466,0.0007480723,0.000079395664],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007994035,0.010364949,0.8499447,0.00038061512,0.00020590847,0.0030033144,0.0005254394,0.0008927438,0.07774489,0.000029940116,0.004906128,0.044007353],"study_design_scores_gemma":[0.011641962,0.022682374,0.8884058,0.0002934768,0.00083549606,0.00004934143,0.0012825908,0.0031198682,0.06333258,0.000079469064,0.007244144,0.0010328654],"about_ca_topic_score_codex":0.000020653632,"about_ca_topic_score_gemma":7.3174186e-7,"teacher_disagreement_score":0.042974487,"about_ca_system_score_codex":0.000029539473,"about_ca_system_score_gemma":0.00034251218,"threshold_uncertainty_score":0.9999045},"labels":[],"label_agreement":null},{"id":"W3041096751","doi":"10.1038/s41467-020-17328-9","title":"Synucleinopathy alters nanoscale organization and diffusion in the brain extracellular space through hyaluronan remodeling","year":2020,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":118,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; LabEx BRAIN; Centre National de la Recherche Scientifique; Institut National de la Santé et de la Recherche Médicale; Université de Bordeaux; Eusko Jaurlaritza; Agence Nationale de la Recherche; Association France Parkinson; Ottawa Hospital Research Institute; Fondation pour l'Aide à la Recherche sur la Sclérose en Plaques","keywords":"Extracellular matrix; Microglia; Extracellular; Neurodegeneration; Neuroscience; Biophysics; Cell biology; Chemistry; Biology; Pathology; Inflammation; Medicine; Disease; Immunology","score_opus":0.05432275051677585,"score_gpt":0.3348001035359066,"score_spread":0.2804773530191308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041096751","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30435044,0.009905357,0.044368804,0.6375893,0.000031550502,0.0014356142,0.000016214784,0.00040065363,0.001902114],"genre_scores_gemma":[0.94090265,0.001375176,0.04854077,0.008965895,0.000031642558,0.000022421189,0.0001065958,0.000024501407,0.000030324069],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992845,0.00008937874,0.00017497086,0.00021222355,0.00012937331,0.00010955576],"domain_scores_gemma":[0.99865144,0.00019872289,0.00006582314,0.00096357864,0.00007349303,0.000046917048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011492512,0.00010049087,0.00012052266,0.00003162345,0.00024956276,0.000024634346,0.0004129232,0.00010748781,0.0000036844779],"category_scores_gemma":[0.0003228516,0.000080208214,0.000024600362,0.0005847472,0.00009932193,0.00009707699,0.00020879843,0.00080216123,0.0000035725634],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006394398,0.00085558416,0.030667009,0.0001485848,0.000022819215,0.00002533935,0.016198834,0.00009704332,0.5904339,0.33136597,0.010280668,0.019840298],"study_design_scores_gemma":[0.0018915489,0.00035292128,0.029709877,0.00030747388,0.00017026161,0.00028597272,0.0023075687,0.060058054,0.006436355,0.0062867375,0.8916016,0.0005915775],"about_ca_topic_score_codex":0.000008601452,"about_ca_topic_score_gemma":0.0000078820285,"teacher_disagreement_score":0.881321,"about_ca_system_score_codex":0.000023037892,"about_ca_system_score_gemma":0.000023133094,"threshold_uncertainty_score":0.34850362},"labels":[],"label_agreement":null},{"id":"W3041520709","doi":"10.1101/2020.07.10.197921","title":"Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Reproducibility; Kurtosis; Human Connectome Project; Diffusion imaging; Diffusion MRI; Imaging phantom; Effective diffusion coefficient; White matter; Pearson product-moment correlation coefficient; Nuclear medicine; Mathematics; Statistics; Medicine; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.13042504876051228,"score_gpt":0.36884988830109555,"score_spread":0.23842483954058327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041520709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97620004,0.0006124661,0.017760798,0.003040376,0.00017715858,0.0014164281,0.00022417234,0.00056264293,0.0000059337817],"genre_scores_gemma":[0.9395048,0.00026604655,0.05942388,0.00024862823,0.0002904533,0.00017505679,0.000001990704,0.0000856228,0.0000035439457],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9956536,0.00022851904,0.0009611914,0.0022915145,0.00053447403,0.0003306905],"domain_scores_gemma":[0.9951878,0.00013812124,0.00085965137,0.0030014357,0.0005651876,0.00024776108],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0017646154,0.0004134852,0.00081261963,0.00013445607,0.00020812752,0.00003684137,0.00022859064,0.00021350554,0.000025529444],"category_scores_gemma":[0.0025187088,0.0004393784,0.00015729087,0.0003278456,0.00023882449,0.00008054632,0.0013041882,0.00071556756,0.000004862783],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016998067,0.00015040622,0.064547375,0.0009997211,0.00003021804,0.000005802694,0.000011326089,0.000017548757,0.93354297,0.00040365328,0.00007655434,0.000044442542],"study_design_scores_gemma":[0.0006540728,0.000080215,0.61426276,0.00053871283,0.00019751137,4.6937945e-8,0.0000014862094,0.005246693,0.37826222,0.00005516318,0.00033021264,0.00037089104],"about_ca_topic_score_codex":0.0005255104,"about_ca_topic_score_gemma":0.0000031537622,"teacher_disagreement_score":0.55528075,"about_ca_system_score_codex":0.0003451009,"about_ca_system_score_gemma":0.00022751874,"threshold_uncertainty_score":0.9998058},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"agree"},{"id":"W3041613148","doi":"10.1089/neu.2020.7170","title":"Diffusion Tensor Imaging in Contact and Non-Contact University-Level Sport Athletes","year":2020,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; Carleton University; Université de Sherbrooke; Université de Montréal","funders":"Canadian Institutes of Health Research","keywords":"Corpus callosum; Fractional anisotropy; Diffusion MRI; White matter; Corticospinal tract; Athletes; Medicine; Pyramidal tracts; Magnetic resonance imaging; Psychology; Tractography; Physical medicine and rehabilitation; Physical therapy; Audiology; Anatomy; Radiology","score_opus":0.1042042585678643,"score_gpt":0.3281349210044294,"score_spread":0.22393066243656512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3041613148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98759174,0.00005932317,0.0015807905,0.010137891,0.00002201218,0.00018431281,0.000004287139,0.000024345305,0.00039531873],"genre_scores_gemma":[0.995022,0.00030551717,0.0027652811,0.0017706472,0.000081786915,4.2673872e-7,8.875402e-7,0.000015473594,0.000038009515],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935365,0.000010656408,0.00023792073,0.00014604536,0.00013040914,0.00012134417],"domain_scores_gemma":[0.99946016,0.000038132348,0.00017483172,0.000095911026,0.00006730468,0.00016363531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058084603,0.000097498996,0.00025412845,0.00011744589,0.00003904698,0.000010430141,0.00009012606,0.000021588723,0.000008635768],"category_scores_gemma":[0.00004299229,0.00008614277,0.000070746304,0.00015202964,0.000023523444,0.00014871264,0.000039743503,0.00034341033,0.0000014162779],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006152218,0.00018229443,0.6994218,0.000060375718,0.000011062854,0.003635622,0.00031136928,0.0000059538393,0.27627864,0.00026177705,0.00088223105,0.018333642],"study_design_scores_gemma":[0.0018750826,0.00040064356,0.97798073,0.00017789207,0.00004124668,0.0007394161,0.00013947696,0.0008273493,0.0019157414,0.00005636083,0.015756346,0.000089692425],"about_ca_topic_score_codex":0.000008858045,"about_ca_topic_score_gemma":6.8729423e-7,"teacher_disagreement_score":0.27855894,"about_ca_system_score_codex":0.000028479704,"about_ca_system_score_gemma":0.000032883236,"threshold_uncertainty_score":0.35128},"labels":[],"label_agreement":null},{"id":"W3042104279","doi":"10.1016/j.neuroimage.2020.117147","title":"Groupwise track filtering via iterative message passing and pruning","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Research and Development; NIH Blueprint for Neuroscience Research; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; National Eye Institute; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Alzheimer's Association; Fujirebio US; BioClinica; U.S. Department of Defense; University of Southern California; Bristol-Myers Squibb; Northern California Institute for Research and Education; Merck; Alzheimer's Drug Discovery Foundation; Johnson and Johnson; AbbVie; National Institute on Aging","keywords":"Human Connectome Project; Computer science; Tractography; Artificial intelligence; Pruning; False positive paradox; Consistency (knowledge bases); Diffusion MRI; Prior probability; Pattern recognition (psychology); Computer vision; Neuroscience; Magnetic resonance imaging","score_opus":0.08999241902420518,"score_gpt":0.33917935358025914,"score_spread":0.24918693455605395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042104279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61402553,0.00020458145,0.35174987,0.024182336,0.000049421953,0.0009196692,0.000021110103,0.0011935701,0.0076539223],"genre_scores_gemma":[0.9639734,0.000043041924,0.030928139,0.0047849882,0.00010081921,0.00002471225,0.000008300203,0.00004024028,0.00009636385],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991571,0.000023602192,0.00016596026,0.00037204518,0.00010690209,0.00017441684],"domain_scores_gemma":[0.9994968,0.000053658434,0.000057861045,0.00019863367,0.000027973932,0.00016503339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035205703,0.00014033755,0.00018713475,0.000034468063,0.00011811105,0.000048309677,0.00006373248,0.000027000473,0.000028028433],"category_scores_gemma":[0.000075620745,0.00013485776,0.000040888175,0.00015823102,0.00007484533,0.00018066262,0.000087495515,0.00028180302,0.000008656387],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004429408,0.00004184497,0.0016836761,0.00009436476,0.0000066018483,0.00026026147,0.00061027,0.0000058802993,0.9718059,0.00028283763,0.0007771863,0.02438693],"study_design_scores_gemma":[0.0055860328,0.0021692861,0.16102333,0.0006674953,0.0004008565,0.0019604287,0.00035900265,0.124076895,0.49314478,0.0030903015,0.20577274,0.0017488493],"about_ca_topic_score_codex":0.0000016027576,"about_ca_topic_score_gemma":1.2304713e-7,"teacher_disagreement_score":0.47866106,"about_ca_system_score_codex":0.00001161644,"about_ca_system_score_gemma":0.000010265341,"threshold_uncertainty_score":0.549934},"labels":[],"label_agreement":null},{"id":"W3042227298","doi":"10.1101/2020.07.15.205401","title":"PhyloBrain atlas: a cortical brain MRI atlas following a phylogenetic approach","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval; Montreal Neurological Institute and Hospital; Université du Québec à Trois-Rivières","funders":"","keywords":"Precuneus; Cortex (anatomy); Neocortex; Neuroscience; Anatomy; Biology; Posterior cingulate; Temporal cortex; Functional magnetic resonance imaging","score_opus":0.04230195230271715,"score_gpt":0.291712293993612,"score_spread":0.24941034169089482,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042227298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67959076,0.0015857138,0.2944497,0.013899546,0.00058545667,0.005504789,0.00032615926,0.0038548312,0.00020308171],"genre_scores_gemma":[0.8462418,0.00009337939,0.14971764,0.0021746058,0.0006152929,0.0008747383,0.000002766163,0.00026605913,0.000013739305],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99578387,0.00015635729,0.00076610537,0.0019003841,0.0006064283,0.0007868704],"domain_scores_gemma":[0.99658066,0.00016018357,0.00035353604,0.001984486,0.00022095231,0.00070016773],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003754823,0.0008055767,0.001098857,0.00023269079,0.00023061418,0.00014460088,0.00064731506,0.0005393008,0.000020131529],"category_scores_gemma":[0.00060680235,0.00085289666,0.00054171216,0.0008232638,0.00020603114,0.00007395848,0.00082615676,0.0019746344,0.000085642576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000072997245,0.00047652196,0.004868428,0.0007341286,0.00027398605,0.00040473806,0.00001756155,0.000047854446,0.98679674,0.0021887561,0.00411164,0.0000066374496],"study_design_scores_gemma":[0.0069551324,0.0011146687,0.22329533,0.0031072637,0.0034682406,0.0000027110716,0.000029541017,0.040989656,0.5820693,0.0002795185,0.13215315,0.006535507],"about_ca_topic_score_codex":0.000013878981,"about_ca_topic_score_gemma":2.1933208e-7,"teacher_disagreement_score":0.4047275,"about_ca_system_score_codex":0.00026190115,"about_ca_system_score_gemma":0.000591748,"threshold_uncertainty_score":0.99939215},"labels":[],"label_agreement":null},{"id":"W3042920381","doi":"10.1016/j.jneumeth.2020.108870","title":"Regional segmentation strategy for DTI analysis of human corpus callosum indicates motor function deficit in mild cognitive impairment","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; University of Warwick; National Institute on Aging; Alzheimer's Disease Neuroimaging Initiative","keywords":"Corpus callosum; White matter; Diffusion MRI; Fractional anisotropy; Ageing; Psychology; Audiology; Cognition; Neuroscience; Medicine; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.3033377687154771,"score_gpt":0.5005663825420017,"score_spread":0.19722861382652462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042920381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5414361,0.000041295014,0.45724002,0.0009165359,0.00002760832,0.00030540867,0.000012852418,0.000010243023,0.000009980781],"genre_scores_gemma":[0.9160231,0.00005571338,0.08270041,0.0011320455,0.00003717448,0.000023278388,0.000006619962,0.000008902417,0.000012760122],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99877876,0.000111100664,0.00052024255,0.00020666265,0.00025755455,0.00012567051],"domain_scores_gemma":[0.99880123,0.0002184421,0.00059880596,0.000074017655,0.00019639039,0.00011113962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051418605,0.00009084357,0.00033236336,0.00041163096,0.000061028022,0.000012182313,0.00010989364,0.00003052992,0.000005049527],"category_scores_gemma":[0.00024877564,0.00007668079,0.00018015786,0.0011468896,0.00011287166,0.00012981491,0.000020046959,0.00018506042,7.976419e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033504644,0.000205158,0.013412927,0.000029011815,0.000028897886,0.0000062954405,0.00010627213,0.0004725187,0.9806083,0.0001670934,0.0000363514,0.0045921253],"study_design_scores_gemma":[0.0021559768,0.0073510497,0.8113146,0.00010696253,0.0015037679,0.00005655536,0.0004710977,0.02584243,0.14915356,0.0016171804,0.00025760123,0.00016925247],"about_ca_topic_score_codex":0.000004687108,"about_ca_topic_score_gemma":7.7999346e-7,"teacher_disagreement_score":0.83145475,"about_ca_system_score_codex":0.000042547104,"about_ca_system_score_gemma":0.00007245807,"threshold_uncertainty_score":0.3126952},"labels":[],"label_agreement":null},{"id":"W3043095919","doi":"10.1016/j.neuroimage.2020.117168","title":"Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Children's Hospital Research Institute; Canadian Institutes of Health Research; Alberta Innovates - Health Solutions; National Imaging Facility","keywords":"Diffusion MRI; White matter; Tractography; Neurite; Neuroscience; Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.024381645378773905,"score_gpt":0.2909073755795447,"score_spread":0.2665257302007708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043095919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952064,0.000055362038,0.0013390474,0.0028573482,0.000012584169,0.00030807915,0.0000016143773,0.00006744328,0.00015207939],"genre_scores_gemma":[0.9955866,0.00014001653,0.0028209193,0.001386137,0.000024025452,0.000009843946,0.000009126678,0.000013500862,0.000009846073],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938065,0.000017290198,0.00014041107,0.00029583118,0.00007141597,0.00009438981],"domain_scores_gemma":[0.9997536,0.000024307854,0.000035842753,0.00010295596,0.000013377687,0.00006990223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000030518073,0.00008420189,0.00012025991,0.00004777043,0.000024730918,0.000020171241,0.0000280988,0.000023626399,0.0000024256617],"category_scores_gemma":[0.00007380369,0.000084742016,0.0000129113005,0.0002593427,0.000034546156,0.00015205216,0.000054167886,0.00022294516,0.0000018158147],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002254527,0.00016127518,0.69826895,0.00010015702,0.00000222975,0.00015079921,0.0017178663,0.0000035291162,0.26221147,0.00024776367,0.00015491874,0.036755547],"study_design_scores_gemma":[0.00062189996,0.00013454231,0.99141496,0.000032533684,0.0000069047483,0.000039865477,0.000045009852,0.0016822941,0.005608602,0.00014777997,0.00019945343,0.00006617768],"about_ca_topic_score_codex":0.000014928865,"about_ca_topic_score_gemma":0.000003097924,"teacher_disagreement_score":0.29314595,"about_ca_system_score_codex":0.000012498548,"about_ca_system_score_gemma":0.0000064945425,"threshold_uncertainty_score":0.3455679},"labels":[],"label_agreement":null},{"id":"W3043265686","doi":"10.1016/j.neuroimage.2020.117172","title":"Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Ministère de l'Enseignement Supérieur et de la Recherche; Max-Planck-Gesellschaft; Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur et de la Recherche Scientifique; Deutsche Forschungsgemeinschaft","keywords":"Diffusion MRI; Computer science; SIGNAL (programming language); Signal-to-noise ratio (imaging); Noise (video); Sensitivity (control systems); Monte Carlo method; Image quality; Algorithm; Artificial intelligence; Encoding (memory); Contrast (vision); Echo (communications protocol); Diffusion; Pattern recognition (psychology); Computer vision; Mathematics; Statistics; Magnetic resonance imaging; Image (mathematics); Physics; Radiology; Medicine; Telecommunications","score_opus":0.07418862732828188,"score_gpt":0.3405270439910454,"score_spread":0.2663384166627635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043265686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77275324,0.000018266954,0.21992445,0.0060723857,0.000011226356,0.0007818986,0.00004738953,0.00026284327,0.00012832107],"genre_scores_gemma":[0.9185423,0.000025387943,0.072496034,0.008763939,0.000064058724,0.000028108805,0.000022871456,0.000037598493,0.00001965814],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988241,0.00008696293,0.00023141595,0.0004934188,0.00014496254,0.00021912913],"domain_scores_gemma":[0.99917597,0.00012114516,0.000055739336,0.0002829178,0.000062522435,0.0003017231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007804208,0.00017448765,0.0002607025,0.00012311449,0.00012112408,0.000028793627,0.000054124786,0.0000466681,0.000030653027],"category_scores_gemma":[0.00012993198,0.00017646329,0.000046924946,0.000499022,0.000069392554,0.00011606035,0.00013224679,0.00028777236,0.000015234352],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007897599,0.00016812164,0.009023693,0.000026327789,0.0000026769178,0.00027892264,0.00013629411,0.000045594057,0.989359,0.000060983988,0.00020071525,0.00061869493],"study_design_scores_gemma":[0.003959397,0.00034547027,0.26487866,0.0001836047,0.000118725424,0.00030201185,0.000086015745,0.598215,0.1282408,0.00020765598,0.0028917578,0.00057091523],"about_ca_topic_score_codex":0.000068560075,"about_ca_topic_score_gemma":0.000007033215,"teacher_disagreement_score":0.8611182,"about_ca_system_score_codex":0.0000314523,"about_ca_system_score_gemma":0.000039341667,"threshold_uncertainty_score":0.7195964},"labels":[],"label_agreement":null},{"id":"W3043374188","doi":"10.1111/ejn.15055","title":"Multivariate white matter alterations are associated with epilepsy duration","year":2020,"lang":"en","type":"preprint","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Engineering and Physical Sciences Research Council; Medical Research Council; National Institute for Health and Care Research; Wellcome Trust","keywords":"Univariate; White matter; Multivariate statistics; Epilepsy; Fractional anisotropy; Multivariate analysis; Univariate analysis; Temporal lobe; Mahalanobis distance; Psychology; Cingulum (brain); Diffusion MRI; Internal medicine; Medicine; Magnetic resonance imaging; Mathematics; Neuroscience; Statistics; Radiology","score_opus":0.09154424593793947,"score_gpt":0.33626451412927505,"score_spread":0.24472026819133558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043374188","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29763645,0.000048452006,0.6362434,0.05935943,0.0007943421,0.0011061433,0.0001208338,0.00030608554,0.00438486],"genre_scores_gemma":[0.9800275,0.000036289213,0.014557208,0.004743599,0.00021613689,0.000005026522,0.000012584492,0.000059778627,0.00034186724],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980552,0.00026510863,0.0006423002,0.00042232612,0.00042622953,0.00018879333],"domain_scores_gemma":[0.99751776,0.000041166997,0.0014588687,0.00039476942,0.00036938026,0.0002180306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034084174,0.00022807703,0.00035678243,0.00015003578,0.00015212076,0.00013437346,0.00040319655,0.000028350627,0.000015471847],"category_scores_gemma":[0.00044705666,0.00017751264,0.0001263493,0.00032070145,0.00015109073,0.0001785331,0.00023822056,0.0011070642,0.000019101088],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006941393,0.0017464561,0.31752807,0.00036128782,0.00012101885,0.011107599,0.0019157088,0.013025637,0.6143517,0.00034319464,0.036835507,0.0019696965],"study_design_scores_gemma":[0.00051080284,0.00044070676,0.9912541,0.0007224546,0.00010590997,0.0005610737,0.000013108251,0.0027585737,0.0005413029,0.00013383778,0.0027682933,0.0001898726],"about_ca_topic_score_codex":3.9857366e-7,"about_ca_topic_score_gemma":2.5139207e-7,"teacher_disagreement_score":0.68239105,"about_ca_system_score_codex":0.00005296641,"about_ca_system_score_gemma":0.00012388024,"threshold_uncertainty_score":0.7238755},"labels":[],"label_agreement":null},{"id":"W3043604393","doi":"10.1016/j.mri.2020.07.007","title":"Evaluation of discrete orthogonal versus polar Stockwell Transform for local multi-resolution texture analysis using brain MRI of multiple sclerosis patients","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Pattern recognition (psychology); Artificial intelligence; Fluid-attenuated inversion recovery; Random forest; Invariant (physics); Computer science; Texture (cosmology); Magnetic resonance imaging; Mathematics; Image (mathematics); Medicine; Radiology","score_opus":0.12231463983093242,"score_gpt":0.35843186599575555,"score_spread":0.2361172261648231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043604393","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13329388,0.0018418148,0.86159384,0.0014531534,0.000024604495,0.0014204571,0.00028908142,0.000048128204,0.000035014946],"genre_scores_gemma":[0.92024726,0.000035057306,0.07931344,0.00014873984,0.000027431268,0.0000744727,0.000119947465,0.000026937381,0.000006721274],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982678,0.000060663082,0.00046527627,0.00038784777,0.0005881939,0.00023021155],"domain_scores_gemma":[0.99872595,0.00012106941,0.00020982543,0.0002688885,0.0005804623,0.000093819894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033526716,0.00016745928,0.0003597321,0.0001387717,0.000084335006,0.000008016619,0.00011728149,0.00004415454,0.000025638248],"category_scores_gemma":[0.00034742863,0.00016510165,0.00023473348,0.00069475325,0.00016542836,0.00011359521,0.000033409644,0.00012918723,4.49065e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017360802,0.00047440504,0.11440559,0.00027299346,0.00012946024,0.000001198304,0.00080276135,0.030486885,0.041497543,0.00009804354,0.00028963375,0.8098054],"study_design_scores_gemma":[0.00481874,0.000265616,0.10279601,0.000095224495,0.001293565,5.7249645e-7,0.00008906928,0.8854265,0.004170278,0.000052638054,0.0008615822,0.00013020363],"about_ca_topic_score_codex":0.000077443634,"about_ca_topic_score_gemma":0.000019549581,"teacher_disagreement_score":0.85493964,"about_ca_system_score_codex":0.00009664336,"about_ca_system_score_gemma":0.000086184904,"threshold_uncertainty_score":0.673265},"labels":[],"label_agreement":null},{"id":"W3043810011","doi":"10.1016/j.schres.2020.05.044","title":"Altered structural connectivity and cytokine levels in Schizophrenia and Genetic high-risk individuals: Associations with disease states and vulnerability","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"National Key Research and Development Program of China; National Science Fund for Distinguished Young Scholars; National High-tech Research and Development Program; China Medical University; Liaoning Revitalization Talents Program; University of Science and Technology Liaoning; National Natural Science Foundation of China","keywords":"Schizophrenia (object-oriented programming); Disease; Vulnerability (computing); Psychology; Neuroscience; Medicine; Psychiatry; Internal medicine","score_opus":0.0964157235275952,"score_gpt":0.38364696221648326,"score_spread":0.28723123868888806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3043810011","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911209,0.00035371154,0.00048160806,0.0064487685,0.000006164144,0.0009595022,0.00047277584,0.00013682527,0.000019754192],"genre_scores_gemma":[0.9784656,0.00028712483,0.020873465,0.00009687192,0.00008469849,0.000102630416,0.000031614094,0.000040293224,0.000017672386],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981718,0.00027391862,0.00021725959,0.0006422343,0.000357747,0.00033705775],"domain_scores_gemma":[0.9986089,0.00043322865,0.00007256951,0.00029394508,0.00011515068,0.00047619612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003362723,0.00017776515,0.0003052994,0.00015993365,0.00027744786,0.00008145453,0.00008718489,0.000053209253,0.000024246368],"category_scores_gemma":[0.00077533186,0.00014694096,0.000016690105,0.00045547105,0.00046543215,0.00012055168,0.00022465631,0.00072667404,0.000002190756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013799041,0.00007612453,0.97547483,0.00011733577,0.00004051804,0.000038427937,0.00024885562,0.000023377956,0.0027936827,0.001738318,0.00016147774,0.017907126],"study_design_scores_gemma":[0.0031866203,0.00029782616,0.9766213,0.000042941287,0.00003699723,0.000015597112,0.000038882856,0.0033607227,0.00038742536,0.015792567,0.00007010486,0.000148985],"about_ca_topic_score_codex":0.00025242503,"about_ca_topic_score_gemma":0.00011341886,"teacher_disagreement_score":0.020391857,"about_ca_system_score_codex":0.0000488052,"about_ca_system_score_gemma":0.00012613833,"threshold_uncertainty_score":0.5992079},"labels":[],"label_agreement":null},{"id":"W3044661579","doi":"10.1007/s42952-020-00082-5","title":"Nonparametric matrix regression function estimation over symmetric positive definite matrices","year":2020,"lang":"en","type":"article","venue":"Journal of the Korean Statistical Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"National Research Foundation of Korea","keywords":"Mathematics; Cholesky decomposition; Positive-definite matrix; Applied mathematics; Smoothing; Estimator; Wishart distribution; Statistics; Eigenvalues and eigenvectors; Multivariate statistics","score_opus":0.04228050699660648,"score_gpt":0.3581747937036231,"score_spread":0.31589428670701664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044661579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045343522,0.00033636787,0.9459151,0.007576621,0.00009708549,0.00028933104,0.00007161826,0.000054901117,0.000315469],"genre_scores_gemma":[0.7683012,0.00020607834,0.22924425,0.001992447,0.00017945022,0.0000028757574,0.000011491482,0.000019626495,0.00004262062],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99883133,0.000048720583,0.00038999872,0.00014382985,0.00044586934,0.0001402608],"domain_scores_gemma":[0.9986187,0.00044710923,0.00043426265,0.00014216118,0.00018655858,0.0001711679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017874711,0.000118919284,0.0002456676,0.000055884666,0.00013843473,0.000030060608,0.00012857014,0.00006286181,0.00003860206],"category_scores_gemma":[0.00072340464,0.00007040949,0.00024668974,0.0010780721,0.000083571635,0.0001134293,0.000063498526,0.00048565833,0.000008980172],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028701918,0.0016509737,0.043785475,0.0009353133,0.0008494884,0.00015622395,0.0013459913,0.0018848657,0.023273502,0.13370994,0.5036443,0.28589374],"study_design_scores_gemma":[0.004815643,0.0031718016,0.64609677,0.0007918548,0.0028623543,0.00088224007,0.0003223125,0.2578365,0.0056351093,0.06382873,0.013130887,0.00062583986],"about_ca_topic_score_codex":0.000004185261,"about_ca_topic_score_gemma":4.015162e-8,"teacher_disagreement_score":0.7229577,"about_ca_system_score_codex":0.00010635803,"about_ca_system_score_gemma":0.000057111603,"threshold_uncertainty_score":0.2871216},"labels":[],"label_agreement":null},{"id":"W3044899728","doi":"10.1016/j.neuroscience.2020.06.027","title":"Corrigendum to “Brain Structural Connectivity Predicts Brain Functional Complexity: Diffusion Tensor Imaging Derived Centrality Accounts for Variance in Fractal Properties of Functional Magnetic Resonance Imaging Signal” [Neuroscience 438C (2020) 1–8]","year":2020,"lang":"en","type":"erratum","venue":"Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Diffusion MRI; Neuroscience; Functional magnetic resonance imaging; Functional connectivity; Centrality; Neuroimaging; Magnetic resonance imaging; Fractal; SIGNAL (programming language); Connectome; Statistical physics; Psychology; Nuclear magnetic resonance; Physics; Computer science; Mathematics; Medicine; Mathematical analysis","score_opus":0.09736855223200129,"score_gpt":0.3124164307252884,"score_spread":0.2150478784932871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044899728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26128417,0.0035876087,0.5131985,0.14574155,0.048912715,0.019474639,0.0050127185,0.0019781685,0.0008099091],"genre_scores_gemma":[0.96993077,0.00006147428,0.0025560192,0.02097946,0.0007512866,0.0004452815,0.00015222872,0.00011638109,0.0050071017],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9946065,0.00016026768,0.0008408747,0.0021778431,0.0012793711,0.0009351207],"domain_scores_gemma":[0.9977625,0.0001928292,0.0005063097,0.0007260664,0.00042274036,0.00038956894],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039451514,0.00062750466,0.0008147719,0.00029066036,0.00050852203,0.0001375956,0.00073824957,0.00013893702,0.00003619518],"category_scores_gemma":[0.0029883776,0.0006004414,0.0002020237,0.0013587645,0.0012381133,0.0005512501,0.00053140364,0.0013025659,0.000002919615],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008085959,0.00030126664,0.0340327,0.00043808663,0.0000017534239,0.000108606335,0.00017091427,0.00021028749,0.79295516,0.00039095854,0.16379969,0.006782007],"study_design_scores_gemma":[0.0012145127,0.00033589383,0.74846715,0.0006178566,0.000039267237,0.0002787235,0.000032769167,0.15253036,0.002815193,0.0009717377,0.09205661,0.0006399305],"about_ca_topic_score_codex":0.00007519105,"about_ca_topic_score_gemma":0.000014594786,"teacher_disagreement_score":0.7901399,"about_ca_system_score_codex":0.00025303502,"about_ca_system_score_gemma":0.000789487,"threshold_uncertainty_score":0.9996447},"labels":[],"label_agreement":null},{"id":"W3044930821","doi":"10.1097/j.pain.0000000000002023","title":"Trigeminal neuralgia diffusivities using Gaussian process classification and merged group tractography","year":2020,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network; University of Toronto","funders":"","keywords":"Trigeminal neuralgia; Tractography; Medicine; Diffusion MRI; Process (computing); Psychology; Artificial intelligence; Computer science; Anesthesia; Radiology; Magnetic resonance imaging","score_opus":0.14605535532845418,"score_gpt":0.3691009170761813,"score_spread":0.22304556174772713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044930821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7262214,0.00019768602,0.2609784,0.0112184035,0.000013660592,0.0005405554,0.000008858461,0.00037274693,0.00044831174],"genre_scores_gemma":[0.990582,0.000052778745,0.007851753,0.0013580414,0.00006897491,0.00004102624,0.000014949629,0.000017640867,0.000012817958],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993888,0.000055882327,0.00013365828,0.00021514019,0.00009309808,0.00011343664],"domain_scores_gemma":[0.99964213,0.00006054642,0.000058492853,0.00010867972,0.000021711034,0.00010844366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016077104,0.00009010064,0.00012528716,0.00004705151,0.000084871404,0.000014876555,0.00004349111,0.000029516004,0.000011385388],"category_scores_gemma":[0.00010398857,0.000080225975,0.000034803936,0.00023455944,0.0000668895,0.00006623452,0.000010577691,0.00013657463,7.2845654e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018197489,0.00020973697,0.14028183,0.0006093741,0.000025400039,0.000021525826,0.001445887,0.0000041733183,0.7965046,0.004265135,0.0013370173,0.05511334],"study_design_scores_gemma":[0.0025199596,0.0009753325,0.56221706,0.00041025897,0.00044758336,0.00018061735,0.003510663,0.376312,0.017018981,0.0078691635,0.02749925,0.0010391378],"about_ca_topic_score_codex":0.0000041630146,"about_ca_topic_score_gemma":4.0567033e-7,"teacher_disagreement_score":0.77948564,"about_ca_system_score_codex":0.0000077184195,"about_ca_system_score_gemma":0.000010499946,"threshold_uncertainty_score":0.32715204},"labels":[],"label_agreement":null},{"id":"W3045895067","doi":"10.1126/sciadv.aba8245","title":"A new method for accurate in vivo mapping of human brain connections using microstructural and anatomical information","year":2020,"lang":"en","type":"article","venue":"Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":115,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Computer science; Human brain; Tractography; Diffusion MRI; Modality (human–computer interaction); Magnetic resonance imaging; Artificial intelligence; Neuroscience; Neuroimaging; Brain anatomy; Medicine; Psychology; Radiology","score_opus":0.08814232277767962,"score_gpt":0.4413802390142868,"score_spread":0.35323791623660716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3045895067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46058446,0.00004194021,0.5356869,0.0032571468,0.000014987046,0.00032497506,0.00000991107,0.000032608754,0.00004708447],"genre_scores_gemma":[0.5303858,0.0000039072315,0.46897596,0.00060371595,0.000015513202,0.0000068679574,0.0000014205169,0.0000023883163,0.000004398729],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99948955,0.0000052006726,0.00017613299,0.00014162155,0.000075497075,0.00011198661],"domain_scores_gemma":[0.9996629,0.00005500857,0.00008801259,0.00006950882,0.000054493437,0.000070100876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011318634,0.000051193194,0.00011389137,0.000108749984,0.00011131921,0.000016955137,0.00007256362,0.000012886437,0.000003268144],"category_scores_gemma":[0.00021144505,0.000046190107,0.000016931379,0.0005630922,0.00014853393,0.0007158549,0.000034297398,0.000056845627,9.295314e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011338403,0.00000229733,0.00082871993,0.000032146112,6.0811226e-7,1.3077491e-7,0.0004324416,0.00010224094,0.9849843,0.0020689229,0.000028679755,0.011508178],"study_design_scores_gemma":[0.0014151921,0.00025498267,0.0056926413,0.00013723985,0.000016686454,0.00006029666,0.0023324778,0.070940495,0.88765365,0.017397307,0.013887868,0.00021117715],"about_ca_topic_score_codex":0.000031252683,"about_ca_topic_score_gemma":0.0000038141015,"teacher_disagreement_score":0.09733066,"about_ca_system_score_codex":0.000026549153,"about_ca_system_score_gemma":0.00008125774,"threshold_uncertainty_score":0.18835779},"labels":[],"label_agreement":null},{"id":"W3046299915","doi":"10.1016/j.jpsychires.2020.07.034","title":"Progression of neuroanatomical abnormalities after first-episode of psychosis: A 3-year longitudinal sMRI study","year":2020,"lang":"en","type":"article","venue":"Journal of Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Galway; Health Research Board","keywords":"Putamen; Psychosis; Internal medicine; Medicine; Cardiology; Thalamus; Nuclear medicine; Antipsychotic; Psychology; Schizophrenia (object-oriented programming); Psychiatry; Radiology","score_opus":0.1758948120279407,"score_gpt":0.4786170864389108,"score_spread":0.3027222744109701,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046299915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9835221,0.00096940045,0.0013407279,0.013007288,0.000065290886,0.0007426757,0.0000075556627,0.000018614957,0.00032634783],"genre_scores_gemma":[0.98489237,0.00042574393,0.014246197,0.00007188239,0.0002851069,0.000037020585,4.8464454e-7,0.000023251303,0.000017956836],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99735934,0.00015321517,0.00083480537,0.00021795134,0.0011894881,0.00024521077],"domain_scores_gemma":[0.99816173,0.00015283046,0.0003817762,0.00033397673,0.0007355818,0.00023412467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008300369,0.00011578255,0.00043334288,0.0004174381,0.000062741936,0.0000130232365,0.00031994007,0.000052157553,0.00006541121],"category_scores_gemma":[0.0002507544,0.00008606049,0.00019850067,0.0010512294,0.00016448292,0.00008962363,0.00010983003,0.0008170832,0.0000034194384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027002865,0.0016176162,0.9798027,0.0003796417,0.000056042172,0.000075739525,0.00043026582,0.000007839429,0.0003672277,0.00025578184,0.012622468,0.0016843614],"study_design_scores_gemma":[0.0053568915,0.018504845,0.95969254,0.00055272185,0.00031181192,0.0003063723,0.0016078199,0.00044231318,0.0030744423,0.0020765327,0.0078397505,0.00023398806],"about_ca_topic_score_codex":0.000017390626,"about_ca_topic_score_gemma":0.0000030957362,"teacher_disagreement_score":0.020110218,"about_ca_system_score_codex":0.000026894926,"about_ca_system_score_gemma":0.00009220838,"threshold_uncertainty_score":0.35498652},"labels":[],"label_agreement":null},{"id":"W3046367338","doi":"10.1016/j.neuroimage.2020.117201","title":"On the cortical connectivity in the macaque brain: A comparison of diffusion tractography and histological tracing data","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":86,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Deutsche Forschungsgemeinschaft; Istituto Italiano di Tecnologia; Biotechnology and Biological Sciences Research Council; Centre d'Imagerie BioMédicale; Ministero dell’Istruzione, dell’Università e della Ricerca; École Polytechnique Fédérale de Lausanne","keywords":"Macaque; Tractography; Tracing; Diffusion MRI; Neuroscience; Diffusion; Computer science; Psychology; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.23989418107237792,"score_gpt":0.4038346123790556,"score_spread":0.16394043130667768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046367338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91475916,0.00003728016,0.006200623,0.077887945,0.000007407731,0.0004747186,0.00002008017,0.00005348565,0.0005593104],"genre_scores_gemma":[0.98998034,0.000019331123,0.00048148457,0.009464461,0.00001864419,0.000015165161,0.000010291987,0.000008708669,0.0000015445887],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990757,0.00014837568,0.00019456261,0.0003113146,0.00015838968,0.00011163046],"domain_scores_gemma":[0.9978876,0.0014819109,0.00006944395,0.00050072576,0.00001240721,0.000047919548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014985536,0.0000925631,0.00020601234,0.000026805475,0.00008018356,0.00001122279,0.00024214605,0.000031874668,0.000010514289],"category_scores_gemma":[0.00094787515,0.0000508639,0.00003482084,0.00022620054,0.00021116223,0.00004098833,0.000106292784,0.0006054576,8.8266694e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013154413,0.0038071447,0.21913473,0.00026696944,0.000025022287,0.0003810477,0.004146796,0.000017901808,0.6366222,0.0622216,0.042371675,0.029689472],"study_design_scores_gemma":[0.0012812562,0.0014759557,0.9334102,0.00008235976,0.00009002538,0.00014708326,0.0004823353,0.043772466,0.005205723,0.0027758046,0.011072606,0.00020417744],"about_ca_topic_score_codex":0.000008039059,"about_ca_topic_score_gemma":0.0000028682518,"teacher_disagreement_score":0.7142755,"about_ca_system_score_codex":0.0000041198086,"about_ca_system_score_gemma":0.0000087620865,"threshold_uncertainty_score":0.26304457},"labels":[],"label_agreement":null},{"id":"W3046471534","doi":"10.1101/2020.08.03.197384","title":"TractoFlow-ABS (Atlas-Based Segmentation)","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"White matter; Tractography; Atlas (anatomy); Diffusion MRI; Hyperintensity; Segmentation; Computer science; Artificial intelligence; Anatomy; Pattern recognition (psychology); Magnetic resonance imaging; Biology; Medicine; Radiology","score_opus":0.05107801343008658,"score_gpt":0.3052864410448513,"score_spread":0.2542084276147647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046471534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6237959,0.0010428845,0.33133623,0.027626762,0.0011213971,0.0065875547,0.0010261054,0.0073136594,0.0001494792],"genre_scores_gemma":[0.8494204,0.00011186592,0.14659575,0.0026330543,0.00042234777,0.00062655134,0.0000031099744,0.00017752987,0.000009352726],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99756515,0.00003721901,0.00052347453,0.0010734554,0.00040268723,0.00039798755],"domain_scores_gemma":[0.99749035,0.000064333406,0.00035560908,0.0013448821,0.0003321652,0.000412687],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014082954,0.0005097604,0.00059135346,0.00019959256,0.00013703153,0.0000975018,0.00035334352,0.0003135825,0.00008773427],"category_scores_gemma":[0.0001360033,0.0005502289,0.00023347155,0.00049649103,0.000114390044,0.00009216387,0.0002184644,0.0010829445,0.00013333032],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006387497,0.000276874,0.004118656,0.00056236464,0.00007335364,0.00012986475,0.000003589773,0.00005405486,0.99179137,0.00094186456,0.001974874,0.000009289837],"study_design_scores_gemma":[0.0011939959,0.00014063928,0.051355917,0.00053621136,0.00036946498,5.245107e-8,0.00000155992,0.0027202533,0.90783066,0.000031182863,0.034984186,0.0008359018],"about_ca_topic_score_codex":0.000010831939,"about_ca_topic_score_gemma":2.0104402e-7,"teacher_disagreement_score":0.22562452,"about_ca_system_score_codex":0.00024251472,"about_ca_system_score_gemma":0.00052958424,"threshold_uncertainty_score":0.99969494},"labels":[],"label_agreement":null},{"id":"W3046971735","doi":"10.1101/2020.08.06.237271","title":"White Matter Disruption in Pediatric Traumatic Brain Injury: Results from ENIGMA Pediatric msTBI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Hospital for Sick Children; University of Toronto; University of Calgary","funders":"Brain Injury Research Center; National Health and Medical Research Council; Medical Research Council; Alberta Children's Hospital Foundation; Children's Hospital Foundation; National Alliance for Research on Schizophrenia and Depression","keywords":"Traumatic brain injury; White matter; Context (archaeology); Medicine; Neuropathology; Concussion; Psychology; Diffusion MRI; Injury prevention; Poison control; Magnetic resonance imaging; Clinical psychology; Psychiatry; Internal medicine; Emergency medicine; Disease; Radiology","score_opus":0.043232185945327774,"score_gpt":0.2990356973281166,"score_spread":0.2558035113827888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046971735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9771583,0.0003740042,0.0062482045,0.011582872,0.00035193024,0.0019687528,0.0012893873,0.0009899742,0.000036540278],"genre_scores_gemma":[0.96834433,0.00079784583,0.027010612,0.0016196873,0.001507719,0.00048571007,0.000011023953,0.00021030438,0.000012765485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960915,0.00013804717,0.0011400288,0.0016074589,0.00046838663,0.00055460224],"domain_scores_gemma":[0.9968685,0.00017005386,0.00066424016,0.0017231142,0.0001928549,0.00038124967],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037321882,0.00065581006,0.00085494656,0.0005836349,0.000094454066,0.000117335185,0.0004926526,0.0004998848,0.00006194762],"category_scores_gemma":[0.00039349153,0.00071526546,0.00021048207,0.00128263,0.000059432794,0.00015849175,0.00046269843,0.0016228408,0.0002653604],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000588999,0.00089415285,0.91551876,0.0020057391,0.000077339035,0.0003181256,0.0001365722,0.00006653922,0.056575283,0.00024079192,0.02356401,0.000013666276],"study_design_scores_gemma":[0.0012864985,0.000086662534,0.99140537,0.00024935883,0.0003504793,4.3685638e-8,0.0000030025703,0.0007058002,0.003384701,0.00004938685,0.001709758,0.00076893205],"about_ca_topic_score_codex":0.00006265276,"about_ca_topic_score_gemma":0.0000022882223,"teacher_disagreement_score":0.0758866,"about_ca_system_score_codex":0.00030178303,"about_ca_system_score_gemma":0.00036230526,"threshold_uncertainty_score":0.99952984},"labels":[],"label_agreement":null},{"id":"W3047160690","doi":"10.1101/2020.08.06.237941","title":"The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fondation EDF; Fondation Institut de Cardiologie de Montréal; Agence Nationale de la Recherche; Réseau en Bio-Imagerie du Quebec; Wellcome Trust; Institut de Cardiologie de Montréal; Fondation Brain Canada","keywords":"Connectome; Diffusion MRI; Connectomics; Tractography; White matter; Human Connectome Project; Myelin; Neuroscience; Metric (unit); Computer science; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Central nervous system","score_opus":0.041626246456411706,"score_gpt":0.2811708767039073,"score_spread":0.23954463024749556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047160690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2698388,0.001961236,0.6586673,0.055178992,0.00065693655,0.008265256,0.00045032732,0.0048451554,0.00013596498],"genre_scores_gemma":[0.9632101,0.00015667288,0.033000384,0.0023524894,0.00063019665,0.00043898282,0.0000022981462,0.00020246334,0.000006385004],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99706197,0.00014185839,0.0005521323,0.0011188034,0.00048473215,0.0006404862],"domain_scores_gemma":[0.99649805,0.00033327492,0.00053867436,0.0014507788,0.0008383128,0.00034089934],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005135115,0.0005874218,0.00067938236,0.00010297728,0.0005375442,0.0001902083,0.0004229652,0.00024764496,0.000009618519],"category_scores_gemma":[0.00027310342,0.00045294975,0.0001646413,0.0007017068,0.00027810325,0.000060556802,0.0005017948,0.0016334833,0.000015624222],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008739423,0.000527132,0.018085487,0.00093207875,0.0018302762,0.0010664155,0.000068413094,0.00037250028,0.9384349,0.020826032,0.016878158,0.00010467785],"study_design_scores_gemma":[0.007814435,0.0011472199,0.20300244,0.0068588033,0.0025735698,0.0000023795153,0.00007731348,0.08578377,0.41612914,0.00009666716,0.27135608,0.0051581715],"about_ca_topic_score_codex":0.00001542603,"about_ca_topic_score_gemma":0.000003194336,"teacher_disagreement_score":0.6933713,"about_ca_system_score_codex":0.00018836893,"about_ca_system_score_gemma":0.0004173765,"threshold_uncertainty_score":0.9997922},"labels":[],"label_agreement":null},{"id":"W3047356090","doi":"10.1101/2020.08.06.234526","title":"Neurofeedback fMRI in the motor system elicits bi-directional changes in activity and white-matter structure in the healthy adult human brain","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"University of Oxford; National Institute for Health and Care Research; Wellcome Trust","keywords":"White matter; Neurofeedback; Neuroscience; Corpus callosum; Neuromodulation; Brain activity and meditation; Motor cortex; Psychology; Diffusion MRI; Fractional anisotropy; Neuroplasticity; Cortex (anatomy); Human brain; Electroencephalography; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.03378423704196926,"score_gpt":0.29339073948751343,"score_spread":0.2596065024455442,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047356090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94498104,0.00013394465,0.00018176807,0.052031625,0.00011159748,0.0021884425,0.0001826499,0.00017784761,0.000011085019],"genre_scores_gemma":[0.9899484,0.00007631625,0.00095622364,0.007941718,0.00030207334,0.00070449343,0.0000010863943,0.00006791063,0.0000017858084],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9976771,0.00037591925,0.0003830658,0.00085659645,0.0003357279,0.0003715803],"domain_scores_gemma":[0.9984797,0.00016973747,0.0002532879,0.00089219713,0.00010750643,0.000097528],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043852293,0.0003935006,0.0005028935,0.00030388174,0.00012850609,0.000088260065,0.0004244045,0.00025809856,0.0000069395414],"category_scores_gemma":[0.00011835989,0.00029540114,0.00005683006,0.00078906334,0.000099418095,0.000068767986,0.00021557807,0.0017616209,0.0000035408925],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000252426,0.00039171265,0.27426243,0.0025628046,0.000029120572,0.00023340355,0.00032550984,0.000035414374,0.7180565,0.0017529232,0.0020866683,0.000011094614],"study_design_scores_gemma":[0.00061246596,0.00009367544,0.99252945,0.00055229873,0.000024118843,6.129493e-7,0.000032091342,0.0004160758,0.004406752,0.000011769215,0.0010514924,0.00026918354],"about_ca_topic_score_codex":0.00021268112,"about_ca_topic_score_gemma":0.00016374432,"teacher_disagreement_score":0.718267,"about_ca_system_score_codex":0.00020891376,"about_ca_system_score_gemma":0.00013362558,"threshold_uncertainty_score":0.9999498},"labels":[],"label_agreement":null},{"id":"W3047649979","doi":"10.1016/j.neuroimage.2021.118312","title":"Permutation-based inference for spatially localized signals in longitudinal MRI data","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Computer science; Univariate; Permutation (music); Neuroimaging; Multiple comparisons problem; False discovery rate; Inference; Artificial intelligence; Alzheimer's Disease Neuroimaging Initiative; Pattern recognition (psychology); Statistical hypothesis testing; Resampling; Statistical power; Spatial analysis; Statistic; Data mining; Machine learning; Mathematics; Disease; Statistics; Alzheimer's disease; Multivariate statistics; Medicine; Neuroscience; Psychology; Pathology; Biology","score_opus":0.18553309047076086,"score_gpt":0.4322014754127328,"score_spread":0.24666838494197194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3047649979","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037024498,0.000083986226,0.95096755,0.009860748,0.000049839047,0.0008868007,0.00023001395,0.0002164169,0.00068017084],"genre_scores_gemma":[0.8911034,0.000042329204,0.10491352,0.0026919588,0.00006554763,0.00014261104,0.00080077053,0.000038784758,0.00020108192],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99873,0.000037280068,0.00027454284,0.0005830062,0.00016597139,0.0002091888],"domain_scores_gemma":[0.9983501,0.00038097714,0.000072521405,0.0009439328,0.00017540061,0.00007706526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012293084,0.00013082124,0.00023071664,0.00007690073,0.000059076687,0.000033034463,0.0002116857,0.000038282076,0.00009287299],"category_scores_gemma":[0.00075693714,0.00013486002,0.000050538863,0.0003044682,0.000062582476,0.00012134746,0.00010279421,0.00018294647,0.000010263176],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011106313,0.0031527553,0.20069095,0.0011224607,0.00005466557,0.002775113,0.00015249586,0.008603083,0.7046799,0.0056807026,0.019944796,0.05203245],"study_design_scores_gemma":[0.008210865,0.0005925507,0.124438345,0.00042327194,0.00022957193,0.00017486731,0.00003225856,0.5971075,0.15401174,0.007338064,0.1066686,0.00077236356],"about_ca_topic_score_codex":0.00001750048,"about_ca_topic_score_gemma":0.000029708672,"teacher_disagreement_score":0.8540789,"about_ca_system_score_codex":0.000024413468,"about_ca_system_score_gemma":0.00028130636,"threshold_uncertainty_score":0.5499432},"labels":[],"label_agreement":null},{"id":"W3049013229","doi":"10.1371/journal.pone.0233244","title":"Multimodal principal component analysis to identify major features of white matter structure and links to reading","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"White matter; Principal component analysis; Diffusion MRI; Neuroscience; Fractional anisotropy; Myelin; Corpus callosum; Superior longitudinal fasciculus; Biology; Nuclear magnetic resonance; Artificial intelligence; Psychology; Computer science; Anatomy; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.0615144840601415,"score_gpt":0.33687436669054377,"score_spread":0.2753598826304023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049013229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9722513,0.000016168773,0.0063864533,0.020630065,0.0000031736738,0.0004847874,0.00006823161,0.00007058531,0.00008922364],"genre_scores_gemma":[0.870207,0.0000038099452,0.12580377,0.003740801,0.000051245435,0.000021260932,0.000026527568,0.000014763705,0.00013082087],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99925274,0.000009642115,0.0001675306,0.00026943994,0.00018461305,0.00011606276],"domain_scores_gemma":[0.9994314,0.000017471137,0.00004889715,0.0002378071,0.00006623965,0.00019821437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000023751507,0.00009489343,0.00029902018,0.00011826243,0.00004842796,0.000010203028,0.00007813783,0.000050049624,0.00006596415],"category_scores_gemma":[0.000035735946,0.00008628768,0.000044009423,0.00039087376,0.000018868288,0.000025398978,0.00015075789,0.00021279186,0.0000073971055],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009127887,0.00014836746,0.22753803,0.00014029731,0.0003294377,0.000006252728,0.0008042441,0.000055554257,0.7702009,0.000055606262,0.00045092264,0.00017909524],"study_design_scores_gemma":[0.00024268478,0.00010129581,0.85133445,0.00008381006,0.00091646105,0.0000029169323,0.000021651551,0.00075199513,0.14617996,0.000050906776,0.00020632624,0.00010756374],"about_ca_topic_score_codex":0.000013767558,"about_ca_topic_score_gemma":0.0000032937166,"teacher_disagreement_score":0.62402093,"about_ca_system_score_codex":0.000014247196,"about_ca_system_score_gemma":0.0000050127046,"threshold_uncertainty_score":0.35187092},"labels":[],"label_agreement":null},{"id":"W3049741828","doi":"10.1016/j.pscychresns.2020.111159","title":"Association of white matter microstructure and extracellular free-water with cognitive performance in the early course of schizophrenia","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"National Institute of Mental Health","keywords":"Fornix; White matter; Stria terminalis; Cingulum (brain); Schizophrenia (object-oriented programming); Psychology; Diffusion MRI; Neuroscience; Extracellular; Cognition; Magnetic resonance imaging; Physiology; Medicine; Fractional anisotropy; Hippocampus; Central nervous system; Chemistry; Psychiatry; Radiology","score_opus":0.044514291600237045,"score_gpt":0.34047741076813665,"score_spread":0.2959631191678996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3049741828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95730376,0.00023417821,0.0002677047,0.041340537,0.00001243324,0.0005453472,0.000025562798,0.000018903103,0.00025156705],"genre_scores_gemma":[0.9965468,0.00006444398,0.0026082234,0.0006201637,0.000054760545,0.000026124322,0.000008625542,0.00002354358,0.000047312922],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872893,0.00011705909,0.00022299706,0.00027523286,0.00038821145,0.0002675624],"domain_scores_gemma":[0.99928373,0.000092970025,0.00009071127,0.00027112543,0.00020119647,0.000060265604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003643922,0.000108852764,0.0001864898,0.00009625825,0.000117132324,0.000019817537,0.0001827235,0.000032178225,0.000018323155],"category_scores_gemma":[0.000043580083,0.00006787058,0.000029619541,0.00038791762,0.00019335716,0.000115332856,0.000114152004,0.0007082031,0.0000026290006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044254868,0.000066937726,0.97115713,0.00024057744,0.000012997928,0.000005666006,0.0012249518,0.0000026281025,0.026074354,0.0000366244,0.0005100246,0.00022557963],"study_design_scores_gemma":[0.0014006264,0.00035387793,0.9891563,0.00022627972,0.00004142858,0.00004360564,0.00038057842,0.0004177365,0.007172502,0.00039997365,0.00032260787,0.00008449424],"about_ca_topic_score_codex":0.000008556634,"about_ca_topic_score_gemma":0.0000028767236,"teacher_disagreement_score":0.040720373,"about_ca_system_score_codex":0.0000100241205,"about_ca_system_score_gemma":0.000048896214,"threshold_uncertainty_score":0.30768296},"labels":[],"label_agreement":null},{"id":"W3056775138","doi":"10.1002/alz.12150","title":"Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Institute on Aging","keywords":"Diffusion MRI; Voxel; Memory clinic; Disease; Diffusion; Alzheimer's disease; Medicine; Pathology; Magnetic resonance imaging; Radiology; Physics; Dementia","score_opus":0.08351238515880283,"score_gpt":0.3376425455055432,"score_spread":0.25413016034674035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3056775138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9395743,0.022986457,0.0036034482,0.02860316,0.0002628296,0.0035696728,0.0002676988,0.00071367814,0.0004187445],"genre_scores_gemma":[0.9892262,0.00025864187,0.0049183895,0.0044353474,0.00015491576,0.00034137242,0.0005855375,0.000063798536,0.00001574917],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982429,0.000049404367,0.0005005687,0.00062854175,0.00025113174,0.00032744856],"domain_scores_gemma":[0.9984605,0.000049977596,0.00014937295,0.0005830635,0.000093108465,0.00066401856],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000053009964,0.00027680365,0.00027421102,0.0000966176,0.0001519009,0.00003347886,0.00022667968,0.00004491767,0.00013059816],"category_scores_gemma":[0.00006462213,0.00026575886,0.00015297811,0.00028699305,0.00009773804,0.0001710019,0.00019693097,0.00022070439,0.00009493117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010578143,0.002745047,0.9296596,0.0000671097,0.0018384914,0.00026698931,0.00059746177,0.000076312055,0.0018832391,0.00018573353,0.015183016,0.046439167],"study_design_scores_gemma":[0.0031073056,0.00026666012,0.94659215,0.00017264152,0.01825206,0.0000025001702,0.000060473198,0.007845721,0.003158766,0.0005054189,0.019307993,0.0007283108],"about_ca_topic_score_codex":0.000019850804,"about_ca_topic_score_gemma":0.0000060575576,"teacher_disagreement_score":0.049651936,"about_ca_system_score_codex":0.0000062724134,"about_ca_system_score_gemma":0.00008294087,"threshold_uncertainty_score":0.99997944},"labels":[],"label_agreement":null},{"id":"W3080109194","doi":"10.1038/s41598-020-70805-5","title":"Extrapyramidal plasticity predicts recovery after spinal cord injury","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College","funders":"Staatssekretariat für Bildung, Forschung und Innovation; Canadian Institutes of Health Research; University of Toronto; Bundesministerium für Bildung und Forschung; Natural Sciences and Engineering Research Council of Canada; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Canada First Research Excellence Fund; Government of Ontario; International Foundation for Research in Paraplegia; Wellcome Trust; McGill University","keywords":"Basal ganglia; Striatum; Thalamus; Globus pallidus; Putamen; Spinal cord injury; Neuroscience; Neurodegeneration; Subthalamic nucleus; Caudate nucleus; Spinal cord; Medicine; Psychology; Internal medicine; Central nervous system; Parkinson's disease; Deep brain stimulation; Dopamine; Disease","score_opus":0.061134288468266074,"score_gpt":0.3448167550792492,"score_spread":0.2836824666109831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080109194","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9621514,0.000083129,0.030640885,0.0029234544,0.001253434,0.0006850999,0.000016053105,0.0005787043,0.0016678422],"genre_scores_gemma":[0.9897825,0.0000074805675,0.008191351,0.00089938607,0.00018236211,0.00007320407,0.000024228058,0.00001985836,0.00081963773],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998339,0.00000996714,0.0003532222,0.00070894754,0.00035703584,0.00023185949],"domain_scores_gemma":[0.9990016,0.000011369974,0.00014355686,0.00046633944,0.00010589198,0.00027121007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015068683,0.00012465028,0.0001769586,0.000067355,0.00012947261,0.00007514335,0.000071991184,0.000046373134,0.00015894181],"category_scores_gemma":[0.00021239898,0.00011258255,0.000092064045,0.00040157334,0.0002459843,0.00012834856,0.00007981678,0.0002024997,0.000037110174],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.009053168,0.0007183838,0.037283845,0.00043087808,0.00006338013,0.007440874,0.00017218274,0.00004059517,0.5241877,0.00041906562,0.3058875,0.11430249],"study_design_scores_gemma":[0.00041165043,0.0040483545,0.040765293,0.0002862021,0.00015342997,0.0017789534,0.000030815034,0.0010070883,0.13995636,0.015609467,0.7954086,0.0005437998],"about_ca_topic_score_codex":0.0000020638022,"about_ca_topic_score_gemma":3.9878591e-7,"teacher_disagreement_score":0.48952112,"about_ca_system_score_codex":0.000030630446,"about_ca_system_score_gemma":0.00011866882,"threshold_uncertainty_score":0.4590983},"labels":[],"label_agreement":null},{"id":"W3080178531","doi":"10.1093/cercor/bhaa229","title":"Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Macaque; Magnetic resonance imaging; Brain size; White matter; Temporal lobe; Neuroimaging; Rhesus macaque; Primate; Brain morphometry; Neuroscience; Brain mapping; Population; Psychology; Biology; Medicine; Radiology; Epilepsy","score_opus":0.06908955090232012,"score_gpt":0.33725810792169447,"score_spread":0.26816855701937437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080178531","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95860493,0.000010869738,0.03570064,0.0044943066,0.000008746336,0.00037621433,0.0002176487,0.000109810724,0.00047685308],"genre_scores_gemma":[0.99058944,0.0000017129834,0.006864343,0.0020436416,0.000018625862,0.000020240628,0.0004389281,0.00001132836,0.0000117547515],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99900854,0.000043693242,0.000326489,0.00022897404,0.00028403883,0.00010824461],"domain_scores_gemma":[0.9991935,0.00014451615,0.00026226262,0.00023470503,0.00007887977,0.000086132466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053253963,0.00012329033,0.00040588217,0.0002166634,0.000032864187,0.0000063316566,0.00012567671,0.00004578017,0.00011650613],"category_scores_gemma":[0.0000885041,0.0001044197,0.00016574666,0.0008271442,0.00007379723,0.000043084376,0.000024228631,0.0001280723,0.000001899941],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043778037,0.00039236803,0.9786523,0.00020544455,0.00033011907,0.0000065639124,0.0004516371,0.0014645793,0.00893654,0.0019056405,0.0011361791,0.0060808533],"study_design_scores_gemma":[0.0005236207,0.0005647223,0.86584085,0.000055673216,0.00056145684,3.458079e-7,0.000038631835,0.12209967,0.009921798,0.00023725034,0.000058028534,0.00009797333],"about_ca_topic_score_codex":0.000052342362,"about_ca_topic_score_gemma":0.0000069753282,"teacher_disagreement_score":0.12063509,"about_ca_system_score_codex":0.000019096356,"about_ca_system_score_gemma":0.00003528501,"threshold_uncertainty_score":0.42581117},"labels":[],"label_agreement":null},{"id":"W3080288479","doi":"10.1007/s00429-020-02129-z","title":"Brain connections derived from diffusion MRI tractography can be highly anatomically accurate—if we know where white matter pathways start, where they end, and where they do not go","year":2020,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Vanderbilt Institute for Clinical and Translational Research; Foundation for the National Institutes of Health","keywords":"Tractography; Voxel; Diffusion MRI; Computer science; Artificial intelligence; Human Connectome Project; White matter; Segmentation; Connectomics; Pattern recognition (psychology); Neuroscience; Connectome; Psychology; Magnetic resonance imaging; Functional connectivity; Medicine; Radiology","score_opus":0.02115534676963457,"score_gpt":0.2536576812219556,"score_spread":0.23250233445232102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080288479","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7865252,0.0013881134,0.014319159,0.19482829,0.00015725901,0.0009750993,0.0011165977,0.00044129146,0.00024902177],"genre_scores_gemma":[0.9838734,0.0018601118,0.0025528995,0.010831806,0.00033754992,0.000049743387,0.0002823733,0.00006887748,0.0001432084],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982831,0.00009027103,0.00034273477,0.00077070436,0.00021946477,0.0002937392],"domain_scores_gemma":[0.99882066,0.00020925161,0.00017878742,0.0003944557,0.00009482691,0.0003019953],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005763645,0.00037451292,0.000396796,0.000105939034,0.0003401484,0.00012530574,0.00010550905,0.00023928533,0.00042503932],"category_scores_gemma":[0.00003514266,0.00030636293,0.00011104762,0.00021058512,0.000118440694,0.000208466,0.000086497734,0.00056683074,0.0000043757527],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012542446,0.00012442653,0.078218915,0.00029957932,0.00020761605,0.00003474546,0.0052556964,0.00003452016,0.7620528,0.0021867254,0.09100885,0.059321884],"study_design_scores_gemma":[0.005633633,0.0012071447,0.4998263,0.00053141656,0.0005750893,0.00022449042,0.003892624,0.001245139,0.004584894,0.023059687,0.45792937,0.0012902096],"about_ca_topic_score_codex":0.0005302583,"about_ca_topic_score_gemma":0.0025546134,"teacher_disagreement_score":0.7574679,"about_ca_system_score_codex":0.000034353317,"about_ca_system_score_gemma":0.000045819677,"threshold_uncertainty_score":0.99993885},"labels":[],"label_agreement":null},{"id":"W3080671127","doi":"10.1093/cercor/bhaa220","title":"Investigating Sexual Dimorphism of Human White Matter in a Harmonized, Multisite Diffusion Magnetic Resonance Imaging Study","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; National Research Foundation of Korea; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Sexual dimorphism; Fractional anisotropy; White matter; Diffusion MRI; Sex characteristics; Neuroimaging; Magnetic resonance imaging; Psychology; Neuroscience; Brain Structure and Function; Biology; Medicine; Endocrinology","score_opus":0.05893061070329219,"score_gpt":0.3263750090167659,"score_spread":0.2674443983134737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080671127","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99524915,0.00021705015,0.0003747154,0.0028659913,0.000013126329,0.00084650423,0.000009080223,0.00012892504,0.00029544317],"genre_scores_gemma":[0.9918457,0.0000031434208,0.005528749,0.0022171205,0.000052324798,0.00006051565,0.0000151706945,0.00003870276,0.00023855078],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987126,0.000039721526,0.00040626436,0.0004379529,0.0001904336,0.00021301862],"domain_scores_gemma":[0.999352,0.000021731214,0.00012200216,0.0003290036,0.000046907073,0.00012835169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006550917,0.00016307076,0.00030367062,0.00007744892,0.00007110672,0.00001331268,0.00014068594,0.000026941876,0.00013079542],"category_scores_gemma":[0.00003996281,0.00015809237,0.000037410595,0.00034093787,0.000102049926,0.000086679705,0.00017736948,0.0003043766,0.00001828154],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017119039,0.00014670608,0.8932807,0.000040223025,0.000001260775,0.000029560351,0.0009085036,8.930602e-7,0.10096294,0.000023393624,0.00041839646,0.004170334],"study_design_scores_gemma":[0.0017162126,0.0003068693,0.99265486,0.00009843681,0.000026574291,0.000014204781,0.00039639085,0.0034081286,0.0008413746,0.00016520728,0.00022810351,0.00014366632],"about_ca_topic_score_codex":0.00011533095,"about_ca_topic_score_gemma":0.000013988139,"teacher_disagreement_score":0.10012156,"about_ca_system_score_codex":0.000027156051,"about_ca_system_score_gemma":0.000014694857,"threshold_uncertainty_score":0.644682},"labels":[],"label_agreement":null},{"id":"W3080676737","doi":"10.3174/ajnr.a6742","title":"Patterning Chronic Active Demyelination in Slowly Expanding/Evolving White Matter MS Lesions","year":2020,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; NeuroRx Research (Canada)","funders":"Biogen","keywords":"Magnetization transfer; Multiple sclerosis; White matter; Medicine; Magnetic resonance imaging; Lesion; Tolerability; Myelin; Diffusion MRI; Nuclear medicine; Pathology; Radiology; Internal medicine; Central nervous system","score_opus":0.0489425887480342,"score_gpt":0.349387086446717,"score_spread":0.3004444976986828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080676737","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91491765,0.00007052505,0.053195074,0.03130727,0.000054323908,0.00014541895,0.0000032121438,0.00003414885,0.00027237827],"genre_scores_gemma":[0.9866822,0.00015579756,0.0075018257,0.00535727,0.00025306884,0.000007884652,0.0000030816589,0.00002608667,0.000012794421],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989922,0.00010032684,0.0004006423,0.00020111485,0.000103582875,0.0002021328],"domain_scores_gemma":[0.9990822,0.00012758367,0.00045086665,0.00012113787,0.00008326421,0.00013493276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007821591,0.00011687314,0.00039237528,0.00018816447,0.000042530417,0.0000071417235,0.00014056813,0.000027512042,0.000072947885],"category_scores_gemma":[0.00012955685,0.000104817685,0.000087964785,0.00035333418,0.00014487252,0.00012133351,0.000042031294,0.00057227473,0.000011019392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033683688,0.00012628116,0.8036472,0.000037965892,0.00004519489,0.0005187255,0.0012653384,0.00068286894,0.120594345,0.000080760445,0.0039944826,0.068670005],"study_design_scores_gemma":[0.0009864894,0.0027282005,0.9857097,0.00012692009,0.000058145848,0.0019888203,0.0002507848,0.0019597777,0.001731974,0.0002246892,0.00406195,0.00017251802],"about_ca_topic_score_codex":0.0000056607273,"about_ca_topic_score_gemma":8.3383776e-7,"teacher_disagreement_score":0.18206254,"about_ca_system_score_codex":0.00010295953,"about_ca_system_score_gemma":0.00007092626,"threshold_uncertainty_score":0.42743412},"labels":[],"label_agreement":null},{"id":"W3081107373","doi":"10.1016/j.jneuroling.2020.100937","title":"Onset age of second language acquisition and fractional anisotropy variation in multilingual young adults","year":2020,"lang":"en","type":"article","venue":"Journal of Neurolinguistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Harvard Graduate School of Education; National Institutes of Health","keywords":"Corpus callosum; Fractional anisotropy; Psychology; Variation (astronomy); White matter; Neuroscience of multilingualism; Second-language acquisition; Linguistics; Medicine; Physics; Neuroscience; Astrophysics","score_opus":0.03194613666379724,"score_gpt":0.33819269978942673,"score_spread":0.3062465631256295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081107373","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98794794,0.00006936016,0.01108285,0.0005693991,0.00007027937,0.00010704129,0.000030343335,0.000014919895,0.000107862616],"genre_scores_gemma":[0.97894883,0.000067507644,0.02000141,0.00063334877,0.00032075544,8.808508e-7,0.000009067181,0.0000118993,0.000006283055],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992887,0.000020955602,0.00036393094,0.0000994623,0.00015597155,0.0000709884],"domain_scores_gemma":[0.99928874,0.00008846604,0.0002911774,0.00007168755,0.00018230038,0.00007761527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007384097,0.00006901121,0.00018680356,0.00008236104,0.000019735444,0.000006462761,0.000043773645,0.000035955174,0.000017103406],"category_scores_gemma":[0.0007323876,0.00006677807,0.00003939442,0.00010598495,0.00003319693,0.000034117944,0.000018430428,0.00027655502,4.6437327e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006611258,0.0014354701,0.12359643,0.0010227113,0.00010285391,0.03322716,0.014101437,0.0009554565,0.8109616,0.0013866839,0.0009313777,0.005667562],"study_design_scores_gemma":[0.008152171,0.0031683687,0.9189696,0.00048567355,0.00028345129,0.014811624,0.00047529896,0.03244763,0.011067939,0.004073563,0.0056971232,0.0003676136],"about_ca_topic_score_codex":0.0000053294198,"about_ca_topic_score_gemma":0.0000022613497,"teacher_disagreement_score":0.7998937,"about_ca_system_score_codex":0.000015465643,"about_ca_system_score_gemma":0.00003939709,"threshold_uncertainty_score":0.27231306},"labels":[],"label_agreement":null},{"id":"W3081243461","doi":"10.1101/2020.08.20.20176883","title":"Characterizing the spatiotemporal variability of Alzheimer’s disease pathology","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Temporal lobe; Pathological; Temporal cortex; Pathology; Disease; Alzheimer's disease; Tau pathology; Neuroscience; Population; Biology; Psychology; Medicine","score_opus":0.13374943599488678,"score_gpt":0.3728952556056796,"score_spread":0.23914581961079281,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081243461","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8921371,0.00031056703,0.029159762,0.07491307,0.00023554599,0.0018875645,0.00022374597,0.00038389157,0.0007487475],"genre_scores_gemma":[0.9913148,0.00010748253,0.0067170267,0.0013022159,0.00017625991,0.0002029879,0.00013375373,0.0000313627,0.000014090194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872965,0.00011613797,0.000383936,0.0004688732,0.00016322268,0.00013820149],"domain_scores_gemma":[0.9982739,0.00008114945,0.00030081382,0.0011232509,0.00008827714,0.00013261611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030204578,0.0001789291,0.00038687693,0.000034414905,0.00004809405,0.0000073196757,0.00024725546,0.000088946,0.000034079043],"category_scores_gemma":[0.00032850204,0.00012933131,0.00017323754,0.00009961384,0.00019825624,0.000018447428,0.0004982483,0.00064137665,0.000006623997],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003628962,0.0007130724,0.86357886,0.0013320281,0.00021601545,0.00031119995,0.0006945947,0.000020288979,0.1083784,0.01141381,0.0012125289,0.011766317],"study_design_scores_gemma":[0.00017768405,0.000049928938,0.9551845,0.00015170747,0.00048537977,0.000015102849,0.0000064956084,0.0010928005,0.010540906,0.023589497,0.0085235005,0.0001824723],"about_ca_topic_score_codex":0.000009091491,"about_ca_topic_score_gemma":1.85526e-7,"teacher_disagreement_score":0.09917772,"about_ca_system_score_codex":0.000016023638,"about_ca_system_score_gemma":0.00014317699,"threshold_uncertainty_score":0.52739775},"labels":[],"label_agreement":null},{"id":"W3081458935","doi":"10.1002/jmri.27322","title":"Diffusion Tensor Imaging for Quantitative Assessment of Anterior Cruciate Ligament Injury Grades and Graft","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CAE (Canada)","funders":"","keywords":"Anterior cruciate ligament; Diffusion MRI; Medicine; Quantitative assessment; Radiology; Nuclear medicine; Magnetic resonance imaging; Risk analysis (engineering)","score_opus":0.04984523915810031,"score_gpt":0.3886791500666985,"score_spread":0.3388339109085982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081458935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8153848,0.051922496,0.09474263,0.036783904,0.000081891914,0.0009008254,0.000028366867,0.00004849044,0.00010661277],"genre_scores_gemma":[0.7834125,0.0048214262,0.21055105,0.0010811384,0.0000715774,0.000018237091,3.8815628e-7,0.000024427969,0.00001925716],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986066,0.000029191551,0.0007205139,0.0002125716,0.00024810445,0.00018301631],"domain_scores_gemma":[0.9987338,0.00011919565,0.0005893883,0.00013691086,0.00028602607,0.00013465919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025350694,0.00014768276,0.00049770955,0.000105628336,0.00006820872,0.000028342778,0.000115695075,0.000014904362,0.000007020446],"category_scores_gemma":[0.00022212476,0.000121622164,0.00014438614,0.00014909313,0.00014364907,0.0001519403,0.00007101962,0.00021223383,1.8847666e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039976212,0.00017178738,0.19853143,0.00029334886,0.000011593156,0.00006315293,0.0005696088,0.0000036535523,0.33789232,0.0002390807,0.00061117136,0.46121308],"study_design_scores_gemma":[0.0048968475,0.0031748617,0.88082623,0.006348173,0.00036254607,0.00058965664,0.0013906488,0.05827178,0.01425597,0.0032778126,0.026187567,0.00041792847],"about_ca_topic_score_codex":0.0000036407544,"about_ca_topic_score_gemma":1.0253519e-7,"teacher_disagreement_score":0.6822948,"about_ca_system_score_codex":0.00003491653,"about_ca_system_score_gemma":0.00006491869,"threshold_uncertainty_score":0.4959608},"labels":[],"label_agreement":null},{"id":"W3081825606","doi":"10.3389/fneur.2020.00841","title":"Structural Network Analysis Using Diffusion MRI Tractography in Parkinson's Disease and Correlations With Motor Impairment","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Parkinson's disease; Grey matter; Psychology; Neuroscience; Correlation; Rating scale; Physical medicine and rehabilitation; Disease; Magnetic resonance imaging; Medicine; Pathology; Radiology; Mathematics; Developmental psychology","score_opus":0.019763466834476988,"score_gpt":0.27370152847529605,"score_spread":0.25393806164081906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081825606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9143171,0.00021072819,0.08113506,0.0037582535,0.00004252477,0.000462513,0.000010464246,0.000052916515,0.000010498767],"genre_scores_gemma":[0.9649773,0.00012116393,0.032923467,0.0018590274,0.000045479832,0.000032631455,0.000024809995,0.000013825269,0.0000022645208],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991755,0.0000468116,0.00016852704,0.00033935628,0.0000749478,0.0001948949],"domain_scores_gemma":[0.99958926,0.00002532981,0.00006482209,0.00015990093,0.000011740221,0.00014893804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028924745,0.00011217035,0.00025867225,0.0002271248,0.000052729247,0.000006384491,0.000051629664,0.000042727854,0.0000044119697],"category_scores_gemma":[0.000010584077,0.00009835184,0.00005091318,0.0009258351,0.00009969874,0.00004717197,0.000035066594,0.00026555656,8.6930406e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063114846,0.000032235457,0.98565376,0.0000100192665,0.000025717298,0.00008514714,0.00006982755,0.012881571,0.00007586514,0.000026708783,0.00017734584,0.00033062816],"study_design_scores_gemma":[0.00050890364,0.000187566,0.6906599,0.0000066169946,0.00017513614,0.000007689054,0.000009214014,0.30712456,0.0000014848711,0.00034973735,0.00090639014,0.00006284049],"about_ca_topic_score_codex":0.000013624104,"about_ca_topic_score_gemma":0.000007709137,"teacher_disagreement_score":0.2949939,"about_ca_system_score_codex":0.000013361872,"about_ca_system_score_gemma":0.000017839417,"threshold_uncertainty_score":0.40106717},"labels":[],"label_agreement":null},{"id":"W3081934577","doi":"10.1016/j.neuroimage.2020.117301","title":"A probabilistic atlas of locus coeruleus pathways to transentorhinal cortex for connectome imaging in Alzheimer's disease","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; NIH Blueprint for Neuroscience Research; National Eye Institute; National Institute on Aging; Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; Johnson and Johnson; Janssen Research and Development; National Institutes of Health; H. Lundbeck A/S; IXICO; National Natural Science Foundation of China; Genentech; GE Healthcare; Fujirebio US; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Southern California; Merck","keywords":"Locus coeruleus; Neuroscience; Connectome; Brainstem; Human Connectome Project; Neuroimaging; Brain atlas; Diffusion MRI; Human brain; Psychology; Medicine; Pathology; Magnetic resonance imaging; Central nervous system; Radiology; Functional connectivity","score_opus":0.09872043544272853,"score_gpt":0.3453332707372245,"score_spread":0.24661283529449596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081934577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8977296,0.00047914655,0.060589913,0.0331682,0.00008329139,0.006169667,0.0006040596,0.0005951003,0.0005810298],"genre_scores_gemma":[0.9913095,0.00001213807,0.0052764653,0.0029644975,0.00006715172,0.00027875957,0.00003304416,0.000051250725,0.0000071556947],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986696,0.000024073766,0.00035490404,0.0005004932,0.00017556558,0.00027532372],"domain_scores_gemma":[0.9989887,0.00012640092,0.00007859072,0.000338405,0.000095035335,0.00037290243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006177912,0.00017724207,0.00031456226,0.00008583725,0.000037664056,0.000012897808,0.00015510879,0.000019074461,0.000017066157],"category_scores_gemma":[0.00032003137,0.00017799782,0.00011717394,0.0003262128,0.00008620649,0.00006762587,0.00004381706,0.0001560706,0.000008714909],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036632856,0.0012371953,0.022596262,0.0008957694,0.000034915352,0.0009793545,0.0010936765,0.00038040208,0.9350079,0.008273049,0.004880008,0.020958146],"study_design_scores_gemma":[0.022903519,0.0059085237,0.5980732,0.0013469928,0.0023362741,0.00034414214,0.0003657367,0.13368532,0.11331656,0.019702416,0.09908662,0.00293069],"about_ca_topic_score_codex":0.000008850922,"about_ca_topic_score_gemma":0.0000013409045,"teacher_disagreement_score":0.8216914,"about_ca_system_score_codex":0.000021407388,"about_ca_system_score_gemma":0.00009020607,"threshold_uncertainty_score":0.72585404},"labels":[],"label_agreement":null},{"id":"W3082175322","doi":"10.1093/texcom/tgaa062","title":"Automatic Segmentation of the Dorsal Claustrum in Humans Using in vivo High-Resolution MRI","year":2020,"lang":"en","type":"article","venue":"Cerebral Cortex Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"H2020 European Research Council; Israel Science Foundation; Iowa Science Foundation","keywords":"Claustrum; Connectomics; Neuroscience; Segmentation; Dorsum; Connectome; Magnetic resonance imaging; Anatomy; Biology; Diffusion MRI; Human Connectome Project; Artificial intelligence; Computer science; Functional connectivity; Medicine; Radiology","score_opus":0.10789577945727273,"score_gpt":0.36548442250502805,"score_spread":0.2575886430477553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082175322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9794123,0.00009297427,0.004909659,0.014030311,0.000021547965,0.0008934187,0.000019113082,0.00010011655,0.0005205433],"genre_scores_gemma":[0.9648997,0.000051164585,0.034418475,0.0005074623,0.000010414397,0.000055952365,0.00002539462,0.000014833223,0.000016582711],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991195,0.00009163936,0.00038704334,0.00015507833,0.00011956677,0.00012713656],"domain_scores_gemma":[0.99878937,0.000056092056,0.00016111374,0.0009158278,0.000042236137,0.000035339817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007373553,0.00008942083,0.00017245577,0.00007935677,0.00010553925,0.0000074160753,0.00039060987,0.000045379253,0.00004590677],"category_scores_gemma":[0.00004903265,0.00007919763,0.000050101175,0.00065423484,0.00015692344,0.000097498,0.00023326733,0.00030367528,0.0000024207022],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008125425,0.0012186199,0.41649136,0.00032715438,0.00004393959,0.0000041932008,0.0039080507,0.0030678392,0.47625175,0.08924233,0.00096902193,0.008394486],"study_design_scores_gemma":[0.0017412399,0.0001213216,0.6219429,0.00039897853,0.0000983322,0.000012203021,0.0006837014,0.35705012,0.010863148,0.005554664,0.0013018503,0.0002315808],"about_ca_topic_score_codex":0.0003188785,"about_ca_topic_score_gemma":0.00018056507,"teacher_disagreement_score":0.4653886,"about_ca_system_score_codex":0.0001151837,"about_ca_system_score_gemma":0.0000669818,"threshold_uncertainty_score":0.32295856},"labels":[],"label_agreement":null},{"id":"W3082607112","doi":"10.1101/2020.08.27.266551","title":"Bundle-specific associations between white matter microstructure and Aβ and tau pathology at their connecting cortical endpoints in older adults at risk of Alzheimer’s disease","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Université de Sherbrooke; McGill University; Douglas Mental Health University Institute","funders":"Université de Sherbrooke","keywords":"Fornix; Uncinate fasciculus; Fractional anisotropy; White matter; Cingulum (brain); Diffusion MRI; Pathology; Fasciculus; Alzheimer's disease; Neuroscience; Psychology; Medicine; Disease; Hippocampus; Magnetic resonance imaging; Radiology","score_opus":0.030335371247178125,"score_gpt":0.26959760588924453,"score_spread":0.23926223464206642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082607112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99266475,0.0014453279,0.0007910094,0.0015157701,0.00006831009,0.0011086628,0.0022468662,0.00015705393,0.0000022179631],"genre_scores_gemma":[0.99129325,0.0006009845,0.007488251,0.00028604522,0.0001271213,0.00009844686,0.000010028718,0.00009451312,0.0000013545213],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978298,0.00013390723,0.00058243884,0.00096961355,0.00015480486,0.0003294172],"domain_scores_gemma":[0.99812615,0.00017010613,0.0005286922,0.00068437407,0.0001640005,0.0003266763],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019704827,0.0003833372,0.0007272197,0.0001426134,0.00017412264,0.000030960127,0.00013519582,0.00030368514,0.00003169188],"category_scores_gemma":[0.00019204331,0.0003805769,0.00009469423,0.00021038012,0.00021234267,0.00004870872,0.00075068645,0.0008860969,0.000005716249],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008151169,0.00007304744,0.92865896,0.00018348076,0.00006925325,0.00003940316,0.00007191583,0.0000022699692,0.07060447,0.00004409591,0.00016488369,0.0000066849902],"study_design_scores_gemma":[0.0008189073,0.000034494286,0.97524256,0.00035090998,0.00029697997,2.403103e-7,0.000005329844,0.00009478257,0.02253309,0.000018770546,0.00030023258,0.0003037122],"about_ca_topic_score_codex":0.000009138005,"about_ca_topic_score_gemma":0.0000025326053,"teacher_disagreement_score":0.048071384,"about_ca_system_score_codex":0.00015547701,"about_ca_system_score_gemma":0.00006960424,"threshold_uncertainty_score":0.99986464},"labels":[],"label_agreement":null},{"id":"W3082755402","doi":"10.1109/embc44109.2020.9175469","title":"Modeling BOLD-fMRI Hemodynamics via Multidimensional Decomposition of Electrophysiology Data: A Simulation Study","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Electroencephalography; Initialization; Matrix decomposition; Computer science; Artificial intelligence; EEG-fMRI; Pattern recognition (psychology); Electrophysiology; Functional magnetic resonance imaging; Local field potential; Neuroscience; Psychology; Physics","score_opus":0.12756332576150622,"score_gpt":0.421047105388077,"score_spread":0.2934837796265708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082755402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4448572,0.000005723997,0.5541612,0.0005546421,0.0000040712994,0.0003085756,0.0000052754813,0.00008607113,0.000017219081],"genre_scores_gemma":[0.9047112,0.0000061752826,0.094447196,0.00056556315,0.00003740131,0.000009793558,0.00020611368,0.000013144648,0.0000034179548],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992752,0.000017744998,0.00021899791,0.00028998632,0.00010687619,0.000091199676],"domain_scores_gemma":[0.9994375,0.000037070477,0.000047481288,0.00033492965,0.00009002658,0.0000530054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003658605,0.00007924651,0.00017456147,0.00003024422,0.000040449922,0.0000017829929,0.0000812006,0.000026259648,0.000009305864],"category_scores_gemma":[0.000024997988,0.00007119132,0.00002570554,0.0001290247,0.000015969135,0.00007809847,0.0001064284,0.00011063464,0.0000032604084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022520921,0.00061626715,0.00042032162,0.000020065343,0.000022671004,0.0000040322416,0.000056585523,0.41305268,0.58308303,0.00048195833,0.00002790565,0.0019892605],"study_design_scores_gemma":[0.00047986594,0.00044992942,0.0006478049,0.000005464405,0.000045372613,0.000004654036,0.000023604955,0.99558854,0.0022445803,0.00042513758,0.000026477106,0.000058542635],"about_ca_topic_score_codex":0.000020322279,"about_ca_topic_score_gemma":0.0000014593513,"teacher_disagreement_score":0.58253586,"about_ca_system_score_codex":0.000015391308,"about_ca_system_score_gemma":0.000019313731,"threshold_uncertainty_score":0.29030982},"labels":[],"label_agreement":null},{"id":"W3083431556","doi":"10.1101/2022.02.10.479780","title":"Assessing Quantitative MRI Techniques using Multimodal Comparisons","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Concordia University","funders":"","keywords":"Fractional anisotropy; White matter; Neuroscience; Context (archaeology); Brain tissue; Diffusion MRI; Grey matter; Set (abstract data type); Psychology; Magnetization transfer; Cognitive neuroscience; Computer science; Contrast (vision); Cognition; Artificial intelligence; Biology; Medicine; Magnetic resonance imaging","score_opus":0.11313463343723394,"score_gpt":0.3854876880421872,"score_spread":0.27235305460495324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083431556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4745173,0.00082934916,0.5159164,0.0012411835,0.00049572246,0.002904303,0.00036415007,0.0036358684,0.000095724834],"genre_scores_gemma":[0.51220906,0.00010933996,0.48672333,0.00027243586,0.00014133386,0.00039113418,0.0000012237723,0.00014904524,0.0000030536107],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9968653,0.0001502037,0.0006711571,0.0012554405,0.00050043705,0.00055748224],"domain_scores_gemma":[0.99685943,0.00012107853,0.0006392071,0.0016665676,0.0004453416,0.00026838615],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046539356,0.000607184,0.0008693023,0.0004428856,0.0004967552,0.0002236101,0.0004831575,0.00031947537,0.00008667478],"category_scores_gemma":[0.00017349815,0.0006899075,0.0002570376,0.00068059354,0.00023222392,0.00025361896,0.0010045333,0.0019514454,0.000009634269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000489044,0.0005496218,0.013903247,0.00043874618,0.00014263243,0.0001522134,0.000011211713,0.00027947445,0.9803874,0.0031137546,0.0009651071,0.000007707193],"study_design_scores_gemma":[0.0011558394,0.0003407159,0.087274104,0.0021786457,0.0010909401,7.2127233e-7,0.00007171399,0.05452122,0.7761591,0.000042162963,0.074412845,0.0027519946],"about_ca_topic_score_codex":0.00009229507,"about_ca_topic_score_gemma":4.104016e-7,"teacher_disagreement_score":0.20422828,"about_ca_system_score_codex":0.00067235535,"about_ca_system_score_gemma":0.00074260513,"threshold_uncertainty_score":0.99955523},"labels":[],"label_agreement":null},{"id":"W3083554083","doi":"10.21105/joss.02343","title":"qMRLab: Quantitative MRI analysis, under one umbrella","year":2020,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":84,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré de Santé et Services Sociaux de Chaudière-Appalache; University of Calgary; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; McGill University; Université de Montréal; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Institut de Cardiologie de Montréal; Fondation Institut de Cardiologie de Montréal; Canada First Research Excellence Fund; Réseau en Bio-Imagerie du Quebec","keywords":"Medicine; Computer science","score_opus":0.19900791780575466,"score_gpt":0.42082807363136354,"score_spread":0.22182015582560888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083554083","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03453426,0.00050605845,0.9234606,0.040704723,0.000012169395,0.00033474702,0.000008613425,0.00006297596,0.00037582585],"genre_scores_gemma":[0.80876553,0.00046443846,0.17924717,0.010621397,0.0001432941,0.0000050973053,0.000007649515,0.0000467333,0.00069869775],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990318,0.00008400197,0.00035451748,0.00012506299,0.00027164197,0.00013296615],"domain_scores_gemma":[0.99866307,0.00024780707,0.00038923987,0.000297662,0.00023826821,0.00016396363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003492547,0.00010820653,0.00040028774,0.000071613715,0.00013546832,0.000047459107,0.00059937185,0.000030027619,0.00014108395],"category_scores_gemma":[0.00019604265,0.00007108165,0.0001663647,0.0007551987,0.0000947284,0.00012866968,0.00021536661,0.00041841296,0.000023690473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.016326206,0.0046286266,0.16266839,0.00078166125,0.024752071,0.0005775633,0.04888071,0.16458215,0.09604969,0.030452121,0.3755834,0.07471741],"study_design_scores_gemma":[0.013258141,0.00894559,0.15010856,0.0014356428,0.03441633,0.002061597,0.020687573,0.011763236,0.03209602,0.04030069,0.68274635,0.0021802543],"about_ca_topic_score_codex":0.000019186926,"about_ca_topic_score_gemma":0.0000016606159,"teacher_disagreement_score":0.77423126,"about_ca_system_score_codex":0.000029273646,"about_ca_system_score_gemma":0.000074972115,"threshold_uncertainty_score":0.28986257},"labels":[],"label_agreement":null},{"id":"W3083577534","doi":"10.1212/wnl.0000000000010669","title":"Developmental neuroplasticity of the white matter connectome in children with perinatal stroke","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Connectomics; Connectome; Diffusion MRI; White matter; Psychology; Neuroscience; Stroke (engine); Neurology; Neuroplasticity; Physical medicine and rehabilitation; Medicine; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.02191565561632836,"score_gpt":0.26123289282167006,"score_spread":0.2393172372053417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083577534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9859808,0.0000025218162,0.0004482677,0.012809566,0.000007975432,0.0002699827,0.00001534638,0.00003599635,0.00042952874],"genre_scores_gemma":[0.9885864,0.0000016232062,0.0009179173,0.010429096,0.000015848333,0.000015963711,0.000001865551,0.000013729153,0.000017509423],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994919,0.000022313197,0.00011249029,0.00019012069,0.00007113848,0.0001120946],"domain_scores_gemma":[0.9997927,0.00001795473,0.00003969712,0.00009829124,0.000014172206,0.000037211124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000011359593,0.000073167066,0.00012815776,0.000024264473,0.000020687836,0.0000017768159,0.00010072681,0.000024319463,0.0000599177],"category_scores_gemma":[0.000018173005,0.000049700604,0.000020902778,0.00013406471,0.000106918305,0.00001868753,0.00008702653,0.00024799028,0.000009163882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015009278,0.000025440126,0.99160576,0.0000059912777,0.0000041310473,0.0000099218,0.000035915316,0.000022101027,0.007927673,0.0000627903,0.00009268417,0.00005750036],"study_design_scores_gemma":[0.00051537994,0.0003573607,0.995561,0.0000029307287,0.000009159897,0.00044873994,0.000001722813,0.0001089218,0.0020803767,0.000009067728,0.0008659061,0.00003944418],"about_ca_topic_score_codex":0.0000051846228,"about_ca_topic_score_gemma":0.0000029658752,"teacher_disagreement_score":0.005847296,"about_ca_system_score_codex":0.000004099268,"about_ca_system_score_gemma":0.000024144723,"threshold_uncertainty_score":0.20267318},"labels":[],"label_agreement":null},{"id":"W3083589568","doi":"10.1007/978-3-030-73018-5_2","title":"Towards Learned Optimal q-Space Sampling in Diffusion MRI","year":2021,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Human Connectome Project; Tractography; Computer science; Sampling (signal processing); Diffusion MRI; SIGNAL (programming language); Artificial intelligence; Connectome; Machine learning; Data mining; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging; Functional connectivity","score_opus":0.12866222041710998,"score_gpt":0.4084565465148323,"score_spread":0.27979432609772237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083589568","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018651683,0.0005800956,0.9350643,0.0009440927,0.000036040663,0.00078769325,0.00001389762,0.00019399049,0.060514692],"genre_scores_gemma":[0.006879574,0.017062914,0.684634,0.00068305363,0.00032511842,0.00011507267,0.0011217949,0.00040857255,0.28876993],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99911875,0.00000417687,0.0003014889,0.0002903673,0.0001733438,0.00011185231],"domain_scores_gemma":[0.9994197,0.000035267993,0.00015421475,0.00025180096,0.000082577346,0.00005643479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009250311,0.00018946355,0.000348823,0.00013718213,0.000054911252,0.0000333813,0.000040731848,0.00016142736,0.00008593253],"category_scores_gemma":[0.00004693309,0.00018193905,0.00005348193,0.00006059961,0.00003615641,0.000030215853,0.00008983031,0.00018749948,0.0000042575466],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009400562,0.00011898822,0.000032761975,0.0006257983,0.0000134829015,0.00001618692,0.00033761765,0.00002637429,0.0013979593,0.9901251,0.00020381389,0.007092485],"study_design_scores_gemma":[0.002613428,0.0005322869,0.0004655245,0.010676168,0.0005973607,0.0003941249,0.00040968714,0.1389212,0.003142311,0.24752402,0.5930495,0.0016743304],"about_ca_topic_score_codex":0.000002642861,"about_ca_topic_score_gemma":0.0000015435477,"teacher_disagreement_score":0.7426011,"about_ca_system_score_codex":0.000045178098,"about_ca_system_score_gemma":0.00003851074,"threshold_uncertainty_score":0.7419259},"labels":[],"label_agreement":null},{"id":"W3083911743","doi":"10.1101/2020.09.07.286807","title":"Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; Health Sciences Centre; University Health Network; Western University; University of Toronto; Centre for Addiction and Mental Health; Queen's University; Toronto Western Hospital; University of British Columbia; Sunnybrook Health Science Centre; St. Michael's Hospital; University of Alberta; University of Calgary; Baycrest Hospital","funders":"Canadian Open Neuroscience Platform; Temerty Family Foundation; University Health Network Foundation; H. Lundbeck A/S; Servier; Mitacs; Michael Smith Health Research BC; Strong; Government of Ontario; Canadian Institutes of Health Research; Sunovion; Centre for Addiction and Mental Health Foundation; Ontario Brain Institute; Pfizer; St. Jude Medical; Fondation Brain Canada; Allergan; National Institutes of Health; Canadian Network for Mood and Anxiety Treatments; Bristol-Myers Squibb","keywords":"Protocol (science); Computer science; Reliability (semiconductor); Visual inspection; Neuroimaging; Reproducibility; Artificial intelligence; Quality (philosophy); Psychology; Statistics; Medicine; Neuroscience; Mathematics; Pathology","score_opus":0.06980533340643963,"score_gpt":0.35876812307758255,"score_spread":0.2889627896711429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3083911743","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087216824,0.000049738857,0.5855098,0.011330778,0.0003669049,0.3095047,0.0021836904,0.0037867622,0.000050869916],"genre_scores_gemma":[0.53711313,0.000010326378,0.18906991,0.0010434437,0.0009512582,0.2715839,0.0000058947358,0.00021738494,0.00000476104],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99717456,0.00006585389,0.0006787751,0.0012739231,0.0003435736,0.0004633349],"domain_scores_gemma":[0.99742013,0.00019947103,0.00030118803,0.0011508297,0.00041943186,0.0005089584],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016115641,0.0005068466,0.00071099435,0.00012407234,0.00019201779,0.0001001351,0.00034408225,0.0004552123,0.00009264657],"category_scores_gemma":[0.00033136274,0.0005215358,0.00027843605,0.00031404683,0.00017679366,0.00006276783,0.00041516777,0.0011772234,0.000050118295],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051713886,0.0008816013,0.014466259,0.00072903326,0.00022618777,0.00007595406,0.0000075614053,0.000028202021,0.96569854,0.0050492254,0.0123121105,0.000008165854],"study_design_scores_gemma":[0.00511472,0.00053892384,0.17656046,0.0011806405,0.0008145254,9.722724e-8,0.0000031469997,0.042776573,0.5013199,0.00044128136,0.26929876,0.0019509798],"about_ca_topic_score_codex":0.000021477439,"about_ca_topic_score_gemma":6.021144e-7,"teacher_disagreement_score":0.46437868,"about_ca_system_score_codex":0.00019189322,"about_ca_system_score_gemma":0.0005648375,"threshold_uncertainty_score":0.9997236},"labels":[],"label_agreement":null},{"id":"W3084002536","doi":"10.1016/j.nicl.2020.102413","title":"Cognitively supernormal older adults maintain a unique structural connectome that is resistant to Alzheimer’s pathology","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Rochester; F. Hoffmann-La Roche; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Connectome; Precuneus; Neuroscience; Psychology; Cognition; Posterior cingulate; Human Connectome Project; Neurodegeneration; Cognitive decline; Diffusion MRI; Alzheimer's disease; Default mode network; Disease; Medicine; Pathology; Functional connectivity; Dementia; Magnetic resonance imaging","score_opus":0.20755074661568657,"score_gpt":0.4352312524798014,"score_spread":0.2276805058641148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084002536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89820236,0.000067969864,0.00815259,0.0904841,0.00014247149,0.0016427023,0.00023600545,0.00061773835,0.0004540492],"genre_scores_gemma":[0.8747155,0.000062263265,0.013929856,0.110642634,0.00040640982,0.00008082085,0.000046156652,0.000073836316,0.000042528518],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972381,0.0002169501,0.0006906589,0.0010986124,0.00027380497,0.0004818988],"domain_scores_gemma":[0.99784523,0.00048756882,0.00014224568,0.0005885683,0.00024723358,0.0006891562],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002317503,0.00030779678,0.0006095166,0.000070894734,0.000119163255,0.000030134512,0.0002889436,0.00016290061,0.00024767904],"category_scores_gemma":[0.0010187433,0.00028024425,0.00025504743,0.00030984342,0.00029872166,0.000108854656,0.0002895183,0.000910009,0.00014120976],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.036352463,0.002818754,0.33943194,0.0007188516,0.0008047491,0.029230004,0.0060778796,0.00000931353,0.09474068,0.010265159,0.31407169,0.16547853],"study_design_scores_gemma":[0.00700524,0.0050287987,0.90778965,0.00024751498,0.000568847,0.00081474683,0.00032262248,0.0015427181,0.01938939,0.0009499901,0.055398222,0.0009422806],"about_ca_topic_score_codex":0.000011396984,"about_ca_topic_score_gemma":0.000001893152,"teacher_disagreement_score":0.5683577,"about_ca_system_score_codex":0.000017800056,"about_ca_system_score_gemma":0.00009538856,"threshold_uncertainty_score":0.99996495},"labels":[],"label_agreement":null},{"id":"W3084006768","doi":"10.1523/jneurosci.0364-20.2020","title":"Corticocortical and Thalamocortical Changes in Functional Connectivity and White Matter Structural Integrity after Reward-Guided Learning of Visuospatial Discriminations in Rhesus Monkeys","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; The Scarborough Hospital; University of Toronto","funders":"Medical Research Council; Wellcome Trust","keywords":"Uncinate fasciculus; Fornix; Neuroscience; Psychology; White matter; Thalamus; Prefrontal cortex; Orbitofrontal cortex; Macaque; Hippocampus; Fractional anisotropy; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.08927754114621453,"score_gpt":0.35651557856865457,"score_spread":0.26723803742244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084006768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98158056,0.000012311374,0.0069880597,0.011218963,0.000037817346,0.00013868818,0.0000020955085,0.000007197045,0.000014300656],"genre_scores_gemma":[0.99781126,0.00003462631,0.0014322359,0.00066497,0.00003868163,0.000006800174,2.7010236e-7,0.0000060129346,0.0000051470506],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991235,0.00004951929,0.00031429756,0.00018719916,0.00020256052,0.00012289075],"domain_scores_gemma":[0.99952316,0.000088129265,0.00013871807,0.000060030805,0.000071787355,0.000118171934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000100680154,0.000079555204,0.00021789076,0.00010862887,0.000030838593,0.00001520321,0.00004931592,0.000029445408,0.000013624162],"category_scores_gemma":[0.0006130438,0.00006341689,0.000025657553,0.00023575073,0.00025444772,0.00014529143,0.00007068775,0.0005013064,1.6897397e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012139735,0.00004128828,0.93282616,0.000025568843,6.2961755e-7,0.00004992146,0.00018105573,0.000033423024,0.06611647,0.00010469041,0.000010204062,0.0004892192],"study_design_scores_gemma":[0.0004333743,0.00034834712,0.98710215,0.000052686075,0.000014802853,0.00036830996,0.00004990199,0.010153444,0.0010889034,0.00032294865,0.000014157955,0.0000509819],"about_ca_topic_score_codex":0.000005958866,"about_ca_topic_score_gemma":0.000007351126,"teacher_disagreement_score":0.065027565,"about_ca_system_score_codex":0.000020100844,"about_ca_system_score_gemma":0.00003864307,"threshold_uncertainty_score":0.25860655},"labels":[],"label_agreement":null},{"id":"W3084284455","doi":"10.1016/j.pscychresns.2020.111184","title":"Cerebrovascular pathology in Alzheimer's disease: Hopes and gaps","year":2020,"lang":"en","type":"review","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Hyperintensity; Disease; Medicine; Diabetes mellitus; Fluid-attenuated inversion recovery; White matter; Vascular disease; Executive dysfunction; Leukoaraiosis; Pathology; Psychology; Bioinformatics; Intensive care medicine; Cardiology; Internal medicine; Magnetic resonance imaging; Cognition; Radiology; Neuropsychology; Psychiatry; Biology; Endocrinology","score_opus":0.23952392100853526,"score_gpt":0.48920274332569236,"score_spread":0.2496788223171571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084284455","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000019653133,0.98396033,0.000104292594,0.012618458,0.00011259904,0.0022752315,0.000043302374,0.00025175855,0.00061438716],"genre_scores_gemma":[0.00006613167,0.9940832,0.0039264117,0.0006896407,0.00036471518,0.0005775258,0.000078509045,0.00018416389,0.000029698998],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959481,0.00059359614,0.00064888917,0.001457878,0.0005612129,0.00079033547],"domain_scores_gemma":[0.99776644,0.00027660202,0.00014044094,0.0011298296,0.00009636516,0.000590327],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00059280434,0.00048376626,0.0014395048,0.00081830955,0.00020218574,0.00008866565,0.00043895078,0.00012894737,0.00002388639],"category_scores_gemma":[0.00031214813,0.00043762094,0.00035560402,0.0014239444,0.00040559843,0.00011191047,0.0005728586,0.0027408944,0.00006648693],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030248024,0.0002247328,0.0032636113,0.0098486375,0.00008437876,0.0010480171,0.00002161724,2.7298321e-7,0.0000041401668,0.002578319,0.0039230017,0.97897303],"study_design_scores_gemma":[0.00032426257,0.000082581995,0.0010121524,0.0057791257,0.0004997078,0.00070960715,0.000009157233,0.000067983805,3.6575892e-7,0.002348115,0.98885655,0.0003103911],"about_ca_topic_score_codex":0.000014200522,"about_ca_topic_score_gemma":0.0000019677543,"teacher_disagreement_score":0.98493356,"about_ca_system_score_codex":0.000064762426,"about_ca_system_score_gemma":0.00069576665,"threshold_uncertainty_score":0.99980754},"labels":[],"label_agreement":null},{"id":"W3084650047","doi":"10.1212/wnl.0000000000010804","title":"Teaching NeuroImages: Stroke With Nondecussating Corticospinal Tracts Causing Ipsilateral Weakness","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Weakness; Facial weakness; Medicine; Diffusion MRI; Stroke (engine); Corticospinal tract; Infarction; Dissection (medical); Anatomy; Magnetic resonance imaging; Radiology; Cardiology","score_opus":0.07169574233355873,"score_gpt":0.3386703085866711,"score_spread":0.26697456625311233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084650047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9291265,0.0000125300285,0.030014124,0.038613606,0.000040240437,0.00033803863,0.000005518214,0.00043951374,0.0014099592],"genre_scores_gemma":[0.9666843,0.000004981053,0.010866428,0.02211895,0.00018883718,0.00002497444,0.000008300745,0.000053184325,0.000050042916],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998719,0.0000584747,0.00024230646,0.0004863645,0.00016235681,0.00033152493],"domain_scores_gemma":[0.99930185,0.000070725415,0.00012216573,0.00026874518,0.000043631557,0.00019290713],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005005932,0.00018470592,0.0002785089,0.000054184748,0.00016262184,0.000022127368,0.0000925032,0.000060927327,0.000016466494],"category_scores_gemma":[0.000080924576,0.00015790689,0.000051096526,0.00012282834,0.000101717684,0.000109680084,0.000067612295,0.0009036926,0.000009734309],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040618195,0.00058563123,0.16779721,0.00027566843,0.000084699896,0.0069443895,0.0014837711,0.0010133722,0.77316445,0.003746919,0.0007104703,0.04013163],"study_design_scores_gemma":[0.0073327012,0.021135386,0.77578354,0.00015769621,0.00063823396,0.01632337,0.000094869756,0.06064185,0.018930849,0.00070355035,0.096835025,0.0014229224],"about_ca_topic_score_codex":0.00003510135,"about_ca_topic_score_gemma":0.0000030448975,"teacher_disagreement_score":0.7542336,"about_ca_system_score_codex":0.000009189176,"about_ca_system_score_gemma":0.000044975597,"threshold_uncertainty_score":0.6439256},"labels":[],"label_agreement":null},{"id":"W3084811013","doi":"10.1101/2020.09.16.299784","title":"A method to remove the influence of fixative concentration on post-mortem T <sub>2</sub> maps using a Kinetic Tensor model","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Fixative; Diffusion MRI; White matter; Brain tissue; Chemistry; Fixation (population genetics); Diffusion; Anatomy; Physics; Magnetic resonance imaging; Biology; Thermodynamics; Medicine; Biochemistry","score_opus":0.05203366430860195,"score_gpt":0.3169298487756952,"score_spread":0.26489618446709323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3084811013","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8177703,0.000052286836,0.17666493,0.002700771,0.0000387514,0.0021583464,0.0003326676,0.00027643304,0.0000054938773],"genre_scores_gemma":[0.7986294,0.000045785477,0.19816883,0.0027403259,0.000098292345,0.00022811866,7.2160157e-7,0.00008782929,6.826629e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976071,0.0001246517,0.000588888,0.0009194221,0.00041911812,0.0003408248],"domain_scores_gemma":[0.996897,0.0001373719,0.00055378163,0.0012188773,0.00094099384,0.00025201467],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029619387,0.0004363802,0.0006045859,0.00013276105,0.00011832188,0.0000442336,0.00037509445,0.00021462602,0.0000015664787],"category_scores_gemma":[0.0004594553,0.00037494232,0.00015203147,0.00061934086,0.00012377372,0.00007108926,0.0003154966,0.0008226004,0.000009595524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011494792,0.00008515563,0.00019461638,0.00019228118,0.0000500085,0.000018405419,0.00003747336,0.022833727,0.9747287,0.0016639412,0.00007051139,0.000010211841],"study_design_scores_gemma":[0.0003377912,0.00017580052,0.019102274,0.00091969606,0.00025255422,1.4589108e-7,0.0000045690194,0.053013954,0.9255353,0.000059863814,0.00022243471,0.00037560338],"about_ca_topic_score_codex":0.000024937606,"about_ca_topic_score_gemma":2.8540526e-7,"teacher_disagreement_score":0.049193405,"about_ca_system_score_codex":0.00024182725,"about_ca_system_score_gemma":0.000548114,"threshold_uncertainty_score":0.99987024},"labels":[],"label_agreement":null},{"id":"W3085265452","doi":"10.1016/j.cortex.2020.08.021","title":"Network-level causal analysis of set-shifting during trail making test part B: A multimodal analysis of a glioma surgery case","year":2020,"lang":"en","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Institut National de la Santé et de la Recherche Médicale; Assistance Publique - Hôpitaux de Paris; Agence Nationale de la Recherche","keywords":"Supramarginal gyrus; Diffusion MRI; Psychology; Neuroscience; Glioma; Tractography; White matter; Middle frontal gyrus; Resting state fMRI; Brain mapping; Default mode network; Functional connectivity; Medicine; Cognition; Functional magnetic resonance imaging; Magnetic resonance imaging; Radiology","score_opus":0.1616672584301673,"score_gpt":0.3648159502766758,"score_spread":0.2031486918465085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3085265452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97760415,0.00007733465,0.021403873,0.00033031683,0.000012084654,0.00018159475,0.00020312273,0.00012705653,0.000060454197],"genre_scores_gemma":[0.99250185,0.0000132137675,0.007071874,0.0001789475,0.0000824502,0.000024349742,0.00008949241,0.000024737046,0.000013058301],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984752,0.00002926725,0.00064739905,0.00039311443,0.0002019472,0.0002530492],"domain_scores_gemma":[0.99849075,0.00043742365,0.00040454886,0.00041137164,0.00012943758,0.00012648283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015534859,0.00015928238,0.0008869908,0.000483198,0.00008291132,0.0000079592055,0.000085873646,0.000054702265,0.00007348905],"category_scores_gemma":[0.00033579182,0.00016061075,0.00047294569,0.0051563224,0.00007756068,0.000050073824,0.00007351595,0.00015925562,8.0646697e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013957353,0.0002572489,0.9118427,0.00023631823,0.0043415274,0.0026284712,0.0007179208,0.0089099035,0.06626572,0.00007856054,0.00026021746,0.0043218564],"study_design_scores_gemma":[0.0003602174,0.000060854534,0.74835527,0.0001094793,0.015906213,0.00018009411,0.0001555065,0.23135866,0.0031622574,0.000016226533,0.00009889651,0.00023631167],"about_ca_topic_score_codex":0.00009496401,"about_ca_topic_score_gemma":0.00006223669,"teacher_disagreement_score":0.22244875,"about_ca_system_score_codex":0.000026067746,"about_ca_system_score_gemma":0.000043369484,"threshold_uncertainty_score":0.6549517},"labels":[],"label_agreement":null},{"id":"W3087146715","doi":"10.1101/2020.09.18.20196014","title":"Associations Between Physical Fitness and Brain Structure in Young Adulthood","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Human Connectome Project; Physical fitness; Brain size; Connectome; Psychology; Magnetic resonance imaging; Medicine; Neuroscience; Physical therapy","score_opus":0.055875665083657676,"score_gpt":0.3655477262436865,"score_spread":0.3096720611600288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087146715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9656314,0.000035503897,0.003150112,0.029545417,0.00003946242,0.00061711436,0.0005669464,0.00021396026,0.00020008735],"genre_scores_gemma":[0.99371177,0.000030830666,0.004922256,0.00037275502,0.00037498676,0.00005766419,0.00045391973,0.000038162325,0.000037652622],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988687,0.000042709198,0.00023957797,0.0005015401,0.00017598057,0.00017146539],"domain_scores_gemma":[0.9992167,0.00012270648,0.00013815232,0.00035849947,0.000048673308,0.0001153038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058331174,0.00019684627,0.0004887022,0.00007711406,0.000046925023,0.000021078871,0.00013789677,0.00015375692,0.0000053808185],"category_scores_gemma":[0.00028497845,0.00019008918,0.00007047314,0.0001955745,0.000053885175,0.00002882023,0.00031058377,0.0010488868,0.0000023307662],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000067992232,0.000057131496,0.9905436,0.00012601705,0.000030200054,0.000017379465,0.00067126326,0.000010137217,0.004679487,0.0011508875,0.0004690479,0.0022380454],"study_design_scores_gemma":[0.00033586877,0.00003017528,0.9543626,0.00012452545,0.000076852746,0.0000056111044,0.000013832897,0.00057341834,0.0014344109,0.042412445,0.0004576121,0.00017267333],"about_ca_topic_score_codex":0.000032659747,"about_ca_topic_score_gemma":0.000015381009,"teacher_disagreement_score":0.041261557,"about_ca_system_score_codex":0.00006007351,"about_ca_system_score_gemma":0.000059072856,"threshold_uncertainty_score":0.7751612},"labels":[],"label_agreement":null},{"id":"W3087638397","doi":"10.3389/fnins.2020.00767","title":"Identification and Classification of Alzheimer’s Disease Patients Using Novel Fractional Motion Model","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Identification (biology); Disease; Alzheimer's disease; Artificial intelligence; Medicine; Neuroscience; Computer science; Psychology; Internal medicine; Biology","score_opus":0.1489907095355701,"score_gpt":0.3591406228863468,"score_spread":0.2101499133507767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087638397","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22540979,0.00002439556,0.77309674,0.0010775543,0.00006313708,0.00026305657,0.000020151694,0.000028011586,0.000017175755],"genre_scores_gemma":[0.9631558,0.00002726993,0.036306713,0.00046364157,0.000010686203,0.000014021804,0.000008963658,0.00000769926,0.0000051774937],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992276,0.000008411176,0.0001976089,0.00030162977,0.00018373846,0.000081015685],"domain_scores_gemma":[0.999576,0.0000050616404,0.00012456514,0.00013760362,0.000059286154,0.000097518154],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046171506,0.000060939758,0.00009027727,0.00008109639,0.000052714622,0.000009145942,0.00006479231,0.000018321896,4.5234805e-7],"category_scores_gemma":[0.00014805415,0.00006481062,0.000019284878,0.00030051137,0.00012962094,0.00021986582,0.000028763494,0.00008496611,1.9403171e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007170346,0.00030830962,0.38669455,0.00003861535,0.0000012703217,6.2047803e-7,0.00007231255,0.0069327964,0.60143155,0.0013766602,0.00037181226,0.0026997854],"study_design_scores_gemma":[0.0001509445,0.000013053232,0.37259057,0.00000846562,0.000014995134,5.7173685e-7,0.00000513786,0.6255572,0.0011364936,0.00042076732,0.00006805201,0.000033780147],"about_ca_topic_score_codex":8.8717024e-7,"about_ca_topic_score_gemma":2.2712719e-8,"teacher_disagreement_score":0.73774606,"about_ca_system_score_codex":0.000021833604,"about_ca_system_score_gemma":0.000036073066,"threshold_uncertainty_score":0.26429003},"labels":[],"label_agreement":null},{"id":"W3087674145","doi":"10.1111/jon.12778","title":"White Matter Lesions in Mild Cognitive Impairment and Idiopathic Parkinson's Disease: Multimodal Advanced MRI and Cognitive Associations","year":2020,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Hyperintensity; Montreal Cognitive Assessment; Cognition; Medicine; Cognitive decline; Cardiology; White matter; Verbal fluency test; Disease; Internal medicine; Psychology; Neuropsychology; Neuroscience; Dementia; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.04168473048135788,"score_gpt":0.3349530886561303,"score_spread":0.2932683581747724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087674145","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9407301,0.0012841821,0.007100228,0.05012641,0.00003297859,0.0005296651,0.000069027315,0.00004146318,0.00008595354],"genre_scores_gemma":[0.9898067,0.00048082942,0.003500107,0.0060624448,0.00008207458,0.000017305852,0.000005716354,0.00002872752,0.00001605492],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988598,0.0000690029,0.00039368577,0.000272826,0.0002057986,0.0001988918],"domain_scores_gemma":[0.99898475,0.00015690512,0.00029331134,0.00007205969,0.00017097886,0.00032196208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001286518,0.00015734775,0.0003217901,0.00014597972,0.00010418156,0.000034536046,0.000051925115,0.000025014406,0.000008833423],"category_scores_gemma":[0.00023878674,0.00014741841,0.000070497095,0.00021694806,0.00009493368,0.00024540132,0.00007842825,0.0005302758,0.0000023494779],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039521,0.00017785655,0.9918129,0.000073535826,0.000023060005,0.00040356844,0.0006060457,0.000024874755,0.0013805339,0.000012167681,0.00034278995,0.004747496],"study_design_scores_gemma":[0.0022641204,0.00020130814,0.9929763,0.0006671343,0.00018109925,0.00018179057,0.00032163845,0.0023289244,0.0001650002,0.00017607662,0.00040727292,0.00012933344],"about_ca_topic_score_codex":0.0000018718486,"about_ca_topic_score_gemma":5.797345e-7,"teacher_disagreement_score":0.04907665,"about_ca_system_score_codex":0.000031807383,"about_ca_system_score_gemma":0.00006354787,"threshold_uncertainty_score":0.6011548},"labels":[],"label_agreement":null},{"id":"W3088376984","doi":"10.1007/s10517-020-04942-2","title":"Brain Changes in the White Matter of the Brain White Matter Changes and Cognitive Functions in Asymptomatic Patients","year":2020,"lang":"en","type":"article","venue":"Bulletin of Experimental Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Montreal Cognitive Assessment; White matter; Asymptomatic; Cognition; Medicine; Cardiology; Atrophy; Psychology; Magnetic resonance imaging; Leukoaraiosis; Neuroscience; Internal medicine; Pathology; Cognitive impairment; Radiology","score_opus":0.029962287783863634,"score_gpt":0.32236275373688467,"score_spread":0.29240046595302105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088376984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67283285,0.00045971302,0.000022071019,0.32523504,0.000018549672,0.00051387015,0.000017326303,0.0000064172755,0.0008941765],"genre_scores_gemma":[0.95319486,0.00002325099,0.00009730743,0.046358168,0.000042047057,0.000104258266,0.000026364323,0.0000072749663,0.00014647281],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938434,0.00008804559,0.00017658337,0.00018206163,0.000061334555,0.000107654814],"domain_scores_gemma":[0.9995911,0.00015794505,0.00009092543,0.00010780911,0.000019108707,0.000033101012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011205845,0.00010110052,0.00022799175,0.00005364646,0.000033361164,0.0000011402166,0.00006313398,0.000047507117,0.00031414654],"category_scores_gemma":[0.000070449154,0.000056622812,0.000015013061,0.00011220819,0.00045514628,0.000005893407,0.00007205749,0.00012698746,0.0000034647019],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013513572,0.00015291807,0.9456753,0.00006850542,0.000011346683,0.0000014892864,0.0049735466,3.8840337e-8,0.023502713,0.000067187306,0.024951775,0.00046004102],"study_design_scores_gemma":[0.0028791218,0.0013483886,0.9692963,0.00047901995,0.000039675553,0.000027211701,0.0057466053,0.000009585629,0.008381994,0.0000864458,0.0116069075,0.000098741984],"about_ca_topic_score_codex":0.00002398746,"about_ca_topic_score_gemma":0.00000936369,"teacher_disagreement_score":0.28036204,"about_ca_system_score_codex":0.00000536578,"about_ca_system_score_gemma":0.00000381709,"threshold_uncertainty_score":0.34396842},"labels":[],"label_agreement":null},{"id":"W3088995957","doi":"10.1038/s41380-020-00882-5","title":"Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort","year":2020,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Health and Medical Research Council; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Percentile; Fractional anisotropy; Normative; Schizophrenia (object-oriented programming); Cohort; Psychology; Locus (genetics); Diffusion MRI; DISC1; Percentile rank; Magnetic resonance imaging; Medicine; Neuroscience; Internal medicine; Psychiatry; Biology; Genetics; Radiology; Statistics; Mathematics","score_opus":0.03462629792867275,"score_gpt":0.3347221910954875,"score_spread":0.30009589316681473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3088995957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82374454,0.00019388301,0.17018948,0.0043100123,0.000045536475,0.00041558794,0.0007629041,0.00008172185,0.00025632262],"genre_scores_gemma":[0.93047875,0.0000052928026,0.064873986,0.004104662,0.00006684432,0.000034678575,0.00040858527,0.000022879929,0.0000043176797],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989277,0.00003101685,0.0003332937,0.00030650262,0.00025119772,0.00015026753],"domain_scores_gemma":[0.99944955,0.000022457258,0.00011986015,0.00024837148,0.00006603444,0.00009371657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053516895,0.00012942695,0.00020668341,0.00008119281,0.000051546307,0.000014450064,0.00014011843,0.00007679893,0.00006436434],"category_scores_gemma":[0.000046440342,0.00013324214,0.000088218374,0.00036981114,0.00004828229,0.000094747986,0.00006595601,0.00033966466,0.0000039036436],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013241598,0.00017097218,0.95287704,0.000042412812,0.00007989838,0.000008720646,0.00023818781,0.0012444122,0.013862456,0.030508632,0.0007371218,0.00009772572],"study_design_scores_gemma":[0.0018299189,0.00007932606,0.91791064,0.000040993233,0.00004462682,0.000013040937,0.000030762745,0.006531235,0.0034095512,0.069659546,0.00029002025,0.00016037379],"about_ca_topic_score_codex":0.000017685645,"about_ca_topic_score_gemma":0.000013326033,"teacher_disagreement_score":0.106734216,"about_ca_system_score_codex":0.000020445976,"about_ca_system_score_gemma":0.000120515404,"threshold_uncertainty_score":0.5433457},"labels":[],"label_agreement":null},{"id":"W3089590362","doi":"10.1101/2020.10.02.324004","title":"White matter microstructural changes in short-term learning of a continuous visuomotor sequence","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Max-Planck-Institut für demografische Forschung; Max-Planck-Gesellschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Heart and Stroke Foundation of Canada","keywords":"White matter; Neuroscience; Neuroplasticity; Psychology; Sequence learning; Functional magnetic resonance imaging; Motor learning; Magnetic resonance imaging; Medicine","score_opus":0.04116007597035395,"score_gpt":0.2983885784040618,"score_spread":0.2572285024337079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3089590362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99434745,0.00020271528,0.001645834,0.0019434651,0.00013109967,0.0011752701,0.00014823183,0.00039597577,0.000009956746],"genre_scores_gemma":[0.9784854,0.00015924475,0.020280555,0.000499582,0.00018200596,0.0002587287,0.0000015262814,0.00012346038,0.0000094852885],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99793285,0.00006034246,0.0005003426,0.0008743249,0.00023605225,0.0003960858],"domain_scores_gemma":[0.9984873,0.00003086241,0.0002468765,0.00080469716,0.00024460693,0.00018564133],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014590126,0.0004254657,0.00077807455,0.00023612508,0.000053569256,0.000047648904,0.00033466195,0.00027022892,0.00005375472],"category_scores_gemma":[0.00007982543,0.0004509684,0.00012224446,0.00039573337,0.00016599617,0.00006176306,0.0004361643,0.0011669673,0.000016427024],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003087953,0.00003355061,0.32194442,0.0004408559,0.000019295947,0.000072993025,0.000015116939,0.0000046163977,0.6773367,0.0000381703,0.00006018027,0.0000032469839],"study_design_scores_gemma":[0.000292586,0.00008784977,0.64856815,0.0008382351,0.00007553108,2.4446402e-7,0.000002949685,0.00028418846,0.3486148,0.0000028257355,0.0008566829,0.00037592242],"about_ca_topic_score_codex":0.000019893972,"about_ca_topic_score_gemma":0.0000010549174,"teacher_disagreement_score":0.32872185,"about_ca_system_score_codex":0.00015581456,"about_ca_system_score_gemma":0.00017527271,"threshold_uncertainty_score":0.9997942},"labels":[],"label_agreement":null},{"id":"W3090019135","doi":"10.1002/dneu.22784","title":"Reduced fractional anisotropy in projection, association, and commissural fiber networks in neonates with prenatal methamphetamine exposure","year":2020,"lang":"en","type":"article","venue":"Developmental Neurobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Children's Hospital","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health","keywords":"Fractional anisotropy; Methamphetamine; White matter; Diffusion MRI; Tractography; Association (psychology); Neuroscience; Confounding; Biology; Internal medicine; Medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.03177529595980899,"score_gpt":0.28344449953862266,"score_spread":0.25166920357881367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090019135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912051,0.000043134078,0.00063661387,0.007265788,0.00002630251,0.00050020777,0.000011534075,0.0000963344,0.0002150078],"genre_scores_gemma":[0.980905,0.000050669816,0.016758902,0.0018126081,0.00003820519,0.000095061514,0.00016290553,0.000017647697,0.00015900067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991582,0.00005142723,0.00022707418,0.000315342,0.0000640296,0.00018390096],"domain_scores_gemma":[0.99967456,0.0000902591,0.00008152969,0.000056340294,0.000039068804,0.000058246227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006186936,0.0001258528,0.00020771752,0.00006812492,0.000043440396,0.0000073292554,0.00004669036,0.00007678838,0.000030406543],"category_scores_gemma":[0.00006497498,0.00011038224,0.000014298665,0.00031799154,0.00004792626,0.00007376016,0.000049567254,0.0003114153,0.000002772437],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047031132,0.00014581192,0.9839281,0.000027977238,0.000029875446,0.00006129807,0.0002725746,0.00019627223,0.010327091,0.00012409016,0.0015111935,0.002905431],"study_design_scores_gemma":[0.0027324005,0.0005365674,0.9683327,0.00005111099,0.000016117545,0.00051511725,0.000110054534,0.0012327846,0.006555235,0.0000823379,0.019572686,0.00026288422],"about_ca_topic_score_codex":0.0000270433,"about_ca_topic_score_gemma":0.000020900501,"teacher_disagreement_score":0.018061493,"about_ca_system_score_codex":0.00009408846,"about_ca_system_score_gemma":0.00005455892,"threshold_uncertainty_score":0.45012572},"labels":[],"label_agreement":null},{"id":"W3090275975","doi":"10.1002/mrm.28543","title":"Myelin water imaging depends on white matter fiber orientation in the human brain","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of British Columbia Hospital","funders":"Canadian Institutes of Health Research; Austrian Science Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; National Multiple Sclerosis Society","keywords":"White matter; Myelin; Voxel; Nuclear magnetic resonance; Orientation (vector space); Fiber tract; Chemistry; Magnetic resonance imaging; Biology; Physics; Neuroscience; Medicine; Mathematics; Central nervous system; Radiology; Geometry","score_opus":0.04368478821322771,"score_gpt":0.3485788716238089,"score_spread":0.3048940834105812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090275975","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48903483,0.00063244294,0.00048819112,0.49478447,0.00003604271,0.0009792651,0.0000031873346,0.00008631452,0.013955243],"genre_scores_gemma":[0.93248063,0.00004355386,0.0012974751,0.06424734,0.00024642417,0.00018885855,0.000044174154,0.00003066779,0.0014208774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985853,0.000071625,0.00037880614,0.0003814972,0.00031139812,0.00027140693],"domain_scores_gemma":[0.999416,0.00008883178,0.000040495896,0.0003651415,0.000028106826,0.0000614034],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00030730074,0.00015593,0.00023430487,0.00011327601,0.000051506733,0.000010404688,0.0001844457,0.00003251828,0.0012226618],"category_scores_gemma":[0.00008107619,0.0000924066,0.00002781604,0.0003550493,0.00013130537,0.000047569152,0.00003586837,0.00041053188,0.00012525673],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029021155,0.00029092882,0.66290164,0.00017187,0.0000025073944,0.0007265729,0.011347906,0.00005591325,0.035791174,0.0009738555,0.14948352,0.13796392],"study_design_scores_gemma":[0.0024496173,0.000493581,0.73423994,0.00035661034,0.000017319739,0.00005647525,0.00041783164,0.0008528979,0.0008587546,0.001440441,0.25865066,0.00016585834],"about_ca_topic_score_codex":0.00004558623,"about_ca_topic_score_gemma":0.000007994094,"teacher_disagreement_score":0.4434458,"about_ca_system_score_codex":0.000034721976,"about_ca_system_score_gemma":0.000008152306,"threshold_uncertainty_score":0.99969035},"labels":[],"label_agreement":null},{"id":"W3090779210","doi":"10.1101/2020.10.01.320507","title":"Axon Diameter Measurements using Diffusion MRI are Infeasible","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsche Forschungsgemeinschaft","keywords":"Axon; SIGNAL (programming language); Diffusion; Metric (unit); Diffusion MRI; Limit (mathematics); Computer science; Information transmission; Ideal (ethics); Physics; Biological system; Neuroscience; Algorithm; Magnetic resonance imaging; Mathematics; Mathematical analysis; Biology; Medicine","score_opus":0.13715317577371608,"score_gpt":0.3221292104715816,"score_spread":0.18497603469786553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090779210","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84820694,0.0006725673,0.14286049,0.0027433394,0.000593087,0.0027202717,0.00020462308,0.0019595555,0.000039121707],"genre_scores_gemma":[0.8716461,0.00022544005,0.12610072,0.0011727106,0.00043489892,0.00022453001,7.2686936e-7,0.00019115172,0.000003737353],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972501,0.000066730434,0.0005217899,0.0011505712,0.000548998,0.0004618399],"domain_scores_gemma":[0.9970812,0.000028201546,0.0005169537,0.0015172856,0.00045010098,0.0004062295],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020757591,0.0005501683,0.00070768106,0.00023369986,0.0001779167,0.000102461374,0.00035803698,0.0003524037,0.00003609491],"category_scores_gemma":[0.00018638022,0.0005735917,0.00022006549,0.00051012565,0.000096352116,0.00010834983,0.00068627985,0.0010026038,0.000043132113],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038856862,0.0002209962,0.060530163,0.0004879249,0.00007379244,0.000057726007,0.0000029728767,0.00003050497,0.93784684,0.00008001474,0.0006270919,0.0000031445065],"study_design_scores_gemma":[0.0014327988,0.00012904724,0.26123857,0.0027679824,0.0007036317,1.588483e-7,0.0000032422818,0.00454044,0.7104295,0.000029242183,0.017362487,0.0013628807],"about_ca_topic_score_codex":0.000024876326,"about_ca_topic_score_gemma":4.3772192e-7,"teacher_disagreement_score":0.22741729,"about_ca_system_score_codex":0.00037615164,"about_ca_system_score_gemma":0.00032407482,"threshold_uncertainty_score":0.9996716},"labels":[],"label_agreement":null},{"id":"W3091718754","doi":"10.1016/j.yebeh.2020.107467","title":"Language lateralization differences between left and right temporal lobe epilepsy as measured by overt word reading fMRI activation and DTI structural connectivity","year":2020,"lang":"en","type":"article","venue":"Epilepsy & Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal University Hospital; University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lateralization of brain function; Inferior longitudinal fasciculus; Psychology; Temporal lobe; Arcuate fasciculus; Diffusion MRI; Uncinate fasciculus; Superior temporal gyrus; Epilepsy; Neuroscience; Audiology; Fasciculus; Functional magnetic resonance imaging; Fractional anisotropy; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.04927764500262327,"score_gpt":0.33239647774136977,"score_spread":0.2831188327387465,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091718754","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917761,0.00006564471,0.004543494,0.0025291657,0.000022389384,0.0006731899,0.000059324222,0.0002674229,0.00006327963],"genre_scores_gemma":[0.9970424,0.000033889744,0.0018471673,0.0005134514,0.0001138431,0.00004607912,0.00025607788,0.000031793905,0.00011527058],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998815,0.000055518733,0.0002461039,0.00045902014,0.00020397469,0.00022039757],"domain_scores_gemma":[0.99932724,0.00006945096,0.0001363421,0.0001952899,0.00005208189,0.00021958254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000069719266,0.00021127729,0.00033571312,0.000052847266,0.00017621742,0.000055643708,0.000071695824,0.000098388475,0.00010170796],"category_scores_gemma":[0.0000850975,0.00018543149,0.000039370476,0.00014114309,0.0001021319,0.00025986455,0.000054419528,0.00024996127,0.0000027140322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044048436,0.000026264053,0.88964295,0.000022910523,0.000009244747,0.000008565439,0.00054228713,1.3044324e-7,0.098661676,0.00010223322,0.00038655486,0.010553138],"study_design_scores_gemma":[0.0006426758,0.00018887686,0.93228483,0.00006672795,0.00013288172,0.000028860535,0.000086311935,0.00015261515,0.06490551,0.00025769311,0.0010261595,0.00022682837],"about_ca_topic_score_codex":0.00016582821,"about_ca_topic_score_gemma":0.0000056993113,"teacher_disagreement_score":0.04264191,"about_ca_system_score_codex":0.00004312507,"about_ca_system_score_gemma":0.000020900196,"threshold_uncertainty_score":0.75616765},"labels":[],"label_agreement":null},{"id":"W3091774503","doi":"10.1016/j.neuroimage.2021.118502","title":"Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":187,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Calgary; Université de Sherbrooke","funders":"National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Fundação para a Ciência e a Tecnologia; National Health and Medical Research Council; Australian Research Council; Medical Research Council; Intellectual and Developmental Disabilities Research Center; National Institutes of Health; Deutsche Forschungsgemeinschaft; State Government of Victoria; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and Technology, Taiwan; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; University of Melbourne; University of Nottingham; European Commission; Vanderbilt Institute for Clinical and Translational Research; Murdoch Children's Research Institute; Children’s Hospital of Wisconsin Research Institute; National Institute on Aging; Royal Children's Hospital Foundation; National Institute for Health and Care Research; Waisman Center; Wellcome Trust; Université de Sherbrooke; National Science Foundation; Compute Canada; Vanderbilt University; Consejo Nacional de Ciencia y Tecnología; National Center for Research Resources; Agence Nationale de la Recherche; Agencia Nacional de Investigación y Desarrollo; National Institute of Mental Health; Children's Hospital Foundation","keywords":"Tractography; Segmentation; White matter; Diffusion MRI; Bundle; Computer science; Artificial intelligence; Fiber bundle; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.05183784141295804,"score_gpt":0.3204624886167076,"score_spread":0.26862464720374957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091774503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74797094,0.00022286245,0.0282503,0.20532711,0.0007639928,0.002553897,0.0012406927,0.0010871483,0.012583036],"genre_scores_gemma":[0.9731454,0.0002947113,0.003109947,0.020769646,0.00022586151,0.00018738244,0.0012817681,0.000095517404,0.0008897311],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99818146,0.00016777072,0.00030126463,0.00074051344,0.0002925332,0.00031645814],"domain_scores_gemma":[0.9977635,0.00037057317,0.000100879246,0.0015555763,0.00008476127,0.00012471009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021677343,0.0002588165,0.00026591404,0.000084000414,0.00025163766,0.00024116697,0.00021542197,0.00006618843,0.00081209483],"category_scores_gemma":[0.00016378879,0.00019213627,0.00016756372,0.00038193565,0.00016049485,0.00041342864,0.00011997272,0.0006205546,0.00013564431],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006244169,0.0045339433,0.17718351,0.00048715278,0.0001821577,0.001118258,0.0011265553,0.000025384137,0.34026045,0.01854912,0.4370777,0.018831357],"study_design_scores_gemma":[0.0010212952,0.00047891485,0.5847583,0.00039774255,0.00035335662,0.0012384783,0.0005072549,0.0003448355,0.031343054,0.024187716,0.35461593,0.000753161],"about_ca_topic_score_codex":0.000008130552,"about_ca_topic_score_gemma":0.000009574601,"teacher_disagreement_score":0.40757474,"about_ca_system_score_codex":0.000028494851,"about_ca_system_score_gemma":0.000027219901,"threshold_uncertainty_score":0.88918686},"labels":[],"label_agreement":null},{"id":"W3092157907","doi":"10.1002/nbm.4427","title":"High spatial resolution nerve‐specific DTI protocol outperforms whole‐brain DTI protocol for imaging the trigeminal nerve in healthy individuals","year":2020,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta Hospital; University of Alberta","funders":"Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Medicine; Fluid-attenuated inversion recovery; Trigeminal neuralgia; Nuclear medicine; Magnetic resonance imaging; Radiology; Anesthesia","score_opus":0.12033944779443834,"score_gpt":0.42098188873727765,"score_spread":0.3006424409428393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092157907","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028968735,0.00001715736,0.023786964,0.22237508,0.000043523294,0.75041986,0.00006696795,0.000250398,0.00014315636],"genre_scores_gemma":[0.054114815,0.0000017480121,0.00968851,0.006523431,0.0008374566,0.9285371,0.0001477334,0.00006404743,0.00008517277],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99705595,0.00009582528,0.0010430756,0.00070532155,0.00049494876,0.00060491],"domain_scores_gemma":[0.9985147,0.00021385239,0.0003376147,0.0005511171,0.00011471985,0.00026797826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010027896,0.00032956796,0.0005532519,0.00034303323,0.00017021604,0.000029996687,0.0003547617,0.00011622153,0.0000783206],"category_scores_gemma":[0.00037188764,0.0002197218,0.000096427524,0.0011731958,0.00030037295,0.00014138468,0.00012391525,0.0007005935,0.000011790756],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021958416,0.0035055124,0.10465223,0.0051762694,0.00006303108,0.0004301131,0.004408713,0.0002067894,0.09818817,0.004785544,0.3622188,0.3944064],"study_design_scores_gemma":[0.022126617,0.0030789634,0.039400157,0.0009816573,0.000024150208,0.00007673569,0.00028623975,0.009423931,0.0027728311,0.0022255715,0.91922414,0.00037897285],"about_ca_topic_score_codex":0.00019559858,"about_ca_topic_score_gemma":0.000014897824,"teacher_disagreement_score":0.5570054,"about_ca_system_score_codex":0.00025378447,"about_ca_system_score_gemma":0.00021098416,"threshold_uncertainty_score":0.8959995},"labels":[],"label_agreement":null},{"id":"W3092191527","doi":"10.1016/j.media.2021.102126","title":"Filtering in tractography using autoencoders (FINTA)","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health","keywords":"Tractography; Artificial intelligence; Computer science; Pattern recognition (psychology); Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.350996486532398,"score_gpt":0.28753471244511597,"score_spread":0.06346177408728204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092191527","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46896568,0.00002578872,0.5282141,0.00044712907,0.0000622557,0.0004690007,0.000019654655,0.0003633134,0.0014330462],"genre_scores_gemma":[0.97555745,0.00017426355,0.02381521,0.0002700838,0.000045115543,0.0000018537147,0.000027063823,0.000035377037,0.000073568255],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987973,0.000025771242,0.00017495269,0.0007259318,0.000050372022,0.00022567857],"domain_scores_gemma":[0.99913013,0.000029513274,0.00012978657,0.00053030555,0.00003931387,0.00014092747],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000048743237,0.00022246817,0.00033053118,0.00029697453,0.00005307135,0.000015366651,0.00024622696,0.00015673252,0.000027941162],"category_scores_gemma":[0.00002005643,0.00027778294,0.00019793319,0.00057407725,0.00009116821,0.000076294535,0.00037761233,0.00083189213,0.000007117045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051632087,0.00078202033,0.13293651,0.0012047405,0.00024344085,0.0052367114,0.0006343252,0.79694766,0.02188828,0.037384555,0.00074504275,0.0014804227],"study_design_scores_gemma":[0.0010321755,0.00008976664,0.015112992,0.0006693035,0.00027828186,0.000040835173,0.00016389914,0.9373699,0.0011908533,0.04110277,0.0023042038,0.0006450616],"about_ca_topic_score_codex":0.00012460332,"about_ca_topic_score_gemma":0.000009552117,"teacher_disagreement_score":0.5065918,"about_ca_system_score_codex":0.00015279601,"about_ca_system_score_gemma":0.00009526138,"threshold_uncertainty_score":0.99996746},"labels":[],"label_agreement":null},{"id":"W3092450803","doi":"","title":"Zytoarchitektonische Charakterisierung und funktionelle Dekodierung des lateralen orbitofrontalen Kortex im humanen Gehirn","year":2020,"lang":"de","type":"dissertation","venue":"Univ. Duesseldorf: Duesseldorfer Dokumenten- und Publikationsserver","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Gynecology; Medicine","score_opus":0.07012353257058548,"score_gpt":0.3584591383864953,"score_spread":0.2883356058159098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092450803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7306005,0.104192674,0.03660535,0.029356262,0.008266686,0.022570835,0.005046838,0.0079566445,0.055404205],"genre_scores_gemma":[0.7684615,0.03558899,0.02458505,0.0044890507,0.0046364535,0.0033179391,0.07347475,0.0020424533,0.08340378],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.98699087,0.0006855126,0.0035594106,0.003938525,0.002074255,0.0027514074],"domain_scores_gemma":[0.9899403,0.00051564415,0.0021402321,0.0033126615,0.0022939201,0.0017972427],"candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0009496085,0.0029062335,0.0027984937,0.0016842121,0.0034294883,0.0016197861,0.00255404,0.0016074751,0.0028805027],"category_scores_gemma":[0.00041976897,0.0030755103,0.0012887863,0.003065974,0.0010529595,0.002947393,0.0008716975,0.0037362967,0.0023918713],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008698964,0.022148073,0.18005835,0.031336103,0.040883396,0.0043670824,0.067828216,0.0011823241,0.09582619,0.2562999,0.23561035,0.055761036],"study_design_scores_gemma":[0.0064303726,0.0014899634,0.052014165,0.0042018527,0.010656877,0.00011929845,0.0038642415,0.0040218313,0.013008385,0.009523555,0.88903165,0.005637791],"about_ca_topic_score_codex":0.0010414512,"about_ca_topic_score_gemma":0.0006359778,"teacher_disagreement_score":0.6534213,"about_ca_system_score_codex":0.0011455016,"about_ca_system_score_gemma":0.001384191,"threshold_uncertainty_score":0.9996886},"labels":[],"label_agreement":null},{"id":"W3092996651","doi":"10.1038/s41598-020-70297-3","title":"HARDI-ZOOMit protocol improves specificity to microstructural changes in presymptomatic myelopathy","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Institut de Valorisation des Données; Agentura Pro Zdravotnický Výzkum České Republiky; Univerzita Palackého v Olomouci; Ministerstvo Školství, Mládeže a Tělovýchovy; Vysoké Učení Technické v Brně; Foundation for the National Institutes of Health; Ministerstvo Zdravotnictví Ceské Republiky; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; Government of Canada; Central European Institute of Technology; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; University of Pennsylvania Health System; University of Pennsylvania","keywords":"Medicine; White matter; Diffusion MRI; Voxel; Magnetic resonance imaging; Spinal cord; Neuroradiology; Reproducibility; Nuclear medicine; Radiology; Neurology","score_opus":0.05608075725010485,"score_gpt":0.34680466035739616,"score_spread":0.2907239031072913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3092996651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.877438,0.000011767377,0.0017498564,0.016673578,0.00063540245,0.101441406,0.000008729821,0.0006336612,0.0014075801],"genre_scores_gemma":[0.91609925,7.121228e-7,0.033544116,0.0017024918,0.00023804427,0.0466626,0.00003195666,0.000047803358,0.0016730544],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982437,0.00001578687,0.000396215,0.00078093994,0.00028628673,0.0002770858],"domain_scores_gemma":[0.9988359,0.000011857344,0.00015837805,0.00066849845,0.00008919603,0.00023615296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024329728,0.000146509,0.00024339736,0.00012214856,0.00011044128,0.000106804386,0.00011899785,0.00003698314,0.00007109784],"category_scores_gemma":[0.0002023321,0.00012474447,0.00005594541,0.00068014156,0.00011108708,0.00008157546,0.00013388252,0.00015651505,0.000031866097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048945443,0.00005967122,0.009885055,0.00016755659,0.0000037539594,0.00032050934,0.000541766,0.000008568131,0.9615467,0.000030775474,0.015603123,0.011783583],"study_design_scores_gemma":[0.0003646782,0.00017967029,0.036608648,0.00014171572,0.000014784917,0.0003725623,0.00006561761,0.00045914526,0.5131174,0.0028856443,0.44552684,0.00026332727],"about_ca_topic_score_codex":0.000007745979,"about_ca_topic_score_gemma":0.0000070302544,"teacher_disagreement_score":0.44842935,"about_ca_system_score_codex":0.00005195279,"about_ca_system_score_gemma":0.000073513635,"threshold_uncertainty_score":0.5086932},"labels":[],"label_agreement":null},{"id":"W3093377457","doi":"10.1002/jdn.10071","title":"Quantitative analyses of high‐angular resolution diffusion imaging (HARDI)‐derived long association fibers in children with sensorineural hearing loss","year":2020,"lang":"en","type":"article","venue":"International Journal of Developmental Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canada Foundation for Innovation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; St. Francis Xavier University","keywords":"Sensorineural hearing loss; Angular resolution (graph drawing); Audiology; Diffusion MRI; Diffusion imaging; Association (psychology); High resolution; Medicine; Hearing loss; Psychology; Magnetic resonance imaging; Geology; Remote sensing; Mathematics; Radiology","score_opus":0.07212138461958567,"score_gpt":0.3727756437675328,"score_spread":0.30065425914794713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093377457","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97717226,0.000020314445,0.018866135,0.0036809496,0.00008844057,0.00012407362,0.0000071345503,0.00001692036,0.000023795754],"genre_scores_gemma":[0.9762023,0.00006827417,0.023075532,0.0005876257,0.000040173913,0.0000019100482,0.0000056071867,0.00000916809,0.000009388054],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986357,0.00003134674,0.00038674456,0.00019055973,0.00063327636,0.0001223825],"domain_scores_gemma":[0.9991267,0.000042113537,0.0004487439,0.000048291477,0.00026072437,0.0000734604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012131284,0.000094993375,0.00018573253,0.00019610104,0.000041436724,0.000023552286,0.00019514539,0.000015595931,0.0000041824696],"category_scores_gemma":[0.00026016307,0.00008065796,0.000052267944,0.00035888707,0.000078943754,0.0003161898,0.00008221484,0.00020062698,6.830357e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015099965,0.00006090461,0.6202177,0.0000034104298,0.000016738852,0.00007863229,0.00013230066,0.00078969495,0.3779527,0.00003444905,0.000021822607,0.00054065255],"study_design_scores_gemma":[0.0007923748,0.00014410507,0.89461,0.000108917804,0.00001904464,0.0005498528,0.00006408837,0.0023672588,0.10119208,0.000041037383,0.00003560724,0.00007562394],"about_ca_topic_score_codex":0.000041441217,"about_ca_topic_score_gemma":0.0000020763036,"teacher_disagreement_score":0.2767606,"about_ca_system_score_codex":0.00020940744,"about_ca_system_score_gemma":0.00008924492,"threshold_uncertainty_score":0.32891363},"labels":[],"label_agreement":null},{"id":"W3093463881","doi":"10.3389/fnhum.2020.568395","title":"Myelin Water Imaging Demonstrates Lower Brain Myelination in Children and Adolescents With Poor Reading Ability","year":2020,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; University of Calgary; University of Alberta","funders":"Networks of Centres of Excellence of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Multiple Sclerosis Society of Canada","keywords":"Reading (process); Myelin; Psychology; Neuroscience; Developmental psychology; Medicine; Audiology; Central nervous system; Philosophy; Linguistics","score_opus":0.019078799648959203,"score_gpt":0.2896266605610808,"score_spread":0.2705478609121216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093463881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94660306,0.000023415629,0.046826605,0.0058475262,0.00003522081,0.0005324097,0.0000030489746,0.00009192354,0.0000367944],"genre_scores_gemma":[0.9919288,0.0000132947225,0.0053003803,0.0026834398,0.00002355856,0.00001964328,0.000004630386,0.00001523612,0.0000110078145],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99882114,0.000031239255,0.00020474255,0.00054241903,0.0001524097,0.00024804514],"domain_scores_gemma":[0.9996647,0.0000062342224,0.000041683892,0.0001675847,0.000022119086,0.000097670156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014634285,0.00012246221,0.00016193866,0.00012324369,0.00009604593,0.00003454895,0.00013371932,0.00002193619,0.0000012928574],"category_scores_gemma":[0.00008025735,0.00009794921,0.000016535865,0.00029906057,0.00025080485,0.00021761114,0.00006670307,0.00025922657,2.4921937e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003201011,0.0000591197,0.93017244,0.000018412704,2.8687705e-7,0.00001688837,0.00010632121,0.00006596826,0.06799432,0.00003136403,0.00019173471,0.0013111262],"study_design_scores_gemma":[0.00075021124,0.00012409598,0.9704573,0.00014317803,0.0000066819553,0.000037123616,0.000035069614,0.018842904,0.008656759,0.00067093724,0.00011983142,0.00015590669],"about_ca_topic_score_codex":0.000011211709,"about_ca_topic_score_gemma":0.0000012605086,"teacher_disagreement_score":0.059337564,"about_ca_system_score_codex":0.000040518968,"about_ca_system_score_gemma":0.000015593898,"threshold_uncertainty_score":0.3994253},"labels":[],"label_agreement":null},{"id":"W3093517549","doi":"10.1002/hbm.25237","title":"Atypical measures of diffusion at the gray‐white matter boundary in autism spectrum disorder in adulthood","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; SickKids Foundation; Centre for Addiction and Mental Health","funders":"Medical Research Council; Department of Psychiatry, University of Toronto; Canadian Institutes of Health Research; Innovative Medicines Initiative; Dr Mortimer and Theresa Sackler Foundation; European Commission; Deutsche Forschungsgemeinschaft; King's College London; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; University of Toronto; European Federation of Pharmaceutical Industries and Associations; Autism Speaks; Simons Foundation Autism Research Initiative; National Institute of Mental Health; Institute of Psychiatry, Psychology and Neuroscience, King’s College London; Ontario Brain Institute; South London and Maudsley NHS Foundation Trust","keywords":"Neurotypical; White matter; Diffusion MRI; Fractional anisotropy; Autism spectrum disorder; Psychology; Neuroscience; Neuroimaging; Autism; Neuropathology; Developmental psychology; Magnetic resonance imaging; Pathology; Medicine","score_opus":0.058128630095982584,"score_gpt":0.3120987991457971,"score_spread":0.2539701690498145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093517549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85002255,0.00012466889,0.0062874164,0.14211018,0.000010912483,0.0005082319,0.0000038567655,0.00006929959,0.0008629],"genre_scores_gemma":[0.9932068,0.000016533653,0.0007894344,0.0056061978,0.000037176713,0.000044062566,0.000014930598,0.000021882439,0.00026300608],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990437,0.000054607528,0.00029350934,0.00026299147,0.00015426254,0.0001909167],"domain_scores_gemma":[0.99955225,0.000053028274,0.00007227949,0.00026513005,0.000007655573,0.00004963961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012746429,0.000112962945,0.00020984141,0.00008266153,0.000112506495,0.000009262005,0.00012275788,0.000042650772,0.00016761279],"category_scores_gemma":[0.00004396756,0.00008729112,0.00005642857,0.00027329384,0.00011854407,0.000035031604,0.00014608065,0.0002972427,0.000016454002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008905826,0.00015892404,0.88021916,0.00014360891,0.0000065386453,0.000026517833,0.0028212508,0.000022499627,0.10523433,0.0041566044,0.0062995767,0.0008219086],"study_design_scores_gemma":[0.0006883817,0.00004484818,0.96598846,0.00018486581,0.0000049494424,0.000010726007,0.00014192618,0.00027646052,0.0001489263,0.006074219,0.026344255,0.00009200797],"about_ca_topic_score_codex":0.000023365825,"about_ca_topic_score_gemma":0.00009708006,"teacher_disagreement_score":0.14318424,"about_ca_system_score_codex":0.000048148097,"about_ca_system_score_gemma":0.000014797202,"threshold_uncertainty_score":0.35596284},"labels":[],"label_agreement":null},{"id":"W3093910113","doi":"10.1002/jmri.27408","title":"Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at <scp>3T</scp> : Reproducibility and Quality of Fit","year":2020,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Fondation Brain Canada","keywords":"Reproducibility; Kurtosis; Human Connectome Project; White matter; Effective diffusion coefficient; Diffusion MRI; Diffusion imaging; Pearson product-moment correlation coefficient; Nuclear medicine; Medicine; Nuclear magnetic resonance; Mathematics; Statistics; Computer science; Magnetic resonance imaging; Physics; Radiology","score_opus":0.12096480288776339,"score_gpt":0.39249192652900705,"score_spread":0.27152712364124365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093910113","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96540534,0.01094434,0.012391937,0.010531988,0.00006974604,0.0003942151,0.0000132087725,0.00005664614,0.00019254624],"genre_scores_gemma":[0.9495167,0.0007018152,0.048672915,0.00070767134,0.00027503123,0.000008344389,0.000003031715,0.000029485878,0.00008497767],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9970627,0.00018786563,0.0011637605,0.0006697648,0.00064235524,0.0002735631],"domain_scores_gemma":[0.99726367,0.00039737206,0.00096044916,0.0006883596,0.00048600344,0.00020415854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019256674,0.000196112,0.0005523246,0.000101369296,0.00014979405,0.00002559172,0.00017571836,0.00003393187,0.000027950937],"category_scores_gemma":[0.0052757976,0.00017680174,0.00014756969,0.00028274933,0.00022950796,0.00019792348,0.00025350938,0.0004161309,0.0000014595913],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024590234,0.00014333264,0.31351584,0.00022885173,0.0000058940527,0.000027544118,0.00056068704,0.000046852685,0.42423585,0.000090721696,0.0011251827,0.25977334],"study_design_scores_gemma":[0.0023303966,0.0005072545,0.92759013,0.0005249328,0.00015068451,0.0002704921,0.00019250432,0.02850134,0.030518299,0.00141503,0.007879504,0.00011943826],"about_ca_topic_score_codex":0.00011650319,"about_ca_topic_score_gemma":0.0000023040034,"teacher_disagreement_score":0.6140743,"about_ca_system_score_codex":0.00011018017,"about_ca_system_score_gemma":0.00008176801,"threshold_uncertainty_score":0.7209766},"labels":[],"label_agreement":null},{"id":"W3093955191","doi":"10.7554/elife.61523","title":"An interactive meta-analysis of MRI biomarkers of myelin","year":2020,"lang":"en","type":"review","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":171,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"National Institute of Mental Health; National Institutes of Health; Wellcome Trust; Wellcome","keywords":"Relaxometry; Myelin; Modalities; Meta-analysis; Pathology; Neuroscience; Magnetic resonance imaging; Medicine; Biology; Radiology","score_opus":0.3227273080608277,"score_gpt":0.5091560169898481,"score_spread":0.18642870892902041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3093955191","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.397272e-7,0.9886437,0.009610235,0.00031359543,0.000011078749,0.0006163304,0.00036209298,0.00006818901,0.00037391242],"genre_scores_gemma":[0.00008316696,0.97894746,0.020279882,0.00018199663,0.000028683999,0.00010916189,0.0002961028,0.000033525084,0.000040008912],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985686,0.00008310677,0.0006881078,0.00035461897,0.00021938888,0.000086159955],"domain_scores_gemma":[0.9981986,0.00016084519,0.00069739023,0.000724809,0.00012224709,0.0000960849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012813411,0.00021389686,0.003537116,0.00036644,0.00001216634,0.000002917026,0.00020577281,0.000079932084,0.00016653615],"category_scores_gemma":[0.00008510001,0.00015244653,0.0023371025,0.0012109678,0.00006845958,0.000032843836,0.000052979245,0.00021932794,0.000006077039],"study_design_candidate":"meta_analysis","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040131574,0.00039924865,0.00001086166,0.006125099,0.37903914,0.000025013404,0.000104337494,0.0000066641455,0.00012111791,0.00043960128,0.004001476,0.6096873],"study_design_scores_gemma":[0.000028781844,0.00005640387,0.0000032421653,0.00016552888,0.34939247,0.0000035738756,0.0000075441535,0.000076485114,0.00013076134,0.000008539421,0.6500563,0.00007035328],"about_ca_topic_score_codex":0.00001287399,"about_ca_topic_score_gemma":9.852594e-7,"teacher_disagreement_score":0.6460548,"about_ca_system_score_codex":0.000026580716,"about_ca_system_score_gemma":0.000095968346,"threshold_uncertainty_score":0.6216589},"labels":[],"label_agreement":null},{"id":"W3094034242","doi":"10.1093/brain/awaa316","title":"Diffuse axonal injury predicts neurodegeneration after moderate–severe traumatic brain injury","year":2020,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":162,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Wolfson Foundation; UK Dementia Research Institute; National Institute for Health and Care Research; Imperial College Healthcare NHS Trust; Brain Research UK; Weston Brain Institute","keywords":"Diffuse axonal injury; Traumatic brain injury; Fractional anisotropy; Neurodegeneration; White matter; Chronic traumatic encephalopathy; Atrophy; Medicine; Neuroscience; Diffusion MRI; Pathology; Poison control; Magnetic resonance imaging; Psychology; Disease; Concussion; Injury prevention; Radiology","score_opus":0.06925358403255308,"score_gpt":0.3321054108816116,"score_spread":0.2628518268490585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094034242","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8053071,0.000055805413,0.05151948,0.14059654,0.000052522446,0.0009939179,0.00014128898,0.00068719505,0.0006461481],"genre_scores_gemma":[0.9366231,0.000015392368,0.008420544,0.053661373,0.0003182636,0.00024415788,0.00008458531,0.00005398407,0.00057860336],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99877757,0.000054592056,0.00029445524,0.0004165962,0.00023155435,0.00022524263],"domain_scores_gemma":[0.999253,0.00006591039,0.00006974189,0.0003409212,0.00004232043,0.00022811262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000073392985,0.00019116941,0.00023023717,0.000058613143,0.00008237803,0.000035108158,0.00010906808,0.00007311086,0.000109030065],"category_scores_gemma":[0.00022236416,0.0001807773,0.00008226525,0.00024034969,0.0000574601,0.00015118397,0.00006453432,0.00028393537,0.00004868729],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025449845,0.0011041239,0.0025128156,0.0005098889,0.000071394155,0.0002073784,0.0018455294,0.00023466567,0.34402004,0.00528114,0.5686108,0.07305724],"study_design_scores_gemma":[0.010346689,0.004771546,0.08218211,0.0007094122,0.00039735867,0.0006624339,0.00021639312,0.2494378,0.1194446,0.016340021,0.51274896,0.0027426968],"about_ca_topic_score_codex":0.0000027397757,"about_ca_topic_score_gemma":0.0000011749173,"teacher_disagreement_score":0.24920313,"about_ca_system_score_codex":0.000028660972,"about_ca_system_score_gemma":0.0000594276,"threshold_uncertainty_score":0.7371884},"labels":[],"label_agreement":null},{"id":"W3094061741","doi":"10.1371/journal.pone.0239116","title":"White matter tract microstructure and cognitive performance after transient ischemic attack","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Alberta Health Services; Alberta Children's Hospital; Foothills Medical Centre; University of Calgary","funders":"Heart and Stroke Foundation of Canada","keywords":"White matter; Microstructure; Cognition; Transient (computer programming); Medicine; Cardiology; Magnetic resonance imaging; Computer science; Materials science; Psychiatry; Radiology; Composite material","score_opus":0.06160278329870132,"score_gpt":0.28698949723346573,"score_spread":0.2253867139347644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094061741","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98865044,0.00016115127,0.00046467243,0.009060963,0.0000023060938,0.00036888287,0.000041590432,0.000084655345,0.0011653103],"genre_scores_gemma":[0.98451877,0.000110765606,0.0067166556,0.008269808,0.000061156265,0.00006411168,0.000020649371,0.000022125387,0.00021595068],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99946827,0.0000040262485,0.00010055898,0.0002169905,0.000092898576,0.00011724404],"domain_scores_gemma":[0.9997308,0.000010099726,0.000025692574,0.00009691949,0.00004001933,0.00009642989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000010209536,0.000096504366,0.00014843085,0.000016027596,0.00002928302,0.000008644613,0.000030014102,0.00003387605,0.00019903119],"category_scores_gemma":[0.0000056426557,0.00008585705,0.000023215323,0.000072200164,0.000055661436,0.000059965732,0.000017725584,0.00020354163,0.00004795706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036622514,0.0004492504,0.71439993,0.00081522035,0.000066069886,0.000024317433,0.0011123241,4.1149667e-7,0.27753323,9.060633e-7,0.0043041366,0.0009279837],"study_design_scores_gemma":[0.000929733,0.00021605661,0.8227893,0.00052634586,0.00039186806,0.00006113012,0.00003965411,0.00051923405,0.17019781,0.000005041897,0.0041113063,0.00021251745],"about_ca_topic_score_codex":1.9583054e-7,"about_ca_topic_score_gemma":5.1016418e-8,"teacher_disagreement_score":0.10838938,"about_ca_system_score_codex":0.0000059311465,"about_ca_system_score_gemma":0.0000072978232,"threshold_uncertainty_score":0.35011488},"labels":[],"label_agreement":null},{"id":"W3094366600","doi":"10.1016/j.dcn.2020.100875","title":"Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines","year":2020,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Voxel; Voxel-based morphometry; White matter; Grey matter; Psychology; Artificial intelligence; Magnetic resonance imaging; Computer science; Medicine","score_opus":0.06792614884400805,"score_gpt":0.3383568891080774,"score_spread":0.2704307402640693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094366600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98877954,0.000031886513,0.008898877,0.0014882337,0.00001742416,0.00038986848,0.000025710477,0.000052307827,0.00031617217],"genre_scores_gemma":[0.9863078,0.0000075273438,0.006920666,0.006681845,0.0000070562833,0.000028899125,0.000008111395,0.000013517869,0.00002456137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989889,0.000017802315,0.00025133952,0.00038806783,0.00018900119,0.0001648571],"domain_scores_gemma":[0.9996454,0.00004866182,0.00008343707,0.000060623544,0.000067435416,0.000094450035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004344467,0.00012337141,0.00021946586,0.00012524107,0.00005766234,0.000017225331,0.00009182929,0.000023187524,0.000014331544],"category_scores_gemma":[0.00018058141,0.00011894587,0.000023554972,0.0006880533,0.0002627265,0.00010956269,0.00009071163,0.00016888902,0.000009930489],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003575969,0.0001244321,0.9764664,0.000025698208,7.12476e-7,0.000010745356,0.0004914092,0.0000013138464,0.019925075,0.0000032105124,0.00008233151,0.0028328905],"study_design_scores_gemma":[0.00056347845,0.00014453144,0.96288896,0.00009645133,0.0000078959765,0.000017442551,0.00017114636,0.0010968955,0.034699943,0.000015169726,0.00018820507,0.0001098774],"about_ca_topic_score_codex":0.0000045720753,"about_ca_topic_score_gemma":7.999627e-7,"teacher_disagreement_score":0.014774869,"about_ca_system_score_codex":0.000012729526,"about_ca_system_score_gemma":0.00006612097,"threshold_uncertainty_score":0.48504716},"labels":[],"label_agreement":null},{"id":"W3095356774","doi":"10.3389/fnhum.2020.509258","title":"White Matter Neuroplasticity: Motor Learning Activates the Internal Capsule and Reduces Hemodynamic Response Variability","year":2020,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Fraser Health; Baycrest Hospital; University of Calgary; Simon Fraser University; University of British Columbia; Surrey Memorial Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroplasticity; Motor learning; Haemodynamic response; Internal capsule; Neuroscience; Psychology; White matter; Medicine; Internal medicine; Magnetic resonance imaging; Heart rate; Radiology","score_opus":0.030897466705632676,"score_gpt":0.303472759518954,"score_spread":0.2725752928133214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095356774","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91117674,0.00000914084,0.08037195,0.007796347,0.00010291182,0.000299696,0.0000039195256,0.000094547366,0.00014476568],"genre_scores_gemma":[0.99353135,0.000012459188,0.0032714761,0.0027685536,0.000032462638,0.000028121005,6.7191905e-7,0.000017082562,0.00033785313],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99879384,0.00017031295,0.00018156934,0.0004930075,0.00015550901,0.00020577529],"domain_scores_gemma":[0.9995102,0.000078634075,0.00007105514,0.00021708304,0.000020946398,0.00010204841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023911569,0.00012179483,0.00015883114,0.00006591129,0.00023229254,0.000056117122,0.00023911256,0.000023801473,0.000009052902],"category_scores_gemma":[0.00057169027,0.00009432946,0.000029341694,0.00027672376,0.00046681875,0.00013203008,0.00016680897,0.00049606594,7.3716666e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025804338,0.000049365033,0.40550473,0.000023667753,0.0000011817204,0.000028393404,0.00043336014,0.000401186,0.59163606,0.000045150624,0.0012381971,0.00038064746],"study_design_scores_gemma":[0.0003312509,0.0003678493,0.8936107,0.0000397081,0.000014755116,0.00006766371,0.00011255495,0.09175108,0.010147747,0.00061366474,0.0027823441,0.00016067438],"about_ca_topic_score_codex":0.0000030962547,"about_ca_topic_score_gemma":9.150828e-8,"teacher_disagreement_score":0.5814883,"about_ca_system_score_codex":0.000031219268,"about_ca_system_score_gemma":0.000023131228,"threshold_uncertainty_score":0.38466436},"labels":[],"label_agreement":null},{"id":"W3095563856","doi":"10.1016/j.neuroimage.2020.117513","title":"Plis de passage in the superior temporal sulcus: Morphology and local connectivity","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Mental Health; National Institutes of Health; NIH Blueprint for Neuroscience Research; Agence Nationale de la Recherche; McDonnell Center for Systems Neuroscience; Aix-Marseille Université","keywords":"Sulcus; Superior temporal sulcus; Anatomy; Functional connectivity; Central sulcus; White matter; Neuroscience; Psychology; Biology; Cartography; Geography; Medicine; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.06893601656193592,"score_gpt":0.33533053490757064,"score_spread":0.2663945183456347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3095563856","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93105155,0.000043584634,0.01861056,0.04903762,0.000009298326,0.00040043908,0.000014778564,0.00013867964,0.0006934992],"genre_scores_gemma":[0.9821527,0.000038354014,0.0021015087,0.015568485,0.000048995335,0.00004796945,0.0000062236163,0.000018384302,0.000017363667],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99923223,0.00007981409,0.00012666265,0.00029038143,0.00008464837,0.0001862494],"domain_scores_gemma":[0.9995055,0.0001290948,0.000027060983,0.00023835771,0.000014113707,0.000085870546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011295361,0.00010195855,0.00016619782,0.000027529753,0.00005261758,0.000015740134,0.00010594345,0.000038613976,0.000020413232],"category_scores_gemma":[0.0001426116,0.00007785082,0.000032827043,0.00018295513,0.00018802696,0.000055969842,0.00006270889,0.00036639813,0.000005514416],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044218227,0.00054814457,0.50692755,0.00018131846,0.000012830356,0.0042193504,0.0023796677,0.000021444928,0.44005978,0.0056460868,0.01591457,0.023647102],"study_design_scores_gemma":[0.0026065016,0.0010609233,0.89317787,0.00003328941,0.00006969575,0.0019870861,0.00059475773,0.007857488,0.017362028,0.0028904427,0.072000585,0.0003593506],"about_ca_topic_score_codex":0.000048364738,"about_ca_topic_score_gemma":0.0000056092904,"teacher_disagreement_score":0.42269775,"about_ca_system_score_codex":0.000014061808,"about_ca_system_score_gemma":0.00002711126,"threshold_uncertainty_score":0.31746644},"labels":[],"label_agreement":null},{"id":"W3097263943","doi":"10.1093/schizbullopen/sgaa057","title":"Frontostriatal Structural Connectivity and Striatal Glutamatergic Levels in Treatment-Resistant Schizophrenia: An Integrative Analysis of DTI and 1H-MRS","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health; McGill University; Douglas Mental Health University Institute","funders":"Japan Society for the Promotion of Science; Japan Agency for Medical Research and Development","keywords":"Caudate nucleus; Psychology; Internal medicine; Glutamatergic; Dorsolateral prefrontal cortex; Schizophrenia (object-oriented programming); Fractional anisotropy; Neuroscience; Prefrontal cortex; White matter; Medicine; Glutamate receptor; Endocrinology; Psychiatry; Magnetic resonance imaging; Cognition","score_opus":0.0678768236902872,"score_gpt":0.35222916742374144,"score_spread":0.28435234373345425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3097263943","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934915,0.00020351239,0.00034733283,0.0038266703,0.0000144626065,0.0011317912,0.00078948017,0.00006947712,0.00012579304],"genre_scores_gemma":[0.9767337,0.00008017239,0.022684196,0.00016424958,0.000035915928,0.00007342327,0.00016278327,0.000027150416,0.000038423866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982977,0.00012861243,0.0004499339,0.00072440534,0.00016246231,0.00023688505],"domain_scores_gemma":[0.9989387,0.0001383867,0.00021296731,0.0003877601,0.000059227772,0.00026299906],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014306822,0.00031501224,0.0009493413,0.00019813998,0.00011349491,0.000092219096,0.00024304958,0.000091841786,0.00019446418],"category_scores_gemma":[0.00013650968,0.00024879523,0.000095797914,0.0005520202,0.00021106751,0.00017422553,0.00029367744,0.00025130823,0.000002135532],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.12871413,0.0021771963,0.2901835,0.0005754173,0.00733047,0.0006519469,0.013523825,0.00036308556,0.28599375,0.044172514,0.0012413781,0.22507279],"study_design_scores_gemma":[0.02451507,0.00374739,0.9286541,0.0002446552,0.002375903,0.00005646893,0.0015195343,0.007545725,0.02603289,0.002582179,0.0017945435,0.0009315817],"about_ca_topic_score_codex":0.0014963101,"about_ca_topic_score_gemma":0.00060639426,"teacher_disagreement_score":0.63847053,"about_ca_system_score_codex":0.000068887646,"about_ca_system_score_gemma":0.000092703085,"threshold_uncertainty_score":0.9999964},"labels":[],"label_agreement":null},{"id":"W3098627671","doi":"10.3389/fnana.2020.599701","title":"In vivo Population Averaged Stereotaxic T2w MRI Brain Template for the Adult Yucatan Micropig","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; Neurosurgery Research and Education Foundation; U.S. Department of Defense","keywords":"Template; Neuroimaging; Brain morphometry; Population; Computer science; Probabilistic logic; Diffusion MRI; Neuroscience; Psychology; Artificial intelligence; Magnetic resonance imaging; Medicine","score_opus":0.03105195263611685,"score_gpt":0.31518982359094383,"score_spread":0.28413787095482695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3098627671","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3380245,0.0005224952,0.38044566,0.27268246,0.0008258702,0.006308493,0.00013208733,0.00045932626,0.0005991304],"genre_scores_gemma":[0.93767,0.00017251071,0.038295195,0.022785496,0.00015940367,0.00036484376,0.000033920795,0.00006922466,0.00044938954],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988941,0.00004198409,0.00031148258,0.0003865803,0.00012223818,0.00024364551],"domain_scores_gemma":[0.99935657,0.00010435377,0.00009024162,0.00033165558,0.000036835085,0.00008033106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000867642,0.00015278354,0.00024293557,0.00012095297,0.00007835374,0.000018486991,0.00019969155,0.00005149014,0.000014229799],"category_scores_gemma":[0.0001750962,0.00012863838,0.00007318874,0.00044292017,0.000045360455,0.00011225401,0.00004594489,0.0003310141,0.0000026740047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007190837,0.0002130749,0.22644508,0.00027854205,0.000038757986,0.0001497161,0.0008743965,0.00033398264,0.009724135,0.0021183258,0.7461483,0.012956607],"study_design_scores_gemma":[0.006539446,0.00038949584,0.07798948,0.00019050407,0.00009832003,0.00008445284,0.00040168545,0.09082483,0.012844489,0.009390683,0.8005875,0.0006591692],"about_ca_topic_score_codex":0.0000498525,"about_ca_topic_score_gemma":0.000013247171,"teacher_disagreement_score":0.59964556,"about_ca_system_score_codex":0.00006323879,"about_ca_system_score_gemma":0.000023585322,"threshold_uncertainty_score":0.5245721},"labels":[],"label_agreement":null},{"id":"W3099889620","doi":"10.3390/brainsci10110879","title":"Association between Structural Connectivity and Generalized Cognitive Spectrum in Alzheimer’s Disease","year":2020,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Clinical Dementia Rating; Cognition; Dementia; Psychology; Diffusion MRI; Association (psychology); Cognitive test; Disease; Alzheimer's disease; Cohort; Physical medicine and rehabilitation; Cognitive psychology; Audiology; Neuroscience; Medicine; Cognitive impairment; Internal medicine; Magnetic resonance imaging","score_opus":0.14003187563627217,"score_gpt":0.4001416751281488,"score_spread":0.2601097994918766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099889620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9151785,0.0001403547,0.0008211509,0.08329493,0.000008664052,0.00027138728,0.000024089119,0.00006448584,0.00019645048],"genre_scores_gemma":[0.99587715,0.000015057938,0.0013323888,0.0026620957,0.000073685165,0.000013010441,0.000007188601,0.0000036441095,0.00001580654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993551,0.00003576712,0.00009085572,0.00024517384,0.00014727829,0.00012582102],"domain_scores_gemma":[0.9995757,0.00019537582,0.000055676974,0.000041339503,0.000015666514,0.00011623786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000151773,0.000058623733,0.00011533746,0.000034155033,0.000091647365,0.000022068787,0.00004762279,0.000016423963,0.000013408617],"category_scores_gemma":[0.000534028,0.000050018632,0.000018332377,0.000285044,0.00012171503,0.00010316434,0.00003513837,0.00008093061,0.000001803438],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020052932,0.0000070622023,0.9941711,0.000004294378,0.0000066336524,0.000004646054,0.00013150553,0.0000029156047,0.000762539,0.0012981026,0.00032163446,0.0032695339],"study_design_scores_gemma":[0.0004292485,0.00007281388,0.9872592,0.000015843987,0.00004439842,0.0000013650241,0.000043998938,0.002160045,0.0012070568,0.008315744,0.0003763301,0.0000739358],"about_ca_topic_score_codex":0.000024021787,"about_ca_topic_score_gemma":0.000005115719,"teacher_disagreement_score":0.08069863,"about_ca_system_score_codex":0.00001674061,"about_ca_system_score_gemma":0.00004148566,"threshold_uncertainty_score":0.20397006},"labels":[],"label_agreement":null},{"id":"W3100033656","doi":"10.1101/2020.07.13.200972","title":"An interactive meta-analysis of MRI biomarkers of myelin","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Polytechnique Montréal","funders":"Wellcome Trust","keywords":"Myelin; Relaxometry; Modalities; Meta-analysis; Computer science; Pathology; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Radiology","score_opus":0.08975004590109842,"score_gpt":0.3442505196969797,"score_spread":0.25450047379588125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100033656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.63791025,0.0032663187,0.33749717,0.008498167,0.00036281056,0.005067507,0.0054451916,0.0018653751,0.000087198256],"genre_scores_gemma":[0.90427333,0.00015171921,0.09494283,0.00031534774,0.000050117116,0.0001866988,0.0000024928368,0.00007628852,0.0000011696595],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975906,0.00010648754,0.00080538396,0.0009228135,0.00035344245,0.00022129621],"domain_scores_gemma":[0.99606556,0.00009943242,0.00095410494,0.0019203617,0.0007180169,0.00024252706],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029617202,0.00040078154,0.0019211533,0.0006305672,0.000035547324,0.00002020482,0.000449604,0.00022578303,0.000110521956],"category_scores_gemma":[0.000160481,0.00037893467,0.0011362424,0.001500025,0.0001805309,0.00009043588,0.00028132772,0.00054908986,0.0000040491227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112174675,0.00035794155,0.0020632478,0.0003204097,0.062613085,0.000020563519,0.000014192879,0.00014657246,0.9335698,0.0005693783,0.00021077026,0.0000018443756],"study_design_scores_gemma":[0.00028273766,0.00016948249,0.035146274,0.00007585409,0.1810048,1.26079565e-8,0.000006765721,0.005282583,0.77628905,0.000013990399,0.0012940218,0.00043442304],"about_ca_topic_score_codex":0.000055327208,"about_ca_topic_score_gemma":9.206227e-7,"teacher_disagreement_score":0.26636305,"about_ca_system_score_codex":0.00008167666,"about_ca_system_score_gemma":0.0002508138,"threshold_uncertainty_score":0.99986625},"labels":[],"label_agreement":null},{"id":"W3100567746","doi":"10.1016/j.nicl.2020.102508","title":"Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study","year":2020,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Neuroimaging; Neuroplasticity; Stroke (engine); White matter; Neuroscience; Physical medicine and rehabilitation; Tractography; Corticospinal tract; Diffusion MRI; Motor learning; Psychology; Machine learning; Medicine; Artificial intelligence; Computer science; Magnetic resonance imaging; Radiology","score_opus":0.14074226609155271,"score_gpt":0.3935484635267317,"score_spread":0.25280619743517896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100567746","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99588436,0.000057682337,0.0016260535,0.0015393641,0.000050307834,0.0005434602,0.00005356747,0.00015364165,0.000091546855],"genre_scores_gemma":[0.9980043,0.00001982075,0.0008141452,0.00084775826,0.00016217367,0.000031868916,0.000007545802,0.000026395066,0.000085954416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986513,0.000114049464,0.000394031,0.0005043612,0.00019911358,0.00013711915],"domain_scores_gemma":[0.9990933,0.00030021166,0.00011513564,0.0002238044,0.00007988029,0.0001876467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014430178,0.00014046114,0.00035953394,0.000032555457,0.000063829175,0.000012556022,0.000060317998,0.000046307676,0.00009161394],"category_scores_gemma":[0.0009458084,0.00012632881,0.00011174527,0.00010407691,0.00018940314,0.00008224731,0.00015585357,0.0007003353,0.000004339167],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055878,0.00022255823,0.98160285,0.00004565079,0.00002487351,0.00013127047,0.00007710787,0.000003625793,0.010673242,0.00004204573,0.000041280866,0.0065767462],"study_design_scores_gemma":[0.0016234404,0.0023228328,0.9895742,0.000008280603,0.00007009173,0.00008189185,0.00003240246,0.0047470443,0.00021899227,0.000027550326,0.0011962545,0.00009699641],"about_ca_topic_score_codex":0.0000050629187,"about_ca_topic_score_gemma":9.520369e-7,"teacher_disagreement_score":0.01045425,"about_ca_system_score_codex":0.000006831658,"about_ca_system_score_gemma":0.000029806395,"threshold_uncertainty_score":0.51515394},"labels":[],"label_agreement":null},{"id":"W3100851471","doi":"10.1101/867606","title":"Diffusion MRI free water is a sensitive marker of age-related changes in the cingulum","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Caisse nationale de solidarité pour l'autonomie; Mitacs; Fondation de France; Fondation pour la Recherche Médicale; Institut National de la Santé et de la Recherche Médicale; Fondation Vaincre Alzheimer; CHIST-ERA; Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Mutuelle Générale de l'Education Nationale; Université de Sherbrooke; Sanofi","keywords":"Cingulum (brain); White matter; Splenium; Diffusion MRI; Inferior longitudinal fasciculus; Hyperintensity; Psychology; Verbal fluency test; Cognitive decline; Audiology; Neuroscience; Magnetic resonance imaging; Cognition; Fractional anisotropy; Neuropsychology; Medicine; Dementia; Pathology; Radiology; Disease","score_opus":0.02285288681428393,"score_gpt":0.26263929191258667,"score_spread":0.23978640509830274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3100851471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873165,0.00015074624,0.0014360307,0.008136813,0.00022909736,0.0021824657,0.0001842881,0.00027181848,0.00009228121],"genre_scores_gemma":[0.9926752,0.00041005973,0.005145557,0.0013247232,0.00010800031,0.00020371874,0.0000014664502,0.000096000906,0.00003529636],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99797523,0.00011377715,0.00043681508,0.0007319119,0.00035416472,0.000388086],"domain_scores_gemma":[0.9972181,0.00007696632,0.00026144998,0.0020932562,0.00026887876,0.00008135337],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048150046,0.00038394064,0.000594905,0.00027296494,0.00006363838,0.000032704607,0.00044267505,0.00035885288,0.000039893723],"category_scores_gemma":[0.00008983768,0.0002693638,0.00014109057,0.00034780955,0.00016299848,0.000040036863,0.00063328573,0.0009657652,0.000023190796],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060485956,0.0002563046,0.0074953847,0.00044911177,0.0000703483,0.00016400001,0.00016297968,0.000008707175,0.9896904,0.0003196892,0.0013185766,0.000004017515],"study_design_scores_gemma":[0.0012073829,0.00012599045,0.20729603,0.0015619056,0.0002466587,2.7599444e-7,0.000020154035,0.00095464935,0.77862746,0.000049888506,0.00933666,0.0005729399],"about_ca_topic_score_codex":0.00007296289,"about_ca_topic_score_gemma":0.0000034432417,"teacher_disagreement_score":0.21106294,"about_ca_system_score_codex":0.00010651919,"about_ca_system_score_gemma":0.00009602051,"threshold_uncertainty_score":0.99997586},"labels":[],"label_agreement":null},{"id":"W3102547238","doi":"10.1101/2020.11.16.385229","title":"Track-To-Learn: A general framework for tractography with deep reinforcement learning","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Tractography; Artificial intelligence; Computer science; Prior probability; Leverage (statistics); Deep learning; Machine learning; Diffusion MRI; Bayesian probability","score_opus":0.03895521377875129,"score_gpt":0.2981409867084565,"score_spread":0.25918577292970524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102547238","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08022746,0.00018721125,0.9114394,0.0035268313,0.00013830196,0.003083111,0.000035105415,0.0013441689,0.000018419887],"genre_scores_gemma":[0.597514,0.000108704095,0.39891067,0.0014772449,0.0004399151,0.0013664806,0.0000014817628,0.00017404965,0.000007444911],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972864,0.00003690857,0.0004996979,0.0012009813,0.0003933995,0.0005826321],"domain_scores_gemma":[0.99745435,0.000092033195,0.00036910127,0.0011032337,0.00041715027,0.0005641294],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019061027,0.0005782723,0.00070986414,0.00028174973,0.00022454163,0.00011871064,0.00036063872,0.00037336446,0.0000250048],"category_scores_gemma":[0.00027655892,0.00056018966,0.00026816534,0.00074100087,0.00008991313,0.00007257661,0.0002258763,0.0016285931,0.000018277664],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019391462,0.0008529854,0.019555906,0.003442392,0.0010998038,0.00029490533,0.00015297631,0.019180225,0.905396,0.04591378,0.002010609,0.00016129775],"study_design_scores_gemma":[0.004796456,0.004909235,0.10209547,0.005134459,0.00235077,6.955358e-7,0.000030346007,0.041223798,0.50232166,0.00040320994,0.33158776,0.005146147],"about_ca_topic_score_codex":0.000008605812,"about_ca_topic_score_gemma":2.8876212e-7,"teacher_disagreement_score":0.51728654,"about_ca_system_score_codex":0.00014454064,"about_ca_system_score_gemma":0.00027416786,"threshold_uncertainty_score":0.99968493},"labels":[],"label_agreement":null},{"id":"W3102824520","doi":"10.1016/j.euroneuro.2020.09.370","title":"P.506 Altered neurite density and dispersion in the white matter of carriers of 16p11.2 copy number variants","year":2020,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medicine; Periprosthetic; Predictive value; Humanities; Internal medicine; Surgery; Philosophy; Arthroplasty","score_opus":0.03874976731888263,"score_gpt":0.33990631581404457,"score_spread":0.30115654849516194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102824520","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850147,0.000027681639,0.0004342722,0.009937058,0.000093358336,0.00042803795,0.000013934201,0.0000576313,0.0039933515],"genre_scores_gemma":[0.9859212,0.000115482944,0.0008401576,0.012948211,0.000091020396,0.000005364254,0.0000038336298,0.00004478599,0.00002996384],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987233,0.0003511786,0.00032307385,0.00032897035,0.00011236854,0.00016106632],"domain_scores_gemma":[0.99938124,0.000067284316,0.00014652468,0.0002618886,0.000044991168,0.00009804177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013513488,0.00013224031,0.00024851933,0.00004547606,0.000029795572,0.000004775744,0.00018929993,0.000018080555,0.0001074701],"category_scores_gemma":[0.00003230259,0.000105529645,0.000053466905,0.00026640887,0.00018531535,0.000041262985,0.000097945805,0.0003153441,0.000020828904],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069730927,0.00019515962,0.40788633,0.0001199199,0.000017837798,0.00025544522,0.0010809572,0.000014200255,0.5646801,0.00009357524,0.0239542,0.0010049733],"study_design_scores_gemma":[0.0018899405,0.00029070908,0.9859838,0.000024912457,0.000079870195,0.00020474254,0.00007809056,0.00027066286,0.0019203719,0.0000392851,0.009110481,0.00010715794],"about_ca_topic_score_codex":0.0000035959367,"about_ca_topic_score_gemma":2.2965351e-7,"teacher_disagreement_score":0.57809746,"about_ca_system_score_codex":0.0000041355706,"about_ca_system_score_gemma":0.000009881881,"threshold_uncertainty_score":0.43033743},"labels":[],"label_agreement":null},{"id":"W3102841078","doi":"10.1002/hbm.25253","title":"Patch‐wise brain age longitudinal reliability","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Pfizer Canada; Fonds de Recherche du Québec - Santé; Alzheimer's Society; Pfizer","keywords":"Longitudinal study; Reliability (semiconductor); Magnetic resonance imaging; Longitudinal data; Neuroimaging; Volunteer; Psychology; Computer science; Audiology; Statistics; Medicine; Data mining; Mathematics; Neuroscience; Radiology; Biology","score_opus":0.17760902915917862,"score_gpt":0.3756412571497676,"score_spread":0.19803222799058898,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102841078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5650093,0.00006823201,0.16229746,0.25937194,0.00003921285,0.0012830286,0.00001611839,0.0017451554,0.010169567],"genre_scores_gemma":[0.9669325,0.000004173567,0.013691938,0.018199865,0.0002813797,0.00006059346,0.000044190987,0.000036792702,0.0007485756],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987545,0.000037801834,0.0002835095,0.00049641903,0.00017304362,0.00025473523],"domain_scores_gemma":[0.9990726,0.000121540616,0.0000804231,0.00047415541,0.00004870576,0.0002025535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019187058,0.00015839907,0.00025411707,0.000049560804,0.000227588,0.000026282936,0.00015191211,0.00005169092,0.00014757433],"category_scores_gemma":[0.00041954123,0.00015938973,0.000110614536,0.0002649902,0.00012547012,0.00007385271,0.00011564777,0.00034126188,0.0000497889],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062411505,0.00027981994,0.07049661,0.00055104936,0.000036077196,0.00048407115,0.0019594936,0.000031901036,0.6190274,0.022586524,0.27987796,0.004606728],"study_design_scores_gemma":[0.0011921335,0.00028003257,0.39190987,0.0002066826,0.0000346803,0.00005480626,0.00017067161,0.0011197524,0.0010097201,0.02077255,0.5828074,0.0004417019],"about_ca_topic_score_codex":0.00001829797,"about_ca_topic_score_gemma":0.0000024660167,"teacher_disagreement_score":0.6180177,"about_ca_system_score_codex":0.000047188525,"about_ca_system_score_gemma":0.000022711707,"threshold_uncertainty_score":0.64997244},"labels":[],"label_agreement":null},{"id":"W3102888858","doi":"10.1007/s12021-020-09497-1","title":"Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography","year":2020,"lang":"en","type":"article","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; U.S. Department of Defense","keywords":"Tractography; Diffusion MRI; White matter; Fiber tract; Bundle; Population; Neuroscience; Computer science; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Radiology; Materials science","score_opus":0.0401730737370954,"score_gpt":0.2885568518185119,"score_spread":0.24838377808141648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3102888858","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9435995,0.000015423477,0.0407804,0.012349016,0.00004066182,0.000695076,0.00011284017,0.0005519948,0.0018550673],"genre_scores_gemma":[0.93233407,0.000022956838,0.05141404,0.015499653,0.00008994003,0.000032459826,0.0004964642,0.000041019633,0.00006938736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989622,0.000014422592,0.00040382284,0.00019381757,0.00023458505,0.00019111161],"domain_scores_gemma":[0.9991146,0.000103086684,0.00016582663,0.00037508202,0.000050939605,0.00019046277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000018891491,0.00018620033,0.00025085785,0.00007052889,0.00011009034,0.00004342869,0.000115911804,0.000056920915,0.00046995282],"category_scores_gemma":[0.000040765222,0.00016345538,0.00013084945,0.00026575598,0.00003511112,0.00018220537,0.000046871006,0.0002457389,0.0002306605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023305473,0.00040923574,0.9616604,0.00028603894,0.000027075335,0.000020734095,0.0006072338,0.0010865203,0.007152958,0.000049363596,0.025329575,0.0031378227],"study_design_scores_gemma":[0.0021661303,0.00038126946,0.8602995,0.00012800205,0.0001829913,0.000022982622,0.00007722245,0.08334087,0.005176355,0.00031742328,0.04744387,0.00046334596],"about_ca_topic_score_codex":0.000017902576,"about_ca_topic_score_gemma":0.0000010842507,"teacher_disagreement_score":0.10136085,"about_ca_system_score_codex":0.000014146898,"about_ca_system_score_gemma":0.000021843092,"threshold_uncertainty_score":0.66655165},"labels":[],"label_agreement":null},{"id":"W3103593486","doi":"10.3389/fpsyg.2020.608049","title":"Associations Between Physical Fitness and Brain Structure in Young Adulthood","year":2020,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Fractional anisotropy; Psychology; Diffusion MRI; White matter; Physical fitness; Connectome; Human Connectome Project; Brain size; Magnetic resonance imaging; Neuroscience; Physical therapy; Medicine","score_opus":0.03718807847145747,"score_gpt":0.3773504608082844,"score_spread":0.34016238233682694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3103593486","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8448802,0.00012222232,0.086411044,0.066990755,0.00012937887,0.0004746605,0.00013569697,0.000112961956,0.0007430586],"genre_scores_gemma":[0.9630904,0.000035468496,0.03351092,0.0031156708,0.00014010977,0.000018099734,0.00006521886,0.000014812271,0.000009263888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99931484,0.00003522287,0.00015384042,0.00028666554,0.000056280915,0.00015316701],"domain_scores_gemma":[0.9997027,0.000031739237,0.000046762325,0.00013966943,0.000013283945,0.000065861175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000032976346,0.000082156206,0.00026409724,0.000078442434,0.000021710463,0.0000037853797,0.000072342045,0.00008038986,0.0000037560758],"category_scores_gemma":[0.000098213844,0.00008378853,0.00002193017,0.0003069636,0.00006406682,0.000036253696,0.000024791438,0.00034534174,9.705016e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002200285,0.000045186818,0.9624868,0.000007762966,0.000007792938,0.000009002167,0.00058727403,0.0000011991302,0.0009643482,0.00025653103,0.017028274,0.018583829],"study_design_scores_gemma":[0.0012378,0.00010014729,0.96357924,0.000013960411,0.000014859849,0.000008274392,0.000065501794,0.00044258192,0.00013726523,0.030923627,0.0033808504,0.000095872],"about_ca_topic_score_codex":0.000005186658,"about_ca_topic_score_gemma":0.000004137519,"teacher_disagreement_score":0.11821022,"about_ca_system_score_codex":0.00002498162,"about_ca_system_score_gemma":0.000010469541,"threshold_uncertainty_score":0.3416797},"labels":[],"label_agreement":null},{"id":"W3105764270","doi":"","title":"Holonomy spin foam models: Asymptotic geometry of the partition function","year":2013,"lang":"en","type":"article","venue":"MPG.PuRe (Max Planck Society)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Narodowe Centrum Nauki; Institut Périmètre de physique théorique; Industry Canada; Government of Canada","keywords":"Partition function (quantum field theory); Spin foam; Holonomy; Immirzi parameter; Curvature; Mathematics; Partition (number theory); Boundary (topology); Spin network; Spins; Geometry; Mathematical analysis; Loop quantum gravity; Physics; Combinatorics; Quantum mechanics; Quantum; Quantum gravity","score_opus":0.054361670690449636,"score_gpt":0.28978365419648305,"score_spread":0.2354219835060334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3105764270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8222199,0.00044734945,0.15545093,0.0084749395,0.00032550417,0.0021926344,0.000044886878,0.00056392833,0.010279936],"genre_scores_gemma":[0.9904628,0.000072634015,0.0066783796,0.0014812887,0.00016607171,0.00020594092,0.000041746378,0.000027950726,0.00086322695],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99907434,0.000017482304,0.00024068796,0.00025556973,0.00019700424,0.00021492803],"domain_scores_gemma":[0.9991505,0.000038132726,0.00014500809,0.0004954261,0.00010434353,0.0000665755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000763441,0.00014071156,0.0002015325,0.000032641397,0.00012187596,0.00001541494,0.00013038173,0.00011243719,0.00010489515],"category_scores_gemma":[0.000020241878,0.00010471924,0.00021549004,0.00036929452,0.00010432814,0.00016795032,0.0000613423,0.00028791194,0.000040665982],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015254552,0.0016558949,0.11967391,0.0011137545,0.0004865221,0.000005649694,0.0010839077,0.0034428276,0.15098605,0.067358814,0.6226045,0.031435665],"study_design_scores_gemma":[0.004871502,0.0012472728,0.42192763,0.0009483283,0.0010536729,0.0001941972,0.0011203577,0.064546734,0.043474138,0.27483788,0.18435135,0.0014269284],"about_ca_topic_score_codex":0.000019183153,"about_ca_topic_score_gemma":9.180865e-7,"teacher_disagreement_score":0.4382531,"about_ca_system_score_codex":0.00005569618,"about_ca_system_score_gemma":0.000038965383,"threshold_uncertainty_score":0.42703268},"labels":[],"label_agreement":null},{"id":"W3106311311","doi":"10.1371/journal.pone.0242696","title":"Free water: A marker of age-related modifications of the cingulum white matter and its association with cognitive decline","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Caisse nationale de solidarité pour l'autonomie; Fondation Plan Alzheimer; Mitacs; Fondation de France; Fondation pour la Recherche Médicale; Fondation Vaincre Alzheimer; Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Sanofi","keywords":"Cingulum (brain); White matter; Splenium; Inferior longitudinal fasciculus; Hyperintensity; Diffusion MRI; Cognitive decline; Psychology; Verbal fluency test; Neuroscience; Cognition; Audiology; Tractography; Neuropsychology; Fractional anisotropy; Medicine; Magnetic resonance imaging; Internal medicine; Dementia; Radiology","score_opus":0.05795097177639184,"score_gpt":0.27184873032045265,"score_spread":0.21389775854406082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106311311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9647761,0.000025260573,0.0006351691,0.032763995,0.0000019042099,0.0005377783,0.000077045224,0.00004098791,0.0011417324],"genre_scores_gemma":[0.9959459,0.0000257158,0.0025225335,0.000809097,0.000010895938,0.000040792413,0.000020484309,0.000013919803,0.0006106701],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99944186,0.00001982101,0.00017060475,0.0001240111,0.0001697616,0.00007395748],"domain_scores_gemma":[0.9994446,0.00004412559,0.00012722002,0.00015649734,0.00019254441,0.000035007484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050183266,0.000058431946,0.00015886227,0.000020066795,0.0000319472,0.0000029827302,0.000061903644,0.00003213967,0.000043728636],"category_scores_gemma":[0.00012754329,0.00003677833,0.00002183377,0.0001376263,0.00004347588,0.000029874016,0.00006846042,0.000119763856,0.0000037434866],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013257455,0.0007536342,0.56640077,0.0002598512,0.0002670815,0.0000018910891,0.0010293772,0.0000042517363,0.43046144,0.00021833542,0.0004107931,0.000060017857],"study_design_scores_gemma":[0.0013828424,0.00016821572,0.5189205,0.0004713317,0.0007353969,0.0000032824935,0.000058441925,0.0019530768,0.4752612,0.00089619134,0.000053956323,0.000095550866],"about_ca_topic_score_codex":0.000003289616,"about_ca_topic_score_gemma":0.0000011854364,"teacher_disagreement_score":0.047480244,"about_ca_system_score_codex":0.000011008487,"about_ca_system_score_gemma":0.000009988775,"threshold_uncertainty_score":0.14997767},"labels":[],"label_agreement":null},{"id":"W3106722478","doi":"10.21203/rs.3.rs-108135/v1","title":"Hippocampal Volume Influences The Correlations Between White Matter Disruption and Tau Protein in aMCI and mild AD","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Hippocampal formation; White matter; Neuroscience; Psychology; Brain size; Medicine; Magnetic resonance imaging","score_opus":0.1586051461463248,"score_gpt":0.45053634798170455,"score_spread":0.2919312018353798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3106722478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.913738,0.0006285448,0.002512896,0.07827035,0.000013368256,0.004199586,0.00014590051,0.00011098774,0.00038036986],"genre_scores_gemma":[0.9949815,0.000299217,0.0027148079,0.00015697695,0.0001173528,0.0010347449,0.00013127727,0.000029649022,0.00053443527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983336,0.00018765777,0.000262303,0.0005253576,0.00040807753,0.000283029],"domain_scores_gemma":[0.99902415,0.000152368,0.00007247779,0.00046558105,0.00013616274,0.00014928526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004328299,0.00016201871,0.000253157,0.00019212023,0.00020815538,0.00009600362,0.00016713515,0.00014980478,0.00004033002],"category_scores_gemma":[0.00018383718,0.00012264734,0.000040431853,0.00034777494,0.00038247867,0.00007361806,0.0006833558,0.0018261485,0.000028690787],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035829235,0.000033533488,0.9915579,0.00058116624,0.000011855691,0.000010551067,0.0006314104,0.000011874535,0.00038224453,0.00018622942,0.0020905363,0.0044668973],"study_design_scores_gemma":[0.00022380841,0.000102334794,0.9801899,0.0008321071,0.000020293865,0.0000066000916,0.00021054424,0.001083806,0.000041550888,0.012374631,0.004794372,0.00012005575],"about_ca_topic_score_codex":0.00011071452,"about_ca_topic_score_gemma":0.000022061033,"teacher_disagreement_score":0.081243545,"about_ca_system_score_codex":0.0000702509,"about_ca_system_score_gemma":0.000098066696,"threshold_uncertainty_score":0.7933808},"labels":[],"label_agreement":null},{"id":"W3107476337","doi":"10.1093/schbul/sbaa169","title":"Orbitofrontal-Striatal Structural Alterations Linked to Negative Symptoms at Different Stages of the Schizophrenia Spectrum","year":2020,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; McGill University","keywords":"Schizophrenia spectrum; Schizophrenia (object-oriented programming); Psychology; Clinical psychology; Orbitofrontal cortex; Psychiatry; Neuroscience; Medicine; Psychosis; Cognition; Prefrontal cortex","score_opus":0.02775570877029532,"score_gpt":0.28608482051685186,"score_spread":0.25832911174655654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107476337","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9216464,0.000047967646,0.0017160287,0.07446643,0.00013207385,0.0013046237,0.00026494372,0.00024041362,0.00018110126],"genre_scores_gemma":[0.9834513,0.000012230533,0.0138450675,0.0016890556,0.00038028933,0.00009786255,0.00005204662,0.000051119936,0.00042099538],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99823105,0.00006482172,0.0005049897,0.00053408043,0.00034779563,0.00031726458],"domain_scores_gemma":[0.9986512,0.00009669415,0.00022032208,0.00065181416,0.000076708115,0.0003032652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040697287,0.00030914016,0.00043206406,0.000066247776,0.00028608597,0.000031022784,0.00036820798,0.00007487341,0.0005193842],"category_scores_gemma":[0.00022531125,0.00021526104,0.00021607534,0.0003603562,0.00016530255,0.00003498725,0.00043565794,0.00044291923,0.00010114752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019149795,0.00064537954,0.0667618,0.00047567353,0.0006348123,0.000052788735,0.00400655,0.00082347885,0.7645339,0.04269202,0.08646895,0.013754874],"study_design_scores_gemma":[0.010172186,0.0016932106,0.4402843,0.0004397737,0.00042781368,0.000114291295,0.00013356886,0.0010738935,0.5081213,0.005042832,0.03139222,0.0011046183],"about_ca_topic_score_codex":0.0000309586,"about_ca_topic_score_gemma":0.000028222135,"teacher_disagreement_score":0.37352252,"about_ca_system_score_codex":0.00011428712,"about_ca_system_score_gemma":0.000056011995,"threshold_uncertainty_score":0.87780905},"labels":[],"label_agreement":null},{"id":"W3107809671","doi":"10.1101/2020.11.27.401950","title":"Predicting Brain Regions Related to Alzheimer’s Disease Based on Global Feature","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences; Institute of Biophysics, Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Betweenness centrality; Centrality; Diffusion MRI; Correlation; Feature (linguistics); Computer science; Pattern recognition (psychology); Graph; Artificial intelligence; Medicine; Mathematics; Theoretical computer science; Magnetic resonance imaging; Statistics","score_opus":0.04347364630648888,"score_gpt":0.3096060437629206,"score_spread":0.26613239745643175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107809671","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27137956,0.0021846707,0.0854062,0.6010912,0.0018968345,0.015490909,0.005703787,0.016394278,0.00045255583],"genre_scores_gemma":[0.9393372,0.000033300752,0.04757308,0.011906997,0.00032429784,0.00062881695,0.000004922603,0.00018092155,0.000010484732],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9969593,0.00008735784,0.00043955154,0.0015044892,0.0004960302,0.00051323645],"domain_scores_gemma":[0.9961106,0.00009162156,0.00029173426,0.0020379901,0.00029894142,0.0011691079],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018525904,0.00060904934,0.0005817552,0.00017319569,0.0002120232,0.00009023071,0.0004687027,0.00038136536,0.000017667648],"category_scores_gemma":[0.0007743543,0.0006487866,0.00026420472,0.0010342851,0.0000947215,0.00005701748,0.0004120138,0.0013584351,0.000071670846],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030380792,0.003510162,0.32049558,0.0026975526,0.0014509071,0.004669873,0.000045214623,0.0056075277,0.33028033,0.0465989,0.28151402,0.00009187362],"study_design_scores_gemma":[0.002684019,0.00065648154,0.8074996,0.005374945,0.0021370612,2.503653e-7,0.0000037962177,0.045061443,0.029298432,0.00023070445,0.104355395,0.0026978746],"about_ca_topic_score_codex":0.000010529742,"about_ca_topic_score_gemma":3.4153447e-7,"teacher_disagreement_score":0.6679576,"about_ca_system_score_codex":0.00032926205,"about_ca_system_score_gemma":0.00075233367,"threshold_uncertainty_score":0.99959636},"labels":[],"label_agreement":null},{"id":"W3108047961","doi":"10.3389/fnagi.2020.594002","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Royal Golden Jubilee (RGJ) Ph.D. Programme; Thailand Research Fund; Chiang Mai University","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Psychology; Cognition; Neuroscience; Executive functions; Cognitive impairment; Dementia; Hippocampus; Audiology; Medicine; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.04357388248549012,"score_gpt":0.3245562028634962,"score_spread":0.2809823203780061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108047961","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97536314,0.000069540634,0.018405888,0.003747965,0.0000738527,0.0021752631,0.00002085979,0.00012501281,0.000018474848],"genre_scores_gemma":[0.99318236,0.00008127415,0.0011857401,0.0052943355,0.000015467735,0.00019040392,0.000011447785,0.00003249624,0.000006475796],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99778235,0.00010929594,0.00037958572,0.00092071336,0.0003295553,0.00047851112],"domain_scores_gemma":[0.99932426,0.00011143723,0.00015913742,0.00016974566,0.00005838204,0.0001770379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023199133,0.00026022666,0.00040668782,0.00037895577,0.00014077623,0.000049984847,0.0001536655,0.000030166635,0.0000012744227],"category_scores_gemma":[0.00030331864,0.00023384311,0.000024934156,0.0011812872,0.00021366592,0.00025251138,0.00013758255,0.0007899853,4.0321368e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043717542,0.001009,0.9929247,0.00006732289,0.0000017397423,0.0001463236,0.003589273,0.000004668176,0.0003850043,8.101055e-7,0.000043816784,0.0013901585],"study_design_scores_gemma":[0.006040589,0.001034719,0.92838216,0.0016708316,0.0000283181,0.000015340413,0.0025965562,0.05979362,0.00013990558,0.00008459904,0.0000020173359,0.00021134471],"about_ca_topic_score_codex":0.000114497256,"about_ca_topic_score_gemma":0.000041737378,"teacher_disagreement_score":0.06454255,"about_ca_system_score_codex":0.00013830281,"about_ca_system_score_gemma":0.00006254144,"threshold_uncertainty_score":0.9535845},"labels":[],"label_agreement":null},{"id":"W3108455943","doi":"10.1101/2020.11.23.20237099","title":"Rapid Microscopic Fractional Anisotropy Imaging via an Optimized Kurtosis Formulation","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Fractional anisotropy; Anisotropy; Diffusion MRI; Kurtosis; Isotropy; Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Orientation (vector space); Thermal diffusivity; Metric (unit); SIGNAL (programming language); Algorithm; Mathematics; Biological system; Computer science; Statistics; Optics; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.08020277305073353,"score_gpt":0.36899173637777877,"score_spread":0.28878896332704523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108455943","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12046024,0.0002620469,0.86513805,0.011102035,0.00026142303,0.0011829337,0.00005133784,0.000997112,0.00054479594],"genre_scores_gemma":[0.69123113,0.00026309685,0.30555433,0.001571232,0.00041167537,0.00022894783,0.0005959222,0.00008225198,0.000061423365],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982474,0.000047120324,0.0004177933,0.00076335354,0.0002763109,0.00024806356],"domain_scores_gemma":[0.998557,0.000048091308,0.00026839983,0.00076298846,0.00014820122,0.00021531984],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011078012,0.0003121469,0.00044861596,0.00013788072,0.00014765377,0.000053315864,0.00022974488,0.00013594446,0.00020629299],"category_scores_gemma":[0.00006218464,0.00031703227,0.00018833723,0.00016058968,0.000057331614,0.00014765566,0.00026403437,0.00080976135,0.000036870308],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067403674,0.0008913004,0.09403995,0.0007402038,0.00020227378,0.00013223082,0.00035725263,0.0014327037,0.8542977,0.0025829566,0.0037792793,0.040870108],"study_design_scores_gemma":[0.0056480644,0.0005043032,0.19796513,0.00087806827,0.0011922269,0.0003699998,0.00006710215,0.44027326,0.17923327,0.07064727,0.10111596,0.0021053671],"about_ca_topic_score_codex":0.000024567906,"about_ca_topic_score_gemma":4.4655098e-7,"teacher_disagreement_score":0.67506444,"about_ca_system_score_codex":0.00011515652,"about_ca_system_score_gemma":0.00010554076,"threshold_uncertainty_score":0.9999282},"labels":[],"label_agreement":null},{"id":"W3108924128","doi":"10.1038/s41598-020-77675-x","title":"Diffusion tensor imaging and arterial tissue: establishing the influence of arterial tissue microstructure on fractional anisotropy, mean diffusivity and tractography","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"European Research Council; European Commission","keywords":"Fractional anisotropy; Elastin; Diffusion MRI; Tractography; Biomedical engineering; Anisotropy; Chemistry; Materials science; Thermal diffusivity; Ex vivo; Nuclear magnetic resonance; Pathology; Medicine; Magnetic resonance imaging; Radiology; Biochemistry; Physics; In vitro; Optics","score_opus":0.018435339693126662,"score_gpt":0.29386585819326205,"score_spread":0.2754305185001354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108924128","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943416,0.000040965304,0.0013337802,0.0032322123,0.00044736583,0.00046644037,0.000019290155,0.00007489594,0.000043460754],"genre_scores_gemma":[0.9970828,0.000014408822,0.0022874072,0.0003515718,0.00017982045,0.000012532334,0.000029692153,0.000014486459,0.000027237631],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986026,0.00002513218,0.000311558,0.0005879071,0.00031228724,0.00016047485],"domain_scores_gemma":[0.9990282,0.00005897124,0.00027042796,0.00040447712,0.00010665685,0.00013128815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017942372,0.00014037559,0.00020148141,0.00007141574,0.00034478147,0.0001883859,0.000070261034,0.000039476177,0.000024209146],"category_scores_gemma":[0.000176717,0.0001006287,0.000034104927,0.00026326597,0.0004887878,0.00020652161,0.000087082364,0.00020509334,4.572597e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006237917,0.000042092066,0.010033821,0.000029291334,0.000003798801,0.000065943364,0.0003799594,0.000008692488,0.98460233,0.000067476445,0.0011607051,0.0035435376],"study_design_scores_gemma":[0.00095146336,0.00022520366,0.67158765,0.0001841107,0.00012650368,0.0019857043,0.0002352227,0.0004090355,0.17950186,0.008686349,0.13574861,0.0003583271],"about_ca_topic_score_codex":0.000026390966,"about_ca_topic_score_gemma":0.0000023220498,"teacher_disagreement_score":0.80510044,"about_ca_system_score_codex":0.000009657262,"about_ca_system_score_gemma":0.00003062505,"threshold_uncertainty_score":0.4103519},"labels":[],"label_agreement":null},{"id":"W3109069154","doi":"10.1101/2020.11.24.396119","title":"Longitudinal white matter changes associated with cognitive training","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada Excellence Research Chairs, Government of Canada; Canadian Institute for Advanced Research","keywords":"Working memory; Task (project management); Cognitive psychology; Psychology; Cognition; Working memory training; Memory span; Transfer of learning; n-back; White matter; Audiology; Neuroscience; Developmental psychology; Medicine","score_opus":0.079318831608745,"score_gpt":0.29595090333812246,"score_spread":0.21663207172937746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109069154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9348309,0.00035276287,0.042300344,0.015494846,0.00024397181,0.0029793447,0.00092935626,0.0026757016,0.00019279985],"genre_scores_gemma":[0.98353565,0.00006217477,0.012951496,0.0023232766,0.00032836632,0.0005745466,0.00000354023,0.00020269981,0.000018276469],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977129,0.000053005064,0.00030318083,0.001087732,0.0003547126,0.0004884298],"domain_scores_gemma":[0.99805695,0.00007412871,0.00039376525,0.0006612461,0.0004938589,0.00032007566],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016331265,0.000525695,0.00070762,0.00017449763,0.00014012164,0.000090533526,0.00023024205,0.00028737754,0.00008982792],"category_scores_gemma":[0.0001749907,0.0005066682,0.0001082439,0.00050817546,0.00017742907,0.000068533576,0.00027731346,0.0011535526,0.00005864619],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051917124,0.00082001527,0.74861884,0.0013097536,0.0014541799,0.0014679859,0.00018274902,0.000017882096,0.24051955,0.0006009633,0.0044669546,0.000021949261],"study_design_scores_gemma":[0.001153705,0.0002723504,0.95214725,0.0029238095,0.00079791824,2.4776315e-7,0.000012614323,0.0002629221,0.039823443,0.000007483893,0.0016837275,0.0009145324],"about_ca_topic_score_codex":0.000005304731,"about_ca_topic_score_gemma":0.0000016826104,"teacher_disagreement_score":0.2035284,"about_ca_system_score_codex":0.00016371401,"about_ca_system_score_gemma":0.00032308014,"threshold_uncertainty_score":0.9997385},"labels":[],"label_agreement":null},{"id":"W3109238976","doi":"10.2478/awutp-2020-0007","title":"Diffusion Magnetic Resonance Imaging with Applications to Cardiac Muscle: Short Review","year":2020,"lang":"en","type":"article","venue":"Annals of West University of Timisoara - Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; University of Toronto","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Tractography; Effective diffusion coefficient; Nuclear magnetic resonance; Medicine; Translation (biology); Biomedical engineering; Nuclear medicine; Radiology; Physics; Chemistry","score_opus":0.0801239907144819,"score_gpt":0.32308060343652434,"score_spread":0.24295661272204244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109238976","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10367999,0.04233653,0.52046025,0.29352733,0.000043688742,0.011157199,0.0009948283,0.0011357528,0.026664425],"genre_scores_gemma":[0.8665191,0.03306953,0.08640958,0.013067245,0.00016532693,0.000020713402,0.00013177117,0.000073098905,0.00054361974],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993361,0.0000126153045,0.000120450764,0.00024299756,0.00016902368,0.00011877186],"domain_scores_gemma":[0.9991568,0.00002208469,0.00007515517,0.0003701563,0.00023745706,0.00013836486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003510345,0.00010201721,0.00029832617,0.000022887129,0.000061035535,0.0000019477914,0.0001722659,0.00001543899,0.000020144613],"category_scores_gemma":[0.000009240186,0.00010828205,0.00009657273,0.00042539535,0.00011379741,0.00006896858,0.000090449495,0.000099385834,0.000009992011],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002492287,0.0007139073,0.015056778,0.002286564,0.000040734503,0.000024913885,0.0006020922,0.0001210992,0.046586853,0.004195293,0.06037578,0.86974674],"study_design_scores_gemma":[0.00042336062,0.00060159346,0.049762405,0.0020881568,0.00035020438,0.0000045013403,0.00019341099,0.00062087766,0.0076747797,0.00031142248,0.9376081,0.0003611783],"about_ca_topic_score_codex":0.000024034653,"about_ca_topic_score_gemma":4.5165444e-7,"teacher_disagreement_score":0.8772323,"about_ca_system_score_codex":0.0000077027635,"about_ca_system_score_gemma":0.000038189504,"threshold_uncertainty_score":0.4415614},"labels":[],"label_agreement":null},{"id":"W3109249627","doi":"10.1101/2020.11.24.396549","title":"Processing the diffusion-weighted magnetic resonance imaging of the PING dataset","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke; McGill University Health Centre","funders":"Canada First Research Excellence Fund; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Diffusion MRI; White matter; Ping (video games); Computer science; Artificial intelligence; Magnetic resonance imaging; Neuroimaging; Visualization; Pattern recognition (psychology); Neuroscience; Medicine; Psychology; Radiology","score_opus":0.031629990539753836,"score_gpt":0.28046295915850156,"score_spread":0.2488329686187477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109249627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74115276,0.06281014,0.062563896,0.1022841,0.001761491,0.015148244,0.010260658,0.0038627628,0.00015594222],"genre_scores_gemma":[0.98030156,0.00035843195,0.016616631,0.0020924895,0.00025655382,0.00025372882,0.000002944574,0.00011358886,0.000004100522],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9978545,0.00007981812,0.00052016095,0.00078615575,0.00041964982,0.00033975014],"domain_scores_gemma":[0.99700224,0.00007037177,0.00048023832,0.0020409054,0.00027634017,0.0001298949],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022460696,0.0003764402,0.0004385915,0.00007724543,0.00031310416,0.00007957571,0.0008757347,0.00012087437,0.000015689395],"category_scores_gemma":[0.00022544582,0.0002534026,0.00013353002,0.0007032609,0.00034309793,0.00007466324,0.0011733896,0.0010741331,0.000006453268],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000069045265,0.00022270539,0.022237752,0.001055405,0.000023298358,0.00004933151,0.0000282757,0.000005757269,0.967903,0.0011790994,0.006965974,0.0002603476],"study_design_scores_gemma":[0.0012150209,0.00007114153,0.43366873,0.004832683,0.0006657665,5.796452e-7,0.000011688605,0.014749245,0.29135218,0.00010423688,0.25227514,0.0010536027],"about_ca_topic_score_codex":0.000027081,"about_ca_topic_score_gemma":3.776287e-7,"teacher_disagreement_score":0.6765508,"about_ca_system_score_codex":0.000092345326,"about_ca_system_score_gemma":0.00058002037,"threshold_uncertainty_score":0.99999183},"labels":[],"label_agreement":null},{"id":"W3110641764","doi":"10.1101/2020.12.03.408567","title":"MASiVar: Multisite, Multiscanner, and Multisubject Acquisitions for Studying Variability in Diffusion Weighted Magnetic Resonance Imaging","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Diffusion MRI; Connectomics; Fractional anisotropy; Connectome; Pattern recognition (psychology); Artificial intelligence; Magnetic resonance imaging; Orientation (vector space); Nuclear magnetic resonance; Computer science; Mathematics; Psychology; Medicine; Neuroscience; Physics; Radiology; Functional connectivity","score_opus":0.03137716795229804,"score_gpt":0.2888891434856524,"score_spread":0.25751197553335436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110641764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87283033,0.0046050046,0.10917564,0.0033574088,0.00030175297,0.0074247415,0.0009559011,0.0013387051,0.000010529431],"genre_scores_gemma":[0.8035147,0.0005237691,0.19379665,0.0004275201,0.00017385055,0.0014195157,0.0000026842067,0.00013757843,0.0000037321981],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9966774,0.00014481522,0.0007073243,0.0016495631,0.0002698175,0.0005510613],"domain_scores_gemma":[0.9974974,0.00034298695,0.00027714323,0.0012132725,0.0003537949,0.00031543538],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00050055725,0.00057323853,0.00078006467,0.00029291466,0.00024261215,0.000099339995,0.00029754435,0.0002585193,0.000012975735],"category_scores_gemma":[0.0005518711,0.0006291903,0.00014654073,0.0005573712,0.00017965325,0.00013042898,0.00066653575,0.00090683176,0.000003969024],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025384876,0.0007327326,0.21708041,0.001071971,0.000025930958,0.00014127279,0.000044371536,0.000007871912,0.7790712,0.00081320055,0.00021400252,0.0005431602],"study_design_scores_gemma":[0.0037154367,0.00012914375,0.8841227,0.0014309948,0.00023807726,3.2426718e-7,0.00000813555,0.0689662,0.03483875,0.00011086424,0.0054746205,0.0009647176],"about_ca_topic_score_codex":0.000082237035,"about_ca_topic_score_gemma":0.000003360361,"teacher_disagreement_score":0.7442325,"about_ca_system_score_codex":0.00028534245,"about_ca_system_score_gemma":0.00017696797,"threshold_uncertainty_score":0.99961597},"labels":[],"label_agreement":null},{"id":"W3110682263","doi":"10.1002/alz.038868","title":"White matter texture abnormalities are associated with delusional severity in a cognitively mixed sample of older adults","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; St. Michael's Hospital","funders":"","keywords":"White matter; Correlation; Psychology; Fluid-attenuated inversion recovery; Audiology; Medicine; Magnetic resonance imaging; Radiology; Mathematics","score_opus":0.03937792891805645,"score_gpt":0.2859561669282072,"score_spread":0.24657823801015075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110682263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9713053,0.0028121043,0.008771119,0.013719376,0.000031301184,0.0014664162,0.000806587,0.00023346239,0.00085433037],"genre_scores_gemma":[0.9890972,0.000010584383,0.0073346095,0.0032083937,0.000024464533,0.00006788115,0.00022571185,0.0000240297,0.000007127902],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990933,0.000031648273,0.00023721834,0.000257544,0.00019751918,0.00018279423],"domain_scores_gemma":[0.99941933,0.00006101892,0.00015648945,0.00013563305,0.00014851727,0.00007902398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051583724,0.00013928559,0.00023955901,0.000043028173,0.00004357157,0.00000682054,0.0000805521,0.00005000395,0.00027220874],"category_scores_gemma":[0.000027278275,0.00012088679,0.000047936657,0.00023567048,0.00007571115,0.000085622436,0.000071952105,0.00017749718,0.000010765345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029421432,0.00031241204,0.98518664,0.000032198088,0.0010650944,0.000027007072,0.0007685756,0.0000034293962,0.0001775949,0.000049508635,0.010372294,0.0017110271],"study_design_scores_gemma":[0.0013182799,0.00009283639,0.9919061,0.00024666588,0.0015340094,0.000008775194,0.0002587361,0.00020492298,0.0033625003,0.00008282591,0.00083280256,0.00015154625],"about_ca_topic_score_codex":0.00005197674,"about_ca_topic_score_gemma":0.00003945435,"teacher_disagreement_score":0.017791893,"about_ca_system_score_codex":0.0000045440493,"about_ca_system_score_gemma":0.0000325181,"threshold_uncertainty_score":0.49296203},"labels":[],"label_agreement":null},{"id":"W3110789430","doi":"10.1162/netn_a_00179","title":"The R1-weighted connectome: complementing brain networks with a myelin-sensitive measure","year":2021,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Montreal Neurological Institute and Hospital; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fondation EDF; Fondation Institut de Cardiologie de Montréal; Agence Nationale de la Recherche; Réseau en Bio-Imagerie du Quebec; Wellcome Trust; Canadian Open Neuroscience Platform; Wellcome","keywords":"Connectome; Tractography; White matter; Diffusion MRI; Connectomics; Myelin; Neuroscience; Human Connectome Project; Computer science; Measure (data warehouse); Biology; Magnetic resonance imaging; Functional connectivity; Data mining; Central nervous system; Medicine","score_opus":0.05441997733237597,"score_gpt":0.3290948789170651,"score_spread":0.27467490158468916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3110789430","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07784054,0.0007113298,0.8692059,0.04379448,0.00057679525,0.0015406752,0.000011350325,0.0009043363,0.005414633],"genre_scores_gemma":[0.97822505,0.00012210729,0.00907351,0.011495495,0.0003379911,0.00005521987,0.000011115067,0.000033897057,0.0006455888],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982028,0.00010138283,0.00022701443,0.00055506633,0.00036377055,0.0005499732],"domain_scores_gemma":[0.9984366,0.00045949698,0.0001279887,0.0005725696,0.000265535,0.00013775074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033926408,0.00016666952,0.00019729859,0.000020212601,0.00094836,0.0001013304,0.00019100518,0.000032148095,0.0000058281767],"category_scores_gemma":[0.00019358551,0.00011282361,0.000056631623,0.0012148392,0.00036477257,0.00007151417,0.00014041958,0.00039878226,0.0000027755648],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011087329,0.0012080289,0.1551574,0.0001276831,0.00014702947,0.0050244266,0.0006420732,0.06353366,0.2575238,0.14320262,0.21011333,0.16221121],"study_design_scores_gemma":[0.0021133167,0.00066466973,0.095014535,0.0005083947,0.00014560482,0.0025062973,0.00018290691,0.32640648,0.009686189,0.0016675366,0.56034064,0.0007634334],"about_ca_topic_score_codex":0.00000218189,"about_ca_topic_score_gemma":0.00001752205,"teacher_disagreement_score":0.90038455,"about_ca_system_score_codex":0.000026825484,"about_ca_system_score_gemma":0.00011339705,"threshold_uncertainty_score":0.7294114},"labels":[],"label_agreement":null},{"id":"W3111014536","doi":"10.1002/alz.040586","title":"Accounting for systematic spatiotemporal variation improves connectome‐based models of tau spreading in human Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Connectome; Entorhinal cortex; Context (archaeology); Human Connectome Project; Neuroscience; Tractography; Inference; Computer science; Diffusion MRI; Biology; Psychology; Artificial intelligence; Hippocampus; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.11507118169260591,"score_gpt":0.3566954503454146,"score_spread":0.2416242686528087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111014536","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18475768,0.01607939,0.77542347,0.007595496,0.0001268835,0.014741605,0.00017735644,0.0007793868,0.00031870964],"genre_scores_gemma":[0.9735504,0.0000039617926,0.025083385,0.0006273663,0.000054695913,0.000502067,0.00013490922,0.00004251595,6.913442e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99859565,0.000035561385,0.0006033004,0.000349814,0.00020454235,0.00021115514],"domain_scores_gemma":[0.99899006,0.0000979684,0.0003612793,0.00031029992,0.00011879959,0.00012158822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022003546,0.00017205214,0.0003866661,0.00011171722,0.00008051515,0.000023279443,0.00014881101,0.000043710468,0.000010941634],"category_scores_gemma":[0.00007687719,0.0001712387,0.00011299445,0.00022983956,0.000035372253,0.00022098207,0.000047204256,0.00009777222,0.0000021521398],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001290415,0.0022931525,0.036320217,0.018313302,0.01120738,0.000053582917,0.002916854,0.007758774,0.8336962,0.07567562,0.0023594494,0.00811509],"study_design_scores_gemma":[0.004336026,0.0004785904,0.011152419,0.0031101687,0.03269465,0.0000026679415,0.00012656079,0.7957896,0.14364341,0.0077701807,0.0001528916,0.00074286055],"about_ca_topic_score_codex":0.000051802625,"about_ca_topic_score_gemma":0.0000028415168,"teacher_disagreement_score":0.7887927,"about_ca_system_score_codex":0.000007892624,"about_ca_system_score_gemma":0.00006461446,"threshold_uncertainty_score":0.6982911},"labels":[],"label_agreement":null},{"id":"W3111428740","doi":"10.18060/24617","title":"Distinctive Patterns of Tau Accumulation and White-Matter Degeneration on Domain-Specific Neuropsychiatric Test Scores","year":2020,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Degeneration (medical); Domain (mathematical analysis); Neuroscience; Test (biology); Psychology; Pathology; Medicine; Biology; Magnetic resonance imaging; Mathematics; Paleontology; Radiology; Mathematical analysis","score_opus":0.05973680750076982,"score_gpt":0.31552738750129644,"score_spread":0.2557905800005266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111428740","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9902189,0.000022557779,0.004997945,0.0036502047,0.000012456962,0.00038663202,0.000023288014,0.000055969536,0.00063208194],"genre_scores_gemma":[0.9904704,0.000053426567,0.008831498,0.00048174206,0.000096850046,0.000022746715,0.000010421968,0.000020717414,0.000012171892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992928,0.000001786527,0.00023151575,0.00024179176,0.00013525995,0.0000968624],"domain_scores_gemma":[0.99947727,0.00003475313,0.00019528782,0.00006267089,0.00015866323,0.00007134365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003582756,0.00010351334,0.00016356127,0.00007514721,0.000038630515,0.000011732241,0.000054839362,0.000029240391,0.000013318009],"category_scores_gemma":[0.000042587497,0.00009211841,0.00003340055,0.00020226395,0.000041719828,0.000095112235,0.000033040356,0.00010310127,0.0000022250515],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008463435,0.000083040344,0.79838556,0.00016205265,0.0000036243919,3.1359968e-7,0.00022022454,0.0000055538326,0.19704406,0.0017452392,0.0011402817,0.0011254456],"study_design_scores_gemma":[0.0005713562,0.0006742864,0.9227373,0.00008134743,0.000032266413,0.000012447208,0.00010430457,0.00034042352,0.073939905,0.00077248696,0.0006242444,0.00010963968],"about_ca_topic_score_codex":0.0000017935427,"about_ca_topic_score_gemma":1.15947415e-7,"teacher_disagreement_score":0.12435176,"about_ca_system_score_codex":0.000011934433,"about_ca_system_score_gemma":0.000007307459,"threshold_uncertainty_score":0.37564796},"labels":[],"label_agreement":null},{"id":"W3111440933","doi":"10.1002/alz.045489","title":"Fractional anisotropy in white matter hyperintensities is linked to associative memory performance","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McMaster University; University of Ottawa; Baycrest Hospital; Thunder Bay Regional Health Sciences Centre; Health Sciences Centre; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Sunnybrook Health Science Centre; Western University","funders":"","keywords":"Fractional anisotropy; Hyperintensity; Diffusion MRI; White matter; Neuroimaging; Cognition; Dementia; Stroke (engine); Medicine; Psychology; Neuroscience; Cardiology; Pathology; Magnetic resonance imaging; Radiology; Disease","score_opus":0.06798351974009484,"score_gpt":0.3225189420411973,"score_spread":0.2545354223011025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111440933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.815612,0.001979234,0.009674699,0.16360933,0.00016455009,0.001461786,0.00009693298,0.0004189359,0.0069825347],"genre_scores_gemma":[0.94108146,0.000033342432,0.02252309,0.036081806,0.00009348468,0.00008191834,0.000026118563,0.00002295152,0.00005582876],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992002,0.000012056661,0.00019221351,0.000262259,0.0001536338,0.0001796121],"domain_scores_gemma":[0.99959165,0.00001568456,0.00005710537,0.00015675087,0.0000807917,0.00009800816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038865946,0.00011585112,0.0001678547,0.00005015263,0.000058088473,0.000012544025,0.00007698972,0.000035444875,0.00055260136],"category_scores_gemma":[0.000009828846,0.00011717771,0.000046851677,0.00018069349,0.000028333721,0.0001093013,0.000070677816,0.00019272509,0.0003789463],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029114753,0.00022185998,0.7843174,0.00002278281,0.0019891895,0.00003234038,0.0029479158,0.00006686736,0.021461416,0.00019393042,0.18041968,0.008035472],"study_design_scores_gemma":[0.0008079286,0.0002625741,0.8855419,0.000045778273,0.0016780759,0.000019121957,0.00028326255,0.001886684,0.024748474,0.00014535047,0.08425138,0.00032942602],"about_ca_topic_score_codex":0.0000103662205,"about_ca_topic_score_gemma":9.764054e-7,"teacher_disagreement_score":0.12752752,"about_ca_system_score_codex":0.000011280175,"about_ca_system_score_gemma":0.000023547096,"threshold_uncertainty_score":0.60505974},"labels":[],"label_agreement":null},{"id":"W3111443408","doi":"10.21203/rs.3.rs-115308/v2","title":"Plasma neurofilament light is associated with white matter damage in Alzheimer's disease","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Biomarker; Neurodegeneration; Diffusion MRI; Atrophy; Pathology; Internal medicine; Cognitive decline; Psychology; Medicine; Neuroscience; Disease; Magnetic resonance imaging; Dementia; Chemistry","score_opus":0.146440074814421,"score_gpt":0.42906368619181134,"score_spread":0.28262361137739034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111443408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5720734,0.0008020076,0.0008392219,0.39710897,0.000096496005,0.011271539,0.0011834875,0.0010723028,0.015552592],"genre_scores_gemma":[0.9938433,0.00019287244,0.0012167608,0.0018841145,0.00010974354,0.0011189139,0.00054935034,0.00013253027,0.00095239934],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968313,0.00021583305,0.00032825823,0.0009970613,0.0010311444,0.0005963769],"domain_scores_gemma":[0.99780715,0.00012721379,0.000111037334,0.0011326296,0.00030393165,0.00051804405],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00028001016,0.00031152467,0.00045283147,0.0003572671,0.00011189691,0.00008939006,0.00038112755,0.00014905726,0.00039632941],"category_scores_gemma":[0.00016003553,0.00026758746,0.00011926793,0.0006682123,0.00013884717,0.000056522345,0.001000226,0.0024720016,0.00016536936],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001156056,0.001463348,0.7892812,0.0011826031,0.0002658229,0.0044549485,0.00094978564,0.00018888393,0.0008823874,0.0004051359,0.19884805,0.00092177733],"study_design_scores_gemma":[0.0016287933,0.0004941564,0.9552363,0.0040497473,0.00022059288,0.00001242473,0.000106628206,0.005721733,0.0019708504,0.0029132403,0.027040385,0.0006051377],"about_ca_topic_score_codex":0.000029807452,"about_ca_topic_score_gemma":0.000011242213,"teacher_disagreement_score":0.42176992,"about_ca_system_score_codex":0.00021650048,"about_ca_system_score_gemma":0.00037746277,"threshold_uncertainty_score":0.99997765},"labels":[],"label_agreement":null},{"id":"W3111518281","doi":"10.1002/alz.039184","title":"Accumulating and heterogeneous network‐knockout profiles in amnestic mild cognitive impairment and Alzheimer’s disease dementia","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Heart and Stroke Foundation; Montreal Neurological Institute and Hospital; University of Toronto; Baycrest Hospital; Ontario Brain Institute","funders":"","keywords":"Diffusion MRI; Dementia; Neuroimaging; Neuroscience; White matter; Psychology; Alzheimer's disease; Disease; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.10004396811114852,"score_gpt":0.35210788709395857,"score_spread":0.25206391898281005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111518281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.772469,0.21412092,0.0034114535,0.0054657278,0.000067131514,0.0037760234,0.000074402196,0.0004360312,0.00017934095],"genre_scores_gemma":[0.9875433,0.00040735127,0.009600842,0.0019662187,0.00011086943,0.00024186219,0.000082023194,0.000046516216,0.0000010074549],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984833,0.00004560884,0.0003584706,0.00056763034,0.00016767702,0.0003773171],"domain_scores_gemma":[0.9992001,0.000077129764,0.00011835641,0.00018676533,0.000046975605,0.0003706614],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000832323,0.0002536728,0.00027703875,0.00005163662,0.00016756772,0.00003923068,0.00007509051,0.000043789263,0.000042127096],"category_scores_gemma":[0.000028680508,0.0002518003,0.00005222569,0.00018784718,0.00011507886,0.00011012447,0.00022121772,0.00018370086,0.000009441428],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090816425,0.0005807726,0.88171774,0.00012681034,0.008763964,0.00043221127,0.0007367856,0.0004293679,0.0017283609,0.0005684767,0.0021013774,0.10190598],"study_design_scores_gemma":[0.007882301,0.0013746578,0.82994914,0.0009011035,0.08086801,0.00016483094,0.00025777807,0.051966827,0.01580098,0.0021032046,0.006966552,0.0017646004],"about_ca_topic_score_codex":0.000018412127,"about_ca_topic_score_gemma":0.000005673587,"teacher_disagreement_score":0.21507435,"about_ca_system_score_codex":0.0000036338154,"about_ca_system_score_gemma":0.00003111628,"threshold_uncertainty_score":0.99999344},"labels":[],"label_agreement":null},{"id":"W3111638781","doi":"10.1002/alz.046324","title":"White matter disintegration along tracts measured by diffusion tensor imaging in people with MCI","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Multivariate analysis of variance; Psychology; Neuroimaging; Medicine; Nuclear medicine; Magnetic resonance imaging; Neuroscience; Radiology; Mathematics","score_opus":0.03570444177021237,"score_gpt":0.2891566206616676,"score_spread":0.2534521788914552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111638781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7746647,0.009324213,0.10039409,0.11014041,0.00007445111,0.0024829472,0.000050593935,0.00068812945,0.0021804867],"genre_scores_gemma":[0.9854568,0.000028180253,0.01032546,0.003885342,0.000035336285,0.00008393816,0.00012893886,0.00004146449,0.0000145225795],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99896175,0.00002216552,0.00023796926,0.00035829964,0.00020663992,0.0002132054],"domain_scores_gemma":[0.9994998,0.000013784792,0.0000848517,0.0002345365,0.000051991876,0.00011502605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000051218474,0.00016323813,0.00018742224,0.000049397153,0.00006532273,0.000029331146,0.000086548185,0.00002734993,0.00012108319],"category_scores_gemma":[0.000009179916,0.00013255411,0.00004020561,0.0002462905,0.000033246415,0.00017584742,0.00003428979,0.0001830676,0.000052481388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000803069,0.00013472368,0.9543075,0.0000064044348,0.00015174414,0.000014559375,0.00035612506,0.000004925046,0.025170669,0.000021727179,0.013919936,0.0058313794],"study_design_scores_gemma":[0.0015422021,0.00012935828,0.95505327,0.000093597664,0.0031109552,0.000049658192,0.00019717506,0.0022906202,0.022566156,0.00006202958,0.014545525,0.00035944124],"about_ca_topic_score_codex":0.00006896754,"about_ca_topic_score_gemma":0.00003863059,"teacher_disagreement_score":0.21079214,"about_ca_system_score_codex":0.000007686245,"about_ca_system_score_gemma":0.00002002837,"threshold_uncertainty_score":0.54054},"labels":[],"label_agreement":null},{"id":"W3111672628","doi":"10.1097/j.pain.0000000000002164","title":"Brainstem trigeminal fiber microstructural abnormalities are associated with treatment response across subtypes of trigeminal neuralgia","year":2020,"lang":"en","type":"article","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Trigeminal neuralgia; Brainstem; Medicine; Diffusion MRI; Fractional anisotropy; Neuroimaging; Lesion; Nociception; Multiple sclerosis; Population; Anesthesia; Pathology; Radiology; Internal medicine; Magnetic resonance imaging","score_opus":0.0669004528063973,"score_gpt":0.33416476945746376,"score_spread":0.2672643166510665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111672628","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99343324,0.00010441894,0.0009845895,0.004545765,0.000008023476,0.00042567,0.00024993398,0.0001869028,0.000061465755],"genre_scores_gemma":[0.9950184,0.0000120596105,0.0023421838,0.00078776217,0.00004229122,0.00004412587,0.00008915214,0.00002692608,0.0016370771],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888396,0.00023213068,0.00024404537,0.00024982807,0.00015083667,0.00023916714],"domain_scores_gemma":[0.9988869,0.0005051802,0.00019116954,0.00020904787,0.00009098665,0.00011675068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004037626,0.00017262428,0.00032977937,0.00002831872,0.00008965964,0.0000135569,0.00008241944,0.00005006141,0.000042020332],"category_scores_gemma":[0.00046665623,0.00012584616,0.00008690992,0.00022924629,0.00014213158,0.00004831816,0.000024132643,0.0001257871,0.00000570987],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.057892565,0.0013871127,0.42956755,0.0010599293,0.00083106797,0.0016913624,0.020629916,0.00012085959,0.35386288,0.00064136414,0.023662211,0.10865319],"study_design_scores_gemma":[0.011532636,0.0107222665,0.5338135,0.0011206853,0.0005556761,0.0005209826,0.005406353,0.0034104157,0.3264998,0.00032635423,0.104854316,0.0012370333],"about_ca_topic_score_codex":0.000014029246,"about_ca_topic_score_gemma":0.0000046852474,"teacher_disagreement_score":0.10741615,"about_ca_system_score_codex":0.00008269493,"about_ca_system_score_gemma":0.000059147074,"threshold_uncertainty_score":0.51318574},"labels":[],"label_agreement":null},{"id":"W3111682232","doi":"10.1002/alz.046670","title":"Tau deposition assessed by [<sup>18</sup>F]MK6240 PET is associated with longitudinal decrease in grey matter density across the spectrum of Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre","funders":"","keywords":"Voxel; Grey matter; Voxel-based morphometry; Nuclear medicine; Atrophy; Standardized uptake value; Alzheimer's Disease Neuroimaging Initiative; Temporal lobe; Medicine; Positron emission tomography; Psychology; Internal medicine; Alzheimer's disease; Pathology; White matter; Magnetic resonance imaging; Neuroscience; Radiology; Disease","score_opus":0.05190336960134045,"score_gpt":0.3251726335937415,"score_spread":0.27326926399240103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111682232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9679452,0.0038130179,0.005197529,0.02106382,0.000017498816,0.001367272,0.00028199714,0.00018326317,0.00013041121],"genre_scores_gemma":[0.99308157,0.000042140593,0.0015271235,0.004794576,0.00003960373,0.000119928154,0.00033624683,0.00005308305,0.0000057337566],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982,0.00008008571,0.0004121479,0.00053187367,0.00036721933,0.00040867415],"domain_scores_gemma":[0.9987469,0.00006441694,0.00024407441,0.0005077647,0.00011616993,0.00032069304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014344712,0.0002745729,0.00035981252,0.00003974414,0.00017513758,0.00004354336,0.00021314905,0.00004707503,0.0003133405],"category_scores_gemma":[0.000045583907,0.00021550203,0.00011780715,0.00043606843,0.0001870333,0.00018568867,0.00012834232,0.000305118,0.00003530373],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066975376,0.0011671432,0.93687844,0.000021044221,0.004399525,0.0003842781,0.00043455494,0.000075125536,0.0072007384,0.00009606043,0.047664046,0.0010093171],"study_design_scores_gemma":[0.0028537284,0.00036303673,0.8655357,0.00019099792,0.019825604,0.000087028464,0.00013136554,0.005375397,0.10348444,0.00035709143,0.0011901861,0.0006054709],"about_ca_topic_score_codex":0.00021530894,"about_ca_topic_score_gemma":0.00003309506,"teacher_disagreement_score":0.0962837,"about_ca_system_score_codex":0.000014593939,"about_ca_system_score_gemma":0.00008558114,"threshold_uncertainty_score":0.8787918},"labels":[],"label_agreement":null},{"id":"W3111845248","doi":"10.1016/j.neuroimage.2020.117619","title":"A simple estimate of axon size with diffusion MRI","year":2020,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Canada Excellence Research Chairs, Government of Canada","keywords":"Axon; White matter; Diffusion MRI; Diffusion; Spherical mean; Myelin; Nuclear magnetic resonance; Neuroscience; Physics; Mathematics; Magnetic resonance imaging; Biology; Central nervous system; Mathematical analysis; Medicine","score_opus":0.050465161706964676,"score_gpt":0.3405098164690698,"score_spread":0.2900446547621051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111845248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8563881,0.000024578618,0.12246873,0.014447511,0.00001374921,0.0008661951,0.000043486965,0.00067765295,0.0050700186],"genre_scores_gemma":[0.95082974,0.000022502192,0.046514645,0.0024585808,0.000035759975,0.000020271731,0.000009002738,0.000034171455,0.00007530594],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99928176,0.000008088603,0.00015327643,0.00026995814,0.00015297139,0.0001339613],"domain_scores_gemma":[0.9993837,0.00006405402,0.00007789099,0.0003053298,0.000050087325,0.0001189774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002005337,0.000108190725,0.00019015482,0.000019755014,0.000038430175,0.000006356288,0.00008539842,0.00002035512,0.000050158502],"category_scores_gemma":[0.00010513264,0.000085276646,0.000043517975,0.00021104937,0.000074420415,0.00004962898,0.00006240835,0.00015546648,0.000009213402],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020263,0.00016213409,0.010276673,0.000109788816,0.0000051069565,0.00006869169,0.000062907246,0.000031480668,0.98494095,0.00040218377,0.0023388641,0.001398606],"study_design_scores_gemma":[0.0064899134,0.004648413,0.36739177,0.00024471985,0.00034679848,0.00044882527,0.00006755423,0.030747112,0.4206149,0.0013196699,0.16697063,0.0007097374],"about_ca_topic_score_codex":0.0000056712797,"about_ca_topic_score_gemma":3.3262782e-7,"teacher_disagreement_score":0.56432605,"about_ca_system_score_codex":0.0000057939687,"about_ca_system_score_gemma":0.000020592572,"threshold_uncertainty_score":0.34774807},"labels":[],"label_agreement":null},{"id":"W3111905944","doi":"10.1002/alz.047386","title":"Longitudinal assessment of neuroinflammation and axonal loss in white matter tracts in Alzheimer’s disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Inferior longitudinal fasciculus; Splenium; White matter; Cingulum (brain); Corpus callosum; Uncinate fasciculus; Psychology; Fasciculus; Neuroinflammation; Fractional anisotropy; Internal medicine; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Disease; Radiology","score_opus":0.07919082554819575,"score_gpt":0.3548226206176054,"score_spread":0.27563179506940966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111905944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.971492,0.005247287,0.0026192947,0.018848946,0.000029703027,0.0010094946,0.000023930124,0.00006645989,0.0006628929],"genre_scores_gemma":[0.99078965,0.00007281092,0.008331405,0.00065409474,0.000028537537,0.00006158113,0.000041584743,0.000019353622,9.59279e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897003,0.000028542676,0.0003534642,0.00031087056,0.00017122354,0.00016588923],"domain_scores_gemma":[0.99951535,0.000023231352,0.00010497301,0.0001865284,0.000030203997,0.00013971693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007380414,0.00012870002,0.00019993828,0.00008960496,0.00002134536,0.000010696795,0.00007066783,0.000026392927,0.00010286557],"category_scores_gemma":[0.000008381086,0.00013136618,0.0000385338,0.00020254421,0.00006093638,0.00014824679,0.00006713112,0.00017065425,0.000008363499],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006321281,0.00013569692,0.99326754,0.00001532577,0.00015837782,0.000067108995,0.000051496812,0.000055981614,0.002434109,0.0003261981,0.00034911843,0.0030758642],"study_design_scores_gemma":[0.00064292265,0.000059478698,0.99242014,0.000038154663,0.0015503124,0.000009365063,0.0000069512,0.002460176,0.0018510727,0.00018616878,0.00066943426,0.00010580749],"about_ca_topic_score_codex":0.000010692373,"about_ca_topic_score_gemma":0.000005869762,"teacher_disagreement_score":0.019297682,"about_ca_system_score_codex":0.00000388108,"about_ca_system_score_gemma":0.00004287635,"threshold_uncertainty_score":0.53569573},"labels":[],"label_agreement":null},{"id":"W3111920673","doi":"10.1002/alz.043961","title":"Pilot study of MRI white matter tissue properties in Alzheimer’s, vascular and mixed dementias","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Northern British Columbia; Simon Fraser University; Vancouver Coastal Health Research Institute; University of British Columbia","funders":"","keywords":"Hyperintensity; White matter; Fractional anisotropy; Diffusion MRI; Medicine; Dementia; Vascular dementia; Atrophy; Nuclear medicine; Cardiology; Internal medicine; Pathology; Magnetic resonance imaging; Radiology; Disease","score_opus":0.11386046946623982,"score_gpt":0.3237406453365572,"score_spread":0.2098801758703174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111920673","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93181497,0.05510293,0.0016415819,0.0072351773,0.000060704027,0.0033993588,0.000010289293,0.00020500306,0.0005300077],"genre_scores_gemma":[0.99240637,0.00012403839,0.0062964447,0.00091524166,0.0000324491,0.00016993003,0.000012524248,0.00003947248,0.000003538506],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987052,0.000051220894,0.00040348773,0.000413547,0.00021439303,0.00021211775],"domain_scores_gemma":[0.9993707,0.0000111321315,0.000103706174,0.0003558409,0.00005084957,0.00010779224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093861054,0.00018627908,0.0003167527,0.00007654187,0.00005397563,0.000015673682,0.00013134484,0.000020675443,0.00013336352],"category_scores_gemma":[0.0000072616567,0.00016721072,0.000030852185,0.00022484236,0.00007217717,0.000106900334,0.00017234747,0.0001533356,0.000030802006],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044366554,0.005053973,0.83054394,0.00010795029,0.015680319,0.00007562759,0.003012253,0.00006739515,0.10286852,0.00014016221,0.017285902,0.024720306],"study_design_scores_gemma":[0.008638395,0.008970735,0.6179827,0.00021331145,0.051270798,0.000038059607,0.0015117839,0.00075696065,0.2729532,0.00019651772,0.03638563,0.0010819237],"about_ca_topic_score_codex":0.00012949712,"about_ca_topic_score_gemma":0.00003321153,"teacher_disagreement_score":0.21256125,"about_ca_system_score_codex":0.0000019983224,"about_ca_system_score_gemma":0.00001635006,"threshold_uncertainty_score":0.6818655},"labels":[],"label_agreement":null},{"id":"W3112025802","doi":"10.1002/alz.041245","title":"Alterations of cortical thickness and gray‐white matter contrast in Alzheimer’s disease and Lewy body‐related cognitive impairment","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"White matter; Gray (unit); Psychology; Grey matter; Temporal lobe; Pathology; Neuroscience; Magnetic resonance imaging; Medicine; Epilepsy; Nuclear medicine; Radiology","score_opus":0.039967246285615064,"score_gpt":0.32078841250019363,"score_spread":0.2808211662145786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112025802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92614186,0.03133093,0.0076957243,0.030606247,0.000054964552,0.0031399664,0.00022449151,0.0001988562,0.0006069658],"genre_scores_gemma":[0.9957699,0.00014297938,0.0016663178,0.0021830508,0.000018811064,0.000110661356,0.000083392326,0.000022635455,0.000002210103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897015,0.00004320856,0.00034614294,0.00033282192,0.00012543876,0.00018221268],"domain_scores_gemma":[0.9994086,0.000060312956,0.00008385053,0.00013827985,0.00006413866,0.00024484028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006402411,0.00015179548,0.00023950801,0.000054220014,0.000069766735,0.0000170128,0.00004475932,0.000039229726,0.00013314145],"category_scores_gemma":[0.000018987006,0.00014255557,0.00003915082,0.00014609075,0.00020350602,0.00009889186,0.00008031234,0.00019467848,0.000012564345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000591024,0.0007528367,0.97143847,0.000051542647,0.004302956,0.0001116453,0.0011928137,0.0000064634883,0.011957244,0.0029064987,0.0022477992,0.004440687],"study_design_scores_gemma":[0.002606652,0.00030010685,0.9701489,0.00013196554,0.016723225,0.000042897092,0.00014902036,0.0028185807,0.0057125953,0.00064017106,0.0004481648,0.00027772845],"about_ca_topic_score_codex":0.000011726222,"about_ca_topic_score_gemma":0.0000021593264,"teacher_disagreement_score":0.06962808,"about_ca_system_score_codex":0.0000019632382,"about_ca_system_score_gemma":0.000031981563,"threshold_uncertainty_score":0.5813247},"labels":[],"label_agreement":null},{"id":"W3112093090","doi":"10.1002/alz.044897","title":"Intrinsic connectivity of the human brain provides scaffold for tau aggregation in clinical variants of Alzheimer's disease","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill Genome Centre; Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Voxel; Tractography; Neuroscience; Population; Psychology; Clinical Dementia Rating; Diffusion MRI; Alzheimer's disease; Medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.11289535342124848,"score_gpt":0.38447076426931176,"score_spread":0.27157541084806325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112093090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95746034,0.008142086,0.005324667,0.024339268,0.00010201798,0.0042697033,0.00011282456,0.00012017009,0.00012894698],"genre_scores_gemma":[0.99487644,0.000018949524,0.0038191325,0.0010491671,0.00006484916,0.00012351549,0.000025757212,0.00002092438,0.0000012412969],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879324,0.000075891025,0.00055210886,0.00029533196,0.0001455283,0.00013791778],"domain_scores_gemma":[0.99895066,0.0001537083,0.0003209092,0.00037631087,0.00010057964,0.00009784475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026915118,0.000111332025,0.00028030266,0.000039086168,0.000055263085,0.000004898549,0.0001571067,0.000042665986,0.000014234213],"category_scores_gemma":[0.00032408538,0.00009077314,0.00015943317,0.00023347438,0.00015518614,0.000081020655,0.00010332108,0.000118257005,0.0000012629208],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007655078,0.002267093,0.61458373,0.00018449561,0.0045932746,0.0000106537,0.00037230528,0.000035574696,0.08206554,0.032225475,0.012444569,0.2504518],"study_design_scores_gemma":[0.0022700012,0.00038713543,0.8874615,0.00016236429,0.008523733,0.0000017613883,0.000024214001,0.0011820477,0.09085986,0.0051906356,0.0037491994,0.00018755792],"about_ca_topic_score_codex":0.000027911256,"about_ca_topic_score_gemma":0.0000083193145,"teacher_disagreement_score":0.27287778,"about_ca_system_score_codex":0.0000029020468,"about_ca_system_score_gemma":0.0000832099,"threshold_uncertainty_score":0.3701621},"labels":[],"label_agreement":null},{"id":"W3112400091","doi":"10.1002/mrm.28620","title":"Apparent propagator anisotropy from single‐shell diffusion MRI acquisitions","year":2020,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; Ministerio de Ciencia e Innovación; Wellcome Trust","keywords":"Fractional anisotropy; Propagator; Anisotropy; Diffusion MRI; Metric (unit); White matter; Diffusion; Computer science; Computation; Physics; Nuclear magnetic resonance; Algorithm; Magnetic resonance imaging; Medicine; Quantum mechanics; Radiology","score_opus":0.06999343753765516,"score_gpt":0.32322286937153166,"score_spread":0.2532294318338765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112400091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5912847,0.030540625,0.07462291,0.28483805,0.00030388712,0.004331179,0.00012184834,0.0012581599,0.012698687],"genre_scores_gemma":[0.9195714,0.0025707276,0.05991387,0.015712442,0.0010007921,0.00030312556,0.00015356884,0.0000754391,0.00069864286],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99829984,0.000034280736,0.00045419153,0.0005549043,0.0003688644,0.0002879012],"domain_scores_gemma":[0.999036,0.00009045367,0.000085662934,0.00046502918,0.0000664052,0.0002564303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006659042,0.0002128647,0.0004226054,0.00007729335,0.000064667634,0.000008785442,0.00018824254,0.00006883263,0.0009099138],"category_scores_gemma":[0.00020345907,0.00017197513,0.00004846023,0.0005157227,0.00023642309,0.000047016747,0.00008984196,0.00032605274,0.000046401987],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006475137,0.0010393695,0.050186,0.0001610494,0.00000818903,0.00058425526,0.0016281209,0.000017193504,0.66537577,0.0015191014,0.06679822,0.21203524],"study_design_scores_gemma":[0.0055194693,0.0034880498,0.13456266,0.0013383246,0.000124246,0.000056787572,0.00039498464,0.010983043,0.009152182,0.005061306,0.8288546,0.00046432565],"about_ca_topic_score_codex":0.00008117261,"about_ca_topic_score_gemma":0.0000051172997,"teacher_disagreement_score":0.7620564,"about_ca_system_score_codex":0.00006981021,"about_ca_system_score_gemma":0.00003530915,"threshold_uncertainty_score":0.9962918},"labels":[],"label_agreement":null},{"id":"W3112713264","doi":"10.21203/rs.3.rs-115308/v1","title":"Plasma neurofilament light and cerebrospinal fluid biomarkers are associated with white matter damage in Alzheimer's disease","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Cerebrospinal fluid; Biomarker; Diffusion MRI; Neurodegeneration; Pathology; Apolipoprotein E; Fractional anisotropy; Internal medicine; Cognitive decline; Medicine; Psychology; Disease; Neuroscience; Magnetic resonance imaging; Dementia; Chemistry","score_opus":0.10977057880377683,"score_gpt":0.39961585327443805,"score_spread":0.2898452744706612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112713264","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88872486,0.00086161424,0.0002714176,0.102324165,0.00004375781,0.005000167,0.00046508908,0.00040575967,0.0019031842],"genre_scores_gemma":[0.9967095,0.00026865932,0.0011083444,0.00052617985,0.00007023394,0.0007148001,0.0003396563,0.000103289836,0.00015931396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970504,0.00023367495,0.00031527926,0.0010275262,0.0008106013,0.00056253787],"domain_scores_gemma":[0.9981183,0.000113757465,0.00013462773,0.00081128225,0.0002508885,0.0005711491],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029418338,0.0003313223,0.0004539392,0.0003744678,0.00014596707,0.00011201093,0.00026614932,0.00014704715,0.00009823789],"category_scores_gemma":[0.00018706359,0.0002870391,0.000083886946,0.00057285634,0.00019274771,0.00006454225,0.0009597065,0.0016352369,0.00002932536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010426264,0.00044614883,0.9725414,0.00084428076,0.00017193412,0.00147127,0.0001582876,0.000038735077,0.0011669728,0.000097056996,0.021634093,0.00038717527],"study_design_scores_gemma":[0.000979042,0.00030869365,0.98921233,0.0028029862,0.00011874699,0.000011009793,0.000108654574,0.0026073116,0.00050149456,0.00056530256,0.0024837991,0.00030061696],"about_ca_topic_score_codex":0.000031785872,"about_ca_topic_score_gemma":0.00002046659,"teacher_disagreement_score":0.10798468,"about_ca_system_score_codex":0.00018351692,"about_ca_system_score_gemma":0.00025007082,"threshold_uncertainty_score":0.99995816},"labels":[],"label_agreement":null},{"id":"W3112764738","doi":"10.1002/alz.040838","title":"Apathy and white matter integrity in amnestic mild cognitive impairment: A whole brain analysis with tract‐based spatial statistics","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; Mental Health Research Canada; University of Ottawa","funders":"","keywords":"Apathy; Fractional anisotropy; Diffusion MRI; White matter; Psychology; Cingulum (brain); Superior longitudinal fasciculus; Corpus callosum; Alzheimer's disease; Geriatric Depression Scale; Audiology; Medicine; Psychiatry; Internal medicine; Cognition; Magnetic resonance imaging; Disease; Neuroscience; Depressive symptoms; Radiology","score_opus":0.049397566919885484,"score_gpt":0.3266559427858993,"score_spread":0.2772583758660138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112764738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27297175,0.0012931055,0.69699305,0.026430491,0.000013991951,0.0014196652,0.0005668394,0.00016712025,0.00014396552],"genre_scores_gemma":[0.95703036,0.0000055737373,0.036362752,0.0061354833,0.000022046714,0.00009592696,0.00031882589,0.000024615323,0.0000044100416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897283,0.000041507858,0.00024039854,0.00038324605,0.00016163438,0.00020035876],"domain_scores_gemma":[0.99943525,0.00008993022,0.00009521664,0.00016506444,0.000066820256,0.00014773798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007041552,0.00017139503,0.00028125828,0.00012326651,0.00005070557,0.000025803865,0.00005885755,0.000038992846,0.00016400733],"category_scores_gemma":[0.000019626725,0.00015050978,0.000044096687,0.00047339904,0.00010214168,0.00006586328,0.000036147758,0.00027461207,0.000023329572],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030749463,0.00041668213,0.9881073,0.000028045808,0.0024602218,0.00010451803,0.00045169325,0.00003241928,0.00040965082,0.000031101357,0.0026139724,0.005036885],"study_design_scores_gemma":[0.002381129,0.00063009013,0.9452383,0.0000733767,0.027786309,0.000013113123,0.00013904442,0.020780724,0.0016041937,0.00012717488,0.0009237655,0.00030276823],"about_ca_topic_score_codex":0.00011108508,"about_ca_topic_score_gemma":0.00008263453,"teacher_disagreement_score":0.6840586,"about_ca_system_score_codex":0.0000051695547,"about_ca_system_score_gemma":0.000040487845,"threshold_uncertainty_score":0.613761},"labels":[],"label_agreement":null},{"id":"W3112901064","doi":"10.1093/neuonc/noaa222.673","title":"QOL-09. WHOLE-BRAIN WHITE MATTER NETWORK CONNECTIVITY IS DISRUPTED BY PEDIATRIC BRAIN TUMOR TREATMENT","year":2020,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"White matter; Magnetic resonance imaging; Medicine; Psychology; Neuroscience; Nuclear medicine; Audiology; Radiology","score_opus":0.04164659635995809,"score_gpt":0.3417017554282418,"score_spread":0.3000551590682837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3112901064","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26578695,0.00016952986,0.010421563,0.7182804,0.00017601745,0.0015917604,0.0001963718,0.00067132176,0.0027061452],"genre_scores_gemma":[0.6742212,0.00009495539,0.005688757,0.3164664,0.0016199778,0.000572025,0.00016168496,0.00014874432,0.0010262564],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99807596,0.00017381879,0.00036120004,0.0007477869,0.00015304348,0.00048820456],"domain_scores_gemma":[0.9982848,0.0006545725,0.0001970988,0.00046744902,0.00005018968,0.00034585863],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008800235,0.00030338648,0.00057050353,0.00005552332,0.00014296113,0.000017813501,0.0001634631,0.000118088676,0.0002944511],"category_scores_gemma":[0.00014669307,0.0002735625,0.0001478824,0.00047758897,0.00010128941,0.000070973394,0.00011790905,0.0004190338,0.00029533287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019206443,0.00036465982,0.087628,0.000028371147,0.000017892977,0.00023398451,0.00022896857,0.000020665108,0.058080606,0.00006557679,0.84929806,0.003841163],"study_design_scores_gemma":[0.0020645317,0.0024145665,0.010650282,0.0000059093513,0.00013975966,0.00022190892,0.000023503804,0.00071287097,0.003178028,0.00027957608,0.9800674,0.0002417201],"about_ca_topic_score_codex":0.000011788787,"about_ca_topic_score_gemma":0.0000034724321,"teacher_disagreement_score":0.40843427,"about_ca_system_score_codex":0.0001733012,"about_ca_system_score_gemma":0.00012456742,"threshold_uncertainty_score":0.9999716},"labels":[],"label_agreement":null},{"id":"W3113026871","doi":"10.1002/alz.041213","title":"Associations between amyloid‐β, white matter disease, functional brain networks, and mobility function: Possible indicators of reserve and resilience","year":2020,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Pittsburgh compound B; Hyperintensity; Digit symbol substitution test; White matter; Cognitive reserve; Cognition; Psychology; Physical medicine and rehabilitation; Dementia; Cardiology; Medicine; Internal medicine; Magnetic resonance imaging; Neuroscience; Cognitive impairment; Disease; Pathology; Radiology","score_opus":0.04768940530050129,"score_gpt":0.308054198797472,"score_spread":0.26036479349697067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113026871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8249075,0.025670873,0.072572075,0.0728228,0.00010244297,0.0019450941,0.0005295466,0.00038200952,0.0010676916],"genre_scores_gemma":[0.9958061,0.000044537108,0.0019643202,0.001837734,0.000099897356,0.000038646976,0.00017205403,0.000015806618,0.000020886018],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989919,0.000037586404,0.00028006418,0.00035503242,0.00018168183,0.0001537552],"domain_scores_gemma":[0.99925566,0.00008721542,0.00014246134,0.00022993993,0.000058982685,0.00022574086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001302094,0.000113958085,0.00019138289,0.00005572957,0.0001419216,0.000018279356,0.00006266369,0.00004446037,0.00012619118],"category_scores_gemma":[0.000039748666,0.00011197964,0.000042919204,0.00033399177,0.00015659089,0.00013397647,0.000117463125,0.00015946027,0.000005638429],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048554823,0.000044833512,0.98399824,0.000008955597,0.00046944275,7.944948e-7,0.00002355503,0.000023500505,0.00013449288,0.00023017416,0.013654692,0.0013627579],"study_design_scores_gemma":[0.00028514603,0.00008282179,0.99316174,0.000012770708,0.002402353,9.1766395e-7,0.000011572694,0.0002624136,0.00025349416,0.0004718219,0.0029627953,0.00009213984],"about_ca_topic_score_codex":0.000010655743,"about_ca_topic_score_gemma":0.0000018649064,"teacher_disagreement_score":0.17089865,"about_ca_system_score_codex":0.0000041996514,"about_ca_system_score_gemma":0.000034438784,"threshold_uncertainty_score":0.45663974},"labels":[],"label_agreement":null},{"id":"W3113161003","doi":"10.1016/j.pscychresns.2020.111234","title":"White matter microstructure across brain-based biotypes for psychosis – findings from the bipolar-schizophrenia network for intermediate phenotypes","year":2020,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Royal Ottawa Mental Health Centre","funders":"National Institute of Mental Health","keywords":"Schizoaffective disorder; Fornix; Bipolar disorder; Fractional anisotropy; White matter; Corpus callosum; Psychosis; Schizophrenia (object-oriented programming); Proband; Medicine; Bipolar I disorder; Internal medicine; Psychology; Psychiatry; Biology; Pathology; Mania; Magnetic resonance imaging; Hippocampus; Genetics; Cognition","score_opus":0.08299371878723376,"score_gpt":0.40371902954084254,"score_spread":0.32072531075360877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113161003","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27882627,0.0016579141,0.07006454,0.6424534,0.00074902846,0.004216368,0.0015040614,0.0004703607,0.00005811754],"genre_scores_gemma":[0.71004635,0.0000891274,0.17857891,0.10443927,0.0045953756,0.0012106731,0.00051726744,0.0003412125,0.00018183004],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99710035,0.00010806657,0.00041573236,0.0009924172,0.00037263896,0.0010107855],"domain_scores_gemma":[0.99744916,0.0010877372,0.000119009266,0.0007839404,0.0002725474,0.00028759136],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00048246342,0.00032388995,0.00036481244,0.000072555056,0.00095461606,0.00024802305,0.0007063696,0.00009377612,0.00006531449],"category_scores_gemma":[0.0003610516,0.0002511731,0.00028892673,0.0007330649,0.00035802246,0.00011555442,0.00018143386,0.00097428984,0.000038652903],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018889803,0.000072543226,0.49002078,0.0002327865,0.000052422056,0.0000022110366,0.00035786326,0.000058342837,0.010831723,0.00030678354,0.49265862,0.0035169425],"study_design_scores_gemma":[0.0050015035,0.00070582586,0.4771742,0.00041235774,0.00014282703,0.00001768315,0.00022302434,0.013714079,0.0019324316,0.017152889,0.48287785,0.00064532075],"about_ca_topic_score_codex":0.00002232238,"about_ca_topic_score_gemma":0.000017376007,"teacher_disagreement_score":0.53801405,"about_ca_system_score_codex":0.000033575336,"about_ca_system_score_gemma":0.00012738156,"threshold_uncertainty_score":0.99999404},"labels":[],"label_agreement":null},{"id":"W3113293558","doi":"10.1186/s41983-020-00232-w","title":"Association between microstructural white matter abnormalities and cognitive functioning in patients with type 2 diabetes mellitus: a diffusion tensor imaging study","year":2020,"lang":"en","type":"article","venue":"The Egyptian Journal of Neurology Psychiatry and Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Cognition; Medicine; Internal medicine; Type 2 Diabetes Mellitus; Type 2 diabetes; Diabetes mellitus; Audiology; Cognitive impairment; Psychology; Psychiatry; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.015475455242107337,"score_gpt":0.25217148923505595,"score_spread":0.2366960339929486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113293558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778004,0.00019721269,0.000028532188,0.021533186,0.00015304529,0.0002544847,0.0000069670245,0.000016770728,0.000009345149],"genre_scores_gemma":[0.99163485,0.00004369668,0.00007757144,0.008055349,0.00015329145,0.0000029926825,0.0000033313984,0.000019183415,0.000009746298],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989809,0.00017570955,0.00033809594,0.00019370644,0.00013430264,0.00017727676],"domain_scores_gemma":[0.9991514,0.00023437351,0.00034492207,0.00007998275,0.00010510149,0.00008421288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017398255,0.00013616157,0.00029247164,0.000096394375,0.00012988911,0.000029694133,0.00005125719,0.00003204762,0.00000861436],"category_scores_gemma":[0.0000638756,0.00009044629,0.000035031666,0.00017790389,0.00009030699,0.00014296129,0.000041991625,0.00053023885,7.9517855e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008397074,0.00006907088,0.9981013,0.0000191698,0.00003792399,0.000011244447,0.00026238183,0.0000019443037,0.00006114031,7.8364604e-7,0.00023005942,0.00036525266],"study_design_scores_gemma":[0.0013141026,0.0012619682,0.99671394,0.000045803186,0.00021781535,0.00005877815,0.00012574183,0.000020320578,0.00000985067,0.000062588566,0.000092499016,0.000076570606],"about_ca_topic_score_codex":6.6752364e-7,"about_ca_topic_score_gemma":3.8904224e-7,"teacher_disagreement_score":0.0138343815,"about_ca_system_score_codex":0.0000047952544,"about_ca_system_score_gemma":0.000018521276,"threshold_uncertainty_score":0.36882925},"labels":[],"label_agreement":null},{"id":"W3114615555","doi":"10.1007/s00429-020-02181-9","title":"Diffusion properties of the fornix assessed by deterministic tractography shows age, sex, volume, cognitive, hemispheric, and twin relationships in young adults from the Human Connectome Project","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke; University of Alberta","funders":"Canadian Institutes of Health Research; Alberta Innovates; Canada Excellence Research Chairs, Government of Canada; Fondation Brain Canada","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Psychology; Hippocampus; Tractography; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.04028816794297815,"score_gpt":0.28474210046871945,"score_spread":0.2444539325257413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114615555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99713206,0.00033121786,0.0012374229,0.00046250905,0.00002786664,0.0005838613,0.00008393788,0.000032873664,0.00010826569],"genre_scores_gemma":[0.99901557,0.000036093763,0.0002308003,0.00031831008,0.00003669871,0.000048778697,0.0001173946,0.000013291806,0.00018307305],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99929214,0.0000877505,0.00018059598,0.00024377948,0.000106682346,0.000089073495],"domain_scores_gemma":[0.9994967,0.00016081163,0.00009357209,0.0001722178,0.000054518856,0.000022210366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006125611,0.00010975374,0.00015226332,0.000023134475,0.00020910798,0.000025117914,0.000037153975,0.000072005656,0.00001083542],"category_scores_gemma":[0.0001976793,0.00006592606,0.000034382578,0.00023106884,0.00013601637,0.000057755053,0.000036411493,0.00027325383,4.8433137e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013302975,0.00006491412,0.5225608,0.00007905667,0.000019632269,0.0000034323828,0.0008102153,5.6900706e-7,0.4693456,0.000068019464,0.00062511204,0.0062896074],"study_design_scores_gemma":[0.0010302104,0.0000837152,0.9810824,0.0002658424,0.00009448594,0.000041481435,0.0011549735,0.00032010145,0.013187019,0.0014184214,0.0012181592,0.000103215396],"about_ca_topic_score_codex":0.00011449843,"about_ca_topic_score_gemma":0.00026377488,"teacher_disagreement_score":0.45852157,"about_ca_system_score_codex":0.000008098223,"about_ca_system_score_gemma":0.000023513052,"threshold_uncertainty_score":0.26883867},"labels":[],"label_agreement":null},{"id":"W3116014849","doi":"10.3171/2020.7.jns201287","title":"Deciphering the frontostriatal circuitry through the fiber dissection technique: direct structural evidence on the morphology and axonal connectivity of the fronto-caudate tract","year":2021,"lang":"en","type":"article","venue":"Journal of neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Anatomy; Neuroscience; Diffusion MRI; Medicine; Caudate nucleus; Fiber tract; Arcuate fasciculus; Biology; Tractography; Magnetic resonance imaging","score_opus":0.1053400262046791,"score_gpt":0.34775164194616287,"score_spread":0.2424116157414838,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116014849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9861492,0.0007187844,0.0016825638,0.0105809495,0.00032274853,0.0003388982,0.000014494955,0.00002222358,0.00017012228],"genre_scores_gemma":[0.99806744,0.00050093693,0.00018564194,0.00096269895,0.00018000574,0.0000219897,5.7966975e-7,0.00001726099,0.00006346682],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99874115,0.00028142563,0.00038329037,0.00016477099,0.0002824591,0.00014691816],"domain_scores_gemma":[0.9967684,0.0021978018,0.00040397164,0.00047637487,0.00012073668,0.00003267034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045837028,0.00013463959,0.000265916,0.00002312972,0.0002686232,0.000031786534,0.00020935568,0.000047974114,0.000036758975],"category_scores_gemma":[0.0009772363,0.000056234494,0.00020728988,0.00023727976,0.00026851174,0.00016556222,0.00007969675,0.00071783666,3.2559308e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005844988,0.00022132637,0.042033866,0.00007527984,0.0001487249,0.0003388813,0.0004628087,0.00039439948,0.92934716,0.00043090133,0.009894937,0.016067196],"study_design_scores_gemma":[0.0004074781,0.00029698235,0.7036012,0.00064682186,0.00027442668,0.01806451,0.00020657618,0.00028408767,0.26047036,0.0036711066,0.011880251,0.00019622323],"about_ca_topic_score_codex":0.000010358719,"about_ca_topic_score_gemma":0.0000029133241,"teacher_disagreement_score":0.6688768,"about_ca_system_score_codex":0.000036354348,"about_ca_system_score_gemma":0.00008151291,"threshold_uncertainty_score":0.3118683},"labels":[],"label_agreement":null},{"id":"W3116037206","doi":"10.1073/pnas.2012533117","title":"Axon morphology is modulated by the local environment and impacts the noninvasive investigation of its structure–function relationship","year":2020,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Vetenskapsrådet; European Synchrotron Radiation Facility","keywords":"Axon; White matter; Soma; Corpus callosum; Magnetic resonance imaging; Diffusion MRI; Biophysics; Nuclear magnetic resonance; Neuroscience; Anatomy; Biology; Physics; Medicine","score_opus":0.09483896768030663,"score_gpt":0.3204994083299202,"score_spread":0.22566044064961355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116037206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9355932,0.00014683547,0.00019559606,0.06355882,0.000003182606,0.0003485312,0.000024367793,0.000009491789,0.00011996537],"genre_scores_gemma":[0.99658936,0.000058502817,0.0007898481,0.0025130361,0.000020249072,0.000009347477,7.2689545e-7,0.0000032011276,0.000015698088],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9991179,0.000007687244,0.00020810419,0.00015953074,0.0004398849,0.000066904315],"domain_scores_gemma":[0.9993981,0.00012355403,0.00033857478,0.0000120227305,0.000096301585,0.000031420303],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026378033,0.00006240834,0.000090387744,0.000031761705,0.00016660137,0.0000055570995,0.00020284092,0.000050344996,0.0000074383083],"category_scores_gemma":[0.00027636168,0.00003165084,0.000027550348,0.0003679388,0.0010672497,0.00013564553,0.000068860165,0.00017935889,3.0309164e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020531936,0.000007762025,0.015413445,0.000032396514,0.0000089850055,2.55605e-9,0.00033953137,0.00017032132,0.96768934,0.014616833,0.0014690483,0.00023180553],"study_design_scores_gemma":[0.0001401703,0.00010570095,0.20505436,0.00003286965,0.0000386588,0.000017856832,0.00013421969,0.0055862344,0.74502677,0.043649416,0.000176856,0.00003688601],"about_ca_topic_score_codex":0.0000024246256,"about_ca_topic_score_gemma":8.43923e-9,"teacher_disagreement_score":0.22266255,"about_ca_system_score_codex":0.000017466582,"about_ca_system_score_gemma":0.000018409355,"threshold_uncertainty_score":0.3932326},"labels":[],"label_agreement":null},{"id":"W3117135956","doi":"10.1101/2020.12.17.423333","title":"Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; London Health Sciences Centre; Western University","funders":"","keywords":"Fiducial marker; Artificial intelligence; Computer science; Image registration; Preprocessor; Neuroimaging; Workflow; Magnetic resonance imaging; Medical physics; Computer vision; Pattern recognition (psychology); Medicine; Radiology; Image (mathematics)","score_opus":0.04189763959645309,"score_gpt":0.3309519131999461,"score_spread":0.289054273603493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3117135956","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8819648,0.0000668811,0.10188686,0.0028194382,0.0001495527,0.0034217031,0.009509672,0.00018023717,8.359716e-7],"genre_scores_gemma":[0.921401,0.0000374514,0.07689524,0.0010789464,0.00016449037,0.00034523456,0.000012815122,0.000064604596,1.8186981e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977545,0.000084530075,0.00075465225,0.00080186664,0.0004059494,0.00019846689],"domain_scores_gemma":[0.99621284,0.00011227422,0.0006782035,0.002231783,0.00039636178,0.00036856043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002257606,0.00027458975,0.0006075473,0.00007581563,0.00005151884,0.000013949195,0.0005574123,0.00020144849,0.000006741048],"category_scores_gemma":[0.0007430511,0.0002101544,0.00014329523,0.00052410515,0.00020672411,0.000033271295,0.00060779497,0.00067834085,0.000006369383],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005729234,0.0009129827,0.98205614,0.00059954193,0.000102125,0.000004648473,0.000004496173,0.000019366167,0.011231825,0.0018757483,0.002599361,0.00002085945],"study_design_scores_gemma":[0.0003583136,0.00008683734,0.9593144,0.0004901456,0.00027406382,1.9667226e-9,3.3999768e-7,0.0002461667,0.010694824,0.000038345053,0.028276248,0.00022030754],"about_ca_topic_score_codex":0.000009930653,"about_ca_topic_score_gemma":2.316588e-7,"teacher_disagreement_score":0.039436225,"about_ca_system_score_codex":0.00006376048,"about_ca_system_score_gemma":0.00039980857,"threshold_uncertainty_score":0.85698473},"labels":[],"label_agreement":null},{"id":"W3119396371","doi":"10.1007/s00429-020-02185-5","title":"Poorer clinical outcomes for older adult monolinguals when matched to bilinguals on brain health","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; York University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Neuroscience of multilingualism; Dementia; Psychology; White matter; Neuroimaging; Cognition; Propensity score matching; Boston Naming Test; Clinical psychology; Neuropsychology; Developmental psychology; Audiology; Medicine; Disease; Psychiatry; Magnetic resonance imaging","score_opus":0.06766428675002974,"score_gpt":0.42087342849979886,"score_spread":0.35320914174976914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119396371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71731925,0.00009912069,0.06287143,0.21756598,0.00033184854,0.0013663002,0.000092332666,0.00024731152,0.00010642946],"genre_scores_gemma":[0.65366817,0.00004411119,0.06485032,0.27829975,0.0006529446,0.000102008045,0.0002284888,0.000060266975,0.0020939072],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99875444,0.000046017976,0.00037393215,0.00049111736,0.00012520968,0.00020927827],"domain_scores_gemma":[0.99867284,0.00052417116,0.00010238386,0.00035659372,0.00016580519,0.00017821077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019043991,0.00015836988,0.00037358937,0.00006856799,0.00012241337,0.000023619,0.000039670747,0.00010799353,0.000040010804],"category_scores_gemma":[0.0011448958,0.00012702,0.000111256704,0.00012209325,0.000028721264,0.00003242541,0.000030567637,0.00019780797,0.0000031224026],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085841975,0.0003377291,0.07147943,0.0003256591,0.0001845633,0.000016858137,0.0014643616,0.000030158557,0.0150293745,0.01937063,0.27943134,0.6114715],"study_design_scores_gemma":[0.0043769022,0.0017527962,0.6155947,0.0002579933,0.00012470788,0.00012305954,0.00048409108,0.00017133977,0.00843185,0.07454118,0.29365066,0.00049072254],"about_ca_topic_score_codex":0.000014512073,"about_ca_topic_score_gemma":0.000012350961,"teacher_disagreement_score":0.61098075,"about_ca_system_score_codex":0.000026630814,"about_ca_system_score_gemma":0.000091246,"threshold_uncertainty_score":0.5179725},"labels":[],"label_agreement":null},{"id":"W3120110232","doi":"10.1101/2021.01.12.21249706","title":"Diffusion basis spectrum imaging in post-hemorrhagic hydrocephalus of prematurity","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Intellectual and Developmental Disabilities Research Center; Doris Duke Charitable Foundation; Child Neurology Foundation; Cerebral Palsy International Research Foundation; Dana Foundation; National Institutes of Health; March of Dimes Foundation","keywords":"White matter; Intraventricular hemorrhage; Fractional anisotropy; Corpus callosum; Hydrocephalus; Diffusion MRI; Medicine; Fiber tract; Pathology; Magnetic resonance imaging; Radiology; Biology; Gestational age","score_opus":0.03179120281831256,"score_gpt":0.3206358706912859,"score_spread":0.28884466787297336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120110232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98788756,0.0009217685,0.00323903,0.005240946,0.00012334679,0.00070598145,0.00002629957,0.00019840676,0.0016566697],"genre_scores_gemma":[0.98573613,0.00049807655,0.012918991,0.0003802228,0.00008103815,0.00008651902,0.00012107381,0.000053413325,0.00012451896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981727,0.00005297445,0.0005175236,0.0006843887,0.00029851176,0.00027390767],"domain_scores_gemma":[0.9983762,0.00006044866,0.0002573979,0.0010827965,0.0001207624,0.000102378115],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020017933,0.00028041573,0.00061628176,0.0002594052,0.000035087778,0.000018216719,0.00025926673,0.00013489055,0.000118382064],"category_scores_gemma":[0.00017471185,0.00027378357,0.00021388613,0.0002963314,0.000089896304,0.000049834336,0.000717459,0.0008978326,0.0000038565813],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014615736,0.0015798445,0.676785,0.002336293,0.000041330924,0.0008268735,0.0006942284,0.00008308697,0.30322093,0.00037119476,0.00019789708,0.013717152],"study_design_scores_gemma":[0.001162611,0.00008092217,0.7730917,0.0024230597,0.00023305461,0.00037554814,0.00016510257,0.009722951,0.2036254,0.007838459,0.00066082587,0.00062041025],"about_ca_topic_score_codex":0.00014876734,"about_ca_topic_score_gemma":0.00002486177,"teacher_disagreement_score":0.09959555,"about_ca_system_score_codex":0.00010452148,"about_ca_system_score_gemma":0.00015562987,"threshold_uncertainty_score":0.99997145},"labels":[],"label_agreement":null},{"id":"W3120177330","doi":"10.1609/aaai.v35i12.17258","title":"Towards Generalized Implementation of Wasserstein Distance in GANs","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Shanghai Jiao Tong University; National Natural Science Foundation of China","keywords":"Duality (order theory); Lipschitz continuity; Mathematics; Constraint (computer-aided design); Duality gap; Sobolev space; Strong duality; Applied mathematics; Perturbation function; Mathematical optimization; Pure mathematics; Mathematical analysis; Optimization problem; Geometry","score_opus":0.16416688522055034,"score_gpt":0.41593591733574564,"score_spread":0.2517690321151953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120177330","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775849,0.000034918237,0.008650092,0.008302797,0.00005452301,0.0004911268,0.000017613567,0.00004074212,0.0048232637],"genre_scores_gemma":[0.9931313,0.00013221087,0.006363695,0.00017082127,0.000018123821,0.00004012635,0.0000028689744,0.000010459695,0.00013041362],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989139,0.000007524073,0.00044870484,0.00024849596,0.00023041929,0.00015098561],"domain_scores_gemma":[0.9990799,0.000019844445,0.00022526014,0.00017848086,0.0004596929,0.000036852212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013565486,0.00010548678,0.0002273869,0.000063928084,0.000037430582,0.000015133538,0.00021004272,0.000036049085,0.000107616965],"category_scores_gemma":[0.00012570787,0.00008535823,0.00007809166,0.0005240973,0.00012726382,0.00007336144,0.00007336391,0.00015292925,0.0000029419184],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006469527,0.0001375367,0.0040551363,0.00006826394,0.0000059828635,8.899268e-7,0.00032928743,0.0000066374696,0.47390798,0.49597,0.000045705805,0.02540788],"study_design_scores_gemma":[0.000057667046,0.00006788637,0.003546345,0.00019702171,0.000017102497,0.000004498926,0.0011505735,0.0010003406,0.92776704,0.06596928,0.00015117276,0.000071082024],"about_ca_topic_score_codex":0.00006901653,"about_ca_topic_score_gemma":0.0000373951,"teacher_disagreement_score":0.45385906,"about_ca_system_score_codex":0.000042552947,"about_ca_system_score_gemma":0.00011974365,"threshold_uncertainty_score":0.34808078},"labels":[],"label_agreement":null},{"id":"W3120261134","doi":"10.1038/s41598-020-79540-3","title":"An atlas for human brain myelin content throughout the adult life span","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; University of British Columbia","funders":"Multiple Sclerosis Society; Natural Sciences and Engineering Research Council of Canada; Vancouver Coastal Health Research Institute; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"Myelin; Neuroimaging; Context (archaeology); White matter; Content (measure theory); Biology; Life span; Neuroscience; Magnetic resonance imaging; Medicine; Evolutionary biology; Central nervous system; Mathematics","score_opus":0.13032617741329613,"score_gpt":0.4150828116473342,"score_spread":0.2847566342340381,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120261134","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86829704,0.00022390751,0.06917079,0.05511285,0.0020686695,0.0023530563,0.000022703194,0.0005961649,0.0021548385],"genre_scores_gemma":[0.9736165,0.000004125379,0.010108744,0.0028031752,0.00023113067,0.00022285337,0.00029843595,0.000028893393,0.012686177],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99842054,0.000025242232,0.00038573547,0.00066570484,0.0002742843,0.00022846987],"domain_scores_gemma":[0.99762547,0.00005004805,0.00017970195,0.0014737854,0.00052227126,0.00014870029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051761064,0.00010765309,0.00017208143,0.00003547875,0.0005561401,0.0001362086,0.000107422195,0.000036872272,0.000045423476],"category_scores_gemma":[0.0005596792,0.000075443655,0.0001232918,0.0002581737,0.00023731573,0.00008347803,0.000049011884,0.00012495762,0.000006165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000147947285,0.00034459474,0.006212214,0.000049953407,0.000023008777,0.0002750538,0.00048192605,0.000018233784,0.86269385,0.011569744,0.11476221,0.0035544303],"study_design_scores_gemma":[0.00045756757,0.00013969619,0.0065489076,0.000086712134,0.00008719654,0.0008935491,0.0005885156,0.0006102768,0.25687218,0.05971133,0.67376715,0.00023694937],"about_ca_topic_score_codex":0.00002050658,"about_ca_topic_score_gemma":0.000026220687,"teacher_disagreement_score":0.60582167,"about_ca_system_score_codex":0.00003350854,"about_ca_system_score_gemma":0.00023647436,"threshold_uncertainty_score":0.42774358},"labels":[],"label_agreement":null},{"id":"W3120303568","doi":"10.1016/j.jns.2021.117317","title":"Peri-hematoma corticospinal tract integrity in intracerebral hemorrhage patients: A diffusion-tensor imaging study","year":2021,"lang":"en","type":"article","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; The Speech and Stuttering Institute; Women and Children’s Health Research Institute; University of Alberta","funders":"Canada Excellence Research Chairs, Government of Canada; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Medicine; Fractional anisotropy; Corticospinal tract; Intracerebral hemorrhage; Edema; White matter; Diffusion MRI; Hematoma; Brain edema; Nuclear medicine; Magnetic resonance imaging; Anesthesia; Radiology; Surgery; Glasgow Coma Scale","score_opus":0.058631785819977515,"score_gpt":0.3563733135864293,"score_spread":0.2977415277664518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120303568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9858464,0.000055971173,0.00021455216,0.013378979,0.00014019813,0.00023062264,0.0000010963771,0.000019118423,0.00011306088],"genre_scores_gemma":[0.99487346,0.000013879288,0.0029065255,0.0021239147,0.00005264117,0.00000498772,1.3730376e-7,0.000004534234,0.000019893714],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99850416,0.00015576892,0.0004405124,0.00023532864,0.00045890428,0.00020532626],"domain_scores_gemma":[0.9991608,0.00013977465,0.00027166074,0.00018113572,0.00015621942,0.000090369314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039349886,0.000105081046,0.00026053615,0.00005781631,0.00017191106,0.00004725245,0.00034619638,0.000026670294,0.00006229445],"category_scores_gemma":[0.0011022427,0.00005333961,0.00012954927,0.0004978216,0.00025048535,0.00014496704,0.00017867678,0.0007644819,0.000001499078],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050809685,0.0018678561,0.99169636,0.0000039893353,0.0000014620695,0.00044421345,0.00004931749,0.000010489832,0.00089539116,0.00005507681,0.0000345662,0.0048904503],"study_design_scores_gemma":[0.0006040266,0.0010811252,0.99318045,0.000028237968,0.000026192878,0.0015998272,0.00017777437,0.0016174505,0.00018036964,0.00127953,0.00016871237,0.000056314064],"about_ca_topic_score_codex":0.0000036393385,"about_ca_topic_score_gemma":0.0000019032037,"teacher_disagreement_score":0.011255064,"about_ca_system_score_codex":0.000025959078,"about_ca_system_score_gemma":0.00008012164,"threshold_uncertainty_score":0.3321336},"labels":[],"label_agreement":null},{"id":"W3120843416","doi":"10.1007/s00234-021-02635-9","title":"Spatial correspondence of spinal cord white matter tracts using diffusion tensor imaging, fibre tractography, and atlas-based segmentation","year":2021,"lang":"en","type":"article","venue":"Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Sunnybrook Health Science Centre; Sunnybrook Hospital; University of Toronto; University of Waterloo","funders":"FedDev Ontario; Mitacs","keywords":"Tractography; Diffusion MRI; White matter; Spinal cord; Anatomy; Neuroradiology; Medicine; Magnetic resonance imaging; Neurology; Radiology","score_opus":0.048857378659725975,"score_gpt":0.3565472024058139,"score_spread":0.3076898237460879,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3120843416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9502396,0.00008660144,0.04722962,0.0019802665,0.000078072946,0.00024130924,0.00001759509,0.00005289096,0.00007402023],"genre_scores_gemma":[0.9802386,0.000036924834,0.017757587,0.0018026831,0.000045505247,0.00001270032,0.000037265974,0.000021846558,0.00004689217],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99906284,0.000072718736,0.00024246724,0.0003500313,0.00010401302,0.0001679048],"domain_scores_gemma":[0.99935436,0.000069837646,0.0001464987,0.00025580576,0.00009980656,0.000073700896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004029418,0.00013054411,0.00024978633,0.000119299315,0.000060620245,0.0000089829355,0.0000523187,0.00005020528,0.0000834481],"category_scores_gemma":[0.00004020773,0.00012595054,0.00006262035,0.00018488143,0.00017115244,0.000058872916,0.00003120576,0.00018773532,0.0000024551734],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039948605,0.00008636173,0.5449717,0.00004718465,0.0000030788804,0.00008492753,0.00001251902,0.000014642956,0.4495836,0.000016183447,0.00020052401,0.004579767],"study_design_scores_gemma":[0.0008403285,0.00055478385,0.95587796,0.00007894642,0.00007496587,0.0013221032,0.00002099794,0.005063764,0.034872398,0.000110526606,0.0010661256,0.00011708148],"about_ca_topic_score_codex":0.000018516203,"about_ca_topic_score_gemma":0.0000020189416,"teacher_disagreement_score":0.4147112,"about_ca_system_score_codex":0.000014039731,"about_ca_system_score_gemma":0.000053643693,"threshold_uncertainty_score":0.5136114},"labels":[],"label_agreement":null},{"id":"W3121662764","doi":"10.1038/s41380-021-01018-z","title":"Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia—a multicenter harmonized diffusion tensor imaging study","year":2021,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Center for Advancing Translational Sciences; National Institute of Mental Health; National Research Foundation of Korea; U.S. Department of Health and Human Services","keywords":"Fractional anisotropy; White matter; Corpus callosum; Schizophrenia (object-oriented programming); Diffusion MRI; Psychology; Confounding; Population; Magnetic resonance imaging; Medicine; Internal medicine; Clinical psychology; Psychiatry; Neuroscience; Radiology","score_opus":0.03999007663752993,"score_gpt":0.3587815498532476,"score_spread":0.31879147321571766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3121662764","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96795124,0.00036656143,0.019992013,0.010727471,0.0000935836,0.00069743954,0.000010853523,0.000074263546,0.000086559994],"genre_scores_gemma":[0.9220124,0.00001347454,0.07576664,0.001988264,0.000090568836,0.000030744286,0.00003277751,0.00003804251,0.000027102444],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983895,0.00023346416,0.00049388193,0.00049956836,0.00017675436,0.0002068274],"domain_scores_gemma":[0.99891615,0.000212373,0.00012510423,0.0006031293,0.000060946648,0.00008228405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025485115,0.00017186077,0.00026022113,0.00010669206,0.00018368647,0.000053461572,0.0001137002,0.00005483365,0.00002381636],"category_scores_gemma":[0.0001813868,0.00013297607,0.000094524075,0.00041451756,0.00008161048,0.000059181762,0.00014652994,0.0006471476,0.0000032047305],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000423811,0.0002027882,0.99807054,0.000022534581,0.000024442475,0.00002812243,0.000040021958,0.000001778837,0.00055388187,0.000248754,0.00010158383,0.00066315604],"study_design_scores_gemma":[0.002478794,0.000028633265,0.9918424,0.000115551076,0.00017712642,0.000044477507,0.00018927401,0.0003762744,0.000060131188,0.0044745314,0.00008237305,0.0001304663],"about_ca_topic_score_codex":0.000010605371,"about_ca_topic_score_gemma":0.000014236745,"teacher_disagreement_score":0.05577463,"about_ca_system_score_codex":0.000012189982,"about_ca_system_score_gemma":0.000043212156,"threshold_uncertainty_score":0.5422607},"labels":[],"label_agreement":null},{"id":"W3122552454","doi":"10.1016/j.nicl.2021.102567","title":"Widespread white matter aberration is associated with the severity of apathy in amnestic Mild Cognitive Impairment: Tract-based spatial statistics analysis","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Lembaga Pengelola Dana Pendidikan; Universitair Medisch Centrum Groningen; ZonMw","keywords":"Apathy; White matter; Psychology; Cognitive impairment; Cognition; Medicine; Audiology; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.07147150062390782,"score_gpt":0.39279993927548174,"score_spread":0.3213284386515739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122552454","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8503838,0.000010333605,0.14287204,0.0055377916,0.000030797128,0.000527115,0.00043790587,0.000054701242,0.00014550025],"genre_scores_gemma":[0.98851705,0.0000145553195,0.004578365,0.006314298,0.00002894697,0.0000458728,0.00032657754,0.000026331425,0.00014802966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99812865,0.00029535493,0.0006155103,0.0004725673,0.0002937863,0.00019412079],"domain_scores_gemma":[0.99724096,0.0015391669,0.00032546686,0.00045147925,0.00035942276,0.00008348623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033268324,0.00016359065,0.000497755,0.000091557784,0.00005854569,0.000020523952,0.00009044634,0.00008423787,0.00018183995],"category_scores_gemma":[0.0007525758,0.00012571983,0.00016633725,0.00081295427,0.0002742187,0.00005505032,0.000038074788,0.0005358138,0.000008719649],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028360862,0.0015919261,0.9944258,0.000027510427,0.00010347178,0.00023544427,0.00010439553,0.00005843516,0.00018865072,0.0000069853877,0.0018894788,0.0010843087],"study_design_scores_gemma":[0.0015854045,0.0003591958,0.98214746,0.0000906741,0.0010992222,0.000016422873,0.000031395724,0.013412341,0.0009968457,0.000092729955,0.00005371827,0.00011461121],"about_ca_topic_score_codex":0.00003399528,"about_ca_topic_score_gemma":0.000120653516,"teacher_disagreement_score":0.13829368,"about_ca_system_score_codex":0.000028316997,"about_ca_system_score_gemma":0.00015668919,"threshold_uncertainty_score":0.51267064},"labels":[],"label_agreement":null},{"id":"W3122665304","doi":"10.3390/electronics10030249","title":"An Ensemble Learning Approach Based on Diffusion Tensor Imaging Measures for Alzheimer’s Disease Classification","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Ministero dello Sviluppo Economico; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; U.S. Department of Defense; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Artificial intelligence; Computer science; Machine learning; Concatenation (mathematics); Diffusion MRI; Feature selection; Ensemble learning; Exploit; Neuroimaging; Curse of dimensionality; Pattern recognition (psychology); Magnetic resonance imaging; Mathematics","score_opus":0.07979652277542423,"score_gpt":0.3556719242560934,"score_spread":0.27587540148066914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122665304","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021593153,0.002898842,0.96498895,0.00740919,0.000027634223,0.0009818273,0.000009895005,0.0006347456,0.0014557885],"genre_scores_gemma":[0.9528686,0.00021169329,0.044319693,0.0015073015,0.00009693096,0.00028831649,0.00046199647,0.000055637312,0.0001898244],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890304,0.00004401579,0.00015074712,0.00042763393,0.00019083494,0.00028372812],"domain_scores_gemma":[0.99905217,0.000053868098,0.000068416506,0.00046255818,0.00022213046,0.00014086317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012672723,0.00013160099,0.00014138836,0.000058933038,0.00022710268,0.000029130268,0.000075536766,0.000032118074,0.000005488376],"category_scores_gemma":[0.00016871453,0.00012704499,0.00008492967,0.00016871173,0.000025263531,0.00005694151,0.000010945554,0.00027142523,0.000002526882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009506871,0.0028109848,0.021244252,0.00013031566,0.000046188416,0.000025498559,0.00008932173,0.006477824,0.529696,0.025706902,0.0030668015,0.40975523],"study_design_scores_gemma":[0.00096006226,0.00025846643,0.009561891,0.000044510314,0.00023763972,0.000016173757,0.000052039435,0.81542,0.02549312,0.001832607,0.14588475,0.00023875525],"about_ca_topic_score_codex":5.232148e-7,"about_ca_topic_score_gemma":4.842272e-7,"teacher_disagreement_score":0.9312754,"about_ca_system_score_codex":0.000083955805,"about_ca_system_score_gemma":0.00023019432,"threshold_uncertainty_score":0.5180744},"labels":[],"label_agreement":null},{"id":"W3123502171","doi":"10.1007/s00701-020-04672-4","title":"Uncrossed corticospinal tracts presenting as transient tumor-related symptomatology","year":2021,"lang":"en","type":"article","venue":"Acta Neurochirurgica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan; Royal University Hospital","funders":"","keywords":"Medicine; Corticospinal tract; Hemiparesis; Diffusion MRI; Pyramidal tracts; Neurosurgery; Neuroradiology; Neurology; Stroke (engine); Radiology; Magnetic resonance imaging; Anatomy; Angiography","score_opus":0.03697971929130505,"score_gpt":0.33792618323306256,"score_spread":0.3009464639417575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3123502171","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691013,0.00008134843,0.00044943322,0.010328437,0.00011404378,0.00040093606,0.0000060387574,0.0005815075,0.01893697],"genre_scores_gemma":[0.9942588,0.00009356275,0.0016318384,0.0026235967,0.000042093998,0.000053483058,0.000041499716,0.000051213116,0.0012038748],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982844,0.00005450376,0.0004314455,0.00056970346,0.0002475407,0.00041241798],"domain_scores_gemma":[0.99879426,0.00012397379,0.00014201604,0.00059297105,0.00012717897,0.00021959677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048932405,0.00020990032,0.00035433078,0.00007013712,0.00018544335,0.0000364104,0.00014250966,0.000070739974,0.00023187874],"category_scores_gemma":[0.00020613779,0.00020550705,0.00016494212,0.00042827398,0.0001173231,0.000091666145,0.00007435617,0.00045484502,0.00006231522],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002530233,0.0018894885,0.009497719,0.0002082888,0.00013168939,0.011035174,0.00036936696,0.000045472047,0.9501121,0.020159557,0.0041406075,0.002157488],"study_design_scores_gemma":[0.004802012,0.0007201187,0.2714415,0.0002797917,0.0005127581,0.054990467,0.00011352168,0.003229786,0.20824185,0.0066572395,0.44811484,0.0008961242],"about_ca_topic_score_codex":0.0000036820868,"about_ca_topic_score_gemma":6.2319754e-7,"teacher_disagreement_score":0.7418703,"about_ca_system_score_codex":0.000022143406,"about_ca_system_score_gemma":0.0001478438,"threshold_uncertainty_score":0.83803344},"labels":[],"label_agreement":null},{"id":"W3124084750","doi":"10.1089/brain.2020.0907","title":"Hierarchical Microstructure Informed Tractography","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Tractography; Diffusion MRI; White matter; Computer science; Artificial intelligence; Magnetic resonance imaging; Radiomics; Pattern recognition (psychology); Radiology; Medicine","score_opus":0.04658254528705097,"score_gpt":0.3559203308303244,"score_spread":0.30933778554327346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124084750","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9161723,0.000098181496,0.039037686,0.036677614,0.00006464814,0.00034824805,0.000036694502,0.00043700484,0.0071275663],"genre_scores_gemma":[0.9705057,0.000021539674,0.022362258,0.006641434,0.00007720304,0.000030160756,0.000039319846,0.000016111688,0.0003062337],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993124,0.000027210566,0.00011864256,0.00026181983,0.00010593441,0.00017396994],"domain_scores_gemma":[0.9990493,0.00036433587,0.000035832953,0.00036840595,0.000075798074,0.00010635094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005826398,0.00010156341,0.00017261911,0.000052761203,0.00008899255,0.000017131544,0.00005153717,0.000067994915,0.00008439704],"category_scores_gemma":[0.0006148474,0.000094661125,0.000116599214,0.00033532403,0.00009023105,0.00006933408,0.00004576442,0.00031560604,0.000006409361],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023305135,0.00077677297,0.068448715,0.0002224361,0.00010550791,0.000624152,0.00035962128,0.000010867,0.71588767,0.057750605,0.04349138,0.11208921],"study_design_scores_gemma":[0.0011978663,0.00011106453,0.41149217,0.000055563305,0.00003613829,0.0015601021,0.000041035073,0.0001604977,0.097788185,0.025114492,0.46218315,0.00025973812],"about_ca_topic_score_codex":0.000004093571,"about_ca_topic_score_gemma":0.000012524295,"teacher_disagreement_score":0.6180995,"about_ca_system_score_codex":0.000023464549,"about_ca_system_score_gemma":0.0001419788,"threshold_uncertainty_score":0.38601688},"labels":[],"label_agreement":null},{"id":"W3124741176","doi":"10.1021/acschemneuro.0c00801","title":"Radiosynthesis, <i>In Vitro</i> and <i>In Vivo</i> Evaluation of [<sup>18</sup>F]CBD-2115 as a First-in-Class Radiotracer for Imaging 4R-Tauopathies","year":2021,"lang":"en","type":"article","venue":"ACS Chemical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Center for Scientific Review; National Institute of Neurological Disorders and Stroke; National Institute on Aging","keywords":"Radioligand; Progressive supranuclear palsy; Radiosynthesis; In vivo; In vitro; Chemistry; Biochemistry; Biology; Molecular biology; Genetics","score_opus":0.049462504594981166,"score_gpt":0.34279656570751943,"score_spread":0.29333406111253824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3124741176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99242246,0.0004542554,0.0007620458,0.004917077,0.00003116426,0.0008563603,0.000021647293,0.000049534105,0.00048543193],"genre_scores_gemma":[0.99290913,0.0002847509,0.004998176,0.0014812314,0.000027157303,0.00023039515,0.000004521409,0.000023379067,0.000041231153],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99807686,0.00005505467,0.00041293568,0.00068940147,0.0004153066,0.00035044077],"domain_scores_gemma":[0.9988858,0.00042044363,0.00009635102,0.00038652218,0.00011658267,0.00009430013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005625221,0.00017057861,0.00034831633,0.00014040344,0.00004820851,0.000022881515,0.00017365707,0.000056191442,0.000008582591],"category_scores_gemma":[0.0018839159,0.00017430978,0.000059211383,0.000733908,0.00027805145,0.00019136393,0.00009523651,0.00024349328,4.5103712e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008567314,0.00019509683,0.003407626,0.0000697546,5.5797193e-7,0.0000261753,0.00007737974,0.00017348155,0.99294484,0.00009945003,0.00013990278,0.0027800684],"study_design_scores_gemma":[0.0012001611,0.00002424228,0.0011358256,0.00015924363,0.000027064394,0.00016448059,0.000053379594,0.07060941,0.92274314,0.0013568026,0.0023790398,0.00014719531],"about_ca_topic_score_codex":0.000012360627,"about_ca_topic_score_gemma":0.0000029889682,"teacher_disagreement_score":0.07043593,"about_ca_system_score_codex":0.00010048954,"about_ca_system_score_gemma":0.0001400999,"threshold_uncertainty_score":0.71081465},"labels":[],"label_agreement":null},{"id":"W3125305379","doi":"10.1371/journal.pcbi.1008584","title":"Voxelized simulation of cerebral oxygen perfusion elucidates hypoxia in aged mouse cortex","year":2021,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Division of Chemical, Bioengineering, Environmental, and Transport Systems; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"Cerebral blood flow; Computer science; Blood flow; Discretization; Hypoxia (environmental); Neuroscience; Perfusion; Biomedical engineering; Chemistry; Oxygen; Biology; Mathematics; Medicine; Cardiology","score_opus":0.0630287532450022,"score_gpt":0.3519936065417261,"score_spread":0.28896485329672394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125305379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9672315,0.00008760038,0.031375777,0.000781737,0.000015469352,0.00024083033,0.000032437256,0.00007465981,0.00015996512],"genre_scores_gemma":[0.96168894,0.000022630256,0.037076455,0.0003600972,0.000026235184,0.000019524734,0.0007245685,0.0000112607395,0.000070322014],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992458,0.000055823755,0.00027063914,0.00023570776,0.00008427105,0.00010774239],"domain_scores_gemma":[0.9992534,0.0003146915,0.000088309855,0.00013834158,0.00017063836,0.000034626195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046451085,0.000081538885,0.00021383096,0.00009698639,0.000033076747,0.0000028855368,0.00004899218,0.000058817146,0.000093596],"category_scores_gemma":[0.00017554287,0.00007875333,0.000045171677,0.00021033929,0.00006025785,0.000030994575,0.000051461175,0.00010988727,0.0000082994575],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001528743,0.00056893745,0.047101382,0.00006522724,0.000022806184,0.000013884737,0.000099294426,0.04537167,0.90075,0.0037652424,0.000089800196,0.0019988941],"study_design_scores_gemma":[0.002905552,0.0002624204,0.46107554,0.000114095696,0.000050235874,0.00004309214,0.000044128636,0.41552347,0.07534141,0.04399202,0.00040911714,0.00023893405],"about_ca_topic_score_codex":0.0000060821544,"about_ca_topic_score_gemma":0.0000028295904,"teacher_disagreement_score":0.8254086,"about_ca_system_score_codex":0.000025811616,"about_ca_system_score_gemma":0.00007013455,"threshold_uncertainty_score":0.32114676},"labels":[],"label_agreement":null},{"id":"W3125928972","doi":"10.1101/2021.01.25.428063","title":"NOMIS: Quantifying morphometric deviations from normality over the lifetime of the adult human brain","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institute of Mental Health; Sanofi Genzyme; Genentech; Fundamental Research Funds for the Central Universities; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Fok Ying Tung Education Foundation; Southwest University; Engineering and Physical Sciences Research Council; Natural Science Foundation of Chongqing; Eisai; National Natural Science Foundation of China; Pfizer; Biogen; BioClinica; Child Mind Institute; University of Southern California; Chongqing Postdoctoral Science Foundation; Northern California Institute for Research and Education; University of Texas at San Antonio; China Postdoctoral Science Foundation; National Center for Research Resources; F. Hoffmann-La Roche; Stavros Niarchos Foundation; Foundation for the National Institutes of Health; Leon Levy Foundation; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Sanofi; Alzheimer's Association","keywords":"Normality; Normative; Pipeline (software); Standard deviation; Quality (philosophy); Human brain; Statistics; Sample (material); Psychology; Artificial intelligence; Computer science; Mathematics; Neuroscience","score_opus":0.05474295651427723,"score_gpt":0.31098378771361856,"score_spread":0.2562408311993413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3125928972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9858192,0.00068265456,0.008166996,0.003249547,0.00024599885,0.0011426909,0.00039432163,0.00028365338,0.000014930405],"genre_scores_gemma":[0.9877847,0.0001504619,0.009927804,0.0015068739,0.0002664895,0.00026373618,0.0000023421746,0.000089691544,0.0000079061465],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99764323,0.00016248127,0.00067555404,0.0007461826,0.00045775162,0.0003148136],"domain_scores_gemma":[0.9955193,0.00026822527,0.0006899359,0.0027150745,0.00067618594,0.0001312802],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003804728,0.0003730528,0.000551344,0.00018241283,0.00035758736,0.00010421243,0.00072363886,0.00026490868,0.00007096083],"category_scores_gemma":[0.000884223,0.00027580044,0.0003286016,0.0013535889,0.00022078115,0.00008607929,0.0008205748,0.0011001837,0.000006965934],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011939033,0.0003059558,0.13076515,0.00026338553,0.0001880872,0.000011453734,0.000023856515,0.000037475664,0.86465275,0.0026193918,0.0011167245,0.000003843532],"study_design_scores_gemma":[0.0003547707,0.000015733118,0.8429903,0.00056298275,0.0002633332,3.575294e-8,0.0000062005392,0.00038983565,0.15294008,0.0000129510645,0.0021843463,0.00027946188],"about_ca_topic_score_codex":0.00047282834,"about_ca_topic_score_gemma":0.000011187705,"teacher_disagreement_score":0.71222514,"about_ca_system_score_codex":0.00017654111,"about_ca_system_score_gemma":0.00042648494,"threshold_uncertainty_score":0.9999694},"labels":[],"label_agreement":null},{"id":"W3126252517","doi":"10.1007/s00429-020-02211-6","title":"A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Tractography; Ising model; Diffusion MRI; Statistical physics; Predictability; White matter; Criticality; Fractional anisotropy; Mathematics; Computer science; Artificial intelligence; Physics; Statistics; Magnetic resonance imaging","score_opus":0.04812751800487218,"score_gpt":0.352832356194857,"score_spread":0.3047048381899848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126252517","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9283256,0.00007445163,0.06325452,0.007709392,0.000023671,0.0005062859,0.00001004496,0.000032296066,0.00006376192],"genre_scores_gemma":[0.9952128,0.000010224271,0.0035042355,0.0011820458,0.000039559814,0.000016559687,0.00000479654,0.000009423433,0.00002035124],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99932855,0.000078283774,0.00020012577,0.00016493928,0.00014291941,0.00008517029],"domain_scores_gemma":[0.9992633,0.00020762191,0.00013040756,0.00031946888,0.00005981069,0.000019415298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013030696,0.000087823246,0.00018121538,0.000050981336,0.000119604185,0.00000889333,0.00006535056,0.000053890613,0.0000029634473],"category_scores_gemma":[0.00015203933,0.000044947003,0.00006271576,0.0004542223,0.00007988449,0.000037877784,0.000073871306,0.00024613846,1.1625014e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014509258,0.00005648677,0.028646262,0.000039093615,0.000011059346,2.5139857e-7,0.000681146,0.0018896611,0.86087924,0.00094090006,0.0004417388,0.10626904],"study_design_scores_gemma":[0.0008024157,0.00020315466,0.48736867,0.0002561437,0.00010696896,0.00002579982,0.0003262307,0.08775587,0.40499598,0.014738747,0.0032781858,0.00014185304],"about_ca_topic_score_codex":0.000029185972,"about_ca_topic_score_gemma":0.00003164927,"teacher_disagreement_score":0.4587224,"about_ca_system_score_codex":0.000011969946,"about_ca_system_score_gemma":0.000025916344,"threshold_uncertainty_score":0.18328854},"labels":[],"label_agreement":null},{"id":"W3126656652","doi":"10.1038/s41390-021-01379-9","title":"Fronto-temporal horn ratio: yet another marker of ventriculomegaly?","year":2021,"lang":"en","type":"article","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"French horn; Ventriculomegaly; Psychology; Biology; Genetics; Pregnancy; Fetus","score_opus":0.15807117622504274,"score_gpt":0.444093068563404,"score_spread":0.2860218923383613,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126656652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8651818,0.009907907,0.040482715,0.019512286,0.0002724184,0.0025397274,0.00014017304,0.00045612766,0.061506815],"genre_scores_gemma":[0.96855944,0.0017846967,0.017633714,0.00014134074,0.00041383694,0.00010747021,0.000061668754,0.000037323705,0.011260504],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99858683,0.000095438605,0.00023764702,0.00028617124,0.00051692815,0.0002769845],"domain_scores_gemma":[0.9987152,0.00018497896,0.000052788982,0.00049470784,0.00046104938,0.00009125814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043735447,0.000078226214,0.00018843546,0.00019530875,0.000073892494,0.000015670534,0.000116595205,0.000055752374,0.00048651788],"category_scores_gemma":[0.00035593685,0.000069867456,0.000078061974,0.0010582971,0.00006813704,0.000055080927,0.00010914308,0.0003267179,0.000054708962],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020673378,0.0010365024,0.6756145,0.0004039754,0.00004332634,0.00047372485,0.00012382677,0.000006095433,0.020880383,0.0030713077,0.28757948,0.010560164],"study_design_scores_gemma":[0.0034104027,0.0006475563,0.30872408,0.00008650081,0.00019329479,0.0003330458,0.00022000716,0.0017760976,0.04707594,0.013208903,0.62378937,0.0005348129],"about_ca_topic_score_codex":0.00003952943,"about_ca_topic_score_gemma":0.0000023551547,"teacher_disagreement_score":0.3668904,"about_ca_system_score_codex":0.000049594742,"about_ca_system_score_gemma":0.0002526952,"threshold_uncertainty_score":0.532703},"labels":[],"label_agreement":null},{"id":"W3126696394","doi":"10.1177/1535759721991161","title":"Emerging Trends in Neuroimaging of Epilepsy","year":2021,"lang":"en","type":"article","venue":"Epiliepsy currents/Epilepsy currents","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Neurological Disorders and Stroke; Canada First Research Excellence Fund; Institute of Neurosciences, Mental Health and Addiction; Foundation for the National Institutes of Health","keywords":"Neuroimaging; Prognostics; Medicine; Epilepsy; Brain function; Magnetic resonance imaging; Neuroscience; Artificial intelligence; Computer science; Psychiatry; Psychology; Radiology; Data mining","score_opus":0.07205264821945591,"score_gpt":0.3910501762932826,"score_spread":0.3189975280738267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126696394","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96810484,0.0034884843,0.008308971,0.0038242952,0.0021526264,0.00091415003,0.00022640603,0.0006619754,0.012318261],"genre_scores_gemma":[0.99164134,0.0008819242,0.0056423536,0.00033093267,0.00020791272,0.00011931485,0.00044394238,0.00010346212,0.00062884385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960054,0.00014904566,0.0012235469,0.0011384683,0.0006742388,0.0008093108],"domain_scores_gemma":[0.99762404,0.000111581445,0.00037181168,0.0012798911,0.0002965011,0.0003161594],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027959328,0.00049951713,0.0009256483,0.00082707143,0.00012736066,0.0000318404,0.00039199748,0.00012113589,0.00065264024],"category_scores_gemma":[0.0002570403,0.0005417722,0.0004048336,0.0024171018,0.00020059057,0.00030477325,0.0003204597,0.0009348946,0.000059035985],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008504103,0.0018615517,0.6868519,0.00022846636,0.000039163784,0.0001460779,0.00023889262,0.0000625901,0.0086540785,0.0011996392,0.0055318,0.2951008],"study_design_scores_gemma":[0.0076408843,0.0003540748,0.80134845,0.0022608945,0.000334991,0.0004875739,0.00031602246,0.007931049,0.03140453,0.0032371094,0.14321554,0.001468876],"about_ca_topic_score_codex":0.00002347014,"about_ca_topic_score_gemma":0.000006006649,"teacher_disagreement_score":0.2936319,"about_ca_system_score_codex":0.0001344765,"about_ca_system_score_gemma":0.0001404382,"threshold_uncertainty_score":0.9997034},"labels":[],"label_agreement":null},{"id":"W3126779283","doi":"10.1101/2021.02.01.21250951","title":"Diffusion kurtosis imaging of white matter in bipolar disorder","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hotchkiss Brain Institute; University of Calgary; University of Toronto","funders":"Canadian Institutes of Health Research; Pfizer Canada; Pfizer","keywords":"White matter; Diffusion MRI; Kurtosis; Fractional anisotropy; Voxel; Magnetic resonance imaging; Bipolar disorder; Nuclear medicine; Tractography; Medicine; Nuclear magnetic resonance; Neuroscience; Psychology; Physics; Radiology; Mathematics; Statistics","score_opus":0.029009777133778905,"score_gpt":0.3198153474433404,"score_spread":0.2908055703095615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126779283","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97548825,0.0018962476,0.0159671,0.0055301767,0.00007964262,0.00044605325,0.000015486861,0.00009283395,0.0004841877],"genre_scores_gemma":[0.98435444,0.0008827547,0.013580543,0.0005784906,0.000042642983,0.00012300804,0.000080237405,0.000053397973,0.00030451216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987245,0.000037231006,0.00038709512,0.0004792114,0.0001847426,0.00018718242],"domain_scores_gemma":[0.99883,0.000028887021,0.00015974673,0.0008418692,0.000081433485,0.000058068992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010848686,0.00019814128,0.0004222618,0.00021412772,0.000038534647,0.000010974581,0.00016963719,0.00008997848,0.0002264757],"category_scores_gemma":[0.00003692594,0.00018733017,0.00013956538,0.00023744295,0.00006772504,0.000035475707,0.00080937473,0.00058630167,0.0000069901803],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075523717,0.00017680271,0.9848788,0.00027421754,0.0000065543863,0.000022908058,0.00019007968,0.00002074581,0.012138163,0.000016648944,0.00014445266,0.0021230904],"study_design_scores_gemma":[0.00029846007,0.0000096413905,0.98319054,0.00083526917,0.000058084453,0.000020307136,0.00005356491,0.0011199809,0.0049038916,0.0004571803,0.008864876,0.0001881936],"about_ca_topic_score_codex":0.000091164824,"about_ca_topic_score_gemma":0.000010895965,"teacher_disagreement_score":0.0088661425,"about_ca_system_score_codex":0.000037758047,"about_ca_system_score_gemma":0.00004581745,"threshold_uncertainty_score":0.76391023},"labels":[],"label_agreement":null},{"id":"W3126805281","doi":"10.1016/j.psychres.2021.113797","title":"Diffusion Tensor Imaging Reveals White Matter Differences in Military Personnel Exposed to Trauma with and without Post-traumatic Stress Disorder","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Canadian Armed Forces; University of Toronto; SickKids Foundation; St Joseph's Health Care; Lawson Health Research Institute; McMaster University; Western University","funders":"Defence Research and Development Canada","keywords":"Diffusion MRI; White matter; Traumatic stress; Psychology; White (mutation); Clinical psychology; Military personnel; Medicine; Magnetic resonance imaging; Radiology; History; Biology","score_opus":0.07344670041803703,"score_gpt":0.3809140165962125,"score_spread":0.30746731617817546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3126805281","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9585107,0.0008206563,0.00069332885,0.038608633,0.00002475197,0.000835925,0.000026955213,0.000059060047,0.00041997305],"genre_scores_gemma":[0.97117394,0.00010025926,0.026488187,0.0010322443,0.000056743527,0.00021573433,0.000022808363,0.000041356707,0.00086874963],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99815196,0.0001307951,0.00024868821,0.00059077126,0.00042747325,0.0004503238],"domain_scores_gemma":[0.9989572,0.00007418623,0.000025983458,0.0005166918,0.00021903797,0.00020690807],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022003416,0.0001734022,0.00029610237,0.00027188373,0.00019998978,0.000037745227,0.00013845814,0.00004001036,0.00012582097],"category_scores_gemma":[0.00005164321,0.00013198695,0.00003621467,0.0005771837,0.00014553226,0.000091510665,0.000116652816,0.00049018575,0.000015770866],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016473647,0.00043491376,0.9920676,0.00027713654,0.000008516341,0.000017928862,0.0020954798,0.0000011502472,0.0028217535,0.00003248282,0.00047722808,0.0016011165],"study_design_scores_gemma":[0.0008591556,0.00022870644,0.98226887,0.0007963515,0.000015902704,0.000103148224,0.01468296,0.00042093088,0.000055824024,0.0003453674,0.00006429181,0.00015852062],"about_ca_topic_score_codex":0.00019507972,"about_ca_topic_score_gemma":0.00066974247,"teacher_disagreement_score":0.03757639,"about_ca_system_score_codex":0.0000326415,"about_ca_system_score_gemma":0.00006689422,"threshold_uncertainty_score":0.53822714},"labels":[],"label_agreement":null},{"id":"W3127043227","doi":"10.1002/mrm.29124","title":"Characterization and correction of time‐varying eddy currents for diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Eddy current; Diffusion; Metric (unit); Diffusion MRI; Mean squared error; Pulsed field gradient; Field (mathematics); Algorithm; Computer science; Physics; Nuclear magnetic resonance; Mathematics; Statistics; Magnetic resonance imaging; Engineering","score_opus":0.041512890690050215,"score_gpt":0.3459751873676657,"score_spread":0.3044622966776155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127043227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9152184,0.009323729,0.06774488,0.003581017,0.0007571283,0.0029260805,0.000042898657,0.00011350244,0.00029233744],"genre_scores_gemma":[0.857117,0.06802436,0.05830036,0.0013296375,0.0013416063,0.0022616908,0.0042683193,0.00021267321,0.0071443478],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99860036,0.000030864492,0.00050433225,0.00048794973,0.00021573534,0.0001607767],"domain_scores_gemma":[0.9990089,0.00013842588,0.00023351911,0.00039745073,0.00016205019,0.000059668353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001812446,0.00019532941,0.00056669104,0.00018315708,0.000036211848,0.0000073724814,0.00008608426,0.00014207578,0.0000612995],"category_scores_gemma":[0.0003508021,0.00017921081,0.000045188393,0.0002097394,0.00013505935,0.000032273463,0.00016049697,0.00036515872,4.6225185e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022655501,0.00026764077,0.017818127,0.0012605706,0.000005251359,0.000012870952,0.0005466722,0.000042754404,0.24425495,0.000020757261,0.00089778623,0.7346461],"study_design_scores_gemma":[0.007466695,0.002110427,0.4647587,0.029358624,0.00045690473,0.00014047277,0.00017548517,0.37277716,0.018695036,0.0010506617,0.10221344,0.0007963898],"about_ca_topic_score_codex":0.000046800684,"about_ca_topic_score_gemma":0.0000022447348,"teacher_disagreement_score":0.7338497,"about_ca_system_score_codex":0.00004762646,"about_ca_system_score_gemma":0.000052913954,"threshold_uncertainty_score":0.73080045},"labels":[],"label_agreement":null},{"id":"W3127196273","doi":"10.21203/rs.3.rs-151934/v1","title":"Regional cerebral blood flow decline can predict atrophy in Alzheimer’s disease spectrum","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Cerebral blood flow; Atrophy; Dementia; Cardiology; Psychology; Medicine; Internal medicine; Neuroscience; Neurodegeneration; Alzheimer's disease; Biomarker; Cerebral atrophy; Pathology; Disease; Biology","score_opus":0.1582735723650386,"score_gpt":0.4389821395994455,"score_spread":0.28070856723440685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127196273","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75435567,0.018386517,0.004447805,0.20688756,0.0003154892,0.010211851,0.0018734619,0.0013319693,0.002189685],"genre_scores_gemma":[0.9787738,0.0023234999,0.013848785,0.00048204928,0.0008271975,0.0010502414,0.0022849173,0.00011666837,0.00029289702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99603844,0.000246604,0.00045446816,0.0011650142,0.0013094111,0.0007860787],"domain_scores_gemma":[0.9970545,0.00017755316,0.00008870228,0.001654057,0.00036386514,0.00066129485],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00046343493,0.0003282335,0.00050672947,0.00052626076,0.0001561497,0.00009446785,0.00047354618,0.00021507818,0.00022179077],"category_scores_gemma":[0.00033998344,0.0003249872,0.0002911133,0.0007033018,0.00028441718,0.000051770377,0.0017155866,0.0028926108,0.000012892384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034331856,0.012972848,0.8419715,0.007560106,0.0013488333,0.023904266,0.0012351811,0.0054248907,0.0024921873,0.011320522,0.0588286,0.02950788],"study_design_scores_gemma":[0.0069640507,0.0014076208,0.81117386,0.0116978595,0.0011187487,0.0004063221,0.00045745986,0.037562706,0.0043300353,0.080211975,0.042682905,0.0019864817],"about_ca_topic_score_codex":0.00048593013,"about_ca_topic_score_gemma":0.00022609683,"teacher_disagreement_score":0.22441807,"about_ca_system_score_codex":0.00021970253,"about_ca_system_score_gemma":0.0015180378,"threshold_uncertainty_score":0.9999202},"labels":[],"label_agreement":null},{"id":"W3127414577","doi":"10.1093/neuonc/noab017","title":"Longitudinal change in fine motor skills after brain radiotherapy and in vivo imaging biomarkers associated with decline","year":2021,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; University of California, San Diego; National Cancer Institute; National Institutes of Health; Centre Technologique des Résidus Industriels; American Cancer Society; U.S. Department of Veterans Affairs; Moores Cancer Center, UC San Diego Health; Georgia Clinical and Translational Science Alliance","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Medicine; Nuclear medicine; Motor cortex; Precentral gyrus; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.03285513162950509,"score_gpt":0.3542082188403241,"score_spread":0.321353087210819,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127414577","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9547143,0.0006281168,0.00063915784,0.043103322,0.00004550822,0.0005938971,0.000021310861,0.00009089307,0.00016349788],"genre_scores_gemma":[0.9774553,0.00043227946,0.007403956,0.014159629,0.000080142956,0.0003511695,0.000017528748,0.000044502875,0.00005549321],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883014,0.00010840979,0.00024304366,0.0004342191,0.00010121029,0.00028295282],"domain_scores_gemma":[0.99913615,0.00041693947,0.000082505045,0.00022550893,0.00005335452,0.00008556458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015964815,0.00015362767,0.00035439656,0.000184538,0.000025848713,0.000009821026,0.00005722018,0.00007487006,0.00008026465],"category_scores_gemma":[0.00023404579,0.00014186383,0.000032110416,0.00046443325,0.000120378514,0.00007414561,0.000067058325,0.00028370583,7.661225e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044129646,0.00052864774,0.72969854,0.000016031601,0.000015710017,0.0032330675,0.00016000832,0.000001425049,0.2459522,0.000018338487,0.0004971152,0.019437637],"study_design_scores_gemma":[0.0052696653,0.00060869934,0.9390067,0.00016837394,0.00003248292,0.0009075764,0.000022574892,0.0015823018,0.009026295,0.00015877638,0.042995088,0.0002214666],"about_ca_topic_score_codex":0.00004188868,"about_ca_topic_score_gemma":0.0007949565,"teacher_disagreement_score":0.23692591,"about_ca_system_score_codex":0.00020112064,"about_ca_system_score_gemma":0.000090786794,"threshold_uncertainty_score":0.5785039},"labels":[],"label_agreement":null},{"id":"W3127794038","doi":"10.1007/s10143-021-01489-2","title":"The corticotegmental connectivity as an integral component of the descending extrapyramidal pathway: novel and direct structural evidence stemming from focused fiber dissections","year":2021,"lang":"en","type":"article","venue":"Neurosurgical Review","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Neuroscience; Anatomy; Internal capsule; White matter; Supplementary motor area; Medicine; Primary motor cortex; Motor cortex; Psychology; Magnetic resonance imaging; Functional magnetic resonance imaging","score_opus":0.1187212393359757,"score_gpt":0.380482071698672,"score_spread":0.2617608323626963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127794038","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983403,0.012097491,0.0005048434,0.002911801,0.000109662426,0.00071630167,0.000041090956,0.000070244845,0.00014553276],"genre_scores_gemma":[0.98922735,0.009182809,0.00093690056,0.0004790921,0.000035321067,0.000046082296,0.0000075803187,0.000016618495,0.000068228466],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99871683,0.00017164365,0.00035104656,0.00035498606,0.00024307313,0.00016241036],"domain_scores_gemma":[0.9983264,0.0008318837,0.00015821177,0.0005001426,0.00007456453,0.00010875841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014854925,0.00014765927,0.0003394689,0.000010011614,0.000304238,0.000037338,0.00013193085,0.00002937956,0.000045268942],"category_scores_gemma":[0.0006356365,0.000082123304,0.00015497838,0.00022807968,0.000236576,0.00009765109,0.00013293733,0.00032879578,0.0000011430421],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020490181,0.0005142468,0.025052713,0.00090322783,0.000072315575,0.00011189704,0.00009860475,0.0000065809313,0.7003292,0.008892094,0.00011242253,0.26370183],"study_design_scores_gemma":[0.002457548,0.0008924282,0.66189736,0.024914542,0.0010811887,0.0033759528,0.00014135442,0.004711275,0.19986485,0.0027806298,0.096955374,0.0009275175],"about_ca_topic_score_codex":0.00004509733,"about_ca_topic_score_gemma":0.000012284187,"teacher_disagreement_score":0.63684464,"about_ca_system_score_codex":0.00003863798,"about_ca_system_score_gemma":0.000057398058,"threshold_uncertainty_score":0.3348891},"labels":[],"label_agreement":null},{"id":"W3128247838","doi":"10.1038/s41398-021-01222-z","title":"Integrity of the uncinate fasciculus is associated with the onset of bipolar disorder: a 6-year followed-up study","year":2021,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Brain and Cognition Discovery Foundation; University Health Network","funders":"National Natural Science Foundation of China","keywords":"Bipolar disorder; Uncinate fasciculus; Psychology; Psychiatry; Fasciculus; Schizophrenia (object-oriented programming); Research integrity; Medicine; Clinical psychology; Diffusion MRI; Magnetic resonance imaging; Cognition","score_opus":0.03653144571639505,"score_gpt":0.3266151584246547,"score_spread":0.29008371270825967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128247838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9624238,0.00053298083,0.0029928032,0.032900795,0.000075857635,0.0006110798,0.0001467339,0.000039221577,0.00027675592],"genre_scores_gemma":[0.99733806,0.000017117598,0.001890619,0.0004343805,0.000017091972,0.000022964,0.00002282588,0.000014456861,0.00024247362],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990883,0.000069399626,0.0002207468,0.00017816693,0.00034928723,0.00009408365],"domain_scores_gemma":[0.9991792,0.00008188721,0.00012627887,0.00039014223,0.00019795947,0.00002454799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014807272,0.000097956065,0.00018014935,0.000025883608,0.0001052752,0.0000039100437,0.00013519179,0.0000377515,0.00004568452],"category_scores_gemma":[0.000027391035,0.000054510147,0.00012645939,0.00052866526,0.00011400931,0.00002924911,0.00001727718,0.00029131057,8.678896e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011726397,0.001241671,0.99005497,0.00003432405,0.00017448311,0.00000112769,0.0007129822,0.000027088643,0.0005408093,0.0049383347,0.0015807649,0.0005762011],"study_design_scores_gemma":[0.0019439433,0.00021553668,0.98656684,0.00012915193,0.00031272523,0.000016441,0.00084343785,0.00016693193,0.0010343079,0.0061328444,0.0025393474,0.00009849882],"about_ca_topic_score_codex":0.000032592685,"about_ca_topic_score_gemma":0.0002756565,"teacher_disagreement_score":0.0349143,"about_ca_system_score_codex":0.000009718855,"about_ca_system_score_gemma":0.00025702114,"threshold_uncertainty_score":0.22228593},"labels":[],"label_agreement":null},{"id":"W3128346820","doi":"10.1016/j.neurobiolaging.2020.12.020","title":"Orthogonal moment diffusion tensor decomposition reveals age-related degeneration patterns in complex fiber architecture","year":2021,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institute on Aging; National Institutes of Health","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; White matter; Tensor (intrinsic definition); Computer science; Nuclear magnetic resonance; Neuroscience; Mathematics; Physics; Psychology; Medicine; Magnetic resonance imaging; Optics; Pure mathematics; Radiology","score_opus":0.04822668176364864,"score_gpt":0.3458820593126448,"score_spread":0.2976553775489962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128346820","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914193,0.000030642008,0.0041588065,0.0037504374,0.000031876556,0.00024012137,0.000017509763,0.000067527064,0.0002837345],"genre_scores_gemma":[0.986029,0.00005219045,0.012417617,0.0008423327,0.000028836188,0.000021914975,0.0004382659,0.000012840302,0.00015699395],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99910474,0.00008898899,0.00030132773,0.0002914838,0.000060810577,0.00015263457],"domain_scores_gemma":[0.99954367,0.000052611584,0.00009824507,0.00021385557,0.000055032746,0.000036606372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005522027,0.0001064159,0.00022510465,0.00010538704,0.000049328013,0.0000040242853,0.000047406033,0.000060780098,0.00007693527],"category_scores_gemma":[0.000012073503,0.00009971984,0.000058433736,0.00015753986,0.00005548916,0.000020636015,0.00004498935,0.00023017137,0.0000027805754],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018510564,0.00014484774,0.05387563,0.00004238243,0.0000073190777,0.0000461107,0.000063191845,0.0004341783,0.940851,0.0003666275,0.00012491422,0.004025328],"study_design_scores_gemma":[0.0009162796,0.00014057056,0.87214786,0.00017740949,0.000035621022,0.00030279256,0.00001111736,0.00036199205,0.123485155,0.0011312099,0.0011537338,0.0001362822],"about_ca_topic_score_codex":0.000005354485,"about_ca_topic_score_gemma":0.000005822963,"teacher_disagreement_score":0.81827223,"about_ca_system_score_codex":0.000025585368,"about_ca_system_score_gemma":0.00001647109,"threshold_uncertainty_score":0.40664572},"labels":[],"label_agreement":null},{"id":"W3128914311","doi":"10.1038/s41598-021-82187-3","title":"Elucidating the complex organization of neural micro-domains in the locust Schistocerca gregaria using dMRI","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"","keywords":"Desert locust; Locust; Kurtosis; Schistocerca; Diffusion MRI; Fractional anisotropy; Computer science; Neuroscience; Magnetic resonance imaging; Artificial intelligence; Neuroimaging; Functional magnetic resonance imaging; Biology; Biological system; Pattern recognition (psychology); Nuclear magnetic resonance; Physics; Medicine; Mathematics; Ecology; Radiology","score_opus":0.08739159166132505,"score_gpt":0.35022054871930064,"score_spread":0.2628289570579756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3128914311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.980699,0.00006471039,0.014726852,0.0029301269,0.00036387256,0.0004900541,0.000002218058,0.000052057047,0.00067108823],"genre_scores_gemma":[0.9874614,0.0000021641747,0.01196438,0.00025760653,0.00003515209,0.00000637887,0.00006607642,0.000013138781,0.00019368927],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884,0.000053406613,0.0003737172,0.00033247404,0.0002619775,0.00013847898],"domain_scores_gemma":[0.9985679,0.00004384417,0.00024469878,0.000861163,0.0002582277,0.00002421646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056713686,0.00007469047,0.0001249145,0.000060715854,0.00033220876,0.00006999755,0.000111495436,0.000022241717,0.000044973884],"category_scores_gemma":[0.0003326096,0.000047958663,0.000040217987,0.0012738724,0.00024158094,0.00006458328,0.000076850934,0.00014635756,0.0000010382581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020513617,0.00009623861,0.026162678,0.000026378992,0.000004029495,0.00022695806,0.0005009686,0.0002224462,0.96847045,0.0006726446,0.002856385,0.0007587448],"study_design_scores_gemma":[0.00071209896,0.000047792968,0.1324813,0.00035831737,0.00021876945,0.014879729,0.0023362362,0.0149119785,0.76401114,0.013282974,0.056327146,0.0004325001],"about_ca_topic_score_codex":0.000026426971,"about_ca_topic_score_gemma":0.00001023876,"teacher_disagreement_score":0.20445932,"about_ca_system_score_codex":0.000042421376,"about_ca_system_score_gemma":0.00013374942,"threshold_uncertainty_score":0.2555115},"labels":[],"label_agreement":null},{"id":"W3129666823","doi":"10.1089/brain.2020.0939","title":"Impaired Structural Connectivity in Parkinson's Disease Patients with Mild Cognitive Impairment: A Study Based on Probabilistic Tractography","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Diffusion MRI; Fractional anisotropy; Connectome; Connectomics; Parkinson's disease; Neuroscience; Psychology; White matter; Magnetic resonance imaging; Artificial intelligence; Pathology; Medicine; Functional connectivity; Disease; Computer science; Radiology","score_opus":0.03133652534068452,"score_gpt":0.3133172704049345,"score_spread":0.28198074506424997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129666823","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99272877,0.000013590683,0.0013633528,0.0016192993,0.000030598985,0.0036930575,0.00021142136,0.00024476624,0.00009515679],"genre_scores_gemma":[0.9974533,7.6925835e-7,0.00046688842,0.0012001239,0.000027772297,0.00068243255,0.0001149123,0.000044454016,0.000009399265],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977821,0.00032826886,0.00023789678,0.0009028857,0.00038413182,0.0003647107],"domain_scores_gemma":[0.99754333,0.0012518554,0.00013021281,0.0005656938,0.00025019064,0.00025869368],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022413817,0.00031911,0.0004351056,0.00019037415,0.00016138545,0.000033398665,0.00008108715,0.00005153122,0.000035432175],"category_scores_gemma":[0.0011018162,0.00027372254,0.00012820982,0.000824413,0.00013818158,0.00013113937,0.000048376754,0.00039353393,0.0000017757402],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025303322,0.0061406824,0.9885289,0.00007125861,0.000036289523,0.00027320415,0.00014034707,0.000096359036,0.00003923313,0.00008875409,0.000046852565,0.002007807],"study_design_scores_gemma":[0.008108386,0.0016359199,0.9852416,0.00022963432,0.00010539848,0.0000063110983,0.00012336936,0.0031138414,0.00020997401,0.0008401706,0.000078188474,0.00030720138],"about_ca_topic_score_codex":0.00004970794,"about_ca_topic_score_gemma":0.00020976696,"teacher_disagreement_score":0.005578054,"about_ca_system_score_codex":0.00014825877,"about_ca_system_score_gemma":0.0002478164,"threshold_uncertainty_score":0.9999715},"labels":[],"label_agreement":null},{"id":"W3129895777","doi":"10.1007/s00429-020-02190-8","title":"Mapping the living mouse brain neural architecture: strain-specific patterns of brain structural and functional connectivity","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"National Institute on Alcohol Abuse and Alcoholism; Erasmus+","keywords":"Neuroscience; Corpus callosum; Splenium; Forebrain; Connectome; Biology; Diffusion MRI; Brain mapping; Resting state fMRI; Human Connectome Project; Functional magnetic resonance imaging; Brain morphometry; Psychology; Functional connectivity; Magnetic resonance imaging; Medicine; Central nervous system","score_opus":0.04202876236868999,"score_gpt":0.2736536775241867,"score_spread":0.23162491515549669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129895777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9064888,0.00042469506,0.075593606,0.01679057,0.00012460747,0.00031645465,0.0001258332,0.00009379596,0.000041653646],"genre_scores_gemma":[0.99388003,0.00002779874,0.0012265252,0.004162182,0.00028140983,0.000013346007,0.00010015387,0.000025515403,0.00028303126],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988108,0.000105024264,0.00024130465,0.0004397716,0.00019854472,0.00020450131],"domain_scores_gemma":[0.99867535,0.000695435,0.00012491326,0.00032503094,0.000094476265,0.000084768435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014008452,0.00020451708,0.00024735945,0.000086104774,0.00026523712,0.000045510464,0.000046861234,0.000091196074,0.00010739297],"category_scores_gemma":[0.0002144906,0.0001525079,0.00007332147,0.0002224301,0.00012907313,0.00010894563,0.0000910207,0.00042229137,2.0483566e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018145965,0.000035239522,0.045138445,0.00021656473,0.00009908804,0.000016648335,0.0009956196,0.00018268294,0.77845985,0.013526413,0.002967678,0.15818031],"study_design_scores_gemma":[0.0007124186,0.00015580002,0.96877927,0.00007557242,0.000032849504,0.0010348652,0.0006072108,0.0007840067,0.005053707,0.007859873,0.014684097,0.00022033234],"about_ca_topic_score_codex":0.00001279968,"about_ca_topic_score_gemma":0.000027333557,"teacher_disagreement_score":0.92364085,"about_ca_system_score_codex":0.000020736814,"about_ca_system_score_gemma":0.000032712516,"threshold_uncertainty_score":0.62190914},"labels":[],"label_agreement":null},{"id":"W3130159341","doi":"10.5167/uzh-44356","title":"Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: an update","year":2010,"lang":"en","type":"article","venue":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Frontotemporal lobar degeneration; Nosology; Nomenclature; Frontotemporal dementia; Degeneration (medical); Neuroscience; Medicine; Psychology; Pathology; Dementia; Disease; Biology; Taxonomy (biology)","score_opus":0.0933618304806381,"score_gpt":0.3342238781920364,"score_spread":0.2408620477113983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130159341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9724345,0.00009143834,0.018620213,0.007298149,0.000035276444,0.000590741,0.0002991781,0.00004262398,0.00058788504],"genre_scores_gemma":[0.9301117,0.00071405707,0.06768093,0.000026707829,0.000027793898,2.1627786e-8,0.000107404834,0.000009674566,0.0013216966],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99883676,0.0001476267,0.00012677794,0.0003640988,0.0002775422,0.0002472127],"domain_scores_gemma":[0.9981751,0.00018083371,0.0002434833,0.00057467,0.0006729174,0.00015300784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004609213,0.0001353043,0.00041848308,0.0003092536,0.000467684,0.000003502272,0.0006681704,0.00023167467,0.00014208903],"category_scores_gemma":[0.00004820009,0.00015362655,0.00015314927,0.00039370867,0.0018804,0.00021282531,0.00040164834,0.00063840934,0.0000012735364],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.014305482,0.0055787307,0.1335336,0.0019117214,0.00063582987,0.0004992888,0.022651024,0.0006356534,0.72407824,0.05136894,0.015934542,0.028866924],"study_design_scores_gemma":[0.026479743,0.016414333,0.47768492,0.00086679397,0.0024771178,0.00039284886,0.14908573,0.031794235,0.015079283,0.008627657,0.26897582,0.0021215274],"about_ca_topic_score_codex":0.0008877049,"about_ca_topic_score_gemma":0.00190771,"teacher_disagreement_score":0.708999,"about_ca_system_score_codex":0.000029974513,"about_ca_system_score_gemma":0.0001740049,"threshold_uncertainty_score":0.69284123},"labels":[],"label_agreement":null},{"id":"W3130233450","doi":"10.1016/j.nicl.2021.102587","title":"Disruption of brainstem monoaminergic fibre tracts in multiple sclerosis as a putative mechanism for cognitive fatigue: a fixel-based analysis","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Wellcome Trust","keywords":"Monoaminergic; Locus coeruleus; Brainstem; Neuroscience; Ventral tegmental area; White matter; Prefrontal cortex; Diffusion MRI; Dopaminergic; Serotonergic; Psychology; Anatomy; Biology; Dopamine; Medicine; Central nervous system; Internal medicine; Serotonin; Cognition; Magnetic resonance imaging","score_opus":0.3259403742709406,"score_gpt":0.4623823037733691,"score_spread":0.1364419295024285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130233450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.76606756,0.000020625039,0.2308748,0.0017590967,0.000032197677,0.00083059806,0.00019896614,0.00009046106,0.00012568118],"genre_scores_gemma":[0.9726685,0.00006685597,0.024698708,0.0018075489,0.000042283755,0.00025302902,0.00033143253,0.000037709837,0.00009388926],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99780214,0.00018406159,0.0008469098,0.0007188521,0.0002117333,0.00023632981],"domain_scores_gemma":[0.9960317,0.0026086408,0.00031449422,0.00041294203,0.0004851958,0.00014700902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002774805,0.00019319121,0.0006951138,0.00021510229,0.000059273087,0.000016182345,0.000094050185,0.00012693575,0.000018088778],"category_scores_gemma":[0.004331086,0.0001932621,0.00054055895,0.0010418075,0.00015920927,0.00009386552,0.00005063104,0.00034866156,0.0000035451442],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0070570377,0.017398568,0.38672695,0.0012195196,0.0014429159,0.0014484486,0.0010805773,0.002046205,0.46870163,0.009995256,0.0005888473,0.102294065],"study_design_scores_gemma":[0.0130721545,0.0022612624,0.60519433,0.00060313876,0.0022953455,0.000036131605,0.0004660509,0.19121088,0.17901415,0.005118875,0.00020151227,0.00052619906],"about_ca_topic_score_codex":0.0000110690735,"about_ca_topic_score_gemma":0.000019259693,"teacher_disagreement_score":0.28968748,"about_ca_system_score_codex":0.000028656756,"about_ca_system_score_gemma":0.00015586965,"threshold_uncertainty_score":0.78809994},"labels":[],"label_agreement":null},{"id":"W3130324448","doi":"10.1101/2021.02.13.431081","title":"Characterizing white matter alterations in drug-naïve de novo Parkinson’s disease with diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Canadian Institutes of Health Research; Sanofi Genzyme; Genentech; H. Lundbeck A/S; Teva Pharmaceutical Industries; Sanofi; Biogen; GlaxoSmithKline; Servier; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; Michael J. Fox Foundation for Parkinson's Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Disease; Neuroscience; Parkinson's disease; Medicine; Laterality; Psychology; Neuroimaging; Magnetic resonance imaging; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.018291322791883106,"score_gpt":0.25894241843590715,"score_spread":0.24065109564402404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130324448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9729929,0.0002177107,0.019208366,0.0056896154,0.00012461045,0.0011790578,0.00014530413,0.00042058065,0.000021853122],"genre_scores_gemma":[0.947962,0.00034541337,0.04800022,0.0022667598,0.0002480536,0.0009837227,0.0000056522067,0.00015624361,0.000031921285],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99760336,0.00008017373,0.00045972868,0.0010608933,0.0002873778,0.00050845783],"domain_scores_gemma":[0.99758,0.000033633987,0.0002614156,0.0014596711,0.0002570875,0.00040822173],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017995344,0.00047145446,0.00052133296,0.00028880837,0.0001454664,0.00018917453,0.00025075747,0.00016973593,0.00008145253],"category_scores_gemma":[0.000044763492,0.00047259525,0.00011760482,0.00047548034,0.00009052091,0.00016659588,0.0003519843,0.00095124665,0.000021357955],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000123061,0.0005294678,0.6522409,0.0005748925,0.00004081872,0.0007378199,0.00005370731,0.00006164646,0.3452171,0.00013034129,0.00028788912,0.0000024061178],"study_design_scores_gemma":[0.0006181315,0.000020955977,0.95543903,0.0019844815,0.00015010776,3.5240464e-7,0.0000069399734,0.0008039608,0.033072826,0.000002722699,0.0073338244,0.00056669227],"about_ca_topic_score_codex":0.00003684835,"about_ca_topic_score_gemma":0.0000074806,"teacher_disagreement_score":0.31214428,"about_ca_system_score_codex":0.00036534198,"about_ca_system_score_gemma":0.0006173915,"threshold_uncertainty_score":0.99977255},"labels":[],"label_agreement":null},{"id":"W3130351912","doi":"10.1007/978-3-030-56215-1_7","title":"Challenges for Tractogram Filtering","year":2021,"lang":"en","type":"book-chapter","venue":"Mathematics and visualization","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; VINNOVA; National Institutes of Health; Université de Sherbrooke","keywords":"Tractography; Perspective (graphical); Computer science; Streamlines, streaklines, and pathlines; Field (mathematics); Artificial intelligence; Diffusion MRI; Mathematics; Engineering; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.24558234345467547,"score_gpt":0.4255824634097051,"score_spread":0.18000011995502965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3130351912","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00005530209,0.0026531003,0.8126372,0.00072032725,0.00004271979,0.001282277,0.000045082572,0.0002721079,0.1822919],"genre_scores_gemma":[0.0044047665,0.04819258,0.5281136,0.00071736105,0.00070840045,0.0005361251,0.0018027868,0.00053990557,0.4149845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99943936,0.0000011054756,0.00019589665,0.00020724656,0.00008216351,0.000074228665],"domain_scores_gemma":[0.999497,0.000049816543,0.00011951269,0.00020001477,0.000092638475,0.000041022606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005190097,0.00013744514,0.00025068113,0.000055364966,0.00004817474,0.000020489044,0.000025406713,0.00010838069,0.000027742186],"category_scores_gemma":[0.00002854431,0.00013138098,0.00006391344,0.0000123116515,0.00002136227,0.000019633504,0.00002551948,0.00006634841,0.0000013750742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000028920529,0.000048420494,6.601204e-7,0.0012730046,0.00002100676,0.0000022364827,0.00010619504,2.9230074e-7,0.00052682625,0.9683123,0.00027091178,0.029435212],"study_design_scores_gemma":[0.00046961152,0.00024669018,0.000021816515,0.0020442577,0.00034724383,0.00013664612,0.00006107892,0.008005694,0.0015254465,0.21051498,0.7762486,0.00037793658],"about_ca_topic_score_codex":1.285725e-7,"about_ca_topic_score_gemma":5.78438e-7,"teacher_disagreement_score":0.7759777,"about_ca_system_score_codex":0.000012308477,"about_ca_system_score_gemma":0.000013128633,"threshold_uncertainty_score":0.53575605},"labels":[],"label_agreement":null},{"id":"W3131390801","doi":"10.1101/2021.02.19.432024","title":"Structural connectome fingerprinting and age prediction in pediatric development: assessing voxel- and surface-based white matter connectivity","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Connectome; Voxel; Connectomics; Computer science; Tractography; White matter; Human Connectome Project; Artificial intelligence; Pattern recognition (psychology); Representation (politics); Functional connectivity; Neuroscience; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.031631753544426267,"score_gpt":0.27295943503408027,"score_spread":0.241327681489654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3131390801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917932,0.00048145064,0.006143492,0.00033188073,0.00014112133,0.0007214739,0.000030090225,0.00034921055,0.000008040962],"genre_scores_gemma":[0.93567765,0.000079528596,0.06373292,0.00021773271,0.00011367341,0.00009014991,0.0000019117028,0.000084043204,0.0000023776126],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977812,0.000089929745,0.00049184647,0.0010331006,0.00022240517,0.00038149266],"domain_scores_gemma":[0.9986372,0.00011729343,0.00030348293,0.00056401506,0.0001977116,0.0001803038],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003817307,0.0004154955,0.0005789873,0.00027422165,0.00018253272,0.00028097632,0.00010881147,0.00028949347,0.000019898845],"category_scores_gemma":[0.00014457773,0.00046515444,0.00005107165,0.00042682703,0.00009707758,0.00020430845,0.00036155878,0.0009011734,0.0000019959366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012324691,0.000046789602,0.91951936,0.0008429553,0.000017655735,0.00008974261,0.000021323383,0.00009192843,0.07932536,0.000014542827,0.000010674493,0.000007356622],"study_design_scores_gemma":[0.0006271919,0.000014386893,0.96874845,0.0005673759,0.000088068075,3.0054122e-7,0.0000046179143,0.0034543262,0.026034184,0.00000239225,0.000065846405,0.00039284464],"about_ca_topic_score_codex":0.00001843392,"about_ca_topic_score_gemma":0.0000030837496,"teacher_disagreement_score":0.057589434,"about_ca_system_score_codex":0.00020320652,"about_ca_system_score_gemma":0.00039917452,"threshold_uncertainty_score":0.99978},"labels":[],"label_agreement":null},{"id":"W3132247007","doi":"10.1089/neur.2020.0035","title":"Changes in White Matter of the Cervical Spinal Cord after a Single Season of Collegiate Football","year":2021,"lang":"en","type":"article","venue":"Neurotrauma Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Spinal cord; Diffusion MRI; Concussion; Spinal cord injury; Medicine; Poison control; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.06885494946166848,"score_gpt":0.3379647180896366,"score_spread":0.2691097686279681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132247007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901968,0.00006083551,0.00009457707,0.006922382,0.00007286532,0.00039133712,0.0000060517978,0.000026670468,0.0022284405],"genre_scores_gemma":[0.99679166,0.000014594558,0.0013404374,0.0012062023,0.000027433214,0.00007479996,0.0000024480341,0.000020816688,0.0005216297],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902314,0.000031641892,0.00032568772,0.00027172433,0.00020633543,0.00014147925],"domain_scores_gemma":[0.9990337,0.00001468523,0.0002027794,0.00059729133,0.00010770208,0.000043845535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005743255,0.000097215954,0.00023475,0.000045560922,0.00001585847,0.0000045875377,0.000055385448,0.000042387,0.00011752844],"category_scores_gemma":[0.000041571067,0.00007656079,0.000085507716,0.0003282844,0.00007436723,0.000022022947,0.000091810485,0.00016170208,9.3926644e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002840215,0.0004398965,0.9244578,0.00022010597,0.00000669774,0.0013306198,0.000042234544,0.0000036672175,0.07065863,0.000035733305,0.00060131616,0.0019192719],"study_design_scores_gemma":[0.00018279176,0.00023191633,0.8988022,0.00024048895,0.00002805651,0.0013402217,0.000009701395,0.000011707644,0.09379852,0.00026195557,0.0050333166,0.000059108694],"about_ca_topic_score_codex":0.000008896681,"about_ca_topic_score_gemma":0.000044735458,"teacher_disagreement_score":0.02565559,"about_ca_system_score_codex":0.000020552341,"about_ca_system_score_gemma":0.000047194277,"threshold_uncertainty_score":0.31220585},"labels":[],"label_agreement":null},{"id":"W3132513078","doi":"10.1101/2021.02.24.432740","title":"Evaluating the reliability of human brain white matter tractometry","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"NIH Blueprint for Neuroscience Research; National Institutes of Health; Washington Research Foundation; Alfred P. Sloan Foundation; University of Washington; McDonnell Center for Systems Neuroscience; Gordon and Betty Moore Foundation","keywords":"Human Connectome Project; Reliability (semiconductor); Computer science; Robustness (evolution); White matter; Reproducibility; Neuroimaging; Reliability engineering; Psychology; Data science; Functional connectivity; Statistics; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.07024448435956597,"score_gpt":0.366954333194649,"score_spread":0.296709848835083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3132513078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98961425,0.0002460124,0.003838394,0.004618187,0.00014462878,0.0011290772,0.00007239045,0.00029979186,0.00003724046],"genre_scores_gemma":[0.9593239,0.000032877415,0.03885971,0.0011624042,0.00019058137,0.0002992358,9.1371606e-7,0.00010616242,0.00002425735],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99742365,0.00017537628,0.0006954744,0.00089756097,0.00047576625,0.00033218108],"domain_scores_gemma":[0.99576515,0.00017529125,0.0005411092,0.0026694376,0.0007120823,0.00013693071],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010652915,0.0003684896,0.000615205,0.00015912445,0.00017098541,0.00007376573,0.00043838468,0.00027936898,0.00018520541],"category_scores_gemma":[0.0005370014,0.00031019194,0.00025335982,0.00061580446,0.000228641,0.00007937128,0.0005173242,0.0012110824,0.000012329924],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016165772,0.00023342429,0.1005391,0.00063855853,0.000042177522,0.000011772566,0.000013359627,0.00003915692,0.89766544,0.00010738102,0.0006901704,0.0000033078197],"study_design_scores_gemma":[0.00034357965,0.00011502629,0.80349135,0.0006880949,0.0002209413,8.15809e-8,0.0000060773623,0.00044384162,0.19360015,0.00001450652,0.00072093675,0.00035540696],"about_ca_topic_score_codex":0.000022015789,"about_ca_topic_score_gemma":3.1628844e-7,"teacher_disagreement_score":0.70406526,"about_ca_system_score_codex":0.00015692951,"about_ca_system_score_gemma":0.00034118077,"threshold_uncertainty_score":0.99993503},"labels":[],"label_agreement":null},{"id":"W3133182125","doi":"10.3389/fnhum.2021.641616","title":"Stable Anatomy Detection in Multimodal Imaging Through Sparse Group Regularization: A Comparative Study of Iron Accumulation in the Aging Brain","year":2021,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; McGill University; University of Alberta","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Interpretability; Neuroimaging; Lasso (programming language); Modalities; Regularization (linguistics); Voxel; Artificial intelligence; Generalizability theory; Computer science; Pattern recognition (psychology); Machine learning; Mathematics; Psychology; Neuroscience; Statistics","score_opus":0.09828210427483391,"score_gpt":0.40152863449063597,"score_spread":0.30324653021580206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133182125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8111111,0.000042587646,0.18733191,0.00048610463,0.00008366634,0.0007787173,0.0000013246882,0.000030725805,0.00013384897],"genre_scores_gemma":[0.9936799,0.000008874144,0.0058201863,0.00035326142,0.00001336786,0.00007999661,0.0000062227923,0.000009424417,0.00002880522],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985626,0.00019840067,0.0003417486,0.00044250416,0.0002601345,0.0001946456],"domain_scores_gemma":[0.9993995,0.000052518924,0.0001247546,0.00036142668,0.00004244512,0.000019357716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030910413,0.00011000936,0.00021398628,0.00022105036,0.000126885,0.00003079494,0.00017596818,0.000021089405,0.0000014072627],"category_scores_gemma":[0.000096277334,0.000103642604,0.000022593973,0.0014990731,0.00013675212,0.0003759488,0.00006455763,0.00027980184,5.034239e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056877583,0.0019158308,0.83033305,0.0000527586,0.0000015245056,0.00018524112,0.01320806,0.023647219,0.12679213,0.0009809362,0.00016927996,0.0026571038],"study_design_scores_gemma":[0.0020694837,0.00018209856,0.77122784,0.000116540425,0.000011864944,0.00003176702,0.00779597,0.20176394,0.0123685505,0.0038742367,0.00038235012,0.00017537775],"about_ca_topic_score_codex":0.00012035847,"about_ca_topic_score_gemma":0.00020182229,"teacher_disagreement_score":0.18256876,"about_ca_system_score_codex":0.00009822094,"about_ca_system_score_gemma":0.00002631942,"threshold_uncertainty_score":0.4226423},"labels":[],"label_agreement":null},{"id":"W3133319420","doi":"10.1002/cjs.11588","title":"A Bayesian latent spatial model for mapping the cortical signature of progression to Alzheimer's disease","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Neuroimaging; Magnetic resonance imaging; Dementia; Alzheimer's Disease Neuroimaging Initiative; Neuroscience; Bayesian probability; Atrophy; Statistical power; Disease; Computer science; Medicine; Psychology; Artificial intelligence; Pathology; Radiology; Mathematics","score_opus":0.10094646596468872,"score_gpt":0.34908440290176074,"score_spread":0.24813793693707203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133319420","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014886521,0.000348933,0.99099404,0.0063523627,0.00004412683,0.0002835419,0.0004700345,0.0000037062307,0.0000146255525],"genre_scores_gemma":[0.7043415,0.000012240965,0.29487297,0.00065528316,0.000058060992,0.000008787786,0.000016792044,0.00001114118,0.000023268582],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99940646,0.0000131678835,0.000243788,0.00007871325,0.00011856509,0.0001392989],"domain_scores_gemma":[0.9986956,0.000074376214,0.00011002737,0.0001376687,0.00042472672,0.0005576031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007334292,0.000061087936,0.0001374551,0.000056043118,0.00008579539,0.00001043857,0.0000726933,0.00002320892,0.000011964134],"category_scores_gemma":[0.00031399127,0.000044486787,0.000048768114,0.00009398556,0.000055731038,0.000016051446,0.000009044524,0.00017941759,1.9475127e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014096507,0.00076850853,0.042479828,0.0008995332,0.0007488453,0.0059096655,0.0050323266,0.030362552,0.02269812,0.16987467,0.23877315,0.48104316],"study_design_scores_gemma":[0.0016337307,0.00068592385,0.056529164,0.0013275794,0.0013042263,0.00044831162,0.0002455752,0.8605715,0.004300808,0.05040005,0.022180766,0.0003723884],"about_ca_topic_score_codex":0.000041168467,"about_ca_topic_score_gemma":0.0002970674,"teacher_disagreement_score":0.8302089,"about_ca_system_score_codex":0.000035320594,"about_ca_system_score_gemma":0.0011659841,"threshold_uncertainty_score":0.20684057},"labels":[],"label_agreement":null},{"id":"W3133409953","doi":"10.3389/fnagi.2021.637002","title":"Structural Network Efficiency Predicts Resilience to Cognitive Decline in Elderly at Risk for Alzheimer’s Disease","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Deutsche Forschungsgemeinschaft; Bundesministerium für Bildung und Forschung; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Janssen Alzheimer Immunotherapy Research And Development; European Commission; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Leibniz-Gemeinschaft; Alzheimer's Association","keywords":"Cognitive decline; Dementia; Cognition; Effects of sleep deprivation on cognitive performance; Psychological resilience; Psychology; Neuroscience; Alzheimer's disease; Internal medicine; Medicine; Disease; Gerontology","score_opus":0.040494512516950125,"score_gpt":0.3454419679452108,"score_spread":0.3049474554282607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133409953","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71159685,0.0007388205,0.2829687,0.0026488665,0.00060204155,0.0011797828,0.000067811576,0.00012226123,0.00007483045],"genre_scores_gemma":[0.94695085,0.00011954941,0.049285464,0.003184375,0.000068675385,0.00017169776,0.000013732669,0.000021765749,0.00018389149],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979835,0.00005754334,0.000298807,0.000844831,0.00028007454,0.000535232],"domain_scores_gemma":[0.999041,0.00014151265,0.00009266386,0.0003728418,0.00008455218,0.00026743734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022448045,0.00016568297,0.00023723661,0.00014837073,0.00023595273,0.0000323885,0.00025583067,0.000029454837,0.0000025947547],"category_scores_gemma":[0.0012863771,0.00016722735,0.00005693986,0.0013092152,0.00021720048,0.00012540848,0.0002402198,0.0002430378,0.0000012286778],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022863821,0.00008443269,0.97689027,0.000021177108,0.000001385697,0.00016320113,0.00012909941,0.00872899,0.0013141077,0.00008570674,0.0022477834,0.010105215],"study_design_scores_gemma":[0.0010815961,0.00021235438,0.8806272,0.00030002705,0.000053738793,0.000032394048,0.000052763156,0.10847088,0.0023559597,0.003076512,0.0034768144,0.00025975757],"about_ca_topic_score_codex":0.000010180126,"about_ca_topic_score_gemma":0.00001814274,"teacher_disagreement_score":0.23535398,"about_ca_system_score_codex":0.000081278566,"about_ca_system_score_gemma":0.00015066663,"threshold_uncertainty_score":0.68193334},"labels":[],"label_agreement":null},{"id":"W3134068182","doi":"10.1038/s41598-021-01773-7","title":"The trajectory of putative astroglial dysfunction in first episode schizophrenia: a longitudinal 7-Tesla MRS study","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; St Joseph's Health Care; Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Compute Canada; Schulich School of Medicine and Dentistry; Academic Medical Organization of Southwestern Ontario; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Medicine; Neuroscience; Longitudinal study; Psychiatry; Trajectory; Physical medicine and rehabilitation; Bioinformatics; Psychology; Biology; Pathology; Physics","score_opus":0.045310519100202104,"score_gpt":0.330401593415809,"score_spread":0.2850910743156069,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134068182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945668,0.00014735048,0.002656105,0.00066322763,0.00088308257,0.0006765824,0.0000033271094,0.000065712644,0.00033780336],"genre_scores_gemma":[0.9961839,0.0000059995773,0.002491194,0.000009048637,0.000039448405,0.000111441565,0.000021260807,0.000011505695,0.0011262113],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984078,0.000043780983,0.00045574253,0.000546028,0.00036344427,0.0001832361],"domain_scores_gemma":[0.99870634,0.00008412766,0.00022068406,0.00069641747,0.00023715004,0.00005527674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006804003,0.00009860032,0.00019119662,0.000097578246,0.00028451637,0.000048332346,0.00006205642,0.000025595862,0.00001381956],"category_scores_gemma":[0.00032076333,0.00007479164,0.00007811783,0.0007230516,0.000262914,0.000074375035,0.00006299686,0.00019458345,0.0000022610195],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033995087,0.0026847073,0.91747403,0.00007825993,0.000085290485,0.0034869574,0.0012525248,0.00055351615,0.052949622,0.000499172,0.006010833,0.01458513],"study_design_scores_gemma":[0.002146185,0.0005767828,0.8236011,0.00020521741,0.00020085965,0.0018546972,0.002248157,0.00077241374,0.13239567,0.0151596805,0.020497078,0.00034212336],"about_ca_topic_score_codex":0.000036712176,"about_ca_topic_score_gemma":0.00022572605,"teacher_disagreement_score":0.093872905,"about_ca_system_score_codex":0.00006000633,"about_ca_system_score_gemma":0.00014851161,"threshold_uncertainty_score":0.30499145},"labels":[],"label_agreement":null},{"id":"W3134107863","doi":"10.1016/j.neuroimage.2021.117919","title":"Structural alterations in cortical and thalamocortical white matter tracts after recovery from prefrontal cortex lesions in macaques","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Fondation Brain Canada","keywords":"White matter; Neuroscience; Lesion; Prefrontal cortex; Fractional anisotropy; Psychology; Cortex (anatomy); Superior longitudinal fasciculus; Diffusion MRI; Tractography; Medicine; Magnetic resonance imaging; Cognition","score_opus":0.03504598857505999,"score_gpt":0.31963753046350757,"score_spread":0.2845915418884476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134107863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943218,0.000085016676,0.00066492334,0.0033178383,0.000046150446,0.0003430528,0.00008208345,0.00006267754,0.0010764571],"genre_scores_gemma":[0.9877774,0.000067036424,0.0092196865,0.0022963996,0.000052561973,0.00009135357,0.00007723654,0.000029457648,0.000388847],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99872553,0.00006962056,0.00033453104,0.00049259217,0.00013241066,0.00024529512],"domain_scores_gemma":[0.99935573,0.00011644212,0.000034491313,0.00033892432,0.000031849762,0.00012254175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000028991526,0.00015583442,0.0002470865,0.00008562312,0.00004409625,0.000048562826,0.000051005118,0.00006799511,0.00046657506],"category_scores_gemma":[0.00007864124,0.00015062417,0.000049447863,0.00016778121,0.000097955344,0.00020489069,0.00009001243,0.00051875535,0.0000196606],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022916691,0.00032527742,0.9065959,0.000028478407,0.0000067516203,0.0020927647,0.00019835496,0.0000067411634,0.08770066,0.00020037347,0.00036804052,0.002247487],"study_design_scores_gemma":[0.0005603234,0.0000637346,0.99426544,0.00006651051,0.000022541311,0.00022682961,0.000028863442,0.0011260347,0.0018040307,0.0014415765,0.00026662607,0.00012748063],"about_ca_topic_score_codex":0.000036390877,"about_ca_topic_score_gemma":0.00015386392,"teacher_disagreement_score":0.08766954,"about_ca_system_score_codex":0.000039186794,"about_ca_system_score_gemma":0.000048703147,"threshold_uncertainty_score":0.61422753},"labels":[],"label_agreement":null},{"id":"W3134935651","doi":"10.3390/jpm11030174","title":"Mapping Brain Microstructure and Network Alterations in Depressive Patients with Suicide Attempts Using Generalized Q-Sampling MRI","year":2021,"lang":"en","type":"article","venue":"Journal of Personalized Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"Ministry of Science and Technology, Taiwan","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Major depressive disorder; Voxel; Magnetic resonance imaging; Internal medicine; Psychology; Medicine; Psychiatry; Mood; Radiology","score_opus":0.06340629866114098,"score_gpt":0.3641723758974253,"score_spread":0.30076607723628435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134935651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9074694,0.003003365,0.07954875,0.009567754,0.00007541741,0.00027520218,0.00000666123,0.000015480866,0.00003797723],"genre_scores_gemma":[0.6208209,0.0006281952,0.36906382,0.007974059,0.0011152878,0.000011539007,0.00008297693,0.000067764406,0.00023546898],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870735,0.00006352848,0.0004971775,0.0002168645,0.00029365811,0.00022140023],"domain_scores_gemma":[0.99872386,0.00015769141,0.00037344813,0.00016184103,0.00042541864,0.00015775455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020663945,0.0001625444,0.00052439945,0.00015859748,0.00011639668,0.00001539567,0.000058647893,0.00005553889,0.000054615415],"category_scores_gemma":[0.00022402764,0.00011719714,0.000054911474,0.0004098686,0.00014019803,0.0001088409,0.00003238908,0.000384351,1.1062921e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012667129,0.00026804235,0.68549466,0.00028040045,0.00029918877,0.00096958724,0.0036532008,0.002704831,0.29612643,0.0007700361,0.0046749315,0.0034919693],"study_design_scores_gemma":[0.06429378,0.0014062307,0.8327379,0.017307745,0.0011061346,0.011259467,0.0025012232,0.0067266193,0.005495796,0.006516606,0.049525015,0.0011234547],"about_ca_topic_score_codex":0.000018867551,"about_ca_topic_score_gemma":0.000009967017,"teacher_disagreement_score":0.29063064,"about_ca_system_score_codex":0.00008353194,"about_ca_system_score_gemma":0.00014165179,"threshold_uncertainty_score":0.47791606},"labels":[],"label_agreement":null},{"id":"W3135033332","doi":"10.1101/2021.03.09.434656","title":"Structural connectome quantifies tumor invasion and predicts survival in glioblastoma patients","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Engineering and Physical Sciences Research Council; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Glioblastoma; Connectome; Overall survival; Computer science; Functional connectivity; Medicine; Biology; Neuroscience; Oncology; Cancer research","score_opus":0.034687329390828775,"score_gpt":0.27299088888515644,"score_spread":0.23830355949432766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135033332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997187,0.0003797455,0.00025427854,0.00025699474,0.00037349487,0.001003249,0.0001368243,0.00040435308,0.0000040200375],"genre_scores_gemma":[0.9938452,0.00019809342,0.0053547476,0.00020736762,0.0001230237,0.00017170128,0.000001637088,0.00009638971,0.0000018040632],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99771357,0.0000797421,0.0004925606,0.0009902446,0.00034063234,0.0003832708],"domain_scores_gemma":[0.99811095,0.000079804566,0.00026682715,0.0009259361,0.00038860843,0.0002278979],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018545636,0.00042434898,0.0006464758,0.00027859112,0.000098225595,0.00011298859,0.00020300341,0.00022709134,0.000019289615],"category_scores_gemma":[0.00036784474,0.00043713304,0.00008355568,0.00042948403,0.00014972874,0.00013853543,0.00058879476,0.00080210215,0.0000034375128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019851569,0.00032679708,0.6181168,0.0012875195,0.000073370815,0.00034725497,0.000031290157,0.000021499023,0.3786632,0.00079944107,0.00012285453,0.000011408027],"study_design_scores_gemma":[0.0011884274,0.00013960635,0.8538319,0.0010718462,0.00007384002,1.4274335e-7,0.00000687877,0.00078663195,0.14208278,0.000008633421,0.0003329816,0.00047635887],"about_ca_topic_score_codex":0.000042628868,"about_ca_topic_score_gemma":0.000008312928,"teacher_disagreement_score":0.23658045,"about_ca_system_score_codex":0.00015323155,"about_ca_system_score_gemma":0.00026143872,"threshold_uncertainty_score":0.9998081},"labels":[],"label_agreement":null},{"id":"W3135193725","doi":"10.1210/clinem/dgab158","title":"Decreased Microstructural Integrity of the Central Somatosensory Tracts in Diabetic Peripheral Neuropathy","year":2021,"lang":"en","type":"article","venue":"The Journal of Clinical Endocrinology & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Somatosensory system; Medicine; Somatosensory evoked potential; Peripheral neuropathy; Internal medicine; Peripheral; Diabetes mellitus; Thalamus; Endocrinology; Anesthesia; Radiology; Psychiatry","score_opus":0.09294132401905102,"score_gpt":0.40400837755605107,"score_spread":0.31106705353700004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135193725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98545825,0.0014370186,0.00021731757,0.012132936,0.0004995295,0.00016430616,0.0000057719785,0.000013892149,0.0000709464],"genre_scores_gemma":[0.9925621,0.0015281426,0.0029600074,0.0026028429,0.00027606403,0.0000019741726,8.848256e-7,0.000016054764,0.000051932402],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99723524,0.0008194328,0.001254386,0.00015472191,0.00021026096,0.00032597338],"domain_scores_gemma":[0.9977678,0.00071358366,0.0006475005,0.0005000098,0.00024584585,0.00012527946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004220018,0.0001402502,0.0007461887,0.00004825226,0.000056493467,0.0000057374295,0.0003678597,0.00007990695,0.000034195808],"category_scores_gemma":[0.0020143916,0.00007538637,0.00041405132,0.0002277166,0.0005813794,0.000058230762,0.00011378715,0.0017449381,9.259365e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018819949,0.0018836765,0.42420155,0.00007994226,0.00024955135,0.0008905064,0.00067784474,0.00009613389,0.5112497,0.007970916,0.00072487886,0.05009331],"study_design_scores_gemma":[0.0020139876,0.00008252408,0.9260458,0.000058496258,0.00024450748,0.0029665488,0.000088947156,0.00005622201,0.059826344,0.0033668282,0.005186004,0.000063807696],"about_ca_topic_score_codex":0.00001411374,"about_ca_topic_score_gemma":0.0000053204185,"teacher_disagreement_score":0.5018442,"about_ca_system_score_codex":0.000015829435,"about_ca_system_score_gemma":0.00031110164,"threshold_uncertainty_score":0.7580984},"labels":[],"label_agreement":null},{"id":"W3135454107","doi":"10.1002/mrm.28694","title":"A simulation study of cell size and volume fraction mapping for tissue with two underlying cell populations using diffusion‐weighted MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Diffusion MRI; Volume fraction; Stability (learning theory); RADIUS; Range (aeronautics); Population; Biological system; Diffusion; Volume (thermodynamics); Microstructure; Biomedical engineering; Computer science; Algorithm; Materials science; Magnetic resonance imaging; Artificial intelligence; Physics; Radiology; Biology; Medicine","score_opus":0.11005256753542923,"score_gpt":0.3968923909314867,"score_spread":0.28683982339605746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135454107","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83084524,0.0011847671,0.16593897,0.00060629967,0.000025422814,0.0012256935,0.000002988321,0.00003818965,0.00013241747],"genre_scores_gemma":[0.8820911,0.00008050821,0.11713286,0.0001081768,0.000048676957,0.00007381863,0.000013519053,0.000025011934,0.000426298],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987954,0.000040823972,0.00040753756,0.00036087233,0.00022823182,0.0001671643],"domain_scores_gemma":[0.9989646,0.00031839,0.00016311905,0.0003067312,0.00018853918,0.000058590012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012422283,0.000140717,0.00034923668,0.00012430009,0.00010781834,0.0000070342653,0.000043563017,0.000041122075,0.000041848103],"category_scores_gemma":[0.00013027113,0.00012155391,0.000015824256,0.0005378716,0.00007253654,0.00006335908,0.00003098419,0.00015743347,2.4191334e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005699731,0.0026443724,0.33621705,0.00083994237,0.000010190611,0.0001376959,0.0037379197,0.012266165,0.5797031,0.00015059036,0.000113899994,0.063609146],"study_design_scores_gemma":[0.011364344,0.0022993798,0.44349155,0.00096574635,0.00023664578,0.00004360454,0.00370557,0.5271513,0.0024713462,0.001789949,0.0062006963,0.00027988982],"about_ca_topic_score_codex":0.00020506165,"about_ca_topic_score_gemma":0.00005141719,"teacher_disagreement_score":0.5772317,"about_ca_system_score_codex":0.00005329199,"about_ca_system_score_gemma":0.000038693746,"threshold_uncertainty_score":0.49568245},"labels":[],"label_agreement":null},{"id":"W3135501797","doi":"10.1002/cjs.11607","title":"Rejoinder: “Statistical disease mapping for heterogeneous neuroimaging studies”","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Viewpoints; Neuroimaging; Disease; Data science; Computer science; Medicine; Psychology; Neuroscience; Pathology","score_opus":0.15595903467508232,"score_gpt":0.37626923437290294,"score_spread":0.22031019969782062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135501797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025765037,0.0017747236,0.9866577,0.007501722,0.00022753082,0.0002016459,0.0009801835,0.000015425136,0.00006456293],"genre_scores_gemma":[0.30003306,0.00035066405,0.69544333,0.0033964391,0.00027324076,0.000014026348,0.00008199995,0.000051385683,0.00035584718],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990679,0.000021533117,0.00036959376,0.00015697152,0.00012385802,0.00026015632],"domain_scores_gemma":[0.99783427,0.00025890538,0.00014175019,0.00019231951,0.00075980765,0.00081293314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093656156,0.000106101965,0.00026093345,0.00011657482,0.00015374261,0.000030725892,0.00007070547,0.000018795858,0.000034144658],"category_scores_gemma":[0.0015251765,0.00010697622,0.000064948144,0.00012188291,0.00012130875,0.000038154096,0.000011730669,0.00019264035,0.0000020648024],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002859328,0.00028837158,0.03239454,0.001948302,0.0007223475,0.07461292,0.0010460977,0.0008860828,0.0036610083,0.15994477,0.58253527,0.14167437],"study_design_scores_gemma":[0.0026029756,0.0004953118,0.020687008,0.0008337348,0.0009421088,0.009257676,0.0006026065,0.007278096,0.0012158235,0.16310374,0.79236674,0.00061419985],"about_ca_topic_score_codex":0.000018734952,"about_ca_topic_score_gemma":0.00014022875,"teacher_disagreement_score":0.29745656,"about_ca_system_score_codex":0.00013494233,"about_ca_system_score_gemma":0.0014181074,"threshold_uncertainty_score":0.43623638},"labels":[],"label_agreement":null},{"id":"W3136007397","doi":"10.5114/fn.2021.104396","title":"Globular glial tauopathy, a newly recognized white matter tauopathy, with depression/anxiety disorder: report and review of classification","year":2021,"lang":"en","type":"article","venue":"Folia Neuropathologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Tauopathy; White matter; Depression (economics); Neuroscience; Biology; Pathology; Medicine; Neurodegeneration; Disease; Magnetic resonance imaging","score_opus":0.03477739766586134,"score_gpt":0.3124173073285762,"score_spread":0.27763990966271485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136007397","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9046827,0.019351583,0.039410647,0.02013632,0.00019523191,0.0030169704,0.000113358496,0.0007758171,0.0123174],"genre_scores_gemma":[0.88094664,0.034273326,0.07453536,0.007822892,0.00012535696,0.00042619676,0.00026050795,0.00010038075,0.0015093256],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99794227,0.00015750415,0.00056909845,0.0008086026,0.00027814764,0.0002443567],"domain_scores_gemma":[0.9980756,0.000041807132,0.00042054738,0.0010012335,0.00032530917,0.00013547234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024153799,0.0002495838,0.00054329954,0.00004996113,0.00011013898,0.000017237917,0.00012426781,0.00008296061,0.00013731232],"category_scores_gemma":[0.00034726542,0.00018554818,0.000113808426,0.00041957662,0.00016729296,0.00008293953,0.00016567615,0.0003058569,0.000015394191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002731393,0.00063137605,0.88910383,0.0020310676,0.00001784757,0.00502016,0.000060650535,0.000001910371,0.07529031,0.00017431672,0.007420229,0.019975178],"study_design_scores_gemma":[0.0015215334,0.00046899315,0.8898359,0.003387686,0.00044013368,0.033455644,0.000046468183,0.00011639274,0.006240026,0.00061227486,0.06341688,0.00045806335],"about_ca_topic_score_codex":0.000003338772,"about_ca_topic_score_gemma":8.3477255e-7,"teacher_disagreement_score":0.069050275,"about_ca_system_score_codex":0.000018220857,"about_ca_system_score_gemma":0.00008507136,"threshold_uncertainty_score":0.75664353},"labels":[],"label_agreement":null},{"id":"W3136241235","doi":"10.1101/2021.03.12.21253413","title":"Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Kurtosis; Diffusion MRI; Medicine; Magnetic resonance imaging; Spinal cord; Computer science; Neuroimaging; Medical physics; Radiology; Statistics","score_opus":0.10223331618829953,"score_gpt":0.42916084790211523,"score_spread":0.3269275317138157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136241235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97030586,0.0006564886,0.02536266,0.0025547207,0.00020445212,0.0004603309,0.000014770631,0.00012328029,0.00031744572],"genre_scores_gemma":[0.9670865,0.0008145752,0.031342283,0.00033654424,0.00015368186,0.000062053645,0.00009025749,0.000039245107,0.00007484695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979628,0.000072483286,0.0008665128,0.00063684944,0.00025003444,0.0002113347],"domain_scores_gemma":[0.9984643,0.00008991618,0.00031781782,0.0008896737,0.00013079695,0.00010753529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037872544,0.00021740726,0.00066209625,0.0001538536,0.000025372954,0.000012327136,0.00023367802,0.00013867622,0.000060234062],"category_scores_gemma":[0.00035847264,0.0002096926,0.00026642386,0.00022401907,0.00014928395,0.0000314774,0.0008154685,0.0011012142,0.0000030419042],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024315566,0.00034486305,0.9173665,0.00025436044,0.000013492757,0.0001901031,0.000034020188,0.000004424253,0.0039574387,0.00012232059,0.00010005902,0.07736926],"study_design_scores_gemma":[0.00090816355,0.00019402291,0.98593724,0.0017609601,0.00010388493,0.00009048939,0.0000849034,0.0021867014,0.0054184976,0.00074236013,0.0023271702,0.00024561802],"about_ca_topic_score_codex":0.00007092918,"about_ca_topic_score_gemma":0.0000075816706,"teacher_disagreement_score":0.07712364,"about_ca_system_score_codex":0.000038899612,"about_ca_system_score_gemma":0.00012728902,"threshold_uncertainty_score":0.85510164},"labels":[],"label_agreement":null},{"id":"W3136806534","doi":"10.1111/ncn3.12495","title":"Diffusion tensor imaging‐based magnetic resonance imaging‐guided focused ultrasound thalamotomy for tremor recurrence after radiofrequency thalamotomy: A case report","year":2021,"lang":"en","type":"article","venue":"Neurology and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Thalamotomy; Medicine; Diffusion MRI; Magnetic resonance imaging; Essential tremor; Focused ultrasound; Radiology; Ultrasound; Nuclear medicine; Physical medicine and rehabilitation; Parkinson's disease; Deep brain stimulation; Pathology","score_opus":0.06493877437241999,"score_gpt":0.3903144337174694,"score_spread":0.3253756593450494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3136806534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9534471,0.0010676744,0.013907065,0.02848396,0.00063537934,0.001840459,0.00007654393,0.00033254272,0.00020928985],"genre_scores_gemma":[0.9437436,0.00025485156,0.015783932,0.039117076,0.00015781571,0.00047297933,0.000011388224,0.000053985637,0.00040439106],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961468,0.0002135161,0.00087453437,0.0018825327,0.00026612708,0.0006164726],"domain_scores_gemma":[0.9965914,0.0012605427,0.00021091504,0.0011689891,0.00030229177,0.00046585937],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005376069,0.0003303656,0.00053023576,0.00011986168,0.00033437964,0.00006404907,0.00025611467,0.00011006742,0.00002884406],"category_scores_gemma":[0.0049240477,0.000300266,0.00022335173,0.000609609,0.0009721128,0.00014251868,0.00015669905,0.000648044,0.0000049210325],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049367745,0.0006674492,0.8657123,0.00004344509,0.0000013783565,0.077294365,0.000019988129,0.0000018971865,0.008584595,0.00012798044,0.001357902,0.045695063],"study_design_scores_gemma":[0.0023943502,0.0010438211,0.7746699,0.00006959367,0.00012120248,0.12768057,0.0000045082647,0.0068004923,0.0009732785,0.0011729948,0.08467727,0.00039202182],"about_ca_topic_score_codex":0.000010463103,"about_ca_topic_score_gemma":0.0000046495393,"teacher_disagreement_score":0.091042355,"about_ca_system_score_codex":0.000015255424,"about_ca_system_score_gemma":0.00024482375,"threshold_uncertainty_score":0.9999449},"labels":[],"label_agreement":null},{"id":"W3137094901","doi":"10.1016/j.neuroimage.2021.117977","title":"The ventral pathway of the human brain: A continuous association tract system","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft","keywords":"Fascicle; Anatomy; Neuroscience; Diffusion MRI; Tractography; External capsule; Internal capsule; White matter; Occipital lobe; Biology; Fiber tract; Connectome; Fractional anisotropy; Magnetic resonance imaging; Functional connectivity; Medicine","score_opus":0.0347466807069396,"score_gpt":0.3143478938263358,"score_spread":0.27960121311939623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3137094901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9537485,0.00016932294,0.0006264996,0.031792466,0.00024032647,0.00074879284,0.00004442063,0.00028312695,0.012346506],"genre_scores_gemma":[0.99510586,0.000011102335,0.0001713842,0.0007440255,0.00007637194,0.000028589124,0.0000056187137,0.000019114608,0.0038379277],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991247,0.00009155999,0.00022032394,0.00017429097,0.00022408456,0.00016501463],"domain_scores_gemma":[0.9989504,0.00017059445,0.00019487807,0.00052452966,0.00012572392,0.00003384273],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015921814,0.000078718556,0.00014836605,0.000010996783,0.00023283837,0.000024354813,0.00013252925,0.00003364527,0.000006214569],"category_scores_gemma":[0.00031172045,0.00004958021,0.00013409826,0.00017648474,0.00004966701,0.000030743828,0.000054593787,0.00024403945,0.0000040597315],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000960751,0.00019973904,0.018281536,0.000078045305,0.00001856113,0.000092439084,0.000108659806,0.0000020646064,0.9524818,0.011892531,0.014358303,0.0024767092],"study_design_scores_gemma":[0.00081512774,0.00011255718,0.60659117,0.00015054437,0.00009094459,0.000347536,0.00015203386,0.000152632,0.217071,0.0006457366,0.17374237,0.0001283499],"about_ca_topic_score_codex":0.000005498312,"about_ca_topic_score_gemma":0.0000020518123,"teacher_disagreement_score":0.7354108,"about_ca_system_score_codex":0.00006694002,"about_ca_system_score_gemma":0.00005443816,"threshold_uncertainty_score":0.20218222},"labels":[],"label_agreement":null},{"id":"W3138439593","doi":"10.1101/2021.03.25.436908","title":"Brain virtual histology with X-ray phase-contrast tomography Part II: 3D morphologies of amyloid-β plaques in Alzheimer’s disease models","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"LabEx PRIMES; Université de Lyon; University of Manchester; European Synchrotron Radiation Facility; Agence Nationale de la Recherche; Mitacs","keywords":"Pathology; Histology; Genetically modified mouse; Biology; Medicine; Transgene","score_opus":0.0469539166426776,"score_gpt":0.29177883625519424,"score_spread":0.24482491961251665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3138439593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96602076,0.0036956272,0.025720634,0.001616018,0.00015581318,0.0015545895,0.00053187006,0.00068904035,0.000015660324],"genre_scores_gemma":[0.9607244,0.0006796575,0.03690274,0.00063202635,0.0001093324,0.0008166575,0.0000065337417,0.00012548713,0.0000031357392],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99705833,0.00011980511,0.0007250309,0.0012261803,0.0003449274,0.000525752],"domain_scores_gemma":[0.99700415,0.00012654724,0.000494897,0.0016406734,0.00041755816,0.00031616547],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025501562,0.0005854761,0.0010547274,0.0004894169,0.00010765424,0.000037540787,0.00040988438,0.00032835992,0.000032471697],"category_scores_gemma":[0.00015710156,0.000573546,0.00019842143,0.00065486325,0.00052418193,0.00017433622,0.00041830124,0.000907905,0.0000012722523],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020257689,0.0076736226,0.04232753,0.00088134705,0.0011978162,0.0027359247,0.00011346243,0.006125312,0.92644036,0.0075240955,0.0028153278,0.00013942775],"study_design_scores_gemma":[0.021656675,0.0047816075,0.20695616,0.010912244,0.0056655407,0.0000024532221,0.00015065234,0.029691067,0.6708141,0.00019583054,0.041783962,0.007389699],"about_ca_topic_score_codex":0.000072625255,"about_ca_topic_score_gemma":0.0000038897765,"teacher_disagreement_score":0.25562626,"about_ca_system_score_codex":0.00012516994,"about_ca_system_score_gemma":0.0006624924,"threshold_uncertainty_score":0.9996716},"labels":[],"label_agreement":null},{"id":"W3139317540","doi":"10.1002/mrm.28734","title":"Efficient whole‐brain tract‐specific T<sub>1</sub> mapping at 3T with slice‐shuffled inversion‐recovery diffusion‐weighted imaging","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Hotchkiss Brain Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Voxel; Corticospinal tract; Imaging phantom; White matter; Corpus callosum; Cingulum (brain); Physics; Nuclear magnetic resonance; Computer science; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Anatomy; Fractional anisotropy; Biology; Optics; Medicine; Radiology","score_opus":0.025301290685456404,"score_gpt":0.27333365642935303,"score_spread":0.24803236574389664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139317540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93189543,0.013392777,0.0058877827,0.044740833,0.00014797648,0.00095282675,0.000013570521,0.0002690116,0.0026998094],"genre_scores_gemma":[0.9712556,0.0029394527,0.013047416,0.008875402,0.00041816654,0.00030600736,0.00017573021,0.00014191844,0.002840336],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99680656,0.00010333887,0.0007033869,0.0010020343,0.0007451027,0.0006395842],"domain_scores_gemma":[0.9979228,0.00040589992,0.00019286766,0.0009851826,0.00021969026,0.00027359682],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003388127,0.00040777755,0.00070296956,0.00036787422,0.00021913924,0.000022082393,0.0002213503,0.00009926858,0.0002745228],"category_scores_gemma":[0.00024170628,0.00033011637,0.00009432272,0.001498759,0.0004277559,0.000060926795,0.00016069663,0.00062934484,0.00005194072],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042084634,0.00065979996,0.01942342,0.00017286287,0.000008061978,0.0024464654,0.00079951406,0.00008260651,0.7711678,0.00031947182,0.027082454,0.1774167],"study_design_scores_gemma":[0.011880852,0.0008867712,0.25896755,0.0048819715,0.000116372525,0.0017985353,0.0011479396,0.022489544,0.04254708,0.0011811631,0.6531711,0.0009311354],"about_ca_topic_score_codex":0.000024742454,"about_ca_topic_score_gemma":0.000016307311,"teacher_disagreement_score":0.7286207,"about_ca_system_score_codex":0.00032645138,"about_ca_system_score_gemma":0.00012831108,"threshold_uncertainty_score":0.99991506},"labels":[],"label_agreement":null},{"id":"W3139494368","doi":"10.1101/2021.03.18.21253884","title":"A ketogenic supplement improves white matter energy supply and processing speed in mild cognitive impairment","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centres Intégré Universitaires de Santé et de Services Sociaux; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"","keywords":"Ketone bodies; Ketogenic diet; White matter; Fornix; Neurocognitive; Medicine; Glucose uptake; Neuroimaging; Positron emission tomography; Nuclear medicine; Internal medicine; Psychology; Neuroscience; Cognition; Insulin; Magnetic resonance imaging; Radiology; Metabolism; Epilepsy","score_opus":0.03849697187696032,"score_gpt":0.33235289532017587,"score_spread":0.29385592344321554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139494368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842162,0.0011711546,0.005765145,0.0072479486,0.00005766137,0.0010575209,0.00007209097,0.00012254251,0.0002897312],"genre_scores_gemma":[0.9860057,0.0005752717,0.0099232,0.0019402187,0.00009786344,0.00048510992,0.00036317972,0.00006576792,0.00054367067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99812067,0.000046467037,0.00044062673,0.00082167395,0.00022385716,0.00034668867],"domain_scores_gemma":[0.9991353,0.00003259434,0.00017195803,0.00040582742,0.000117994656,0.00013631454],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011739889,0.0003320732,0.00048190012,0.00019654066,0.000055937122,0.00006953049,0.00011777907,0.00013168214,0.00018239618],"category_scores_gemma":[0.00001628641,0.0003157424,0.00010392274,0.00018246473,0.00009527528,0.00005525224,0.00057574676,0.00050632306,0.0000031087638],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014849294,0.0005212914,0.9745809,0.001000518,0.000066652334,0.00020080025,0.0008540533,0.0000066866696,0.01577665,0.000034237044,0.0010527985,0.0057569286],"study_design_scores_gemma":[0.0019452248,0.00017512901,0.95782816,0.0026738497,0.00026839718,0.00016717715,0.0005195276,0.0011980303,0.030963952,0.0010602884,0.0025922896,0.00060796394],"about_ca_topic_score_codex":0.00009265553,"about_ca_topic_score_gemma":0.00004333618,"teacher_disagreement_score":0.01675272,"about_ca_system_score_codex":0.00009863487,"about_ca_system_score_gemma":0.00015729779,"threshold_uncertainty_score":0.9999295},"labels":[],"label_agreement":null},{"id":"W3139861652","doi":"10.1016/j.intell.2021.101541","title":"No evidence for an effect of a working memory training program on white matter microstructure","year":2021,"lang":"en","type":"article","venue":"Intelligence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Alberta Health Services","funders":"Canadian Institutes of Health Research; Alberta Innovates; Natural Sciences and Engineering Research Council of Canada; Canadian Psychological Association","keywords":"Working memory; Fractional anisotropy; Diffusion MRI; Psychology; White matter; Working memory training; Neuroimaging; Cognition; Cognitive psychology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.22426969416796966,"score_gpt":0.44995420595229985,"score_spread":0.2256845117843302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3139861652","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7685462,0.00087720226,0.2179559,0.0021677902,0.00034273078,0.00441261,0.000024364977,0.0006235311,0.0050496287],"genre_scores_gemma":[0.9099421,0.000037767404,0.08849852,0.0007045324,0.00009801998,0.00024414001,0.000010904497,0.00002400133,0.00044002326],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99921393,0.000026125885,0.00018617405,0.000306927,0.000102111466,0.0001647011],"domain_scores_gemma":[0.9991062,0.0002568001,0.00007259127,0.0003891486,0.00011854555,0.000056668207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011829816,0.00011282747,0.00019882616,0.000035634745,0.00004467656,0.000015704882,0.0001128772,0.00004519633,0.00005311413],"category_scores_gemma":[0.00019234243,0.00009427357,0.00008253752,0.0001671889,0.000066616296,0.000049819446,0.000026356098,0.00016063241,0.000011910731],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007088814,0.00019296774,0.014750866,0.0007634172,0.000024811292,0.00003095467,0.0007166728,0.000139437,0.23604794,0.0003019799,0.0008770851,0.745445],"study_design_scores_gemma":[0.00017184901,0.0022155812,0.002925418,0.0023224873,0.00007172896,0.00017711078,0.0000751727,0.0014245516,0.98183423,0.00094892207,0.0076418845,0.00019109054],"about_ca_topic_score_codex":0.0000015996131,"about_ca_topic_score_gemma":0.0000010033793,"teacher_disagreement_score":0.74578625,"about_ca_system_score_codex":0.000019072533,"about_ca_system_score_gemma":0.00003443214,"threshold_uncertainty_score":0.3844365},"labels":[],"label_agreement":null},{"id":"W3143007731","doi":"10.1016/j.neuroimage.2021.117980","title":"Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; National Institute on Aging; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; University of Washington; Centre d'Imagerie BioMédicale; Pfizer; Biogen; BioClinica; Massachusetts General Hospital; University of Minnesota; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Johnson and Johnson; Meso Scale Diagnostics; F. Hoffmann-La Roche; Agence Nationale de la Recherche; University of Southern California; National Institutes of Health; University of California; National Institute of Dental and Craniofacial Research; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Janssen Alzheimer Immunotherapy Research And Development; AbbVie; Fujirebio Europe; Université Côte d’Azur; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Bayesian inference; Neurodegeneration; Artificial intelligence; Bayesian probability; Computer science; Inference; Expectation propagation; Parametric statistics; Belief propagation; Neuroscience; Propagation of uncertainty; Formalism (music); Machine learning; Biology; Mathematics; Physics; Disease; Algorithm; Medicine; Pathology","score_opus":0.05664511417678205,"score_gpt":0.3206182696660025,"score_spread":0.26397315548922046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143007731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9843754,0.000085336345,0.011493041,0.002881696,0.000011607021,0.00064723863,0.000007286919,0.00004848776,0.0004498734],"genre_scores_gemma":[0.9966151,0.00000977103,0.0027665666,0.0002763721,0.000019501602,0.000080013975,0.000034880024,0.000017646034,0.00018014079],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99893606,0.00023395728,0.00031701662,0.00020607428,0.0002088206,0.00009809634],"domain_scores_gemma":[0.9993062,0.00015285684,0.0001677689,0.00025360615,0.00009704037,0.000022512177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020275533,0.00007915834,0.00016371248,0.00004596476,0.000039834635,0.000013914028,0.0000761222,0.0000291925,0.0000026721943],"category_scores_gemma":[0.00089000637,0.00006376331,0.000034113855,0.00030288482,0.00008243956,0.00008110913,0.000027434417,0.00025906574,7.0805146e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000045181514,0.00008726534,0.003362358,0.00012707367,0.0000012428037,0.0000077132445,0.0000792684,0.00025077377,0.9930311,0.0021218641,0.0001302935,0.00079655077],"study_design_scores_gemma":[0.0007422203,0.00042267007,0.0327655,0.0003958066,0.000031880558,0.00015700895,0.0002848511,0.06250404,0.8993732,0.0007262443,0.002428871,0.0001677366],"about_ca_topic_score_codex":0.000021509097,"about_ca_topic_score_gemma":0.0000017279831,"teacher_disagreement_score":0.0936579,"about_ca_system_score_codex":0.000011428648,"about_ca_system_score_gemma":0.000047220412,"threshold_uncertainty_score":0.26001924},"labels":[],"label_agreement":null},{"id":"W3143481006","doi":"","title":"White matter imaging correlates of early cognitive impairment detected by the MoCA after TIA and minor stroke","year":2017,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute for Health and Care Research","keywords":"Medicine; Minor stroke; Montreal Cognitive Assessment; Stroke (engine); Cognitive impairment; White matter; Leukoaraiosis; Hyperintensity; Cognition; Ischemic stroke; Neuroimaging; Cardiology; Internal medicine; Magnetic resonance imaging; Psychiatry; Radiology; Ischemia; Stenosis","score_opus":0.026834965760165214,"score_gpt":0.28905289281901914,"score_spread":0.26221792705885394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3143481006","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97836286,0.00004758134,0.008895334,0.002631777,0.000011167944,0.0008011048,0.0007158234,0.000039211816,0.008495152],"genre_scores_gemma":[0.9914393,0.00039196183,0.0030575106,0.000030597505,0.000009190602,9.441996e-7,0.00003814531,0.0000170922,0.0050152587],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859256,0.000119646655,0.000112467846,0.00039514483,0.0003768882,0.00040331963],"domain_scores_gemma":[0.9984192,0.00021663068,0.0002012796,0.00061666843,0.00034182554,0.00020437685],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023179803,0.00016338374,0.000275014,0.00029986908,0.0009469015,0.00003190583,0.0006046504,0.00005406086,0.00014539727],"category_scores_gemma":[0.000036457852,0.00016397184,0.0001320279,0.00017076486,0.0020787676,0.00036818188,0.0010070883,0.0005419404,0.000005878454],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021895024,0.00017425262,0.9871597,0.00008411969,0.00010588397,0.00013190029,0.0013569999,6.2180396e-7,0.0024249216,0.00018365002,0.0021550264,0.0040334053],"study_design_scores_gemma":[0.0019021768,0.0005027195,0.9831241,0.00019084524,0.00015001111,0.00002704351,0.0043447334,0.00063763047,0.00043509007,0.0006395484,0.007879108,0.00016702732],"about_ca_topic_score_codex":0.0005323888,"about_ca_topic_score_gemma":0.000102968,"teacher_disagreement_score":0.013076452,"about_ca_system_score_codex":0.00006680739,"about_ca_system_score_gemma":0.00009000098,"threshold_uncertainty_score":0.76593065},"labels":[],"label_agreement":null},{"id":"W3144676319","doi":"10.1002/hbm.25398","title":"Beware of white matter hyperintensities causing systematic errors in <scp>FreeSurfer</scp> gray matter segmentations!","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centres Intégré Universitaires de Santé et de Services Sociaux; Université Laval; University of Alberta","funders":"National Institute on Aging; Canadian Institutes of Health Research; Alzheimer Society; Sanofi","keywords":"White matter; Hyperintensity; Gray (unit); Neuroscience; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.0652553427233796,"score_gpt":0.3261504929430581,"score_spread":0.26089515021967846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144676319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9738564,0.00014184622,0.017692484,0.004292133,0.000046412544,0.0007337856,0.000013710543,0.00012804345,0.0030952059],"genre_scores_gemma":[0.97889084,0.000004362421,0.012040891,0.00451977,0.000036558515,0.000117829004,0.00006178434,0.000044929915,0.004283016],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986589,0.00008094642,0.00053467584,0.0003069301,0.00017752958,0.00024104048],"domain_scores_gemma":[0.9989603,0.0001819477,0.00017631135,0.00047821252,0.0001506572,0.000052553278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017783503,0.00016583994,0.00043752056,0.0002310363,0.00017938018,0.000024622308,0.000073447874,0.000048806964,0.000117933225],"category_scores_gemma":[0.000113833594,0.00016879679,0.000092749215,0.00032771425,0.000084059895,0.00009869745,0.00011529339,0.00019431965,0.000030948548],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003319191,0.0001933997,0.4234443,0.019374514,0.00007721381,0.0002630832,0.010848926,0.00019885288,0.52371657,0.0010934492,0.020775441,0.000010940381],"study_design_scores_gemma":[0.0012214304,0.00005191801,0.9347179,0.019622842,0.00014642232,0.00088895764,0.02786236,0.0005946583,0.009584236,0.003472398,0.0015494986,0.00028736368],"about_ca_topic_score_codex":0.000020006933,"about_ca_topic_score_gemma":0.000017663722,"teacher_disagreement_score":0.5141323,"about_ca_system_score_codex":0.000073123316,"about_ca_system_score_gemma":0.000027668651,"threshold_uncertainty_score":0.68833333},"labels":[],"label_agreement":null},{"id":"W3148107305","doi":"10.1016/j.neuropsychologia.2021.107847","title":"Diffusion property and functional connectivity of superior longitudinal fasciculus underpin human metacognition","year":2021,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Psychology; Precuneus; Mnemonic; Superior longitudinal fasciculus; Arcuate fasciculus; Neuroscience; Cognitive psychology; Inferior longitudinal fasciculus; Fractional anisotropy; Metacognition; Functional magnetic resonance imaging; Diffusion MRI; Cognition; Magnetic resonance imaging","score_opus":0.14087174292486895,"score_gpt":0.3699412326271836,"score_spread":0.22906948970231464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148107305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98749244,0.00007256165,0.008590497,0.0014350682,0.00005453354,0.00022959533,0.000010045666,0.00012060477,0.0019946396],"genre_scores_gemma":[0.9968103,0.00008682773,0.0020563651,0.000525629,0.000040999083,0.000028659995,0.000030876825,0.000014800861,0.00040552704],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991676,0.000049889073,0.00016613137,0.00037472873,0.00012933143,0.00011229932],"domain_scores_gemma":[0.9994391,0.00003819284,0.00005737743,0.0002618184,0.0001462016,0.00005731722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006124792,0.00010220145,0.00018536262,0.000046372705,0.00010516949,0.000010059933,0.000030221507,0.000045392182,0.000104570725],"category_scores_gemma":[0.000091553426,0.00007325443,0.000054011158,0.00019198583,0.00014224178,0.00005637814,0.000060310755,0.00018730301,0.000003914822],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006226306,0.00038801978,0.04031899,0.00003242774,0.000011199137,0.000058140882,0.000010453484,6.790479e-7,0.94973487,0.0010773574,0.00039894908,0.0079066465],"study_design_scores_gemma":[0.00076814997,0.00028308647,0.9508172,0.000044324974,0.000059705704,0.0005445395,0.000018408788,0.000051878076,0.045083504,0.0012203306,0.0010200638,0.00008878135],"about_ca_topic_score_codex":0.0000051596085,"about_ca_topic_score_gemma":0.0000019125544,"teacher_disagreement_score":0.91049826,"about_ca_system_score_codex":0.000011639135,"about_ca_system_score_gemma":0.000019591916,"threshold_uncertainty_score":0.2987229},"labels":[],"label_agreement":null},{"id":"W3148237534","doi":"10.1101/2021.04.07.438845","title":"Enabling constrained spherical deconvolution and diffusional variance decomposition with tensor-valued diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Deconvolution; Fractional anisotropy; Tensor (intrinsic definition); Anisotropy; Orientation (vector space); Diffusion; Computer science; Angular resolution (graph drawing); White matter; Computation; Variance (accounting); Tractography; Algorithm; Mathematics; Physics; Magnetic resonance imaging; Geometry; Optics","score_opus":0.02162703153090347,"score_gpt":0.27457103590002124,"score_spread":0.2529440043691178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148237534","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7369538,0.0005243736,0.26011437,0.0008780889,0.00011068521,0.00085005246,0.000054399727,0.0005052554,0.000008987086],"genre_scores_gemma":[0.7405789,0.00050657324,0.25802964,0.0004176233,0.00018762074,0.00018994421,0.0000035027756,0.000081337836,0.0000048525803],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99760836,0.000075255244,0.00043571775,0.0011260933,0.00036127804,0.0003933106],"domain_scores_gemma":[0.997955,0.000071729584,0.00031590596,0.0008487683,0.000488527,0.00032002397],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018001557,0.00046316077,0.0005992175,0.00012870683,0.00026145874,0.00013547722,0.00015187902,0.00033183902,0.000043401906],"category_scores_gemma":[0.00009760328,0.00043986426,0.00010135816,0.000369262,0.00025937278,0.00012507664,0.00033858573,0.0008225637,0.0000039041315],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014108336,0.00036313056,0.012149772,0.00030985297,0.00007199517,0.00016892317,0.0000067308715,0.00004385459,0.985598,0.0010790142,0.000051637173,0.000015999796],"study_design_scores_gemma":[0.0051548537,0.0005317355,0.6759195,0.00513294,0.0010354411,0.000009069649,0.000027485172,0.0339466,0.27207062,0.0000458364,0.0038884843,0.0022374524],"about_ca_topic_score_codex":0.000021704845,"about_ca_topic_score_gemma":8.929751e-7,"teacher_disagreement_score":0.7135274,"about_ca_system_score_codex":0.00021259788,"about_ca_system_score_gemma":0.00042929983,"threshold_uncertainty_score":0.99980533},"labels":[],"label_agreement":null},{"id":"W3148446709","doi":"10.1101/2021.03.26.21254351","title":"In Vivo Cortical Microstructure: A Proxy for Tauopathy and Cognitive impairment in the Elderly with and without MCI/Dementia","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Japan Atomic Energy Agency; National Institutes of Health; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; BioClinica; U.S. Department of Defense; Canon Medical Systems USA; Alzheimer's Disease Neuroimaging Initiative; University of Toronto; Bristol-Myers Squibb; National Alliance for Research on Schizophrenia and Depression; Biogen; National Institute on Aging; Alzheimer's Association; Brain and Behavior Research Foundation","keywords":"Dementia; Psychology; Tauopathy; Fractional anisotropy; Diffusion MRI; Cognitive impairment; Neuroscience; Cognitive decline; Positron emission tomography; Audiology; Correlation; Proxy (statistics); Cognition; Internal medicine; Nuclear medicine; Medicine; Disease; Magnetic resonance imaging; Radiology; Statistics; Neurodegeneration","score_opus":0.027234502302790314,"score_gpt":0.33433572023084923,"score_spread":0.3071012179280589,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148446709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9855121,0.00051735016,0.00825705,0.002611423,0.000019610789,0.0029753787,0.00004177214,0.000028438444,0.00003689306],"genre_scores_gemma":[0.9859853,0.00014360655,0.011732859,0.00075806596,0.00003395813,0.001269726,0.000027028489,0.000025717765,0.000023729419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99890023,0.000051035717,0.00022811267,0.000499451,0.00012557041,0.00019558502],"domain_scores_gemma":[0.9994533,0.00008593543,0.00008619338,0.00025454903,0.000065148895,0.000054858778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020677755,0.00019654956,0.00031367634,0.000070210524,0.000048633574,0.00004332635,0.00007415701,0.00007445057,0.000006910791],"category_scores_gemma":[0.000058258225,0.000130759,0.00003086041,0.000109782726,0.00016248866,0.000030994077,0.00013659733,0.000535903,8.186904e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005520527,0.00037925996,0.9823286,0.0007262469,0.00007966362,0.00017685,0.0022991288,0.0000020495654,0.011402524,0.0003130501,0.00012442558,0.0016161565],"study_design_scores_gemma":[0.006589748,0.0020420097,0.9602755,0.002507706,0.0008879141,0.0011471483,0.0018592853,0.001336976,0.015280134,0.005564331,0.0018708481,0.000638442],"about_ca_topic_score_codex":0.000025059602,"about_ca_topic_score_gemma":0.000055462675,"teacher_disagreement_score":0.022053136,"about_ca_system_score_codex":0.000017908003,"about_ca_system_score_gemma":0.00007664388,"threshold_uncertainty_score":0.5332197},"labels":[],"label_agreement":null},{"id":"W3152388697","doi":"10.1101/2021.04.01.21254814","title":"Multi-tract multi-symptom relationships in pediatric concussion","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Toronto; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital; Hospital for Sick Children; McGill University","funders":"","keywords":"Concussion; White matter; Diffusion MRI; Psychopathology; Psychology; Connectome; Medicine; Clinical psychology; Neuroscience; Poison control; Functional connectivity; Injury prevention; Magnetic resonance imaging; Radiology","score_opus":0.15730719273781815,"score_gpt":0.3896156803775997,"score_spread":0.23230848763978154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152388697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9426519,0.0011514884,0.052148025,0.001986599,0.00022863953,0.0011107521,0.000019674682,0.0004509766,0.0002519383],"genre_scores_gemma":[0.8561305,0.0014426237,0.14097829,0.00017373596,0.0001631251,0.00028875942,0.00019664253,0.00006183985,0.00056450156],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980543,0.0001323024,0.0005439063,0.00076620013,0.00023296679,0.00027029586],"domain_scores_gemma":[0.99835855,0.00017126369,0.00023402186,0.0009532201,0.00012413017,0.0001588235],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033539464,0.0002908381,0.00045479738,0.0002991075,0.00009123329,0.00003216773,0.00021208762,0.00035293348,0.000044746033],"category_scores_gemma":[0.0005857015,0.00027160262,0.00016777111,0.00041559755,0.000049831026,0.000064376974,0.00036989825,0.0021447216,0.000032337204],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008897733,0.0005728526,0.99574953,0.00019848558,0.000006157547,0.00015059022,0.00017780486,0.00014686305,0.002271318,0.00003557104,0.00012111649,0.0005608386],"study_design_scores_gemma":[0.0008481394,0.000018257666,0.98939604,0.00029209722,0.00009427072,0.000042852324,0.000042272994,0.0064844936,0.0008751347,0.00011777552,0.0015253361,0.0002633263],"about_ca_topic_score_codex":0.000029224635,"about_ca_topic_score_gemma":0.000021151835,"teacher_disagreement_score":0.08883026,"about_ca_system_score_codex":0.00012266377,"about_ca_system_score_gemma":0.00020841394,"threshold_uncertainty_score":0.9999736},"labels":[],"label_agreement":null},{"id":"W3152390874","doi":"10.1080/01616412.2021.1910903","title":"Microstructural changes in the cingulate gyrus of patients with mild cognitive impairment induced by cerebral small vessel disease","year":2021,"lang":"en","type":"article","venue":"Neurological Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Gyrus; Fractional anisotropy; Diffusion MRI; Internal medicine; Posterior cingulate; Cingulate cortex; Anterior cingulate cortex; Psychology; Medicine; Cardiology; Lingual gyrus; Montreal Cognitive Assessment; Cognitive impairment; Cognition; Neuroscience; Disease; Magnetic resonance imaging; Radiology; Central nervous system","score_opus":0.13667093288349458,"score_gpt":0.40059210810136614,"score_spread":0.26392117521787156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152390874","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99045336,0.000051582003,0.00001839246,0.00846289,0.000007695604,0.0008246313,0.00007028855,0.000024735462,0.000086448665],"genre_scores_gemma":[0.99769884,0.00003527358,0.0002523569,0.0017324041,0.00001931063,0.00013097849,0.000088284134,0.000012082861,0.000030464042],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985003,0.00024292561,0.00013613811,0.00035859665,0.00042399738,0.00033805045],"domain_scores_gemma":[0.9989216,0.00037086112,0.000038344642,0.00027476178,0.0002736628,0.00012078836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018299035,0.00010344676,0.00016113673,0.00005101566,0.000086444794,0.000016078566,0.00015576433,0.000046070043,0.00003742711],"category_scores_gemma":[0.00034789613,0.000059540827,0.00003218492,0.00046469676,0.00021161893,0.000019819528,0.0001468006,0.00063807546,0.0000018632742],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035875745,0.0018099707,0.9595471,0.00010386731,0.000016552169,0.00033467656,0.00024907323,0.000001255965,0.027149893,0.00031814043,0.0006301142,0.006251778],"study_design_scores_gemma":[0.0012005109,0.0013323162,0.9875955,0.000037702634,0.000012813483,0.000005563141,0.000040552935,0.000035395584,0.008693076,0.0006407702,0.00034608043,0.000059730013],"about_ca_topic_score_codex":0.0000139595095,"about_ca_topic_score_gemma":0.000007316381,"teacher_disagreement_score":0.028048385,"about_ca_system_score_codex":0.000014887572,"about_ca_system_score_gemma":0.00006111909,"threshold_uncertainty_score":0.27721557},"labels":[],"label_agreement":null},{"id":"W3152927637","doi":"10.1017/cjn.2021.64","title":"Corpus Callosum Remodeling in Glioma: Constancy of Fiber Density and Anisotropy in MRI","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Brain Research Centre","keywords":"Corpus callosum; Glioma; Medicine; Anisotropy; Nuclear magnetic resonance; Neuroscience; Pathology; Physics; Psychology; Optics; Cancer research","score_opus":0.0583567899094615,"score_gpt":0.3174384119447719,"score_spread":0.2590816220353104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152927637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921777,0.0017841625,0.00010462214,0.005122996,0.00011484823,0.00011875829,0.000005987382,0.000008677614,0.00056221243],"genre_scores_gemma":[0.9824344,0.0009473901,0.015351725,0.0012068262,0.000042688156,0.0000013254414,2.339426e-7,0.000006809833,0.000008583694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973625,0.00036441014,0.00079496787,0.00042101365,0.00038097973,0.00067612145],"domain_scores_gemma":[0.9979497,0.00032471292,0.00041531204,0.00013236412,0.0003933541,0.00078454026],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0016948294,0.00018324623,0.0005009638,0.000754527,0.0004920156,0.000107560874,0.00046625073,0.000116349496,0.00003716058],"category_scores_gemma":[0.0013761373,0.00013915895,0.000102405,0.0014760669,0.0036398475,0.00037491182,0.00006126986,0.00093040767,2.6738155e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006848498,0.00004682432,0.9801388,0.000011486911,0.0000030000647,0.013440745,0.00011140865,0.0011292567,0.001326658,0.0018041652,0.00007137635,0.0018478048],"study_design_scores_gemma":[0.0012303881,0.020790514,0.7667315,0.0002793855,0.00004673183,0.12455397,0.00027364015,0.0047223386,0.0031996241,0.07620359,0.0015792268,0.00038906396],"about_ca_topic_score_codex":0.00083871966,"about_ca_topic_score_gemma":0.03365772,"teacher_disagreement_score":0.21340726,"about_ca_system_score_codex":0.0001411727,"about_ca_system_score_gemma":0.00230478,"threshold_uncertainty_score":0.99907166},"labels":[],"label_agreement":null},{"id":"W3153160982","doi":"10.1016/j.pscychresns.2021.111289","title":"White matter microstructure in youth at risk for serious mental illness: A comparative analysis","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Ottawa; Queen's University; University of Alberta; University Health Network; Health Sciences Centre; University of Toronto; St. Michael's Hospital; Sunnybrook Health Science Centre; McMaster University; University of British Columbia; St. Joseph’s Healthcare Hamilton; University of Calgary; Ontario Brain Institute; Baycrest Hospital; Alberta Children's Hospital","funders":"Mathison Centre for Mental Health Research and Education; Canadian Institutes of Health Research; Bristol-Myers Squibb Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Fractional anisotropy; Fasciculus; White matter; Uncinate fasciculus; Superior longitudinal fasciculus; Inferior longitudinal fasciculus; Diffusion MRI; Medicine; Psychology; Internal medicine; Cardiology; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.09192182509794831,"score_gpt":0.4323466069880066,"score_spread":0.34042478189005826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153160982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97617656,0.0005334077,0.0025200816,0.01705503,0.00014763394,0.0013736017,0.00056796486,0.00011307288,0.0015126684],"genre_scores_gemma":[0.977116,0.00014471567,0.019883886,0.0012403664,0.000112500056,0.0001840918,0.00036623614,0.00004366051,0.0009085749],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976372,0.00020417671,0.0003465043,0.00082801626,0.0003757446,0.0006083754],"domain_scores_gemma":[0.99865454,0.00010679449,0.00009627716,0.00072046154,0.00025547767,0.00016643284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031162694,0.00020792421,0.00042680738,0.00051547465,0.00046834574,0.00007958791,0.00019286682,0.000048717848,0.00014603176],"category_scores_gemma":[0.00004600922,0.00020243484,0.00023179344,0.002035844,0.00017752718,0.0001076877,0.00024721387,0.0007750005,0.00002640384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022871688,0.00017615281,0.9856194,0.00006279068,0.00009640049,0.000025413136,0.00153084,0.00007345754,0.005297558,0.00007125927,0.006553795,0.0002641851],"study_design_scores_gemma":[0.0022840905,0.000121682395,0.96897876,0.00010498336,0.0004140449,0.0002041927,0.0032024407,0.005766413,0.0026868493,0.0024683583,0.0133642545,0.00040391355],"about_ca_topic_score_codex":0.000046302495,"about_ca_topic_score_gemma":0.0001654604,"teacher_disagreement_score":0.017363803,"about_ca_system_score_codex":0.00014125653,"about_ca_system_score_gemma":0.00012431447,"threshold_uncertainty_score":0.82550526},"labels":[],"label_agreement":null},{"id":"W3153408593","doi":"10.1007/s00429-021-02267-y","title":"White matter microstructural changes in short-term learning of a continuous visuomotor sequence","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Max-Planck-Institut für demografische Forschung; Fonds de recherche du Québec – Nature et technologies; Max-Planck-Gesellschaft; Heart and Stroke Foundation of Canada; Réseau en Bio-Imagerie du Quebec; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"White matter; Neuroscience; Neuroplasticity; Psychology; Sequence learning; Functional magnetic resonance imaging; Motor learning; Magnetic resonance imaging; Medicine","score_opus":0.02711165707829397,"score_gpt":0.3069827895872639,"score_spread":0.2798711325089699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153408593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99611527,0.00012044787,0.001481517,0.0018904269,0.000048978283,0.00016715139,0.000013962381,0.00003890626,0.00012332006],"genre_scores_gemma":[0.99616003,0.000028165128,0.002270423,0.00088550977,0.000067441346,0.000009562691,0.000070632086,0.000012500047,0.00049575],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99946207,0.000020308149,0.00012491217,0.0002170805,0.00006602659,0.0001096319],"domain_scores_gemma":[0.99972844,0.000021922702,0.000033653378,0.00012822881,0.00005504752,0.000032716944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002890184,0.00008994767,0.0001685327,0.000057226614,0.000037009217,0.00001098838,0.000021755968,0.000057555586,0.00011383718],"category_scores_gemma":[0.000021116604,0.00007996187,0.000023465636,0.00014291535,0.000052052397,0.000043880606,0.000027770795,0.00018117038,5.5527386e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003887888,0.0000050968124,0.40343776,0.00004928264,0.0000045208903,0.000011429907,0.000105606516,0.0000025296445,0.5877702,0.000072400646,0.0001571679,0.00834511],"study_design_scores_gemma":[0.0003145201,0.0001090574,0.94954306,0.000073891024,0.000023917522,0.00039573904,0.000088980014,0.00008043513,0.04574955,0.00053072965,0.003002257,0.0000878924],"about_ca_topic_score_codex":0.0000050746007,"about_ca_topic_score_gemma":0.000010931524,"teacher_disagreement_score":0.54610527,"about_ca_system_score_codex":0.000014264856,"about_ca_system_score_gemma":0.000014968016,"threshold_uncertainty_score":0.32607505},"labels":[],"label_agreement":null},{"id":"W3155343819","doi":"10.1038/s41598-021-87801-y","title":"A longitudinal analysis of brain extracellular free water in HIV infected individuals","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Cart; Neuroinflammation; White matter; Human immunodeficiency virus (HIV); Biomarker; Medicine; Grey matter; Internal medicine; Antiretroviral therapy; Inflammation; Immunology; Viral load; Biology; Magnetic resonance imaging","score_opus":0.047501977787179815,"score_gpt":0.3340657475831126,"score_spread":0.2865637697959328,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155343819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9908184,0.00012147976,0.006348929,0.0017114705,0.00014049765,0.00020809627,0.000008514449,0.000068642876,0.0005739772],"genre_scores_gemma":[0.98865926,0.0000028721786,0.007339089,0.00003885749,0.000010698473,0.000025168336,0.00036889268,0.000009707091,0.0035454677],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99836534,0.000029385808,0.0005077973,0.0005651967,0.0003322098,0.0002000661],"domain_scores_gemma":[0.9982681,0.00003425163,0.00014114346,0.0012919037,0.00019567335,0.000068927926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067096687,0.00008819626,0.00030632198,0.00051034294,0.0000595854,0.00003639612,0.00007447428,0.00004205929,0.00030768898],"category_scores_gemma":[0.00031297814,0.000070995746,0.00014375246,0.0020377275,0.00014055686,0.00006705513,0.00012665927,0.00012011625,0.0000030209678],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035483113,0.00023680588,0.55461526,0.000022228262,0.00008425338,0.0012458363,0.00016493438,0.00011751115,0.4387682,0.00021645801,0.0042681037,0.00025686383],"study_design_scores_gemma":[0.0002885273,0.00001971156,0.32763818,0.000069837915,0.0005383043,0.00040182858,0.000034222037,0.0006053444,0.618258,0.010787171,0.041200973,0.0001579054],"about_ca_topic_score_codex":0.000012436628,"about_ca_topic_score_gemma":0.000024359175,"teacher_disagreement_score":0.22697708,"about_ca_system_score_codex":0.000026803831,"about_ca_system_score_gemma":0.000079629914,"threshold_uncertainty_score":0.33689785},"labels":[],"label_agreement":null},{"id":"W3155614392","doi":"10.1016/j.nicl.2021.102682","title":"Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Gates Cambridge Trust; Evelyn Trust; Royal College of Anaesthetists; National Institute for Health and Care Research; UCLH Biomedical Research Centre; Medical Research Council; Canadian Institute for Advanced Research; Cambridge Trust; University of Cambridge","keywords":"Consciousness; Covert; Psychology; Diffusion MRI; Neuroscience; Connectome; Human brain; Wakefulness; Minimally conscious state; Insula; Persistent vegetative state; Traumatic brain injury; Connectomics; Brain Structure and Function; Cognition; Medicine; Functional connectivity; Psychiatry; Electroencephalography; Magnetic resonance imaging; Philosophy; Radiology","score_opus":0.061548807699788086,"score_gpt":0.39124322639458503,"score_spread":0.32969441869479693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155614392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776611,0.000057820496,0.0022420443,0.018614432,0.00013966732,0.00052167015,0.00020899833,0.0002001007,0.00035416643],"genre_scores_gemma":[0.97047234,0.00003207354,0.0017786282,0.025863133,0.00020410525,0.000043317414,0.00015645316,0.00006972063,0.0013802429],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975929,0.0002477064,0.0007540264,0.00072169607,0.00033258743,0.00035103454],"domain_scores_gemma":[0.99693346,0.0012621478,0.00032849348,0.000884518,0.00038217977,0.0002091951],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002805901,0.00025833113,0.00068011903,0.00004524451,0.00006941757,0.000033525783,0.00018443108,0.00021444562,0.00035157058],"category_scores_gemma":[0.0016556042,0.00021991157,0.00025286718,0.00035184895,0.000380512,0.0001766872,0.00027321425,0.0009784652,0.000006964777],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027586096,0.0011137675,0.9054837,0.00010550957,0.00025804032,0.0018839372,0.000095858326,0.0000200918,0.012853018,0.000142989,0.06845688,0.006827592],"study_design_scores_gemma":[0.0027741268,0.00078454654,0.97814476,0.00025365988,0.00016417078,0.0002937708,0.000012284257,0.0036788043,0.0029166194,0.0004219846,0.0101841865,0.00037111054],"about_ca_topic_score_codex":0.0000036918111,"about_ca_topic_score_gemma":0.000006088419,"teacher_disagreement_score":0.07266103,"about_ca_system_score_codex":0.00002477021,"about_ca_system_score_gemma":0.00017850092,"threshold_uncertainty_score":0.89677334},"labels":[],"label_agreement":null},{"id":"W3155621432","doi":"10.1101/2021.04.15.440008","title":"Analyzing Brain Morphology in Alzheimer’s Disease Using Discriminative and Generative Spiral Networks","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Quest High Performance Computing; National Institutes of Health; Genentech; U.S. National Library of Medicine; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Biogen; Northwestern University; Pfizer; BioClinica; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Discriminative model; Artificial intelligence; Computer science; Pattern recognition (psychology); Brain morphometry; Deep learning; Polygon mesh; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.06827813142636037,"score_gpt":0.3267201999764108,"score_spread":0.2584420685500504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155621432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8784877,0.004765161,0.11345057,0.0019129856,0.00014869309,0.0009502115,0.000070560374,0.00021196557,0.000002142174],"genre_scores_gemma":[0.9433887,0.0004431677,0.054806612,0.0007979164,0.00024419534,0.00021234072,0.0000022905126,0.00010334654,0.0000014004186],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9976959,0.00015330434,0.0004091732,0.0011345779,0.00015770824,0.00044933878],"domain_scores_gemma":[0.9981968,0.00007972726,0.00027632696,0.00086836907,0.00024461278,0.0003341791],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024185314,0.00045889945,0.0006638409,0.00028813758,0.00013017608,0.00009472292,0.00017140267,0.00025468148,0.00001132198],"category_scores_gemma":[0.0001925876,0.00049756665,0.0001182425,0.0004996765,0.0002417063,0.00012791723,0.0005773433,0.0009934609,8.01154e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021245104,0.0007699967,0.24177821,0.00047532166,0.0004909014,0.003085363,0.000067395624,0.006118814,0.7438139,0.002788079,0.00033065517,0.00006896747],"study_design_scores_gemma":[0.0017491678,0.00012894829,0.7516686,0.002263801,0.001548528,7.3752943e-7,0.000029020399,0.16873796,0.07144087,0.000038587226,0.00055760745,0.0018362105],"about_ca_topic_score_codex":0.00005024502,"about_ca_topic_score_gemma":0.0000026895782,"teacher_disagreement_score":0.672373,"about_ca_system_score_codex":0.00019424883,"about_ca_system_score_gemma":0.00037598537,"threshold_uncertainty_score":0.9997476},"labels":[],"label_agreement":null},{"id":"W3156076616","doi":"10.1016/j.neuroimage.2021.118084","title":"Association between breastfeeding during infancy and white matter microstructure in early childhood","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Alberta Children's Hospital Foundation; Alberta Innovates; Alberta Innovates - Health Solutions; Fondation pour la Recherche Médicale; Children's Hospital Foundation","keywords":"Breastfeeding; Association (psychology); White matter; White (mutation); Psychology; Developmental psychology; Pediatrics; Medicine; Genetics; Biology; Magnetic resonance imaging","score_opus":0.013563087550743673,"score_gpt":0.27665195303463025,"score_spread":0.2630888654838866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156076616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9909395,0.00003886133,0.00010858894,0.0074542905,0.000022503711,0.00017417932,0.000024376717,0.00009600455,0.001141675],"genre_scores_gemma":[0.99553514,0.000040453117,0.0026865932,0.0007638682,0.0001122923,0.0000121275425,0.000019439209,0.000030440327,0.0007996588],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914944,0.00002166405,0.0001821241,0.00032148618,0.000118582175,0.0002067123],"domain_scores_gemma":[0.9995693,0.000031278338,0.00007283057,0.0002151747,0.00004710162,0.00006433537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041773088,0.00011352556,0.00018429852,0.00007653918,0.000064344866,0.000043238284,0.000043644995,0.00006068228,0.00004050275],"category_scores_gemma":[0.00005228464,0.00012172747,0.0000360835,0.00023668032,0.000017340775,0.00012717789,0.00008449839,0.0003668006,0.000011712003],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033764318,0.00001850752,0.9502362,0.000024797817,0.000005878174,0.00004953874,0.0001610897,3.764953e-7,0.048706762,0.0000059439017,0.00020002754,0.0005875242],"study_design_scores_gemma":[0.00057154533,0.000013077419,0.9880611,0.00005794756,0.00003111519,0.00015731205,0.000008485725,0.0000028433076,0.010256106,0.0002550885,0.00049207255,0.00009335177],"about_ca_topic_score_codex":0.0000058367614,"about_ca_topic_score_gemma":0.0000016874789,"teacher_disagreement_score":0.03845066,"about_ca_system_score_codex":0.000034581342,"about_ca_system_score_gemma":0.000017806258,"threshold_uncertainty_score":0.49639022},"labels":[],"label_agreement":null},{"id":"W3157261413","doi":"10.1016/j.media.2021.102093","title":"Track-to-Learn: A general framework for tractography with deep reinforcement learning","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Tractography; Reinforcement learning; Artificial intelligence; Computer science; Leverage (statistics); Deep learning; Machine learning; Artificial neural network; Prior probability; Diffusion MRI; Bayesian probability; Magnetic resonance imaging","score_opus":0.02872814233882151,"score_gpt":0.36618501131255343,"score_spread":0.33745686897373195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157261413","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015056881,0.00008116573,0.97365427,0.010084747,0.000009837242,0.000266697,0.0000018221275,0.00017436115,0.0006702271],"genre_scores_gemma":[0.42556107,0.00013686548,0.5672974,0.0052075665,0.00017761257,0.00025923675,0.00018137244,0.000034653407,0.0011441957],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983939,0.00003165636,0.00029353678,0.00044100577,0.0005351157,0.0003047977],"domain_scores_gemma":[0.99866843,0.00016203223,0.00007714288,0.0004265931,0.00023910133,0.00042669225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018855456,0.00015315005,0.00042026737,0.00024182048,0.00014012799,0.000036118377,0.00011536521,0.00009279147,0.0008859508],"category_scores_gemma":[0.0007312249,0.00012123758,0.00036428717,0.0020203195,0.00008655681,0.00005398693,0.000043273874,0.00046225547,0.000010482581],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021467316,0.0048647267,0.15401341,0.0009762996,0.01782873,0.005428767,0.003279643,0.041134972,0.051580306,0.038942862,0.014623289,0.66518027],"study_design_scores_gemma":[0.00521556,0.0026618887,0.035956953,0.00065737485,0.019247787,0.00045507489,0.0011873336,0.5439157,0.047431946,0.0068212776,0.33462122,0.0018279074],"about_ca_topic_score_codex":0.0000122269785,"about_ca_topic_score_gemma":0.000011847303,"teacher_disagreement_score":0.6633524,"about_ca_system_score_codex":0.000026401338,"about_ca_system_score_gemma":0.00007602268,"threshold_uncertainty_score":0.970054},"labels":[],"label_agreement":null},{"id":"W3157623118","doi":"10.1002/dev.22125","title":"Prenatal antidepressant exposure and sex differences in neonatal corpus callosum microstructure","year":2021,"lang":"en","type":"article","venue":"Developmental Psychobiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto; BC Children's Hospital; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Serotonin reuptake inhibitor; Diffusion MRI; White matter; Psychology; Offspring; Sertraline; Prenatal cocaine exposure; Internal medicine; Physiology; Antidepressant; Medicine; Pregnancy; Prenatal exposure; Neuroscience; Biology; Hippocampus; Magnetic resonance imaging; Genetics","score_opus":0.03536373551815285,"score_gpt":0.3114868481929179,"score_spread":0.276123112674765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157623118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997196,0.00086755404,0.0004309724,0.0006603377,0.00009411744,0.00020483235,0.000045535267,0.00006369172,0.00043696817],"genre_scores_gemma":[0.9827862,0.00034512533,0.015388201,0.00085841684,0.000026607822,0.00003293467,0.00015939622,0.000012549613,0.00039061793],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991039,0.000023445631,0.00020448718,0.00040795043,0.000052647138,0.00020759119],"domain_scores_gemma":[0.9996972,0.000034077977,0.00003981764,0.00014057473,0.000021842372,0.00006648614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003068189,0.00013812252,0.0002327553,0.00005473504,0.000049847928,0.000009744135,0.00006838602,0.000098017226,0.00006379031],"category_scores_gemma":[0.000017362345,0.00011951487,0.000023904202,0.00012910606,0.00013475803,0.00003511817,0.00009746873,0.00021769379,0.0000036267982],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004205696,0.000047152484,0.9199842,0.000034279736,0.000016893175,0.00020585983,0.0002283841,6.9609634e-8,0.065207645,0.00023168826,0.00039246745,0.013609281],"study_design_scores_gemma":[0.001055157,0.00006306787,0.9414148,0.00008503414,0.000007710711,0.003517714,0.00020704922,0.000009268154,0.04240256,0.0010693334,0.009986991,0.00018134389],"about_ca_topic_score_codex":0.000012713863,"about_ca_topic_score_gemma":0.000024850007,"teacher_disagreement_score":0.022805087,"about_ca_system_score_codex":0.000026156291,"about_ca_system_score_gemma":0.00005673551,"threshold_uncertainty_score":0.48736748},"labels":[],"label_agreement":null},{"id":"W3157703355","doi":"10.1503/jpn.200167","title":"Acute conceptual disorganization in untreated first-episode psychosis: a combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum","year":2021,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Lawson Health Research Institute; Dalhousie University; Western University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Chrysalis","keywords":"Fractional anisotropy; Cingulum (brain); White matter; Glutamate receptor; Neuroscience; Glutathione; Psychology; Anterior cingulate cortex; Internal medicine; Oxidative stress; Psychosis; Diffusion MRI; Chemistry; Magnetic resonance imaging; Pathology; Medicine; Psychiatry; Cognition; Biochemistry; Radiology","score_opus":0.01456719505833476,"score_gpt":0.2988177442904961,"score_spread":0.28425054923216136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157703355","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99182934,0.0010345316,0.0006130246,0.0060776514,0.00020188879,0.00021484222,0.000002353242,0.000009036348,0.00001731799],"genre_scores_gemma":[0.9969549,0.000976088,0.0014777757,0.000525616,0.000023715522,0.0000029649811,1.737962e-7,0.000008035822,0.00003069724],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999149,0.00004792301,0.0003100113,0.00020413748,0.0001821882,0.00010669104],"domain_scores_gemma":[0.99944955,0.000027801954,0.00020492951,0.00018681923,0.00007752057,0.000053348613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000083710496,0.0000861361,0.00017985124,0.00006460698,0.00012789501,0.000018284803,0.0001061451,0.000015761132,0.0000027733306],"category_scores_gemma":[0.00007699764,0.00006147633,0.000025513335,0.00062706345,0.00017913779,0.00009835718,0.00006513693,0.00020071144,3.8431658e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007568711,0.0005825583,0.9434845,0.0000118946855,0.0000010670558,0.000015589481,0.00024220417,0.0000050582507,0.055047426,0.00020055685,0.0000866624,0.00024682743],"study_design_scores_gemma":[0.0019767547,0.000884751,0.98940974,0.0002269986,0.000059412283,0.0004412131,0.00046008546,0.000776379,0.00477829,0.0007284276,0.00019495212,0.000062988016],"about_ca_topic_score_codex":0.000009489424,"about_ca_topic_score_gemma":0.000049510963,"teacher_disagreement_score":0.050269138,"about_ca_system_score_codex":0.000009920574,"about_ca_system_score_gemma":0.000032502954,"threshold_uncertainty_score":0.25069317},"labels":[],"label_agreement":null},{"id":"W3157720323","doi":"10.3389/fnagi.2021.644137","title":"Automated Midline Estimation for Symmetry Analysis of Cerebral Hemispheres in FLAIR MRI","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Toronto; Toronto Metropolitan University","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Consortium canadien en neurodégénérescence associée au vieillissement; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Sagittal plane; Neuroimaging; Curvature; Artificial intelligence; Hausdorff distance; Pattern recognition (psychology); Mathematics; Computer science; Medicine; Anatomy; Neuroscience; Psychology; Geometry","score_opus":0.032223451133355986,"score_gpt":0.3523278105059971,"score_spread":0.3201043593726411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157720323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35884666,0.0001231614,0.6387354,0.0015169402,0.00015355884,0.00029527827,0.000020483514,0.00020431956,0.00010417636],"genre_scores_gemma":[0.72570467,0.000029708828,0.27368355,0.00040442112,0.0000058785126,0.000031338852,0.000024033718,0.000008818561,0.00010757137],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989735,0.00002121201,0.00028635858,0.00037879765,0.00014799747,0.00019214614],"domain_scores_gemma":[0.99945706,0.00004974581,0.00009394167,0.0002979403,0.000057895337,0.0000434413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013506546,0.000087250555,0.00028606958,0.00038333706,0.000037645455,0.000012144011,0.00012459086,0.000029669885,0.0000024010014],"category_scores_gemma":[0.0003579154,0.00009148322,0.000074123236,0.0029154953,0.000101058686,0.00009706369,0.000042258773,0.00010990091,1.0149848e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038554026,0.00033482138,0.87872416,0.00016398718,0.000017373342,0.000046798104,0.00014363776,0.03797475,0.07245534,0.00053057563,0.003754204,0.005815822],"study_design_scores_gemma":[0.00030112817,0.000019423394,0.16374044,0.00006001562,0.00006588157,0.000005958447,0.000036468176,0.8089883,0.025848983,0.0005090021,0.0003569608,0.00006746705],"about_ca_topic_score_codex":0.000013408117,"about_ca_topic_score_gemma":0.000006839838,"teacher_disagreement_score":0.7710135,"about_ca_system_score_codex":0.000056903726,"about_ca_system_score_gemma":0.00006571082,"threshold_uncertainty_score":0.37305775},"labels":[],"label_agreement":null},{"id":"W3157741688","doi":"10.1101/2021.04.30.442198","title":"Multimodal brain features at preschool age and the relationship with pre-reading measures one year later: an exploratory study","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Psychology; White matter; Fasciculus; Reading (process); Diffusion MRI; Association (psychology); Default mode network; Uncinate fasciculus; Developmental psychology; Cognitive psychology; Grey matter; Superior longitudinal fasciculus; Neuroscience; Audiology; Functional connectivity; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.049359507871745915,"score_gpt":0.29129701714609696,"score_spread":0.24193750927435104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157741688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921819,0.0005935347,0.0022978657,0.0010150691,0.000066256536,0.0031290539,0.000046931254,0.0006556503,0.000013716548],"genre_scores_gemma":[0.98052245,0.000109855544,0.017474815,0.00030034006,0.00021857966,0.0011734769,0.0000020323632,0.00016067001,0.000037767244],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972746,0.0003865225,0.0004011295,0.0011067512,0.00047675386,0.00035428777],"domain_scores_gemma":[0.9969583,0.00025815782,0.00029390113,0.001876432,0.00033074385,0.0002824268],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007400792,0.00048316916,0.0006398351,0.00016454209,0.00040308305,0.00025514813,0.00031926803,0.00025723426,0.0000093658655],"category_scores_gemma":[0.0005168824,0.00037527253,0.00009020269,0.00033735088,0.00031186623,0.00021154222,0.00053808076,0.0012921084,0.000003900174],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020875135,0.0022877706,0.63093287,0.00077172765,0.0008754874,0.00062721473,0.0016026992,0.00027882436,0.35696176,0.002689217,0.00086524955,0.000019688816],"study_design_scores_gemma":[0.0030015046,0.00021393881,0.97519433,0.00066083187,0.0004274755,3.2967907e-7,0.000093764844,0.00018663135,0.019233188,0.00001671455,0.00040324425,0.0005680236],"about_ca_topic_score_codex":0.000056431483,"about_ca_topic_score_gemma":0.00003311668,"teacher_disagreement_score":0.3442615,"about_ca_system_score_codex":0.00018075385,"about_ca_system_score_gemma":0.00024206581,"threshold_uncertainty_score":0.99986994},"labels":[],"label_agreement":null},{"id":"W3157892933","doi":"10.1016/j.neuroimage.2021.118105","title":"Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Artificial intelligence; Sulcus; Cortex (anatomy); Segmentation; Pattern recognition (psychology); Computer vision; Computer science; Neuroscience; Physics; Nuclear magnetic resonance; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.062893996120765,"score_gpt":0.36465059032077024,"score_spread":0.3017565942000052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3157892933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83391905,0.00001598489,0.15037617,0.010960674,0.00013983228,0.0013156494,0.00008434058,0.0023832775,0.0008050344],"genre_scores_gemma":[0.8266153,0.000005510983,0.16199294,0.010574794,0.0000954406,0.0001427231,0.00028571053,0.00007577172,0.0002118084],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855345,0.000057471247,0.0003077104,0.00054488034,0.00023522678,0.0003012282],"domain_scores_gemma":[0.9989175,0.00021367395,0.000114210394,0.0004156854,0.00017703242,0.00016188774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006970575,0.00019231193,0.00022905726,0.00007507945,0.0002525343,0.00005257705,0.00007423482,0.000039981125,0.000041086627],"category_scores_gemma":[0.00045397205,0.00018866135,0.00011084708,0.00023958205,0.000096885255,0.0000906505,0.000045859768,0.0002699811,0.00001597608],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006524199,0.00024667414,0.017621648,0.00006787138,0.0000044727412,0.00010147925,0.00002071177,0.000031438605,0.97558606,0.000870417,0.0030601658,0.0023238156],"study_design_scores_gemma":[0.0028529335,0.00034397485,0.22107024,0.00015340639,0.00011066532,0.00014851891,0.0000593076,0.49610683,0.27566966,0.0005723876,0.0026366762,0.00027539372],"about_ca_topic_score_codex":0.0000034059922,"about_ca_topic_score_gemma":5.2206065e-7,"teacher_disagreement_score":0.6999164,"about_ca_system_score_codex":0.00006858791,"about_ca_system_score_gemma":0.00011398597,"threshold_uncertainty_score":0.76933867},"labels":[],"label_agreement":null},{"id":"W3158036197","doi":"10.3174/ajnr.a7135","title":"Diffusion MRI Microstructural Abnormalities at Term-Equivalent Age Are Associated with Neurodevelopmental Outcomes at 3 Years of Age in Very Preterm Infants","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Cincinnati Children's Hospital Medical Center","keywords":"Bayley Scales of Infant Development; Medicine; Toddler; Corpus callosum; Corticospinal tract; Gestational age; White matter; Diffusion MRI; Pediatrics; Superior longitudinal fasciculus; Fornix; Inferior longitudinal fasciculus; Cohort; Motor skill; Audiology; Cognition; Fractional anisotropy; Psychomotor learning; Psychology; Magnetic resonance imaging; Internal medicine; Developmental psychology; Pathology; Radiology; Psychiatry; Hippocampus","score_opus":0.027758594541992417,"score_gpt":0.30327428062151734,"score_spread":0.2755156860795249,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158036197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9989991,0.00004228916,0.000021434511,0.0006546533,0.00007978082,0.00012328834,0.000025376243,0.000018855497,0.00003517432],"genre_scores_gemma":[0.99676615,0.0002476807,0.0017106591,0.0010527024,0.000017808767,0.0000040453583,0.000024265859,0.000025480018,0.00015123372],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99870396,0.00014453118,0.00051608053,0.00021397762,0.00018087398,0.00024056122],"domain_scores_gemma":[0.99866784,0.00019234707,0.0007480564,0.00022221735,0.00007719795,0.00009235204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006957551,0.00015494236,0.0006887674,0.00014518498,0.00004043999,0.0000055633873,0.000138568,0.000034102046,0.000014499418],"category_scores_gemma":[0.00013678827,0.0001283736,0.00010717625,0.00022815373,0.00045911781,0.000060106006,0.00015724904,0.00029567283,5.340755e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002914637,0.00007153646,0.8706979,0.000012645744,0.00003846868,0.0038720588,0.0003156421,0.0000133465055,0.12368348,0.000003478465,0.00011085737,0.000889108],"study_design_scores_gemma":[0.0010570649,0.0006958322,0.9893657,0.00012288496,0.000039264454,0.0041799257,0.00010234175,0.0000045061083,0.003976165,0.000020807449,0.00032814362,0.00010734556],"about_ca_topic_score_codex":0.000007701238,"about_ca_topic_score_gemma":0.000025903244,"teacher_disagreement_score":0.11970732,"about_ca_system_score_codex":0.00015741152,"about_ca_system_score_gemma":0.00006264684,"threshold_uncertainty_score":0.5234924},"labels":[],"label_agreement":null},{"id":"W3158162652","doi":"10.1101/2021.05.04.442563","title":"BigBrainWarp: Toolbox for integration of BigBrain 3D histology with multimodal neuroimaging","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canada Research Chairs; Canada First Research Excellence Fund; Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada","keywords":"Toolbox; Neuroimaging; Computer science; Cytoarchitecture; Workflow; Neuroanatomy; Data science; Neuroscience; Psychology","score_opus":0.040886385645263826,"score_gpt":0.29584191244531444,"score_spread":0.2549555268000506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158162652","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48186815,0.00046043022,0.51207876,0.0021565098,0.00031139713,0.0021987124,0.00023198347,0.0006724907,0.000021562613],"genre_scores_gemma":[0.67134625,0.000064736756,0.3272585,0.0004735055,0.00014654332,0.0005715688,0.0000039146794,0.00012721558,0.000007793216],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99754024,0.00006858787,0.00061270065,0.0010889595,0.00026923788,0.00042028446],"domain_scores_gemma":[0.99670213,0.0001550128,0.00056241686,0.0014461478,0.000956127,0.00017816205],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026325067,0.0004889406,0.00083501684,0.00034363606,0.00011475242,0.000056762867,0.00030097322,0.00029663663,0.000014726812],"category_scores_gemma":[0.00042739918,0.00047429878,0.00020151216,0.00045999303,0.00024999288,0.000121231904,0.00019220987,0.0007664986,0.0000018437385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014166156,0.0002905377,0.002599279,0.0006955385,0.00008866188,0.00005690805,0.000018593884,0.00006788997,0.994613,0.0011291248,0.0002232428,0.000075541626],"study_design_scores_gemma":[0.0025269163,0.0005412501,0.055597488,0.0019051334,0.00071072095,0.0000011181783,0.000019031462,0.015583718,0.9097417,0.000015549276,0.012166769,0.0011905993],"about_ca_topic_score_codex":0.000041539046,"about_ca_topic_score_gemma":0.0000024927979,"teacher_disagreement_score":0.18947808,"about_ca_system_score_codex":0.00019410373,"about_ca_system_score_gemma":0.0006749993,"threshold_uncertainty_score":0.9997709},"labels":[],"label_agreement":null},{"id":"W3158290997","doi":"10.21203/rs.3.rs-134624/v1","title":"Alterations of White Matter Integrity in Cerebral Small Vessel Disease and Their Correlation with Cognitive Performance: A Trace-Based Spatial Statistics Study","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Anhui University of Science and Technology; Anhui University","keywords":"Internal capsule; White matter; Fasciculus; Hyperintensity; Corona radiata (embryology); Cognition; Diffusion MRI; Psychology; Neuropsychology; Cardiology; Medicine; Audiology; Internal medicine; Magnetic resonance imaging; Neuroscience; Radiology; Fractional anisotropy","score_opus":0.10786503691275992,"score_gpt":0.4086379345883682,"score_spread":0.30077289767560833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158290997","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82592183,0.000069011985,0.17021939,0.0005557543,0.000011089379,0.0025662058,0.00058271876,0.000027712435,0.000046295474],"genre_scores_gemma":[0.99205434,0.000063776395,0.0059626307,0.000035426176,0.000035545596,0.00078508246,0.000973555,0.000032669093,0.000056963858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99837637,0.00025760208,0.0002977473,0.00048171284,0.0003603349,0.0002262302],"domain_scores_gemma":[0.99819845,0.00029725645,0.00010339092,0.00040796568,0.0008487626,0.00014416907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034147137,0.00018790427,0.0003226638,0.00024450858,0.00014956245,0.0000488398,0.00008598905,0.000079398436,0.00005979415],"category_scores_gemma":[0.00015906394,0.00015081091,0.00003380461,0.0002841941,0.00020964559,0.000055937107,0.00025566624,0.001582347,0.0000012429332],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063996547,0.0012078444,0.9921319,0.0015098613,0.000027277749,0.000041240794,0.0018909813,0.00050117035,0.000033364737,0.000025868685,0.00004239788,0.0019481605],"study_design_scores_gemma":[0.00124159,0.00060606067,0.9316138,0.0025048228,0.00006164709,0.000003919231,0.0016262044,0.06177801,0.00022761813,0.00019352716,0.000008367895,0.00013445657],"about_ca_topic_score_codex":0.00021071867,"about_ca_topic_score_gemma":0.00026983782,"teacher_disagreement_score":0.16613252,"about_ca_system_score_codex":0.00009384747,"about_ca_system_score_gemma":0.0006668163,"threshold_uncertainty_score":0.6874598},"labels":[],"label_agreement":null},{"id":"W3158401871","doi":"10.1093/neuros/nyab129","title":"Enhanced Fiber Tractography Using Edema Correction: Application and Evaluation in High-Grade Gliomas","year":2021,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; Diffusion MRI; Edema; Fractional anisotropy; Magnetic resonance imaging; Tractography; Fiber tract; Functional magnetic resonance imaging; Radiology; Nuclear medicine; Surgery","score_opus":0.06992008219545898,"score_gpt":0.3594106578960899,"score_spread":0.2894905757006309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158401871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9804245,0.0002100766,0.017319134,0.00090156915,0.0001924802,0.00044755448,0.0000029065952,0.00013070619,0.00037103752],"genre_scores_gemma":[0.99513507,0.00013441556,0.0038689522,0.00047440542,0.000089719506,0.00014852223,0.000038148766,0.000024197083,0.000086549655],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99893326,0.00006283349,0.00025168556,0.00039436523,0.00020921238,0.00014866465],"domain_scores_gemma":[0.99929833,0.00012932805,0.00009172735,0.00029941395,0.00011825884,0.00006295092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015908193,0.00011106677,0.00018956403,0.00018151046,0.00007098115,0.000019554074,0.000025151334,0.00006030774,0.00003596584],"category_scores_gemma":[0.00010116863,0.00012175678,0.00005485494,0.0007863737,0.000044069933,0.0001029779,0.000022266278,0.00017219545,0.000003494565],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059630023,0.00036412734,0.019263504,0.000047416637,0.000008409659,0.000035612113,0.00004149387,0.00061616045,0.89341486,0.00017192299,0.0004863106,0.08549055],"study_design_scores_gemma":[0.0018735382,0.00010882463,0.49902835,0.00024273881,0.00021336593,0.0010099419,0.000054707587,0.054082785,0.41818008,0.0032429025,0.021461947,0.000500834],"about_ca_topic_score_codex":0.000017748003,"about_ca_topic_score_gemma":0.000004134006,"teacher_disagreement_score":0.47976485,"about_ca_system_score_codex":0.00003862257,"about_ca_system_score_gemma":0.000063503525,"threshold_uncertainty_score":0.4965097},"labels":[],"label_agreement":null},{"id":"W3158565540","doi":"10.1038/s41598-021-93804-6","title":"Distinct tumor signatures using deep learning-based characterization of the peritumoral microenvironment in glioblastomas and brain metastases","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Diffusion MRI; Medicine; Convolutional neural network; Tumour heterogeneity; Pathology; Radiology; Magnetic resonance imaging; Artificial intelligence; Computer science; Cancer; Internal medicine","score_opus":0.021725531046511117,"score_gpt":0.2862008277712664,"score_spread":0.2644752967247553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158565540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958059,0.000096194,0.0031581884,0.0005400798,0.0001249582,0.00023710291,0.0000039024567,0.000022023229,0.000011641172],"genre_scores_gemma":[0.9972438,0.0000013395108,0.0024122968,0.00009598523,0.0000092186965,0.000011763995,0.000052998803,0.000009890321,0.0001626906],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907345,0.000050966235,0.00024483266,0.00034227956,0.00018019327,0.00010826366],"domain_scores_gemma":[0.99935883,0.000020367608,0.00019883699,0.00034418394,0.00004199018,0.000035774003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024005324,0.0000744338,0.00013348223,0.000060766808,0.00012724665,0.000030800693,0.00003228754,0.000014639912,0.00002777333],"category_scores_gemma":[0.00017311773,0.00005757415,0.000043346907,0.00032184063,0.00022565761,0.00004198974,0.000062212646,0.000114375616,1.4903581e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000061345336,0.000078647594,0.040183302,0.000031833562,0.0000018502293,0.00018724852,0.000035727426,0.00022080934,0.95875424,0.000009830687,0.000017939803,0.00047246512],"study_design_scores_gemma":[0.0001609162,0.000024746927,0.23448752,0.00014113536,0.00003174422,0.00050106435,0.000031931457,0.0051997527,0.7512062,0.00023266567,0.007898613,0.00008366536],"about_ca_topic_score_codex":0.000004627392,"about_ca_topic_score_gemma":0.000007158564,"teacher_disagreement_score":0.20754796,"about_ca_system_score_codex":0.000030547333,"about_ca_system_score_gemma":0.000064996464,"threshold_uncertainty_score":0.23478058},"labels":[],"label_agreement":null},{"id":"W3158925026","doi":"10.1016/j.mri.2021.04.015","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Linear regression; Kurtosis; Tensor (intrinsic definition); Mathematics; Nuclear magnetic resonance; Orientation (vector space); Physics; Algorithm; Biological system; Statistics; Optics; Magnetic resonance imaging; Geometry; Medicine","score_opus":0.033325878600253406,"score_gpt":0.3471952327520925,"score_spread":0.31386935415183914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158925026","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10579139,0.032468583,0.8391126,0.016217353,0.00042450146,0.0013212468,0.00003639067,0.0012735015,0.0033544542],"genre_scores_gemma":[0.32902062,0.0010033409,0.6647014,0.0028921477,0.00039415862,0.00012122975,0.000245875,0.000099314886,0.0015219069],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99824554,0.000057390203,0.00038549257,0.00063196046,0.00030764364,0.00037199122],"domain_scores_gemma":[0.99870175,0.000061648745,0.00013102828,0.000677269,0.00027525675,0.00015307424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012483315,0.00023723596,0.00028707387,0.00010904886,0.00028217022,0.00006446148,0.0001248392,0.00004164647,0.00043529595],"category_scores_gemma":[0.0000874159,0.00023096423,0.00010360431,0.00033850028,0.000089868445,0.0003970284,0.00009179533,0.00032848766,0.000025654006],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016177008,0.00028281362,0.028428959,0.000046306308,0.0000033475078,0.00023830397,0.00007406907,0.00006935612,0.3503395,0.00056845363,0.0014707944,0.6183163],"study_design_scores_gemma":[0.004464866,0.00016478861,0.11492762,0.00058385107,0.00011805167,0.0017273503,0.00012606638,0.41868076,0.100387014,0.0047864453,0.35336304,0.00067013316],"about_ca_topic_score_codex":0.000020280444,"about_ca_topic_score_gemma":6.847136e-7,"teacher_disagreement_score":0.6176462,"about_ca_system_score_codex":0.00009464607,"about_ca_system_score_gemma":0.000108591215,"threshold_uncertainty_score":0.94184476},"labels":[],"label_agreement":null},{"id":"W3159817322","doi":"10.1002/hbm.25447","title":"Surface‐Based Connectivity Integration: An atlas‐free approach to jointly study functional and structural connectivity","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"Connectomics; Connectome; Atlas (anatomy); Human Connectome Project; Computer science; Functional connectivity; Diffusion MRI; Brain atlas; Artificial intelligence; White matter; Tractography; Neuroscience; Machine learning; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Biology; Medicine","score_opus":0.16487722636405025,"score_gpt":0.3651398220156734,"score_spread":0.20026259565162316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159817322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81409246,0.00001363998,0.18121044,0.0027110963,0.000030436277,0.0007466492,0.000013227768,0.00025214496,0.0009298925],"genre_scores_gemma":[0.9696531,2.9728335e-7,0.028410353,0.0014153692,0.00010499496,0.00007597971,0.00009817421,0.000026420936,0.00021530097],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99854094,0.00014554278,0.00022439646,0.00065726833,0.00022544875,0.0002063923],"domain_scores_gemma":[0.99874115,0.00017261962,0.00007047,0.0006551792,0.00019275134,0.0001678074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030679905,0.00019427153,0.0002986883,0.00008626493,0.00047990336,0.000075235,0.000091852555,0.00004950813,0.000050532402],"category_scores_gemma":[0.0003208371,0.00019170853,0.000053958043,0.00031584667,0.00007809682,0.00015773319,0.0001268288,0.00030456737,0.0000020343753],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014414355,0.0016108964,0.10174271,0.00014215175,0.00009403762,0.00006481496,0.0020465855,0.0011232368,0.8515101,0.033531822,0.0053914683,0.0025980214],"study_design_scores_gemma":[0.00194246,0.00041606723,0.97233903,0.000059755843,0.000041537987,0.00013216684,0.0019113034,0.011327234,0.0031458905,0.0070692473,0.0012746925,0.0003405828],"about_ca_topic_score_codex":0.0000396339,"about_ca_topic_score_gemma":0.00007699484,"teacher_disagreement_score":0.87059635,"about_ca_system_score_codex":0.000080001555,"about_ca_system_score_gemma":0.000067075576,"threshold_uncertainty_score":0.7817647},"labels":[],"label_agreement":null},{"id":"W3159963675","doi":"10.1007/s11682-021-00474-z","title":"Microstructural white matter alterations in Alzheimer’s disease and amnestic mild cognitive impairment and its diagnostic value based on diffusion kurtosis imaging: a tract-based spatial statistics study","year":2021,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Psychology; Corpus callosum; Montreal Cognitive Assessment; Receiver operating characteristic; Splenium; Kurtosis; Audiology; Alzheimer's disease; Internal medicine; Cognition; Medicine; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Neuroscience; Disease; Radiology; Statistics; Mathematics","score_opus":0.031105694128074186,"score_gpt":0.34146480268428503,"score_spread":0.31035910855621085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3159963675","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860356,0.0004256331,0.004799867,0.0067854193,0.000037304297,0.0013993203,0.00044820923,0.00006393455,0.0000047244707],"genre_scores_gemma":[0.9927689,0.000019799674,0.0032911676,0.0031786498,0.000031493462,0.00039748434,0.00025422472,0.000037177568,0.0000211053],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986734,0.00009722248,0.00026646833,0.0005540868,0.00017301527,0.00023580242],"domain_scores_gemma":[0.99888223,0.0005324643,0.00007182334,0.00019531668,0.0000941282,0.00022405492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008019089,0.00024235628,0.00023546127,0.00015054941,0.00019608866,0.00010514947,0.000034111687,0.000019779041,0.000029737705],"category_scores_gemma":[0.00017774942,0.00023066587,0.000029916939,0.0001295796,0.000115678165,0.00007708887,0.000054088763,0.0002137734,0.0000015805942],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010639577,0.0014819894,0.98908865,0.000047769074,0.000005438624,0.00058159704,0.00021743558,0.0000108045015,0.0025314256,0.0000077982495,0.00020457723,0.0057161395],"study_design_scores_gemma":[0.0030359426,0.00014302095,0.9678237,0.00037031583,0.00077963935,0.000079528545,0.00017768727,0.026559755,0.00074697897,0.00003927541,0.000011382124,0.0002328122],"about_ca_topic_score_codex":0.00006987632,"about_ca_topic_score_gemma":0.0000126078685,"teacher_disagreement_score":0.02654895,"about_ca_system_score_codex":0.000029398476,"about_ca_system_score_gemma":0.00007559567,"threshold_uncertainty_score":0.9406281},"labels":[],"label_agreement":null},{"id":"W3160785216","doi":"10.1089/brain.2020.0919","title":"Selective Effects of Healthy Cognitive Aging and Catechol- <i>O</i> -Methyl Transferase Polymorphism on Limbic White Matter Tracts","year":2021,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Uncinate fasciculus; Cingulum (brain); White matter; Fractional anisotropy; Psychology; Fasciculus; Diffusion MRI; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.02791763727745839,"score_gpt":0.32847616901103766,"score_spread":0.30055853173357927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160785216","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9530311,0.00027983094,0.017948698,0.026293607,0.000041482588,0.0008442769,0.000038050995,0.00014216523,0.0013807395],"genre_scores_gemma":[0.9866867,0.000059787446,0.0009935972,0.011857918,0.00004656117,0.00011174264,0.00001605703,0.00003824247,0.00018938987],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987243,0.00016008725,0.00019317721,0.00051794475,0.00015128432,0.00025324526],"domain_scores_gemma":[0.9977376,0.0016340062,0.00008039976,0.00026483898,0.00013808056,0.00014510698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016386,0.00019249356,0.0003860386,0.00010945857,0.00012182089,0.000012308009,0.000040031427,0.00008080475,0.000018037776],"category_scores_gemma":[0.00039163046,0.0001959737,0.000084474246,0.00035690516,0.000110042834,0.00008728828,0.000037603353,0.0004096433,0.000005828584],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001265403,0.002991425,0.06256881,0.0017429201,0.00020677278,0.0004947984,0.002204975,0.0000051572347,0.8614793,0.002255352,0.0039520143,0.060833104],"study_design_scores_gemma":[0.0023677922,0.00070799794,0.27615094,0.0004971649,0.00009838713,0.00020932229,0.00006721155,0.00004016871,0.71747994,0.0017715861,0.00038519353,0.00022428921],"about_ca_topic_score_codex":0.000022785925,"about_ca_topic_score_gemma":0.000013106346,"teacher_disagreement_score":0.21358214,"about_ca_system_score_codex":0.000047726076,"about_ca_system_score_gemma":0.00010162954,"threshold_uncertainty_score":0.79915756},"labels":[],"label_agreement":null},{"id":"W3161462824","doi":"10.7554/elife.62929","title":"Bundle-specific associations between white matter microstructure and Aβ and tau pathology in preclinical Alzheimer’s disease","year":2021,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Université de Sherbrooke; McGill University; Douglas Mental Health University Institute","funders":"National Institute on Aging; Canadian Institutes of Health Research; Canada Foundation for Innovation; Fondation Jean-Louis Lévesque; Douglas Foundation","keywords":"Uncinate fasciculus; White matter; Fractional anisotropy; Cingulum (brain); Pathology; Diffusion MRI; Pathological; Fasciculus; Senile plaques; Medicine; Alzheimer's disease; Neuroscience; Disease; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.10071480621012831,"score_gpt":0.3869831842590818,"score_spread":0.2862683780489535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161462824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96950275,0.0026460374,0.0009773315,0.026001392,0.000035618552,0.00030289195,0.00022719035,0.00007326113,0.0002335538],"genre_scores_gemma":[0.9840725,0.00054742175,0.011719564,0.0030798623,0.00014594989,0.000028526798,0.00018205821,0.000019950978,0.00020415867],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992513,0.000037678114,0.00020331667,0.00029992507,0.00007435642,0.00013338792],"domain_scores_gemma":[0.99946,0.00009133321,0.000050087936,0.0002307852,0.000040945833,0.00012686952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007023732,0.00008481778,0.00019618157,0.00003543042,0.00005501983,0.000016406071,0.000032117205,0.000065328204,0.00004351409],"category_scores_gemma":[0.00006463602,0.00008235025,0.000027300464,0.00010432705,0.00008183693,0.000035735313,0.00007690922,0.0002282053,0.000008113283],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008480359,0.00004450568,0.9937896,0.0000061698474,0.0000076022093,0.00003662575,0.000056315796,4.0070134e-7,0.00059795356,0.00015569064,0.004206896,0.0010897318],"study_design_scores_gemma":[0.00037250327,0.000018009734,0.9816261,0.000020682184,0.000056716075,0.00003018998,0.000010485422,0.0000072818834,0.00033896972,0.0011606459,0.016284166,0.00007426484],"about_ca_topic_score_codex":0.0000014721137,"about_ca_topic_score_gemma":0.000002822187,"teacher_disagreement_score":0.022921529,"about_ca_system_score_codex":0.000013146886,"about_ca_system_score_gemma":0.000031226,"threshold_uncertainty_score":0.33581457},"labels":[],"label_agreement":null},{"id":"W3161498656","doi":"10.1016/j.euroneuro.2021.04.007","title":"White matter microstructure alterations in cortico-striatal networks are associated with parkinsonism in schizophrenia spectrum disorders","year":2021,"lang":"en","type":"article","venue":"European Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre; University of Ottawa","funders":"Canadian Institutes of Health Research; Bundesministerium für Bildung und Forschung; Bundesministerium für Forschung und Technologie; Paul Scherrer Institut; Deutsche Forschungsgemeinschaft","keywords":"Parkinsonism; Fractional anisotropy; White matter; Corpus callosum; Neuroscience; Psychology; Diffusion MRI; Medicine; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.016529657064770126,"score_gpt":0.2938555308694761,"score_spread":0.27732587380470597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161498656","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9840238,0.000105104584,0.0014100351,0.011163405,0.00027472788,0.00057540456,0.00002961363,0.00025792967,0.0021599438],"genre_scores_gemma":[0.9913346,0.00020897514,0.00083057355,0.0068272115,0.00014158296,0.000039753908,0.000100088095,0.0001322625,0.0003849621],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979379,0.00040526607,0.00045716044,0.00064930005,0.00011237547,0.0004379762],"domain_scores_gemma":[0.9991935,0.000073830466,0.00019571168,0.00037977909,0.000036703845,0.00012045624],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00010790566,0.00025500695,0.00032870244,0.00017511418,0.000074473784,0.000035434372,0.00015489751,0.000056642315,0.0001785085],"category_scores_gemma":[0.000037278136,0.0002490545,0.00006301086,0.0007957368,0.0001239121,0.00007666336,0.000087257744,0.00092131644,0.000026915735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014740998,0.0012014874,0.9401971,0.000029948851,0.000067151836,0.0048682494,0.0002405252,0.0054631946,0.035584565,0.00010473643,0.009460496,0.0013084182],"study_design_scores_gemma":[0.00479104,0.00011882587,0.98789483,0.00008047309,0.000035984758,0.00021411122,0.00001647764,0.0009861485,0.00014593724,0.00011210249,0.005378276,0.00022578095],"about_ca_topic_score_codex":0.0000035701748,"about_ca_topic_score_gemma":0.00011887997,"teacher_disagreement_score":0.047697715,"about_ca_system_score_codex":0.000062382074,"about_ca_system_score_gemma":0.00004905683,"threshold_uncertainty_score":0.9999962},"labels":[],"label_agreement":null},{"id":"W3161771687","doi":"10.1016/j.ynirp.2021.100010","title":"Diffusion imaging changes in the treated tract following focused ultrasound thalamotomy for tremor","year":2021,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; Hotchkiss Brain Institute; University of Alberta; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation","keywords":"Thalamotomy; Medicine; Diffusion MRI; Thalamus; Dentate nucleus; Lesion; Fractional anisotropy; Internal capsule; Essential tremor; White matter; Magnetic resonance imaging; Tractography; Neuroscience; Radiology; Psychology; Pathology; Cerebellum; Parkinson's disease; Deep brain stimulation; Internal medicine; Physical medicine and rehabilitation","score_opus":0.054547398926522266,"score_gpt":0.34742060279631054,"score_spread":0.29287320386978827,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161771687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98375696,0.00023366859,0.0032613168,0.008254572,0.00012230642,0.0015659485,0.000008898781,0.00030348668,0.0024928472],"genre_scores_gemma":[0.992688,0.000086393076,0.0045445072,0.0016183553,0.000116338386,0.00034060856,0.0000889739,0.000058462367,0.00045834298],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984099,0.000058948262,0.00035566138,0.00059469644,0.00025801815,0.00032277277],"domain_scores_gemma":[0.9985186,0.00036833755,0.00016201701,0.0008062151,0.00007746822,0.00006737088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026799078,0.00020255407,0.00030053634,0.000098593584,0.00015634106,0.0000626213,0.000087576904,0.000040489896,0.00001621845],"category_scores_gemma":[0.0005253353,0.00015374254,0.00021105172,0.00042201614,0.00003867254,0.00010256143,0.00003264983,0.00024918022,0.0000010012515],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036759415,0.0007906446,0.2174074,0.0000818544,0.000013579361,0.021666603,0.00028289968,0.0000021879114,0.73135716,0.00004846504,0.0017789807,0.026533468],"study_design_scores_gemma":[0.0028612474,0.00026380146,0.6429741,0.000358586,0.00043209098,0.029614497,0.00034510822,0.00092682504,0.210414,0.0027172826,0.108460404,0.00063207623],"about_ca_topic_score_codex":0.000019222422,"about_ca_topic_score_gemma":0.000011537593,"teacher_disagreement_score":0.52094316,"about_ca_system_score_codex":0.00003934003,"about_ca_system_score_gemma":0.00005703053,"threshold_uncertainty_score":0.6269439},"labels":[],"label_agreement":null},{"id":"W3161909371","doi":"10.21203/rs.3.rs-115316/v3","title":"Plasma P-tau181 levels reflects white matter microstructural changes across Alzheimer’s disease progression","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Biomarker; Dementia; Alzheimer's Disease Neuroimaging Initiative; Internal medicine; Cognitive decline; Prospective cohort study; Psychology; Medicine; Neuroimaging; Cohort; Disease; Cardiology; Oncology; Neuroscience; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.2598738981199028,"score_gpt":0.531342639002622,"score_spread":0.2714687408827192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3161909371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93737257,0.005457943,0.0006187689,0.04653652,0.0002977733,0.006068164,0.0018019972,0.0007512347,0.0010950264],"genre_scores_gemma":[0.9818363,0.00050412,0.012142446,0.0005195833,0.000505272,0.0015502261,0.0012556097,0.00015202383,0.0015343833],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.995934,0.00023451021,0.00033925817,0.001288735,0.0011313736,0.0010720945],"domain_scores_gemma":[0.99650025,0.00011206486,0.00015272417,0.0017634886,0.00085466146,0.00061678444],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0004217709,0.00042549009,0.00052851235,0.00023286774,0.0004633572,0.00031005612,0.00047142108,0.0003041595,0.00037201555],"category_scores_gemma":[0.0001773627,0.0003658558,0.00021929518,0.000486543,0.00039093377,0.000091834096,0.0024000786,0.0023985037,0.00007964471],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029474956,0.0019496342,0.5229324,0.014257369,0.0006695617,0.0059175184,0.0056903856,0.00011139732,0.103839934,0.00027914756,0.12475341,0.21665174],"study_design_scores_gemma":[0.0016225709,0.00042756432,0.848181,0.010866837,0.00023849546,0.00029419461,0.00076921884,0.0008850037,0.09282504,0.0018908461,0.04075918,0.0012400239],"about_ca_topic_score_codex":0.000022987231,"about_ca_topic_score_gemma":0.000017483719,"teacher_disagreement_score":0.32524863,"about_ca_system_score_codex":0.00020890468,"about_ca_system_score_gemma":0.0004504399,"threshold_uncertainty_score":0.999903},"labels":[],"label_agreement":null},{"id":"W3162365865","doi":"10.1089/brain.2020.0930","title":"Cortical Surfaces Integration with Tractography for Structural Connectivity Analysis","year":2021,"lang":"en","type":"review","venue":"Brain Connectivity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Université de Sherbrooke","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Computer science; Neuroscience; Artificial intelligence; Magnetic resonance imaging; Psychology","score_opus":0.12736148527299299,"score_gpt":0.4353202302168239,"score_spread":0.3079587449438309,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162365865","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026154234,0.70367396,0.28860846,0.0006395133,0.000062929925,0.003399052,0.00044985884,0.0004219698,0.00012880389],"genre_scores_gemma":[0.055791035,0.91168714,0.02793985,0.0003445927,0.00023544393,0.0016917256,0.0020004457,0.00016393374,0.00014584915],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977091,0.0002675081,0.00045520082,0.0009933031,0.00024142682,0.00033343717],"domain_scores_gemma":[0.99495083,0.003430012,0.00038782536,0.00078786747,0.0002824112,0.00016104466],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038122392,0.0005031141,0.002505552,0.00037105987,0.00023082705,0.00006838137,0.00014132637,0.00026577423,0.000035755445],"category_scores_gemma":[0.0010249882,0.00036697276,0.0012380464,0.0018544836,0.00018264432,0.00012247007,0.000046978388,0.00072206167,0.0000011730757],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009064804,0.00026956334,0.0007542555,0.0030567897,0.0023026993,0.000031217383,0.000033832635,0.000009839629,0.0000392052,0.0057741236,0.00061124057,0.9870266],"study_design_scores_gemma":[0.0009842818,0.00070982554,0.005072465,0.0040413565,0.022188831,0.00039305002,0.000056921497,0.0021550257,0.00015989534,0.0009159767,0.96214324,0.0011791493],"about_ca_topic_score_codex":0.00003629149,"about_ca_topic_score_gemma":0.00016369877,"teacher_disagreement_score":0.9858474,"about_ca_system_score_codex":0.00012236767,"about_ca_system_score_gemma":0.00029509948,"threshold_uncertainty_score":0.9998782},"labels":[],"label_agreement":null},{"id":"W3162628709","doi":"10.1002/hbm.25459","title":"De‐identification procedures for magnetic resonance images and the impact on structural brain measures at different ages","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Norman Cousins Center for Psychoneuroimmunology; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; GE Healthcare; Genentech; National Institutes of Health; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Association; Fujirebio US; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Merck; Alzheimer's Drug Discovery Foundation; AbbVie; Foundation for the National Institutes of Health; Meso Scale Diagnostics","keywords":"Voxel; Intraclass correlation; Psychology; Brain size; Magnetic resonance imaging; Neuroimaging; Audiology; Medicine; Neuroscience; Developmental psychology; Radiology; Psychometrics","score_opus":0.05968867952673323,"score_gpt":0.3625555965484898,"score_spread":0.30286691702175655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162628709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96080345,0.002500047,0.005702971,0.029436577,0.000017138063,0.001123217,0.000028477481,0.0001588827,0.00022924466],"genre_scores_gemma":[0.99354565,0.00006790743,0.001164185,0.001671506,0.00009869996,0.00025319264,0.000045839013,0.000024908486,0.0031280895],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991041,0.00006427785,0.00018990302,0.00031430082,0.00012729934,0.00020014634],"domain_scores_gemma":[0.99906886,0.0003872955,0.0000814094,0.00033114653,0.000077615674,0.000053665837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001845292,0.00014454527,0.0001879454,0.000048461494,0.00045398425,0.00007768461,0.00008569478,0.00003264923,0.000020934976],"category_scores_gemma":[0.0005870369,0.00009398974,0.00008881123,0.00008395015,0.0001693844,0.000036392797,0.00005429446,0.00012577795,8.2132374e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017176618,0.00004109764,0.0058824597,0.0001885993,0.000019538253,0.000007866626,0.0007703085,0.000014781163,0.93707585,0.012803132,0.028731646,0.014292978],"study_design_scores_gemma":[0.0013961097,0.00009126465,0.94388986,0.0002059168,0.00002787519,0.00010901045,0.000099842924,0.00078897673,0.014150626,0.03323476,0.00586126,0.00014450627],"about_ca_topic_score_codex":0.000007672303,"about_ca_topic_score_gemma":0.000007955405,"teacher_disagreement_score":0.9380074,"about_ca_system_score_codex":0.00007636082,"about_ca_system_score_gemma":0.000020789821,"threshold_uncertainty_score":0.38327903},"labels":[],"label_agreement":null},{"id":"W3162733792","doi":"10.1002/hbm.25455","title":"Enhanced detection of cortical atrophy in Alzheimer's disease using structural MRI with anatomically constrained longitudinal registration","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; Canadian Institutes of Health Research; School of Medicine, Indiana University; National Institute on Aging; National Institutes of Health","keywords":"Atrophy; Magnetic resonance imaging; Neuroimaging; Brain size; Alzheimer's disease; Cognitive impairment; Neuroscience; Psychology; Cognition; Medicine; Pathology; Disease; Radiology","score_opus":0.07463761926639617,"score_gpt":0.35159303328661884,"score_spread":0.27695541402022267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162733792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7487929,0.000044228924,0.25021642,0.00053578,0.000009214277,0.00023770079,0.0000034603993,0.000056001118,0.00010430093],"genre_scores_gemma":[0.9789352,0.000002615105,0.020820139,0.00012842819,0.000044162545,0.000014756177,0.000030111918,0.000015490468,0.000009105597],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990465,0.000040684714,0.0002966602,0.0003050263,0.0001528705,0.00015824058],"domain_scores_gemma":[0.9993667,0.000049410177,0.00012584643,0.0002527914,0.000117393734,0.000087886605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006930386,0.00011248903,0.0002016297,0.00009102502,0.000116349314,0.000014512906,0.000043029802,0.000035354908,0.00001966955],"category_scores_gemma":[0.00007752219,0.0001107485,0.00005033179,0.00028301572,0.0001778284,0.000077412544,0.000023495322,0.00019988984,3.276859e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010032425,0.00004062642,0.0066753123,0.000042494696,0.000022669432,0.00008911504,0.000055177927,0.0002417715,0.9878199,0.004380882,0.0000041677804,0.0005275661],"study_design_scores_gemma":[0.0022198597,0.00021328653,0.87944025,0.0006216248,0.00020120681,0.00024570423,0.00024541878,0.027642725,0.082942285,0.0057792007,0.00009119088,0.00035724818],"about_ca_topic_score_codex":0.0000147550045,"about_ca_topic_score_gemma":0.00002746363,"teacher_disagreement_score":0.9048776,"about_ca_system_score_codex":0.00005331019,"about_ca_system_score_gemma":0.000102469516,"threshold_uncertainty_score":0.4516193},"labels":[],"label_agreement":null},{"id":"W3163201789","doi":"10.3389/fnins.2021.634063","title":"Advanced Analysis of Diffusion Tensor Imaging Along With Machine Learning Provides New Sensitive Measures of Tissue Pathology and Intra-Lesion Activity in Multiple Sclerosis","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"NIH Blueprint for Neuroscience Research; Division of Graduate Education; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; Alberta Innovates; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Government of Alberta","keywords":"Diffusion MRI; Fractional anisotropy; Tractography; Lesion; White matter; Medicine; Voxel; Receiver operating characteristic; Multiple sclerosis; Orientation (vector space); Artificial intelligence; Magnetic resonance imaging; Pattern recognition (psychology); Nuclear medicine; Radiology; Computer science; Pathology; Mathematics","score_opus":0.05387696443768367,"score_gpt":0.29893961324391133,"score_spread":0.24506264880622766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163201789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8285664,0.00014802965,0.1706349,0.0003779276,0.00002240444,0.00021381504,0.000006413449,0.000021698004,0.000008412238],"genre_scores_gemma":[0.94437695,0.00041671665,0.055077422,0.00008317957,0.0000028533796,0.000006251235,0.0000033783804,0.000009423913,0.000023802022],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989388,0.00009114471,0.00019917352,0.0004379826,0.0001723944,0.00016052628],"domain_scores_gemma":[0.99944097,0.000081151564,0.000148796,0.00020159691,0.00007208932,0.000055395547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001377189,0.00010511411,0.00038104833,0.00036253742,0.00005091605,0.000006287184,0.00006145871,0.000024451681,4.3840458e-7],"category_scores_gemma":[0.0005508034,0.00009198431,0.00002871429,0.0013932622,0.00026710355,0.00012964381,0.00007824313,0.0002094348,1.5153244e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075661505,0.000056035675,0.4690354,0.000013537777,0.0000018674918,0.000050747894,0.00013394935,0.00079110084,0.4967064,0.0000030264353,0.0000018873401,0.033130407],"study_design_scores_gemma":[0.0005189421,0.00009737898,0.72608036,0.00011490615,0.000058391244,0.00002855329,0.00014067758,0.06685692,0.20596969,0.000027355673,0.00003737626,0.00006944315],"about_ca_topic_score_codex":0.00014389853,"about_ca_topic_score_gemma":0.00010167961,"teacher_disagreement_score":0.2907367,"about_ca_system_score_codex":0.00002966394,"about_ca_system_score_gemma":0.000054472315,"threshold_uncertainty_score":0.37510112},"labels":[],"label_agreement":null},{"id":"W3163549178","doi":"10.3389/fneur.2021.631330","title":"Case Report: An MRI Traumatic Brain Injury Longitudinal Case Study at 7 Tesla: Pre- and Post-injury Structural Network and Volumetric Reorganization and Recovery","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"National Institute of Mental Health; National Institutes of Health; U.S. Department of Defense","keywords":"Traumatic brain injury; White matter; Fractional anisotropy; Neuroimaging; Diffuse axonal injury; Diffusion MRI; Blast injury; Connectome; Medicine; Tractography; Psychology; Poison control; Physical medicine and rehabilitation; Magnetic resonance imaging; Neuroscience; Radiology; Functional connectivity; Psychiatry","score_opus":0.02542905139534749,"score_gpt":0.3231293955100278,"score_spread":0.29770034411468027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163549178","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937979,0.0006059361,0.003071245,0.0014254448,0.000215868,0.000769001,0.000018999084,0.00008538623,0.000010202461],"genre_scores_gemma":[0.98539525,0.00015197534,0.0131329,0.0009683779,0.00008690609,0.000034528683,0.000037061378,0.000037563408,0.00015543393],"study_design_codex":"observational","study_design_gemma":"case_report","domain_scores_codex":[0.998404,0.00018701637,0.00037864293,0.00069484947,0.00008685954,0.00024863376],"domain_scores_gemma":[0.9990897,0.00011343387,0.0001466782,0.00042868668,0.00008340969,0.00013805363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020584562,0.00018477863,0.000374626,0.00020766881,0.00021134426,0.000028631177,0.000038143207,0.00010674987,0.000007782202],"category_scores_gemma":[0.0003023743,0.00019039726,0.000018936631,0.0005572223,0.00015376645,0.00015528381,0.00016848523,0.000331814,1.2252447e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003404011,0.000106545136,0.817003,0.0000495403,0.000026108984,0.1677535,0.00037763297,0.000022191012,0.00032948997,0.000015196298,0.0032744387,0.010701919],"study_design_scores_gemma":[0.0008727815,0.0021650742,0.35849428,0.000011498728,0.00013952982,0.63355345,0.00034607056,0.0031522012,0.000057567664,0.00073200953,0.00027947265,0.00019605077],"about_ca_topic_score_codex":0.0000999207,"about_ca_topic_score_gemma":0.00013103135,"teacher_disagreement_score":0.46579996,"about_ca_system_score_codex":0.000032092,"about_ca_system_score_gemma":0.000040525305,"threshold_uncertainty_score":0.7764175},"labels":[],"label_agreement":null},{"id":"W3163922138","doi":"10.1176/appi.ajp.2020.20111581r","title":"Ubiquitous Dopamine Deficit Hypotheses in Cocaine Use Disorder Lack Support: Response to Leyton","year":2021,"lang":"en","type":"letter","venue":"American Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal College of Physicians and Surgeons of Canada","funders":"National Institute of Mental Health","keywords":"Dopamine; Psychology; Addiction; Neuroscience; Psychiatry; Psychoanalysis; Medicine","score_opus":0.05656430066100987,"score_gpt":0.35209508265787426,"score_spread":0.2955307819968644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163922138","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25275016,0.00031715157,0.0033725316,0.74259114,0.00041288626,0.00035731855,0.000060813167,0.000052073265,0.00008593281],"genre_scores_gemma":[0.03444974,0.00068693777,0.13527574,0.82331455,0.003077222,0.000048541177,0.00007818331,0.00025702207,0.0028120659],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973881,0.00022967457,0.0009852869,0.00044264045,0.000498514,0.0004557881],"domain_scores_gemma":[0.9973973,0.00047266678,0.00089496904,0.0007588745,0.00027824345,0.0001979357],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032586043,0.0003870236,0.0010829355,0.00070715544,0.000048399717,0.00004596494,0.00034072655,0.000158325,0.000096456846],"category_scores_gemma":[0.0004104397,0.00034535513,0.00032082744,0.000943903,0.00020582958,0.00010245137,0.00008227512,0.0021909527,0.000017535644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020107713,0.0005160124,0.04521484,0.00012798177,0.000109030996,0.0033248907,0.00009004162,0.000043114607,0.0014636521,0.000033284494,0.93858683,0.008479523],"study_design_scores_gemma":[0.00092779694,0.002879323,0.022090206,0.000860239,0.00019171277,0.003729852,0.00027259358,0.000004000336,0.00007054893,0.00022533297,0.9683446,0.0004037922],"about_ca_topic_score_codex":0.00006770501,"about_ca_topic_score_gemma":0.00004130067,"teacher_disagreement_score":0.21830042,"about_ca_system_score_codex":0.00014052517,"about_ca_system_score_gemma":0.000668895,"threshold_uncertainty_score":0.99989986},"labels":[],"label_agreement":null},{"id":"W3163936868","doi":"10.1002/hbm.25473","title":"Comparison of structural MRI brain measures between 1.5 and 3 T: Data from the Lothian Birth Cohort 1936","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Medical Research Council; National Institutes of Health; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Age UK; Medical Research Council Canada; Mrs Gladys Row Fogo Charitable Trust; Wellcome Trust; University of Texas at Austin","keywords":"Cohort; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology; Pathology","score_opus":0.25965208150653385,"score_gpt":0.44026309963532184,"score_spread":0.180611018128788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163936868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8988112,0.0012320979,0.05354243,0.04389106,0.000037882248,0.0007290861,0.00040663304,0.00024843361,0.0011011743],"genre_scores_gemma":[0.9871077,0.000012856001,0.010307042,0.0014660864,0.00024371925,0.000008490054,0.0006316636,0.000022478505,0.00019997546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988564,0.000075925636,0.00030325848,0.0004044668,0.00020664408,0.00015326054],"domain_scores_gemma":[0.9982839,0.00042000864,0.00012997599,0.0010403903,0.00006285781,0.00006283923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026336274,0.0001215672,0.00032056522,0.000034225293,0.00025472013,0.00003228179,0.00028562435,0.000042448006,0.000051706516],"category_scores_gemma":[0.00024851027,0.00009715896,0.000034080156,0.00015306045,0.00017524272,0.00006869243,0.00031478255,0.00026446828,0.0000016948819],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004210236,0.00001747206,0.9059487,0.000041264273,0.000068490524,0.000005475142,0.00050574477,0.0000036764668,0.06650551,0.0016633705,0.022481678,0.0027544377],"study_design_scores_gemma":[0.00029613156,0.000019313755,0.9140843,0.0001334866,0.000048416656,0.000009124512,0.00027030346,0.0006425319,0.0012935674,0.0053263316,0.077772364,0.00010411781],"about_ca_topic_score_codex":0.000093487615,"about_ca_topic_score_gemma":0.00006637761,"teacher_disagreement_score":0.08829649,"about_ca_system_score_codex":0.000014828395,"about_ca_system_score_gemma":0.000034483375,"threshold_uncertainty_score":0.39620274},"labels":[],"label_agreement":null},{"id":"W3164344838","doi":"10.1017/s1092852921000584","title":"Investigation of endophenotype potential of decreased fractional anisotropy in pediatric bipolar disorder patients and unrelated offspring of bipolar disorder patients","year":2021,"lang":"en","type":"article","venue":"CNS Spectrums","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Endophenotype; Fractional anisotropy; Bipolar disorder; Bipolar I disorder; Offspring; Medicine; Psychology; Internal medicine; Cardiology; Diffusion MRI; Magnetic resonance imaging; Neuroscience; Mania; Lithium (medication); Pregnancy; Cognition; Biology; Radiology; Genetics","score_opus":0.014430948029039365,"score_gpt":0.2563086905501126,"score_spread":0.24187774252107322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164344838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950474,0.0009770158,0.0033952706,0.00012937534,0.00003846751,0.000309851,0.000057401216,0.000025146737,0.00002010032],"genre_scores_gemma":[0.9936208,0.00082024327,0.0052687125,0.0000294526,0.000019539339,0.000010240988,0.00020129232,0.000021575026,0.00000815067],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989352,0.000036508074,0.00042051682,0.00023812399,0.00023536119,0.00013427933],"domain_scores_gemma":[0.9992049,0.000048652564,0.00026521392,0.00021154835,0.00020234656,0.00006735777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046609097,0.000117397794,0.00025440753,0.00019669122,0.00003602019,0.000002884074,0.000054524935,0.000066257526,0.00003330651],"category_scores_gemma":[0.00015046512,0.00011992541,0.000054922137,0.0005712563,0.000092233684,0.00010814014,0.000058563255,0.00016499864,6.8105544e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006121062,0.00040685385,0.9772333,0.00010367922,0.00001368492,0.0000013867958,0.000040078525,0.00004070797,0.019961216,0.000846742,0.000009772246,0.0012814001],"study_design_scores_gemma":[0.0017643076,0.00018840258,0.96902287,0.00004657598,0.00008441782,0.0000020599284,0.000013814132,0.0005083893,0.026319092,0.001645002,0.00031380824,0.00009126957],"about_ca_topic_score_codex":0.0001448086,"about_ca_topic_score_gemma":0.000011953328,"teacher_disagreement_score":0.008210407,"about_ca_system_score_codex":0.000030132931,"about_ca_system_score_gemma":0.0000822792,"threshold_uncertainty_score":0.48904163},"labels":[],"label_agreement":null},{"id":"W3164541516","doi":"10.1038/s41380-021-01128-8","title":"White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis","year":2021,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"National Center for Advancing Translational Sciences; National Institute of Mental Health; National Institute of General Medical Sciences; National Health and Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; U.S. Department of Health and Human Services","keywords":"Psychosis; White matter; Prodrome; Fractional anisotropy; Psychology; Internal medicine; Cohort; Prospective cohort study; Magnetic resonance imaging; Young adult; Medicine; Pediatrics; Psychiatry","score_opus":0.015880431222333433,"score_gpt":0.2987346395342591,"score_spread":0.28285420831192565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164541516","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74367714,0.00030755805,0.034057785,0.22101682,0.00007632504,0.0005453744,0.000034131845,0.00006559651,0.00021926143],"genre_scores_gemma":[0.8369441,0.00015381072,0.09139198,0.070631936,0.00004413304,0.00047271178,0.000042399366,0.00006125516,0.0002576918],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989494,0.00004644502,0.00019955247,0.0004269481,0.0001546655,0.00022298226],"domain_scores_gemma":[0.99930006,0.0000096589165,0.00005502743,0.00044069756,0.00004517061,0.00014935437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009407805,0.00016109468,0.0001733545,0.000103072416,0.00009420164,0.000026372663,0.000081223414,0.000055183107,0.000040664778],"category_scores_gemma":[0.000010403923,0.00013591869,0.00004346972,0.0005244716,0.000016812326,0.000022973434,0.00003060297,0.00023700428,0.000031411782],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005026587,0.0011848257,0.6266617,0.00024043617,0.00018240741,0.00007642523,0.0042885025,0.0001127128,0.10862371,0.00021552315,0.23067766,0.02723339],"study_design_scores_gemma":[0.0011455672,0.00014449396,0.88701814,0.00054053566,0.00011303646,0.0001251366,0.00036055382,0.000048628375,0.04614252,0.000713634,0.06321028,0.00043749096],"about_ca_topic_score_codex":0.000014935336,"about_ca_topic_score_gemma":0.0001135046,"teacher_disagreement_score":0.2603564,"about_ca_system_score_codex":0.00003445517,"about_ca_system_score_gemma":0.000019470275,"threshold_uncertainty_score":0.5542603},"labels":[],"label_agreement":null},{"id":"W3164886172","doi":"10.1016/j.jneumeth.2021.109226","title":"Label-free assessment of myelin status using birefringence microscopy","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Myelin; Luxol fast blue stain; White matter; Birefringence; Electron microscope; Pathology; Microscopy; Staining; Anatomy; Neuroscience; Biology; Magnetic resonance imaging; Central nervous system; Medicine; Optics; Radiology; Physics","score_opus":0.28839138692666705,"score_gpt":0.5819041405328899,"score_spread":0.2935127536062228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3164886172","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28896722,0.00023043051,0.7095106,0.00077969005,0.00025823442,0.00007821439,0.0000056885583,0.000014737894,0.00015518446],"genre_scores_gemma":[0.07095092,0.00048625047,0.9278382,0.0005986244,0.0000497239,0.0000012639697,1.7127664e-7,0.0000133893855,0.000061439285],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99849284,0.00017779143,0.0005243655,0.00021457988,0.00036894516,0.00022146323],"domain_scores_gemma":[0.998277,0.00016267848,0.00050572073,0.00046738467,0.0004281388,0.00015909568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008155661,0.00009961914,0.00032531004,0.00014351546,0.00008005068,0.000022024098,0.00027271532,0.00002888006,0.00000866005],"category_scores_gemma":[0.0011889432,0.00008382811,0.000099678175,0.00075726345,0.00018374322,0.00015547387,0.00015781124,0.0003359566,9.6100436e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000098395385,0.00014806961,0.0038221837,0.000025175616,0.000002297582,0.00007186262,0.000018116358,0.000097977856,0.98723984,0.0002543981,0.00004218596,0.008268052],"study_design_scores_gemma":[0.00057682645,0.00038761555,0.035802815,0.00016053535,0.00007380216,0.0014113092,0.000038197926,0.009516775,0.9405007,0.0017581818,0.009674832,0.000098410725],"about_ca_topic_score_codex":0.0000026861403,"about_ca_topic_score_gemma":1.2543273e-7,"teacher_disagreement_score":0.21832761,"about_ca_system_score_codex":0.00006498417,"about_ca_system_score_gemma":0.00055082346,"threshold_uncertainty_score":0.34184113},"labels":[],"label_agreement":null},{"id":"W3165679058","doi":"10.3389/fncom.2021.659838","title":"Predicting Brain Regions Related to Alzheimer's Disease Based on Global Feature","year":2021,"lang":"en","type":"article","venue":"Frontiers in Computational Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences; Institute of Biophysics, Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Betweenness centrality; Centrality; Diffusion MRI; Neurology; Neuroimaging; Computer science; Feature (linguistics); Connectome; Graph; Connectomics; Artificial intelligence; Medicine; Neuroscience; Pattern recognition (psychology); Psychology; Functional connectivity; Magnetic resonance imaging; Mathematics; Theoretical computer science; Statistics","score_opus":0.03708595069693046,"score_gpt":0.34776959948722636,"score_spread":0.3106836487902959,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165679058","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02529249,0.00012765575,0.7995404,0.17232648,0.0006461083,0.0006801413,0.00011880007,0.00033239665,0.0009355514],"genre_scores_gemma":[0.75241446,0.0000038155586,0.2210513,0.026188688,0.00002614291,0.000046706053,0.000059183712,0.000014796466,0.00019487116],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986994,0.000045130353,0.00015884828,0.0005366296,0.00035833623,0.00020163262],"domain_scores_gemma":[0.9992727,0.00008623523,0.000046973913,0.00027177413,0.000085803,0.00023649083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000749628,0.00011191267,0.00012673321,0.00010136132,0.00014482446,0.000027972446,0.00013819539,0.000029515902,0.0000024872813],"category_scores_gemma":[0.0005062344,0.000118079384,0.000052906475,0.0013039802,0.00009885193,0.00006834556,0.00005362837,0.00020551313,0.0000026778832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013130713,0.0004229303,0.39201066,0.000014042096,0.0000037958841,0.000578735,0.000024269644,0.525346,0.00025545715,0.0086676385,0.06900535,0.0035398284],"study_design_scores_gemma":[0.00033441573,0.00006562149,0.41739023,0.00008199933,0.000012868803,0.000037935544,0.000008679594,0.56317407,0.00004098825,0.013366335,0.005386754,0.000100099554],"about_ca_topic_score_codex":0.0000010056435,"about_ca_topic_score_gemma":3.6205782e-7,"teacher_disagreement_score":0.727122,"about_ca_system_score_codex":0.00007867042,"about_ca_system_score_gemma":0.00026943997,"threshold_uncertainty_score":0.48151374},"labels":[],"label_agreement":null},{"id":"W3165788838","doi":"10.1037/cap0000275","title":"A brief introduction to intraindividual variability and spin.","year":2021,"lang":"en","type":"article","venue":"Canadian Psychology/Psychologie canadienne","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Psychology","score_opus":0.07052637932699653,"score_gpt":0.3777353813754468,"score_spread":0.3072090020484503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165788838","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.67264324,0.00012921894,0.005194052,0.30770305,0.0008477511,0.0008186332,0.00019703669,0.000266776,0.012200232],"genre_scores_gemma":[0.9144542,0.00009988384,0.028567433,0.05494472,0.000723356,0.00017040312,0.00014202092,0.000051702995,0.0008462345],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99747336,0.00007938932,0.0003132788,0.0011948609,0.000079221434,0.0008598654],"domain_scores_gemma":[0.99678874,0.00004634108,0.000052448413,0.0012328391,0.00021085312,0.0016687604],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043111775,0.00023233058,0.00032890748,0.0003138013,0.00018220057,0.000030795934,0.0001833908,0.00020717725,0.0004020826],"category_scores_gemma":[0.00084621174,0.00025792012,0.000059500926,0.000787941,0.0002485803,0.00006514728,0.000045166307,0.0004592129,0.00004032207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014343944,0.00030281467,0.03870973,0.00005597627,0.00012480986,0.0015671897,0.0005479706,0.0000068835025,0.019605942,0.03860212,0.58809614,0.31223696],"study_design_scores_gemma":[0.00061329623,0.0002402373,0.26862234,0.000017281704,0.00004277918,0.0021289885,0.000081604056,0.0000078488465,0.00026470984,0.0061072786,0.72160894,0.00026470862],"about_ca_topic_score_codex":0.0062802453,"about_ca_topic_score_gemma":0.076689176,"teacher_disagreement_score":0.31197226,"about_ca_system_score_codex":0.00037966119,"about_ca_system_score_gemma":0.00043326983,"threshold_uncertainty_score":0.9999873},"labels":[],"label_agreement":null},{"id":"W3166306566","doi":"10.1101/2021.05.14.444187","title":"The structure of hippocampal circuitry relates to rapid category learning in humans","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Categorization; Hippocampal formation; White matter; Concept learning; Association (psychology); Hippocampus; Mnemonic; Cognition","score_opus":0.02551244806637266,"score_gpt":0.27511098520776806,"score_spread":0.2495985371413954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166306566","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9935954,0.0016659878,0.0022429042,0.0009537927,0.00022071847,0.0009355318,0.000036251076,0.00033188408,0.00001750414],"genre_scores_gemma":[0.9914343,0.0006057572,0.0073445444,0.00025477106,0.00014825378,0.00009679448,9.08017e-7,0.00010563358,0.000009087991],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978793,0.000106924395,0.00056726456,0.0007550211,0.00029049904,0.00040096094],"domain_scores_gemma":[0.9977065,0.00012366276,0.0003181948,0.0013261236,0.00035438073,0.00017116765],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028986402,0.00035326232,0.00054822845,0.0002147712,0.00017490111,0.00007057548,0.00039406097,0.00032426283,0.00002854186],"category_scores_gemma":[0.00040390482,0.00031785938,0.00013638285,0.0006185878,0.00013444848,0.00005336515,0.0004109131,0.001729447,0.0000040946147],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024923256,0.000074825875,0.026983913,0.00027753998,0.00005095893,0.000049214905,0.000039062455,0.00023512509,0.97117037,0.0009453498,0.00012034259,0.000028388882],"study_design_scores_gemma":[0.0006055554,0.00013067479,0.349111,0.0012941994,0.00015920875,1.4084478e-7,0.000049593782,0.00019840575,0.6385094,0.00006742338,0.009182962,0.0006914266],"about_ca_topic_score_codex":0.000034848184,"about_ca_topic_score_gemma":0.0000044234143,"teacher_disagreement_score":0.33266094,"about_ca_system_score_codex":0.00018644301,"about_ca_system_score_gemma":0.00048681817,"threshold_uncertainty_score":0.99992734},"labels":[],"label_agreement":null},{"id":"W3166979605","doi":"10.1002/hbm.25558","title":"Characterizing white matter alterations subject to clinical laterality in drug‐naïve de novo Parkinson's disease","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Laterality; Disease; Psychology; Neuroscience; Parkinson's disease; Medicine; Magnetic resonance imaging; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.10862896568650543,"score_gpt":0.40270430730402984,"score_spread":0.2940753416175244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3166979605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92675555,0.000015269949,0.012459131,0.05926064,0.00004282152,0.0003971095,0.000017390774,0.00014672465,0.0009053864],"genre_scores_gemma":[0.95314014,0.000008308076,0.011937802,0.032614157,0.0002581717,0.00014084471,0.00010294353,0.000030207375,0.0017674492],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985611,0.00013086136,0.00042888307,0.000466698,0.00010999282,0.0003024628],"domain_scores_gemma":[0.99902475,0.000101236095,0.00006832021,0.00050864805,0.000058529276,0.00023854391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000370704,0.00013684788,0.00024666957,0.00011636983,0.00016685102,0.00006192434,0.000097032345,0.00003706112,0.00018553743],"category_scores_gemma":[0.00013783731,0.00015152628,0.00010239482,0.0002712024,0.000040766423,0.000095700394,0.00010749789,0.00030867042,0.00005402013],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018877046,0.0001648589,0.94511044,0.000067221445,0.000008013638,0.00024990315,0.0005740063,0.000007925718,0.04748764,0.0007682338,0.0052760537,0.00026684024],"study_design_scores_gemma":[0.00033909242,0.0000099951485,0.9131083,0.00024158524,0.000010542129,0.000027644965,0.0000408273,0.000098984165,0.00024953557,0.0012361646,0.08449493,0.00014238704],"about_ca_topic_score_codex":0.000011167046,"about_ca_topic_score_gemma":0.000032613585,"teacher_disagreement_score":0.07921888,"about_ca_system_score_codex":0.000080509686,"about_ca_system_score_gemma":0.00007468388,"threshold_uncertainty_score":0.6179063},"labels":[],"label_agreement":null},{"id":"W3168177125","doi":"10.21203/rs.3.rs-147275/v1","title":"Reorganisation of diffusion microstructure in the precuneus is associated with preserved cognitive function in Parkinson’s disease","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université de Sherbrooke; Centre Hospitalier de l’Université de Montréal; McGill University","funders":"","keywords":"Precuneus; Posterior cingulate; Fractional anisotropy; Diffusion MRI; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Cortex (anatomy); Cognition; Radiology","score_opus":0.0950145283492425,"score_gpt":0.40520083031699733,"score_spread":0.3101863019677548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168177125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99317,0.00047103292,0.00047556902,0.00253938,0.00001550253,0.0029395802,0.00019985468,0.000042288466,0.00014677279],"genre_scores_gemma":[0.9972193,0.0004460836,0.00018641136,0.00013514647,0.00003449441,0.0006467456,0.0011981922,0.00003412906,0.000099488774],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99751645,0.0005551647,0.0002965703,0.00055257464,0.0007990657,0.00028016634],"domain_scores_gemma":[0.99809295,0.0004093326,0.00015117369,0.00061016827,0.0006580534,0.00007834538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006487483,0.0001725936,0.00030059105,0.0002902089,0.000080997794,0.000045760225,0.00019750811,0.00018246443,0.000053912696],"category_scores_gemma":[0.0010656607,0.00012445086,0.00007175165,0.0008648066,0.00014917676,0.000059500286,0.00032921604,0.0016178879,7.4039093e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025916789,0.0017639083,0.9698702,0.0017940911,0.000080687874,0.00030640484,0.0052633453,0.000084792395,0.0146772675,0.000096746786,0.00075270433,0.0027181492],"study_design_scores_gemma":[0.000971348,0.00022244187,0.9883367,0.003924758,0.00006104499,0.0000036646468,0.0013801772,0.00055322214,0.0021638859,0.0019850477,0.00028334596,0.000114403396],"about_ca_topic_score_codex":0.0002874243,"about_ca_topic_score_gemma":0.00026097064,"teacher_disagreement_score":0.018466437,"about_ca_system_score_codex":0.00020648076,"about_ca_system_score_gemma":0.00041909335,"threshold_uncertainty_score":0.70290077},"labels":[],"label_agreement":null},{"id":"W3170550114","doi":"10.1016/j.dcn.2021.101008","title":"Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies","year":2021,"lang":"en","type":"review","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":85,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute of Mental Health; Helse Sør-Øst RHF; Brain and Behavior Research Foundation; Norges Forskningsråd; Canada Research Chairs; National Alliance for Research on Schizophrenia and Depression; National Institute for Health and Care Research","keywords":"Psychology; White matter; Executive functions; Diffusion MRI; Cognition; Extant taxon; Working memory; Concordance; Cognitive psychology; Developmental psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.06617718641593107,"score_gpt":0.37325152030611547,"score_spread":0.3070743338901844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170550114","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006021856,0.9919213,0.00032499118,0.000060059403,0.000050863455,0.0013874235,0.000119707176,0.000026367119,0.00008742492],"genre_scores_gemma":[0.00069324893,0.98936296,0.00903476,0.00048532177,0.000008928952,0.00014532782,0.000057498844,0.000027325816,0.0001846393],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.9981667,0.000052189152,0.00069021987,0.0006346191,0.00025451308,0.00020180002],"domain_scores_gemma":[0.9990017,0.0000669603,0.00044728216,0.0001435141,0.00024536243,0.000095195115],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000105384905,0.00035178408,0.0012368634,0.000164944,0.00031916398,0.000009186104,0.000100287274,0.00006409996,0.000009766236],"category_scores_gemma":[0.0001783424,0.00028207892,0.00009679495,0.0006269868,0.0005402351,0.00007858445,0.0007132577,0.00030800872,0.0000011440843],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031014708,0.0005852116,0.014360403,0.34475458,0.000189695,0.00008991682,0.0041447408,1.5255994e-8,0.0062446077,0.000019304021,0.00047327753,0.62910724],"study_design_scores_gemma":[0.0006800603,0.00010033158,0.15570575,0.69169337,0.0010512287,0.0034315228,0.0013146601,3.3965847e-7,0.0026596952,0.000010290231,0.14254123,0.0008115579],"about_ca_topic_score_codex":2.628821e-7,"about_ca_topic_score_gemma":2.9288472e-7,"teacher_disagreement_score":0.62829566,"about_ca_system_score_codex":0.00005709602,"about_ca_system_score_gemma":0.00034423696,"threshold_uncertainty_score":0.99996316},"labels":[],"label_agreement":null},{"id":"W3170936042","doi":"10.1002/nbm.4564","title":"MRI of healthy brain aging: A review","year":2021,"lang":"en","type":"review","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Brain aging; Hyperintensity; Aging brain; White matter; Magnetic resonance imaging; Neuroscience; Healthy aging; Human brain; Brain size; Psychology; Medicine; Cognition; Gerontology; Radiology","score_opus":0.20429981294684432,"score_gpt":0.5203831557151053,"score_spread":0.316083342768261,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3170936042","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[1.203992e-7,0.9747193,0.0005857668,0.021850485,0.00007712894,0.0018503559,0.000036568796,0.00009076513,0.0007895442],"genre_scores_gemma":[4.1622798e-7,0.9854218,0.005690882,0.0072083916,0.00025882872,0.00029387212,0.0005647233,0.00006386283,0.0004972305],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99746835,0.00010871731,0.0012688416,0.0005458117,0.00032275182,0.0002855046],"domain_scores_gemma":[0.9979012,0.00027153356,0.0005126152,0.0010008138,0.00010996602,0.00020388057],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005540566,0.00034043245,0.003194959,0.0004573267,0.000020722126,0.0000021921667,0.00022332734,0.00016679575,0.000173066],"category_scores_gemma":[0.0004649846,0.00025656493,0.00034407925,0.0019842726,0.00017071202,0.00002041001,0.00010552891,0.0006370393,0.000011963235],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021001633,0.00014101613,0.000006667559,0.14640641,0.000025485055,0.00006470728,0.0000073118695,8.179252e-9,0.000004477173,0.00026436133,0.07889468,0.7741828],"study_design_scores_gemma":[0.00024938653,0.00013548434,0.000003134579,0.2549832,0.00037058443,0.00033465962,0.0000027681965,0.0000010004177,0.0000013909527,0.000032309043,0.743768,0.00011809543],"about_ca_topic_score_codex":0.000019549716,"about_ca_topic_score_gemma":0.0000012433417,"teacher_disagreement_score":0.77406466,"about_ca_system_score_codex":0.00015554702,"about_ca_system_score_gemma":0.0006131329,"threshold_uncertainty_score":0.9999887},"labels":[],"label_agreement":null},{"id":"W3171044630","doi":"10.1093/brain/awab232","title":"Potential optimization of focused ultrasound capsulotomy for obsessive compulsive disorder","year":2021,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; University Health Network; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Deutsche Forschungsgemeinschaft","keywords":"Lesion; Medicine; Internal capsule; Magnetic resonance imaging; Deep brain stimulation; Diffusion MRI; Tractography; Radiology; Psychology; Surgery; Internal medicine; White matter; Parkinson's disease","score_opus":0.03192254523100007,"score_gpt":0.3354573587349589,"score_spread":0.30353481350395883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171044630","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030578911,0.00008811817,0.96432537,0.004025049,0.000030274754,0.0005532569,0.00006148482,0.00006895856,0.00026856718],"genre_scores_gemma":[0.6004504,0.000044963585,0.39719275,0.00088970497,0.00007571852,0.00013678403,0.00039930543,0.00002971209,0.0007806748],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99950385,0.000013613053,0.000143466,0.00016846212,0.00007566091,0.0000949183],"domain_scores_gemma":[0.99936277,0.00012879014,0.000077116114,0.00019280962,0.00020292314,0.000035601803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002911574,0.00006549678,0.00014199241,0.000028125074,0.000047390877,0.0000060426064,0.00004010989,0.00003183695,0.00004024175],"category_scores_gemma":[0.00024874797,0.00006434973,0.00006855273,0.00014291202,0.00004421877,0.00003387493,0.000018106011,0.00005101943,8.2553095e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041338088,0.0018675902,0.0072353603,0.00060952554,0.00021784264,0.00008851189,0.00063357054,0.05811997,0.82736343,0.031292908,0.03630841,0.03584953],"study_design_scores_gemma":[0.021053992,0.0010743585,0.044190373,0.00064525637,0.00077863433,0.00078654493,0.0011695572,0.13179041,0.6350008,0.029277444,0.13293293,0.0012996806],"about_ca_topic_score_codex":0.000005028702,"about_ca_topic_score_gemma":0.0000011540843,"teacher_disagreement_score":0.5698715,"about_ca_system_score_codex":0.000013275811,"about_ca_system_score_gemma":0.000056358116,"threshold_uncertainty_score":0.2624106},"labels":[],"label_agreement":null},{"id":"W3171052867","doi":"","title":"A generalized SMT-based framework for Diusion MRI microstructural model estimation","year":2017,"lang":"en","type":"article","venue":"Medical Image Computing and Computer-Assisted Intervention","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Estimation; Estimation theory; Artificial intelligence; Algorithm; Materials science; Mathematical optimization; Applied mathematics; Mathematics; Engineering","score_opus":0.06444238563923192,"score_gpt":0.4156114653257816,"score_spread":0.35116907968654965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171052867","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20394999,0.00004683793,0.79148275,0.003658402,0.00018016156,0.0004118138,0.000008674618,0.00024342768,0.000017980343],"genre_scores_gemma":[0.48380467,0.000006265156,0.51546174,0.0004510993,0.00013488723,0.00002236506,0.00007808331,0.000017595481,0.00002329403],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985642,0.000040909723,0.00044102207,0.0004522823,0.000257497,0.00024412647],"domain_scores_gemma":[0.998677,0.000118295466,0.00034276646,0.00050640746,0.00016007773,0.00019545478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031096386,0.00019710229,0.00032174715,0.000080514576,0.0006546978,0.00021172833,0.0002449858,0.00015085608,0.000013363594],"category_scores_gemma":[0.00033578457,0.0001757456,0.00023004635,0.000052358355,0.00021296025,0.00011592199,0.00021591761,0.00031206687,0.0000018517953],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020461346,0.00043931967,0.0006857258,0.0005085649,0.000041436786,0.00002130205,0.00005879949,0.0004632024,0.0029132215,0.0049596606,0.0017900902,0.9879141],"study_design_scores_gemma":[0.002066439,0.00026251422,0.009549884,0.00145484,0.0000668624,0.00008678671,0.000003473793,0.9768582,0.0017444462,0.00753375,0.0002091119,0.00016370563],"about_ca_topic_score_codex":0.000017632921,"about_ca_topic_score_gemma":0.0000012543193,"teacher_disagreement_score":0.98775035,"about_ca_system_score_codex":0.000046741738,"about_ca_system_score_gemma":0.000039929753,"threshold_uncertainty_score":0.7166698},"labels":[],"label_agreement":null},{"id":"W3171255193","doi":"10.3389/fnagi.2021.639795","title":"Interactions Between Aging and Alzheimer’s Disease on Structural Brain Networks","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; National Natural Science Foundation of China; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Genentech; IXICO; University of Houston; University of Southern California; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Betweenness centrality; Clustering coefficient; Modularity (biology); Neuroscience; Diffusion MRI; Neuroimaging; Psychology; Tractography; Centrality; Computer science; Cluster analysis; Magnetic resonance imaging; Medicine; Artificial intelligence; Biology; Mathematics; Statistics; Evolutionary biology","score_opus":0.060436463965796064,"score_gpt":0.3658315133192387,"score_spread":0.30539504935344264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171255193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.548442,0.0013758522,0.3947268,0.051724177,0.0017353822,0.00072036986,0.000032282987,0.00052055443,0.0007225502],"genre_scores_gemma":[0.9825541,0.00007239304,0.012514453,0.0045017973,0.000091453854,0.000017163191,0.0000100520865,0.000017106695,0.00022151697],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891716,0.00003832319,0.00015743011,0.00049316627,0.00014375993,0.00025015706],"domain_scores_gemma":[0.99935323,0.00007697445,0.00004979069,0.00031878016,0.000024151557,0.00017704663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071942464,0.00011986476,0.0001580155,0.00012950775,0.00017852323,0.000052570256,0.00010931257,0.000013703492,0.0000027412834],"category_scores_gemma":[0.00017132277,0.00012026293,0.000035490117,0.00046853698,0.00016996902,0.00015416826,0.000098960474,0.00035301168,4.2570852e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017419845,0.000041085077,0.95544034,0.000016057325,0.000004269216,0.00029167774,0.00007710671,0.0012377974,0.0020391778,0.00059422216,0.0053751026,0.03486577],"study_design_scores_gemma":[0.0003848935,0.000040894105,0.8958289,0.00021206134,0.000054234875,0.00009440412,0.000054435965,0.0804576,0.001559832,0.002051709,0.0190253,0.00023573567],"about_ca_topic_score_codex":0.000003050136,"about_ca_topic_score_gemma":6.8521587e-7,"teacher_disagreement_score":0.43411207,"about_ca_system_score_codex":0.00003444441,"about_ca_system_score_gemma":0.00004262336,"threshold_uncertainty_score":0.490418},"labels":[],"label_agreement":null},{"id":"W3171260877","doi":"10.1016/j.neuroimage.2021.118250","title":"Multi-modal imaging of a single mouse brain over five orders of magnitude of resolution","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Argonne National Laboratory; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; National Cancer Institute; National Center for Research Resources; National Institute of Neurological Disorders and Stroke; McKnight Foundation; National Institute of Mental Health; Ontario Ministry of Research, Innovation and Science","keywords":"Connectomics; Micrometer; Diffusion MRI; Neuroimaging; Scale (ratio); Resolution (logic); Neuroscience; Computer science; Connectome; Physics; Magnetic resonance imaging; Artificial intelligence; Optics; Biology; Medicine","score_opus":0.05473079709339063,"score_gpt":0.34866846951896274,"score_spread":0.2939376724255721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171260877","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9658432,0.00013216563,0.030621774,0.0018680718,0.000028522343,0.00034421336,0.00008998871,0.00009555421,0.0009765356],"genre_scores_gemma":[0.9136495,0.00003233295,0.085204616,0.00047721047,0.000015376343,0.000009618286,0.000025043324,0.00003236309,0.00055390864],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989968,0.000043137294,0.00034800163,0.00027031507,0.00019176814,0.00014999091],"domain_scores_gemma":[0.99888915,0.00009873683,0.00020908017,0.00048671072,0.00026766118,0.00004865796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007134533,0.00011029522,0.00027584255,0.000098662735,0.00002423464,0.0000034804073,0.000089138004,0.000029261191,0.000035847137],"category_scores_gemma":[0.0003319441,0.00011681262,0.000110345994,0.0002649492,0.00017397257,0.000079651014,0.00009754703,0.00014696793,0.0000011284968],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051623923,0.00050550763,0.0032128303,0.00013568017,0.000007546376,0.000031752137,0.00008148796,0.000035613502,0.9937791,0.00035499834,0.0010132537,0.0007905785],"study_design_scores_gemma":[0.0015038903,0.00017192237,0.040795524,0.00012202621,0.000056893765,0.00006010527,0.00007400271,0.0036940323,0.9498216,0.00021424363,0.0033710524,0.00011472282],"about_ca_topic_score_codex":0.000054331245,"about_ca_topic_score_gemma":0.0000041957587,"teacher_disagreement_score":0.05458284,"about_ca_system_score_codex":0.000019385494,"about_ca_system_score_gemma":0.000060235605,"threshold_uncertainty_score":0.47634804},"labels":[],"label_agreement":null},{"id":"W3171357627","doi":"10.1101/2020.05.04.076521","title":"Multimodal principal component analysis to identify major features of white matter structure and links to reading","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Wellcome Trust","keywords":"White matter; Principal component analysis; Diffusion MRI; Neuroscience; Fractional anisotropy; Corpus callosum; Artificial intelligence; Psychology; Computer science; Nuclear magnetic resonance; Pattern recognition (psychology); Physics; Magnetic resonance imaging; Medicine","score_opus":0.0253761641619497,"score_gpt":0.30986733703346947,"score_spread":0.28449117287151976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171357627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96559656,0.00009634438,0.026478468,0.005289754,0.0001133015,0.0014825913,0.00064074114,0.0002961756,0.000006093801],"genre_scores_gemma":[0.85063946,0.000019147265,0.14728385,0.0016590694,0.00016961386,0.00013171045,0.0000023448433,0.00008650164,0.000008304588],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99758685,0.000045165816,0.0005360409,0.0011258086,0.00036001456,0.00034610793],"domain_scores_gemma":[0.9975623,0.000034582376,0.00029370512,0.0012347846,0.0003396467,0.00053497026],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013757363,0.00045200056,0.0009010246,0.00057470833,0.0001278355,0.00007448186,0.00034723827,0.00038198847,0.000040873074],"category_scores_gemma":[0.00009803269,0.00045818652,0.00019207045,0.0010079882,0.00006746697,0.000050003706,0.0011364018,0.001077574,0.000011567726],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000840082,0.00006072833,0.13678306,0.0004341373,0.0004353389,0.000034477984,0.00005177123,0.00018630782,0.86123806,0.00016515763,0.00052370405,0.000003240241],"study_design_scores_gemma":[0.00023911598,0.000046997528,0.83706564,0.00024779487,0.0009175931,7.8446e-8,0.0000019834604,0.0002890109,0.15955114,0.0000044253575,0.0012730822,0.0003631586],"about_ca_topic_score_codex":0.00005063576,"about_ca_topic_score_gemma":0.0000023697821,"teacher_disagreement_score":0.7016869,"about_ca_system_score_codex":0.00012258117,"about_ca_system_score_gemma":0.00009296217,"threshold_uncertainty_score":0.999787},"labels":[],"label_agreement":null},{"id":"W3172378891","doi":"10.31234/osf.io/468xa","title":"Using Diffusion Tensor Imaging to examine brain structural plasticity and language experience","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; Neuroimaging; White matter; Variation (astronomy); Computer science; Psychology; Neuroscience; Physics; Magnetic resonance imaging; Medicine","score_opus":0.08196933927449837,"score_gpt":0.4069727400210898,"score_spread":0.3250034007465914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172378891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8295183,0.000052289877,0.1677817,0.001248007,0.000058140493,0.00073900435,0.000021986543,0.00022946879,0.00035108702],"genre_scores_gemma":[0.8871852,0.000008656562,0.110368215,0.0016309061,0.00009454531,0.00003266785,0.000020673568,0.00003241613,0.0006267252],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99884635,0.000013534284,0.00020138753,0.00057224586,0.00015714864,0.0002093114],"domain_scores_gemma":[0.9992129,0.000080228565,0.00007868944,0.00043413378,0.00005335937,0.00014064326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003580032,0.00022327743,0.00030216697,0.00010956709,0.00007059736,0.00003746368,0.000116706,0.00006320333,0.000056147463],"category_scores_gemma":[0.00014016149,0.00018330124,0.000041930114,0.000081412814,0.000064810985,0.000043626867,0.0007981134,0.00034106034,0.0000036610902],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081255064,0.000049554408,0.0975449,0.00033408296,0.0000127309495,0.00007072875,0.0022600354,0.00042489675,0.885533,0.00045025712,0.0006704062,0.012568205],"study_design_scores_gemma":[0.0021309466,0.0002192898,0.47934943,0.0020717934,0.00023075189,0.0011633445,0.0026148993,0.42247427,0.08203783,0.0016534352,0.0041121086,0.0019418785],"about_ca_topic_score_codex":0.00018593052,"about_ca_topic_score_gemma":0.000002698488,"teacher_disagreement_score":0.8034951,"about_ca_system_score_codex":0.00006156385,"about_ca_system_score_gemma":0.000028692568,"threshold_uncertainty_score":0.74748075},"labels":[],"label_agreement":null},{"id":"W3172893236","doi":"10.1016/j.media.2021.102126","title":"Filtering in tractography using autoencoders (FINTA)","year":2021,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Mental Health","keywords":"Tractography; Streamlines, streaklines, and pathlines; Artificial intelligence; Autoencoder; Pattern recognition (psychology); Computer science; Deep learning; Filter (signal processing); Diffusion MRI; Human Connectome Project; Voxel; Computer vision; Physics; Magnetic resonance imaging; Functional connectivity","score_opus":0.08399795419258586,"score_gpt":0.4187703104105577,"score_spread":0.3347723562179718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3172893236","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16882396,0.00013141507,0.825212,0.0042972323,0.000014283368,0.000075026655,0.0000039936986,0.00012210547,0.0013199644],"genre_scores_gemma":[0.7406739,0.00020336434,0.2568757,0.0019669875,0.00005490154,0.000019257322,0.00005822797,0.00001923895,0.00012843669],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883157,0.000032812608,0.00027474668,0.00031422218,0.00034253593,0.00020413252],"domain_scores_gemma":[0.9993006,0.000055669734,0.00004425836,0.0003530782,0.00006548242,0.00018090615],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015440874,0.00009689312,0.00032466202,0.00035070692,0.000042390024,0.000017810631,0.000085867025,0.00006155189,0.0009991055],"category_scores_gemma":[0.00026958712,0.00009168677,0.00026707049,0.002407519,0.000096524556,0.00007251657,0.000057045345,0.00029935056,0.00000519698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089967085,0.0030264559,0.5652593,0.00031990738,0.002532465,0.01745422,0.00071593927,0.0023924012,0.31903598,0.00087809504,0.0027119857,0.0855833],"study_design_scores_gemma":[0.001631362,0.00005892351,0.12491369,0.0003069348,0.0034389303,0.00046753418,0.0004126025,0.82262206,0.032991204,0.001509544,0.011073087,0.00057409983],"about_ca_topic_score_codex":0.00008175387,"about_ca_topic_score_gemma":0.000049875143,"teacher_disagreement_score":0.8202297,"about_ca_system_score_codex":0.0000353387,"about_ca_system_score_gemma":0.00008093113,"threshold_uncertainty_score":0.9999141},"labels":[],"label_agreement":null},{"id":"W3173340191","doi":"10.1101/2021.06.29.450089","title":"Not all voxels are created equal: reducing estimation bias in regional NODDI metrics using tissue-weighted means","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; UK Dementia Research Institute; University College London Hospitals NHS Foundation Trust; Brain Research Trust; Wolfson Foundation; British Heart Foundation; University College London; National Institute for Health and Care Research; Brain Research UK; Wellcome Trust; Alzheimer's Society; Weston Brain Institute; Alzheimer's Association","keywords":"Region of interest; Voxel; Pattern recognition (psychology); Neuroimaging; Metric (unit); Partial volume; Artificial intelligence; Brain tissue; Brain size; Statistics; Computer science; Nuclear medicine; Mathematics; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology","score_opus":0.15899215065156422,"score_gpt":0.35014540538944305,"score_spread":0.19115325473787884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173340191","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8421277,0.0010918973,0.152326,0.0014527239,0.00028455816,0.0015642532,0.00013453355,0.0010096466,0.000008719696],"genre_scores_gemma":[0.7509088,0.0004000917,0.24756129,0.0005778217,0.00018649436,0.00017592743,0.000007973032,0.00017607954,0.000005520276],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9962377,0.00016046503,0.0009499994,0.0014174711,0.00063590246,0.0005984866],"domain_scores_gemma":[0.99619424,0.00018438052,0.00082062004,0.0016435379,0.0008484942,0.00030874382],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005792965,0.00063092547,0.00095757,0.0009456521,0.00014744558,0.00017164469,0.00036325312,0.00057109655,0.000031283413],"category_scores_gemma":[0.00083040807,0.0007165717,0.0001745761,0.0020114717,0.00011941365,0.00021449373,0.00041077464,0.0013030992,0.000010408077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000077204444,0.0005274793,0.006006008,0.00075812405,0.000146843,0.0005058685,0.000033183922,0.0025358174,0.9885292,0.00054373057,0.0002977279,0.000038824295],"study_design_scores_gemma":[0.0013195346,0.00009793168,0.050122105,0.0046953172,0.00060742116,0.0000012772124,0.000012832999,0.1272485,0.810008,0.00002174618,0.004462678,0.0014026839],"about_ca_topic_score_codex":0.0002669298,"about_ca_topic_score_gemma":0.000003314447,"teacher_disagreement_score":0.1785212,"about_ca_system_score_codex":0.00083957403,"about_ca_system_score_gemma":0.0006519764,"threshold_uncertainty_score":0.9995285},"labels":[],"label_agreement":null},{"id":"W3173857605","doi":"10.1002/hbm.25569","title":"<scp>R2</scp>* and quantitative susceptibility mapping in deep gray matter of 498 healthy controls from 5 to 90 years","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"Globus pallidus; Putamen; Quantitative susceptibility mapping; Thalamus; Grey matter; Basal ganglia; Psychology; Caudate nucleus; Neuroscience; Physiology; White matter; Biology; Magnetic resonance imaging; Medicine; Central nervous system; Radiology","score_opus":0.08088783876411572,"score_gpt":0.36662992453581006,"score_spread":0.28574208577169435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3173857605","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9513194,0.00022899764,0.042216875,0.004862994,0.000019071693,0.0005914568,0.000019453466,0.00006848677,0.0006732503],"genre_scores_gemma":[0.9476381,0.000017260325,0.04499317,0.006999289,0.000043250202,0.00006158457,0.00004250292,0.000026163658,0.00017867889],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99862045,0.00009698557,0.00041447143,0.00047021362,0.00013920313,0.00025870337],"domain_scores_gemma":[0.9987256,0.00054405764,0.00012120234,0.0004056352,0.000087500535,0.000115999595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028119195,0.00013707306,0.00040003762,0.00016288913,0.00008530815,0.000019528794,0.00008419296,0.000055317407,0.000047315858],"category_scores_gemma":[0.00037751527,0.00015319862,0.000057673507,0.00032191686,0.00010058837,0.000063652864,0.00010647386,0.00023954915,0.000014574595],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016951997,0.00016904331,0.22449338,0.00020021835,0.000030750092,0.00005506242,0.005359767,0.000015768954,0.7605208,0.0042460696,0.0039252345,0.0009669376],"study_design_scores_gemma":[0.0009601049,0.00008571448,0.9720099,0.00035349154,0.000011026478,0.000009095885,0.002296163,0.0001946727,0.00094911415,0.01159855,0.011449275,0.00008291551],"about_ca_topic_score_codex":0.00014875166,"about_ca_topic_score_gemma":0.00012743675,"teacher_disagreement_score":0.7595717,"about_ca_system_score_codex":0.000059226524,"about_ca_system_score_gemma":0.00003444714,"threshold_uncertainty_score":0.6247259},"labels":[],"label_agreement":null},{"id":"W3174049805","doi":"10.1101/2021.06.22.449454","title":"Prevalence of white matter pathways coming into a single diffusion MRI voxel orientation: the bottleneck issue in tractography","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; National Center for Research Resources; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; Voxel; White matter; Diffusion MRI; Bottleneck; Neuroscience; Human Connectome Project; Human brain; Computer science; Orientation (vector space); Artificial intelligence; Psychology; Pattern recognition (psychology); Magnetic resonance imaging; Functional connectivity; Medicine; Mathematics","score_opus":0.025976492956288122,"score_gpt":0.2696573909334546,"score_spread":0.24368089797716647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174049805","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9805667,0.0009330116,0.014761023,0.0020193707,0.00022674366,0.001209948,0.00006771887,0.00019442146,0.000021062071],"genre_scores_gemma":[0.9561345,0.00058198854,0.042118117,0.0005777904,0.00013744873,0.00035671584,0.000001013898,0.00008352304,0.000008909892],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99777913,0.000098753524,0.0006448672,0.00081636955,0.00035530273,0.00030557398],"domain_scores_gemma":[0.99746424,0.000085975276,0.00045890358,0.0015069286,0.00036520444,0.000118775766],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029268622,0.00036569216,0.00049467455,0.00025545355,0.00016683154,0.00005928731,0.00038175643,0.00023319654,0.00008923749],"category_scores_gemma":[0.00008288557,0.00032607492,0.00017696954,0.0007596176,0.00019522067,0.00012151565,0.00053014304,0.00077551906,0.000007108047],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032240547,0.00049699534,0.3044823,0.0015415563,0.000027595339,0.000035844492,0.0001877804,0.000028446284,0.69284326,0.00011074938,0.00020506023,0.0000081601775],"study_design_scores_gemma":[0.0005363039,0.000076648284,0.7517904,0.0022316435,0.00016466991,1.6731049e-7,0.000034341087,0.000392301,0.24228941,0.000014952409,0.002056181,0.00041299313],"about_ca_topic_score_codex":0.000038487848,"about_ca_topic_score_gemma":0.0000021645424,"teacher_disagreement_score":0.45055386,"about_ca_system_score_codex":0.00013352318,"about_ca_system_score_gemma":0.00018389276,"threshold_uncertainty_score":0.9999191},"labels":[],"label_agreement":null},{"id":"W3174077831","doi":"10.1093/rheumatology/keab511","title":"Brain white matter extracellular free-water increases are related to reduced neurocognitive function in systemic lupus erythematosus","year":2021,"lang":"en","type":"article","venue":"Lara D. Veeken","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sleep & Circadian Network","funders":"Ministry of Health","keywords":"Extracellular; Medicine; Neurocognitive; White matter; Diffusion MRI; Atrophy; Neuroinflammation; Brain size; Internal medicine; Pathology; Endocrinology; Magnetic resonance imaging; Inflammation; Cognition; Biology; Psychiatry; Radiology","score_opus":0.02265788854553042,"score_gpt":0.2786848351868136,"score_spread":0.25602694664128317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174077831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98299676,0.00027810302,0.0026607013,0.011803182,0.000103113256,0.00082347763,0.00003128133,0.0002721246,0.0010312307],"genre_scores_gemma":[0.9872435,0.0000193168,0.0014509768,0.0033096555,0.00005814058,0.0002691947,0.00014555086,0.00006515827,0.0074385167],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985365,0.00009682731,0.00036176792,0.00052038033,0.00017786148,0.00030664305],"domain_scores_gemma":[0.99893034,0.00006491721,0.000077187295,0.00065679336,0.00013729923,0.00013344393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012090255,0.0001924755,0.0003198543,0.0001486827,0.00006614261,0.00002898545,0.00010759217,0.00009901036,0.0002163917],"category_scores_gemma":[0.00013098332,0.00017115082,0.00008111467,0.0003821021,0.000028923143,0.0000979914,0.00013706055,0.00031096605,0.00025306366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004998553,0.00054381083,0.1983765,0.00031510458,0.000055064924,0.002000495,0.0006655,0.000069977315,0.77461165,0.00033311802,0.021945385,0.00058351905],"study_design_scores_gemma":[0.014246949,0.0009765798,0.50949496,0.0068206503,0.00081114983,0.03787455,0.003286457,0.0010790471,0.33542413,0.018607032,0.06887908,0.002499404],"about_ca_topic_score_codex":0.000017963157,"about_ca_topic_score_gemma":0.000008549503,"teacher_disagreement_score":0.43918756,"about_ca_system_score_codex":0.00006646008,"about_ca_system_score_gemma":0.000028066026,"threshold_uncertainty_score":0.69793284},"labels":[],"label_agreement":null},{"id":"W3174282872","doi":"","title":"Perfusion/diffusion mismatchに関する最近の話題","year":2010,"lang":"ja","type":"article","venue":"Canadian parliamentary review","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Perfusion; Diffusion; Cardiology; Internal medicine; Medicine; Physics; Thermodynamics","score_opus":0.04829081779812482,"score_gpt":0.33282828308288426,"score_spread":0.2845374652847594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174282872","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13428903,0.5250358,0.00030574066,0.28241313,0.0040021325,0.0120730465,0.0014197937,0.00069530186,0.039766017],"genre_scores_gemma":[0.1473384,0.6642194,0.009588058,0.16734825,0.0014450137,0.0004942433,0.00090116845,0.00023173899,0.008433747],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974419,0.00006360982,0.00066588854,0.00073391176,0.00029489156,0.0007998124],"domain_scores_gemma":[0.9963158,0.000056339642,0.00019608214,0.0015091453,0.0001207251,0.001801933],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00031857705,0.00044806622,0.0007053,0.00018261316,0.00039804183,0.00004081962,0.00047452725,0.00017353792,0.012308551],"category_scores_gemma":[0.00010596638,0.00042915333,0.00027291555,0.00049770536,0.00020980206,0.00012859942,0.000091732545,0.0011755379,0.0016555745],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008612354,0.00018407767,0.0048820013,0.003496042,0.00003913946,0.00032957975,0.000103837665,1.2475311e-7,0.011488989,0.0008143834,0.64091253,0.33774072],"study_design_scores_gemma":[0.00032682376,0.00007939535,0.0017463352,0.0069933604,0.0004227257,0.0002908545,0.000055851433,0.00007587238,0.0002603864,0.00017785112,0.98915017,0.00042039782],"about_ca_topic_score_codex":0.060551245,"about_ca_topic_score_gemma":0.06724467,"teacher_disagreement_score":0.34823763,"about_ca_system_score_codex":0.00029414316,"about_ca_system_score_gemma":0.00080067967,"threshold_uncertainty_score":0.999816},"labels":[],"label_agreement":null},{"id":"W3174344947","doi":"10.1161/str.48.suppl_1.wp442","title":"Abstract WP442: Diffusion Tensor Imaging of White Matter Tracts in Transient Ischemic Attack Patients","year":2017,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Fractional anisotropy; Diffusion MRI; White matter; Uncinate fasciculus; Cardiology; Superior longitudinal fasciculus; Dementia; Internal medicine; Cognitive decline; Magnetic resonance imaging; Radiology","score_opus":0.03859279093100426,"score_gpt":0.3377309742285529,"score_spread":0.29913818329754865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174344947","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9823989,0.000014768217,0.00028960497,0.0020457588,0.000034201243,0.00032095876,0.000042230895,0.000034182132,0.014819346],"genre_scores_gemma":[0.9966314,0.000020278698,0.0024310616,0.00025377862,0.000025621888,0.000020329895,0.000017791948,0.000020934984,0.00057882],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999215,0.0000041452395,0.00023971856,0.00021685619,0.00014652,0.00017776867],"domain_scores_gemma":[0.99918866,0.0000134039565,0.00016074895,0.00052279414,0.000054680997,0.000059736885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000043692304,0.00010720218,0.00018447153,0.000068023335,0.0001024255,0.0000106868065,0.00013810363,0.00003121024,0.0000739751],"category_scores_gemma":[0.000026081305,0.00009490716,0.000065439854,0.000028659226,0.00007584593,0.00011546233,0.000051367635,0.00018417179,0.000015193662],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003675048,0.00021539922,0.94821364,0.000045912417,0.0000024461838,0.000006885525,0.00009650766,0.0000020082257,0.04600977,0.0000030947008,0.0027609773,0.0026066222],"study_design_scores_gemma":[0.0009235643,0.000023408093,0.9820182,0.00014809394,0.000014315465,0.000004152558,0.000015705673,0.00007671036,0.008908789,0.000011476601,0.0077761537,0.000079459984],"about_ca_topic_score_codex":0.000020752315,"about_ca_topic_score_gemma":0.000002812846,"teacher_disagreement_score":0.037100982,"about_ca_system_score_codex":0.000025042422,"about_ca_system_score_gemma":0.0000120467685,"threshold_uncertainty_score":0.38702017},"labels":[],"label_agreement":null},{"id":"W3174662759","doi":"10.1161/circ.140.suppl_2.286","title":"Abstract 286: Cerebral Microstructure Disruptions are Associated With Poor Neurologic Outcomes in Comatose Cardiac Arrest Patients","year":2019,"lang":"en","type":"article","venue":"Circulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kimberly-Clark (Canada)","funders":"","keywords":"Medicine; Fractional anisotropy; Kurtosis; Cardiology; Logistic regression; Diffusion MRI; Prospective cohort study; Internal medicine; Anesthesia; Magnetic resonance imaging; Radiology","score_opus":0.02416700681812992,"score_gpt":0.29152147231346537,"score_spread":0.2673544654953354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174662759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9978711,0.000008643606,0.00013712735,0.0006749734,0.000095403404,0.0008102773,0.000065059576,0.00015695844,0.00018047167],"genre_scores_gemma":[0.9989299,0.0000018703543,0.00020782891,0.00037507573,0.000016526,0.000035963985,0.00038536367,0.000023454322,0.000023995055],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992297,0.000019872414,0.00018493594,0.00025680364,0.00014475775,0.00016387984],"domain_scores_gemma":[0.99941564,0.000046702302,0.00015612996,0.00026141596,0.00007219295,0.000047919373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037263682,0.00012655102,0.00022988924,0.00007549881,0.00005303045,0.000015443708,0.000052587497,0.00007781647,0.000018595032],"category_scores_gemma":[0.000059589587,0.00010365702,0.000057963465,0.00019982646,0.000026753494,0.000103186256,0.00001719818,0.00021171856,0.000018343002],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016087655,0.00012355889,0.99605983,0.000015335005,0.000009179741,0.0000030707006,0.00002223902,0.00021491389,0.0032716435,0.0000816722,0.000039401188,0.00014307487],"study_design_scores_gemma":[0.00078468065,0.00003333664,0.9981538,0.000044767203,0.000025424313,0.000001462232,0.000013046587,0.00036487106,0.00008074441,0.0002853276,0.00010586223,0.00010664262],"about_ca_topic_score_codex":0.0000107359665,"about_ca_topic_score_gemma":0.000008079388,"teacher_disagreement_score":0.003190899,"about_ca_system_score_codex":0.000075206466,"about_ca_system_score_gemma":0.000016431972,"threshold_uncertainty_score":0.42270106},"labels":[],"label_agreement":null},{"id":"W3175695364","doi":"10.3389/fnins.2021.646034","title":"Bundle-Specific Axon Diameter Index as a New Contrast to Differentiate White Matter Tracts","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"EPSRC Centre for Doctoral Training in Medical Imaging; Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca; Engineering and Physical Sciences Research Council; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Wolfson Foundation; Wellcome Trust; National Science Foundation","keywords":"White matter; Voxel; Axon; Diffusion MRI; Corpus callosum; Internal capsule; Tractography; Bundle; Spherical mean; Neuroscience; Magnetic resonance imaging; Anatomy; Computer science; Artificial intelligence; Biology; Mathematics; Materials science; Mathematical analysis; Medicine; Radiology","score_opus":0.045165965578742466,"score_gpt":0.3122785943264132,"score_spread":0.2671126287476707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175695364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20469035,0.00012688489,0.77593726,0.015506851,0.000923785,0.0005997533,0.000010493912,0.00013986515,0.002064766],"genre_scores_gemma":[0.92053,0.0001422788,0.05151248,0.020460606,0.00008332304,0.00006123633,0.0000049895875,0.00003711142,0.0071679433],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983996,0.000029523999,0.00024100962,0.0006778165,0.0002683977,0.00038362163],"domain_scores_gemma":[0.99899274,0.000020296931,0.000055229986,0.0005325761,0.000041173622,0.00035799257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000553271,0.00016383591,0.0002562012,0.00018202559,0.00007285588,0.000075373966,0.00022817921,0.00004465639,0.00007017449],"category_scores_gemma":[0.00012761765,0.00015835199,0.00006282485,0.00078348594,0.000103703394,0.00014821229,0.000105948915,0.00028426462,0.000037017697],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010009908,0.00044584542,0.7425908,0.000022637425,0.0000024460796,0.0002460223,0.0002128707,0.00006893418,0.0881156,0.00024330609,0.1594765,0.008474942],"study_design_scores_gemma":[0.00074392126,0.00015463513,0.8091641,0.00010243192,0.000012510197,0.00017353607,0.000043696316,0.00070458034,0.014114528,0.001999494,0.17251928,0.00026727884],"about_ca_topic_score_codex":0.0000061426517,"about_ca_topic_score_gemma":0.0000021943245,"teacher_disagreement_score":0.7244248,"about_ca_system_score_codex":0.0000577159,"about_ca_system_score_gemma":0.00010322057,"threshold_uncertainty_score":0.6457407},"labels":[],"label_agreement":null},{"id":"W3176867663","doi":"10.1111/pcn.13284","title":"White matter volume not associated with hallucinations in clinical high risk and first‐episode psychosis: A voxel‐based morphometry study","year":2021,"lang":"en","type":"letter","venue":"Psychiatry and Clinical Neurosciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science","keywords":"Psychosis; White matter; Voxel; Voxel-based morphometry; Psychology; Psychiatry; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07058490476996315,"score_gpt":0.38631676436407925,"score_spread":0.3157318595941161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3176867663","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50829285,0.0001167341,0.00073237746,0.48830163,0.0011029996,0.0011028213,0.00014067025,0.00013538984,0.00007452951],"genre_scores_gemma":[0.59341323,0.0008825986,0.0064631067,0.39650726,0.000940419,0.00027728154,0.000082071994,0.000084610256,0.0013494327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99483943,0.00066704466,0.0014738523,0.0019410641,0.00059040077,0.00048819563],"domain_scores_gemma":[0.9967377,0.0013100748,0.00072856067,0.0008620658,0.00012326449,0.00023831804],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0012225524,0.0004601218,0.0010963037,0.0002891203,0.00037557405,0.00016164093,0.00036224676,0.0005428769,0.000064422835],"category_scores_gemma":[0.0008043567,0.00036537668,0.0002277905,0.0011136443,0.0009873215,0.00014183338,0.00014271608,0.003677845,0.000007664099],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006402441,0.0026233587,0.9395163,0.000053749194,0.000032398748,0.000098772405,0.000005555226,0.000003377876,1.9559427e-7,0.0000045320603,0.057325225,0.00027250778],"study_design_scores_gemma":[0.0021993283,0.002568205,0.9799179,0.00039145863,0.00044704715,0.00003251444,0.00004295856,0.00079695357,2.942432e-7,0.00016824446,0.013046911,0.00038821588],"about_ca_topic_score_codex":0.00011828149,"about_ca_topic_score_gemma":0.00055246137,"teacher_disagreement_score":0.091794394,"about_ca_system_score_codex":0.000019664696,"about_ca_system_score_gemma":0.00012209637,"threshold_uncertainty_score":0.99987984},"labels":[],"label_agreement":null},{"id":"W3177104451","doi":"10.1016/j.tins.2021.06.002","title":"An X-ray for myelin","year":2021,"lang":"en","type":"letter","venue":"Trends in Neurosciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Women and Children’s Health Research Institute; University of Alberta","funders":"","keywords":"Remyelination; Myelin; Neuroscience; Central nervous system; Multiple sclerosis; White matter; Disease treatment; Myelin sheath; Computer science; Medicine; Magnetic resonance imaging; Psychology; Immunology; Radiology; Intensive care medicine","score_opus":0.18808728128717964,"score_gpt":0.43850808719444506,"score_spread":0.25042080590726545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177104451","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025584286,0.00009577378,0.0050404235,0.98854375,0.0008374112,0.00047413705,0.00012760577,0.00036592828,0.001956518],"genre_scores_gemma":[0.014198788,0.00013220515,0.042522244,0.9274089,0.0019825315,0.00049243897,0.0005125788,0.00008053071,0.0126698045],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99837416,0.00003797764,0.00024454875,0.00076218665,0.00025278347,0.000328338],"domain_scores_gemma":[0.99911135,0.00010702332,0.000093870556,0.0005912936,0.00004194307,0.00005450925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000103738275,0.00019005121,0.00030625385,0.000358914,0.00008824147,0.00004750858,0.00033064323,0.0001642559,0.00003979039],"category_scores_gemma":[0.0000716254,0.00016484501,0.00010639952,0.0007161178,0.00022279097,0.0000877898,0.000035949754,0.0007188713,0.0000013954342],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010950859,0.00019177496,0.000797987,0.000084166764,0.0000020407238,0.00046755967,0.000026633756,0.000029058128,0.010822565,0.00018472565,0.9504879,0.03689461],"study_design_scores_gemma":[0.00019194391,0.00029211317,0.0019624052,0.000055395765,0.000022147111,0.000050323262,0.000005916947,0.001164929,0.00076177536,0.00039562877,0.9949193,0.00017811591],"about_ca_topic_score_codex":0.0000071103154,"about_ca_topic_score_gemma":0.0000033719225,"teacher_disagreement_score":0.061134897,"about_ca_system_score_codex":0.000025223468,"about_ca_system_score_gemma":0.00006923,"threshold_uncertainty_score":0.67221844},"labels":[],"label_agreement":null},{"id":"W3177207463","doi":"10.1002/mrm.28886","title":"Design and characterization of a 3D‐printed axon‐mimetic phantom for diffusion MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Fondation Brain Canada","keywords":"Kurtosis; Imaging phantom; Materials science; Biomedical engineering; Diffusion MRI; Reproducibility; Thermal diffusivity; Diffusion; Effective diffusion coefficient; Nuclear magnetic resonance; Nuclear medicine; Chemistry; Magnetic resonance imaging; Physics; Mathematics; Medicine; Radiology","score_opus":0.051198182673256036,"score_gpt":0.33682873781737016,"score_spread":0.2856305551441141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177207463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4567247,0.0042901314,0.5290372,0.008074176,0.00005594479,0.001537709,0.0000079607,0.00006893302,0.00020324494],"genre_scores_gemma":[0.6275293,0.012231078,0.3551276,0.0017908134,0.0001820367,0.0006210157,0.00013670887,0.00006536364,0.002316056],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99903506,0.000035760924,0.00033699762,0.0002911641,0.00014958602,0.00015143455],"domain_scores_gemma":[0.99928325,0.00016400541,0.00008451663,0.00027709763,0.00013628337,0.00005487207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018569126,0.00010992215,0.00032451522,0.00009978231,0.000028104578,0.0000030213305,0.000053796295,0.00004686857,0.000057263544],"category_scores_gemma":[0.00022459893,0.00009319976,0.000018319211,0.00034018082,0.00014266084,0.000027032089,0.00003560305,0.00010080824,4.802224e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016083792,0.00012918105,0.0036404065,0.00015869856,0.0000017797404,0.000023308197,0.0001856686,0.000001518654,0.8433113,0.00032937335,0.00013794508,0.15191998],"study_design_scores_gemma":[0.012149201,0.0033506928,0.5557097,0.004189521,0.00024408069,0.00039046744,0.0001778791,0.08324326,0.20721439,0.005065987,0.12780362,0.00046119542],"about_ca_topic_score_codex":0.000007940189,"about_ca_topic_score_gemma":0.0000010417278,"teacher_disagreement_score":0.6360969,"about_ca_system_score_codex":0.000018778068,"about_ca_system_score_gemma":0.00003717171,"threshold_uncertainty_score":0.38005757},"labels":[],"label_agreement":null},{"id":"W3178219752","doi":"10.1002/hbm.25580","title":"Longitudinal white matter changes associated with cognitive training","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Working memory; Psychology; White matter; Cognitive psychology; Task (project management); Cognition; n-back; Diffusion MRI; Neuroscience; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.17053381450328395,"score_gpt":0.3590997047724677,"score_spread":0.18856589026918377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3178219752","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8698065,0.000089758454,0.06236192,0.036754336,0.000027099719,0.0005978849,0.000027747334,0.00064027344,0.02969446],"genre_scores_gemma":[0.9854346,0.000002680082,0.003112609,0.0063658403,0.00009697468,0.00007487384,0.00014837616,0.000036092682,0.004727957],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991491,0.000030506171,0.00012046717,0.00032199084,0.00013767008,0.00024026269],"domain_scores_gemma":[0.99943763,0.00009968342,0.00007943003,0.00017691679,0.00013912436,0.00006724291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010185925,0.00012623183,0.00020607236,0.000074407384,0.00022480004,0.000029333252,0.000043943193,0.00003911739,0.00034118118],"category_scores_gemma":[0.000087125336,0.00011993293,0.00003877772,0.00025890482,0.00007884516,0.000046381916,0.00004084493,0.00021804425,0.000017163278],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058223657,0.00046873267,0.786192,0.00022601611,0.0003934559,0.0014614937,0.0076970286,0.0000075282155,0.16998537,0.0039716447,0.024706153,0.0048323777],"study_design_scores_gemma":[0.00087896595,0.00008968156,0.9896839,0.0010578951,0.00006306142,0.00021273144,0.0011741244,0.000046039433,0.0006714781,0.0009192042,0.00499065,0.00021226128],"about_ca_topic_score_codex":0.0000014339619,"about_ca_topic_score_gemma":0.000021451724,"teacher_disagreement_score":0.20349193,"about_ca_system_score_codex":0.00003645257,"about_ca_system_score_gemma":0.000032807187,"threshold_uncertainty_score":0.4890723},"labels":[],"label_agreement":null},{"id":"W3179211250","doi":"10.3389/fneur.2021.673060","title":"Peripheral Nerve Focused Ultrasound Lesioning—Visualization and Assessment Using Diffusion Weighted Imaging","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Toronto Western Hospital; Hospital for Sick Children; University of Toronto; University Health Network","funders":"Hospital for Sick Children; Mitacs; Fondation Brain Canada","keywords":"Diffusion MRI; Tractography; Fractional anisotropy; Magnetic resonance imaging; Medicine; Sciatic nerve; Lesion; Biomedical engineering; Ultrasound; Magnetic resonance neurography; Radiology; Nuclear medicine; Pathology; Anatomy","score_opus":0.03251555172701872,"score_gpt":0.34715136693088894,"score_spread":0.31463581520387024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179211250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.72024786,0.0003427281,0.27700335,0.0017193034,0.00018703191,0.0002004809,0.0000023153664,0.00008731677,0.0002096099],"genre_scores_gemma":[0.84326327,0.0003324449,0.15430504,0.0018572591,0.00006291686,0.0000231734,0.000048117294,0.000036025434,0.00007172562],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989798,0.000096810174,0.00021528288,0.00039546337,0.00010153966,0.00021110644],"domain_scores_gemma":[0.99953544,0.000044751436,0.000072194765,0.00022770574,0.000056590627,0.000063314044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006623673,0.00012440624,0.00023225498,0.00012397247,0.00011012065,0.00002083871,0.00004757165,0.00006256684,0.00001611884],"category_scores_gemma":[0.00004854179,0.00012802212,0.000033723307,0.00026721507,0.00009707275,0.00008068594,0.00006957726,0.00027435584,1.8018564e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010218217,0.00018128991,0.9013401,0.000032883174,0.000009179259,0.00035691747,0.00011751787,0.000031278523,0.08646161,0.0017947704,0.0013273156,0.008244911],"study_design_scores_gemma":[0.0048075034,0.00031760565,0.5300067,0.00011504662,0.00013917121,0.002277355,0.00019462821,0.4157919,0.0064016175,0.013014693,0.026445175,0.0004885817],"about_ca_topic_score_codex":0.000015668998,"about_ca_topic_score_gemma":0.0000023505527,"teacher_disagreement_score":0.4157606,"about_ca_system_score_codex":0.000050319657,"about_ca_system_score_gemma":0.00006472099,"threshold_uncertainty_score":0.5220591},"labels":[],"label_agreement":null},{"id":"W3179308066","doi":"10.3389/fnhum.2021.662031","title":"Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review","year":2021,"lang":"en","type":"review","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":147,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Russian Science Foundation; Russian Foundation for Basic Research","keywords":"White matter; Cognition; Psychology; Neuroimaging; Developmental psychology; Brain Structure and Function; Neuroscience; Lateralization of brain function; Cognitive psychology; Medicine; Magnetic resonance imaging","score_opus":0.12143790301349104,"score_gpt":0.41143635391207445,"score_spread":0.2899984508985834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179308066","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000006236893,0.9709854,0.02507673,0.0006366582,0.000107712964,0.0018128917,0.000026143483,0.00006180756,0.001286422],"genre_scores_gemma":[0.00007918826,0.9805298,0.0149039095,0.002694885,0.000036898055,0.00039386892,0.000060793638,0.000032790096,0.0012679102],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998392,0.00009087045,0.0003854625,0.0007556527,0.00017378102,0.00020226934],"domain_scores_gemma":[0.9993376,0.000027333163,0.00014869959,0.0002929916,0.00006814628,0.00012519924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014298173,0.00022909405,0.00076741615,0.00029334787,0.00018748992,0.000048193833,0.0001147044,0.000075155025,0.000013713029],"category_scores_gemma":[0.00013006454,0.0002200007,0.00007543109,0.00091190526,0.00017743674,0.00012119006,0.00013313451,0.0004276086,0.0000016592599],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000075289195,0.00039103665,0.010427327,0.04756943,0.000032252912,0.00037780765,0.0004170706,0.0000053499593,0.000042995784,0.0021961336,0.3765956,0.56193745],"study_design_scores_gemma":[0.00014924703,0.000071160044,0.004774867,0.020508567,0.00040458908,0.0003438432,0.000010529282,0.00003823535,0.0000015669333,0.0008852032,0.9725016,0.00031060033],"about_ca_topic_score_codex":6.803148e-7,"about_ca_topic_score_gemma":4.847945e-7,"teacher_disagreement_score":0.595906,"about_ca_system_score_codex":0.00007215699,"about_ca_system_score_gemma":0.00007514247,"threshold_uncertainty_score":0.8971368},"labels":[],"label_agreement":null},{"id":"W3179371357","doi":"10.1002/mrm.28926","title":"MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Connectomics; Diffusion MRI; Fractional anisotropy; Connectome; Pattern recognition (psychology); Artificial intelligence; Orientation (vector space); Data set; Computer science; Nuclear magnetic resonance; Mathematics; Statistics; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Physics; Functional connectivity; Radiology","score_opus":0.046346992715682184,"score_gpt":0.3551013306261533,"score_spread":0.30875433791047113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3179371357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93732166,0.010185884,0.033834178,0.014523561,0.00012327448,0.0029856155,0.000043039436,0.00016545491,0.00081731],"genre_scores_gemma":[0.85637486,0.0034144563,0.1373222,0.0010588205,0.00013693175,0.0007940937,0.00007880875,0.000042831656,0.0007769924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981232,0.00011079845,0.00053696835,0.00067353185,0.00021684302,0.00033860482],"domain_scores_gemma":[0.9984231,0.0007276487,0.000070648915,0.00052248535,0.00014010347,0.000116021285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005092121,0.00020546645,0.00049948646,0.00018347523,0.00009074025,0.000008950611,0.00009351717,0.00009357313,0.00009812321],"category_scores_gemma":[0.000800203,0.00018164053,0.00004039779,0.00064178207,0.00020608869,0.000058803784,0.0000997678,0.00030333374,0.0000012201923],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039487792,0.0012151609,0.5225175,0.00038831632,0.0000062760546,0.00040791513,0.0011179771,0.000011072721,0.060754422,0.0015672203,0.0012303833,0.4103889],"study_design_scores_gemma":[0.009090682,0.00045864555,0.9196019,0.0011494044,0.000051032872,0.00014370678,0.00033454236,0.035427213,0.0014462881,0.004482268,0.02756255,0.00025173943],"about_ca_topic_score_codex":0.00016605982,"about_ca_topic_score_gemma":0.00014878015,"teacher_disagreement_score":0.41013715,"about_ca_system_score_codex":0.000092361544,"about_ca_system_score_gemma":0.000042323038,"threshold_uncertainty_score":0.7407086},"labels":[],"label_agreement":null},{"id":"W3183527235","doi":"10.3389/fnagi.2021.711579","title":"Specific White Matter Tracts and Diffusion Properties Predict Conversion From Mild Cognitive Impairment to Alzheimer’s Disease","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; National Institute of General Medical Sciences; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Inferior longitudinal fasciculus; Fasciculus; Neuroscience; Posterior cingulate; Superior longitudinal fasciculus; Alzheimer's disease; Psychology; Medicine; Cardiology; Disease; Internal medicine; Cognition; Magnetic resonance imaging; Radiology","score_opus":0.05234523500382029,"score_gpt":0.29539372389360896,"score_spread":0.24304848888978867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183527235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9626042,0.00096311094,0.02684434,0.008170777,0.0004084359,0.0007414527,0.000049055998,0.00010783035,0.00011077311],"genre_scores_gemma":[0.9831936,0.00036303225,0.010234442,0.005793316,0.000040119157,0.000057133013,0.000015219876,0.000019791956,0.0002833661],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99865156,0.00003771938,0.00017168914,0.00064739736,0.00024230978,0.00024932658],"domain_scores_gemma":[0.9993629,0.000019675326,0.000044890727,0.0002684307,0.000044962322,0.00025914598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005617911,0.00014430743,0.0001755129,0.00011893053,0.00013094809,0.000052663978,0.00010281574,0.000022041,0.000013908004],"category_scores_gemma":[0.000041069703,0.00013021544,0.00003263813,0.00032574777,0.00017986001,0.00015720467,0.00016752095,0.00017749415,0.000005619117],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015641251,0.00021714115,0.96260697,0.00002550952,0.0000022411775,0.00019040023,0.00041649598,0.000014548277,0.024638304,0.0000031343527,0.010499226,0.0012295963],"study_design_scores_gemma":[0.00059444434,0.00006492277,0.9754707,0.00045410683,0.000041618914,0.00001739504,0.00020068401,0.0030737699,0.016271584,0.00011153664,0.0035373645,0.00016187954],"about_ca_topic_score_codex":0.0000071807635,"about_ca_topic_score_gemma":2.8680142e-7,"teacher_disagreement_score":0.020589355,"about_ca_system_score_codex":0.000038714836,"about_ca_system_score_gemma":0.000048334998,"threshold_uncertainty_score":0.5310032},"labels":[],"label_agreement":null},{"id":"W3183649267","doi":"10.3174/ajnr.a7221","title":"Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; Selegiline; Atlas (anatomy); Spinal cord; Disease; Parkinson's disease; Internal medicine; Psychiatry; Anatomy","score_opus":0.11762002267790271,"score_gpt":0.3967953965679264,"score_spread":0.27917537389002367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183649267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89545864,0.00018085366,0.09857377,0.005598342,0.000054866123,0.000079028556,0.0000015716525,0.000014273299,0.000038687525],"genre_scores_gemma":[0.9444394,0.00036620602,0.054298066,0.0007993177,0.00007213638,0.0000040030764,0.0000024956098,0.000012852979,0.0000055264113],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99888897,0.00013466201,0.0005384609,0.00016428971,0.00013287863,0.00014075683],"domain_scores_gemma":[0.99866456,0.0001484183,0.00054729456,0.0001991288,0.0003748636,0.00006574113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015994984,0.00008730553,0.00042339458,0.00023434573,0.000019221678,0.000003395896,0.0001178878,0.000026512149,0.0000046789264],"category_scores_gemma":[0.00046479917,0.00007941471,0.000085758824,0.0006825423,0.00016635667,0.000033082466,0.00001661011,0.00028459862,0.0000011954924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034850591,0.0006096883,0.55058753,0.00012573357,0.000044523353,0.00085913535,0.000051042844,0.00047295942,0.29324347,0.0034800714,0.00053490314,0.14650586],"study_design_scores_gemma":[0.0012817763,0.005931257,0.96181625,0.00013252032,0.00012720433,0.0036156902,0.00009118398,0.000270619,0.018674333,0.00091373036,0.006952913,0.00019253792],"about_ca_topic_score_codex":0.000005572068,"about_ca_topic_score_gemma":0.000001878615,"teacher_disagreement_score":0.4112287,"about_ca_system_score_codex":0.000038779246,"about_ca_system_score_gemma":0.00042164585,"threshold_uncertainty_score":0.3238438},"labels":[],"label_agreement":null},{"id":"W3183779008","doi":"10.3390/brainsci11070943","title":"Brain Structural Connectivity Differences in Patients with Normal Cognition and Cognitive Impairment","year":2021,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Dementia; Psychology; Cognition; Montreal Cognitive Assessment; Magnetic resonance imaging; Audiology; Neuroimaging; Neuroscience; Cognitive impairment; Medicine; Pathology; Disease; Radiology","score_opus":0.03887840872240967,"score_gpt":0.32956948718832185,"score_spread":0.2906910784659122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183779008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99438417,0.00002530971,0.000718707,0.004052064,0.000012413851,0.00031303853,0.000018695937,0.000035355435,0.00044027492],"genre_scores_gemma":[0.99674606,0.0000030399733,0.0019438693,0.00121205,0.000011721123,0.000026242084,0.00001666151,0.0000034786226,0.000036895715],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924004,0.000037619677,0.00009372508,0.00028751433,0.000192552,0.00014855541],"domain_scores_gemma":[0.99950343,0.00025825837,0.000044468656,0.000060562346,0.000079813326,0.000053451247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011572002,0.00007837846,0.00012161623,0.000056565117,0.00013636061,0.00003137133,0.00003670889,0.000018166797,0.000022623622],"category_scores_gemma":[0.00018443602,0.00005645205,0.000012422988,0.00032355418,0.0003634436,0.0001545513,0.000040967607,0.00008352259,6.540705e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054586464,0.000086461165,0.9928101,0.000011175483,0.000004071228,0.00000832389,0.00014921956,4.170742e-7,0.0004169277,0.0004766038,0.000046239755,0.0059358906],"study_design_scores_gemma":[0.0010866652,0.000432336,0.99434423,0.0000949583,0.000010356574,0.000021120595,0.0002657424,0.00018585642,0.0018562232,0.001599897,0.000020560965,0.000082045364],"about_ca_topic_score_codex":0.000012148105,"about_ca_topic_score_gemma":0.000031362284,"teacher_disagreement_score":0.0058538453,"about_ca_system_score_codex":0.00001105472,"about_ca_system_score_gemma":0.00006361962,"threshold_uncertainty_score":0.23020478},"labels":[],"label_agreement":null},{"id":"W3184054006","doi":"10.1016/j.neubiorev.2021.07.020","title":"White matter integrity differences in obesity: A meta-analysis of diffusion tensor imaging studies","year":2021,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Fondation Institut Universitaire de Cardiologie et de Pneumologie de Québec","keywords":"Fractional anisotropy; Diffusion MRI; Corpus callosum; White matter; Meta-analysis; Obesity; Medicine; Psychology; Neuroscience; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.6445659611611562,"score_gpt":0.5369526380442776,"score_spread":0.10761332311687855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184054006","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00047355756,0.9971081,0.00022637748,0.00007819815,0.0000789246,0.0018681152,0.00009118566,0.000052021933,0.000023515011],"genre_scores_gemma":[0.00038593475,0.9953288,0.0024211395,0.00068865385,0.000015653295,0.0007739645,0.000041310403,0.00003497433,0.00030957183],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957091,0.0003555337,0.0017499533,0.0012898257,0.00049268705,0.00040286194],"domain_scores_gemma":[0.9972125,0.000019538484,0.0010891082,0.001355237,0.00018522133,0.00013838237],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006699584,0.00066306134,0.008662222,0.0009180042,0.00009906616,0.000050852253,0.0005539391,0.00011871972,0.00017138023],"category_scores_gemma":[0.0002974712,0.00039989108,0.003495574,0.004119673,0.00046123998,0.00014496755,0.0004495639,0.0008982756,0.0000117375985],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025345505,0.0010091545,0.16679686,0.006276855,0.00012555963,0.00013450588,0.000082420345,1.1577639e-7,0.00007724214,0.000045365916,0.0007771399,0.8246722],"study_design_scores_gemma":[0.00004775436,0.000043611493,0.010941072,0.0027681654,0.18399607,0.000052373118,0.000024766041,0.000014155104,0.0000011456078,0.000009086796,0.80178326,0.00031854503],"about_ca_topic_score_codex":0.000030164405,"about_ca_topic_score_gemma":0.000011769301,"teacher_disagreement_score":0.8243537,"about_ca_system_score_codex":0.000107196625,"about_ca_system_score_gemma":0.00011943297,"threshold_uncertainty_score":0.9998453},"labels":[],"label_agreement":null},{"id":"W3184630054","doi":"10.3389/fnhum.2021.681634","title":"Effect of Aerobic Exercise on White Matter Tract Microstructure in Young and Middle-Aged Healthy Adults","year":2021,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé; National Institute on Aging; National Institutes of Health; Réseau québécois de recherche sur le vieillissement","keywords":"Fractional anisotropy; Cardiorespiratory fitness; Aerobic exercise; White matter; Fasciculus; Medicine; Psychology; Physical therapy; Internal medicine; Magnetic resonance imaging","score_opus":0.019214955661276026,"score_gpt":0.3080646965863459,"score_spread":0.2888497409250699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184630054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99778074,0.00014821485,0.00085879525,0.00039009957,0.00017295784,0.0004930679,0.0000070009414,0.000028078995,0.00012101641],"genre_scores_gemma":[0.9962612,0.000117291274,0.0027242296,0.0006922817,0.000009988872,0.00003629205,0.000005060407,0.00001605868,0.00013760453],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99885803,0.000064027096,0.0002358092,0.00047908578,0.000140918,0.00022210476],"domain_scores_gemma":[0.9994698,0.000025053736,0.00007849404,0.00034156116,0.000017180155,0.00006787332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012813465,0.00013245533,0.0002876935,0.00018184696,0.00006962771,0.000014743029,0.00011887932,0.000044899924,0.000005366221],"category_scores_gemma":[0.000045747383,0.00012119576,0.000034176228,0.00042275386,0.00019621244,0.00007697559,0.000045925994,0.00032503114,2.2688371e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027976435,0.00010930959,0.9555586,0.0002605234,2.7980295e-7,0.00008081771,0.00025920302,0.00004289532,0.042102303,0.000010918113,0.0005837701,0.0007116397],"study_design_scores_gemma":[0.0013212162,0.0005813629,0.9677563,0.0006385409,0.000009227604,0.0000920304,0.00003426496,0.00036463735,0.02886772,0.00014351367,0.00007402353,0.00011717787],"about_ca_topic_score_codex":0.0000089303785,"about_ca_topic_score_gemma":0.000006843996,"teacher_disagreement_score":0.013234583,"about_ca_system_score_codex":0.000037458576,"about_ca_system_score_gemma":0.000020704043,"threshold_uncertainty_score":0.49422196},"labels":[],"label_agreement":null},{"id":"W3184734890","doi":"10.15829/1728-8800-2021-2915","title":"White matter integrity of watershed areas is potentially influenced by hypoperfusion in the presence permanent atrial fibrillation","year":2021,"lang":"en","type":"article","venue":"CARDIOVASCULAR THERAPY AND PREVENTION","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Russian Foundation for Basic Research","keywords":"Medicine; White matter; Atrial fibrillation; Cardiology; Internal medicine; Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Nuclear medicine; Radiology","score_opus":0.041633377116252576,"score_gpt":0.306946594806841,"score_spread":0.2653132176905884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3184734890","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9796137,0.0057257703,0.0122029865,0.0017262757,0.000027119033,0.0005558862,0.000007242077,0.000017118797,0.00012386628],"genre_scores_gemma":[0.99288553,0.005186368,0.0013554536,0.00024466083,0.00006507853,0.000016233347,0.0000941211,0.00000884143,0.00014372995],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99910706,0.00018785006,0.0001900539,0.00021948903,0.00021021097,0.00008534851],"domain_scores_gemma":[0.999461,0.000018996821,0.00004743353,0.0003703468,0.00008123289,0.000020981792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034906543,0.000083836174,0.00019228244,0.000031521187,0.000050760635,0.000016717908,0.000054300388,0.000055798835,0.000034961762],"category_scores_gemma":[0.000013119491,0.000060038048,0.0003357823,0.00014290576,0.000040083323,0.00008430204,0.00002586469,0.00012889113,0.0000013321594],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008699339,0.00021802129,0.2876568,0.00034452113,0.00089674164,0.000045762426,0.0041455715,0.00077694794,0.16185583,0.0002608951,0.0031532175,0.5397757],"study_design_scores_gemma":[0.004867371,0.00030548024,0.82567245,0.00043205763,0.0004673937,0.000355258,0.00037165565,0.0005941285,0.07765946,0.0069075623,0.08200362,0.00036358132],"about_ca_topic_score_codex":0.000018619752,"about_ca_topic_score_gemma":6.877406e-7,"teacher_disagreement_score":0.53941214,"about_ca_system_score_codex":0.000011402292,"about_ca_system_score_gemma":0.000019367853,"threshold_uncertainty_score":0.24482806},"labels":[],"label_agreement":null},{"id":"W3185192526","doi":"10.1002/hbm.25574","title":"Improving the predictive potential of diffusion <scp>MRI</scp> in schizophrenia using normative models—Towards subject‐level classification","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Center for Advancing Translational Sciences; Medical Research Council; National Institute of Mental Health; Ministry of Health, State of Israel; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Fractional anisotropy; Normative; White matter; Diffusion MRI; Psychology; Raw score; Magnetic resonance imaging; Statistics; Artificial intelligence; Computer science; Medicine; Mathematics; Radiology","score_opus":0.12060438267775916,"score_gpt":0.32961247517300546,"score_spread":0.2090080924952463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185192526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5061478,0.000058291087,0.49189794,0.00057679816,0.000024236384,0.00041520403,0.000021431551,0.00007828644,0.000779998],"genre_scores_gemma":[0.9751407,0.000023346138,0.024136545,0.00027560288,0.0001002338,0.000056239824,0.00006807305,0.00003097972,0.00016828578],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855924,0.000111961,0.00044006325,0.00036984103,0.00027577058,0.0002431048],"domain_scores_gemma":[0.99883777,0.0001392822,0.0002870229,0.00045912055,0.00022207011,0.00005470616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003062701,0.00016654268,0.0002602269,0.00018547365,0.00030522805,0.000028401219,0.0001573191,0.00008222058,0.00000494214],"category_scores_gemma":[0.00024839144,0.00014530844,0.000097615484,0.00049510394,0.00014162262,0.000202418,0.00018182259,0.000409149,9.998299e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013935938,0.00010996388,0.00035423448,0.00008727073,0.000015452493,0.00001149401,0.0015147573,0.0009922676,0.9896951,0.0045665135,0.000110662906,0.0025283885],"study_design_scores_gemma":[0.001793351,0.00008252623,0.20705858,0.00063029287,0.00007818364,0.00010691884,0.004785209,0.7429821,0.021132007,0.020904772,0.00030399667,0.00014208801],"about_ca_topic_score_codex":0.00010249788,"about_ca_topic_score_gemma":0.000013507735,"teacher_disagreement_score":0.9685631,"about_ca_system_score_codex":0.00013316421,"about_ca_system_score_gemma":0.00014866256,"threshold_uncertainty_score":0.5925506},"labels":[],"label_agreement":null},{"id":"W3186594303","doi":"10.1186/s12938-021-00909-0","title":"ABrainVis: an android brain image visualization tool","year":2021,"lang":"en","type":"article","venue":"BioMedical Engineering OnLine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Horizon 2020 Framework Programme; Horizon 2020; Agencia Nacional de Investigación y Desarrollo; Centre for Biotechnology and Bioengineering; European Commission","keywords":"Visualization; Computer science; Android (operating system); Computer vision; Human–computer interaction; Artificial intelligence; Computer graphics (images); Operating system","score_opus":0.03580716144072872,"score_gpt":0.36973839245388457,"score_spread":0.33393123101315586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186594303","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18997356,0.0001447906,0.79851335,0.009801672,0.000108953725,0.00022942838,0.000090454974,0.0010749695,0.000062812],"genre_scores_gemma":[0.35048842,0.00024508033,0.6330171,0.0077668712,0.0015261271,0.00008677712,0.005503166,0.00018190347,0.0011845109],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99900806,0.000011892658,0.00024413288,0.00030081696,0.0002273532,0.00020772034],"domain_scores_gemma":[0.9992519,0.00005268863,0.000030502093,0.00035760607,0.00009119729,0.00021609539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009134638,0.00013105849,0.0001888589,0.000094148636,0.000035897607,0.000018169847,0.000075866716,0.00008082329,0.00010228705],"category_scores_gemma":[0.0005103893,0.0001274464,0.000055178913,0.00045683177,0.00005227296,0.00009398981,0.00004964879,0.00017894863,0.000009511392],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022041195,0.0013737875,0.00015071432,0.00020896904,0.000031315027,0.00039569382,0.000057779485,0.00006205879,0.9578365,0.008366007,0.007451402,0.024043694],"study_design_scores_gemma":[0.0018655594,0.00042101947,0.010200422,0.0002833573,0.000071073446,0.0008190563,0.00004210067,0.2444885,0.037062097,0.00066908804,0.7035724,0.000505327],"about_ca_topic_score_codex":0.0000018555482,"about_ca_topic_score_gemma":3.86077e-7,"teacher_disagreement_score":0.92077446,"about_ca_system_score_codex":0.000038342292,"about_ca_system_score_gemma":0.000074886484,"threshold_uncertainty_score":0.5197114},"labels":[],"label_agreement":null},{"id":"W3186964932","doi":"10.82308/16280","title":"This is your brain on disk: the impact of numerical instabilities in neuroscience","year":2021,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Health Canada; Canada First Research Excellence Fund; Canadian Open Neuroscience Platform; Compute Canada; Mitacs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Neuroscience; Computational neuroscience; Computer science; Psychology; Cognitive science","score_opus":0.07802095761333774,"score_gpt":0.3609086670552924,"score_spread":0.2828877094419546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186964932","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97623146,0.00004735874,0.0000072353346,0.0021881424,0.00005326241,0.0004097024,0.00030945797,0.0001282509,0.02062515],"genre_scores_gemma":[0.9948644,0.00008137387,0.0007733763,0.0030720262,0.000012049531,0.00005919603,0.000008334196,0.00004034346,0.0010888943],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99807936,0.00016260054,0.000415337,0.00058031856,0.00038760065,0.00037476374],"domain_scores_gemma":[0.99830294,0.0003415101,0.00013616134,0.0009262824,0.0001413577,0.00015173078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034629597,0.0002342924,0.0003476821,0.000116255535,0.0002908934,0.000019898062,0.00031201146,0.00008092073,0.0001924725],"category_scores_gemma":[0.0015361792,0.00016803463,0.00024260294,0.0010036095,0.00020401258,0.00021911638,0.00019393956,0.00076850195,0.000023852492],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028793252,0.002405223,0.017628657,0.00014143178,0.000045388366,0.00023562767,0.00008396265,0.00031088028,0.6800563,0.19634968,0.00029049462,0.102164425],"study_design_scores_gemma":[0.0028048833,0.0020381468,0.24169864,0.00059252704,0.0000977396,0.0006499733,0.0003120412,0.0022287369,0.50207675,0.06608882,0.18029909,0.0011126704],"about_ca_topic_score_codex":0.00018771434,"about_ca_topic_score_gemma":0.000007810259,"teacher_disagreement_score":0.22406998,"about_ca_system_score_codex":0.00025148457,"about_ca_system_score_gemma":0.000069981295,"threshold_uncertainty_score":0.68522537},"labels":[],"label_agreement":null},{"id":"W3187151879","doi":"10.21203/rs.3.rs-747810/v1","title":"The Value of Diffusion Kurtosis Imaging In Detecting Delayed Brain Development of Premature Infants","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Kurtosis; Diffusion MRI; Value (mathematics); Diffusion; Brain development; Medicine; Psychology; Neuroscience; Physics; Radiology; Mathematics; Statistics; Magnetic resonance imaging","score_opus":0.08059295761425733,"score_gpt":0.4464782498589613,"score_spread":0.36588529224470395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187151879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889979,0.0014383884,0.0053932965,0.0022432695,0.000029901634,0.0014986172,0.000012537617,0.00005426482,0.00033183125],"genre_scores_gemma":[0.970941,0.0004821691,0.028101679,0.000026580577,0.000028470258,0.00027815494,0.000045065357,0.00003661535,0.000060234503],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974673,0.00025430083,0.00061650365,0.00044480176,0.00083491625,0.00038218807],"domain_scores_gemma":[0.9973733,0.0008348615,0.00022227815,0.0008751994,0.0006133551,0.00008102465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016227112,0.00016708973,0.00037163385,0.00031771284,0.00019989732,0.00003102211,0.00035004056,0.00013629626,0.0000085382035],"category_scores_gemma":[0.0015504799,0.00012809697,0.00011093934,0.00060495234,0.00015120901,0.000032390766,0.001479602,0.001553067,5.3595323e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005612914,0.00083724555,0.08111522,0.0061936453,0.00011601142,0.00009624553,0.009491908,0.00034926974,0.59385407,0.0005542846,0.0005192147,0.3063116],"study_design_scores_gemma":[0.0014434896,0.00016561664,0.33319166,0.021149311,0.000046082932,0.000046234676,0.0057989843,0.014041988,0.61626595,0.0041160397,0.00324761,0.000487003],"about_ca_topic_score_codex":0.00014042814,"about_ca_topic_score_gemma":0.00006297197,"teacher_disagreement_score":0.3058246,"about_ca_system_score_codex":0.00019542348,"about_ca_system_score_gemma":0.000635983,"threshold_uncertainty_score":0.67473894},"labels":[],"label_agreement":null},{"id":"W3187199062","doi":"10.3389/fnins.2021.665017","title":"Modern Technology in Multi-Shell Diffusion MRI Reveals Diffuse White Matter Changes in Young Adults With Relapsing-Remitting Multiple Sclerosis","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"White matter; Fornix; Diffusion MRI; Fractional anisotropy; Multiple sclerosis; Tractography; Medicine; Superior longitudinal fasciculus; Corticospinal tract; Uncinate fasciculus; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Psychology; Internal medicine; Hippocampus; Psychiatry","score_opus":0.0393002842218396,"score_gpt":0.2780610686705374,"score_spread":0.23876078444869783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187199062","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9162593,0.00019610944,0.077115506,0.005357368,0.00019389209,0.00064418156,0.000008295342,0.0001391589,0.00008617999],"genre_scores_gemma":[0.88679916,0.00057275605,0.111078106,0.0009491804,0.000010235373,0.00014627494,0.0000044893377,0.000034912417,0.0004049038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800867,0.000050736133,0.00032380736,0.0009034537,0.00022446622,0.000488886],"domain_scores_gemma":[0.9991364,0.000031078245,0.00012207044,0.0005820877,0.000051526236,0.000076846736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014587857,0.00020386667,0.000344123,0.0005851063,0.000088004854,0.000026421296,0.00026259327,0.000107755885,0.0000024353546],"category_scores_gemma":[0.00025230047,0.00019149712,0.000027451428,0.0018336007,0.00024905332,0.00015854482,0.0002096952,0.000549777,0.0000014212693],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000050012623,0.0003120666,0.8700321,0.00003583756,3.411484e-7,0.00009701429,0.00034588168,0.00011677961,0.12753108,0.000004924453,0.00013671647,0.001337281],"study_design_scores_gemma":[0.0027222254,0.0000868437,0.9048282,0.0014063785,0.0000066766697,0.00010173547,0.00037200205,0.08068899,0.009107022,0.00030102956,0.00012823318,0.0002506607],"about_ca_topic_score_codex":0.000033391134,"about_ca_topic_score_gemma":0.0003075045,"teacher_disagreement_score":0.118424065,"about_ca_system_score_codex":0.00013081351,"about_ca_system_score_gemma":0.00003649503,"threshold_uncertainty_score":0.78090256},"labels":[],"label_agreement":null},{"id":"W3187359846","doi":"10.1109/isbi52829.2022.9761680","title":"Reproducibility and Evolution of Diffusion Mri Measurements Within the Cervical Spinal Cord in Multiple Sclerosis","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"EMI","keywords":"Multiple sclerosis; Spinal cord; Diffusion MRI; Reproducibility; Diffusion; Magnetic resonance imaging; Medicine; Computer science; Radiology; Physics; Mathematics","score_opus":0.09399315719702295,"score_gpt":0.3408187529118911,"score_spread":0.24682559571486817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187359846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9419244,0.00015368768,0.0059950612,0.049471803,0.00090212066,0.00088491477,0.00010632602,0.00012530164,0.00043636665],"genre_scores_gemma":[0.9969796,0.000039922754,0.0014699568,0.0010057208,0.00013246936,0.0002023188,0.000053030628,0.000021414966,0.000095546544],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99710345,0.0001373515,0.00056827295,0.00088202726,0.0011082172,0.00020064886],"domain_scores_gemma":[0.99871266,0.00011349169,0.0002298129,0.00072103785,0.00011050465,0.000112480695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00149988,0.00016044626,0.00022663655,0.00019229359,0.00023474476,0.000017570252,0.0003458011,0.000032534525,0.000095006246],"category_scores_gemma":[0.00039927388,0.00012889956,0.00008303628,0.00045931217,0.0003575352,0.00007322244,0.0003221952,0.00056106725,0.0000031122047],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022811538,0.0023333714,0.4373899,0.00007227409,0.000051707164,0.000024229474,0.00020861931,0.00016524557,0.54129523,0.0012200014,0.0030898598,0.011868397],"study_design_scores_gemma":[0.0053594196,0.0019781298,0.8530771,0.00057028583,0.000117455114,0.00035007746,0.00049913843,0.090165086,0.027614173,0.003537431,0.016198788,0.000532873],"about_ca_topic_score_codex":0.00028290114,"about_ca_topic_score_gemma":0.00000754632,"teacher_disagreement_score":0.51368105,"about_ca_system_score_codex":0.00051526213,"about_ca_system_score_gemma":0.000064185144,"threshold_uncertainty_score":0.52563715},"labels":[],"label_agreement":null},{"id":"W3187580021","doi":"10.1101/2021.08.08.455570","title":"Empirical Transmit Field Bias Correction of T1w/T2w Myelin Maps","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Japan Agency for Medical Research and Development","keywords":"Spurious relationship; Myelin; Field (mathematics); Computer science; Statistics; Psychology; Mathematics; Neuroscience","score_opus":0.06883031625254665,"score_gpt":0.3200902671224307,"score_spread":0.25125995086988406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3187580021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90509605,0.0010309581,0.086387016,0.0035891857,0.0012648756,0.0013696598,0.00013313474,0.0010309353,0.00009816118],"genre_scores_gemma":[0.96225566,0.0006682584,0.035406582,0.0009883591,0.00032163734,0.0002202715,0.0000017959006,0.00010732903,0.00003013498],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977573,0.00007827699,0.00063417153,0.0008556165,0.0003469654,0.00032768087],"domain_scores_gemma":[0.9973853,0.00015038619,0.0003409671,0.0013751745,0.0005330902,0.00021505481],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025257125,0.00039027873,0.00069763337,0.00027326192,0.000080721504,0.000047684134,0.0002612233,0.00047361644,0.00009301271],"category_scores_gemma":[0.00036465103,0.00041468238,0.00029347022,0.0006341292,0.00009681986,0.00006943107,0.00019996673,0.0011245492,0.000012895036],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001596329,0.0008653352,0.0384137,0.0012730545,0.00020701789,0.00018014947,0.00003590286,0.000083336614,0.9497777,0.00026453924,0.008613172,0.00012642586],"study_design_scores_gemma":[0.0005404928,0.00017624468,0.042938016,0.0011753867,0.00031243745,2.4076084e-7,0.0000055698947,0.0011105017,0.9193232,0.000007769998,0.033884928,0.0005251864],"about_ca_topic_score_codex":0.00003702678,"about_ca_topic_score_gemma":0.0000010194256,"teacher_disagreement_score":0.057159554,"about_ca_system_score_codex":0.00012885153,"about_ca_system_score_gemma":0.0004901326,"threshold_uncertainty_score":0.9998305},"labels":[],"label_agreement":null},{"id":"W3188867876","doi":"10.1101/2021.08.04.455122","title":"Test-retest reproducibility of <i>in vivo</i> oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Reproducibility; Diffusion MRI; Kurtosis; Voxel; Fractional anisotropy; Anisotropy; Nuclear magnetic resonance; Isotropy; Materials science; Sample size determination; Region of interest; Thermal diffusivity; Sensitivity (control systems); Biomedical engineering; Nuclear medicine; Mathematics; Physics; Magnetic resonance imaging; Statistics; Computer science; Medicine; Artificial intelligence; Radiology; Optics","score_opus":0.023801361879635646,"score_gpt":0.27499152429824186,"score_spread":0.2511901624186062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188867876","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961236,0.0011264731,0.0004612198,0.00062276766,0.000114131675,0.0012551915,0.00011082848,0.00017482307,0.000010951358],"genre_scores_gemma":[0.9408598,0.0010899844,0.05758306,0.00016669139,0.00006508875,0.00014980162,6.729151e-7,0.00007592862,0.00000896589],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.996341,0.000081364225,0.00081329537,0.0021284265,0.00023902324,0.0003968972],"domain_scores_gemma":[0.9966165,0.00017889639,0.00043021442,0.0023618154,0.00025543568,0.00015712979],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006965265,0.0004005885,0.0007866159,0.00023870877,0.00008042674,0.00003621292,0.00020411322,0.0002644819,0.000013297563],"category_scores_gemma":[0.00097624096,0.00043526836,0.00009480814,0.0006562716,0.00019180623,0.000067610126,0.00087372854,0.00070339965,0.000001048145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013693053,0.0002276053,0.3761825,0.00048055738,0.0000051876764,0.000028570073,0.00001299227,0.0000072628063,0.6229753,0.000030515108,0.000034347027,0.0000014789454],"study_design_scores_gemma":[0.0005471622,0.00006385417,0.40567648,0.0013357761,0.000039879298,1.5908948e-7,0.000004374019,0.0004182527,0.59121644,0.0000048172024,0.00042283215,0.00026997158],"about_ca_topic_score_codex":0.00017640505,"about_ca_topic_score_gemma":0.000018371127,"teacher_disagreement_score":0.05712184,"about_ca_system_score_codex":0.00041772408,"about_ca_system_score_gemma":0.00023702071,"threshold_uncertainty_score":0.9998099},"labels":[],"label_agreement":null},{"id":"W3188868842","doi":"10.1002/brb3.3159","title":"Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord","year":2023,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Région Bretagne; Mitacs; Institut National de la Santé et de la Recherche Médicale; Conseil Régional de Bretagne; European Commission","keywords":"Multiple sclerosis; Diffusion MRI; Spinal cord; Medicine; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Physical medicine and rehabilitation; Psychology; Psychiatry","score_opus":0.1573476211009158,"score_gpt":0.3692881384332028,"score_spread":0.211940517332287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188868842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9976741,0.000047287005,0.00046239674,0.001250451,0.000024507593,0.00041110715,0.000010095136,0.00009017223,0.000029895942],"genre_scores_gemma":[0.9988653,0.00003501192,0.0007305639,0.00010442441,0.000025166482,0.0001659944,0.000016595894,0.000011480115,0.00004545798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935466,0.000064076296,0.00015685275,0.00016489434,0.0001511454,0.00010837716],"domain_scores_gemma":[0.9994389,0.0002848965,0.000050348757,0.00015132378,0.000037695525,0.00003688112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038496146,0.00007710162,0.0001416501,0.00005889091,0.0000917772,0.000010856785,0.00006524965,0.000034009416,0.0000015557717],"category_scores_gemma":[0.00017960939,0.000053556025,0.00003665576,0.0002121136,0.00014136986,0.000031015486,0.00006640776,0.0001433861,7.0182097e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007686803,0.0003426979,0.8145953,0.00034525013,0.0000054298544,0.000032745254,0.00031926704,0.0000066346665,0.15710132,0.003222307,0.00029476438,0.02296564],"study_design_scores_gemma":[0.000510264,0.0001595413,0.99263144,0.0004580796,0.000024977053,0.000026556087,0.00016474832,0.00019305633,0.005224408,0.0003470016,0.0002002785,0.000059638438],"about_ca_topic_score_codex":0.00017331312,"about_ca_topic_score_gemma":0.00002396808,"teacher_disagreement_score":0.17803618,"about_ca_system_score_codex":0.00001530975,"about_ca_system_score_gemma":0.000015352492,"threshold_uncertainty_score":0.21839513},"labels":[],"label_agreement":null},{"id":"W3189777777","doi":"10.3389/fnimg.2022.930496","title":"Manifold-aware synthesis of high-resolution diffusion from structural imaging","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Fractional anisotropy; Diffusion; Metric (unit); Computer science; Tractography; Voxel; Artificial intelligence; Similarity (geometry); Resolution (logic); Image resolution; Anisotropic diffusion; Euclidean space; Mathematics; Computer vision; Image (mathematics); Mathematical analysis; Physics","score_opus":0.019672773296069864,"score_gpt":0.2769453763328992,"score_spread":0.2572726030368293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3189777777","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9149094,0.0005271503,0.07885917,0.003476977,0.00071934646,0.00062332046,0.00018402748,0.00031866954,0.00038189904],"genre_scores_gemma":[0.9599841,0.000047053545,0.039224274,0.00043171155,0.000056105968,0.00010297461,0.000061428575,0.000048579364,0.000043753058],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984389,0.00008820632,0.0003698145,0.0004888661,0.00033005996,0.00028413313],"domain_scores_gemma":[0.99913967,0.000076010474,0.000178482,0.0005058432,0.00003534937,0.00006465227],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102713006,0.00017703914,0.0003525392,0.00032985967,0.00021243577,0.000012811616,0.00023759945,0.00001806993,0.000073340045],"category_scores_gemma":[0.00006409961,0.00019534345,0.00009379184,0.00041222843,0.00007351545,0.00013222225,0.00030342332,0.00042926322,8.5202817e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033230218,0.00022472168,0.8696932,0.00008956031,0.000027005946,0.0003227489,0.00027299335,0.0013462377,0.047239147,0.00085370685,0.010325549,0.06927281],"study_design_scores_gemma":[0.0021954167,0.00010620661,0.6325321,0.000248487,0.00021917904,0.00026726164,0.0012566966,0.3165574,0.017485688,0.021170424,0.007296245,0.00066489953],"about_ca_topic_score_codex":0.00037581893,"about_ca_topic_score_gemma":0.0000013156935,"teacher_disagreement_score":0.31521115,"about_ca_system_score_codex":0.00018487575,"about_ca_system_score_gemma":0.00003502976,"threshold_uncertainty_score":0.7965875},"labels":[],"label_agreement":null},{"id":"W3190336459","doi":"10.3389/fnagi.2021.681208","title":"The Associations Between White Matter Disruptions and Cognitive Decline at the Early Stage of Subcortical Vascular Cognitive Impairment: A Case–Control Study","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"China-Japan Friendship Hospital; National Natural Science Foundation of China","keywords":"Cognition; Audiology; Psychology; White matter; Cognitive decline; Montreal Cognitive Assessment; Diffusion MRI; Neuropsychology; Cognitive impairment; Neuroscience; Medicine; Internal medicine; Disease; Dementia","score_opus":0.02873667231514283,"score_gpt":0.337903273763327,"score_spread":0.3091666014481842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190336459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93072367,0.00016211667,0.06476512,0.0029297809,0.00007198325,0.0009486398,0.00031854358,0.000030150768,0.000050017086],"genre_scores_gemma":[0.997972,0.00006229397,0.0005358938,0.0007970281,0.000019812382,0.00010817107,0.000005845256,0.00001419802,0.00048474746],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856347,0.0001974587,0.00029906988,0.00039148744,0.00028428817,0.00026422527],"domain_scores_gemma":[0.9988656,0.0005203747,0.00012661953,0.00027445744,0.00013441675,0.00007853822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042759423,0.000118342585,0.00022452067,0.000061826846,0.0005676524,0.00005792202,0.00011109162,0.000023564542,0.0000055774476],"category_scores_gemma":[0.00047095472,0.00008154211,0.000064340835,0.0005413003,0.00053082424,0.00009446424,0.00020091052,0.00027905076,0.0000011239238],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014058152,0.00014544406,0.9982889,0.0000049772357,0.0000177183,0.00016179383,0.00043517482,0.0000049760692,0.00012221283,0.000016389677,0.000057403897,0.00073094823],"study_design_scores_gemma":[0.0009235334,0.00011991777,0.9963388,0.000034659144,0.00022058577,0.00007276475,0.0011873111,0.00060561846,0.00019446257,0.00013024709,0.000094828254,0.000077281315],"about_ca_topic_score_codex":0.000025265304,"about_ca_topic_score_gemma":0.00003331083,"teacher_disagreement_score":0.06724836,"about_ca_system_score_codex":0.000044577122,"about_ca_system_score_gemma":0.00005085029,"threshold_uncertainty_score":0.43659806},"labels":[],"label_agreement":null},{"id":"W3190769832","doi":"10.1007/s00429-021-02358-w","title":"Dissecting whole-brain conduction delays through MRI microstructural measures","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health; Wellcome Trust; Wellcome","keywords":"Thermal conduction; Tractography; Nerve conduction velocity; Neuroscience; White matter; Constant (computer programming); Statistical physics; Physics; Computer science; Psychology; Magnetic resonance imaging","score_opus":0.04994246506520538,"score_gpt":0.3266202289761371,"score_spread":0.2766777639109317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190769832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88806796,0.00082753383,0.0801323,0.028838174,0.0006073775,0.0004007803,0.000047857775,0.0003584017,0.00071959256],"genre_scores_gemma":[0.9810297,0.000028148574,0.0121965455,0.004207812,0.0005486496,0.0000147049095,0.0002663004,0.000030687912,0.0016774681],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906534,0.000027519296,0.00018665589,0.00040112736,0.00013923303,0.00018014273],"domain_scores_gemma":[0.9993517,0.00006563631,0.00007766389,0.00025641182,0.0001829267,0.00006570105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052251035,0.00016211369,0.00018572697,0.000038801416,0.0002601257,0.000045107918,0.00003132207,0.00010715095,0.000057950732],"category_scores_gemma":[0.00016884036,0.00014171096,0.000060087437,0.00023481315,0.00007849791,0.00018643428,0.000034992063,0.00028614284,0.0000019744343],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009475688,0.000013867384,0.0031748242,0.00004894181,0.000035375448,0.000014137791,0.00022378116,0.000024531731,0.9546313,0.0043961587,0.0147210015,0.022621315],"study_design_scores_gemma":[0.0017696747,0.0002920592,0.07050007,0.00011030251,0.00020871873,0.003199791,0.0010192955,0.00025980794,0.2393183,0.0775599,0.60528725,0.000474849],"about_ca_topic_score_codex":0.000014155279,"about_ca_topic_score_gemma":0.00001207324,"teacher_disagreement_score":0.715313,"about_ca_system_score_codex":0.000032157044,"about_ca_system_score_gemma":0.00003251841,"threshold_uncertainty_score":0.57788056},"labels":[],"label_agreement":null},{"id":"W3190885595","doi":"10.3389/fsurg.2021.646465","title":"Constrained-Spherical Deconvolution Tractography in the Evaluation of the Corticospinal Tract in Glioma Surgery","year":2021,"lang":"en","type":"article","venue":"Frontiers in Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"ETH Zürich Foundation; Henan Provincial People's Hospital; Eidgenössische Technische Hochschule Zürich","keywords":"Tractography; Corticospinal tract; Fractional anisotropy; Diffusion MRI; Glioma; Medicine; Superior longitudinal fasciculus; White matter; Precentral gyrus; Motor cortex; Brain tumor; Nuclear medicine; Radiology; Magnetic resonance imaging; Pathology","score_opus":0.1080247719335625,"score_gpt":0.35704447353103375,"score_spread":0.24901970159747125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3190885595","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.990741,0.0010708823,0.005048046,0.0021751064,0.00027262588,0.00042836808,0.0000056416366,0.000018356339,0.0002399478],"genre_scores_gemma":[0.99692094,0.00016765286,0.0024557721,0.00028063473,0.000025333797,0.00011664972,0.000018747996,0.000010535539,0.0000037033183],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99827826,0.00035427476,0.0005407045,0.00022674046,0.0003970177,0.00020299591],"domain_scores_gemma":[0.9987936,0.000564694,0.00015718205,0.00035800552,0.00009938539,0.000027120139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015935681,0.00010208969,0.00033987325,0.00022589587,0.000028628006,0.000007756292,0.00007974879,0.00007054046,0.000020431551],"category_scores_gemma":[0.0008538152,0.00007502355,0.00019735779,0.0016589182,0.00017496555,0.00007846743,0.0000147862165,0.00029952388,3.0985592e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044408993,0.00047513563,0.9581736,0.00002454169,0.000005979794,0.00006399947,0.00009087553,0.000059004175,0.0013184416,0.00006165924,0.0029153512,0.036767036],"study_design_scores_gemma":[0.0002814649,0.000008115049,0.9926852,0.00017227374,0.000034350618,0.0001144162,0.0003941847,0.002033904,0.001312476,0.0022446148,0.0006423383,0.00007664695],"about_ca_topic_score_codex":0.00003372621,"about_ca_topic_score_gemma":0.000023729082,"teacher_disagreement_score":0.036690388,"about_ca_system_score_codex":0.00009787797,"about_ca_system_score_gemma":0.00036704543,"threshold_uncertainty_score":0.30593714},"labels":[],"label_agreement":null},{"id":"W3191188472","doi":"10.3389/fnagi.2021.700764","title":"White Matter Integrity Underlies the Physical-Cognitive Correlations in Subjective Cognitive Decline","year":2021,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministry of Science and Technology, Taiwan; Ministry of Education, India; Chang Gung Memorial Hospital; Chang Gung Medical Foundation; Shanghai Educational Development Foundation; Ministry of Education","keywords":"Montreal Cognitive Assessment; Cognitive decline; Cognition; Fractional anisotropy; Diffusion MRI; White matter; Effects of sleep deprivation on cognitive performance; Psychology; Dementia; Medicine; Physical medicine and rehabilitation; Gerontology; Internal medicine; Neuroscience; Magnetic resonance imaging; Cognitive impairment; Disease","score_opus":0.04874514009417484,"score_gpt":0.35189715554083767,"score_spread":0.3031520154466628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191188472","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.70168614,0.00009564303,0.2837973,0.011083857,0.00031638276,0.00057068473,0.000027610775,0.00008984969,0.002332549],"genre_scores_gemma":[0.99004686,0.0000590978,0.0038157185,0.0053949784,0.000035697205,0.00004674926,0.000010421131,0.000016321126,0.0005741798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99871725,0.000101229714,0.0001908061,0.0005101768,0.00020780964,0.00027275446],"domain_scores_gemma":[0.99927795,0.0002496779,0.00007197135,0.00022733702,0.000120040444,0.00005303224],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014569693,0.00013997768,0.00020977794,0.00014793864,0.00015651276,0.000043007403,0.00014619649,0.00003089604,0.0000061710803],"category_scores_gemma":[0.0005128776,0.00011433285,0.00005690895,0.0012801236,0.00049899856,0.00018375946,0.00015471077,0.00074452296,0.000007119378],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002135429,0.00020802951,0.99600935,0.00000852591,0.0000017222695,0.00006477551,0.0012173558,0.00005075982,0.0005203611,0.00019363267,0.00032077823,0.0013833268],"study_design_scores_gemma":[0.00044051599,0.000032353477,0.9778183,0.00020527365,0.000022728918,0.000059938535,0.0023113203,0.009679937,0.0019508208,0.0071678692,0.00018756022,0.00012336756],"about_ca_topic_score_codex":0.000016998361,"about_ca_topic_score_gemma":0.00002031315,"teacher_disagreement_score":0.2883607,"about_ca_system_score_codex":0.000074436924,"about_ca_system_score_gemma":0.00011459978,"threshold_uncertainty_score":0.46623582},"labels":[],"label_agreement":null},{"id":"W3191534335","doi":"10.1016/j.pscychresns.2021.111341","title":"Diffusion kurtosis imaging of white matter in bipolar disorder","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Hotchkiss Brain Institute; University of Calgary; University of Toronto","funders":"Canadian Institutes of Health Research; Pfizer Canada","keywords":"Diffusion MRI; White matter; Kurtosis; Fractional anisotropy; Voxel; Magnetic resonance imaging; Tractography; Nuclear magnetic resonance; Nuclear medicine; Medicine; Neuroscience; Physics; Psychology; Radiology; Mathematics; Statistics","score_opus":0.06794406722086672,"score_gpt":0.4084647973020994,"score_spread":0.3405207300812327,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191534335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91200626,0.004567515,0.0041206144,0.07340028,0.00018147596,0.0006158875,0.000016017068,0.00014812933,0.004943845],"genre_scores_gemma":[0.97905886,0.00069956516,0.01783934,0.0014748407,0.00010445526,0.000071379385,0.0000223047,0.000080240316,0.00064898655],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997612,0.0001876551,0.0004326005,0.00064072944,0.000552826,0.00057421305],"domain_scores_gemma":[0.99850255,0.000114763585,0.00007429247,0.00087331916,0.00029094008,0.00014413433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004116162,0.0001705942,0.0002962616,0.0005508525,0.00023575552,0.000032794684,0.00021709845,0.000034083383,0.0002444482],"category_scores_gemma":[0.00013516698,0.00017234228,0.000117130316,0.0015451239,0.00019739695,0.00016779895,0.0004638944,0.00089669076,0.0000353358],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003177426,0.00043068532,0.9604929,0.00016668643,0.0000043830887,0.000054551325,0.00009864021,0.000006595383,0.03242457,0.00043182957,0.0021364538,0.0037209487],"study_design_scores_gemma":[0.0009383389,0.000042697786,0.9610352,0.0003918905,0.000019362842,0.00022899182,0.00030242346,0.0025280402,0.0024585575,0.0036024977,0.028258553,0.00019342519],"about_ca_topic_score_codex":0.00005988241,"about_ca_topic_score_gemma":0.000015440135,"teacher_disagreement_score":0.07192545,"about_ca_system_score_codex":0.000045495683,"about_ca_system_score_gemma":0.00018106413,"threshold_uncertainty_score":0.70279145},"labels":[],"label_agreement":null},{"id":"W3191793176","doi":"10.1155/2021/2120130","title":"Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination","year":2021,"lang":"en","type":"article","venue":"Contrast Media & Molecular Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; Corpus callosum; Magnetic resonance imaging; Psychology; Frontal lobe; Internal medicine; Medicine; Audiology; Cardiology; Cognition; Psychiatry; Neuroscience; Cognitive impairment; Radiology","score_opus":0.007086150495768873,"score_gpt":0.25996472607507454,"score_spread":0.25287857557930565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191793176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9798775,0.00082957046,0.016231697,0.0018638488,0.000012988125,0.001070577,0.000019686437,0.000029776622,0.000064361855],"genre_scores_gemma":[0.9781602,0.00007905037,0.02068448,0.0006975934,0.000004405773,0.00025745833,0.00007208762,0.000041994146,0.0000027536482],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99835396,0.00011282793,0.00042745116,0.00044236856,0.0003468613,0.0003165132],"domain_scores_gemma":[0.9988321,0.00015678153,0.00020003128,0.0002615897,0.00048022324,0.00006926068],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010228839,0.00021014956,0.0004150256,0.00026231358,0.000025704347,0.000010896326,0.00008863035,0.000022257456,0.000014366576],"category_scores_gemma":[0.00014979018,0.0001843708,0.000048205486,0.0006992842,0.00019382026,0.00011955191,0.000048934824,0.00024549788,6.0392597e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004842376,0.0007484894,0.9832695,0.000059576436,0.0000068374557,0.00019300336,0.00038553379,0.000031352814,0.008376226,0.00013005295,0.000010452733,0.0063047446],"study_design_scores_gemma":[0.0049400944,0.00048644393,0.9755365,0.00097077707,0.000073472154,0.000018061311,0.00021480222,0.0033041872,0.0140587,0.00022124381,0.000015825784,0.00015985593],"about_ca_topic_score_codex":0.00002685759,"about_ca_topic_score_gemma":0.000016758717,"teacher_disagreement_score":0.0077329567,"about_ca_system_score_codex":0.00007235062,"about_ca_system_score_gemma":0.00008206927,"threshold_uncertainty_score":0.7518423},"labels":[],"label_agreement":null},{"id":"W3192358327","doi":"10.1002/hipo.23382","title":"The structure of hippocampal circuitry relates to rapid category learning in humans","year":2021,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Ontario Research Foundation; Fondation Brain Canada","keywords":"Psychology; Categorization; White matter; Entorhinal cortex; Hippocampal formation; Neuroscience; Cognitive psychology; Cognitive science; Artificial intelligence; Computer science","score_opus":0.03010554406010817,"score_gpt":0.31270841839144264,"score_spread":0.28260287433133446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3192358327","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99215424,0.001119562,0.0012649127,0.0029073372,0.000080865284,0.00031479515,0.0000048066604,0.00013132655,0.0020221581],"genre_scores_gemma":[0.99644905,0.00021198597,0.0021796494,0.00051256764,0.0000511366,0.000014914321,0.00001884853,0.000025515172,0.0005363333],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99904037,0.000054978587,0.0002651278,0.00026599245,0.00014907839,0.00022445957],"domain_scores_gemma":[0.9991716,0.00014874354,0.00007585081,0.0004297837,0.00009645175,0.00007755127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010331675,0.00011290182,0.0002019132,0.00006732053,0.00013141062,0.000012547978,0.00011623127,0.000068552254,0.000061620034],"category_scores_gemma":[0.00023463897,0.00009007574,0.00006152242,0.0004021992,0.00007791646,0.00003198045,0.0000675622,0.00046999546,0.000008693343],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001028088,0.00018388644,0.09960072,0.00014481663,0.000046238863,0.00017591618,0.0015538211,0.00056809996,0.6942443,0.016011652,0.0026396827,0.18472806],"study_design_scores_gemma":[0.0027089445,0.0006866972,0.30041233,0.0006361004,0.00016502524,0.0005438901,0.0029631248,0.00040712213,0.29633176,0.24589242,0.14842671,0.0008258844],"about_ca_topic_score_codex":0.000009650039,"about_ca_topic_score_gemma":0.00001852257,"teacher_disagreement_score":0.39791256,"about_ca_system_score_codex":0.00004415812,"about_ca_system_score_gemma":0.000103750564,"threshold_uncertainty_score":0.3673182},"labels":[],"label_agreement":null},{"id":"W3193894044","doi":"10.1093/biostatistics/kxab031","title":"Estimation for the bivariate quantile varying coefficient model with application to diffusion tensor imaging data analysis","year":2021,"lang":"en","type":"article","venue":"Biostatistics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; National Cancer Institute; National Institute of Mental Health; Canadian Statistical Sciences Institute; Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Interpretability; Bivariate analysis; Computer science; Quantile; Diffusion MRI; Quantile regression; Data set; Artificial intelligence; Mathematics; Econometrics; Machine learning","score_opus":0.085489773200644,"score_gpt":0.39188917805165296,"score_spread":0.30639940485100897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3193894044","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008085672,0.000040208175,0.9928052,0.004689255,0.000012742515,0.00076100026,0.00075020245,0.00010322932,0.000029627283],"genre_scores_gemma":[0.3963839,0.00002148457,0.6015606,0.00063107774,0.000017729335,0.00010387351,0.0011974439,0.000016650194,0.00006724321],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910575,0.000008887756,0.00018582003,0.0003923817,0.00016510709,0.00014203842],"domain_scores_gemma":[0.9984291,0.00021727713,0.00008860653,0.0009872254,0.00021504847,0.000062704494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001097967,0.00009942883,0.00015080083,0.000073880045,0.0002167416,0.000039419963,0.00014956208,0.000016209875,0.0000032500136],"category_scores_gemma":[0.00020519485,0.000070233946,0.000027729606,0.00062895456,0.000032867938,0.000039786362,0.00011524972,0.000064418084,0.0000031829707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002938858,0.00063363183,0.0067086266,0.00018702015,0.0003054106,0.000020459911,0.00032506388,0.6636387,0.035328105,0.048925314,0.008062713,0.23557104],"study_design_scores_gemma":[0.00023769758,0.000022425003,0.0029053264,0.000021188955,0.0008672673,0.000011660654,0.000029390076,0.9909968,0.00082614477,0.00057243276,0.003419153,0.00009053501],"about_ca_topic_score_codex":0.000022776541,"about_ca_topic_score_gemma":0.000008418841,"teacher_disagreement_score":0.39557534,"about_ca_system_score_codex":0.000031558728,"about_ca_system_score_gemma":0.00006330606,"threshold_uncertainty_score":0.2864057},"labels":[],"label_agreement":null},{"id":"W3194483091","doi":"10.1007/s13365-021-01000-z","title":"Long-term sequelae of herpes simplex virus encephalitis–related white matter injury: correlation of neuropsychological outcome and diffusion tensor imaging","year":2021,"lang":"en","type":"article","venue":"Journal of NeuroVirology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Inferior longitudinal fasciculus; Fornix; Fractional anisotropy; Uncinate fasciculus; White matter; Corpus callosum; Diffusion MRI; Fasciculus; Cingulum (brain); Medicine; Psychology; Splenium; Neuropsychology; Neuroscience; Audiology; Magnetic resonance imaging; Radiology; Hippocampus; Cognition","score_opus":0.04289657789806872,"score_gpt":0.3650554783402334,"score_spread":0.32215890044216466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194483091","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9893404,0.00014962284,0.0053434847,0.0047686677,0.000119617835,0.0001294895,0.000013383558,0.000019652121,0.000115628136],"genre_scores_gemma":[0.9956762,0.0003236076,0.0015949238,0.0022157202,0.000037612,0.0000019875483,0.000005793007,0.000022065771,0.00012206783],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984694,0.00014350317,0.00083862065,0.00022246571,0.00016641381,0.00015959868],"domain_scores_gemma":[0.99861413,0.00012493604,0.0007020158,0.00024903848,0.0002189385,0.00009091776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012280775,0.00013570646,0.00048091033,0.00015806872,0.00003611771,0.0000065298523,0.000097435644,0.00008282055,0.00015963143],"category_scores_gemma":[0.0001465477,0.000111487905,0.00012348575,0.0001831599,0.00023475043,0.00010139173,0.00009043171,0.0003916687,0.0000024692083],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023865925,0.00020481781,0.75294256,0.00003426593,0.000010044891,0.00037574922,0.000032615608,0.000010765129,0.23842019,0.0000642859,0.0001284626,0.007537592],"study_design_scores_gemma":[0.0008660348,0.00047766222,0.990815,0.000041987845,0.000108118285,0.0045650788,0.000012084627,0.00027825232,0.0017701916,0.00040930035,0.00058513234,0.00007117069],"about_ca_topic_score_codex":0.0000021694786,"about_ca_topic_score_gemma":4.6959056e-7,"teacher_disagreement_score":0.23787244,"about_ca_system_score_codex":0.000012276885,"about_ca_system_score_gemma":0.000025797875,"threshold_uncertainty_score":0.45463446},"labels":[],"label_agreement":null},{"id":"W3194760139","doi":"10.1038/s41597-021-00941-8","title":"Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers","year":2021,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Centre Hospitalier Universitaire de Sherbrooke; International Collaboration On Repair Discoveries; University of British Columbia; Université de Montréal; Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute","funders":"National Institute of Neurological Disorders and Stroke; Staatssekretariat für Bildung, Forschung und Innovation; Economic and Social Research Council; Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; CRIS Cancer Foundation; Regione Puglia; University College London Hospitals NHS Foundation Trust; Ministero dell’Istruzione, dell’Università e della Ricerca; Ministero della Salute; Concordia University; Agentura Pro Zdravotnický Výzkum České Republiky; National Institutes of Health; Rosetrees Trust; European Commission; Multiple Sclerosis Society; Bundesministerium für Bildung und Forschung; National Imaging Facility; National Institute for Health and Care Research; University of Pennsylvania; SpinalCure Australia; University of Minnesota; National Science Foundation; Compute Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Polytechnique Montréal; Wellcome Trust; Institut de Valorisation des Données; AstraZeneca; Craig H. Neilsen Foundation; McGill University; Canada First Research Excellence Fund; Max-Planck-Gesellschaft","keywords":"Protocol (science); Reproducibility; Computer science; Spinal cord; Documentation; Data mining; Medicine; Statistics; Mathematics; Pathology","score_opus":0.6245720496163727,"score_gpt":0.5767339061992035,"score_spread":0.04783814341716919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194760139","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97710985,0.00088953576,0.00205192,0.009303352,0.0002566038,0.0007403863,0.009503441,0.000037135735,0.00010778686],"genre_scores_gemma":[0.9789385,0.000099192366,0.01814502,0.0002599098,0.00001516891,0.000009316887,0.0017568694,0.000009039199,0.00076698064],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9976369,0.000044819986,0.00019837862,0.0017907402,0.00016344877,0.00016570064],"domain_scores_gemma":[0.98995715,0.000044924953,0.00011040975,0.0097200265,0.00009863014,0.00006886664],"candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0017389944,0.000074910815,0.00016230528,0.000013965857,0.00027861982,0.00038245367,0.0020976078,0.00001643681,0.000017623679],"category_scores_gemma":[0.0016168478,0.000051979492,0.000009079192,0.00034067745,0.00087198993,0.00073388603,0.014951757,0.00011193956,0.0000011823142],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00120456,0.001297933,0.23418726,0.0011080113,0.00015555492,0.00006166913,0.0009659761,0.0000049692617,0.22136533,0.0059276978,0.41619608,0.11752496],"study_design_scores_gemma":[0.000780884,0.00017075146,0.5823219,0.00032497212,0.00019970427,0.00010520746,0.0009842508,0.0027938688,0.1386297,0.008398251,0.2650311,0.00025944266],"about_ca_topic_score_codex":0.000051584786,"about_ca_topic_score_gemma":0.00013941227,"teacher_disagreement_score":0.3481346,"about_ca_system_score_codex":0.000006068723,"about_ca_system_score_gemma":0.00010308314,"threshold_uncertainty_score":0.9930151},"labels":[{"model":"gemma","categories":["metaresearch","open_science"],"domain":"reproducibility","study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high"},{"model":"gpt","categories":["metaresearch","open_science"],"domain":"reproducibility","study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W3194855278","doi":"10.7554/elife.70119","title":"The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging","year":2021,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":96,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Sick Kids Foundation; Canadian Institutes of Health Research; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Helmholtz Association; Natural Sciences and Engineering Research Council of Canada","keywords":"Toolbox; Neuroimaging; Workflow; Computer science; Data science; Artificial intelligence; Human–computer interaction; Neuroscience; Psychology; Database","score_opus":0.06421679196745048,"score_gpt":0.3615662247518344,"score_spread":0.29734943278438397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194855278","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.106019795,0.0004789123,0.85274714,0.03703027,0.00013197685,0.0009538366,0.000030563475,0.00025533309,0.0023521583],"genre_scores_gemma":[0.7706884,0.00008702641,0.2251333,0.0025887543,0.00011100178,0.00019316174,0.00005460275,0.000036070924,0.0011076928],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993384,0.00002256654,0.0001836969,0.00020181306,0.0001126085,0.00014092377],"domain_scores_gemma":[0.99907035,0.00024770474,0.00008847311,0.000344804,0.0002096827,0.000039000064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010153605,0.00008350383,0.00014918936,0.00003373228,0.00012063943,0.000009125033,0.00007113763,0.0000250653,0.000005179726],"category_scores_gemma":[0.0003463956,0.000055412118,0.00005054272,0.00015725904,0.00012272722,0.00003705148,0.00002154798,0.00012359483,0.0000013420314],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051269826,0.0003619492,0.004826786,0.00011752629,0.0000643345,0.000052147912,0.00050673634,0.00009285855,0.64295644,0.045411814,0.014329689,0.290767],"study_design_scores_gemma":[0.0022647302,0.0005511353,0.013841139,0.0001411333,0.00013181077,0.0004036869,0.00035330968,0.021782722,0.3284839,0.0015380323,0.6302456,0.0002627384],"about_ca_topic_score_codex":0.0000087972485,"about_ca_topic_score_gemma":0.00001286596,"teacher_disagreement_score":0.6646686,"about_ca_system_score_codex":0.000022225191,"about_ca_system_score_gemma":0.000096727425,"threshold_uncertainty_score":0.22596405},"labels":[],"label_agreement":null},{"id":"W3194917267","doi":"10.1002/ana.26201","title":"Interaction between Preterm White Matter Injury and Childhood Thalamic Growth","year":2021,"lang":"en","type":"article","venue":"Annals of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; SickKids Foundation; Hospital for Sick Children; BC Children's Hospital; University of Toronto","funders":"Canadian Institutes of Health Research; Kids Brain Health Network","keywords":"Gestational age; White matter; Medicine; Fractional anisotropy; Brain size; Thalamus; Magnetic resonance imaging; Diffusion MRI; Pediatrics; Cohort; Psychology; Internal medicine; Radiology","score_opus":0.06890977092527792,"score_gpt":0.37642765328013633,"score_spread":0.30751788235485844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3194917267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9540456,0.000045223995,0.00029172396,0.0440783,0.000025888941,0.00011453772,0.0000147753335,0.000045163935,0.0013387662],"genre_scores_gemma":[0.98792684,0.00023840401,0.0004934388,0.011150667,0.00006240763,0.00001152078,0.000019650874,0.0000150147225,0.00008207324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999415,0.000033919245,0.00016115932,0.00022287671,0.000049539616,0.000117542775],"domain_scores_gemma":[0.99953467,0.000049381502,0.00007462033,0.00021674324,0.00008169668,0.000042873704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003238964,0.00007552444,0.00018008109,0.000060159575,0.000023563856,0.000004248741,0.00004208138,0.000049968705,0.000042866995],"category_scores_gemma":[0.000030431635,0.00007364758,0.000041796076,0.00008411087,0.000059222253,0.00005806402,0.00006980302,0.00019673756,0.0000075660055],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005858921,0.00009718755,0.980445,0.000044286957,0.000023068806,0.00002887247,0.0000613194,3.4501335e-7,0.010849988,0.00026999175,0.00462704,0.0034942643],"study_design_scores_gemma":[0.00013296987,0.00030046768,0.96409446,0.00001576088,0.000023948833,0.0002587008,0.0000026664206,0.000008860674,0.027300764,0.0038858105,0.003924279,0.000051292896],"about_ca_topic_score_codex":0.000002226844,"about_ca_topic_score_gemma":2.9267724e-7,"teacher_disagreement_score":0.033881206,"about_ca_system_score_codex":0.000001022998,"about_ca_system_score_gemma":0.000011673524,"threshold_uncertainty_score":0.3003261},"labels":[],"label_agreement":null},{"id":"W3196049305","doi":"10.1101/2021.08.18.456666","title":"Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Université de Montréal; Heart and Stroke Foundation; York University; Montreal Heart Institute; Toronto Western Hospital; University Health Network; Ottawa Hospital; Thunder Bay Regional Research Institute; University of Ottawa; Toronto Rehabilitation Institute; Sunnybrook Health Science Centre; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Western University; University of Toronto","funders":"Faculty of Health Sciences, Queen's University; Canadian Institutes of Health Research; London Health Sciences Foundation; Temerty Family Foundation; Health Sciences Centre Foundation; University of Ottawa; Ontario Brain Institute; Government of Ontario; Queen's University; Centre for Addiction and Mental Health Foundation; McMaster University","keywords":"Segmentation; Artificial intelligence; Computer science; Robustness (evolution); Pattern recognition (psychology); Convolutional neural network; Neuroimaging; Bayesian probability; Hyperintensity; Deep learning; Hausdorff distance; Pipeline (software); Machine learning; Magnetic resonance imaging; Medicine","score_opus":0.019726898143484255,"score_gpt":0.2693101865244165,"score_spread":0.24958328838093227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196049305","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2238011,0.00023335112,0.77362716,0.00073029916,0.00017888892,0.0012158897,0.00006231363,0.00014645052,0.000004567179],"genre_scores_gemma":[0.7310859,0.000101953716,0.26813293,0.00026963156,0.000109485605,0.0002423537,0.000004323688,0.00004837998,0.0000050581284],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99855345,0.000036482557,0.00040499706,0.00062642025,0.00015812999,0.0002205216],"domain_scores_gemma":[0.9982271,0.000054998356,0.0003597117,0.0006889164,0.00055400754,0.00011526276],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001829316,0.0002658057,0.00045531333,0.00009532086,0.00013955288,0.000041744355,0.000105125066,0.00022028094,0.000013638277],"category_scores_gemma":[0.000098235265,0.00029582324,0.00010382109,0.00018749863,0.000103749815,0.00008846663,0.00019972266,0.0003171464,5.425704e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015963676,0.00073714496,0.17322545,0.0072878613,0.0005240877,0.00006943152,0.00015959518,0.028099718,0.78427595,0.0018545485,0.0020838417,0.00008601833],"study_design_scores_gemma":[0.0026624054,0.00014769757,0.45726693,0.0020193807,0.0009584887,2.9857964e-7,0.000030711464,0.40569645,0.12888785,0.000058027905,0.001133386,0.0011383824],"about_ca_topic_score_codex":0.000011277753,"about_ca_topic_score_gemma":0.0000038048797,"teacher_disagreement_score":0.6553881,"about_ca_system_score_codex":0.00013161663,"about_ca_system_score_gemma":0.00012666809,"threshold_uncertainty_score":0.9999494},"labels":[],"label_agreement":null},{"id":"W3196211813","doi":"10.1101/2020.10.07.321083","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Calgary; Université de Sherbrooke","funders":"National Institutes of Health; Ministry of Science and Technology, Taiwan; University of Melbourne; Consejo Nacional de Ciencia y Tecnología; Agence Nationale de la Recherche; State Government of Victoria; European Commission; Children's Hospital Foundation; Royal Children's Hospital Foundation; Murdoch Children's Research Institute; Medical Research Council; Children’s Hospital of Wisconsin Research Institute; Agencia Nacional de Investigación y Desarrollo; Vanderbilt University","keywords":"Tractography; Segmentation; White matter; Diffusion MRI; Bundle; Computer science; Artificial intelligence; Pattern recognition (psychology); Medicine; Magnetic resonance imaging; Radiology","score_opus":0.042360413678278766,"score_gpt":0.2801282551985172,"score_spread":0.23776784152023844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196211813","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80262905,0.00068768405,0.06487414,0.11183415,0.0019204834,0.0085286405,0.0060932147,0.00330446,0.00012817458],"genre_scores_gemma":[0.98336035,0.00044959117,0.008540671,0.0059364024,0.000568025,0.0008860891,0.00003842954,0.00021344273,0.000006989145],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99654526,0.00020463401,0.00063361664,0.00160202,0.0004908252,0.000523622],"domain_scores_gemma":[0.9957685,0.00025915942,0.00042871878,0.0029743086,0.00022568124,0.00034362508],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005527731,0.0007147304,0.0007024065,0.00022309895,0.00031251163,0.0004989392,0.0006744442,0.00037182294,0.00024344512],"category_scores_gemma":[0.00023175294,0.0005791078,0.0003003737,0.00057644595,0.0002552409,0.0003420186,0.0004932634,0.0018551574,0.00014496283],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081621716,0.002929874,0.17345214,0.0028323508,0.0010161899,0.0002900395,0.00019290406,0.00005134977,0.7093476,0.018618753,0.09039652,0.000056029636],"study_design_scores_gemma":[0.0011412624,0.0004850822,0.7586727,0.0033293283,0.0013252355,0.0000010319441,0.000053432374,0.0007749886,0.09802251,0.0011644096,0.13249837,0.002531639],"about_ca_topic_score_codex":0.000023425233,"about_ca_topic_score_gemma":0.000002111719,"teacher_disagreement_score":0.61132514,"about_ca_system_score_codex":0.00017403132,"about_ca_system_score_gemma":0.0001487859,"threshold_uncertainty_score":0.99966604},"labels":[],"label_agreement":null},{"id":"W3196689162","doi":"10.1002/hbm.25625","title":"A <scp>meta‐analysis</scp> of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the <scp>ENIGMA Consortium</scp>","year":2021,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Instituto de Salud Carlos III; Medical Research Council; National Institutes of Health; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; National Health and Medical Research Council; Norges Forskningsråd; Fundação Amazônia Paraense de Amparo à Pesquisa; National Center for Advancing Translational Sciences; Commonwealth Health Research Board; Wellcome Trust; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Department of Energy, Labor and Economic Growth; Center for Integrated Healthcare, U.S. Department of Veterans Affairs; U.S. Department of Veterans Affairs; Eunice Kennedy Shriver National Institute of Child Health and Human Development; U.S. Department of Energy; Science Foundation Ireland; National Science Foundation","keywords":"Putamen; Thalamus; Neuroscience; Psychology; Schizophrenia (object-oriented programming); Amygdala; Ventral striatum; Hippocampus; Striatum; Caudate nucleus; Nucleus accumbens; Psychosis; Psychiatry; Central nervous system; Dopamine","score_opus":0.09715958766816828,"score_gpt":0.36313971700197795,"score_spread":0.26598012933380966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196689162","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01979005,0.96994543,0.005488489,0.0006661671,0.000021600512,0.003225605,0.0002011944,0.00025674477,0.0004047077],"genre_scores_gemma":[0.12836826,0.76704353,0.08023332,0.009937224,0.0007832602,0.0043106014,0.0047787516,0.001139035,0.0034059917],"study_design_codex":"meta_analysis","study_design_gemma":"not_applicable","domain_scores_codex":[0.99516,0.00070250075,0.0015018506,0.0011565984,0.0006922905,0.000786764],"domain_scores_gemma":[0.9937814,0.0032227074,0.0013204298,0.001204087,0.00020807509,0.000263339],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010381966,0.0009305791,0.0046051717,0.0012283493,0.0004744428,0.00013881375,0.0005697652,0.00026463353,0.00002952143],"category_scores_gemma":[0.00039878237,0.0006243408,0.00076514645,0.0026933409,0.0008102612,0.0001678456,0.00029402057,0.0014852858,0.0000018181839],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020736718,0.0021186231,0.061507016,0.20649171,0.38341433,0.0021426207,0.051221594,0.0016829413,0.0006415171,0.07299868,0.028791562,0.18878204],"study_design_scores_gemma":[0.005583587,0.0010814748,0.028828526,0.01511651,0.11883609,0.0024989152,0.010982633,0.0026808283,0.000019479407,0.0018406265,0.81155574,0.0009755599],"about_ca_topic_score_codex":0.00014097938,"about_ca_topic_score_gemma":0.00045630647,"teacher_disagreement_score":0.7827642,"about_ca_system_score_codex":0.00012018021,"about_ca_system_score_gemma":0.0003177162,"threshold_uncertainty_score":0.9996208},"labels":[],"label_agreement":null},{"id":"W3197146939","doi":"10.3389/fnins.2021.716538","title":"Tractography in Curvilinear Coordinates","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Canadian Open Neuroscience Platform; Natural Sciences and Engineering Research Council of Canada; NIH Blueprint for Neuroscience Research; Canada Research Chairs","keywords":"Curvilinear coordinates; Bipolar coordinates; Orthogonal coordinates; Log-polar coordinates; Cartesian coordinate system; Parabolic coordinates; Context (archaeology); Action-angle coordinates; Spherical coordinate system; Coordinate system; Tractography; Cartesian tensor; Parallel coordinates; Computer science; Generalized coordinates; Spatial reference system; Polar coordinate system; Visualization; Artificial intelligence; Mathematics; Geometry; Mathematical analysis; Diffusion MRI; Data visualization; Geology; Tensor field","score_opus":0.0487326283880001,"score_gpt":0.3453726620877228,"score_spread":0.29664003369972275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3197146939","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81728727,0.0011051823,0.16256084,0.010797587,0.0010843307,0.0007238317,0.000015327187,0.0003156682,0.0061099823],"genre_scores_gemma":[0.94613916,0.0003143527,0.05143179,0.0017912659,0.000014799346,0.000031754407,0.0000029647028,0.000010971963,0.00026295776],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99915004,0.000020028037,0.0001513233,0.00035851428,0.000120566714,0.00019954385],"domain_scores_gemma":[0.9996141,0.000016908703,0.000026839627,0.00026032646,0.000025819869,0.000055958564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079273705,0.00007273585,0.00014192337,0.00018838677,0.000031641168,0.000013311386,0.00011614249,0.000025713316,0.000003671094],"category_scores_gemma":[0.00016397868,0.0000737409,0.000036057132,0.0014154346,0.00013698278,0.00009724076,0.000040305582,0.00022311996,8.568521e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014171689,0.00027991566,0.9445216,0.000018336263,3.7071032e-7,0.0003328658,0.000040262483,0.000052389565,0.04346838,0.0007197643,0.0031384344,0.007413487],"study_design_scores_gemma":[0.00087716186,0.00010088631,0.8232634,0.0001060684,0.0000074012587,0.00012965902,0.00012244568,0.013455689,0.03192827,0.006034248,0.12374296,0.00023179896],"about_ca_topic_score_codex":0.000004137768,"about_ca_topic_score_gemma":0.0000024191345,"teacher_disagreement_score":0.12885189,"about_ca_system_score_codex":0.00002146763,"about_ca_system_score_gemma":0.000048197326,"threshold_uncertainty_score":0.30070665},"labels":[],"label_agreement":null},{"id":"W3199529899","doi":"10.1002/jnr.24956","title":"Decline in executive function in patients with white matter hyperintensities from the static and dynamic perspectives of amplitude of low‐frequency fluctuations","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Hyperintensity; Psychology; Cardiology; Neuropsychology; Internal medicine; Montreal Cognitive Assessment; Audiology; Thalamus; Executive dysfunction; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Cognitive impairment; Radiology","score_opus":0.06153936429534189,"score_gpt":0.3895119271631789,"score_spread":0.327972562867837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199529899","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926799,0.000075729375,0.0028377776,0.0041810274,0.000012118773,0.00016191594,0.00001130079,0.0000015550357,0.000038688304],"genre_scores_gemma":[0.99732774,0.00015740958,0.0023258154,0.00014979573,0.000004975984,0.0000042879474,0.000001051984,0.0000052141477,0.000023693003],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989701,0.00009727151,0.00025592488,0.00013561966,0.00042661442,0.00011447422],"domain_scores_gemma":[0.99873036,0.00023957633,0.00011640639,0.00015346853,0.00072659616,0.000033599637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002980834,0.000046528898,0.00015053248,0.0001905166,0.00003863812,0.0000125150655,0.00009244347,0.00001223824,0.0000067542296],"category_scores_gemma":[0.00044185814,0.000029955192,0.000019055598,0.0006250511,0.00041244627,0.00013347277,0.000060878876,0.0003125169,1.3858742e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022802317,0.00039302922,0.8692672,0.000027946382,0.0000034406935,0.000022600034,0.001608884,0.000080355516,0.12775458,0.00018036555,0.000024546187,0.00040902407],"study_design_scores_gemma":[0.0004460852,0.0003785637,0.99274,0.0001892027,0.0000056016293,0.000019112378,0.0026690895,0.00034589358,0.00059345085,0.0025832811,0.000006780864,0.000022964467],"about_ca_topic_score_codex":0.000031954558,"about_ca_topic_score_gemma":0.000024390638,"teacher_disagreement_score":0.12716113,"about_ca_system_score_codex":0.000048571794,"about_ca_system_score_gemma":0.00014651236,"threshold_uncertainty_score":0.15196756},"labels":[],"label_agreement":null},{"id":"W3199608123","doi":"10.1007/s00406-021-01333-0","title":"Disruptions in white matter microstructure associated with impaired visual associative memory in schizophrenia-spectrum illness","year":2021,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Douglas Mental Health University Institute; Douglas College","funders":"National Health and Medical Research Council; Brain and Behavior Research Foundation","keywords":"Schizophrenia (object-oriented programming); White matter; Neuroscience; Psychology; Schizophrenia spectrum; Cognitive psychology; Psychiatry; Audiology; Medicine; Psychosis; Magnetic resonance imaging","score_opus":0.026608320910158332,"score_gpt":0.34983101417011303,"score_spread":0.3232226932599547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199608123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99076974,0.000050739713,0.0010318144,0.005544527,0.00013598567,0.0002308735,0.000036025835,0.000046301615,0.0021539698],"genre_scores_gemma":[0.9925557,0.00014398388,0.005289438,0.0016048085,0.000045524775,0.0000049579,0.00001246225,0.000024465788,0.0003186561],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998051,0.0003943975,0.00056172116,0.000588542,0.00014782154,0.0002565075],"domain_scores_gemma":[0.99911994,0.0002347757,0.0002246709,0.00027708465,0.000020097104,0.00012344816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026733798,0.00015534372,0.00032469022,0.00010883586,0.00010140793,0.00002229311,0.00015899645,0.0000316294,0.000011922812],"category_scores_gemma":[0.0003005757,0.00013128688,0.00009016241,0.0005724164,0.0006320434,0.00008603377,0.00014665605,0.00058708305,0.0000018868421],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018197432,0.00074450363,0.9949897,0.000021801454,0.0000048749444,0.00007573608,0.0001574168,0.000015230858,0.0023893781,0.00027367342,0.00004330778,0.0011023984],"study_design_scores_gemma":[0.0015348186,0.0003054286,0.99568415,0.00028816814,0.00001963835,0.000048320147,0.000107630076,0.0004048945,0.000101974336,0.0013015474,0.000059772345,0.00014368958],"about_ca_topic_score_codex":0.0000022735633,"about_ca_topic_score_gemma":0.000068962014,"teacher_disagreement_score":0.004257624,"about_ca_system_score_codex":0.000008846666,"about_ca_system_score_gemma":0.00011035337,"threshold_uncertainty_score":0.5353724},"labels":[],"label_agreement":null},{"id":"W3199893527","doi":"10.1101/2021.09.17.460781","title":"Mapping pontocerebellar connectivity with diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Cerebellum; Pons; Neuroscience; Diffusion MRI; Tractography; Context (archaeology); Anatomy; Biology; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.029267526832652456,"score_gpt":0.2656240162776656,"score_spread":0.2363564894450131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199893527","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87700874,0.0005304895,0.11829358,0.0013964066,0.00016947972,0.0013728944,0.00005059639,0.0011284935,0.000049295675],"genre_scores_gemma":[0.913059,0.00044532734,0.08514324,0.0005749634,0.00026130653,0.00034460536,0.000001075509,0.00015884297,0.000011660609],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99745643,0.00006554123,0.00038088835,0.001236283,0.00039655773,0.0004643177],"domain_scores_gemma":[0.99685735,0.00006406612,0.00033443162,0.0018789448,0.00056234386,0.0003028456],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022836188,0.00052794133,0.0007191472,0.00021038085,0.00020602472,0.00012578616,0.0002720848,0.00034952018,0.00004269704],"category_scores_gemma":[0.000117634816,0.00050160935,0.00016017526,0.00057303143,0.00013355231,0.00009864691,0.0005336082,0.0011140455,0.000012137164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006560112,0.00047894364,0.036182955,0.00076715654,0.00014811198,0.00040715316,0.000017680777,0.000029172905,0.9611181,0.00044968203,0.00032574072,0.000009685916],"study_design_scores_gemma":[0.0018486646,0.00022959287,0.41624716,0.0037412017,0.00039933596,0.000001043365,0.000027680222,0.0021377853,0.54880154,0.000011038284,0.024846429,0.0017085059],"about_ca_topic_score_codex":0.00004447831,"about_ca_topic_score_gemma":0.0000018493852,"teacher_disagreement_score":0.41231656,"about_ca_system_score_codex":0.00027764903,"about_ca_system_score_gemma":0.00054720475,"threshold_uncertainty_score":0.9997436},"labels":[],"label_agreement":null},{"id":"W3200681050","doi":"10.1002/hbm.25661","title":"A method to remove the influence of fixative concentration on postmortem <scp> T <sub>2</sub> </scp> maps using a kinetic tensor model","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIHR Oxford Biomedical Research Centre; Wellcome; Medical Research Council; National Institute for Health and Care Research; Alzheimer Society; Wellcome Trust","keywords":"Fixative; Diffusion MRI; White matter; Chemistry; Brain tissue; Anatomy; Biology; Magnetic resonance imaging; Biochemistry; Medicine","score_opus":0.09044121792273278,"score_gpt":0.36699808206781487,"score_spread":0.27655686414508207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3200681050","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7186919,0.000021263764,0.27810988,0.0019661027,0.0000059726617,0.0005761379,0.000013651735,0.00007720885,0.0005379258],"genre_scores_gemma":[0.8705284,0.0000065825066,0.122468844,0.006697421,0.000053671727,0.000054464457,0.000019688321,0.000030594758,0.00014032346],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99867916,0.000109418645,0.00034061202,0.00039215956,0.00023868021,0.00023995202],"domain_scores_gemma":[0.99853504,0.00041161204,0.00019477878,0.000486953,0.00028608687,0.00008555916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026430248,0.00016174863,0.00025590888,0.000074778545,0.0002105908,0.000022801543,0.00012345311,0.000051572297,0.0000014445393],"category_scores_gemma":[0.0005353407,0.00013930172,0.00008013661,0.00043224677,0.000076478216,0.00006370609,0.0000812787,0.00025280143,0.0000037121852],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000049532446,0.000047600694,0.00013250322,0.000042394873,0.00001476718,0.000014165073,0.0010464235,0.02464123,0.9647224,0.0080658775,0.00067255634,0.00059516326],"study_design_scores_gemma":[0.0009539595,0.00024382958,0.050518695,0.0014068068,0.00011963006,0.0001813922,0.0010462985,0.10716128,0.8112998,0.022722814,0.004132845,0.0002126338],"about_ca_topic_score_codex":0.000007750913,"about_ca_topic_score_gemma":0.0000016360253,"teacher_disagreement_score":0.15564103,"about_ca_system_score_codex":0.00008016668,"about_ca_system_score_gemma":0.000084687534,"threshold_uncertainty_score":0.5680559},"labels":[],"label_agreement":null},{"id":"W3202356255","doi":"10.1016/j.nicl.2021.102843","title":"White matter alterations and cognitive outcomes in children born very low birth weight","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; Holland Bloorview Kids Rehabilitation Hospital; Hospital for Sick Children; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Low birth weight; Birth weight; Psychology; Cognition; Pediatrics; Developmental psychology; Medicine; Neuroscience; Biology; Magnetic resonance imaging; Pregnancy; Genetics","score_opus":0.051137502502351204,"score_gpt":0.3935662870963747,"score_spread":0.3424287845940235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202356255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98379636,0.0000768387,0.0023222102,0.011834822,0.00007118636,0.00043572354,0.000071836956,0.00012050944,0.0012705065],"genre_scores_gemma":[0.9780794,0.00027264297,0.005464388,0.014336489,0.00013279877,0.00005378431,0.0000813484,0.00003972317,0.0015394465],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985101,0.00010109464,0.0004805182,0.0005791017,0.00012339461,0.00020576266],"domain_scores_gemma":[0.99894387,0.00035882532,0.00007415468,0.00039685352,0.000089949426,0.0001363799],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116194904,0.00015501125,0.0003646419,0.00007338921,0.00006523224,0.000036797745,0.000063002706,0.000071999944,0.000165166],"category_scores_gemma":[0.00035836935,0.0001423111,0.000111464025,0.00019823751,0.00017669721,0.000113347305,0.00012588025,0.00054158986,0.00007875967],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025801086,0.00041808604,0.99602634,0.000010781823,0.000015110289,0.00013227026,0.0000125346705,3.1363166e-7,0.00016855713,0.00005760185,0.0014642605,0.0016683416],"study_design_scores_gemma":[0.0012892229,0.00008503194,0.9961353,0.000057921967,0.000055939927,0.00023246375,0.0000062028726,0.000107650114,0.00033327748,0.00029994655,0.0012752159,0.00012185425],"about_ca_topic_score_codex":0.0000022793895,"about_ca_topic_score_gemma":0.000003314157,"teacher_disagreement_score":0.005716988,"about_ca_system_score_codex":0.000008295639,"about_ca_system_score_gemma":0.00006170622,"threshold_uncertainty_score":0.5803278},"labels":[],"label_agreement":null},{"id":"W3202656322","doi":"10.3174/ajnr.a7295","title":"Filtered Diffusion-Weighted MRI of the Human Cervical Spinal Cord: Feasibility and Application to Traumatic Spinal Cord Injury","year":2021,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Neurotrauma Foundation","funders":"Rehabilitation Research and Development Service; Bryon Riesch Paralysis Foundation; Medical College of Wisconsin; Craig H. Neilsen Foundation; U.S. Department of Veterans Affairs","keywords":"Medicine; Spinal cord; Spinal cord injury; Diffusion MRI; Magnetic resonance imaging; Anesthesia; Radiology","score_opus":0.062088821371703184,"score_gpt":0.3950407478468111,"score_spread":0.3329519264751079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202656322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97462004,0.00006375187,0.017969904,0.006917465,0.000050794722,0.00031204554,0.00001000733,0.000018255389,0.00003770193],"genre_scores_gemma":[0.9877493,0.000087133005,0.010221629,0.0018163684,0.00008215347,0.000012603814,0.0000027622882,0.00001634894,0.000011696451],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986514,0.00018031165,0.0005656743,0.00026620465,0.00016824465,0.00016815087],"domain_scores_gemma":[0.99850297,0.0000733131,0.00053725706,0.00049097533,0.00022698658,0.0001684755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012536359,0.00013384213,0.00052671245,0.00008900451,0.00009150889,0.0000061034466,0.00021624897,0.000032645792,0.000014826918],"category_scores_gemma":[0.00011504423,0.000097150536,0.00012279065,0.0004533003,0.00048629934,0.000032592863,0.00010519947,0.00037685697,8.986077e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005842497,0.0008642813,0.098134406,0.00012309472,0.00006400434,0.0000840556,0.00008984306,0.000005634225,0.67845887,0.002126491,0.000831227,0.21337561],"study_design_scores_gemma":[0.0006628966,0.014313778,0.9689331,0.00011872148,0.00012077194,0.0035789323,0.00011635985,0.000119349526,0.006708848,0.002295561,0.0029080487,0.00012361484],"about_ca_topic_score_codex":0.000012952824,"about_ca_topic_score_gemma":0.000002251327,"teacher_disagreement_score":0.8707987,"about_ca_system_score_codex":0.00004343632,"about_ca_system_score_gemma":0.000079041674,"threshold_uncertainty_score":0.3961684},"labels":[],"label_agreement":null},{"id":"W3203270152","doi":"10.1016/j.nicl.2021.102837","title":"Non-parametric combination of multimodal MRI for lesion detection in focal epilepsy","year":2021,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"UCLH Biomedical Research Centre; Medical Research Council; National Institute for Health and Care Research","keywords":"Epilepsy; Lesion; Parametric statistics; Diffusion MRI; Medicine; Psychology; Magnetic resonance imaging; Neuroscience; Physical medicine and rehabilitation; Radiology; Psychiatry; Mathematics; Statistics","score_opus":0.14676615194554532,"score_gpt":0.45722586180286245,"score_spread":0.31045970985731713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203270152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7884383,0.000039201124,0.20808958,0.0019389418,0.000206313,0.0009075621,0.000009270376,0.00009328112,0.00027752656],"genre_scores_gemma":[0.9567982,0.00024108528,0.04210479,0.0005435629,0.00008747366,0.00008339372,0.000031262214,0.000027247514,0.000083006045],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99847114,0.00006603656,0.0006722149,0.00046594217,0.0001565136,0.00016813511],"domain_scores_gemma":[0.99840933,0.00071671617,0.00016425633,0.0004168828,0.00021215071,0.00008068025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034914166,0.00011011479,0.00035789405,0.00012390585,0.00004000168,0.000007770103,0.00007899319,0.00012163058,0.0000087762555],"category_scores_gemma":[0.0015395671,0.00011373631,0.00019890314,0.0005632948,0.00009754147,0.000061829196,0.000058982037,0.00038136903,0.0000050631324],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014027471,0.0071963235,0.23489097,0.00028830313,0.000026137284,0.00020166779,0.00004099645,0.00010580524,0.30223635,0.0012375063,0.0020638828,0.4503093],"study_design_scores_gemma":[0.0052762087,0.0014461725,0.773261,0.000095835916,0.000056127516,0.00007629176,0.00001552863,0.07163473,0.13977532,0.0024084062,0.005782244,0.00017213021],"about_ca_topic_score_codex":0.0000065319296,"about_ca_topic_score_gemma":0.0000048525676,"teacher_disagreement_score":0.53837,"about_ca_system_score_codex":0.000029529823,"about_ca_system_score_gemma":0.00006770995,"threshold_uncertainty_score":0.4638032},"labels":[],"label_agreement":null},{"id":"W3203635121","doi":"10.1002/hipo.23388","title":"High resolution diffusion tensor imaging of the hippocampus across the healthy lifespan","year":2021,"lang":"en","type":"article","venue":"Hippocampus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Diffusion MRI; Hippocampus; Hippocampal formation; Psychology; Magnetic resonance imaging; Neuroscience; Medicine; Radiology","score_opus":0.03252926129270064,"score_gpt":0.33305139974362924,"score_spread":0.3005221384509286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203635121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94918704,0.0009884305,0.0031181904,0.045255166,0.00032298546,0.0005806534,0.000029009463,0.00018153588,0.00033697125],"genre_scores_gemma":[0.98965704,0.0002795343,0.004189739,0.005163412,0.00017966835,0.00006378287,0.000020267044,0.000034797646,0.00041177217],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99849933,0.0001173151,0.00035706037,0.00036286746,0.00031146253,0.0003519412],"domain_scores_gemma":[0.9981923,0.00014909964,0.00021492227,0.0011315929,0.00022118435,0.00009087502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024036075,0.00016213745,0.00024641273,0.000026827545,0.00047897393,0.000021274966,0.00023846731,0.00005937369,0.000026509975],"category_scores_gemma":[0.00025860532,0.00009784253,0.00015971366,0.0004910884,0.00028791782,0.00005471819,0.00026102964,0.0004084564,0.000011584637],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067751657,0.0015423197,0.36961794,0.0005216116,0.00009700388,0.00015078101,0.0021737614,0.00024094242,0.14990163,0.018016739,0.03188402,0.42517576],"study_design_scores_gemma":[0.0030503285,0.00022387119,0.7884426,0.00065694953,0.00022744267,0.0014252398,0.001190086,0.0029185084,0.025392823,0.107356794,0.0686325,0.00048283645],"about_ca_topic_score_codex":0.0000636689,"about_ca_topic_score_gemma":0.00001624966,"teacher_disagreement_score":0.42469293,"about_ca_system_score_codex":0.000078383906,"about_ca_system_score_gemma":0.00013789072,"threshold_uncertainty_score":0.39899027},"labels":[],"label_agreement":null},{"id":"W3203853664","doi":"10.1101/2021.09.30.462636","title":"Normalizing automatic spinal cord cross-sectional area measures","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Institut de Valorisation des Données; Canada First Research Excellence Fund","keywords":"Spinal cord; Medicine; Normalization (sociology); Correlation; Cohort; Cross-sectional study; Atrophy; Pathology; Mathematics","score_opus":0.08411689390072308,"score_gpt":0.3385049444262137,"score_spread":0.2543880505254906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203853664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9556777,0.0009483333,0.039767046,0.00031917778,0.0005932821,0.0009203827,0.000085208245,0.0016491119,0.00003979286],"genre_scores_gemma":[0.9215321,0.00022027787,0.07671832,0.0004920965,0.00043672716,0.00044750117,0.0000016615281,0.00013958754,0.000011757368],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9969742,0.000058575137,0.0006946467,0.0011393875,0.00061536045,0.00051788765],"domain_scores_gemma":[0.9967699,0.000042827738,0.00041972645,0.0015579403,0.0008835829,0.0003260216],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037805055,0.0005332973,0.00063587236,0.00025396116,0.00028186478,0.00032790526,0.00038247716,0.00040802258,0.000115779665],"category_scores_gemma":[0.0003168358,0.0005832775,0.0002943256,0.000479288,0.00019336554,0.00016159302,0.00048803014,0.0012246253,0.000033588167],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014747767,0.00042140068,0.24853534,0.0011747385,0.00022105181,0.00035092465,0.0000034033544,0.00006444415,0.7478148,0.00082615623,0.00040597035,0.000034306602],"study_design_scores_gemma":[0.0004996668,0.000157564,0.84843415,0.0010242525,0.00016537218,9.4300754e-7,0.0000015459827,0.0018395296,0.1422824,0.000008462105,0.0049070846,0.00067900924],"about_ca_topic_score_codex":0.000030349735,"about_ca_topic_score_gemma":6.754363e-7,"teacher_disagreement_score":0.6055324,"about_ca_system_score_codex":0.000372193,"about_ca_system_score_gemma":0.0007661683,"threshold_uncertainty_score":0.99966186},"labels":[],"label_agreement":null},{"id":"W3203992831","doi":"","title":"Frequency tuned bipolar oscillating gradients for mapping diffusion kurtosis dispersion in the human brain","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Kurtosis; Dispersion (optics); Thermal diffusivity; Diffusion; Oscillation (cell signaling); Waveform; Weighting; Physics; Nuclear magnetic resonance; Biological system; Acoustics; Mathematics; Chemistry; Statistics; Optics; Voltage","score_opus":0.16218353994770468,"score_gpt":0.2735423262054324,"score_spread":0.11135878625772772,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3203992831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91936576,0.00009510084,0.07797604,0.0009451347,0.00006209358,0.0011159246,0.00002288395,0.00013052997,0.00028652026],"genre_scores_gemma":[0.99509764,0.00025191164,0.003662629,0.0004010687,0.00006689285,0.000013213609,0.00021050044,0.000031938802,0.00026417998],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985313,0.00008852193,0.00023410661,0.0007785043,0.00008806616,0.0002795092],"domain_scores_gemma":[0.99866426,0.00016374218,0.00019637255,0.0008041591,0.00009523279,0.000076239216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022970478,0.00023832958,0.00031535747,0.00023936688,0.00032376236,0.00003639232,0.00037998226,0.00016807049,0.000013759083],"category_scores_gemma":[0.00010935305,0.0002219209,0.00024377351,0.00052663224,0.000082282306,0.00008502559,0.00040657533,0.00058121665,0.0000017129106],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078361496,0.0012412405,0.6689173,0.0012918247,0.00014103272,0.00067219185,0.0032844984,0.002589128,0.26770332,0.04972095,0.00072896515,0.003631183],"study_design_scores_gemma":[0.011894341,0.0008260768,0.5497563,0.009071972,0.0015754099,0.00016771352,0.010369949,0.18172626,0.0068173646,0.20677018,0.016950425,0.0040740347],"about_ca_topic_score_codex":0.0002353213,"about_ca_topic_score_gemma":0.000041394156,"teacher_disagreement_score":0.26088595,"about_ca_system_score_codex":0.00020715903,"about_ca_system_score_gemma":0.0000497659,"threshold_uncertainty_score":0.9049671},"labels":[],"label_agreement":null},{"id":"W3204608968","doi":"10.1007/978-3-030-87615-9_13","title":"Accelerating Geometry-Based Spherical Harmonics Glyphs Rendering for dMRI Using Modern OpenGL","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"OpenGL; Computer science; Spherical harmonics; Rendering (computer graphics); Slicing; Computer graphics (images); Ellipsoid; Voxel; Shader; Visualization; Spline (mechanical); Computer vision; Artificial intelligence; Computational science; Physics","score_opus":0.15591232312858366,"score_gpt":0.3677652341556015,"score_spread":0.2118529110270178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204608968","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00074070616,0.00030707804,0.99686325,0.0007018935,0.00018651142,0.00071078097,0.000010341345,0.00015080614,0.00032862712],"genre_scores_gemma":[0.08398551,0.000015224253,0.91364455,0.0018327205,0.00030409903,0.000025386653,0.000021010115,0.000064721855,0.00010675153],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997748,0.000007727439,0.00037908924,0.0010310138,0.00041112374,0.00042304088],"domain_scores_gemma":[0.9984219,0.0002802671,0.00018362532,0.0007429778,0.00024370839,0.00012753575],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023670337,0.0003326503,0.00048384923,0.00022199887,0.0002614543,0.00016133345,0.000464906,0.0001822313,0.000018322686],"category_scores_gemma":[0.0001441193,0.00032569678,0.00013719295,0.00037375547,0.00025445598,0.000114181705,0.00035079572,0.00068146706,8.8982506e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045325643,0.0000846987,0.000115494826,0.0003338401,0.000021645594,0.00014905065,0.00022052004,0.23379746,0.03962184,0.003040898,0.000024819741,0.72254443],"study_design_scores_gemma":[0.00035867118,0.00010008584,0.000013197325,0.0006239036,0.00003135109,0.00008071497,3.3513953e-7,0.9643799,0.017823596,0.014662066,0.0015855788,0.00034062093],"about_ca_topic_score_codex":0.000007850283,"about_ca_topic_score_gemma":0.000005205933,"teacher_disagreement_score":0.7305824,"about_ca_system_score_codex":0.0003097116,"about_ca_system_score_gemma":0.00054977264,"threshold_uncertainty_score":0.99991953},"labels":[],"label_agreement":null},{"id":"W3204968122","doi":"10.1016/j.radonc.2021.09.020","title":"Accuracy and precision of apparent diffusion coefficient measurements on a 1.5 T MR-Linac in central nervous system tumour patients","year":2021,"lang":"en","type":"article","venue":"Radiotherapy and Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Health Sciences Centre; Sunnybrook Health Science Centre; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Terry Fox Research Institute","keywords":"Nuclear medicine; Repeatability; Effective diffusion coefficient; Medicine; White matter; Linear particle accelerator; Magnetic resonance imaging; Diffusion MRI; Radiology; Physics; Beam (structure); Chemistry; Optics","score_opus":0.055838435799754865,"score_gpt":0.35810832614363014,"score_spread":0.3022698903438753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204968122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941682,0.00094720453,0.0035613424,0.00050295546,0.00007277712,0.00052530604,0.0000066775106,0.000030322302,0.00018517885],"genre_scores_gemma":[0.9955717,0.0013519488,0.0026776423,0.00029714423,0.000027731434,0.000030716987,0.000011832846,0.000011800041,0.000019505575],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99913764,0.00007727633,0.0002451787,0.0002519574,0.00013652623,0.00015144183],"domain_scores_gemma":[0.9995019,0.000100398895,0.00010584965,0.00015475899,0.00006217432,0.00007491254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000099566525,0.00009685274,0.0002858207,0.00006655796,0.0000440591,0.000004561115,0.000036578684,0.00006245564,0.000005935952],"category_scores_gemma":[0.00004419187,0.00008022495,0.000027706219,0.00011351338,0.00004485468,0.00001995126,0.000026536394,0.00011157566,2.4495017e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014976948,0.003668749,0.29055586,0.00034544492,0.00003618597,0.00008332976,0.0011399041,0.00016992971,0.1715657,0.0011020865,0.00036204894,0.52947307],"study_design_scores_gemma":[0.009133923,0.003240939,0.9228927,0.00085616624,0.000053089683,0.00016360257,0.00022165805,0.0068121706,0.03254577,0.00010472172,0.02374614,0.0002291302],"about_ca_topic_score_codex":0.000013659291,"about_ca_topic_score_gemma":0.000008506827,"teacher_disagreement_score":0.6323368,"about_ca_system_score_codex":0.00026586177,"about_ca_system_score_gemma":0.000053654174,"threshold_uncertainty_score":0.32714784},"labels":[],"label_agreement":null},{"id":"W3205458840","doi":"10.1101/2021.10.07.463554","title":"The Role of the Temporal Pole in Temporal Lobe Epilepsy: A Diffusion Kurtosis Imaging Study","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Temporal lobe; Uncinate fasciculus; White matter; Kurtosis; Diffusion MRI; Epilepsy; Magnetic resonance imaging; Lobe; Medicine; Nuclear medicine; Anatomy; Fractional anisotropy; Radiology","score_opus":0.019207167610335946,"score_gpt":0.2722601760187516,"score_spread":0.2530530084084156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205458840","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99365896,0.0015196032,0.00047802186,0.0016460953,0.00024738253,0.0021489405,0.00004710342,0.0002346514,0.000019239851],"genre_scores_gemma":[0.9953736,0.00019846814,0.0034908422,0.00019755015,0.00013485075,0.000490576,4.6504593e-7,0.000106210005,0.000007447553],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973045,0.00020271589,0.00073843804,0.00083729223,0.00048751122,0.00042953866],"domain_scores_gemma":[0.9965298,0.000090473426,0.0005440247,0.0023577318,0.00034619856,0.00013173599],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00056167797,0.00042225936,0.00060061144,0.00015838833,0.000278055,0.000112690854,0.0007070454,0.00015532257,0.000009507112],"category_scores_gemma":[0.0002190802,0.0003010099,0.00023457203,0.0008277538,0.00022268944,0.00008050812,0.0012462833,0.0011213006,0.0000025549596],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029203873,0.0006211471,0.80062646,0.00006733721,0.000033821492,0.00002780366,0.000030104165,0.0000055385167,0.19832289,0.00015750199,0.00005376625,0.00002441171],"study_design_scores_gemma":[0.00074957026,0.00005603194,0.89706457,0.0007802322,0.00015353964,1.1402816e-7,0.00016507778,0.0010355285,0.09446397,0.000028259481,0.0051183063,0.00038481463],"about_ca_topic_score_codex":0.0004967354,"about_ca_topic_score_gemma":0.000029342105,"teacher_disagreement_score":0.103858925,"about_ca_system_score_codex":0.00021699307,"about_ca_system_score_gemma":0.00053110154,"threshold_uncertainty_score":0.9999442},"labels":[],"label_agreement":null},{"id":"W3205614966","doi":"10.1016/j.media.2021.102257","title":"Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia","year":2022,"lang":"en","type":"article","venue":"Amsterdam UMC (VU Amsterdam) - Institutional Repository","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Institute on Aging; National Institute for Health and Care Research; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; Nvidia; University of Southern California; UK Research and Innovation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; University College London Hospitals NHS Foundation Trust; European Commission; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Benchmark (surveying); Neuroimaging; Machine learning; Set (abstract data type); Deep learning; Categorization; Psychology; Neuroscience","score_opus":0.03671884635202357,"score_gpt":0.32375161572273836,"score_spread":0.2870327693707148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3205614966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.734935,0.00052708195,0.25107247,0.005889234,0.0005145211,0.0040592398,0.00019828022,0.00033159292,0.002472599],"genre_scores_gemma":[0.9854649,0.000009616635,0.009835352,0.002326041,0.00024645965,0.0013443457,0.00033713254,0.00003919118,0.00039698312],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99795026,0.00010683011,0.0005553026,0.0007138007,0.0003638349,0.0003100002],"domain_scores_gemma":[0.9989287,0.00019347519,0.0002199778,0.00042356964,0.00010778991,0.00012645582],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022943447,0.00024495192,0.00028577252,0.00025441856,0.0011051815,0.00005276761,0.00017330992,0.00006221244,0.00001300612],"category_scores_gemma":[0.00008943491,0.00027858632,0.00010228453,0.00033926524,0.00023039503,0.00031512242,0.00025605515,0.0003403853,0.0000018385019],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028039454,0.0025755174,0.06776923,0.0005171035,0.00038728132,0.0008021782,0.0023496116,0.092106625,0.67808884,0.10870153,0.009635186,0.034262944],"study_design_scores_gemma":[0.016049495,0.002053084,0.17409723,0.00035641252,0.0006431513,0.002849443,0.0008282093,0.30057597,0.028157998,0.014349959,0.4580047,0.0020343284],"about_ca_topic_score_codex":0.000087755696,"about_ca_topic_score_gemma":0.00003692972,"teacher_disagreement_score":0.64993083,"about_ca_system_score_codex":0.0003387842,"about_ca_system_score_gemma":0.00024559273,"threshold_uncertainty_score":0.9999666},"labels":[],"label_agreement":null},{"id":"W3206070921","doi":"10.1007/s00429-021-02408-3","title":"Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"","keywords":"Fiducial marker; Computer science; Artificial intelligence; Image registration; Preprocessor; Neuroimaging; Workflow; Neurology; Parkinson's disease; Magnetic resonance imaging; Medical physics; Pattern recognition (psychology); Computer vision; Medicine; Radiology; Pathology; Psychology; Neuroscience; Image (mathematics); Disease","score_opus":0.025050995292173212,"score_gpt":0.34424131761762145,"score_spread":0.31919032232544825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206070921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9012839,0.000031409618,0.09478941,0.0023751596,0.0000484393,0.00046052152,0.0009888735,0.000015616619,0.0000066332072],"genre_scores_gemma":[0.98624635,0.00000682496,0.011086167,0.0020086835,0.00006653645,0.000015310678,0.0005562529,0.0000071181935,0.000006755563],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99940664,0.000028511009,0.00019333635,0.00020137896,0.00011663336,0.0000535214],"domain_scores_gemma":[0.9992753,0.00008021729,0.00010064166,0.00038463253,0.000091105445,0.00006809137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000046114743,0.000057997386,0.0001326315,0.00001753135,0.000034319008,0.0000030853175,0.000039602517,0.000043406115,0.000011982818],"category_scores_gemma":[0.00021537355,0.00003691517,0.00002821613,0.00018792227,0.00006478592,0.000022059394,0.00004190953,0.00010763744,2.2414724e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060716615,0.00012705609,0.95794535,0.00005666438,0.000020218937,5.1850543e-7,0.000021010388,0.000008689189,0.0012672857,0.0030088616,0.006065546,0.030871626],"study_design_scores_gemma":[0.0002713453,0.00007551574,0.9204494,0.000033248405,0.00006762276,0.0000012409112,0.0000056125155,0.00005294667,0.0006578647,0.004569613,0.07377815,0.000037476104],"about_ca_topic_score_codex":0.0000025645552,"about_ca_topic_score_gemma":0.0000019641475,"teacher_disagreement_score":0.08496241,"about_ca_system_score_codex":0.000005931359,"about_ca_system_score_gemma":0.000036757854,"threshold_uncertainty_score":0.1505357},"labels":[],"label_agreement":null},{"id":"W3206188152","doi":"","title":"脳卒中をめぐる最近の話題 超急性期診断の最前線-Diffusion,Perfusion MRIを中心に-","year":2004,"lang":"zh","type":"article","venue":"Pharma Medica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Diffusion; Medicine; Computer science; Physics","score_opus":0.06127557304407322,"score_gpt":0.382143045496436,"score_spread":0.3208674724523628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206188152","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23976947,0.023623426,0.1906692,0.29850966,0.0066739786,0.008526626,0.00043054597,0.005771978,0.22602512],"genre_scores_gemma":[0.9531303,0.018848313,0.01064595,0.0105390195,0.0024752722,0.00023817048,0.00015479616,0.0001796847,0.0037884598],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962256,0.000072412426,0.0007968,0.00096566236,0.0010271411,0.00091239327],"domain_scores_gemma":[0.99730504,0.0001374625,0.00029290008,0.0011044213,0.00018117501,0.0009790083],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00041336197,0.0005406491,0.0006331307,0.00024745677,0.0004962603,0.000039665483,0.0005816364,0.00024118615,0.0024869991],"category_scores_gemma":[0.00030905174,0.00049281045,0.00025648845,0.0007094442,0.00047769892,0.00019108722,0.00039102772,0.0012042595,0.0013068331],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007465045,0.0075659165,0.0036676056,0.001033658,0.00024439147,0.002129571,0.0038031999,0.0001552465,0.36289063,0.053920638,0.1694949,0.39434776],"study_design_scores_gemma":[0.010671602,0.0006626602,0.0020521192,0.0019685489,0.0007106914,0.0007603448,0.0002757969,0.0017460033,0.03482812,0.025291536,0.91999286,0.0010396884],"about_ca_topic_score_codex":0.00011151924,"about_ca_topic_score_gemma":0.0000023077225,"teacher_disagreement_score":0.750498,"about_ca_system_score_codex":0.00029767072,"about_ca_system_score_gemma":0.000461139,"threshold_uncertainty_score":0.99975234},"labels":[],"label_agreement":null},{"id":"W3206632789","doi":"10.1016/j.mri.2021.10.014","title":"Axon diameter inferences in the human corpus callosum using oscillating gradient spin echo sequences","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Corpus callosum; Axon; Echo (communications protocol); Gradient echo; Spin echo; Physics; Anatomy; Nuclear magnetic resonance; Neuroscience; Biology; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.09164087711832948,"score_gpt":0.37349322110462685,"score_spread":0.2818523439862974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3206632789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98077446,0.007183408,0.0036121437,0.0035571097,0.000070897906,0.0004836996,0.0000060647085,0.00011796305,0.0041942443],"genre_scores_gemma":[0.96470225,0.00020394108,0.033319872,0.0013988606,0.00008561762,0.0000662158,0.000007939669,0.000021419633,0.00019388313],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984631,0.00008847951,0.00036017873,0.00044129926,0.00028733673,0.0003596197],"domain_scores_gemma":[0.9991737,0.0001098507,0.00009805317,0.00048148143,0.00008434643,0.000052561994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002410678,0.00017447186,0.00023191395,0.00009232152,0.00021146674,0.00009267874,0.00019253122,0.000028336726,0.000045251967],"category_scores_gemma":[0.00014284544,0.00013581265,0.000068634305,0.00053442764,0.00020044715,0.00010873887,0.000089755944,0.00032684303,0.0000032078174],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006955495,0.00012947171,0.7097852,0.00006205128,0.0000022403342,0.0005544072,0.0007545497,0.000050213468,0.11074451,0.0024790717,0.00018730924,0.17524396],"study_design_scores_gemma":[0.00172239,0.0002680894,0.8369168,0.0018660437,0.00012327949,0.0017927764,0.0019813783,0.041253474,0.021475598,0.023691086,0.06799151,0.0009175716],"about_ca_topic_score_codex":0.000300297,"about_ca_topic_score_gemma":0.00004863878,"teacher_disagreement_score":0.17432639,"about_ca_system_score_codex":0.00007323682,"about_ca_system_score_gemma":0.000076606724,"threshold_uncertainty_score":0.5538279},"labels":[],"label_agreement":null},{"id":"W3207240923","doi":"10.1016/j.pscychresns.2021.111396","title":"Association between frontal cortico-limbic white-matter microstructure and risk for pediatric depression","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; CBCL; White matter; Psychology; Uncinate fasciculus; Cingulum (brain); Diffusion MRI; Child Behavior Checklist; Anxiety; Major depressive disorder; Clinical psychology; Psychiatry; Magnetic resonance imaging; Medicine; Radiology; Mood","score_opus":0.05857890424942056,"score_gpt":0.3986610323987461,"score_spread":0.34008212814932554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207240923","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97374886,0.001293625,0.0071590845,0.015772305,0.00022594756,0.00090879615,0.00016062401,0.00016798006,0.00056276744],"genre_scores_gemma":[0.95347714,0.000999806,0.04190667,0.0007588126,0.0011489909,0.00014775335,0.00014074976,0.000095795236,0.001324305],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99782777,0.00016061396,0.00031139114,0.000695113,0.00044436677,0.00056075037],"domain_scores_gemma":[0.9984059,0.00038107144,0.0001553186,0.0004781136,0.00036949237,0.0002101597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043133413,0.00017298186,0.00026591704,0.00019742169,0.0005243877,0.00012225905,0.00012540587,0.00009216923,0.000052841708],"category_scores_gemma":[0.00042362724,0.0001700448,0.00010288435,0.00046201047,0.00005814593,0.00014468713,0.00018518962,0.00096554606,0.000017946526],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003723196,0.000060135008,0.973432,0.00013827265,0.000024637438,0.0000066873326,0.000033837623,0.0000013598528,0.0033214604,0.000019303552,0.021616984,0.0013080636],"study_design_scores_gemma":[0.0009412638,0.00006907812,0.9873853,0.000042339245,0.00021850127,0.00007635312,0.000050187966,0.0002777902,0.0007411364,0.0038560883,0.006189321,0.00015268933],"about_ca_topic_score_codex":0.000012096261,"about_ca_topic_score_gemma":0.0000054211855,"teacher_disagreement_score":0.034747586,"about_ca_system_score_codex":0.00008583108,"about_ca_system_score_gemma":0.00015368563,"threshold_uncertainty_score":0.6934226},"labels":[],"label_agreement":null},{"id":"W3207755099","doi":"10.1101/2021.10.13.464139","title":"An atlas of white matter anatomy, its variability, and reproducibility based on Constrained Spherical Deconvolution of diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek; National Institutes of Health","keywords":"Diffusion MRI; Tractography; White matter; Fornix; Anatomy; Fractional anisotropy; Human Connectome Project; Computer science; Reproducibility; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Cartography; Psychology; Biology; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Functional connectivity","score_opus":0.02369214734514877,"score_gpt":0.2909940875997623,"score_spread":0.2673019402546135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3207755099","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9678631,0.000066980436,0.029467821,0.00097539666,0.00011481126,0.0011419172,0.0001674521,0.0001857454,0.000016808392],"genre_scores_gemma":[0.9321953,0.00005174595,0.06731853,0.00021977254,0.00006193987,0.00009354206,0.0000024669164,0.000054795604,0.0000019135555],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9968081,0.00020409157,0.00069522293,0.0017503729,0.0003042808,0.00023789261],"domain_scores_gemma":[0.99511987,0.00010673064,0.00047489163,0.0033819836,0.00070570305,0.00021083491],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00097459025,0.00034019176,0.0007367285,0.00012495757,0.00007942894,0.000021803931,0.00020423379,0.0003099526,0.00010447771],"category_scores_gemma":[0.00051092426,0.0003470149,0.00013147407,0.00037457756,0.00031503724,0.00007636179,0.00033671956,0.00054225815,0.0000014065511],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011127842,0.00090230233,0.3258964,0.0010739521,0.000024643621,0.000010909744,0.0000073028523,0.00008912095,0.67163306,0.00020448805,0.00004224349,0.000004276312],"study_design_scores_gemma":[0.0005644048,0.00017739221,0.66506267,0.0005640105,0.0001356482,8.5073395e-8,0.0000023421858,0.010558174,0.3225075,0.000010734911,0.00014061591,0.0002764063],"about_ca_topic_score_codex":0.000017973161,"about_ca_topic_score_gemma":4.663857e-7,"teacher_disagreement_score":0.34912556,"about_ca_system_score_codex":0.00012324407,"about_ca_system_score_gemma":0.00040684448,"threshold_uncertainty_score":0.9998982},"labels":[],"label_agreement":null},{"id":"W3208508987","doi":"10.5281/zenodo.4157687","title":"avdvorak/multivariate-template: version 1.0.0","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Multivariate statistics; Artificial intelligence; Machine learning","score_opus":0.12869363969680372,"score_gpt":0.33034807317076487,"score_spread":0.20165443347396114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208508987","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.093043506,0.00021747244,0.29103947,0.084942095,0.0001739642,0.0038327354,0.00075155677,0.015579965,0.51041925],"genre_scores_gemma":[0.9896765,0.000068058864,0.0054948526,0.0017881907,0.00017021764,6.4005945e-8,0.0012648671,0.0010639401,0.00047333006],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990318,0.000060686154,0.00015770523,0.00033885663,0.00020808539,0.0002028983],"domain_scores_gemma":[0.99913955,0.000012060835,0.0000573893,0.00030648967,0.00024773207,0.00023676487],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00011676447,0.00009884248,0.00012235472,0.000070680595,0.0009028193,0.00012654733,0.00033945937,0.00004135924,0.005602812],"category_scores_gemma":[0.0003281994,0.000100858175,0.000045039935,0.00041049594,0.0000773545,0.000120407065,0.00051702064,0.000258275,0.00662039],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035382496,0.00026354444,0.000030412693,0.00014021617,0.00004046065,0.000067149784,0.0007863869,0.00004331403,0.15576272,0.007637064,0.75864154,0.07623339],"study_design_scores_gemma":[0.000559135,0.00026446147,0.0006910044,0.000021836373,0.000017594264,0.00009596865,0.0000640766,0.00093464466,0.004147073,0.00016031227,0.99294394,0.000099980585],"about_ca_topic_score_codex":0.000003923566,"about_ca_topic_score_gemma":5.973745e-9,"teacher_disagreement_score":0.89663297,"about_ca_system_score_codex":0.000056212364,"about_ca_system_score_gemma":0.0000025019215,"threshold_uncertainty_score":0.9953062},"labels":[],"label_agreement":null},{"id":"W3208639644","doi":"","title":"Characterizing Peritumoral Tissue Using Free Water Elimination in Clinical DTI","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Diffusion MRI; Infiltration (HVAC); Brain tissue; Initialization; Computer science; Tractography; Free water; Compartment (ship); Biomedical engineering; Magnetic resonance imaging; Radiology; Materials science; Medicine; Geology","score_opus":0.19620907455896044,"score_gpt":0.4656549720747833,"score_spread":0.2694458975158228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208639644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9594355,0.000003877041,0.031502116,0.0056289756,0.00006774696,0.00026164082,0.0000014249954,0.00015174555,0.0029469791],"genre_scores_gemma":[0.9356281,0.00000785129,0.062183898,0.001316344,0.00030133463,0.000011506767,0.000011381478,0.000014860527,0.0005247249],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99928963,0.000016351718,0.0002613792,0.00020120048,0.00007546814,0.00015597786],"domain_scores_gemma":[0.9995519,0.00001380406,0.000029640709,0.00029968636,0.000056988403,0.000048007587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016565286,0.00006812989,0.00013575572,0.00006368396,0.000046585512,0.000014267122,0.00007191882,0.000042005468,0.000120357065],"category_scores_gemma":[0.00004790393,0.000050533206,0.000026734426,0.00007606275,0.00008695049,0.000135626,0.000102887425,0.00009933754,0.000032228283],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006321002,0.00023544738,0.01754218,0.000021711181,0.000003814887,0.00003198537,0.00019207779,2.8065287e-7,0.9416568,0.0029705227,0.00043412563,0.036847826],"study_design_scores_gemma":[0.0013356598,0.0005147531,0.16558859,0.00012503126,0.00003395181,0.00017308397,0.000069442925,0.0059225657,0.7714856,0.0036779025,0.050811272,0.00026209996],"about_ca_topic_score_codex":0.000022256698,"about_ca_topic_score_gemma":0.0000050959734,"teacher_disagreement_score":0.17017117,"about_ca_system_score_codex":0.000028297338,"about_ca_system_score_gemma":0.000011902963,"threshold_uncertainty_score":0.20606844},"labels":[],"label_agreement":null},{"id":"W3208816240","doi":"10.1089/neur.2021.0036","title":"Decreases in Dorsal Cervical Spinal Cord White Matter Tract Integrity Are Associated with Elevated Levels of Serum MicroRNA Biomarkers in NCAA Division I Collegiate Football Players","year":2021,"lang":"en","type":"article","venue":"Neurotrauma Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Fractional anisotropy; Medicine; White matter; Corticospinal tract; Spinal cord; Diffusion MRI; Fasciculus; Spinal cord injury; Concussion; Anatomy; Magnetic resonance imaging; Internal medicine; Poison control; Radiology; Injury prevention","score_opus":0.08260471337765157,"score_gpt":0.3508856733318611,"score_spread":0.26828095995420953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208816240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99688876,0.00004599723,0.000214668,0.0016675655,0.000051327646,0.00068299525,0.0000623479,0.00010668975,0.00027963595],"genre_scores_gemma":[0.9979107,0.00001626742,0.0012548653,0.00058055425,0.000009317651,0.00005069053,0.000044148488,0.000050995877,0.00008250498],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997636,0.00012121632,0.00082265475,0.00068509806,0.00036459928,0.00037042832],"domain_scores_gemma":[0.9984809,0.00009468219,0.0005328515,0.0005385507,0.0002186723,0.00013431945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002412693,0.00027039988,0.000574229,0.0002316849,0.000045038138,0.00002085905,0.00009462602,0.00014902087,0.000119929675],"category_scores_gemma":[0.00030540602,0.000244545,0.00011012809,0.0009854619,0.000092882845,0.00010692186,0.00007412828,0.0006391709,0.0000015969082],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050322205,0.0008967515,0.9611237,0.00007643487,0.000029912939,0.009151862,0.000023822035,0.000013161573,0.02681351,0.0000054633633,0.00018029514,0.0011818775],"study_design_scores_gemma":[0.0011433384,0.00042893353,0.96768785,0.0010060491,0.000047482677,0.0016384209,0.00005402286,0.000106488515,0.02743688,0.00010170964,0.0001446919,0.0002041098],"about_ca_topic_score_codex":0.00010798702,"about_ca_topic_score_gemma":0.00021450597,"teacher_disagreement_score":0.007513441,"about_ca_system_score_codex":0.00014330568,"about_ca_system_score_gemma":0.00019529615,"threshold_uncertainty_score":0.9972256},"labels":[],"label_agreement":null},{"id":"W3208866695","doi":"10.5281/zenodo.19460155","title":"neurostuff/NiMARE: 0.0.8","year":2021,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Computer science","score_opus":0.19147225510793817,"score_gpt":0.4414745749230314,"score_spread":0.25000231981509324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3208866695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51039636,0.00023109694,0.007199653,0.03754418,0.00012054036,0.0011565036,0.000046486795,0.00003456531,0.4432706],"genre_scores_gemma":[0.69410896,0.000089097244,0.26694193,0.0029388813,0.00009938049,0.00003332877,0.000076437056,0.00003194986,0.035680015],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995397,0.000008195272,0.000085624175,0.00021515417,0.00006173513,0.00008959029],"domain_scores_gemma":[0.9995142,0.000016446076,0.000021643451,0.0003406645,0.000049048325,0.000057982317],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000031011263,0.000050664934,0.00009591547,0.00001214431,0.00004632485,0.000038336384,0.000099728844,0.00001714811,0.0014181811],"category_scores_gemma":[0.000047444137,0.000047874684,0.000026660122,0.0001393951,0.000021012984,0.000053719476,0.00015997449,0.00009156317,0.00023946294],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059347192,0.000523272,0.007542402,0.00001433526,0.00001884998,0.0009483628,0.00014233793,0.0000027983476,0.37155625,0.0011642461,0.021977985,0.5960498],"study_design_scores_gemma":[0.0002613138,0.00003432606,0.004595902,0.000017920178,0.000018163775,0.00024510853,0.000020278723,0.000039499882,0.13458265,0.00032329166,0.8598049,0.00005659199],"about_ca_topic_score_codex":0.0000019942042,"about_ca_topic_score_gemma":0.0000015314882,"teacher_disagreement_score":0.83782697,"about_ca_system_score_codex":0.000009949724,"about_ca_system_score_gemma":0.0000632025,"threshold_uncertainty_score":0.9994947},"labels":[],"label_agreement":null},{"id":"W3209571802","doi":"10.1016/j.neubiorev.2021.10.028","title":"Neuromelanin accumulation in patients with schizophrenia: A systematic review and meta-analysis","year":2021,"lang":"en","type":"review","venue":"Neuroscience & Biobehavioral Reviews","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; Royal Ottawa Mental Health Centre; University of Ottawa; Centre for Addiction and Mental Health; Ontario Institute for Cancer Research; University of Toronto","funders":"National Institute of Mental Health","keywords":"Neuromelanin; Substantia nigra; Dopamine; Schizophrenia (object-oriented programming); Biomarker; Striatum; Meta-analysis; Magnetic resonance imaging; Neuroscience; Internal medicine; Neuroimaging; Medicine; Psychology; Neurology; Pathology; Psychiatry; Dopaminergic; Chemistry; Radiology","score_opus":0.40284195319826493,"score_gpt":0.48643771540453445,"score_spread":0.08359576220626952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209571802","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000012560297,0.9903872,0.00014858843,0.00002322481,0.000013899509,0.0092783095,0.000064104075,0.00006589275,0.0000062101526],"genre_scores_gemma":[0.000028380702,0.99466777,0.0015758547,0.0012287465,0.000005290217,0.0022123468,0.00014584897,0.000051506144,0.00008427628],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9960616,0.00037352974,0.0015587382,0.0012062619,0.00047655866,0.00032326338],"domain_scores_gemma":[0.9971549,0.000009661216,0.0010929075,0.0014280551,0.00012323959,0.00019123161],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005118094,0.0006503862,0.009334444,0.00047313067,0.00008811268,0.000079679354,0.0003297077,0.00011481786,0.00004544672],"category_scores_gemma":[0.0003293379,0.00037644853,0.0014592111,0.0039403094,0.00013075226,0.000190169,0.00016001733,0.000582592,0.0000095512],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004995488,0.0006363168,0.00048878574,0.90109724,0.0001444262,0.00007706689,0.000006446499,3.5863488e-7,0.0000013189114,0.000060122486,0.00015742975,0.09732547],"study_design_scores_gemma":[0.000115175906,0.00012475459,0.0003153595,0.036860418,0.6400513,0.000047650996,3.1434695e-7,0.0000020343525,4.6622223e-8,0.0000010897345,0.3221712,0.00031063703],"about_ca_topic_score_codex":0.000005734188,"about_ca_topic_score_gemma":0.0000033581262,"teacher_disagreement_score":0.86423683,"about_ca_system_score_codex":0.00007101768,"about_ca_system_score_gemma":0.00010666693,"threshold_uncertainty_score":0.99986875},"labels":[],"label_agreement":null},{"id":"W3209666936","doi":"10.1016/j.celrep.2021.109890","title":"fMRI neurofeedback in the motor system elicits bidirectional changes in activity and in white matter structure in the adult human brain","year":2021,"lang":"en","type":"article","venue":"Cell Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"FP7 People: Marie-Curie Actions; NIHR Oxford Biomedical Research Centre; H2020 Marie Skłodowska-Curie Actions; National Institute for Health and Care Research; Wellcome Trust","keywords":"Neurofeedback; White matter; Neuroscience; Corpus callosum; Brain activity and meditation; Psychology; Human brain; Neuroplasticity; Brain mapping; Electroencephalography; Medicine; Magnetic resonance imaging","score_opus":0.02481250611896547,"score_gpt":0.3001290599775655,"score_spread":0.27531655385860004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209666936","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9864223,0.00005705475,0.000015304604,0.011684208,0.000034262976,0.0005298923,0.000004197383,0.000022049842,0.0012307529],"genre_scores_gemma":[0.9973614,0.000019677726,0.0001201734,0.0020284797,0.000048119113,0.00011272904,0.000011828806,0.000012974193,0.00028457426],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99905753,0.00012294715,0.00021513912,0.0003084152,0.0001485348,0.00014741324],"domain_scores_gemma":[0.9994194,0.00007316266,0.0000948122,0.0003652692,0.000027384873,0.000019994897],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022154473,0.00010356228,0.00016202558,0.000107009444,0.000037332404,0.000018924491,0.000056004737,0.00005346638,0.000012690054],"category_scores_gemma":[0.000042793865,0.00007068686,0.000019976058,0.0003778505,0.0000306464,0.00003920499,0.0000369496,0.00037902308,5.3539026e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026113605,0.0002104393,0.7840499,0.00024188586,0.0000017847946,0.0030116742,0.0012201227,0.000022523265,0.20913585,0.00008127174,0.0014254977,0.0005728925],"study_design_scores_gemma":[0.0002180394,0.000019371424,0.9893202,0.00013102192,0.000004344333,0.0010738886,0.0003255014,0.00006810046,0.0072617866,0.00025375397,0.0012549129,0.00006903843],"about_ca_topic_score_codex":0.00014666116,"about_ca_topic_score_gemma":0.0013535311,"teacher_disagreement_score":0.20527029,"about_ca_system_score_codex":0.000047279293,"about_ca_system_score_gemma":0.000024410268,"threshold_uncertainty_score":0.28825265},"labels":[],"label_agreement":null},{"id":"W3209702035","doi":"10.5281/zenodo.580063","title":"Tractography Challenge ISMRM 2015 Code of the Scoring System","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Code (set theory); Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging; Programming language; Set (abstract data type)","score_opus":0.13340641378992615,"score_gpt":0.34685046412274023,"score_spread":0.21344405033281408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209702035","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13391514,0.00042129363,0.03118034,0.025188083,0.00034959265,0.0034843225,0.0005870269,0.0036671802,0.801207],"genre_scores_gemma":[0.99846923,0.000092672635,0.0005878751,0.000042922144,0.00007099508,8.379987e-8,0.000042162905,0.00044108785,0.00025293857],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999167,0.000053203483,0.00016689277,0.0002246564,0.00022477956,0.00016344691],"domain_scores_gemma":[0.99838144,0.000008991807,0.00018289717,0.0010557858,0.00028895977,0.00008192228],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00024712883,0.000080121165,0.00012413683,0.00007742481,0.001931709,0.00013990559,0.0008147039,0.000032418702,0.00020433872],"category_scores_gemma":[0.00021348822,0.00006477502,0.00007030937,0.00013889912,0.00021646447,0.0001116848,0.00065073645,0.00020960458,0.00019387572],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033747114,0.0015601133,0.0010969149,0.002061833,0.000270391,0.000070964656,0.0026709195,0.000053782318,0.15081069,0.22929107,0.19355385,0.418222],"study_design_scores_gemma":[0.00047331245,0.0001319412,0.01685296,0.00022883233,0.00003468511,0.0001432001,0.00016378092,0.00026370896,0.0044750487,0.00026000608,0.97687256,0.000099971374],"about_ca_topic_score_codex":0.000009189816,"about_ca_topic_score_gemma":1.3793097e-7,"teacher_disagreement_score":0.8645541,"about_ca_system_score_codex":0.000046001973,"about_ca_system_score_gemma":0.0000025603115,"threshold_uncertainty_score":0.99936765},"labels":[],"label_agreement":null},{"id":"W3209967316","doi":"10.1016/j.neuroimage.2021.118687","title":"Recycling diagnostic MRI for empowering brain morphometric research – Critical &amp; practical assessment on learning-based image super-resolution","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"Key Medical Subjects of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Xuzhou Medical University; Hospital for Sick Children; National Natural Science Foundation of China; Azrieli Foundation; China Postdoctoral Science Foundation; Ministry of Science and Technology of the People's Republic of China; Jiangsu Province Postdoctoral Science Foundation","keywords":"Voxel; Computer science; Artificial intelligence; Isotropy; Resolution (logic); Ground truth; Pattern recognition (psychology); Image quality; Sample (material); Image (mathematics); Computer vision; Data mining; Physics; Optics","score_opus":0.25825090133019807,"score_gpt":0.5526592950398811,"score_spread":0.294408393709683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209967316","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05228875,0.00008002527,0.8136588,0.12978795,0.00015372195,0.0013320877,0.000039478255,0.00055615103,0.002103076],"genre_scores_gemma":[0.60100925,0.000102429476,0.3941922,0.0026532772,0.00028414672,0.00055447576,0.00018229628,0.00012655917,0.00089539844],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969443,0.00039296763,0.0003871253,0.00089919125,0.0007025025,0.0006739303],"domain_scores_gemma":[0.98302,0.015241481,0.000060496674,0.00072819804,0.00067904545,0.00027079097],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0010454956,0.00022165249,0.0003245973,0.0004256498,0.00049724965,0.00013995075,0.00012812964,0.00010578052,0.000130864],"category_scores_gemma":[0.04122823,0.00023366556,0.00017057458,0.0011617967,0.00023745149,0.00016612734,0.00013416908,0.001579413,0.00006800108],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004811604,0.0035888446,0.0046390523,0.00066509796,0.000029599008,0.0020336004,0.000056607667,0.00072199455,0.90537435,0.013186705,0.06437637,0.0048466297],"study_design_scores_gemma":[0.0038154784,0.0030617812,0.035077848,0.0006634125,0.00019747739,0.00070147385,0.00013842572,0.044373013,0.1065792,0.0036878341,0.80086154,0.00084253785],"about_ca_topic_score_codex":0.0000053945873,"about_ca_topic_score_gemma":0.0000019691581,"teacher_disagreement_score":0.79879516,"about_ca_system_score_codex":0.00019603645,"about_ca_system_score_gemma":0.0003269871,"threshold_uncertainty_score":0.9668479},"labels":[],"label_agreement":null},{"id":"W3210063353","doi":"10.1371/journal.pone.0255711","title":"Test-retest reproducibility of in vivo oscillating gradient and microscopic anisotropy diffusion MRI in mice at 9.4 Tesla","year":2021,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Reproducibility; Kurtosis; Diffusion MRI; Fractional anisotropy; Voxel; Nuclear magnetic resonance; Region of interest; Sample size determination; Materials science; Biomedical engineering; Mathematics; Physics; Computer science; Statistics; Magnetic resonance imaging; Artificial intelligence; Medicine; Radiology","score_opus":0.06626205067740572,"score_gpt":0.30785945127531145,"score_spread":0.24159740059790574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210063353","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99718374,0.0002674305,0.00005599491,0.0017899993,0.000004986411,0.00038701235,0.000014179817,0.0000423151,0.00025431192],"genre_scores_gemma":[0.94326395,0.00038558888,0.055823505,0.00013034644,0.000016347713,0.000027219094,0.0000069281646,0.000013303659,0.00033281217],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99883014,0.000023131019,0.00028263402,0.0006099228,0.0001159272,0.0001382325],"domain_scores_gemma":[0.9990237,0.00014438185,0.000075918484,0.0006469668,0.00006551484,0.00004355862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017067877,0.00008360483,0.00025686386,0.000056271856,0.000032633143,0.0000037718812,0.00003888148,0.00003432471,0.000018791896],"category_scores_gemma":[0.0008316972,0.000084125626,0.000018687759,0.00029072928,0.000065125605,0.000028408016,0.00013859286,0.00013752446,8.474469e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007295612,0.0006496394,0.4362658,0.00010985679,0.0000017058233,0.000006331944,0.000068836765,4.50368e-7,0.56278753,0.000023945155,0.000015776706,0.00006283662],"study_design_scores_gemma":[0.00049350195,0.00009528251,0.23410198,0.0005185999,0.000021070224,0.000009709765,0.000025194131,0.0004668273,0.7637002,0.00043574086,0.000068192494,0.000063722015],"about_ca_topic_score_codex":0.000054135646,"about_ca_topic_score_gemma":0.00005204299,"teacher_disagreement_score":0.20216382,"about_ca_system_score_codex":0.00008422159,"about_ca_system_score_gemma":0.000024579587,"threshold_uncertainty_score":0.34305435},"labels":[],"label_agreement":null},{"id":"W3210569499","doi":"10.5281/zenodo.4314291","title":"dMRIPrep: a robust preprocessing pipeline for diffusion MRI","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Pipeline (software); Preprocessor; Computer science; Artificial intelligence; Pattern recognition (psychology)","score_opus":0.1353888152438295,"score_gpt":0.3273362676861259,"score_spread":0.19194745244229638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3210569499","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004522262,0.000072357914,0.9530772,0.017111184,0.000021752054,0.0012894185,0.00012818418,0.002344004,0.021433666],"genre_scores_gemma":[0.9266609,0.00024805055,0.059793618,0.0045152893,0.00073413656,9.653498e-7,0.0029804134,0.0029334652,0.0021331415],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988741,0.000039403832,0.00021309557,0.00045244658,0.00019021153,0.00023068943],"domain_scores_gemma":[0.9989307,0.000018613147,0.00008651802,0.00034204542,0.00041289188,0.00020925314],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00017278726,0.000112361035,0.00014728164,0.00007192905,0.0010639516,0.00017307857,0.00034011938,0.00004048854,0.001193301],"category_scores_gemma":[0.00064223516,0.00011190034,0.000058025067,0.0003759629,0.000080275524,0.0001253082,0.0004707155,0.00019782041,0.00048799085],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058416865,0.00045924674,0.00002965096,0.0006154874,0.00002998534,0.000018513183,0.0014021122,0.0003868584,0.12541075,0.0037587772,0.5745488,0.29275566],"study_design_scores_gemma":[0.0007311822,0.00023277148,0.00011394878,0.000054778935,0.000028185359,0.00007926917,0.00008198855,0.026158227,0.0034558382,0.00028816488,0.9686561,0.0001195293],"about_ca_topic_score_codex":0.0000014160873,"about_ca_topic_score_gemma":1.7098355e-8,"teacher_disagreement_score":0.92213863,"about_ca_system_score_codex":0.000051611867,"about_ca_system_score_gemma":0.0000039761085,"threshold_uncertainty_score":0.99971974},"labels":[],"label_agreement":null},{"id":"W3211014836","doi":"10.1136/bmjresp-2021-bssconf.32","title":"36 Literature review on the effects of acute and chronic alcohol use on the glymphatic transport system","year":2021,"lang":"en","type":"article","venue":"Abstracts","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Clinical trial; Medicine; Clinical study design; Disease; Clinical research; Intensive care medicine; Internal medicine","score_opus":0.03487616025582492,"score_gpt":0.32028279475918303,"score_spread":0.2854066345033581,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211014836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.937469,0.029838664,0.00008828819,0.026994003,0.00009306235,0.0027498782,0.00004580333,0.00017756707,0.0025437549],"genre_scores_gemma":[0.973926,0.02154319,0.00012369582,0.0039155073,0.000037318907,0.000100489306,0.000019808413,0.000015670734,0.00031834038],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99936765,0.000028179344,0.00017688429,0.0001784803,0.00014362174,0.00010519434],"domain_scores_gemma":[0.99882424,0.00045274151,0.000091814414,0.0005359547,0.00005428544,0.000040992305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010094232,0.0001091982,0.00019266305,0.000014487925,0.00006079439,0.000011853566,0.00007150612,0.00003420069,0.000005214286],"category_scores_gemma":[0.000093595394,0.00005539044,0.00006744985,0.00016229463,0.000042265205,0.00003769386,0.0000102549875,0.00018353798,0.0000055333044],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004128388,0.001654249,0.0013057122,0.08570061,0.0012760093,0.007023352,0.0011103343,0.000037787835,0.64604706,0.1706643,0.043239992,0.041527744],"study_design_scores_gemma":[0.0016424796,0.0009279369,0.12796502,0.16007672,0.0019002783,0.0016607877,0.00003693992,0.00007450547,0.6453912,0.0005891875,0.05931401,0.00042088056],"about_ca_topic_score_codex":0.0000015539428,"about_ca_topic_score_gemma":4.996168e-7,"teacher_disagreement_score":0.1700751,"about_ca_system_score_codex":0.000029147013,"about_ca_system_score_gemma":0.000038888407,"threshold_uncertainty_score":0.22587565},"labels":[],"label_agreement":null},{"id":"W3211352396","doi":"10.7759/cureus.19355","title":"Diagnostic Implications of White Matter Tract Involvement by Intra-axial Brain Tumors","year":2021,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Medicine; Diffusion MRI; White matter; Infiltration (HVAC); Astrocytoma; Brain tumor; Radiology; Magnetic resonance imaging; Pathology; Glioma","score_opus":0.04048906555426739,"score_gpt":0.33835216436658977,"score_spread":0.29786309881232237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211352396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7488032,0.0017638956,0.054557554,0.18049607,0.00013167992,0.0015655621,0.0004651331,0.0005412096,0.011675703],"genre_scores_gemma":[0.9851096,0.000095867326,0.009060775,0.0042639673,0.00007029241,0.00017390017,0.00021219751,0.000025980578,0.0009873747],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99929786,0.000014934551,0.00023197052,0.00022240072,0.00009333251,0.00013951433],"domain_scores_gemma":[0.9991531,0.0001390318,0.00007550059,0.00046270152,0.00008919118,0.00008050117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003807958,0.00009112682,0.00015979985,0.000022007373,0.00006337244,0.0000061415053,0.00008546172,0.000032587603,0.00037018838],"category_scores_gemma":[0.0001347419,0.00008876217,0.00006031244,0.00016266125,0.00005607598,0.000044765555,0.000060840663,0.00011901516,0.00002704735],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009537564,0.0012247715,0.28066918,0.00010619183,0.000032939894,0.000023206732,0.0003860245,0.000005114795,0.1593563,0.003384632,0.55268836,0.0021137712],"study_design_scores_gemma":[0.0010750644,0.0002501871,0.667855,0.00022543505,0.00017651985,0.000278093,0.00030224957,0.000070319744,0.12692408,0.009895242,0.19256434,0.00038342352],"about_ca_topic_score_codex":0.000009894497,"about_ca_topic_score_gemma":0.0000035230291,"teacher_disagreement_score":0.38718587,"about_ca_system_score_codex":0.000039907736,"about_ca_system_score_gemma":0.000051330622,"threshold_uncertainty_score":0.4053303},"labels":[],"label_agreement":null},{"id":"W3211737115","doi":"10.1002/trc2.12217","title":"A ketogenic supplement improves white matter energy supply and processing speed in mild cognitive impairment","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Translational Research & Clinical Interventions","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Ketone bodies; White matter; Neurocognitive; Ketogenic diet; Medicine; Glucose uptake; Fornix; Positron emission tomography; Neuroimaging; Cognition; Internal medicine; Psychology; Nuclear medicine; Neuroscience; Insulin; Magnetic resonance imaging; Radiology; Metabolism; Epilepsy; Hippocampus","score_opus":0.32843368658637434,"score_gpt":0.5277430677723072,"score_spread":0.19930938118593283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211737115","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51188153,0.11096285,0.1451586,0.21733992,0.0003893618,0.0072839675,0.0011254167,0.0004318912,0.0054264464],"genre_scores_gemma":[0.9830628,0.0007006357,0.014157547,0.00076948584,0.000094545496,0.0003290045,0.0005407834,0.000036288144,0.00030891006],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968123,0.00033030525,0.0010883836,0.0007109373,0.0005741113,0.00048400537],"domain_scores_gemma":[0.99837124,0.00044341234,0.000105041916,0.00027383163,0.0005565153,0.00024997597],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009498216,0.0001859147,0.0003273716,0.00026986096,0.00021954757,0.00008609725,0.0001290335,0.00009599309,0.0017563163],"category_scores_gemma":[0.00008654151,0.0001863811,0.00037897687,0.0005471226,0.000356763,0.00020390695,0.00015907893,0.0006135898,0.000027966009],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059305324,0.0052643185,0.90825886,0.00022023359,0.0025756604,0.00011937369,0.00023530729,0.000005451762,0.0021105753,0.004279115,0.008284175,0.06805391],"study_design_scores_gemma":[0.0036653131,0.00053725246,0.969916,0.0010990087,0.0015091563,0.00005671171,0.00024310903,0.001384776,0.0027457378,0.009203304,0.009363516,0.0002761137],"about_ca_topic_score_codex":0.000057590543,"about_ca_topic_score_gemma":0.00025436355,"teacher_disagreement_score":0.47118127,"about_ca_system_score_codex":0.000020370644,"about_ca_system_score_gemma":0.0002611843,"threshold_uncertainty_score":0.99915624},"labels":[],"label_agreement":null},{"id":"W3212030657","doi":"10.1212/wnl.94.15_supplement.2728","title":"Braak Neurofibrillary Tangle Staging Prediction Using In Vivo MRI Metrics (2728)","year":2020,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Hôpital de l'Enfant-Jésus","funders":"","keywords":"Tangle; Neurofibrillary tangle; Neuroscience; Alzheimer's disease; Medicine; In vivo; Audiology; Psychology; Pathology; Disease; Biology; Mathematics; Senile plaques","score_opus":0.09292557713855468,"score_gpt":0.3396425162714804,"score_spread":0.24671693913292572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212030657","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9262238,0.000108273336,0.05003036,0.021143189,0.00013289244,0.00050634006,0.000025757081,0.0005063983,0.0013229887],"genre_scores_gemma":[0.9743537,0.00014700186,0.0067671095,0.018426921,0.00021831052,0.00001528664,0.000008511429,0.00004615198,0.000017052122],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989293,0.00005046185,0.00024267667,0.00040656573,0.00012813092,0.00024285767],"domain_scores_gemma":[0.9994538,0.0000769681,0.000071333816,0.0002455476,0.000035075074,0.0001172648],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054361473,0.00012169146,0.00022093081,0.00017643714,0.000051396597,0.000007944632,0.000088384695,0.00007812897,0.000030901847],"category_scores_gemma":[0.000120585966,0.00013063705,0.00004720475,0.000753822,0.000053381198,0.00008051642,0.00009219445,0.00036583657,0.000005976038],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060535443,0.00018495426,0.50901705,0.00011713137,0.000017086662,0.00080411293,0.00020186442,0.0034801625,0.4754587,0.0013993267,0.0053551127,0.0033591255],"study_design_scores_gemma":[0.0031528426,0.0036802825,0.092810564,0.00004098935,0.00017056576,0.0013703242,0.000024387096,0.44385865,0.040892567,0.0016697652,0.4117982,0.0005308285],"about_ca_topic_score_codex":0.000022166658,"about_ca_topic_score_gemma":0.0000010313352,"teacher_disagreement_score":0.44037852,"about_ca_system_score_codex":0.000019522928,"about_ca_system_score_gemma":0.0000344924,"threshold_uncertainty_score":0.5327224},"labels":[],"label_agreement":null},{"id":"W3212499163","doi":"10.1016/j.nano.2021.102478","title":"Superparamagnetic iron oxide nanoparticles-based detection of neuronal activity","year":2021,"lang":"en","type":"article","venue":"Nanomedicine Nanotechnology Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal","funders":"Savoy Foundation; Réseau en Bio-Imagerie du Quebec","keywords":"Dynamic light scattering; Magnetic resonance imaging; Iron oxide nanoparticles; Premovement neuronal activity; Superparamagnetism; Chemistry; Biophysics; Brain activity and meditation; Nanoparticle; Nuclear magnetic resonance; Materials science; Neuroscience; Nanotechnology; Magnetic field; Biology; Electroencephalography; Medicine; Magnetization; Physics","score_opus":0.03365988542931305,"score_gpt":0.33988345502532513,"score_spread":0.3062235695960121,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3212499163","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9616701,0.001938338,0.010325466,0.02522637,0.00010976787,0.00032648904,0.000007046792,0.00025221982,0.00014419387],"genre_scores_gemma":[0.99499726,0.0007338686,0.0023344667,0.0016342379,0.0000735353,0.0000525062,0.000029522955,0.000021748709,0.00012284516],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985138,0.00009401213,0.00039855388,0.0005348742,0.00013199664,0.0003267327],"domain_scores_gemma":[0.99869734,0.00028622503,0.00015827536,0.0005393295,0.00018188995,0.00013691773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027819598,0.00022382101,0.0006468978,0.0002989525,0.000110007335,0.0000012041965,0.00010050367,0.00035781265,0.00006798289],"category_scores_gemma":[0.0007814001,0.00017689366,0.000056883244,0.000617745,0.0017422374,0.00003197661,0.00007548915,0.00049301033,0.0000027179622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002543316,0.00016296959,0.008689563,0.00008464495,0.00001564567,0.00003994574,0.000013220373,0.0000010298899,0.94419646,0.0012900832,0.00004737175,0.04520476],"study_design_scores_gemma":[0.0033004866,0.002529253,0.05374062,0.00015966366,0.00021334506,0.000609325,0.00005250011,0.0003491585,0.927901,0.0018246314,0.009172439,0.00014753541],"about_ca_topic_score_codex":0.000037992053,"about_ca_topic_score_gemma":0.00000975196,"teacher_disagreement_score":0.045057222,"about_ca_system_score_codex":0.000033388747,"about_ca_system_score_gemma":0.00012050222,"threshold_uncertainty_score":0.72135144},"labels":[],"label_agreement":null},{"id":"W3213266407","doi":"10.1038/s41598-021-01476-z","title":"Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trinity College","funders":"European Research Council","keywords":"Magnetic resonance imaging; Diffusion; Diffusion MRI; Gaussian; Nuclear magnetic resonance; Computer science; Statistical physics; Medicine; Physics; Chemistry; Radiology; Computational chemistry; Thermodynamics","score_opus":0.07428836332777075,"score_gpt":0.3216931236854927,"score_spread":0.24740476035772194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213266407","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99103105,0.00018613908,0.0060455464,0.00032301573,0.0019128781,0.00026024334,0.0000020648818,0.00012143327,0.000117607684],"genre_scores_gemma":[0.9568459,0.000027236249,0.041265175,0.000055347606,0.00017785378,0.000014770268,0.00011309624,0.000030459476,0.0014701877],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986254,0.000010851806,0.00030904415,0.0006089455,0.00024177083,0.00020399614],"domain_scores_gemma":[0.9988293,0.000006119016,0.00011853118,0.0007067595,0.00024876167,0.00009050196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000099572266,0.000113019865,0.00015317413,0.00007638943,0.00034565513,0.00013530313,0.000049565602,0.00003279683,0.00014756617],"category_scores_gemma":[0.00012087358,0.00010827219,0.000030930503,0.00076080457,0.00011879559,0.00020095104,0.00010120675,0.00009738042,0.000006890973],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031545076,0.000028092727,0.0037635271,0.000017884993,8.7753205e-7,0.00039434028,0.00008921575,0.0000021234123,0.98795915,0.000032467826,0.00039683003,0.007312327],"study_design_scores_gemma":[0.00015116717,0.000015278536,0.016435178,0.000113336915,0.00002191879,0.002190048,0.000040744268,0.0002168021,0.9045267,0.00069521606,0.07547076,0.00012284397],"about_ca_topic_score_codex":0.000006744113,"about_ca_topic_score_gemma":0.0000011702548,"teacher_disagreement_score":0.08343246,"about_ca_system_score_codex":0.000053621538,"about_ca_system_score_gemma":0.00012893148,"threshold_uncertainty_score":0.44152117},"labels":[],"label_agreement":null},{"id":"W3213593937","doi":"10.1101/2021.11.13.468500","title":"Home literacy environment mediates the relationship between socioeconomic status and white matter structure in infants","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"White matter; Fractional anisotropy; Developmental psychology; Psychology; Association (psychology); Socioeconomic status; Fasciculus; Reading (process); Diffusion MRI; Phonological awareness; Superior longitudinal fasciculus; Literacy; Medicine; Population; Magnetic resonance imaging; Environmental health","score_opus":0.02378477614273908,"score_gpt":0.27320301918842405,"score_spread":0.24941824304568497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213593937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99468493,0.0010457474,0.00048104697,0.0025471565,0.000086777894,0.0007610659,0.0002805158,0.00011052495,0.0000022544748],"genre_scores_gemma":[0.9882722,0.0005380305,0.010153196,0.00055960956,0.00020249283,0.00018088928,0.0000050411454,0.00008281864,0.000005728788],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982344,0.00008209079,0.00045314102,0.0007186388,0.00015796018,0.00035378573],"domain_scores_gemma":[0.99824446,0.00023022128,0.00026077332,0.0010432078,0.000053437252,0.00016786643],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017683735,0.00033805965,0.00044059573,0.00016199435,0.00011632231,0.0001391863,0.0001891273,0.0002757487,0.00009920646],"category_scores_gemma":[0.000068518595,0.00029972167,0.00006833389,0.00013428145,0.0001568062,0.00013775563,0.000422478,0.0011436269,0.000020088093],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000071938975,0.000023596638,0.9948357,0.0001444201,0.000026217915,0.000010056016,0.0000480962,0.00001394358,0.0047579217,0.00006895837,0.000059838036,0.000004103487],"study_design_scores_gemma":[0.00039411517,0.000012124749,0.9956422,0.00022127222,0.00008566449,4.852838e-8,0.0000047920416,0.000049986505,0.0021154587,0.00007273736,0.0011171616,0.00028443476],"about_ca_topic_score_codex":0.000014967423,"about_ca_topic_score_gemma":8.3620637e-7,"teacher_disagreement_score":0.009672149,"about_ca_system_score_codex":0.00023345576,"about_ca_system_score_gemma":0.0001624,"threshold_uncertainty_score":0.99994546},"labels":[],"label_agreement":null},{"id":"W3214279120","doi":"10.52294/e6198273-b8e3-4b63-babb-6e6b0da10669","title":"Evaluating the Reliability of Human Brain White Matter Tractometry","year":2021,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":82,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIH Blueprint for Neuroscience Research; National Institute of Mental Health; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Washington Research Foundation; Alfred P. Sloan Foundation; University of Washington; McDonnell Center for Systems Neuroscience; Gordon and Betty Moore Foundation","keywords":"Human Connectome Project; Reliability (semiconductor); Computer science; White matter; Neuroimaging; Reproducibility; Robustness (evolution); Reliability engineering; Diffusion MRI; Psychology; Functional connectivity; Statistics; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging","score_opus":0.09514027686437139,"score_gpt":0.42951816728008857,"score_spread":0.3343778904157172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214279120","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7244396,0.00008314345,0.0017701219,0.267171,0.00004516222,0.00039196134,0.000011318957,0.0001212057,0.0059664394],"genre_scores_gemma":[0.9120092,0.0000076111764,0.0055505745,0.08053489,0.000064335545,0.000030135297,0.000017113045,0.000024030827,0.0017621418],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991489,0.00007058012,0.00020718043,0.00026439998,0.00019067198,0.00011825795],"domain_scores_gemma":[0.9969632,0.0020818755,0.000074144424,0.0007212864,0.00012055838,0.00003893903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015902334,0.00008920889,0.00015549327,0.000025342937,0.000085973996,0.000008791231,0.00010299754,0.000038959297,0.00028729605],"category_scores_gemma":[0.0027520426,0.000059734015,0.00008903372,0.0002879462,0.000075413445,0.000035944784,0.00006103293,0.00031081284,0.000011743457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002381868,0.00022474922,0.07816918,0.000097471726,0.000008141208,0.000022537824,0.0001300837,0.000012154854,0.8515551,0.00048284404,0.06686019,0.00241372],"study_design_scores_gemma":[0.0007238261,0.00044319362,0.75999105,0.000101013495,0.00011333749,0.00034857873,0.000062268824,0.0010161066,0.039885357,0.0039375545,0.19317082,0.00020691332],"about_ca_topic_score_codex":0.0000023129837,"about_ca_topic_score_gemma":4.637028e-7,"teacher_disagreement_score":0.81166977,"about_ca_system_score_codex":0.000010823503,"about_ca_system_score_gemma":0.000028409466,"threshold_uncertainty_score":0.3294651},"labels":[],"label_agreement":null},{"id":"W3214837645","doi":"10.1101/2021.11.23.21266731","title":"In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of British Columbia Hospital; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"White matter; Diffusion MRI; Fractional anisotropy; Hyperintensity; Neuroimaging; Myelin; Pathology; Medicine; Magnetic resonance imaging; Internal medicine; Radiology; Central nervous system","score_opus":0.01906411290487649,"score_gpt":0.3011506869429577,"score_spread":0.28208657403808124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214837645","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97373545,0.0008675826,0.00063698733,0.023736538,0.00011474055,0.000428295,0.00004869754,0.00004552676,0.00038616403],"genre_scores_gemma":[0.96862066,0.00042960807,0.021210397,0.007526615,0.00013130221,0.00011514249,0.000044680313,0.00006925747,0.0018523268],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998544,0.000038740236,0.00034282668,0.00069572794,0.00012737572,0.0002513686],"domain_scores_gemma":[0.999293,0.00002661598,0.00008249124,0.00044560095,0.00006913752,0.00008311043],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009744458,0.00029445128,0.00047329284,0.00022225795,0.000038283826,0.00007376338,0.00009514271,0.00013088949,0.00081338396],"category_scores_gemma":[0.00001401079,0.00028312305,0.000041202326,0.00010588625,0.00016992992,0.00008021648,0.00056712935,0.00077936566,0.0000067336982],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022919674,0.000020328218,0.9588468,0.00030735388,0.000004320033,0.00025061195,0.00068991596,0.000010017141,0.037379395,0.0000068962227,0.0023204735,0.00014097348],"study_design_scores_gemma":[0.0003499301,0.00000817477,0.9858649,0.00069959887,0.000022590519,0.0009066327,0.00036992866,0.0002349555,0.0040648524,0.00060721475,0.006593344,0.00027790348],"about_ca_topic_score_codex":0.00006710765,"about_ca_topic_score_gemma":0.000032169388,"teacher_disagreement_score":0.03331454,"about_ca_system_score_codex":0.000043411546,"about_ca_system_score_gemma":0.000037191356,"threshold_uncertainty_score":0.9999621},"labels":[],"label_agreement":null},{"id":"W3214870749","doi":"10.1016/j.neuroimage.2021.118749","title":"Not all voxels are created equal: Reducing estimation bias in regional NODDI metrics using tissue-weighted means","year":2021,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; UK Dementia Research Institute; British Heart Foundation; University College London; National Institute for Health and Care Research; Alzheimer's Society; Wellcome Trust; Weston Brain Institute; Wolfson Foundation; Brain Research Trust; Brain Research UK; Alzheimer's Association; University College London Hospitals NHS Foundation Trust; U.S. Department of Defense","keywords":"Voxel; Region of interest; Pattern recognition (psychology); Neuroimaging; Metric (unit); Partial volume; Artificial intelligence; Brain tissue; Brain size; Statistics; Computer science; Psychology; Magnetic resonance imaging; Mathematics; Neuroscience; Medicine; Radiology","score_opus":0.3020479958614572,"score_gpt":0.41969500748286503,"score_spread":0.11764701162140784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3214870749","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7962903,0.00035606843,0.19025941,0.009703514,0.00013912536,0.00092605955,0.000056070934,0.0007953929,0.0014740549],"genre_scores_gemma":[0.8230819,0.0001832397,0.17277448,0.003092693,0.00009843923,0.000033830456,0.00018527599,0.000094006704,0.00045615132],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9981174,0.000101399,0.00045344152,0.00062566344,0.00036976387,0.00033231956],"domain_scores_gemma":[0.99855673,0.0002330953,0.00021111124,0.000630529,0.00023411833,0.00013442288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017133917,0.00022221738,0.00035917506,0.00035074545,0.00009866045,0.000048213933,0.00012166215,0.00009211071,0.000051854164],"category_scores_gemma":[0.0007115902,0.00023543525,0.00008070986,0.0014341578,0.00006785121,0.00019348998,0.0000938151,0.00043306284,0.000017980972],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011075672,0.00060232176,0.0038275777,0.00016325345,0.000026114396,0.0019127557,0.00020592341,0.0018273279,0.97223324,0.0011991748,0.0028858883,0.015005667],"study_design_scores_gemma":[0.0024571987,0.0002461861,0.03833338,0.0007252276,0.0002854094,0.0015873448,0.00008469221,0.3243245,0.5924941,0.0021592963,0.036558043,0.00074463437],"about_ca_topic_score_codex":0.00007925073,"about_ca_topic_score_gemma":0.000005707651,"teacher_disagreement_score":0.37973917,"about_ca_system_score_codex":0.00013535008,"about_ca_system_score_gemma":0.0001025598,"threshold_uncertainty_score":0.9600771},"labels":[],"label_agreement":null},{"id":"W3215234842","doi":"10.1007/s00429-021-02407-4","title":"Imaging functional neuroplasticity in human white matter tracts","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; University of Victoria; University of Calgary; Surrey Memorial Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Fraser Health Authority","keywords":"Corpus callosum; Neuroplasticity; Diffusion MRI; White matter; Internal capsule; Neuroscience; Functional magnetic resonance imaging; Fractional anisotropy; Magnetic resonance imaging; Psychology; Tractography; Medicine; Radiology","score_opus":0.025644029195805183,"score_gpt":0.2894671375390891,"score_spread":0.26382310834328393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215234842","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95306957,0.000080259095,0.037218776,0.007188377,0.00013801864,0.00015836408,0.000011120643,0.00009855208,0.0020369831],"genre_scores_gemma":[0.9919347,0.0000041258704,0.0012322945,0.0058384975,0.00015072509,0.000008174512,0.00007979295,0.000014744504,0.0007369509],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993849,0.000018155128,0.0001282882,0.00026537932,0.00008752067,0.00011576193],"domain_scores_gemma":[0.99970466,0.000030355208,0.000031017014,0.00013996947,0.000044898145,0.000049130504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000026967075,0.000091637485,0.00010742175,0.00006654549,0.00008537795,0.000020740352,0.000014608795,0.000034518802,0.00034264504],"category_scores_gemma":[0.00002544191,0.00008638268,0.000025546595,0.00015872269,0.000034111195,0.00008656583,0.000022511296,0.0002141451,0.0000033206913],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007598615,0.000053528664,0.77481544,0.00004851172,0.000007986779,0.00006707504,0.000042937,0.00007113657,0.20300245,0.0019876363,0.013572941,0.0062543876],"study_design_scores_gemma":[0.00046586947,0.000024094084,0.9776019,0.000020949212,0.000022980392,0.00041791186,0.000019500743,0.00019622872,0.0021997772,0.004500858,0.014450815,0.000079115875],"about_ca_topic_score_codex":0.0000030274698,"about_ca_topic_score_gemma":0.000005861187,"teacher_disagreement_score":0.20278648,"about_ca_system_score_codex":0.000016776474,"about_ca_system_score_gemma":0.000018109646,"threshold_uncertainty_score":0.37517232},"labels":[],"label_agreement":null},{"id":"W3215319807","doi":"10.1101/2021.11.22.469616","title":"mrHARDIflow : A pipeline tailored for the preprocessing and analysis of Multi-Resolution High Angular diffusion MRI and its application to a variability study of the PRIME-DE database","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Computer science; Scanner; Robustness (evolution); Scalability; Pipeline (software); Computer vision; Artificial intelligence; Database; Magnetic resonance imaging","score_opus":0.031154277854292922,"score_gpt":0.3048001280941482,"score_spread":0.27364585023985527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215319807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5567242,0.0002927845,0.4400264,0.0002858166,0.000019766267,0.0024413536,0.00016247788,0.000047123754,6.73512e-8],"genre_scores_gemma":[0.94838834,0.0001242841,0.050347574,0.00007019123,0.000037458794,0.0009944553,0.0000026884559,0.000033683198,0.000001302489],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998224,0.0001184577,0.0004661666,0.0007880648,0.00023184386,0.0001714558],"domain_scores_gemma":[0.99703914,0.00015729667,0.00044100295,0.0015707534,0.00069457013,0.000097215845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084610283,0.0002256989,0.00052338187,0.00015246273,0.00017024935,0.000030076017,0.00023422524,0.00011877498,0.0000014410596],"category_scores_gemma":[0.00067332824,0.00016691325,0.00009844211,0.00093264796,0.00008232146,0.000051635332,0.0006398615,0.0002688684,4.6360075e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009850733,0.0008599474,0.02691504,0.00058552757,0.00027174354,7.199062e-7,0.00011038329,0.0010709664,0.96996397,0.000074527794,0.0000066328766,0.00004206236],"study_design_scores_gemma":[0.00081879646,0.00006629755,0.4846317,0.00028851014,0.0032858106,3.085286e-8,0.000030503577,0.3361691,0.17440961,0.0000033064978,0.00010010615,0.00019623943],"about_ca_topic_score_codex":0.00012426457,"about_ca_topic_score_gemma":0.0000106135785,"teacher_disagreement_score":0.79555434,"about_ca_system_score_codex":0.0000795968,"about_ca_system_score_gemma":0.00016398948,"threshold_uncertainty_score":0.6806525},"labels":[],"label_agreement":null},{"id":"W3215445514","doi":"10.1093/neuonc/noab196.915","title":"ITVT-03. Use of Functional MRI and DTI for Surgical Planning of Maximal Extent of Resection of CNS Tumors - A Single Neurosurgical Center’s Experience","year":2021,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Medicine; Magnetic resonance imaging; Diffusion MRI; Neuronavigation; Surgical planning; Functional imaging; Functional magnetic resonance imaging; Neuroimaging; Radiology; Nuclear medicine","score_opus":0.1644279284472633,"score_gpt":0.3897089641072013,"score_spread":0.22528103565993798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215445514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912463,0.000063449916,0.007312845,0.0006481608,0.00009859362,0.0003289156,0.000053266485,0.00002475382,0.00022371855],"genre_scores_gemma":[0.9936599,0.00007590811,0.0059967986,0.00011207211,0.00004141207,0.000052005966,0.000022070986,0.000016189375,0.000023619163],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987921,0.00006668541,0.0005137827,0.00030483922,0.00017106826,0.0001515391],"domain_scores_gemma":[0.9985088,0.00063135626,0.0003026641,0.00022693643,0.00025938073,0.00007086027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008188101,0.00010104797,0.00043383654,0.000094843,0.000033034547,0.0000023878897,0.00005223807,0.00007361108,0.000028452183],"category_scores_gemma":[0.00030429097,0.00009706113,0.00010432563,0.00019657217,0.0003208129,0.000060665527,0.00009378244,0.0001549719,1.0656892e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016779484,0.00097353273,0.019543758,0.00013923626,0.000010497567,0.00011184819,0.00015003067,0.00018222006,0.9748523,0.00094477343,0.00027587017,0.0011379648],"study_design_scores_gemma":[0.0045872387,0.006720268,0.036259927,0.00020290737,0.00008905797,0.003146359,0.00025156475,0.0023350434,0.8814802,0.000287969,0.06449194,0.00014749025],"about_ca_topic_score_codex":0.000008002882,"about_ca_topic_score_gemma":0.000001120156,"teacher_disagreement_score":0.09337209,"about_ca_system_score_codex":0.000026403784,"about_ca_system_score_gemma":0.00009427395,"threshold_uncertainty_score":0.3958038},"labels":[],"label_agreement":null},{"id":"W3215447310","doi":"10.1101/2021.11.29.470422","title":"<i>TractoInferno</i> : A large-scale, open-source, multi-site database for machine learning dMRI tractography","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Sherbrooke","funders":"","keywords":"Computer science; Tractography; Benchmarking; Artificial intelligence; Diffusion MRI; Database; Pipeline (software); Human Connectome Project; Artificial neural network; Data mining; Machine learning; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging","score_opus":0.047021800294677674,"score_gpt":0.3130632676630124,"score_spread":0.2660414673683347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215447310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22709964,0.0023710534,0.75873506,0.0011578192,0.00036951917,0.005185637,0.0030209972,0.002038344,0.00002192215],"genre_scores_gemma":[0.5899646,0.0012594298,0.40481094,0.0013773154,0.00030547715,0.0017601923,0.000060040857,0.0004056007,0.000056410914],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9959243,0.00011571377,0.0008041589,0.0019105426,0.00039462978,0.0008506854],"domain_scores_gemma":[0.9955182,0.00016861701,0.00065130374,0.0023911933,0.00073686434,0.0005338242],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007364477,0.0008091019,0.0011220241,0.00038163378,0.00044966876,0.00044460263,0.0008205731,0.0004783304,0.000058956626],"category_scores_gemma":[0.00040643965,0.00087698497,0.00047070513,0.0008182462,0.00012047304,0.00033711028,0.0015549025,0.0022180262,0.000012640019],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002104769,0.002256348,0.057391573,0.0014450835,0.00026811214,0.00016980463,0.00004056596,0.00009523768,0.9368847,0.00022285487,0.0009765999,0.00003862522],"study_design_scores_gemma":[0.006579163,0.00030345938,0.07763593,0.0027507446,0.0012207646,9.4023477e-7,0.000021719305,0.024756983,0.23529376,0.0000033947483,0.64895463,0.002478505],"about_ca_topic_score_codex":0.000094005656,"about_ca_topic_score_gemma":0.000017236784,"teacher_disagreement_score":0.70159096,"about_ca_system_score_codex":0.0001402038,"about_ca_system_score_gemma":0.00047064363,"threshold_uncertainty_score":0.9993681},"labels":[],"label_agreement":null},{"id":"W3215549172","doi":"10.48550/arxiv.2111.12187","title":"Input Convex Gradient Networks","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Mathematics; Regular polygon; Parameterized complexity; Convex hull; Convex combination; Pure mathematics; Vector space; Balanced flow; Computer science; Geometry; Combinatorics; Mathematical analysis; Convex optimization","score_opus":0.15044413650334715,"score_gpt":0.24829550352961968,"score_spread":0.09785136702627253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3215549172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3314833,0.00020198918,0.66227245,0.0004961339,0.00022724933,0.0005838581,0.000012257351,0.0005191548,0.0042035757],"genre_scores_gemma":[0.9935366,0.0011410271,0.0022222423,0.0006151242,0.0001176791,0.00000380547,0.00014182788,0.00003575773,0.0021859654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987133,0.00003444595,0.00015547179,0.0007963181,0.000048152688,0.00025228213],"domain_scores_gemma":[0.9984469,0.000039563078,0.00013898393,0.0010368411,0.0001503519,0.00018737173],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000059641025,0.00023389125,0.00036447006,0.00010746074,0.00008998023,0.000024868134,0.00025129234,0.00021566913,0.00008291442],"category_scores_gemma":[0.000021003507,0.00027216572,0.00022400219,0.00033124685,0.00012704171,0.000050423918,0.0006556793,0.0008311237,0.000014294949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004915588,0.0022213566,0.1043203,0.0011228215,0.0009473943,0.011516285,0.00043119313,0.5703163,0.0012181511,0.2819119,0.018338086,0.0071646175],"study_design_scores_gemma":[0.002582877,0.0002903061,0.020161193,0.0013740198,0.0015231437,0.00025480276,0.00036267267,0.89553666,0.0016279571,0.034259245,0.040226772,0.0018003215],"about_ca_topic_score_codex":0.000036864254,"about_ca_topic_score_gemma":0.000005539798,"teacher_disagreement_score":0.6620532,"about_ca_system_score_codex":0.0001555127,"about_ca_system_score_gemma":0.00011390537,"threshold_uncertainty_score":0.99997306},"labels":[],"label_agreement":null},{"id":"W3216140919","doi":"10.1002/brb3.2433","title":"Frontal interhemispheric structural connectivity, attention, and executive function in children with perinatal stroke","year":2021,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; Alberta Children's Hospital","funders":"Canadian Institutes of Health Research; Alberta Innovates; Heart and Stroke Foundation of Canada","keywords":"Executive dysfunction; Tractography; Stroke (engine); White matter; Cognition; Diffusion MRI; Psychology; Executive functions; Attention deficit hyperactivity disorder; Rating scale; Frontal lobe; Neuroimaging; Medicine; Neuroscience; Clinical psychology; Neuropsychology; Magnetic resonance imaging; Developmental psychology; Radiology","score_opus":0.01785670701827037,"score_gpt":0.2981783903366468,"score_spread":0.2803216833183764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216140919","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9980513,0.000100776415,0.0010617409,0.00039683928,0.000010889042,0.00024483152,0.000020594616,0.000042937787,0.00007008525],"genre_scores_gemma":[0.9968482,0.000012338803,0.0023851409,0.00013320289,0.00001784381,0.000052511386,0.00004094404,0.0000094156885,0.00050039194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99956286,0.0000100093785,0.00006903695,0.00022012477,0.000054435266,0.00008353703],"domain_scores_gemma":[0.9998083,0.000010884697,0.000022181326,0.000089093104,0.000026331172,0.00004321998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001884544,0.00007663797,0.000103576735,0.00002116499,0.00004627165,0.00001559351,0.000014493328,0.000026773612,0.00002220302],"category_scores_gemma":[0.000009420009,0.0000650988,0.000015235944,0.000064362954,0.00006708528,0.000067252324,0.000040599072,0.0001149581,2.7575493e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003907062,0.000056979887,0.94840914,0.0000075235744,0.0000069526245,0.000021642953,0.00003442125,6.66988e-8,0.03653951,0.00015021839,0.00004800105,0.014686454],"study_design_scores_gemma":[0.0009142314,0.0001543499,0.99491936,0.000026427371,0.000052635292,0.0010802102,0.0001527112,0.000024732588,0.0024307335,0.00004841036,0.00012100666,0.00007517982],"about_ca_topic_score_codex":0.00002653122,"about_ca_topic_score_gemma":0.000029447056,"teacher_disagreement_score":0.046510212,"about_ca_system_score_codex":0.000017611377,"about_ca_system_score_gemma":0.000013841538,"threshold_uncertainty_score":0.2654652},"labels":[],"label_agreement":null},{"id":"W3216458294","doi":"10.1016/j.compbiomed.2021.105090","title":"Dual feature correlation guided multi-task learning for Alzheimer's disease prediction","year":2021,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Fundamental Research Funds for the Central Universities; Liaoning Revitalization Talents Program; National Natural Science Foundation of China","keywords":"Correlation; Computer science; Artificial intelligence; Cognition; Alzheimer's Disease Neuroimaging Initiative; Machine learning; Neuroimaging; Multi-task learning; Feature (linguistics); Task (project management); Curse of dimensionality; Pattern recognition (psychology); Cognitive impairment; Psychology; Mathematics; Neuroscience","score_opus":0.07918633278049354,"score_gpt":0.4018860805692192,"score_spread":0.3226997477887257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216458294","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037618916,0.005185586,0.9316573,0.023896651,0.000523868,0.0007570821,0.000015276546,0.00021202673,0.00013326343],"genre_scores_gemma":[0.91185796,0.0010749222,0.08237803,0.0026421521,0.00048239648,0.00010524761,0.0011352265,0.000018063458,0.00030598798],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993893,0.000034248187,0.00015090419,0.00027132098,0.00003416779,0.00012009358],"domain_scores_gemma":[0.9995331,0.00013154554,0.000050274637,0.00012537424,0.00006965972,0.00009000909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010198202,0.000088155175,0.00018047044,0.00006695737,0.000083814106,0.0000020016864,0.000024033852,0.00007749291,0.0000040551363],"category_scores_gemma":[0.00019144187,0.0000732783,0.00002419827,0.00011203885,0.00013198725,0.000024411755,0.0000318397,0.0002051843,4.489512e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006029171,0.00042530522,0.7639627,0.00019452718,0.00015284517,0.0001897984,0.00069364434,0.00076644577,0.027353218,0.018431854,0.040544298,0.14668249],"study_design_scores_gemma":[0.00860182,0.00085629657,0.61373657,0.0007272827,0.00044550505,0.00043567273,0.00012565783,0.213155,0.00055992894,0.008162228,0.15292875,0.00026530572],"about_ca_topic_score_codex":0.0000022192385,"about_ca_topic_score_gemma":8.572775e-7,"teacher_disagreement_score":0.8742391,"about_ca_system_score_codex":0.000015814843,"about_ca_system_score_gemma":0.000029450573,"threshold_uncertainty_score":0.29882026},"labels":[],"label_agreement":null},{"id":"W3216761169","doi":"10.1177/02841851211056471","title":"Factors associated with brain white matter damage in type 2 diabetes mellitus: a tract-based spatial statistics study","year":2021,"lang":"en","type":"article","venue":"Acta Radiologica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Corpus callosum; Fractional anisotropy; White matter; Internal medicine; Cardiology; Fasciculus; Diabetes mellitus; Type 2 Diabetes Mellitus; Superior longitudinal fasciculus; Diffusion MRI; Body mass index; Blood pressure; Corona radiata (embryology); Audiology; Pathology; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.07034474516005974,"score_gpt":0.32769987980378895,"score_spread":0.2573551346437292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216761169","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99438405,0.000036387464,0.002244663,0.002409741,0.000021487731,0.00047813574,0.000086703454,0.0001261892,0.00021264917],"genre_scores_gemma":[0.99482286,0.000009249987,0.0029425984,0.0015581754,0.000018940053,0.00004682747,0.00040786696,0.000024518302,0.00016895107],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99893767,0.00013272131,0.00021218245,0.00033983449,0.00013113755,0.00024644154],"domain_scores_gemma":[0.9989595,0.0004406899,0.00009787143,0.00034412145,0.00008920892,0.000068618676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011621794,0.0001671106,0.00034020445,0.000058804053,0.000054446584,0.000018005832,0.000093630304,0.000066550005,0.0003328625],"category_scores_gemma":[0.0003830727,0.00011803784,0.000028822176,0.0003252613,0.00006813935,0.00003733808,0.00002732446,0.00028543366,0.000004770992],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026628539,0.0008276136,0.9926625,0.00000871362,0.000024500945,0.00010886726,0.00011923766,0.000020450376,0.002423263,0.000012471383,0.0035242734,0.00024149573],"study_design_scores_gemma":[0.0008254253,0.0007062219,0.99549884,0.000037613016,0.000051782245,0.000001983138,0.00012461988,0.00041149856,0.00079980853,0.00011857481,0.0012776785,0.00014594253],"about_ca_topic_score_codex":0.0000084309795,"about_ca_topic_score_gemma":0.00004226367,"teacher_disagreement_score":0.0028363669,"about_ca_system_score_codex":0.00006700682,"about_ca_system_score_gemma":0.00007220889,"threshold_uncertainty_score":0.48134434},"labels":[],"label_agreement":null},{"id":"W33447915","doi":"10.1007/s00234-021-02635-9","title":"288. 炎症性動脈硬化指標と生活習慣における検討 : 飲酒、喫煙、運動、食習慣(栄養・消化,一般口演,第63回日本体力医学会大会)","year":2008,"lang":"en","type":"article","venue":"体力科學","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FedDev Ontario; Mitacs","keywords":"Computer science","score_opus":0.17646132887085025,"score_gpt":0.3917036621466515,"score_spread":0.21524233327580122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W33447915","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5990786,0.0025750701,0.07750942,0.032734346,0.0005114719,0.003571516,0.000097188466,0.004880049,0.27904233],"genre_scores_gemma":[0.9517343,0.0006417863,0.03143344,0.0038464132,0.00037314295,0.00014279463,0.000050178412,0.000059418824,0.011718494],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99867034,0.000014866111,0.00027476178,0.0004181254,0.0002582458,0.0003636639],"domain_scores_gemma":[0.9987763,0.00004505752,0.000080579724,0.00077441445,0.00009671396,0.00022692581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006624489,0.0002047994,0.00030994925,0.00010515331,0.00020751066,0.0000107547185,0.00015152915,0.00009669846,0.0001660178],"category_scores_gemma":[0.000064764456,0.00018829165,0.00014986513,0.00032136263,0.00016960817,0.00008716452,0.00006211252,0.0003497398,0.00028146466],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005881946,0.002985655,0.12567495,0.00042260168,0.00024182112,0.00227885,0.0009137258,0.00004952066,0.169176,0.046617597,0.55083203,0.10021906],"study_design_scores_gemma":[0.0016250603,0.00042167108,0.1233165,0.00012924061,0.00013381976,0.0020195555,0.00003549012,0.0004342496,0.034486506,0.0037938266,0.83312947,0.00047459683],"about_ca_topic_score_codex":0.00001787574,"about_ca_topic_score_gemma":0.0000011622453,"teacher_disagreement_score":0.35265574,"about_ca_system_score_codex":0.00006531391,"about_ca_system_score_gemma":0.00009993686,"threshold_uncertainty_score":0.7678311},"labels":[],"label_agreement":null},{"id":"W38132263","doi":"10.3390/diagnostics13243679","title":"桃李不言 大音希声——记叶世昌先生对中国货币史的研究","year":2008,"lang":"en","type":"article","venue":"钱币博览","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.18060222629279177,"score_gpt":0.3952616925043475,"score_spread":0.21465946621155574,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W38132263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7206455,0.00042810553,0.05982721,0.018463157,0.00015743703,0.0009500887,0.000014948268,0.002039922,0.19747363],"genre_scores_gemma":[0.96062577,0.000175465,0.030539166,0.0020350239,0.00014063482,0.0000372512,0.000010369311,0.000019252197,0.0064170463],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995619,0.000004222084,0.00008736889,0.00014390267,0.00008606488,0.00011656277],"domain_scores_gemma":[0.9995729,0.000016087424,0.000021631591,0.00029323797,0.000029192439,0.00006697854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000022093009,0.000059694008,0.0000932688,0.000031676267,0.000078187324,0.0000020150244,0.00005071887,0.000024439825,0.000087869426],"category_scores_gemma":[0.000024369365,0.00005251278,0.000040073686,0.00011390828,0.00006259551,0.000028928049,0.000022336802,0.00010515969,0.00016638685],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015562959,0.001197574,0.11009498,0.00013346465,0.000064803804,0.0011531385,0.00071332377,0.000017470977,0.14461002,0.072857775,0.59819746,0.07080434],"study_design_scores_gemma":[0.00047252135,0.000114050235,0.040905375,0.000025750904,0.000020247067,0.0010104039,0.000011123841,0.00016969172,0.019395227,0.0028375553,0.93490005,0.00013797898],"about_ca_topic_score_codex":0.0000053555455,"about_ca_topic_score_gemma":1.94421e-7,"teacher_disagreement_score":0.33670262,"about_ca_system_score_codex":0.000015045823,"about_ca_system_score_gemma":0.00002191826,"threshold_uncertainty_score":0.2141409},"labels":[],"label_agreement":null},{"id":"W4200038265","doi":"10.1016/j.jneumeth.2021.109435","title":"A methodological scoping review of the integration of fMRI to guide dMRI tractography. What has been done and what can be improved: A 20-year perspective","year":2021,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"","keywords":"Tractography; Computer science; Modalities; Human Connectome Project; Connectomics; False positive paradox; Data science; Psychology; Artificial intelligence; Diffusion MRI; Connectome; Functional connectivity; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.39824712150147756,"score_gpt":0.5446234452325527,"score_spread":0.14637632373107512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200038265","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035152603,0.029697703,0.81510365,0.11806659,0.00046999316,0.0013888218,0.0000072472426,0.000023336304,0.00009006523],"genre_scores_gemma":[0.006566386,0.06836496,0.91798365,0.006980388,0.00004297708,0.000013708897,2.4899558e-7,0.000011252823,0.000036424088],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979138,0.00073892076,0.0006226441,0.00026896852,0.00031659644,0.00013907692],"domain_scores_gemma":[0.9975482,0.0006454719,0.0006211046,0.00034451718,0.0007166039,0.00012410466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024712922,0.00011544566,0.0005432061,0.0001312103,0.00008732098,0.000079203826,0.00023057485,0.000036914964,0.0000051380066],"category_scores_gemma":[0.006714732,0.00007162293,0.00021526273,0.0010305091,0.00033277637,0.00049612246,0.0001227975,0.0003595531,1.6996514e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022190196,0.000065192165,0.000046475336,0.0002923661,0.0000037009243,0.000006460932,0.0003081839,0.0000027505941,0.9632855,0.0002373322,0.000049272705,0.035680573],"study_design_scores_gemma":[0.0004354438,0.0011117152,0.006599883,0.041487765,0.00024185193,0.0012798599,0.003941433,0.00013929098,0.93929887,0.0025873687,0.0027192472,0.00015724996],"about_ca_topic_score_codex":0.000008707695,"about_ca_topic_score_gemma":0.000003871502,"teacher_disagreement_score":0.1110862,"about_ca_system_score_codex":0.00003930638,"about_ca_system_score_gemma":0.00027301387,"threshold_uncertainty_score":0.8038646},"labels":[],"label_agreement":null},{"id":"W4200205313","doi":"10.1002/nbm.4685","title":"Validation of cardiac diffusion tensor imaging sequences: A multicentre test–retest phantom study","year":2021,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Office of AIDS Research; NIHR Oxford Biomedical Research Centre; National Heart, Lung, and Blood Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute of Biomedical Imaging and Bioengineering; British Heart Foundation; National Institute for Health and Care Research","keywords":"Reproducibility; Repeatability; Diffusion MRI; Imaging phantom; Fractional anisotropy; Materials science; Biomedical engineering; Nuclear medicine; Nuclear magnetic resonance; Artifact (error); Analytical Chemistry (journal); Medicine; Chemistry; Magnetic resonance imaging; Computer science; Radiology; Physics; Artificial intelligence; Chromatography","score_opus":0.04574986128022169,"score_gpt":0.3680587431632073,"score_spread":0.3223088818829856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200205313","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938178,0.0005787064,0.0006453713,0.0032954032,0.00007717802,0.0009387478,0.000030998388,0.00013568987,0.0004800777],"genre_scores_gemma":[0.99296486,0.00026031316,0.0060163615,0.0002877093,0.000102546524,0.00005815459,0.000100405356,0.000021833215,0.00018779768],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99864805,0.000044829085,0.00041853025,0.00036805947,0.00032128065,0.00019925833],"domain_scores_gemma":[0.9988929,0.00019690243,0.00012928802,0.00044672674,0.00022715436,0.00010705351],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020264482,0.00014310656,0.00037397505,0.00020157534,0.000042389565,0.0000063158586,0.00008502887,0.000034456003,0.000059741003],"category_scores_gemma":[0.0005740609,0.00011852254,0.000053518128,0.0008866479,0.00011836771,0.00006382229,0.00006832735,0.00016766242,0.000004475875],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016717764,0.00079662446,0.5746888,0.00006225495,0.000008642746,0.00008627171,0.00039361062,0.000001678323,0.41578808,0.0000112118805,0.00018683137,0.007959288],"study_design_scores_gemma":[0.005915845,0.0008407702,0.6941521,0.0014659312,0.00041978114,0.00016565349,0.006499681,0.0037780337,0.277087,0.0004515157,0.008809656,0.00041401395],"about_ca_topic_score_codex":0.000104733845,"about_ca_topic_score_gemma":0.000003616617,"teacher_disagreement_score":0.1387011,"about_ca_system_score_codex":0.000081246326,"about_ca_system_score_gemma":0.00008866581,"threshold_uncertainty_score":0.4833209},"labels":[],"label_agreement":null},{"id":"W4200321350","doi":"10.1093/cercor/bhab439","title":"Spatial probability maps of the segments of the postcentral sulcus in the human brain","year":2021,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Postcentral gyrus; Somatosensory system; Sulcus; Central sulcus; Anatomy; Functional magnetic resonance imaging; Magnetic resonance imaging; Parietal lobe; Cortex (anatomy); Neuroscience; Psychology; Biology; Medicine; Motor cortex; Radiology","score_opus":0.04755524965718038,"score_gpt":0.32514418009237955,"score_spread":0.27758893043519917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200321350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98912233,0.000020649506,0.00012318601,0.008810664,0.000042345124,0.00069102267,0.00003910934,0.00001544107,0.0011352778],"genre_scores_gemma":[0.9983532,0.000002084719,0.00032290345,0.0010031242,0.00002720203,0.00002073956,0.000014579276,0.000007780166,0.0002484024],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99915767,0.0001045533,0.00024008527,0.0001655159,0.00020185497,0.00013032336],"domain_scores_gemma":[0.99904644,0.00004622461,0.00011283982,0.0007114418,0.0000635444,0.000019483829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012778208,0.00007554643,0.00013859729,0.00001056996,0.000069656155,0.0000045409834,0.0002627921,0.000030617713,0.000038260187],"category_scores_gemma":[0.00010603551,0.000037780992,0.00010863762,0.00025388968,0.00017954902,0.000020548967,0.00013110603,0.00021635537,5.9919836e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031400934,0.00070561876,0.7596566,0.0001260376,0.000017210117,0.0000057285865,0.00058584614,0.00000567248,0.21610478,0.016783422,0.003424426,0.0025532588],"study_design_scores_gemma":[0.00043241563,0.000040876243,0.9398127,0.00006598996,0.000023758475,0.000021330912,0.000067765075,0.000029913177,0.044739865,0.01353045,0.0011931665,0.0000417349],"about_ca_topic_score_codex":0.00010001563,"about_ca_topic_score_gemma":0.0001062166,"teacher_disagreement_score":0.18015613,"about_ca_system_score_codex":0.00002964601,"about_ca_system_score_gemma":0.00007574609,"threshold_uncertainty_score":0.15406641},"labels":[],"label_agreement":null},{"id":"W4200330348","doi":"10.1016/j.pscychresns.2021.111428","title":"Four-modality imaging of unmedicated subjects with schizophrenia: 18F-fluorodeoxyglucose and 18F-fallypride PET, diffusion tensor imaging, and MRI","year":2021,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Psychology; Neuroscience; Dopaminergic; Magnetic resonance imaging; Medicine; Dopamine; Radiology","score_opus":0.05762162498280654,"score_gpt":0.37071795394895124,"score_spread":0.3130963289661447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200330348","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9300017,0.0034415524,0.0043557333,0.059471145,0.00009816729,0.00093332777,0.000033299024,0.0003601592,0.0013049181],"genre_scores_gemma":[0.95091707,0.0018192069,0.045720108,0.0009897619,0.0001618745,0.00007498445,0.000029266927,0.00012062255,0.00016708235],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99592805,0.0003024089,0.0005691034,0.0013295134,0.0010000143,0.0008709097],"domain_scores_gemma":[0.9971512,0.00033493686,0.00020067593,0.0010329692,0.00074590254,0.0005343024],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00082041416,0.00039246338,0.0005820297,0.00047302397,0.0005390497,0.00013711755,0.00027288237,0.000028532992,0.00002579142],"category_scores_gemma":[0.00043727504,0.00035135675,0.00009490603,0.0011526446,0.0011114486,0.00032576823,0.0006109804,0.0013948897,0.0000042437605],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005611618,0.00050986884,0.8972848,0.0006200362,0.000043786393,0.001250645,0.00009663102,0.000002868947,0.0861684,0.0019101114,0.0016594467,0.009892241],"study_design_scores_gemma":[0.0064827474,0.00031028836,0.93327224,0.0014531619,0.0002453732,0.0155445,0.00074697356,0.014244584,0.009051843,0.013767654,0.0041118376,0.000768795],"about_ca_topic_score_codex":0.00012460681,"about_ca_topic_score_gemma":0.000022919863,"teacher_disagreement_score":0.077116564,"about_ca_system_score_codex":0.000058232363,"about_ca_system_score_gemma":0.0005180111,"threshold_uncertainty_score":0.99989384},"labels":[],"label_agreement":null},{"id":"W4200417977","doi":"10.1007/s00406-021-01363-8","title":"Cognitive and functional deficits are associated with white matter abnormalities in two independent cohorts of patients with schizophrenia","year":2021,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children","funders":"Ludwig-Maximilians-Universität München","keywords":"Schizophrenia (object-oriented programming); White matter; Psychology; Cognition; Clinical psychology; Psychiatry; Medicine; Developmental psychology; Magnetic resonance imaging","score_opus":0.03436377019830333,"score_gpt":0.3209828638814905,"score_spread":0.28661909368318716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200417977","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965932,0.000034953566,0.0012875417,0.0003636762,0.00004931376,0.00018098624,0.00004979705,0.000015961214,0.0014246042],"genre_scores_gemma":[0.9966232,0.000070949005,0.002444508,0.0007275752,0.000017102893,0.0000029034625,0.00001447214,0.000013232468,0.000086022206],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99880874,0.00016008744,0.00034183415,0.00038276467,0.0001823618,0.000124229],"domain_scores_gemma":[0.99926555,0.0002021958,0.00023339897,0.00014797355,0.00006325614,0.000087625005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012805618,0.00010591353,0.0002328393,0.00005891717,0.000057662688,0.000010495543,0.000053143212,0.00001048604,0.0000060147677],"category_scores_gemma":[0.00012308541,0.00008046059,0.000031728956,0.00017946375,0.00069719675,0.000071065464,0.00009339909,0.0002458422,3.746513e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000529251,0.00055115647,0.99817663,0.000030930885,0.0000066218768,0.000014654885,0.000038475835,0.0000073701826,0.000046975743,0.00023237026,0.00001007303,0.00035546505],"study_design_scores_gemma":[0.00231593,0.0004561507,0.99616694,0.00050195423,0.000040087798,0.000021687718,0.000081227925,0.000039758663,0.000029511893,0.00025366986,0.000009736775,0.00008331475],"about_ca_topic_score_codex":0.0000010773167,"about_ca_topic_score_gemma":0.000020262389,"teacher_disagreement_score":0.0020096852,"about_ca_system_score_codex":0.0000014806668,"about_ca_system_score_gemma":0.000051902247,"threshold_uncertainty_score":0.32810876},"labels":[],"label_agreement":null},{"id":"W4200455317","doi":"10.1101/2021.10.27.466088","title":"White matter microstructural integrity across the adult lifespan: Combined perspective of diffusion tensor and kurtosis imaging","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Canada Research Chairs; Compute Canada","keywords":"Kurtosis; Diffusion MRI; Thermal diffusivity; White matter; Fractional anisotropy; Gaussian; Diffusion; Statistical physics; Statistics; Physics; Mathematics; Medicine; Magnetic resonance imaging; Thermodynamics; Radiology","score_opus":0.01770437538986872,"score_gpt":0.2846548328734352,"score_spread":0.26695045748356644,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200455317","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867013,0.0005876567,0.0014848174,0.00961075,0.00018751342,0.00094479066,0.00024924005,0.00022651418,0.000007430962],"genre_scores_gemma":[0.9812579,0.00032829345,0.016683953,0.0013377721,0.00014224157,0.0001455991,8.4565187e-7,0.000093993986,0.000009378037],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979182,0.00008382845,0.0004587145,0.00089639175,0.000259532,0.0003833239],"domain_scores_gemma":[0.99674225,0.000072633724,0.00039770725,0.0013187926,0.0013118726,0.00015675784],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018775728,0.00044152097,0.00063087494,0.000093193295,0.00023663904,0.000145011,0.00031365122,0.00020878372,0.00002851669],"category_scores_gemma":[0.0001985802,0.00034787893,0.00018153938,0.00032860378,0.00045741347,0.00009707249,0.0008992983,0.0012904615,0.000003623671],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007502949,0.00012452796,0.5188174,0.0003249511,0.0000732498,0.000025221025,0.0001546362,0.000001053563,0.47978583,0.00034057046,0.0002738259,0.0000037039129],"study_design_scores_gemma":[0.00060047663,0.00003385545,0.89088625,0.00067335815,0.00017336136,5.8271513e-7,0.0001826645,0.00036612377,0.10657251,0.000015258212,0.00015084601,0.00034471258],"about_ca_topic_score_codex":0.0001597772,"about_ca_topic_score_gemma":0.0000025462289,"teacher_disagreement_score":0.37321332,"about_ca_system_score_codex":0.00017548323,"about_ca_system_score_gemma":0.0001617354,"threshold_uncertainty_score":0.9998973},"labels":[],"label_agreement":null},{"id":"W4200483886","doi":"10.1088/1361-6560/ac46de","title":"Biophysical compartment models for single-shell diffusion MRI in the human brain: a model fitting comparison","year":2021,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University Health Network; University of Toronto; McMaster University; University of Alberta; University of British Columbia; St. Joseph’s Healthcare Hamilton; Canadian Imperial Bank of Commerce (Canada); University of Calgary; Baycrest Hospital","funders":"National Center for Research Resources; Canadian Institutes of Health Research","keywords":"Diffusion MRI; Markov chain Monte Carlo; Fractional anisotropy; Weighting; Computer science; Bayesian probability; Isotropy; Algorithm; Artificial intelligence; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.537934954370117,"score_gpt":0.4927854029736477,"score_spread":0.045149551396469256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200483886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6432585,0.00026679732,0.31196415,0.042094987,0.000029846404,0.0008196175,0.000011811283,0.000049552586,0.0015047442],"genre_scores_gemma":[0.9892733,0.000081198654,0.0063333986,0.0038634737,0.00018222064,0.000100472236,0.0001378159,0.000009535932,0.00001855915],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991877,0.00004224556,0.00025306083,0.00027757775,0.00006037653,0.00017904695],"domain_scores_gemma":[0.9993716,0.00028039014,0.000061707135,0.00021328931,0.00004138021,0.000031626336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001454405,0.00011114084,0.00034469817,0.000035655292,0.00007081232,0.000003863194,0.0000735537,0.000042479434,0.0000011535643],"category_scores_gemma":[0.000029232791,0.00007256234,0.000035195542,0.00016967664,0.0001629548,0.000023953608,0.000054651406,0.00021551819,2.1476335e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044838787,0.0013910151,0.0051510422,0.000110951754,0.000011461301,0.000008012976,0.001678326,0.0018706622,0.77541214,0.20459579,0.0028161479,0.0069095874],"study_design_scores_gemma":[0.002212421,0.0005140695,0.000624536,0.0002054913,0.00004162342,0.000015897716,0.0005837663,0.68095505,0.0040933974,0.30798954,0.0026284622,0.00013572357],"about_ca_topic_score_codex":0.000015508667,"about_ca_topic_score_gemma":0.000007731842,"teacher_disagreement_score":0.7713188,"about_ca_system_score_codex":0.000021798178,"about_ca_system_score_gemma":0.000015274038,"threshold_uncertainty_score":0.2959006},"labels":[],"label_agreement":null},{"id":"W4200493340","doi":"10.1101/2021.12.07.471599","title":"Enabling complex fibre geometries using 3D printed axon-mimetic phantoms","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Imaging phantom; Diffusion MRI; Orientation (vector space); Curvature; Kurtosis; Ground truth; Thermal diffusivity; Physics; Geometry; Nuclear magnetic resonance; Materials science; Artificial intelligence; Mathematics; Optics; Computer science; Magnetic resonance imaging; Statistics","score_opus":0.08271906865514647,"score_gpt":0.3199696242514774,"score_spread":0.23725055559633093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200493340","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8435358,0.0018817639,0.15018012,0.00058609835,0.00038270507,0.0016113293,0.00016894723,0.0016334181,0.000019804596],"genre_scores_gemma":[0.7768157,0.00042959454,0.22156662,0.0004596463,0.00036233035,0.00015886719,0.0000031404136,0.0001956815,0.000008421777],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99651015,0.0000726961,0.0007667719,0.001417877,0.00051953725,0.0007129631],"domain_scores_gemma":[0.9959313,0.00012281287,0.0005250293,0.0020945666,0.0009499328,0.0003763607],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033146987,0.00069639325,0.001019496,0.0006174289,0.0002873792,0.00027529706,0.00046606894,0.00042164113,0.000115713425],"category_scores_gemma":[0.0005342555,0.00076195644,0.00028283536,0.0015414977,0.00024160524,0.00016799853,0.0009530355,0.0012494023,0.000016432941],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027811358,0.00023012915,0.003997615,0.0007425771,0.00014919021,0.00017738127,0.000006947187,0.00010646024,0.99428385,0.00016115136,0.000100361,0.000016520411],"study_design_scores_gemma":[0.0010652149,0.00010748188,0.04187515,0.0027996781,0.0007161724,0.0000012535861,0.00001557191,0.011178511,0.9211831,0.000007678104,0.019589558,0.0014605956],"about_ca_topic_score_codex":0.000050829407,"about_ca_topic_score_gemma":4.858948e-7,"teacher_disagreement_score":0.07310072,"about_ca_system_score_codex":0.00040937733,"about_ca_system_score_gemma":0.00072225626,"threshold_uncertainty_score":0.99948317},"labels":[],"label_agreement":null},{"id":"W4200493474","doi":"10.1101/2021.12.17.473211","title":"Amyloid-PET of the white matter: relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Université de Montréal; Hotchkiss Brain Institute; Université Laval; University of Calgary; Sunnybrook Health Science Centre; Jewish General Hospital; Baycrest Hospital; McGill University; Montreal Heart Institute; University of British Columbia; Western University; University of Toronto; Université de Sherbrooke; McMaster University; Montreal Neurological Institute and Hospital; Lawson Health Research Institute","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Free water; Diffusion MRI; Positron emission tomography; Hyperintensity; Neuroscience; Psychology; Alzheimer's disease; Pathology; Medicine; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.023179154392127223,"score_gpt":0.2449430478635914,"score_spread":0.22176389347146416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200493474","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956892,0.00010954911,0.0009827297,0.0018761294,0.000036377416,0.0010709976,0.00017327991,0.00005759591,0.000004122353],"genre_scores_gemma":[0.9827841,0.000026888289,0.016576312,0.0003388802,0.000019234449,0.00020181334,0.0000031102259,0.00004570078,0.000003943666],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99883634,0.000056360044,0.00027324882,0.00049054663,0.00016820699,0.00017532456],"domain_scores_gemma":[0.99864805,0.00002526,0.00012494157,0.0008107255,0.0002367198,0.00015429077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012558211,0.00021464696,0.00025436346,0.00012514918,0.00006940416,0.000050608945,0.00014699313,0.00006998503,0.000015744501],"category_scores_gemma":[0.0000906784,0.00015938439,0.00003250526,0.00020158965,0.000096231706,0.000062305444,0.0005633512,0.0005026584,0.000002030294],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006406126,0.00016156261,0.98880506,0.00039098406,0.000027028975,0.0000070138335,0.000011438711,0.0000071412132,0.0104088,0.000050021932,0.00006543155,0.0000014793884],"study_design_scores_gemma":[0.00066421635,0.000025797866,0.9882087,0.0010590055,0.00021379323,2.5418174e-8,0.0000016953713,0.00001997769,0.00949628,0.00001736806,0.000113361784,0.00017973995],"about_ca_topic_score_codex":0.000015651998,"about_ca_topic_score_gemma":0.0000039631905,"teacher_disagreement_score":0.015593582,"about_ca_system_score_codex":0.00004225458,"about_ca_system_score_gemma":0.000084474355,"threshold_uncertainty_score":0.6499507},"labels":[],"label_agreement":null},{"id":"W4200552231","doi":"10.31234/osf.io/7xcun","title":"Sex- and age-specific associations between cardiometabolic risk and white matter brain age in the UK Biobank cohort","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Universitetet i Oslo; Wellcome Trust; British Heart Foundation; Academy of Medical Sciences; Diabetes UK; Alzheimer's Society","keywords":"Demography; Body mass index; Cohort; Waist–hip ratio; Risk factor; Menopause; Obesity; Medicine; Gerontology; Waist; Psychology; Internal medicine","score_opus":0.05854564324355751,"score_gpt":0.3373226994688593,"score_spread":0.2787770562253018,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200552231","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94836926,0.0011508062,0.021458913,0.015937565,0.000059699894,0.002195812,0.00049605535,0.00020703752,0.010124862],"genre_scores_gemma":[0.9793076,0.0030778043,0.012761621,0.002063451,0.00022049605,0.00027976758,0.0007246435,0.000042153897,0.0015224861],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998426,0.00016115313,0.00035017045,0.00061988126,0.00022323497,0.00021952014],"domain_scores_gemma":[0.99867487,0.0002559272,0.00014641273,0.0008002284,0.00004706297,0.00007548801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055206014,0.00024105578,0.0006526975,0.00019176798,0.00011825765,0.00015257378,0.00015047751,0.00018116541,0.000044086682],"category_scores_gemma":[0.000057266592,0.0001863026,0.00010211738,0.00031686033,0.000126748,0.000032439184,0.00039948267,0.00094499404,0.0000042356146],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000012575065,0.000025161753,0.9878635,0.000025925976,0.000058227262,0.000040385567,0.00040760494,0.0000028053544,0.00008287992,0.000120793404,0.008859859,0.0025116208],"study_design_scores_gemma":[0.00022368584,0.000009125694,0.9785686,0.000046828987,0.00018650672,0.000019695319,0.00012385035,0.000008368911,0.000048917853,0.0020564299,0.018531872,0.00017612691],"about_ca_topic_score_codex":0.00021352973,"about_ca_topic_score_gemma":0.00006139419,"teacher_disagreement_score":0.030938327,"about_ca_system_score_codex":0.000048473565,"about_ca_system_score_gemma":0.000030215286,"threshold_uncertainty_score":0.75971997},"labels":[],"label_agreement":null},{"id":"W4200578182","doi":"10.1101/2021.12.17.472836","title":"Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; Massachusetts General Hospital","keywords":"Human Connectome Project; Tractography; Computer science; Diffusion MRI; Robustness (evolution); Connectome; Artificial intelligence; Voxel; Data mining; Pattern recognition (psychology); Functional connectivity; Neuroscience; Magnetic resonance imaging; Psychology","score_opus":0.08035216910427097,"score_gpt":0.3338652420559231,"score_spread":0.25351307295165215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200578182","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26632,0.005800159,0.7201609,0.0036617692,0.00049477065,0.0022667865,0.0005686343,0.00072208775,0.000004868084],"genre_scores_gemma":[0.33816898,0.0011543623,0.6575844,0.0011535488,0.00074726564,0.0009878271,0.000014769641,0.00018429967,0.0000045009965],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9965525,0.00027215588,0.00071979157,0.0016609739,0.00029963764,0.0004949185],"domain_scores_gemma":[0.9952262,0.0010159941,0.0005355698,0.0024875198,0.00044157202,0.00029312476],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003588453,0.00069712964,0.0009222333,0.00012458043,0.00036965887,0.00019036437,0.00068031444,0.0005988183,0.000032315977],"category_scores_gemma":[0.0006244699,0.0005897763,0.00039612944,0.00029769272,0.0001440048,0.00012791948,0.00083169504,0.0013969681,0.000009241279],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000454703,0.00043549133,0.0003784813,0.0001326913,0.00016304864,0.000045417106,0.00009156896,0.000031191506,0.99781287,0.00039312412,0.0003454867,0.00012518332],"study_design_scores_gemma":[0.003964682,0.00017860702,0.1509869,0.003074466,0.00089965726,1.02425204e-7,0.00011839088,0.06105079,0.62110996,0.00017705359,0.15624395,0.0021954242],"about_ca_topic_score_codex":0.00015709022,"about_ca_topic_score_gemma":0.0000048894613,"teacher_disagreement_score":0.37670287,"about_ca_system_score_codex":0.00024502957,"about_ca_system_score_gemma":0.000404843,"threshold_uncertainty_score":0.99965537},"labels":[],"label_agreement":null},{"id":"W4200585223","doi":"10.1002/hbm.25697","title":"Prevalence of white matter pathways coming into a single white matter voxel orientation: The bottleneck issue in tractography","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":104,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Mental Health; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; White matter; Voxel; Diffusion MRI; Neuroscience; Bottleneck; Human brain; Human Connectome Project; Orientation (vector space); Computer science; Artificial intelligence; Psychology; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging; Medicine; Mathematics; Geometry","score_opus":0.05801554952653782,"score_gpt":0.32155955402790426,"score_spread":0.26354400450136645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200585223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91579556,0.00025214406,0.037030507,0.039088845,0.000064688036,0.0007880221,0.000015141108,0.00012982187,0.0068352856],"genre_scores_gemma":[0.973216,0.000012600112,0.01705952,0.0077614626,0.00008753686,0.00009810456,0.0000240541,0.000033301276,0.0017074288],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99877006,0.000070030444,0.00040650985,0.0003594426,0.00018133558,0.00021260564],"domain_scores_gemma":[0.9990414,0.00010041849,0.00015921601,0.0005580836,0.000094879106,0.000046050187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019714804,0.0001476405,0.00021747903,0.00014777109,0.00023648351,0.000026972726,0.00015356112,0.000047215024,0.0006989657],"category_scores_gemma":[0.00003057061,0.00013142754,0.00009441923,0.00047149629,0.00013238507,0.00011828142,0.00011865301,0.0002545671,0.000025508692],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009801042,0.00019756114,0.71885705,0.0006643007,0.000013103507,0.000026696389,0.0066144615,0.000022426811,0.26179358,0.00058243633,0.010880917,0.00033767114],"study_design_scores_gemma":[0.0004794862,0.000041928182,0.9751759,0.0007351726,0.000027151513,0.000056762794,0.001006373,0.00009866221,0.0034436013,0.0036311497,0.015127607,0.00017621617],"about_ca_topic_score_codex":0.0000074651466,"about_ca_topic_score_gemma":0.000007260143,"teacher_disagreement_score":0.25834998,"about_ca_system_score_codex":0.000036950314,"about_ca_system_score_gemma":0.000021424825,"threshold_uncertainty_score":0.7653184},"labels":[],"label_agreement":null},{"id":"W4205229274","doi":"10.1002/alz.051360","title":"Analysis of brain structural connectivity networks and white matter integrity in patients with mild cognitive impairment","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cognitive impairment; White matter; Fractional anisotropy; Diffusion MRI; Cognition; Psychology; Medicine; Nuclear medicine; Internal medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.02606042901082808,"score_gpt":0.31049336192514965,"score_spread":0.2844329329143216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205229274","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945324,0.000869665,0.0034033423,0.0007305468,0.000010401107,0.00033321054,0.000037183523,0.000018299776,0.000064936416],"genre_scores_gemma":[0.99644744,0.000008538023,0.0026043204,0.00070213684,0.000006066289,0.000025320467,0.00019276126,0.000010143936,0.000003286278],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992659,0.00004080221,0.00018059777,0.00026752992,0.00010914386,0.00013603942],"domain_scores_gemma":[0.9994993,0.000055753684,0.00008532658,0.00018166073,0.00012898612,0.00004895229],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060693845,0.000106402564,0.00025865255,0.00009616721,0.00003192587,0.000008408187,0.00003063952,0.00003263151,0.00013010675],"category_scores_gemma":[0.000008012777,0.00008917799,0.000048355305,0.00046766785,0.00007132808,0.00006152668,0.000062438114,0.00016404851,6.459278e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009344053,0.00012198808,0.99403375,0.000003382727,0.0037765352,0.0000035470966,0.000052302887,0.000025574353,0.000019506928,0.000019692641,0.00013912484,0.0017111399],"study_design_scores_gemma":[0.0009639691,0.000097314725,0.98541504,0.000034081622,0.011270122,0.0000017672706,0.0000364898,0.0012204506,0.0008172745,0.00003673469,0.000018889506,0.000087880195],"about_ca_topic_score_codex":0.000038094735,"about_ca_topic_score_gemma":0.000075330056,"teacher_disagreement_score":0.0086187385,"about_ca_system_score_codex":0.000005072517,"about_ca_system_score_gemma":0.000016354275,"threshold_uncertainty_score":0.36365733},"labels":[],"label_agreement":null},{"id":"W4205515100","doi":"10.31979/etd.w5fp-ccq6","title":"Prediction of Financial Capacity using Diffusion Compartment Imaging","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Eisai; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Cingulum (brain); Neuropsychology; Magnetic resonance imaging; Psychology; Cardiology; Orientation (vector space); Dementia; Cognition; Medicine; Neuroscience; Audiology; Cognitive psychology; Fractional anisotropy; Internal medicine; Disease; Radiology; Mathematics","score_opus":0.10866506152888376,"score_gpt":0.3604616811346808,"score_spread":0.251796619605797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205515100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9725154,0.00019219313,0.020047378,0.00009213239,0.00025738307,0.00060024526,0.00007430426,0.00017604759,0.0060449373],"genre_scores_gemma":[0.9446202,0.00017283409,0.049453195,0.00018632268,0.00019065938,0.000057062145,0.0027587893,0.000049886024,0.002511078],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990666,0.000012297017,0.0003231054,0.00027445468,0.00020636464,0.00011719622],"domain_scores_gemma":[0.999257,0.000013746449,0.0001910568,0.00028489737,0.00020295435,0.000050294442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000040770108,0.00015143605,0.0003190852,0.000095683245,0.00007354991,0.0000063866783,0.000045459507,0.000079636564,0.000080468606],"category_scores_gemma":[0.00003527068,0.00014573579,0.0001169945,0.00015324545,0.000026960275,0.000038006303,0.000019033863,0.00022422898,9.581532e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016046835,0.000942356,0.024653433,0.0011264778,0.000035215468,0.000027211574,0.00043279855,0.000026527501,0.9490884,0.0040428857,0.0037792888,0.015684925],"study_design_scores_gemma":[0.0018516688,0.00018620511,0.3377302,0.003346191,0.0009973984,0.00018585434,0.00059747265,0.023874333,0.60878766,0.0028300907,0.019018155,0.00059476646],"about_ca_topic_score_codex":0.000073635536,"about_ca_topic_score_gemma":0.000011556979,"teacher_disagreement_score":0.34030074,"about_ca_system_score_codex":0.0000792795,"about_ca_system_score_gemma":0.00012335923,"threshold_uncertainty_score":0.5942933},"labels":[],"label_agreement":null},{"id":"W4205639396","doi":"10.3389/fnins.2021.799576","title":"Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure","year":2022,"lang":"en","type":"review","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":233,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Research Manitoba; Health Sciences Centre Foundation","keywords":"Diffusion MRI; White matter; Fractional anisotropy; Context (archaeology); Voxel; Thermal diffusivity; Neuroscience; Population; Tractography; Psychology; Medicine; Computer science; Artificial intelligence; Physics; Magnetic resonance imaging; Biology; Radiology","score_opus":0.041825050475849765,"score_gpt":0.3434758084675319,"score_spread":0.3016507579916821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205639396","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08408033,0.7864976,0.11045896,0.00073223724,0.007871162,0.007242525,0.0023728171,0.00022321097,0.00052117516],"genre_scores_gemma":[0.009881968,0.950852,0.03828316,0.0004257685,0.0001658744,0.00006784599,0.00007265015,0.000106776795,0.00014397793],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977504,0.0001329877,0.00059101696,0.00076106476,0.00045147334,0.0003130511],"domain_scores_gemma":[0.9987312,0.00004627259,0.0006133039,0.0004632779,0.000030798394,0.000115164905],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013773474,0.00033397262,0.0011370744,0.00047336088,0.00014702987,0.000023071685,0.00037228627,0.00014350718,0.00007248441],"category_scores_gemma":[0.00008758631,0.00031444716,0.00026454424,0.000743259,0.00081382005,0.00014218356,0.0004326663,0.00060905254,3.144875e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008961096,0.0025663578,0.34603474,0.025743937,0.00018308965,0.0005110209,0.00030103765,0.00013603232,0.04061575,0.00047323207,0.013380866,0.56915784],"study_design_scores_gemma":[0.002315631,0.00057039014,0.09039853,0.0029579417,0.0013109173,0.0033747423,0.00006257182,0.0025402666,0.00023413621,0.001828885,0.8930583,0.0013477083],"about_ca_topic_score_codex":0.000040261068,"about_ca_topic_score_gemma":4.9441957e-7,"teacher_disagreement_score":0.8796774,"about_ca_system_score_codex":0.00012912329,"about_ca_system_score_gemma":0.00028473506,"threshold_uncertainty_score":0.99993074},"labels":[],"label_agreement":null},{"id":"W4205716735","doi":"10.1002/alz.051190","title":"White matter microstructure and cognitive functioning across healthy older adults with different APOE alleles","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Apolipoprotein E; Fractional anisotropy; White matter; Psychology; Diffusion MRI; Cognition; Episodic memory; Alzheimer's Disease Neuroimaging Initiative; Medicine; Internal medicine; Neuroscience; Disease; Cognitive impairment; Magnetic resonance imaging","score_opus":0.024305911436220465,"score_gpt":0.31245738016338737,"score_spread":0.2881514687271669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205716735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9619833,0.021676827,0.010710362,0.004506575,0.000059362806,0.0006146574,0.000061488834,0.00013676818,0.00025061917],"genre_scores_gemma":[0.98856014,0.00012760585,0.007024965,0.003831197,0.000056885165,0.000093361086,0.00021085757,0.00003570311,0.000059294896],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999023,0.000018308607,0.00016464034,0.00041625026,0.00011965614,0.00025809836],"domain_scores_gemma":[0.99944544,0.000022940072,0.00007404121,0.00021862214,0.00013244775,0.000106534055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000023107033,0.00017180569,0.00018891924,0.000022136846,0.00020338446,0.00004151634,0.000035589084,0.00004595834,0.00025054376],"category_scores_gemma":[0.0000032210155,0.00013694528,0.00003600083,0.00010104916,0.00009007064,0.000068892135,0.0000816275,0.00019159791,0.000012387184],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00071639224,0.00032204748,0.93821543,0.00009070434,0.003959271,0.00008755892,0.0015215967,0.0000013646443,0.002786521,0.00007813469,0.007533367,0.044687618],"study_design_scores_gemma":[0.0023793739,0.00017299343,0.9688387,0.0002646561,0.0043022004,0.00040009533,0.00082589645,0.00002690365,0.017685939,0.000053524636,0.0047901897,0.00025954083],"about_ca_topic_score_codex":0.0000077237455,"about_ca_topic_score_gemma":0.000022258002,"teacher_disagreement_score":0.044428077,"about_ca_system_score_codex":0.0000032101573,"about_ca_system_score_gemma":0.000021351005,"threshold_uncertainty_score":0.55844665},"labels":[],"label_agreement":null},{"id":"W4205861790","doi":"10.1002/alz.049730","title":"The combined influence of beta‐amyloid and vascular risk on prospective brain atrophy in clinically normal individuals","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Atrophy; Fractional anisotropy; Medicine; Cardiology; White matter; Pittsburgh compound B; Internal medicine; Hyperintensity; Cerebral amyloid angiopathy; Pathology; Psychology; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.0271120764827758,"score_gpt":0.3268977708647837,"score_spread":0.2997856943820079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205861790","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912307,0.0051935497,0.00028401,0.0023122842,0.00001831828,0.0005936412,0.000015186556,0.00004202725,0.00031023845],"genre_scores_gemma":[0.9902797,0.0008008288,0.00812811,0.0006618689,0.000016323878,0.00008081456,0.000011682784,0.00001519272,0.000005505343],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988966,0.00008353366,0.00037705488,0.00028381209,0.00019064255,0.00016832851],"domain_scores_gemma":[0.99896497,0.00028730393,0.00015972336,0.00042739822,0.00010520873,0.000055419587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033496323,0.00010995205,0.00020718269,0.00003783643,0.00010850481,0.000015057498,0.00010628508,0.000042428775,0.000008893856],"category_scores_gemma":[0.00015481241,0.000086364955,0.00006954613,0.00022549702,0.00016539788,0.000055570814,0.00012088054,0.00026643998,0.000005389079],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001198959,0.00044037314,0.9606247,0.000009528319,0.0030209986,0.000016120766,0.00019939174,0.00007180188,0.0071408967,0.006351416,0.00045603717,0.021548856],"study_design_scores_gemma":[0.0013673935,0.00045711655,0.9614714,0.00004837175,0.002558528,0.0000056108415,0.00003328127,0.000050655406,0.02605751,0.00319677,0.0046353326,0.000118057134],"about_ca_topic_score_codex":0.000026214879,"about_ca_topic_score_gemma":0.000008541827,"teacher_disagreement_score":0.0214308,"about_ca_system_score_codex":0.0000034504528,"about_ca_system_score_gemma":0.000048279842,"threshold_uncertainty_score":0.35218605},"labels":[],"label_agreement":null},{"id":"W4205927150","doi":"10.1101/2022.01.10.475656","title":"Microstructural Impairments in a Topologically Distinct Prefrontal-Habenular Connection in Cocaine Addiction","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Drug Abuse; Canadian Institutes of Health Research; Icahn School of Medicine at Mount Sinai","keywords":"Ventral tegmental area; Neuroscience; Addiction; Prefrontal cortex; Diffusion MRI; Psychology; Habenula; Internal capsule; Thalamus; Tractography; Disconnection; Ventral pallidum; White matter; Cognition; Globus pallidus; Dopamine; Basal ganglia; Medicine; Central nervous system; Dopaminergic","score_opus":0.02543391117313611,"score_gpt":0.28640703832978925,"score_spread":0.26097312715665316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205927150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9952359,0.00034276803,0.0011711466,0.0004391293,0.00039827536,0.0017167039,0.00021799111,0.00046424818,0.000013843763],"genre_scores_gemma":[0.9897603,0.00016785602,0.008605696,0.0002553601,0.00014735133,0.00097223895,0.000007533084,0.00007555312,0.000008139472],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9977057,0.00011039762,0.0005805882,0.0009294069,0.00025868817,0.00041524033],"domain_scores_gemma":[0.9985871,0.000040813888,0.00029327176,0.0008166062,0.00013011979,0.00013213897],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030687556,0.000383554,0.0005344073,0.00035091958,0.00011380604,0.00003901013,0.00024797814,0.00026312447,0.00017103003],"category_scores_gemma":[0.00021148428,0.0004089358,0.00011315367,0.00055746257,0.000103181286,0.00008685037,0.00046830694,0.0012783314,0.0000057480975],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031027527,0.0006403782,0.30029455,0.00026197426,0.000050561186,0.0005756582,0.000015152222,0.00013412611,0.69711244,0.00026708018,0.0003190569,0.000018762858],"study_design_scores_gemma":[0.0012378806,0.00021756785,0.9746593,0.00030547837,0.000059872327,5.2489406e-7,0.0000054999277,0.0008364999,0.018270502,0.0000306821,0.0039526625,0.0004235289],"about_ca_topic_score_codex":0.00020340743,"about_ca_topic_score_gemma":0.000013863839,"teacher_disagreement_score":0.6788419,"about_ca_system_score_codex":0.0010376656,"about_ca_system_score_gemma":0.0002104847,"threshold_uncertainty_score":0.99983627},"labels":[],"label_agreement":null},{"id":"W4205978437","doi":"10.3389/fnins.2021.638175","title":"Combined Structural MR and Diffusion Tensor Imaging Classify the Presence of Alzheimer’s Disease With the Same Performance as MR Combined With Amyloid Positron Emission Tomography: A Data Integration Approach","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; Fundação para a Ciência e a Tecnologia; F. Hoffmann-La Roche; University of Southern California; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Artificial intelligence; Pattern recognition (psychology); Positron emission tomography; Support vector machine; Neuroimaging; Computer science; Classifier (UML); Feature selection; Modality (human–computer interaction); Magnetic resonance imaging; Nuclear medicine; Medicine; Radiology","score_opus":0.03241276084161613,"score_gpt":0.28934658956922693,"score_spread":0.2569338287276108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205978437","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9797554,0.00021582023,0.011946424,0.0065115946,0.00007992078,0.0013330376,0.00003647032,0.000066580615,0.00005477523],"genre_scores_gemma":[0.9928997,0.000059030615,0.006021933,0.000743109,0.000008914477,0.00013336597,0.00004061955,0.000016855709,0.000076470315],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984825,0.0000965823,0.00017658355,0.00054779317,0.00047846875,0.00021805122],"domain_scores_gemma":[0.99877226,0.00004175869,0.00016958325,0.00088433106,0.000043115782,0.00008894121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020539461,0.00016167673,0.00017944258,0.00010893461,0.0005883263,0.000039169037,0.0006477175,0.000011204437,0.0000012162046],"category_scores_gemma":[0.000051418487,0.000083191284,0.000020593949,0.0007658665,0.0008082263,0.00027960853,0.00044319918,0.00042561957,2.4154135e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027073685,0.00027153647,0.94293,0.00005249385,0.000007810105,0.00002032395,0.0005868353,0.00060912344,0.043298535,0.00042507218,0.0024490221,0.00664188],"study_design_scores_gemma":[0.00083071727,0.0006641259,0.472416,0.00006766583,0.00008509445,0.00007772103,0.00066221395,0.52317595,0.0011683163,0.00019148404,0.00051938393,0.00014128289],"about_ca_topic_score_codex":0.000028499746,"about_ca_topic_score_gemma":9.4956823e-7,"teacher_disagreement_score":0.52256685,"about_ca_system_score_codex":0.00002356791,"about_ca_system_score_gemma":0.00008375291,"threshold_uncertainty_score":0.45249897},"labels":[],"label_agreement":null},{"id":"W4206092563","doi":"10.1002/alz.056416","title":"Myelin integrity in older adults with vascular cognitive impairment: Implications for mobility performance","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Positive Living Society of British Columbia; University of British Columbia; Vancouver Coastal Health","funders":"","keywords":"White matter; Myelin; Neurology; Medicine; Psychology; Magnetic resonance imaging; Nuclear medicine; Internal medicine; Audiology; Neuroscience; Radiology; Central nervous system","score_opus":0.04503786162681742,"score_gpt":0.3370960401804146,"score_spread":0.29205817855359717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206092563","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9422325,0.009195275,0.040736813,0.0036637974,0.000031787942,0.003400145,0.000111796224,0.0002055876,0.0004223337],"genre_scores_gemma":[0.96835905,0.00022894664,0.029006112,0.00058531977,0.000024656787,0.0015075186,0.00025669782,0.000024671428,0.0000070475335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99894094,0.000020161147,0.00024921034,0.00045011833,0.00009856891,0.00024101057],"domain_scores_gemma":[0.9990591,0.000059454444,0.000067561785,0.00042083816,0.00031403522,0.0000790572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012377948,0.00014457869,0.0001938954,0.000049378097,0.00010031504,0.000012391654,0.00007648407,0.00004886444,0.00005046274],"category_scores_gemma":[0.000025280762,0.0001290688,0.00007918011,0.00029102265,0.00007139627,0.000107054795,0.00005129411,0.00021267262,0.000008369024],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001054172,0.006610269,0.67475057,0.00027240562,0.0057760812,0.000023192872,0.001058341,0.000021579051,0.0041560377,0.0026581904,0.0027823544,0.30083683],"study_design_scores_gemma":[0.0038134377,0.00031817827,0.94006914,0.00035445305,0.0046853293,0.00004505633,0.00024083117,0.00069477304,0.04504095,0.00045235138,0.004002047,0.00028348397],"about_ca_topic_score_codex":0.000019244073,"about_ca_topic_score_gemma":0.000027572227,"teacher_disagreement_score":0.30055335,"about_ca_system_score_codex":0.000012049184,"about_ca_system_score_gemma":0.00010588957,"threshold_uncertainty_score":0.52632725},"labels":[],"label_agreement":null},{"id":"W4206153254","doi":"10.1101/2022.01.11.22268989","title":"Network-based spreading of grey matter changes across different stages of psychosis","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Grey matter; Psychosis; Antipsychotic; Schizophrenia (object-oriented programming); Psychology; Medicine; Psychiatry; White matter; Magnetic resonance imaging","score_opus":0.09373276968866529,"score_gpt":0.3875963083002898,"score_spread":0.2938635386116245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206153254","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842408,0.00033776573,0.009490413,0.004187566,0.00020456588,0.00082607445,0.00026731208,0.00013778653,0.00030774742],"genre_scores_gemma":[0.9915789,0.00021395429,0.00634788,0.0006969926,0.00011585402,0.0005099474,0.00011551515,0.00006280945,0.0003581914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985706,0.000049346483,0.00038152948,0.0004468934,0.00028672875,0.0002648559],"domain_scores_gemma":[0.9982842,0.00010014097,0.00044050402,0.0010202389,0.00008615722,0.00006872687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017712827,0.00024026069,0.00060840184,0.00009044231,0.000060234837,0.000007648523,0.00030603743,0.000095520605,0.00043330516],"category_scores_gemma":[0.000023037788,0.00021446985,0.0001701333,0.00015959867,0.0001166088,0.000011322943,0.00048379457,0.0005253414,0.0000019213242],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006421178,0.00021693221,0.9850282,0.0009961762,0.000046006408,0.000005321585,0.00012244101,0.00042387453,0.00909336,0.00008764999,0.0027373168,0.001178525],"study_design_scores_gemma":[0.00079880195,0.000311349,0.8978137,0.0015725184,0.0002810817,0.000007051294,0.000051012525,0.0004684621,0.08011132,0.0026380983,0.015479236,0.00046741017],"about_ca_topic_score_codex":0.00003313767,"about_ca_topic_score_gemma":0.0000070592464,"teacher_disagreement_score":0.08721452,"about_ca_system_score_codex":0.000044348784,"about_ca_system_score_gemma":0.000020880478,"threshold_uncertainty_score":0.87458265},"labels":[],"label_agreement":null},{"id":"W4206253725","doi":"10.1002/alz.058103","title":"Associations between iron deposition in the brain and grey matter volumes in cognitively unimpaired adults","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Grey matter; Magnetic resonance imaging; Voxel; Nuclear medicine; Voxel-based morphometry; Psychology; White matter; Cerebrospinal fluid; Brain size; Cohort; Medicine; Pathology; Internal medicine; Neuroscience; Radiology","score_opus":0.04714768964547058,"score_gpt":0.32440531956596186,"score_spread":0.2772576299204913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206253725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9674118,0.0030422295,0.0010468538,0.02710523,0.000013608685,0.0005711291,0.00006807507,0.00004970545,0.00069137546],"genre_scores_gemma":[0.99362206,0.00003862169,0.003354056,0.0025405677,0.00003306857,0.00006963251,0.00032096542,0.000012387103,0.0000086552445],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992637,0.00008111126,0.00019802806,0.00020752048,0.000105404084,0.00014424848],"domain_scores_gemma":[0.99959934,0.00011792183,0.00005709308,0.00014919789,0.00004782875,0.000028636638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012540091,0.000081780345,0.0001265621,0.00005596462,0.00006428962,0.000022862007,0.000048650076,0.000039443268,0.000023875351],"category_scores_gemma":[0.000028340697,0.0000738697,0.000026202082,0.00023319414,0.00003417304,0.000089653484,0.000037385937,0.00014678507,0.000013274342],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013591129,0.00017361002,0.96729386,0.0000059748604,0.00024922084,0.00003760604,0.00054586685,4.6512065e-7,0.0018904392,0.00014183526,0.0038527835,0.025794765],"study_design_scores_gemma":[0.0006213907,0.000032030694,0.99291813,0.000051713563,0.000968995,0.000014405688,0.00012285095,0.000059940827,0.0040326584,0.00046974933,0.00062808464,0.00008004377],"about_ca_topic_score_codex":0.00011587446,"about_ca_topic_score_gemma":0.00012941094,"teacher_disagreement_score":0.026210254,"about_ca_system_score_codex":0.0000071982276,"about_ca_system_score_gemma":0.000020826013,"threshold_uncertainty_score":0.3012319},"labels":[],"label_agreement":null},{"id":"W4206560698","doi":"10.1002/alz.055678","title":"Ketones and improved cognition in MCI: Links to ApoE and white matter energetics","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Cognition; White matter; Placebo; Effects of sleep deprivation on cognitive performance; Psychology; Medicine; Verbal fluency test; Audiology; Nuclear medicine; Internal medicine; Neuroscience; Neuropsychology; Magnetic resonance imaging; Radiology; Pathology","score_opus":0.04084458212425861,"score_gpt":0.31930468599660033,"score_spread":0.2784601038723417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206560698","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9012793,0.029115614,0.015634531,0.04875791,0.0001389284,0.0013263478,0.000044378776,0.00023358752,0.0034694339],"genre_scores_gemma":[0.95794684,0.00028887228,0.037559643,0.003994868,0.000031119456,0.000067554836,0.000042271648,0.0000178736,0.00005095466],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994208,0.000011726587,0.0001432061,0.00024325772,0.00005402949,0.00012693673],"domain_scores_gemma":[0.9996752,0.000014617171,0.000026120344,0.00016174825,0.000047602538,0.00007471618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038930328,0.000085911386,0.0001142104,0.000049456194,0.000037494352,0.000018776665,0.000023349885,0.00005014385,0.00006525037],"category_scores_gemma":[0.000007351939,0.00008754943,0.00001496632,0.000105160965,0.000029669163,0.00004547195,0.000080174956,0.00012296413,0.0000117030495],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011691206,0.00047132224,0.3506146,0.000068631736,0.0014931132,0.00010802251,0.0005699819,0.000004241224,0.49643022,0.00084472523,0.013570826,0.13570742],"study_design_scores_gemma":[0.0023272994,0.00024608025,0.45658776,0.000195665,0.008232477,0.00025421332,0.0001882874,0.00093006284,0.42089802,0.0032667948,0.106240235,0.0006331014],"about_ca_topic_score_codex":0.000007323476,"about_ca_topic_score_gemma":0.000012515999,"teacher_disagreement_score":0.13507432,"about_ca_system_score_codex":0.0000015687655,"about_ca_system_score_gemma":0.000011493324,"threshold_uncertainty_score":0.3570162},"labels":[],"label_agreement":null},{"id":"W4206800957","doi":"10.1101/2022.01.17.476369","title":"A Whole-Brain 3D Myeloarchitectonic Atlas: Mapping the Vogt-Vogt Legacy to the Cortical Surface","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Institute for Basic Science; Deutsche Forschungsgemeinschaft; National Alliance for Research on Schizophrenia and Depression","keywords":"Brain atlas; Atlas (anatomy); Myelin; Neuroscience; Neuroimaging; White matter; Biology; Cartography; Computer science; Magnetic resonance imaging; Anatomy; Medicine; Geography; Central nervous system","score_opus":0.049788065188359466,"score_gpt":0.29421963033638515,"score_spread":0.2444315651480257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206800957","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8173122,0.0011300643,0.04221084,0.1317471,0.00067729485,0.004959174,0.00032950958,0.0015681423,0.000065683824],"genre_scores_gemma":[0.96208906,0.00009385943,0.028768538,0.006682082,0.0005723901,0.0014429713,0.0000016913724,0.00022767272,0.000121745754],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963262,0.00030259052,0.00065037847,0.001262518,0.0006849095,0.00077340147],"domain_scores_gemma":[0.9953789,0.00043892144,0.00032086854,0.0032684882,0.0002520976,0.00034072547],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001059873,0.000592883,0.0006122685,0.00017362073,0.0008272466,0.0002589184,0.0012781007,0.00020175068,0.0001145627],"category_scores_gemma":[0.0006653688,0.0004347338,0.00026786962,0.0012093292,0.00028985442,0.000082749684,0.0019316628,0.0029828988,0.00012561596],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014615513,0.00043346456,0.0034968625,0.00041320245,0.0002866886,0.00020621205,0.00016476863,0.002054285,0.9652404,0.004740231,0.02274533,0.00007239686],"study_design_scores_gemma":[0.00058230705,0.00016347482,0.0817935,0.00049276324,0.00024651882,7.0927734e-7,0.00004494882,0.003126741,0.018418944,0.000019741663,0.8942384,0.00087193283],"about_ca_topic_score_codex":0.00005918634,"about_ca_topic_score_gemma":0.0000026748974,"teacher_disagreement_score":0.94682145,"about_ca_system_score_codex":0.0004000241,"about_ca_system_score_gemma":0.0006734197,"threshold_uncertainty_score":0.99981046},"labels":[],"label_agreement":null},{"id":"W4206984152","doi":"10.3233/jad-215390","title":"Cognitive Improvement via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Amnesic Mild Cognitive Impairment Patients","year":2022,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Neuroplasticity; Transcranial magnetic stimulation; Angular gyrus; Cognition; Cognitive impairment; Intervention (counseling); Hippocampus","score_opus":0.028464114671112827,"score_gpt":0.3009957416685747,"score_spread":0.27253162699746186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206984152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995152,0.00044459087,0.0023291428,0.00019984633,0.000099383724,0.0015324742,0.00019990193,0.000023987353,0.000018659397],"genre_scores_gemma":[0.99943966,0.00001589668,0.00010910411,0.00024320417,0.000050110433,0.00006309989,0.00004605674,0.000029274679,0.0000035962235],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981044,0.00019178963,0.0006971094,0.00024056167,0.0005709057,0.00019526297],"domain_scores_gemma":[0.99855655,0.00015918091,0.000548595,0.00015602674,0.00042242056,0.0001572449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024963717,0.0001778271,0.00032053544,0.00018445689,0.0001503337,0.000011655256,0.000111889814,0.000022693139,0.00004674891],"category_scores_gemma":[0.00006678459,0.00014164922,0.0001757795,0.00028933416,0.00009951956,0.00013318626,0.0000656666,0.0004575055,7.308071e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02732907,0.016197555,0.8505339,0.0007818239,0.0015554611,0.0020068805,0.0073949043,0.0059841643,0.050315555,0.00023649464,0.00015343401,0.037510745],"study_design_scores_gemma":[0.0053307274,0.0028894632,0.9786182,0.00063705933,0.0023894992,0.000063437255,0.00097636646,0.0036673401,0.0051522106,0.00010676537,0.000007512756,0.00016141072],"about_ca_topic_score_codex":0.00002701562,"about_ca_topic_score_gemma":0.0000010021644,"teacher_disagreement_score":0.12808429,"about_ca_system_score_codex":0.000119267635,"about_ca_system_score_gemma":0.00015736814,"threshold_uncertainty_score":0.57762873},"labels":[],"label_agreement":null},{"id":"W4210244170","doi":"10.1002/alz.056596","title":"Disintegration of anterior thalamic radiation fibers in cerebrovascular disease subjects with periventricular white matter hyperintensities leads to lower executive function performance","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Health Sciences Centre; Thunder Bay Regional Health Sciences Centre; McMaster University; Queen's University; University of Toronto; University of Ottawa; Baycrest Hospital; Robarts Clinical Trials; Sunnybrook Health Science Centre; Western University","funders":"","keywords":"Hyperintensity; White matter; Diffusion MRI; Fractional anisotropy; Cardiology; Medicine; Internal medicine; Cognitive decline; Cognition; Psychology; Magnetic resonance imaging; Disease; Radiology; Dementia; Psychiatry","score_opus":0.016608014104505017,"score_gpt":0.25779614916939525,"score_spread":0.24118813506489023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210244170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865476,0.0028333592,0.008923605,0.00087889534,0.00007162607,0.0005021496,0.000009447177,0.000043806696,0.00018952135],"genre_scores_gemma":[0.9956329,0.00011762764,0.0033900691,0.00055602234,0.000026475767,0.000096915384,0.00009875575,0.00002455479,0.00005670419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991063,0.00002675153,0.00021689432,0.00030580707,0.00018042776,0.00016381945],"domain_scores_gemma":[0.9993584,0.000008252686,0.000075781485,0.00032167416,0.00016464482,0.000071257324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004792803,0.00014108125,0.00019545869,0.000094940675,0.000046482266,0.000015480187,0.0000453546,0.000026840904,0.00013121583],"category_scores_gemma":[0.000007596409,0.00012367548,0.000073752955,0.00031178453,0.000046272035,0.00016987382,0.000033149583,0.00009392635,0.000021586991],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050030067,0.00024486444,0.9723184,0.00004704046,0.00066433346,0.000048488222,0.00030569333,0.00026406706,0.02040632,0.000048570357,0.0007021711,0.0044497396],"study_design_scores_gemma":[0.00060244603,0.00021700702,0.9307502,0.00024517544,0.0024472487,0.00003487327,0.0001741717,0.00046065886,0.06405657,0.000016577138,0.0008268144,0.00016825215],"about_ca_topic_score_codex":0.000011192597,"about_ca_topic_score_gemma":0.0000066789494,"teacher_disagreement_score":0.043650247,"about_ca_system_score_codex":0.000017529188,"about_ca_system_score_gemma":0.00004737134,"threshold_uncertainty_score":0.504334},"labels":[],"label_agreement":null},{"id":"W4210253522","doi":"10.1002/alz.057516","title":"Melatonin mediates the reversibility of brain hyperphosphorylated tau protein induced by synthetic torpor in rats","year":2021,"lang":"en","type":"article","venue":"Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Melatonin; Torpor; Hypothermia; Tau protein; Neuroprotection; Microtubule; Hippocampal formation; Internal medicine; Hyperphosphorylation; Hibernation (computing); Chemistry; Endocrinology; Neuroscience; Biology; Cell biology; Medicine; Kinase; Alzheimer's disease; Thermoregulation","score_opus":0.026989462709062443,"score_gpt":0.2679016563641245,"score_spread":0.24091219365506206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210253522","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9753019,0.00037877762,0.0005688922,0.013168242,0.00005438736,0.0010053405,0.00014537465,0.00011349665,0.009263578],"genre_scores_gemma":[0.98960626,0.00015320715,0.0018901741,0.00041919478,0.000018129336,0.000048055346,0.0001162559,0.000029732853,0.0077189677],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99805176,0.00019347134,0.00038936397,0.0006359774,0.0003325864,0.00039681685],"domain_scores_gemma":[0.99851614,0.0003087701,0.00018619142,0.00069949834,0.00017161839,0.000117795804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002779312,0.00026716298,0.00047897373,0.0001301396,0.00020764045,0.000011608654,0.00033512124,0.00010214935,0.00008986303],"category_scores_gemma":[0.00015892247,0.00022440524,0.0001406324,0.00060661824,0.00037618808,0.00010372713,0.0004074184,0.000427339,0.000019083518],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048324364,0.001416293,0.031065376,0.00023268025,0.00024089318,0.0006798073,0.0010343901,0.00006116528,0.9185028,0.037657935,0.00695285,0.0016725658],"study_design_scores_gemma":[0.00431888,0.0006693093,0.18430392,0.00083335885,0.00049028255,0.00040759947,0.0022348075,0.0008824228,0.73229474,0.005496877,0.0668994,0.0011683919],"about_ca_topic_score_codex":0.00005595804,"about_ca_topic_score_gemma":0.000035042813,"teacher_disagreement_score":0.18620804,"about_ca_system_score_codex":0.00016692364,"about_ca_system_score_gemma":0.00022010347,"threshold_uncertainty_score":0.915098},"labels":[],"label_agreement":null},{"id":"W4210319484","doi":"10.1002/alz.054719","title":"The relationship between brain‐age association and prediction: The impact of parameter selection","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Smoothing; Correlation; Brain atlas; Neuroimaging; Psychology; Pattern recognition (psychology); Artificial intelligence; Mathematics; Statistics; Neuroscience; Computer science","score_opus":0.09597595793657968,"score_gpt":0.3752855147917894,"score_spread":0.27930955685520975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210319484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9497792,0.014742385,0.00973242,0.023207102,0.00009228788,0.0009807717,0.00005740584,0.00021178098,0.0011966211],"genre_scores_gemma":[0.99797034,0.00007608008,0.0015957201,0.000106056475,0.00007825514,0.00003907069,0.000043434764,0.000010096579,0.00008095393],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993732,0.00006676809,0.00018633093,0.00013186623,0.00013151862,0.00011033399],"domain_scores_gemma":[0.998632,0.0009111078,0.000121653975,0.00020347055,0.000100863974,0.000030881893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002320251,0.00006604396,0.00008954975,0.000018050763,0.0002643864,0.000027837554,0.000042424508,0.0000423135,0.000012927903],"category_scores_gemma":[0.00032953522,0.000041108375,0.00007025133,0.00021803619,0.00004684379,0.00006149517,0.000030248611,0.00016603754,0.0000027532042],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006835386,0.000021391512,0.9820621,0.0000013939565,0.0012713901,5.54445e-7,0.0000417991,0.0000035706998,0.0012734965,0.00072838744,0.008504278,0.0060847723],"study_design_scores_gemma":[0.00017618049,0.00006486021,0.98323953,0.000008722399,0.0024171057,0.0000132279165,0.000013324796,0.00011064817,0.004104396,0.0034330413,0.0063814074,0.00003757478],"about_ca_topic_score_codex":0.000019693029,"about_ca_topic_score_gemma":0.000004253828,"teacher_disagreement_score":0.048191108,"about_ca_system_score_codex":0.000013890188,"about_ca_system_score_gemma":0.000039493876,"threshold_uncertainty_score":0.20334733},"labels":[],"label_agreement":null},{"id":"W4210405032","doi":"10.1002/alz.053965","title":"The role of Alzheimer’s disease pathology in frontotemporal dementia related syndromes","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute; Occupational Cancer Research Centre; University of Toronto","funders":"","keywords":"Progressive supranuclear palsy; Frontotemporal lobar degeneration; Frontotemporal dementia; Fractional anisotropy; Psychology; Default mode network; Corticobasal degeneration; Diffusion MRI; Biomarker; Boston Naming Test; Pathology; Dementia; Medicine; Neuroscience; Disease; Magnetic resonance imaging; Cognition; Radiology","score_opus":0.044343327790258937,"score_gpt":0.324316545520545,"score_spread":0.27997321773028605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210405032","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1206467,0.86663616,0.0005417577,0.007593539,0.00021676479,0.0010721309,0.00007505727,0.00023477273,0.0029831256],"genre_scores_gemma":[0.9913221,0.0010026739,0.0071594445,0.00018927846,0.000018673118,0.00007215691,0.00018732074,0.000030852003,0.000017493194],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99851906,0.00008673112,0.0004939654,0.0004289523,0.00018969011,0.0002816147],"domain_scores_gemma":[0.9984766,0.00005377552,0.0001628755,0.001105277,0.000090383575,0.00011104347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021252343,0.00015153935,0.00025127272,0.000055754823,0.00011037472,0.000013529992,0.00025458288,0.00005610867,0.00011019065],"category_scores_gemma":[0.00004757932,0.00012675521,0.000088676104,0.00025660935,0.00015103807,0.00009873771,0.00028466134,0.00019811551,0.00002272021],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023528363,0.0015728332,0.66581875,0.00002045026,0.016964763,0.0013081921,0.00027097246,0.000026828495,0.02878432,0.021335786,0.0074886302,0.25617316],"study_design_scores_gemma":[0.0028934767,0.00022089617,0.6139141,0.00017566781,0.05461979,0.00037528845,0.00042270377,0.0031892457,0.06357408,0.039317522,0.22054857,0.0007487094],"about_ca_topic_score_codex":0.000032910528,"about_ca_topic_score_gemma":0.000023414861,"teacher_disagreement_score":0.8706754,"about_ca_system_score_codex":0.0000037115876,"about_ca_system_score_gemma":0.00012869379,"threshold_uncertainty_score":0.51689273},"labels":[],"label_agreement":null},{"id":"W4210406453","doi":"10.1002/mp.15495","title":"Learning white matter subject‐specific segmentation from structural MRI","year":2022,"lang":"en","type":"article","venue":"Medical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Tractography; Artificial intelligence; Computer science; Segmentation; Diffusion MRI; Human Connectome Project; Deep learning; Convolutional neural network; Context (archaeology); Voxel; Pattern recognition (psychology); Connectome; White matter; Magnetic resonance imaging; Psychology; Neuroscience; Medicine; Radiology","score_opus":0.031295192215812576,"score_gpt":0.32322768654696477,"score_spread":0.2919324943311522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210406453","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6551044,0.00011229574,0.32516524,0.014862439,0.00027934017,0.0005659369,0.000038917584,0.0005259346,0.0033455163],"genre_scores_gemma":[0.99121594,0.000022337459,0.0046841153,0.00257496,0.00037279652,0.0000893942,0.00037449802,0.000027940134,0.0006380256],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989495,0.000036165566,0.0001459329,0.00023475428,0.00048988813,0.00014370475],"domain_scores_gemma":[0.99957836,0.0000458384,0.000057945952,0.00019752981,0.000020225963,0.000100075755],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000059221966,0.00008871185,0.00013186966,0.00001908319,0.00021165791,0.000009741769,0.00010408254,0.000021969374,0.0033607392],"category_scores_gemma":[0.000009989263,0.00008395167,0.000052041793,0.00016553377,0.00005762405,0.000045196262,0.0001158839,0.00057178846,0.000058915484],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001840469,0.00035447776,0.7373455,0.00004433492,0.000065825894,0.00014920159,0.0018844657,0.000993098,0.013388175,0.0011251305,0.11114168,0.13332407],"study_design_scores_gemma":[0.0063312277,0.0010838817,0.41474867,0.00016022036,0.00025366203,0.00030056998,0.0015415956,0.02219462,0.04212564,0.09486657,0.41500267,0.0013906687],"about_ca_topic_score_codex":0.000014397197,"about_ca_topic_score_gemma":2.9467023e-7,"teacher_disagreement_score":0.33611155,"about_ca_system_score_codex":0.000067954425,"about_ca_system_score_gemma":0.00002918643,"threshold_uncertainty_score":0.9975503},"labels":[],"label_agreement":null},{"id":"W4210439792","doi":"10.3389/fnagi.2021.760663","title":"Tract Specific White Matter Lesion Load Affects White Matter Microstructure and Their Relationships With Functional Connectivity and Cognitive Decline","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"White matter; Hyperintensity; Cognition; Diffusion MRI; Psychology; Cognitive decline; Audiology; Neuropsychology; Effects of sleep deprivation on cognitive performance; Neuroscience; Cardiology; Internal medicine; Medicine; Magnetic resonance imaging; Dementia; Disease; Radiology","score_opus":0.03774630673990567,"score_gpt":0.2767593812260608,"score_spread":0.23901307448615514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210439792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8773604,0.00019982026,0.115667254,0.005864997,0.00017037593,0.00045288826,0.000042058393,0.000059757673,0.00018243263],"genre_scores_gemma":[0.9908076,0.000028607046,0.0056619095,0.0030113081,0.000023745311,0.00005599559,0.000011776991,0.000021875534,0.00037718588],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99880946,0.00009158385,0.000121208264,0.00056938303,0.00020061257,0.00020773844],"domain_scores_gemma":[0.99953777,0.00008890086,0.0000851182,0.00018353158,0.00002855754,0.000076150856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021990346,0.00015783524,0.0001775178,0.00015384743,0.00047231448,0.000048423823,0.00007491024,0.000025331386,0.000024076691],"category_scores_gemma":[0.000028241415,0.00013170067,0.000020422682,0.00041030266,0.0003206388,0.00018310554,0.00014801479,0.00058550376,8.6190903e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000092121016,0.000048946087,0.99004334,0.000015970674,0.000001064163,0.00001983098,0.00022924929,0.00008735569,0.005584467,0.000010210493,0.0034152293,0.0004522218],"study_design_scores_gemma":[0.0005710172,0.00009042638,0.9935323,0.000049241004,0.000011755723,0.000691808,0.00026438033,0.0011250261,0.00038754582,0.0005411105,0.0025960323,0.00013934291],"about_ca_topic_score_codex":0.0000017876908,"about_ca_topic_score_gemma":0.0000014543376,"teacher_disagreement_score":0.113447174,"about_ca_system_score_codex":0.000062141546,"about_ca_system_score_gemma":0.00003665927,"threshold_uncertainty_score":0.5370597},"labels":[],"label_agreement":null},{"id":"W4210500523","doi":"10.1007/s12975-022-00988-8","title":"Normal-Appearing White Matter Deteriorates over the Year After an Ischemic Stroke and Is Associated with Global Cognition","year":2022,"lang":"en","type":"article","venue":"Translational Stroke Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"White matter; Fractional anisotropy; Medicine; Diffusion MRI; Montreal Cognitive Assessment; Hyperintensity; Cardiology; Cognition; Neurology; Confounding; Internal medicine; Stroke (engine); Effects of sleep deprivation on cognitive performance; Magnetic resonance imaging; Cognitive impairment; Psychiatry; Radiology","score_opus":0.07415460791681681,"score_gpt":0.38086795688106484,"score_spread":0.306713348964248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210500523","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889716,0.000073736315,0.0010473954,0.0038831164,0.000005041295,0.00044790324,0.0005967075,0.00004907368,0.0049254484],"genre_scores_gemma":[0.99662864,0.000009479544,0.0014772819,0.00042872556,0.000034152516,0.00023839923,0.00011046945,0.000017492568,0.0010553598],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987414,0.000078869416,0.00011552913,0.00023846402,0.00058990996,0.00023586639],"domain_scores_gemma":[0.99956465,0.00006147741,0.00002687186,0.00016548553,0.00010982774,0.000071693765],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00028177025,0.000084226645,0.00009159443,0.00005630978,0.00035204078,0.000044321394,0.00008669379,0.000026922027,0.0012466],"category_scores_gemma":[0.0000056559165,0.00006563854,0.000029543517,0.00023793745,0.00014515269,0.000121715886,0.000054538486,0.00042154265,0.000012077903],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006014485,0.0001387463,0.9878854,0.000016710366,0.000060251772,0.000014104588,0.00026371176,0.000028069166,0.0073520695,0.000117590134,0.0019562736,0.0015656141],"study_design_scores_gemma":[0.00087444414,0.00023463966,0.99060875,0.000025803443,0.00004366613,0.000044208926,0.00013573334,0.0014374009,0.0005785103,0.00036868302,0.005545455,0.00010270268],"about_ca_topic_score_codex":0.000018664476,"about_ca_topic_score_gemma":0.00001368728,"teacher_disagreement_score":0.007657062,"about_ca_system_score_codex":0.00005372764,"about_ca_system_score_gemma":0.0000553517,"threshold_uncertainty_score":0.9996664},"labels":[],"label_agreement":null},{"id":"W4210549501","doi":"10.1002/alz.052413","title":"Sparse canonical correlation analysis reveals relationships between TDP‐43 within the entorhinal cortex and fractional anisotropy across widespread white matter tracts","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Fractional anisotropy; Entorhinal cortex; Alzheimer's Disease Neuroimaging Initiative; Dementia; Neuropathology; Diffusion MRI; Correlation; Psychology; Betweenness centrality; Neuroscience; Nuclear medicine; Medicine; Biology; Pathology; Disease; Magnetic resonance imaging; Mathematics; Statistics; Hippocampus; Radiology","score_opus":0.08395536839006018,"score_gpt":0.35662408367163384,"score_spread":0.27266871528157366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210549501","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8768579,0.006001527,0.101363674,0.013582888,0.00016880462,0.00081132527,0.00016770145,0.00020060585,0.0008456263],"genre_scores_gemma":[0.9798918,0.00004253251,0.018517293,0.00069888076,0.0001169467,0.00005816942,0.00045060477,0.00002612971,0.00019768921],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99838364,0.00013651358,0.00047059503,0.0004559469,0.00031058205,0.00024273922],"domain_scores_gemma":[0.9986592,0.00026161893,0.00026034485,0.0005096461,0.00016095718,0.00014821417],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034393434,0.00017947835,0.00028377533,0.000063915,0.0004626285,0.00007900187,0.00009709004,0.000103792154,0.0003051746],"category_scores_gemma":[0.000072807234,0.00015133694,0.00013154137,0.0005451719,0.00013977174,0.00021305491,0.00008615632,0.0005232495,0.0000679978],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026736558,0.00007570851,0.9905862,0.0000030956755,0.0034975756,0.000015362823,0.00020006036,0.00009748731,0.001783523,0.000935082,0.0022716348,0.0005075256],"study_design_scores_gemma":[0.00032977847,0.000029742816,0.9714564,0.000019777168,0.019886857,0.000077179684,0.00010209323,0.0006689574,0.0013899249,0.0010688013,0.004819177,0.00015132382],"about_ca_topic_score_codex":0.000044061562,"about_ca_topic_score_gemma":0.00006457875,"teacher_disagreement_score":0.10303391,"about_ca_system_score_codex":0.00001625178,"about_ca_system_score_gemma":0.00007894506,"threshold_uncertainty_score":0.61713415},"labels":[],"label_agreement":null},{"id":"W4210571894","doi":"10.1002/alz.055493","title":"Characterizing white matter hemodynamic markers of lesion burden and cognitive function using arterial spin labeling MRI","year":2021,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Hyperintensity; Montreal Cognitive Assessment; Magnetic resonance imaging; Cardiology; Cerebral blood flow; Hemodynamics; Psychology; Medicine; Cognition; Diffusion MRI; Effects of sleep deprivation on cognitive performance; Internal medicine; Neuroscience; Nuclear medicine; Cognitive impairment; Radiology","score_opus":0.049086049455011826,"score_gpt":0.3258690307130059,"score_spread":0.27678298125799405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210571894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9482825,0.0044389917,0.04521143,0.0011552244,0.00013768856,0.00037346804,0.00002338577,0.000067628775,0.00030968085],"genre_scores_gemma":[0.9787834,0.00006987367,0.020482015,0.0004045182,0.00010542248,0.000013810856,0.000105076455,0.000025317317,0.000010563287],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99924725,0.000024120125,0.00022088717,0.00026550374,0.00010123809,0.00014101012],"domain_scores_gemma":[0.9995717,0.000015783553,0.00011382886,0.0001559453,0.000096929216,0.000045817196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000061241786,0.00011072034,0.000168676,0.00005489969,0.00007754605,0.000017903269,0.000026643604,0.000040509505,0.0001596863],"category_scores_gemma":[0.000005771635,0.000117651485,0.000041732357,0.00010988256,0.000047324134,0.00010801203,0.00007164258,0.00009385263,0.000007978925],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016677633,0.000038238486,0.008412859,0.000025082962,0.0010836759,0.0000118464195,0.000062092186,0.000002851947,0.97175145,0.000031545937,0.000076263954,0.018337296],"study_design_scores_gemma":[0.004961928,0.0004802478,0.30084205,0.00167299,0.0675949,0.0005290985,0.00094156293,0.014327085,0.60061973,0.0008469055,0.006178902,0.0010046279],"about_ca_topic_score_codex":0.000012036879,"about_ca_topic_score_gemma":9.2377076e-7,"teacher_disagreement_score":0.37113175,"about_ca_system_score_codex":0.0000031860345,"about_ca_system_score_gemma":0.00002442317,"threshold_uncertainty_score":0.4797688},"labels":[],"label_agreement":null},{"id":"W4210845950","doi":"10.1016/j.nicl.2022.102955","title":"FLAIR MRI biomarkers of the normal appearing brain matter are related to cognition","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Heart Institute; St. Michael's Hospital; Université de Montréal; University of Toronto; Toronto Metropolitan University","funders":"National Institute on Aging; Canadian Institutes of Health Research; Canada Foundation for Innovation; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Alzheimer's Disease Neuroimaging Initiative; U.S. Department of Defense","keywords":"Fluid-attenuated inversion recovery; White matter; Kurtosis; Biomarker; Diffusion MRI; Magnetic resonance imaging; Brain size; Fractional anisotropy; Psychology; Voxel-based morphometry; Medicine; Nuclear medicine; Internal medicine; Pathology; Radiology; Chemistry; Mathematics","score_opus":0.07843850859328935,"score_gpt":0.40044685290848925,"score_spread":0.32200834431519987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210845950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.914234,0.000013071694,0.0015678952,0.077483974,0.00027796064,0.0010715525,0.000057998568,0.00021063519,0.005082955],"genre_scores_gemma":[0.97981566,0.0000056630506,0.0021976468,0.01676687,0.000041501862,0.000085635525,0.000015268974,0.000037974958,0.0010338026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984575,0.00018459883,0.0005345381,0.00038953958,0.0002534391,0.00018036383],"domain_scores_gemma":[0.99875414,0.0002624319,0.00020101194,0.000629357,0.000055790857,0.00009727909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040330683,0.00010676698,0.00022381052,0.000065795466,0.0001840282,0.0000074719474,0.00023254288,0.000039369144,0.00027228126],"category_scores_gemma":[0.0003615491,0.000090319765,0.00020237993,0.0004392485,0.0001471056,0.00004065014,0.00047197554,0.00064411096,0.00005223062],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007739034,0.0013485494,0.67884755,0.00011236029,0.000092430266,0.000228923,0.00013153923,0.00017353508,0.08431932,0.0003325404,0.22476248,0.0088768555],"study_design_scores_gemma":[0.0011171472,0.00037640188,0.9393433,0.000068145,0.00008920444,0.00029321766,0.00006914106,0.0005970743,0.0025332388,0.0006572867,0.05470142,0.00015446231],"about_ca_topic_score_codex":0.0000032339358,"about_ca_topic_score_gemma":4.465491e-7,"teacher_disagreement_score":0.2604957,"about_ca_system_score_codex":0.000020591317,"about_ca_system_score_gemma":0.000033077704,"threshold_uncertainty_score":0.3683133},"labels":[],"label_agreement":null},{"id":"W4211031588","doi":"10.1002/hbm.25777","title":"Tractostorm 2: Optimizing tractography dissection reproducibility with segmentation protocol dissemination","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; Mitacs; Fonds de Recherche du Québec - Santé; National Institute of Child Health and Human Development; Natural Sciences and Engineering Research Council of Canada; National Institute of General Medical Sciences; Vanderbilt Institute for Clinical and Translational Research; Instrumentariumin Tiedesäätiö; National Institutes of Health; Orionin Tutkimussäätiö; Emil Aaltosen Säätiö; Savoy Foundation; Fonds de recherche du Québec – Nature et technologies; Brain Research Foundation","keywords":"Tractography; Protocol (science); Computer science; Voxel; Reproducibility; Diffusion MRI; Neuroimaging; Artificial intelligence; Segmentation; Connectomics; Psychology; Connectome; Neuroscience; Magnetic resonance imaging; Medicine; Radiology; Pathology; Functional connectivity","score_opus":0.07698099408215822,"score_gpt":0.3921579084499347,"score_spread":0.3151769143677765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211031588","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7404823,0.0000095544965,0.13645251,0.007699967,0.00005183081,0.10781323,0.000018898123,0.0015392583,0.005932468],"genre_scores_gemma":[0.8913095,3.081704e-7,0.01609206,0.0002775711,0.00006556692,0.091764055,0.00012917092,0.000033669112,0.00032807328],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99855417,0.000060248232,0.00026128427,0.00068648503,0.00027501557,0.00016282602],"domain_scores_gemma":[0.998998,0.00005684471,0.0001883239,0.0006449697,0.00005911754,0.000052762232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005934288,0.00012812941,0.00014166273,0.00019409048,0.00078613183,0.00002746733,0.00007616393,0.000021023494,0.00012838273],"category_scores_gemma":[0.000061836814,0.00012421836,0.00006317124,0.0004936505,0.000048304526,0.00017297587,0.000042305295,0.00032904133,7.042063e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017483618,0.0006348243,0.018259149,0.00017928504,0.000022999522,0.00001712788,0.0016608348,0.00019172509,0.96609557,0.0019315012,0.0020752256,0.008756903],"study_design_scores_gemma":[0.003087023,0.0019589001,0.87064254,0.0003433843,0.000109641296,0.000661765,0.0064559374,0.0011889616,0.034819327,0.0040471866,0.075823635,0.00086167763],"about_ca_topic_score_codex":0.000007575808,"about_ca_topic_score_gemma":0.0000024876263,"teacher_disagreement_score":0.93127626,"about_ca_system_score_codex":0.00016455083,"about_ca_system_score_gemma":0.000020329995,"threshold_uncertainty_score":0.60463697},"labels":[],"label_agreement":null},{"id":"W4212817125","doi":"10.3389/fninf.2022.777853","title":"Assessing the Reliability of Template-Based Clustering for Tractography in Healthy Human Adults","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Cluster analysis; Human Connectome Project; Tractography; Reliability (semiconductor); Pattern recognition (psychology); Computer science; Artificial intelligence; White matter; Centroid; Neuroscience; Psychology; Functional connectivity; Medicine; Magnetic resonance imaging; Physics","score_opus":0.05859852119323517,"score_gpt":0.3744245438312235,"score_spread":0.3158260226379883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212817125","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80408645,0.000034152195,0.19148356,0.0018375147,0.00023422141,0.0019299785,0.000033510358,0.00007991637,0.000280724],"genre_scores_gemma":[0.8919086,0.000010904094,0.107042275,0.0007415282,0.000012707026,0.00023745927,0.000028206938,0.000015642916,0.000002676029],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888504,0.00004043595,0.0005787281,0.00013000662,0.00017328658,0.00019250876],"domain_scores_gemma":[0.9991927,0.00012344639,0.00022520425,0.00039391193,0.000031684824,0.000033067234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040631706,0.000094422896,0.00022832442,0.00024043645,0.00017097707,0.000012153258,0.00017127949,0.000023363902,0.0000018963924],"category_scores_gemma":[0.000080813224,0.00008218521,0.00008004493,0.00046915305,0.00007325311,0.0001411641,0.000058616533,0.00038296706,4.269823e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002550016,0.0021473905,0.79095566,0.0044804295,0.000019608196,0.000019681926,0.004563792,0.14349288,0.00087340723,0.0005226932,0.019228077,0.031146389],"study_design_scores_gemma":[0.004327912,0.0011923728,0.0729748,0.00021551302,0.000029847757,0.000017129098,0.0034351603,0.89632547,0.00046504362,0.00243041,0.018347071,0.00023929843],"about_ca_topic_score_codex":0.000013904965,"about_ca_topic_score_gemma":0.0000032894811,"teacher_disagreement_score":0.7528326,"about_ca_system_score_codex":0.00008205968,"about_ca_system_score_gemma":0.00005986873,"threshold_uncertainty_score":0.33514157},"labels":[],"label_agreement":null},{"id":"W4212975352","doi":"10.21203/rs.3.rs-310196/v1","title":"Stimulating Lifestyle is associated with Maintenance of White Matter Integrity with Age","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Structural integrity; White (mutation); Gerontology; Medicine; Engineering; Biology; Genetics","score_opus":0.13341940710485356,"score_gpt":0.44221142403800795,"score_spread":0.3087920169331544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212975352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9636228,0.00014783947,0.019185968,0.008039537,0.000016949989,0.0023102004,0.00023673083,0.00024700412,0.006192968],"genre_scores_gemma":[0.970918,0.00006322667,0.02554497,0.00026679874,0.00004627439,0.00025235038,0.00027293002,0.000076226606,0.0025592335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997442,0.00016982113,0.0003093149,0.0006751736,0.00092417427,0.0004795161],"domain_scores_gemma":[0.99677527,0.0002562058,0.00019271782,0.0010889374,0.001530589,0.00015628559],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00056055165,0.00023868322,0.00056284614,0.00019647369,0.00016791746,0.00005005444,0.00025196877,0.0001954475,0.00020805231],"category_scores_gemma":[0.0003598201,0.00017358924,0.00009960809,0.00061537896,0.0003579817,0.000053406537,0.00080850604,0.002873635,0.0000058187916],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037969497,0.0008443102,0.9816919,0.002927347,0.00026075583,0.001170839,0.0019006735,0.00038905288,0.0018680531,0.00023802443,0.007557611,0.00077176146],"study_design_scores_gemma":[0.0026215767,0.0018559002,0.9309519,0.04452564,0.00022470736,0.00017938981,0.0020146014,0.0050596534,0.0075469096,0.0019977116,0.002109278,0.00091272185],"about_ca_topic_score_codex":0.00015658526,"about_ca_topic_score_gemma":0.00004935235,"teacher_disagreement_score":0.050739963,"about_ca_system_score_codex":0.00021420566,"about_ca_system_score_gemma":0.0004703271,"threshold_uncertainty_score":0.9994268},"labels":[],"label_agreement":null},{"id":"W4212986928","doi":"10.1101/2022.01.31.478189","title":"Micapipe: A Pipeline for Multimodal Neuroimaging and Connectome Analysis","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Human Connectome Project; Connectome; Neuroimaging; Tractography; Connectomics; Computer science; Diffusion MRI; Artificial intelligence; Neuroscience; Pipeline (software); Functional connectivity; Pattern recognition (psychology); Psychology; Magnetic resonance imaging; Medicine","score_opus":0.03801779878377539,"score_gpt":0.31009455201891645,"score_spread":0.2720767532351411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212986928","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75874776,0.0015678488,0.22815673,0.0042341626,0.00032215373,0.0037348722,0.0014927599,0.0017286377,0.000015091794],"genre_scores_gemma":[0.9025187,0.00032352822,0.09448043,0.0009863286,0.00022536145,0.0012883773,0.000004994822,0.00015431354,0.000017981538],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99729943,0.000058200814,0.0005317229,0.00135772,0.00028515758,0.00046774306],"domain_scores_gemma":[0.9973844,0.0001722628,0.00036356825,0.0014473452,0.00034020285,0.00029218438],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035636124,0.00048375968,0.00087043055,0.00061816943,0.0002696008,0.00009589196,0.00031612522,0.00017290303,0.00006465682],"category_scores_gemma":[0.00028618754,0.00053966936,0.00034386045,0.0009204277,0.00013996229,0.00007244262,0.00065236684,0.0008822591,0.0000028700265],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027386317,0.0006785068,0.06953115,0.001317512,0.0010668291,0.00015548318,0.000019953095,0.00041119536,0.9225932,0.0022616254,0.0016513526,0.000039378796],"study_design_scores_gemma":[0.006247042,0.0004222951,0.40378848,0.0005194581,0.013234913,5.8853135e-7,0.000019893547,0.26877052,0.13307728,0.000098031254,0.17004311,0.003778407],"about_ca_topic_score_codex":0.00003346208,"about_ca_topic_score_gemma":5.961698e-7,"teacher_disagreement_score":0.78951585,"about_ca_system_score_codex":0.00016194857,"about_ca_system_score_gemma":0.00021288848,"threshold_uncertainty_score":0.9997055},"labels":[],"label_agreement":null},{"id":"W4213009037","doi":"10.1101/2022.02.17.480894","title":"Experience-dependent learning and myelin plasticity in individuals with stroke","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Myelin; Motor learning; Neuroplasticity; Stroke (engine); Psychology; Physical medicine and rehabilitation; Neuroscience; Medicine; Central nervous system; Physics","score_opus":0.02986012469849179,"score_gpt":0.29213734550915443,"score_spread":0.2622772208106626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213009037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99300927,0.00026104093,0.004795757,0.00028021727,0.000066477754,0.00096708746,0.00011193317,0.0004847038,0.000023542218],"genre_scores_gemma":[0.9722324,0.00040781876,0.026093826,0.00015059274,0.0000831877,0.0009157356,5.048678e-7,0.00009590273,0.000020022268],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997813,0.00007370311,0.0003766875,0.0009288634,0.00042977987,0.00037796455],"domain_scores_gemma":[0.99884,0.000082455896,0.0002627335,0.00051210163,0.000105206076,0.00019755546],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021870952,0.00036275166,0.00049052795,0.00029924163,0.00017278915,0.00007171536,0.00021802331,0.00017220971,0.000081582766],"category_scores_gemma":[0.00015695838,0.00036405664,0.0000465619,0.0003285125,0.00014018787,0.00007559943,0.0006616468,0.0016929876,0.0000034577392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007238332,0.00026739712,0.808696,0.0002611424,0.00005936079,0.00018988704,0.00006860733,0.0003291388,0.18953303,0.00047929533,0.00003247734,0.000011283185],"study_design_scores_gemma":[0.0024194592,0.0005040151,0.8163453,0.00095623673,0.00023621062,5.976309e-7,0.00011132537,0.0012232019,0.14596933,0.000008695991,0.030859534,0.0013661191],"about_ca_topic_score_codex":0.000037524,"about_ca_topic_score_gemma":0.0000015280557,"teacher_disagreement_score":0.043563694,"about_ca_system_score_codex":0.00021306607,"about_ca_system_score_gemma":0.00025560637,"threshold_uncertainty_score":0.99988115},"labels":[],"label_agreement":null},{"id":"W4214809227","doi":"10.1093/braincomms/fcac053","title":"Symptoms reported by Canadians posted in Havana are linked with reduced white matter fibre density","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; Dalhousie University","funders":"Nova Scotia Health Authority; Canadian Institutes of Health Research; Global Affairs Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Cohort; Medicine; Splenium; Fornix; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.04936856139944717,"score_gpt":0.3234184711738703,"score_spread":0.2740499097744231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214809227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5702551,0.0002296904,0.0009788481,0.41960216,0.000022355642,0.0017016988,0.00030528015,0.000458787,0.0064461064],"genre_scores_gemma":[0.9786212,0.000019753277,0.006888836,0.009416524,0.000008178354,0.00054622383,0.0008086677,0.00004393241,0.0036467074],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988949,0.00012837446,0.00030680996,0.00029118572,0.00016031781,0.00021846412],"domain_scores_gemma":[0.99697524,0.0001302814,0.0001919762,0.0024918085,0.00009096918,0.00011973574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014659265,0.00013061064,0.00021056607,0.00014186247,0.00045392607,0.000016051077,0.00046251697,0.00003812512,0.00012075471],"category_scores_gemma":[0.000060667793,0.00013757747,0.000041440748,0.00066178455,0.00013125641,0.000055026074,0.00030462534,0.00058506196,0.000007946653],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013439955,0.0010102275,0.5670427,0.000041053514,0.000100253965,0.00013464026,0.0013751579,0.00011749619,0.0253244,0.0010042737,0.40200487,0.001710514],"study_design_scores_gemma":[0.0016039928,0.00022469979,0.7377815,0.0001607518,0.00010745556,0.0010634611,0.0011987938,0.0020432316,0.00042764092,0.0006068415,0.25427592,0.00050569023],"about_ca_topic_score_codex":0.0018412832,"about_ca_topic_score_gemma":0.0026442674,"teacher_disagreement_score":0.4101856,"about_ca_system_score_codex":0.00023700898,"about_ca_system_score_gemma":0.0001562975,"threshold_uncertainty_score":0.56102467},"labels":[],"label_agreement":null},{"id":"W4214903121","doi":"10.1016/j.biopsych.2022.02.959","title":"Virtual Ontogeny of Cortical Growth Preceding Mental Illness","year":2022,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; University of Calgary; Centre Hospitalier Universitaire Sainte-Justine; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Cilag; Singapore Bioimaging Consortium; Scottish Mental Health Research Network; National Center for Complementary and Integrative Health; National Institute on Drug Abuse; European Regional Development Fund; H2020 Marie Skłodowska-Curie Actions; Horizon 2020; Medizinische Fakultät, Westfälische Wilhelms-Universität Münster; Instituto de Salud Carlos III; National Health and Medical Research Council; National Center for Advancing Translational Sciences; Seventh Framework Programme; NIH Clinical Center; Ramsay Health Care; National Institute on Alcohol Abuse and Alcoholism; Stiftelsen för Strategisk Forskning; Medical Research Council; Siemens Healthineers; Innovative Medicines Initiative; Interdisziplinäres Zentrum für Klinische Forschung, Universitätsklinikum Würzburg; Hartmann Müller-Stiftung für Medizinische Forschung; Medical Research Council Canada; University of Cape Town; Centro de Investigación Biomédica en Red de Salud Mental; Society for Mental Health Research; National Institute of Neurological Disorders and Stroke; Universität Zürich; Australian Schizophrenia Research Bank; Norges Forskningsråd; Ministerio de Ciencia e Innovación; Meath Foundation; Clinical and Translational Science Institute, University of California, San Francisco; National Institute of Mental Health; Helse Sør-Øst RHF; Hospital de Clínicas de Porto Alegre; Brain and Behavior Research Foundation; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Centre of Excellence in Cognition and its Disorders, Australian Research Council; Ministero della Salute; Macquarie University; Generalitat de Catalunya; Natural Sciences and Engineering Research Council of Canada; American Foundation for Suicide Prevention; Bundesministerium für Bildung und Forschung; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Deutsche Forschungsgemeinschaft; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Institute of Biomedical Imaging and Bioengineering; University of Melbourne; Stiftelsen för Strategisk Forskning; National Institute for Health and Care Research; National Research Foundation; South African Medical Research Council; Swinburne University of Technology; Ministerio de Ciencia, Innovación y Universidades; Health Research Board; Pratt Foundation; Centres de Recerca de Catalunya; National Institutes of Health; Children's Hospital Foundation; Fundação Instituto de Pesquisas Econômicas; Wellcome Trust; University of California, San Francisco; Simons Foundation Autism Research Initiative; Schizophrenia Research Fund; Sylvia and Charles Viertel Charitable Foundation; Australian Research Council; Fresenius Medical Care North America; National Institute on Aging; Jack Brockhoff Foundation; EU Joint Programme – Neurodegenerative Disease Research; Bill and Melinda Gates Foundation; National Center for Research Resources; National Alliance for Research on Schizophrenia and Depression; Biogen; Hjärnfonden; Ministerstvo Zdravotnictví Ceské Republiky; European Commission; Russian Foundation for Basic Research; National Healthcare Group; European Federation of Pharmaceutical Industries and Associations; Carnegie Corporation of New York; Chiropractic and Osteopathic College of Australasia; Collier Charitable Fund; Indiana Clinical and Translational Sciences Institute; Autism Speaks; Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul; Horizon 2020 Framework Programme; Vetenskapsrådet; University of Minnesota; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; U.S. Department of Veterans Affairs","keywords":"DISC1; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; Psychosis; Cerebral cortex; Neuroscience; Psychology; Autism; Biology; Gene; Psychiatry; Genetics","score_opus":0.07596099524132206,"score_gpt":0.3527165624234762,"score_spread":0.27675556718215416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214903121","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914232,0.00015337893,0.003161838,0.0022893853,0.00047495848,0.00037456423,0.000049806942,0.00018746265,0.0018854429],"genre_scores_gemma":[0.9901131,0.000047190955,0.008556755,0.0009147574,0.00012489199,0.0000944696,0.000042507065,0.000009950367,0.0000964228],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991903,0.000032019838,0.0002278534,0.00024848638,0.00014551338,0.0001558766],"domain_scores_gemma":[0.99960345,0.000040074225,0.00007171131,0.00017664528,0.000032495795,0.00007560726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000108337896,0.00009065673,0.00017796613,0.000030227795,0.00032813862,0.0000038441685,0.00013271526,0.00003957436,0.000256516],"category_scores_gemma":[0.0000690657,0.00007037379,0.00009541998,0.00017193671,0.00011580226,0.00001538125,0.00016761172,0.00027619378,0.000003892887],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009138091,0.0023334336,0.6090163,0.00004042943,0.000056406734,0.000008728094,0.00012363383,0.000007072544,0.0996096,0.2560552,0.026216973,0.005618434],"study_design_scores_gemma":[0.0059847585,0.014409752,0.70273703,0.00013020642,0.00023186693,0.0008808773,0.003692266,0.0008963579,0.019528225,0.09215998,0.15789987,0.001448825],"about_ca_topic_score_codex":0.0000046648747,"about_ca_topic_score_gemma":3.1270125e-7,"teacher_disagreement_score":0.16389522,"about_ca_system_score_codex":0.000035078585,"about_ca_system_score_gemma":0.000032400447,"threshold_uncertainty_score":0.28697598},"labels":[],"label_agreement":null},{"id":"W4220706494","doi":"10.1016/j.nicl.2022.103001","title":"Patterns of white and gray structural abnormality associated with paediatric demyelinating disorders","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Toronto; Montreal Neurological Institute and Hospital; Hospital for Sick Children; SickKids Foundation","funders":"","keywords":"White matter; Optic neuritis; Medicine; Multiple sclerosis; Diffusion MRI; Optic nerve; Pathology; Clinically isolated syndrome; Abnormality; Lesion; Ophthalmology; Neuroscience; Psychology; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.059620413644246334,"score_gpt":0.3791815617327682,"score_spread":0.3195611480885219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220706494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99623734,0.0000314595,0.0013957482,0.0015258428,0.000049798382,0.00036685978,0.00008425355,0.00014042118,0.00016829066],"genre_scores_gemma":[0.996707,0.00008011257,0.0022819387,0.00071111385,0.000045127836,0.00003718653,0.000043250184,0.00002908853,0.000065171924],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99847966,0.00018522902,0.0004857127,0.00039562178,0.0002627278,0.0001910458],"domain_scores_gemma":[0.9988061,0.0004223315,0.00028763863,0.00032135763,0.00006109592,0.00010144544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040225885,0.00012863023,0.0003142391,0.00006202913,0.00026779962,0.000006612999,0.000116624054,0.000034813314,0.000047561993],"category_scores_gemma":[0.00043102252,0.000110872425,0.00009392832,0.00026543037,0.00012063681,0.000060605347,0.00031347846,0.0006603413,2.5665946e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058983816,0.00013454835,0.9940829,0.000021243375,0.000012114381,0.00002002716,0.00004271276,0.000020368361,0.00007598164,0.000096397256,0.000064054664,0.0053706416],"study_design_scores_gemma":[0.00109943,0.00074726145,0.99544686,0.000012601027,0.00008515242,0.000065633525,0.00005298854,0.0013912992,0.000022124035,0.00040189677,0.00056445017,0.0001103161],"about_ca_topic_score_codex":0.000010268678,"about_ca_topic_score_gemma":0.0000065829827,"teacher_disagreement_score":0.0052603255,"about_ca_system_score_codex":0.000017872973,"about_ca_system_score_gemma":0.000037752787,"threshold_uncertainty_score":0.45212463},"labels":[],"label_agreement":null},{"id":"W4220724235","doi":"10.21203/rs.3.rs-1335010/v1","title":"Abnormal Brain Functional and Structural Connectivity Between the Left Supplementary Motor Area and Inferior Frontal Gyrus in Moyamoya Disease","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Zhejiang University; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Supramarginal gyrus; Superior frontal gyrus; White matter; Diffusion MRI; Neuroscience; Resting state fMRI; Middle frontal gyrus; Cognition; Functional magnetic resonance imaging; Supplementary motor area; Inferior frontal gyrus; Medial frontal gyrus; Psychology; Functional connectivity; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.11024288447271696,"score_gpt":0.4234494933137933,"score_spread":0.3132066088410763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220724235","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9786079,0.00044249048,0.00028465368,0.014524492,0.000036879595,0.0024099671,0.0035461993,0.00006223633,0.0000852175],"genre_scores_gemma":[0.9966971,0.00015271269,0.00039784852,0.00019778423,0.00019714059,0.0006300829,0.0015284609,0.000033206314,0.00016563822],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977478,0.00028634636,0.00025098896,0.00064142625,0.0006678292,0.00040565658],"domain_scores_gemma":[0.9982494,0.00078110857,0.00006010691,0.00054754934,0.00009121711,0.0002706096],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006852487,0.0002195549,0.00030493332,0.00024610976,0.0004521447,0.0000707091,0.00018003453,0.000076184086,0.0009729302],"category_scores_gemma":[0.00029421103,0.00017550169,0.00007352954,0.0001355966,0.00036562062,0.00007159038,0.0018863883,0.0020303174,7.98758e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031480103,0.000048920014,0.9946976,0.00030577477,0.000030341449,0.00006558685,0.00015582635,0.000029927645,0.00021409932,0.00030547593,0.0015466808,0.0022849867],"study_design_scores_gemma":[0.0006559709,0.00017745118,0.98379785,0.00010270169,0.000028561199,0.000024177474,0.00029283622,0.0013275961,0.000041990843,0.0074429233,0.00594921,0.00015871415],"about_ca_topic_score_codex":0.0008180371,"about_ca_topic_score_gemma":0.0001589946,"teacher_disagreement_score":0.018089263,"about_ca_system_score_codex":0.00027706038,"about_ca_system_score_gemma":0.00028234549,"threshold_uncertainty_score":0.99994034},"labels":[],"label_agreement":null},{"id":"W4220726715","doi":"10.1016/j.neurobiolaging.2022.03.008","title":"DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants","year":2022,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"Medical Research Council; Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Kurtosis; Diffusion MRI; Thermal diffusivity; Fractional anisotropy; White matter; Biobank; Statistics; Medicine; Physics; Mathematics; Magnetic resonance imaging; Biology; Radiology; Bioinformatics","score_opus":0.0469883646580052,"score_gpt":0.3343319057677442,"score_spread":0.287343541109739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220726715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.994689,0.000033016862,0.00017741465,0.004658686,0.000028270266,0.00027021323,0.000028827324,0.0000117860845,0.000102782134],"genre_scores_gemma":[0.99910027,0.000017515898,0.00010293667,0.00072925864,0.000003885243,0.000026142887,0.0000052334995,0.0000055445125,0.000009208354],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990562,0.00030445418,0.00027967218,0.00017756801,0.00005753772,0.0001245443],"domain_scores_gemma":[0.9992153,0.00027137398,0.00016483206,0.00031646466,0.000020784439,0.000011262553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000447497,0.00007072691,0.00021818485,0.00004609043,0.00004692404,0.0000013440495,0.00010340817,0.00001853616,0.00003624872],"category_scores_gemma":[0.000028893817,0.000044682696,0.00004259371,0.00014197177,0.00037184084,0.000015618294,0.0001496213,0.00025407327,2.1688669e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002837903,0.00008439589,0.85358876,0.000047189194,0.000009364763,0.0000058191513,0.0013877677,0.00003624464,0.14443101,0.00006147413,0.000037959726,0.00028161547],"study_design_scores_gemma":[0.0001863339,0.00014194135,0.95020163,0.000039154642,0.000034543424,0.000048289443,0.0003557738,0.00016234898,0.04834172,0.00040514974,0.000043175995,0.000039908715],"about_ca_topic_score_codex":0.000052967385,"about_ca_topic_score_gemma":0.000016940076,"teacher_disagreement_score":0.09661288,"about_ca_system_score_codex":0.0000060656334,"about_ca_system_score_gemma":0.000009420833,"threshold_uncertainty_score":0.18221076},"labels":[],"label_agreement":null},{"id":"W4220833183","doi":"10.1109/tmi.2022.3161947","title":"Invertible Modeling of Bidirectional Relationships in Neuroimaging With Normalizing Flows: Application to Brain Aging","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Calgary Foundation; University of Calgary","keywords":"Brain morphometry; Neuroimaging; Computer science; Artificial intelligence; Generative model; Machine learning; Pattern recognition (psychology); Generative grammar; Psychology; Neuroscience; Magnetic resonance imaging","score_opus":0.051741779957651196,"score_gpt":0.3277829044766381,"score_spread":0.2760411245189869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220833183","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06756795,0.000036977923,0.91411304,0.017056352,0.000071734525,0.00054585334,0.000011078389,0.00024428,0.00035273976],"genre_scores_gemma":[0.9782296,0.00001487596,0.018360144,0.0027249323,0.000034918135,0.00051686435,0.000011626254,0.000051673233,0.000055359324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99785095,0.00011551936,0.00047579466,0.00047912833,0.0007772978,0.00030127552],"domain_scores_gemma":[0.99901456,0.00022665273,0.000082080565,0.00036948133,0.000083470775,0.00022377919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006293578,0.00017396657,0.00025359375,0.00071084243,0.00043648054,0.000013074477,0.00018066485,0.000029602721,0.00008957559],"category_scores_gemma":[0.000059033835,0.00018307182,0.00007582858,0.0014075335,0.00006216292,0.00017636498,0.000011129674,0.0011609764,0.0000054579154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022829363,0.00062545494,0.008190976,0.000079041434,0.000022354707,0.00006129904,0.00066662615,0.9220432,0.019942764,0.0003047217,0.00021558267,0.047619686],"study_design_scores_gemma":[0.00080995593,0.0000780073,0.00046759145,0.00020127052,0.000034339097,0.00032802054,0.00041672864,0.9925933,0.0031901153,0.00027161883,0.0014183078,0.00019075898],"about_ca_topic_score_codex":0.00022614335,"about_ca_topic_score_gemma":0.000046067846,"teacher_disagreement_score":0.91066164,"about_ca_system_score_codex":0.00021317875,"about_ca_system_score_gemma":0.00017476162,"threshold_uncertainty_score":0.7465452},"labels":[],"label_agreement":null},{"id":"W4220882089","doi":"10.3389/fnana.2022.837485","title":"Cytoarchitectonic Maps of the Human Metathalamus in 3D Space","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; National Research Council Canada; Montreal Neurological Institute and Hospital","funders":"Max-Planck-Gesellschaft; Horizon 2020 Framework Programme; Forschungszentrum Jülich; Bundesministerium für Bildung und Forschung; European Commission","keywords":"Space (punctuation); Neuroscience; Psychology; Artificial intelligence; Cognitive science; Computer science","score_opus":0.025310085183022385,"score_gpt":0.30436510360463737,"score_spread":0.27905501842161495,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220882089","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860078,0.00052556366,0.0017062306,0.0051653036,0.00028669814,0.001214525,0.000037903137,0.000104538296,0.0049514007],"genre_scores_gemma":[0.9891569,0.000026546715,0.009580728,0.00046856987,0.0000107657515,0.00018467267,0.000007283801,0.000027206623,0.00053732307],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989867,0.00009965197,0.00023832459,0.00025828503,0.00022402237,0.00019300573],"domain_scores_gemma":[0.9993156,0.000022945665,0.0000937811,0.0005232845,0.000012737338,0.000031616255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013880988,0.000099630815,0.00023039615,0.00025049964,0.00008637045,0.0000029195078,0.00029073283,0.00001744789,0.000024923533],"category_scores_gemma":[0.000033586224,0.00008646317,0.000078815436,0.00083924894,0.00011452583,0.000026319889,0.00022932624,0.00058384624,4.062374e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012031127,0.00095010217,0.9150378,0.00013441572,0.000035364534,0.00032272216,0.00071174896,0.001710487,0.016708912,0.012411836,0.038276035,0.013580246],"study_design_scores_gemma":[0.0052262857,0.00047038542,0.40415588,0.00013769124,0.00013381385,0.0003892242,0.0008658162,0.006376285,0.019887289,0.0442008,0.5175548,0.0006017392],"about_ca_topic_score_codex":0.00004030395,"about_ca_topic_score_gemma":0.0000054021198,"teacher_disagreement_score":0.51088196,"about_ca_system_score_codex":0.00009994101,"about_ca_system_score_gemma":0.000046554153,"threshold_uncertainty_score":0.3525866},"labels":[],"label_agreement":null},{"id":"W4220892781","doi":"10.32920/19400750.v1","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Orientation (vector space); Metric (unit); Linear regression; Diffusion; Tensor (intrinsic definition); Dispersion (optics); SIGNAL (programming language); Biological system; Nuclear magnetic resonance; Physics; Materials science; Statistical physics; Mathematics; Computer science; Optics; Statistics; Magnetic resonance imaging; Geometry; Radiology; Medicine; Biology","score_opus":0.07503130547690681,"score_gpt":0.4057850943838871,"score_spread":0.33075378890698026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220892781","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01787352,0.0002722115,0.9729532,0.003734846,0.00031279947,0.0014491365,0.000050826646,0.001153522,0.0021999637],"genre_scores_gemma":[0.1320932,0.00046192936,0.8608696,0.0015601018,0.0004024446,0.0004584348,0.002698698,0.00010354057,0.001352069],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982979,0.00005240051,0.00039969722,0.00070051115,0.00032522963,0.00022424465],"domain_scores_gemma":[0.9985175,0.000045486016,0.0002826128,0.00088739034,0.00013341336,0.00013356577],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014083233,0.00028656094,0.00036846992,0.00019162451,0.00029295255,0.000032940752,0.00019596236,0.000114882896,0.0020823139],"category_scores_gemma":[0.000027622838,0.000258841,0.00016591887,0.00013232302,0.00003978905,0.00015919776,0.0004977488,0.0010103079,0.0000114991335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035610688,0.004985496,0.0284839,0.0014266052,0.00033783985,0.00031632875,0.0006249129,0.032832157,0.65958655,0.013211405,0.035233125,0.2194006],"study_design_scores_gemma":[0.0039656283,0.00039183986,0.00896095,0.0004500899,0.0003770874,0.00035253138,0.00012192623,0.7317355,0.038671043,0.027178137,0.18661481,0.0011804212],"about_ca_topic_score_codex":0.00005296781,"about_ca_topic_score_gemma":4.053437e-7,"teacher_disagreement_score":0.6989034,"about_ca_system_score_codex":0.00021824864,"about_ca_system_score_gemma":0.00012979265,"threshold_uncertainty_score":0.9999864},"labels":[],"label_agreement":null},{"id":"W4220920055","doi":"10.1101/2022.03.28.485689","title":"Mapping the subcortical connectome using in vivo diffusion MRI: feasibility and reliability","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Tractography; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Thalamus; Connectomics; Computer science; Reliability (semiconductor); Artificial intelligence; Psychology; Pattern recognition (psychology); Functional connectivity; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.07093723532006117,"score_gpt":0.31211429899570076,"score_spread":0.24117706367563957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220920055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9894022,0.0005289828,0.0060567753,0.0014340206,0.00016683369,0.0019429807,0.00009521151,0.0003657015,0.0000073189935],"genre_scores_gemma":[0.98044,0.0004529005,0.01824035,0.0003817189,0.00010565358,0.00030387577,2.4164646e-7,0.00007316316,0.0000020671887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736625,0.0001840495,0.0005743468,0.0011302009,0.00033914324,0.0004060001],"domain_scores_gemma":[0.9974407,0.00018945747,0.00024048614,0.0017807048,0.00016347886,0.00018515378],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008676432,0.0003643293,0.00055187766,0.0001847134,0.00027969028,0.00006113447,0.00030356654,0.00021396269,0.00007689989],"category_scores_gemma":[0.00046540314,0.00031695346,0.00011738721,0.00062100665,0.00029063,0.0000677103,0.0011610492,0.0014459415,0.0000013240863],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007978177,0.0003957142,0.504343,0.0004888139,0.000017996117,0.000064830776,0.00002157092,0.00009375769,0.49373484,0.0006846719,0.00007277742,0.0000022918014],"study_design_scores_gemma":[0.00085153745,0.00007161344,0.95926785,0.00041850415,0.00010811256,3.2312272e-7,0.000019204297,0.010684387,0.021629006,0.00009577464,0.00626535,0.00058835204],"about_ca_topic_score_codex":0.000116881514,"about_ca_topic_score_gemma":0.0000013726013,"teacher_disagreement_score":0.47210583,"about_ca_system_score_codex":0.0006265977,"about_ca_system_score_gemma":0.00030529674,"threshold_uncertainty_score":0.99992824},"labels":[],"label_agreement":null},{"id":"W4220973849","doi":"10.7554/elife.73153","title":"The Digital Brain Bank, an open access platform for post-mortem imaging datasets","year":2022,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Medical Research Council; Université de Lyon; Medical Research Council Canada; China Scholarship Council; Max-Planck-Gesellschaft; NIHR Oxford Biomedical Research Centre; Wellcome Trust; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; National Research Foundation; University of Oxford; Motor Neurone Disease Association; Cancer Research UK; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; Alzheimer Society; Smithsonian Institution; Wellcome","keywords":"Neuroimaging; Neuroanatomy; Diffusion MRI; Magnetic resonance imaging; Human brain; Tractography; Neuroinformatics; Functional magnetic resonance imaging; Brain mapping","score_opus":0.14061197562562738,"score_gpt":0.46248749162799835,"score_spread":0.32187551600237096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220973849","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3965508,0.0009960185,0.0896776,0.4222868,0.0009678583,0.023261193,0.038222674,0.0030098278,0.025027227],"genre_scores_gemma":[0.9656908,0.00001758602,0.00412655,0.02162257,0.00019083922,0.0014675702,0.005758351,0.00006872797,0.0010570381],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991938,0.000008103634,0.00016083263,0.00025930145,0.00018205293,0.00019591286],"domain_scores_gemma":[0.99903816,0.00015080957,0.00007271269,0.00061277376,0.00003790656,0.00008763207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002211056,0.000086679014,0.000106032734,0.000030674506,0.00068653986,0.00037748806,0.0009815734,0.000007609909,0.000036496273],"category_scores_gemma":[0.00013304866,0.000066652115,0.00003215942,0.00012926153,0.000041957283,0.00072193163,0.0012218968,0.00015703484,0.0000037320203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039680413,0.0003755912,0.0041348236,0.00002283381,0.000028707142,0.000040293457,0.00012554559,0.00002422004,0.0041123508,0.01576002,0.7550243,0.21995448],"study_design_scores_gemma":[0.00049113965,0.00013729697,0.0025719027,0.000006095759,0.00001265233,0.00009168101,0.00017057113,0.0013837579,0.0008902901,0.0017424807,0.9924021,0.00010003159],"about_ca_topic_score_codex":0.000023742874,"about_ca_topic_score_gemma":0.0000045735364,"teacher_disagreement_score":0.56913996,"about_ca_system_score_codex":0.000045949208,"about_ca_system_score_gemma":0.00007747234,"threshold_uncertainty_score":0.5280379},"labels":[],"label_agreement":null},{"id":"W4220984722","doi":"10.3389/fneur.2022.835050","title":"Alterations of the White Matter in Patients With Knee Osteoarthritis: A Diffusion Tensor Imaging Study With Tract-Based Spatial Statistics","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Health Commission of Sichuan Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Splenium; Corpus callosum; White matter; Diffusion MRI; Fractional anisotropy; Superior longitudinal fasciculus; Medicine; Corona radiata (embryology); Fasciculus; Cingulum (brain); Inferior longitudinal fasciculus; Magnetic resonance imaging; Anatomy; Internal medicine; Radiology","score_opus":0.0071472348454115755,"score_gpt":0.2394243477610844,"score_spread":0.23227711291567282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220984722","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96391195,0.0000072433927,0.032264486,0.0020648253,0.00009238978,0.0015070894,0.000094700954,0.000021908487,0.00003543014],"genre_scores_gemma":[0.98896325,3.3498108e-7,0.008795415,0.001798107,0.0000076121846,0.00035057234,0.00003393931,0.000025335372,0.000025461113],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902326,0.00013155142,0.00022589136,0.0002618453,0.00019383973,0.00016358617],"domain_scores_gemma":[0.9994566,0.000027003858,0.00011708196,0.000333874,0.000041228122,0.000024235973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004642068,0.000105792096,0.00020442759,0.00016585378,0.00009214132,0.000004500996,0.000103377984,0.000013862823,0.00002864178],"category_scores_gemma":[0.000011844273,0.000078094774,0.000016027288,0.00026948345,0.00010644514,0.000029969742,0.000064763335,0.00038463512,2.6841198e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008563151,0.0010011559,0.99494445,0.000007119908,0.000002602544,0.000042215208,0.00016712745,0.0010212469,0.000011480579,0.000005379021,0.00064175826,0.0012991477],"study_design_scores_gemma":[0.0043030656,0.0026401165,0.98921055,0.000011888242,0.000026893718,0.000014370325,0.00008639749,0.0031696183,0.000005839373,0.00006289041,0.00039736848,0.000071021954],"about_ca_topic_score_codex":0.000034878136,"about_ca_topic_score_gemma":0.000056315796,"teacher_disagreement_score":0.025051294,"about_ca_system_score_codex":0.000028925868,"about_ca_system_score_gemma":0.00004455695,"threshold_uncertainty_score":0.31846124},"labels":[],"label_agreement":null},{"id":"W4221029104","doi":"10.1016/j.jmr.2022.107205","title":"Orientation dependence of inhomogeneous magnetization transfer and dipolar order relaxation rate in phospholipid bilayers","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries","funders":"Natural Sciences and Engineering Research Council of Canada; International Collaboration on Repair Discoveries","keywords":"Magnetization transfer; Nuclear magnetic resonance; Anisotropy; Dipole; Chemistry; Orientation (vector space); Condensed matter physics; Molecular physics; Materials science; Physics; Optics; Magnetic resonance imaging; Geometry","score_opus":0.021364488013100896,"score_gpt":0.2865378253357739,"score_spread":0.265173337322673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221029104","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9810656,0.0070873806,0.010507467,0.0008763752,0.000055622168,0.00030168926,0.000007757424,0.000009655394,0.000088486486],"genre_scores_gemma":[0.9878237,0.0030311847,0.008757086,0.00018580726,0.000021135655,0.000022076121,0.0000034431193,0.000013241046,0.00014232939],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99901044,0.0000683649,0.0004356516,0.00013328451,0.0002575719,0.000094691895],"domain_scores_gemma":[0.99944603,0.00005409944,0.00017967944,0.00012284261,0.00015608154,0.000041271927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000323963,0.00007372021,0.00017338622,0.00014841693,0.00005073735,0.0000053817243,0.000074301,0.000023648121,0.00008092358],"category_scores_gemma":[0.00010951964,0.000070796385,0.000030721603,0.00047772753,0.00004998748,0.00008878537,0.000022622373,0.00022730995,2.5865674e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001920876,0.00075448316,0.17420322,0.00020095865,0.000012093169,0.00021575927,0.0020506142,0.00439635,0.37693766,0.0028684956,0.00049512216,0.43594438],"study_design_scores_gemma":[0.004948195,0.004064284,0.8950544,0.0002675961,0.00012619157,0.0012989267,0.0004291996,0.0058463123,0.039706156,0.0034203005,0.04455966,0.00027878137],"about_ca_topic_score_codex":0.000016043754,"about_ca_topic_score_gemma":0.0000037295808,"teacher_disagreement_score":0.7208512,"about_ca_system_score_codex":0.000053640648,"about_ca_system_score_gemma":0.00007634135,"threshold_uncertainty_score":0.28869927},"labels":[],"label_agreement":null},{"id":"W4221037987","doi":"10.1101/2022.03.22.22272765","title":"Generalized and specific whole-brain white matter abnormalities in human cocaine and heroin use disorders","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Cocaine dependence; Heroin; Diffusion MRI; Psychology; Craving; Medicine; Internal medicine; Psychiatry; Drug; Magnetic resonance imaging; Addiction; Radiology","score_opus":0.06394637745264112,"score_gpt":0.3343087726792535,"score_spread":0.27036239522661243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221037987","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9738491,0.0005599097,0.00065386837,0.023480445,0.000046468915,0.00082136405,0.000078888406,0.00014162429,0.0003683285],"genre_scores_gemma":[0.9752504,0.0012050243,0.009078316,0.0028426505,0.00010031398,0.00061935245,0.00040700327,0.00011155195,0.010385365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985509,0.00009496334,0.00035186147,0.0005999837,0.00016472786,0.00023754852],"domain_scores_gemma":[0.9990842,0.00007306146,0.000118016396,0.0006131155,0.000019651454,0.00009199168],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022246095,0.00026733876,0.00042013868,0.00021930793,0.00011616761,0.000064439715,0.00012585535,0.00008788354,0.0002568473],"category_scores_gemma":[0.00001972976,0.00026908322,0.000056737914,0.00012166653,0.00019488754,0.00007049025,0.0006131952,0.00071099325,0.0000025573972],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040790994,0.00008782082,0.98284656,0.00023802085,0.000014490391,0.00004342499,0.00047051144,0.000033350083,0.004887263,0.0014737964,0.00958799,0.0002760068],"study_design_scores_gemma":[0.0011625678,0.00006932053,0.79132015,0.00016914087,0.000032553202,0.00005488714,0.00013880261,0.0001021967,0.00023923321,0.008531731,0.19779663,0.00038278475],"about_ca_topic_score_codex":0.00013456182,"about_ca_topic_score_gemma":0.00005637729,"teacher_disagreement_score":0.19152638,"about_ca_system_score_codex":0.0000488909,"about_ca_system_score_gemma":0.000015308877,"threshold_uncertainty_score":0.99997616},"labels":[],"label_agreement":null},{"id":"W4221040583","doi":"10.21203/rs.3.rs-1393610/v1","title":"The Influence of Regions of Interest on Tractography Virtual Dissection Protocols: General Principles to Learn and to Follow","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université de Montréal","funders":"National Center for Research Resources; National Institutes of Health; Savoy Foundation; Vanderbilt Institute for Clinical and Translational Research","keywords":"Tractography; Dissection (medical); Computer science; Psychology; Artificial intelligence; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.32864026398653134,"score_gpt":0.5148451807995919,"score_spread":0.1862049168130605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221040583","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9744999,0.000024666537,0.00087656575,0.0041949525,0.000013880458,0.019954102,0.00006674092,0.00006126339,0.00030794373],"genre_scores_gemma":[0.96914655,0.0001471139,0.001734888,0.000053811233,0.000045966328,0.02818308,0.000019892275,0.000031446478,0.0006372368],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9983185,0.0001734967,0.0003211424,0.00043398511,0.00051049085,0.00024238077],"domain_scores_gemma":[0.9981419,0.00032896633,0.000111446294,0.0008894118,0.0003611611,0.00016713442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064715813,0.00013512165,0.0002498629,0.00041912086,0.00024023985,0.000027440003,0.00033855435,0.00006792341,0.0000071202303],"category_scores_gemma":[0.0007946834,0.000102011814,0.00010911426,0.00062171544,0.00019377373,0.0000237301,0.0009313076,0.0010945575,9.607804e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010474027,0.0043297545,0.115695015,0.0065279636,0.00040507776,0.000099940335,0.006370485,0.0359915,0.33088994,0.37282607,0.008328618,0.10806163],"study_design_scores_gemma":[0.0009381575,0.013432129,0.5825451,0.006327252,0.00004687442,0.00003191901,0.0016726726,0.0003950766,0.029188719,0.010653853,0.3542698,0.0004984435],"about_ca_topic_score_codex":0.00009364986,"about_ca_topic_score_gemma":0.000058244863,"teacher_disagreement_score":0.4668501,"about_ca_system_score_codex":0.00008093745,"about_ca_system_score_gemma":0.00013441185,"threshold_uncertainty_score":0.47553682},"labels":[],"label_agreement":null},{"id":"W4221046825","doi":"10.21203/rs.3.rs-1423555/v1","title":"The Structural Connectivity of The Human Angular Gyrus as Revealed by Microdissection and Diffusion Tractography","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Angular gyrus; Microdissection; Diffusion MRI; Diffusion; Neuroscience; Psychology; Computer science; Physics; Biology; Medicine; Radiology; Magnetic resonance imaging; Gene; Genetics; Cognition","score_opus":0.07222415710054751,"score_gpt":0.4551734764729809,"score_spread":0.38294931937243337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221046825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9920333,0.001266478,0.00005579713,0.0041553113,0.000048066224,0.0019228155,0.00013079058,0.00006475613,0.00032266646],"genre_scores_gemma":[0.9982983,0.00074491,0.000100715755,0.000041806965,0.000049556078,0.00030646488,0.000081982624,0.00002710225,0.00034917708],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981287,0.0003821422,0.00021425179,0.0004202906,0.0006059964,0.00024860966],"domain_scores_gemma":[0.99833155,0.0003104121,0.00014371423,0.0009320592,0.00020783009,0.000074421005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064327585,0.0001442184,0.00021785605,0.00011377728,0.0012163422,0.000042756397,0.00030809862,0.000100251986,0.000043016513],"category_scores_gemma":[0.00025808957,0.000088088156,0.00015508334,0.0003788691,0.0004478668,0.000023165505,0.0009543642,0.0018080338,2.394226e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026170711,0.00031590083,0.20926623,0.0011275739,0.000091971306,0.000013079662,0.00068338006,0.000006718418,0.7592727,0.0038058246,0.011452992,0.013701956],"study_design_scores_gemma":[0.00068266736,0.0004893549,0.8879044,0.0004598351,0.00006717423,0.00006888637,0.00085060234,0.00015519223,0.028749945,0.04491632,0.03541827,0.00023736896],"about_ca_topic_score_codex":0.0005440189,"about_ca_topic_score_gemma":0.0000246956,"teacher_disagreement_score":0.73052275,"about_ca_system_score_codex":0.000095806456,"about_ca_system_score_gemma":0.00006284072,"threshold_uncertainty_score":0.93552434},"labels":[],"label_agreement":null},{"id":"W4221101861","doi":"10.3174/ajnr.a7472","title":"Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates—A Quantitative MRI Study","year":2022,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Child, Adolescent and Family Mental Health","funders":"","keywords":"Fractional anisotropy; Medicine; Internal capsule; Diffusion MRI; Gestational age; Effective diffusion coefficient; Pons; Gestation; Tegmentum; Nuclear medicine; Magnetic resonance imaging; Midbrain; Anatomy; Internal medicine; White matter; Radiology; Pregnancy; Central nervous system","score_opus":0.0733770881790462,"score_gpt":0.3562800812240091,"score_spread":0.2829029930449629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221101861","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99424344,0.00011298636,0.0011132673,0.0033614838,0.00005394038,0.0010225606,0.00002968698,0.0000135665905,0.00004907268],"genre_scores_gemma":[0.9957182,0.000056304125,0.003317679,0.00069637573,0.000039061502,0.0001327289,0.0000024847056,0.000015844635,0.000021332817],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99882036,0.00033942363,0.00035833093,0.0001877424,0.00016595298,0.00012816532],"domain_scores_gemma":[0.9984575,0.00052231003,0.0006218082,0.00026467687,0.000068471374,0.000065264736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014934503,0.00011144409,0.0004548491,0.00007118023,0.00011357018,0.000004666079,0.00021972215,0.000009470825,0.00005407104],"category_scores_gemma":[0.000061629966,0.00007608433,0.00007764181,0.0001698981,0.00041923134,0.000031174455,0.000143161,0.0005002157,1.891233e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018637757,0.00093630276,0.95432335,0.000012027628,0.0002281992,0.00036340108,0.0033966985,0.000083901316,0.026249414,0.0005733108,0.0016970667,0.010272525],"study_design_scores_gemma":[0.0013064553,0.012277266,0.9722002,0.000018286353,0.00021278579,0.0026272323,0.0043607363,0.00026650948,0.00039392387,0.00081394933,0.005406741,0.00011587839],"about_ca_topic_score_codex":0.000040310148,"about_ca_topic_score_gemma":0.0000013082916,"teacher_disagreement_score":0.025855491,"about_ca_system_score_codex":0.000022064602,"about_ca_system_score_gemma":0.000030832234,"threshold_uncertainty_score":0.3102629},"labels":[],"label_agreement":null},{"id":"W4221112866","doi":"10.1016/j.neuroimage.2022.119029","title":"An atlas of white matter anatomy, its variability, and reproducibility based on constrained spherical deconvolution of diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":103,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke; Vlaamse regering; KU Leuven; Fonds Wetenschappelijk Onderzoek; National Institutes of Health","keywords":"Diffusion MRI; Tractography; White matter; Human Connectome Project; Fractional anisotropy; Anatomy; Computer science; Fornix; Artificial intelligence; Reproducibility; Pattern recognition (psychology); Neuroscience; Psychology; Biology; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Functional connectivity","score_opus":0.030804057224314514,"score_gpt":0.33078766648538926,"score_spread":0.29998360926107476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221112866","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98655754,0.0000062079685,0.00822798,0.0031789301,0.000038588318,0.00069341494,0.00009180592,0.00009148792,0.0011140315],"genre_scores_gemma":[0.9901955,0.0000042344363,0.008898513,0.00072698685,0.000014977956,0.000042700583,0.000031363812,0.000019623225,0.00006607268],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99832135,0.00019165025,0.00033466096,0.000789904,0.00023275518,0.00012965682],"domain_scores_gemma":[0.99820346,0.00011838338,0.00015481267,0.0013574577,0.000085396314,0.00008048127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053626153,0.00011641054,0.00026081587,0.00006250388,0.000118508804,0.0000035215508,0.00010908163,0.000027655082,0.00038659276],"category_scores_gemma":[0.00019764647,0.00011389729,0.000059303817,0.0002447025,0.00019684578,0.000053591666,0.00015736125,0.00024823655,0.0000010789586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005021028,0.0018040639,0.51291037,0.00021899011,0.0000046451055,0.000017394708,0.000083113366,0.0003526016,0.4816216,0.000520024,0.0007850971,0.0011799749],"study_design_scores_gemma":[0.001314306,0.0015223821,0.90979356,0.000027426782,0.000060254795,0.00006826976,0.000027843475,0.05033557,0.033565853,0.0010666226,0.0020482964,0.0001696452],"about_ca_topic_score_codex":0.000008522041,"about_ca_topic_score_gemma":2.9818867e-7,"teacher_disagreement_score":0.44805574,"about_ca_system_score_codex":0.00003317356,"about_ca_system_score_gemma":0.00004677431,"threshold_uncertainty_score":0.46445966},"labels":[],"label_agreement":null},{"id":"W4223539301","doi":"10.1016/j.nicl.2022.103002","title":"Diffusion tensor tractography of the fornix in cerebral amyloid angiopathy, mild cognitive impairment and Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Foothills Medical Centre; Alberta Health Services; University of Calgary; Women and Children’s Health Research Institute; University of Alberta","funders":"Consortium canadien en neurodégénérescence associée au vieillissement; Canada Research Chairs; Canadian Stroke Network; Heart and Stroke Foundation of Canada; Canadian Institutes of Health Research; Alzheimer Society; Fondation Brain Canada","keywords":"Cerebral amyloid angiopathy; Fornix; Diffusion MRI; Tractography; Medicine; Cognitive impairment; Disease; Neuroscience; Alzheimer's disease; Amyloid (mycology); Cognition; Psychology; Pathology; Magnetic resonance imaging; Dementia; Hippocampus; Radiology","score_opus":0.10528279284658656,"score_gpt":0.3941783179935285,"score_spread":0.28889552514694194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223539301","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99406105,0.00024663808,0.0000827618,0.004046119,0.000080711034,0.0011397288,0.00015689891,0.0000639342,0.00012214166],"genre_scores_gemma":[0.99625957,0.0001334882,0.00047149978,0.0028545258,0.000045942135,0.00015685485,0.000018038754,0.00002758657,0.000032495216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99841785,0.00019125396,0.0004925736,0.0004505263,0.00025327082,0.000194508],"domain_scores_gemma":[0.99889034,0.0003266595,0.00017017654,0.00041427888,0.000041114476,0.00015743483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024708515,0.00013748645,0.00027932276,0.00008864535,0.00014022042,0.000006594159,0.00014608909,0.000029259561,0.000038699767],"category_scores_gemma":[0.00018968523,0.000104980434,0.00025774958,0.0003292632,0.00031530915,0.000041956708,0.00036543226,0.00061763456,9.634003e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007186722,0.0016673226,0.99101716,0.000018972458,0.000012300446,0.00006964769,0.00005770147,0.000002280099,0.0007385555,0.00008591104,0.00072711456,0.004884341],"study_design_scores_gemma":[0.0018236989,0.0005521818,0.99436325,0.00004559246,0.00016648918,0.00003527723,0.000068866444,0.0004739908,0.00017903953,0.0005007543,0.0016955966,0.00009525036],"about_ca_topic_score_codex":0.000009327634,"about_ca_topic_score_gemma":0.0000014321399,"teacher_disagreement_score":0.0047890902,"about_ca_system_score_codex":0.000010727976,"about_ca_system_score_gemma":0.000051002546,"threshold_uncertainty_score":0.42809778},"labels":[],"label_agreement":null},{"id":"W4223585515","doi":"10.1101/2022.04.06.487283","title":"DeepParcellation: a novel deep learning method for robust brain magnetic resonance imaging parcellation in older East Asians","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Research Foundation; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; Ministry of Science and ICT, South Korea; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Korea Brain Research Institute; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Magnetic resonance imaging; Dementia; Similarity (geometry); Brain aging; Neuroscience; Psychology; Brain morphometry; Medicine; Artificial intelligence; Computer science; Pathology; Cognition; Disease; Radiology","score_opus":0.036701757709266446,"score_gpt":0.30073401899341573,"score_spread":0.2640322612841493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223585515","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021137524,0.0032442713,0.9666545,0.0039167125,0.00023683494,0.0037093302,0.00012906385,0.0009021681,0.00006962854],"genre_scores_gemma":[0.41422972,0.00013759662,0.58256775,0.00065344386,0.0002855605,0.0018156791,0.0000066394973,0.0002442293,0.00005935218],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99674755,0.00015094255,0.0007237813,0.0013758935,0.00039298588,0.0006088182],"domain_scores_gemma":[0.99774694,0.00025264852,0.0004362368,0.001063586,0.00030919194,0.00019139721],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00088740606,0.0005179163,0.00063026865,0.00046530302,0.00031192534,0.00009813538,0.00034582464,0.00022193532,0.00012247953],"category_scores_gemma":[0.0003847822,0.00064026844,0.00019770041,0.0007935823,0.00008280715,0.0001064658,0.00040753177,0.001407914,0.0000052994983],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047243998,0.001336313,0.1547913,0.0021446387,0.000072579984,0.0001833302,0.0002580305,0.04091834,0.79118544,0.005451667,0.00093440147,0.002251508],"study_design_scores_gemma":[0.0032853882,0.00017231145,0.34316468,0.00094588555,0.00023858629,8.14565e-7,0.00004166798,0.50527716,0.008066128,0.00004200233,0.13736123,0.001404171],"about_ca_topic_score_codex":0.000034317087,"about_ca_topic_score_gemma":0.0000031978636,"teacher_disagreement_score":0.7831193,"about_ca_system_score_codex":0.00050104334,"about_ca_system_score_gemma":0.00026451374,"threshold_uncertainty_score":0.9996049},"labels":[],"label_agreement":null},{"id":"W4223652742","doi":"10.1093/brain/awac138","title":"Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; European Research Council; Stiftelsen för Gamla Tjänarinnor; Familjen Erling-Perssons Stiftelse; School of Medicine, Indiana University; Vetenskapsrådet; UK Dementia Research Institute; National Institutes of Health; Olav Thon Stiftelsen; Hjärnfonden; European Commission; Alzheimer's Drug Discovery Foundation; National Institute on Aging; Alzheimer's Association","keywords":"Hippocampal formation; Alzheimer's disease; Psychology; Dementia; Neuroscience; Pathology; Dentate gyrus; Medicine; Disease","score_opus":0.043931317747419346,"score_gpt":0.32520332046530426,"score_spread":0.2812720027178849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223652742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9672344,0.0003360339,0.0009237303,0.030401245,0.000030024576,0.00059698115,0.00004391482,0.00009858442,0.00033511492],"genre_scores_gemma":[0.9928694,0.0000083081395,0.0029881764,0.0038845856,0.000016931048,0.00012790963,0.00003273032,0.00001319969,0.000058769612],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99952585,0.00002498258,0.00009801682,0.00019295253,0.000058206955,0.000100020035],"domain_scores_gemma":[0.99963075,0.00007061529,0.000023822595,0.00017747925,0.000006583457,0.00009077027],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072471135,0.00006862533,0.000077472,0.00009378668,0.00008540531,0.0000062801596,0.000047808793,0.000013801291,0.00004236828],"category_scores_gemma":[0.000059433358,0.00006320011,0.000021017493,0.0001858436,0.000023351125,0.000023090653,0.00008055092,0.0001203107,0.0000014174113],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002021448,0.0003673881,0.15924554,0.00006734175,0.00012253944,0.0001776564,0.0030840838,0.00051870535,0.382451,0.011989863,0.13671,0.30324444],"study_design_scores_gemma":[0.0016991115,0.0002949508,0.7010521,0.00006027797,0.00005587318,0.00014742182,0.0005740268,0.0030382352,0.0096469065,0.025866995,0.2571625,0.00040155876],"about_ca_topic_score_codex":0.00001394475,"about_ca_topic_score_gemma":0.000003290821,"teacher_disagreement_score":0.5418066,"about_ca_system_score_codex":0.000022677134,"about_ca_system_score_gemma":0.000021643982,"threshold_uncertainty_score":0.25772256},"labels":[],"label_agreement":null},{"id":"W4223898804","doi":"10.1371/journal.pone.0265112","title":"Getting the nod: Pediatric head motion in a transdiagnostic sample during movie- and resting-state fMRI","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital; University of Waterloo","funders":"BC Children's Hospital","keywords":"Motion (physics); Artifact (error); Motion sickness; Artificial intelligence; Rotation (mathematics); Computer science; Translation (biology); Head (geology); Computer vision; Psychology; Biology","score_opus":0.08971848270196725,"score_gpt":0.30490450389511703,"score_spread":0.21518602119314978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223898804","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9926607,0.00024426114,0.0012313323,0.0050815106,0.0000052581095,0.0005671145,0.000019258585,0.00013521832,0.00005533915],"genre_scores_gemma":[0.99130434,0.00025373863,0.0076764445,0.0002986634,0.000056929228,0.00032451987,0.000011270412,0.000020940943,0.00005317603],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925536,0.000037655223,0.00016784546,0.00020217942,0.0001758765,0.00016109593],"domain_scores_gemma":[0.99939674,0.00030187354,0.00005255281,0.00019231257,0.000018205445,0.000038295144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014797956,0.00007209734,0.0001232503,0.0000864574,0.00023467313,0.000008635632,0.00006247157,0.000010400078,0.000016546195],"category_scores_gemma":[0.00028381395,0.00006508913,0.000018079303,0.0003095331,0.000022281842,0.000035741417,0.00006429625,0.0003198078,0.0000011893651],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020634587,0.003316598,0.8627239,0.0011069636,0.000045254365,0.00015434837,0.0032893934,0.0012185439,0.119419076,0.00038599884,0.000101424564,0.008032141],"study_design_scores_gemma":[0.0023930974,0.00037585568,0.9594166,0.00026808766,0.0003345699,0.000114157905,0.00025953117,0.015474913,0.012223343,0.008511789,0.00025018328,0.00037781746],"about_ca_topic_score_codex":0.000070511254,"about_ca_topic_score_gemma":0.000010470338,"teacher_disagreement_score":0.107195735,"about_ca_system_score_codex":0.000045103305,"about_ca_system_score_gemma":0.000014267301,"threshold_uncertainty_score":0.26542577},"labels":[],"label_agreement":null},{"id":"W4223972788","doi":"10.31234/osf.io/kt5gz","title":"Beyond the brain localization of complex traits: Distributed white matter markers of personality","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Government of Canada; University of Oregon","keywords":"Neuroimaging; Neuroticism; Psychology; Big Five personality traits; Univariate; White matter; Personality; Diffusion MRI; Multivariate statistics; Openness to experience; Cognitive psychology; Computer science; Neuroscience; Machine learning; Social psychology; Magnetic resonance imaging; Medicine","score_opus":0.061644776505234054,"score_gpt":0.3498774670672752,"score_spread":0.28823269056204115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223972788","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0113558015,0.00005493169,0.91522115,0.05112622,0.000042798365,0.0017480857,0.0026226444,0.00015733589,0.017671049],"genre_scores_gemma":[0.9746953,0.000028547964,0.014599909,0.0056029013,0.000036059548,0.00020565889,0.003295955,0.000040555587,0.0014950786],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99884874,0.0000786467,0.00040713476,0.00028923195,0.00026531162,0.00011091761],"domain_scores_gemma":[0.9988822,0.0000972269,0.0003039537,0.0005557701,0.00012350047,0.000037355523],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000216039,0.00014786358,0.00033300024,0.000050329876,0.000060923863,0.000005503325,0.00022736024,0.000063040556,0.003627582],"category_scores_gemma":[0.000035471367,0.000110157474,0.0001567305,0.00020796702,0.00021016251,0.000015347088,0.00036055146,0.00035422144,0.000001131493],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055516855,0.0009428948,0.14868666,0.0026749487,0.00031568317,0.000006127669,0.00084594125,0.0037742034,0.004429308,0.015564564,0.8183606,0.003843878],"study_design_scores_gemma":[0.001148369,0.00025438372,0.7511615,0.00025403072,0.00047854622,0.00004558166,0.0010851655,0.025885891,0.0016071588,0.028183324,0.18937814,0.00051788305],"about_ca_topic_score_codex":0.00007060062,"about_ca_topic_score_gemma":0.000003341107,"teacher_disagreement_score":0.9633395,"about_ca_system_score_codex":0.000056403434,"about_ca_system_score_gemma":0.00006222621,"threshold_uncertainty_score":0.9972832},"labels":[],"label_agreement":null},{"id":"W4224041279","doi":"10.1101/2022.04.01.486632","title":"Microstructural alterations in tract development in college football: a longitudinal diffusion MRI study","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Diffusion MRI; Concussion; Fractional anisotropy; Football; Corpus callosum; Psychology; Cingulum (brain); White matter; Superior longitudinal fasciculus; Medicine; Fasciculus; American football; Physical therapy; Nuclear medicine; Magnetic resonance imaging; Anatomy; Poison control; Radiology; Injury prevention","score_opus":0.041154211829111435,"score_gpt":0.3058215730080448,"score_spread":0.26466736117893336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224041279","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99443036,0.0001744112,0.0009365311,0.000529102,0.00021552626,0.0032662,0.00014053732,0.00029772613,0.000009591199],"genre_scores_gemma":[0.97111505,0.000062975065,0.026568508,0.00014374928,0.000077808574,0.0019211977,0.0000025028755,0.00009601732,0.000012204133],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99712664,0.00010963812,0.00080283405,0.0011104407,0.00039491444,0.0004555185],"domain_scores_gemma":[0.9983658,0.000052711042,0.0002666344,0.0010113053,0.0001432953,0.00016020983],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038550523,0.00046366962,0.00063028134,0.0006030725,0.00021421455,0.000060928236,0.00036495365,0.00016700078,0.000080092024],"category_scores_gemma":[0.000063989995,0.0005061704,0.00009048479,0.00087165704,0.00005682077,0.00009120514,0.0006920937,0.0013774247,0.000005879792],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016277956,0.003159976,0.7686802,0.0002472634,0.000055133107,0.0009579651,0.00013846945,0.00014670385,0.2258547,0.00037694792,0.00021228919,0.000007559672],"study_design_scores_gemma":[0.0014224934,0.00012839769,0.97948235,0.00026922306,0.000049594793,2.7236874e-7,0.000026748605,0.00039841913,0.013789423,0.00000485511,0.003933803,0.0004944082],"about_ca_topic_score_codex":0.00010250695,"about_ca_topic_score_gemma":0.000042876418,"teacher_disagreement_score":0.21206526,"about_ca_system_score_codex":0.0009861782,"about_ca_system_score_gemma":0.00068764895,"threshold_uncertainty_score":0.999739},"labels":[],"label_agreement":null},{"id":"W4224122545","doi":"10.3390/curroncol29040230","title":"DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects","year":2022,"lang":"en","type":"article","venue":"Current Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Diffusion MRI; Fractional anisotropy; Metastasis; Effective diffusion coefficient; Pathology; Lesion; White matter; Magnetic resonance imaging; Nuclear medicine; Glioblastoma; Internal medicine; Radiology; Cancer; Cancer research","score_opus":0.17464533463702409,"score_gpt":0.47267599084693895,"score_spread":0.29803065620991487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224122545","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99338764,0.00039887655,0.00043782138,0.002098017,0.000082172206,0.0025930402,0.000031064017,0.00018445906,0.0007869038],"genre_scores_gemma":[0.99650645,0.000020194713,0.0012800348,0.00025099574,0.00001751384,0.0018007866,0.000009656467,0.000014820885,0.00009952033],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989366,0.00012642327,0.00020131248,0.00036676755,0.0001625126,0.00020641723],"domain_scores_gemma":[0.999385,0.00009117552,0.000095483716,0.00020610813,0.00009345037,0.00012877368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016382209,0.00013100701,0.00036477638,0.00014735755,0.0002785406,0.0000061066303,0.00007010055,0.0000142555455,0.000039803068],"category_scores_gemma":[0.00001623526,0.000110734436,0.000022811644,0.00046666764,0.00009935558,0.000039563223,0.00017236202,0.0004062168,0.0000042242627],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.020389253,0.023339704,0.7864355,0.00027336937,0.00065789133,0.00056493015,0.082864515,0.000289082,0.0007504303,0.026073819,0.01806306,0.040298495],"study_design_scores_gemma":[0.01765844,0.1668486,0.2540025,0.00009331122,0.0008623244,0.002870569,0.067002,0.0005686189,0.0014405972,0.0045185913,0.4831645,0.0009699456],"about_ca_topic_score_codex":0.000013820994,"about_ca_topic_score_gemma":0.00003070294,"teacher_disagreement_score":0.5324329,"about_ca_system_score_codex":0.0002655471,"about_ca_system_score_gemma":0.00012798293,"threshold_uncertainty_score":0.45156193},"labels":[],"label_agreement":null},{"id":"W4224223785","doi":"10.3390/brainsci12040482","title":"Association between Changes in White Matter Microstructure and Cognitive Impairment in White Matter Lesions","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Fractional anisotropy; Inferior longitudinal fasciculus; Diffusion MRI; Fasciculus; White matter; Hyperintensity; Superior longitudinal fasciculus; Corticospinal tract; Uncinate fasciculus; Psychology; Medicine; Cardiology; Audiology; Pathology; Magnetic resonance imaging; Radiology","score_opus":0.03759646584237306,"score_gpt":0.34284817022069564,"score_spread":0.30525170437832255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224223785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89072126,0.000036288755,0.00009595136,0.10805461,0.000019243065,0.0004151096,0.00006698587,0.000023157718,0.0005673881],"genre_scores_gemma":[0.9892743,0.000008064116,0.0013067032,0.0079291435,0.000027660128,0.00013312275,0.000018863846,0.0000069633184,0.0012951538],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991347,0.000058093432,0.00012872857,0.0002816074,0.0001995102,0.00019735945],"domain_scores_gemma":[0.99967444,0.000119584096,0.00007719338,0.00007667225,0.000016239846,0.000035855202],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038463317,0.00007613929,0.00012796231,0.00019388444,0.00017417036,0.000025143818,0.00008444817,0.000024544248,0.0003012334],"category_scores_gemma":[0.000026120095,0.000068025685,0.000015381476,0.00050111057,0.000091283866,0.00006783384,0.00013010323,0.00019029563,0.0000064282067],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046765936,0.000020728738,0.9925548,0.00000693786,0.0000017908715,0.0000030119616,0.0005946466,0.0000039554275,0.0006162814,0.0000084165695,0.005746896,0.00043789062],"study_design_scores_gemma":[0.00029745346,0.0000798527,0.99591494,0.000037821534,0.000009252802,0.000013946543,0.0006259018,0.000032778094,0.00019913411,0.0008466877,0.001867409,0.00007482202],"about_ca_topic_score_codex":0.000021424981,"about_ca_topic_score_gemma":0.000052785905,"teacher_disagreement_score":0.10012546,"about_ca_system_score_codex":0.00008394388,"about_ca_system_score_gemma":0.000026055755,"threshold_uncertainty_score":0.32982945},"labels":[],"label_agreement":null},{"id":"W4224248311","doi":"10.1111/ejn.15668","title":"Sulci and gyri are topological cerebral landmarks in individual subjects: a study of brain navigation during tumour resection","year":2022,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Neuronavigation; Corticospinal tract; Tractography; Diffusion MRI; Medicine; Lesion; Human brain; Magnetic resonance imaging; Cortex (anatomy); Resection; Transcranial magnetic stimulation; Pyramidal tracts; Neuroscience; Neuroplasticity; Anatomy; Brain mapping; Psychology; Radiology; Pathology; Surgery; Stimulation","score_opus":0.08499377395791288,"score_gpt":0.3500477181503772,"score_spread":0.2650539441924643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224248311","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99852264,0.000021715032,0.00015239201,0.0009503379,0.00006273357,0.00018807963,0.000004050371,0.000015802383,0.00008225916],"genre_scores_gemma":[0.99946296,0.00000949961,0.00025235317,0.00019818405,0.000036225083,0.0000028817042,5.538419e-7,0.000009550839,0.000027801343],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99864787,0.00037680828,0.0003396742,0.00018648915,0.000332301,0.00011683125],"domain_scores_gemma":[0.99940234,0.000049393602,0.00032889235,0.000115272895,0.00004204637,0.000062050734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007607232,0.000068125824,0.00014955689,0.00018926644,0.00015189523,0.000015990372,0.00017806896,0.000005592993,0.0000039265],"category_scores_gemma":[0.00026879678,0.000059112175,0.00002644477,0.00043904135,0.00008228393,0.00011390945,0.00018985823,0.00046176382,1.1102525e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006008731,0.0012681818,0.4490929,0.000043744218,0.000003819304,0.002453782,0.0019574084,0.0006495785,0.5427663,0.000067767396,0.00012433756,0.0009713516],"study_design_scores_gemma":[0.0011677267,0.002418577,0.9918681,0.00004321894,0.000008700336,0.0018218668,0.0010112027,0.00010567778,0.0013260612,0.00005232028,0.00012767634,0.000048884423],"about_ca_topic_score_codex":0.0000035162714,"about_ca_topic_score_gemma":0.0000012771499,"teacher_disagreement_score":0.5427752,"about_ca_system_score_codex":0.000028733446,"about_ca_system_score_gemma":0.000019624906,"threshold_uncertainty_score":0.24105245},"labels":[],"label_agreement":null},{"id":"W4224438895","doi":"10.1002/hbm.25885","title":"Longitudinal white matter microstructural changes in pediatric mild traumatic brain injury: An<scp>A‐CAP</scp>study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; University of British Columbia; University of Alberta; Ontario Brain Institute; Université de Montréal; Hotchkiss Brain Institute; Centre Hospitalier Universitaire Sainte-Justine; University of Ottawa; Stollery Children's Hospital; Alberta Children's Hospital; Children's Hospital of Eastern Ontario; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; White matter; Traumatic brain injury; Medicine; Superior longitudinal fasciculus; Concussion; Post-concussion syndrome; Poison control; Diffusion MRI; Uncinate fasciculus; Pediatrics; Anesthesia; Injury prevention; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.10865613396813091,"score_gpt":0.36390818923137197,"score_spread":0.2552520552632411,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224438895","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99056876,0.00006987786,0.000341246,0.0068885465,0.00005884318,0.0013834431,0.00002570526,0.00026709193,0.00039649897],"genre_scores_gemma":[0.99097383,0.000003969098,0.0018256957,0.004893387,0.00024563636,0.0005430626,0.000090202506,0.00006985076,0.0013543558],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99798805,0.0001641195,0.00041307617,0.0006429217,0.00031432204,0.0004775434],"domain_scores_gemma":[0.99893355,0.00013339234,0.0001812471,0.0006012892,0.000033442062,0.00011709126],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000437096,0.00027295118,0.00038307553,0.0005807393,0.0005546985,0.000053521406,0.00031510496,0.00004261349,0.00024407405],"category_scores_gemma":[0.0000558149,0.00029469997,0.000074758944,0.0007544935,0.00005871091,0.00012226868,0.00026617668,0.0006292552,0.000017609764],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014215659,0.00045570292,0.9217551,0.00016619136,0.000015832855,0.0000824017,0.006365123,0.000025191339,0.029912647,0.00018005876,0.04073345,0.00029411507],"study_design_scores_gemma":[0.0009330248,0.00042962618,0.9889981,0.000030896244,0.000034834025,0.00010525374,0.0028751455,0.00012376504,0.00006913217,0.0011210378,0.0051211882,0.00015795765],"about_ca_topic_score_codex":0.000037056394,"about_ca_topic_score_gemma":0.00006983596,"teacher_disagreement_score":0.06724307,"about_ca_system_score_codex":0.000137445,"about_ca_system_score_gemma":0.000026213795,"threshold_uncertainty_score":0.9999505},"labels":[],"label_agreement":null},{"id":"W4224927688","doi":"10.3389/fneur.2022.794618","title":"Superior Longitudinal Fasciculus: A Review of the Anatomical Descriptions With Functional Correlates","year":2022,"lang":"en","type":"review","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":181,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Arcuate fasciculus; Confusion; Uncinate fasciculus; Superior longitudinal fasciculus; Lateralization of brain function; Tractography; Diffusion MRI; Psychology; Neuroscience; Frontal lobe; Association (psychology); Anatomy; Medicine; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.09409050236680269,"score_gpt":0.34079267399001545,"score_spread":0.24670217162321276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224927688","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00003246389,0.9942283,0.0021248278,0.001360011,0.00045533484,0.0015363211,0.000046777088,0.000052971693,0.00016299465],"genre_scores_gemma":[0.000019788868,0.99563324,0.0019927993,0.0013212592,0.00004135213,0.00074771413,0.000086741646,0.000045219113,0.000111867404],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99838436,0.00020202006,0.0005209561,0.00046596426,0.00021008219,0.00021664808],"domain_scores_gemma":[0.99891096,0.0001009351,0.00026991998,0.00063090795,0.000036074438,0.000051222418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013228144,0.00024771533,0.0012512365,0.00018903692,0.00009054031,0.0000030155352,0.0002865911,0.00012142069,0.0001783454],"category_scores_gemma":[0.00011680137,0.00015752055,0.00034285354,0.00080655294,0.0003466341,0.000028233522,0.00017600322,0.0012371627,0.0000019413185],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003510308,0.0010469755,0.04395894,0.09708005,0.00043595463,0.0004210252,0.000032031505,0.000019281002,0.0000023847574,0.0028206294,0.21081792,0.6430138],"study_design_scores_gemma":[0.00019003385,0.00018339585,0.00071442185,0.0072213174,0.0007147024,0.0014605045,0.0000025588786,0.000027435566,2.2585306e-7,0.00012798393,0.9892407,0.00011670648],"about_ca_topic_score_codex":0.0000036059828,"about_ca_topic_score_gemma":0.0000013279304,"teacher_disagreement_score":0.7784228,"about_ca_system_score_codex":0.00008225726,"about_ca_system_score_gemma":0.00029866328,"threshold_uncertainty_score":0.64235014},"labels":[],"label_agreement":null},{"id":"W4224938342","doi":"10.3389/fnagi.2022.787516","title":"Modeling the Properties of White Matter Tracts Using Diffusion Tensor Imaging to Characterize Patterns of Injury in Aging and Neurodegenerative Disease","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Meso Scale Diagnostics; Medical Research Council; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; White matter; Ventriculomegaly; Tractography; Atlas (anatomy); Internal capsule; Magnetic resonance imaging; Neuroimaging; Neuroscience; Medicine; Psychology; Radiology; Anatomy; Biology","score_opus":0.04696226911690202,"score_gpt":0.2971753095410107,"score_spread":0.25021304042410863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224938342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9460487,0.00007481632,0.049904935,0.0032846106,0.00013768993,0.0004990674,0.000025555986,0.00002191044,0.0000027602189],"genre_scores_gemma":[0.9946145,0.000032733333,0.0029877336,0.002239567,0.000012677333,0.00006328344,0.0000011857438,0.000021698554,0.000026651343],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867564,0.00008927557,0.00032177113,0.00041871183,0.0002588361,0.00023578393],"domain_scores_gemma":[0.999473,0.000010419624,0.0001067873,0.00030614558,0.00003156842,0.00007209756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020810506,0.00012984111,0.00022077822,0.00032163895,0.0002287639,0.000017465134,0.00021774926,0.000007388085,0.0000015493191],"category_scores_gemma":[0.00006173595,0.0001064415,0.0000317556,0.00048806032,0.000114539456,0.00017190697,0.0004304813,0.00027175996,3.3681854e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047320107,0.00006311569,0.72246164,0.000048658705,3.576735e-7,0.000012409032,0.001096039,0.01203053,0.26381993,0.0000047099015,0.000009577311,0.0004057274],"study_design_scores_gemma":[0.00020422821,0.000031266776,0.40509942,0.0002615383,0.000012211515,0.000020461506,0.00040284346,0.587557,0.006191454,0.000047145513,0.000052784442,0.00011964192],"about_ca_topic_score_codex":0.0000567467,"about_ca_topic_score_gemma":6.23755e-7,"teacher_disagreement_score":0.5755265,"about_ca_system_score_codex":0.00005283517,"about_ca_system_score_gemma":0.000043094467,"threshold_uncertainty_score":0.43405584},"labels":[],"label_agreement":null},{"id":"W4224946110","doi":"10.1101/2022.01.27.477925","title":"High spatial overlap but diverging age-related trajectories of cortical MRI markers aiming to represent intracortical myelin and microstructure","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Weston Brain Institute","keywords":"White matter; Magnetic resonance imaging; Myelin; Correlation; Nuclear magnetic resonance; Neuroscience; Psychology; Medicine; Mathematics; Physics; Radiology; Central nervous system; Geometry","score_opus":0.017823158920201615,"score_gpt":0.2704345351924193,"score_spread":0.25261137627221764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224946110","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9841616,0.00023385846,0.011747489,0.0012498827,0.00047294126,0.0013493868,0.0003479231,0.00042950484,0.0000074090544],"genre_scores_gemma":[0.9536127,0.0002006645,0.045410927,0.00024247386,0.00020327575,0.00020284575,0.0000026408018,0.00011465577,0.000009854994],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99701613,0.000105173036,0.00079422805,0.0011397337,0.00047531872,0.0004694256],"domain_scores_gemma":[0.9977114,0.00014819176,0.00033125578,0.0011806757,0.00023939504,0.0003890395],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028686872,0.00046944933,0.00081024726,0.00025093002,0.00022583122,0.000063362604,0.0003061997,0.00031730512,0.00011549094],"category_scores_gemma":[0.000480372,0.0005014912,0.00015610408,0.00043433733,0.0003338538,0.00005939991,0.0011225791,0.001538771,0.000002410489],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034789759,0.00015787076,0.030961003,0.00043292547,0.00017081248,0.00033225262,0.000036756745,0.00022606947,0.9648892,0.0021410927,0.00027754513,0.00002656884],"study_design_scores_gemma":[0.0010078351,0.00027982233,0.75892127,0.00059182016,0.00057014875,9.1118886e-7,0.00002760281,0.001097645,0.2345925,0.000062867155,0.0020125671,0.0008350154],"about_ca_topic_score_codex":0.00025134362,"about_ca_topic_score_gemma":0.000001524693,"teacher_disagreement_score":0.73029673,"about_ca_system_score_codex":0.00024081954,"about_ca_system_score_gemma":0.00025761395,"threshold_uncertainty_score":0.9997437},"labels":[],"label_agreement":null},{"id":"W4224993524","doi":"10.1016/j.biopsych.2022.02.397","title":"P163. Fiber Density vs. Dispersion in 16p11.2 Deletion: A Multi-Site Study of Advanced Diffusion MRI Measures","year":2022,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Dispersion (optics); Kurtosis; White matter; Nuclear magnetic resonance; Fiber; Autism; Autism spectrum disorder; Neuroscience; Psychology; Magnetic resonance imaging; Medicine; Materials science; Physics; Mathematics; Statistics; Optics; Radiology; Developmental psychology","score_opus":0.07287817465902083,"score_gpt":0.34748943342616767,"score_spread":0.27461125876714687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224993524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9955872,0.0002784189,0.0012040222,0.0016631655,0.00010806668,0.0009194326,0.000014030809,0.00013300046,0.0000926405],"genre_scores_gemma":[0.98699754,0.00010589736,0.012116709,0.00046606807,0.000039154074,0.00014840106,0.000031006824,0.000011662904,0.00008356059],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879545,0.000117720236,0.00030321535,0.0004208291,0.00019211222,0.00017066873],"domain_scores_gemma":[0.99938506,0.00003512948,0.00011460403,0.00035961924,0.00004082852,0.00006478284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016394383,0.00013491121,0.00028301214,0.00008264539,0.00016243967,0.000002685727,0.0001306781,0.000054436172,0.00013059296],"category_scores_gemma":[0.000039443814,0.00010287022,0.000085271255,0.0003300218,0.000053427888,0.0000234846,0.00021724602,0.00034447465,0.000006512703],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090674596,0.0051177456,0.97152543,0.00001823706,0.000009017392,0.000011263081,0.00013457685,0.00014291522,0.016271962,0.00019067762,0.0006600817,0.005011362],"study_design_scores_gemma":[0.0026275117,0.0019382641,0.98462814,0.00003165758,0.000023142846,0.000024307605,0.0006135061,0.0003239282,0.000117335265,0.00048953673,0.00902424,0.00015843788],"about_ca_topic_score_codex":0.00003369246,"about_ca_topic_score_gemma":0.000025466492,"teacher_disagreement_score":0.016154626,"about_ca_system_score_codex":0.00005871997,"about_ca_system_score_gemma":0.000021178359,"threshold_uncertainty_score":0.41949257},"labels":[],"label_agreement":null},{"id":"W4225269802","doi":"10.1002/hbm.25882","title":"Sex‐ and age‐specific associations between cardiometabolic risk and white matter brain age in the <scp>UK</scp> Biobank cohort","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"H2020 European Research Council; Helse Sør-Øst RHF; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Diabetes UK; Universitetet i Oslo; Fondation Leenaards; Horizon 2020 Framework Programme; Academy of Medical Sciences; Norges Forskningsråd; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Commission; Wellcome Trust; Alzheimer's Society; British Heart Foundation; National Science Foundation","keywords":"Body mass index; Demography; Cohort; Risk factor; Waist–hip ratio; Biobank; Gerontology; Waist; Medicine; Psychology; Internal medicine; Biology; Bioinformatics","score_opus":0.06227182811688249,"score_gpt":0.3181738456354622,"score_spread":0.2559020175185797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225269802","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98505676,0.00028382122,0.002811784,0.0059869844,0.000020691235,0.0010206742,0.00014300559,0.00014231402,0.004533961],"genre_scores_gemma":[0.99232954,0.00005804868,0.0012769883,0.004044962,0.00017525008,0.0002754594,0.00021047847,0.000036593756,0.0015926728],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99845636,0.00026104957,0.0003029888,0.00042299926,0.00026362148,0.00029300718],"domain_scores_gemma":[0.99876577,0.0005658002,0.00014593867,0.00043915783,0.000017871515,0.00006545322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011134335,0.000166882,0.00036859437,0.0002996012,0.0007982764,0.000083433,0.00016697535,0.000043972315,0.000024968707],"category_scores_gemma":[0.0001075438,0.00015614221,0.000065233,0.00056592026,0.00012749809,0.000054028005,0.00020746306,0.0005949438,0.000004147431],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[4.12747e-7,0.000025545318,0.95093983,0.000013717666,0.00003156374,0.00003694411,0.002663469,0.000006029736,0.0029229564,0.00078777695,0.04174601,0.0008257274],"study_design_scores_gemma":[0.0003229039,0.000025296726,0.8131699,0.000012706672,0.000035434165,0.000024248475,0.00064720964,0.000009534026,0.000005926246,0.0040600393,0.18162936,0.000057413614],"about_ca_topic_score_codex":0.000042788284,"about_ca_topic_score_gemma":0.000010098758,"teacher_disagreement_score":0.13988335,"about_ca_system_score_codex":0.00006713587,"about_ca_system_score_gemma":0.000011267703,"threshold_uncertainty_score":0.6367294},"labels":[],"label_agreement":null},{"id":"W4225585094","doi":"10.3389/fnagi.2022.793991","title":"Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Alzheimer's Disease Neuroimaging Initiative","keywords":"White matter; Diffusion MRI; Cognitive impairment; Cognition; Montreal Cognitive Assessment; Neuroscience; Psychology; Effects of sleep deprivation on cognitive performance; Cohort; Cognitive decline; Magnetic resonance imaging; Internal medicine; Medicine; Audiology; Dementia; Disease; Radiology","score_opus":0.017339194989355808,"score_gpt":0.29404084236498956,"score_spread":0.27670164737563374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225585094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96921825,0.000014811592,0.029559352,0.00070548145,0.00006238413,0.00037330366,0.000029453344,0.000018980254,0.000018000012],"genre_scores_gemma":[0.99649966,0.0000030607944,0.0020774573,0.0013383657,0.0000025050965,0.000039188435,0.000011713354,0.0000072226353,0.000020813595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902445,0.000071976385,0.00015907601,0.0003713992,0.00019366432,0.00017942116],"domain_scores_gemma":[0.9996339,0.00004466601,0.00009302294,0.0001593753,0.000026420486,0.000042600743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016603788,0.00009227463,0.00024034573,0.0003872556,0.00008632563,0.0000092065975,0.000095961324,0.0000124533435,0.000006508368],"category_scores_gemma":[0.000032458425,0.0000828471,0.000027561784,0.0015004093,0.00020105684,0.000086778135,0.00013042634,0.0003624641,1.785541e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009479205,0.00007990348,0.99634445,0.000006498519,0.0000053534645,0.000004641534,0.0001515405,0.0027807956,0.000016408289,0.0000050705426,0.0001424122,0.00036814707],"study_design_scores_gemma":[0.00062319543,0.00015152215,0.9325007,0.000022676379,0.000048910475,0.0000023517007,0.0001104483,0.06638336,0.000019656258,0.000051997533,0.000011821646,0.00007332118],"about_ca_topic_score_codex":0.000032479427,"about_ca_topic_score_gemma":0.00000690249,"teacher_disagreement_score":0.0638437,"about_ca_system_score_codex":0.000074072115,"about_ca_system_score_gemma":0.000018434232,"threshold_uncertainty_score":0.33784068},"labels":[],"label_agreement":null},{"id":"W4225621567","doi":"10.1161/circulationaha.122.059281","title":"What Turns the White Matter White? Metabolomic Clues to the Origin of Age-Related Cerebral White Matter Hyperintensities","year":2022,"lang":"en","type":"letter","venue":"Circulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Medical Research Council; Canadian Institutes of Health Research","keywords":"Hyperintensity; Medicine; White matter; White (mutation); Leukoaraiosis; Pathology; Magnetic resonance imaging; Radiology; Genetics; Biology","score_opus":0.04332406163886266,"score_gpt":0.3005223714069434,"score_spread":0.2571983097680807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225621567","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02884291,0.00031067594,0.0016882013,0.9647598,0.0007757473,0.0018057008,0.0000902692,0.00019101753,0.0015356528],"genre_scores_gemma":[0.32977504,0.000069351365,0.00092911546,0.6544787,0.0010351882,0.0005415734,0.001154854,0.00017742677,0.011838747],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978401,0.00017034699,0.00059628405,0.00056940195,0.0004700866,0.00035379076],"domain_scores_gemma":[0.99797314,0.00007874407,0.00036524155,0.0013643962,0.0001721923,0.00004627189],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021857055,0.00037442768,0.00053168886,0.00022749467,0.00021400453,0.00012816892,0.00041618568,0.0002329379,0.002538956],"category_scores_gemma":[0.000017053759,0.0002479973,0.00029012733,0.00044266332,0.00019407437,0.00021890047,0.00020160268,0.0015109467,0.00024321063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003116393,0.000022152959,0.067109965,0.00013204537,0.00009504966,0.000027875332,0.0018442532,0.0007536459,0.00029836438,0.000074819465,0.9294892,0.00012146772],"study_design_scores_gemma":[0.00022241483,0.00002866533,0.26602316,0.00015775341,0.00037272915,0.00023116711,0.0003967677,0.00028828328,0.000044314344,0.0010768577,0.7308642,0.00029368929],"about_ca_topic_score_codex":0.000020526799,"about_ca_topic_score_gemma":0.000003822887,"teacher_disagreement_score":0.31028113,"about_ca_system_score_codex":0.0001341998,"about_ca_system_score_gemma":0.000043780175,"threshold_uncertainty_score":0.9999972},"labels":[],"label_agreement":null},{"id":"W4225657792","doi":"10.1093/cercor/bhac132","title":"Morphological patterns and spatial probability maps of the superior parietal sulcus in the human brain","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Sulcus; Superior parietal lobule; Central sulcus; Parietal lobe; Anatomy; Magnetic resonance imaging; Human brain; Biology; Intraparietal sulcus; Brain mapping; Superior temporal sulcus; Neuroscience; Posterior parietal cortex; Functional magnetic resonance imaging; Medicine; Motor cortex; Radiology","score_opus":0.05620476894711453,"score_gpt":0.3182109479310378,"score_spread":0.2620061789839233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225657792","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99248505,0.000012066158,0.00020553083,0.0062810155,0.00001777018,0.00069040415,0.000072718656,0.000029796316,0.0002056517],"genre_scores_gemma":[0.99835724,0.0000013397225,0.00014188637,0.0012312816,0.000022890466,0.00014396186,0.00002996698,0.000007277604,0.00006414414],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992342,0.000106005355,0.00017534688,0.00020499599,0.00015974019,0.000119738084],"domain_scores_gemma":[0.99949384,0.000050890852,0.000051596653,0.0003667691,0.000013341715,0.000023551249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018354933,0.000074690244,0.00013334645,0.00001660944,0.00016218856,0.0000064984997,0.00018185347,0.00002124749,0.00013476306],"category_scores_gemma":[0.00004166467,0.000043021246,0.000053638956,0.00012286486,0.00017434491,0.00001747583,0.00022048235,0.00033547083,3.4851888e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035939836,0.00032376085,0.9688438,0.00003221823,0.000004190286,0.0000249983,0.00037511977,0.000002786896,0.022433499,0.004771901,0.0010148315,0.0021369196],"study_design_scores_gemma":[0.00040543996,0.00020498915,0.98779017,0.000006692244,0.000012644916,0.00015612123,0.00014401886,0.00007682271,0.0005437026,0.008259891,0.0023454886,0.000054008877],"about_ca_topic_score_codex":0.00023791219,"about_ca_topic_score_gemma":0.000062530424,"teacher_disagreement_score":0.021889796,"about_ca_system_score_codex":0.00002513942,"about_ca_system_score_gemma":0.000019542915,"threshold_uncertainty_score":0.17543554},"labels":[],"label_agreement":null},{"id":"W4225907467","doi":"10.1371/journal.pone.0252736","title":"Comparison of CPU and GPU bayesian estimates of fibre orientations from diffusion MRI","year":2022,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; BC Children's Hospital","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; University of California, Los Angeles; Massachusetts General Hospital; BC Children's Hospital; University of Minnesota","keywords":"Markov chain Monte Carlo; Computer science; Voxel; Diffusion; Central processing unit; Bayesian probability; Monte Carlo method; Markov chain; Algorithm; Diffusion MRI; Artificial intelligence; Statistics; Mathematics; Physics; Magnetic resonance imaging; Machine learning","score_opus":0.09944525400692586,"score_gpt":0.36143400305254497,"score_spread":0.2619887490456191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225907467","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98393697,0.00015465605,0.014202334,0.0010287212,0.0000049517466,0.0002736437,0.00012291236,0.000059358423,0.00021644316],"genre_scores_gemma":[0.8876846,0.000033544344,0.11204903,0.00004116069,0.000008648867,0.000037826285,0.0000991986,0.000008930806,0.000037099293],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99949896,0.000009798942,0.00016573853,0.00011722315,0.00015454416,0.00005371286],"domain_scores_gemma":[0.9995721,0.000084201245,0.000094884024,0.00018192062,0.00003439371,0.000032521464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000020605588,0.000047561676,0.00019387956,0.000041731568,0.00007294798,0.0000016758505,0.000045135974,0.0000111384725,0.000113009126],"category_scores_gemma":[0.000026461017,0.00004795009,0.0000177065,0.000118017546,0.000049161976,0.000020391293,0.000081516235,0.0000905214,4.38609e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047632493,0.002159632,0.311436,0.00009715506,0.00003732763,0.0000011926178,0.00053615286,0.000016914766,0.68308246,0.00088501483,0.00037846912,0.001322087],"study_design_scores_gemma":[0.001139535,0.000980011,0.122259475,0.00029011676,0.0004946717,0.0000045197057,0.00069851545,0.034462128,0.8280442,0.010844919,0.00062569656,0.00015622473],"about_ca_topic_score_codex":0.00003847627,"about_ca_topic_score_gemma":0.0000012001524,"teacher_disagreement_score":0.1891765,"about_ca_system_score_codex":0.000010993088,"about_ca_system_score_gemma":0.0000107508295,"threshold_uncertainty_score":0.1955348},"labels":[],"label_agreement":null},{"id":"W4226030876","doi":"10.3389/fnins.2022.833209","title":"Enabling Complex Fibre Geometries Using 3D Printed Axon-Mimetic Phantoms","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Imaging phantom; Diffusion MRI; Orientation (vector space); Kurtosis; Curvature; Nuclear magnetic resonance; Ground truth; Thermal diffusivity; Fractional anisotropy; Physics; Materials science; Magnetic resonance imaging; Geometry; Artificial intelligence; Optics; Mathematics; Computer science; Statistics","score_opus":0.11453495099876031,"score_gpt":0.36135206985105894,"score_spread":0.24681711885229862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226030876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3763695,0.0002654323,0.61970013,0.0012510017,0.000740287,0.0008446217,0.000030500314,0.00034030038,0.00045822724],"genre_scores_gemma":[0.87610465,0.000048876118,0.121919684,0.001555553,0.000025200143,0.00005871466,0.000005848571,0.000022346614,0.0002591191],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985792,0.0000357955,0.00022587321,0.00048228243,0.00034551203,0.00033130794],"domain_scores_gemma":[0.9993909,0.000033821703,0.000092599825,0.00037065105,0.000030150135,0.00008186056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018477112,0.000120713674,0.00020716534,0.00046399378,0.00038322757,0.000028271481,0.00031905912,0.00001582842,0.000022204107],"category_scores_gemma":[0.0002191196,0.00012690076,0.00004420912,0.0021728987,0.0002533425,0.0001258227,0.00030737327,0.0003324583,5.347424e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012456968,0.0004915961,0.15381956,0.00008065447,0.000004286279,0.00024858257,0.00025896615,0.00756649,0.81220263,0.0005003844,0.00535732,0.01934495],"study_design_scores_gemma":[0.0015276626,0.00065339496,0.061746813,0.00009764258,0.000052827818,0.0008640632,0.00065391423,0.5843773,0.024119368,0.0022345707,0.32300505,0.0006673914],"about_ca_topic_score_codex":0.000011882986,"about_ca_topic_score_gemma":1.464482e-7,"teacher_disagreement_score":0.78808326,"about_ca_system_score_codex":0.00014436484,"about_ca_system_score_gemma":0.00007197458,"threshold_uncertainty_score":0.51748633},"labels":[],"label_agreement":null},{"id":"W4226193026","doi":"","title":"The Digital Brain Bank, an open access platform for post-mortem imaging datasets","year":2022,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; China Scholarship Council; Motor Neurone Disease Association; NIHR Oxford Biomedical Research Centre; Medical Research Council Canada; Cancer Research UK; Medical Research Council; Wellcome","keywords":"Neuroimaging; Neuroanatomy; Neuroinformatics; Magnetic resonance imaging; Computer science; Diffusion MRI; Brain atlas; Neuroscience; Artificial intelligence; Medicine; Data science; Biology; Radiology","score_opus":0.10528278185127639,"score_gpt":0.3835696911694888,"score_spread":0.2782869093182124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226193026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5366738,0.00012446265,0.1836832,0.102414295,0.0001999611,0.016106052,0.051525917,0.00087069086,0.10840165],"genre_scores_gemma":[0.9540941,0.0005785967,0.02327673,0.0006755992,0.00007816759,0.000014456187,0.009548672,0.00009995051,0.011633712],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977519,0.00014767513,0.00014920601,0.00064822496,0.00063673884,0.0006662575],"domain_scores_gemma":[0.9973175,0.0007813434,0.0001700638,0.0010645117,0.000307294,0.00035927942],"candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.0008211014,0.00018263722,0.000296234,0.0004941354,0.004064788,0.00022790878,0.004325869,0.00003127842,0.00012983977],"category_scores_gemma":[0.00014677171,0.00020125325,0.00015282129,0.00084787095,0.0008255092,0.0021948174,0.008043616,0.0007523098,0.0000018461855],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.02102157,0.0028186068,0.03248262,0.00034589917,0.00051614456,0.0014674993,0.003126768,0.00021734854,0.008930265,0.19946696,0.37025735,0.35934895],"study_design_scores_gemma":[0.0019946266,0.00094463676,0.007944353,0.000027513428,0.000044109,0.000065092354,0.012770851,0.0043514697,0.00005372573,0.007616603,0.9639679,0.00021909387],"about_ca_topic_score_codex":0.0005179219,"about_ca_topic_score_gemma":0.00032635825,"teacher_disagreement_score":0.59371054,"about_ca_system_score_codex":0.0003172733,"about_ca_system_score_gemma":0.00052664103,"threshold_uncertainty_score":0.99997914},"labels":[],"label_agreement":null},{"id":"W4226413061","doi":"10.3389/fneur.2021.789254","title":"The Value of Diffusion Kurtosis Imaging in Detecting Delayed Brain Development of Premature Infants","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Natural Science Foundation of China","keywords":"Kurtosis; Diffusion MRI; Neuroimaging; Neuroscience; Brain development; Medicine; Psychology; Magnetic resonance imaging; Radiology; Mathematics; Statistics","score_opus":0.014259231192256949,"score_gpt":0.2942469011439578,"score_spread":0.2799876699517008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226413061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97050583,0.0005025831,0.02439569,0.004032212,0.00013060772,0.0002567245,0.0000017013447,0.000024723045,0.0001499341],"genre_scores_gemma":[0.9356949,0.00010998647,0.063429266,0.0006842829,0.000009662609,0.000032331176,0.0000038509584,0.000014577904,0.000021167347],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990266,0.00008624822,0.00038618705,0.00021929819,0.00009891543,0.0001827433],"domain_scores_gemma":[0.9993552,0.00016261375,0.00013567822,0.0002754452,0.00004666145,0.000024416255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019410472,0.00008444636,0.0002313594,0.00012150099,0.00004798739,0.000002369327,0.00011091356,0.000055905715,0.000001556584],"category_scores_gemma":[0.0003295859,0.00007086552,0.00003445003,0.00033075296,0.000082265964,0.000024514937,0.00011618926,0.0002998411,1.1911702e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045500594,0.0001979577,0.7000436,0.000081238046,0.000016024393,0.000085169,0.0009898639,0.00013449937,0.1984615,0.00027117736,0.0010214574,0.09824251],"study_design_scores_gemma":[0.002067786,0.00014388125,0.74845994,0.00021186341,0.000029952342,0.00017420122,0.0003423601,0.016053636,0.2145115,0.0052823573,0.012522922,0.00019961799],"about_ca_topic_score_codex":0.0000086423515,"about_ca_topic_score_gemma":0.000023951776,"teacher_disagreement_score":0.09804289,"about_ca_system_score_codex":0.00002072979,"about_ca_system_score_gemma":0.00007753323,"threshold_uncertainty_score":0.28898123},"labels":[],"label_agreement":null},{"id":"W4229022032","doi":"10.1093/noajnl/vdac064","title":"Abnormalities of structural brain connectivity in pediatric brain tumor survivors","year":2022,"lang":"en","type":"article","venue":"Neuro-Oncology Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Hospital for Sick Children; University of Toronto","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Context (archaeology); Sulcus; Right hemisphere; Lateralization of brain function; Nuclear medicine; Medicine; Brain tumor; Psychology; Internal medicine; Neuroscience; Pathology; Magnetic resonance imaging; Audiology; Biology; Radiology","score_opus":0.03163942454611122,"score_gpt":0.35211736591377624,"score_spread":0.320477941367665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229022032","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879473,0.00059535354,0.0003051929,0.008839702,0.00023893292,0.00056077837,0.000058778263,0.00015510879,0.0012988794],"genre_scores_gemma":[0.99400175,0.000094046954,0.0018318115,0.003616826,0.000086679756,0.00024066528,0.000016413238,0.000024506651,0.00008728747],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984588,0.00028155086,0.0003797765,0.00038313886,0.00020799358,0.00028875293],"domain_scores_gemma":[0.9977589,0.0015833324,0.00025013788,0.00029792072,0.00004629573,0.000063416875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030965172,0.00015664521,0.00041325178,0.00023912473,0.00015653778,0.0000031141817,0.00019688255,0.00003322706,0.00011210037],"category_scores_gemma":[0.0005353484,0.00015964851,0.00007607882,0.0005635217,0.0001863178,0.00015605324,0.0001867339,0.00054764043,0.0000013234119],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066661485,0.0004452526,0.93626744,0.00023567944,0.000011154502,0.00042819668,0.00060769345,0.0017757665,0.03569676,0.010770867,0.0026506719,0.010443924],"study_design_scores_gemma":[0.004872032,0.0046386276,0.5512191,0.000021686043,0.00009765378,0.0020593735,0.0016725844,0.0013481926,0.017513363,0.03245177,0.3833612,0.0007443988],"about_ca_topic_score_codex":0.00005826895,"about_ca_topic_score_gemma":0.00011109083,"teacher_disagreement_score":0.38504827,"about_ca_system_score_codex":0.00010380785,"about_ca_system_score_gemma":0.00014269342,"threshold_uncertainty_score":0.65102774},"labels":[],"label_agreement":null},{"id":"W4229333559","doi":"10.1016/j.media.2022.102476","title":"Bridging the gap between constrained spherical deconvolution and diffusional variance decomposition via tensor‐valued diffusion MRI","year":2022,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Deconvolution; Fractional anisotropy; Computer science; Tensor (intrinsic definition); Anisotropy; Orientation (vector space); Algorithm; Diffusion; White matter; Mathematics; Artificial intelligence; Physics; Magnetic resonance imaging; Geometry; Optics","score_opus":0.02731257130503184,"score_gpt":0.34251903067927053,"score_spread":0.3152064593742387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229333559","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20063663,0.00008549467,0.78096473,0.01772747,0.00001838005,0.0002495096,0.000030215337,0.00013037551,0.00015721294],"genre_scores_gemma":[0.97252935,0.000065191496,0.02429633,0.0023596785,0.00018227761,0.000108020686,0.00029027465,0.00001839422,0.000150476],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980404,0.00016942115,0.00036824576,0.0004320238,0.0007426591,0.00024727278],"domain_scores_gemma":[0.9989742,0.00022083646,0.00013260687,0.00035721116,0.000069510235,0.00024564262],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00046871972,0.0001529024,0.00037769758,0.00012425183,0.0006742145,0.00002646563,0.00017589034,0.000051851373,0.0012584854],"category_scores_gemma":[0.00016396662,0.00011516933,0.00019735543,0.00094450085,0.0003707228,0.00006496926,0.0002868017,0.00052715815,0.00000567977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000580989,0.0028492445,0.3720867,0.00015879767,0.002922822,0.0010182923,0.000746395,0.00045409414,0.27187872,0.0043559577,0.014624504,0.32832348],"study_design_scores_gemma":[0.0016655943,0.00020375279,0.24452,0.00003745437,0.0032143306,0.00045500076,0.00012275997,0.7411597,0.0007313346,0.0028203004,0.004723757,0.0003460808],"about_ca_topic_score_codex":0.00007933303,"about_ca_topic_score_gemma":0.0000034365687,"teacher_disagreement_score":0.7718927,"about_ca_system_score_codex":0.00008835333,"about_ca_system_score_gemma":0.000055155742,"threshold_uncertainty_score":0.9996545},"labels":[],"label_agreement":null},{"id":"W4229451685","doi":"10.1016/j.dscb.2022.100036","title":"Functional, but minimal microstructural brain changes present in aging Canadian football league players years after retirement","year":2022,"lang":"en","type":"article","venue":"Brain Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Psychology; Athletes; Neuropsychology; Football; Magnetic resonance imaging; Audiology; Medicine; Physical therapy; Neuroscience; Cognition; Radiology","score_opus":0.038363793545055834,"score_gpt":0.29983283175473396,"score_spread":0.26146903820967815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229451685","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.890442,0.0002478577,0.00011962703,0.107757345,0.00011369442,0.00079707766,0.00009468804,0.00008820247,0.00033947182],"genre_scores_gemma":[0.9878897,0.000018502315,0.00079988537,0.008096903,0.00008427368,0.0006117169,0.0001241793,0.00003553927,0.0023392658],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9988161,0.00004251234,0.00016650729,0.00037182763,0.00022334822,0.00037972903],"domain_scores_gemma":[0.99946284,0.00006246149,0.000046883324,0.00026914288,0.000014625097,0.00014403596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012180364,0.00014142696,0.00014373152,0.0002619533,0.00013703198,0.000015460508,0.00012338687,0.00003153869,0.0004179466],"category_scores_gemma":[0.00004112851,0.00016451502,0.000060497845,0.00026936547,0.00007758305,0.000039153634,0.000110960165,0.0002951987,0.0000070356036],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089997274,0.0004628985,0.27503535,0.00019844796,0.0001244152,0.00051566755,0.0042749797,0.0017265554,0.04475704,0.001553432,0.61056674,0.059884485],"study_design_scores_gemma":[0.0012001033,0.00018602783,0.51450163,0.00003110713,0.000015033584,0.000046357673,0.0011170454,0.00038429807,0.0003658662,0.0006307545,0.4812254,0.0002963932],"about_ca_topic_score_codex":0.01646748,"about_ca_topic_score_gemma":0.048956834,"teacher_disagreement_score":0.23946625,"about_ca_system_score_codex":0.00030752175,"about_ca_system_score_gemma":0.0001110644,"threshold_uncertainty_score":0.99008197},"labels":[],"label_agreement":null},{"id":"W4230255018","doi":"10.1016/s0304394002013332","title":"Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins","year":2003,"lang":"en","type":"article","venue":"Neuroscience Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; McMaster University","funders":"","keywords":"Heritability; Corpus callosum; Concordance; Dizygotic twins; Trait; Magnetic resonance imaging; Dizygotic twin; Lateralization of brain function; Psychology; Twin study; Biology; Audiology; Developmental psychology; Neuroscience; Evolutionary biology; Genetics; Medicine","score_opus":0.05944971591487432,"score_gpt":0.35070261120484103,"score_spread":0.29125289528996673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230255018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99517184,0.000003871098,0.00062746863,0.0034883763,0.000039703118,0.000568354,0.0000018794843,0.000029380326,0.00006909332],"genre_scores_gemma":[0.98529047,0.000005810308,0.00148684,0.013134662,0.000008088328,0.00002507442,8.417571e-8,0.000011538508,0.00003741819],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990164,0.00005730271,0.00018890917,0.00035728226,0.00019790625,0.00018217527],"domain_scores_gemma":[0.99933517,0.00004322048,0.00005890516,0.00047718178,0.000015134092,0.00007036855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009688795,0.00009723898,0.00013532478,0.000045129287,0.00009489453,0.0000154173,0.0001950432,0.000016651456,0.0000028466432],"category_scores_gemma":[0.00011019197,0.000072521325,0.000025877132,0.0002938737,0.00033010577,0.00006034158,0.000052181415,0.00015588735,2.6523355e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021919986,0.0001644229,0.3535919,0.0000044489248,2.7285822e-7,0.000014863219,0.000117845615,0.0000119314345,0.6458239,0.00009954628,0.00003616597,0.00013254993],"study_design_scores_gemma":[0.00047354767,0.0003460717,0.9635454,0.000014836428,0.000017257304,0.000055407432,0.000029034092,0.00029966538,0.034269735,0.00019287011,0.00066403946,0.000092142334],"about_ca_topic_score_codex":0.000021712503,"about_ca_topic_score_gemma":0.000008446747,"teacher_disagreement_score":0.61155415,"about_ca_system_score_codex":0.000014020208,"about_ca_system_score_gemma":0.000020308815,"threshold_uncertainty_score":0.2957334},"labels":[],"label_agreement":null},{"id":"W4230311787","doi":"10.21203/rs.3.rs-374535/v1","title":"Distinct Tumor Signatures using Deep Learning-based Characterization of the Peritumoral Microenvironment in Glioblastomas and Brain Metastases","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"National Institutes of Health","keywords":"Diffusion MRI; Medicine; Convolutional neural network; Glioblastoma; Infiltration (HVAC); Pathology; Radiology; Nuclear medicine; Artificial intelligence; Magnetic resonance imaging; Computer science; Cancer research; Materials science","score_opus":0.06634612594131742,"score_gpt":0.39094249697938477,"score_spread":0.3245963710380674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230311787","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9925798,0.0004936405,0.0040802453,0.0015521628,0.000015233803,0.0011642694,0.00007252915,0.000032581473,0.0000094904835],"genre_scores_gemma":[0.9970106,0.00007009297,0.0023635118,0.00007832679,0.000034562432,0.00013981557,0.00023368301,0.000036842357,0.00003259594],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980704,0.00045786228,0.0002695405,0.00046057516,0.00047815117,0.0002634641],"domain_scores_gemma":[0.9990007,0.00016742933,0.00014649799,0.00048630472,0.0001247096,0.000074316136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044387768,0.00017024009,0.0003218037,0.00021424102,0.00013826745,0.000044512235,0.00015822791,0.000076969816,0.000042722746],"category_scores_gemma":[0.00043597436,0.00013614677,0.00009703554,0.00034178075,0.00031505633,0.000033289693,0.00065894343,0.0013275084,2.86128e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015340754,0.0004558361,0.069502935,0.0019955605,0.000021309765,0.00013196988,0.00025363947,0.0024135273,0.92268115,0.000049694274,0.000014408565,0.002326555],"study_design_scores_gemma":[0.0007113648,0.00025745336,0.812891,0.003411271,0.000055905388,0.000043402455,0.00028930148,0.041269746,0.13912278,0.00013263307,0.0015563023,0.00025881434],"about_ca_topic_score_codex":0.00007447674,"about_ca_topic_score_gemma":0.00002553444,"teacher_disagreement_score":0.78355837,"about_ca_system_score_codex":0.0001630105,"about_ca_system_score_gemma":0.00017782631,"threshold_uncertainty_score":0.5767437},"labels":[],"label_agreement":null},{"id":"W4231279597","doi":"10.1016/j.jalz.2013.05.849","title":"P2–203: Relationship between cortical thinning and cortical FDG hypometabolism in individuals with progressive MCI and Alzheimer's disease","year":2013,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Atrophy; Neuroimaging; Psychology; Cognitive impairment; Cohort; Alzheimer's Disease Neuroimaging Initiative; Medicine; Internal medicine; Disease; Nuclear medicine; Cardiology; Pathology; Neuroscience","score_opus":0.07706400431917466,"score_gpt":0.34619877079463623,"score_spread":0.2691347664754616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231279597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9578509,0.035244305,0.0009897709,0.0038870585,0.000017610277,0.0016410012,0.000022266553,0.00018252303,0.00016460978],"genre_scores_gemma":[0.97269607,0.000061558654,0.026262607,0.00043629739,0.00006251133,0.00037400879,0.000063399784,0.000039517923,0.0000040179993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998479,0.000073074974,0.00036500432,0.00047034823,0.0002610645,0.00035149758],"domain_scores_gemma":[0.99879634,0.00028982447,0.00011472049,0.00032636288,0.000071391885,0.00040134587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015336029,0.00022019177,0.00030694506,0.00013916499,0.00019493328,0.00007092811,0.00008746417,0.00007267865,0.000047387526],"category_scores_gemma":[0.000108245615,0.00018112075,0.000030114954,0.00026769773,0.00035328197,0.00028525045,0.00013267946,0.0004666746,0.000018561654],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018307072,0.00008895511,0.98856956,0.000005323576,0.00056137156,0.000019028012,0.00010368512,5.0320347e-7,0.00009040957,0.0029864353,0.0002584598,0.007297973],"study_design_scores_gemma":[0.0008254446,0.00009989724,0.98670244,0.00006789501,0.007987921,0.000028298053,0.000046426398,0.00013293247,0.00032674347,0.0027591072,0.0008148756,0.00020798812],"about_ca_topic_score_codex":0.000024445304,"about_ca_topic_score_gemma":0.0000010797181,"teacher_disagreement_score":0.035182748,"about_ca_system_score_codex":0.0000034959219,"about_ca_system_score_gemma":0.000049036287,"threshold_uncertainty_score":0.7385889},"labels":[],"label_agreement":null},{"id":"W4231317324","doi":"10.1101/2021.10.25.465703","title":"Investigating the genetic and environmental basis of head micromovements during MRI","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Genome-wide association study; Impulsivity; Body mass index; Population; Genetic association; Neuroimaging; Psychology; Demography; Medicine; Biology; Clinical psychology; Internal medicine; Genetics; Psychiatry; Single-nucleotide polymorphism; Genotype; Environmental health","score_opus":0.025875395584793588,"score_gpt":0.25961296857272276,"score_spread":0.23373757298792916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231317324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960381,0.0012651368,0.0011984729,0.0005361952,0.0000619155,0.0006802765,0.000100402,0.00011718628,0.0000023402988],"genre_scores_gemma":[0.944248,0.0009900661,0.05413975,0.00030761398,0.00008904761,0.0001501406,6.518678e-7,0.000071151524,0.0000035506514],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99847466,0.000047835012,0.00039889876,0.00060662697,0.00022689441,0.00024506735],"domain_scores_gemma":[0.99846655,0.000033634682,0.0002973104,0.0010023896,0.00005719554,0.0001429138],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012221524,0.00028319212,0.00036355102,0.00008030088,0.00014602722,0.000046456953,0.00019662715,0.00013848033,0.00001614876],"category_scores_gemma":[0.000052411426,0.00026084686,0.0000896966,0.00016337026,0.00024531625,0.000042083346,0.00059882033,0.00050143653,0.0000015138228],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000032863936,0.00007442798,0.091235116,0.00031774113,0.00004649552,0.000013988101,0.000010975594,0.000010773444,0.90825045,0.000016865759,0.000016050257,0.000003823045],"study_design_scores_gemma":[0.00022429325,0.000016946633,0.44861072,0.0004116979,0.0000974959,1.343279e-7,0.000007533572,0.00017352475,0.55009824,0.0000020404354,0.00019876396,0.00015859285],"about_ca_topic_score_codex":0.000025209543,"about_ca_topic_score_gemma":4.9481247e-7,"teacher_disagreement_score":0.3581522,"about_ca_system_score_codex":0.000099090415,"about_ca_system_score_gemma":0.00011141916,"threshold_uncertainty_score":0.9999844},"labels":[],"label_agreement":null},{"id":"W4231680536","doi":"10.1016/s0006-3223(11)00616-0","title":"Table of Contents","year":2011,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Linear regression; White matter; Statistics; Psychology; Scanner; Sample (material); Table of contents; Cover (algebra); Regression; Regression analysis; Table (database); Mathematics; Medicine; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Radiology; Data mining","score_opus":0.26798391095176916,"score_gpt":0.37317102709016786,"score_spread":0.1051871161383987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4231680536","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90992993,0.0006236398,0.012716093,0.0014698955,0.00023612168,0.00050126854,0.000021746553,0.00034043836,0.074160844],"genre_scores_gemma":[0.928894,0.000058978454,0.07015592,0.00068552914,0.00003226832,0.000013750474,0.000004821165,0.0000040646105,0.00015068617],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99963623,0.0000059450254,0.00012101378,0.00012034669,0.000033369037,0.00008310748],"domain_scores_gemma":[0.9997075,0.000006547723,0.000044739525,0.00017119982,0.00002745285,0.00004254578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000025279092,0.00004843489,0.00011143231,0.00001567572,0.000016530352,5.249444e-7,0.00005984198,0.00004391713,0.00016059051],"category_scores_gemma":[0.000018078415,0.000031616597,0.000042896107,0.000078000434,0.000072264986,0.000010705375,0.0000211555,0.00006564386,0.000013997181],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013830035,0.00062651274,0.90806973,0.000020228787,0.000012266495,0.000001761853,0.000011656018,2.7329936e-8,0.01849461,0.06521017,0.0058039757,0.0016107672],"study_design_scores_gemma":[0.0005965661,0.0007783694,0.9198859,0.000047480495,0.000021971728,0.00003285502,0.000039155464,0.000008599187,0.008233727,0.045659125,0.024587736,0.000108565226],"about_ca_topic_score_codex":0.000006608184,"about_ca_topic_score_gemma":1.9655879e-7,"teacher_disagreement_score":0.074010156,"about_ca_system_score_codex":0.0000022275356,"about_ca_system_score_gemma":0.000008993415,"threshold_uncertainty_score":0.17583534},"labels":[],"label_agreement":null},{"id":"W4232561243","doi":"10.1016/j.jalz.2019.06.2810","title":"P2‐403: CORTICAL IRON DEPOSITION IN ALZHEIMER'S DISEASE CONTRASTS WITH AGE‐RELATED SUBCORTICAL DEPOSITION","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University Health Centre; Douglas Mental Health University Institute; Douglas College; McGill University","funders":"","keywords":"Neuropathology; Putamen; Neuroimaging; Prefrontal cortex; Neuroscience; Postmortem studies; Alzheimer's Disease Neuroimaging Initiative; Psychology; Voxel; Amyloid (mycology); Medicine; Disease; Internal medicine; Cognition; Pathology; Cognitive impairment; Radiology","score_opus":0.026840669788554594,"score_gpt":0.3035336072908793,"score_spread":0.2766929375023247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232561243","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754746,0.009038458,0.009349806,0.002046921,0.000103819984,0.0022563916,0.00001581555,0.0004382532,0.0012759662],"genre_scores_gemma":[0.99081606,0.000066162655,0.007954454,0.0005999593,0.000034200653,0.00017056632,0.0002966673,0.000055846933,0.0000060885304],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982444,0.00006294185,0.00043242055,0.0005357084,0.000316015,0.00040848082],"domain_scores_gemma":[0.99900705,0.00005600616,0.00010144078,0.00048081207,0.00006282885,0.00029184492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008456344,0.00024391696,0.000294355,0.000109503846,0.00008690021,0.000031860753,0.00010570429,0.00009152501,0.00014524965],"category_scores_gemma":[0.000010591574,0.00021942801,0.00008443993,0.0002768492,0.00015084968,0.00019260809,0.000051931354,0.0003683815,0.000163499],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004327322,0.004598134,0.7065877,0.00007672931,0.008173973,0.0030677896,0.00022634117,0.00030631223,0.18971142,0.020648554,0.0012723515,0.061003376],"study_design_scores_gemma":[0.005910479,0.0012018488,0.889858,0.00037298357,0.033893086,0.00035721908,0.000043741,0.0099611925,0.055863455,0.0010223805,0.0005839376,0.0009316822],"about_ca_topic_score_codex":0.000035663532,"about_ca_topic_score_gemma":0.000016083643,"teacher_disagreement_score":0.18327029,"about_ca_system_score_codex":0.00001661401,"about_ca_system_score_gemma":0.000056866316,"threshold_uncertainty_score":0.89480144},"labels":[],"label_agreement":null},{"id":"W4232624499","doi":"10.1016/j.jalz.2014.05.1648","title":"P4‐132: WHITE MATTER ABNORMALITIES AND STRUCTURAL PARIETAL DISCONNECTIONS IN ALZHEIMER'S DISEASE","year":2014,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Supramarginal gyrus; Fractional anisotropy; Parietal lobe; Angular gyrus; White matter; Temporal lobe; Superior frontal gyrus; Psychology; Neuroscience; Diffusion MRI; Posterior parietal cortex; Middle frontal gyrus; Medicine; Magnetic resonance imaging; Radiology; Cognition; Epilepsy; Functional magnetic resonance imaging","score_opus":0.03596019351917197,"score_gpt":0.3119363544781281,"score_spread":0.27597616095895616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232624499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9208636,0.037854962,0.007311536,0.024399681,0.00036437425,0.0019256901,0.00012790167,0.0006175214,0.0065347035],"genre_scores_gemma":[0.99430424,0.000047495538,0.004152165,0.0011615216,0.00008596602,0.00011721256,0.00007398485,0.000030399022,0.000027038906],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989918,0.000035170175,0.00024808903,0.0003344675,0.00012543981,0.00026503275],"domain_scores_gemma":[0.9993312,0.00003337587,0.00006344079,0.00037159395,0.000029020119,0.00017139676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000070716844,0.00017436297,0.0001842937,0.000090675894,0.00014182224,0.000041768628,0.00008377877,0.00003413271,0.00024997757],"category_scores_gemma":[0.00000982644,0.0001582237,0.00005734772,0.0001172496,0.00014827169,0.00020334678,0.00009629619,0.0001627487,0.000036028523],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007533924,0.00008494103,0.9756626,0.000011264226,0.000999434,0.000014873007,0.00018598684,0.000023486924,0.00031065996,0.006792716,0.004087348,0.011751374],"study_design_scores_gemma":[0.0007074544,0.00006565767,0.9659362,0.00003685827,0.0062716445,0.000051564504,0.00005382966,0.0014549132,0.0011801046,0.0048856395,0.019040974,0.00031518503],"about_ca_topic_score_codex":0.00007032075,"about_ca_topic_score_gemma":0.00002595561,"teacher_disagreement_score":0.07344059,"about_ca_system_score_codex":0.000003403685,"about_ca_system_score_gemma":0.000018339653,"threshold_uncertainty_score":0.64521754},"labels":[],"label_agreement":null},{"id":"W4233862762","doi":"10.7287/peerj.preprints.2323","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Corpus callosum; Diffusion MRI; Myelin; Ex vivo; Magnetic resonance imaging; Neuroscience; Hippocampus; Central nervous system; Thalamus; Cerebellum; Pathology; Nuclear magnetic resonance; Biology; Anatomy; Medicine; In vivo; Physics; Radiology","score_opus":0.09378277241434148,"score_gpt":0.3918385396305597,"score_spread":0.29805576721621824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233862762","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040470146,0.00019824466,0.70976067,0.21045601,0.000191869,0.0029169908,0.00046444952,0.00067705166,0.034864556],"genre_scores_gemma":[0.49027497,0.00032222655,0.2961239,0.00593192,0.00028313443,0.0005712784,0.0000676738,0.00021129318,0.20621361],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884987,0.00004034471,0.00032210982,0.000401372,0.00022329342,0.00016299429],"domain_scores_gemma":[0.99803376,0.000168603,0.00026346502,0.0013133866,0.00015828072,0.00006247364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121685516,0.00020236408,0.00035817924,0.00006810083,0.000045089375,0.0000074859986,0.0003401644,0.00012514435,0.00010438],"category_scores_gemma":[0.00015866956,0.000110775894,0.00020267697,0.00010684628,0.00023934981,0.000027428303,0.00065785943,0.0004353522,0.00002707187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009584305,0.00035389856,0.0012789374,0.0003575357,0.000106843305,0.0000051903453,0.00025521507,0.000026487553,0.59735286,0.18945909,0.20877019,0.0019379108],"study_design_scores_gemma":[0.0010927122,0.00023030885,0.0023665132,0.0012457296,0.0001748891,0.000025925736,0.0001332246,0.00043697757,0.59639037,0.12632065,0.27109975,0.00048293453],"about_ca_topic_score_codex":0.000026197262,"about_ca_topic_score_gemma":0.0000034706275,"teacher_disagreement_score":0.4498048,"about_ca_system_score_codex":0.00004521532,"about_ca_system_score_gemma":0.00010871395,"threshold_uncertainty_score":0.451731},"labels":[],"label_agreement":null},{"id":"W4234003016","doi":"10.1007/s00429-021-02239-2","title":"Correction to: A comparison of diffusion tractography techniques in simulating the generalized Ising model to predict the intrinsic activity of the brain","year":2021,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Tractography; Ising model; Diffusion MRI; Diffusion; Neuroscience; Computer science; Statistical physics; Psychology; Physics; Medicine; Magnetic resonance imaging; Thermodynamics; Radiology","score_opus":0.03754665196289863,"score_gpt":0.3380409139241214,"score_spread":0.30049426196122275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234003016","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87318957,0.000036371584,0.11952259,0.0064315517,0.000091307265,0.0006145312,0.000007633497,0.000037911886,0.000068537964],"genre_scores_gemma":[0.9955476,0.0000065592544,0.002906186,0.0014030774,0.000052759977,0.00002412471,0.0000049104237,0.000010236253,0.000044544693],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992861,0.00008288328,0.0002064475,0.00018538309,0.0001498872,0.000089310684],"domain_scores_gemma":[0.999219,0.0002547398,0.00012303909,0.000302127,0.000075683725,0.000025439593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013908096,0.000092746326,0.0001769088,0.00006905043,0.0001363452,0.000010727224,0.00006070685,0.0000487979,0.0000027341748],"category_scores_gemma":[0.000268358,0.000050287363,0.000060924187,0.0006127733,0.000053407995,0.00004048444,0.00007162835,0.0002598108,2.1770896e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020848316,0.000054303262,0.018388374,0.00002551683,0.000009375043,1.7456125e-7,0.00082924124,0.005065547,0.804472,0.00028642587,0.0017880726,0.16887248],"study_design_scores_gemma":[0.00060725317,0.0002891068,0.45260838,0.00032739268,0.000089814865,0.000028544335,0.0003811519,0.1341936,0.40299645,0.0047776722,0.0035595135,0.00014112327],"about_ca_topic_score_codex":0.00006394444,"about_ca_topic_score_gemma":0.00008894457,"teacher_disagreement_score":0.43422002,"about_ca_system_score_codex":0.00001945905,"about_ca_system_score_gemma":0.000027500393,"threshold_uncertainty_score":0.20506592},"labels":[],"label_agreement":null},{"id":"W4234641868","doi":"10.1109/cvpr.2009.5204044","title":"3D stochastic completion fields for fiber tractography","year":2009,"lang":"en","type":"article","venue":"2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Tractography; Random walk; Statistical physics; Stochastic differential equation; Brownian motion; Computer science; Diffusion; Monte Carlo method; Stochastic process; Algorithm; Voxel; Diffusion MRI; Mathematical optimization; Applied mathematics; Mathematics; Artificial intelligence; Physics; Statistics","score_opus":0.10372641488124447,"score_gpt":0.35089019035030916,"score_spread":0.2471637754690647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234641868","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022755928,0.00002328409,0.97089446,0.0047485856,0.00024828577,0.0008573062,0.000051217143,0.00030853754,0.00011240068],"genre_scores_gemma":[0.66855276,0.00014962128,0.3095549,0.020414475,0.00078495604,0.00006989287,0.00036045598,0.000030810163,0.00008210089],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985094,0.000034514716,0.0003502225,0.0005999741,0.00020933062,0.0002965497],"domain_scores_gemma":[0.9989535,0.00017737673,0.00013974505,0.00029901348,0.0002497796,0.00018059119],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000116323376,0.00029913854,0.00036424721,0.000094209114,0.00022510899,0.00013424133,0.00011714103,0.00018133449,0.00008047677],"category_scores_gemma":[0.0000028218747,0.00027274466,0.00027479528,0.00018162646,0.00007012206,0.000118873795,0.000027743421,0.00038704497,0.000028582666],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054466112,0.00029179896,0.000024963243,0.000035131226,0.000022790397,0.0000032430362,0.00011746918,0.00016377516,0.00009027653,0.00004618608,0.027519368,0.9716305],"study_design_scores_gemma":[0.00289686,0.0030568433,0.013604763,0.0012256517,0.00011128705,0.0001233507,0.000015679727,0.9677145,0.00014387292,0.0038951684,0.006530942,0.0006810639],"about_ca_topic_score_codex":0.0000014712548,"about_ca_topic_score_gemma":4.319691e-7,"teacher_disagreement_score":0.9709495,"about_ca_system_score_codex":0.000021820884,"about_ca_system_score_gemma":0.000020792193,"threshold_uncertainty_score":0.99997246},"labels":[],"label_agreement":null},{"id":"W4234739227","doi":"10.3389/fnins.2020.00543","title":"Histological Correlates of Diffusion-Weighted Magnetic Resonance Microscopy in a Mouse Model of Mesial Temporal Lobe Epilepsy","year":2020,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"BrainLinks-BrainTools; European Research Council; Albert-Ludwigs-Universität Freiburg; Deutsche Forschungsgemeinschaft","keywords":"Hippocampal formation; Diffusion MRI; Hippocampal sclerosis; Magnetic resonance imaging; Pathology; Temporal lobe; Granule cell; Pyramidal cell; Epilepsy; Fractional anisotropy; Nuclear magnetic resonance; Hippocampus; Neuroscience; Dentate gyrus; Medicine; Biology; Physics; Radiology","score_opus":0.039886745281695335,"score_gpt":0.29802722689831507,"score_spread":0.25814048161661973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234739227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91137904,0.0005066734,0.086332016,0.0010748571,0.00008509641,0.00044444657,0.00003170098,0.000053476164,0.00009270933],"genre_scores_gemma":[0.89815116,0.0002729012,0.1007448,0.00065679726,0.0000060240222,0.00002273691,0.0000019843553,0.0000113603255,0.00013225916],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872637,0.00003101035,0.00040483027,0.0004276271,0.00020236683,0.00020779876],"domain_scores_gemma":[0.99947006,0.000025379097,0.00013034543,0.00025425418,0.000031497115,0.000088444285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071237206,0.00011985257,0.00035323968,0.00012511261,0.000026118716,0.0000033147155,0.00028947997,0.000058900197,0.0000030348747],"category_scores_gemma":[0.00021180746,0.00010878444,0.000048294496,0.0006409938,0.00052578346,0.00006625586,0.00010226384,0.00025966202,3.1164146e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002885642,0.0002823861,0.467007,0.000040268686,2.1133692e-7,0.000021509055,0.0001997999,0.00025668656,0.52951974,0.00030648152,0.0010250078,0.0010523256],"study_design_scores_gemma":[0.0019069213,0.000960271,0.075501665,0.00013493751,0.0000144230125,0.000014535238,0.000059599195,0.8372563,0.07974892,0.0026959563,0.0014529881,0.00025347684],"about_ca_topic_score_codex":0.000011776017,"about_ca_topic_score_gemma":5.774456e-7,"teacher_disagreement_score":0.8369996,"about_ca_system_score_codex":0.000033985027,"about_ca_system_score_gemma":0.00007206762,"threshold_uncertainty_score":0.4436101},"labels":[],"label_agreement":null},{"id":"W4235000785","doi":"10.1016/j.jalz.2017.06.2347","title":"[IC‐P‐074]: LONGITUDINAL DIFFUSION TENSOR IMAGING AS A PREDICTOR OF COGNITIVE DOMAINS DECLINE IN EARLY STAGE PARKINSON's DISEASE: ICICLE‐PD STUDY","year":2017,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Ontario Brain Institute","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Parkinson's disease; White matter; Cognition; Cognitive decline; Dementia; Internal medicine; Medicine; Population; Psychology; Disease; Cardiology; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.05910597243118143,"score_gpt":0.3704345674666382,"score_spread":0.3113285950354568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235000785","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9917963,0.003291573,0.0014515211,0.0010880984,0.00005973585,0.0017288472,0.00011062964,0.00012223395,0.00035104144],"genre_scores_gemma":[0.9975025,0.00012864631,0.0016744072,0.00024578942,0.000075497876,0.00024315785,0.00004631567,0.000049617676,0.000034061926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981507,0.000051172356,0.00044993107,0.000583281,0.00041628638,0.00034860315],"domain_scores_gemma":[0.998293,0.000084764106,0.00036332716,0.0008825097,0.00016103112,0.00021539048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021026586,0.00025027303,0.00036498162,0.00014693792,0.00029280552,0.000057247427,0.00032341722,0.000033726257,0.000059672842],"category_scores_gemma":[0.00017905481,0.00023241465,0.00010918901,0.00012753595,0.00024601768,0.000250233,0.00041968847,0.00023556263,0.00001649466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004519975,0.0014325236,0.9902443,0.000009863838,0.00076437247,0.00025578585,0.00020914643,5.596594e-7,0.0011277808,0.00014088978,0.00011596886,0.005246774],"study_design_scores_gemma":[0.0030874296,0.00030712513,0.98541886,0.00017715101,0.0058200457,0.000007399266,0.00017938325,0.00022935432,0.002010984,0.00031530662,0.002243996,0.00020298308],"about_ca_topic_score_codex":0.00051499304,"about_ca_topic_score_gemma":0.00009732469,"teacher_disagreement_score":0.0057061864,"about_ca_system_score_codex":0.000009632612,"about_ca_system_score_gemma":0.000064512715,"threshold_uncertainty_score":0.94775945},"labels":[],"label_agreement":null},{"id":"W4235690983","doi":"10.1017/cjn.2019.81","title":"GP.05 Intraoperative acquisition of diffusion tensor imaging in cranial neurosurgery: readout-segmented DTI versus standard single-shot DTI","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton","funders":"","keywords":"Diffusion MRI; Medicine; White matter; Nuclear medicine; Artifact (error); Magnetic resonance imaging; Tractography; Radiology; Neuroscience","score_opus":0.07378926848671195,"score_gpt":0.32793155746016317,"score_spread":0.2541422889734512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235690983","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900927,0.00025341765,0.00011192232,0.0070534097,0.00071310694,0.00036941748,0.000025210797,0.000026465865,0.0013543528],"genre_scores_gemma":[0.9945132,0.00022259659,0.002575711,0.0025156913,0.00013659561,0.000003599229,0.0000011490998,0.000016644666,0.00001482099],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9960534,0.00051480945,0.0010570292,0.00059563294,0.0007896847,0.0009894228],"domain_scores_gemma":[0.9968787,0.00055503397,0.00081181875,0.0002128634,0.0005557193,0.0009858761],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00198231,0.00032035875,0.0006794622,0.0011554987,0.00075630954,0.0002474363,0.00088489876,0.00012286175,0.00015842612],"category_scores_gemma":[0.0012250841,0.00022935675,0.000220907,0.0015017599,0.003253073,0.00081354496,0.00007449318,0.001090219,0.0000019033105],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012370945,0.00009656765,0.9825554,0.000012794172,0.0000069826615,0.0030917784,0.00022785162,0.0010358864,0.007294804,0.00047277912,0.00027365523,0.0036943946],"study_design_scores_gemma":[0.0041899565,0.16886806,0.77393997,0.0004637508,0.0001263482,0.028285468,0.0008285726,0.0055851075,0.005044744,0.0076575824,0.004155274,0.00085518137],"about_ca_topic_score_codex":0.0005375907,"about_ca_topic_score_gemma":0.0050693047,"teacher_disagreement_score":0.20861547,"about_ca_system_score_codex":0.00033651062,"about_ca_system_score_gemma":0.0015413861,"threshold_uncertainty_score":0.9994595},"labels":[],"label_agreement":null},{"id":"W4236543179","doi":"10.31234/osf.io/eymkz","title":"Acute conceptual disorganization in untreated first-episode psychosis: A combined magnetic resonance spectroscopy and diffusion imaging study of the cingulum","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Lawson Health Research Institute; Western University","funders":"","keywords":"Cingulum (brain); Fractional anisotropy; White matter; Glutamate receptor; Psychology; Glutathione; Diffusion MRI; Neuroscience; Psychosis; Internal medicine; Magnetic resonance imaging; Chemistry; Medicine; Psychiatry; Radiology; Biochemistry","score_opus":0.025169377874137196,"score_gpt":0.31330688316521743,"score_spread":0.28813750529108023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236543179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9826498,0.0005012195,0.003939841,0.009237995,0.0000629099,0.0031077834,0.000025381763,0.00022638433,0.0002487044],"genre_scores_gemma":[0.9954236,0.00058944564,0.0031611568,0.0004186305,0.000025554415,0.00018652013,0.000027477225,0.000046554072,0.00012104044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99852014,0.00005397774,0.0004330011,0.00061048125,0.00021093685,0.00017149486],"domain_scores_gemma":[0.9989561,0.000042124662,0.00019726428,0.0006633176,0.000079042744,0.00006214214],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000048561098,0.000251689,0.00044550645,0.00008291153,0.00008520671,0.00001931638,0.00022107757,0.000068202804,0.000025893865],"category_scores_gemma":[0.00006356489,0.00018972725,0.000046144345,0.00046412757,0.00015970354,0.000028797069,0.0006064812,0.00049949175,8.448058e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019297937,0.0009370199,0.9853215,0.00009346058,0.000017656948,0.000013256318,0.001852201,0.000014703062,0.009596573,0.00040790153,0.0008230695,0.0007296404],"study_design_scores_gemma":[0.005657716,0.0009056342,0.96172714,0.0009910092,0.00043939095,0.000020645832,0.0011755299,0.015360777,0.008631934,0.004139482,0.00054796337,0.0004027784],"about_ca_topic_score_codex":0.00053014787,"about_ca_topic_score_gemma":0.0002816517,"teacher_disagreement_score":0.0235944,"about_ca_system_score_codex":0.000059284048,"about_ca_system_score_gemma":0.000020227659,"threshold_uncertainty_score":0.7736853},"labels":[],"label_agreement":null},{"id":"W4237118391","doi":"10.31234/osf.io/wd98h","title":"An Initial Investigation of Disrupted Intracortical Myelin as a Novel Brain Marker of Alcohol Use Disorder","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Precuneus; White matter; Neuroscience; Psychology; Posterior cingulate; Anterior cingulate cortex; Ventromedial prefrontal cortex; Neuroimaging; Insula; Prefrontal cortex; Medicine; Magnetic resonance imaging; Cortex (anatomy); Functional magnetic resonance imaging; Cognition","score_opus":0.15440208597497676,"score_gpt":0.42620404116303323,"score_spread":0.2718019551880565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237118391","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6770024,0.000009465225,0.3085861,0.012250646,0.000035033787,0.0011707942,0.00015717838,0.00024871665,0.0005397291],"genre_scores_gemma":[0.8653011,0.00002313108,0.13200474,0.0019078868,0.0000745568,0.00009980741,0.0004894307,0.00004323996,0.00005611116],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984058,0.000042971384,0.00065151433,0.0004863963,0.00027163973,0.00014164922],"domain_scores_gemma":[0.99844396,0.0001691753,0.00028187816,0.00069251534,0.00021443875,0.00019800969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010438059,0.00021797261,0.00047306358,0.0001103198,0.000020222255,0.00001356815,0.00017348563,0.000203907,0.00011599533],"category_scores_gemma":[0.00062209606,0.00019879495,0.0001245988,0.00020857897,0.00027452208,0.000092066904,0.0002686634,0.0005688497,0.0000032432692],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00086576014,0.0013197201,0.056329556,0.0010522255,0.00017938501,0.000026440099,0.00058907724,0.00018059555,0.8881286,0.039302327,0.0021786091,0.009847699],"study_design_scores_gemma":[0.0044593853,0.0015539492,0.57975745,0.0014054631,0.00095187436,0.000117538395,0.00021817541,0.09931925,0.21449198,0.09226881,0.0042578406,0.0011982917],"about_ca_topic_score_codex":0.00023630515,"about_ca_topic_score_gemma":0.000007975293,"teacher_disagreement_score":0.6736366,"about_ca_system_score_codex":0.000022312883,"about_ca_system_score_gemma":0.0001918916,"threshold_uncertainty_score":0.81066227},"labels":[],"label_agreement":null},{"id":"W4237123821","doi":"10.31234/osf.io/kyxbq","title":"Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies","year":2020,"lang":"en","type":"review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Helse Sør-Øst RHF; Norges Forskningsråd; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"White matter; Diffusion MRI; Executive functions; Extant taxon; Psychology; Cognition; Working memory; Concordance; Cognitive psychology; Developmental psychology; Magnetic resonance imaging; Neuroscience; Medicine","score_opus":0.04825682532562744,"score_gpt":0.3622717479132317,"score_spread":0.3140149225876043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237123821","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011713617,0.9974664,0.00048398445,0.0004700808,0.000011179684,0.0012835987,0.00003575408,0.000035112575,0.00009675592],"genre_scores_gemma":[0.000020929418,0.9749614,0.024365151,0.00024157342,0.000018020512,0.000089521825,0.000031050666,0.000023712613,0.0002486257],"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989255,0.000018332927,0.00056862953,0.000296052,0.00009778717,0.000093708884],"domain_scores_gemma":[0.9992849,0.000022115222,0.00032929788,0.00021765853,0.00008572723,0.000060284325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041713447,0.00024332051,0.0013528216,0.00007130199,0.00009722488,0.000002175825,0.00005351398,0.000060591974,0.000018743014],"category_scores_gemma":[0.000024047904,0.00016318687,0.00009937099,0.00020712902,0.00012051358,0.000021774924,0.00030854598,0.00022888195,0.0000011951926],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007739902,0.00008625164,0.00072648,0.5960629,0.00023906438,0.0000045677975,0.00093672855,5.213969e-9,0.00019801146,0.000026890842,0.0023934168,0.39931792],"study_design_scores_gemma":[0.00020200505,0.000031775588,0.0038096788,0.29694587,0.0010368978,0.00029159334,0.00016562245,1.1837133e-7,0.00008181767,0.000015507389,0.6972172,0.00020187479],"about_ca_topic_score_codex":3.1543564e-7,"about_ca_topic_score_gemma":2.1057986e-7,"teacher_disagreement_score":0.6948238,"about_ca_system_score_codex":0.000025479343,"about_ca_system_score_gemma":0.00007099992,"threshold_uncertainty_score":0.6654567},"labels":[],"label_agreement":null},{"id":"W4237537945","doi":"10.21203/rs.3.rs-17303/v6","title":"Detection of gray matter microstructural changes in Alzheimer’s disease continuum using fiber orientation","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Meso Scale Diagnostics; National Research Foundation of Korea; National Research Foundation; Korea Health Industry Development Institute; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; University of California, San Diego; Biogen; BioClinica; Eli Lilly and Company; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Bristol-Myers Squibb; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Orientation (vector space); Materials science; Neuroscience; Nanotechnology; Psychology; Mathematics; Geometry","score_opus":0.18775313634604998,"score_gpt":0.4719486250206884,"score_spread":0.2841954886746384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237537945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99021596,0.00063449814,0.0017308109,0.0044215294,0.00007460374,0.0025301096,0.00019249428,0.000093972674,0.00010604398],"genre_scores_gemma":[0.9957174,0.000083219624,0.003440984,0.00009345777,0.00014466194,0.00021996419,0.00019867961,0.000041380903,0.00006022782],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985032,0.00011753782,0.00024644312,0.00047024098,0.00039708812,0.000265469],"domain_scores_gemma":[0.99892443,0.000062370884,0.0001164933,0.00043827938,0.00030980745,0.00014861087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001746058,0.00015254867,0.0002723867,0.00032132326,0.00006225884,0.000024920455,0.00012425108,0.00010334372,0.00010251517],"category_scores_gemma":[0.00010197044,0.00014612812,0.00008173023,0.00037630353,0.00014044011,0.000042096835,0.00034547283,0.0008211212,0.000015521146],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001127859,0.00022583974,0.12875883,0.003292464,0.00008261156,0.00013367129,0.0007677938,0.00010491567,0.84561855,0.00007811524,0.0014354552,0.018373908],"study_design_scores_gemma":[0.0011424161,0.00025456524,0.58359927,0.0024952306,0.00021543412,0.00002623607,0.00023361936,0.0033032936,0.3951848,0.008322209,0.004785294,0.00043764792],"about_ca_topic_score_codex":0.00021039553,"about_ca_topic_score_gemma":0.000043360018,"teacher_disagreement_score":0.45484045,"about_ca_system_score_codex":0.00012542591,"about_ca_system_score_gemma":0.00011694457,"threshold_uncertainty_score":0.59589314},"labels":[],"label_agreement":null},{"id":"W4238246613","doi":"10.1093/oxfordhb/9780198827474.013.6","title":"Diffusion imaging perspectives on brain development in childhood and adolescence","year":2021,"lang":"en","type":"reference-entry","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Brain development; Diffusion imaging; Tractography; Reading (process); Psychology; Cognition; Neuroscience; Cognitive science; Computer science; Cognitive psychology; Magnetic resonance imaging; Medicine; Political science","score_opus":0.03218922117453214,"score_gpt":0.32445512791405023,"score_spread":0.2922659067395181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238246613","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09433952,0.04441953,0.033317946,0.076424144,0.00039371342,0.005892173,0.000079346144,0.0018220097,0.74331164],"genre_scores_gemma":[0.33283117,0.2897902,0.19534644,0.016740525,0.00097370223,0.00071639783,0.001111413,0.00039285398,0.16209728],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986827,0.00002200213,0.0002311105,0.0006474125,0.00020638989,0.00021043287],"domain_scores_gemma":[0.9993784,0.000084749794,0.0000712902,0.00032158877,0.000054551565,0.00008942228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005996802,0.0002453499,0.00034335512,0.00019665799,0.000071388,0.000024129895,0.000081921586,0.00008743362,0.00005391922],"category_scores_gemma":[0.00012569956,0.00020822906,0.000042189033,0.00018518085,0.000054553082,0.000031317708,0.000146068,0.0006524954,0.0000050224203],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004475416,0.0017592928,0.01929312,0.000600795,0.000030006808,0.00026240599,0.0024957077,5.2484387e-7,0.00027704443,0.0041721826,0.07963786,0.8914263],"study_design_scores_gemma":[0.002101419,0.00013173885,0.37687147,0.015754037,0.000060530958,0.00036574632,0.0029711335,0.00013160329,0.0016179248,0.0009208789,0.5980112,0.0010623094],"about_ca_topic_score_codex":0.000013061701,"about_ca_topic_score_gemma":0.000006817106,"teacher_disagreement_score":0.890364,"about_ca_system_score_codex":0.00016067257,"about_ca_system_score_gemma":0.00021415742,"threshold_uncertainty_score":0.8491335},"labels":[],"label_agreement":null},{"id":"W4240121982","doi":"10.21203/rs.3.rs-151934/v3","title":"Regional cerebral blood flow decline can predict atrophy in Alzheimer’s disease spectrum","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Novartis Pharmaceuticals Corporation; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Cerebral blood flow; Medicine; Neuroscience; Cardiology; Disease; Neurodegeneration; Psychology; Internal medicine; Cerebral atrophy; Alzheimer's disease; Pathology","score_opus":0.1582735723650386,"score_gpt":0.4389821395994455,"score_spread":0.28070856723440685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4240121982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75435567,0.018386517,0.004447805,0.20688756,0.0003154892,0.010211851,0.0018734619,0.0013319693,0.002189685],"genre_scores_gemma":[0.9787738,0.0023234999,0.013848785,0.00048204928,0.0008271975,0.0010502414,0.0022849173,0.00011666837,0.00029289702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99603844,0.000246604,0.00045446816,0.0011650142,0.0013094111,0.0007860787],"domain_scores_gemma":[0.9970545,0.00017755316,0.00008870228,0.001654057,0.00036386514,0.00066129485],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00046343493,0.0003282335,0.00050672947,0.00052626076,0.0001561497,0.00009446785,0.00047354618,0.00021507818,0.00022179077],"category_scores_gemma":[0.00033998344,0.0003249872,0.0002911133,0.0007033018,0.00028441718,0.000051770377,0.0017155866,0.0028926108,0.000012892384],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034331856,0.012972848,0.8419715,0.007560106,0.0013488333,0.023904266,0.0012351811,0.0054248907,0.0024921873,0.011320522,0.0588286,0.02950788],"study_design_scores_gemma":[0.0069640507,0.0014076208,0.81117386,0.0116978595,0.0011187487,0.0004063221,0.00045745986,0.037562706,0.0043300353,0.080211975,0.042682905,0.0019864817],"about_ca_topic_score_codex":0.00048593013,"about_ca_topic_score_gemma":0.00022609683,"teacher_disagreement_score":0.22441807,"about_ca_system_score_codex":0.00021970253,"about_ca_system_score_gemma":0.0015180378,"threshold_uncertainty_score":0.9999202},"labels":[],"label_agreement":null},{"id":"W4243148449","doi":"10.14740/jnr498","title":"A Rare Case Presenting With Acute Stroke-Like Clinic: Todd’s Paralysis in the Setting of Frontal Dural-Based Tumor","year":2018,"lang":"en","type":"article","venue":"Journal of Neurology Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Neuroimaging; Stroke (engine); Lesion; Presentation (obstetrics); Paralysis; Radiology; Diffusion MRI; Surgery; Magnetic resonance imaging; Psychiatry","score_opus":0.13547468796090717,"score_gpt":0.4708616918822766,"score_spread":0.33538700392136944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243148449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98393726,0.00004042597,0.00058791373,0.014813884,0.000024840054,0.00034145554,0.000007342435,0.000010631527,0.0002362254],"genre_scores_gemma":[0.99371564,0.000019572497,0.0049988423,0.0010045344,0.00015500803,0.000020091316,0.0000013768555,0.00001700766,0.00006790536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980284,0.00046649933,0.0004992499,0.00019997808,0.00047454832,0.00033132845],"domain_scores_gemma":[0.99798715,0.00071055064,0.0003277832,0.00037846257,0.00051661447,0.00007943749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015854975,0.000093771574,0.0003235278,0.00036585983,0.00014656587,0.0000148720455,0.00028914525,0.000047963007,0.000034931953],"category_scores_gemma":[0.00033613047,0.00005657071,0.00010377834,0.00052253675,0.0004078949,0.00008303586,0.000079226775,0.0013124594,0.0000028943816],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007549872,0.0010587389,0.85833055,0.00011480137,0.00017342459,0.07470438,0.0010978151,0.00007146304,0.04175158,0.000042435666,0.013487299,0.0016176472],"study_design_scores_gemma":[0.014313893,0.033246957,0.5615511,0.0004105892,0.0009062892,0.32179368,0.0018721424,0.018774822,0.02920933,0.0012802221,0.016117118,0.00052386866],"about_ca_topic_score_codex":0.00003112265,"about_ca_topic_score_gemma":0.0000464028,"teacher_disagreement_score":0.29677945,"about_ca_system_score_codex":0.000016234979,"about_ca_system_score_gemma":0.00017199735,"threshold_uncertainty_score":0.57020557},"labels":[],"label_agreement":null},{"id":"W4244275492","doi":"10.22215/etd/2006-06365","title":"Rician noise corrected multi-component analysis of the MR diffusion signal decay for human brain in vivo","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Rician fading; Noise (video); Physics; Computer science; Telecommunications; Artificial intelligence","score_opus":0.037154925508596816,"score_gpt":0.36313552015658856,"score_spread":0.32598059464799173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244275492","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.965399,0.000033045322,0.02992306,0.00038365115,0.00005961204,0.00207488,0.00011982852,0.00013362453,0.0018732629],"genre_scores_gemma":[0.9703364,0.000009711278,0.0062726885,0.00027187043,0.000034861092,0.00035342816,0.0027135161,0.000051112736,0.019956442],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987696,0.000028200999,0.0004907223,0.0003485278,0.00019878086,0.00016419408],"domain_scores_gemma":[0.99894667,0.00012451538,0.0003218316,0.00042285022,0.00014560694,0.00003853984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008170892,0.00020370925,0.00051024585,0.0004851683,0.00010005487,0.000006726682,0.000171277,0.00014063039,0.00006831007],"category_scores_gemma":[0.000027674583,0.0001464367,0.00035525646,0.0009378831,0.000031657306,0.000016899574,0.000022463466,0.00021575179,3.6653404e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009862466,0.0008599403,0.010042231,0.0001120885,0.00010814029,0.0000016207493,0.0001472246,0.00018416891,0.9842034,0.00060077646,0.0023742071,0.0012675773],"study_design_scores_gemma":[0.0020622138,0.00013787331,0.6488989,0.00041274587,0.0023798086,0.0000017032286,0.00025391992,0.035978515,0.30505365,0.00035172285,0.0040526506,0.0004162747],"about_ca_topic_score_codex":0.0008939407,"about_ca_topic_score_gemma":0.005113576,"teacher_disagreement_score":0.67914975,"about_ca_system_score_codex":0.00007588559,"about_ca_system_score_gemma":0.000037873553,"threshold_uncertainty_score":0.59715146},"labels":[],"label_agreement":null},{"id":"W4244753611","doi":"10.1002/0470018860.s00314","title":"Cerebral Commissures","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Cognitive Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Corpus callosum; Commissure; Neuroscience; Psychology; Brain asymmetry; Anatomy; Biology; Lateralization of brain function","score_opus":0.03512739118725164,"score_gpt":0.367432128356595,"score_spread":0.3323047371693434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244753611","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011887666,0.00039336339,0.002507109,0.0002781936,0.00007200805,0.00050886057,0.00007429906,0.00023911982,0.9958082],"genre_scores_gemma":[0.022749104,0.0010859354,0.013126078,0.0003284402,0.0003921625,0.00004899654,0.000022601285,0.00016347443,0.9620832],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881834,0.000009369254,0.00017025924,0.00038617046,0.0003932418,0.00022265085],"domain_scores_gemma":[0.9991735,0.00006385952,0.00018245472,0.00030973114,0.00014421021,0.00012624932],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001056232,0.00016490748,0.00027812071,0.0003170543,0.000051310562,0.0000067619785,0.00023863284,0.00006928262,0.0016828194],"category_scores_gemma":[0.0002887325,0.00014576259,0.000058627982,0.00048278167,0.0011660405,0.00005363078,0.00009395098,0.00020943774,0.00007501823],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005503029,0.0005312818,0.008699337,0.00026194332,0.000049237435,0.00003602434,0.00036647747,3.804788e-7,0.00093775603,0.007848686,0.7387982,0.24241562],"study_design_scores_gemma":[0.0002934381,0.00009205356,0.0052869082,0.00064218434,0.000061250605,0.000021831314,0.0000410964,0.000008987222,0.0014470327,0.0003374394,0.9915942,0.00017358115],"about_ca_topic_score_codex":0.000021218122,"about_ca_topic_score_gemma":0.000005941957,"teacher_disagreement_score":0.25279596,"about_ca_system_score_codex":0.00001851162,"about_ca_system_score_gemma":0.00024047967,"threshold_uncertainty_score":0.9992298},"labels":[],"label_agreement":null},{"id":"W4246958620","doi":"10.1016/j.clinph.2014.10.202","title":"43. Cerebellar activity in cervical dystonia during a motor timing task: An fMRI study","year":2015,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Cervical dystonia; Dystonia; Cerebellum; Neuroscience; Neurology; Supplementary motor area; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Psychology; Movement disorders; Motor cortex; Physical medicine and rehabilitation; Pathology; Radiology","score_opus":0.21298018463733398,"score_gpt":0.45605786596873243,"score_spread":0.24307768133139845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4246958620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974785,0.000007888317,0.00019966697,0.0010367254,0.00014090171,0.0007681579,0.0000041585895,0.00024428294,0.00011971128],"genre_scores_gemma":[0.99700606,0.000028549317,0.0016684404,0.0007708434,0.00030583833,0.00007231053,0.000005688148,0.00004358195,0.000098668366],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99783367,0.00040839394,0.0005117948,0.00077130744,0.0001431638,0.0003316707],"domain_scores_gemma":[0.99838567,0.00024103464,0.00012246615,0.00082631805,0.0000771052,0.0003473997],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002122405,0.00019040404,0.000567201,0.0000868302,0.0000661713,0.000008471372,0.00022950192,0.0001280432,0.0000124101125],"category_scores_gemma":[0.00047379313,0.0001700303,0.00010008714,0.00023826215,0.00018969423,0.000087878776,0.00024961925,0.00080314715,0.000055636967],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042418074,0.015319138,0.3091495,0.00009449829,0.000051209103,0.0016503354,0.00034187568,0.00019099144,0.65589815,0.00018617524,0.000277112,0.0125991795],"study_design_scores_gemma":[0.0023607465,0.0038285772,0.98942643,0.000015415042,0.00003739051,0.000049305563,0.000046433466,0.0018279711,0.000664153,0.0005619843,0.001005985,0.00017560647],"about_ca_topic_score_codex":0.00002608734,"about_ca_topic_score_gemma":0.000006506774,"teacher_disagreement_score":0.68027693,"about_ca_system_score_codex":0.00004350298,"about_ca_system_score_gemma":0.000070408794,"threshold_uncertainty_score":0.6933634},"labels":[],"label_agreement":null},{"id":"W4247546798","doi":"10.1002/(sici)1520-6777(2000)19:2<176::aid-nau7>3.3.co;2-y","title":"Editorial comment","year":2000,"lang":"en","type":"editorial","venue":"Neurourology and Urodynamics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Misericordia Community Hospital","funders":"","keywords":"Citation; Library science; Center (category theory); Medicine; Computer science","score_opus":0.015255911939679404,"score_gpt":0.32280369128638764,"score_spread":0.30754777934670824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247546798","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00027550908,0.000096363045,0.00029680366,0.0054046838,0.9913394,0.00038472103,0.00015502753,0.00029232315,0.0017552009],"genre_scores_gemma":[0.00018291903,0.0029649867,0.0006509423,0.002664565,0.9920417,0.000058074005,0.00060440745,0.00007972872,0.0007526623],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984784,0.00005019718,0.0002755469,0.0005972307,0.000302983,0.00029565717],"domain_scores_gemma":[0.99875784,0.00036145863,0.000116566196,0.00053140114,0.00009434499,0.00013840962],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008802066,0.00030316957,0.00046052958,0.000102490536,0.00013470356,0.000019403771,0.00015191696,0.00088657386,0.000028911361],"category_scores_gemma":[0.0001702809,0.00029480027,0.00009074523,0.00008629377,0.00019408895,0.00003205313,0.00011124562,0.0019528315,0.000018237533],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023594721,0.000088270855,0.000047651152,0.00003632684,0.000016465086,0.000034659937,0.000005317996,0.0000033587905,0.00002413549,0.0002110297,0.99770606,0.0015907922],"study_design_scores_gemma":[0.0006669841,0.0005388496,0.00007546597,0.000016076141,0.0001833649,0.000051761235,5.658684e-7,0.00030264028,0.0000018994384,0.0011426689,0.9968351,0.00018463765],"about_ca_topic_score_codex":0.000009154349,"about_ca_topic_score_gemma":0.0000019905126,"teacher_disagreement_score":0.0028686237,"about_ca_system_score_codex":0.000028321369,"about_ca_system_score_gemma":0.000117836586,"threshold_uncertainty_score":0.9999504},"labels":[],"label_agreement":null},{"id":"W4248396262","doi":"10.1515/iupac.88.1498","title":"White Matter","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","score_opus":0.0487649783676308,"score_gpt":0.49893799785971954,"score_spread":0.45017301949208877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248396262","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000028556982,0.0001632066,0.0007546408,0.006203841,0.00014985683,0.00049484614,0.99167985,0.00014938606,0.00037580013],"genre_scores_gemma":[0.000018259603,0.00047989114,0.001877153,0.0022571862,0.000612237,0.000048449874,0.9913077,0.00005467336,0.0033444786],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983829,0.000013920379,0.00029696114,0.0004880155,0.0005307491,0.00028743327],"domain_scores_gemma":[0.9972274,0.000017860277,0.0002692957,0.0020359894,0.00028724936,0.00016222509],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013333782,0.00032180743,0.0005516977,0.00013533501,0.00017276604,0.0000551517,0.00036699264,0.000217704,0.0027249933],"category_scores_gemma":[0.000117699914,0.00027782074,0.0001645231,0.00006726363,0.00016408939,0.00005561603,0.00018443448,0.00071741844,0.000020280515],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057977475,0.00016165417,0.00064141466,0.00015249968,0.000026124633,0.000098525845,0.0000017096833,2.1034613e-7,0.000004145852,0.0000026803814,0.99828595,0.00056709134],"study_design_scores_gemma":[0.0004688327,0.00011010583,0.0024014935,0.0003693759,0.0002030214,0.00014198387,0.0000021125625,0.0000039721854,0.000011619695,0.00020876329,0.99583,0.00024872718],"about_ca_topic_score_codex":0.000025995982,"about_ca_topic_score_gemma":0.000027416494,"teacher_disagreement_score":0.003946655,"about_ca_system_score_codex":0.00015282442,"about_ca_system_score_gemma":0.00030307146,"threshold_uncertainty_score":0.9999674},"labels":[],"label_agreement":null},{"id":"W4249581603","doi":"10.1017/cjn.2019.183","title":"P.087 The influence of disease lateralization in Parkinson’s Disease on tractography in DBS patients","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Motor cortex; Diffusion MRI; Parkinson's disease; Lateralization of brain function; Medicine; Neuroscience; Cortex (anatomy); Disease; Tractography; White matter; Psychology; Magnetic resonance imaging; Pathology; Stimulation; Radiology","score_opus":0.032662868879588206,"score_gpt":0.29722750021525907,"score_spread":0.2645646313356709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249581603","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99388254,0.00015413418,0.000006549025,0.005233549,0.00012329686,0.00035282286,0.000012253957,0.000008132392,0.00022669729],"genre_scores_gemma":[0.9957572,0.00027127934,0.00023507132,0.003686551,0.000029443043,0.0000057153943,4.922859e-7,0.0000072687135,0.000006938184],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9974264,0.00037102614,0.00068678445,0.0003644859,0.00055106,0.0006002399],"domain_scores_gemma":[0.9978115,0.00032102555,0.0004970758,0.00018352624,0.00022912302,0.000957766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00130551,0.00018720757,0.0003123341,0.00095905067,0.0003806461,0.00010772582,0.00091013446,0.00005252861,0.000033627177],"category_scores_gemma":[0.001097582,0.00011191541,0.0001388018,0.0015704008,0.0021067401,0.0005009573,0.00003193719,0.0007847292,0.0000011529946],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021487226,0.00007195243,0.981691,0.000008945183,0.000001467903,0.0005391318,0.00007628961,0.016268043,0.000019040888,0.0005705318,0.000035820984,0.00050291966],"study_design_scores_gemma":[0.00032877843,0.010131527,0.97851855,0.00010322541,0.0000106119705,0.00019848323,0.000018991648,0.00078176934,0.000014000547,0.008483788,0.001305625,0.00010465685],"about_ca_topic_score_codex":0.0004670329,"about_ca_topic_score_gemma":0.005254622,"teacher_disagreement_score":0.015486274,"about_ca_system_score_codex":0.00011642772,"about_ca_system_score_gemma":0.0011552422,"threshold_uncertainty_score":0.7762372},"labels":[],"label_agreement":null},{"id":"W4249932430","doi":"10.1007/s00062-015-0425-8","title":"Erratum to: Diagnostics to Look beyond the Normal Appearing Brain Tissue (NABT)? A Neuroimaging Study of Patients with Primary Headache and NABT Using Magnetization Transfer Imaging and Diffusion Magnetic Resonance","year":2015,"lang":"en","type":"erratum","venue":"Clinical Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Neuroimaging; Magnetic resonance imaging; Diffusion MRI; Medicine; Magnetization transfer; Nuclear magnetic resonance; Radiology; Physics; Psychiatry","score_opus":0.043791940382237465,"score_gpt":0.35648342893521096,"score_spread":0.31269148855297346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249932430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98012924,0.0028144992,0.003460484,0.0067086034,0.0012885258,0.0049076476,0.00008101527,0.00014018184,0.00046979764],"genre_scores_gemma":[0.9191477,0.0037039348,0.016192416,0.05003585,0.0025798576,0.00061502564,0.0006774965,0.0008721328,0.0061756363],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99651915,0.00043400165,0.0009994932,0.0011945233,0.00037951642,0.0004733191],"domain_scores_gemma":[0.9974302,0.0008189955,0.00020486861,0.0008627107,0.00030513195,0.00037810951],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00046510677,0.00047966462,0.00106619,0.00022269019,0.00020124925,0.000042531483,0.00030887936,0.000202319,0.0000036189379],"category_scores_gemma":[0.0009956209,0.0003699809,0.00005593648,0.0004555999,0.0005133922,0.00008806641,0.00047424587,0.0014788668,0.000001200396],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013632665,0.0019289162,0.717028,0.0004384325,0.00003537789,0.00024223031,0.0010504721,0.00006721066,0.0014507312,0.00003919165,0.20255658,0.07379956],"study_design_scores_gemma":[0.0030083943,0.0076865186,0.8833866,0.00036383048,0.00043900628,0.00016380507,0.000099005316,0.0018435605,0.000006845383,0.00012487939,0.10237302,0.0005045269],"about_ca_topic_score_codex":0.00004415692,"about_ca_topic_score_gemma":0.000021904085,"teacher_disagreement_score":0.16635858,"about_ca_system_score_codex":0.000043158227,"about_ca_system_score_gemma":0.00016118784,"threshold_uncertainty_score":0.9998752},"labels":[],"label_agreement":null},{"id":"W4250695708","doi":"10.1016/j.jalz.2019.06.4828","title":"F5‐02‐02: HIGHER LITERACY ASSOCIATES WITH BETTER BRAIN STRUCTURE AND COGNITION IN MIDDLE‐AGED INDIVIDUALS","year":2019,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Cognition; White matter; Psychology; Literacy; Diffusion MRI; Logistic regression; Effects of sleep deprivation on cognitive performance; Medicine; Clinical psychology; Internal medicine; Gerontology; Neuroscience; Magnetic resonance imaging","score_opus":0.03492232176081524,"score_gpt":0.30974468124041904,"score_spread":0.2748223594796038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250695708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98999405,0.0037045835,0.00010061628,0.0047416743,0.000036806345,0.0007557964,0.00005581663,0.00011000843,0.0005006668],"genre_scores_gemma":[0.98275566,0.000025431238,0.012524601,0.0042674234,0.00004797681,0.00005111087,0.00021850594,0.000033169326,0.000076118056],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990493,0.000035453562,0.0001995821,0.0003277176,0.00016830779,0.00021963126],"domain_scores_gemma":[0.9994802,0.00007449507,0.000103888095,0.00023592824,0.000046021512,0.00005946901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008339902,0.00015998856,0.00020617757,0.000092737915,0.00004957142,0.000042864864,0.00006740482,0.0000704254,0.0003604458],"category_scores_gemma":[0.0000075797816,0.00013482521,0.000026863072,0.0001634745,0.000043815566,0.00020094185,0.00005209733,0.00023930211,0.000021601225],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006386826,0.00017159841,0.93096423,0.0000325012,0.0020658886,0.00002385523,0.00045958502,0.0000011478895,0.040604074,0.0004227491,0.0059882547,0.01920225],"study_design_scores_gemma":[0.0027324075,0.00025531754,0.9230098,0.00023574804,0.003820322,0.00003461523,0.000026959286,0.000024667903,0.038692098,0.004189818,0.026609944,0.00036829902],"about_ca_topic_score_codex":0.000013152339,"about_ca_topic_score_gemma":0.0000053509093,"teacher_disagreement_score":0.020621689,"about_ca_system_score_codex":0.000005172868,"about_ca_system_score_gemma":0.000013534793,"threshold_uncertainty_score":0.5498013},"labels":[],"label_agreement":null},{"id":"W4252126261","doi":"10.1017/s0317167100120591","title":"Program - 39th Canadian Congress of Neurological Sciences - Calgary, AB","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"Pfizer (Canada)","funders":"","keywords":"Action (physics); Medicine; Neuroscience; Psychology; Political science; Physics","score_opus":0.07349139815938738,"score_gpt":0.34707564195235424,"score_spread":0.27358424379296686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252126261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97853124,0.0008257369,0.000101220714,0.01484046,0.0006110575,0.00056392513,0.000024193338,0.000070837654,0.0044313283],"genre_scores_gemma":[0.9720917,0.0004794908,0.021270767,0.0058869543,0.0002122877,0.0000135177,9.4486774e-7,0.000021051816,0.00002333608],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9942254,0.00046161326,0.0013115446,0.0008813947,0.0011131484,0.0020069382],"domain_scores_gemma":[0.99403024,0.00034030926,0.0009992429,0.0003002557,0.00072758633,0.0036023762],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0031767085,0.00048298054,0.00086520443,0.0016857006,0.0032279538,0.00046968457,0.002523878,0.00029267298,0.00015276312],"category_scores_gemma":[0.002109785,0.00032883775,0.00039660838,0.0026546812,0.016879357,0.00084557757,0.000103884246,0.0018116403,0.0000046823793],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013108033,0.00023474793,0.957961,0.000026589285,0.000027831658,0.011148734,0.00019157131,0.0044018347,0.00019565325,0.013854214,0.0014290098,0.0103977285],"study_design_scores_gemma":[0.0018719877,0.29132402,0.47079045,0.00029815233,0.0002396011,0.1223158,0.00026808577,0.0026882426,0.0012265643,0.078821026,0.0289622,0.0011938479],"about_ca_topic_score_codex":0.019788727,"about_ca_topic_score_gemma":0.18562065,"teacher_disagreement_score":0.48717055,"about_ca_system_score_codex":0.00030977212,"about_ca_system_score_gemma":0.00979974,"threshold_uncertainty_score":0.9999164},"labels":[],"label_agreement":null},{"id":"W4252441736","doi":"10.1002/jmri.21928","title":"Response","year":2009,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Corpus callosum; Diffusion MRI; Consistency (knowledge bases); White matter; Range (aeronautics); Statistics; Limit (mathematics); Psychology; Mathematics; Computer science; Medicine; Artificial intelligence; Neuroscience; Magnetic resonance imaging; Mathematical analysis; Radiology","score_opus":0.031608599297337725,"score_gpt":0.3474184962907703,"score_spread":0.3158098969934326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252441736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7114639,0.052599978,0.03442349,0.19146264,0.00021163524,0.00056250824,0.0000042866623,0.0002190369,0.00905252],"genre_scores_gemma":[0.9129678,0.00044724924,0.081008635,0.0045972476,0.00014171653,0.0000018244708,2.4470162e-7,0.000013620764,0.00082167366],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999143,0.000031921398,0.00033682713,0.00010571483,0.0002256679,0.0001568782],"domain_scores_gemma":[0.99927044,0.000068752575,0.00016333522,0.00022518844,0.00017340947,0.00009885736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035504397,0.00008510986,0.00018872826,0.0001292365,0.000042542353,0.00001772174,0.00011758868,0.000015307043,0.000041089712],"category_scores_gemma":[0.00023529635,0.00007040129,0.000094831135,0.0001823778,0.000049624017,0.00011156331,0.000012021988,0.00024012463,0.000005612113],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001122135,0.00014274177,0.007405823,0.0000047467533,0.0000012415716,0.0005252235,0.00006495437,0.0000036624688,0.09469957,0.00040975594,0.015505429,0.88011473],"study_design_scores_gemma":[0.0010615335,0.0007477948,0.42251435,0.00021988306,0.000032192675,0.0040245526,0.000029113116,0.00039932108,0.0049033593,0.0042224033,0.5617454,0.000100093814],"about_ca_topic_score_codex":4.0548326e-7,"about_ca_topic_score_gemma":1.576928e-8,"teacher_disagreement_score":0.8800146,"about_ca_system_score_codex":0.00004042,"about_ca_system_score_gemma":0.000071616516,"threshold_uncertainty_score":0.28708813},"labels":[],"label_agreement":null},{"id":"W4252507602","doi":"10.1017/s0317167100000809","title":"35th Meeting of the Canadian Congress of Neurological Sciences June 13- 17, 2000 Ottawa, Ontario Program and Abstracts","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"Medical Research Council; University of Cambridge; Heart and Stroke Foundation of Canada","keywords":"Library science; Action (physics); Political science; Medicine; Computer science; Physics","score_opus":0.051961381451173516,"score_gpt":0.312746832703439,"score_spread":0.2607854512522655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4252507602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785037,0.00055237155,0.000001754544,0.010437369,0.00030896667,0.00043863518,0.000022436923,0.00002186469,0.009712886],"genre_scores_gemma":[0.9914772,0.00021453404,0.004899129,0.003109209,0.00009441651,0.0000062696745,3.6751504e-7,0.000011688139,0.00018722196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99543434,0.00046559362,0.00125976,0.00062858785,0.0009276929,0.0012840081],"domain_scores_gemma":[0.99601674,0.0003893818,0.0010429252,0.00025316505,0.00046914633,0.00182863],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0033071071,0.00034901936,0.000676133,0.0007030435,0.002871261,0.00031579792,0.0018828028,0.00021958322,0.00030669558],"category_scores_gemma":[0.0011818896,0.0002093642,0.00025992247,0.0016277368,0.015563643,0.00053247425,0.00007324955,0.001565584,8.878252e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056177334,0.000073043295,0.9879689,0.0000122272795,0.000011968803,0.0009489002,0.00026434456,0.0024698419,0.00007957758,0.00050960016,0.0011341337,0.006471278],"study_design_scores_gemma":[0.0004365011,0.03850917,0.90325415,0.00015369663,0.00010126029,0.02162994,0.0000816,0.001070267,0.00037853786,0.007181882,0.02686531,0.00033767725],"about_ca_topic_score_codex":0.15515088,"about_ca_topic_score_gemma":0.9298571,"teacher_disagreement_score":0.7747062,"about_ca_system_score_codex":0.00021834824,"about_ca_system_score_gemma":0.008310667,"threshold_uncertainty_score":0.99842685},"labels":[],"label_agreement":null},{"id":"W4253133942","doi":"10.1016/j.jalz.2016.06.1900","title":"P3‐238: Associations Between Quantitative Tractography at 3T MRI and Cognitive Function in Alzheimer’s Disease","year":2016,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Queen's University; University of Toronto","funders":"","keywords":"Tractography; Disease; Cognition; Medicine; Neuroscience; Diffusion MRI; Psychology; Magnetic resonance imaging; Pathology; Radiology","score_opus":0.09366932744883896,"score_gpt":0.3640812705890986,"score_spread":0.2704119431402596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253133942","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.68809116,0.13827033,0.13211963,0.028061274,0.0003164597,0.006054325,0.002554565,0.0012180359,0.0033142196],"genre_scores_gemma":[0.995333,0.0003286694,0.003461928,0.00038470392,0.000049466576,0.00017867546,0.00021783185,0.00003328569,0.000012408695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99875015,0.000056167333,0.0003060851,0.00043118183,0.00019113204,0.00026529204],"domain_scores_gemma":[0.99903727,0.00029443853,0.0001590275,0.00021246872,0.00010571173,0.00019106064],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013160372,0.00018236364,0.00023616293,0.00018333853,0.00015645486,0.00001483141,0.000058969374,0.000058886228,0.000078959354],"category_scores_gemma":[0.00005271857,0.0001487134,0.000090097565,0.0002911032,0.00014607988,0.00022056156,0.00006916097,0.00012584831,0.0000534191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028533084,0.00029810547,0.90569925,0.0000035033665,0.0051332293,0.000015053799,0.00013094269,3.2764567e-7,0.0030678448,0.0037286035,0.0023398108,0.07929801],"study_design_scores_gemma":[0.0013274718,0.00021313713,0.96175075,0.000086904154,0.02271105,0.0000019987635,0.000034851866,0.000016751384,0.0034834517,0.00418459,0.0059487363,0.00024030874],"about_ca_topic_score_codex":0.000028319415,"about_ca_topic_score_gemma":0.00002478043,"teacher_disagreement_score":0.3072419,"about_ca_system_score_codex":0.000010009467,"about_ca_system_score_gemma":0.000032316057,"threshold_uncertainty_score":0.60643566},"labels":[],"label_agreement":null},{"id":"W4254125247","doi":"10.7287/peerj.preprints.2323v1","title":"Whole-brain ex-vivo quantitative MRI of the cuprizone mouse","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Corpus callosum; Ex vivo; Diffusion MRI; Myelin; Magnetic resonance imaging; Central nervous system; Neuroscience; Hippocampus; Cerebellum; Thalamus; Pathology; Nuclear magnetic resonance; Medicine; Anatomy; Biology; In vivo; Physics; Radiology","score_opus":0.09378277241434148,"score_gpt":0.3918385396305597,"score_spread":0.29805576721621824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254125247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040470146,0.00019824466,0.70976067,0.21045601,0.000191869,0.0029169908,0.00046444952,0.00067705166,0.034864556],"genre_scores_gemma":[0.49027497,0.00032222655,0.2961239,0.00593192,0.00028313443,0.0005712784,0.0000676738,0.00021129318,0.20621361],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884987,0.00004034471,0.00032210982,0.000401372,0.00022329342,0.00016299429],"domain_scores_gemma":[0.99803376,0.000168603,0.00026346502,0.0013133866,0.00015828072,0.00006247364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000121685516,0.00020236408,0.00035817924,0.00006810083,0.000045089375,0.0000074859986,0.0003401644,0.00012514435,0.00010438],"category_scores_gemma":[0.00015866956,0.000110775894,0.00020267697,0.00010684628,0.00023934981,0.000027428303,0.00065785943,0.0004353522,0.00002707187],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009584305,0.00035389856,0.0012789374,0.0003575357,0.000106843305,0.0000051903453,0.00025521507,0.000026487553,0.59735286,0.18945909,0.20877019,0.0019379108],"study_design_scores_gemma":[0.0010927122,0.00023030885,0.0023665132,0.0012457296,0.0001748891,0.000025925736,0.0001332246,0.00043697757,0.59639037,0.12632065,0.27109975,0.00048293453],"about_ca_topic_score_codex":0.000026197262,"about_ca_topic_score_gemma":0.0000034706275,"teacher_disagreement_score":0.4498048,"about_ca_system_score_codex":0.00004521532,"about_ca_system_score_gemma":0.00010871395,"threshold_uncertainty_score":0.451731},"labels":[],"label_agreement":null},{"id":"W4254767907","doi":"10.21203/rs.3.rs-276635/v1","title":"The trajectory of putative astroglial dysfunction in first episode schizophrenia: A longitudinal 7-Tesla MRS study","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Schulich School of Medicine and Dentistry; Canadian Institutes of Health Research; Academic Medical Organization of Southwestern Ontario; Natural Sciences and Engineering Research Council of Canada; Chrysalis","keywords":"Schizophrenia (object-oriented programming); Inositol; Anterior cingulate cortex; Psychosis; Antipsychotic; Internal medicine; Psychology; Cortex (anatomy); Magnetic resonance imaging; Psychiatry; Medicine; Neuroscience; Endocrinology; Cognition; Receptor; Radiology","score_opus":0.14077035095529916,"score_gpt":0.44873519592468875,"score_spread":0.3079648449693896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254767907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.987527,0.000953463,0.004190474,0.0024017785,0.00010790861,0.0042948653,0.00008533648,0.00011517015,0.00032397022],"genre_scores_gemma":[0.9951146,0.00039970325,0.0024148258,0.0000068387394,0.00015959452,0.0015623627,0.00009729312,0.000044907334,0.00019987284],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968603,0.00044187123,0.0004890511,0.0007313119,0.0010170927,0.0004603432],"domain_scores_gemma":[0.99720454,0.00078607537,0.00015244688,0.0009809656,0.0007590884,0.00011687972],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0012813889,0.00023054142,0.0004749881,0.00036395554,0.0003020184,0.00006822774,0.00032955318,0.00014642894,0.000021111113],"category_scores_gemma":[0.00084514014,0.00018094067,0.00018090394,0.00075368705,0.00036419777,0.00005607567,0.0007607244,0.002625078,0.0000044643207],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00561243,0.00916858,0.92060024,0.0033448501,0.0006081421,0.0012280429,0.0053653712,0.003639117,0.003355312,0.0015139439,0.002518586,0.0430454],"study_design_scores_gemma":[0.00319555,0.002158124,0.9756488,0.0018351714,0.00010933746,0.00003989365,0.007297247,0.0021246648,0.0035504007,0.0026505769,0.001051948,0.0003382791],"about_ca_topic_score_codex":0.00071142777,"about_ca_topic_score_gemma":0.00088253187,"teacher_disagreement_score":0.055048585,"about_ca_system_score_codex":0.00035114764,"about_ca_system_score_gemma":0.00042876744,"threshold_uncertainty_score":0.9996759},"labels":[],"label_agreement":null},{"id":"W4255397424","doi":"10.1017/cbo9781316146187.006","title":"Neuroimaging","year":2015,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Neuroimaging; Psychology; Neuroscience","score_opus":0.11606178957780547,"score_gpt":0.2965323569849975,"score_spread":0.18047056740719206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255397424","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000020086214,0.0001376514,0.0026468297,0.0001637989,0.000060564496,0.000515185,0.000111396286,0.0005638295,0.99578065],"genre_scores_gemma":[0.00045417357,0.000103671504,0.0016296232,0.00028577837,0.00012761903,0.0000010911468,0.00006780618,0.0000775064,0.9972527],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989485,0.000008846923,0.00013810671,0.00047462035,0.00022786653,0.00020203747],"domain_scores_gemma":[0.99864846,0.000023271416,0.00013822145,0.0007280923,0.00021596579,0.000245955],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000044506854,0.00027811746,0.00035087217,0.00014642367,0.00009539244,0.000014534595,0.00022850353,0.00015328827,0.0000038628123],"category_scores_gemma":[0.000009867046,0.0003263831,0.00016259585,0.000007966626,0.00019177522,0.000045160625,0.00027001632,0.0005746344,0.00002153266],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055225406,0.000009920466,0.0000034703462,0.00005072476,0.00003067052,0.00057934376,0.000004951026,6.4827117e-7,0.00017360384,0.8248763,0.17186293,0.0023521958],"study_design_scores_gemma":[0.0004456039,0.00005345543,0.000011954265,0.00014186221,0.00025617154,0.00016968064,0.000003778843,0.00006487242,0.00021165033,0.00006900405,0.99831283,0.00025916524],"about_ca_topic_score_codex":0.000016620883,"about_ca_topic_score_gemma":7.2430474e-8,"teacher_disagreement_score":0.8264499,"about_ca_system_score_codex":0.00017015621,"about_ca_system_score_gemma":0.00012389543,"threshold_uncertainty_score":0.9999188},"labels":[],"label_agreement":null},{"id":"W4280492380","doi":"10.1016/j.compbiomed.2022.105603","title":"Biomarkers identification for Schizophrenia via VAE and GSDAE-based data augmentation","year":2022,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Artificial intelligence; Pattern recognition (psychology); Feature selection; Autoencoder; Generative model; Identification (biology); Regularization (linguistics); Inference; Machine learning; Data mining; Deep learning; Generative grammar","score_opus":0.10161320967396054,"score_gpt":0.4258322277452344,"score_spread":0.32421901807127385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280492380","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15886852,0.0011582026,0.8156809,0.022614062,0.00034870196,0.001129381,0.00006848859,0.000103492115,0.000028215385],"genre_scores_gemma":[0.9546138,0.00013005393,0.041385677,0.0019604834,0.00008181468,0.00015262258,0.0016530749,0.000008724637,0.0000137294755],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993359,0.00003502647,0.00017837984,0.00031803147,0.00004053468,0.000092159884],"domain_scores_gemma":[0.9994129,0.00018968956,0.00006925354,0.0002702008,0.000016788048,0.000041157615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000303652,0.000069511036,0.00014166899,0.00013543208,0.0001349044,0.0000022665058,0.00009742075,0.000025612557,0.000005147575],"category_scores_gemma":[0.000050905684,0.00006198325,0.0000080810205,0.00012962529,0.00018910332,0.000029304214,0.00010940802,0.0000946988,1.2349147e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023806565,0.00039650867,0.10441855,0.00034210272,0.00011269915,0.000019490646,0.00036378362,0.00003894933,0.17553467,0.01647593,0.02160622,0.67831045],"study_design_scores_gemma":[0.028304938,0.0037815839,0.40073022,0.0003045303,0.00042191928,0.0004588375,0.00043586505,0.37196967,0.0034771578,0.082539804,0.10690687,0.00066858355],"about_ca_topic_score_codex":0.000013759585,"about_ca_topic_score_gemma":0.0000014910514,"teacher_disagreement_score":0.7957453,"about_ca_system_score_codex":0.000023891664,"about_ca_system_score_gemma":0.00001758007,"threshold_uncertainty_score":0.25276035},"labels":[],"label_agreement":null},{"id":"W4280493865","doi":"10.1177/0271678x221101644","title":"Global changes in diffusion tensor imaging during acute ischemic stroke and post-stroke cognitive performance","year":2022,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diffusion MRI; Stroke (engine); Ischemic stroke; Neuroimaging; Cognition; Medicine; Neuroscience; Cardiology; Psychology; Magnetic resonance imaging; Ischemia; Radiology; Physics","score_opus":0.012207150588037046,"score_gpt":0.2742123465121005,"score_spread":0.26200519592406346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280493865","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948173,0.0020858324,0.000116991425,0.0020639985,0.00011522523,0.00026914087,0.00024172287,0.00003701464,0.0002527816],"genre_scores_gemma":[0.9915335,0.0009695213,0.005993299,0.00073925324,0.00025293525,0.000028407738,0.000009630101,0.000025000332,0.00044846316],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986711,0.000043673408,0.00037488574,0.00023093187,0.0003843037,0.0002950658],"domain_scores_gemma":[0.9992177,0.000029271452,0.00029922294,0.00014601476,0.00016287607,0.00014491033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017913185,0.0001860077,0.00043301535,0.00023802333,0.0001889415,0.000022396156,0.00014359185,0.000029776718,0.0000712949],"category_scores_gemma":[0.00004916977,0.00016450827,0.00011142344,0.00023829691,0.000064848544,0.00022714036,0.00022586588,0.00059703225,9.686702e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011133128,0.00060482556,0.3911388,0.0001055853,0.00021452329,0.0004997414,0.00046278478,0.000035245142,0.57025945,0.000039214057,0.00023521908,0.03529128],"study_design_scores_gemma":[0.010147233,0.00051251415,0.88680065,0.0002713912,0.0013877389,0.0121914605,0.00077424105,0.0018944833,0.08084311,0.00006602847,0.0047260313,0.000385124],"about_ca_topic_score_codex":0.000008362831,"about_ca_topic_score_gemma":0.0000021615278,"teacher_disagreement_score":0.49566185,"about_ca_system_score_codex":0.000051283107,"about_ca_system_score_gemma":0.000057921432,"threshold_uncertainty_score":0.6708452},"labels":[],"label_agreement":null},{"id":"W4280537356","doi":"10.1101/2022.05.11.491489","title":"The length of the thalamo-cortical white matter fibers brings insight into sex differences in sleep spindle frequency","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Université de Montréal; Université de Sherbrooke; McGill University; École de Technologie Supérieure; Montreal Neurological Institute and Hospital; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Hôpital du Sacré-Cœur de Montréal","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Thalamus; Neuroscience; White matter; Sleep spindle; Gyrus; Psychology; Cortex (anatomy); Tractography; Superior frontal gyrus; Anatomy; Biology; Electroencephalography; Medicine; Functional magnetic resonance imaging; Slow-wave sleep; Magnetic resonance imaging","score_opus":0.024161190902236205,"score_gpt":0.26232258600818487,"score_spread":0.23816139510594866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280537356","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99270904,0.00052205916,0.0006410775,0.0041508777,0.00032190038,0.0012750279,0.00004471434,0.00018619435,0.0001490976],"genre_scores_gemma":[0.9935685,0.0002686602,0.0048073716,0.0005547238,0.00009961606,0.0005808381,2.718246e-7,0.000085716645,0.00003429508],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975578,0.00016144144,0.00064890564,0.00075049425,0.00047249222,0.00040884022],"domain_scores_gemma":[0.9973236,0.00013565268,0.00040442185,0.0018706808,0.00014479064,0.00012088444],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037687272,0.00038476085,0.0005223812,0.00014540805,0.00031917362,0.000063756175,0.000875506,0.00019725952,0.00009858117],"category_scores_gemma":[0.00015019168,0.00026745853,0.00018909771,0.00059728656,0.0003820949,0.00006805878,0.0010131983,0.0017067001,0.000008571369],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022378916,0.00019350993,0.92699474,0.00024223654,0.000061376646,0.000020363515,0.0000900205,0.000012750969,0.07040388,0.0017473134,0.00020395513,0.0000074618865],"study_design_scores_gemma":[0.00027274815,0.000048742695,0.9666646,0.00028762963,0.00009076873,9.1333035e-8,0.000012837539,0.0002433776,0.028612573,0.00008847997,0.0033625606,0.00031557467],"about_ca_topic_score_codex":0.00012056945,"about_ca_topic_score_gemma":0.0000063460825,"teacher_disagreement_score":0.041791305,"about_ca_system_score_codex":0.00025651962,"about_ca_system_score_gemma":0.00027045395,"threshold_uncertainty_score":0.99997777},"labels":[],"label_agreement":null},{"id":"W4280549307","doi":"10.1101/2022.04.19.22274057","title":"Exploring biomarkers of processing speed and executive function: the role of the anterior thalamic radiations","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; Vancouver Coastal Health; University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Stroke (engine); Executive dysfunction; Diffusion MRI; Medicine; Trail Making Test; White matter; Executive functions; Cognition; Physical medicine and rehabilitation; Lesion; Psychology; Neuroscience; Magnetic resonance imaging; Cognitive impairment; Pathology; Neuropsychology; Radiology","score_opus":0.10194698660944355,"score_gpt":0.32275737196566856,"score_spread":0.220810385356225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280549307","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934891,0.0015950149,0.00091514905,0.0016787649,0.0001144112,0.00081768224,0.000034345056,0.000064089814,0.0012914494],"genre_scores_gemma":[0.9983629,0.0004890735,0.0007548271,0.000055815253,0.000040887215,0.00019464073,0.0000065574645,0.000021810232,0.000073499956],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991695,0.00004844231,0.0002637748,0.00024185111,0.00018198705,0.000094427516],"domain_scores_gemma":[0.99899244,0.00006058503,0.0003267454,0.0005299388,0.00006653822,0.000023729828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016703336,0.00012050195,0.0002202353,0.00007378027,0.00015850285,0.000008107795,0.0001970989,0.000030826894,0.00001564798],"category_scores_gemma":[0.000057884165,0.000076469645,0.00009988535,0.00025603213,0.00020607821,0.000041361207,0.00044030076,0.0003548905,1.4124498e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029621404,0.00036565232,0.58133346,0.0012378381,0.00038063386,0.0000058436635,0.005382192,0.00034617414,0.333534,0.0025046556,0.00015423384,0.07445913],"study_design_scores_gemma":[0.00050157297,0.00012272275,0.90612805,0.0010236017,0.0005905355,0.000057485682,0.0035176615,0.0037419756,0.06382699,0.00800889,0.012225915,0.00025462086],"about_ca_topic_score_codex":0.000024142382,"about_ca_topic_score_gemma":8.8347474e-7,"teacher_disagreement_score":0.3247946,"about_ca_system_score_codex":0.000029902667,"about_ca_system_score_gemma":0.00008311146,"threshold_uncertainty_score":0.31183416},"labels":[],"label_agreement":null},{"id":"W4280562686","doi":"10.1212/wnl.0000000000200517","title":"Observational Study of Neuroimaging Biomarkers of Severe Upper Limb Impairment After Stroke","year":2022,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Neurological Disorders and Stroke; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Nursing Research","keywords":"Motor impairment; Fractional anisotropy; Corpus callosum; Neuroimaging; Corticospinal tract; Physical medicine and rehabilitation; Diffusion MRI; Medicine; White matter; Psychology; Magnetic resonance imaging; Audiology; Neuroscience; Radiology","score_opus":0.0760459045021783,"score_gpt":0.3456945657486392,"score_spread":0.2696486612464609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280562686","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99518746,0.000030200466,0.000103414,0.0036749935,0.00006667375,0.0006094553,0.000048426533,0.00005762836,0.00022176094],"genre_scores_gemma":[0.99637747,0.000006275165,0.0009762899,0.0022760548,0.000017463239,0.0002465509,0.000011956331,0.000020869482,0.000067072506],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99896216,0.00008748386,0.00029710733,0.00027519857,0.00023100116,0.00014703047],"domain_scores_gemma":[0.9992987,0.000091158516,0.00013837765,0.00037406362,0.00005895018,0.000038761606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008966813,0.00009545624,0.00021389654,0.00014543826,0.000058044712,0.0000014170714,0.00012405029,0.000017800246,0.00019770245],"category_scores_gemma":[0.000021300437,0.00009742314,0.000073217125,0.00020749445,0.00006543445,0.000029687513,0.00022642674,0.0002430805,9.0512043e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017060579,0.0018127968,0.9741649,0.000027447339,0.000048710237,0.00007675532,0.0001758945,0.00031126357,0.020110063,0.00018143821,0.00065975304,0.0007249384],"study_design_scores_gemma":[0.0011609549,0.0059369034,0.9850107,0.0000022654979,0.0000658856,0.0002065143,0.000071491726,0.00053310033,0.00042284362,0.0002200225,0.0062959776,0.00007333226],"about_ca_topic_score_codex":0.000033506254,"about_ca_topic_score_gemma":0.0000017182241,"teacher_disagreement_score":0.01968722,"about_ca_system_score_codex":0.0000134768525,"about_ca_system_score_gemma":0.000039263196,"threshold_uncertainty_score":0.39728},"labels":[],"label_agreement":null},{"id":"W4280563409","doi":"10.1093/cercor/bhac180","title":"White matter microstructural variability linked to differential attentional skills and impulsive behavior in a pediatric population","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Cégep de Sherbrooke; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"National Institute of Environmental Health Sciences","keywords":"White matter; Impulsivity; Population; Psychology; Neuroscience; Functional magnetic resonance imaging; Neuroimaging; Magnetic resonance imaging; Cognitive psychology; Developmental psychology; Medicine; Radiology","score_opus":0.014650175285967577,"score_gpt":0.30153995045083176,"score_spread":0.2868897751648642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280563409","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9973487,0.000004760778,0.00054816913,0.0010287211,0.00008911569,0.0008050895,0.00008725692,0.00005613876,0.00003203055],"genre_scores_gemma":[0.9954129,0.0000017604042,0.0030149925,0.00064862,0.00009116901,0.00026647397,0.00026243136,0.000017542516,0.00028413694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99905396,0.00003920492,0.00023152327,0.0003567196,0.00014767401,0.0001709371],"domain_scores_gemma":[0.9995962,0.00002016416,0.00006321564,0.00020290361,0.000031410535,0.00008615269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005199955,0.00011178857,0.00016320712,0.00012650022,0.00012221147,0.000014854667,0.00006708312,0.000029909563,0.0006743969],"category_scores_gemma":[0.000012787848,0.00011191573,0.000051207793,0.0002272983,0.000020967034,0.000053031596,0.0001852199,0.00024429202,0.0000066434295],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034021225,0.00013103869,0.9957867,0.000014301764,0.0000016571137,0.0000054704583,0.000041856096,0.000003426497,0.0030740395,0.00008497438,0.00028247756,0.00054000696],"study_design_scores_gemma":[0.00049924414,0.000090224705,0.998125,0.0000032736757,0.0000477604,0.00008659846,0.000008979829,0.00007818454,0.000017480297,0.00087986834,0.00005204369,0.00011133497],"about_ca_topic_score_codex":0.000029594581,"about_ca_topic_score_gemma":0.0000041628364,"teacher_disagreement_score":0.0030565592,"about_ca_system_score_codex":0.00010315609,"about_ca_system_score_gemma":0.000016244068,"threshold_uncertainty_score":0.7384173},"labels":[],"label_agreement":null},{"id":"W4280598875","doi":"10.1002/ca.23914","title":"Preoperative and postoperative <scp>high angular resolution diffusion imaging</scp> tractography of cerebellar pathways in posterior fossa tumors","year":2022,"lang":"en","type":"article","venue":"Clinical Anatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Tractography; Medicine; Fractional anisotropy; Effective diffusion coefficient; Magnetic resonance imaging; Diffusion MRI; Cerebellum; Diffusion imaging; Radiology; Posterior fossa; Nuclear medicine; Internal medicine","score_opus":0.04282424492428531,"score_gpt":0.3541130383842525,"score_spread":0.3112887934599672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280598875","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958417,0.0004973597,0.00052389654,0.0017522101,0.000044575718,0.00081080623,0.000086523956,0.00008137059,0.00036156172],"genre_scores_gemma":[0.9949324,0.00016666544,0.0035903666,0.0010101551,0.000029819645,0.00012255207,0.000060228886,0.000024206489,0.00006358242],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982749,0.00019368186,0.00061731477,0.0004861755,0.00021809798,0.00020982513],"domain_scores_gemma":[0.9989174,0.0003264359,0.00018853635,0.00032830847,0.000115667215,0.00012366752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037667403,0.00016126496,0.00042117678,0.00014272801,0.00017152436,0.0000107201195,0.000121944766,0.00005068637,0.000022369295],"category_scores_gemma":[0.00026451412,0.00014611619,0.00012488384,0.00046372166,0.00029599236,0.000090688925,0.0002492754,0.00056672003,0.0000010931293],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029463606,0.0027936494,0.9126717,0.00010381556,0.000053439526,0.0004181827,0.0023805876,0.00003075044,0.044168252,0.010667443,0.0018240871,0.024593472],"study_design_scores_gemma":[0.0033784956,0.0017361566,0.96069163,0.00016185558,0.00008441623,0.0002449611,0.001880801,0.0031068737,0.0060076467,0.0067913756,0.015734194,0.00018158866],"about_ca_topic_score_codex":0.00006707968,"about_ca_topic_score_gemma":0.000005553671,"teacher_disagreement_score":0.048019953,"about_ca_system_score_codex":0.000042705127,"about_ca_system_score_gemma":0.000069437636,"threshold_uncertainty_score":0.5958445},"labels":[],"label_agreement":null},{"id":"W4280629767","doi":"10.1097/md.0000000000029214","title":"Correlations between COMT polymorphism and brain structure and cognition in elderly subjects","year":2022,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Catechol-O-methyl transferase; Cognition; Medicine; Montreal Cognitive Assessment; Cognitive decline; Superior longitudinal fasciculus; Caudate nucleus; Allele; Diffusion MRI; Audiology; Clinical psychology; Fractional anisotropy; Internal medicine; Psychiatry; Genetics; Cognitive impairment; Dementia; Magnetic resonance imaging; Biology; Gene","score_opus":0.044510029291516824,"score_gpt":0.33149150137047917,"score_spread":0.28698147207896235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4280629767","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94145846,0.000569065,0.002093025,0.0547022,0.00003290356,0.0004754791,0.000050329043,0.00009096471,0.00052758894],"genre_scores_gemma":[0.99686897,0.00003935918,0.00075935485,0.0018116053,0.00008886746,0.00003949151,0.00017632246,0.000013448024,0.00020255949],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993768,0.000030450374,0.00015437027,0.00019384154,0.00013607596,0.000108489345],"domain_scores_gemma":[0.9995785,0.00015277098,0.000048201655,0.00013056153,0.000016090326,0.00007392665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000101377096,0.00008198958,0.0001786258,0.0001551406,0.000138477,0.0000028070456,0.00003182412,0.000025740774,0.00011381712],"category_scores_gemma":[0.000073917996,0.000074273834,0.000008405703,0.00023716032,0.00012610207,0.000032219752,0.000051740262,0.0003150869,3.685465e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017289915,0.00015695443,0.75495666,0.00015872506,0.00004588402,0.0001769699,0.0026180143,0.00001263297,0.06644163,0.008719091,0.021634959,0.14490555],"study_design_scores_gemma":[0.0036444117,0.001036801,0.94277763,0.0001323633,0.00013210601,0.0004978899,0.00039431892,0.00044301295,0.0005098493,0.021536853,0.0287237,0.00017104413],"about_ca_topic_score_codex":0.000052819934,"about_ca_topic_score_gemma":0.0000077037985,"teacher_disagreement_score":0.18782096,"about_ca_system_score_codex":0.000024620631,"about_ca_system_score_gemma":0.000015713667,"threshold_uncertainty_score":0.3028799},"labels":[],"label_agreement":null},{"id":"W4281289426","doi":"10.3389/fradi.2022.794981","title":"Diffusion Kurtosis Imaging of Neonatal Spinal Cord in Clinical Routine","year":2022,"lang":"en","type":"article","venue":"Frontiers in Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"Università degli Studi di Genova","keywords":"Diffusion MRI; Kurtosis; Medicine; White matter; Magnetic resonance imaging; Spinal cord; Neuroimaging; Computer science; Radiology","score_opus":0.04729330494408518,"score_gpt":0.38113999078831995,"score_spread":0.33384668584423477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281289426","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92044854,0.0011848819,0.07441746,0.0027569896,0.00048200853,0.00037796723,0.000014541337,0.000055333996,0.00026227016],"genre_scores_gemma":[0.9465742,0.00023717858,0.05242167,0.00054904073,0.000047923102,0.000072825635,0.000028076143,0.000013302482,0.000055765595],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988749,0.00011753822,0.00045628607,0.00027921007,0.000083826286,0.00018822528],"domain_scores_gemma":[0.99952453,0.00004970618,0.00011549831,0.00025662995,0.000013561454,0.000040084942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032752543,0.000081492304,0.00036824963,0.00022359779,0.00003730034,9.1668574e-7,0.0001454569,0.00003506202,0.00003673508],"category_scores_gemma":[0.000104233484,0.00008482449,0.00006957053,0.0002779779,0.00017121695,0.000022480297,0.00015126319,0.0004775113,4.5303742e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008285434,0.00015113466,0.8989824,0.000010203386,0.0000043955274,0.00007805037,0.000034276687,0.00002295003,0.00046414704,0.0003382151,0.004880869,0.09420478],"study_design_scores_gemma":[0.0035441373,0.0015360699,0.93250775,0.000052472707,0.00003164781,0.00060361566,0.00069309503,0.012278738,0.00023711077,0.0051432378,0.04317336,0.00019875703],"about_ca_topic_score_codex":0.000029752586,"about_ca_topic_score_gemma":0.000001433931,"teacher_disagreement_score":0.094006024,"about_ca_system_score_codex":0.00008378909,"about_ca_system_score_gemma":0.000038047117,"threshold_uncertainty_score":0.34590423},"labels":[],"label_agreement":null},{"id":"W4281297704","doi":"10.1101/2022.05.04.22274510","title":"Altered Lateralization of the Cingulum in Deployment-Related Traumatic Brain Injury: An ENIGMA Military-Relevant Brain Injury Study","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Medical Research and Materiel Command; Clinical Science Research and Development; Ministerie van Defensie; Rehabilitation Research and Development Service; National Alliance for Research on Schizophrenia and Depression; National Institute of Mental Health; Health Services Research and Development; U.S. Department of Veterans Affairs; U.S. Department of Defense","keywords":"Traumatic brain injury; Fractional anisotropy; Cingulum (brain); Neuroimaging; Psychology; Concussion; Brain Structure and Function; White matter; Diffusion MRI; Lateralization of brain function; Brain size; Cognition; Magnetic resonance imaging; Medicine; Poison control; Neuroscience; Psychiatry; Injury prevention; Radiology","score_opus":0.06554209670476593,"score_gpt":0.38058240944582533,"score_spread":0.31504031274105937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281297704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98908484,0.00010213224,0.00053634995,0.0056180307,0.000263013,0.003963839,0.000087313594,0.00027446335,0.00007004678],"genre_scores_gemma":[0.9967155,0.000050029754,0.0010336337,0.00083665334,0.000044186607,0.0007072639,0.0001584951,0.00010427049,0.0003499614],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9966792,0.00065331557,0.0010740904,0.000779825,0.0005117587,0.00030179674],"domain_scores_gemma":[0.99754727,0.00012659884,0.00039690227,0.0017519837,0.00007788475,0.00009938934],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009043906,0.0003668345,0.000667094,0.00034193933,0.00012686221,0.000012589677,0.0006341228,0.00014683444,0.00014041882],"category_scores_gemma":[0.00033647934,0.0003046627,0.00017743942,0.0006660325,0.0001104287,0.00007360207,0.00073933706,0.0011680046,0.0000019250044],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041348956,0.004812738,0.92534554,0.000795002,0.00022269278,0.000048189624,0.013727655,0.0016133038,0.04393087,0.00067451264,0.002487988,0.005928038],"study_design_scores_gemma":[0.0029043928,0.0020066192,0.9492267,0.0011966366,0.00038020615,0.000029003755,0.0014853029,0.015923314,0.0061997813,0.016129352,0.0036212741,0.0008974128],"about_ca_topic_score_codex":0.00042767107,"about_ca_topic_score_gemma":0.0001976859,"teacher_disagreement_score":0.03773109,"about_ca_system_score_codex":0.00019538011,"about_ca_system_score_gemma":0.00013509017,"threshold_uncertainty_score":0.9999406},"labels":[],"label_agreement":null},{"id":"W4281570665","doi":"10.1016/j.neuroimage.2022.119327","title":"Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"H2020 Marie Skłodowska-Curie Actions; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Drug Abuse; National Institute of Mental Health; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; National Institute on Aging; National Institute of Allergy and Infectious Diseases; Horizon 2020; Centre d'Imagerie BioMédicale; Eunice Kennedy Shriver National Institute of Child Health and Human Development; European Commission; Wellcome Trust; National Institute of Neurological Disorders and Stroke; Massachusetts General Hospital; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Tractography; Computer science; Diffusion MRI; Robustness (evolution); Connectome; Artificial intelligence; Voxel; Pattern recognition (psychology); Data mining; Functional connectivity; Neuroscience; Magnetic resonance imaging; Psychology","score_opus":0.13432231346441117,"score_gpt":0.3886919784398079,"score_spread":0.2543696649753967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281570665","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1304867,0.0011173034,0.8448367,0.019738713,0.0002599024,0.0020324416,0.00048511755,0.0005586128,0.00048449897],"genre_scores_gemma":[0.2490377,0.0002356293,0.7391341,0.009095852,0.00042677423,0.0010747404,0.00047755658,0.00013988458,0.00037781303],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819404,0.00025932744,0.0003327414,0.00070946146,0.00022408116,0.0002803621],"domain_scores_gemma":[0.9973446,0.0014179664,0.00016679637,0.00091551594,0.000045499135,0.00010958734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017080124,0.00024324078,0.00031733807,0.000060533388,0.00064972433,0.00003493815,0.00039728172,0.00005121731,0.00010869589],"category_scores_gemma":[0.00023115131,0.00019304734,0.00019194472,0.00018237102,0.000079420926,0.00009237544,0.00040931557,0.0006780387,0.000008311671],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013135117,0.00055248156,0.00016341053,0.000013580834,0.000023065159,0.000057755336,0.0010178593,0.0000805785,0.95075536,0.0007498168,0.005714098,0.040740676],"study_design_scores_gemma":[0.0029475752,0.00042745195,0.026646951,0.000040049224,0.000118254866,0.0000275904,0.0005946157,0.09659471,0.01351288,0.007074037,0.85160357,0.0004123024],"about_ca_topic_score_codex":0.0000875856,"about_ca_topic_score_gemma":0.0000037434074,"teacher_disagreement_score":0.93724245,"about_ca_system_score_codex":0.0000649429,"about_ca_system_score_gemma":0.00004152884,"threshold_uncertainty_score":0.78722423},"labels":[],"label_agreement":null},{"id":"W4281657612","doi":"10.1007/s00429-022-02518-6","title":"The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow","year":2022,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt Institute for Clinical and Translational Research","keywords":"Neuroimaging; Set (abstract data type); Tractography; Neuroanatomy; Computer science; Psychology; Diffusion MRI; Data science; Cognitive psychology; Neuroscience; Medicine; Radiology","score_opus":0.07176942609469703,"score_gpt":0.34135799450916915,"score_spread":0.2695885684144721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281657612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99207217,0.000007881131,0.0028483362,0.0022641998,0.000021598935,0.0027068595,0.000016603253,0.00002618741,0.000036151167],"genre_scores_gemma":[0.9976285,0.000004609044,0.00064320763,0.0005388181,0.000029383722,0.0009946396,0.0000060957145,0.0000075949065,0.00014714396],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995495,0.000023446002,0.00012886149,0.0001523704,0.00008271833,0.00006309477],"domain_scores_gemma":[0.99964106,0.00005541796,0.000064121115,0.00016061132,0.00003475616,0.00004405526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006511043,0.00006177601,0.00008920954,0.00008252582,0.00017081658,0.0000065323675,0.00003770137,0.00001792712,0.0000030334706],"category_scores_gemma":[0.00006708897,0.00004465634,0.00002473729,0.00022556934,0.000043872504,0.000025901098,0.000046046833,0.00012697697,5.0048133e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029698268,0.00012353859,0.022342276,0.00007827612,0.00004673883,0.0000018864704,0.0008674919,0.0037227466,0.77690834,0.08232271,0.0023447853,0.10827141],"study_design_scores_gemma":[0.0006389167,0.0054714954,0.75329214,0.00008867051,0.0000379765,0.00007379755,0.00040213333,0.00011547671,0.012044364,0.006127193,0.22157517,0.00013267643],"about_ca_topic_score_codex":0.000010758887,"about_ca_topic_score_gemma":0.000016988413,"teacher_disagreement_score":0.76486397,"about_ca_system_score_codex":0.000009712385,"about_ca_system_score_gemma":0.00000993701,"threshold_uncertainty_score":0.18210328},"labels":[],"label_agreement":null},{"id":"W4281754482","doi":"10.1093/braincomms/fcac142","title":"In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre; University of British Columbia Hospital; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"White matter; Diffusion MRI; Hyperintensity; Fractional anisotropy; Myelin; Pathology; Magnetic resonance imaging; Medicine; Internal medicine; Central nervous system; Radiology","score_opus":0.026915909698966844,"score_gpt":0.3236446105651628,"score_spread":0.29672870086619596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281754482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5161316,0.0013316121,0.00053566793,0.47772408,0.000035698762,0.0007541381,0.00016383831,0.00008196471,0.0032414275],"genre_scores_gemma":[0.9463222,0.0001737947,0.028341264,0.022168031,0.000018404104,0.00027269704,0.000051604216,0.000031304808,0.0026207238],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99926686,0.00007718386,0.00021164237,0.00022181177,0.000076808385,0.00014567947],"domain_scores_gemma":[0.9990412,0.000103592545,0.000046577028,0.00073785946,0.000028117729,0.000042638145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000116575146,0.00010789498,0.00015874284,0.00017033628,0.00021896964,0.000024577743,0.0001954613,0.000021093667,0.00070929655],"category_scores_gemma":[0.000013845327,0.00011667922,0.00001719604,0.0001867512,0.00020363973,0.000087598375,0.00068821217,0.00040280088,0.0000051034817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027523323,0.00008336534,0.9181315,0.000035368867,0.0000036117683,0.000015232724,0.0021449735,0.000021259026,0.03065763,0.0006902045,0.047638,0.00055136665],"study_design_scores_gemma":[0.00053844805,0.000019343423,0.7588731,0.000057401998,0.000009358987,0.0008958763,0.0017871724,0.0011044435,0.00020803226,0.0021260972,0.23420191,0.00017880765],"about_ca_topic_score_codex":0.000075280106,"about_ca_topic_score_gemma":0.000051381303,"teacher_disagreement_score":0.45555604,"about_ca_system_score_codex":0.000048428206,"about_ca_system_score_gemma":0.000020611673,"threshold_uncertainty_score":0.77663},"labels":[],"label_agreement":null},{"id":"W4281954245","doi":"10.1016/j.neuroimage.2022.119360","title":"Empirical transmit field bias correction of T1w/T2w myelin maps","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institute on Aging; National Institutes of Health; Japan Agency for Medical Research and Development","keywords":"Spurious relationship; Myelin; Field (mathematics); Computer science; Statistics; Psychology; Mathematics; Neuroscience","score_opus":0.12724169319513529,"score_gpt":0.3814851359127153,"score_spread":0.25424344271758004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281954245","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88000715,0.00017931094,0.04860503,0.033265945,0.00095976965,0.0015845515,0.00012536829,0.0011164299,0.034156464],"genre_scores_gemma":[0.98927355,0.00004605863,0.0031231868,0.004726491,0.00007190116,0.00010220747,0.000031328567,0.00003378688,0.002591514],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990357,0.00005709053,0.00024254777,0.00027993412,0.00023496823,0.00014971691],"domain_scores_gemma":[0.9992779,0.00015424185,0.00008001673,0.00038533442,0.0000398623,0.00006265396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009940458,0.00010112902,0.00018614111,0.00012537677,0.00012022619,0.0000052368214,0.0001172953,0.000025993017,0.0004011769],"category_scores_gemma":[0.00010064482,0.00010297065,0.00011382858,0.00038964316,0.000042599295,0.00003959216,0.00006931708,0.00044528686,0.000010567005],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009609141,0.0018848458,0.049616273,0.00019208239,0.000036776262,0.00039101735,0.00072237384,0.00044011918,0.36714855,0.00092900114,0.43978193,0.13789609],"study_design_scores_gemma":[0.0010240088,0.0015725935,0.019478643,0.000025678697,0.00009139146,0.0004649193,0.00008080647,0.0037979516,0.0972506,0.0011482382,0.8748395,0.00022568756],"about_ca_topic_score_codex":0.000014409207,"about_ca_topic_score_gemma":5.2971876e-7,"teacher_disagreement_score":0.43505752,"about_ca_system_score_codex":0.000025628193,"about_ca_system_score_gemma":0.000037188693,"threshold_uncertainty_score":0.43926057},"labels":[],"label_agreement":null},{"id":"W4281974427","doi":"10.1177/00048674211031477","title":"Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression","year":2022,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Science Fund for Distinguished Young Scholars; National Natural Science Foundation of China-Liaoning Joint Fund; Liaoning Revitalization Talents Program; China Medical University; Department of Science and Technology of Liaoning Province; Foundation of Liaoning Province Education Administration; Natural Science Foundation of Liaoning Province; National Natural Science Foundation of China","keywords":"Corpus callosum; White matter; Major depressive disorder; Diffusion MRI; Endophenotype; Bipolar disorder; Superior longitudinal fasciculus; Hyperintensity; Medicine; Psychology; Internal medicine; Psychiatry; Pathology; Fractional anisotropy; Magnetic resonance imaging; Radiology","score_opus":0.02563210456338421,"score_gpt":0.2948717239300923,"score_spread":0.2692396193667081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281974427","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9898115,0.000082265404,0.0028989532,0.0058487463,0.0005743677,0.0005675864,0.00013556982,0.000031147127,0.000049865364],"genre_scores_gemma":[0.9627967,0.00003550461,0.036218118,0.00017023219,0.00042023364,0.000020677957,0.00008029796,0.00001758015,0.00024066359],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991277,0.000017948398,0.00038552488,0.000106066946,0.00024109514,0.00012169517],"domain_scores_gemma":[0.9990891,0.000045118944,0.00050343707,0.00013466924,0.00010021466,0.00012741644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000084787964,0.00010775805,0.0002204281,0.000106328254,0.0001138568,0.000013149305,0.00009063228,0.000027880606,0.000048219586],"category_scores_gemma":[0.000024888222,0.00008061941,0.000060276965,0.000078494675,0.000033413504,0.00019712026,0.000034737834,0.000248006,3.4177938e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031038863,0.00040024304,0.937874,0.00009597136,0.00007094637,0.000004858714,0.00061086926,0.00004819703,0.0074755005,0.00065709424,0.036807656,0.01285077],"study_design_scores_gemma":[0.021059768,0.0039664623,0.81948185,0.0007454199,0.0006414986,0.000995131,0.0015882796,0.00049725175,0.0054763663,0.021588465,0.12359015,0.00036937464],"about_ca_topic_score_codex":0.000099122466,"about_ca_topic_score_gemma":9.928893e-7,"teacher_disagreement_score":0.11839217,"about_ca_system_score_codex":0.000021076317,"about_ca_system_score_gemma":0.00014461599,"threshold_uncertainty_score":0.3287564},"labels":[],"label_agreement":null},{"id":"W4282822545","doi":"10.1101/2022.06.11.495736","title":"CAT – A Computational Anatomy Toolbox for the Analysis of Structural MRI Data","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":626,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Alexander von Humboldt-Stiftung; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Bristol-Myers Squibb; Royal Society; Northern California Institute for Research and Education; Royal Society Te Apārangi; Pfizer; BioClinica; Biogen; F. Hoffmann-La Roche; University of Auckland; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Computer science; Toolbox; Workflow; Suite; Preprocessor; Visualization; USable; Graphical user interface; Data science; Human–computer interaction; Data mining; Artificial intelligence; World Wide Web","score_opus":0.0678759867942592,"score_gpt":0.3525822282139926,"score_spread":0.2847062414197334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282822545","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4432635,0.0022264535,0.5177588,0.008141618,0.0006940182,0.006308547,0.020609342,0.0009820481,0.000015702599],"genre_scores_gemma":[0.84184086,0.00007931479,0.15701735,0.00035841754,0.00011916987,0.0004760991,0.000042168445,0.000061155675,0.0000054884713],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99806523,0.00004010051,0.00046465654,0.00082416285,0.00036886556,0.00023697644],"domain_scores_gemma":[0.9961754,0.0002893888,0.00044331927,0.002604939,0.00039197147,0.00009495578],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035588394,0.0002709111,0.000569673,0.0003058036,0.00022895166,0.000043886368,0.0009554063,0.000105796316,0.000098399825],"category_scores_gemma":[0.00015431854,0.00023126707,0.000233901,0.000978307,0.0001438616,0.000056655208,0.0008747582,0.00040820945,8.642725e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013957815,0.0020787448,0.30194798,0.005658268,0.037843544,0.00019080366,0.00017996502,0.25756854,0.24194647,0.10396096,0.046964776,0.00026416892],"study_design_scores_gemma":[0.0007454451,0.000066497254,0.45388618,0.00009068976,0.0069051087,6.414916e-8,0.000010326964,0.48146352,0.0042406195,0.00006412738,0.051938992,0.0005884309],"about_ca_topic_score_codex":0.00005789856,"about_ca_topic_score_gemma":0.0000019840968,"teacher_disagreement_score":0.39857733,"about_ca_system_score_codex":0.0001401616,"about_ca_system_score_gemma":0.00043149924,"threshold_uncertainty_score":0.94307977},"labels":[],"label_agreement":null},{"id":"W4282833640","doi":"10.1161/strokeaha.122.039723","title":"Detecting Silent Acute Microinfarcts in Cerebral Small Vessel Disease Using Submillimeter Diffusion-Weighted Magnetic Resonance Imaging: Preliminary Results","year":2022,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Ottawa; University of Toronto; University Health Network","funders":"Heart and Stroke Foundation of Canada","keywords":"Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Physics; Nuclear medicine; Radiology","score_opus":0.03517151638038429,"score_gpt":0.29654916584640717,"score_spread":0.2613776494660229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4282833640","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993433,0.001681747,0.000976584,0.0022321967,0.00008740602,0.0008253242,0.00033248795,0.00020748838,0.00022376626],"genre_scores_gemma":[0.97566634,0.00006171106,0.022358634,0.0007441685,0.00006824044,0.00019259242,0.00007719018,0.000057680885,0.0007734315],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982533,0.000073687464,0.00039378344,0.00059189065,0.00025356913,0.00043378523],"domain_scores_gemma":[0.9989606,0.0000869224,0.0001259254,0.0006047935,0.000045398436,0.00017635657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013751173,0.00021073868,0.00023011971,0.00017592916,0.0002974906,0.000019871706,0.00020536939,0.000023680888,0.000041008647],"category_scores_gemma":[0.000062479274,0.00021972996,0.00010136347,0.00037358908,0.00007562407,0.00006415119,0.00041439137,0.0005049289,0.0000028983925],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011962806,0.0017437633,0.23314314,0.0001820352,0.000031855914,0.002890675,0.001082858,0.00020439668,0.6486264,0.00019233584,0.0021501726,0.0977896],"study_design_scores_gemma":[0.011704877,0.0018306831,0.7467628,0.00058814464,0.0005409448,0.0010198692,0.0005342074,0.13338684,0.03641837,0.0018561597,0.06398904,0.0013680634],"about_ca_topic_score_codex":0.00006868316,"about_ca_topic_score_gemma":0.000002192714,"teacher_disagreement_score":0.612208,"about_ca_system_score_codex":0.00020093966,"about_ca_system_score_gemma":0.000092018,"threshold_uncertainty_score":0.8960328},"labels":[],"label_agreement":null},{"id":"W4283073900","doi":"10.1007/s12021-022-09590-7","title":"Fast Streamline Search: An Exact Technique for Diffusion MRI Tractography","year":2022,"lang":"en","type":"article","venue":"Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research","keywords":"Streamlines, streaklines, and pathlines; Tractography; Diffusion MRI; Cluster analysis; Computer science; Representation (politics); Artificial intelligence; Upper and lower bounds; Hierarchical clustering; Pattern recognition (psychology); Algorithm; Mathematics; Physics; Magnetic resonance imaging","score_opus":0.07827359738203357,"score_gpt":0.3607827391509589,"score_spread":0.2825091417689253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283073900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17643024,0.000016764187,0.81051356,0.0027510482,0.00009528642,0.004907796,0.0004642871,0.0010627336,0.0037583178],"genre_scores_gemma":[0.7327686,0.00010115432,0.26192582,0.0025756985,0.000107794694,0.0014067917,0.00069033256,0.00009510259,0.00032874654],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988704,0.000023423865,0.00034756816,0.00018771985,0.0003054122,0.00026552],"domain_scores_gemma":[0.9989995,0.00007887453,0.00011211121,0.0005906651,0.00006963556,0.00014926538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017497805,0.00015288767,0.00019715051,0.00022044082,0.0003702547,0.000022231328,0.00020909317,0.00003295741,0.000055521847],"category_scores_gemma":[0.000027917604,0.00014584234,0.00012300473,0.00036457874,0.00005020177,0.0001876343,0.00013389463,0.0004351639,0.0000024244366],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018606413,0.008643194,0.013619139,0.0020913142,0.00010745737,0.00015133053,0.0051949513,0.007178129,0.63803047,0.030223345,0.043994833,0.24890517],"study_design_scores_gemma":[0.004149481,0.008655509,0.006500852,0.00009017217,0.00022102808,0.0018940767,0.00221398,0.20875068,0.09184348,0.0037292636,0.6709341,0.0010174229],"about_ca_topic_score_codex":0.0000034575828,"about_ca_topic_score_gemma":4.3202914e-7,"teacher_disagreement_score":0.62693924,"about_ca_system_score_codex":0.00002757505,"about_ca_system_score_gemma":0.000049439772,"threshold_uncertainty_score":0.59472775},"labels":[],"label_agreement":null},{"id":"W4283075736","doi":"10.3389/fneur.2022.850642","title":"Multisite Harmonization of Structural DTI Networks in Children: An A-CAP Study","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; BC Children's Hospital; University of British Columbia; Stollery Children's Hospital; Hotchkiss Brain Institute; Centre Hospitalier Universitaire Sainte-Justine; Alberta Children's Hospital; University of Alberta; Université de Montréal; Children's Hospital of Eastern Ontario; University of Calgary","funders":"Canadian Institutes of Health Research; Killam Trusts; Alberta Children's Hospital Foundation; Scuola IMT Alti Studi Lucca; Children's Hospital Foundation","keywords":"Diffusion MRI; Adjacency matrix; Harmonization; Connectome; Computer science; Connectomics; Neuroimaging; Context (archaeology); Artificial intelligence; Fractional anisotropy; Data mining; Graph; Medicine; Psychology; Radiology; Theoretical computer science; Neuroscience; Functional connectivity; Magnetic resonance imaging; Biology; Psychiatry","score_opus":0.022990030547424906,"score_gpt":0.3128539605034561,"score_spread":0.28986392995603116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283075736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98594195,0.00011657366,0.012469738,0.0003404373,0.00016060504,0.00089252484,0.0000072481093,0.000054130283,0.000016772805],"genre_scores_gemma":[0.99374807,0.000015471265,0.0053602187,0.00065467856,0.000028310234,0.00010882872,0.000051532566,0.000019835927,0.000013034686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990536,0.00014651025,0.00024376647,0.00029753929,0.000094862655,0.00016371465],"domain_scores_gemma":[0.9995633,0.0000127918,0.000085232365,0.0002919886,0.000015576285,0.00003116238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009548388,0.00008678431,0.00022296228,0.00022573853,0.000051246097,0.0000021126982,0.00014141509,0.00003333465,0.000016899845],"category_scores_gemma":[0.000016163502,0.000095626725,0.00002144824,0.00040451845,0.000051265066,0.000047256504,0.00010184788,0.00043651232,1.0160907e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018502094,0.00022617716,0.9829432,0.0000017605108,0.000004817809,0.000024071773,0.00011928365,0.01326055,0.00013922356,0.000041460233,0.00028920933,0.0027652483],"study_design_scores_gemma":[0.0012168296,0.0008473961,0.9310722,0.0000011813931,0.000011794862,0.00006041484,0.00006241539,0.06605967,0.000038699884,0.00041260134,0.00015353931,0.000063295134],"about_ca_topic_score_codex":0.00006716484,"about_ca_topic_score_gemma":0.000011456123,"teacher_disagreement_score":0.05279912,"about_ca_system_score_codex":0.000024327454,"about_ca_system_score_gemma":0.000009497044,"threshold_uncertainty_score":0.38995448},"labels":[],"label_agreement":null},{"id":"W4283212390","doi":"10.3389/fpain.2022.880831","title":"White Matter Diffusion Properties in Chronic Temporomandibular Disorders: An Exploratory Analysis","year":2022,"lang":"en","type":"article","venue":"Frontiers in Pain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; University of Alberta; Women and Children's Health Research Institute","keywords":"White matter; Diffusion MRI; Medicine; Diffusion; Orofacial pain; White (mutation); Psychology; Physics; Physical therapy; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.08547716123083193,"score_gpt":0.37210132091537773,"score_spread":0.2866241596845458,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283212390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9579969,0.0017962165,0.031435236,0.006269608,0.000050909883,0.0016682347,0.000011814397,0.00012987113,0.0006411933],"genre_scores_gemma":[0.9922673,0.00022997744,0.004471033,0.00025798555,0.000030013976,0.0014923834,0.00006909292,0.000032706095,0.0011494817],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99745744,0.0008975204,0.0002453468,0.00045168266,0.00053687533,0.0004111127],"domain_scores_gemma":[0.99919933,0.000033398755,0.000032650543,0.00061270996,0.000037925438,0.00008395895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024077985,0.00010713536,0.00025565785,0.0013440823,0.00022666607,0.000019723375,0.00026914812,0.0000379832,0.00021210115],"category_scores_gemma":[0.000048879094,0.00010066692,0.000060566443,0.0022298812,0.00014286555,0.000116559575,0.00026348405,0.0007818361,0.0000041539133],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094659954,0.00038979584,0.97893155,0.000055440767,0.000020724647,0.000032971304,0.0009052773,0.0007828547,0.00076198054,0.000014006816,0.015567028,0.0024437367],"study_design_scores_gemma":[0.0021659695,0.0014195904,0.65035474,0.0001586187,0.00007330849,0.0000058477135,0.016477898,0.22656555,0.00030286732,0.0064193914,0.095500246,0.0005559878],"about_ca_topic_score_codex":0.00009350101,"about_ca_topic_score_gemma":0.00016038804,"teacher_disagreement_score":0.3285768,"about_ca_system_score_codex":0.00072649674,"about_ca_system_score_gemma":0.00012530304,"threshold_uncertainty_score":0.41050777},"labels":[],"label_agreement":null},{"id":"W4283271593","doi":"10.21203/rs.3.rs-1742219/v1","title":"Characterization of Extracellular Free Water Pathologies in Schizophrenia Using Multi-Site Diffusion MRI Harmonization","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Medical Research Council; National Alliance for Research on Schizophrenia and Depression; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Harmonization; Characterization (materials science); Schizophrenia (object-oriented programming); Diffusion; Extracellular; Nuclear magnetic resonance; Chemistry; Medicine; Materials science; Nanotechnology; Psychiatry; Physics; Biochemistry; Thermodynamics","score_opus":0.1785688321069545,"score_gpt":0.4328049450671547,"score_spread":0.2542361129602002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283271593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9281331,0.00022802281,0.068508804,0.0007742292,0.000052275034,0.0019192939,0.0002171742,0.00014736403,0.000019773908],"genre_scores_gemma":[0.9620965,0.0012300889,0.033408217,0.00001584107,0.000068759655,0.00039142361,0.0024378786,0.000071659546,0.00027961208],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99758,0.00029440515,0.0004670252,0.00061360607,0.00067424704,0.0003707333],"domain_scores_gemma":[0.998257,0.000052722728,0.00014572007,0.001118122,0.0003566846,0.00006976511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007312361,0.00019855592,0.0003678902,0.00074469385,0.00017932756,0.000034362125,0.0003371361,0.00019674933,0.00014869064],"category_scores_gemma":[0.00022157306,0.00017195103,0.00009637462,0.00046097342,0.00013587147,0.000087786655,0.0022091223,0.0014349242,0.0000042720176],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001941638,0.00044939827,0.0185623,0.0007472848,0.0000056358895,0.00008212793,0.00047580778,0.00035225786,0.9779949,0.00011187269,0.0000084915755,0.0010157644],"study_design_scores_gemma":[0.003695007,0.0004910083,0.3751275,0.0029266146,0.00007821108,0.000056930337,0.00042665875,0.09337821,0.5148195,0.004803047,0.0034724986,0.0007248132],"about_ca_topic_score_codex":0.000100657824,"about_ca_topic_score_gemma":0.0000038875487,"teacher_disagreement_score":0.4631754,"about_ca_system_score_codex":0.0002706434,"about_ca_system_score_gemma":0.00012346193,"threshold_uncertainty_score":0.70119596},"labels":[],"label_agreement":null},{"id":"W4283688598","doi":"10.21203/rs.3.rs-1712962/v1","title":"Free water diffusion MRI differentiates suicide ideators from attempters with treatment-resistant depression","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"University of Ottawa","keywords":"Depression (economics); Diffusion; Psychology; Medicine; Physics; Economics; Thermodynamics; Keynesian economics","score_opus":0.10717113802621164,"score_gpt":0.4225724224553515,"score_spread":0.31540128442913984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283688598","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98880327,0.00075041206,0.0019057575,0.0034703352,0.00006363525,0.00274801,0.0011945885,0.00048214733,0.00058183353],"genre_scores_gemma":[0.987437,0.0013127623,0.0033387134,0.00006535687,0.00017604299,0.00225518,0.0036083057,0.00015396859,0.0016526536],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961536,0.0002670627,0.0003576145,0.0012194354,0.0012773717,0.0007249115],"domain_scores_gemma":[0.99668443,0.0002783292,0.00009877598,0.0024165418,0.00020054588,0.00032135978],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002129671,0.000443624,0.0005885623,0.00041268743,0.0005690003,0.00010179368,0.00057552895,0.0001846473,0.0010778854],"category_scores_gemma":[0.000050599403,0.00026554792,0.00022047418,0.00021259303,0.00019349904,0.000054575587,0.0024382675,0.001479217,0.000019671766],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005048357,0.0030969372,0.74469715,0.0014513949,0.00064259034,0.0015607484,0.00186481,0.00028062396,0.22166173,0.00028861046,0.009991869,0.009415169],"study_design_scores_gemma":[0.011292293,0.0060940264,0.5009759,0.008196222,0.0009613204,0.000058021516,0.002081276,0.0020911135,0.35455388,0.030947309,0.080433115,0.0023155229],"about_ca_topic_score_codex":0.0024067252,"about_ca_topic_score_gemma":0.00013919701,"teacher_disagreement_score":0.24372123,"about_ca_system_score_codex":0.0006965045,"about_ca_system_score_gemma":0.00014898628,"threshold_uncertainty_score":0.9999797},"labels":[],"label_agreement":null},{"id":"W4283789043","doi":"10.1093/cercor/bhac236","title":"Optimal blocking of the cerebral cortex for cytoarchitectonic examination: a neuronavigation-based approach","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Human Frontier Science Program","keywords":"Cytoarchitecture; Sulcus; Cortex (anatomy); Central sulcus; Anatomy; Cerebral cortex; Neuroscience; Coronal plane; Somatosensory system; Neuroanatomy; Biology; Motor cortex","score_opus":0.05106301895722977,"score_gpt":0.3133843964435513,"score_spread":0.26232137748632156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283789043","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9211842,0.0000513022,0.07272926,0.0018812098,0.00013013043,0.002292403,0.00014974014,0.0002371268,0.0013446708],"genre_scores_gemma":[0.97596073,7.809972e-7,0.021802783,0.00074964436,0.00007466954,0.00070605084,0.00015973157,0.00004718237,0.0004984028],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99858207,0.0000721316,0.00032771422,0.0004076279,0.00035593714,0.00025450275],"domain_scores_gemma":[0.9988748,0.00011689972,0.00023564929,0.0005986773,0.00010683615,0.00006715034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017621809,0.00016373234,0.00023767579,0.00008652767,0.00043115998,0.000012568097,0.00032661928,0.00003359359,0.00009678518],"category_scores_gemma":[0.00005543161,0.00013968625,0.00021011678,0.0004818034,0.00015950517,0.000042468673,0.00017031579,0.00037101452,8.431148e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025682861,0.008519986,0.21750842,0.002883002,0.00048264704,0.000049789858,0.0031857623,0.10550748,0.3498756,0.126572,0.012307571,0.17053945],"study_design_scores_gemma":[0.0050451807,0.0015295334,0.52855366,0.00009916873,0.00035874665,0.00033428177,0.00044777675,0.4259741,0.019753745,0.0018409229,0.015446271,0.0006166165],"about_ca_topic_score_codex":0.000009980512,"about_ca_topic_score_gemma":7.264355e-7,"teacher_disagreement_score":0.33012185,"about_ca_system_score_codex":0.000098392535,"about_ca_system_score_gemma":0.0001773865,"threshold_uncertainty_score":0.56962395},"labels":[],"label_agreement":null},{"id":"W4283823743","doi":"10.1038/s41380-022-01636-1","title":"Neurodevelopmental model of schizophrenia revisited: similarity in individual deviation and idiosyncrasy from the normative model of whole-brain white matter tracts and shared brain-cognition covariation with ADHD and ASD","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Schizophrenia (object-oriented programming); Neurodevelopmental disorder; White matter; Cognition; Autism; Autism spectrum disorder; Attention deficit hyperactivity disorder; Neuroscience; Developmental psychology; Psychiatry; Magnetic resonance imaging; Medicine","score_opus":0.03444389929824264,"score_gpt":0.283240859361831,"score_spread":0.24879696006358837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4283823743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9185727,0.00012504966,0.06660759,0.01354072,0.000007306271,0.00058317365,0.00050512736,0.000018710827,0.000039580733],"genre_scores_gemma":[0.9393215,0.000011938864,0.056720156,0.0035057645,0.000007546391,0.00006135871,0.0003475507,0.000019109502,0.000005055864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990702,0.00008145048,0.00027577183,0.0002501455,0.00022530106,0.000097092256],"domain_scores_gemma":[0.9994882,0.000046508827,0.00020529682,0.00017815284,0.00004354249,0.00003833225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016790768,0.00012908012,0.00019438652,0.00009726167,0.00009629072,0.000016262651,0.000064451175,0.000035033856,0.000005046496],"category_scores_gemma":[0.00002364513,0.0001136007,0.000020584877,0.00019183094,0.00006303579,0.00013552803,0.00010087881,0.0002570773,1.2456e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035022877,0.0013967017,0.52694756,0.0009887216,0.00037141287,0.000016224032,0.02214564,0.025153564,0.397393,0.006057398,0.007626961,0.00840055],"study_design_scores_gemma":[0.005213062,0.00033641033,0.7607101,0.00035198784,0.00028073395,0.000078177756,0.0008623823,0.19970897,0.002443138,0.029614192,0.00003591395,0.0003649163],"about_ca_topic_score_codex":0.000011929176,"about_ca_topic_score_gemma":0.0000074527234,"teacher_disagreement_score":0.39494985,"about_ca_system_score_codex":0.00001583087,"about_ca_system_score_gemma":0.00006889189,"threshold_uncertainty_score":0.46325022},"labels":[],"label_agreement":null},{"id":"W4284671617","doi":"10.1002/hbm.26003","title":"Memory retrieval brain–behavior disconnection in mild traumatic brain injury: A magnetoencephalography and diffusion tensor imaging study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital; London Health Sciences Centre; SickKids Foundation; University of Toronto; Western University; Mental Health Research Canada; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Canadian Institute for Military and Veteran Health Research; Institute of Development and Economic Alternatives; Defence Research and Development Canada; Brain and Behavior Research Foundation","keywords":"Magnetoencephalography; Disconnection; Diffusion MRI; Traumatic brain injury; Psychology; Neuroscience; Tractography; Medicine; Magnetic resonance imaging; Electroencephalography; Psychiatry; Radiology","score_opus":0.09037558169320231,"score_gpt":0.3688843118268361,"score_spread":0.2785087301336338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284671617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848565,0.00010011159,0.0011925299,0.010850706,0.00005005852,0.0023864254,0.000013542602,0.00033330274,0.00021685354],"genre_scores_gemma":[0.9946826,0.000005284088,0.0010689818,0.0030457426,0.00006735215,0.00059403124,0.000040009625,0.00005407838,0.0004419104],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9979055,0.00022740009,0.00048521676,0.00067336415,0.000348939,0.00035957235],"domain_scores_gemma":[0.99900144,0.0002148687,0.00016341022,0.00048095206,0.000032000644,0.00010734208],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00070468633,0.00024792002,0.0003643925,0.0007268852,0.0007964291,0.000049139893,0.00016834447,0.00003152255,0.00011216811],"category_scores_gemma":[0.00015229372,0.00026408574,0.00009247637,0.0009064595,0.0001366575,0.00015193009,0.00026559987,0.00061892235,0.0000012811593],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020344551,0.0021937646,0.47587818,0.00017404526,0.000024801746,0.00025825904,0.009452051,0.000013957969,0.49121168,0.0005515119,0.006904704,0.013133601],"study_design_scores_gemma":[0.0022463428,0.0006531852,0.9787246,0.00012560483,0.000051316583,0.00015258288,0.0121911755,0.00079810293,0.0000685818,0.0016940105,0.0029468765,0.0003475915],"about_ca_topic_score_codex":0.000099541,"about_ca_topic_score_gemma":0.0000239894,"teacher_disagreement_score":0.5028464,"about_ca_system_score_codex":0.0001327687,"about_ca_system_score_gemma":0.000022449192,"threshold_uncertainty_score":0.9999811},"labels":[],"label_agreement":null},{"id":"W4284896909","doi":"10.1016/j.nicl.2022.103106","title":"The Open-Access European Prevention of Alzheimer’s Dementia (EPAD) MRI dataset and processing workflow","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"UCLH Biomedical Research Centre; Horizon 2020; Medical Research Council; University College London Hospitals Biomedical Research Centre; Innovative Medicines Initiative; Hartstichting; Alzheimer’s Research UK; ZonMw; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Nano-Convergence Foundation; Fondation Leducq; HORIZON EUROPE Framework Programme; Wellcome Trust; Alzheimer's Society; Rijksdienst voor Ondernemend Nederland; Velux Stiftung; National Institute for Health and Care Research; Alzheimer Society; Alzheimer Nederland; EU Joint Programme – Neurodegenerative Disease Research; UK Dementia Research Institute; Velux Fonden; University College London","keywords":"Computer science; Artificial intelligence; Neuroimaging; Fluid-attenuated inversion recovery; Pattern recognition (psychology); Pipeline (software); Magnetic resonance imaging; Medicine; Radiology; Psychiatry","score_opus":0.33589439662155296,"score_gpt":0.5270368599658383,"score_spread":0.1911424633442853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284896909","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56137234,0.03076071,0.15195891,0.16119184,0.0029417207,0.029751604,0.004857761,0.0027414141,0.054423694],"genre_scores_gemma":[0.9750287,0.0010803025,0.01955374,0.0032426128,0.00014666103,0.0001719575,0.0005180866,0.00007581191,0.00018211798],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819964,0.0003559834,0.0006049752,0.0004658668,0.00020613312,0.00016740905],"domain_scores_gemma":[0.9986807,0.0001801688,0.00032447584,0.0006761375,0.000048383783,0.00009014798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011644936,0.00011069852,0.00022663029,0.000033809127,0.00049226306,0.00014617071,0.0007376546,0.000015635784,0.000048436195],"category_scores_gemma":[0.00019127605,0.000089258174,0.00006420817,0.00022861591,0.00025356177,0.00025418727,0.0024533644,0.00046193931,0.0000026185091],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056199793,0.0014971318,0.031353883,0.00006639135,0.00018744974,0.0001512648,0.000035772693,0.000024403009,0.0028513337,0.000755962,0.17004378,0.79247063],"study_design_scores_gemma":[0.0017152737,0.000841223,0.12646773,0.00006363595,0.0006989246,0.00017541782,0.00003310228,0.0018802636,0.0004766392,0.0022911294,0.8651484,0.00020820615],"about_ca_topic_score_codex":0.000004605701,"about_ca_topic_score_gemma":0.0000013276554,"teacher_disagreement_score":0.79226243,"about_ca_system_score_codex":0.000005226765,"about_ca_system_score_gemma":0.000066710774,"threshold_uncertainty_score":0.37861392},"labels":[],"label_agreement":null},{"id":"W4284992187","doi":"10.1101/2022.07.06.22277331","title":"A dataset of multi-contrast unbiased average MRI templates of a Parkinson’s disease population","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Concordia University; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Fluid-attenuated inversion recovery; Template; Voxel; Parkinson's disease; Contrast (vision); Population; Magnetic resonance imaging; Nuclear medicine; Medicine; Computer science; Artificial intelligence; Pathology; Radiology; Disease","score_opus":0.08957193115287045,"score_gpt":0.3733878206738385,"score_spread":0.2838158895209681,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284992187","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93741655,0.00039229245,0.035307854,0.00075353164,0.00011573303,0.0019530709,0.02384956,0.00017770406,0.000033722346],"genre_scores_gemma":[0.9657317,0.00018060254,0.01952846,0.00012445093,0.000034670014,0.00029976005,0.014013753,0.00004062182,0.00004602404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984603,0.000063192965,0.00056884397,0.0004761985,0.00028077286,0.00015069079],"domain_scores_gemma":[0.9981,0.0000784746,0.00050789805,0.0011177008,0.00006608749,0.00012985995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001893691,0.00020665172,0.00048092203,0.00016532146,0.000050511,0.0000052221085,0.0002492312,0.000064842985,0.00014719559],"category_scores_gemma":[0.00013388912,0.0002013654,0.0001475327,0.0001585897,0.00007265534,0.00003320029,0.00038755185,0.00041549143,0.0000015385989],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005390619,0.0013009978,0.97976154,0.0014604302,0.000106037514,0.000103503146,0.000101190446,0.003318986,0.008469075,0.00034820836,0.0028688577,0.0016221334],"study_design_scores_gemma":[0.0013036937,0.00011293212,0.9389158,0.00048421696,0.000378744,0.000010004458,0.000017602886,0.023399154,0.003828297,0.0017052018,0.029509615,0.00033475985],"about_ca_topic_score_codex":0.00021973207,"about_ca_topic_score_gemma":0.0000072294292,"teacher_disagreement_score":0.04084574,"about_ca_system_score_codex":0.00005239301,"about_ca_system_score_gemma":0.00007963411,"threshold_uncertainty_score":0.8211443},"labels":[],"label_agreement":null},{"id":"W4284994255","doi":"10.1016/j.nicl.2022.103105","title":"Volumetric and structural connectivity abnormalities co-localise in TLE","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"UCLH Biomedical Research Centre; Medical Research Council; University College London Hospitals NHS Foundation Trust; University of Western Australia; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; National Imaging Facility; UK Research and Innovation; Wellcome Trust","keywords":"White matter; Grey matter; Diffusion MRI; Temporal lobe; Tractography; Epilepsy; Lateralization of brain function; Neuroscience; Magnetic resonance imaging; Psychology; Anatomy; Medicine; Radiology","score_opus":0.1469820276962668,"score_gpt":0.4532205269882004,"score_spread":0.3062384992919336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284994255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99574566,0.00010046744,0.00048717804,0.0019006579,0.00010004262,0.0003855546,0.000048560716,0.00016244178,0.0010694431],"genre_scores_gemma":[0.99549335,0.000078213736,0.0015073982,0.0024010902,0.00007436088,0.00006481318,0.000019083445,0.0000233961,0.00033826756],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985723,0.00019050116,0.00039738844,0.00043866635,0.00019290736,0.0002082516],"domain_scores_gemma":[0.998846,0.0005522274,0.000085240135,0.00037298098,0.000027788836,0.000115778836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042514264,0.00011452244,0.0003006785,0.00014232256,0.00015739675,0.000016186894,0.000108312764,0.000035147725,0.00015317157],"category_scores_gemma":[0.00056198845,0.00011618571,0.000079340185,0.0003612195,0.00022976608,0.000083148756,0.00021430297,0.0007964752,0.00000468833],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023826194,0.00029753157,0.974873,0.000034090357,0.00000724475,0.00035812176,0.00006811383,0.000016797972,0.00065086526,0.0011345111,0.0044686357,0.017852813],"study_design_scores_gemma":[0.0014949068,0.0006068011,0.95406884,0.000006722322,0.000024136558,0.00046619037,0.000071934184,0.005155983,0.00016286738,0.0021483214,0.03563454,0.00015876006],"about_ca_topic_score_codex":0.000036165642,"about_ca_topic_score_gemma":0.0000029579717,"teacher_disagreement_score":0.031165905,"about_ca_system_score_codex":0.000035692694,"about_ca_system_score_gemma":0.000047279293,"threshold_uncertainty_score":0.47379157},"labels":[],"label_agreement":null},{"id":"W4285227449","doi":"10.2139/ssrn.4097565","title":"In-Vivo Along Muscle Fascicle Strain Heterogeneity is Not Affected by Image Registration Parameters: Robustness Testing of Combined Magnetic Resonance-Diffusion Tensor Imaging Method","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Diffusion MRI; Magnetic resonance imaging; Fascicle; Robustness (evolution); Nuclear magnetic resonance; In vivo; Image registration; Biomedical engineering; Materials science; Medicine; Anatomy; Physics; Computer vision; Chemistry; Computer science; Radiology; Image (mathematics); Biology","score_opus":0.03139744674650294,"score_gpt":0.32171733679284575,"score_spread":0.29031989004634284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285227449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89258856,0.0007806572,0.10173273,0.004108517,0.000034509685,0.0005600759,0.000059811566,0.000090754154,0.0000443749],"genre_scores_gemma":[0.957424,0.00019489578,0.0414038,0.0006296195,0.000031467014,0.000070751244,0.000014586162,0.000046373385,0.00018454948],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99747425,0.00022803152,0.0005310269,0.00039196454,0.00035909825,0.001015643],"domain_scores_gemma":[0.9989727,0.00013461518,0.00033192924,0.0003428424,0.00013771863,0.00008017955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012773088,0.00019320424,0.0003182194,0.00017512341,0.0002932309,0.000028803432,0.00022556148,0.000035575384,0.00003839385],"category_scores_gemma":[0.00018186399,0.00020015468,0.0001095047,0.0006255412,0.00007886932,0.00020585365,0.00009289822,0.0015890647,4.0604647e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019762387,0.0006212907,0.007258589,0.000030196665,0.000013218565,0.000031448195,0.000095697695,0.00027427144,0.9305113,0.00058765325,0.0005198809,0.05985883],"study_design_scores_gemma":[0.023096588,0.008661296,0.09341373,0.00059056096,0.00059886527,0.010499604,0.0043775425,0.35830805,0.422763,0.06966513,0.005919581,0.0021060936],"about_ca_topic_score_codex":0.00018940608,"about_ca_topic_score_gemma":0.000042233976,"teacher_disagreement_score":0.5077483,"about_ca_system_score_codex":0.00058951613,"about_ca_system_score_gemma":0.00044539323,"threshold_uncertainty_score":0.8162071},"labels":[],"label_agreement":null},{"id":"W4285490115","doi":"10.1016/j.nic.2022.05.001","title":"Cerebral White Matter Tract Anatomy","year":2022,"lang":"en","type":"review","venue":"Neuroimaging Clinics of North America","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"White matter; Diffusion MRI; Medicine; Neuroscience; Tractography; Anatomy; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.11286402580904348,"score_gpt":0.42788729430903943,"score_spread":0.31502326849999596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285490115","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000925524,0.9896911,0.0009633267,0.0011529599,0.00032646142,0.002024836,0.00051545055,0.0005366153,0.0046967394],"genre_scores_gemma":[0.00006520384,0.9872373,0.008255915,0.0026437505,0.00014566354,0.00023688984,0.000615005,0.00023724267,0.0005630441],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965013,0.00015129162,0.0014069244,0.001007636,0.00046530803,0.00046753715],"domain_scores_gemma":[0.9962216,0.0004990818,0.0013660146,0.0016165935,0.000078515855,0.00021818592],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012473468,0.00058390154,0.0023514312,0.00041749544,0.00013937862,0.000022589928,0.00063422596,0.000080822145,0.0008243581],"category_scores_gemma":[0.00013887776,0.00055389514,0.001111168,0.001097376,0.0002824149,0.00009991074,0.00037527506,0.0018458306,0.00012942843],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008920246,0.00032310374,0.024849003,0.0034912114,0.000044689292,0.00010118267,0.000011848509,0.0000033024864,3.7206462e-8,0.000005556547,0.006510621,0.9646505],"study_design_scores_gemma":[0.00019739212,0.00018372346,0.003549055,0.00080319337,0.0009413744,0.0003777895,0.000003634224,0.000044681532,8.074333e-8,0.00002476728,0.9934985,0.00037578962],"about_ca_topic_score_codex":0.0000087238805,"about_ca_topic_score_gemma":2.8433368e-7,"teacher_disagreement_score":0.9869879,"about_ca_system_score_codex":0.00007533797,"about_ca_system_score_gemma":0.00034622554,"threshold_uncertainty_score":0.99969125},"labels":[],"label_agreement":null},{"id":"W4286236408","doi":"10.48550/arxiv.2207.07778","title":"High-resolution diffusion-weighted imaging at 7 Tesla: single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Sharpening; Image resolution; Diffusion MRI; Signal-to-noise ratio (imaging); Physics; Resolution (logic); Image quality; Nuclear magnetic resonance; Optics; Computer science; Magnetic resonance imaging; Artificial intelligence; Image (mathematics)","score_opus":0.088585658381082,"score_gpt":0.2588581358627997,"score_spread":0.1702724774817177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286236408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90416664,0.00014271353,0.092828035,0.0006540433,0.000101332516,0.0011512297,0.00023630567,0.00036487365,0.0003548288],"genre_scores_gemma":[0.9975221,0.00037383792,0.00081249553,0.00022503117,0.00012971385,0.000014357072,0.00036292564,0.000054707147,0.00050478755],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99804115,0.00012096887,0.0002567596,0.0011169745,0.000122004865,0.00034211692],"domain_scores_gemma":[0.99831015,0.00029530103,0.0002742473,0.0007351975,0.0001224012,0.00026271824],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013698741,0.0004602292,0.00047727107,0.00037741827,0.00053890806,0.00005425913,0.0001992685,0.00013533623,0.00012529455],"category_scores_gemma":[0.00008598034,0.0004193357,0.00014505556,0.00038974057,0.0001992106,0.00014931416,0.0009861975,0.0006636021,0.000003917422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.019930044,0.0039239214,0.18888727,0.0011262408,0.00081717334,0.0015768927,0.004439554,0.13330199,0.57547355,0.03191343,0.011503704,0.027106205],"study_design_scores_gemma":[0.00785334,0.003102328,0.23423542,0.0015224052,0.0013870697,0.00029128,0.00090801885,0.67569304,0.029288227,0.033333357,0.0090600755,0.0033254428],"about_ca_topic_score_codex":0.00066673657,"about_ca_topic_score_gemma":0.000025729967,"teacher_disagreement_score":0.5461854,"about_ca_system_score_codex":0.00075812615,"about_ca_system_score_gemma":0.00009636525,"threshold_uncertainty_score":0.99982584},"labels":[],"label_agreement":null},{"id":"W4286252873","doi":"10.1016/j.neuroimage.2022.119495","title":"Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Eye Institute; Research to Prevent Blindness; National Science Foundation; National Institutes of Health; Foundation Fighting Blindness; Lions Clubs International Foundation","keywords":"Optic tract; Retinal ganglion cell; White matter; Retinal; Optic radiation; Optic nerve; Optic chiasm; Retina; Visual system; Biology; Diffusion MRI; Anatomy; Ophthalmology; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.032697869291006966,"score_gpt":0.30696674204759333,"score_spread":0.27426887275658635,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286252873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9888542,0.00001731163,0.0018453575,0.001926197,0.00011193522,0.00068845926,0.000037558035,0.0004362438,0.0060826866],"genre_scores_gemma":[0.9854254,0.000010875528,0.0037596356,0.00237316,0.00007974243,0.00012247864,0.00003946343,0.00005292014,0.008136283],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99867016,0.00004656594,0.00020714382,0.00048207678,0.00034898726,0.0002450865],"domain_scores_gemma":[0.99914026,0.00004488765,0.00012011191,0.0004952312,0.00009528735,0.00010421784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009761951,0.0001679324,0.00017751024,0.000077815814,0.00040867383,0.000029497778,0.0001107122,0.000030037834,0.0007342353],"category_scores_gemma":[0.000016549533,0.00015755765,0.00007345339,0.00033599552,0.000080004385,0.00008038984,0.000105727144,0.0006752037,0.00004426723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043982193,0.005263406,0.069613904,0.0003340648,0.000068083995,0.008277601,0.0013572412,0.0025586705,0.8062819,0.00046558285,0.096700735,0.00468058],"study_design_scores_gemma":[0.0063174535,0.0044316133,0.24839482,0.000063377665,0.00039473292,0.013001434,0.000134417,0.005902947,0.44841075,0.0002881844,0.2717249,0.0009353618],"about_ca_topic_score_codex":0.000027121456,"about_ca_topic_score_gemma":3.3255827e-7,"teacher_disagreement_score":0.35787115,"about_ca_system_score_codex":0.00009824076,"about_ca_system_score_gemma":0.000046608948,"threshold_uncertainty_score":0.8039361},"labels":[],"label_agreement":null},{"id":"W4286255720","doi":"10.1016/j.neurobiolaging.2022.03.020","title":"Myelin Content and Gait Impairment in Older Adults with Cerebral Small Vessel Disease and Mild Cognitive Impairment","year":2022,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Hospital and Health Sciences Centre; University of British Columbia Hospital; University of British Columbia; International Collaboration On Repair Discoveries; Vancouver Coastal Health","funders":"Canadian Institutes of Health Research","keywords":"Hyperintensity; White matter; Corpus callosum; Myelin; Cingulum (brain); Psychology; Gait; Posterior cingulate; Internal medicine; Cardiology; Magnetic resonance imaging; Medicine; Audiology; Physical medicine and rehabilitation; Cognition; Neuroscience; Radiology; Central nervous system; Fractional anisotropy","score_opus":0.03428768788565538,"score_gpt":0.2841490144208272,"score_spread":0.2498613265351718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286255720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99551207,0.0002547811,0.00013162519,0.0030437487,0.00001551105,0.0009312332,0.000045671637,0.000047121142,0.000018215735],"genre_scores_gemma":[0.997364,0.000101956146,0.00079767377,0.0014234461,0.000011439985,0.00021649705,0.00003724677,0.000015884572,0.000031853815],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991844,0.00005250997,0.00017646467,0.00034952216,0.000055065673,0.000182007],"domain_scores_gemma":[0.99959695,0.00006966989,0.00008250014,0.00012797004,0.00003112072,0.000091774295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007059202,0.000120630255,0.00020309417,0.00007896485,0.00008363681,0.0000030367894,0.00004350805,0.0000150318365,0.000013103697],"category_scores_gemma":[0.0000080295595,0.00010349192,0.000022961876,0.00008981508,0.00015734746,0.000022146061,0.00014854979,0.00021833162,1.8546817e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018235105,0.0007694792,0.9920844,0.00023152992,0.00003267761,0.00011198676,0.0010242492,0.000025814177,0.0019953882,0.00015493277,0.00013970512,0.0016063227],"study_design_scores_gemma":[0.004079225,0.0010919397,0.99181193,0.0002542079,0.00006351291,0.00011277821,0.00070366036,0.0002475217,0.0013804678,0.000078022145,0.00006182582,0.00011490163],"about_ca_topic_score_codex":0.00003613032,"about_ca_topic_score_gemma":0.000003948478,"teacher_disagreement_score":0.0022557145,"about_ca_system_score_codex":0.000022933109,"about_ca_system_score_gemma":0.000028974837,"threshold_uncertainty_score":0.4220278},"labels":[],"label_agreement":null},{"id":"W4286560425","doi":"10.1093/braincomms/fcac187","title":"Structural disconnection and functional reorganization in Fabry disease: a multimodal MRI study","year":2022,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Connectome; Confounding; Disease; Functional connectivity; Fabry disease; Resting state fMRI; Diffusion MRI; Neuroscience; Medicine; Magnetic resonance imaging; Psychology; Cardiology; Internal medicine; Radiology","score_opus":0.08221085080168757,"score_gpt":0.3653587070523829,"score_spread":0.28314785625069533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286560425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8999614,0.00031595034,0.014605683,0.082352005,0.00006017558,0.0019897337,0.00007427912,0.00033069035,0.00031006103],"genre_scores_gemma":[0.9945428,0.000023184211,0.0035885596,0.00062013685,0.00001994801,0.0005518946,0.0003137848,0.000017842252,0.00032186805],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99925375,0.00013345295,0.00017836114,0.00021106507,0.00013435465,0.00008903145],"domain_scores_gemma":[0.9988531,0.00015684207,0.000056355668,0.0008345225,0.0000395926,0.000059622456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013841852,0.000076770404,0.00009372571,0.0001225181,0.0005608305,0.000014474063,0.00014330314,0.000011680369,0.0000727811],"category_scores_gemma":[0.00011942352,0.00008298788,0.00002078349,0.00042772765,0.000072670824,0.00008329306,0.00042255514,0.00028376924,0.0000010605205],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029325977,0.0023475294,0.92716527,0.000032521395,0.00004465215,0.0000142945055,0.0023511336,0.0020353913,0.004045665,0.043536916,0.005129161,0.013004216],"study_design_scores_gemma":[0.0010203929,0.00011201665,0.9433764,0.000009448767,0.00003251359,0.000046847585,0.0012341097,0.042639427,0.000009669801,0.0042453553,0.007152076,0.00012174509],"about_ca_topic_score_codex":0.00005569922,"about_ca_topic_score_gemma":0.000051847444,"teacher_disagreement_score":0.094581366,"about_ca_system_score_codex":0.000098917604,"about_ca_system_score_gemma":0.000049346592,"threshold_uncertainty_score":0.43135118},"labels":[],"label_agreement":null},{"id":"W4286630390","doi":"10.3389/fnagi.2022.859873","title":"Longitudinal Intraindividual Cognitive Variability Is Associated With Reduction in Regional Cerebral Blood Flow Among Alzheimer’s Disease Biomarker-Positive Older Adults","year":2022,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Johnson and Johnson Pharmaceutical Research and Development; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; Servier; Eisai; Janssen Alzheimer Immunotherapy Research And Development; Northern California Institute for Research and Education; F. Hoffmann-La Roche; Biogen; BioClinica; Novartis Pharmaceuticals Corporation; Pfizer; Bristol-Myers Squibb; Eli Lilly and Company; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; University of Southern California; H. Lundbeck A/S; U.S. Department of Veterans Affairs; Foundation for the National Institutes of Health","keywords":"Biomarker; Medicine; Cerebral blood flow; Neuropsychology; Dementia; Magnetic resonance imaging; Alzheimer's Disease Neuroimaging Initiative; Cardiology; Internal medicine; Neuroimaging; Cerebrospinal fluid; Cognitive decline; Alzheimer's disease; Oncology; Disease; Psychology; Cognition; Radiology; Psychiatry","score_opus":0.040029280014623594,"score_gpt":0.3003318392567934,"score_spread":0.26030255924216983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286630390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98296076,0.00007541983,0.012539186,0.0026448164,0.0002498546,0.0011510786,0.00018823383,0.00014239525,0.00004826033],"genre_scores_gemma":[0.99522793,0.000014195318,0.003550649,0.0007273414,0.000022005486,0.00031037722,0.00008692057,0.000024227062,0.00003634365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976542,0.00020553193,0.00026741685,0.00094871724,0.0005178473,0.00040627754],"domain_scores_gemma":[0.99926203,0.00007590847,0.00015633584,0.0002693647,0.000073514355,0.00016283698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042368026,0.00019730785,0.00023977958,0.00031220872,0.00031258303,0.000028647877,0.00021032142,0.00003033829,0.000013332505],"category_scores_gemma":[0.00024272459,0.0001864718,0.00005406319,0.0014276797,0.0005942934,0.00026247004,0.0001533178,0.0005693182,1.8583333e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035371762,0.00091752823,0.9930724,0.0000101518135,0.000014706148,0.0002606392,0.00082344795,0.00017848027,0.00014626044,0.000021623187,0.00092330296,0.0032777567],"study_design_scores_gemma":[0.0016110014,0.00016319723,0.9755201,0.00026796415,0.00012165411,0.00009594187,0.000293045,0.021019528,0.00032567867,0.00033845415,0.000029424426,0.00021404987],"about_ca_topic_score_codex":0.0000381504,"about_ca_topic_score_gemma":0.0000033788363,"teacher_disagreement_score":0.020841047,"about_ca_system_score_codex":0.00017333061,"about_ca_system_score_gemma":0.00016696223,"threshold_uncertainty_score":0.76040995},"labels":[],"label_agreement":null},{"id":"W4286640335","doi":"10.1016/j.neuroimage.2022.119488","title":"Short-term repeatability and long-term reproducibility of quantitative MR imaging biomarkers in a single centre longitudinal study","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"Canadian Institutes of Health Research; University of Calgary","keywords":"Reproducibility; Repeatability; Fractional anisotropy; Coefficient of variation; Nuclear medicine; Medicine; Diffusion MRI; Cerebral blood flow; Biomedical engineering; Pathology; Radiology; Magnetic resonance imaging; Mathematics; Statistics; Internal medicine","score_opus":0.12233916128991092,"score_gpt":0.39077567043713873,"score_spread":0.26843650914722783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286640335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964865,0.0001592222,0.0004733553,0.00093616487,0.00004233406,0.0015610683,0.00004904261,0.00013151167,0.00016079751],"genre_scores_gemma":[0.9981241,0.000009360942,0.0016311761,0.00006167245,0.000011304708,0.00008233341,0.00002302514,0.000030068777,0.00002694462],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9972,0.00023352403,0.00050802145,0.0015258073,0.00028456296,0.00024809668],"domain_scores_gemma":[0.99774456,0.00014985983,0.00013416962,0.0018052983,0.0000842429,0.00008186327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088709913,0.00018399072,0.00037221122,0.00016189918,0.0001360686,0.000015338026,0.00015361817,0.000013605377,0.000038770555],"category_scores_gemma":[0.00048467537,0.00019244167,0.0000751739,0.0004873322,0.0002434749,0.00012800777,0.00044585095,0.0003597901,5.026339e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002819697,0.0021186606,0.94104964,0.000084452266,0.000015240637,0.00031838255,0.00040988548,0.0000023441075,0.051497772,0.00002253525,0.000032575575,0.0041665654],"study_design_scores_gemma":[0.00066595525,0.00044298824,0.9950528,0.000027370752,0.000059881084,0.00011121447,0.00039681973,0.00014081955,0.0028169933,0.00012878152,0.000023723669,0.00013262547],"about_ca_topic_score_codex":0.00005815228,"about_ca_topic_score_gemma":0.000036673904,"teacher_disagreement_score":0.054003213,"about_ca_system_score_codex":0.00010989566,"about_ca_system_score_gemma":0.000033228152,"threshold_uncertainty_score":0.7847544},"labels":[],"label_agreement":null},{"id":"W4286714342","doi":"10.26599/bsa.2019.9050012","title":"Visualizing the neuroanatomical changes in Han Chinese adulthood: A pseudo-longitudinal study based on age-related large-scale statistical Chinese brain atlases","year":2019,"lang":"en","type":"article","venue":"Brain Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute","funders":"","keywords":"Atrophy; Neuroscience; Brain cortex; Neuropathology; Brain size; Cortex (anatomy); Psychology; Anatomy; Biology; Medicine; Magnetic resonance imaging; Pathology; Internal medicine","score_opus":0.029240193825797067,"score_gpt":0.40026859882694077,"score_spread":0.3710284050011437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286714342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97805005,0.000056758825,0.0041001616,0.015337293,0.0001255298,0.0016873929,0.000027660899,0.00022513303,0.0003900325],"genre_scores_gemma":[0.9916224,0.000013567769,0.0042419187,0.003714657,0.000057350866,0.00018260798,0.000017170936,0.000033148674,0.00011721253],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970364,0.00015332288,0.00038630905,0.0010025338,0.00079608546,0.00062534737],"domain_scores_gemma":[0.99745643,0.0013547788,0.0001471023,0.0007785124,0.00006953412,0.00019361434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084197,0.00031233867,0.00042432954,0.0003484596,0.0003464764,0.00008375237,0.0005629059,0.000043780776,0.000054552504],"category_scores_gemma":[0.001736644,0.00019335127,0.00006445578,0.0022886046,0.0006570789,0.0003231365,0.00016806285,0.00049055874,0.0000281609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000327876,0.0019540587,0.9718389,0.00005155222,0.0000071412237,0.00022647764,0.0011525825,0.00089857384,0.015347876,0.0018075298,0.00024276732,0.006144681],"study_design_scores_gemma":[0.0024628234,0.0013127167,0.9022565,0.00015023592,0.000015958403,0.00005807034,0.0007696246,0.08795956,0.00032171965,0.0026668329,0.0016805601,0.00034540784],"about_ca_topic_score_codex":0.000024707004,"about_ca_topic_score_gemma":0.00025394157,"teacher_disagreement_score":0.08706098,"about_ca_system_score_codex":0.00008162674,"about_ca_system_score_gemma":0.00012312223,"threshold_uncertainty_score":0.7884636},"labels":[],"label_agreement":null},{"id":"W4286718003","doi":"10.31083/j.jin2105129","title":"Gait Disorders and Magnetic Resonance Imaging Characteristics in Older Adults with Cerebral Small Vessel Disease","year":2022,"lang":"en","type":"article","venue":"Journal of Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Magnetic resonance imaging; Gait; Tinetti test; Fractional anisotropy; Diffusion MRI; Medicine; White matter; Internal medicine; Rating scale; Cardiology; Psychology; Physical medicine and rehabilitation; Radiology","score_opus":0.015324358451782647,"score_gpt":0.2831349522743294,"score_spread":0.26781059382254674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286718003","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98845905,0.000648335,0.0055558514,0.0048371633,0.00007101344,0.0003123418,0.000021379798,0.000017415492,0.000077476456],"genre_scores_gemma":[0.9957778,0.00027609887,0.002407761,0.0013736454,0.00001798147,0.000029184486,9.44641e-7,0.000012689885,0.000103905775],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990804,0.00004421413,0.00024701538,0.00023172505,0.00023769407,0.00015894539],"domain_scores_gemma":[0.99939954,0.000051862866,0.00019693724,0.00013707066,0.000086556436,0.00012804539],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011323607,0.00011647529,0.00018143743,0.000119533506,0.00012514107,0.000022800954,0.00016233837,0.000005721816,0.0000103317525],"category_scores_gemma":[0.0001808003,0.00008098384,0.000032655345,0.00038506783,0.00023474157,0.00013692278,0.00007569461,0.00048180504,1.111678e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010635033,0.0005876892,0.9328438,0.000036371544,7.6137496e-7,0.00053157634,0.0009915462,0.00002048496,0.0056662485,0.000748044,0.00031345864,0.057196517],"study_design_scores_gemma":[0.0008577147,0.0006082355,0.9886074,0.0002430504,0.000012978269,0.0003951459,0.00045331282,0.0036651576,0.00014448808,0.0003162032,0.0045995563,0.00009672849],"about_ca_topic_score_codex":0.000005691921,"about_ca_topic_score_gemma":0.0000028840084,"teacher_disagreement_score":0.057099786,"about_ca_system_score_codex":0.000049570055,"about_ca_system_score_gemma":0.00011261521,"threshold_uncertainty_score":0.3302425},"labels":[],"label_agreement":null},{"id":"W4286784827","doi":"10.48550/arxiv.1904.13281","title":"CT-To-MR Conditional Generative Adversarial Networks for Ischemic Stroke\\n Lesion Segmentation","year":2019,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Segmentation; Computer science; Artificial intelligence; Discriminator; Stroke (engine); Convolutional neural network; Ground truth; Pattern recognition (psychology); Magnetic resonance imaging; Diffusion MRI; Noise (video); Radiology; Medicine; Image (mathematics); Physics","score_opus":0.14085385024045802,"score_gpt":0.28094112281661066,"score_spread":0.14008727257615264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286784827","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10384573,0.000044430264,0.8883958,0.000442041,0.0006988186,0.004403988,0.00081315765,0.00019648107,0.0011595446],"genre_scores_gemma":[0.96856517,0.00078964554,0.015788129,0.00081149413,0.0008966778,0.00006184511,0.0026552184,0.00009199616,0.010339806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967309,0.000103954706,0.0004989838,0.0018807034,0.00016920274,0.0006162232],"domain_scores_gemma":[0.99718446,0.00034444404,0.00058613956,0.0010144829,0.00048573478,0.00038475916],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022424606,0.0006365624,0.00069339713,0.00033056614,0.00045134197,0.000052009887,0.0005463761,0.0003030422,0.00019177733],"category_scores_gemma":[0.00006712905,0.00079187524,0.00047103775,0.000462295,0.00021110107,0.00028418945,0.0006119937,0.0009117935,0.00014530554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012274185,0.00035082057,0.0018089883,0.00018183129,0.00029006362,0.00006536647,0.000099153774,0.9274125,0.020599246,0.030788057,0.016144212,0.001032306],"study_design_scores_gemma":[0.0055230074,0.0006506662,0.0006735105,0.00044409247,0.0012358652,0.000025498171,0.00041608184,0.9379646,0.021488138,0.004852486,0.02555874,0.0011672927],"about_ca_topic_score_codex":0.000033186112,"about_ca_topic_score_gemma":0.0000054268667,"teacher_disagreement_score":0.8726077,"about_ca_system_score_codex":0.00079187966,"about_ca_system_score_gemma":0.00036705533,"threshold_uncertainty_score":0.9994532},"labels":[],"label_agreement":null},{"id":"W4287241074","doi":"10.48550/arxiv.2104.01708","title":"A unified framework for non-negative matrix and tensor factorisations\\n with a smoothed Wasserstein loss","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tensor (intrinsic definition); Metric (unit); Matrix (chemical analysis); Mathematics; Applied mathematics; Mathematical optimization; Dual (grammatical number); Space (punctuation); Regular polygon; Function (biology); Wasserstein metric; Algorithm; Computer science; Algebra over a field; Pure mathematics; Geometry","score_opus":0.12318298998261953,"score_gpt":0.2823722297802872,"score_spread":0.15918923979766766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287241074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4517505,0.00002140132,0.5464322,0.00047177603,0.000025980185,0.0009813117,0.000055793964,0.00014058486,0.000120477365],"genre_scores_gemma":[0.89690036,0.00019350457,0.101421595,0.00010210942,0.00005284559,0.000023144663,0.000070160364,0.000045875564,0.0011904301],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99870527,0.000028161037,0.00015304117,0.00082375266,0.000062165884,0.0002276103],"domain_scores_gemma":[0.9983172,0.0002950077,0.00020909801,0.00073143234,0.00029527408,0.00015202202],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005871898,0.00028151285,0.00042269568,0.00014765374,0.0001507126,0.000041908464,0.0001709691,0.0002446344,0.000016130189],"category_scores_gemma":[0.00010213746,0.00027508204,0.00012650069,0.00036202557,0.00018371615,0.000082951265,0.00022185915,0.0005898265,0.000001973265],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050009857,0.0018476904,0.14129052,0.0037167473,0.0021065688,0.002251606,0.0041834037,0.022951553,0.004684335,0.80992955,0.00077605224,0.0012609608],"study_design_scores_gemma":[0.013103348,0.002063192,0.05887011,0.0062061204,0.0051313303,0.00024319369,0.009404299,0.14440379,0.016243134,0.7355418,0.004890854,0.0038988253],"about_ca_topic_score_codex":0.000057054236,"about_ca_topic_score_gemma":0.000014012682,"teacher_disagreement_score":0.44514984,"about_ca_system_score_codex":0.00013747861,"about_ca_system_score_gemma":0.0001894124,"threshold_uncertainty_score":0.99997014},"labels":[],"label_agreement":null},{"id":"W4288709490","doi":"10.1111/ejn.15785","title":"Effect of number of diffusion‐encoding directions in diffusion metrics of 5‐year‐olds using tract‐based spatial statistical analysis","year":2022,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Suomalainen Lääkäriseura Duodecim; Suomen Aivosäätiö; Signe ja Ane Gyllenbergin Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Juho Vainion Säätiö; Suomalais-Norjalainen Lääketieteen Säätiö; Suomen Lääketieteen Säätiö","keywords":"Diffusion MRI; Fractional anisotropy; Scalar (mathematics); Intraclass correlation; Mathematics; Statistics; Reproducibility; Psychology; Medicine; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.055459933730030775,"score_gpt":0.37664017462963556,"score_spread":0.3211802408996048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4288709490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.857166,0.000012240176,0.14235596,0.000053185733,0.00007856126,0.00010944603,0.000028621951,0.000007730383,0.00018826187],"genre_scores_gemma":[0.9914508,0.000030765183,0.008436567,0.000038646223,0.000015717413,9.937104e-7,0.0000014101638,0.000014232988,0.000010854675],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9978861,0.0005407262,0.00067905156,0.00018054596,0.00058400235,0.00012953792],"domain_scores_gemma":[0.9984766,0.0004003423,0.0007077238,0.00021889809,0.000112384165,0.00008405343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011018967,0.0000946333,0.00040656468,0.0006998181,0.00009560571,0.000005776786,0.00022915684,0.000008689826,0.00003878427],"category_scores_gemma":[0.0008614974,0.00007997159,0.00016385378,0.0025335227,0.00017406713,0.00006315316,0.00012130492,0.00032793285,1.3176606e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019425596,0.00064415665,0.21400832,0.00004816594,0.000006923738,0.00015821979,0.00006909525,0.0048620803,0.7761277,0.000055814904,0.000008774717,0.0038165136],"study_design_scores_gemma":[0.0016483404,0.0024096025,0.8811478,0.00011844767,0.0005467189,0.00030647765,0.00003899842,0.07312758,0.040160924,0.000022301943,0.00034400975,0.00012879715],"about_ca_topic_score_codex":0.000024793773,"about_ca_topic_score_gemma":3.8001687e-7,"teacher_disagreement_score":0.73596674,"about_ca_system_score_codex":0.000046616387,"about_ca_system_score_gemma":0.000058129965,"threshold_uncertainty_score":0.32611468},"labels":[],"label_agreement":null},{"id":"W4289518521","doi":"10.1101/2022.07.29.502031","title":"Mapping the Macrostructure and Microstructure of the in vivo Human Hippocampus using Diffusion MRI","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; McGill University; Montreal Neurological Institute and Hospital; Western University","funders":"National Institute of Dental and Craniofacial Research; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Open Neuroscience Platform; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; University of Southern California","keywords":"Diffusion MRI; Neuroscience; Hippocampal formation; Subiculum; Neurite; Fractional anisotropy; Hippocampus; Psychology; Materials science; Biology; Magnetic resonance imaging; Medicine; Dentate gyrus","score_opus":0.029645112361038742,"score_gpt":0.2796732401389287,"score_spread":0.25002812777788996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289518521","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960987,0.0007229015,0.00048460264,0.00083157065,0.00023149174,0.0013144145,0.00019848449,0.00011261247,0.000005233155],"genre_scores_gemma":[0.99285424,0.00016237938,0.006262966,0.00043519915,0.0001077908,0.00009245797,2.744918e-7,0.000079824385,0.0000048621437],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982738,0.00009863846,0.00043597614,0.0006264612,0.00027650586,0.00028861672],"domain_scores_gemma":[0.99792564,0.000039013565,0.00044819165,0.0014022288,0.00011254298,0.000072377756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023365385,0.0003414722,0.00042869957,0.00015621778,0.0004040854,0.000046045072,0.0004744414,0.00022342388,0.0000351263],"category_scores_gemma":[0.000055754906,0.00024110614,0.000120930636,0.00058285537,0.00029389892,0.000035956604,0.0013163567,0.0013891767,1.320554e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011323218,0.00003097731,0.039192636,0.00027609683,0.0000188431,0.000011116283,0.0000383478,0.00007641669,0.95998603,0.00027755575,0.000078259116,0.0000023949822],"study_design_scores_gemma":[0.00076875085,0.00003433899,0.77676433,0.001001727,0.000138441,9.81608e-7,0.000036142446,0.0009558258,0.21249644,0.00032093847,0.006969983,0.00051209657],"about_ca_topic_score_codex":0.00007634009,"about_ca_topic_score_gemma":0.000002529627,"teacher_disagreement_score":0.7474896,"about_ca_system_score_codex":0.00019156898,"about_ca_system_score_gemma":0.00017841604,"threshold_uncertainty_score":0.98320234},"labels":[],"label_agreement":null},{"id":"W4289526123","doi":"10.1016/j.jns.2022.120377","title":"Timing stroke: A review on stroke pathophysiology and its influence over time on diffusion measures","year":2022,"lang":"en","type":"review","venue":"Journal of the Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Montréal; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal","funders":"","keywords":"Diffusion MRI; Stroke (engine); Medicine; Pathophysiology; Neuroinflammation; Ischemia; Neuroscience; Pathology; Disease; Cardiology; Magnetic resonance imaging; Radiology; Psychology","score_opus":0.16587531255986399,"score_gpt":0.40956497275471926,"score_spread":0.24368966019485527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289526123","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009735291,0.986038,0.0000026714035,0.0031764172,0.00010177138,0.0006747714,0.000017830747,0.000024216955,0.00022898082],"genre_scores_gemma":[0.00035139357,0.9918666,0.00011145947,0.0074232053,0.00008233073,0.000023054286,4.6065648e-7,0.000009665778,0.00013183725],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99788094,0.0004167701,0.0005068556,0.00034943532,0.0006465644,0.00019945763],"domain_scores_gemma":[0.99805593,0.0007147835,0.0008478395,0.0002435705,0.00003870963,0.00009917805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067887787,0.00022474412,0.0009625574,0.00010436819,0.00030993536,0.000018270786,0.0006384526,0.000078212826,0.000094435694],"category_scores_gemma":[0.0012256147,0.00009775294,0.0003822969,0.00033455537,0.00022191765,0.000050620016,0.00030123262,0.001205702,0.0000053672024],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007681186,0.0002735015,0.00006348091,0.001876776,0.000022480654,0.00011487387,0.0000047413823,0.000041083986,0.000989444,0.00026175944,0.0015868314,0.9946882],"study_design_scores_gemma":[0.00010409814,0.0031592823,0.00050355826,0.006830053,0.00031310378,0.00057486515,3.9142682e-7,0.00004031257,0.000006934259,0.00034429113,0.9880066,0.00011651132],"about_ca_topic_score_codex":2.6422512e-7,"about_ca_topic_score_gemma":2.1199519e-8,"teacher_disagreement_score":0.9945717,"about_ca_system_score_codex":0.000029935498,"about_ca_system_score_gemma":0.00008786319,"threshold_uncertainty_score":0.5238242},"labels":[],"label_agreement":null},{"id":"W4289653886","doi":"10.1101/2022.08.01.502396","title":"RELIEF: a structured multivariate approach for removal of latent inter-scanner effects","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; University of Toronto; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Scanner; Generalizability theory; Computer science; Harmonization; Univariate; Multivariate statistics; Data science; Artificial intelligence; Machine learning; Data mining; Statistics; Mathematics","score_opus":0.03422065117062607,"score_gpt":0.29290118778850355,"score_spread":0.2586805366178775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289653886","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44172448,0.001144614,0.5432813,0.0007156934,0.0010077762,0.009506781,0.0010090388,0.0015497771,0.000060533846],"genre_scores_gemma":[0.6377492,0.000058701713,0.36033908,0.0001852082,0.00017073694,0.0013263891,0.0000038090895,0.00014520911,0.000021694517],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9976008,0.00007559797,0.0005778384,0.0010358344,0.00030786713,0.000402058],"domain_scores_gemma":[0.99721825,0.00009190337,0.00055004423,0.0015917562,0.00035743092,0.00019060972],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003118477,0.00046946193,0.00080365106,0.0002561998,0.00012718963,0.000029539182,0.00043330036,0.00028016983,0.00002117356],"category_scores_gemma":[0.00026047637,0.00046650652,0.00031469433,0.0003634495,0.00011012673,0.000046956295,0.0006483055,0.0009265266,0.0000012892879],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002861099,0.0004928853,0.0013194103,0.0026983884,0.00023999866,0.000075796845,0.000015055252,0.00024022884,0.99103796,0.0028920404,0.0006761031,0.000026010379],"study_design_scores_gemma":[0.0047616963,0.0007788824,0.073896445,0.001299365,0.0012978705,0.0000010871706,0.000004993553,0.018071678,0.84667426,0.00011501325,0.051339835,0.0017588667],"about_ca_topic_score_codex":0.000030052108,"about_ca_topic_score_gemma":1.0471604e-7,"teacher_disagreement_score":0.1960247,"about_ca_system_score_codex":0.00025958076,"about_ca_system_score_gemma":0.0002940233,"threshold_uncertainty_score":0.9997787},"labels":[],"label_agreement":null},{"id":"W4289824396","doi":"10.2139/ssrn.4157505","title":"Transformer-Based Framework for Fiber Orientation Estimation &amp; Tractography","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Tractography; Orientation (vector space); Transformer; Computer science; Artificial intelligence; Computer vision; Medicine; Diffusion MRI; Radiology; Mathematics; Engineering; Electrical engineering; Magnetic resonance imaging","score_opus":0.03911101223605253,"score_gpt":0.36791293678473064,"score_spread":0.3288019245486781,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289824396","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029052075,0.00018782576,0.96423,0.0057360604,0.00004646815,0.00053543353,0.000013660636,0.000101117956,0.000097341894],"genre_scores_gemma":[0.7586998,0.00015399649,0.23944545,0.0006104919,0.000103458726,0.00037925015,0.00013426873,0.00003909868,0.00043423864],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986983,0.00002332144,0.00020631013,0.000162651,0.00021443794,0.0006949758],"domain_scores_gemma":[0.99954146,0.00008089024,0.00011782711,0.0001462357,0.000059159083,0.000054409422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043264838,0.00009512351,0.00011702654,0.00014654758,0.00044310535,0.000014431192,0.000085542524,0.000030634223,0.00011105832],"category_scores_gemma":[0.00004142479,0.0000935654,0.00016201905,0.00031197004,0.000022952738,0.000076532,0.0000039382217,0.0012609524,0.0000035145983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011122101,0.00087446533,0.0013501127,0.000057983278,0.00014228626,0.000002541819,0.00026301076,0.0064038355,0.005905145,0.666533,0.0011174357,0.31623802],"study_design_scores_gemma":[0.0014178513,0.0010539726,0.00038878497,0.000022006827,0.0001547205,0.00044581122,0.00023246366,0.0023700458,0.0011923189,0.9118606,0.08068789,0.0001735354],"about_ca_topic_score_codex":0.0000031680966,"about_ca_topic_score_gemma":0.000004227853,"teacher_disagreement_score":0.7296477,"about_ca_system_score_codex":0.00038011398,"about_ca_system_score_gemma":0.0005774843,"threshold_uncertainty_score":0.5478281},"labels":[],"label_agreement":null},{"id":"W4289842561","doi":"10.1162/netn_a_00271","title":"Coupling of the spatial distributions between sMRI and PET reveals the progression of Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Eisai; Servier; Beijing Normal University; Genentech; IXICO; National Natural Science Foundation of China; Fundamental Research Funds for the Central Universities; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Atrophy; Dementia; Neuroimaging; Positron emission tomography; Biomarker; Coupling (piping); Neuroscience; Psychology; Disease; Cognition; Medicine; Internal medicine; Oncology; Biology","score_opus":0.07338864199117781,"score_gpt":0.3675490857390655,"score_spread":0.29416044374788763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289842561","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9793961,0.0004339645,0.0108483,0.007728763,0.00015543633,0.0011435634,0.00017436352,0.00006010226,0.000059415772],"genre_scores_gemma":[0.9992402,0.00003883529,0.00035936254,0.00020968572,0.000054692286,0.000067348934,0.000005520661,0.000006223545,0.000018102419],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919635,0.000029963858,0.00017420255,0.00018804778,0.00027764466,0.00013377052],"domain_scores_gemma":[0.9992702,0.00008406614,0.00016859353,0.0003900443,0.000030286285,0.000056779678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021216382,0.00005933725,0.00010644332,0.000012020521,0.0005379273,0.0000055110795,0.00021928597,0.0000055103396,0.0000035779913],"category_scores_gemma":[0.00009023636,0.000035662488,0.000042486947,0.00043813942,0.00041441323,0.00002410013,0.00036162563,0.00018313141,5.2126055e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006111646,0.00019598939,0.95145255,0.000036759597,0.0000050006747,0.000009323793,0.000048959857,0.0072683976,0.02480798,0.007283359,0.002748374,0.0060821786],"study_design_scores_gemma":[0.0001434896,0.00013601696,0.97330105,0.000064082255,0.000115923045,0.000023550492,0.000007939227,0.015807,0.0017195628,0.0016265169,0.006993083,0.000061764076],"about_ca_topic_score_codex":0.0000041482344,"about_ca_topic_score_gemma":1.9234398e-7,"teacher_disagreement_score":0.023088418,"about_ca_system_score_codex":0.000006009221,"about_ca_system_score_gemma":0.00004789748,"threshold_uncertainty_score":0.41373563},"labels":[],"label_agreement":null},{"id":"W4289929478","doi":"10.1016/j.wneu.2022.07.110","title":"The Central Sulcus of the Insula: A Highly Reliable Radiographic Landmark for Identification of the Rolandic Sulcus","year":2022,"lang":"en","type":"article","venue":"World Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Medicine; Sulcus; Sagittal plane; Anatomy; Radiography; Central sulcus; Magnetic resonance imaging; Nuclear medicine; Landmark; Radiology; Motor cortex; Cartography","score_opus":0.027592499231980566,"score_gpt":0.2773337247215422,"score_spread":0.24974122548956165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4289929478","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.971221,0.000631199,0.0003439145,0.023654643,0.0012572999,0.002210725,0.0002300237,0.00012029495,0.0003308798],"genre_scores_gemma":[0.99700767,0.00015381127,0.00004982676,0.00053274655,0.00005038031,0.00033671365,0.000011128906,0.000026582855,0.0018311663],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986826,0.00010005764,0.0004647974,0.00022045402,0.00030135066,0.00023071503],"domain_scores_gemma":[0.9981618,0.0004360097,0.00042625674,0.0008773642,0.00006342191,0.000035162193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004000358,0.00010348147,0.00018982789,0.00010414261,0.0005768891,0.000012906048,0.00035740598,0.00001556683,0.000005501547],"category_scores_gemma":[0.00016853416,0.00005753716,0.00029722537,0.0012489137,0.00019006715,0.000029498,0.00014506435,0.00025641022,2.0795065e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001068319,0.00075419137,0.5610909,0.00022841984,0.00008491003,0.00000609479,0.0001945439,0.0007263309,0.29563934,0.025028083,0.11126772,0.0039111623],"study_design_scores_gemma":[0.0006480059,0.0000802686,0.48693788,0.000051384202,0.00014053789,0.000047020225,0.000025464844,0.0006256804,0.05698879,0.0044818236,0.4498477,0.0001254617],"about_ca_topic_score_codex":0.000027586128,"about_ca_topic_score_gemma":0.000008424402,"teacher_disagreement_score":0.33857995,"about_ca_system_score_codex":0.000029475901,"about_ca_system_score_gemma":0.00007310958,"threshold_uncertainty_score":0.44370225},"labels":[],"label_agreement":null},{"id":"W4290098649","doi":"10.21203/rs.3.rs-1922630/v1","title":"Fast sensorimotor learning in middle-aged adults","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Psychology; Neuroplasticity; Fractional anisotropy; Cognition; Cognitive training; Effects of sleep deprivation on cognitive performance; Diffusion MRI; Physical medicine and rehabilitation; Audiology; Neuroscience; Cognitive psychology; Developmental psychology; Medicine","score_opus":0.20696149849299145,"score_gpt":0.4705725445906173,"score_spread":0.26361104609762587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290098649","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97187245,0.00077070727,0.0010816708,0.0066224528,0.00012315418,0.0054751527,0.00014217958,0.0010193621,0.012892852],"genre_scores_gemma":[0.9839338,0.00096264033,0.0057512615,0.00009887794,0.00024340326,0.0020268327,0.00046735443,0.000108366854,0.00640746],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968233,0.00042917504,0.0003338841,0.0008321671,0.0009796523,0.00060182135],"domain_scores_gemma":[0.99824125,0.0003089704,0.00008668932,0.0009333422,0.00024184916,0.00018791191],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0009389747,0.0002149939,0.00038091405,0.0006606003,0.00027329868,0.000040901035,0.0003380871,0.00016871562,0.0004985227],"category_scores_gemma":[0.0007094522,0.00022410041,0.00014393707,0.00068731146,0.000120235636,0.000032885444,0.0015744064,0.006501001,0.00004388882],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050570155,0.005632819,0.7215152,0.027777037,0.00023542598,0.0073654642,0.0114978235,0.014050181,0.023134945,0.0052080057,0.030550959,0.14797513],"study_design_scores_gemma":[0.0064534303,0.0030557388,0.47006077,0.015071006,0.00007883962,0.00022408215,0.010027104,0.02104767,0.0047441334,0.009737178,0.4575022,0.0019978585],"about_ca_topic_score_codex":0.00027217154,"about_ca_topic_score_gemma":0.000018455103,"teacher_disagreement_score":0.42695123,"about_ca_system_score_codex":0.00052729476,"about_ca_system_score_gemma":0.0003266982,"threshold_uncertainty_score":0.995791},"labels":[],"label_agreement":null},{"id":"W4290633165","doi":"10.1002/hbm.26018","title":"Automated slice‐specific z‐shimming for functional magnetic resonance imaging of the human spinal cord","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; Medical Research Council; Horizon 2020 Framework Programme; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Medical Research Council Canada; FP7 Ideas: European Research Council; Wellcome Trust","keywords":"Spinal cord; Magnetic resonance imaging; Functional magnetic resonance imaging; Nuclear magnetic resonance; Neuroscience; Medicine; Physics; Psychology; Radiology","score_opus":0.10556802429438292,"score_gpt":0.3559360423848104,"score_spread":0.2503680180904275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290633165","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9014122,0.0035181679,0.061854675,0.020298384,0.000526513,0.0047353143,0.00012970938,0.0025591129,0.0049659247],"genre_scores_gemma":[0.9917284,0.000002306465,0.004701343,0.00141513,0.00014025753,0.0004266344,0.00004444099,0.00004151264,0.0014999472],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987691,0.00004518079,0.0003391031,0.0003400462,0.00026470196,0.00024187898],"domain_scores_gemma":[0.9991675,0.00007391789,0.00017763655,0.0004642612,0.00007851311,0.00003817457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002760462,0.00013200719,0.00018591262,0.00012212916,0.0012590375,0.00001625645,0.00022850095,0.00001700132,0.00014596665],"category_scores_gemma":[0.000038440547,0.00012653254,0.00013060324,0.0003421168,0.00013801025,0.00004454366,0.0001964593,0.00027489176,0.0000012992675],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000101976584,0.00014364328,0.008601989,0.00011488497,0.0000074156574,0.0000072919506,0.000167912,0.00004557277,0.8841141,0.04450341,0.053001795,0.009190022],"study_design_scores_gemma":[0.001100109,0.00032852887,0.49354294,0.00019194909,0.00002394274,0.000115411895,0.00034834968,0.0025305096,0.00092339964,0.006012381,0.49467644,0.00020603111],"about_ca_topic_score_codex":0.000007839417,"about_ca_topic_score_gemma":8.4091783e-7,"teacher_disagreement_score":0.8831907,"about_ca_system_score_codex":0.00010829611,"about_ca_system_score_gemma":0.00003252772,"threshold_uncertainty_score":0.96836257},"labels":[],"label_agreement":null},{"id":"W4290793146","doi":"10.1016/j.neuroimage.2022.119553","title":"Mapping the subcortical connectome using in vivo diffusion MRI: Feasibility and reliability","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health; NIH Blueprint for Neuroscience Research; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Tractography; Connectome; Human Connectome Project; Diffusion MRI; Neuroscience; Thalamus; Connectomics; Reliability (semiconductor); Computer science; Psychology; Artificial intelligence; Magnetic resonance imaging; Functional connectivity; Medicine; Physics; Radiology","score_opus":0.11618284452136339,"score_gpt":0.3562926542491656,"score_spread":0.24010980972780221,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4290793146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99183923,0.00006457146,0.00265918,0.004170444,0.00003878858,0.0007725809,0.00001568481,0.00012345825,0.00031608096],"genre_scores_gemma":[0.99577814,0.00004383341,0.0027969487,0.0012295574,0.000023149361,0.00006114063,0.0000024090223,0.00001872259,0.000046107227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988004,0.00013152021,0.00023730405,0.00043060875,0.0001981402,0.00020201081],"domain_scores_gemma":[0.99910665,0.00018247508,0.0000529487,0.00056820887,0.000025002888,0.00006474175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032217964,0.000106473315,0.00017515586,0.00006526058,0.00029042715,0.000014492168,0.000110579764,0.000019268273,0.00009133654],"category_scores_gemma":[0.00019650267,0.000085075444,0.000046936733,0.00037752697,0.0001653954,0.00005290094,0.00035488003,0.0004992424,7.3657185e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017231554,0.0005602418,0.62013054,0.00007344643,0.000002363977,0.00014200124,0.00029539457,0.00014329684,0.37616765,0.0007766315,0.0005351629,0.0010009736],"study_design_scores_gemma":[0.0013114566,0.00023600896,0.93212664,0.000025716206,0.000027897371,0.000539938,0.0002879672,0.038040616,0.0025981627,0.0045625414,0.020019693,0.00022334643],"about_ca_topic_score_codex":0.00005251922,"about_ca_topic_score_gemma":0.0000017994357,"teacher_disagreement_score":0.3735695,"about_ca_system_score_codex":0.000110348636,"about_ca_system_score_gemma":0.000032008043,"threshold_uncertainty_score":0.34692758},"labels":[],"label_agreement":null},{"id":"W4291002081","doi":"10.9734/indj/2022/v17i430208","title":"Early Detection of White Matter Changes with Cognitive Decline in Parkinson's Patients","year":2022,"lang":"en","type":"article","venue":"International Neuropsychiatric Disease Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Cingulum (brain); White matter; Diffusion MRI; Cognitive decline; Psychology; Dementia; Parkinson's disease; Cognition; Medicine; Audiology; Atrophy; Neuroscience; Disease; Fractional anisotropy; Internal medicine; Magnetic resonance imaging; Radiology","score_opus":0.014975402961141188,"score_gpt":0.2894924931585816,"score_spread":0.2745170901974404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4291002081","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99112225,0.000040640498,0.001988206,0.0058344984,0.0002471763,0.00026776342,0.000087502885,0.000022573187,0.00038936775],"genre_scores_gemma":[0.99712044,0.000047237016,0.00055473606,0.0018559231,0.00013517821,0.000066515044,0.00002330974,0.000023923545,0.00017272822],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989556,0.000048812926,0.00020803687,0.00018451961,0.0004857342,0.00011728292],"domain_scores_gemma":[0.99931943,0.000027752996,0.0002471923,0.00009848703,0.00019156541,0.00011556159],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006786956,0.00009679421,0.00011248416,0.00038578105,0.00012995863,0.000013602271,0.00013549245,0.000009253507,0.00020346855],"category_scores_gemma":[0.00002826282,0.00008616097,0.000058408103,0.00033604068,0.000029716899,0.000081537924,0.0001167423,0.00034026167,0.0000034635455],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015667,0.0006512359,0.99478006,0.0000085416605,0.000017220196,0.000066555454,0.00003883254,0.0000765397,0.000096199736,0.000017615555,0.00019353404,0.0024869523],"study_design_scores_gemma":[0.001865642,0.00046421983,0.9900651,0.00003278136,0.000051214087,0.00013591375,0.00002348571,0.00019705419,0.000028282191,0.00031977656,0.006738771,0.00007777644],"about_ca_topic_score_codex":0.0000063203474,"about_ca_topic_score_gemma":0.0000034274199,"teacher_disagreement_score":0.0065452373,"about_ca_system_score_codex":0.000056658107,"about_ca_system_score_gemma":0.00005014551,"threshold_uncertainty_score":0.35135424},"labels":[],"label_agreement":null},{"id":"W4292014087","doi":"10.1159/000526000","title":"Ablation Surgeries for Treatment-Resistant Depression: A Meta-Analysis and Systematic Review of Reported Case Series","year":2022,"lang":"en","type":"review","venue":"Stereotactic and Functional Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Adler; University of British Columbia","funders":"","keywords":"Medicine; Ablative case; Meta-analysis; Systematic review; Depression (economics); Anterior cingulate cortex; Surgery; MEDLINE; Internal medicine; Psychiatry; Cognition","score_opus":0.2617888168909946,"score_gpt":0.39205422181553734,"score_spread":0.13026540492454275,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292014087","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000126761515,0.99592286,0.00062248757,0.00013274062,0.000060654602,0.00273502,0.00041484964,0.00006278689,0.000035893132],"genre_scores_gemma":[0.0001031991,0.9942843,0.00033501253,0.00016857091,0.000026453356,0.003495983,0.0005273924,0.000044841334,0.0010142728],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99745035,0.00021165326,0.0013622515,0.00058641215,0.00024262423,0.00014667907],"domain_scores_gemma":[0.9957651,0.0019920652,0.0014221413,0.0006073722,0.0001134682,0.00009985101],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041831238,0.00038355833,0.0045701903,0.00035418815,0.00023332084,0.000024227073,0.000027518441,0.00006748158,0.0001672376],"category_scores_gemma":[0.00052219303,0.00025471675,0.001797257,0.00062376267,0.000086886546,0.00011215378,0.00005077578,0.00011602738,2.2454842e-7],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120349556,0.0001206585,0.000049610175,0.95765024,0.036188215,0.00068124116,0.000006571841,1.6348723e-7,0.0000018759682,0.00011557703,0.00021581847,0.004849662],"study_design_scores_gemma":[0.00011255671,0.00019129249,0.000013743907,0.017367102,0.66610116,0.024437567,0.000011714777,0.0000064487463,0.0000017278012,0.000042920045,0.29148,0.00023376355],"about_ca_topic_score_codex":0.000010140369,"about_ca_topic_score_gemma":0.0000013221457,"teacher_disagreement_score":0.9402832,"about_ca_system_score_codex":0.000041950592,"about_ca_system_score_gemma":0.00013475702,"threshold_uncertainty_score":0.9999905},"labels":[],"label_agreement":null},{"id":"W4292413392","doi":"10.1038/s41380-022-01731-3","title":"Cognitive deficits, clinical variables, and white matter microstructure in schizophrenia: a multisite harmonization study","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Research Foundation of Korea; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Research Foundation; Medical Research Council; University of Cincinnati; Schizophrenia Research Fund; National Alliance for Research on Schizophrenia and Depression; U.S. Department of Veterans Affairs; Brain and Behavior Research Foundation; National Science Foundation","keywords":"Schizophrenia (object-oriented programming); Cognition; Psychology; Working memory; Mediation; Effects of sleep deprivation on cognitive performance; White matter; Fractional anisotropy; Verbal memory; Clinical psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.02501691172374539,"score_gpt":0.34480780221093577,"score_spread":0.3197908904871904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292413392","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775797,0.0004558106,0.0183899,0.0020216275,0.00011940845,0.001151394,0.000044686643,0.00007829247,0.00015915254],"genre_scores_gemma":[0.96598506,0.000016744927,0.029847702,0.0037672394,0.000035292396,0.0001703133,0.000076943186,0.000039187897,0.0000615162],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988034,0.00012465019,0.00030855942,0.00045823256,0.00014936786,0.00015581757],"domain_scores_gemma":[0.9995264,0.000020201956,0.00008697638,0.00026493246,0.000037611688,0.00006388905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015789858,0.00013691884,0.00021345956,0.00011666288,0.00013371833,0.00001792861,0.00007583047,0.000038266044,0.00007767619],"category_scores_gemma":[0.000019438849,0.00014440116,0.00004749479,0.00036020306,0.000040573763,0.000031904703,0.00015609838,0.00052878086,0.0000050025387],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024190736,0.00061659917,0.9961537,0.000019985453,0.000023784094,0.0000639784,0.000088805224,0.000022912427,0.0010003329,0.0002038489,0.0007746628,0.00078949746],"study_design_scores_gemma":[0.0043883855,0.00036371237,0.9914531,0.000045787012,0.00013206464,0.00026481345,0.00048717897,0.0003510697,0.000073318515,0.001604811,0.0006364506,0.00019931323],"about_ca_topic_score_codex":0.0000144510395,"about_ca_topic_score_gemma":0.000007526225,"teacher_disagreement_score":0.011594668,"about_ca_system_score_codex":0.000022915245,"about_ca_system_score_gemma":0.000045420136,"threshold_uncertainty_score":0.5888508},"labels":[],"label_agreement":null},{"id":"W4292566611","doi":"10.3389/fnhum.2022.965602","title":"Multimodal brain features at 3 years of age and their relationship with pre-reading measures 1 year later","year":2022,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Psychology; White matter; Diffusion MRI; Uncinate fasciculus; Default mode network; Reading (process); Superior longitudinal fasciculus; Functional connectivity; Developmental psychology; Association (psychology); Neuroscience; Audiology; Cognitive psychology; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.04279008716357276,"score_gpt":0.3086494361133311,"score_spread":0.2658593489497584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292566611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9914785,0.000050281433,0.00731324,0.00038297995,0.000049032373,0.0003449581,0.000014032544,0.00005685703,0.00031009232],"genre_scores_gemma":[0.9923919,0.0000059212384,0.0062303827,0.00024176716,0.0000073197616,0.00004399739,0.000003837619,0.000013383573,0.001061527],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930865,0.000039310322,0.00010701121,0.00026381106,0.0001534707,0.00012775304],"domain_scores_gemma":[0.99963814,0.00003707552,0.000057947633,0.0002177033,0.00000984691,0.00003931575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001296257,0.00007035848,0.00012196425,0.0001365347,0.0001910141,0.000009288851,0.0001228708,0.00001472355,0.0000028946856],"category_scores_gemma":[0.000067832865,0.00006170134,0.000018789655,0.0002490204,0.0002629157,0.000057020956,0.000114317976,0.00021746267,3.4655617e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012681654,0.000111789064,0.8798167,0.00002295132,0.0000023974926,0.000066903005,0.001750771,0.0018569244,0.10745084,0.0010856322,0.0060833604,0.0016248722],"study_design_scores_gemma":[0.0004094718,0.00020133264,0.9901988,0.000021104663,0.000004870666,0.000052448122,0.00010974446,0.0010018868,0.0023902352,0.0016467848,0.0038746218,0.000088683206],"about_ca_topic_score_codex":0.000010463752,"about_ca_topic_score_gemma":0.0000025788675,"teacher_disagreement_score":0.11038208,"about_ca_system_score_codex":0.00004432391,"about_ca_system_score_gemma":0.000013195885,"threshold_uncertainty_score":0.25161076},"labels":[],"label_agreement":null},{"id":"W4292623168","doi":"10.1101/2022.08.20.22279023","title":"Brain microstructural changes and fatigue after COVID-19","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Corpus callosum; Medicine; White matter; Diffusion MRI; Fractional anisotropy; Fornix; Magnetic resonance imaging; Internal medicine; Inferior longitudinal fasciculus; Neuropsychology; Cardiology; Audiology; Cognition; Pathology; Psychiatry; Radiology","score_opus":0.11186541563252606,"score_gpt":0.40289117827494497,"score_spread":0.2910257626424189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292623168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9016062,0.0011625267,0.0042991717,0.09069566,0.0001641879,0.0010781575,0.0002548044,0.00045100247,0.00028830522],"genre_scores_gemma":[0.95667905,0.0005002787,0.015488903,0.02366205,0.000217753,0.0012558457,0.00025867933,0.000072354946,0.0018650751],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99889463,0.000042001364,0.00016219263,0.00055230275,0.00015867213,0.00019018968],"domain_scores_gemma":[0.9989592,0.000081054015,0.000101528014,0.00061891065,0.000024733978,0.0002145646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012527479,0.00021418776,0.0002862779,0.00011555437,0.00010780072,0.000023807668,0.000151708,0.000092913084,0.00046276674],"category_scores_gemma":[0.0001590361,0.00019819564,0.00006450441,0.00009611412,0.00013590873,0.000014976418,0.00080137147,0.0006623394,0.0000020759257],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073028007,0.00026806133,0.7963324,0.0050498545,0.0002281094,0.0018400995,0.0035337927,0.00008719315,0.09082578,0.003202925,0.060161714,0.037739795],"study_design_scores_gemma":[0.00070136343,0.00013905158,0.12100418,0.00011290727,0.00012510357,0.00039830364,0.00008304596,0.00019850692,0.0030385226,0.011153011,0.86251855,0.0005274467],"about_ca_topic_score_codex":0.000040319886,"about_ca_topic_score_gemma":0.000012938072,"teacher_disagreement_score":0.80235684,"about_ca_system_score_codex":0.00009012155,"about_ca_system_score_gemma":0.000089671244,"threshold_uncertainty_score":0.8082184},"labels":[],"label_agreement":null},{"id":"W4292641174","doi":"10.48550/arxiv.1504.01800","title":"A Multicomponent Approach to Nonrigid Registration of Diffusion Tensor\\n Images","year":2015,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Affine transformation; Diffusion MRI; Structure tensor; Tensor (intrinsic definition); Distortion (music); Image registration; Computer vision; Mutual information; Diffusion; Orientation (vector space); Artificial intelligence; Computer science; Mathematics; Image (mathematics); Geometry; Physics; Medicine","score_opus":0.22305616961517938,"score_gpt":0.27127235530929783,"score_spread":0.04821618569411845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292641174","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37909463,0.00006512324,0.6063606,0.00038708217,0.00012915816,0.0022001055,0.000097624135,0.0002265392,0.011439126],"genre_scores_gemma":[0.97260046,0.00067288463,0.022221768,0.00012048834,0.00013358243,0.000012624768,0.0001455087,0.00006615255,0.0040265424],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99676794,0.00014428633,0.00067125197,0.0016918643,0.00024800052,0.00047664106],"domain_scores_gemma":[0.99564844,0.000101524776,0.00078132364,0.0020881407,0.00079535716,0.00058521336],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039439474,0.0005778754,0.00087621267,0.0004433437,0.00017148933,0.000029152088,0.00077927666,0.00034126113,0.000023204559],"category_scores_gemma":[0.0001726389,0.00063858874,0.0003267214,0.00078836526,0.00029183208,0.00016226787,0.0010414025,0.00082109106,0.000059005644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005684666,0.019167794,0.038527057,0.00435464,0.0008286362,0.0007282051,0.00297122,0.45524076,0.2644282,0.18368441,0.016705468,0.007678938],"study_design_scores_gemma":[0.0072868117,0.0015148609,0.030135814,0.0024602828,0.0025137742,0.00012533624,0.0020763206,0.8846919,0.01600436,0.030121816,0.02016867,0.00290003],"about_ca_topic_score_codex":0.00034872815,"about_ca_topic_score_gemma":0.000003840019,"teacher_disagreement_score":0.5935058,"about_ca_system_score_codex":0.00046316243,"about_ca_system_score_gemma":0.00026692843,"threshold_uncertainty_score":0.99960655},"labels":[],"label_agreement":null},{"id":"W4292641265","doi":"10.1007/s00429-022-02551-5","title":"The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography","year":2022,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Angular gyrus; Neuroscience; Microdissection; Tractography; Diffusion MRI; Anatomy; Psychology; Brainstem; Posterior parietal cortex; Biology; Medicine; Functional magnetic resonance imaging; Magnetic resonance imaging","score_opus":0.011173589145117246,"score_gpt":0.2782518399114742,"score_spread":0.26707825076635694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292641265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99584746,0.00040776137,0.00026863712,0.002867389,0.00009249751,0.0003923387,0.000035584202,0.00003771667,0.000050591196],"genre_scores_gemma":[0.99906206,0.00002600309,0.000056635574,0.0006251709,0.000039916325,0.000021041811,0.000028856735,0.000009469598,0.00013083234],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994324,0.00006110938,0.00011531011,0.00018497914,0.00012241103,0.000083783765],"domain_scores_gemma":[0.9995736,0.00006528642,0.000105092404,0.00020261461,0.000025601097,0.000027803328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079862846,0.00008528122,0.00009929322,0.000030305191,0.00096818124,0.000013153095,0.000045039516,0.000031951957,0.000018452081],"category_scores_gemma":[0.000029525921,0.000051561707,0.0000436583,0.00017879259,0.00012521104,0.000034835994,0.000060242437,0.00024057094,1.9033669e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012449511,0.000014745267,0.04751324,0.00001862046,0.000016629761,4.1288385e-7,0.00012878732,0.0000017558683,0.92878056,0.0017571849,0.0035840846,0.018059483],"study_design_scores_gemma":[0.0006887038,0.0003511271,0.91604435,0.000010205287,0.0000787071,0.00025271415,0.00028086026,0.0000712957,0.0132655315,0.026514148,0.04234242,0.00009990837],"about_ca_topic_score_codex":0.000057131474,"about_ca_topic_score_gemma":0.000009291407,"teacher_disagreement_score":0.915515,"about_ca_system_score_codex":0.0000147408355,"about_ca_system_score_gemma":0.0000066317866,"threshold_uncertainty_score":0.7446565},"labels":[],"label_agreement":null},{"id":"W4292801117","doi":"10.1101/2022.08.20.504656","title":"Is adiposity associated with white-matter microstructural health and intelligence differently in men and women?","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Obesity; Medicine; Cardiovascular health; Association (psychology); Physiology; Internal medicine; Psychology; Disease; Magnetic resonance imaging","score_opus":0.027059186536733584,"score_gpt":0.28264055320521936,"score_spread":0.2555813666684858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292801117","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995151,0.0006221868,0.0006422081,0.0020814368,0.00004127919,0.0010323714,0.00022584185,0.00019630847,0.000007373998],"genre_scores_gemma":[0.99260896,0.00039505246,0.004510114,0.002037195,0.000026608895,0.00033644823,0.0000016179508,0.000071958304,0.000012023432],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99809945,0.000077531666,0.00035714125,0.0008336366,0.00020592666,0.00042631986],"domain_scores_gemma":[0.99865943,0.000040331022,0.00029061627,0.00063032453,0.00007656397,0.0003027338],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018603375,0.00035740188,0.00056901475,0.00018896598,0.00015968073,0.00007260717,0.0001714182,0.00013189435,0.000057154128],"category_scores_gemma":[0.000039480674,0.00033916597,0.000031698513,0.00033072373,0.00015357383,0.000062923296,0.00049483386,0.00091076165,0.0000011840767],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009750339,0.000142458,0.970393,0.00040186755,0.00008019308,0.00003050415,0.000250076,0.0000028281195,0.028309107,0.00006710128,0.00021556701,0.000009803931],"study_design_scores_gemma":[0.00043993798,0.00018652067,0.98970103,0.0004248286,0.00004114085,2.0556048e-7,0.000029429399,0.00019000359,0.008284853,0.00001657131,0.00030617582,0.00037931104],"about_ca_topic_score_codex":0.00004951106,"about_ca_topic_score_gemma":0.0000017142161,"teacher_disagreement_score":0.020024253,"about_ca_system_score_codex":0.00042212798,"about_ca_system_score_gemma":0.00023483564,"threshold_uncertainty_score":0.99990606},"labels":[],"label_agreement":null},{"id":"W4293085811","doi":"10.32920/19400750","title":"Rapid microscopic fractional anisotropy imaging via an optimized linear regression formulation","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; Anisotropy; Orientation (vector space); Metric (unit); Linear regression; Diffusion; Tensor (intrinsic definition); Dispersion (optics); SIGNAL (programming language); Diffusion imaging; Biological system; Anisotropic diffusion; Nuclear magnetic resonance; Materials science; Physics; Statistical physics; Mathematics; Optics; Computer science; Statistics; Magnetic resonance imaging; Geometry; Medicine; Radiology; Biology","score_opus":0.07503130547690681,"score_gpt":0.4057850943838871,"score_spread":0.33075378890698026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293085811","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01787352,0.0002722115,0.9729532,0.003734846,0.00031279947,0.0014491365,0.000050826646,0.001153522,0.0021999637],"genre_scores_gemma":[0.1320932,0.00046192936,0.8608696,0.0015601018,0.0004024446,0.0004584348,0.002698698,0.00010354057,0.001352069],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982979,0.00005240051,0.00039969722,0.00070051115,0.00032522963,0.00022424465],"domain_scores_gemma":[0.9985175,0.000045486016,0.0002826128,0.00088739034,0.00013341336,0.00013356577],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00014083233,0.00028656094,0.00036846992,0.00019162451,0.00029295255,0.000032940752,0.00019596236,0.000114882896,0.0020823139],"category_scores_gemma":[0.000027622838,0.000258841,0.00016591887,0.00013232302,0.00003978905,0.00015919776,0.0004977488,0.0010103079,0.0000114991335],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035610688,0.004985496,0.0284839,0.0014266052,0.00033783985,0.00031632875,0.0006249129,0.032832157,0.65958655,0.013211405,0.035233125,0.2194006],"study_design_scores_gemma":[0.0039656283,0.00039183986,0.00896095,0.0004500899,0.0003770874,0.00035253138,0.00012192623,0.7317355,0.038671043,0.027178137,0.18661481,0.0011804212],"about_ca_topic_score_codex":0.00005296781,"about_ca_topic_score_gemma":4.053437e-7,"teacher_disagreement_score":0.6989034,"about_ca_system_score_codex":0.00021824864,"about_ca_system_score_gemma":0.00012979265,"threshold_uncertainty_score":0.9999864},"labels":[],"label_agreement":null},{"id":"W4293228443","doi":"10.3917/pls.533.0062","title":"Matière noire : la piste de la gravité modifiée passe un test crucial","year":2022,"lang":"fr","type":"article","venue":"Pour la Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Political science","score_opus":0.02845197219609951,"score_gpt":0.3509279306608677,"score_spread":0.3224759584647682,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293228443","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3454068,0.004452613,0.20448558,0.17520525,0.0015241606,0.0024609263,0.0008359294,0.0015836182,0.26404515],"genre_scores_gemma":[0.95122,0.00017441818,0.037185427,0.00093504624,0.0002588051,0.00019275883,0.0000038012522,0.00003355442,0.009996235],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979641,0.00021689611,0.00023036111,0.0005286873,0.00050979975,0.0005501998],"domain_scores_gemma":[0.99815094,0.0008710166,0.00012335024,0.0005250813,0.0000808511,0.00024876403],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014707164,0.00017573881,0.00018571677,0.00012706575,0.0008930413,0.00010776149,0.0007106638,0.00005322925,0.00020201966],"category_scores_gemma":[0.0007074346,0.00018714664,0.000068920745,0.001078611,0.0015834982,0.0001647072,0.00050450896,0.0006606599,0.00004215914],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034555782,0.0013886779,0.014430153,0.00015016783,0.000010103779,0.00084378186,0.0025019618,0.0008864469,0.25021023,0.5540937,0.009953991,0.16549619],"study_design_scores_gemma":[0.0010929798,0.00022124885,0.04478509,0.00031328836,0.00012806158,0.0032651576,0.00079237577,0.043790445,0.019535538,0.13439085,0.7510491,0.0006358725],"about_ca_topic_score_codex":0.00010571465,"about_ca_topic_score_gemma":0.000002278362,"teacher_disagreement_score":0.7410951,"about_ca_system_score_codex":0.00029843635,"about_ca_system_score_gemma":0.00066974055,"threshold_uncertainty_score":0.76316184},"labels":[],"label_agreement":null},{"id":"W4293516794","doi":"10.1016/j.neuro.2022.08.010","title":"Impact of chronic exposure to legacy environmental contaminants on the corpus callosum microstructure: A diffusion MRI study of Inuit adolescents","year":2022,"lang":"en","type":"article","venue":"NeuroToxicology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université Laval; Centre hospitalier de l'Université Laval; Université du Québec à Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"National Institute of Environmental Health Sciences; Canadian Institutes of Health Research","keywords":"Corpus callosum; Fractional anisotropy; White matter; Diffusion MRI; Methylmercury; Medicine; Physiology; Population; Magnetic resonance imaging; Internal medicine; Pathology; Environmental health; Chemistry; Environmental chemistry; Bioaccumulation; Radiology","score_opus":0.02814817612175857,"score_gpt":0.3256252322540136,"score_spread":0.297477056132255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293516794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960998,0.000017268203,0.00003529625,0.00030681447,0.00006954003,0.0033395307,0.000093934264,0.00002808835,0.000009696216],"genre_scores_gemma":[0.9988077,0.000011196597,0.000024289928,0.00062656467,0.000022822323,0.00042385163,0.000006428797,0.000027397913,0.0000497226],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99882567,0.0001485405,0.00028565835,0.0003126106,0.00022771998,0.00019979758],"domain_scores_gemma":[0.999116,0.000060873055,0.00018560853,0.00055725826,0.000013414921,0.00006686328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006408157,0.00014965162,0.0002921629,0.00009466837,0.00013099043,0.0000030594363,0.0002478994,0.000034161818,0.00016616315],"category_scores_gemma":[0.000025747142,0.000108780296,0.000090721034,0.00017399564,0.00009243423,0.00001758637,0.00032180396,0.00038188917,0.0000024387632],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005042649,0.0026862817,0.16583394,0.000012240181,0.00001630795,0.0000372773,0.00043663432,0.00012906769,0.82837176,0.000024369396,0.00019660077,0.0017512403],"study_design_scores_gemma":[0.0019784796,0.02547449,0.9527824,0.000019917114,0.000040862906,0.00013467635,0.00017301463,0.00006212084,0.018566927,0.00002639217,0.0006522492,0.00008845438],"about_ca_topic_score_codex":0.00003974675,"about_ca_topic_score_gemma":0.00001791999,"teacher_disagreement_score":0.80980486,"about_ca_system_score_codex":0.000238167,"about_ca_system_score_gemma":0.00006333989,"threshold_uncertainty_score":0.44359317},"labels":[],"label_agreement":null},{"id":"W4293660702","doi":"10.1016/j.nicl.2022.103174","title":"Exploring biomarkers of processing speed and executive function: The role of the anterior thalamic radiations","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Vancouver Coastal Health; University of British Columbia","funders":"Canadian Institutes of Health Research; University of British Columbia","keywords":"Diffusion MRI; Executive dysfunction; White matter; Hyperintensity; Stroke (engine); Psychology; Medicine; Trail Making Test; Superior longitudinal fasciculus; Lesion; Cognition; Neuroscience; Physical medicine and rehabilitation; Fractional anisotropy; Magnetic resonance imaging; Pathology; Cognitive impairment; Neuropsychology; Radiology","score_opus":0.18443924449726584,"score_gpt":0.38463418022909,"score_spread":0.20019493573182418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293660702","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99440414,0.0003171226,0.0004000096,0.0032520404,0.00011660696,0.00052174507,0.000020978232,0.000054202388,0.00091314234],"genre_scores_gemma":[0.998726,0.00015183119,0.0005272936,0.0004183809,0.000048366073,0.000053487747,0.0000018474947,0.000016329725,0.000056454468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989746,0.00012323038,0.0003982066,0.00023145831,0.0001750684,0.000097425895],"domain_scores_gemma":[0.99900186,0.00026081855,0.00024814723,0.0004017561,0.000054607506,0.000032794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002842695,0.00007691671,0.00018776754,0.000038772134,0.00023796588,0.000006375914,0.00015307296,0.000014787958,0.000013018775],"category_scores_gemma":[0.00021730701,0.00005058503,0.000117334195,0.0003191789,0.00036338592,0.0000711784,0.00023292765,0.000343199,2.9979253e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009924764,0.0012204158,0.46449357,0.00015281199,0.0001283062,0.00001896388,0.0011451517,0.000068425645,0.29979172,0.0019643116,0.0010173975,0.22900644],"study_design_scores_gemma":[0.00093593507,0.00054687297,0.96540487,0.00007740277,0.00022621102,0.00015019733,0.001310514,0.0040435595,0.0076917442,0.0014977994,0.018003738,0.00011118081],"about_ca_topic_score_codex":0.0000054666193,"about_ca_topic_score_gemma":2.754852e-7,"teacher_disagreement_score":0.5009113,"about_ca_system_score_codex":0.00001074817,"about_ca_system_score_gemma":0.00005811279,"threshold_uncertainty_score":0.20627975},"labels":[],"label_agreement":null},{"id":"W4294189365","doi":"10.1192/j.eurpsy.2022.429","title":"A multicentric multimodal in vivo microscopy MRI study of bipolar disorder reveals axonal loss and demyelination","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto; Ontario Brain Institute","funders":"","keywords":"Cingulum (brain); White matter; Corpus callosum; Splenium; Uncinate fasciculus; Inferior longitudinal fasciculus; Magnetic resonance imaging; Tractography; Arcuate fasciculus; Myelin; Medicine; Superior longitudinal fasciculus; Anatomy; Fornix; Neuroscience; Pathology; Fractional anisotropy; Psychology; Central nervous system; Radiology; Hippocampus","score_opus":0.019438719799737627,"score_gpt":0.3273875229278142,"score_spread":0.3079488031280766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294189365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99509716,0.0012264007,0.0014370495,0.0010087644,0.000092842245,0.0008316725,0.000030606177,0.00006893159,0.00020656563],"genre_scores_gemma":[0.9817559,0.000066697794,0.017605977,0.0003118409,0.000049726626,0.000040468905,0.000008539653,0.000035428067,0.00012540695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989052,0.0001691274,0.00031613783,0.00030271648,0.00016838739,0.00013844926],"domain_scores_gemma":[0.999497,0.000027746471,0.00012763952,0.0002687513,0.00002899996,0.000049873852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025356372,0.000107738204,0.00016155199,0.00017737284,0.00012243148,0.0000055884225,0.00010953394,0.00001077737,0.000043936212],"category_scores_gemma":[0.000021674408,0.00011078176,0.00003140341,0.0003732627,0.000037347327,0.000038359547,0.00015098036,0.0002608225,0.0000024832902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013669924,0.0024654863,0.9862743,0.000055858804,0.000012965848,0.000019612273,0.0009755639,0.00014008397,0.00685047,0.00021925691,0.0007787375,0.0020709673],"study_design_scores_gemma":[0.0069999266,0.0011780303,0.9570133,0.00011116718,0.00009230723,0.00010559876,0.0028068568,0.0022093693,0.00019678302,0.00037836705,0.028612502,0.00029576974],"about_ca_topic_score_codex":0.00002719052,"about_ca_topic_score_gemma":0.000008142472,"teacher_disagreement_score":0.029260976,"about_ca_system_score_codex":0.000026076372,"about_ca_system_score_gemma":0.00002114329,"threshold_uncertainty_score":0.4517549},"labels":[],"label_agreement":null},{"id":"W4294199809","doi":"10.1192/j.eurpsy.2022.251","title":"White matter microstructure associated with the range of attentional and impulsive performance in school-aged children","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"","keywords":"Impulsivity; Psychology; Neurocognitive; White matter; Endophenotype; Neuroimaging; Cognition; Neuroscience; Developmental psychology; Magnetic resonance imaging; Medicine","score_opus":0.009093180430131595,"score_gpt":0.24474063660160772,"score_spread":0.23564745617147612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294199809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99294496,0.00019228294,0.000046323177,0.0051005627,0.000028365472,0.0003011441,0.000050660637,0.00003137542,0.0013043403],"genre_scores_gemma":[0.9960113,0.000008855675,0.0012638508,0.0021194704,0.00004090922,0.000015273994,0.000047011552,0.000025961644,0.00046736404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939126,0.00008480645,0.00013002912,0.00017341391,0.000117767086,0.00010275129],"domain_scores_gemma":[0.9996355,0.000008992985,0.00010451317,0.00020297765,0.000019049708,0.000028973402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001425515,0.00008238272,0.00009912477,0.000050642637,0.00014159366,0.0000063102075,0.00010354684,0.0000084233025,0.00012924711],"category_scores_gemma":[0.000003863032,0.00005804997,0.00002716916,0.00019742978,0.00006926142,0.000030373962,0.000085458225,0.00035821344,0.000003859472],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005547939,0.000046827532,0.99388695,0.000008961209,0.000013383614,0.0000017769432,0.00010833043,0.00001931014,0.00021006331,0.000019717643,0.0055894204,0.000039779283],"study_design_scores_gemma":[0.0008659561,0.00009803001,0.9983782,0.000057372014,0.000023241662,0.00010961814,0.00008443762,0.000010010308,0.000005204914,0.000043821696,0.0002603107,0.00006375049],"about_ca_topic_score_codex":0.0000015522679,"about_ca_topic_score_gemma":0.000002139192,"teacher_disagreement_score":0.0053291097,"about_ca_system_score_codex":0.000016888027,"about_ca_system_score_gemma":0.000021602627,"threshold_uncertainty_score":0.2367209},"labels":[],"label_agreement":null},{"id":"W4294200726","doi":"10.1192/j.eurpsy.2022.555","title":"The effect of antidepressant treatment on white matter integrity in Major Depression","year":2022,"lang":"en","type":"article","venue":"European Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Institut universitaire en santé mentale de Montréal","funders":"Pfizer Canada; Pfizer","keywords":"Fasciculus; White matter; Inferior longitudinal fasciculus; Fractional anisotropy; Uncinate fasciculus; Corpus callosum; Superior longitudinal fasciculus; Diffusion MRI; Major depressive disorder; Medicine; Medial longitudinal fasciculus; Depression (economics); Psychology; Internal medicine; Magnetic resonance imaging; Cardiology; Neuroscience; Radiology; Central nervous system","score_opus":0.021723174116192047,"score_gpt":0.3239204356339096,"score_spread":0.30219726151771753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294200726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97313493,0.0004298488,0.00016695439,0.0042363363,0.00019670554,0.00061802776,0.000017060001,0.000078011726,0.021122098],"genre_scores_gemma":[0.9977275,0.00002545432,0.0009823182,0.00040683767,0.00005290353,0.00007417695,0.0000098560795,0.000030561856,0.00069035124],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907947,0.00025983542,0.00019281547,0.00021872135,0.00012613797,0.00012303436],"domain_scores_gemma":[0.9993064,0.000063390195,0.000082078186,0.0005097333,0.000006543422,0.0000318768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002335098,0.000106075786,0.00013705959,0.000055643126,0.00015407754,0.0000057305538,0.00013798193,0.000008426043,0.00006112246],"category_scores_gemma":[0.000009125578,0.00006291769,0.00007565281,0.00013189045,0.000034270746,0.000013524815,0.00009335085,0.0003038947,0.000024949699],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040479627,0.00021224405,0.9866419,0.000019367928,0.000008857882,0.000014572482,0.000053103864,0.000032981225,0.0005684575,0.00014040056,0.0074292696,0.0044740723],"study_design_scores_gemma":[0.0020374774,0.0018038788,0.964828,0.00017515935,0.00004432798,0.000064670516,0.00007619568,0.000081085454,0.0025751912,0.0002026131,0.02799804,0.00011335898],"about_ca_topic_score_codex":0.000007999187,"about_ca_topic_score_gemma":0.0000019067031,"teacher_disagreement_score":0.024592582,"about_ca_system_score_codex":0.000037830694,"about_ca_system_score_gemma":0.000011596783,"threshold_uncertainty_score":0.25657088},"labels":[],"label_agreement":null},{"id":"W4294308349","doi":"10.3390/life12091362","title":"Associations of Peak-Width Skeletonized Mean Diffusivity and Post-Stroke Cognition","year":2022,"lang":"en","type":"article","venue":"Life","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Edinburgh Imaging; Biotechnology and Biological Sciences Research Council; College of Medicine and Veterinary Medicine, University of Edinburgh; Medical Research Council; UK Dementia Research Institute; Fondation Leducq; University of Edinburgh; Economic and Social Research Council; Stroke Association; Scottish Funding Council; Dunhill Medical Trust; Wellcome Trust; Alzheimer's Society; Edinburgh and Lothians Health Foundation; British Heart Foundation; Mrs Gladys Row Fogo Charitable Trust; Alzheimer’s Society; Wellcome","keywords":"Montreal Cognitive Assessment; Stroke (engine); Cognition; Cognitive decline; Medicine; Internal medicine; Effects of sleep deprivation on cognitive performance; Physical therapy; Psychology; Cardiology; Cognitive impairment; Dementia; Psychiatry; Disease","score_opus":0.04974978913352166,"score_gpt":0.3303395844695595,"score_spread":0.28058979533603784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294308349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98820823,0.00007813228,0.0027274764,0.00530225,0.000029164255,0.0004222821,0.00072242366,0.00016528265,0.002344773],"genre_scores_gemma":[0.99388885,0.000026767617,0.0038585274,0.0014770152,0.00003039778,0.000064924054,0.0001478209,0.0000110722585,0.0004946223],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994841,0.000029060586,0.00013433093,0.00012420952,0.00014717515,0.000081107035],"domain_scores_gemma":[0.9995632,0.00007039056,0.00009777325,0.0001434761,0.00006583901,0.00005928938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008202456,0.000051945604,0.00013682675,0.000049362017,0.00014281017,0.0000036239287,0.000036949274,0.000014876664,0.00007251798],"category_scores_gemma":[0.00014330314,0.00005413307,0.000040849467,0.00010238851,0.00003458589,0.00002770318,0.000072393246,0.00013552855,0.0000013171059],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015693592,0.0012574326,0.06954922,0.00008709076,0.00011054602,0.000011818296,0.00087698,0.000010369931,0.89956415,0.010927733,0.00443578,0.013011928],"study_design_scores_gemma":[0.004563824,0.0009232648,0.9276745,0.000037852755,0.000509878,0.00008750527,0.00059600367,0.0013364215,0.024223669,0.009124928,0.030533945,0.0003882425],"about_ca_topic_score_codex":0.000026746504,"about_ca_topic_score_gemma":0.0000024735257,"teacher_disagreement_score":0.8753405,"about_ca_system_score_codex":0.000023243601,"about_ca_system_score_gemma":0.000034421737,"threshold_uncertainty_score":0.22074826},"labels":[],"label_agreement":null},{"id":"W4294718699","doi":"10.1016/j.ynirp.2022.100126","title":"Tract-specific differences in white matter microstructure between young adult APOE ε4 carriers and non-carriers: A replication and extension study","year":2022,"lang":"en","type":"article","venue":"Neuroimage Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College","funders":"Medical Research Council; Wellcome Trust","keywords":"Fractional anisotropy; Apolipoprotein E; Cingulum (brain); White matter; Psychology; Internal medicine; Medicine; Disease","score_opus":0.036526208518974874,"score_gpt":0.3096968281929188,"score_spread":0.27317061967394396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294718699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99625766,0.00012009344,0.00025789812,0.0015308999,0.00006899309,0.0014502069,0.000024907677,0.00010345851,0.00018589995],"genre_scores_gemma":[0.997962,0.00008408625,0.00093862007,0.00043269154,0.000055861372,0.00023847242,0.000041315012,0.000045115594,0.00020183416],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978272,0.00006913306,0.0004931343,0.0010832528,0.0002940148,0.00023331228],"domain_scores_gemma":[0.9984647,0.000041670286,0.00026695553,0.0010166536,0.000075564625,0.00013444877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022126103,0.00021965768,0.00037336035,0.00017393405,0.00026657595,0.00005295546,0.000074475494,0.000045013,0.000031003878],"category_scores_gemma":[0.00006105799,0.00021010828,0.00004183387,0.00030531661,0.00010875926,0.00012671962,0.00019052855,0.0005399703,5.272156e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030427213,0.000091722206,0.9747315,0.000023538256,0.000005281491,0.0007405106,0.0007194231,8.56599e-7,0.02127229,0.0000017364275,0.0007649818,0.0016177337],"study_design_scores_gemma":[0.0004329263,0.00023873565,0.99408245,0.00002395862,0.000049070353,0.0027942106,0.00054863445,0.00004222195,0.00044436174,0.00022426128,0.0009467924,0.00017239661],"about_ca_topic_score_codex":0.00005303041,"about_ca_topic_score_gemma":0.0000042573183,"teacher_disagreement_score":0.020827929,"about_ca_system_score_codex":0.000053886648,"about_ca_system_score_gemma":0.000028366892,"threshold_uncertainty_score":0.8567967},"labels":[],"label_agreement":null},{"id":"W4294739485","doi":"10.1016/j.neuroimage.2022.119617","title":"A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research","keywords":"Brain atlas; Atlas (anatomy); Myelin; Neuroscience; Retinotopy; Neuroimaging; Cortex (anatomy); Biology; Cartography; Brain mapping; White matter; Computer science; Anatomy; Magnetic resonance imaging; Medicine; Visual cortex; Geography; Central nervous system","score_opus":0.07721935417495718,"score_gpt":0.3325616364907312,"score_spread":0.25534228231577405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294739485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5352379,0.00014467232,0.020728745,0.43816805,0.00017402961,0.0020068116,0.00006208492,0.00058180053,0.0028958954],"genre_scores_gemma":[0.95834565,0.000009756438,0.0053147385,0.03127429,0.00017967007,0.00038409804,0.000021891778,0.0000790027,0.004390883],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.998031,0.0002426054,0.0002932751,0.0005257458,0.00046077603,0.00044658908],"domain_scores_gemma":[0.99801785,0.00050304324,0.000080833124,0.0012153554,0.00004402934,0.00013888751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041403787,0.00020213789,0.00021564559,0.000065295084,0.000973525,0.000081355094,0.00059226237,0.000021037511,0.00014643041],"category_scores_gemma":[0.00031847594,0.00013416698,0.00012980646,0.0008030999,0.00017848234,0.00007092433,0.00068073475,0.0012300544,0.00013012179],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002821456,0.00053194043,0.0015443022,0.000060277565,0.000047633563,0.0004659791,0.0022136993,0.0036204157,0.68821573,0.00510695,0.26849368,0.029417261],"study_design_scores_gemma":[0.00040132823,0.0002765412,0.018555544,0.000016237953,0.00003635066,0.00046452606,0.0003011377,0.0045441203,0.0011002601,0.00032711355,0.9738066,0.00017020144],"about_ca_topic_score_codex":0.000026912749,"about_ca_topic_score_gemma":0.0000039864753,"teacher_disagreement_score":0.70531297,"about_ca_system_score_codex":0.000071162416,"about_ca_system_score_gemma":0.000084662206,"threshold_uncertainty_score":0.74876654},"labels":[],"label_agreement":null},{"id":"W4294897416","doi":"10.1089/neu.2022.0276","title":"White Matter Integrity Relates to Cognition in Service Members and Veterans after Complicated Mild, Moderate, and Severe Traumatic Brain Injury, But Not Uncomplicated Mild Traumatic Brain Injury","year":2022,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Traumatic brain injury; Fractional anisotropy; White matter; Diffusion MRI; Neuropsychology; Superior longitudinal fasciculus; Psychology; Inferior longitudinal fasciculus; Uncinate fasciculus; Cognition; Post-concussion syndrome; Medicine; Poison control; Audiology; Neuroscience; Concussion; Psychiatry; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.13366667320116277,"score_gpt":0.3737104255208235,"score_spread":0.24004375231966074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4294897416","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9304703,0.0000468449,0.00063809246,0.06741432,0.0000387053,0.0010581426,0.00016476736,0.00006670057,0.000102147766],"genre_scores_gemma":[0.96893257,0.000024382867,0.0033163477,0.027250864,0.000030683183,0.00025908317,0.00002219288,0.00006629507,0.000097576914],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9976901,0.00025266074,0.0009330913,0.0004440794,0.00035693645,0.00032313532],"domain_scores_gemma":[0.9986314,0.00025322728,0.0003345968,0.00034027096,0.00016340034,0.00027706806],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038992954,0.00031969338,0.00061845966,0.0004746198,0.00017727358,0.000066214074,0.00020949812,0.000083295236,0.00015844415],"category_scores_gemma":[0.00005123806,0.0003051126,0.00009620184,0.0006536863,0.00009459734,0.00025066105,0.00014068844,0.0013553363,0.000006781242],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.06731384,0.009322349,0.1402551,0.0068160193,0.0010423006,0.0021541377,0.04348369,0.004129188,0.5298905,0.00045117526,0.15079015,0.044351567],"study_design_scores_gemma":[0.0073908283,0.0032616304,0.94993186,0.0016146085,0.00038350114,0.007915953,0.0015660054,0.013553641,0.0052986774,0.00438178,0.0036112517,0.0010902919],"about_ca_topic_score_codex":0.00005531395,"about_ca_topic_score_gemma":0.000027777602,"teacher_disagreement_score":0.8096767,"about_ca_system_score_codex":0.00010540366,"about_ca_system_score_gemma":0.000041887954,"threshold_uncertainty_score":0.9999401},"labels":[],"label_agreement":null},{"id":"W4295129670","doi":"10.1016/j.compbiomed.2022.106078","title":"Atlas-guided parcellation: Individualized functionally-homogenous parcellation in cerebral cortex","year":2022,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Sport Centre Pacific; University of British Columbia","funders":"National Natural Science Foundation of China; Cyrus Tang Foundation","keywords":"Voxel; Artificial intelligence; Homogeneity (statistics); Pattern recognition (psychology); Functional magnetic resonance imaging; Correlation; Computer science; Resting state fMRI; Neuroimaging; Brain atlas; Functional connectivity; Default mode network; Psychology; Neuroscience; Machine learning; Mathematics","score_opus":0.07038896253105667,"score_gpt":0.3744579412408374,"score_spread":0.3040689787097808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295129670","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9681252,0.0008236645,0.015469982,0.011168259,0.0003842188,0.0008296987,0.000010935813,0.00012633378,0.0030616615],"genre_scores_gemma":[0.9900492,0.0001784639,0.0066426876,0.002438754,0.00013782567,0.000080408936,0.00033242075,0.000010602247,0.00012968322],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897563,0.0000963245,0.00032535483,0.0003250326,0.000099170014,0.00017847378],"domain_scores_gemma":[0.9994969,0.00015458003,0.00008796103,0.00017637208,0.000023381945,0.00006079937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028948023,0.0001135282,0.0002780404,0.0002465168,0.00012599892,0.0000019006468,0.00007577165,0.000054113418,0.00016917467],"category_scores_gemma":[0.00002881819,0.00010237407,0.000021781541,0.00032179465,0.00018183723,0.000020158735,0.0001129019,0.00030916824,0.0000014494924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034411065,0.00026732378,0.93197757,0.00004951514,0.000029644978,0.00008293263,0.0010339187,0.00030598338,0.00760687,0.02159439,0.0068138265,0.029893907],"study_design_scores_gemma":[0.006733656,0.0010605991,0.85319906,0.00009756864,0.000040098486,0.000616821,0.00020657586,0.0072175064,0.00008853537,0.03195656,0.09854606,0.00023696161],"about_ca_topic_score_codex":0.000048356116,"about_ca_topic_score_gemma":0.000007632742,"teacher_disagreement_score":0.091732234,"about_ca_system_score_codex":0.00007711338,"about_ca_system_score_gemma":0.00003648239,"threshold_uncertainty_score":0.41746935},"labels":[],"label_agreement":null},{"id":"W4295367041","doi":"10.1002/hbm.26064","title":"<scp>Test–retest</scp> reliability of diffusion tensor imaging scalars in 5‐year‐olds","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Varsinais-Suomen Rahasto; Varsinais-Suomen Sairaanhoitopiiri; Suomen Aivosäätiö; Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Juho Vainion Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Sigrid Juséliuksen Säätiö; Suomen Lääketieteen Säätiö","keywords":"Fractional anisotropy; Diffusion MRI; Repeatability; Intraclass correlation; Psychology; Reliability (semiconductor); Population; Statistics; Mathematics; Nuclear medicine; Reproducibility; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.04213064672382869,"score_gpt":0.3199502017890604,"score_spread":0.2778195550652317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295367041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890022,0.000059432557,0.0029809778,0.0037519445,0.000027515061,0.0006703671,0.000016725477,0.00026888857,0.0032219018],"genre_scores_gemma":[0.98954105,0.0000059847575,0.00809381,0.0011789796,0.00004155879,0.00014459383,0.00003593704,0.000037924434,0.0009201546],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985021,0.000074430274,0.00042152047,0.00042883388,0.00028109233,0.00029207268],"domain_scores_gemma":[0.99865973,0.00045726472,0.00016250598,0.000582472,0.00006423737,0.00007380078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053076365,0.00014513984,0.0002824482,0.00025233233,0.00028811986,0.000011002273,0.00019629682,0.000028546849,0.000061199746],"category_scores_gemma":[0.00082265347,0.0001574485,0.00009343137,0.00051982043,0.00012905172,0.00006945126,0.00031209073,0.00047268128,0.000003348761],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004112255,0.00032297664,0.6715447,0.00010375611,0.0000025972024,0.000028773711,0.0005039636,0.00007485119,0.31764072,0.0020923088,0.0070457472,0.0006355239],"study_design_scores_gemma":[0.000961939,0.000111678986,0.93413377,0.00016555317,0.000013349661,0.000048326245,0.0007890006,0.0026911458,0.0007408226,0.01511026,0.045138948,0.00009520715],"about_ca_topic_score_codex":0.000033666318,"about_ca_topic_score_gemma":0.0000014078196,"teacher_disagreement_score":0.3168999,"about_ca_system_score_codex":0.00014031914,"about_ca_system_score_gemma":0.000033082033,"threshold_uncertainty_score":0.64205635},"labels":[],"label_agreement":null},{"id":"W4295709252","doi":"10.1016/j.nicl.2022.103201","title":"The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canadian Institutes of Health Research; Epilepsy Research Program of the Ontario Brain Institute; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Ontario Brain Institute","keywords":"Temporal lobe; White matter; Epilepsy; Diffusion MRI; Uncinate fasciculus; Anatomy; Cortex (anatomy); Magnetic resonance imaging; Nuclear magnetic resonance; Pathology; Neuroscience; Fractional anisotropy; Medicine; Psychology; Physics; Radiology","score_opus":0.06548771072459326,"score_gpt":0.3982843438262933,"score_spread":0.33279663310170005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295709252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9882314,0.0001449246,0.00008471444,0.008999319,0.00020069379,0.0014213511,0.000019505143,0.000113730785,0.0007843273],"genre_scores_gemma":[0.99762183,0.000039899536,0.00043880462,0.0013112451,0.00008538716,0.00020070226,0.0000057792513,0.000041255476,0.00025510468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99731964,0.0005370366,0.0008803736,0.0005178983,0.00046189746,0.0002831416],"domain_scores_gemma":[0.9978148,0.0005301522,0.00031301982,0.0012027365,0.000055536642,0.00008378127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009999381,0.00016538017,0.00035173522,0.00006734221,0.0004693553,0.000021280915,0.00057779916,0.000026514146,0.00003494951],"category_scores_gemma":[0.00047529355,0.00010709082,0.00025119097,0.00055676705,0.00031803406,0.000054213728,0.0009882529,0.001126249,0.000003621895],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015255781,0.001541182,0.98401284,0.0000036669862,0.0000054055963,0.000035767956,0.000086020766,0.0000045936745,0.0021833898,0.00013886568,0.0008795511,0.01095615],"study_design_scores_gemma":[0.001463197,0.0005168713,0.9294921,0.00001868714,0.00005017717,0.000055740224,0.0009805899,0.0024840538,0.00024942006,0.001797407,0.06277098,0.000120758246],"about_ca_topic_score_codex":0.00014669703,"about_ca_topic_score_gemma":0.0000245368,"teacher_disagreement_score":0.061891425,"about_ca_system_score_codex":0.000045198627,"about_ca_system_score_gemma":0.00010748789,"threshold_uncertainty_score":0.4893054},"labels":[],"label_agreement":null},{"id":"W4295747743","doi":"10.1007/978-3-031-16431-6_20","title":"Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression","year":2022,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Computer science; Normative; Bayesian probability; Diffusion MRI; Artificial intelligence; Regression; Tensor (intrinsic definition); Diffusion; Multilevel model; Pattern recognition (psychology); Data mining; Algorithm; Machine learning; Statistics; Mathematics; Magnetic resonance imaging","score_opus":0.06032372092394443,"score_gpt":0.35846170821556356,"score_spread":0.2981379872916191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295747743","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19921704,0.00006374427,0.7996554,0.00070937065,0.00008272186,0.0002101071,0.00000374192,0.000054931992,0.0000029407463],"genre_scores_gemma":[0.5401074,0.0000038206713,0.4595075,0.00034922594,0.000018278773,0.000005307492,0.0000018717361,0.0000062643635,2.677077e-7],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986302,0.00004612449,0.00025063634,0.0004010034,0.00043526743,0.0002367682],"domain_scores_gemma":[0.9992398,0.00012526967,0.00010528781,0.00035680403,0.00010222711,0.000070588954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032938868,0.00011488265,0.00019358136,0.00052871916,0.00034411298,0.000019931942,0.00027979986,0.000018236591,0.000004726271],"category_scores_gemma":[0.00013696704,0.0000946203,0.000045245582,0.0019410293,0.00018792959,0.00013736481,0.00060070393,0.0004904101,1.960326e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039813942,0.00022335145,0.043047655,0.000036273024,0.0000019602367,0.000037107537,0.0017645846,0.6988843,0.14286327,0.000040104853,0.0000026232606,0.11305892],"study_design_scores_gemma":[0.00029849357,0.00005069513,0.0010388988,0.00008695348,0.000006293539,0.000103764476,0.0000042724005,0.9907333,0.0061864206,0.0013857227,0.000011997457,0.000093187344],"about_ca_topic_score_codex":0.000040417337,"about_ca_topic_score_gemma":0.0000010699569,"teacher_disagreement_score":0.3408904,"about_ca_system_score_codex":0.00015624348,"about_ca_system_score_gemma":0.000096781725,"threshold_uncertainty_score":0.38585037},"labels":[],"label_agreement":null},{"id":"W4295993249","doi":"10.1016/j.neuroimage.2022.119600","title":"Bundle-o-graphy: improving structural connectivity estimation with adaptive microstructure-informed tractography","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Discriminative model; Computer science; Artificial intelligence; Bundle; Diffusion MRI; Bayes' theorem; Ground truth; Human Connectome Project; Fiber bundle; Pattern recognition (psychology); Generative model; Probabilistic logic; Bayesian probability; Representation (politics); Generative grammar; Machine learning; Magnetic resonance imaging; Neuroscience; Functional connectivity; Psychology","score_opus":0.03406274172665822,"score_gpt":0.31311198960471576,"score_spread":0.2790492478780575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4295993249","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.952442,0.000039864,0.04329834,0.0009602643,0.000090349014,0.0012248331,0.00014709077,0.0006492579,0.001148019],"genre_scores_gemma":[0.9426374,0.000003583679,0.05608618,0.0008962455,0.000033917568,0.00017200931,0.0000776701,0.000048059726,0.000044937886],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99864036,0.000042886393,0.00021647877,0.00047251966,0.00032349315,0.00030425595],"domain_scores_gemma":[0.99904364,0.00009984349,0.00018896339,0.00047981576,0.000074936455,0.000112792346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006545451,0.0002314156,0.00024975577,0.00021577363,0.0005245709,0.000036930276,0.00015424893,0.000029694647,0.00007317454],"category_scores_gemma":[0.00004302748,0.00020474175,0.00012176895,0.00060942525,0.00015801475,0.00024224013,0.00010631934,0.00064541306,0.0000016874072],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0066490825,0.0012654733,0.08664884,0.0005730803,0.0003016036,0.00079945364,0.0019412986,0.01002897,0.7209934,0.014201022,0.004279054,0.15231873],"study_design_scores_gemma":[0.0066339625,0.007723353,0.8066343,0.00006830442,0.0004965702,0.00572005,0.00061669457,0.10497822,0.04278279,0.009574389,0.01325497,0.0015164115],"about_ca_topic_score_codex":0.000054483935,"about_ca_topic_score_gemma":0.000006312093,"teacher_disagreement_score":0.7199854,"about_ca_system_score_codex":0.00007900065,"about_ca_system_score_gemma":0.000103593986,"threshold_uncertainty_score":0.8349126},"labels":[],"label_agreement":null},{"id":"W4296485917","doi":"10.26034/cortica.2022.3137","title":"Sex differences and symptom based gray and white matter densities in schizophrenia","year":2022,"lang":"en","type":"article","venue":"Cortica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Institute of Gender and Health; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"White matter; Frontal lobe; Superior frontal gyrus; Cerebellum; Voxel; Psychology; Gyrus; Gray (unit); Audiology; Parietal lobe; Anatomy; Medicine; Magnetic resonance imaging; Neuroscience; Nuclear medicine; Radiology; Cognition","score_opus":0.02989271862009877,"score_gpt":0.2875582029222318,"score_spread":0.257665484302133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296485917","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.995263,0.00008386159,0.0008124254,0.00322353,0.00000993723,0.00015503298,0.00000665869,0.000055049582,0.00039049875],"genre_scores_gemma":[0.9954963,0.00001945687,0.0027263518,0.0013745778,0.000009656517,0.0000833511,0.00000418081,0.000008643461,0.00027751824],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9995775,0.000015929158,0.00008878976,0.00015703742,0.00007002858,0.000090665555],"domain_scores_gemma":[0.99976283,0.000038933766,0.000019462723,0.00012971609,0.000007660168,0.000041419917],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029338118,0.00005921692,0.00011088268,0.000057251887,0.00008012895,0.000010652898,0.000028913293,0.000010316857,0.00011519616],"category_scores_gemma":[0.00000670245,0.000053265772,0.00000995852,0.00007568505,0.00007491589,0.000018424867,0.00006618048,0.00012012358,0.0000014648822],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048396523,0.00003971182,0.99528784,0.000023041079,0.0000025426843,0.000018357136,0.000113494854,0.00000159257,0.0020163099,0.0003985542,0.0004949521,0.0015552277],"study_design_scores_gemma":[0.00043104694,0.00007679679,0.9947486,0.000018287892,0.00001579915,0.00005202441,0.00009605003,0.0020361957,0.00022555192,0.0013618316,0.00086599245,0.00007184888],"about_ca_topic_score_codex":0.0000053994854,"about_ca_topic_score_gemma":0.00000169874,"teacher_disagreement_score":0.0020346032,"about_ca_system_score_codex":0.000011325022,"about_ca_system_score_gemma":0.00001383131,"threshold_uncertainty_score":0.21721151},"labels":[],"label_agreement":null},{"id":"W4296618322","doi":"10.1002/jnr.25126","title":"Altered neurovascular coupling in thyroid‐associated ophthalmopathy: A combined resting‐state <scp>fMRI</scp> and arterial spin labeling study","year":2022,"lang":"en","type":"article","venue":"Journal of Neuroscience Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Cerebral blood flow; Neurovascular bundle; Cardiology; Medicine; Functional magnetic resonance imaging; Resting state fMRI; Internal medicine; Magnetic resonance imaging; Precuneus; Neuroscience; Psychology; Anatomy; Radiology","score_opus":0.17298659590854634,"score_gpt":0.43993548916888753,"score_spread":0.2669488932603412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296618322","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99793786,0.00008449061,0.00013130473,0.0008072538,0.00016785196,0.00079851574,0.0000040588357,0.000034176963,0.000034489472],"genre_scores_gemma":[0.99910146,0.0001367281,0.00038559313,0.00013996413,0.00006372849,0.000046365338,8.341084e-7,0.000029944,0.00009538726],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9965262,0.00040738037,0.0006055276,0.0004321129,0.0014897026,0.0005390842],"domain_scores_gemma":[0.998307,0.0005170048,0.00029447977,0.00033025543,0.00032977868,0.00022148824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043800566,0.00013521791,0.0003585465,0.0006920951,0.0006288179,0.000114858354,0.00044855304,0.000021233103,0.0000020409543],"category_scores_gemma":[0.003959043,0.00012740828,0.00006694064,0.0018327484,0.00020769,0.00019267159,0.00050450943,0.0016282203,5.1876503e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017334186,0.0017200573,0.07278948,0.000023107994,0.0000063438756,0.002800234,0.00064636924,0.0034584252,0.9177961,0.000023039232,0.00023457829,0.00032896016],"study_design_scores_gemma":[0.009580016,0.017970143,0.85449827,0.00024463495,0.000054001266,0.0036503505,0.0027851036,0.10220876,0.0049800156,0.002451349,0.0013676642,0.0002097012],"about_ca_topic_score_codex":0.000026154183,"about_ca_topic_score_gemma":0.0000013329528,"teacher_disagreement_score":0.91281605,"about_ca_system_score_codex":0.00014873447,"about_ca_system_score_gemma":0.00026504495,"threshold_uncertainty_score":0.7073898},"labels":[],"label_agreement":null},{"id":"W4296663335","doi":"10.3389/fnimg.2022.917806","title":"DORIS: A diffusion MRI-based 10 tissue class deep learning segmentation algorithm tailored to improve anatomically-constrained tractography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; National Institute of Biomedical Imaging and Bioengineering; NIH Blueprint for Neuroscience Research; Alzheimer's Association; National Institute on Aging; National Institutes of Health; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; European Commission; Agence Nationale de la Recherche; Medical Research Council; McDonnell Center for Systems Neuroscience","keywords":"Tractography; Doris (gastropod); Diffusion MRI; Segmentation; Artificial intelligence; Computer science; Class (philosophy); Algorithm; Computer vision; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.012902484986013471,"score_gpt":0.29168088301827916,"score_spread":0.2787783980322657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296663335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.073744684,0.00013638716,0.9176262,0.0053388975,0.0004555878,0.0016714039,0.000030375062,0.0005872736,0.000409207],"genre_scores_gemma":[0.5455244,0.000033695615,0.45040083,0.0026748232,0.0000878151,0.0007481492,0.00018052004,0.00010147469,0.00024828254],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977876,0.00013921269,0.00044103878,0.00075945235,0.00040765246,0.00046505235],"domain_scores_gemma":[0.9990998,0.00006640114,0.00016853766,0.0004029988,0.000062437575,0.00019982216],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021853416,0.00026569114,0.00036441002,0.00075448473,0.0003466622,0.000046571993,0.00023287199,0.00004212379,0.00008905391],"category_scores_gemma":[0.00007888361,0.0003060839,0.000119287346,0.0011520837,0.00009356116,0.00013281306,0.0001511583,0.0008652322,0.000003970269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004601891,0.00065230415,0.03402688,0.00007521325,0.000029150757,0.0003446243,0.00066022796,0.005896599,0.27670947,0.000058633843,0.006112058,0.6749746],"study_design_scores_gemma":[0.005766688,0.0012769267,0.011425793,0.0000977015,0.0001526862,0.00012082952,0.002604052,0.8141591,0.026167618,0.0010503631,0.13624188,0.0009363599],"about_ca_topic_score_codex":0.00002252377,"about_ca_topic_score_gemma":8.1207804e-7,"teacher_disagreement_score":0.8082625,"about_ca_system_score_codex":0.00024514899,"about_ca_system_score_gemma":0.000059811893,"threshold_uncertainty_score":0.99993914},"labels":[],"label_agreement":null},{"id":"W4297461623","doi":"10.1007/s10072-022-06408-x","title":"The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study","year":2022,"lang":"en","type":"article","venue":"Neurological Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cingulum (brain); Neuroradiology; Neurology; Cognitive impairment; Kurtosis; Medicine; Diffusion MRI; Neurosurgery; Cognition; Psychology; Radiology; Magnetic resonance imaging; Psychiatry; Fractional anisotropy","score_opus":0.024239557699782158,"score_gpt":0.3122071600327727,"score_spread":0.28796760233299057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297461623","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99606156,0.00002348951,0.000015765272,0.0025268737,0.000039117764,0.001026421,0.000015203209,0.00007512813,0.00021646386],"genre_scores_gemma":[0.99841744,0.0000052123514,0.00027749463,0.0011185922,0.0000055167766,0.00013166366,0.0000034262105,0.000005564625,0.000035067165],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998708,0.00010072161,0.00019957227,0.00033044512,0.0004279378,0.00023328912],"domain_scores_gemma":[0.9994279,0.00019611594,0.000103718376,0.00014014698,0.000069225876,0.00006290225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021499139,0.00009994056,0.00013747356,0.00005416974,0.001005801,0.000023461454,0.00023404014,0.000008802494,0.00003309269],"category_scores_gemma":[0.000072559415,0.00005200277,0.000035790294,0.0005549238,0.00042280692,0.000049311955,0.00033670364,0.00020807936,7.487139e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002537722,0.00029140228,0.9968863,0.0000017386437,0.0000036639335,0.0000069416164,0.0003827875,0.000022044496,0.0003518973,0.00010690899,0.000041089377,0.0016514228],"study_design_scores_gemma":[0.0006748875,0.0046951124,0.9924407,0.000007567884,0.000024755898,0.00002039228,0.00096988154,0.00017064018,0.00022432933,0.00047435184,0.00022565499,0.000071696384],"about_ca_topic_score_codex":0.000031527783,"about_ca_topic_score_gemma":0.0000029149157,"teacher_disagreement_score":0.0044456013,"about_ca_system_score_codex":0.000012985388,"about_ca_system_score_gemma":0.00001810987,"threshold_uncertainty_score":0.773591},"labels":[],"label_agreement":null},{"id":"W4297822196","doi":"10.21203/rs.3.rs-2022169/v1","title":"Electrostimulation of the white matter of the posterior insula and medial operculum: perception of vibrations, heat, and pain","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Institut National de la Santé et de la Recherche Médicale","keywords":"Insula; Operculum (bryozoa); Somatosensory system; White matter; Sensory system; Medicine; Parietal lobe; Sensation; Hypoalgesia; Anatomy; Psychology; Audiology; Neuroscience; Magnetic resonance imaging; Radiology; Nociception; Hyperalgesia; Biology","score_opus":0.06407759378008372,"score_gpt":0.41256655149382077,"score_spread":0.34848895771373706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297822196","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9866624,0.00017492152,0.00070000096,0.010432718,0.000018105598,0.0017224586,0.00012872573,0.0000120974455,0.00014860179],"genre_scores_gemma":[0.99822277,0.0002274359,0.001084321,0.000110593646,0.000030292884,0.00014348928,0.000052542568,0.000017739607,0.00011084299],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984355,0.00045104607,0.00027523187,0.0002317597,0.000485391,0.00012109302],"domain_scores_gemma":[0.9989039,0.0001402134,0.0001003033,0.0005772152,0.00024501092,0.00003340972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077653315,0.000090293965,0.00020513644,0.00011712873,0.00013586572,0.0000107073865,0.00016842214,0.000074952615,0.00011319882],"category_scores_gemma":[0.0002112317,0.00005848942,0.00006755801,0.00025933754,0.00030766168,0.000031533167,0.0008162372,0.0006155409,1.8183121e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016420991,0.00016861851,0.61652815,0.0019028301,0.000022496717,5.887188e-7,0.0016937138,0.00025117077,0.37497565,0.00025200643,0.00099559,0.0030449752],"study_design_scores_gemma":[0.00026864337,0.00023019456,0.98895323,0.00057104486,0.000032373646,0.00001249481,0.000408433,0.0034862298,0.0042571025,0.0013862064,0.00032942192,0.00006461759],"about_ca_topic_score_codex":0.000098970064,"about_ca_topic_score_gemma":0.0000076101637,"teacher_disagreement_score":0.37242508,"about_ca_system_score_codex":0.000055212062,"about_ca_system_score_gemma":0.00013300644,"threshold_uncertainty_score":0.2674253},"labels":[],"label_agreement":null},{"id":"W4297911674","doi":"10.1016/j.neuroimage.2022.119644","title":"Increased myelination plays a central role in white matter neuroplasticity","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Coastal Health; Fraser Health; University of Calgary; University of Victoria; University of British Columbia; Surrey Memorial Hospital; Simon Fraser University","funders":"","keywords":"Diffusion MRI; White matter; Neuroplasticity; Neuroscience; Myelin; Central nervous system; Tractography; Magnetic resonance imaging; Psychology; Medicine; Radiology","score_opus":0.024190274219737764,"score_gpt":0.28991659301385425,"score_spread":0.2657263187941165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297911674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9869933,0.000012727942,0.0026143617,0.0034017623,0.0000625039,0.00056129455,0.000059080856,0.00023699031,0.0060579884],"genre_scores_gemma":[0.993402,0.000005792764,0.0016869574,0.004239708,0.0000488849,0.00015606759,0.000050479037,0.000038695187,0.00037143327],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988186,0.00008213196,0.00022353392,0.00036344826,0.00023199667,0.0002803388],"domain_scores_gemma":[0.99944407,0.000050081664,0.00006298993,0.0003280753,0.000024535077,0.000090261776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007659346,0.00012413121,0.00016174452,0.00015600817,0.00013111626,0.000015340236,0.00012371427,0.00001795732,0.00056743703],"category_scores_gemma":[0.00004989169,0.00013729619,0.000053573127,0.000361162,0.000035080404,0.000081861144,0.00015981263,0.0004810859,0.000037103266],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022442984,0.0006511067,0.8947515,0.000031482294,0.00000312657,0.0003719408,0.00014104473,0.00064047595,0.095478274,0.0003715264,0.006467711,0.0008673908],"study_design_scores_gemma":[0.0007589199,0.00014007906,0.97482556,0.0000073845986,0.000016230772,0.00021697213,0.00002374785,0.0077341762,0.0015301042,0.00034355704,0.014282286,0.00012096336],"about_ca_topic_score_codex":0.000027404107,"about_ca_topic_score_gemma":0.0000025188924,"teacher_disagreement_score":0.09394817,"about_ca_system_score_codex":0.00007915961,"about_ca_system_score_gemma":0.00003757339,"threshold_uncertainty_score":0.6213038},"labels":[],"label_agreement":null},{"id":"W4297963061","doi":"10.1101/2022.09.29.510004","title":"Sensitivity of diffusion-tensor and correlated diffusion imaging to white-matter microstructural abnormalities: application in COVID-19","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Waterloo; University of Toronto; Baycrest Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Coronavirus disease 2019 (COVID-19); Diffusion; Fractional anisotropy; Tractography; Medicine; Nuclear magnetic resonance; Diffusion imaging; Magnetic resonance imaging; Nuclear medicine; Physics; Radiology; Pathology","score_opus":0.01685869738868113,"score_gpt":0.2796618620612028,"score_spread":0.2628031646725217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297963061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9729897,0.0001983718,0.02136657,0.0027181972,0.00012930158,0.0019018895,0.0003750286,0.0003148342,0.0000061141573],"genre_scores_gemma":[0.9854582,0.00014037927,0.011444914,0.0023474458,0.000061603234,0.00043732696,0.000004802399,0.00009539864,0.000009962056],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975735,0.00015074531,0.0006186402,0.0009830749,0.00029985662,0.0003741858],"domain_scores_gemma":[0.99778014,0.000144481,0.0003969798,0.0011102054,0.00021186858,0.00035634168],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047104267,0.00041523593,0.00063616567,0.00045637414,0.00017894123,0.00004973695,0.00019114597,0.00017689163,0.0000688905],"category_scores_gemma":[0.00022636313,0.0004492385,0.00009532083,0.00057665707,0.00016132793,0.00009561253,0.0009570315,0.00082541094,0.000006145542],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085662425,0.000099709054,0.50963926,0.00042423588,0.000010864704,0.00004823506,0.000053692725,0.00009637626,0.4892658,0.00007171367,0.00019634554,0.000008132576],"study_design_scores_gemma":[0.0008830898,0.000036955076,0.97692096,0.00039241448,0.000090106005,0.0000013139152,0.000034099685,0.004201543,0.013423655,0.000013778553,0.0034646234,0.0005374646],"about_ca_topic_score_codex":0.0004991613,"about_ca_topic_score_gemma":0.000006057688,"teacher_disagreement_score":0.47584215,"about_ca_system_score_codex":0.00044873415,"about_ca_system_score_gemma":0.00025249048,"threshold_uncertainty_score":0.9997959},"labels":[],"label_agreement":null},{"id":"W4298142118","doi":"10.3389/fnana.2022.894606","title":"Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Institute of Mental Health; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Segmentation; Computer science; Artificial intelligence; Neuroanatomy; Neuroimaging; Software; Image segmentation; Pattern recognition (psychology); Computer vision; Neuroscience; Psychology","score_opus":0.030732867687438735,"score_gpt":0.34200946561814477,"score_spread":0.31127659793070606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4298142118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9929565,0.00037145067,0.0040976107,0.00045612644,0.00009509812,0.0012816321,0.000020629817,0.00007587887,0.00064504985],"genre_scores_gemma":[0.93542457,0.00002127155,0.06394448,0.00028151996,0.000009478134,0.00020666468,0.000058419515,0.000023688945,0.00002993584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981431,0.00012521955,0.0004150459,0.00061555667,0.000409461,0.00029163173],"domain_scores_gemma":[0.9992005,0.00001299553,0.00011754286,0.00050995493,0.00006820404,0.00009077653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003467119,0.0001308736,0.0002683454,0.00052316464,0.00018909993,0.000031623073,0.00076585886,0.00002241974,0.000021467657],"category_scores_gemma":[0.00005843029,0.00014278172,0.00002150092,0.0016312377,0.0004086889,0.00032224547,0.0004336604,0.0004155182,1.3634268e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085045665,0.0017838557,0.75446385,0.0000753102,0.000004077666,0.00018579423,0.00048629646,0.0013228516,0.14846417,0.044696722,0.004805662,0.042860948],"study_design_scores_gemma":[0.003093023,0.0006129219,0.8704015,0.000027731576,0.000025815403,0.00008529384,0.0006135193,0.09328052,0.007764939,0.02233628,0.0014539172,0.0003045564],"about_ca_topic_score_codex":0.00018362707,"about_ca_topic_score_gemma":0.000003761834,"teacher_disagreement_score":0.14069922,"about_ca_system_score_codex":0.0002714792,"about_ca_system_score_gemma":0.00015786942,"threshold_uncertainty_score":0.58224696},"labels":[],"label_agreement":null},{"id":"W4299506631","doi":"10.17615/ncz1-ak18","title":"Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Brain Science Foundation","keywords":"Tractography; Diffusion MRI; Nuclear magnetic resonance; Cluster analysis; Magnetic resonance imaging; Medicine; Computer science; Physics; Artificial intelligence; Radiology","score_opus":0.1799741018889793,"score_gpt":0.37187285938033854,"score_spread":0.19189875749135923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299506631","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09511502,0.0006369639,0.90164775,0.0015502812,0.00001341023,0.000335309,0.000020787464,0.00016081857,0.0005196746],"genre_scores_gemma":[0.21715271,0.000016157692,0.7822712,0.0004650237,0.000024692547,0.000011838662,0.000007954363,0.00001842838,0.00003198911],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933726,0.00002482692,0.00020141625,0.00020956412,0.0001265303,0.00010041141],"domain_scores_gemma":[0.99950707,0.0001380193,0.00009534628,0.00014715012,0.000056595156,0.00005584272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050696646,0.00009617713,0.00019048496,0.00008033175,0.0000566008,0.000014956694,0.00006823288,0.000036002853,0.000015791706],"category_scores_gemma":[0.0001354974,0.00008653141,0.000053639982,0.00041644814,0.00009736478,0.00020009774,0.00006027992,0.000110568006,5.0806955e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031506876,0.0002834863,0.004016764,0.00027579692,0.000011567967,0.000008339463,0.002942948,0.0001242242,0.82034445,0.1222724,0.00011088354,0.049294084],"study_design_scores_gemma":[0.0026234007,0.001776986,0.13507175,0.00057909114,0.00019848111,0.00005545349,0.0014301982,0.69645715,0.13911773,0.010608268,0.011616563,0.00046491012],"about_ca_topic_score_codex":0.000008814628,"about_ca_topic_score_gemma":3.318579e-7,"teacher_disagreement_score":0.69633293,"about_ca_system_score_codex":0.0000061826304,"about_ca_system_score_gemma":0.000023013592,"threshold_uncertainty_score":0.35286483},"labels":[],"label_agreement":null},{"id":"W4302027680","doi":"10.1002/mrm.29473","title":"Tuned bipolar oscillating gradients for mapping frequency dispersion of diffusion kurtosis in the human brain","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund","keywords":"Kurtosis; Dispersion (optics); Thermal diffusivity; Diffusion; Oscillation (cell signaling); Nuclear magnetic resonance; Biological system; Diffusion MRI; Chemistry; Computational physics; Acoustics; Physics; Optics; Mathematics; Magnetic resonance imaging; Statistics; Thermodynamics","score_opus":0.06187219147033289,"score_gpt":0.3443169510520472,"score_spread":0.2824447595817143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302027680","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.977956,0.004958341,0.00080234365,0.014301086,0.000047443384,0.001446111,0.0000128369575,0.00003339829,0.00044246795],"genre_scores_gemma":[0.992856,0.00029020946,0.0047724047,0.0012928714,0.00006196809,0.0004793381,0.000035973153,0.000020765317,0.00019042962],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985049,0.000094840965,0.00048693834,0.00030327804,0.0003727024,0.00023737183],"domain_scores_gemma":[0.9991048,0.00029974183,0.00013282507,0.00039642488,0.00003251526,0.000033675766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075269694,0.00012295869,0.0003015283,0.00024994227,0.00018464214,0.0000025570466,0.00024284591,0.00002740428,0.00007847072],"category_scores_gemma":[0.00034284886,0.00009081384,0.000048305654,0.00079463393,0.00014316116,0.000026007947,0.00008598674,0.00030274363,2.4250042e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082205086,0.00043011253,0.40679613,0.00022862357,0.000002247063,0.000041585547,0.0047228457,0.000014714777,0.46234402,0.003649407,0.0024792075,0.119208895],"study_design_scores_gemma":[0.0050956313,0.0023601386,0.84756505,0.0010064451,0.00003439287,0.0000705703,0.0027576126,0.003576678,0.0005075536,0.012022068,0.12477014,0.00023372078],"about_ca_topic_score_codex":0.00026989635,"about_ca_topic_score_gemma":0.000017523733,"teacher_disagreement_score":0.4618365,"about_ca_system_score_codex":0.000085118816,"about_ca_system_score_gemma":0.000016679165,"threshold_uncertainty_score":0.37032807},"labels":[],"label_agreement":null},{"id":"W4302363019","doi":"10.1016/j.neuron.2022.09.011","title":"Prefrontal-habenular microstructural impairments in human cocaine and heroin addiction","year":2022,"lang":"en","type":"article","venue":"Neuron","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; Canadian Institutes of Health Research; Icahn School of Medicine at Mount Sinai; Harvard Medical School","keywords":"Addiction; Prefrontal cortex; Neuroscience; Cocaine dependence; Psychology; Habenula; Human brain; Heroin; Neuroimaging; Psychiatry; Drug; Cognition; Central nervous system","score_opus":0.028194442079618052,"score_gpt":0.3241973988713929,"score_spread":0.2960029567917748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302363019","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9985062,0.00008076818,0.000052709427,0.000661391,0.00003260484,0.000370907,0.000017079936,0.00009912866,0.00017921641],"genre_scores_gemma":[0.9981992,0.000017096338,0.0007315947,0.00057869666,0.00002242451,0.00008182859,0.000054605272,0.000017378055,0.00029715995],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994417,0.000024297993,0.00011562037,0.00020734305,0.000095440955,0.00011561571],"domain_scores_gemma":[0.9997491,0.000007162537,0.000036377038,0.00016320175,0.000006878503,0.000037283495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000371831,0.00007126562,0.00009396079,0.000060423885,0.00013136196,0.000005568649,0.00004307184,0.00001252579,0.000055389926],"category_scores_gemma":[0.0000053130043,0.00007509443,0.000018611401,0.00010155474,0.000028923885,0.00003850346,0.00009389717,0.000219112,8.242602e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007344541,0.00013017507,0.034284636,0.00001634345,0.0000035866078,0.00011570244,0.00010167119,0.000021290374,0.957859,0.0001301621,0.0018670141,0.0053970143],"study_design_scores_gemma":[0.002800786,0.0015268688,0.90311676,0.000030494028,0.000038699414,0.001446739,0.00007650256,0.00067823386,0.020400824,0.0013803128,0.06828075,0.00022301573],"about_ca_topic_score_codex":0.000037492635,"about_ca_topic_score_gemma":0.000003471244,"teacher_disagreement_score":0.93745816,"about_ca_system_score_codex":0.000064595195,"about_ca_system_score_gemma":0.00000765379,"threshold_uncertainty_score":0.3062262},"labels":[],"label_agreement":null},{"id":"W4303432678","doi":"10.1093/cercor/bhac329","title":"Difference in axon diameter and myelin thickness between excitatory and inhibitory callosally projecting axons in mice","year":2022,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Medical Research Council; Canadian Institutes of Health Research; European Commission; Medical Research Council Canada; McGill University","keywords":"Excitatory postsynaptic potential; Inhibitory postsynaptic potential; Axon; Neuroscience; Myelin; Soma; Chemistry; Biophysics; Biology; Central nervous system","score_opus":0.058794826539761064,"score_gpt":0.3208896550543648,"score_spread":0.26209482851460375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4303432678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975715,0.00018507683,0.0005143074,0.000802814,0.000025832054,0.00055584236,0.000014919986,0.00007984343,0.00024980726],"genre_scores_gemma":[0.9963598,0.000030359275,0.0027705312,0.00044466852,0.000046441703,0.00018831028,0.0000146777165,0.00002200773,0.00012316405],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989905,0.00006644229,0.00023853668,0.0003720407,0.00013058695,0.0002019346],"domain_scores_gemma":[0.9995527,0.00013621357,0.00006391402,0.00016045857,0.000017225453,0.00006944913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017908905,0.00012255905,0.00022690734,0.00016673881,0.00010015996,0.000011960388,0.00007221643,0.000041031202,0.00001048375],"category_scores_gemma":[0.000056505778,0.00012407976,0.000020308331,0.00023899964,0.00009289144,0.000061500985,0.00021557213,0.0005911406,6.004069e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003672975,0.00007669516,0.9600706,0.00008303203,0.0000044331405,0.000037963375,0.0006603637,0.0000012931902,0.024923237,0.0003015397,0.00007611294,0.013728007],"study_design_scores_gemma":[0.0007231602,0.00013512388,0.99559695,0.00008469762,0.000015994397,0.000056266214,0.00041718927,0.0003493984,0.00042857078,0.0013785082,0.000654637,0.00015948154],"about_ca_topic_score_codex":0.00013392615,"about_ca_topic_score_gemma":0.000066344786,"teacher_disagreement_score":0.03552638,"about_ca_system_score_codex":0.00007435556,"about_ca_system_score_gemma":0.000055130484,"threshold_uncertainty_score":0.5059826},"labels":[],"label_agreement":null},{"id":"W4304118622","doi":"10.1038/s42003-022-03983-9","title":"Specific disruption of the ventral anterior temporo-frontal network reveals key implications for language comprehension and cognition","year":2022,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"European Social Fund; State Scholarships Foundation; Hellenic Foundation for Research and Innovation; European Commission","keywords":"Cognition; Middle temporal gyrus; Lesion; Neuroscience; Internal capsule; Angular gyrus; Frontal lobe; Anterior cingulate cortex; Psychology; Prefrontal cortex; Inferior frontal gyrus; Diffusion MRI; Middle frontal gyrus; Comprehension; White matter; Medicine; Pathology; Magnetic resonance imaging; Computer science; Radiology","score_opus":0.1049965279805815,"score_gpt":0.39294438898633793,"score_spread":0.2879478610057564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304118622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9124467,0.009315152,0.03599402,0.03539128,0.00016485988,0.0040284237,0.0011280767,0.00023454685,0.0012969589],"genre_scores_gemma":[0.9765342,0.0006356185,0.021297757,0.0003453319,0.00003195595,0.0005731634,0.0005317471,0.000011301766,0.00003892246],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993908,0.00010378897,0.00022496181,0.00014400641,0.000029004681,0.00010746318],"domain_scores_gemma":[0.9986631,0.00015343809,0.000158071,0.0009445655,0.00005535378,0.000025473579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012287193,0.00006449969,0.00014080833,0.000033257238,0.0005179012,0.000003620405,0.000262839,0.000027619946,0.000011684689],"category_scores_gemma":[0.000023623923,0.000054505683,0.00006214508,0.00016099702,0.00023987422,0.00002080752,0.00039583395,0.00013431498,4.0236827e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014190792,0.00047702642,0.07249372,0.000047093283,0.00003990212,2.0549047e-7,0.0005431238,0.000017807908,0.8207062,0.07569484,0.005504895,0.024333322],"study_design_scores_gemma":[0.0017812793,0.0006259765,0.73809326,0.00013767893,0.00020924647,0.0003456264,0.00057272334,0.0013769327,0.002337301,0.057646558,0.19658986,0.0002835873],"about_ca_topic_score_codex":0.000005812454,"about_ca_topic_score_gemma":0.000004211997,"teacher_disagreement_score":0.81836885,"about_ca_system_score_codex":0.0000329058,"about_ca_system_score_gemma":0.000017129238,"threshold_uncertainty_score":0.39833298},"labels":[],"label_agreement":null},{"id":"W4304481348","doi":"10.1002/hbm.26104","title":"Identification of central amygdala and trigeminal motor nucleus connectivity in humans: An <scp>ultra‐high</scp> field diffusion <scp>MRI</scp> study","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Krembil Foundation; Mount Sinai Hospital; Centre for Social Innovation; University of Toronto; University Health Network; Discovery Centre","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; University of Toronto; Faculty of Dentistry, University of Toronto; Natural Sciences and Engineering Research Council of Canada; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Neuroscience; Connectome; Tractography; Amygdala; Nucleus; Brainstem; Central nucleus of the amygdala; Stria terminalis; Diffusion MRI; Biology; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity","score_opus":0.043829506699589335,"score_gpt":0.3251770234243049,"score_spread":0.28134751672471553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304481348","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99215645,0.00005891887,0.0054621384,0.0003025339,0.00005347054,0.0014984049,0.000041483712,0.00018485375,0.00024175426],"genre_scores_gemma":[0.9980738,0.000019691288,0.00055864704,0.00033597666,0.00008714815,0.0002755231,0.00006260698,0.000037345813,0.0005492442],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99797666,0.00019638031,0.00054415094,0.0006105527,0.0003306824,0.0003416013],"domain_scores_gemma":[0.9983588,0.00061241735,0.00029855376,0.0005603096,0.00005638976,0.00011357105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063057395,0.00019982949,0.00036546704,0.0003120329,0.0005125155,0.000037950907,0.00022533438,0.00005620098,0.000019071716],"category_scores_gemma":[0.0004962621,0.00022477553,0.000065821885,0.00035455156,0.00008914831,0.00015862905,0.00015683637,0.00048690985,0.0000010086337],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000141977425,0.0016412672,0.11494004,0.00011235939,0.00002069856,0.00003583627,0.006362797,0.000035904868,0.87073064,0.0036584586,0.0013868922,0.0010609038],"study_design_scores_gemma":[0.001856655,0.0010565058,0.97097456,0.000077668745,0.000046293913,0.000024532943,0.010145784,0.000803982,0.0054126442,0.0037151151,0.005808665,0.00007759221],"about_ca_topic_score_codex":0.00014848543,"about_ca_topic_score_gemma":0.00003482946,"teacher_disagreement_score":0.865318,"about_ca_system_score_codex":0.00010665535,"about_ca_system_score_gemma":0.000027165936,"threshold_uncertainty_score":0.91660804},"labels":[],"label_agreement":null},{"id":"W4304783064","doi":"10.1038/s41597-022-01695-7","title":"An analysis-ready and quality controlled resource for pediatric brain white-matter research","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Montréal; Institut Universitaire en Santé Mentale de Québec; Western University; Polytechnique Montréal; Concordia University; University of Toronto","funders":"Child Mind Institute; University of Pennsylvania; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"White matter; Quality (philosophy); Computer science; Medicine; Physics","score_opus":0.3514407486686759,"score_gpt":0.5218421750821093,"score_spread":0.17040142641343337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4304783064","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7427654,0.0007960949,0.10033197,0.09260526,0.00038067202,0.010280312,0.047799427,0.00075975026,0.004281086],"genre_scores_gemma":[0.93415385,0.000005249098,0.014971694,0.0019507277,0.00018762647,0.00072258234,0.025438376,0.00003467873,0.022535209],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977356,0.00026311015,0.00026823365,0.00095171615,0.0005116879,0.0002696347],"domain_scores_gemma":[0.99635416,0.0005371943,0.000085391635,0.0027578701,0.00013487188,0.00013051661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0068010213,0.000075651624,0.00026034765,0.00046618682,0.0009422806,0.00014729986,0.0006983605,0.000017593467,0.00021330753],"category_scores_gemma":[0.00050634466,0.000067594534,0.00004537871,0.0014859488,0.00019342893,0.0001315703,0.00073335913,0.0002372707,0.000008187257],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041197776,0.0004278301,0.100400604,0.000053904467,0.000051263905,0.0000033329477,0.00019476408,0.000048304497,0.0028537787,0.0016218,0.89296114,0.00097130885],"study_design_scores_gemma":[0.003110473,0.0002055519,0.057114314,0.0000029239582,0.0005216541,0.00000947438,0.0007056791,0.022281218,0.000071159026,0.0015833691,0.91419065,0.00020352232],"about_ca_topic_score_codex":0.000024427976,"about_ca_topic_score_gemma":0.000015056142,"teacher_disagreement_score":0.19138843,"about_ca_system_score_codex":0.000032119144,"about_ca_system_score_gemma":0.000069698486,"threshold_uncertainty_score":0.72473556},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"medium"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"high"}],"label_agreement":"split"},{"id":"W4306173734","doi":"10.1016/j.neuroimage.2022.119684","title":"Mapping pontocerebellar connectivity with diffusion MRI","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Concordia University","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada; McGill University; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Pons; Cerebellum; Neuroscience; Tractography; Diffusion MRI; Anatomy; Context (archaeology); Pontine nuclei; Psychology; Biology; Medicine; Magnetic resonance imaging","score_opus":0.04411292630631987,"score_gpt":0.30452868455082743,"score_spread":0.2604157582445076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306173734","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93571776,0.000040515948,0.042093635,0.007000207,0.000051166433,0.0008999723,0.000021936177,0.0006956516,0.01347914],"genre_scores_gemma":[0.98876965,0.000019531268,0.007415167,0.0024661527,0.000044235298,0.00015955618,0.000018273915,0.000042702275,0.0010647138],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990216,0.000042412135,0.000117944335,0.00037027628,0.00025152141,0.00019626062],"domain_scores_gemma":[0.99929637,0.000051847142,0.0000660662,0.00047261117,0.00003363789,0.000079455116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008235121,0.00012008706,0.00016288944,0.00008519582,0.00035631904,0.000012058665,0.00010899759,0.000013415906,0.0001822172],"category_scores_gemma":[0.000022330672,0.00010729032,0.000048400903,0.00033398203,0.000053060077,0.00005132491,0.00018651655,0.00038141417,0.000008705339],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070167094,0.0017405644,0.10171286,0.00015458046,0.000039250346,0.0016818361,0.00067328353,0.00027719024,0.84571666,0.0040050703,0.021882929,0.021414137],"study_design_scores_gemma":[0.0030392914,0.0016946511,0.21267062,0.000047987127,0.00007202099,0.0029345897,0.00044566847,0.0056472295,0.013394118,0.0017130424,0.75777394,0.00056682964],"about_ca_topic_score_codex":0.000014721225,"about_ca_topic_score_gemma":8.420921e-7,"teacher_disagreement_score":0.83232254,"about_ca_system_score_codex":0.000054873737,"about_ca_system_score_gemma":0.000034590314,"threshold_uncertainty_score":0.43751723},"labels":[],"label_agreement":null},{"id":"W4306176742","doi":"10.1002/jmri.28482","title":"Feasibility of <scp>MRI</scp> Quantification of Myelin Water Fraction in the Fetal Guinea Pig Brain","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Children’s Health Research Institute; Lawson Health Research Institute; Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fetus; Myelin; Myelin basic protein; Medicine; White matter; Corpus callosum; Internal medicine; Coefficient of variation; Endocrinology; Pregnancy; Biology; Pathology; Magnetic resonance imaging; Central nervous system; Chemistry; Radiology","score_opus":0.05353232407632565,"score_gpt":0.34840714456400684,"score_spread":0.2948748204876812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306176742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691734,0.0033962596,0.012783741,0.013609637,0.00008046094,0.00050141825,0.000012373566,0.000014886546,0.0004278608],"genre_scores_gemma":[0.99164605,0.00015462434,0.00756275,0.00040727403,0.00006005569,0.000021921014,0.00000551906,0.000014085921,0.00012770735],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982783,0.0001691244,0.00075141893,0.00016440504,0.0004764057,0.00016035397],"domain_scores_gemma":[0.99862146,0.0002773159,0.0004791422,0.00038513873,0.00020528611,0.00003162362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014245132,0.00009607663,0.0002719202,0.00017723057,0.00007415042,0.000009571793,0.0002551544,0.000017120032,0.000038383878],"category_scores_gemma":[0.00036396182,0.000066769346,0.00012020989,0.00030949037,0.00011395233,0.00012230028,0.00006026183,0.00047299807,8.459985e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026892073,0.0011680499,0.2275171,0.00015401475,0.000007634001,0.000079491496,0.0018233197,0.00057327456,0.6312609,0.00044531815,0.010344403,0.12635761],"study_design_scores_gemma":[0.0024110777,0.0008252163,0.7741663,0.00022242553,0.000100502664,0.0012433706,0.0029020326,0.008724651,0.05141171,0.0068500447,0.15104009,0.00010256186],"about_ca_topic_score_codex":0.000025619824,"about_ca_topic_score_gemma":0.0000011155613,"teacher_disagreement_score":0.5798492,"about_ca_system_score_codex":0.00007660546,"about_ca_system_score_gemma":0.000058669815,"threshold_uncertainty_score":0.2722775},"labels":[],"label_agreement":null},{"id":"W4306931098","doi":"10.3233/atde220538","title":"Meridian Sinew Therapy for Cerebral Blood Flow and Brain Function in Sub-Healthy Individuals: A Study of ASL and rsfMRI","year":2022,"lang":"en","type":"book-chapter","venue":"Advances in transdisciplinary engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Traditional Chinese Medicine Bureau of Guangdong Province; Guangdong Science and Technology Department; Natural Science Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Cerebral blood flow; Medicine; Meridian (astronomy); Superior frontal gyrus; Acupuncture; Gyrus; Resting state fMRI; Montreal Cognitive Assessment; Frontal lobe; Cardiology; Physical therapy; Cognition; Functional magnetic resonance imaging; Cognitive impairment; Radiology; Pathology","score_opus":0.032346120394926334,"score_gpt":0.3186001702887488,"score_spread":0.28625404989382247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4306931098","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8980838,0.06787952,0.0179642,0.0021368768,0.00030872098,0.010870532,0.00048457776,0.00041994112,0.0018518358],"genre_scores_gemma":[0.9427872,0.030149728,0.02374246,0.00018700708,0.00017957411,0.0017431218,0.00028737483,0.00030705036,0.0006165357],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99860877,0.000011694369,0.00047349086,0.0005185578,0.00016509049,0.0002224146],"domain_scores_gemma":[0.99934554,0.00019443827,0.000109929824,0.00025808986,0.00001922603,0.00007279714],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019233616,0.00030532945,0.00055740215,0.00041258358,0.000070994094,0.000006183418,0.00008650764,0.000096384945,0.000012544207],"category_scores_gemma":[0.000011140416,0.00032413477,0.000056623983,0.00012995138,0.000049466984,0.00018120544,0.00004964518,0.00048613155,6.405671e-8],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010873177,0.009246814,0.042432413,0.01837232,0.001266985,0.00065268524,0.054037716,0.09788183,0.013521997,0.052794162,0.00019497247,0.6987249],"study_design_scores_gemma":[0.12273813,0.11020455,0.18917342,0.0120631615,0.0029420594,0.0013777177,0.010013946,0.054613557,0.0022659642,0.1098115,0.37505236,0.009743618],"about_ca_topic_score_codex":0.0000046943055,"about_ca_topic_score_gemma":0.000060046546,"teacher_disagreement_score":0.6889813,"about_ca_system_score_codex":0.000038642847,"about_ca_system_score_gemma":0.000031400516,"threshold_uncertainty_score":0.9999211},"labels":[],"label_agreement":null},{"id":"W4307023621","doi":"10.1155/2022/5860364","title":"Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity","year":2022,"lang":"en","type":"article","venue":"International Journal of Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Ontario Brain Institute; St Joseph's Health Care; Health Sciences Centre; Ottawa Hospital; Parkwood Institute; McMaster University; Thunder Bay Regional Research Institute; Queen's University; Public Health Ontario; Baycrest Hospital; Western University; University of Toronto; Sunnybrook Health Science Centre","funders":"Baycrest Foundation; London Health Sciences Foundation; Faculty of Health Sciences, Queen's University; Bruyère Research Institute; Centre for Addiction and Mental Health Foundation; McMaster University; Temerty Family Foundation; University of Ottawa; Ontario Brain Institute; Government of Ontario; Thunder Bay Regional Health Sciences Centre","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Medicine; Hyperintensity; Stroke (engine); Pathology; Magnetic resonance imaging; Radiology; Physics","score_opus":0.021862689021175837,"score_gpt":0.32708012986146767,"score_spread":0.30521744084029184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307023621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.893938,0.0002034613,0.10145069,0.0040829643,0.00008568288,0.00017658499,0.000026515883,0.000014571443,0.000021546308],"genre_scores_gemma":[0.9894281,0.000074320546,0.0101043265,0.0002963963,0.000041088384,0.000006956515,0.000019809939,0.000017947235,0.000011055489],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99833304,0.000062142004,0.00049524405,0.00021549634,0.0007514326,0.00014266805],"domain_scores_gemma":[0.9990026,0.00009846031,0.00033096847,0.00013938572,0.0001903647,0.00023825419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033578742,0.00012601614,0.0002873569,0.0007465167,0.00010808293,0.00002880367,0.00015459889,0.000014543621,0.000051475432],"category_scores_gemma":[0.00016019978,0.00010193988,0.000080754035,0.00037225735,0.00012380123,0.0001836104,0.00027730878,0.00046094242,4.396526e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010035142,0.00023886345,0.9913861,0.000020241889,0.0000409699,0.000039857583,0.00031959772,0.00034982484,0.000528287,0.000013817906,0.0001465609,0.006815532],"study_design_scores_gemma":[0.0010686279,0.00006745986,0.9655368,0.00018501662,0.00010852753,0.00030895395,0.00054585095,0.030255876,0.0001124487,0.00011322744,0.0015942447,0.00010297785],"about_ca_topic_score_codex":0.000092869865,"about_ca_topic_score_gemma":0.0000014034945,"teacher_disagreement_score":0.09549011,"about_ca_system_score_codex":0.00012549323,"about_ca_system_score_gemma":0.000048594025,"threshold_uncertainty_score":0.41569877},"labels":[],"label_agreement":null},{"id":"W4307114714","doi":"10.1111/jopy.12788","title":"Beyond the brain localization of complex traits: Distributed white matter markers of personality","year":2022,"lang":"en","type":"article","venue":"Journal of Personality","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; University of Oregon","keywords":"Neuroticism; Neuroimaging; Psychology; Big Five personality traits; Univariate; Personality; White matter; Facet (psychology); Diffusion MRI; Multivariate statistics; Cognitive psychology; Social psychology; Machine learning; Neuroscience; Magnetic resonance imaging; Computer science","score_opus":0.055804336765749675,"score_gpt":0.33999560487893665,"score_spread":0.28419126811318696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307114714","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7381116,0.00023924584,0.16414925,0.09333763,0.00008967801,0.00066090934,0.0015681706,0.00003193576,0.0018115401],"genre_scores_gemma":[0.99458504,0.000007791275,0.0024549572,0.0026892212,0.00005840581,0.0000079756455,0.00005814179,0.000012431194,0.00012602247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984467,0.00019582245,0.00057238305,0.00012558443,0.00053678313,0.00012272902],"domain_scores_gemma":[0.9986012,0.00013698192,0.0007086599,0.00020217449,0.0002833,0.000067684414],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008880182,0.00010045613,0.00032732554,0.000057290126,0.0001394061,0.0000056159774,0.00020262804,0.000024734178,0.0013306126],"category_scores_gemma":[0.00008349651,0.00007466703,0.00023708101,0.00033966108,0.00022562631,0.00006301689,0.000065581225,0.00034024564,4.467987e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002642697,0.0018991686,0.5918662,0.00067376625,0.000400079,0.000036761587,0.0033707311,0.00111139,0.03167026,0.0035034267,0.35929465,0.003530901],"study_design_scores_gemma":[0.0012654131,0.0004979133,0.92869914,0.00005636919,0.00021148233,0.00048271674,0.0019121557,0.0022608102,0.000648445,0.0031775632,0.060657743,0.0001302761],"about_ca_topic_score_codex":0.000027956716,"about_ca_topic_score_gemma":0.0000018730179,"teacher_disagreement_score":0.33683294,"about_ca_system_score_codex":0.000110208646,"about_ca_system_score_gemma":0.00009727744,"threshold_uncertainty_score":0.9995823},"labels":[],"label_agreement":null},{"id":"W4307340727","doi":"10.17116/jnevro202212210196","title":"Cerebral perfusion and tractography in obese children","year":2022,"lang":"en","type":"article","venue":"S S Korsakov Journal of Neurology and Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Fractional anisotropy; Raven's Progressive Matrices; Neuropsychological assessment; Tractography; Montreal Cognitive Assessment; Neuropsychology; Magnetic resonance imaging; Intelligence quotient; Audiology; Cognition; Psychiatry; Radiology; Cognitive impairment","score_opus":0.017065449582909144,"score_gpt":0.29665190567300537,"score_spread":0.27958645609009625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307340727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9787091,0.0018642718,0.00006515232,0.018943986,0.00015013218,0.00012007732,0.000004718076,0.000013109728,0.00012943761],"genre_scores_gemma":[0.99400634,0.0005927356,0.0017546873,0.0035235914,0.00009364201,0.000004760927,0.000002008182,0.0000105187055,0.000011706094],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935013,0.00006732277,0.00023002377,0.00014449879,0.00009128773,0.0001167212],"domain_scores_gemma":[0.9996451,0.000030834915,0.00013245025,0.00010126829,0.000015699079,0.000074641874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015775558,0.00007893944,0.0001763305,0.0002395131,0.00012175729,0.0000041654216,0.000065290085,0.000037043435,0.00003665345],"category_scores_gemma":[0.000008891133,0.00006988035,0.00005317066,0.00016853787,0.00007679411,0.000047575835,0.00005459616,0.00077160995,1.5391741e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004359757,0.00020277248,0.9941877,0.000008350312,0.000008176917,0.00003354063,0.00007089949,0.000007736556,0.0004642449,0.0007482671,0.0007937658,0.003038531],"study_design_scores_gemma":[0.0012923498,0.0015002606,0.9765117,0.000011504106,0.000036945006,0.008635768,0.000031897525,0.0000355232,0.000017155882,0.0077584707,0.0041068867,0.00006150299],"about_ca_topic_score_codex":0.0000045537076,"about_ca_topic_score_gemma":0.0000026466932,"teacher_disagreement_score":0.017676003,"about_ca_system_score_codex":0.0000030809376,"about_ca_system_score_gemma":0.000032356165,"threshold_uncertainty_score":0.3352304},"labels":[],"label_agreement":null},{"id":"W4307498148","doi":"10.1002/jmri.28424","title":"Intersession Repeatability of <scp>Diffusion‐Tensor</scp> Imaging in the Supraspinatus and the Infraspinatus Muscles of Volunteers","year":2022,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec à Trois-Rivières; Centre Hospitalier de l’Université de Montréal","funders":"Fonds de Recherche du Québec - Santé; Réseau en Bio-Imagerie du Quebec","keywords":"Fractional anisotropy; Diffusion MRI; Repeatability; Medicine; Nuclear medicine; Rotator cuff; Effective diffusion coefficient; Anatomy; Magnetic resonance imaging; Mathematics; Radiology","score_opus":0.017500954583511984,"score_gpt":0.29959514730501957,"score_spread":0.2820941927215076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307498148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9653883,0.02616812,0.0008145979,0.0065878932,0.00008543902,0.0004894636,0.0000071042023,0.000017097433,0.00044195924],"genre_scores_gemma":[0.99491435,0.0012061482,0.0031154533,0.0006348067,0.00003337005,0.000028292538,7.98051e-7,0.000020044818,0.000046715468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979877,0.00026881575,0.00080332387,0.00020250045,0.0005234699,0.00021418737],"domain_scores_gemma":[0.9980367,0.0006301442,0.0005900942,0.0004741803,0.00022276853,0.000046125497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016298129,0.0001401086,0.00040797621,0.00020382497,0.0001453561,0.000016475358,0.00039528808,0.000015740365,0.000016482338],"category_scores_gemma":[0.0011074012,0.00008550127,0.00014621827,0.00043517145,0.0005916332,0.00013802826,0.00027165032,0.0007329675,1.2861163e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004581184,0.00049156894,0.7195764,0.0001840698,0.000007466095,0.00014611834,0.0046927487,0.000087746426,0.025363473,0.0013010132,0.002307549,0.24538372],"study_design_scores_gemma":[0.0035671582,0.00035495282,0.9440837,0.00055593636,0.0000996019,0.001561971,0.011547573,0.0062116995,0.0010002536,0.004118465,0.026827086,0.00007162753],"about_ca_topic_score_codex":0.00011080032,"about_ca_topic_score_gemma":0.000002184941,"teacher_disagreement_score":0.2453121,"about_ca_system_score_codex":0.000063806416,"about_ca_system_score_gemma":0.00008050666,"threshold_uncertainty_score":0.34866408},"labels":[],"label_agreement":null},{"id":"W4307658818","doi":"10.1038/s41537-022-00293-1","title":"In Vivo 7-Tesla MRI Investigation of Brain Iron and Its Metabolic Correlates in Chronic Schizophrenia","year":2022,"lang":"en","type":"article","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute on Drug Abuse; National Institute on Aging; National Health and Medical Research Council; National Institute of Mental Health; Medical Research Council; Brigham and Women's Hospital; National Imaging Facility; Compute Canada; University of Melbourne; Royal Melbourne Hospital; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Putamen; Schizophrenia (object-oriented programming); Quantitative susceptibility mapping; Oxidative stress; Magnetic resonance imaging; Neuroscience; Psychology; Phosphocreatine; Pathology; Medicine; Internal medicine; Nuclear magnetic resonance; Psychiatry; Radiology; Energy metabolism","score_opus":0.025750503139497286,"score_gpt":0.3004865554387543,"score_spread":0.274736052299257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307658818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99158317,0.0030055086,0.00006984039,0.0043786294,0.00005253949,0.0006656534,0.000036229747,0.0000837138,0.0001246931],"genre_scores_gemma":[0.99481773,0.0002973102,0.0038469587,0.00042274743,0.000053703454,0.00023527705,0.000023151963,0.00003352473,0.00026959015],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986913,0.00008914316,0.0003988939,0.00037927818,0.00021246125,0.00022890203],"domain_scores_gemma":[0.9993489,0.00009680986,0.0001472553,0.00029546567,0.00002737377,0.00008420946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026640604,0.00016507752,0.00033576012,0.00039984623,0.00008247786,0.000007249577,0.00013442799,0.00005265171,0.00012176362],"category_scores_gemma":[0.000072845716,0.00017685794,0.00004438963,0.0008236229,0.00008968082,0.00014276021,0.00017256403,0.0005186567,0.0000041035537],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012565887,0.00020832753,0.028994923,0.00023588097,0.000020850151,0.000067593304,0.000667476,0.0011950674,0.8951612,0.06414459,0.003050675,0.004996814],"study_design_scores_gemma":[0.027757991,0.0017984848,0.4070423,0.00077074574,0.00024732764,0.00065218366,0.0003051736,0.051634114,0.37509653,0.10219772,0.030907433,0.0015899972],"about_ca_topic_score_codex":0.000054925924,"about_ca_topic_score_gemma":0.000041830488,"teacher_disagreement_score":0.5200647,"about_ca_system_score_codex":0.0001235204,"about_ca_system_score_gemma":0.00018214576,"threshold_uncertainty_score":0.7212058},"labels":[],"label_agreement":null},{"id":"W4307722372","doi":"10.1016/j.neuroimage.2022.119703","title":"CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":79,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; NIH Blueprint for Neuroscience Research; Horizon 2020; Medical Research Council; McDonnell Center for Systems Neuroscience; Bundesministerium für Bildung und Forschung; Alzheimer’s Society; Fundo Regional para a Ciência e Tecnologia; ZonMw; HORIZON EUROPE Framework Programme; University of Southern California; Alzheimer's Society; U.S. National Library of Medicine; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; EU Joint Programme – Neurodegenerative Disease Research; National Institutes of Health; National Ataxia Foundation; Deutsches Zentrum für Neurodegenerative Erkrankungen; GlaxoSmithKline","keywords":"Spinocerebellar ataxia; Human Connectome Project; Computer science; Artificial intelligence; Segmentation; Preprocessor; Deep learning; Mossy fiber (hippocampus); Cerebellum; Pattern recognition (psychology); Deep cerebellar nuclei; Normalization (sociology); Backbone network; Cerebellar cortex; Neuroscience; Ataxia; Biology; Functional connectivity","score_opus":0.035276769178398275,"score_gpt":0.3144704341371228,"score_spread":0.2791936649587245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307722372","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3939324,0.00055810076,0.5838512,0.0097084595,0.00022630648,0.005364012,0.00010738459,0.0014824087,0.004769723],"genre_scores_gemma":[0.9546206,0.00019733129,0.035996012,0.0022181603,0.00015128442,0.001156414,0.0002187473,0.00010877675,0.0053326646],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989737,0.000034325178,0.00020828754,0.00039535257,0.00016422902,0.00022405625],"domain_scores_gemma":[0.99943686,0.00007660367,0.00010334697,0.00024408112,0.00005495266,0.0000841543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012710634,0.00013021509,0.000174028,0.00008823339,0.0004238778,0.000021268177,0.00007659316,0.000020126537,0.00008476927],"category_scores_gemma":[0.00006662032,0.00014021335,0.000057371195,0.00019956144,0.000044313332,0.00007771812,0.00012365554,0.00031969056,0.0000049091946],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005209402,0.00042689077,0.019391961,0.00022635596,0.000019309184,0.00006427552,0.00032181406,0.0010979276,0.8427184,0.0010772864,0.009560191,0.12457464],"study_design_scores_gemma":[0.006851141,0.0021107807,0.01817612,0.000046680754,0.00032452706,0.00076700695,0.00069502636,0.31718644,0.08377475,0.0022300421,0.56709343,0.00074406853],"about_ca_topic_score_codex":0.000006814006,"about_ca_topic_score_gemma":0.0000018673268,"teacher_disagreement_score":0.7589437,"about_ca_system_score_codex":0.000043904136,"about_ca_system_score_gemma":0.000019943931,"threshold_uncertainty_score":0.5717734},"labels":[],"label_agreement":null},{"id":"W4307829684","doi":"10.1101/2022.10.28.514160","title":"Linking Enlarged Choroid Plexus with Plasma Analyte and Structural Phenotypes in Clinical High Risk for Psychosis: A Multisite Neuroimaging Study","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Psychosis; Choroid plexus; Ventricle; Neuroimaging; Cerebrospinal fluid; Internal medicine; Prodrome; Medicine; Lateral ventricles; White matter; Cardiology; Endocrinology; Pathology; Magnetic resonance imaging; Psychiatry; Radiology; Central nervous system","score_opus":0.03820997945918215,"score_gpt":0.3331895124935982,"score_spread":0.29497953303441604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307829684","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9900022,0.0003435779,0.0043296563,0.0002752783,0.00027320892,0.003872388,0.00037926744,0.00052308606,0.0000013147417],"genre_scores_gemma":[0.92686206,0.0003097275,0.070754305,0.00024501016,0.00028468162,0.0013527869,0.00000286867,0.00018633479,0.0000022156266],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961882,0.00022660111,0.0009269406,0.0017421981,0.00037980027,0.0005362282],"domain_scores_gemma":[0.99712104,0.00026194053,0.0007125545,0.0014076402,0.00024619262,0.00025062033],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00085504964,0.00059308234,0.0009952434,0.00040682103,0.00034190054,0.00012855249,0.00038993388,0.0001946857,0.000012099038],"category_scores_gemma":[0.00026091206,0.00057506375,0.00015084136,0.000585326,0.00014842962,0.00012520209,0.0005378202,0.0020698658,0.00000106964],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005325167,0.00042379258,0.992788,0.0002288556,0.00019168228,0.00009796271,0.00003390828,0.00023067283,0.005239822,0.00010413287,0.000026358832,0.000102251244],"study_design_scores_gemma":[0.0041238107,0.0005969801,0.981559,0.00032152233,0.000567152,2.1545576e-7,0.000018406248,0.009884172,0.0012306665,0.000020326539,0.001051275,0.0006265188],"about_ca_topic_score_codex":0.00023297952,"about_ca_topic_score_gemma":0.000031732117,"teacher_disagreement_score":0.06642465,"about_ca_system_score_codex":0.0001620634,"about_ca_system_score_gemma":0.00016652755,"threshold_uncertainty_score":0.9996701},"labels":[],"label_agreement":null},{"id":"W4307859783","doi":"10.1101/2022.10.27.22281560","title":"Estimation of free water-corrected microscopic fractional anisotropy","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Free water; Orientation (vector space); Diffusion; Dispersion (optics); Partial volume; Nuclear magnetic resonance; Materials science; Voxel; Metric (unit); Tensor (intrinsic definition); Biological system; Physics; Mathematics; Computer science; Optics; Magnetic resonance imaging; Artificial intelligence; Geology; Geometry; Medicine; Biology; Thermodynamics; Radiology","score_opus":0.04915096970614418,"score_gpt":0.35753922482154593,"score_spread":0.30838825511540174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307859783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87005997,0.00007703187,0.12568289,0.0020617,0.00033543917,0.0006768471,0.0001272646,0.00033877796,0.00064005516],"genre_scores_gemma":[0.9091906,0.000081852166,0.08855008,0.00021040006,0.00009048804,0.000336739,0.0007924867,0.00004785988,0.0006995107],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99884623,0.000032629,0.00033335265,0.00037287053,0.00026436817,0.00015052977],"domain_scores_gemma":[0.99875176,0.000041492487,0.00017448167,0.0008951995,0.000082744125,0.00005433956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009821607,0.00016697955,0.00030848462,0.00013683726,0.00008353212,0.000008504268,0.00025470922,0.00009507883,0.0007141739],"category_scores_gemma":[0.00009422908,0.00014563266,0.00011432331,0.00010663034,0.0000656468,0.00002883206,0.00059387943,0.0006500479,0.00001125476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029343856,0.0013577524,0.08772515,0.0015509422,0.00018996847,0.000075407486,0.0004688246,0.011285123,0.871429,0.0032714603,0.01175188,0.01060101],"study_design_scores_gemma":[0.0014828551,0.00037944203,0.10444476,0.00042645476,0.0003941194,0.00013623302,0.000042738186,0.023324382,0.76351684,0.054826256,0.050420295,0.0006056183],"about_ca_topic_score_codex":0.00004081351,"about_ca_topic_score_gemma":7.3293717e-7,"teacher_disagreement_score":0.10791219,"about_ca_system_score_codex":0.00009307016,"about_ca_system_score_gemma":0.00008523033,"threshold_uncertainty_score":0.7819703},"labels":[],"label_agreement":null},{"id":"W4307921398","doi":"10.1038/s41598-022-21615-4","title":"Author Correction: Speed-dependent and mode-dependent modulations of spatiotemporal modules in human locomotion extracted via tensor decomposition","year":2022,"lang":"en","type":"erratum","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Rehabilitation Institute; University Health Network","funders":"","keywords":"Decomposition; Tensor (intrinsic definition); Computer science; Tensor decomposition; Mode (computer interface); Biological system; Artificial intelligence; Topology (electrical circuits); Pattern recognition (psychology); Mathematics; Biology; Pure mathematics; Human–computer interaction; Combinatorics; Ecology","score_opus":0.046317595438620435,"score_gpt":0.36548290600621053,"score_spread":0.3191653105675901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307921398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.708455,0.001149954,0.12608926,0.0044395346,0.12995058,0.01256792,0.00038413168,0.0018736623,0.015089912],"genre_scores_gemma":[0.8789775,0.00003099353,0.0035478068,0.000021318447,0.00024905687,0.00017283257,0.004697834,0.00007828467,0.11222439],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9963774,0.00008443195,0.0011551047,0.0012095952,0.00090079795,0.00027263747],"domain_scores_gemma":[0.99726,0.0000251842,0.0010695015,0.0011841201,0.0003238933,0.00013734109],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007017776,0.0003037435,0.00054421724,0.0008450785,0.00047261154,0.00008713807,0.00011938455,0.00023899222,0.00026300078],"category_scores_gemma":[0.00007655027,0.00032795517,0.00013534467,0.00061400444,0.00023324422,0.00019740491,0.00016402794,0.0009171239,0.0000016364204],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000115323804,0.0030356427,0.01588607,0.00079350226,0.00011015997,0.0015315373,0.00069770566,0.011372611,0.23001383,0.0003132222,0.72020495,0.015925474],"study_design_scores_gemma":[0.0025706163,0.001289518,0.2053738,0.003052996,0.0012420946,0.013749653,0.0004477887,0.30152267,0.06588284,0.087655,0.3140649,0.0031481388],"about_ca_topic_score_codex":0.00030444015,"about_ca_topic_score_gemma":0.00010575537,"teacher_disagreement_score":0.40614003,"about_ca_system_score_codex":0.00034105158,"about_ca_system_score_gemma":0.00017275134,"threshold_uncertainty_score":0.99991727},"labels":[],"label_agreement":null},{"id":"W4307934660","doi":"10.1016/j.clinph.2022.10.012","title":"Integration of white matter architecture to stereo-EEG better describes epileptic spike propagation","year":2022,"lang":"en","type":"article","venue":"Clinical Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Stereoelectroencephalography; Spike (software development); White matter; Tractography; Electroencephalography; Diffusion MRI; Epilepsy; Neuroscience; Connectome; Computer science; Pattern recognition (psychology); Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Functional connectivity; Epilepsy surgery; Radiology","score_opus":0.08989667930491678,"score_gpt":0.3891797241400694,"score_spread":0.2992830448351526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4307934660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96129113,0.000003325397,0.024659395,0.01293609,0.0001583085,0.00066213676,0.000020415137,0.000084411055,0.0001847734],"genre_scores_gemma":[0.96647805,0.000004072466,0.01386513,0.018940043,0.00013038734,0.00018026785,0.000053486758,0.000029857412,0.00031869087],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99852794,0.00022068822,0.0005348447,0.00042419424,0.0001230231,0.00016933134],"domain_scores_gemma":[0.9990279,0.0001611994,0.00015561433,0.000498434,0.00007064377,0.00008622762],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009878935,0.00012533292,0.00033814678,0.00010015214,0.00012150568,0.0000033168124,0.00016679188,0.000043526317,0.00028599805],"category_scores_gemma":[0.00013148972,0.00010556788,0.00013573811,0.0002343797,0.00013827675,0.00003213031,0.00031013045,0.0005559611,0.000050931278],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005972058,0.00057942135,0.017572626,0.000052357478,0.0000162523,0.000023992536,0.00014420312,0.00041002428,0.9419744,0.00036824564,0.0047435528,0.03351774],"study_design_scores_gemma":[0.000711,0.004324977,0.9638805,0.000040255753,0.00007901965,0.000111293506,0.000030068819,0.0006549598,0.0041638394,0.006246741,0.019537238,0.00022013976],"about_ca_topic_score_codex":0.0000028049305,"about_ca_topic_score_gemma":3.8870516e-7,"teacher_disagreement_score":0.94630784,"about_ca_system_score_codex":0.000017379562,"about_ca_system_score_gemma":0.000024081743,"threshold_uncertainty_score":0.43049332},"labels":[],"label_agreement":null},{"id":"W4308327065","doi":"10.1016/j.brainres.2022.148152","title":"Diffusion tensor imaging of superficial prefrontal white matter in healthy aging","year":2022,"lang":"en","type":"article","venue":"Brain Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University Hospital Foundation","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Prefrontal cortex; Psychology; Neuroscience; Voxel; Orbitofrontal cortex; Tractography; Dorsolateral prefrontal cortex; Magnetic resonance imaging; Medicine; Cognition; Radiology","score_opus":0.11251255876961173,"score_gpt":0.4458502737399943,"score_spread":0.33333771497038256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308327065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9235075,0.0001218434,0.0004925996,0.07292333,0.000022918544,0.00073406147,0.000020226025,0.000052932457,0.0021245766],"genre_scores_gemma":[0.9947418,0.000013377692,0.0021368577,0.001777574,0.00004635902,0.00021019642,0.000021263259,0.000027133448,0.0010254366],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99844915,0.00017429657,0.00022534732,0.0002921386,0.000506175,0.00035288368],"domain_scores_gemma":[0.9993478,0.00015289815,0.000030760217,0.0003302199,0.00006859743,0.00006969123],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006796742,0.00006860632,0.0001532281,0.00038944656,0.00020528793,0.0000079512465,0.00016382219,0.000014667553,0.0004724031],"category_scores_gemma":[0.00007432813,0.000068738766,0.00003844407,0.00054854405,0.0001048037,0.000044198103,0.00039985092,0.0006703155,0.000010754991],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026334857,0.00033453092,0.94244295,0.00007209693,0.0000019130628,0.000053315158,0.00048236694,0.000017937082,0.03420554,0.00040371757,0.017736543,0.003985723],"study_design_scores_gemma":[0.0016264535,0.00044731647,0.9501374,0.00009562745,0.000003886932,0.00014879293,0.00232964,0.0039662006,0.0013486007,0.0015829871,0.038158108,0.0001549946],"about_ca_topic_score_codex":0.0002099281,"about_ca_topic_score_gemma":0.000011805402,"teacher_disagreement_score":0.07123429,"about_ca_system_score_codex":0.00016435685,"about_ca_system_score_gemma":0.00009518672,"threshold_uncertainty_score":0.5172483},"labels":[],"label_agreement":null},{"id":"W4308510056","doi":"10.1148/radiol.222302","title":"Ultralow-Field-Strength MRI and Artificial Intelligence: How Low Can We Go and How High Can We Reach?","year":2022,"lang":"en","type":"letter","venue":"Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Artificial intelligence; Magnetic resonance imaging; MEDLINE; Nuclear medicine; Medical physics; Computer science; Radiology","score_opus":0.044520975019822495,"score_gpt":0.30500679687531934,"score_spread":0.26048582185549685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308510056","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003189095,0.00080205366,0.0045401724,0.99004275,0.00025898375,0.0005932638,0.00025571388,0.00020903324,0.00010893008],"genre_scores_gemma":[0.16294026,0.04393895,0.027999738,0.74006647,0.008783434,0.0010712164,0.0030934203,0.00035153647,0.011754961],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982787,0.000116959534,0.00021341842,0.0007820686,0.00014847759,0.00046041803],"domain_scores_gemma":[0.9986988,0.0003772509,0.0001739473,0.0005882306,0.000038459504,0.00012336289],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000089441055,0.0003570565,0.0006514641,0.00020161667,0.0001679956,0.000034967456,0.00020105884,0.00049882417,0.00009697449],"category_scores_gemma":[0.000104980376,0.00033094516,0.000077282784,0.00016216305,0.0003174071,0.000026680134,0.00008216111,0.0021768617,0.0000013706203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004808442,0.000028017907,0.00024570414,0.00020761084,0.000064614185,0.0006792359,0.00018016428,0.0000013337267,0.003057919,0.002446056,0.9450789,0.04796235],"study_design_scores_gemma":[0.00013845957,0.00062304613,0.00005122428,0.0000679956,0.00014587237,0.0015463613,0.000093115385,0.000090036025,0.0025662533,0.017318312,0.9769952,0.0003641244],"about_ca_topic_score_codex":0.000070069735,"about_ca_topic_score_gemma":0.00002602101,"teacher_disagreement_score":0.24997628,"about_ca_system_score_codex":0.0000940839,"about_ca_system_score_gemma":0.00009104703,"threshold_uncertainty_score":0.9999143},"labels":[],"label_agreement":null},{"id":"W4308890622","doi":"10.1038/s41380-022-01833-y","title":"Whole-brain white matter abnormalities in human cocaine and heroin use disorders: association with craving, recency, and cumulative use","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; Canadian Institutes of Health Research; National Institute on Drug Abuse; U.S. Department of Health and Human Services; Government of Canada; National Center for Advancing Translational Sciences","keywords":"Fractional anisotropy; White matter; Psychology; Cocaine dependence; Craving; Addiction; Diffusion MRI; Heroin; Psychiatry; Internal medicine; Medicine; Drug; Magnetic resonance imaging","score_opus":0.020536309574435675,"score_gpt":0.30000881505397486,"score_spread":0.27947250547953917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308890622","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96525323,0.00013904736,0.0023868869,0.031433534,0.000023352344,0.00047722828,0.000033058266,0.00007144822,0.00018223868],"genre_scores_gemma":[0.9803196,0.000018864283,0.011876944,0.0052262065,0.00001616106,0.00014293214,0.00008901348,0.000044499848,0.0022657823],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904084,0.00009349734,0.00018614065,0.00030777146,0.00018848159,0.00018329371],"domain_scores_gemma":[0.99952406,0.000044268112,0.00011443664,0.00023879776,0.000026283155,0.000052140073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014120905,0.00013830568,0.00016944297,0.00011808343,0.00017069798,0.000048389327,0.000046464265,0.000031388794,0.000028161552],"category_scores_gemma":[0.000023666116,0.000139047,0.000025430338,0.00020646883,0.0000518188,0.000168826,0.00008616487,0.0003093787,7.2945295e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004373025,0.0001222701,0.99133116,0.000032159773,0.000017251374,0.000011104655,0.00033051512,0.00005124753,0.002158294,0.0013219708,0.004526973,0.000053318723],"study_design_scores_gemma":[0.0018660545,0.00041703397,0.973615,0.00011298139,0.000058477082,0.00008143274,0.00052085257,0.00021034073,0.0001716784,0.0067772274,0.015869234,0.00029968773],"about_ca_topic_score_codex":0.0001250205,"about_ca_topic_score_gemma":0.00010900777,"teacher_disagreement_score":0.02620733,"about_ca_system_score_codex":0.00007184853,"about_ca_system_score_gemma":0.000023241295,"threshold_uncertainty_score":0.56701726},"labels":[],"label_agreement":null},{"id":"W4309047156","doi":"10.1016/j.neuroimage.2022.119750","title":"Comparing myelin-sensitive magnetic resonance imaging measures and resulting g-ratios in healthy and multiple sclerosis brains","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Philips (Canada)","funders":"Faculty of Medicine, Munich University of Technology; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Friedrich-Ebert-Stiftung; Deutsche Forschungsgemeinschaft","keywords":"Myelin; Multiple sclerosis; Magnetization transfer; Magnetic resonance imaging; White matter; Nuclear magnetic resonance; Chemistry; Nuclear medicine; Medicine; Central nervous system; Internal medicine; Physics; Radiology; Immunology","score_opus":0.11514152422329235,"score_gpt":0.31839195281027893,"score_spread":0.20325042858698658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309047156","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.989622,0.001916489,0.000851216,0.005901657,0.000032301865,0.00073537533,0.000031050746,0.00020829822,0.00070163485],"genre_scores_gemma":[0.9904093,0.0002940163,0.0061452757,0.0029511729,0.000033763106,0.00006665846,0.000009716268,0.000036891433,0.00005321725],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985932,0.000112849426,0.0002849457,0.00052871637,0.0002050883,0.00027516898],"domain_scores_gemma":[0.99928963,0.00021328112,0.00007912487,0.00027644803,0.00004228958,0.00009920498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025898384,0.00014857127,0.00024282893,0.00014802295,0.00037065116,0.000033034783,0.00006715332,0.000014607754,0.0000035318258],"category_scores_gemma":[0.00024822375,0.00016979122,0.000025198584,0.0002819644,0.00012612417,0.00009859466,0.00024949806,0.000482294,7.9529883e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007393775,0.00022236143,0.63591444,0.00007970619,0.0000026430887,0.0002744344,0.0012614495,0.00012513404,0.2577537,0.00038533242,0.00072953355,0.102511905],"study_design_scores_gemma":[0.0025075094,0.00027569762,0.94361484,0.00009365126,0.000017013213,0.00031218326,0.00038315103,0.040850118,0.0017139297,0.00015725555,0.009854879,0.00021975898],"about_ca_topic_score_codex":0.00011988917,"about_ca_topic_score_gemma":0.00003175923,"teacher_disagreement_score":0.30770043,"about_ca_system_score_codex":0.000056425415,"about_ca_system_score_gemma":0.000028977378,"threshold_uncertainty_score":0.69238853},"labels":[],"label_agreement":null},{"id":"W4309508399","doi":"10.1093/brain/awac436","title":"Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status","year":2022,"lang":"en","type":"review","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":94,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Ministero dell’Istruzione, dell’Università e della Ricerca; Stichting MS Research; Fundação de Amparo à Pesquisa do Estado de São Paulo; Canada Research Chairs; Università degli Studi G. d'Annunzio Chieti - Pescara; ZonMw; Dipartimenti di Eccellenza","keywords":"Neuroscience; Positron emission tomography; Magnetic resonance imaging; Pet imaging; Myelin; Psychology; Medicine; Medical physics; Radiology; Central nervous system","score_opus":0.22788593565350854,"score_gpt":0.46522329672626705,"score_spread":0.23733736107275852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309508399","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000044631393,0.9948075,0.0029205605,0.00030540302,0.000005181559,0.0012639234,0.00015944315,0.00015997399,0.0003334261],"genre_scores_gemma":[0.000019926234,0.9567469,0.04246986,0.000096398355,0.000019283494,0.00027642754,0.00027198636,0.000055173517,0.00004403921],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989798,0.000115606104,0.00028836608,0.00037395398,0.00010510725,0.00013715857],"domain_scores_gemma":[0.9989492,0.00031224694,0.00028633382,0.00034146674,0.00003867853,0.00007206344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022191682,0.00023089144,0.0007277016,0.00016242915,0.000081685066,0.00001475764,0.000069572314,0.000027122724,0.000024362798],"category_scores_gemma":[0.000052037147,0.00016462641,0.000059440354,0.00024356287,0.00012818581,0.0000918843,0.000087533524,0.00024809781,2.4347057e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013323609,0.00004271603,0.000024707288,0.005284507,0.000022467959,0.000016152555,0.00010692188,4.7554376e-8,0.000035557572,0.0040917913,0.00012770385,0.9902341],"study_design_scores_gemma":[0.0001277055,0.0003176296,0.000011076966,0.0041262214,0.00016803028,0.0005152842,0.0001271069,0.000028832024,0.00006879936,0.00073714333,0.9936064,0.00016577508],"about_ca_topic_score_codex":0.000027829632,"about_ca_topic_score_gemma":0.0000025974964,"teacher_disagreement_score":0.9934787,"about_ca_system_score_codex":0.00003695319,"about_ca_system_score_gemma":0.00010191266,"threshold_uncertainty_score":0.671327},"labels":[],"label_agreement":null},{"id":"W4309772416","doi":"10.1016/j.pscychresns.2022.111568","title":"Better characterization of attention and hyperactivity/impulsivity in children with ADHD: The key to understanding the underlying white matter microstructure","year":2022,"lang":"en","type":"review","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health and Social Services Centre University Institute of Geriatrics of Sherbrooke; Q & T Research; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Université de Sherbrooke","keywords":"Endophenotype; Impulsivity; Diffusion MRI; Psychology; Attention deficit hyperactivity disorder; White matter; Cognitive psychology; Neuroscience; Clinical psychology; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.2097419401037088,"score_gpt":0.4361291023351229,"score_spread":0.2263871622314141,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309772416","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36478814,0.41425034,0.01744421,0.17247464,0.0006830256,0.02848965,0.0005620326,0.0003741395,0.00093380077],"genre_scores_gemma":[0.13839321,0.8519551,0.002994834,0.0033337618,0.0005686535,0.0015128035,0.00048985827,0.0004591586,0.0002925892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973186,0.00056883256,0.0004174927,0.0006935909,0.0005541261,0.00044734278],"domain_scores_gemma":[0.9985277,0.00025429283,0.00025991135,0.00083136116,0.000042718548,0.00008399435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074960425,0.00030834347,0.0005970144,0.00050671154,0.00057716796,0.00013089665,0.0003776161,0.00005975208,0.000040090363],"category_scores_gemma":[0.000036238944,0.00018578811,0.00012335712,0.001400624,0.00024728713,0.0001616984,0.00039820967,0.0020736037,0.000003547775],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015377172,0.00032200283,0.7849909,0.007021015,0.00020922093,0.000020112228,0.0008811875,0.000007138315,0.0020854182,0.0006587616,0.00082467915,0.20282578],"study_design_scores_gemma":[0.00086662424,0.00034646597,0.770126,0.0065083983,0.00068859756,0.0026106767,0.00065925723,0.000108171014,0.0000045221204,0.001827083,0.21550874,0.00074549206],"about_ca_topic_score_codex":0.000025836489,"about_ca_topic_score_gemma":0.000006615227,"teacher_disagreement_score":0.43770477,"about_ca_system_score_codex":0.00018083237,"about_ca_system_score_gemma":0.00016630182,"threshold_uncertainty_score":0.90088916},"labels":[],"label_agreement":null},{"id":"W4309900061","doi":"10.21203/rs.3.rs-2259594/v1","title":"Corticostriatal Structural Connectivity and Integrity in Children with Hydrocephalus and Executive Dysfunction","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Executive dysfunction; Hydrocephalus; Psychology; Executive functions; Neuroscience; Cognition; Medicine; Psychiatry; Magnetic resonance imaging; Radiology; Neuropsychology","score_opus":0.09079463897647834,"score_gpt":0.42693618329914906,"score_spread":0.33614154432267074,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4309900061","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9956184,0.00037595927,0.00045569116,0.00090243196,0.000014797835,0.0021726722,0.00016535023,0.00009518738,0.00019952621],"genre_scores_gemma":[0.9978045,0.00039703396,0.0009863519,0.000024808043,0.000048643466,0.0004127114,0.0002358723,0.000026340904,0.000063741274],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982724,0.00017457861,0.00016067846,0.0006678976,0.00044183715,0.0002825817],"domain_scores_gemma":[0.99913484,0.00014149629,0.00006650917,0.0003893836,0.00013390038,0.00013388394],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0004057018,0.00017506226,0.00030194016,0.0002714318,0.00019950734,0.000044143562,0.00008945219,0.00011064063,0.000027740818],"category_scores_gemma":[0.00024186882,0.00014720863,0.00002792638,0.00029427474,0.00025004108,0.00006797846,0.0008708355,0.0030419312,4.045398e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004775554,0.00009627778,0.98981893,0.0002418335,0.000042750507,0.000035372337,0.00020957195,0.00002065842,0.00035011294,0.0007231951,0.000109045264,0.007874704],"study_design_scores_gemma":[0.0009972027,0.0005713971,0.9903564,0.00023514208,0.000026382675,0.00024589992,0.00035088067,0.0013101785,0.0002767048,0.005379136,0.00009872627,0.00015197616],"about_ca_topic_score_codex":0.00091915217,"about_ca_topic_score_gemma":0.000052118376,"teacher_disagreement_score":0.0077227275,"about_ca_system_score_codex":0.00025659928,"about_ca_system_score_gemma":0.00018991501,"threshold_uncertainty_score":0.9992581},"labels":[],"label_agreement":null},{"id":"W4310030087","doi":"10.1101/2022.11.23.22282135","title":"Predicting cognitive decline in a low-dimensional representation of brain morphology","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; Fundamental Research Funds for the Central Universities; Center for Advanced Brain Imaging; McDonnell Center for Systems Neuroscience; Alvin J. Siteman Cancer Center; Genentech; National Institutes of Health; IXICO; Servier; National Science Foundation; China Postdoctoral Science Foundation; Foundation for the National Institutes of Health; Stavros Niarchos Foundation; University of Southern California; Eisai; National Natural Science Foundation of China; U.S. Department of Defense; Commonwealth Scientific and Industrial Research Organisation; Northern California Institute for Research and Education; Dana Foundation; H. Lundbeck A/S; Bristol-Myers Squibb; Southwest University; Natural Science Foundation of Chongqing; Université Laval; Natural Sciences and Engineering Research Council of Canada; Child Mind Institute; Pfizer; Biogen; BioClinica; Canadian Institutes of Health Research; Foundation for Barnes-Jewish Hospital; F. Hoffmann-La Roche; Yale University; Novartis Pharmaceuticals Corporation; American Hearing Research Foundation; Biotechnology and Biological Sciences Research Council; Chongqing Postdoctoral Science Foundation; New York State Office of Mental Health; Alzheimer's Association; Leon Levy Foundation; Alzheimer's Disease Neuroimaging Initiative; James S. McDonnell Foundation; Eli Lilly and Company; Alliance de recherche numérique du Canada; Canada First Research Excellence Fund; Brain Research Foundation; Meso Scale Diagnostics; Fok Ying Tung Education Foundation","keywords":"Neurodegeneration; Cognitive decline; Neuroimaging; Cognition; Psychology; Representation (politics); Neuroscience; Cognitive neuroscience; Alzheimer's disease; Pattern recognition (psychology); Artificial intelligence; Medicine; Disease; Computer science; Cognitive psychology; Pathology; Dementia","score_opus":0.07750956191120476,"score_gpt":0.40477031115933704,"score_spread":0.3272607492481323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310030087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99051964,0.000088501525,0.0032884637,0.004450125,0.00009211938,0.0008777135,0.000095560186,0.00011645199,0.00047142015],"genre_scores_gemma":[0.99124825,0.000043889297,0.0065426105,0.0010318697,0.00006347366,0.00041685766,0.0004471632,0.000033484695,0.00017242183],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984617,0.00010973243,0.0004931445,0.00051369873,0.00026451016,0.00015719185],"domain_scores_gemma":[0.99866885,0.00044712922,0.00031412768,0.0004057325,0.00011252661,0.00005163141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030323863,0.00014948996,0.00040508868,0.00023816846,0.00003636876,0.0000030461908,0.00013320528,0.00010298077,0.0002109751],"category_scores_gemma":[0.000836665,0.00015877036,0.00010371844,0.0003024409,0.00010474788,0.000021537318,0.00081578875,0.00081495586,0.0000023306209],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002349886,0.0003749133,0.9763396,0.00019479032,0.000029184213,0.00017136712,0.00015951558,0.0011128304,0.01997352,0.00017663845,0.00019924607,0.0010334271],"study_design_scores_gemma":[0.0018266976,0.00022954146,0.9534505,0.0009200679,0.000114202994,0.00015481614,0.00015061945,0.010701728,0.022216015,0.009545522,0.00043371445,0.0002565902],"about_ca_topic_score_codex":0.00013182679,"about_ca_topic_score_gemma":0.000009932685,"teacher_disagreement_score":0.02288909,"about_ca_system_score_codex":0.000055483106,"about_ca_system_score_gemma":0.000113804854,"threshold_uncertainty_score":0.64744675},"labels":[],"label_agreement":null},{"id":"W4310060197","doi":"10.1038/s41380-022-01870-7","title":"Accelerated cortical thinning precedes and predicts conversion to psychosis: The NAPLS3 longitudinal study of youth at clinical high-risk","year":2022,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Mental Health; U.S. Department of Health and Human Services; National Science Foundation","keywords":"Psychosis; Prodrome; Psychology; Neuroimaging; Medicine; Internal medicine; Neuroscience; Psychiatry","score_opus":0.08466840974853318,"score_gpt":0.38405835442455993,"score_spread":0.29938994467602675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310060197","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99208856,0.0002205126,0.0035682234,0.0024336367,0.0002461611,0.0012176007,0.000032727756,0.000119736374,0.00007286032],"genre_scores_gemma":[0.9940744,0.000041484553,0.0044835308,0.0011322802,0.00004896897,0.0001403616,0.000018746416,0.000030037425,0.000030203975],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99836767,0.00022676568,0.00041270623,0.0004675641,0.00034663998,0.00017866291],"domain_scores_gemma":[0.9989985,0.000062511484,0.00016345078,0.00058181724,0.000059055095,0.00013467092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037040876,0.00014313639,0.00025906527,0.00006468534,0.0004193783,0.000012089285,0.00019269978,0.000034605295,0.000037174155],"category_scores_gemma":[0.00006436345,0.00011199683,0.000075499505,0.00034571683,0.0000895132,0.000023773697,0.00037772136,0.0005471539,0.0000023163827],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061636156,0.0012825906,0.9931173,0.000023394114,0.000112634996,0.000012422012,0.00060282066,0.00010421143,0.0008875476,0.0002911537,0.0024640404,0.00048556182],"study_design_scores_gemma":[0.0033486711,0.004837196,0.98542047,0.000063024694,0.0006894441,0.00007656224,0.0027492177,0.00055207015,0.0007783484,0.00049002876,0.0007786574,0.00021628912],"about_ca_topic_score_codex":0.00006523404,"about_ca_topic_score_gemma":0.000006728307,"teacher_disagreement_score":0.0076967706,"about_ca_system_score_codex":0.00003074995,"about_ca_system_score_gemma":0.00003618183,"threshold_uncertainty_score":0.4567098},"labels":[],"label_agreement":null},{"id":"W4310060332","doi":"10.1038/s41597-022-01833-1","title":"TractoInferno - A large-scale, open-source, multi-site database for machine learning dMRI tractography","year":2022,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada; Wellcome Trust","keywords":"Computer science; Tractography; Scale (ratio); Database; Artificial intelligence; Diffusion MRI; Cartography; Magnetic resonance imaging; Medicine; Geography","score_opus":0.17628452514973905,"score_gpt":0.40893639807620985,"score_spread":0.2326518729264708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310060332","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01682703,0.0005593973,0.8746315,0.0033587143,0.0005931184,0.0041834502,0.098179646,0.0009099359,0.0007571521],"genre_scores_gemma":[0.19899508,0.00007959909,0.5228777,0.0019345926,0.00015874063,0.0013042343,0.2406809,0.00019838789,0.03377079],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976888,0.000055906323,0.00029823306,0.0011956074,0.0003627712,0.00039873002],"domain_scores_gemma":[0.99683195,0.0000967507,0.00015959928,0.002671687,0.00007061695,0.00016940193],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0015749015,0.00016343473,0.00023958359,0.00024371297,0.0014995061,0.00024755165,0.0016127165,0.00002339076,0.00040143207],"category_scores_gemma":[0.00019818303,0.00015987012,0.0000808717,0.00089844014,0.00013354402,0.00050522387,0.0030408883,0.0005368907,0.000017772558],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007000723,0.007656968,0.036283653,0.00032090652,0.000119897595,0.00008722642,0.0013562719,0.0003173903,0.14746787,0.0014116329,0.71857524,0.085702844],"study_design_scores_gemma":[0.0014149433,0.000082460465,0.0011504653,0.000019449299,0.0000699386,0.000052824493,0.00015051823,0.07220827,0.0004291373,0.00007579253,0.92417866,0.00016753653],"about_ca_topic_score_codex":0.000050842744,"about_ca_topic_score_gemma":0.000058808182,"teacher_disagreement_score":0.3517539,"about_ca_system_score_codex":0.00002836081,"about_ca_system_score_gemma":0.0000832712,"threshold_uncertainty_score":0.9998004},"labels":[],"label_agreement":null},{"id":"W4310191118","doi":"10.3389/fnana.2022.960475","title":"Histology-informed automatic parcellation of white matter tracts in the rat spinal cord","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute; Polytechnique Montréal","funders":"Canadian Institutes of Health Research; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Polytechnique Montréal; Réseau en Bio-Imagerie du Quebec","keywords":"White matter; Axon; Spinal cord; Morphometrics; Neuroscience; Anatomy; Segmentation; Biology; Myelin; Brain atlas; Corticospinal tract; Cluster analysis; Artificial intelligence; Diffusion MRI; Central nervous system; Pattern recognition (psychology); Computer science; Magnetic resonance imaging; Medicine; Zoology; Radiology","score_opus":0.033636958698236595,"score_gpt":0.3281442183020419,"score_spread":0.2945072596038053,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310191118","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9833854,0.00016393876,0.0031631934,0.007773649,0.00026240828,0.0010299413,0.000005560171,0.000069347814,0.004146568],"genre_scores_gemma":[0.9882933,0.000020336098,0.009082063,0.0021645103,0.000010172922,0.00018726567,0.000014728248,0.000014378844,0.0002132818],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990609,0.000080107406,0.0003166081,0.0001792539,0.00019688903,0.00016618399],"domain_scores_gemma":[0.99946916,0.000037227375,0.00013183647,0.00032255612,0.000014617533,0.000024578603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014668853,0.000092190145,0.00020715107,0.00025553643,0.00008494805,0.0000034510044,0.00018982354,0.000022846172,0.00007712175],"category_scores_gemma":[0.000028893333,0.000079380436,0.000046223497,0.0004693627,0.00007626924,0.000055660472,0.00006458132,0.00036740303,0.000002124606],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047214513,0.00036614656,0.8558242,0.00017560099,0.0000077114155,0.00016976504,0.0008750303,0.00017510663,0.0004250303,0.0005213711,0.12517427,0.015813665],"study_design_scores_gemma":[0.0017550022,0.00071760616,0.8245226,0.000062319166,0.000050477003,0.00038792877,0.0008507495,0.014689956,0.000296032,0.004177398,0.15227309,0.00021680784],"about_ca_topic_score_codex":0.000007350474,"about_ca_topic_score_gemma":0.0000018715361,"teacher_disagreement_score":0.03130153,"about_ca_system_score_codex":0.00010513942,"about_ca_system_score_gemma":0.000052678864,"threshold_uncertainty_score":0.32370403},"labels":[],"label_agreement":null},{"id":"W4310461041","doi":"10.1002/mpr.1955","title":"White‐matter correlates of anxiety: The contribution of the corpus‐callosum to the study of anxiety and stress‐related disorders","year":2022,"lang":"en","type":"article","venue":"International Journal of Methods in Psychiatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Ministry of Health, British Columbia; Ministry of Health, State of Israel; Deutsche Forschungsgemeinschaft","keywords":"Corpus callosum; Psychology; Fractional anisotropy; Anxiety; White matter; Cognition; Diffusion MRI; Neuropathology; Clinical psychology; Neuroscience; Internal medicine; Medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.06260866962514129,"score_gpt":0.48691996670838406,"score_spread":0.4243112970832428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310461041","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9625889,0.0007949058,0.008249752,0.026566498,0.00040944887,0.0010697134,0.000032789267,0.0000037775148,0.00028421558],"genre_scores_gemma":[0.9910899,0.0007822449,0.007861583,0.0001043752,0.000041588915,0.00004174551,0.0000015521749,0.0000105979425,0.00006641389],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968093,0.0011866287,0.0007459314,0.00014266938,0.000984014,0.00013146029],"domain_scores_gemma":[0.9976081,0.00078929256,0.0005273098,0.00032730494,0.00071237126,0.000035598023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045793233,0.00007686332,0.000221023,0.00033092726,0.00012618664,0.00000939032,0.0007978603,0.00003086117,0.000051581555],"category_scores_gemma":[0.00054175564,0.00004118274,0.00011436211,0.0010485208,0.00018034877,0.000035759964,0.0004169679,0.0010115316,1.9954021e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039741088,0.00063990586,0.980657,0.00000914702,0.000095780546,8.0134555e-7,0.0009155094,0.001161528,0.00084178295,0.0011607757,0.0012411262,0.012879237],"study_design_scores_gemma":[0.0018936754,0.00083279423,0.9731681,0.00007691164,0.00007387947,0.00015600587,0.003554909,0.0012320131,0.00066677085,0.013156044,0.0051289448,0.00006000181],"about_ca_topic_score_codex":0.000064791675,"about_ca_topic_score_gemma":0.00001652246,"teacher_disagreement_score":0.028500998,"about_ca_system_score_codex":0.000069436435,"about_ca_system_score_gemma":0.00010313806,"threshold_uncertainty_score":0.43946573},"labels":[],"label_agreement":null},{"id":"W4310490701","doi":"10.32473/ufjur.24.130754","title":"Evaluating Spatial Filtering on Diffusion MRI Data Harmonization in Parkinsonism","year":2022,"lang":"en","type":"article","venue":"UF Journal of Undergraduate Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"University of Florida","keywords":"Parkinsonism; Filter (signal processing); Artificial intelligence; Progressive supranuclear palsy; Computer science; Gaussian filter; Pattern recognition (psychology); Atrophy; Machine learning; Data mining; Medicine; Computer vision; Disease; Pathology","score_opus":0.4707908280101828,"score_gpt":0.5337617081473054,"score_spread":0.0629708801371226,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310490701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6433305,0.0004202333,0.15116179,0.20206547,0.00027082846,0.001406916,0.000046567424,0.00007338448,0.001224311],"genre_scores_gemma":[0.9858758,0.0006022399,0.012962273,0.00013833941,0.000137656,0.000019613579,0.00003356323,0.000026233663,0.00020431499],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974523,0.00037410468,0.00039728798,0.00025304552,0.0012607949,0.00026245424],"domain_scores_gemma":[0.9987205,0.0002884337,0.0001739114,0.00051326345,0.00020920637,0.00009462931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027315933,0.0000817409,0.00018047343,0.0005098554,0.00032890314,0.000032278484,0.00043331354,0.000021016416,0.00004685579],"category_scores_gemma":[0.00047983747,0.000074463234,0.000037773963,0.0005841502,0.00004947992,0.00011733368,0.0006024169,0.001215154,0.0000045512634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002609429,0.0029794637,0.016105393,0.00020627117,0.00008208404,0.0013941142,0.0005910738,0.019266771,0.46106642,0.00749278,0.015887246,0.47231895],"study_design_scores_gemma":[0.009974875,0.009331083,0.020392016,0.001285653,0.00009797542,0.0023166647,0.0006516268,0.6648893,0.026662108,0.1384768,0.12531544,0.0006065088],"about_ca_topic_score_codex":0.00004447272,"about_ca_topic_score_gemma":0.0000047013873,"teacher_disagreement_score":0.6456225,"about_ca_system_score_codex":0.00029148968,"about_ca_system_score_gemma":0.00021099925,"threshold_uncertainty_score":0.5279307},"labels":[],"label_agreement":null},{"id":"W4310540129","doi":"10.3390/brainsci12121651","title":"Beyond the Dorsal Column Medial Lemniscus in Proprioception and Stroke: A White Matter Investigation","year":2022,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Medial lemniscus; Proprioception; Dorsum; White matter; Stroke (engine); Dorsal column nuclei; Anatomy; Physical medicine and rehabilitation; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Physics","score_opus":0.04855541148761758,"score_gpt":0.33101048278254025,"score_spread":0.28245507129492264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310540129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.894824,0.00003980186,0.00027796428,0.10308338,0.000038482085,0.00042712287,0.0000073655665,0.000036326877,0.0012655302],"genre_scores_gemma":[0.99060345,0.0000049501655,0.002885823,0.005572596,0.00003390937,0.00018712816,0.000005210651,0.0000043587515,0.00070255855],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99927753,0.000050638508,0.00010817633,0.00020251062,0.00024915597,0.00011201577],"domain_scores_gemma":[0.99974966,0.00006004737,0.00004656857,0.000105045554,0.000011825293,0.00002687698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004988028,0.000047937516,0.00006214174,0.00007406472,0.0003275978,0.000030537278,0.000106181185,0.000010968673,0.0000856073],"category_scores_gemma":[0.00004110565,0.000033208373,0.000012595912,0.00037358984,0.00043191126,0.00009049505,0.00009411788,0.00014323041,0.0000027628487],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030311314,0.0000696628,0.91295105,0.00001787977,0.0000023895057,0.000007968547,0.0032004393,0.00013330477,0.044078287,0.0054216753,0.02606246,0.008024575],"study_design_scores_gemma":[0.0006950651,0.00039172522,0.9366814,0.00001849811,0.000013963283,0.00017792541,0.0017383827,0.003693818,0.0013635347,0.031641364,0.023415739,0.00016861182],"about_ca_topic_score_codex":0.000024896217,"about_ca_topic_score_gemma":0.00002050997,"teacher_disagreement_score":0.09751078,"about_ca_system_score_codex":0.0000246964,"about_ca_system_score_gemma":0.000063174804,"threshold_uncertainty_score":0.25196508},"labels":[],"label_agreement":null},{"id":"W4310700692","doi":"10.1002/hbm.26165","title":"Fast three‐dimensional image generation for healthy brain aging using diffeomorphic registration","year":2022,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Center for Innovative Medicine; Eisai Incorporated; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; VINNOVA; Takeda Pharmaceuticals U.S.A.; Barncancerfonden; U.S. Department of Defense; Eli Lilly and Company; China Scholarship Council; Eisai; Fundación CajaCanarias; Alzheimer's Association; Stiftelsen för Gamla Tjänarinnor; Fujirebio US; Pfizer; BioClinica; Biogen; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; AbbVie; Hjärnfonden; F. Hoffmann-La Roche; Merck; Alzheimerfonden; Alzheimer's Drug Discovery Foundation; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Demensfonden; Meso Scale Diagnostics","keywords":"Neuroimaging; Artificial intelligence; Image registration; Magnetic resonance imaging; Pattern recognition (psychology); Computer science; Computer vision; Psychology; Image (mathematics); Neuroscience; Medicine; Radiology","score_opus":0.20356372646919996,"score_gpt":0.39389332839480556,"score_spread":0.1903296019256056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310700692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3617235,0.000052951065,0.60064495,0.035774842,0.000092047194,0.0012846761,0.000032873446,0.00027328328,0.00012085042],"genre_scores_gemma":[0.86101216,0.0000012269559,0.12282734,0.013106954,0.00090595253,0.0005415487,0.0008234048,0.00007846499,0.00070296274],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866253,0.000055965236,0.000337324,0.00042834246,0.00025259136,0.00026322858],"domain_scores_gemma":[0.99919116,0.00011496624,0.00020265234,0.0003398329,0.00007688247,0.00007448368],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.00047312857,0.00014593985,0.00019227045,0.00016469297,0.0015494488,0.000036971418,0.00009336094,0.000029144194,0.00007004826],"category_scores_gemma":[0.000083578234,0.0001703623,0.00008917419,0.00021050233,0.00006109402,0.000108489054,0.00008985962,0.00026129038,0.0000013417392],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001966781,0.00007254313,0.00033829617,0.000061012353,0.000008681998,0.0000061346145,0.000116034294,0.0007130835,0.97116053,0.008036186,0.018835658,0.0006321458],"study_design_scores_gemma":[0.0049108574,0.0010157358,0.019620094,0.0002584225,0.00010535232,0.0008106659,0.00044776782,0.8186009,0.0034856668,0.034319002,0.11535469,0.0010708652],"about_ca_topic_score_codex":0.000029667337,"about_ca_topic_score_gemma":0.000013487942,"teacher_disagreement_score":0.9676749,"about_ca_system_score_codex":0.00021547827,"about_ca_system_score_gemma":0.00007537321,"threshold_uncertainty_score":0.9997504},"labels":[],"label_agreement":null},{"id":"W4311103151","doi":"10.1101/2022.12.01.518514","title":"High-frequency longitudinal white matter diffusion- &amp; myelin-based MRI database: reliability and variability","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"","keywords":"Intraclass correlation; Reliability (semiconductor); Consistency (knowledge bases); Repeatability; White matter; Fiber bundle; Diffusion MRI; Diffusion; Fiber; Computer science; Nuclear medicine; Nuclear magnetic resonance; Statistics; Magnetic resonance imaging; Medicine; Materials science; Mathematics; Radiology; Physics; Artificial intelligence; Reproducibility","score_opus":0.030333482124366103,"score_gpt":0.28518161278224397,"score_spread":0.25484813065787787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311103151","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8925244,0.00025827714,0.09286772,0.007905767,0.0005366416,0.0025549373,0.0021416745,0.0011834184,0.000027133372],"genre_scores_gemma":[0.7715281,0.00016113039,0.22596562,0.0009680612,0.00023746034,0.00095922884,0.000016127196,0.00014563066,0.000018631186],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9955678,0.0002513743,0.0008191897,0.0021997052,0.0005829658,0.00057898555],"domain_scores_gemma":[0.9940714,0.00020224515,0.00046035327,0.0043722363,0.00046341537,0.00043034248],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0011452677,0.0006959269,0.0008681789,0.00024666009,0.00038252244,0.000103315884,0.00053215865,0.00033091274,0.0011677811],"category_scores_gemma":[0.00044177976,0.00072306144,0.00019324532,0.0005580067,0.00044078773,0.00012800866,0.0013026726,0.001886211,0.000043928256],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000116072995,0.00079846464,0.8633223,0.0014798361,0.000054509732,0.000063533145,0.0000041378516,0.00012788501,0.13102174,0.0009211675,0.0020883537,0.000002002393],"study_design_scores_gemma":[0.0009210431,0.0000722727,0.9766822,0.00040555026,0.00038278135,2.0965732e-7,8.804999e-7,0.00059139315,0.006948671,0.00013315139,0.012895595,0.0009662561],"about_ca_topic_score_codex":0.0001472279,"about_ca_topic_score_gemma":0.0000018992912,"teacher_disagreement_score":0.1330979,"about_ca_system_score_codex":0.00050659495,"about_ca_system_score_gemma":0.00058688584,"threshold_uncertainty_score":0.9997453},"labels":[],"label_agreement":null},{"id":"W4311287570","doi":"10.1002/mrm.29552","title":"Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; University of Toronto; University of British Columbia; International Collaboration On Repair Discoveries; Hospital for Sick Children; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"White matter; Magnetization transfer; Reproducibility; Nuclear magnetic resonance; Correlation; Correlation coefficient; Nuclear medicine; Myelin; Chemistry; Magnetic resonance imaging; Physics; Medicine; Internal medicine; Mathematics; Chromatography; Central nervous system; Statistics; Radiology","score_opus":0.023432144280844287,"score_gpt":0.3453809960211719,"score_spread":0.3219488517403276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311287570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81021065,0.007894742,0.00016867882,0.17799878,0.00007635361,0.0026428138,0.0000048186503,0.000027766935,0.00097541785],"genre_scores_gemma":[0.9939482,0.0004069813,0.00052641885,0.0041460013,0.000052669435,0.0006666129,0.000019217749,0.000011588782,0.00022227781],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981547,0.0004879361,0.00044575465,0.0004401342,0.00033843573,0.00013304206],"domain_scores_gemma":[0.997709,0.0013026315,0.000117752024,0.0008070269,0.000040734056,0.000022865297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037233885,0.000094271156,0.00026297197,0.00009880926,0.00009094928,0.0000023995774,0.00013705941,0.00002003664,0.00009013929],"category_scores_gemma":[0.0022323714,0.000051883002,0.00002383774,0.0007747287,0.0004678478,0.00002123941,0.000060352442,0.00032320502,7.004152e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006681534,0.0002017776,0.5458031,0.000342696,0.000007797841,0.00004395066,0.006894568,0.00014903814,0.0005533361,0.004257721,0.026097124,0.40896732],"study_design_scores_gemma":[0.014324643,0.004503025,0.9085236,0.00027020898,0.000062237814,0.00020054569,0.0011297422,0.0068422058,0.00010940565,0.005372848,0.058537733,0.0001237761],"about_ca_topic_score_codex":0.00036507408,"about_ca_topic_score_gemma":0.000021057407,"teacher_disagreement_score":0.40884352,"about_ca_system_score_codex":0.0000426402,"about_ca_system_score_gemma":0.000023137576,"threshold_uncertainty_score":0.26725182},"labels":[],"label_agreement":null},{"id":"W4311472414","doi":"10.52294/1cdce19c-e6db-4684-97cb-ae709da06a3f","title":"Visual QC Protocol for FreeSurfer Cortical Parcellations from Anatomical MRI","year":2022,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; St. Joseph’s Healthcare Hamilton; Health Sciences Centre; University Health Network; Western University; University of Toronto; Centre for Addiction and Mental Health; Queen's University; Toronto Western Hospital; University of British Columbia; Sunnybrook Health Science Centre; St. Michael's Hospital; University of Alberta; University of Calgary; Baycrest Hospital","funders":"","keywords":"Protocol (science); Neuroimaging; Computer science; Reliability (semiconductor); Visual inspection; Artificial intelligence; Reproducibility; Quality (philosophy); Neuroscience; Psychology; Medicine; Statistics; Pathology; Mathematics","score_opus":0.07041366652472753,"score_gpt":0.4066132231350453,"score_spread":0.33619955661031775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311472414","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02112007,0.000021488982,0.2572968,0.27285433,0.00029031848,0.44055584,0.0009427912,0.0023333428,0.0045850175],"genre_scores_gemma":[0.20420678,0.0000015906721,0.033754736,0.07350622,0.00043840625,0.68663824,0.00039736804,0.0001239175,0.0009327285],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892586,0.000044965098,0.00022111966,0.00039209187,0.00021207663,0.00020389885],"domain_scores_gemma":[0.99732745,0.002111419,0.00005289947,0.0003439069,0.000044178374,0.00012017641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049785227,0.00013048548,0.00017989548,0.000044048542,0.00030404722,0.000013330866,0.00012439891,0.00004100413,0.00047241704],"category_scores_gemma":[0.00058549613,0.00011772374,0.00010977816,0.00016579227,0.00005675283,0.00003026457,0.00011664278,0.00044918957,0.000009822704],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012489752,0.001659099,0.010423411,0.00005240957,0.000045213914,0.00009540848,0.00010612719,0.000092681454,0.1190303,0.011254602,0.852226,0.0037657279],"study_design_scores_gemma":[0.0011413133,0.00035173647,0.0042224973,0.000005960989,0.00003225402,0.000042476928,0.000011953364,0.01652275,0.0012192109,0.002351163,0.97397983,0.00011887741],"about_ca_topic_score_codex":0.000008343851,"about_ca_topic_score_gemma":0.0000011026476,"teacher_disagreement_score":0.24608241,"about_ca_system_score_codex":0.00003786877,"about_ca_system_score_gemma":0.000052820833,"threshold_uncertainty_score":0.51726353},"labels":[],"label_agreement":null},{"id":"W4311574494","doi":"10.1038/s41398-022-02261-w","title":"Differential association of antioxidative defense genes with white matter integrity in youth bipolar disorder","year":2022,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Hospital for Sick Children; University of Toronto; Heart and Stroke Foundation; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; University of Toronto; Myriad Genetics; Fondation Brain Canada; Centre for Addiction and Mental Health Foundation; Temerty Faculty of Medicine, University of Toronto; Government of Canada; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; SOD2; White matter; Allele; Oxidative stress; Diffusion MRI; Internal medicine; Superoxide dismutase; Psychology; Endocrinology; Biology; Genetics; Medicine; Magnetic resonance imaging; Gene","score_opus":0.027996501178580567,"score_gpt":0.29947439151782645,"score_spread":0.2714778903392459,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311574494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95527023,0.0002263827,0.033423338,0.009827392,0.00006472575,0.00038509181,0.00035722798,0.0000459054,0.0003997232],"genre_scores_gemma":[0.9865613,0.000017300661,0.012642392,0.00028592133,0.000031093186,0.000043607804,0.00027354647,0.000017267768,0.0001275587],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99917084,0.000046622255,0.00021548146,0.00018602856,0.0002728484,0.00010819947],"domain_scores_gemma":[0.9996548,0.00002475416,0.00011537459,0.00013191595,0.00004840465,0.000024731899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071000875,0.00009115585,0.00015086628,0.00011613055,0.00007487613,0.0000035247149,0.000058109046,0.000030437823,0.0004076454],"category_scores_gemma":[0.0000023144087,0.00008288525,0.000057772868,0.0002845214,0.000028204751,0.00005410549,0.0000124071,0.00031682986,0.0000023978562],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018990136,0.0003415508,0.99669874,0.00001987028,0.000020727817,3.1925552e-7,0.00031814296,0.00023984461,0.00034072888,0.0014146123,0.00016087586,0.00025468747],"study_design_scores_gemma":[0.0012234052,0.00010506707,0.99393374,0.000027029546,0.000064632004,0.000007011757,0.00022260095,0.00033555747,0.00010746539,0.0027871772,0.0010814671,0.00010486509],"about_ca_topic_score_codex":0.000029213465,"about_ca_topic_score_gemma":0.000046144294,"teacher_disagreement_score":0.031291097,"about_ca_system_score_codex":0.000034719436,"about_ca_system_score_gemma":0.00007142096,"threshold_uncertainty_score":0.44634312},"labels":[],"label_agreement":null},{"id":"W4311877713","doi":"10.3389/fnins.2022.1040799","title":"Integration of structural brain networks is related to openness to experience: A diffusion MRI study with CSD-based tractography","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Openness to experience; Connectome; Tractography; Psychology; Diffusion MRI; Connectomics; Trait; Personality; Cognitive psychology; Human Connectome Project; Neuroscience; Computer science; Social psychology; Magnetic resonance imaging; Medicine; Functional connectivity","score_opus":0.024578000767506724,"score_gpt":0.33974930545799886,"score_spread":0.31517130469049215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311877713","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7746085,0.000007627575,0.22183624,0.0018644684,0.00018868537,0.0014048173,0.000007863798,0.000055202345,0.000026628964],"genre_scores_gemma":[0.9764064,0.0000015023681,0.020087652,0.003011729,0.0000045769407,0.00039943928,0.000003867983,0.000015464608,0.000069367874],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99855524,0.000063354055,0.00025293513,0.0005341921,0.0003812583,0.00021303762],"domain_scores_gemma":[0.99931884,0.000024286066,0.000088789064,0.00041308466,0.00004238701,0.00011258692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015279296,0.00012708356,0.00020821908,0.00036385958,0.00020303196,0.000017688506,0.00034393911,0.000017177697,0.000010097466],"category_scores_gemma":[0.00006096682,0.00010714898,0.00003336413,0.0027292199,0.00011146876,0.000100201156,0.00016673592,0.00027705228,8.921613e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001341557,0.0011461072,0.7296812,0.000014584734,0.0000037310729,0.00009323163,0.01173211,0.049573157,0.18552433,0.0001735349,0.005806324,0.014910151],"study_design_scores_gemma":[0.002091152,0.00653915,0.7521476,0.000100389065,0.000025097537,0.0000500182,0.0072180806,0.21979624,0.00769042,0.0002911364,0.003597646,0.0004530508],"about_ca_topic_score_codex":0.000025233448,"about_ca_topic_score_gemma":0.0000037533669,"teacher_disagreement_score":0.20179793,"about_ca_system_score_codex":0.00005641083,"about_ca_system_score_gemma":0.00003743508,"threshold_uncertainty_score":0.43694088},"labels":[],"label_agreement":null},{"id":"W4311924630","doi":"10.1101/2022.12.18.520881","title":"A Unified Filtering Method for Estimating Asymmetric Orientation Distribution Functions: Where and How Asymmetry Occurs in the Brain","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health","keywords":"Computer science; Asymmetry; Voxel; Orientation (vector space); Diffusion MRI; Artificial intelligence; Human Connectome Project; Algorithm; Pattern recognition (psychology); Computer vision; Mathematics; Functional connectivity; Magnetic resonance imaging; Physics","score_opus":0.042332525860050964,"score_gpt":0.3286316681822924,"score_spread":0.2862991423222414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311924630","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049254037,0.00047900912,0.9401238,0.006404881,0.00029948933,0.0024365247,0.0006513769,0.00034506785,0.000005809471],"genre_scores_gemma":[0.5084931,0.0000900012,0.48787695,0.000459595,0.00022718855,0.002741792,0.000021055052,0.00008045563,0.000009851824],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998052,0.00018516177,0.00033791512,0.00080520153,0.00029028743,0.00032945836],"domain_scores_gemma":[0.9979467,0.00057896174,0.0003631206,0.0008169413,0.00019971562,0.00009457645],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012341796,0.00032418143,0.0003837066,0.00032499843,0.0003336749,0.0001622335,0.00024216427,0.00017402889,0.0000058237874],"category_scores_gemma":[0.0012293434,0.00030850925,0.00010642575,0.0012796032,0.000056229477,0.00012845386,0.0002619613,0.00086224877,7.601807e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012339427,0.003017977,0.085261986,0.015721241,0.0009214062,0.0003514829,0.00047739886,0.004499638,0.7613601,0.06691422,0.053800423,0.0064401967],"study_design_scores_gemma":[0.008327317,0.0014667985,0.36351866,0.0031677163,0.0018935545,0.0000039053884,0.000763031,0.31243196,0.052195508,0.0005208707,0.2517652,0.003945469],"about_ca_topic_score_codex":0.00003160548,"about_ca_topic_score_gemma":0.0000013592089,"teacher_disagreement_score":0.70916456,"about_ca_system_score_codex":0.00032296544,"about_ca_system_score_gemma":0.00017086772,"threshold_uncertainty_score":0.9999367},"labels":[],"label_agreement":null},{"id":"W4312086371","doi":"10.1002/alz.068292","title":"White Matter Correlates of Spoken Discourse in Cerebrovascular Disease","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Audiology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.033520605855789705,"score_gpt":0.3179134904236161,"score_spread":0.2843928845678264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086371","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9494563,0.029905166,0.0032668964,0.011112353,0.00021678943,0.0020306793,0.00015088878,0.00023225836,0.0036287191],"genre_scores_gemma":[0.9959623,0.000032703865,0.0031164573,0.0004970935,0.000013740767,0.00019040778,0.00008467702,0.00002515764,0.0000774425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991993,0.000026812662,0.00021401084,0.00022257428,0.0001833251,0.00015397747],"domain_scores_gemma":[0.99941695,0.0000112301,0.00007162739,0.0004112504,0.000018398987,0.000070528826],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000079398735,0.000093605304,0.00014924616,0.00009013891,0.00006043276,0.0000038831517,0.00011811416,0.000011284035,0.0018368029],"category_scores_gemma":[0.0000031705702,0.00009378408,0.000088035384,0.00019814199,0.000056526755,0.00005167972,0.00015817603,0.00015686273,0.00003931635],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004046258,0.00027981258,0.99280715,0.000006254632,0.00042064194,0.000018791676,0.000061197956,0.00007089747,0.0002229923,0.0003728269,0.004570158,0.0011288194],"study_design_scores_gemma":[0.0008032371,0.00007538421,0.9730379,0.000026983005,0.005834919,0.00002009694,0.00011057117,0.00038303173,0.0010862189,0.0012179682,0.017216576,0.00018713156],"about_ca_topic_score_codex":0.000019335754,"about_ca_topic_score_gemma":0.0000011724409,"teacher_disagreement_score":0.04650607,"about_ca_system_score_codex":0.000005816315,"about_ca_system_score_gemma":0.000027789209,"threshold_uncertainty_score":0.99907565},"labels":[],"label_agreement":null},{"id":"W4312086405","doi":"10.1002/alz.068795","title":"Resistance training improves white matter structural connectivity in older adults at‐risk for cognitive decline","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Western University","funders":"","keywords":"Resistance training; White matter; Cognition; Cognitive decline; Psychology; Gerontology; Training (meteorology); Resistance (ecology); Cognitive training; Physical medicine and rehabilitation; Medicine; Cognitive psychology; Neuroscience; Physical therapy; Dementia; Internal medicine; Geography; Disease; Magnetic resonance imaging; Biology","score_opus":0.038947083124337915,"score_gpt":0.3301936722006875,"score_spread":0.2912465890763496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086405","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9865818,0.0043345043,0.0037643686,0.002581951,0.00009105734,0.0018739847,0.00029568758,0.00012073468,0.00035589558],"genre_scores_gemma":[0.9833915,0.000012987794,0.013809378,0.0013893975,0.00004383999,0.0010381301,0.00018578528,0.000038341288,0.00009058903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99882805,0.000045359357,0.00026122146,0.00043390773,0.00015184254,0.0002796043],"domain_scores_gemma":[0.99937004,0.00012847298,0.00015987137,0.00022415086,0.000060223112,0.0000572509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016089446,0.00014943964,0.00021253552,0.000069411566,0.00029033903,0.000010175413,0.00009863628,0.000025890036,0.00028221062],"category_scores_gemma":[0.000029852756,0.00015444455,0.00007999771,0.00016328377,0.000056059347,0.00007640366,0.00017943433,0.0002307306,0.0000046874666],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042417636,0.0004937593,0.87734556,0.000077656194,0.002893448,0.00004965168,0.0045225727,0.000027424185,0.0067662597,0.0006507124,0.0106648505,0.09226636],"study_design_scores_gemma":[0.005349881,0.00024217615,0.96439725,0.000078195226,0.0040119295,0.000038226484,0.00080074125,0.0010810592,0.008205144,0.002172236,0.013204563,0.00041856972],"about_ca_topic_score_codex":0.000019055627,"about_ca_topic_score_gemma":0.00009873804,"teacher_disagreement_score":0.09184779,"about_ca_system_score_codex":0.000018561055,"about_ca_system_score_gemma":0.000027588778,"threshold_uncertainty_score":0.62980664},"labels":[],"label_agreement":null},{"id":"W4312086512","doi":"10.1002/alz.066686","title":"Cerebrovascular injury markers explain the effect of systemic vascular risk on cognitive decline in older adults with lower amyloid burden","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Toronto; Sunnybrook Hospital","funders":"","keywords":"Pittsburgh compound B; Medicine; Cognitive decline; Internal medicine; Cardiology; Effects of sleep deprivation on cognitive performance; Cerebral amyloid angiopathy; Framingham Risk Score; Neuroimaging; Hyperintensity; Cognition; Dementia; Disease; Magnetic resonance imaging; Radiology; Psychiatry","score_opus":0.010788339552064754,"score_gpt":0.27557401571480294,"score_spread":0.2647856761627382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086512","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9871427,0.008665875,0.00095751433,0.0002653421,0.00005186618,0.0026462122,0.000043999065,0.00008318144,0.0001433566],"genre_scores_gemma":[0.9977232,0.00026728644,0.0004192508,0.00025528506,0.000034343993,0.0011781519,0.00006701762,0.000050188824,0.0000052830333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982313,0.00031983352,0.00032295383,0.0004229773,0.00046008712,0.00024285678],"domain_scores_gemma":[0.9988896,0.00019717237,0.00020293084,0.0005971835,0.00005666264,0.00005645399],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006011268,0.0002179775,0.00033212415,0.00012442174,0.00016476716,0.000007648751,0.00020856621,0.00003381648,0.0001647699],"category_scores_gemma":[0.000037824095,0.00014959821,0.0001599077,0.0004004647,0.00009701278,0.000043050808,0.00017636913,0.00043315568,0.000010521735],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.026314251,0.0026320035,0.6549869,0.0005661527,0.047179032,0.0003434327,0.0036712484,0.0025439358,0.0074122604,0.00030551845,0.006395074,0.24765015],"study_design_scores_gemma":[0.08416627,0.044443123,0.34503618,0.010028791,0.18799537,0.00091445964,0.009901569,0.008641066,0.26703426,0.00033178707,0.03735568,0.004151421],"about_ca_topic_score_codex":0.00024096067,"about_ca_topic_score_gemma":0.0000070719857,"teacher_disagreement_score":0.30995077,"about_ca_system_score_codex":0.000016998296,"about_ca_system_score_gemma":0.000028989618,"threshold_uncertainty_score":0.6100438},"labels":[],"label_agreement":null},{"id":"W4312086854","doi":"10.1002/alz.066978","title":"Lower myelin content is associated with poorer gait variability in older adults with cerebral small vessel disease and mild cognitive impairment","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health","funders":"","keywords":"White matter; Myelin; Cognitive decline; Corpus callosum; Hyperintensity; Cingulum (brain); Psychology; Internal medicine; Cardiology; Medicine; Magnetic resonance imaging; Disease; Neuroscience; Dementia; Radiology; Central nervous system; Fractional anisotropy","score_opus":0.039101377893707726,"score_gpt":0.2804363250279132,"score_spread":0.2413349471342055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312086854","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99243504,0.0017166354,0.0007778351,0.0025759123,0.000022486049,0.002061123,0.0002056857,0.00011188014,0.000093389426],"genre_scores_gemma":[0.99470353,0.000019888179,0.001533234,0.0025931941,0.000014220836,0.000862916,0.00021595106,0.000037950907,0.000019142964],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856704,0.00008992702,0.00024099668,0.0005485994,0.00025929188,0.000294143],"domain_scores_gemma":[0.9992208,0.00007642099,0.000119957986,0.00028285143,0.00012019591,0.0001797863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021095725,0.00020653049,0.00023725018,0.000053239757,0.00014651773,0.000015190897,0.00008052475,0.000025463461,0.00028860802],"category_scores_gemma":[0.000020804611,0.00016890846,0.000042775893,0.00023443939,0.000116323,0.0000632514,0.00013571813,0.00027640283,0.0000023721825],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051349453,0.004540236,0.9771917,0.000033589888,0.004548298,0.00025489513,0.0011290254,0.000010434928,0.00014556632,0.00019453735,0.0019117865,0.004905012],"study_design_scores_gemma":[0.00721922,0.000852135,0.98154324,0.00025226508,0.007238193,0.000019701412,0.0004001468,0.00059325906,0.0009999059,0.00015546328,0.0003892656,0.00033722873],"about_ca_topic_score_codex":0.00011961386,"about_ca_topic_score_gemma":0.00002009561,"teacher_disagreement_score":0.0045677833,"about_ca_system_score_codex":0.000027997914,"about_ca_system_score_gemma":0.00008159147,"threshold_uncertainty_score":0.6887887},"labels":[],"label_agreement":null},{"id":"W4312087182","doi":"10.1002/alz.065756","title":"White Matter Correlates of Spoken Discourse in Cerebrovascular Disease","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Audiology; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.033520605855789705,"score_gpt":0.3179134904236161,"score_spread":0.2843928845678264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9494563,0.029905166,0.0032668964,0.011112353,0.00021678943,0.0020306793,0.00015088878,0.00023225836,0.0036287191],"genre_scores_gemma":[0.9959623,0.000032703865,0.0031164573,0.0004970935,0.000013740767,0.00019040778,0.00008467702,0.00002515764,0.0000774425],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991993,0.000026812662,0.00021401084,0.00022257428,0.0001833251,0.00015397747],"domain_scores_gemma":[0.99941695,0.0000112301,0.00007162739,0.0004112504,0.000018398987,0.000070528826],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000079398735,0.000093605304,0.00014924616,0.00009013891,0.00006043276,0.0000038831517,0.00011811416,0.000011284035,0.0018368029],"category_scores_gemma":[0.0000031705702,0.00009378408,0.000088035384,0.00019814199,0.000056526755,0.00005167972,0.00015817603,0.00015686273,0.00003931635],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004046258,0.00027981258,0.99280715,0.000006254632,0.00042064194,0.000018791676,0.000061197956,0.00007089747,0.0002229923,0.0003728269,0.004570158,0.0011288194],"study_design_scores_gemma":[0.0008032371,0.00007538421,0.9730379,0.000026983005,0.005834919,0.00002009694,0.00011057117,0.00038303173,0.0010862189,0.0012179682,0.017216576,0.00018713156],"about_ca_topic_score_codex":0.000019335754,"about_ca_topic_score_gemma":0.0000011724409,"teacher_disagreement_score":0.04650607,"about_ca_system_score_codex":0.000005816315,"about_ca_system_score_gemma":0.000027789209,"threshold_uncertainty_score":0.99907565},"labels":[],"label_agreement":null},{"id":"W4312087263","doi":"10.1002/alz.066988","title":"Higher physical activity is associated with greater myelin content in older adults with cerebral small vessel disease and mild cognitive impairment","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia; International Collaboration On Repair Discoveries; British Columbia Centre of Excellence for Women's Health; Vancouver Coastal Health","funders":"","keywords":"Myelin; White matter; Hyperintensity; Corpus callosum; Cognitive decline; Psychology; Internal medicine; Population; Physiology; Medicine; Dementia; Magnetic resonance imaging; Endocrinology; Cardiology; Pathology; Disease; Radiology; Central nervous system","score_opus":0.05984605743675004,"score_gpt":0.2982998726162618,"score_spread":0.23845381517951175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087263","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99543524,0.0006587509,0.00010929566,0.0022760155,0.000012978389,0.0012432947,0.00011870163,0.000089748886,0.000055969296],"genre_scores_gemma":[0.997402,0.000008152073,0.0003697259,0.0012303378,0.000022028478,0.0007813947,0.000095178155,0.00003652174,0.00005464088],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989312,0.00004877422,0.00010810769,0.0004404098,0.00022015367,0.00025134996],"domain_scores_gemma":[0.9994871,0.000031926545,0.00008942368,0.00019165948,0.000060289032,0.00013961924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004707194,0.00018842409,0.00021940237,0.0000435296,0.00012373964,0.000013560482,0.000057834117,0.000017288614,0.00011294675],"category_scores_gemma":[0.0000026798127,0.00014681363,0.000039286206,0.00016024611,0.000089746965,0.000058393056,0.00011045742,0.00024120571,0.0000025045713],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010229104,0.008647173,0.9491797,0.000047186433,0.009175565,0.00053316704,0.0025215782,0.000010539307,0.00081416883,0.00017108904,0.003572634,0.0150980875],"study_design_scores_gemma":[0.0058453744,0.0006655405,0.98290193,0.0001574111,0.0054719476,0.000009938969,0.00014844329,0.00035243508,0.0039424077,0.00003373071,0.00022889489,0.0002419385],"about_ca_topic_score_codex":0.00009341567,"about_ca_topic_score_gemma":0.000008998314,"teacher_disagreement_score":0.03372223,"about_ca_system_score_codex":0.000020064945,"about_ca_system_score_gemma":0.000037519352,"threshold_uncertainty_score":0.5986886},"labels":[],"label_agreement":null},{"id":"W4312087292","doi":"10.1002/alz.066359","title":"An examination of white matter integrity and functional network organization in Subjective Cognitive Decline using Diffusional Kurtosis Imaging‐based tractography resting state fMRI","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Inferior longitudinal fasciculus; Fasciculus; Uncinate fasciculus; Fractional anisotropy; White matter; Cingulum (brain); Resting state fMRI; Medicine; Posterior cingulate; Boston Naming Test; Neuroscience; Cognition; Connectome; Clinical Dementia Rating; Diffusion MRI; Psychology; Audiology; Functional connectivity; Magnetic resonance imaging; Neuropsychology; Cognitive impairment; Radiology","score_opus":0.04443760373324732,"score_gpt":0.3156384580665687,"score_spread":0.27120085433332136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087292","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93205935,0.00061973673,0.06637874,0.00035859144,0.000035892368,0.00041425633,0.000045000317,0.00005146383,0.000036959955],"genre_scores_gemma":[0.98188263,0.00000700546,0.017009363,0.0005582723,0.000029911107,0.00005055656,0.00043331378,0.000028156903,8.164585e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988938,0.00012928205,0.00028650466,0.0003071595,0.00023156067,0.0001516768],"domain_scores_gemma":[0.99928105,0.00009799816,0.00018837074,0.0001243855,0.00026010023,0.000048102174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029955417,0.00011973942,0.00015046305,0.00020223667,0.0002884869,0.000012065265,0.000046907535,0.000019921361,0.00021086192],"category_scores_gemma":[0.000027055301,0.00013189987,0.000026594676,0.0008329834,0.000078546356,0.00015761031,0.000117389085,0.00028598466,4.4978367e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008652843,0.0003017144,0.985069,0.000005104028,0.00014449409,0.000003727656,0.00016801967,0.0007326815,0.008963915,0.000028889992,0.000026952452,0.0044690017],"study_design_scores_gemma":[0.0007152164,0.00007579677,0.9784108,0.000035955425,0.0010823645,0.00001927424,0.00013096137,0.01529578,0.003775416,0.00031686324,0.00002716496,0.00011444995],"about_ca_topic_score_codex":0.00006275555,"about_ca_topic_score_gemma":0.000010897785,"teacher_disagreement_score":0.049823247,"about_ca_system_score_codex":0.000014756061,"about_ca_system_score_gemma":0.00005665613,"threshold_uncertainty_score":0.537872},"labels":[],"label_agreement":null},{"id":"W4312087783","doi":"10.1002/alz.064157","title":"Plasma phospho‐tau predicts differences in white matter microstructural complexity and cognition in non‐demented older adults","year":2022,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Dementia; Biomarker; Neuropsychology; Neuroimaging; Psychology; Internal medicine; Cognition; Medicine; Fornix; Magnetic resonance imaging; Audiology; Disease; Neuroscience; Biology; Hippocampus; Radiology","score_opus":0.04020375663040978,"score_gpt":0.2927602548210552,"score_spread":0.25255649819064546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312087783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9960329,0.001272891,0.00009571657,0.0013107304,0.00005713506,0.0008911222,0.00009429286,0.000056736284,0.0001884877],"genre_scores_gemma":[0.99514395,0.000034277513,0.0032547335,0.00089084177,0.000014022931,0.00032993307,0.00030323677,0.000018893687,0.000010138888],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989137,0.000035563717,0.00028602476,0.00035932878,0.00016707763,0.00023831853],"domain_scores_gemma":[0.99963355,0.000018877627,0.00008698245,0.00018033218,0.000023292998,0.00005696707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007024142,0.00014945095,0.00020108005,0.000119465236,0.000115917785,0.000015765372,0.00009417889,0.000027513683,0.0005784167],"category_scores_gemma":[0.0000028914505,0.0001504759,0.000028257464,0.00020429274,0.00009671021,0.00008544896,0.00018241868,0.0002579437,0.0000073383817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019908289,0.00022200542,0.9884421,0.00001669265,0.00023773035,0.000022214552,0.000520639,0.0000014105495,0.002174957,0.00003430022,0.002094487,0.0060343584],"study_design_scores_gemma":[0.0022405256,0.00009483361,0.990904,0.00006215288,0.00062758784,0.00004384623,0.00020105172,0.00091503933,0.0041166954,0.00029837678,0.00034773108,0.00014821134],"about_ca_topic_score_codex":0.00012315404,"about_ca_topic_score_gemma":0.00006385889,"teacher_disagreement_score":0.0058861473,"about_ca_system_score_codex":0.0000113817205,"about_ca_system_score_gemma":0.000013337985,"threshold_uncertainty_score":0.63332576},"labels":[],"label_agreement":null},{"id":"W4312213372","doi":"10.1101/2022.12.24.22283926","title":"Multimodal Analysis of Secondary Cerebellar Alterations after Pediatric Traumatic Brain Injury","year":2022,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"Brain Injury Research Center; National Health and Medical Research Council; Medical Research Council; Helse Midt-Norge; South African Medical Research Council; Norges Teknisk-Naturvitenskapelige Universitet","keywords":"Cerebellum; Traumatic brain injury; Neuroimaging; Diffusion MRI; White matter; Psychology; Neuroscience; Brain size; Voxel-based morphometry; Medicine; Magnetic resonance imaging; Psychiatry; Radiology","score_opus":0.04868032266590174,"score_gpt":0.3628992471601479,"score_spread":0.31421892449424615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312213372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98192984,0.0003338985,0.013525142,0.0016975141,0.0000977464,0.0008507609,0.00077536947,0.00019779814,0.0005919051],"genre_scores_gemma":[0.98054487,0.0002028409,0.016530506,0.00064361584,0.000120679906,0.00079668267,0.00058284606,0.000051374038,0.00052657095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981671,0.00009256048,0.0006397492,0.0005717199,0.00033040572,0.00019844869],"domain_scores_gemma":[0.99813026,0.00014647386,0.00032830946,0.0011869593,0.000097342636,0.000110632674],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00024539573,0.0002534317,0.00069718657,0.00089709123,0.000085939,0.000015519896,0.0002570094,0.00011798908,0.0019784027],"category_scores_gemma":[0.00009321775,0.00025656697,0.00048854586,0.0010794499,0.000062728024,0.000036973524,0.00043523812,0.0009172402,0.000005942563],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020400854,0.001479999,0.97170615,0.0021423819,0.0019900545,0.00010707403,0.0020414107,0.004170663,0.003835017,0.00054660946,0.0045808004,0.007195844],"study_design_scores_gemma":[0.0005724004,0.00021472582,0.9555553,0.000074138174,0.008561871,0.0000119199985,0.00008538759,0.020338677,0.0012270941,0.0019619926,0.010756074,0.000640424],"about_ca_topic_score_codex":0.000031374027,"about_ca_topic_score_gemma":0.000008693788,"teacher_disagreement_score":0.016168013,"about_ca_system_score_codex":0.00007622736,"about_ca_system_score_gemma":0.00017404441,"threshold_uncertainty_score":0.9999887},"labels":[],"label_agreement":null},{"id":"W4312278544","doi":"10.1007/978-3-031-21206-2_11","title":"Clustering in Tractography Using Autoencoders (CINTA)","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Cluster analysis; Artificial intelligence; Computer science; Pattern recognition (psychology); Streamlines, streaklines, and pathlines; Autoencoder; Thresholding; Diffusion MRI; Artificial neural network; Magnetic resonance imaging; Physics; Image (mathematics); Medicine; Radiology","score_opus":0.0737373760954931,"score_gpt":0.34269315229404446,"score_spread":0.2689557761985514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312278544","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054066663,0.0001535353,0.9957497,0.00067234354,0.0002133434,0.00047209335,0.0000044771464,0.00013368986,0.002060136],"genre_scores_gemma":[0.1717564,0.00008245057,0.8257685,0.002050003,0.0001615792,0.000022843386,0.000009480564,0.000060775004,0.00008799866],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99820226,0.000009180246,0.00030591319,0.00076150615,0.00039559897,0.00032554593],"domain_scores_gemma":[0.99908274,0.000104775245,0.00012557223,0.0005692466,0.0000393033,0.00007835366],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022637703,0.00025018142,0.00033775475,0.00089919363,0.00013415648,0.000038330483,0.00041511096,0.00009858648,0.000061656414],"category_scores_gemma":[0.000022085367,0.00025342702,0.00009259868,0.000552969,0.00034298294,0.00012181511,0.00035078524,0.0009790197,0.0000012774163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005390413,0.00011885398,0.002589719,0.0001796101,0.0000139874755,0.00059005315,0.0009364227,0.5798075,0.0032779605,0.0032364223,0.000023486184,0.40917206],"study_design_scores_gemma":[0.00038984822,0.00017671296,0.0006958586,0.0005987764,0.000021913746,0.00037429048,6.495192e-7,0.95215774,0.00045370453,0.03815806,0.0064847786,0.00048764973],"about_ca_topic_score_codex":0.000043427164,"about_ca_topic_score_gemma":0.000036174264,"teacher_disagreement_score":0.4086844,"about_ca_system_score_codex":0.0003157902,"about_ca_system_score_gemma":0.00018541422,"threshold_uncertainty_score":0.9999918},"labels":[],"label_agreement":null},{"id":"W4312612315","doi":"10.52547/nl.1.1.21","title":"Diffusion tensor imaging (DTI) and plasma p-tau 181 in Alzheimer’s disease","year":2022,"lang":"en","type":"article","venue":"Neurology Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Biomarker; White matter; Diffusion MRI; Disease; Internal medicine; Alzheimer's disease; Medicine; Pathogenesis; Tau protein; Psychology; Oncology; Neuroscience; Pathology; Magnetic resonance imaging; Biology; Biochemistry; Radiology","score_opus":0.03587092914053536,"score_gpt":0.3040637019575926,"score_spread":0.2681927728170572,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312612315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84782016,0.000112267735,0.000168413,0.15132785,0.00005537536,0.00030371972,0.000011712356,0.00013197333,0.0000685247],"genre_scores_gemma":[0.92729974,0.000030881016,0.00049262703,0.07191749,0.000036111604,0.00016621003,0.000019768358,0.000025020066,0.000012145121],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991051,0.000059981154,0.00014172579,0.00036725865,0.00010832007,0.0002176446],"domain_scores_gemma":[0.9995222,0.00006657085,0.000046084602,0.00026445562,0.000006715723,0.000093941875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054751123,0.00010771356,0.00014002084,0.00014182324,0.00014363711,0.00000530296,0.00008571137,0.00001316657,0.000034928908],"category_scores_gemma":[0.000022862057,0.00011169077,0.000033010238,0.00013561256,0.00011675047,0.000036974576,0.00018547753,0.00043475165,0.0000029440962],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046577197,0.00017618452,0.9459732,0.000009923187,0.0000070143697,0.001459716,0.00007170788,0.00016086047,0.036644273,0.00036193166,0.0072704265,0.0073989998],"study_design_scores_gemma":[0.0015209743,0.00013774884,0.9132003,0.000006426632,0.00008354407,0.00061505195,0.000012079569,0.008093247,0.00017761881,0.00041201757,0.07556237,0.00017861725],"about_ca_topic_score_codex":0.000020552234,"about_ca_topic_score_gemma":0.0000012378533,"teacher_disagreement_score":0.07947958,"about_ca_system_score_codex":0.000013458272,"about_ca_system_score_gemma":0.000011885853,"threshold_uncertainty_score":0.45546177},"labels":[],"label_agreement":null},{"id":"W4313038530","doi":"10.1016/j.procs.2022.11.103","title":"Reproduced correlations between integrity of white matter tracts and self-reported anxiety","year":2022,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Research Council Canada; National Research Center \"Kurchatov Institute\"","keywords":"White matter; Uncinate fasciculus; Fractional anisotropy; Cingulum (brain); Anxiety; Fasciculus; Diffusion MRI; Psychology; Corpus callosum; Lateralization of brain function; Superior longitudinal fasciculus; Medicine; Audiology; Clinical psychology; Neuroscience; Psychiatry; Magnetic resonance imaging; Radiology","score_opus":0.057215155383079114,"score_gpt":0.33287231757531144,"score_spread":0.27565716219223235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313038530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89681876,0.00001595071,0.09944436,0.0026797608,0.000068992376,0.00043117304,0.000007660845,0.00019175047,0.00034162082],"genre_scores_gemma":[0.8725144,0.0000067518167,0.12701268,0.0003219463,0.000046747176,0.000043022323,0.000005880417,0.0000066869006,0.00004186736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99886733,0.000011638737,0.00022768234,0.00046053473,0.00028420685,0.0001486085],"domain_scores_gemma":[0.99918556,0.00003210545,0.0001397472,0.0003950539,0.00015669902,0.00009083356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003837156,0.00007696035,0.0001415121,0.0001168865,0.00036728734,0.0000132552,0.00017632297,0.0000146177135,0.000014550544],"category_scores_gemma":[0.00004028612,0.00007291011,0.000024046902,0.00076486374,0.0001788703,0.00015213579,0.0004210595,0.00028594708,0.000001483878],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000052390105,0.00013467121,0.99020374,0.00003525268,0.000007535626,0.0000024910948,0.0009164686,0.000036072084,0.0030744935,0.00033890957,0.00063750654,0.0046076137],"study_design_scores_gemma":[0.00021961077,0.000138013,0.97809714,0.000017169878,0.0000492371,0.0003150328,0.000017002481,0.012889646,0.0038954886,0.0014040524,0.0028408996,0.00011670554],"about_ca_topic_score_codex":0.0000042356633,"about_ca_topic_score_gemma":1.1705182e-7,"teacher_disagreement_score":0.027568325,"about_ca_system_score_codex":0.00004082346,"about_ca_system_score_gemma":0.00015532004,"threshold_uncertainty_score":0.2973188},"labels":[],"label_agreement":null},{"id":"W4313252611","doi":"10.1016/j.nicl.2022.103309","title":"White matter microstructure predicts measures of clinical symptoms in chronic back pain patients","year":2022,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Nova Scotia Health Authority","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Melbourne","keywords":"Corpus callosum; Splenium; White matter; Spinothalamic tract; Diffusion MRI; Psychology; Medicine; Physical medicine and rehabilitation; Magnetic resonance imaging; Neuroscience; Nociception; Internal medicine; Radiology","score_opus":0.10740137050114074,"score_gpt":0.4093564515229179,"score_spread":0.30195508102177715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313252611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99224234,0.0000636748,0.0009839885,0.0028996218,0.00044249272,0.0013492277,0.00015887788,0.00013397196,0.0017258265],"genre_scores_gemma":[0.9890809,0.00010279391,0.0027970548,0.007059791,0.00025311322,0.000087600805,0.00010211508,0.00007066213,0.00044597132],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99574393,0.0008656375,0.0017909607,0.00080186833,0.00045237129,0.00034521086],"domain_scores_gemma":[0.99768764,0.0006140942,0.00044244633,0.0009491144,0.00012051746,0.00018620629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015647395,0.00021993452,0.0007409323,0.00013164313,0.00007917984,0.000010182705,0.00036562045,0.00012945871,0.0006952288],"category_scores_gemma":[0.000817679,0.0002093558,0.00035523323,0.00039718466,0.00034494622,0.00006781796,0.00040489493,0.0015911793,0.000042296524],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026635214,0.0007123935,0.96341723,0.000059676975,0.000013617535,0.00003442006,0.000016094127,0.000036129255,0.00026945007,0.00001352357,0.02524314,0.009917964],"study_design_scores_gemma":[0.002923896,0.0014742338,0.93707913,0.000050784358,0.000038483966,0.000023488245,0.000004793781,0.0007070319,0.00005117424,0.00017388804,0.057323493,0.00014962777],"about_ca_topic_score_codex":0.0000057937045,"about_ca_topic_score_gemma":0.0000027996794,"teacher_disagreement_score":0.032080352,"about_ca_system_score_codex":0.00007681791,"about_ca_system_score_gemma":0.00020535768,"threshold_uncertainty_score":0.8537282},"labels":[],"label_agreement":null},{"id":"W4313334378","doi":"10.1016/j.dcn.2022.101193","title":"Longitudinal associations between adolescent catch-up sleep, white-matter maturation and internalizing problems","year":2022,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Trinity College","funders":"Horizon 2020; Medical Research Council; Université Paris-Sud; Fédération pour la Recherche sur le Cerveau; Emil Aaltosen Säätiö; Fondation pour la Recherche Médicale; Université de Strasbourg; Institut National de la Santé et de la Recherche Médicale; Agence Nationale de la Recherche; GlaxoSmithKline; Deutsche Forschungsgemeinschaft; University College Dublin; European Commission; Jalmari ja Rauha Ahokkaan Säätiö; King's College London; Fondation de France; Bundesministerium für Bildung und Forschung; National Institute for Health and Care Research; Academy of Finland; King’s College London; National Institutes of Health; Fondation de l'Avenir pour la Recherche Médicale Appliquée; South London and Maudsley NHS Foundation Trust","keywords":"Fractional anisotropy; White matter; Psychology; Sleep (system call); Longitudinal study; Diffusion MRI; Population; Superior longitudinal fasciculus; Uncinate fasciculus; Developmental psychology; Demography; Medicine; Magnetic resonance imaging","score_opus":0.0980913715547408,"score_gpt":0.34515107974111536,"score_spread":0.24705970818637457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313334378","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96693134,0.00002271121,0.028486619,0.0022380394,0.00014872408,0.0008407218,0.00016772897,0.00014464693,0.0010194943],"genre_scores_gemma":[0.9947323,0.000009989883,0.001535112,0.002914688,0.000025771435,0.00016710312,0.000095522206,0.000016874787,0.00050259015],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987348,0.00004154163,0.00022450867,0.0004482034,0.00033264855,0.00021832672],"domain_scores_gemma":[0.9995922,0.00004422438,0.00012306412,0.000074028816,0.000072959665,0.00009354307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013674043,0.00012754982,0.0001480263,0.00011110871,0.00061548303,0.000051073494,0.00010595973,0.00001592496,0.00004679624],"category_scores_gemma":[0.00006470251,0.00013271936,0.000028874048,0.00038242442,0.00012143305,0.00017396249,0.0003116452,0.00031277828,0.000010857294],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014467202,0.0000627273,0.99162334,0.000012461635,0.0000031519107,0.000009052166,0.00028697084,0.0000018893326,0.005902212,0.000028625933,0.00042342284,0.0016316617],"study_design_scores_gemma":[0.0002973051,0.000075327865,0.99492335,0.00004583377,0.000024522098,0.00015754072,0.00016841407,0.00012722246,0.0022779275,0.000104032,0.0016584418,0.0001400722],"about_ca_topic_score_codex":0.000008042063,"about_ca_topic_score_gemma":0.0000014394307,"teacher_disagreement_score":0.027801033,"about_ca_system_score_codex":0.00016294539,"about_ca_system_score_gemma":0.00005455685,"threshold_uncertainty_score":0.54121387},"labels":[],"label_agreement":null},{"id":"W4313419144","doi":"10.1016/j.psychres.2022.115039","title":"Distinct and shared white matter abnormalities when ADHD is comorbid with ASD: A preliminary diffusion tensor imaging study","year":2022,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"London Health Sciences Centre; Western University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health","keywords":"Comorbidity; Neuropathology; Fractional anisotropy; Attention deficit hyperactivity disorder; Diffusion MRI; White matter; Autism spectrum disorder; Psychology; Cohort; Autism; Uncinate fasciculus; Clinical psychology; Psychiatry; Medicine; Disease; Internal medicine; Magnetic resonance imaging","score_opus":0.10049090643462247,"score_gpt":0.4031020353481133,"score_spread":0.30261112891349085,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313419144","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94313055,0.00031389567,0.00029066115,0.051370878,0.00004927534,0.0017626612,0.000105590785,0.00016871053,0.0028077506],"genre_scores_gemma":[0.9860953,0.000013802179,0.005846288,0.0011034223,0.00012336178,0.0009718776,0.000043366766,0.000057926067,0.005744674],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979981,0.00016113793,0.00021233593,0.000527819,0.00069937255,0.0004011907],"domain_scores_gemma":[0.99896145,0.000073187926,0.000053817435,0.0006450506,0.00012561544,0.00014086868],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00042712162,0.00015589973,0.00020367705,0.00023198902,0.0007859622,0.00006592856,0.00022324378,0.00001587502,0.0011743597],"category_scores_gemma":[0.000012567871,0.00012784055,0.00003598639,0.00033650978,0.00016971843,0.00010233616,0.00061965035,0.0007490412,0.000018932786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00057565176,0.00069993,0.9227245,0.00009215073,0.000016421,0.00004278891,0.0019152125,4.738447e-7,0.00004363959,0.000039288498,0.07335885,0.0004910837],"study_design_scores_gemma":[0.0012551765,0.001501717,0.9732525,0.00007638496,0.000045710465,0.00042197495,0.008970123,0.0005451909,0.000004168811,0.0015493466,0.012209221,0.00016851237],"about_ca_topic_score_codex":0.00014604544,"about_ca_topic_score_gemma":0.0000072981766,"teacher_disagreement_score":0.061149627,"about_ca_system_score_codex":0.000056580106,"about_ca_system_score_gemma":0.00007702532,"threshold_uncertainty_score":0.9997387},"labels":[],"label_agreement":null},{"id":"W4313500687","doi":"10.1002/brb3.2863","title":"Whole‐brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Fundação de Amparo à Pesquisa do Estado de São Paulo","keywords":"Fornix; Cingulum (brain); White matter; Atrophy; Neuroscience; Hippocampal formation; Diffusion MRI; Temporal lobe; Psychology; Cerebrospinal fluid; Alzheimer's disease; Pathology; Disease; Hippocampus; Medicine; Fractional anisotropy; Epilepsy; Magnetic resonance imaging","score_opus":0.07152290366549785,"score_gpt":0.34101124241715397,"score_spread":0.2694883387516561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313500687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98186964,0.00007375003,0.00007772249,0.016560221,0.0000071295103,0.0010867576,0.00004829523,0.00025871646,0.000017795463],"genre_scores_gemma":[0.99593306,0.0000069498824,0.0013711941,0.00082451804,0.000013171559,0.0006518451,0.000109026376,0.000029689736,0.0010605227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991929,0.0000314946,0.00013278153,0.00030544572,0.00012138466,0.0002159848],"domain_scores_gemma":[0.9995094,0.00006029411,0.000044389963,0.00018599129,0.000020161755,0.00017976732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013030732,0.0001262063,0.00016686281,0.000104925755,0.00006605977,0.000023132654,0.000042083047,0.000044477227,0.0000067988303],"category_scores_gemma":[0.00011847593,0.00010707915,0.000023227842,0.00031286693,0.00013694109,0.00005929515,0.000042147796,0.00015822992,0.0000054282473],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032260828,0.0011369109,0.8214492,0.00008258869,0.000051711122,0.0013463275,0.00046166996,0.000005946021,0.047725067,0.0004438945,0.019505465,0.107468575],"study_design_scores_gemma":[0.0011275221,0.0002119456,0.9945579,0.00017043261,0.00013487558,0.000015915044,0.00006363948,0.000358594,0.0003512003,0.00037552146,0.0024572394,0.00017519202],"about_ca_topic_score_codex":0.000021915159,"about_ca_topic_score_gemma":0.0000132244,"teacher_disagreement_score":0.1731087,"about_ca_system_score_codex":0.00001694228,"about_ca_system_score_gemma":0.000031943273,"threshold_uncertainty_score":0.4366561},"labels":[],"label_agreement":null},{"id":"W4313521977","doi":"10.21203/rs.3.rs-2411825/v1","title":"Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Tractography; Computer science; Artificial intelligence; Imaging phantom; Ground truth; Segmentation; Machine learning; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.2766481564113543,"score_gpt":0.4807213100057173,"score_spread":0.20407315359436295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313521977","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25809962,0.009929752,0.35884556,0.17088258,0.0021658926,0.068833366,0.0072926516,0.031270843,0.092679724],"genre_scores_gemma":[0.9595155,0.002129507,0.029361127,0.000103717735,0.0008327093,0.0052481834,0.00083419436,0.00055331044,0.0014217317],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9941445,0.00030194115,0.00066217675,0.001741998,0.0019022342,0.0012471523],"domain_scores_gemma":[0.99542534,0.00026015617,0.00028399206,0.002491479,0.0009494069,0.0005896494],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0014162991,0.0006382797,0.0009304904,0.0020350942,0.00037377613,0.00023325432,0.0007012443,0.0004599581,0.000064139116],"category_scores_gemma":[0.000053551314,0.0005366147,0.0005055768,0.001870148,0.00034357616,0.00015333729,0.00072953524,0.0039590662,0.00022343085],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0045859506,0.008567188,0.67304575,0.1031377,0.004234041,0.012364899,0.009616566,0.0012961106,0.0069403094,0.007080035,0.13896209,0.030169342],"study_design_scores_gemma":[0.006566696,0.0033328116,0.8413362,0.047880605,0.0009910701,0.0009437225,0.008322471,0.005163021,0.002207078,0.005566288,0.07365687,0.0040331553],"about_ca_topic_score_codex":0.0002262112,"about_ca_topic_score_gemma":0.000011691278,"teacher_disagreement_score":0.7014159,"about_ca_system_score_codex":0.00018293085,"about_ca_system_score_gemma":0.00027185882,"threshold_uncertainty_score":0.99970853},"labels":[],"label_agreement":null},{"id":"W4313550273","doi":"10.7554/elife.82088.sa1","title":"Decision letter: Fiber-specific structural properties relate to reading skills in children and adolescents","year":2022,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Reading (process); White matter; Psychology; Dyslexia; Cognitive psychology; Developmental psychology; Medicine; Linguistics","score_opus":0.037144882136376275,"score_gpt":0.3360365700604452,"score_spread":0.2988916879240689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313550273","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23610784,0.15830316,0.0038587977,0.5365328,0.0030910983,0.045472153,0.0014885414,0.003294794,0.011850807],"genre_scores_gemma":[0.033274714,0.12039016,0.110156804,0.09940398,0.0014323536,0.0018605032,0.003147805,0.00065120065,0.6296825],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99818075,0.00003266509,0.00046377687,0.0006956972,0.00035954508,0.00026755515],"domain_scores_gemma":[0.99905586,0.000024702553,0.00011231831,0.00063216145,0.00005278194,0.00012219259],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014112693,0.00030168297,0.0005729151,0.00023877558,0.00010656225,0.000024695233,0.00021100932,0.000089857,0.00052270066],"category_scores_gemma":[0.00006995155,0.0002344376,0.000082170845,0.0003170674,0.000040937295,0.000055993554,0.00039198447,0.0008056273,0.00003068271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027722746,0.000034484223,0.0016256328,0.00035756815,0.0000091307975,0.000013681571,0.00002001531,0.0000039657034,0.00011645761,0.000021304513,0.89099795,0.10677209],"study_design_scores_gemma":[0.00034539937,0.00006971727,0.019601345,0.009062417,0.000049317998,0.00022359725,0.0000014176068,0.0000069650187,0.000083994535,0.00014156286,0.9701309,0.00028333382],"about_ca_topic_score_codex":0.00005183341,"about_ca_topic_score_gemma":0.0000037298878,"teacher_disagreement_score":0.61783165,"about_ca_system_score_codex":0.00016009793,"about_ca_system_score_gemma":0.000027777032,"threshold_uncertainty_score":0.9560088},"labels":[],"label_agreement":null},{"id":"W4313655558","doi":"10.1016/j.nicl.2023.103324","title":"Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Department of Psychiatry, University of Toronto; Ministry of Science and Technology, Taiwan; Chang Gung Memorial Hospital, Linkou; Chang Gung Medical Foundation; University of Toronto","keywords":"White matter; Psychology; Stimulation; Diffusion MRI; Transcranial magnetic stimulation; Autism; Magnetic resonance imaging; Randomized controlled trial; Audiology; Medicine; Neuroscience; Anesthesia; Internal medicine; Developmental psychology","score_opus":0.06673426277084818,"score_gpt":0.3888181888932402,"score_spread":0.322083926122392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313655558","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9970864,0.000010452839,0.000290187,0.0017076948,0.000030585725,0.0007304725,0.000018111072,0.00007458561,0.00005147934],"genre_scores_gemma":[0.9979535,0.00006537163,0.0010160063,0.0007847025,0.000027830793,0.0000097278935,0.000020111005,0.00003446992,0.00008832001],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99885345,0.000065648936,0.0003958062,0.0003745488,0.00015540946,0.00015513891],"domain_scores_gemma":[0.9991694,0.00015414077,0.0001651454,0.00041425045,0.00003189944,0.0000651288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011878299,0.00013398057,0.0003463314,0.00011306314,0.000021324295,0.0000058053456,0.0000869145,0.00007587676,0.000005100711],"category_scores_gemma":[0.00009523314,0.00010639032,0.000059593065,0.00027288037,0.00020697496,0.000040391646,0.000072597344,0.00037436833,0.000009559256],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024447948,0.00020516143,0.993994,0.00015913595,0.000006851495,0.000031173317,0.000019547668,0.000037316197,0.0038616543,0.000025335743,0.0004263593,0.0009889585],"study_design_scores_gemma":[0.0019844417,0.00065603055,0.9949122,0.0005020019,0.00004343641,0.000042788644,0.0000013499917,0.00042449465,0.00093411136,0.00039533546,0.000025933285,0.000077867364],"about_ca_topic_score_codex":0.000005405884,"about_ca_topic_score_gemma":8.347493e-7,"teacher_disagreement_score":0.002927543,"about_ca_system_score_codex":0.000006451786,"about_ca_system_score_gemma":0.000015862774,"threshold_uncertainty_score":0.43384713},"labels":[],"label_agreement":null},{"id":"W4313830827","doi":"10.1016/j.mri.2023.01.004","title":"Mapping the impact of nonlinear gradient fields with noise on diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Diffusion MRI; Noise (video); Nonlinear system; Diffusion; Thermal diffusivity; SIGNAL (programming language); Statistical physics; Physics; Voxel; Scaling; Magnitude (astronomy); Tensor (intrinsic definition); Mathematics; Computer science; Artificial intelligence; Geometry","score_opus":0.03687265794660073,"score_gpt":0.32537116381545517,"score_spread":0.28849850586885445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313830827","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9824787,0.0007927617,0.004607928,0.008557613,0.00002874474,0.00069489353,0.000014253686,0.00027750226,0.0025476057],"genre_scores_gemma":[0.99247855,0.00040031903,0.0055474327,0.0004138903,0.000069364025,0.00007663567,0.000011394122,0.00003134485,0.0009710903],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991189,0.00001576266,0.00017935429,0.0002448312,0.00020004473,0.00024107823],"domain_scores_gemma":[0.99921215,0.00008987426,0.0000689898,0.00051840674,0.000057220394,0.000053375352],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009963992,0.00013123675,0.00016630976,0.000112750866,0.00010396645,0.000012860406,0.00013350829,0.000017653472,0.000027804685],"category_scores_gemma":[0.000036472502,0.000075730786,0.000084206076,0.00059255946,0.00012265747,0.000030018471,0.00006154565,0.0002035285,0.0000145295735],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038729305,0.0004222968,0.26694578,0.00011400348,0.000014584528,0.00022096327,0.0012789482,0.0011504949,0.031261344,0.00066264294,0.017978232,0.6795634],"study_design_scores_gemma":[0.0009847108,0.0006680424,0.8643186,0.0005492788,0.000021919392,0.00010287031,0.0001728018,0.09731788,0.0020671347,0.0007540277,0.03285133,0.00019138177],"about_ca_topic_score_codex":0.00008337086,"about_ca_topic_score_gemma":0.0000010709412,"teacher_disagreement_score":0.6793721,"about_ca_system_score_codex":0.00003137889,"about_ca_system_score_gemma":0.000031693628,"threshold_uncertainty_score":0.30882117},"labels":[],"label_agreement":null},{"id":"W4315499033","doi":"10.1101/2023.01.10.523345","title":"Associative white matter tracts selectively predict sensorimotor learning","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Kavli Foundation; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust; National Institutes of Health; National Science Foundation","keywords":"White matter; Psychology; Fractional anisotropy; Associative learning; Tractography; Cognitive psychology; Lateralization of brain function; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.04177059425958879,"score_gpt":0.2909614061685393,"score_spread":0.24919081190895054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315499033","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9531371,0.00022060824,0.027791075,0.005991024,0.0008428821,0.0040942626,0.0006593172,0.0070533995,0.00021032349],"genre_scores_gemma":[0.96716267,0.00021780348,0.029598463,0.0007893918,0.0006939033,0.0007823297,0.000002247035,0.00038821265,0.00036495415],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99686724,0.00014046668,0.000542978,0.0012798524,0.00049578014,0.0006737123],"domain_scores_gemma":[0.9972927,0.00014394884,0.0005917749,0.00096896023,0.0006811048,0.00032148784],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.00040304102,0.0006005116,0.0007670055,0.00034375355,0.00024873632,0.00011696928,0.0003068582,0.0005246579,0.0000574741],"category_scores_gemma":[0.0004599805,0.0006528764,0.00024443527,0.00069767534,0.000111065194,0.00012347913,0.00039660983,0.00230511,0.0003891362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096133605,0.00037818696,0.68753535,0.00069388485,0.0004574314,0.00023787704,0.000042367577,0.00015614206,0.2965694,0.00017141581,0.013657582,0.0000041978737],"study_design_scores_gemma":[0.00050217035,0.000110085806,0.9364246,0.0006083583,0.00028699316,9.637595e-8,0.000004181188,0.000843132,0.050706852,0.000011268138,0.009850084,0.0006521883],"about_ca_topic_score_codex":0.000019647428,"about_ca_topic_score_gemma":3.6926005e-7,"teacher_disagreement_score":0.24888922,"about_ca_system_score_codex":0.0005706477,"about_ca_system_score_gemma":0.0004321777,"threshold_uncertainty_score":0.9999966},"labels":[],"label_agreement":null},{"id":"W4317103370","doi":"10.1016/j.jmbbm.2023.105681","title":"In-vivo along muscle fascicle strain heterogeneity is not affected by image registration parameters: Robustness testing of combined magnetic resonance-diffusion tensor imaging method","year":2023,"lang":"en","type":"article","venue":"Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Montreal Heart Institute","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Diffusion MRI; Magnetic resonance imaging; Robustness (evolution); Fascicle; Image registration; Nuclear magnetic resonance; Physics; Anatomy; Computer science; Medicine; Computer vision; Radiology; Image (mathematics); Chemistry","score_opus":0.05323243145861169,"score_gpt":0.3489436163711821,"score_spread":0.2957111849125704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317103370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98507535,0.000073293304,0.007405433,0.0038095578,0.0013289445,0.0010980645,0.0011608496,0.000047839356,6.7428124e-7],"genre_scores_gemma":[0.93899995,0.00013707284,0.060257282,0.00021460878,0.00020786816,0.00005076974,0.00002967469,0.000090223766,0.000012553464],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98961943,0.00091434695,0.005725033,0.0005603843,0.0024643908,0.0007163851],"domain_scores_gemma":[0.99228275,0.000694924,0.004460919,0.00080961373,0.0011039791,0.00064781564],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0056547895,0.000556608,0.002561529,0.00072198693,0.00010748403,0.00006279631,0.0013039289,0.0005626695,0.00050632254],"category_scores_gemma":[0.002587465,0.00039364575,0.0006699256,0.001497725,0.0008508256,0.00035908647,0.00052843784,0.0008168764,0.0000019717593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011566671,0.0031152554,0.00026384697,0.0003385792,0.000034065157,0.0003569763,0.000034044846,6.9736774e-7,0.98427457,0.000058934875,0.00067021925,0.009696124],"study_design_scores_gemma":[0.0051337206,0.0035215786,0.013173563,0.0018929093,0.0010026497,0.0012489742,0.000094151495,0.00018843597,0.9727364,0.00054405053,0.00014865134,0.0003148761],"about_ca_topic_score_codex":0.00010235956,"about_ca_topic_score_gemma":0.0000013460607,"teacher_disagreement_score":0.05285185,"about_ca_system_score_codex":0.00018395655,"about_ca_system_score_gemma":0.0003399949,"threshold_uncertainty_score":0.9998515},"labels":[],"label_agreement":null},{"id":"W4317659503","doi":"10.1101/2023.01.20.524929","title":"Assessment of white matter hyperintensity severity using multimodal MRI in Alzheimer’s Disease","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Alzheimer Society","keywords":"Hyperintensity; Fluid-attenuated inversion recovery; White matter; Magnetic resonance imaging; Atrophy; Disease; Psychology; Cardiology; Neuroimaging; Alzheimer's disease; Cognitive impairment; Neuroscience; Medicine; Audiology; Pathology; Radiology","score_opus":0.07256484529055424,"score_gpt":0.3385269432707606,"score_spread":0.26596209798020637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317659503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9768891,0.00010499278,0.01901328,0.0014542339,0.00026638524,0.00141442,0.0003722199,0.00047867157,0.0000067278684],"genre_scores_gemma":[0.8906634,0.000108574495,0.10848449,0.0003250624,0.000103013874,0.00018449005,0.0000011665282,0.00012687466,0.0000029461864],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99768865,0.000066134526,0.0005898368,0.0009285865,0.00033488785,0.00039191774],"domain_scores_gemma":[0.9974268,0.00003633766,0.00034855196,0.0015276157,0.00038068122,0.00028002178],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00029293104,0.00040914424,0.00069194863,0.00031558046,0.000096943295,0.000026788295,0.00027861356,0.0002155589,0.000031412714],"category_scores_gemma":[0.00005513644,0.00045222303,0.00018284147,0.00044613107,0.00014686809,0.00008249589,0.00089278456,0.0008562825,0.000013605451],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033817003,0.00029779144,0.904834,0.00038781817,0.000064787586,0.00010662729,0.0000038001867,0.0005214947,0.09351481,0.00008370915,0.00015081327,5.491093e-7],"study_design_scores_gemma":[0.00035724562,0.000015623462,0.96866715,0.0006130053,0.0002513943,3.7678866e-8,0.0000013894394,0.02102977,0.00841541,0.000007500099,0.00027215297,0.00036930517],"about_ca_topic_score_codex":0.000121114186,"about_ca_topic_score_gemma":0.0000014740102,"teacher_disagreement_score":0.089471206,"about_ca_system_score_codex":0.00025281237,"about_ca_system_score_gemma":0.00050924247,"threshold_uncertainty_score":0.99979293},"labels":[],"label_agreement":null},{"id":"W4317778265","doi":"10.1016/j.neuroimage.2023.119892","title":"MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer’s disease progression modelling","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"FP7 Coordination of Research Activities; National Institute on Aging; Agencia Estatal de Investigación; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Institució Catalana de Recerca i Estudis Avançats; Northern California Institute for Research and Education; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; Agence Nationale de la Recherche; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; European Commission; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Autoencoder; Modalities; Computer science; Artificial intelligence; Missing data; Set (abstract data type); Modality (human–computer interaction); Recurrent neural network; Data set; Pattern recognition (psychology); Baseline (sea); Machine learning; Artificial neural network","score_opus":0.22031147126135492,"score_gpt":0.42699075770952316,"score_spread":0.20667928644816824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317778265","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031530852,0.00013941895,0.98609734,0.0065654353,0.00023623194,0.0021139982,0.00022967324,0.00138337,0.000081437145],"genre_scores_gemma":[0.4850683,0.00025685906,0.5079372,0.0014838302,0.00056249043,0.0024936325,0.0011290675,0.00022034222,0.00084829977],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984575,0.000025543384,0.0002857531,0.000591159,0.0002793889,0.000360661],"domain_scores_gemma":[0.9989297,0.00013155927,0.00010428761,0.00043335554,0.00015311727,0.00024798256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001243815,0.00020770142,0.00020064098,0.00014388068,0.00023699162,0.000028690829,0.00013300561,0.00005065376,0.000011623412],"category_scores_gemma":[0.00013163633,0.00019277171,0.00015072884,0.00030292413,0.000058788537,0.00013137727,0.000093293354,0.00022819967,0.00004782634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054159374,0.010450343,0.008468211,0.001751437,0.00037183065,0.001133873,0.0015244125,0.61961585,0.040772513,0.018061986,0.12990564,0.16252795],"study_design_scores_gemma":[0.0011036794,0.00010390685,0.007286595,0.000076772725,0.00011123537,0.000009305084,0.000005246993,0.9790242,0.0004377461,0.0022673716,0.009397208,0.00017677389],"about_ca_topic_score_codex":0.0000026619273,"about_ca_topic_score_gemma":2.121095e-7,"teacher_disagreement_score":0.4819152,"about_ca_system_score_codex":0.000026020976,"about_ca_system_score_gemma":0.00008099088,"threshold_uncertainty_score":0.7861002},"labels":[],"label_agreement":null},{"id":"W4317866086","doi":"10.1007/s00429-023-02609-y","title":"Correction to: Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological‑consistent iron‑rich deep brain nucleus subregion identification","year":2023,"lang":"en","type":"erratum","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Atlas (anatomy); Red nucleus; Identification (biology); Neurology; Neuroscience; Brain atlas; Nucleus; Biology; Psychology; Anatomy; Ecology","score_opus":0.04363649922660308,"score_gpt":0.31754877701462625,"score_spread":0.2739122777880232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317866086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71818715,0.001157333,0.124735534,0.06562201,0.07259535,0.008894033,0.0004428787,0.0029998575,0.00536587],"genre_scores_gemma":[0.92102355,0.0013725519,0.011670864,0.0060429014,0.0027087447,0.00071723724,0.007538824,0.00027288796,0.048652463],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99683505,0.00020759541,0.0007188142,0.0014367552,0.00039889576,0.0004028956],"domain_scores_gemma":[0.9982772,0.000244593,0.00044025655,0.00061743805,0.00021647457,0.00020404039],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030663994,0.0005110074,0.0007080847,0.0005102358,0.00028073962,0.00007535897,0.00013636868,0.0007274069,0.00003912153],"category_scores_gemma":[0.0014972802,0.00046189115,0.00015798165,0.0009359096,0.00038812292,0.00020775822,0.00012348294,0.0015309046,0.000021671996],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014995789,0.00017374875,0.007314707,0.00029562085,0.00005922943,0.00008245868,0.00036719322,0.0003159052,0.005798695,0.0024322956,0.87288,0.10878056],"study_design_scores_gemma":[0.0011055894,0.0016694863,0.8338425,0.00022936828,0.00029130594,0.0005290876,0.0003133714,0.0054857037,0.00009970178,0.010985144,0.14477342,0.0006753003],"about_ca_topic_score_codex":0.00047778786,"about_ca_topic_score_gemma":0.0032491488,"teacher_disagreement_score":0.82652783,"about_ca_system_score_codex":0.00033955058,"about_ca_system_score_gemma":0.00013033964,"threshold_uncertainty_score":0.9997833},"labels":[],"label_agreement":null},{"id":"W4317930664","doi":"10.1177/0271678x231152001","title":"Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease","year":2023,"lang":"en","type":"article","venue":"Journal of Cerebral Blood Flow & Metabolism","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hotchkiss Brain Institute; Université Laval; University of Calgary; Baycrest Hospital; Health Sciences Centre; McGill University; Montreal Heart Institute; University of British Columbia; Western University; University of Toronto; Université de Sherbrooke; McMaster University; Montreal Neurological Institute and Hospital; Lawson Health Research Institute; Jewish General Hospital; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Esperion Therapeutics; Amarin Corporation; Biogen; National Institutes of Health; Canada Research Chairs; AstraZeneca; Eli Lilly and Company; Pfizer; Novo Nordisk; Eisai; U.S. Department of Defense; Sanofi; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Dementia; Fractional anisotropy; Free water; Diffusion MRI; Positron emission tomography; Neuroscience; Hyperintensity; Alzheimer's disease; Psychology; Cognitive decline; Medicine; Pathology; Magnetic resonance imaging; Internal medicine; Disease; Radiology","score_opus":0.023072828295658956,"score_gpt":0.2654199776694309,"score_spread":0.24234714937377191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317930664","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99332356,0.00010991715,0.00022162257,0.005897735,0.000035671797,0.00032333154,0.00004282651,0.000013344288,0.00003198223],"genre_scores_gemma":[0.98944545,0.000032534736,0.01000781,0.00036133413,0.000043188353,0.000011488708,0.000012555621,0.000016812324,0.00006882158],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991934,0.00004525253,0.00030882726,0.00012368943,0.00020030675,0.0001285254],"domain_scores_gemma":[0.99938506,0.000030106452,0.00013220852,0.00019814206,0.00012774469,0.00012673461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016770241,0.00009966381,0.00021574854,0.00016931105,0.00005158803,0.000017137774,0.00009914886,0.000020155294,0.000020214475],"category_scores_gemma":[0.00007300103,0.000057609304,0.000042419793,0.000223816,0.000053579133,0.00012083421,0.00011123821,0.00028949272,0.000002547637],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001847185,0.00017059011,0.9972975,0.00005969906,0.00004461296,0.0000074846703,0.00015723352,0.000025484074,0.0008414748,0.00009728106,0.00058737595,0.0005264982],"study_design_scores_gemma":[0.0022546058,0.00006384407,0.99229133,0.00020680051,0.0005113664,0.000024053557,0.000014179078,0.00003055696,0.0011327423,0.0030414814,0.00036310323,0.0000659531],"about_ca_topic_score_codex":0.000003983814,"about_ca_topic_score_gemma":0.000003855553,"teacher_disagreement_score":0.009786188,"about_ca_system_score_codex":0.0000049867485,"about_ca_system_score_gemma":0.000020889487,"threshold_uncertainty_score":0.23492393},"labels":[],"label_agreement":null},{"id":"W4317933699","doi":"10.1016/j.ijrobp.2023.01.024","title":"Insult to Short-Range White Matter Connectivity in Childhood Brain Tumor Survivors","year":2023,"lang":"en","type":"article","venue":"International Journal of Radiation Oncology*Biology*Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children","funders":"Canadian Cancer Society Research Institute; Canadian Institutes of Health Research","keywords":"White matter; Medicine; Fractional anisotropy; Diffusion MRI; Medulloblastoma; Typically developing; Brain tumor; Radiation therapy; Magnetic resonance imaging; Pathology; Surgery; Radiology; Psychiatry","score_opus":0.03820561362493503,"score_gpt":0.3736504431100189,"score_spread":0.33544482948508386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4317933699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9439274,0.00002935528,0.017162865,0.036931835,0.0006530799,0.00039125347,0.00007485667,0.00011340898,0.0007159104],"genre_scores_gemma":[0.98824,0.00008248047,0.0036342605,0.0069473167,0.0008647055,0.00004485671,0.00006686372,0.000034463716,0.00008503129],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856347,0.00013113447,0.0005907995,0.00026466968,0.00021273013,0.00023717931],"domain_scores_gemma":[0.9985931,0.00039720992,0.0003330447,0.00018651456,0.0003599906,0.00013013043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053332583,0.00016473365,0.00039370323,0.0003730747,0.00004722275,0.000017255228,0.0003126664,0.000105249776,0.000049411177],"category_scores_gemma":[0.0004029643,0.0001553622,0.00014128069,0.00053430366,0.00007952715,0.00018772435,0.00009179955,0.00049213733,0.000112995585],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108094886,0.0003576314,0.9585417,0.0000046830214,0.000066199624,0.00007206187,0.00038972322,0.0005649178,0.002836568,0.0020977154,0.006270287,0.02869043],"study_design_scores_gemma":[0.0017826393,0.00042106424,0.95277464,0.000058084333,0.000024888335,0.00022567551,0.000060057308,0.00088237604,0.0010089093,0.010210302,0.032386217,0.00016511697],"about_ca_topic_score_codex":0.000020050617,"about_ca_topic_score_gemma":0.000015690692,"teacher_disagreement_score":0.044312585,"about_ca_system_score_codex":0.00038495602,"about_ca_system_score_gemma":0.00018990642,"threshold_uncertainty_score":0.6335487},"labels":[],"label_agreement":null},{"id":"W4318141881","doi":"10.21203/rs.3.rs-2451435/v1","title":"Redefining the connectome: A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Connectome; Modal; Computer science; Artificial intelligence; Functional connectivity; Neuroscience; Psychology","score_opus":0.31056101900612093,"score_gpt":0.4733101727138448,"score_spread":0.16274915370772386,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318141881","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9187157,0.0017360987,0.056808848,0.014954486,0.00012950662,0.0053296513,0.0003417402,0.000810919,0.0011730344],"genre_scores_gemma":[0.98884284,0.0011674258,0.0089311935,0.000054806467,0.00007938801,0.000533392,0.000090714544,0.000064010324,0.00023623752],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99744326,0.00036073627,0.00036498107,0.0007006131,0.0007096369,0.00042077413],"domain_scores_gemma":[0.9964913,0.0016246706,0.00015307288,0.0009397787,0.0006276915,0.00016349019],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016782857,0.00021082468,0.0004853235,0.0006693417,0.00026500813,0.000064401785,0.00027616194,0.00025763453,0.000012072706],"category_scores_gemma":[0.0021916348,0.00015823834,0.00013636333,0.0010973853,0.00051400805,0.000048978396,0.0010983336,0.0018465462,0.000011708756],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004271274,0.006405337,0.38270262,0.02195313,0.0015774756,0.00093974406,0.005219138,0.00026251597,0.2306879,0.17491564,0.05614127,0.11492397],"study_design_scores_gemma":[0.0077317758,0.0025988903,0.55495685,0.008201609,0.0004792246,0.00027261258,0.0030214798,0.17914101,0.04002729,0.18987447,0.012068506,0.0016262732],"about_ca_topic_score_codex":0.00037432482,"about_ca_topic_score_gemma":0.00002353054,"teacher_disagreement_score":0.19066061,"about_ca_system_score_codex":0.00017095328,"about_ca_system_score_gemma":0.00023454307,"threshold_uncertainty_score":0.8022427},"labels":[],"label_agreement":null},{"id":"W4318240362","doi":"10.3233/jad-220519","title":"Fully Connected Multi-Kernel Convolutional Neural Network Based on Alzheimer’s Disease Diagnosis","year":2023,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research","keywords":"Convolutional neural network; Artificial intelligence; Computer science; Diffusion MRI; Deep learning; Pattern recognition (psychology); Fractional anisotropy; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.12976706223023116,"score_gpt":0.3755037390369411,"score_spread":0.24573667680670996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318240362","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7210108,0.04730715,0.024126643,0.1920105,0.0033411,0.0066889655,0.0017384496,0.0032641208,0.0005122916],"genre_scores_gemma":[0.9898276,0.00026802617,0.003851914,0.0050266455,0.0006308424,0.00014504681,0.00013765245,0.00007353973,0.000038774604],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997845,0.00009618081,0.0006252013,0.00035917602,0.0006260599,0.00044837611],"domain_scores_gemma":[0.9971055,0.00029815632,0.00040813923,0.0005085124,0.0003813221,0.0012983818],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022489729,0.00029147093,0.00040777828,0.00026814538,0.00020418124,0.000035629535,0.0002325457,0.000053411404,0.00018595796],"category_scores_gemma":[0.000294511,0.00025121955,0.00046856288,0.0006454639,0.0001616969,0.00016160448,0.000064672386,0.00043599858,0.00007825965],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007894277,0.0048748767,0.5727543,0.0001043272,0.0014603992,0.006000635,0.000051245028,0.074518025,0.00035896635,0.0020692574,0.3153672,0.01454647],"study_design_scores_gemma":[0.003004908,0.00034037788,0.82109827,0.00031666542,0.0033106254,0.000031113377,0.0000115046305,0.15755086,0.00015261318,0.0009626282,0.012872863,0.00034754223],"about_ca_topic_score_codex":0.0000030743242,"about_ca_topic_score_gemma":3.4191842e-7,"teacher_disagreement_score":0.30249435,"about_ca_system_score_codex":0.000043230648,"about_ca_system_score_gemma":0.0004076528,"threshold_uncertainty_score":0.999994},"labels":[],"label_agreement":null},{"id":"W4318700719","doi":"10.1101/2023.01.29.526138","title":"Sex differences, asymmetry and age-related white matter development in infants and 5-year-olds as assessed with Tract-Based Spatial Statistics","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Suomen Lääketieteen Säätiö; Suomen Kulttuurirahasto; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Suomalainen Lääkäriseura Duodecim; Alfred Kordelinin Säätiö; Juho Vainion Säätiö; National Alliance for Research on Schizophrenia and Depression","keywords":"Corpus callosum; Fractional anisotropy; White matter; Lateralization of brain function; Diffusion MRI; Psychology; Developmental psychology; Gestational age; Early childhood; Brain asymmetry; Cognition; Audiology; Medicine; Pregnancy; Neuroscience; Magnetic resonance imaging; Biology","score_opus":0.02810981522604555,"score_gpt":0.2750988080261762,"score_spread":0.24698899280013065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318700719","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9700104,0.00006680835,0.02764773,0.00053284573,0.00008310305,0.0010651238,0.00018124632,0.0003995016,0.0000132555715],"genre_scores_gemma":[0.90434855,0.00009821731,0.094811805,0.00028591818,0.000035572513,0.0002644523,0.0000046958467,0.00012090125,0.000029905976],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978981,0.000056427725,0.00048954994,0.00087082764,0.0003185618,0.00036650742],"domain_scores_gemma":[0.9986329,0.0001105753,0.00026615144,0.0006088186,0.00015065796,0.00023087527],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023699486,0.00043961467,0.00061075285,0.00035359553,0.00009132021,0.000116046744,0.00014762822,0.00030272035,0.000027237997],"category_scores_gemma":[0.00007692509,0.00041520735,0.000023951583,0.0003796379,0.00017877045,0.000056093464,0.00021037209,0.0008383359,0.00001785053],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007234983,0.00022791623,0.987163,0.00056901434,0.00006458352,0.00039174917,0.000021387634,0.000010179556,0.011108895,0.00015791913,0.000185054,0.00002793626],"study_design_scores_gemma":[0.0011240339,0.00008234744,0.98745984,0.0008554866,0.000087584944,2.0024339e-7,0.0000029092325,0.0008020047,0.008717484,0.000015236196,0.00038475374,0.00046811043],"about_ca_topic_score_codex":0.000106969026,"about_ca_topic_score_gemma":0.000014103633,"teacher_disagreement_score":0.06716408,"about_ca_system_score_codex":0.00012308412,"about_ca_system_score_gemma":0.000499912,"threshold_uncertainty_score":0.99982995},"labels":[],"label_agreement":null},{"id":"W4318773574","doi":"10.1016/j.media.2023.102761","title":"Generative Sampling in Bundle Tractography using Autoencoders (GESTA)","year":2023,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Compute Canada; McDonnell Center for Systems Neuroscience; Réseau en Bio-Imagerie du Quebec; National Institutes of Health; Université de Sherbrooke","keywords":"Tractography; Streamlines, streaklines, and pathlines; Artificial intelligence; Human Connectome Project; White matter; Pattern recognition (psychology); Diffusion MRI; Computer science; Mathematics; Computer vision; Physics; Neuroscience; Psychology; Magnetic resonance imaging","score_opus":0.1638148958616718,"score_gpt":0.45533188993030915,"score_spread":0.29151699406863735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318773574","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27437463,0.000045884935,0.7200361,0.0047413968,0.000014689048,0.0001538242,0.000007797874,0.00031657406,0.00030912846],"genre_scores_gemma":[0.7738529,0.00033329122,0.22375514,0.0015417152,0.000111748595,0.000063770545,0.00016127588,0.000035101526,0.00014505853],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998549,0.00003987836,0.00031526585,0.00036245,0.00044424378,0.00028915238],"domain_scores_gemma":[0.999232,0.000120489276,0.00006171454,0.000317756,0.00006079028,0.00020723796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033526638,0.00012481805,0.00036400833,0.00089243054,0.00008674375,0.000021016165,0.00011892671,0.0000759025,0.00026466514],"category_scores_gemma":[0.00031273346,0.00011136678,0.000251769,0.0050740964,0.0001539211,0.000086832944,0.000054888293,0.0003286306,0.000018701385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014465666,0.0029895043,0.7714041,0.00028048037,0.0031704134,0.0028923815,0.002461497,0.02501825,0.128787,0.0017230863,0.006877275,0.054251388],"study_design_scores_gemma":[0.00064617995,0.00006274988,0.0713459,0.000087236855,0.0011718757,0.000028333705,0.00035053023,0.9196947,0.0020563428,0.0017439938,0.0025354915,0.00027661255],"about_ca_topic_score_codex":0.00017410044,"about_ca_topic_score_gemma":0.00007545807,"teacher_disagreement_score":0.8946765,"about_ca_system_score_codex":0.000045906963,"about_ca_system_score_gemma":0.000067873116,"threshold_uncertainty_score":0.45414057},"labels":[],"label_agreement":null},{"id":"W4318959460","doi":"10.1101/2023.01.23.525278","title":"White matter microstructure is associated with the precision of visual working memory","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"University of Queensland","keywords":"Working memory; White matter; Diffusion MRI; Visual memory; Association (psychology); Task (project management); Psychology; Neuroimaging; Cognitive psychology; Computer science; Neuroscience; Cognition; Magnetic resonance imaging; Medicine","score_opus":0.03186044187941617,"score_gpt":0.28591289136372405,"score_spread":0.2540524494843079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318959460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9873002,0.00023293657,0.0051559163,0.0044809906,0.00028015894,0.0015825434,0.0002099536,0.00073665875,0.000020622216],"genre_scores_gemma":[0.99115807,0.00007186358,0.007010397,0.0011190258,0.00017454161,0.00019312176,0.000001309467,0.00018890793,0.00008273929],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980333,0.000062111896,0.00040355886,0.0007427973,0.000410192,0.00034808222],"domain_scores_gemma":[0.9975639,0.000109318855,0.0005583712,0.001255665,0.00040340738,0.000109343855],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030528137,0.00039817102,0.00054880884,0.00017576326,0.00014527583,0.00006391526,0.00038517624,0.00032890966,0.00005024334],"category_scores_gemma":[0.000077862656,0.00029015885,0.00014360689,0.0006623857,0.00019041705,0.000043243985,0.00044086785,0.0009947969,0.000025544097],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020721818,0.00030479094,0.26000786,0.000561615,0.0004900308,0.00010451235,0.00008075844,0.00010739187,0.7110725,0.000067515466,0.026982535,0.000013261006],"study_design_scores_gemma":[0.0005525819,0.00008950516,0.8112636,0.0021050551,0.00035462278,1.1705116e-7,0.000006451704,0.0002879357,0.18205442,0.00001014521,0.0028000253,0.0004755356],"about_ca_topic_score_codex":0.00000933378,"about_ca_topic_score_gemma":9.811345e-7,"teacher_disagreement_score":0.55125576,"about_ca_system_score_codex":0.00013122823,"about_ca_system_score_gemma":0.00020613326,"threshold_uncertainty_score":0.99995506},"labels":[],"label_agreement":null},{"id":"W4319441713","doi":"10.1115/1.4056848","title":"Wavelet-Based Methods to Partition Multibody Systems With Contact in Dynamic Simulation","year":2023,"lang":"en","type":"article","venue":"Journal of Computational and Nonlinear Dynamics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"CM Labs Simulations (Canada); McGill University","funders":"","keywords":"Multibody system; Partition (number theory); Dynamical systems theory; Computer science; Metric (unit); Topology (electrical circuits); Redundancy (engineering); Constraint (computer-aided design); Wavelet; Theoretical computer science; Mathematics; Artificial intelligence; Physics; Engineering; Classical mechanics; Geometry","score_opus":0.05140150529499968,"score_gpt":0.43491788771209844,"score_spread":0.38351638241709873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319441713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3663402,0.000011950702,0.63219386,0.0012066856,0.000025632113,0.00017425466,0.000012361681,0.000026265909,0.0000088032175],"genre_scores_gemma":[0.6761211,0.0000089730265,0.32360435,0.00013120928,0.000028944654,0.0000048175552,0.00007404784,0.000010372009,0.000016209797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992856,0.00003869496,0.00030857514,0.0001014322,0.00017526528,0.00009046086],"domain_scores_gemma":[0.9991621,0.00031126957,0.00015151214,0.000058789818,0.00023845375,0.00007789617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027627594,0.00007680774,0.00019051025,0.00027195655,0.000035566267,0.00001584903,0.00003293696,0.000029251776,9.88783e-7],"category_scores_gemma":[0.000055847246,0.00006079953,0.000030955212,0.00036917045,0.000017862738,0.000062581195,0.000010207619,0.0001427788,0.0000016027103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023148298,0.000087760905,0.0026828907,0.00004567496,0.000012639622,0.000037157974,0.00003172431,0.98062724,0.00044327197,0.0004653098,0.000010043566,0.015324783],"study_design_scores_gemma":[0.0007739958,0.00031193162,0.06075284,0.00015358978,0.000018989305,0.000073076786,0.00003465661,0.9367761,0.000015484558,0.0007496449,0.00027977247,0.000059923164],"about_ca_topic_score_codex":0.00000420606,"about_ca_topic_score_gemma":0.0000046288465,"teacher_disagreement_score":0.3097809,"about_ca_system_score_codex":0.0000848031,"about_ca_system_score_gemma":0.000072746,"threshold_uncertainty_score":0.2479333},"labels":[],"label_agreement":null},{"id":"W4319733470","doi":"10.1038/s41598-023-28560-w","title":"Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies; Université de Sherbrooke","keywords":"Tractography; Computer science; Artificial intelligence; Ground truth; Imaging phantom; Segmentation; White matter; Machine learning; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.07451182870939092,"score_gpt":0.34913634223885504,"score_spread":0.2746245135294641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319733470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88558537,0.0004619771,0.046256345,0.012145359,0.0051667364,0.005531877,0.0000753462,0.008650277,0.036126718],"genre_scores_gemma":[0.9847584,0.000027859864,0.01207165,0.000078610065,0.00013398335,0.0003641254,0.00018467438,0.000088229324,0.002292518],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99692065,0.000030153058,0.0005739699,0.001208094,0.0007216571,0.00054547965],"domain_scores_gemma":[0.9974756,0.000026557638,0.00037681177,0.0016144691,0.00022926362,0.00027727062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089266064,0.00027675543,0.00037638206,0.0008174797,0.00036958215,0.00019153938,0.00015205835,0.00008182386,0.0000436025],"category_scores_gemma":[0.000015753549,0.00022136194,0.00021819,0.0025045,0.00025662663,0.0002472979,0.000064647225,0.00030161766,0.00008878191],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028677343,0.0018282841,0.62054724,0.0024142936,0.000499211,0.020882746,0.0038672993,0.00029585513,0.09697932,0.0009567936,0.23648985,0.014952337],"study_design_scores_gemma":[0.0024901603,0.0006456754,0.49342135,0.0031416758,0.00083334063,0.013519573,0.00294495,0.0025004593,0.02417023,0.0050319554,0.4489685,0.002332161],"about_ca_topic_score_codex":0.000013939236,"about_ca_topic_score_gemma":0.0000018196387,"teacher_disagreement_score":0.21247864,"about_ca_system_score_codex":0.000030383819,"about_ca_system_score_gemma":0.00007180877,"threshold_uncertainty_score":0.9026878},"labels":[],"label_agreement":null},{"id":"W4319940240","doi":"10.1101/2023.02.09.527696","title":"Development of White Matter Fiber Covariance Networks Supports Executive Function in Youth","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Pennsylvania","keywords":"Covariance; White matter; Covariance function; Psychology; Fiber; Executive functions; Function (biology); Mathematics; Neuroscience; Cognition; Materials science; Medicine; Statistics; Biology; Cell biology","score_opus":0.04343906616440578,"score_gpt":0.2736918858668719,"score_spread":0.23025281970246608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319940240","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7615796,0.0002581782,0.23190467,0.00075419486,0.00083836296,0.0030505625,0.00029514293,0.0012376944,0.00008162884],"genre_scores_gemma":[0.91323256,0.0000669673,0.085654974,0.00029271212,0.00013494045,0.0003897037,0.000004780493,0.00014020123,0.00008318622],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99783117,0.00003530198,0.00068946905,0.0008049617,0.00025411023,0.00038497194],"domain_scores_gemma":[0.9981988,0.000027130078,0.00041687817,0.0009632983,0.00026110868,0.00013277154],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003306167,0.00036299738,0.0005440073,0.00028482085,0.00009199748,0.000021494736,0.0001936059,0.0003123732,0.0000683239],"category_scores_gemma":[0.000032583644,0.00039392326,0.00009277045,0.000580081,0.000076853445,0.00006599912,0.0004635073,0.00072568096,0.00005663685],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010502496,0.0020439646,0.7265273,0.0038360986,0.00082994864,0.0005216585,0.0007724918,0.006005219,0.24380812,0.0011854627,0.013347483,0.000072032715],"study_design_scores_gemma":[0.0006330373,0.000040000705,0.9617399,0.001733758,0.0001778941,4.6487692e-8,0.000011294038,0.0007454441,0.027254038,0.0000096783415,0.007018259,0.00063665677],"about_ca_topic_score_codex":0.000013762935,"about_ca_topic_score_gemma":0.000001566391,"teacher_disagreement_score":0.23521261,"about_ca_system_score_codex":0.00021635155,"about_ca_system_score_gemma":0.000369997,"threshold_uncertainty_score":0.9998513},"labels":[],"label_agreement":null},{"id":"W4320491340","doi":"10.3390/biomedicines11020535","title":"Seeking the Amygdala: Novel Use of Diffusion Tensor Imaging to Delineate the Basolateral Amygdala","year":2023,"lang":"en","type":"article","venue":"Biomedicines","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"National Institute of Mental Health; University of California, Irvine; Loma Linda University","keywords":"Neuroscience; Diffusion MRI; Amygdala; Basolateral amygdala; Neuroimaging; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.1406367710354835,"score_gpt":0.3719878487178744,"score_spread":0.23135107768239088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320491340","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82357424,0.0001039979,0.05327842,0.120962664,0.00026464942,0.0011221502,0.000042142317,0.0005488007,0.00010296002],"genre_scores_gemma":[0.98669404,0.00014341803,0.005751537,0.005576328,0.00041133782,0.000099488745,0.00003641913,0.00004460266,0.0012428242],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988713,0.000018988083,0.00031435047,0.0002631801,0.0002685294,0.00026362267],"domain_scores_gemma":[0.99880034,0.00025214668,0.00009883053,0.0006012194,0.00016237615,0.00008507176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022744578,0.00015444952,0.00021487335,0.00018013627,0.00019399148,0.000019996993,0.00020246055,0.000027168244,0.0000107929145],"category_scores_gemma":[0.00024121426,0.0000751253,0.00007730179,0.0010275394,0.00020646308,0.0000588116,0.00018057977,0.00015180641,0.000017816146],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007834022,0.00009349555,0.07931425,0.000062370644,0.000027152977,0.00002304205,0.0006421974,0.00003748175,0.8689607,0.00035620926,0.027449539,0.022955233],"study_design_scores_gemma":[0.0010963355,0.00015517898,0.5109846,0.00060138165,0.0001868098,0.00022162413,0.0005381674,0.04773344,0.0066958778,0.00028256836,0.43124634,0.00025769018],"about_ca_topic_score_codex":0.00012680395,"about_ca_topic_score_gemma":0.0000026882387,"teacher_disagreement_score":0.8622648,"about_ca_system_score_codex":0.000019335423,"about_ca_system_score_gemma":0.000021841917,"threshold_uncertainty_score":0.3063521},"labels":[],"label_agreement":null},{"id":"W4320718974","doi":"10.1101/2023.02.10.23285704","title":"The genetic architecture of human cerebellar morphology supports a key role for the cerebellum in human evolution and psychopathology","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Helse Sør-Øst RHF; Nasjonalforeningen for Folkehelsen; Norges Forskningsråd; Universitetet i Oslo; Stiftelsen Kristian Gerhard Jebsen","keywords":"Cerebellum; Genetic architecture; Imaging genetics; Human Connectome Project; Neuroimaging; Psychopathology; Neuroscience; Brain morphometry; Biology; Genome-wide association study; Evolutionary biology; Psychology; Genetics; Single-nucleotide polymorphism; Gene; Functional connectivity; Phenotype; Medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.04637048212933488,"score_gpt":0.3531794992495026,"score_spread":0.3068090171201677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320718974","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96883583,0.0010466003,0.021470502,0.006184976,0.00013362116,0.0020710512,0.000043294694,0.000120488265,0.00009366371],"genre_scores_gemma":[0.99537545,0.00038333322,0.0026358594,0.000115207615,0.00013195317,0.0008305427,0.00004259973,0.00005918394,0.00042588572],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985447,0.00008569864,0.00044165144,0.00051993516,0.000121441175,0.00028659645],"domain_scores_gemma":[0.99839395,0.00023682926,0.00025571577,0.0009977776,0.00006815603,0.00004755421],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041198527,0.00020563828,0.00036687727,0.00014283268,0.00024141824,0.000010330204,0.00031263393,0.00019632351,0.000005830055],"category_scores_gemma":[0.00008449268,0.00013491322,0.000112407586,0.00013674932,0.00043105774,0.000006173973,0.0003352809,0.0006630797,0.0000010627721],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021151808,0.00035868437,0.5851214,0.00086447457,0.00013412496,0.000099444005,0.0015771372,0.0009828282,0.3849477,0.012537254,0.002903372,0.010262089],"study_design_scores_gemma":[0.00082838547,0.00038041518,0.6918841,0.00017858019,0.00020532835,0.00022311205,0.00011988568,0.00066918693,0.0038030804,0.29347533,0.007985642,0.00024693526],"about_ca_topic_score_codex":0.00010771647,"about_ca_topic_score_gemma":0.00018790839,"teacher_disagreement_score":0.3811446,"about_ca_system_score_codex":0.000034341396,"about_ca_system_score_gemma":0.00004366407,"threshold_uncertainty_score":0.55016017},"labels":[],"label_agreement":null},{"id":"W4320857731","doi":"10.1038/s41597-023-01942-5","title":"A longitudinal microstructural MRI dataset in healthy C57Bl/6 mice at 9.4 Tesla","year":2023,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Congressionally Directed Medical Research Programs; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Government of Canada; U.S. Department of Defense","keywords":"Diffusion MRI; Fractional anisotropy; Magnetic resonance imaging; Neuroimaging; Human Connectome Project; Computer science; Magnetization transfer; Nuclear magnetic resonance; Artificial intelligence; Pattern recognition (psychology); Neuroscience; Radiology; Physics; Medicine; Biology; Functional connectivity","score_opus":0.20877625383579276,"score_gpt":0.4405094157300159,"score_spread":0.23173316189422313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320857731","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75852835,0.00045274917,0.0012141388,0.036333025,0.0015108158,0.002204025,0.1979658,0.0011745648,0.0006165447],"genre_scores_gemma":[0.33945045,0.00019357551,0.04102847,0.0024082104,0.00024777924,0.000105195075,0.6042326,0.000079507874,0.012254194],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982534,0.000016982385,0.00022863499,0.0009159878,0.00022897596,0.0003560198],"domain_scores_gemma":[0.9973794,0.000048662554,0.000059382404,0.0023649507,0.000029901106,0.000117702475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046656516,0.00010745064,0.00015064387,0.00020891846,0.00023901198,0.000068620335,0.0007104283,0.00002963683,0.000096315365],"category_scores_gemma":[0.000109782304,0.00009710446,0.000019037006,0.00120692,0.00025285923,0.00021245607,0.0013171331,0.00017343655,0.000494422],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004871532,0.000034350327,0.005901056,0.00003784656,0.000002565953,0.000051427323,0.000023443927,0.0000020868665,0.020857979,0.000076595876,0.9716401,0.0013238515],"study_design_scores_gemma":[0.0005339215,0.000038715858,0.03874206,0.000049607654,0.000016889338,0.00015701563,0.00002718625,0.0024614234,0.0019614352,0.00040996616,0.9554651,0.0001366939],"about_ca_topic_score_codex":0.000055581473,"about_ca_topic_score_gemma":0.00010405322,"teacher_disagreement_score":0.4190779,"about_ca_system_score_codex":0.0000637766,"about_ca_system_score_gemma":0.00007779725,"threshold_uncertainty_score":0.6354959},"labels":[],"label_agreement":null},{"id":"W4320898602","doi":"10.1016/j.brs.2023.01.782","title":"Tractography analysis of subcallosal cingulate DBS for treatment-resistant depression using normative connectome data","year":2023,"lang":"en","type":"article","venue":"Brain stimulation","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Tractography; White matter; Connectome; Human Connectome Project; Neuroscience; Psychology; Depression (economics); Medicine; Magnetic resonance imaging; Functional connectivity; Radiology","score_opus":0.27062777260093585,"score_gpt":0.47059152272070376,"score_spread":0.1999637501197679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320898602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77749616,0.000020326752,0.22090955,0.00031124585,0.000013072361,0.00064281066,0.00039359534,0.00018022693,0.00003299951],"genre_scores_gemma":[0.9758898,0.000011051293,0.021144664,0.000052309286,0.000025807018,0.000029783969,0.0028009843,0.000018099116,0.000027472388],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991461,0.000023638568,0.00028037833,0.00028437114,0.00013213676,0.00013339925],"domain_scores_gemma":[0.9987069,0.00045831923,0.0001741898,0.00051961787,0.000095184856,0.00004580494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014990855,0.00010452984,0.00029101668,0.00051632733,0.000092208335,0.0000085770625,0.000081211496,0.000043973232,0.000008629961],"category_scores_gemma":[0.00014638249,0.00009017696,0.00012481486,0.0014546883,0.000035204946,0.0001270538,0.000038616156,0.000029641902,7.9340015e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012612515,0.00047823307,0.14262041,0.00016120315,0.0013879444,0.000011528655,0.0007455932,0.082808055,0.7446446,0.0011862743,0.00068632944,0.024008602],"study_design_scores_gemma":[0.0009103865,0.00010723612,0.23275231,0.000034947854,0.0010286217,0.0000011693614,0.000026973301,0.76001555,0.0038138682,0.0005525872,0.00067516894,0.00008119754],"about_ca_topic_score_codex":0.00004577454,"about_ca_topic_score_gemma":0.000009080495,"teacher_disagreement_score":0.7408307,"about_ca_system_score_codex":0.000034417662,"about_ca_system_score_gemma":0.00002455762,"threshold_uncertainty_score":0.36773098},"labels":[],"label_agreement":null},{"id":"W4320912460","doi":"10.1038/s41598-023-29557-1","title":"Relationship between manual dexterity and left–right asymmetry of anatomical and functional properties of corticofugal tracts revealed by T2-weighted brain images","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Left and right; Asymmetry; Anatomy; Brain asymmetry; Lateralization of brain function; Neuroscience; Computer science; Psychology; Biology; Artificial intelligence; Physics","score_opus":0.06480155682821778,"score_gpt":0.33021053953528096,"score_spread":0.26540898270706315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320912460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971719,0.00015855872,0.0007068392,0.0012822761,0.00011161722,0.0003407748,0.00002602551,0.00010220187,0.00009981617],"genre_scores_gemma":[0.99662316,0.000007043332,0.0015643617,0.000021346706,0.000020918389,0.000010034588,0.00011496088,0.000011839809,0.0016263227],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99859387,0.000033829358,0.0004926128,0.00042691999,0.00030712195,0.00014567227],"domain_scores_gemma":[0.9990391,0.00013091476,0.00024935117,0.00034261492,0.00013463874,0.000103384664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006065441,0.00009672713,0.00024086291,0.00019073149,0.00014945309,0.000025600275,0.000033191805,0.000059283288,0.000011117876],"category_scores_gemma":[0.0004184308,0.0000795747,0.000039628023,0.000390991,0.0006251203,0.00012530314,0.000063351385,0.00014040261,9.915861e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021177293,0.00005411405,0.6696136,0.00013367609,0.0000091773945,0.000025869906,0.000052304313,2.5820987e-7,0.3151451,0.00015194465,0.014288838,0.0005039403],"study_design_scores_gemma":[0.00016529596,0.000037256006,0.8175258,0.00007617012,0.000044363238,0.0002055295,0.000022240662,0.000067782086,0.17288233,0.007230891,0.001666671,0.00007568354],"about_ca_topic_score_codex":0.000007192516,"about_ca_topic_score_gemma":7.2338497e-7,"teacher_disagreement_score":0.14791219,"about_ca_system_score_codex":0.000014927316,"about_ca_system_score_gemma":0.00006354352,"threshold_uncertainty_score":0.32449618},"labels":[],"label_agreement":null},{"id":"W4321013998","doi":"10.1016/j.jagp.2022.12.219","title":"Brain-cognition relationships in late-life depression: a systematic review of magnetic resonance imaging studies","year":2023,"lang":"en","type":"review","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Occupational Cancer Research Centre; Toronto Dementia Research Alliance; St. Michael's Hospital; Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Late life depression; Precuneus; Dementia; Cognition; Medicine; Psychology; Anterior cingulate cortex; Entorhinal cortex; Posterior cingulate; Clinical psychology; Psychiatry; Internal medicine; Hippocampus; Disease","score_opus":0.09401243504466945,"score_gpt":0.4095725928797684,"score_spread":0.31556015783509894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321013998","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000017367116,0.995918,0.0002086409,0.0017826867,0.00024234792,0.001671936,0.000021741122,0.000055936805,0.000081356],"genre_scores_gemma":[0.000052193995,0.9905764,0.008126669,0.0006549827,0.00022618439,0.0001994074,0.000012205964,0.000085772044,0.00006622437],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9953559,0.0005773149,0.0030269397,0.00033995643,0.0004486174,0.00025125418],"domain_scores_gemma":[0.9933851,0.0010643703,0.00443644,0.00060082454,0.00036036668,0.0001529511],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001379137,0.000373807,0.0040828157,0.0008633059,0.00006847886,0.0000090750245,0.00032350086,0.000066062945,0.000006655667],"category_scores_gemma":[0.0025523084,0.0002787057,0.0007078956,0.0028601913,0.0001793454,0.00009473959,0.00007791511,0.0009982057,0.000011831816],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022226595,0.000112392096,0.0002980112,0.8893051,0.00011390655,0.000047556292,0.000044100114,5.80612e-7,2.9812492e-7,0.00005348464,0.0041802493,0.105822094],"study_design_scores_gemma":[0.0003527317,0.00021699084,0.0002112863,0.97255415,0.0044293436,0.0008181102,0.00019136358,0.0000052888367,8.023087e-8,0.00073458,0.020242482,0.00024360538],"about_ca_topic_score_codex":0.000003013184,"about_ca_topic_score_gemma":7.933064e-7,"teacher_disagreement_score":0.10557849,"about_ca_system_score_codex":0.00012086555,"about_ca_system_score_gemma":0.0007226087,"threshold_uncertainty_score":0.9999665},"labels":[],"label_agreement":null},{"id":"W4321014026","doi":"10.1016/j.jagp.2022.12.218","title":"Brain-cognition associations in late-life depression or mild cognitive impairment: A multivariate analysis of white and gray matter integrity","year":2023,"lang":"en","type":"article","venue":"American Journal of Geriatric Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Occupational Cancer Research Centre; Health Sciences Centre; Toronto Dementia Research Alliance; University of Toronto; University Health Network; St. Michael's Hospital; Sunnybrook Health Science Centre; Centre for Addiction and Mental Health","funders":"","keywords":"Fractional anisotropy; Dementia; White matter; Psychology; Cognition; Late life depression; Major depressive disorder; Hyperintensity; Cognitive decline; Effects of sleep deprivation on cognitive performance; Clinical psychology; Magnetic resonance imaging; Audiology; Psychiatry; Medicine; Internal medicine; Disease; Radiology","score_opus":0.03032322072128631,"score_gpt":0.36112719030288865,"score_spread":0.33080396958160235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321014026","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98845947,0.0000731362,0.004792514,0.0061046365,0.000076532466,0.00026197717,0.00010167888,0.000036528618,0.0000935366],"genre_scores_gemma":[0.98839134,0.0003185206,0.009989491,0.0011068862,0.00007402935,0.000017144534,0.00004078013,0.000019498963,0.00004232468],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99858856,0.000114369395,0.00066786195,0.00021061278,0.00022551545,0.00019305554],"domain_scores_gemma":[0.99824536,0.00029985316,0.000965926,0.00014273229,0.0002038243,0.00014230252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038756093,0.00014073959,0.0005999739,0.0012018644,0.00008416887,0.000009895855,0.00008111405,0.00005026052,0.000042204683],"category_scores_gemma":[0.00020650137,0.000109131885,0.00019754564,0.003636628,0.00010007771,0.000112404414,0.000054482596,0.00039042588,0.0000030745027],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006570895,0.00034568767,0.9934815,0.00003209442,0.00047580025,0.000010412303,0.0006430196,0.00005757685,0.00046863238,0.000011477402,0.0013426994,0.0024739793],"study_design_scores_gemma":[0.0015386932,0.0003827134,0.9944145,0.00018084676,0.0012395335,0.000021171782,0.00070018315,0.0008001972,0.00004035975,0.0005428473,0.000030196043,0.000108752036],"about_ca_topic_score_codex":0.00007649008,"about_ca_topic_score_gemma":0.00002150682,"teacher_disagreement_score":0.0051969765,"about_ca_system_score_codex":0.0000404783,"about_ca_system_score_gemma":0.00015471847,"threshold_uncertainty_score":0.4450269},"labels":[],"label_agreement":null},{"id":"W4321368652","doi":"10.1016/j.dib.2023.108999","title":"Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Institute for Basic Science; Albert-Ludwigs-Universität Freiburg; Sungkyunkwan University; Deutsche Forschungsgemeinschaft; National Alliance for Research on Schizophrenia and Depression","keywords":"Neuroimaging; Data science; Psychology; Neuroscience; Computer science","score_opus":0.2434314223278611,"score_gpt":0.41462192978624557,"score_spread":0.17119050745838446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321368652","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38252074,0.003479873,0.03709788,0.52232474,0.0009448884,0.021198705,0.01395326,0.0023607584,0.01611918],"genre_scores_gemma":[0.98308283,0.0004685082,0.0015967902,0.003201063,0.00015451795,0.000138927,0.011293992,0.00003373589,0.000029646402],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985486,0.00010322443,0.00032498036,0.0005448531,0.00020796485,0.00027036874],"domain_scores_gemma":[0.99602276,0.00081524835,0.00007111012,0.0030342154,0.00001926009,0.000037399295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094955816,0.00011841435,0.00016319776,0.000092908514,0.00013324578,0.00006791663,0.001273195,0.000029165878,0.00000565271],"category_scores_gemma":[0.00065672625,0.00007950801,0.000023558767,0.0006134263,0.00015643075,0.00032278072,0.00075991254,0.0004577472,0.000011932839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009313693,0.0014406454,0.11082823,0.0006442608,0.0000763245,0.0006116989,0.0023404332,0.00016019843,0.014547167,0.06949643,0.46823734,0.33068588],"study_design_scores_gemma":[0.00088224444,0.000044218043,0.12444961,0.000082960505,0.000026335823,0.000059020716,0.00056421635,0.04923843,0.00004634423,0.0014529374,0.8230218,0.0001318714],"about_ca_topic_score_codex":0.00015225315,"about_ca_topic_score_gemma":0.000035882906,"teacher_disagreement_score":0.6005621,"about_ca_system_score_codex":0.000017584518,"about_ca_system_score_gemma":0.00008343224,"threshold_uncertainty_score":0.32422426},"labels":[],"label_agreement":null},{"id":"W4321452105","doi":"10.1002/hbm.26239","title":"Integrated diffusion image operator (<scp>iDIO</scp>): A pipeline for automated configuration and processing of diffusion <scp>MRI</scp> data","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; National Institute on Aging; Chang Gung Medical Foundation; Shanghai Educational Development Foundation; Eisai; Servier; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Science and Technology Council; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Computer science; Human Connectome Project; Pipeline (software); Data mining; Preprocessor; Data processing; Image processing; Workflow; Artificial intelligence; Data pre-processing; Diffusion MRI; Image quality; Software; Pattern recognition (psychology); Computer vision; Image (mathematics); Database","score_opus":0.09895152468378401,"score_gpt":0.3742674330731081,"score_spread":0.27531590838932407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321452105","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6915343,0.00015489638,0.30123413,0.0016742722,0.000043510892,0.0021271212,0.00023752844,0.0024294849,0.0005647881],"genre_scores_gemma":[0.9394082,0.00020427367,0.047402173,0.0011842563,0.00029138778,0.00036935264,0.0072759106,0.00017552878,0.0036889173],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981467,0.00005171302,0.000567108,0.00065603905,0.00023168676,0.00034672968],"domain_scores_gemma":[0.9981796,0.00044734878,0.00028855162,0.0006623699,0.00029764278,0.00012447644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049272313,0.00025795487,0.00041756468,0.00031945246,0.0004685388,0.00008868576,0.00026642368,0.00011428679,0.000003838249],"category_scores_gemma":[0.0015153991,0.00023348488,0.000052189174,0.0006869828,0.00015859502,0.0002942087,0.00028653492,0.00023598026,0.0000059228764],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004764746,0.000095068346,0.00035101807,0.00045022796,0.000009983594,0.000007835299,0.00068799796,0.000006069773,0.9461162,0.00032662792,0.048485182,0.0034589884],"study_design_scores_gemma":[0.0027402847,0.00020068459,0.021078855,0.0016409074,0.000103054546,0.000048824095,0.0025118478,0.83342576,0.025899624,0.0013264007,0.11088711,0.00013662885],"about_ca_topic_score_codex":0.000017372273,"about_ca_topic_score_gemma":0.0000049984615,"teacher_disagreement_score":0.9202166,"about_ca_system_score_codex":0.000039085382,"about_ca_system_score_gemma":0.00007472765,"threshold_uncertainty_score":0.9521237},"labels":[],"label_agreement":null},{"id":"W4321496860","doi":"10.3389/fnins.2023.1049609","title":"Effect of sex on the APOE4-aging interaction in the white matter microstructure of cognitively normal older adults using diffusion-tensor MRI with orthogonal-tensor decomposition (DT-DOME)","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Center for Advancing Translational Sciences; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Faculty of Medicine, Chiang Mai University; Thailand Research Fund; Canadian Institutes of Health Research; National Institutes of Health; Royal Golden Jubilee (RGJ) Ph.D. Programme; Chiang Mai University","keywords":"White matter; Diffusion MRI; Psychology; Fasciculus; Neuroscience; Fractional anisotropy; Medicine; Magnetic resonance imaging","score_opus":0.015611776959650317,"score_gpt":0.31666505784390103,"score_spread":0.3010532808842507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321496860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906431,0.000006530259,0.0068366765,0.0014491124,0.000118322445,0.0008380247,0.000018971601,0.000027132208,0.0000621537],"genre_scores_gemma":[0.99737173,0.000017890608,0.0014835274,0.00100883,0.00001878972,0.00004525826,0.0000071569257,0.000015867512,0.00003095244],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988439,0.00014234563,0.00022948734,0.00031938255,0.000262995,0.00020190212],"domain_scores_gemma":[0.99933237,0.00017979262,0.00016140993,0.0002553621,0.000046759007,0.000024312378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027691165,0.000136589,0.00020403335,0.0002410088,0.000104856015,0.000015185091,0.00019244506,0.000029981156,0.0000038526136],"category_scores_gemma":[0.00005081262,0.000077499,0.000044881614,0.0009287002,0.00025103166,0.00011246232,0.00005123867,0.00030620088,7.705016e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006615558,0.00011134315,0.8962028,0.00013713403,0.0000026166897,0.000041486008,0.001210307,0.0009585475,0.098164104,0.000011079636,0.0006815661,0.0018174405],"study_design_scores_gemma":[0.0009438505,0.00041315047,0.93685853,0.00081499136,0.00002727374,0.00015308068,0.00066180486,0.03310947,0.026775278,0.000037773443,0.00009071093,0.00011405664],"about_ca_topic_score_codex":0.000010529292,"about_ca_topic_score_gemma":0.00000144265,"teacher_disagreement_score":0.071388826,"about_ca_system_score_codex":0.000027165208,"about_ca_system_score_gemma":0.000016000206,"threshold_uncertainty_score":0.31603175},"labels":[],"label_agreement":null},{"id":"W4321598136","doi":"10.3390/biology12030353","title":"Morphological Abnormalities in Early-Onset Schizophrenia Revealed by Structural Magnetic Resonance Imaging","year":2023,"lang":"en","type":"article","venue":"Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institutes of Health; St. Francis Xavier University","keywords":"Neurotypical; Schizophrenia (object-oriented programming); Magnetic resonance imaging; Cuneus; Neuroscience; Superior temporal gyrus; Inferior temporal gyrus; Gyrus; Cortex (anatomy); Biology; Anatomy; Psychology; Functional magnetic resonance imaging; Temporal lobe; Precuneus; Medicine; Radiology; Epilepsy; Psychiatry","score_opus":0.039681147442310195,"score_gpt":0.3397763233286215,"score_spread":0.3000951758863113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321598136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99493784,0.0013797645,0.00009103265,0.0026337623,0.000043161264,0.00024001209,0.00007882308,0.00035385843,0.00024174897],"genre_scores_gemma":[0.99499816,0.00021148857,0.0032360235,0.00065229123,0.000044990884,0.000091203845,0.00011479052,0.0000136057815,0.0006374643],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991263,0.000048189235,0.00019823131,0.0002876704,0.000046746605,0.00029282607],"domain_scores_gemma":[0.9995752,0.00007773956,0.000034867386,0.00024148445,0.000020820782,0.00004987587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009167106,0.00010760409,0.00019129911,0.00009604111,0.00005071903,0.0000058192363,0.0001103608,0.000060327435,0.000052681648],"category_scores_gemma":[0.00007723844,0.000089622525,0.00003360619,0.00029266637,0.00019455391,0.000029593615,0.0000790603,0.00020545934,0.000046370857],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014141851,0.000016997812,0.9503079,0.000010702485,0.0000013146254,0.00013973705,0.000045733846,4.7156217e-7,0.019454682,0.0017661585,0.011196075,0.016918823],"study_design_scores_gemma":[0.0007159656,0.00013414229,0.9650586,0.000024236526,0.0000054887937,0.0002525046,0.000019834812,0.00031390262,0.0006257515,0.009985738,0.022736454,0.00012732849],"about_ca_topic_score_codex":0.000063943604,"about_ca_topic_score_gemma":0.0000024913707,"teacher_disagreement_score":0.01882893,"about_ca_system_score_codex":0.00002348226,"about_ca_system_score_gemma":0.00001613282,"threshold_uncertainty_score":0.36547005},"labels":[],"label_agreement":null},{"id":"W4321844994","doi":"10.1007/978-3-030-98661-2_108","title":"A Survey on Deep Learning-Based Diffeomorphic Mapping","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Diffeomorphism; Artificial intelligence; Computer science; Autoencoder; Deep learning; Polygon mesh; Convolutional neural network; Segmentation; Unsupervised learning; Pattern recognition (psychology); Machine learning; Mathematics","score_opus":0.16712890854143733,"score_gpt":0.3412837986051227,"score_spread":0.17415489006368537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4321844994","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009547795,0.00008939562,0.10786792,0.0036468552,0.0001359524,0.0016487725,0.00009555754,0.00448979,0.8819303],"genre_scores_gemma":[0.010047647,0.00016707857,0.001815732,0.0018523611,0.000114881856,0.00006145566,0.00090847653,0.00022212426,0.98481023],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99880654,0.000020954141,0.0002475296,0.0004749732,0.00025343045,0.00019655553],"domain_scores_gemma":[0.9986923,0.00044337244,0.00013374245,0.00052735663,0.00009355405,0.00010970199],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020385822,0.00028381115,0.0003958826,0.00024273114,0.00009188595,0.000012684197,0.00010843357,0.00018615217,0.0003549251],"category_scores_gemma":[0.0001526743,0.000252754,0.00014578996,0.00007159958,0.00007302883,0.000009065194,0.000050064587,0.00082559907,0.0007645258],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015020496,0.0009433974,0.015378338,0.0018577746,0.0008641808,0.0024098537,0.00013454143,0.0020567502,0.0021910388,0.55216223,0.24945837,0.17104147],"study_design_scores_gemma":[0.0011366974,0.0007357096,0.042993624,0.0014068417,0.0001384358,0.000023870394,0.0000036350423,0.0074181575,0.00023288635,0.0139170075,0.9310197,0.00097341766],"about_ca_topic_score_codex":0.000024495721,"about_ca_topic_score_gemma":0.000025702453,"teacher_disagreement_score":0.68156135,"about_ca_system_score_codex":0.00005982491,"about_ca_system_score_gemma":0.00004086994,"threshold_uncertainty_score":0.9999925},"labels":[],"label_agreement":null},{"id":"W4322630837","doi":"10.1101/2023.02.25.530046","title":"Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute on Aging; National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Tractography; Diffusion MRI; Context (archaeology); Convolutional neural network; Computer science; Artificial intelligence; Diffusion; Magnetic resonance imaging; Neuroscience; Medicine; Psychology; Radiology; Physics; Biology","score_opus":0.035304940686680525,"score_gpt":0.2762823238498559,"score_spread":0.24097738316317538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322630837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96415687,0.0015743083,0.027549101,0.0014602572,0.00064128224,0.0016282205,0.0009612861,0.002026376,0.000002304086],"genre_scores_gemma":[0.99141544,0.0014239557,0.0058205985,0.0003844892,0.00032089677,0.00042601803,0.000026539768,0.00017866945,0.000003381855],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99698085,0.000117406744,0.0006440238,0.0012989378,0.00039393216,0.0005648512],"domain_scores_gemma":[0.99756396,0.00021790138,0.0004810094,0.00095245754,0.0003740903,0.00041055493],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024845806,0.0006042287,0.0008396784,0.00030831224,0.00022490842,0.00011675339,0.00028852143,0.0005985232,0.000020904548],"category_scores_gemma":[0.00014118645,0.00061253895,0.0002490282,0.00063519843,0.00026790416,0.00008567525,0.00050841307,0.0015386124,0.000008883643],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008216606,0.0036798473,0.3994446,0.000915103,0.0018277835,0.00055822794,0.000052718377,0.00021547465,0.5739211,0.007139365,0.011166093,0.00025803267],"study_design_scores_gemma":[0.0020126437,0.000118150776,0.7242253,0.0009751503,0.0005642771,1.1129858e-7,0.000004360626,0.26136607,0.00712056,0.000104613886,0.0024418836,0.0010668798],"about_ca_topic_score_codex":0.000102609054,"about_ca_topic_score_gemma":0.0000035438788,"teacher_disagreement_score":0.56680053,"about_ca_system_score_codex":0.00020688014,"about_ca_system_score_gemma":0.0001298894,"threshold_uncertainty_score":0.9996326},"labels":[],"label_agreement":null},{"id":"W4322723775","doi":"10.1016/j.jmbbm.2023.105744","title":"Transversely-isotropic brain in vivo MR elastography with anisotropic damping","year":2023,"lang":"en","type":"article","venue":"Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; Office of Naval Research; National Institutes of Health","keywords":"Transverse isotropy; Anisotropy; Elastography; Magnetic resonance elastography; Isotropy; Imaging phantom; Fractional anisotropy; Stiffness; Diffusion MRI; Physics; Population; Estimator; White matter; Biomedical engineering; Materials science; Nuclear magnetic resonance; Magnetic resonance imaging; Mathematics; Acoustics; Optics; Statistics; Ultrasound; Radiology; Medicine","score_opus":0.037647189582221526,"score_gpt":0.3225610409264671,"score_spread":0.28491385134424557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322723775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98766637,0.00005283227,0.004037973,0.0047437246,0.002028363,0.0010417319,0.00036717585,0.000059543214,0.0000023064147],"genre_scores_gemma":[0.9852587,0.0003222838,0.013462966,0.00022003287,0.0005281735,0.00005818094,0.000019682158,0.000108226865,0.000021744678],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.98987895,0.0005948567,0.005171618,0.00051488547,0.0029942594,0.0008454437],"domain_scores_gemma":[0.9934755,0.0004651511,0.0036549065,0.0008105585,0.000717006,0.000876875],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0033144015,0.0006186714,0.0028707914,0.001352096,0.00011242726,0.00005252717,0.001586208,0.00071309396,0.0011243108],"category_scores_gemma":[0.0008380256,0.0003876283,0.0008833243,0.0020482526,0.0010529945,0.00028203157,0.00039477996,0.0010371313,0.0000059889267],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001932782,0.0023487606,0.00039591812,0.0003258452,0.00012111996,0.000878392,0.00005708625,8.373033e-7,0.99105006,0.00067460106,0.0005892646,0.0016253564],"study_design_scores_gemma":[0.006505739,0.0069666905,0.007849683,0.002584249,0.0015340913,0.0030208027,0.00018635059,0.000005866793,0.96828115,0.0011119518,0.0015733396,0.00038008182],"about_ca_topic_score_codex":0.00003554947,"about_ca_topic_score_gemma":0.0000022881968,"teacher_disagreement_score":0.022768883,"about_ca_system_score_codex":0.00019817936,"about_ca_system_score_gemma":0.00051216746,"threshold_uncertainty_score":0.99985754},"labels":[],"label_agreement":null},{"id":"W4323066381","doi":"10.1093/schbul/sbac216","title":"Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls","year":2023,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health","keywords":"Neurocognitive; Psychology; White matter; Cognition; Social cognition; Schizophrenia (object-oriented programming); Neuropsychology; Diffusion MRI; Corpus callosum; Developmental psychology; Cognitive psychology; Clinical psychology; Neuroscience; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.02368602726047368,"score_gpt":0.3091226926225757,"score_spread":0.285436665362102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323066381","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9164034,0.00004640723,0.0014186924,0.07911019,0.000038418573,0.0014006618,0.00058475166,0.00070546987,0.0002919731],"genre_scores_gemma":[0.9910615,0.00015963458,0.005629967,0.0018425504,0.00015986187,0.00039814855,0.00050504593,0.00007876597,0.00016449783],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981394,0.00009045252,0.00038565928,0.00060061907,0.00027569933,0.0005082133],"domain_scores_gemma":[0.9991402,0.00015788015,0.0002658549,0.0002073369,0.000059163292,0.00016953508],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00023689489,0.00028688682,0.0003954224,0.00016746054,0.00081860303,0.0001253507,0.00008074249,0.00012226986,0.00006237594],"category_scores_gemma":[0.000065476845,0.0002720607,0.000059510312,0.00043865692,0.00032154057,0.00010353236,0.00011868259,0.00045800384,0.0000940109],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049956753,0.0007033528,0.95533127,0.00038633138,0.0003729721,0.00006307132,0.0021721493,0.000016850912,0.0030105046,0.004409806,0.0145955235,0.013942523],"study_design_scores_gemma":[0.0074194847,0.00023724466,0.98258823,0.00007895786,0.00014554635,0.0000412936,0.00014710057,0.00011339236,0.000105629406,0.0048610074,0.0039491956,0.00031289828],"about_ca_topic_score_codex":0.00004704935,"about_ca_topic_score_gemma":0.00005054891,"teacher_disagreement_score":0.07726764,"about_ca_system_score_codex":0.00002217374,"about_ca_system_score_gemma":0.000040744802,"threshold_uncertainty_score":0.9999732},"labels":[],"label_agreement":null},{"id":"W4323073897","doi":"10.1101/2023.03.01.530710","title":"The Human Brain Connectome Weighted by the Myelin Content and Total Intra-Axonal Cross-Sectional Area of White Matter Tracts","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canadian Institutes of Health Research; Hospital for Sick Children; Fondation Brain Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Connectome; Diffusion MRI; Myelin; Neuroscience; Human brain; Human Connectome Project; Connectomics; Computer science; Psychology; Biology; Functional connectivity; Central nervous system; Medicine; Magnetic resonance imaging","score_opus":0.06648026584508343,"score_gpt":0.3067531004412651,"score_spread":0.24027283459618165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323073897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9874156,0.00034520245,0.0019422699,0.007999484,0.0002445542,0.0011381411,0.0005847686,0.00031917772,0.000010800142],"genre_scores_gemma":[0.99706477,0.00009893597,0.0011112051,0.00080041273,0.00022694076,0.00043360234,0.0000036728923,0.00010078601,0.00015968396],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9978608,0.000074523225,0.00063399854,0.0006920538,0.0003785208,0.00036009078],"domain_scores_gemma":[0.9976962,0.00032404743,0.0004182318,0.00097651733,0.00042906072,0.00015594444],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00056348724,0.00035891638,0.00041055537,0.00010143809,0.00055379065,0.00014030565,0.00033377775,0.00024268318,0.00004533793],"category_scores_gemma":[0.00015392585,0.00024983453,0.00014590124,0.0002547055,0.00055775495,0.00006246091,0.0004334111,0.00092983665,0.00001422341],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006835423,0.00013338662,0.3187427,0.0001735182,0.00015966396,0.000015790127,0.000011912394,0.000007248585,0.67214674,0.001654646,0.0068836473,0.0000024209583],"study_design_scores_gemma":[0.0005452391,0.000054405453,0.95422405,0.00016245215,0.0000630083,5.445347e-7,0.0000034425993,0.00021698816,0.03949862,0.00004768176,0.0049163937,0.00026715136],"about_ca_topic_score_codex":0.00002945114,"about_ca_topic_score_gemma":0.0000016318259,"teacher_disagreement_score":0.6354814,"about_ca_system_score_codex":0.00009989081,"about_ca_system_score_gemma":0.00014210795,"threshold_uncertainty_score":0.9999954},"labels":[],"label_agreement":null},{"id":"W4323269182","doi":"10.1016/j.nicl.2023.103367","title":"Aberrant frontal lobe “U”-shaped association fibers in first-episode schizophrenia: A 7-Tesla Diffusion Imaging Study","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Dalhousie University; Schulich School of Medicine and Dentistry; Western University; Canada Foundation for Innovation; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; McGill University; Chrysalis","keywords":"Frontal lobe; Schizophrenia (object-oriented programming); Diffusion MRI; Association (psychology); Neuroscience; Temporal lobe; Psychology; Medicine; Magnetic resonance imaging; Psychiatry; Epilepsy; Radiology","score_opus":0.08897231508810213,"score_gpt":0.4085580601756791,"score_spread":0.319585745087577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323269182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9860969,0.0000314083,0.0007274609,0.009540107,0.00039991876,0.0015372706,0.000021938044,0.0010543333,0.00059065747],"genre_scores_gemma":[0.99443895,0.00019449973,0.0021461467,0.0014656191,0.00034712008,0.00019312705,0.00005804954,0.000084573374,0.0010719108],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99679303,0.00021174196,0.0010083596,0.0009603538,0.00050064514,0.0005258611],"domain_scores_gemma":[0.9976942,0.0009895461,0.0002796606,0.0007433226,0.000092690105,0.00020061419],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009919752,0.00027595367,0.00060504914,0.00026206629,0.00018021656,0.00004792207,0.00024562207,0.00012200299,0.00005205379],"category_scores_gemma":[0.0018305774,0.00026883298,0.0002521907,0.0008319562,0.00008832059,0.00016819841,0.00029795634,0.0010862915,0.0002409061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002668583,0.0013234572,0.97725034,0.000019278528,0.000015168707,0.00058878824,0.000106429485,0.000007922861,0.0013188542,0.000016783415,0.013618224,0.0054678773],"study_design_scores_gemma":[0.004739617,0.0003556716,0.968775,0.00007791183,0.000088345965,0.000031113424,0.00010038063,0.018890176,0.000037630296,0.0004105883,0.006259815,0.00023375617],"about_ca_topic_score_codex":0.000102448896,"about_ca_topic_score_gemma":0.00011613571,"teacher_disagreement_score":0.018882254,"about_ca_system_score_codex":0.00016480607,"about_ca_system_score_gemma":0.000046828336,"threshold_uncertainty_score":0.9999764},"labels":[],"label_agreement":null},{"id":"W4323347970","doi":"10.1093/cercor/bhad052","title":"Loss of age-related laminar differentiation of intracortical myelin in bipolar disorder","year":2023,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McGill University; Montreal Neurological Institute and Hospital; St. Joseph’s Healthcare Hamilton","funders":"Canadian Institutes of Health Research; McMaster University; Brain and Behavior Research Foundation","keywords":"Myelin; Neuroscience; Bipolar disorder; Psychology; Medicine; Cognition; Central nervous system","score_opus":0.031139920224618242,"score_gpt":0.3214482965989662,"score_spread":0.2903083763743479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323347970","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9963551,0.000101881196,0.002387812,0.0006175989,0.000028311713,0.00027661052,0.000011798129,0.00011905893,0.00010178291],"genre_scores_gemma":[0.998525,0.0001449002,0.00091666327,0.000027965125,0.000012638503,0.000018132614,0.000093676594,0.00001716863,0.00024383946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920046,0.000017803419,0.00035056053,0.00016656467,0.0001263361,0.00013828884],"domain_scores_gemma":[0.9995504,0.000041867257,0.000093235074,0.00023082558,0.0000442218,0.000039423732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060355065,0.000079335354,0.000219729,0.00015158905,0.000015510834,0.0000018553287,0.000068737805,0.00006128099,0.000060035247],"category_scores_gemma":[0.000066436914,0.000072038005,0.00007060827,0.000574181,0.00011356803,0.00003707597,0.00004631797,0.00015746585,0.000013232393],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104253224,0.00057292904,0.79886466,0.00025640574,0.000039363007,0.000057209145,0.00028681094,0.00004085606,0.14279388,0.02268446,0.00037726693,0.03392191],"study_design_scores_gemma":[0.0006146273,0.00012930454,0.9818258,0.000085461266,0.00003992051,0.0000072058715,0.000034182325,0.004044985,0.005498679,0.0070476653,0.00059831096,0.000073834766],"about_ca_topic_score_codex":0.000029257137,"about_ca_topic_score_gemma":0.000009486455,"teacher_disagreement_score":0.18296117,"about_ca_system_score_codex":0.000015517202,"about_ca_system_score_gemma":0.000017617424,"threshold_uncertainty_score":0.29376245},"labels":[],"label_agreement":null},{"id":"W4323364366","doi":"10.3389/fnins.2023.1074730","title":"Estimation of free water-corrected microscopic fractional anisotropy","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Anisotropy; Diffusion MRI; Fractional anisotropy; Orientation (vector space); Free water; Nuclear magnetic resonance; Partial volume; Diffusion; Dispersion (optics); SIGNAL (programming language); Voxel; Materials science; Biological system; Physics; Biomedical engineering; Computer science; Mathematics; Optics; Artificial intelligence; Geology; Magnetic resonance imaging; Geometry; Medicine; Biology; Radiology; Thermodynamics","score_opus":0.036493819689401505,"score_gpt":0.33623006747423156,"score_spread":0.29973624778483005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323364366","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.58634084,0.0000118549215,0.4107199,0.0015386693,0.0006331016,0.00030207817,0.000014122431,0.00025865744,0.00018076079],"genre_scores_gemma":[0.92570907,0.00006122496,0.07338972,0.00033708333,0.00001644365,0.000037976144,0.000017283044,0.0000121894955,0.00041901486],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99922496,0.000012394442,0.00016617417,0.0002474558,0.00017267153,0.00017631803],"domain_scores_gemma":[0.9995805,0.000015917461,0.00004263073,0.00029555918,0.000025622749,0.00003977828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007483682,0.00006664005,0.00012269604,0.00022331208,0.00005891285,0.000007363048,0.00016865892,0.000025940137,0.0000043437476],"category_scores_gemma":[0.00017018607,0.000056908793,0.000026065693,0.00071012846,0.00014842994,0.000107086475,0.00007101845,0.00012002887,0.0000051819393],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040382034,0.00013063027,0.07253406,0.00004688155,0.0000010515136,0.000026156787,0.000095406205,0.0026869879,0.89363843,0.00044506288,0.02329773,0.007057209],"study_design_scores_gemma":[0.00083275,0.00021750195,0.30373004,0.00008591659,0.000013626804,0.000048619942,0.000044391036,0.27512985,0.39583933,0.014004356,0.009884405,0.00016921069],"about_ca_topic_score_codex":0.000006732676,"about_ca_topic_score_gemma":2.443708e-7,"teacher_disagreement_score":0.49779913,"about_ca_system_score_codex":0.000030503641,"about_ca_system_score_gemma":0.000029685367,"threshold_uncertainty_score":0.23206732},"labels":[],"label_agreement":null},{"id":"W4323364368","doi":"10.3389/fnut.2023.1108360","title":"Extended and replicated white matter changes in obesity: Voxel-based and region of interest meta-analyses of diffusion tensor imaging studies","year":2023,"lang":"en","type":"article","venue":"Frontiers in Nutrition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Voxel; White matter; Diffusion; Meta-analysis; Psychology; Computer science; Cognitive psychology; Medicine; Physics; Artificial intelligence; Magnetic resonance imaging; Internal medicine; Radiology","score_opus":0.2617820086621642,"score_gpt":0.409704120920407,"score_spread":0.14792211225824276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323364368","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97659075,0.0050886762,0.008112327,0.009398402,0.000025078456,0.00067978556,0.000014857883,0.000072820476,0.00001730216],"genre_scores_gemma":[0.98187166,0.0046827765,0.013015857,0.00018703831,0.000009026578,0.00014688811,0.000029424555,0.000012980452,0.000044325305],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992989,0.000047505946,0.00024691055,0.0002452895,0.00006399782,0.00009744473],"domain_scores_gemma":[0.99952924,0.000046706155,0.00012617002,0.000205975,0.00006929659,0.00002259978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014899884,0.000095237294,0.00044138936,0.00052157167,0.000020163843,0.0000034251568,0.000034404573,0.00003033915,0.0000016203119],"category_scores_gemma":[0.00006349313,0.00007992776,0.000043727545,0.00043002015,0.000144062,0.000047096106,0.00004305504,0.00008497866,1.4722555e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022233938,0.00039718897,0.93649477,0.0019113682,0.00013642514,0.000038544575,0.00022225252,0.0000032084963,0.048236113,0.00003361291,0.009619499,0.0026846554],"study_design_scores_gemma":[0.0036769928,0.00025417926,0.86077344,0.0024885347,0.0015338872,0.00004865085,0.0022055947,0.010288037,0.10171792,0.016181843,0.0005367639,0.00029414665],"about_ca_topic_score_codex":0.000012864762,"about_ca_topic_score_gemma":0.000008213719,"teacher_disagreement_score":0.075721346,"about_ca_system_score_codex":0.000024833858,"about_ca_system_score_gemma":0.0000036914282,"threshold_uncertainty_score":0.32593596},"labels":[],"label_agreement":null},{"id":"W4323534158","doi":"10.1002/oby.23686","title":"Is adiposity associated with white matter microstructural health and intelligence differently in males and females?","year":2023,"lang":"en","type":"article","venue":"Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; Biobank; Diffusion MRI; Medicine; Obesity; Fractional anisotropy; Abdominal obesity; Cardiovascular health; Physiology; Internal medicine; Demography; Metabolic syndrome; Magnetic resonance imaging; Bioinformatics; Biology","score_opus":0.06887097637335537,"score_gpt":0.347940609240043,"score_spread":0.2790696328666876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323534158","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99367225,0.00008865066,0.00041280597,0.0054019135,0.0000064203105,0.00024428728,0.000023332686,0.000096658834,0.00005365072],"genre_scores_gemma":[0.99670744,0.00016641896,0.0011209529,0.0014987866,0.0000069641687,0.000009535186,0.00002919072,0.000010202042,0.0004505216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99942553,0.00001851742,0.000105157174,0.00022315046,0.00006469305,0.00016296055],"domain_scores_gemma":[0.9996796,0.00002688552,0.000048000336,0.00013650919,0.000018682498,0.000090312926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055729874,0.000088976005,0.00016720717,0.000053349744,0.000079946854,0.00001434234,0.000035705125,0.000029315277,0.000013156203],"category_scores_gemma":[0.000011050046,0.000071939416,0.0000117292975,0.00018709403,0.000086725755,0.000039323204,0.000061020477,0.00013716657,0.0000061607843],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016536662,0.000022584923,0.99826103,0.000045520646,0.000004532495,0.0000071447357,0.00022575879,1.9230262e-7,0.0003779165,0.0000484544,0.00035523582,0.0006351176],"study_design_scores_gemma":[0.00014769475,0.00006861879,0.9977856,0.0001237285,0.000008033827,0.00003194904,0.000039748684,0.00013774486,0.0008764332,0.00062447507,0.00008637783,0.00006955959],"about_ca_topic_score_codex":0.000035236524,"about_ca_topic_score_gemma":0.00005027992,"teacher_disagreement_score":0.003903127,"about_ca_system_score_codex":0.000033369884,"about_ca_system_score_gemma":0.00001569706,"threshold_uncertainty_score":0.2933604},"labels":[],"label_agreement":null},{"id":"W4323536554","doi":"10.1101/2023.03.03.23286579","title":"What has brain diffusion MRI taught us about chronic pain: a narrative review","year":2023,"lang":"en","type":"review","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arthritis Society","keywords":"Chronic pain; Diffusion MRI; Narrative review; Medicine; Neuroscience; White matter; Harmonization; Psychology; Intensive care medicine; Magnetic resonance imaging; Radiology","score_opus":0.15357747015557532,"score_gpt":0.43233466999705067,"score_spread":0.27875719984147534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323536554","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000031848342,0.9793228,0.0012375613,0.014232461,0.00024026936,0.0040318184,0.000026194994,0.00075776473,0.00014794133],"genre_scores_gemma":[4.212128e-7,0.98529345,0.00065418106,0.003659886,0.000480844,0.0020710486,0.00043650044,0.00019783921,0.0072058477],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99689394,0.00037922108,0.00093386124,0.000936381,0.00039257412,0.00046403962],"domain_scores_gemma":[0.99715364,0.0005326593,0.0005589999,0.0014157518,0.00011345756,0.00022548414],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009358448,0.0006243072,0.0023380439,0.00020274568,0.00024180085,0.00007634379,0.00042936875,0.0002412378,0.00017920605],"category_scores_gemma":[0.0006326462,0.00046134202,0.00074225676,0.001149929,0.00019646404,0.00014143402,0.00022723414,0.0009524648,0.000381378],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000021099506,0.000075851116,0.000008110828,0.0993142,0.0000781761,0.00013788338,0.000065938555,9.72203e-8,0.0000079564925,0.00013575394,0.105250865,0.79492307],"study_design_scores_gemma":[0.000115392526,0.000098037366,0.000009021572,0.23857488,0.00049667346,0.00011018206,0.000008267027,0.000016277903,0.000001591824,0.000104180566,0.7601752,0.00029025163],"about_ca_topic_score_codex":0.0000053600993,"about_ca_topic_score_gemma":0.000008894602,"teacher_disagreement_score":0.7946328,"about_ca_system_score_codex":0.00029589786,"about_ca_system_score_gemma":0.00045998424,"threshold_uncertainty_score":0.9997838},"labels":[],"label_agreement":null},{"id":"W4323665786","doi":"10.3389/fnimg.2023.1099301","title":"Optimizing automated white matter hyperintensity segmentation in individuals with stroke","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council; National Institute of Neurological Disorders and Stroke; Medical Research Council; National Institutes of Health; University of Melbourne; Canadian Institutes of Health Research; National Imaging Facility","keywords":"Segmentation; Hyperintensity; Stroke (engine); Artificial intelligence; Computer science; Machine learning; Medicine; Magnetic resonance imaging; Engineering","score_opus":0.031687756835165094,"score_gpt":0.3118026041172791,"score_spread":0.280114847282114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323665786","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96009374,0.00003101529,0.030865787,0.005426026,0.00014890998,0.00077593705,0.000015906242,0.0013963558,0.001246337],"genre_scores_gemma":[0.79196733,0.00004529351,0.20602293,0.0014097934,0.000019230793,0.00010191586,0.000049559603,0.000053395972,0.00033055324],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987757,0.000035636032,0.00025345574,0.0004064528,0.0001884486,0.00034029823],"domain_scores_gemma":[0.99952084,0.000021708436,0.0000726361,0.0002924017,0.000033158736,0.000059264643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014379519,0.0001577843,0.00025700842,0.0006101403,0.00005443471,0.000031676995,0.00010022747,0.00003191388,0.0000091257625],"category_scores_gemma":[0.000020499638,0.00015455377,0.000031613145,0.00089031074,0.00006503209,0.00019349984,0.00007248312,0.00033017359,0.000017562015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024333629,0.000036034464,0.9857551,0.000029901183,0.0000054056154,0.00013597924,0.0002902644,0.0016308156,0.0032337622,0.000004193444,0.0079740565,0.0008801628],"study_design_scores_gemma":[0.0010101018,0.00003588525,0.9260696,0.00013028625,0.000017459884,0.00008135032,0.00045245292,0.06981271,0.001346042,0.00009421544,0.00078451884,0.0001653628],"about_ca_topic_score_codex":0.000012725934,"about_ca_topic_score_gemma":0.0000017638403,"teacher_disagreement_score":0.17515714,"about_ca_system_score_codex":0.000087983935,"about_ca_system_score_gemma":0.000024039364,"threshold_uncertainty_score":0.63025194},"labels":[],"label_agreement":null},{"id":"W4323804540","doi":"10.1002/hbm.26259","title":"High spatial overlap but diverging age‐related trajectories of cortical magnetic resonance imaging markers aiming to represent intracortical myelin and microstructure","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; Polytechnique Montréal; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Weston Brain Institute","keywords":"Cytoarchitecture; Magnetic resonance imaging; Myelin; White matter; Neuroscience; Neuroimaging; Nuclear magnetic resonance; Psychology; Medicine; Central nervous system; Physics; Radiology","score_opus":0.030363313889827343,"score_gpt":0.31018636863866406,"score_spread":0.27982305474883673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323804540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98657966,0.00019968401,0.0071049975,0.0048722196,0.00007416381,0.0005835547,0.000019381692,0.00039057157,0.00017577846],"genre_scores_gemma":[0.99066657,0.00002661685,0.008140979,0.0005413423,0.000112770045,0.000037276386,0.000034761866,0.000041891442,0.00039776557],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983024,0.000052917992,0.00048597675,0.0005247565,0.00024752985,0.00038639057],"domain_scores_gemma":[0.99904895,0.00025082304,0.00008913333,0.00038514793,0.0000653877,0.00016054971],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000224176,0.00019579387,0.0003466519,0.00021727048,0.00028755082,0.00003490702,0.00012097863,0.00006421336,0.000050511368],"category_scores_gemma":[0.0004467875,0.00020255685,0.00006817703,0.00045279824,0.0002999069,0.00006209975,0.0002366237,0.0003857786,0.000004948596],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008789675,0.000030044845,0.045602985,0.00012779816,0.00001299081,0.00028839122,0.0009587956,0.000039401522,0.92808473,0.004712284,0.0019417603,0.018112931],"study_design_scores_gemma":[0.00067722105,0.00009844514,0.9857232,0.00039972537,0.00004089814,0.000089635316,0.0004804672,0.0026179194,0.002394301,0.0050636656,0.0021853421,0.00022917666],"about_ca_topic_score_codex":0.00013364923,"about_ca_topic_score_gemma":0.000006189436,"teacher_disagreement_score":0.9401202,"about_ca_system_score_codex":0.000048682716,"about_ca_system_score_gemma":0.00002302878,"threshold_uncertainty_score":0.8260029},"labels":[],"label_agreement":null},{"id":"W4323830526","doi":"10.1101/2023.03.07.531625","title":"Effect of number of diffusion encoding directions in Neonatal Diffusion Tensor Imaging using Tract-Based Spatial Statistical analysis","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Turun Yliopistollinen Keskussairaala; Alfred Kordelinin Säätiö; Varsinais-Suomen Sairaanhoitopiiri; Emil Aaltosen Säätiö; Jane ja Aatos Erkon Säätiö","keywords":"Diffusion MRI; Weighting; Scalar (mathematics); Fractional anisotropy; Mathematics; Statistics; Physics; Medicine; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.026794206629695828,"score_gpt":0.324801201422658,"score_spread":0.29800699479296217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323830526","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8246267,0.0000662475,0.17364323,0.00007807423,0.00013815073,0.0007655568,0.00040457593,0.000274761,0.0000027036142],"genre_scores_gemma":[0.9695909,0.00007963498,0.029982952,0.00001994514,0.000082864964,0.00013059769,0.000005307425,0.00010619154,0.0000016189333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99736387,0.00018322396,0.0008293766,0.00081659906,0.00044646524,0.00036048525],"domain_scores_gemma":[0.9975736,0.0004860769,0.00056572445,0.0009312814,0.0002820114,0.00016126753],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005349038,0.00041334284,0.0010820561,0.0008704459,0.000097000244,0.00002481576,0.00020858765,0.00021916984,0.000037765676],"category_scores_gemma":[0.0005240822,0.00041010734,0.00031219426,0.001477406,0.00018441479,0.00006097994,0.00027604657,0.00071414746,0.0000033076892],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108679276,0.00021626425,0.60682654,0.00061848515,0.00007723134,0.0000746956,0.0000060582433,0.0004254876,0.3915441,0.000053804837,0.0000052091186,0.0000434141],"study_design_scores_gemma":[0.0010776902,0.000084739266,0.6677347,0.0011571965,0.0016117803,1.2637082e-7,0.0000023636344,0.11944625,0.20839562,0.0000040574223,0.00007804411,0.00040745962],"about_ca_topic_score_codex":0.0009096294,"about_ca_topic_score_gemma":0.000007059911,"teacher_disagreement_score":0.1831485,"about_ca_system_score_codex":0.00025868922,"about_ca_system_score_gemma":0.00021916702,"threshold_uncertainty_score":0.9998351},"labels":[],"label_agreement":null},{"id":"W4323832879","doi":"10.3233/jad-220476","title":"Localized White Matter Tract Integrity Measured by Diffusion Tensor Imaging Is Altered in People with Mild Cognitive Impairment and Associated with Dual-Task and Single-Task Gait Speed","year":2023,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkwood Institute; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; White matter; Cognitive impairment; Task (project management); Dual (grammatical number); Gait; Physical medicine and rehabilitation; Cognition; Tractography; Psychology; Diffusion; Neuroscience; Medicine; Cognitive psychology; Magnetic resonance imaging; Physics; Engineering; Radiology; Art","score_opus":0.04157488697593542,"score_gpt":0.3099691442676982,"score_spread":0.2683942572917628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323832879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881371,0.00092986337,0.00043408535,0.009678355,0.000014898859,0.0005900087,0.00013585376,0.000056838002,0.000022994802],"genre_scores_gemma":[0.99769,0.00013498115,0.00047983511,0.0015177187,0.00003125496,0.000015553707,0.00004939029,0.000043459302,0.00003776952],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99861294,0.00007387429,0.00037683552,0.0002945444,0.00038142665,0.00026035123],"domain_scores_gemma":[0.99879986,0.000087519766,0.00033127025,0.00014618435,0.00024751434,0.00038765577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021793807,0.00022560541,0.0004257419,0.00021019283,0.00007998204,0.000048482165,0.000047937185,0.000035788376,0.000026219588],"category_scores_gemma":[0.000060939772,0.00015662353,0.00006370256,0.00036525223,0.00013099462,0.00019340836,0.000041057658,0.00039861532,0.0000022170602],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002136597,0.0009758812,0.9867653,0.00003336975,0.00020787503,0.0003384196,0.00055531744,0.0000029977539,0.0029228746,5.0311974e-7,0.005412246,0.00064862147],"study_design_scores_gemma":[0.00568639,0.0004308488,0.98878264,0.0010340887,0.0012550604,0.00020719176,0.00036021514,0.0013218238,0.00053235336,0.000086608896,0.000094763396,0.00020801077],"about_ca_topic_score_codex":0.000020932255,"about_ca_topic_score_gemma":0.0000051200195,"teacher_disagreement_score":0.009552936,"about_ca_system_score_codex":0.0000524005,"about_ca_system_score_gemma":0.00007974317,"threshold_uncertainty_score":0.6386922},"labels":[],"label_agreement":null},{"id":"W4323856839","doi":"10.3389/fnagi.2023.1065245","title":"White matter and gray matter changes related to cognition in community populations","year":2023,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Chinese Academy of Sciences","keywords":"Cognition; White matter; Neurocognitive; Fractional anisotropy; Psychology; Verbal fluency test; Effects of sleep deprivation on cognitive performance; Montreal Cognitive Assessment; Memory span; Diffusion MRI; Audiology; Population; Neuropsychology; Working memory; Cognitive test; Neuroscience; Medicine; Magnetic resonance imaging; Cognitive impairment","score_opus":0.0700859625679672,"score_gpt":0.3546782653068439,"score_spread":0.2845923027388767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323856839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96505284,0.00001305314,0.007795946,0.02553044,0.00023825883,0.0004877559,0.000010681375,0.00019233911,0.0006786699],"genre_scores_gemma":[0.9849275,0.000029138877,0.008030079,0.006132608,0.000005644281,0.00007796937,0.000014366026,0.000015658856,0.00076707423],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992381,0.000058303503,0.00014164687,0.00024369257,0.00010292661,0.00021536903],"domain_scores_gemma":[0.9996229,0.000019249494,0.000031942098,0.0002486415,0.000013758493,0.00006355004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020110191,0.000084021245,0.00012248321,0.00048320316,0.00013915646,0.000023534154,0.00010756245,0.000025530815,0.00000590416],"category_scores_gemma":[0.00004645122,0.000086665226,0.000011654648,0.00120241,0.00010462406,0.00009870669,0.00010542721,0.00030723136,0.000018628421],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003880565,0.000026685419,0.98791593,0.000016897151,1.9564416e-7,0.000010673762,0.00038345685,0.00006653148,0.0028595128,0.000022120767,0.008208165,0.00048593746],"study_design_scores_gemma":[0.00016753147,0.000025432484,0.99301374,0.00010672158,0.0000041090393,0.00002185887,0.0001231595,0.002260379,0.00018853584,0.0030338075,0.00097273424,0.00008197614],"about_ca_topic_score_codex":0.000026293917,"about_ca_topic_score_gemma":0.000015974862,"teacher_disagreement_score":0.019874606,"about_ca_system_score_codex":0.000028811743,"about_ca_system_score_gemma":0.0000065076288,"threshold_uncertainty_score":0.35341054},"labels":[],"label_agreement":null},{"id":"W4323863580","doi":"10.1093/braincomms/fcad061","title":"Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Western University; Sunnybrook Health Science Centre; Toronto Western Hospital; Université Laval","funders":"NIHR Cambridge Biomedical Research Centre; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; UK Dementia Research Institute; Ministero della Salute; Brain Research UK; Deutsche Forschungsgemeinschaft; Wolfson Foundation; Wellcome Trust; Alzheimer's Society; Agence Nationale de la Recherche; University College London; National Institute for Health and Care Research; EU Joint Programme – Neurodegenerative Disease Research; Nvidia","keywords":"Frontotemporal dementia; Grey matter; White matter; Diffusion MRI; C9orf72; Dementia; Medicine; Psychology; Oncology; Internal medicine; Pathology; Disease; Magnetic resonance imaging; Radiology","score_opus":0.1365431826319456,"score_gpt":0.42514686797683204,"score_spread":0.28860368534488645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323863580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94750434,0.0028638276,0.006913596,0.03710404,0.00014128553,0.0038700963,0.00017294096,0.0007684135,0.00066145643],"genre_scores_gemma":[0.8961465,0.0009110291,0.09972647,0.0013175582,0.00010208267,0.0009392593,0.0007342868,0.00005588342,0.00006695032],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99708885,0.00053708977,0.0010340735,0.0005369503,0.00039722098,0.00040582218],"domain_scores_gemma":[0.9956723,0.001187664,0.00031058775,0.0025607739,0.00010910952,0.00015956198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005836522,0.00027063637,0.00041259977,0.00012968785,0.00050072523,0.00006560471,0.0011659418,0.00015243019,0.00007386993],"category_scores_gemma":[0.00043569668,0.00021859068,0.00015462536,0.00060165353,0.0004957672,0.00015471107,0.0008924992,0.0006860284,0.000057023848],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024527684,0.00013751085,0.97493124,0.000013850931,0.0001782991,0.000009802064,0.00046683106,0.00004517349,0.00007424929,0.0001577087,0.019632924,0.0043278704],"study_design_scores_gemma":[0.0010705204,0.00010781481,0.94738215,0.00022489128,0.00025575256,0.00001089911,0.00014522295,0.03955566,0.00001564851,0.004709062,0.0063296366,0.00019275799],"about_ca_topic_score_codex":0.00024871595,"about_ca_topic_score_gemma":0.00033536303,"teacher_disagreement_score":0.09281287,"about_ca_system_score_codex":0.00008034834,"about_ca_system_score_gemma":0.00017461994,"threshold_uncertainty_score":0.8913869},"labels":[],"label_agreement":null},{"id":"W4324355161","doi":"10.1101/2023.03.14.532658","title":"In search of a unifying theory of white matter aging: improving the understanding of tract-wise degeneration using multi-parametric signatures of morphometry and microstructure","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Degeneration (medical); Parametric statistics; Human Connectome Project; Thermal diffusivity; Psychology; Biology; Neuroscience; Pathology; Medicine; Magnetic resonance imaging; Mathematics; Physics; Statistics; Functional connectivity; Radiology","score_opus":0.09189810883467651,"score_gpt":0.31844812878931894,"score_spread":0.2265500199546424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324355161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92644876,0.00089821144,0.07156291,0.00011023182,0.00006627431,0.0007519479,0.00012376465,0.00003728273,5.9821394e-7],"genre_scores_gemma":[0.95077044,0.00014288834,0.048924513,0.000041557145,0.00003004725,0.000018704093,4.5286632e-7,0.000069650865,0.0000017635033],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983031,0.00011677183,0.00065954914,0.00043825607,0.00026378973,0.00021849723],"domain_scores_gemma":[0.9980518,0.00023493139,0.0006906467,0.00068484707,0.00028332556,0.000054455366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075640756,0.00024650228,0.0005802007,0.00094719836,0.0000737813,0.000015524667,0.00022244685,0.0002443585,0.000005310166],"category_scores_gemma":[0.00019623266,0.00021498757,0.00009893377,0.0013131988,0.00030021797,0.00008001185,0.00036820475,0.00068375433,1.03154555e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034843968,0.000075943884,0.09460142,0.0017074276,0.0000355519,0.0000053165154,0.00007730461,0.0009745939,0.9020245,0.00045795404,0.0000034719499,0.0000016377596],"study_design_scores_gemma":[0.0004374839,0.000032539978,0.21373406,0.000950073,0.00013958475,1.4576655e-7,0.000075087744,0.0050476487,0.77937037,0.000042916567,0.0000019518334,0.00016814172],"about_ca_topic_score_codex":0.000079162906,"about_ca_topic_score_gemma":0.0000010504912,"teacher_disagreement_score":0.12265416,"about_ca_system_score_codex":0.00014733759,"about_ca_system_score_gemma":0.00022716665,"threshold_uncertainty_score":0.87669384},"labels":[],"label_agreement":null},{"id":"W4324378556","doi":"10.1117/12.2649029","title":"Exploring the Allen mouse connectivity experiments with new neuroinformatic tools for neurophotonics, diffusion MRI and tractography applications","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Université de Bordeaux; Agence Nationale de la Recherche","keywords":"Python (programming language); Computer science; Visualization; Software; Diffusion MRI; Tractography; Brain atlas; Artificial intelligence; Atlas (anatomy); Data visualization; Computer graphics (images); Programming language; Biology","score_opus":0.30295458175807344,"score_gpt":0.3719235383472306,"score_spread":0.06896895658915714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4324378556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34345955,0.000085670974,0.63568586,0.007543012,0.00008311604,0.011015958,0.000092133574,0.0014865728,0.0005481473],"genre_scores_gemma":[0.75379413,0.010991239,0.18488929,0.0034525765,0.00043443628,0.04148962,0.0006033438,0.0005120302,0.0038333177],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99862397,0.000015263982,0.00032854988,0.0005724534,0.000205243,0.00025452083],"domain_scores_gemma":[0.9980686,0.00041188928,0.00019240999,0.0010841881,0.000076023665,0.0001668983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000097976925,0.00030951848,0.00035950134,0.0001334957,0.00024995615,0.00013820462,0.00023988727,0.00006215617,0.0000036294375],"category_scores_gemma":[0.000052234936,0.0002064161,0.00013315737,0.0001549505,0.00009855756,0.0002166117,0.0003935823,0.00051809684,0.0000046283876],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054193586,0.007340127,0.019265914,0.014075021,0.0026747677,0.000091944996,0.020209119,0.0068444605,0.24512647,0.06826071,0.058317162,0.55237496],"study_design_scores_gemma":[0.014189753,0.0039681825,0.112370625,0.0022547115,0.0028233055,0.0005776573,0.0045909625,0.08016652,0.1529096,0.037283298,0.5835354,0.005329998],"about_ca_topic_score_codex":0.000066620974,"about_ca_topic_score_gemma":0.0000125970555,"teacher_disagreement_score":0.54704493,"about_ca_system_score_codex":0.000026198251,"about_ca_system_score_gemma":0.00007886672,"threshold_uncertainty_score":0.8417404},"labels":[],"label_agreement":null},{"id":"W4353016846","doi":"10.1002/hbm.26238","title":"Sex differences, asymmetry, and age‐related white matter development in infants and 5‐year‐olds as assessed with <scp>tract‐based</scp> spatial statistics","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Suomen Lääketieteen Säätiö; Suomen Kulttuurirahasto; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Juho Vainion Säätiö; Suomalainen Lääkäriseura Duodecim; Suomen Aivosäätiö; Alfred Kordelinin Säätiö; National Alliance for Research on Schizophrenia and Depression","keywords":"Fractional anisotropy; Corpus callosum; White matter; Diffusion MRI; Lateralization of brain function; Psychology; Gestational age; Developmental psychology; Cognition; Brain asymmetry; Audiology; Physiology; Medicine; Neuroscience; Pregnancy; Biology; Magnetic resonance imaging","score_opus":0.050480306237762694,"score_gpt":0.32137547676796113,"score_spread":0.27089517053019846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4353016846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95719135,0.00001181146,0.03955158,0.0009958079,0.00001278521,0.0004876896,0.000013658513,0.00022157532,0.0015137194],"genre_scores_gemma":[0.9709922,0.00001057064,0.026102394,0.00091736804,0.000020609466,0.00006869974,0.0001431465,0.00003699094,0.0017080101],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884737,0.000036457765,0.00027404667,0.00036746258,0.00019487062,0.00027980722],"domain_scores_gemma":[0.99931073,0.0002570389,0.00009736142,0.00019668174,0.00003292291,0.000105261664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019516093,0.00017831894,0.00026199032,0.0002872921,0.00016795895,0.00006128861,0.000065902655,0.00006894988,0.000028939246],"category_scores_gemma":[0.000082438884,0.00016355586,0.0000106522475,0.00033220573,0.0001171798,0.00005615091,0.00007557808,0.00028128413,0.00001733954],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000641189,0.00007899691,0.9847647,0.00018692676,0.000022387923,0.00026525956,0.0012579919,0.000008491656,0.005900913,0.00076028355,0.0041183354,0.0026293227],"study_design_scores_gemma":[0.0009589398,0.000074421434,0.99173474,0.00028732902,0.000012344723,0.000031147498,0.00016303515,0.00090254983,0.00015076272,0.0019686555,0.0036152115,0.0001008312],"about_ca_topic_score_codex":0.000042903728,"about_ca_topic_score_gemma":0.000037740203,"teacher_disagreement_score":0.013800836,"about_ca_system_score_codex":0.000033637054,"about_ca_system_score_gemma":0.000054708835,"threshold_uncertainty_score":0.66696143},"labels":[],"label_agreement":null},{"id":"W4360604116","doi":"10.1016/j.mri.2023.03.014","title":"Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Voxel; Diffusion MRI; Orientation (vector space); Computer science; SIGNAL (programming language); Preprocessor; Weighting; Algorithm; Artificial intelligence; Mathematics; Physics; Magnetic resonance imaging; Geometry","score_opus":0.02409103062778193,"score_gpt":0.2986922381842282,"score_spread":0.27460120755644624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360604116","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9426898,0.0020162226,0.04939241,0.0021063606,0.00046199872,0.0018110444,0.000045532084,0.0005828673,0.0008938103],"genre_scores_gemma":[0.9639682,0.00022601728,0.03438729,0.00014072862,0.0001016224,0.00044791488,0.000050747032,0.000051819814,0.00062562904],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99868727,0.00002050851,0.0004154611,0.00037394764,0.00017950182,0.0003232978],"domain_scores_gemma":[0.9993264,0.00012582666,0.0001171455,0.0002533563,0.00012576101,0.000051509174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020433681,0.00014914972,0.00025136422,0.0003615733,0.00010268412,0.000016399803,0.00008100651,0.00002383271,0.000019140609],"category_scores_gemma":[0.000070598006,0.00014860583,0.000083848645,0.00067264354,0.00015942765,0.000044186258,0.000052809566,0.00015671483,0.0000030031526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001578929,0.00015323007,0.053449355,0.0001364479,0.0000014693611,0.000017315979,0.00020854674,0.0003927548,0.03224054,0.00031992552,0.0006166806,0.91230583],"study_design_scores_gemma":[0.0010992397,0.000061918865,0.043865807,0.0004377003,0.000019620047,0.000109275585,0.00029243753,0.941715,0.0062633934,0.0012272531,0.0047642593,0.00014410823],"about_ca_topic_score_codex":0.000051402945,"about_ca_topic_score_gemma":0.0000024079802,"teacher_disagreement_score":0.9413222,"about_ca_system_score_codex":0.00007545765,"about_ca_system_score_gemma":0.000038003356,"threshold_uncertainty_score":0.60599697},"labels":[],"label_agreement":null},{"id":"W4360839182","doi":"10.1016/j.nicl.2023.103385","title":"Alzheimer’s and vascular disease classification using regional texture biomarkers in FLAIR MRI","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Health Sciences Centre; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Canada Research Chairs; St. Michael's Hospital","funders":"Alzheimer Society; Alzheimer's Society; Government of Ontario; Consortium canadien en neurodégénérescence associée au vieillissement; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Fluid-attenuated inversion recovery; White matter; Medicine; Biomarker; Vascular dementia; Dementia; Diffusion MRI; Hyperintensity; Disease; Pathology; Imaging biomarker; Magnetic resonance imaging; Radiology; Internal medicine; Oncology; Biology","score_opus":0.39486666729096026,"score_gpt":0.48821036076686747,"score_spread":0.09334369347590721,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4360839182","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9581846,0.0006299755,0.0061594066,0.032305554,0.00016659051,0.0013416762,0.000026233953,0.0008685722,0.00031736796],"genre_scores_gemma":[0.98461026,0.0017804282,0.009960521,0.003123541,0.00022667565,0.000066462686,0.00010077851,0.00006606634,0.000065288026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99840933,0.00010033087,0.00044083057,0.0006278506,0.00019884108,0.00022281757],"domain_scores_gemma":[0.9987965,0.00025432426,0.00009266131,0.0005597596,0.00004939594,0.0002473222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035643473,0.00014297661,0.00023978428,0.00015784605,0.0000801645,0.00001852245,0.000099566474,0.00008613204,0.000009743127],"category_scores_gemma":[0.0003630694,0.00013653375,0.00013273276,0.00052670314,0.00027186662,0.00009318328,0.00009192289,0.00038581993,0.00002578254],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005886213,0.0009624472,0.8890875,0.0001453631,0.00018909674,0.0008928365,0.00006238856,0.00007379914,0.019412618,0.002173773,0.03855766,0.047853902],"study_design_scores_gemma":[0.0007802196,0.000056547582,0.92531776,0.00006350052,0.00015437926,0.000026319149,0.000015399173,0.046040017,0.000020040608,0.0010101475,0.026382975,0.00013267141],"about_ca_topic_score_codex":0.000005117229,"about_ca_topic_score_gemma":9.708447e-7,"teacher_disagreement_score":0.047721233,"about_ca_system_score_codex":0.000016880871,"about_ca_system_score_gemma":0.000078543824,"threshold_uncertainty_score":0.5567685},"labels":[],"label_agreement":null},{"id":"W4361007742","doi":"10.1002/uog.26208","title":"Diffusion tensor imaging of fetal spinal cord: feasibility and gestational‐age‐related changes","year":2023,"lang":"en","type":"article","venue":"Ultrasound in Obstetrics and Gynecology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Diffusion MRI; Effective diffusion coefficient; Spinal cord; Nuclear medicine; White matter; Magnetic resonance imaging; Gestational age; Fractional anisotropy; Sagittal plane; Radiology; Pregnancy","score_opus":0.06200324316163612,"score_gpt":0.3519602656798965,"score_spread":0.2899570225182604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361007742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9971032,0.0008511267,0.00014547873,0.0011417699,0.000091935704,0.00034576282,0.00002052306,0.00007502835,0.00022517289],"genre_scores_gemma":[0.9928649,0.0048461165,0.0018715116,0.00017436419,0.000008277952,0.000024273784,0.000051742692,0.000011858619,0.0001469578],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99922395,0.000025974054,0.00021424818,0.000271944,0.000089646484,0.00017426629],"domain_scores_gemma":[0.9949343,0.004712377,0.00007921489,0.00015065791,0.000063983935,0.00005942675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014948433,0.000091239766,0.00021616856,0.00026035224,0.00006310232,0.0000075891767,0.000041761454,0.000061007166,0.000016670661],"category_scores_gemma":[0.006726736,0.00008781942,0.000021166228,0.0005972663,0.00021897485,0.00003394992,0.00005324403,0.00016184323,0.0000019800823],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059865393,0.000188227,0.86373144,0.00011676993,0.000009052697,0.00009190127,0.00013143457,0.0000031359175,0.01604155,0.003674648,0.00013261694,0.11581934],"study_design_scores_gemma":[0.0008643442,0.00036620107,0.98400444,0.000026172042,0.000020902398,0.00010412301,0.0001595791,0.00060209254,0.00017903594,0.008593507,0.004989824,0.00008977611],"about_ca_topic_score_codex":0.000016526928,"about_ca_topic_score_gemma":0.000009671528,"teacher_disagreement_score":0.12027299,"about_ca_system_score_codex":0.000041696836,"about_ca_system_score_gemma":0.000018566763,"threshold_uncertainty_score":0.8053017},"labels":[],"label_agreement":null},{"id":"W4361264359","doi":"10.1016/j.neuroimage.2023.120069","title":"White matter microstructure is associated with the precision of visual working memory","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Health and Medical Research Council; University of Queensland","keywords":"Working memory; Fasciculus; White matter; Inferior longitudinal fasciculus; Diffusion MRI; Superior longitudinal fasciculus; Psychology; Computer science; Neuroscience; Artificial intelligence; Tractography; Cognition; Medicine; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.038105556396323445,"score_gpt":0.33059862579653004,"score_spread":0.2924930694002066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4361264359","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98518467,0.000017910757,0.0008004372,0.010513371,0.000045155746,0.00048544738,0.000020988125,0.00030160692,0.002630399],"genre_scores_gemma":[0.99266183,0.000014803063,0.00068847416,0.0034624294,0.000040275852,0.000022445487,0.000023561535,0.000043563443,0.003042598],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99919,0.000028930783,0.00014548407,0.00024890612,0.00020963547,0.00017709998],"domain_scores_gemma":[0.99931157,0.000104538085,0.00011014328,0.0003747917,0.000062641375,0.000036325688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008747766,0.00011464218,0.00016594862,0.00007042054,0.00009316465,0.000016029317,0.00012406439,0.000039232422,0.000088889545],"category_scores_gemma":[0.0000320194,0.00007190912,0.00005620363,0.00057215744,0.000105279876,0.00003819655,0.00008259459,0.0002571272,0.00003642354],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002590224,0.00018662262,0.22620898,0.0000770747,0.000057086214,0.00018660746,0.00096446753,0.000049190254,0.43378878,0.00003797788,0.3299474,0.008236777],"study_design_scores_gemma":[0.00061341986,0.00018225354,0.9515996,0.00016231487,0.000076356046,0.000080422054,0.0000624803,0.0005733211,0.034988858,0.00019717145,0.011324752,0.00013904326],"about_ca_topic_score_codex":0.0000016442369,"about_ca_topic_score_gemma":7.561634e-7,"teacher_disagreement_score":0.7253906,"about_ca_system_score_codex":0.000012114268,"about_ca_system_score_gemma":0.000016206659,"threshold_uncertainty_score":0.29323688},"labels":[],"label_agreement":null},{"id":"W4362506763","doi":"10.7554/elife.83727","title":"Spatiotemporal tissue maturation of thalamocortical pathways in the human fetal brain","year":2023,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Centre For Medical Engineering, King’s College London; NIHR Sheffield Biomedical Research Centre; European Research Council; Engineering and Physical Sciences Research Council; Menzies Centre for Australian Studies, King's College London, University of London; Medical Research Council Canada; Medical Research Council Centre for Neurodevelopmental Disorders; European Commission; National Institute for Health and Care Research; King's College London; King's College Hospital NHS Foundation Trust; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Subplate; Neuroscience; Thalamus; White matter; Biology; Human brain; Tractography; Cortex (anatomy); Cerebral cortex; Biological neural network; Connectome; Diffusion MRI; Anatomy; Magnetic resonance imaging; Medicine; Functional connectivity","score_opus":0.11742736846466226,"score_gpt":0.40423544583298354,"score_spread":0.28680807736832126,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362506763","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98417205,0.00001130672,0.002091602,0.011570202,0.000016083173,0.00042243782,0.0000067339042,0.00015200807,0.0015575568],"genre_scores_gemma":[0.9975942,0.0000072618172,0.0014269246,0.0006527407,0.000066948945,0.000049250277,0.00006684255,0.000008892783,0.00012694437],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994534,0.000022144472,0.00016529135,0.00010399002,0.0001652635,0.000089866284],"domain_scores_gemma":[0.99965465,0.000053461074,0.000039621707,0.00021196583,0.000019911227,0.000020414209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001565635,0.000049070848,0.00008976158,0.000054259763,0.00003602164,0.0000048237866,0.000066843226,0.000027279593,0.000012460796],"category_scores_gemma":[0.00007053589,0.000035230536,0.000023632185,0.00027212792,0.000042034135,0.000030539144,0.000021499167,0.00011620868,0.000019846644],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000053770316,0.0004207369,0.05286847,0.00012238862,0.000011021527,0.00014792781,0.0016634901,0.000029140152,0.764026,0.117283136,0.04357631,0.019797612],"study_design_scores_gemma":[0.00054539205,0.0002138223,0.8806083,0.00006416987,0.000014354164,0.000036910584,0.00020716852,0.0013805537,0.09179893,0.0068676486,0.018154094,0.000108621425],"about_ca_topic_score_codex":0.000015644338,"about_ca_topic_score_gemma":0.0000054467046,"teacher_disagreement_score":0.82773983,"about_ca_system_score_codex":0.000008960137,"about_ca_system_score_gemma":0.00001465275,"threshold_uncertainty_score":0.14366595},"labels":[],"label_agreement":null},{"id":"W4362603986","doi":"10.1117/12.2653884","title":"Mapping the impact of approximate gradient nonlinearity fields correction on tractography","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health","keywords":"Tractography; Diffusion MRI; Connectomics; Nonlinear system; Population; Voxel; Computer science; Statistical physics; Connectome; Artificial intelligence; Physics; Functional connectivity","score_opus":0.1186722705274807,"score_gpt":0.3889556291316619,"score_spread":0.2702833586041812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362603986","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9467386,0.000006948165,0.042448543,0.002433548,0.00008389841,0.0005161725,0.000008494496,0.0005117218,0.007252044],"genre_scores_gemma":[0.9982053,0.00005655937,0.0011904297,0.00014719364,0.000033574728,0.00003217106,0.000016255675,0.000007890563,0.00031062125],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99958026,0.000008692581,0.000114150855,0.00011321527,0.00008079472,0.0001028888],"domain_scores_gemma":[0.99957407,0.0000706355,0.000043786258,0.000249587,0.00003185713,0.000030053237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008710924,0.000061509934,0.00009417635,0.00010768562,0.00005781324,0.0000042081792,0.000049407852,0.000026514377,0.000020197198],"category_scores_gemma":[0.000027638165,0.00003482317,0.00013087127,0.00057115976,0.000035961883,0.000017607796,0.000015973776,0.00015736569,0.000006138458],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067715236,0.0033616545,0.24574701,0.00030086905,0.00041462036,0.000044642788,0.0029628817,0.0069456873,0.09995825,0.012491619,0.2720238,0.3550718],"study_design_scores_gemma":[0.000660646,0.001042266,0.7875374,0.00013775837,0.00003675413,0.00006800634,0.00044202877,0.1724795,0.02606537,0.0064959438,0.0048286174,0.00020572053],"about_ca_topic_score_codex":0.000093837036,"about_ca_topic_score_gemma":0.0000014802597,"teacher_disagreement_score":0.54179037,"about_ca_system_score_codex":0.000012787007,"about_ca_system_score_gemma":0.000010548771,"threshold_uncertainty_score":0.14200476},"labels":[],"label_agreement":null},{"id":"W4362604797","doi":"10.1117/12.2654398","title":"Deep constrained spherical deconvolution for robust harmonization","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Computer science; Deconvolution; Artificial intelligence; Diffusion MRI; Regularization (linguistics); Scanner; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Algorithm","score_opus":0.11887214630771932,"score_gpt":0.36715950605732395,"score_spread":0.24828735974960464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362604797","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027140318,0.000007573083,0.98877716,0.005203921,0.000024409877,0.0005036895,0.0000031491697,0.0009040543,0.0018619985],"genre_scores_gemma":[0.2963819,0.000048225334,0.698704,0.0012509477,0.00010024806,0.0002694143,0.00022342098,0.000027903256,0.0029939243],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995791,0.0000032688174,0.00010415406,0.00014477322,0.00005123161,0.00011752981],"domain_scores_gemma":[0.99969745,0.000045224868,0.000022707869,0.000120086435,0.000066050474,0.000048512546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004319138,0.00005095872,0.00007738005,0.00003231767,0.000061440725,0.0000060395387,0.000027771855,0.00002878302,0.00006909885],"category_scores_gemma":[0.00007507102,0.000045978006,0.000036764108,0.00025855834,0.000035438417,0.000033143762,0.000012272307,0.000039127357,0.0000397686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035222326,0.00059753493,0.022612777,0.0003415069,0.000087972665,0.000033921788,0.00018067323,0.007988709,0.18283807,0.2249733,0.2781471,0.2818462],"study_design_scores_gemma":[0.0011608879,0.0001690114,0.009245051,0.000019815941,0.000051066854,0.000044410583,0.00008645794,0.9212138,0.011194228,0.008571795,0.048084766,0.00015869187],"about_ca_topic_score_codex":0.0000016730423,"about_ca_topic_score_gemma":8.9607755e-7,"teacher_disagreement_score":0.9132251,"about_ca_system_score_codex":0.000022121378,"about_ca_system_score_gemma":0.000018840261,"threshold_uncertainty_score":0.18749286},"labels":[],"label_agreement":null},{"id":"W4362663285","doi":"10.1101/2023.04.03.535465","title":"Implementation considerations for deep learning with diffusion MRI streamline tractography","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Vanderbilt University; National Science Foundation","keywords":"Tractography; Diffusion MRI; Deep learning; Computer science; Artificial intelligence; Diffusion; Data science; Magnetic resonance imaging; Medicine; Radiology; Physics","score_opus":0.051166974466269,"score_gpt":0.32417606579841096,"score_spread":0.27300909133214196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362663285","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5259289,0.00021235329,0.4610734,0.0040466296,0.000241287,0.005016806,0.0004628835,0.0030114406,0.000006303798],"genre_scores_gemma":[0.831411,0.0003604301,0.16589665,0.00024033416,0.00022946425,0.0016664257,0.0000096124695,0.00017855108,0.000007551569],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9979958,0.000040708088,0.00046129242,0.0008520581,0.0002646707,0.0003854709],"domain_scores_gemma":[0.9979123,0.00020868529,0.00038856507,0.0007567125,0.0005413851,0.0001923822],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021934677,0.00039489218,0.0004472812,0.0003512754,0.00034889445,0.00010671591,0.00011878874,0.00020672612,0.000029361661],"category_scores_gemma":[0.00013658263,0.0003827291,0.00016138151,0.0004142969,0.00008943439,0.00009107163,0.00013145478,0.00067702297,0.000008231435],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024188787,0.0007530598,0.14369008,0.0013611953,0.000512353,0.00011711882,0.000055209817,0.0009610758,0.8436705,0.0064530456,0.0020936362,0.00009084381],"study_design_scores_gemma":[0.0061077843,0.0013518736,0.59153384,0.001566108,0.0019395419,5.757104e-7,0.00009004252,0.011210069,0.35464072,0.00038814868,0.028811833,0.0023594685],"about_ca_topic_score_codex":0.00003703048,"about_ca_topic_score_gemma":0.000014467997,"teacher_disagreement_score":0.48902977,"about_ca_system_score_codex":0.00010906054,"about_ca_system_score_gemma":0.00023525006,"threshold_uncertainty_score":0.9998625},"labels":[],"label_agreement":null},{"id":"W4362696909","doi":"10.1016/j.mri.2023.03.023","title":"Neural network algorithms predict new diffusion MRI data for multi-compartmental analysis of brain microstructure in a clinical setting","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of British Columbia; Hotchkiss Brain Institute; Ontario Brain Institute; St. Michael's Hospital; University of Calgary","funders":"National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Multiple Sclerosis Society of Canada; McDonnell Center for Systems Neuroscience; NIH Blueprint for Neuroscience Research; University of Calgary; Biogen Idec; Biogen; Government of Alberta; Fondation Brain Canada; Roche","keywords":"Human Connectome Project; Diffusion MRI; Convolutional neural network; Computer science; Diffusion imaging; Pattern recognition (psychology); Artificial intelligence; Artificial neural network; Magnetic resonance imaging; Medicine; Neuroscience; Functional connectivity; Radiology; Psychology","score_opus":0.09936934055020735,"score_gpt":0.42619241693129273,"score_spread":0.3268230763810854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362696909","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80434155,0.009187501,0.15487532,0.024341997,0.00043308464,0.004456027,0.0014009539,0.00089045,0.00007309224],"genre_scores_gemma":[0.2821377,0.0006752957,0.7077322,0.003412597,0.00076185993,0.00018784104,0.0033561392,0.000127641,0.0016087547],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979523,0.000052171235,0.0007135365,0.0006820175,0.00018648036,0.0004134931],"domain_scores_gemma":[0.99840736,0.00033581557,0.00018198279,0.0009232349,0.000042246687,0.00010933605],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004994856,0.00017773785,0.00051310426,0.00022130627,0.000081280006,0.00002170298,0.0003577334,0.00004626861,0.000016449627],"category_scores_gemma":[0.00024788172,0.0001677056,0.00016021592,0.0014565291,0.00012467167,0.000092949456,0.00035648549,0.00025928562,0.0000013951116],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009233244,0.00009589395,0.62977636,0.000037863334,0.000022071941,0.00002934596,0.000080122896,0.00072583713,0.0019946562,0.000018266252,0.035722174,0.33140507],"study_design_scores_gemma":[0.0010503781,0.00004273569,0.4465526,0.00006364796,0.00012610258,0.000008277647,0.00002494597,0.53163385,0.000023382107,0.00012388016,0.02027189,0.000078312805],"about_ca_topic_score_codex":0.000053714917,"about_ca_topic_score_gemma":0.000022104528,"teacher_disagreement_score":0.55285686,"about_ca_system_score_codex":0.0000272368,"about_ca_system_score_gemma":0.000053057433,"threshold_uncertainty_score":0.6838836},"labels":[],"label_agreement":null},{"id":"W4362704266","doi":"10.1038/s41598-023-33055-9","title":"Three-round learning strategy based on 3D deep convolutional GANs for Alzheimer’s disease staging","year":2023,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; National Natural Science Foundation of China; Eisai; Genentech; IXICO; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Overfitting; Artificial intelligence; Computer science; Interpretability; Deep learning; Convolutional neural network; Machine learning; Task (project management); Discriminator; Transfer of learning; Feature (linguistics); Generative model; Generative adversarial network; Generative grammar; Pattern recognition (psychology); Artificial neural network","score_opus":0.12479615419464202,"score_gpt":0.3798533453630848,"score_spread":0.2550571911684428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362704266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18711254,0.00028912493,0.7926448,0.0064151785,0.0027852482,0.0041417754,0.000057490906,0.003189877,0.0033639593],"genre_scores_gemma":[0.98976487,0.000002501852,0.0073365737,0.00017223983,0.00009955254,0.00028723184,0.00066736655,0.000036394034,0.0016332722],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832106,0.000011016358,0.0002826387,0.000677921,0.00039545016,0.0003119453],"domain_scores_gemma":[0.99880475,0.000093189956,0.00014919874,0.00059381564,0.00016381693,0.00019525841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055544043,0.0001236767,0.00013753741,0.00019529708,0.00053625053,0.00009479267,0.00006444782,0.000027594882,0.00006152804],"category_scores_gemma":[0.00019571165,0.00011625557,0.000102345424,0.0005107014,0.0001781198,0.00007610165,0.00002938333,0.00015115872,0.00002431438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008053173,0.0017704311,0.3551225,0.0006422959,0.00020957593,0.0051557627,0.00027649736,0.25001,0.056443967,0.022229945,0.20515126,0.10218243],"study_design_scores_gemma":[0.0006107897,0.00018474653,0.04684537,0.00017684775,0.0002230869,0.00006423052,0.000059235495,0.7193232,0.0026870738,0.05343035,0.17600207,0.00039299513],"about_ca_topic_score_codex":0.0000047785175,"about_ca_topic_score_gemma":0.000002620195,"teacher_disagreement_score":0.80265236,"about_ca_system_score_codex":0.00004434813,"about_ca_system_score_gemma":0.0002442022,"threshold_uncertainty_score":0.47407645},"labels":[],"label_agreement":null},{"id":"W4363645571","doi":"10.1002/mrm.29666","title":"Single‐shot spiral diffusion‐weighted imaging at 7T using expanded encoding with compressed sensing","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Regularization (linguistics); Computer science; Diffusion MRI; Encoding (memory); Image resolution; Compressed sensing; Spiral (railway); Algorithm; Image quality; Iterative reconstruction; Wavelet; Conjugate gradient method; Artificial intelligence; Computer vision; Pattern recognition (psychology); Mathematics; Magnetic resonance imaging; Image (mathematics); Mathematical analysis","score_opus":0.10138470792243831,"score_gpt":0.3523189457130428,"score_spread":0.2509342377906045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4363645571","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98507714,0.0018352888,0.0036028917,0.0043984284,0.000098662014,0.0008357132,0.000004149025,0.0005715587,0.0035761436],"genre_scores_gemma":[0.9758206,0.00033636796,0.021299757,0.0012046313,0.00024039668,0.00003227152,0.000041826068,0.000083339546,0.0009407913],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99774474,0.00005023588,0.0005050803,0.00061259815,0.0005167212,0.0005706514],"domain_scores_gemma":[0.9988101,0.00020326622,0.00013627857,0.0005889536,0.00010173243,0.00015966315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023040317,0.00029667214,0.0005435763,0.0003918753,0.00019971238,0.000015397667,0.00014696288,0.000057745274,0.00011415801],"category_scores_gemma":[0.00012362373,0.00023099377,0.00004433074,0.0013231456,0.00040468643,0.00007747865,0.00014946962,0.00033935477,0.000010573208],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003890192,0.00011730607,0.082020566,0.00012288705,0.0000046530186,0.0013863473,0.0007159355,0.000057107827,0.8386327,0.00008464731,0.0015329779,0.074935846],"study_design_scores_gemma":[0.020460103,0.0020273232,0.30020222,0.011733105,0.00035311785,0.0034293232,0.0016570549,0.48427317,0.056684263,0.0023389817,0.1151823,0.0016590331],"about_ca_topic_score_codex":0.00013344534,"about_ca_topic_score_gemma":0.00002132809,"teacher_disagreement_score":0.78194845,"about_ca_system_score_codex":0.00019847123,"about_ca_system_score_gemma":0.00003872144,"threshold_uncertainty_score":0.9419652},"labels":[],"label_agreement":null},{"id":"W4363676591","doi":"10.1016/j.biopsych.2023.02.360","title":"120. Glymphatic Clearance Function in Schizophrenia Subtypes According to Treatment Response","year":2023,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Glymphatic system; Schizophrenia (object-oriented programming); Neurodegeneration; Neuroscience; Neuroimaging; Medicine; Pathology; Psychology; Cerebrospinal fluid; Psychiatry","score_opus":0.11014765128766592,"score_gpt":0.38029847410212214,"score_spread":0.27015082281445624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4363676591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9890405,0.00014156575,0.0010114511,0.008425726,0.00017622925,0.00047087122,0.0000056173294,0.0005393393,0.0001887218],"genre_scores_gemma":[0.9899836,0.00011891073,0.008223444,0.0011388704,0.00013278115,0.00016984485,0.0000149807265,0.000013724341,0.00020381407],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991519,0.000049743972,0.00018167867,0.00033874167,0.000065660635,0.00021228431],"domain_scores_gemma":[0.9995201,0.000083801315,0.000032953412,0.00026112556,0.000014371674,0.00008764494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014197656,0.00011800598,0.00017878787,0.00013839408,0.000065635,0.000008088428,0.000068178684,0.00007095752,0.0000179165],"category_scores_gemma":[0.00009699296,0.00008445559,0.00006329631,0.0006686638,0.000029989282,0.000025398123,0.000032875963,0.00007838294,0.00027097977],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.024101008,0.0006833247,0.8404231,0.000034696586,0.000027576241,0.000038947885,0.000050894352,0.000110690475,0.05128747,0.0070495806,0.0028928732,0.073299855],"study_design_scores_gemma":[0.0009457941,0.001242929,0.9795181,0.00006707822,0.000010814059,0.000012368986,0.00007317369,0.00013031834,0.00023728,0.00526835,0.012375692,0.00011807198],"about_ca_topic_score_codex":0.000007559951,"about_ca_topic_score_gemma":0.0000035896608,"teacher_disagreement_score":0.13909505,"about_ca_system_score_codex":0.00007307999,"about_ca_system_score_gemma":0.000040198018,"threshold_uncertainty_score":0.3482987},"labels":[],"label_agreement":null},{"id":"W4365142548","doi":"10.1101/2023.04.10.23288366","title":"Cortical microstructural associations with CSF amyloid and pTau","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Amyloid (mycology); Neuroscience; Pathology; Psychology; Medicine","score_opus":0.08353576868100436,"score_gpt":0.36181041664311303,"score_spread":0.27827464796210866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4365142548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98559225,0.000068958456,0.004638167,0.007811223,0.000095234565,0.0006237868,0.00013172581,0.0006854913,0.0003531373],"genre_scores_gemma":[0.9726553,0.00015955794,0.02501553,0.00046331857,0.00013920444,0.00014544887,0.00019426657,0.00006376693,0.0011636353],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99895376,0.00002134534,0.00020898679,0.00043867299,0.00017409264,0.00020314199],"domain_scores_gemma":[0.9991141,0.00009038829,0.00011503206,0.00045910428,0.00010051249,0.0001208869],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008821977,0.00018260705,0.00030499118,0.000074811636,0.00011412763,0.000035776433,0.000098819095,0.00012610071,0.00001223069],"category_scores_gemma":[0.00013929549,0.00014599487,0.000056111712,0.00013230367,0.00014468144,0.000023530913,0.0002587286,0.0007695449,0.000015948874],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058966714,0.00008986045,0.9625589,0.00023404828,0.00013874764,0.00012896102,0.00021535825,0.000019374344,0.028809816,0.0026142355,0.0034592552,0.0016724503],"study_design_scores_gemma":[0.00032770028,0.000067307985,0.9874659,0.00014786374,0.00017669765,0.00008884935,0.000017785007,0.00033990457,0.0022726436,0.005426885,0.003458116,0.00021030776],"about_ca_topic_score_codex":0.000024649325,"about_ca_topic_score_gemma":0.000009206202,"teacher_disagreement_score":0.026537172,"about_ca_system_score_codex":0.000051842115,"about_ca_system_score_gemma":0.00007186799,"threshold_uncertainty_score":0.5953498},"labels":[],"label_agreement":null},{"id":"W4366083018","doi":"10.1002/hbm.26310","title":"High‐frequency longitudinal white matter diffusion‐ and myelin‐based <scp>MRI</scp> database: Reliability and variability","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Intraclass correlation; Consistency (knowledge bases); White matter; Reliability (semiconductor); Diffusion MRI; Diffusion; Fiber; Nuclear magnetic resonance; Fiber tract; Effective diffusion coefficient; Data consistency; Psychology; Computer science; Magnetic resonance imaging; Chemistry; Statistics; Physics; Medicine; Mathematics; Database; Artificial intelligence; Radiology; Reproducibility","score_opus":0.061417180567841935,"score_gpt":0.32881093711402615,"score_spread":0.2673937565461842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366083018","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9212519,0.000031792555,0.06084979,0.015405359,0.000040436676,0.00081546407,0.00007614609,0.0006820668,0.0008470574],"genre_scores_gemma":[0.9564836,0.000030032663,0.039620608,0.0022761289,0.00013689697,0.00015184649,0.00028394492,0.000046329,0.0009706038],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981915,0.00009231803,0.0003655505,0.0007954308,0.00020651837,0.00034868988],"domain_scores_gemma":[0.99823254,0.0005343512,0.00010601473,0.0008682005,0.00008254477,0.00017634053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007911953,0.00022397625,0.00031445816,0.00016685153,0.0004268684,0.000047895828,0.00011724328,0.000079000936,0.000086448694],"category_scores_gemma":[0.00047891724,0.00021355231,0.000052363393,0.0003877951,0.0003481818,0.0001338888,0.00023956064,0.0003501258,0.00002874841],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006470822,0.00011142452,0.8525174,0.0006398746,0.000012922304,0.000039973285,0.00022190323,0.000013542215,0.11411466,0.0041611227,0.027825657,0.00033503442],"study_design_scores_gemma":[0.0005943832,0.000041087787,0.9696817,0.00017320253,0.000030375015,0.000025463427,0.000055537275,0.0010390927,0.00013941592,0.021378879,0.0067371507,0.000103727354],"about_ca_topic_score_codex":0.000037429676,"about_ca_topic_score_gemma":0.0000038316175,"teacher_disagreement_score":0.11716427,"about_ca_system_score_codex":0.000048537364,"about_ca_system_score_gemma":0.000028251467,"threshold_uncertainty_score":0.870841},"labels":[],"label_agreement":null},{"id":"W4366738674","doi":"10.5281/zenodo.7853832","title":"What matters in reinforcement learning for tractography - Datasets","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Tractography; Reinforcement; Computer science; Artificial intelligence; Psychology; Social psychology; Diffusion MRI; Medicine","score_opus":0.09395881842475623,"score_gpt":0.34581672891885146,"score_spread":0.2518579104940952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366738674","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21589002,0.0005490794,0.481895,0.17911121,0.0009694965,0.022522295,0.0018350857,0.031484265,0.065743536],"genre_scores_gemma":[0.95817757,0.0014332935,0.0026578845,0.002261171,0.0001469073,0.0000021086853,0.031191178,0.002089953,0.0020399273],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990417,0.000045521843,0.00018747541,0.00028779203,0.00016973008,0.00026783062],"domain_scores_gemma":[0.9994087,0.000028904024,0.000056878405,0.0003103062,0.00010263708,0.00009256312],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003368372,0.00008732471,0.00010902014,0.0003436856,0.00062837196,0.00023382214,0.0002616491,0.000029037481,0.000703038],"category_scores_gemma":[0.0001770475,0.00009313244,0.000037960293,0.0007419657,0.00006262193,0.00026764438,0.00029263482,0.00020769893,0.00083636015],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022281188,0.00019033738,0.00004732048,0.00026941753,0.000037231563,0.000040905565,0.0009136801,0.001841493,0.032724578,0.0034622513,0.7918182,0.16843176],"study_design_scores_gemma":[0.00053864584,0.00020499348,0.0009408305,0.00007558415,0.000009833465,0.000035331384,0.00029463155,0.0024514585,0.0008084472,0.00023673495,0.994312,0.00009151129],"about_ca_topic_score_codex":0.0000036593926,"about_ca_topic_score_gemma":7.382999e-8,"teacher_disagreement_score":0.7422876,"about_ca_system_score_codex":0.00005427141,"about_ca_system_score_gemma":0.0000017393257,"threshold_uncertainty_score":0.9999416},"labels":[],"label_agreement":null},{"id":"W4366752941","doi":"10.1016/j.neuroimage.2023.120129","title":"Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"H2020 European Research Council; UCLH Biomedical Research Centre; Engineering and Physical Sciences Research Council; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; H2020 Marie Skłodowska-Curie Actions; University of California, San Diego; Genentech; National Institutes of Health; Horizon 2020; UK Dementia Research Institute; National Institute of Neurological Disorders and Stroke; IXICO; HORIZON EUROPE Framework Programme; Servier; Eisai; Wolfson Foundation; Eli Lilly and Company; Brain Research UK; National Institute on Aging; National Institute for Health and Care Research; European Research Council; Northern California Institute for Research and Education; Alzheimer’s Research UK; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Alzheimer's Society; University College London; University of Southern California; Wellcome Trust; Synarc; Medpace; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; European Commission; Alzheimer's Disease Neuroimaging Initiative; Medical Research Council; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Diffusion MRI; Neuroimaging; Segmentation; White matter; Artificial intelligence; Thalamus; Computer science; Bayesian probability; Probabilistic logic; Magnetic resonance imaging; Pattern recognition (psychology); Brain atlas; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.08031163095989832,"score_gpt":0.3801650050487406,"score_spread":0.2998533740888423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366752941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97540563,0.0000120809345,0.022940546,0.00066521746,0.00003208683,0.00040187675,0.000012318499,0.00032249707,0.00020772411],"genre_scores_gemma":[0.98004067,0.00012084015,0.019399138,0.0002270285,0.000033617136,0.000014104461,0.000037348895,0.000027743537,0.00009950846],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992088,0.000032951895,0.00019449706,0.00030822057,0.00010218337,0.00015336215],"domain_scores_gemma":[0.9994642,0.000040599818,0.000104137536,0.00027930748,0.000035892866,0.00007582854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000062756124,0.00010867429,0.0001718408,0.00009534373,0.00008748564,0.000011964296,0.00006464645,0.000042013125,0.000014695266],"category_scores_gemma":[0.000037835656,0.00009602987,0.000035884394,0.00024167255,0.000099708464,0.00012140969,0.000077055956,0.00013460939,0.0000031522027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035610443,0.00006659078,0.0038370641,0.000034383702,0.0000021697213,0.000028335515,0.000054076623,0.000011949629,0.9924757,0.00013459258,0.00012042381,0.0031990984],"study_design_scores_gemma":[0.002147148,0.0010708818,0.35177922,0.000095876065,0.00017147945,0.00031777364,0.0001885372,0.5225892,0.11656674,0.0028932386,0.0017800266,0.00039988998],"about_ca_topic_score_codex":0.000016311213,"about_ca_topic_score_gemma":9.233096e-7,"teacher_disagreement_score":0.875909,"about_ca_system_score_codex":0.000020369562,"about_ca_system_score_gemma":0.00001472096,"threshold_uncertainty_score":0.39159846},"labels":[],"label_agreement":null},{"id":"W4366827617","doi":"10.1038/s41380-023-02068-1","title":"Characterization of the extracellular free water signal in schizophrenia using multi-site diffusion MRI harmonization","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"National Health and Medical Research Council; National Institute of Mental Health; Medical Research Council; Brain and Behavior Research Foundation; National Alliance for Research on Schizophrenia and Depression; National Institutes of Health; National Science Foundation; U.S. Department of Health and Human Services; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Brigham and Women's Hospital","keywords":"Schizophrenia (object-oriented programming); Harmonization; Extracellular; Neuroscience; Diffusion MRI; Nuclear magnetic resonance; Characterization (materials science); Psychology; Magnetic resonance imaging; Medicine; Biology; Psychiatry; Biochemistry; Nanotechnology; Materials science; Physics; Radiology","score_opus":0.030776632982658692,"score_gpt":0.29431359015335473,"score_spread":0.26353695717069603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366827617","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80400527,0.000041349806,0.1933758,0.001954443,0.00009662188,0.00041364905,0.000011078419,0.000093055074,0.000008726367],"genre_scores_gemma":[0.97460854,0.00002604709,0.024810648,0.00022462476,0.000039072238,0.00002312412,0.00013344415,0.000038283357,0.00009621193],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999146,0.000038945476,0.0002516465,0.00022973136,0.00017361931,0.00016008965],"domain_scores_gemma":[0.99935615,0.0000037020334,0.000082617866,0.00048043716,0.000044097997,0.000033001008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008676551,0.00010885902,0.00012957717,0.00014174829,0.0000725913,0.000008936587,0.00013452888,0.00005524197,0.000014765763],"category_scores_gemma":[0.00001028819,0.00007854905,0.00007500413,0.0005218389,0.000038921076,0.000049712024,0.000115216346,0.00015555965,0.000007809468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000340162,0.000103019,0.021219922,0.00004070988,0.000004072663,0.000005895699,0.00005703395,0.00018706873,0.97780275,0.00031107178,0.000012516969,0.000221907],"study_design_scores_gemma":[0.0017268753,0.000034921188,0.15573515,0.0002656619,0.000056791814,0.000023967174,0.000016087139,0.051954225,0.78781104,0.0017873504,0.00041952293,0.00016844033],"about_ca_topic_score_codex":0.000010576093,"about_ca_topic_score_gemma":0.000002887499,"teacher_disagreement_score":0.18999176,"about_ca_system_score_codex":0.000021547856,"about_ca_system_score_gemma":0.000030901036,"threshold_uncertainty_score":0.32031375},"labels":[],"label_agreement":null},{"id":"W4367053067","doi":"10.1002/hbm.26311","title":"Direct localization and delineation of human pedunculopontine nucleus based on a self‐supervised magnetic resonance image super‐resolution method","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Atlas (anatomy); Brain atlas; Magnetic resonance imaging; Image resolution; Artificial intelligence; Pedunculopontine nucleus; Computer science; Nuclear magnetic resonance; Neuroscience; Human brain; Pattern recognition (psychology); Computer vision; Physics; Deep brain stimulation; Parkinson's disease; Anatomy; Biology; Pathology; Medicine; Radiology","score_opus":0.061177494505413925,"score_gpt":0.35817446245265144,"score_spread":0.2969969679472375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367053067","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21211274,0.00016934864,0.7795977,0.0033117442,0.000024858724,0.0012957988,0.000028010652,0.0014220452,0.0020377862],"genre_scores_gemma":[0.84427726,0.000060470753,0.15257375,0.0013776016,0.00013799594,0.00016173394,0.00037694574,0.0000855765,0.00094865146],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987099,0.00010632836,0.0003529548,0.0003959996,0.00022403333,0.00021078766],"domain_scores_gemma":[0.9991769,0.00015045993,0.00009490438,0.00037005075,0.0001427837,0.00006487484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046938783,0.00016053948,0.0002538854,0.00031933305,0.00030304727,0.000019552177,0.000077604374,0.00006228735,0.000030737403],"category_scores_gemma":[0.00018434077,0.00016774211,0.00005950869,0.0006174076,0.00007267463,0.000076101715,0.00004501878,0.00012855876,0.0000047975072],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004210255,0.00018648995,0.0030492232,0.00034980717,0.0000073149777,0.000014486998,0.00056752196,0.0003765715,0.97595817,0.003394804,0.0049127406,0.011140758],"study_design_scores_gemma":[0.0021702205,0.000592108,0.119922616,0.0006757025,0.00007011602,0.000012248551,0.00014655346,0.8333121,0.0077464804,0.0011101714,0.033913374,0.0003283394],"about_ca_topic_score_codex":0.00003727016,"about_ca_topic_score_gemma":0.0000055416062,"teacher_disagreement_score":0.9682117,"about_ca_system_score_codex":0.000049802205,"about_ca_system_score_gemma":0.000020527223,"threshold_uncertainty_score":0.68403244},"labels":[],"label_agreement":null},{"id":"W4367296532","doi":"10.1212/wnl.0000000000202734","title":"White Matter and Gray Matter Changes Related to Cognition in Community populations (P12-6.008)","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Neurocognitive; White matter; Cognition; Effects of sleep deprivation on cognitive performance; Fractional anisotropy; Psychology; Verbal fluency test; Diffusion MRI; Memory span; Population; Audiology; Cognitive test; Neuropsychology; Medicine; Neuroscience; Magnetic resonance imaging; Working memory; Cognitive impairment; Radiology","score_opus":0.0840708708878097,"score_gpt":0.367682698456357,"score_spread":0.2836118275685473,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367296532","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89979005,0.000004766309,0.00016242193,0.09803967,0.000038826274,0.00035358532,0.0000123704685,0.00019037777,0.0014079281],"genre_scores_gemma":[0.9751087,0.000017537492,0.0005247079,0.023713212,0.000012974979,0.00013138553,0.00009338594,0.000022451914,0.00037567934],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938893,0.000098358,0.00013022331,0.00017008127,0.000046224784,0.00016617047],"domain_scores_gemma":[0.99958026,0.000057555702,0.000029164783,0.00025771192,0.000021364527,0.00005396153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093502196,0.00008008935,0.00013132393,0.00023386486,0.000088406574,0.000005569006,0.000051008323,0.000066482746,0.00011384843],"category_scores_gemma":[0.00001795276,0.000080348196,0.0000141304745,0.00033949662,0.00005057332,0.000027634847,0.00008822736,0.0003839774,0.00032881522],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006442957,0.000062311316,0.98414606,0.000023525101,0.0000029091752,0.000028439943,0.0002939209,0.000016333599,0.0035945347,0.00024401257,0.010972021,0.0005515086],"study_design_scores_gemma":[0.00027430945,0.00019715482,0.98898774,0.000013008413,0.000013297766,0.000114289636,0.000009197631,0.0001237557,0.00008805039,0.006074494,0.0040444504,0.0000602636],"about_ca_topic_score_codex":0.000048317073,"about_ca_topic_score_gemma":0.00011369718,"teacher_disagreement_score":0.07531861,"about_ca_system_score_codex":0.000005338533,"about_ca_system_score_gemma":0.00000319111,"threshold_uncertainty_score":0.4226364},"labels":[],"label_agreement":null},{"id":"W4367320574","doi":"10.3174/ajnr.a7855","title":"Associating<i>IDH</i>and<i>TERT</i>Mutations in Glioma with Diffusion Anisotropy in Normal-Appearing White Matter","year":2023,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Türkiye Bilimsel ve Teknolojik Araştırma Kurumu","keywords":"Fractional anisotropy; White matter; Medicine; Diffusion MRI; Bonferroni correction; Glioma; Nuclear medicine; Internal medicine; Mann–Whitney U test; Pathology; Gastroenterology; Magnetic resonance imaging; Radiology","score_opus":0.02101469649579027,"score_gpt":0.30984541082314465,"score_spread":0.2888307143273544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367320574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9907925,0.000011476114,0.0010958471,0.007800937,0.000023416665,0.00011929901,0.0000029497146,0.000034839777,0.000118737335],"genre_scores_gemma":[0.99185735,0.00010642656,0.006635088,0.0012955763,0.000038062743,0.00001159627,0.000003849111,0.000023611396,0.00002841373],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990498,0.00008780696,0.00035738063,0.00017011353,0.00010095989,0.00023394021],"domain_scores_gemma":[0.9992965,0.00014409542,0.00030807333,0.00012989932,0.000045302953,0.00007612025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014067754,0.000105173414,0.00036731292,0.00044930313,0.00003744621,0.000008076082,0.000086269654,0.000023950557,0.0000052217765],"category_scores_gemma":[0.000051111096,0.00008673582,0.000036300462,0.0008508207,0.00017067086,0.00007899991,0.00004429539,0.00037890254,0.0000041349213],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009678892,0.000043763783,0.98284596,0.000007132983,0.0000063761154,0.00051817024,0.00024735162,0.00017146076,0.014268139,0.000040772615,0.00018102331,0.0015730747],"study_design_scores_gemma":[0.0008251574,0.0009132962,0.9939748,0.0000719772,0.000017248967,0.0026462085,0.00014892223,0.0004887709,0.00011927886,0.00027204482,0.00044137615,0.00008092417],"about_ca_topic_score_codex":0.000025790714,"about_ca_topic_score_gemma":0.000008580435,"teacher_disagreement_score":0.014148861,"about_ca_system_score_codex":0.00004358704,"about_ca_system_score_gemma":0.0000348444,"threshold_uncertainty_score":0.3536984},"labels":[],"label_agreement":null},{"id":"W4368339382","doi":"10.1016/j.bandl.2023.105270","title":"White matter correlates of reading subskills in children with and without reading disability","year":2023,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Brock University; SickKids Foundation; Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Ontario; Canada First Research Excellence Fund; Nvidia","keywords":"Fractional anisotropy; Psychology; Reading (process); White matter; Diffusion MRI; Uncinate fasciculus; Fasciculus; Reading disability; Reading comprehension; Superior longitudinal fasciculus; Arcuate fasciculus; Dyslexia; Developmental psychology; Linguistics; Magnetic resonance imaging; Medicine","score_opus":0.014394871813121029,"score_gpt":0.314149667571959,"score_spread":0.29975479575883796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368339382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99787635,0.000041408326,0.00012457818,0.001147822,0.0000022766305,0.00023874735,0.000008568358,0.00007355903,0.00048670574],"genre_scores_gemma":[0.9978133,0.000023936016,0.0013889378,0.00022867222,0.000010289601,0.000013901697,0.000021367176,0.000012164341,0.0004874251],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996002,0.000011219603,0.000091205395,0.00015738579,0.00004505798,0.00009494212],"domain_scores_gemma":[0.9997409,0.000046322355,0.000028847282,0.00014336234,0.0000058444525,0.00003473369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000096594296,0.00006119475,0.00012800348,0.00004421578,0.000021519863,0.0000052606197,0.000021390257,0.000022046816,0.000013470473],"category_scores_gemma":[0.000027031092,0.000046230245,0.00000951774,0.00016057496,0.00010304997,0.000032824682,0.000027393773,0.000081387625,0.0000017249397],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014175436,0.00001552711,0.99644524,0.000027066286,0.000004367491,0.0000025601366,0.0006761186,7.353396e-7,0.0013693223,0.00012917034,0.0001564554,0.0011592677],"study_design_scores_gemma":[0.00033797094,0.000031786545,0.9983633,0.00011502157,0.000010510769,0.00006775757,0.0002564982,0.00011905888,0.0004938846,0.0001237581,0.000027771017,0.000052666255],"about_ca_topic_score_codex":0.000048921076,"about_ca_topic_score_gemma":0.0000081361895,"teacher_disagreement_score":0.0019180818,"about_ca_system_score_codex":0.0000063869675,"about_ca_system_score_gemma":0.0000031063382,"threshold_uncertainty_score":0.18852147},"labels":[],"label_agreement":null},{"id":"W4368362973","doi":"10.1016/j.jad.2023.04.136","title":"The relationship of white matter microstructure with psychomotor disturbance and relapse in remitted psychotic depression","year":2023,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University Health Network; University of Toronto","funders":"U.S. Public Health Service; National Institute of Mental Health; University of Toronto; Pfizer","keywords":"Psychology; Psychomotor learning; White matter; Psychomotor disorder; Fractional anisotropy; Psychiatry; Psychosis; Medicine; Cognition; Magnetic resonance imaging","score_opus":0.016400556689521555,"score_gpt":0.31944355355226056,"score_spread":0.303042996862739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368362973","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928667,0.0002978186,0.0019024183,0.004388186,0.00003602104,0.0003096271,0.0000026254393,0.000013668109,0.00018295382],"genre_scores_gemma":[0.99824536,0.00026811985,0.001239619,0.0000881,0.00001397791,0.000011417411,0.0000015925326,0.000014721316,0.00011707678],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994469,0.000038276405,0.00019354557,0.000109384055,0.000116400945,0.000095479685],"domain_scores_gemma":[0.9992624,0.00025908873,0.00021866216,0.00015763342,0.00006740023,0.000034812725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013769059,0.000076790464,0.00014164437,0.00011088231,0.00009949232,0.0000060383263,0.00006099192,0.000034028013,0.0000021565104],"category_scores_gemma":[0.00011722169,0.00004485287,0.00003656678,0.00045572774,0.00011714344,0.00006752746,0.00001586624,0.00030816766,6.303167e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003329907,0.00003184088,0.9940645,0.000025708485,0.000010649363,0.0000033418453,0.0002511902,0.000027573598,0.0017219876,0.000055869725,0.0016832046,0.0017911239],"study_design_scores_gemma":[0.0010029277,0.00015131445,0.9920585,0.00027012965,0.00002224565,0.000071995644,0.00014602189,0.00003625986,0.00015245452,0.005552085,0.0004905999,0.000045459765],"about_ca_topic_score_codex":0.0000032728897,"about_ca_topic_score_gemma":0.000017932,"teacher_disagreement_score":0.0054962155,"about_ca_system_score_codex":0.000019241257,"about_ca_system_score_gemma":0.000016308315,"threshold_uncertainty_score":0.18290469},"labels":[],"label_agreement":null},{"id":"W4368372507","doi":"10.21203/rs.3.rs-2874508/v1","title":"Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; European Commission","keywords":"White matter; Tractography; Grey matter; Cognition; Computer science; Functional organization; Diffusion MRI; Voxel; Artificial intelligence; Prior probability; Pattern recognition (psychology); Neuroscience; Psychology; Magnetic resonance imaging; Bayesian probability","score_opus":0.1250502369518265,"score_gpt":0.44807553347470047,"score_spread":0.323025296522874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4368372507","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33047065,0.00021353338,0.29063162,0.3549123,0.00045674416,0.01364248,0.004812232,0.0014035149,0.0034569271],"genre_scores_gemma":[0.97980076,0.00004862879,0.0015598219,0.0004072591,0.00038196563,0.0024890867,0.0014186077,0.00007904536,0.01381484],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9979304,0.00014673796,0.00034931028,0.00048207634,0.0007033415,0.00038810557],"domain_scores_gemma":[0.99696183,0.0007936066,0.00015799754,0.00070862373,0.0012544504,0.00012347507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072637363,0.00016823596,0.00027315237,0.00025116917,0.0006211868,0.000047091922,0.00019157417,0.00017308834,0.0003812649],"category_scores_gemma":[0.0010948088,0.00012868355,0.00015261745,0.00074893935,0.00012681767,0.000054848733,0.0007964467,0.0013213214,0.00012566973],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004068956,0.0006039197,0.034769036,0.001301549,0.00028088014,0.000003726271,0.00056569465,0.0008098965,0.17183156,0.0014209251,0.785651,0.002354875],"study_design_scores_gemma":[0.0016311541,0.0007503849,0.7660171,0.003029198,0.0002095946,0.000017817722,0.001570249,0.0039783013,0.057595044,0.017116077,0.14728396,0.00080111617],"about_ca_topic_score_codex":0.00011408426,"about_ca_topic_score_gemma":0.0000046359714,"teacher_disagreement_score":0.7312481,"about_ca_system_score_codex":0.00036521372,"about_ca_system_score_gemma":0.00022004588,"threshold_uncertainty_score":0.57405573},"labels":[],"label_agreement":null},{"id":"W4372218972","doi":"10.1016/j.neuroimage.2023.120159","title":"High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Sharpening; Image resolution; Diffusion MRI; Signal-to-noise ratio (imaging); Resolution (logic); Physics; Image quality; Nuclear magnetic resonance; Optics; Computer science; Magnetic resonance imaging; Artificial intelligence; Image (mathematics)","score_opus":0.052073682086251974,"score_gpt":0.32530789748682415,"score_spread":0.2732342154005722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372218972","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9814572,0.00009570501,0.011377258,0.004649858,0.00008861937,0.0010096264,0.00013658634,0.00085125305,0.00033389367],"genre_scores_gemma":[0.9969627,0.00017190148,0.0011980949,0.0008242883,0.00020425692,0.00007563857,0.00017516156,0.00007243335,0.00031547775],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982559,0.000078316836,0.00031284802,0.0007008601,0.00023824541,0.0004138222],"domain_scores_gemma":[0.99860436,0.00042875612,0.00012832494,0.0005010021,0.0000935821,0.0002439505],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013890314,0.0003454799,0.0003457531,0.00029852267,0.0004096235,0.0000813134,0.000095205716,0.000061821374,0.000034676013],"category_scores_gemma":[0.00026839247,0.0002640796,0.00007961398,0.00053128897,0.00016790307,0.00020250361,0.00020450995,0.00028878194,0.000024535966],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005620794,0.00013259068,0.005312029,0.00003580398,0.000009573206,0.00006332163,0.00025655454,0.00005747406,0.9732512,0.00015312794,0.00589027,0.01427598],"study_design_scores_gemma":[0.003256267,0.0018920562,0.70808464,0.00036290556,0.00014331269,0.00041012486,0.00010840595,0.07208452,0.2011999,0.0019680085,0.009632634,0.0008572251],"about_ca_topic_score_codex":0.00014632885,"about_ca_topic_score_gemma":0.000008294444,"teacher_disagreement_score":0.7720513,"about_ca_system_score_codex":0.00012831016,"about_ca_system_score_gemma":0.00003223957,"threshold_uncertainty_score":0.99998116},"labels":[],"label_agreement":null},{"id":"W4372403590","doi":"10.1101/2023.05.05.539590","title":"Predicting Parkinson’s disease progression using MRI-based white matter radiomic biomarker and machine learning: a reproducibility and replicability study","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University","funders":"Michael J. Fox Foundation for Parkinson's Research","keywords":"Artificial intelligence; Replicate; Robustness (evolution); Neuroimaging; Machine learning; Magnetic resonance imaging; Biomarker; Cohort; Parkinson's disease; Imaging biomarker; Reproducibility; Population; Medicine; Computer science; Feature selection; Disease; Internal medicine; Statistics; Radiology; Mathematics; Biology","score_opus":0.07022890400720562,"score_gpt":0.32764046722167534,"score_spread":0.25741156321446973,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372403590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9877355,0.0006380523,0.0039080987,0.0019554798,0.00012510279,0.004078163,0.00015740047,0.0014012455,9.231907e-7],"genre_scores_gemma":[0.97735137,0.00009471297,0.02135132,0.00014733049,0.00013437563,0.00071830227,0.0000021477013,0.0001937219,0.0000067128985],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9944492,0.00031463735,0.0007329482,0.0036632398,0.0003831067,0.00045686512],"domain_scores_gemma":[0.9947498,0.00011511668,0.00051274407,0.003853264,0.0002720827,0.0004970236],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002194999,0.00057816156,0.00072079815,0.00027785517,0.0003681258,0.00014652425,0.00020539034,0.00021621234,0.000011882135],"category_scores_gemma":[0.001060823,0.00055797317,0.000117050964,0.0004826729,0.00029413786,0.00010281341,0.0008747352,0.0010664667,0.000003739382],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026376362,0.0005035421,0.962953,0.000940681,0.00005708967,0.00007421204,0.0000128622105,0.000050345327,0.03508976,0.0000017726611,0.00004211701,0.000010858554],"study_design_scores_gemma":[0.0008190485,0.00010746981,0.9565306,0.0007088072,0.00038315137,1.7659686e-7,0.0000038661315,0.037107043,0.0033111384,0.0000062535764,0.0005667808,0.00045569782],"about_ca_topic_score_codex":0.00007448497,"about_ca_topic_score_gemma":0.0000014226703,"teacher_disagreement_score":0.0370567,"about_ca_system_score_codex":0.00024108579,"about_ca_system_score_gemma":0.00029108865,"threshold_uncertainty_score":0.9996872},"labels":[],"label_agreement":null},{"id":"W4376122082","doi":"10.1002/hbm.26322","title":"Feasibility of diffusion‐tensor and correlated diffusion imaging for studying white‐matter microstructural abnormalities: Application in <scp>COVID</scp>‐19","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Waterloo; Toronto Metropolitan University; University of Toronto; St. Michael's Hospital; Baycrest Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"White matter; Diffusion MRI; Magnetic resonance imaging; Fractional anisotropy; Diffusion; Tractography; Coronavirus disease 2019 (COVID-19); Diffusion imaging; Nuclear magnetic resonance; Medicine; Nuclear medicine; Pathology; Radiology; Physics","score_opus":0.07821745750001177,"score_gpt":0.3565695099885581,"score_spread":0.27835205248854633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376122082","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9740766,0.000050425562,0.02228049,0.0012686726,0.000025666184,0.0018363249,0.000029616636,0.00029191634,0.00014027761],"genre_scores_gemma":[0.99464846,0.000013802274,0.0031699557,0.0010962309,0.000043086773,0.0002512479,0.00014707605,0.000039032526,0.00059110054],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984944,0.0000451293,0.00049402023,0.0004982853,0.00014534361,0.00032283267],"domain_scores_gemma":[0.9987061,0.00048871466,0.00020812424,0.0004083716,0.000090141104,0.00009856935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039542577,0.00018750087,0.00032507084,0.0003036233,0.00031734907,0.000026412854,0.00012103491,0.00006200705,0.000008521577],"category_scores_gemma":[0.00027642606,0.00018534521,0.0000722366,0.0004467946,0.00014809158,0.00010614702,0.00016947603,0.00020952274,0.0000035288708],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000103772745,0.000042284824,0.7597956,0.00032573895,0.0000044925096,0.000002902143,0.002440402,0.000014507391,0.2349867,0.00026869756,0.0017776109,0.00033066716],"study_design_scores_gemma":[0.0014994836,0.000029103017,0.98061085,0.00018762813,0.00001812116,0.000031291802,0.0027028138,0.0075277984,0.00009420234,0.0052305525,0.001976404,0.00009173069],"about_ca_topic_score_codex":0.000052186744,"about_ca_topic_score_gemma":0.0000085224865,"teacher_disagreement_score":0.2348925,"about_ca_system_score_codex":0.00009514589,"about_ca_system_score_gemma":0.000022365186,"threshold_uncertainty_score":0.7558158},"labels":[],"label_agreement":null},{"id":"W4376224771","doi":"10.1093/cercor/bhad130","title":"Face recognition ability can be predicted by microstructural properties of white matter: a study of diffusion tensor imaging (DTI)","year":2023,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; Hamilton Health Sciences","funders":"Natural Science Foundation of Zhejiang Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Fractional anisotropy; Corpus callosum; Inferior longitudinal fasciculus; Diffusion MRI; White matter; Lateralization of brain function; Psychology; Arcuate fasciculus; Fasciculus; Correlation; Tractography; Audiology; Neuroscience; Medicine; Mathematics; Magnetic resonance imaging; Geometry","score_opus":0.051613508482347005,"score_gpt":0.30152868559539225,"score_spread":0.24991517711304526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376224771","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99649245,0.000016703076,0.00009196989,0.0015005253,0.000032179567,0.0011792327,0.0003959058,0.00024389042,0.00004714305],"genre_scores_gemma":[0.99886775,0.0000100545685,0.00034622537,0.00017588871,0.000016012458,0.000070340306,0.00024164804,0.00002628867,0.00024578616],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99892074,0.000035421956,0.0003653793,0.00031205852,0.00018753092,0.00017888614],"domain_scores_gemma":[0.9992232,0.000015077348,0.00016554366,0.00036986778,0.00016593268,0.00006040518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059491787,0.00013787345,0.00027513527,0.00008711021,0.000098057084,0.000006253258,0.00010029629,0.00003098083,0.00005258569],"category_scores_gemma":[0.000040611714,0.00011094686,0.000054857243,0.00033202273,0.00013269403,0.00006465008,0.00013156388,0.0001475266,0.0000020090508],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009057629,0.00019934836,0.5445261,0.00013292892,0.000010983983,0.0000018427413,0.001000706,0.0000012259359,0.45065027,4.8518064e-7,0.0018272256,0.00155834],"study_design_scores_gemma":[0.0011079101,0.00027006536,0.94190454,0.00013724713,0.000080622296,0.000023111637,0.0016968645,0.0008676186,0.053533174,0.00014184167,0.00010710699,0.00012987676],"about_ca_topic_score_codex":0.00017957651,"about_ca_topic_score_gemma":0.0000101784,"teacher_disagreement_score":0.39737847,"about_ca_system_score_codex":0.000032191147,"about_ca_system_score_gemma":0.000022048873,"threshold_uncertainty_score":0.45242816},"labels":[],"label_agreement":null},{"id":"W4376270889","doi":"10.1101/2023.05.10.23289785","title":"Microscopic fractional anisotropy asymmetry in unilateral temporal lobe epilepsy","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fractional anisotropy; Temporal lobe; Diffusion MRI; Axon; Magnetic resonance imaging; Hippocampus; Subiculum; Anisotropy; Epilepsy; Neuroscience; Medicine; Psychology; Dentate gyrus; Radiology; Physics","score_opus":0.09615239241896996,"score_gpt":0.3864693774516486,"score_spread":0.29031698503267866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376270889","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96536845,0.00014033189,0.023477202,0.0077990424,0.00063098135,0.0009785868,0.0000927658,0.00087500765,0.00063762016],"genre_scores_gemma":[0.95538205,0.00025421163,0.039838035,0.0007695217,0.00034138383,0.0002738537,0.00044869212,0.00010501458,0.0025872437],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9982658,0.000041259984,0.00044783283,0.00068393827,0.0002487245,0.00031243096],"domain_scores_gemma":[0.99883807,0.00006555861,0.00016973187,0.00074079307,0.000068317924,0.00011753749],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00017206838,0.00027935088,0.0004471577,0.00031946562,0.000057637102,0.000028443133,0.00024210675,0.00025029105,0.00006757204],"category_scores_gemma":[0.000077193974,0.00027896793,0.00014399806,0.00033715888,0.000092040114,0.000045793025,0.00039950112,0.001274398,0.00013239459],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036436948,0.00016200046,0.9887462,0.00017021775,0.000019906316,0.00019212282,0.000025478368,0.0000739474,0.0064818086,0.00085430953,0.0029279399,0.0003095891],"study_design_scores_gemma":[0.00073369493,0.00008754467,0.93138427,0.0006012636,0.000052757572,0.00006791063,0.000015871163,0.0015634652,0.0048795366,0.024901805,0.035316773,0.0003951178],"about_ca_topic_score_codex":0.00014361579,"about_ca_topic_score_gemma":0.000013770073,"teacher_disagreement_score":0.057361986,"about_ca_system_score_codex":0.00016273916,"about_ca_system_score_gemma":0.00015766188,"threshold_uncertainty_score":0.99996626},"labels":[],"label_agreement":null},{"id":"W4376277450","doi":"10.1038/s41380-023-02031-0","title":"The organization of frontostriatal brain wiring in non-affective early psychosis compared with healthy subjects using a novel diffusion imaging fiber cluster analysis","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"U.S. Department of Veterans Affairs; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression; U.S. Department of Health and Human Services","keywords":"Tractography; Diffusion MRI; Neuroscience; Psychology; Psychosis; White matter; Connectome; Magnetic resonance imaging; Fiber; Schizophrenia (object-oriented programming); Human Connectome Project; Medicine; Chemistry; Psychiatry; Functional connectivity; Radiology","score_opus":0.015669458494087435,"score_gpt":0.3155367137008391,"score_spread":0.2998672552067516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376277450","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77626324,0.000043153275,0.21890481,0.004067281,0.000038721297,0.00054258347,0.000007753104,0.00008308576,0.000049361726],"genre_scores_gemma":[0.97859085,0.000009943004,0.020648362,0.00058119436,0.000026429687,0.000030508983,0.000049115886,0.00004576493,0.000017832359],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99886876,0.000050627645,0.00027822587,0.0003408208,0.00022263032,0.00023894904],"domain_scores_gemma":[0.9991569,0.00007496566,0.00017004792,0.00043776078,0.00009937218,0.000060942944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019650324,0.00014841084,0.00026292927,0.0003132591,0.0001479461,0.000022623253,0.00011221858,0.00003338864,0.0000050968247],"category_scores_gemma":[0.00004178358,0.00011705867,0.00008445208,0.0026108304,0.000058204012,0.00006161742,0.00006129274,0.00017866615,0.0000034356467],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003002645,0.0002863706,0.923833,0.00007789216,0.00019622644,0.000008384006,0.00041635425,0.0033126797,0.07018132,0.0001549922,0.00033696878,0.00089552236],"study_design_scores_gemma":[0.0036605266,0.00015120125,0.9168756,0.00033472243,0.0004757698,0.00003269119,0.0002832124,0.07389952,0.003657066,0.0002381742,0.00010744079,0.00028404847],"about_ca_topic_score_codex":0.00025194138,"about_ca_topic_score_gemma":0.00008675229,"teacher_disagreement_score":0.2023276,"about_ca_system_score_codex":0.000065916036,"about_ca_system_score_gemma":0.00005780967,"threshold_uncertainty_score":0.4773514},"labels":[],"label_agreement":null},{"id":"W4377014295","doi":"10.1212/wnl.0000000000207408","title":"Association of Cortical and Subcortical Microstructure With Clinical Progression and Fluid Biomarkers in Patients With Parkinson Disease","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Avid Radiopharmaceuticals; Sanofi Genzyme; Allergan; H. Lundbeck A/S; Higher Education Discipline Innovation Project; Servier; Genentech; National Natural Science Foundation of China; Voyager Therapeutics; Neurocrine Biosciences; Biogen; Celgene; Verily Life Sciences; Teva Pharmaceutical Industries; Sanofi; GlaxoSmithKline; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb","keywords":"Internal medicine; Biomarker; Medicine; Montreal Cognitive Assessment; Parkinson's disease; Putamen; Diffusion MRI; Neurology; Psychology; Disease; Oncology; Cardiology; Magnetic resonance imaging; Psychiatry; Radiology; Cognitive impairment; Biology","score_opus":0.01979690020336478,"score_gpt":0.3407179896663006,"score_spread":0.32092108946293585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377014295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99615914,0.0000146369775,0.000053483247,0.0033336312,0.0000128600705,0.00035714943,0.000008757829,0.000052593747,0.0000077802715],"genre_scores_gemma":[0.9987133,0.00006946639,0.00075500284,0.00039330666,0.00001031655,0.000019469844,0.000023885912,0.000011759855,0.0000034667435],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999282,0.000055477612,0.00017235636,0.00024833283,0.000106945,0.00013489682],"domain_scores_gemma":[0.99953234,0.0001403535,0.00006898804,0.00012004331,0.00003895899,0.000099309014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008285048,0.000069581416,0.00016700402,0.00005625536,0.000024121173,0.000002973913,0.000021833017,0.000066869,0.0000017172284],"category_scores_gemma":[0.00012857965,0.00004802119,0.00001122076,0.0001623849,0.00017897226,0.000021870092,0.000034972993,0.000192065,3.8948787e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030051947,0.00009132201,0.9942509,0.00001932735,0.000010556174,0.000032616455,0.0000060294155,4.7026984e-7,0.00032494866,0.000046741487,0.000112355556,0.0020995184],"study_design_scores_gemma":[0.0016075335,0.0014579576,0.9955723,0.000018289325,0.00004967588,0.000008037433,7.6777695e-7,0.0003412243,0.0000384884,0.00009788533,0.0007652235,0.00004256406],"about_ca_topic_score_codex":0.0000015875873,"about_ca_topic_score_gemma":0.000003045669,"teacher_disagreement_score":0.0029403246,"about_ca_system_score_codex":0.0000055219894,"about_ca_system_score_gemma":0.000019763607,"threshold_uncertainty_score":0.19582473},"labels":[],"label_agreement":null},{"id":"W4377014380","doi":"10.1101/2023.05.17.541182","title":"Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Vanderbilt University; University of Southern California; Vanderbilt Memory and Alzheimer's Center; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association; Vanderbilt University Medical Center; Foundation for the National Institutes of Health","keywords":"White matter; Diffusion MRI; Diffusion; Longitudinal data; Materials science; Psychology; Magnetic resonance imaging; Medicine; Computer science; Physics; Data mining; Radiology; Thermodynamics","score_opus":0.0937509714158721,"score_gpt":0.3236515467001635,"score_spread":0.2299005752842914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377014380","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98761153,0.00019184875,0.0049655815,0.005552873,0.00024875003,0.00091283757,0.00020790396,0.0003070275,0.0000016384672],"genre_scores_gemma":[0.96567124,0.00027840157,0.032922886,0.00069382007,0.00018660045,0.0001264086,0.000005998238,0.00010519905,0.000009421626],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99693924,0.00005795038,0.0006670737,0.00143944,0.00029477596,0.00060153625],"domain_scores_gemma":[0.99783045,0.00007240771,0.00021092182,0.0015531675,0.0001061822,0.00022685943],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00045154063,0.0004801681,0.00067577907,0.0006359964,0.00011102726,0.00016424162,0.00064337737,0.00021807848,0.000019875926],"category_scores_gemma":[0.000089237874,0.00048695464,0.000049723985,0.0006587052,0.000103340666,0.00021250594,0.0031926828,0.0010907921,0.00002334162],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045115146,0.000057109777,0.9187204,0.00028776785,0.0000123740865,0.00015253945,0.000023837132,0.000023260998,0.08048747,0.000017237875,0.0001674143,0.0000054731204],"study_design_scores_gemma":[0.0005793639,0.000025661058,0.98951465,0.0012095594,0.0000408359,4.718608e-7,0.0000066287134,0.0029833808,0.0048334855,0.000005805133,0.00032655543,0.00047360786],"about_ca_topic_score_codex":0.00029932987,"about_ca_topic_score_gemma":0.00005255764,"teacher_disagreement_score":0.075653985,"about_ca_system_score_codex":0.00014037268,"about_ca_system_score_gemma":0.0001345767,"threshold_uncertainty_score":0.9997582},"labels":[],"label_agreement":null},{"id":"W4377103901","doi":"10.1002/dad2.12425","title":"White matter microstructural metrics are sensitively associated with clinical staging in Alzheimer's disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Office of the Director; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; National Institute of General Medical Sciences; H. Lundbeck A/S; Servier; Eisai; Vanderbilt University Medical Center; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Vanderbilt University; University of Southern California; Vanderbilt Memory and Alzheimer's Center; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Neuroimaging; Diffusion MRI; Metric (unit); Magnetic resonance imaging; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Multivariate statistics; Medicine; Disease; Internal medicine; Psychology; Neuroscience; Statistics; Radiology; Mathematics","score_opus":0.11201449902615865,"score_gpt":0.41138578791807917,"score_spread":0.29937128889192055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377103901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.988179,0.0041708266,0.0003087779,0.004494297,0.00037653508,0.0015014866,0.00025965495,0.0006498662,0.000059527116],"genre_scores_gemma":[0.99303335,0.00081358396,0.0036770597,0.0006581596,0.00026149984,0.0010172953,0.00039398653,0.00013319534,0.000011897892],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99646276,0.00019680792,0.0007862153,0.0010257895,0.00073439884,0.0007940359],"domain_scores_gemma":[0.9973639,0.0005086522,0.00041261877,0.0007263491,0.0002268662,0.000761583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00042987574,0.0004788475,0.00058826804,0.0004919387,0.00027367088,0.000151211,0.00023952483,0.00007882941,0.00005764626],"category_scores_gemma":[0.00013219115,0.00045467023,0.00025702253,0.0015427489,0.00014369964,0.00036830196,0.00028828892,0.0005220684,0.00004361872],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000097214746,0.0005319174,0.9919011,0.000019131414,0.0015255536,0.0006924144,0.000025428733,0.00014313654,0.000030677325,0.00001827161,0.0021770538,0.0028381005],"study_design_scores_gemma":[0.0012514569,0.00005744609,0.98802346,0.00065713696,0.007683912,0.0000016860199,0.00012992369,0.0007973916,0.00040878277,0.00011000435,0.00040086254,0.00047792788],"about_ca_topic_score_codex":0.00003054085,"about_ca_topic_score_gemma":0.000004616502,"teacher_disagreement_score":0.0061583584,"about_ca_system_score_codex":0.00010172731,"about_ca_system_score_gemma":0.00021990521,"threshold_uncertainty_score":0.9997905},"labels":[],"label_agreement":null},{"id":"W4377197047","doi":"10.1016/j.biopsych.2023.05.014","title":"Prenatal and Postnatal Maternal Depressive Symptoms Are Associated With White Matter Integrity in 5-Year-Olds in a Sex-Specific Manner","year":2023,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Suomen Aivosäätiö; Emil Aaltosen Säätiö; Sigrid Juséliuksen Säätiö; Brain and Behavior Research Foundation; Signe ja Ane Gyllenbergin Säätiö; Päivikki ja Sakari Sohlbergin Säätiö; Alfred Kordelinin Säätiö; Varsinais-Suomen Sairaanhoitopiiri; Suomalainen Lääkäriseura Duodecim; Juho Vainion Säätiö; National Alliance for Research on Schizophrenia and Depression; Suomen Kulttuurirahasto; Suomen Lääketieteen Säätiö; Turun Yliopisto; Academy of Finland","keywords":"Edinburgh Postnatal Depression Scale; Offspring; Pregnancy; Anxiety; Child Behavior Checklist; Fractional anisotropy; Psychology; Medicine; White matter; Prenatal care; Obstetrics; Clinical psychology; Pediatrics; Psychiatry; Depressive symptoms","score_opus":0.04145281537157792,"score_gpt":0.30919734968013257,"score_spread":0.26774453430855466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377197047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99606067,0.00011282777,0.000073985975,0.0027809015,0.000051242783,0.00036066663,0.000073613424,0.00019565999,0.00029040923],"genre_scores_gemma":[0.9977894,0.00007110829,0.0010703716,0.00062165275,0.000052554235,0.00008718736,0.00008410638,0.000016842314,0.00020679357],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989779,0.00004209822,0.00020557229,0.0004119785,0.00009679921,0.0002656465],"domain_scores_gemma":[0.99960196,0.00003957339,0.00007419921,0.0001926263,0.000021338892,0.00007027931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000092789836,0.00015250003,0.000234171,0.00011948861,0.00003386278,0.000016192,0.00009778176,0.00015348241,0.000052645155],"category_scores_gemma":[0.000017915736,0.00010131867,0.000032457745,0.0003298927,0.000109629575,0.000046876772,0.000092845934,0.00046986123,0.000026939135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013024942,0.00011747973,0.99803525,0.00001780368,0.000007529006,0.00008993389,0.000020721727,0.0000019360148,0.00010239225,0.00025451236,0.001058353,0.0001638649],"study_design_scores_gemma":[0.00096748496,0.00013799906,0.9967495,0.00033374008,0.000004608225,0.000076768265,0.000071980954,0.00005780383,0.00006352446,0.0012660808,0.00013925883,0.00013120107],"about_ca_topic_score_codex":0.000013970219,"about_ca_topic_score_gemma":0.000025115158,"teacher_disagreement_score":0.0021592488,"about_ca_system_score_codex":0.000036178728,"about_ca_system_score_gemma":0.000012982028,"threshold_uncertainty_score":0.41316554},"labels":[],"label_agreement":null},{"id":"W4377694396","doi":"10.21203/rs.3.rs-2950610/v1","title":"Radiomic tractometry: a rich and tract-specific class of imaging biomarkers for neuroscience and medical applications","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; Allergan; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Neurocrine Biosciences; Novartis Pharmaceuticals Corporation; Voyager Therapeutics; Biogen; BioClinica; F. Hoffmann-La Roche; Celgene; Meso Scale Diagnostics; Teva Pharmaceutical Industries; Verily Life Sciences; Northern California Institute for Research and Education; University of Southern California; Deutsche Forschungsgemeinschaft; GlaxoSmithKline; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Association; Michael J. Fox Foundation for Parkinson's Research; Foundation for the National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative","keywords":"Python (programming language); Computer science; Diffusion MRI; Neuroimaging; Data science; Neuroscience; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.210662261618314,"score_gpt":0.4964466536060208,"score_spread":0.2857843919877068,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377694396","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3189237,0.012997896,0.53272706,0.11054957,0.00017648224,0.020836309,0.001748886,0.0012826058,0.00075747987],"genre_scores_gemma":[0.9781871,0.010159346,0.008855507,0.00017478352,0.00017153117,0.0021613827,0.000109403074,0.00008483213,0.00009615151],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973953,0.000076615004,0.00037625944,0.00089647813,0.00083446194,0.00042092756],"domain_scores_gemma":[0.9975889,0.00092404365,0.00012284493,0.0006107262,0.00033591702,0.0004175716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012429706,0.000184199,0.00038602884,0.000639899,0.00020007235,0.00006180284,0.00033167654,0.00016532664,0.000008034037],"category_scores_gemma":[0.0008072824,0.00017395325,0.00008394843,0.0009469617,0.0008765733,0.000055664364,0.0005742834,0.0009998198,0.0000015972345],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093184004,0.00231529,0.14269376,0.024772974,0.00015836263,0.00025108337,0.0012698836,0.000050097016,0.19034867,0.016576668,0.053493444,0.5671379],"study_design_scores_gemma":[0.005528573,0.0013517811,0.40180227,0.0045474675,0.00026104436,0.0007010881,0.0016031974,0.115675345,0.009826615,0.02928598,0.42786422,0.0015524076],"about_ca_topic_score_codex":0.000018728859,"about_ca_topic_score_gemma":8.05841e-7,"teacher_disagreement_score":0.6592634,"about_ca_system_score_codex":0.00006456385,"about_ca_system_score_gemma":0.00027182652,"threshold_uncertainty_score":0.7093607},"labels":[],"label_agreement":null},{"id":"W4377834853","doi":"10.1007/978-3-031-10909-6_29","title":"fMRI of Human Visual Pathways","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Island Health","funders":"","keywords":"Neuroscience; White matter; Functional magnetic resonance imaging; Diffusion MRI; Human brain; Visual system; Magnetic resonance imaging; Sensory system; Psychology; Visual cortex; Medicine; Radiology","score_opus":0.16550002138002212,"score_gpt":0.3929910768654471,"score_spread":0.22749105548542498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377834853","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009635108,0.00002182233,0.0018901938,0.00034953165,0.000023085804,0.00037146197,0.00002751753,0.0006777294,0.99654233],"genre_scores_gemma":[0.0077124,0.00014790747,0.002812719,0.00025531903,0.00011779022,0.000022072874,0.00013140497,0.00009966315,0.98870075],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99929,0.0000012671567,0.0002374358,0.0002276265,0.00015203722,0.00009162227],"domain_scores_gemma":[0.9993876,0.000025250702,0.00010903017,0.0003582872,0.000066570174,0.000053256328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033781766,0.00014284643,0.00029284283,0.00011008626,0.00003144162,0.0000022835566,0.00007033171,0.0001138446,0.00035512925],"category_scores_gemma":[0.0000068217937,0.00012604726,0.00012307828,0.000024534273,0.00007650944,0.000010547703,0.00007164193,0.00022474084,0.00012209389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000044084263,0.000024640773,0.000012523437,0.000078769306,0.000018656947,0.000023177321,0.0000073425044,8.3128974e-8,0.010063027,0.9746581,0.011456764,0.0036525596],"study_design_scores_gemma":[0.0005585335,0.0008414836,0.00034396627,0.0007960949,0.00026047195,0.000051523028,0.000012386736,0.00004774018,0.021675281,0.4832543,0.49165776,0.00050043006],"about_ca_topic_score_codex":0.000004297176,"about_ca_topic_score_gemma":0.0000012803429,"teacher_disagreement_score":0.49140373,"about_ca_system_score_codex":0.000017027314,"about_ca_system_score_gemma":0.00002632779,"threshold_uncertainty_score":0.51400584},"labels":[],"label_agreement":null},{"id":"W4378472763","doi":"10.1016/j.neuroimage.2023.120198","title":"Cell specificity of Manganese-enhanced MRI signal in the cerebellum","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto; Ontario Institute for Cancer Research","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; School of Medicine, New York University; National Cancer Institute; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; New York State Stem Cell Science","keywords":"Cytoarchitecture; Cerebellum; Purkinje cell; Neuroscience; Cerebellar cortex; Biology; Anatomy; Cell type; Cell","score_opus":0.06808518125131767,"score_gpt":0.3376798203724341,"score_spread":0.2695946391211164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378472763","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96165806,0.00003000814,0.005850096,0.0046691527,0.000044586668,0.0008053574,0.00002243525,0.00033218745,0.026588097],"genre_scores_gemma":[0.9968268,0.00010714996,0.0013314616,0.00063758506,0.00005636978,0.000041867428,0.000014999186,0.000023465302,0.00096029043],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990616,0.000045600314,0.00021775083,0.00025868285,0.00021337358,0.00020298087],"domain_scores_gemma":[0.9992253,0.00014097597,0.00006875574,0.0004939786,0.00003595686,0.00003502906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015669169,0.00010374567,0.00016678554,0.00011612532,0.000037965045,0.0000084135645,0.00020676192,0.000030178146,0.000055048047],"category_scores_gemma":[0.000025696836,0.000078800156,0.00007025566,0.00074109173,0.00008942473,0.000042261756,0.00005575065,0.0002798424,0.00007903872],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000059139216,0.00032500972,0.002831858,0.00011356183,0.0000023742598,0.00020987907,0.0004749372,0.000067062974,0.97107124,0.0007366664,0.022445323,0.0016629538],"study_design_scores_gemma":[0.0014302015,0.00043059,0.23526044,0.000080150356,0.00004431205,0.00007847935,0.00046984735,0.0022719828,0.7001269,0.0040611,0.055458143,0.000287877],"about_ca_topic_score_codex":0.000010474953,"about_ca_topic_score_gemma":0.0000014073222,"teacher_disagreement_score":0.27094436,"about_ca_system_score_codex":0.000010436363,"about_ca_system_score_gemma":0.000017726108,"threshold_uncertainty_score":0.3213377},"labels":[],"label_agreement":null},{"id":"W4378575432","doi":"10.1016/j.nicl.2023.103444","title":"The impact of temporal lobe epilepsy surgery on picture naming and its relationship to network metric change","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; University College London Hospitals NHS Foundation Trust; University College London Hospitals Biomedical Research Centre; Epilepsy Society; University of Western Australia; Medical Research Charities Group; University College London; National Imaging Facility; National Institute for Health and Care Research; UK Research and Innovation; Newton Fund; Epilepsy Research UK; UCLH Biomedical Research Centre; Academy of Medical Sciences; Wellcome Trust","keywords":"Temporal lobe; Tractography; Betweenness centrality; Diffusion MRI; Lateralization of brain function; Epilepsy; Psychology; White matter; Connectome; Feature selection; Artificial intelligence; Centrality; Pattern recognition (psychology); Cognitive psychology; Computer science; Mathematics; Statistics; Neuroscience; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.3339156314521448,"score_gpt":0.48605804025157634,"score_spread":0.15214240879943153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378575432","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99139214,0.00016705017,0.00040920734,0.0065430147,0.00017622416,0.0008158954,0.000025984044,0.00028621827,0.00018428081],"genre_scores_gemma":[0.9971541,0.0004564545,0.00055637036,0.001053033,0.00047212146,0.00007004788,0.000023541808,0.000038235976,0.00017606477],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984335,0.00014769971,0.00054165634,0.00038585428,0.00019585868,0.00029546412],"domain_scores_gemma":[0.9936286,0.0053962343,0.00017223654,0.0005208256,0.000084622036,0.00019747137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008529189,0.00014824446,0.0003575921,0.00016589151,0.00018596616,0.000018791021,0.00011858029,0.00008681468,0.000005880331],"category_scores_gemma":[0.004343611,0.000099506746,0.00023707715,0.0013951322,0.000088357076,0.000056163357,0.00011692198,0.0005292325,0.00003629457],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017238499,0.00008828474,0.96542645,0.000019733572,0.00001470453,0.000050769126,0.000019160878,0.000058694663,0.00010505864,0.00061242946,0.020561887,0.012870435],"study_design_scores_gemma":[0.00019019986,0.00043567806,0.9924659,0.00007153663,0.00002656539,0.000017823584,0.0000071373724,0.0013713408,0.00002670834,0.00089150656,0.0044098687,0.00008573414],"about_ca_topic_score_codex":0.000006268832,"about_ca_topic_score_gemma":0.0000011576589,"teacher_disagreement_score":0.027039442,"about_ca_system_score_codex":0.000018083445,"about_ca_system_score_gemma":0.00004427752,"threshold_uncertainty_score":0.5200022},"labels":[],"label_agreement":null},{"id":"W4378746244","doi":"10.3389/fneur.2023.1167026","title":"A comparison of altered white matter microstructure in youth born with congenital heart disease or born preterm","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Centre Hospitalier Universitaire Sainte-Justine; McGill University; Philips (Canada); Jewish General Hospital; Montreal Children's Hospital; McGill University Health Centre","funders":"Canadian Institutes of Health Research; McGill University Health Centre; Alliance de recherche numérique du Canada; Centre hospitalier universitaire Sainte-Justine; Jewish General Hospital; McGill University","keywords":"White matter; Diffusion MRI; Medicine; Axon; Cardiology; Gestational age; Internal medicine; Magnetic resonance imaging; Anatomy; Biology; Pregnancy; Radiology; Genetics","score_opus":0.035608033584056654,"score_gpt":0.3282288594003829,"score_spread":0.2926208258163262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378746244","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9911135,0.000056821595,0.0014717681,0.0062726084,0.00014131662,0.00065684796,0.00012725557,0.00009577254,0.00006413295],"genre_scores_gemma":[0.99166363,0.000011825801,0.0056093317,0.0023760744,0.00002971196,0.00006418218,0.00008960575,0.0000337863,0.00012185351],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99897,0.00004799528,0.00027512826,0.0003460947,0.00008984515,0.00027094493],"domain_scores_gemma":[0.99943566,0.00002346316,0.00007750778,0.00035830223,0.00002331781,0.00008173115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038461476,0.00013842672,0.000381829,0.00025130186,0.000020547937,0.000004912997,0.00011183956,0.000066751134,0.0000167563],"category_scores_gemma":[0.000020827876,0.000112167145,0.000033922097,0.0004071462,0.00018078867,0.000039498893,0.000058306938,0.00032158347,0.0000040223676],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022548705,0.00006874074,0.980925,0.000037970585,0.0000068096865,0.00009050534,0.00040217934,0.00007712733,0.000644039,0.00000387782,0.015399397,0.00008943055],"study_design_scores_gemma":[0.0013110136,0.00041529132,0.99381,0.000029023053,0.000038728303,0.000039892828,0.00009682573,0.0015898712,0.00027722513,0.0002599588,0.002022183,0.00010999815],"about_ca_topic_score_codex":0.000010364135,"about_ca_topic_score_gemma":0.000014933597,"teacher_disagreement_score":0.013377214,"about_ca_system_score_codex":0.00001339244,"about_ca_system_score_gemma":0.00004312864,"threshold_uncertainty_score":0.45740432},"labels":[],"label_agreement":null},{"id":"W4379348402","doi":"10.1017/cjn.2023.205","title":"P.115 MRI based methodology for assessment of white matter neuroplasticity: preclinical validation using human motor training data","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Burnaby Hospital; University of Winnipeg","funders":"","keywords":"Diffusion MRI; White matter; Corticospinal tract; Medicine; Magnetic resonance imaging; Preclinical research; Physical medicine and rehabilitation; Nuclear medicine; Radiology; Medical physics","score_opus":0.5785829321442595,"score_gpt":0.5028159455403525,"score_spread":0.07576698660390702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379348402","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9727466,0.000041091498,0.01913419,0.0069645727,0.00037086752,0.00037654038,0.000078975136,0.000036475394,0.00025065237],"genre_scores_gemma":[0.86373085,0.000035490946,0.13377622,0.0022166881,0.00019837184,0.000006091661,0.000004623291,0.000017117778,0.000014544844],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9958785,0.0008668972,0.00112123,0.0006538286,0.0005652964,0.0009142535],"domain_scores_gemma":[0.99545664,0.0017935944,0.00097451673,0.00033432627,0.0004826487,0.00095828227],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.006625803,0.00024802567,0.0006502626,0.0010629385,0.0020185385,0.00016237875,0.0016672832,0.00014716288,0.000084307474],"category_scores_gemma":[0.002959592,0.00018230034,0.0002160055,0.0013147637,0.0034766058,0.0005540511,0.00015678801,0.0008712287,6.6184026e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000825009,0.00004543576,0.9823065,0.000030274452,0.000013323566,0.0006606758,0.00010998114,0.012504171,0.002125345,0.0005710731,0.00078454026,0.0007662083],"study_design_scores_gemma":[0.0010826149,0.064668365,0.6817708,0.0001607026,0.00031121587,0.01190776,0.00022137322,0.21469408,0.0006194128,0.020406075,0.0036578,0.00049977674],"about_ca_topic_score_codex":0.00016436195,"about_ca_topic_score_gemma":0.0012990849,"teacher_disagreement_score":0.30053565,"about_ca_system_score_codex":0.00010486304,"about_ca_system_score_gemma":0.0029342852,"threshold_uncertainty_score":0.9992807},"labels":[],"label_agreement":null},{"id":"W4379390288","doi":"10.1101/2023.06.01.543240","title":"A population-averaged structural connectomic brain atlas of 422 HCP-Aging subjects","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Alliance de recherche numérique du Canada","keywords":"Diffusion MRI; Connectome; Human Connectome Project; Population; White matter; Connectomics; Segmentation; Neuroscience; Artificial intelligence; Computer science; Deep brain stimulation; Orientation (vector space); Spatial normalization; Brain atlas; Pattern recognition (psychology); Voxel; Medicine; Psychology; Magnetic resonance imaging; Parkinson's disease; Pathology; Functional connectivity","score_opus":0.04262580790053069,"score_gpt":0.30554831055006126,"score_spread":0.26292250264953054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379390288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99171525,0.00019763292,0.0033943767,0.0013018061,0.00039201556,0.0013621442,0.00023827623,0.0013944261,0.000004074784],"genre_scores_gemma":[0.98100233,0.00008330355,0.017843204,0.00030879176,0.00030667146,0.00021976752,0.0000049028536,0.0002083354,0.00002267267],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9973863,0.000086309556,0.00069602375,0.0009751673,0.00039166192,0.000464573],"domain_scores_gemma":[0.9971188,0.00020942795,0.00057806954,0.0015211869,0.00035152485,0.00022100123],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033386107,0.00048856327,0.00082035677,0.00041684395,0.00015266518,0.000057800415,0.00037527955,0.00031293614,0.000028702974],"category_scores_gemma":[0.0005063283,0.0005243926,0.00022968369,0.0006551707,0.00011666441,0.00009679275,0.00043256223,0.00093090226,0.000023977973],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006566524,0.00007384319,0.120912835,0.0011326079,0.0001598674,0.00009310324,0.000021394686,0.00020161581,0.8744537,0.0020178168,0.00086008484,0.000007419303],"study_design_scores_gemma":[0.0009420124,0.00007009384,0.7599158,0.0010930437,0.00020155511,1.89996e-7,0.0000028141628,0.002387526,0.23384027,0.00013112342,0.0007293458,0.0006861802],"about_ca_topic_score_codex":0.00021767087,"about_ca_topic_score_gemma":0.00000343383,"teacher_disagreement_score":0.6406135,"about_ca_system_score_codex":0.00024768442,"about_ca_system_score_gemma":0.00029552117,"threshold_uncertainty_score":0.99972075},"labels":[],"label_agreement":null},{"id":"W4379928270","doi":"10.1016/j.cortex.2023.04.018","title":"Effects of anterior temporal lobe resection on cortical morphology","year":2023,"lang":"es","type":"article","venue":"Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; University College London Hospitals NHS Foundation Trust; University College London; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; Instituto Serrapilheira; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Imaging Facility; UK Research and Innovation","keywords":"Supramarginal gyrus; Temporal lobe; Psychology; Epilepsy surgery; Anterior temporal lobectomy; Orbitofrontal cortex; Postcentral gyrus; Temporal cortex; Occipital lobe; Cortex (anatomy); Frontal lobe; Neuroscience; Superior temporal gyrus; Anatomy; Epilepsy; Functional magnetic resonance imaging; Medicine; Prefrontal cortex; Cognition","score_opus":0.04304128046949076,"score_gpt":0.37140187266760205,"score_spread":0.3283605921981113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4379928270","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9942191,0.00014599567,0.0025072903,0.0011220174,0.0003218248,0.00067289476,0.000018766876,0.00035355357,0.0006385424],"genre_scores_gemma":[0.9975006,0.00072861166,0.00033405557,0.00032682947,0.00017911283,0.00007501557,0.000027581442,0.00003788433,0.0007903268],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99883044,0.00006087782,0.00030824656,0.000363082,0.0001728951,0.00026447655],"domain_scores_gemma":[0.99900186,0.00029667112,0.00013140771,0.00040917273,0.000062732965,0.00009814687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011025418,0.00014975118,0.00033061515,0.00014183212,0.000075264004,0.000007847262,0.000111210604,0.00011187942,0.000038515147],"category_scores_gemma":[0.0002761913,0.00014041044,0.00009522139,0.00049296155,0.00020435125,0.000028157674,0.000080660466,0.00033100529,0.00027035724],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047435472,0.00041508058,0.02767165,0.0006678032,0.000034542565,0.0004605345,0.000049950493,0.000002970544,0.9468423,0.0040375404,0.009840279,0.009502957],"study_design_scores_gemma":[0.0010426104,0.0022937453,0.85877514,0.0008626787,0.00013088607,0.000065331806,0.000022881679,0.001127098,0.12679423,0.0009289574,0.007786638,0.00016978905],"about_ca_topic_score_codex":0.000017866918,"about_ca_topic_score_gemma":6.3580853e-7,"teacher_disagreement_score":0.8311035,"about_ca_system_score_codex":0.00003693525,"about_ca_system_score_gemma":0.000037777652,"threshold_uncertainty_score":0.5725772},"labels":[],"label_agreement":null},{"id":"W4380185499","doi":"10.1055/s-0043-1767469","title":"Asymmetric hearing loss is associated with altered white matter mesostructure and cortical measures in temporal and occipital regions","year":2023,"lang":"en","type":"article","venue":"Laryngo-Rhino-Otologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Audiology; Hearing loss; Neuroscience; Structural integrity; Diffusion imaging; Occipital region; Magnetic resonance imaging; Medicine; Psychology; Anatomy; Radiology","score_opus":0.08130976247714956,"score_gpt":0.3346195078895302,"score_spread":0.25330974541238066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380185499","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98596275,0.00020158339,0.0005630229,0.011641677,0.000033858432,0.00063069555,0.000032897995,0.00044105522,0.0004924605],"genre_scores_gemma":[0.9951566,0.0001671609,0.0024806838,0.0016052215,0.00003293306,0.00007864408,0.000059534665,0.00003732543,0.0003818891],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99856865,0.000054275275,0.00025899327,0.0005002661,0.00021292013,0.00040490745],"domain_scores_gemma":[0.9992102,0.00015335143,0.0000810992,0.0003497728,0.000056891437,0.0001487058],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015554014,0.00021627912,0.0003947002,0.00027774877,0.00013053266,0.00003819583,0.0001004661,0.00014537066,0.00001664889],"category_scores_gemma":[0.00020771055,0.00017095255,0.000040449388,0.00087126717,0.00020345289,0.000110623216,0.00015209279,0.00050701224,0.000009608817],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000769131,0.00004802391,0.9915661,0.00003241332,0.000028601835,0.00025682,0.0001420389,0.0000023336245,0.0005225323,0.00019559985,0.006713618,0.00041501032],"study_design_scores_gemma":[0.00093196984,0.00019326576,0.99412334,0.000116201794,0.000054801276,0.0003394792,0.000067126144,0.0004306954,0.0004205796,0.0018059432,0.0013113024,0.00020527688],"about_ca_topic_score_codex":0.00005515201,"about_ca_topic_score_gemma":0.000045216897,"teacher_disagreement_score":0.0100364555,"about_ca_system_score_codex":0.000055309272,"about_ca_system_score_gemma":0.000035366687,"threshold_uncertainty_score":0.6971243},"labels":[],"label_agreement":null},{"id":"W4380272571","doi":"10.1101/2023.06.09.544263","title":"Gauge equivariant convolutional neural networks for diffusion mri","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Equivariant map; Convolutional neural network; Gauge (firearms); Diffusion MRI; Diffusion; Physics; Computer science; Quantum electrodynamics; Statistical physics; Mathematics; Artificial intelligence; Geography; Pure mathematics; Medicine; Magnetic resonance imaging; Quantum mechanics; Radiology","score_opus":0.060881123169515,"score_gpt":0.3081433741238512,"score_spread":0.24726225095433618,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380272571","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12148593,0.00077189185,0.8591531,0.0068925107,0.001938756,0.004800904,0.0012090165,0.0037371877,0.000010712662],"genre_scores_gemma":[0.9387976,0.00042375564,0.056489132,0.0008772884,0.0013819054,0.0016968331,0.000010472566,0.00027441728,0.000048575715],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973881,0.000039163766,0.00054315967,0.0010959983,0.0003155423,0.00061803224],"domain_scores_gemma":[0.99742347,0.00015487046,0.00033914763,0.0013141204,0.0004613409,0.00030706092],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003173564,0.0004844358,0.0005941168,0.00021476898,0.0002505952,0.00007968008,0.0003670578,0.00043445785,0.000022156177],"category_scores_gemma":[0.00019433988,0.0005007795,0.00028416867,0.00038174697,0.00014475394,0.00006855446,0.00059638877,0.00088413584,0.000022100401],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006187838,0.0011918972,0.018974671,0.002155854,0.0004713976,0.00032243345,0.000009245083,0.0034917444,0.8608128,0.06693768,0.044983845,0.000029679059],"study_design_scores_gemma":[0.0038653554,0.0004675403,0.24965307,0.0018684753,0.0010119339,5.1870234e-7,0.000003215176,0.6319194,0.033704385,0.0004301467,0.07454979,0.0025262167],"about_ca_topic_score_codex":0.000022095152,"about_ca_topic_score_gemma":5.8150005e-7,"teacher_disagreement_score":0.8271084,"about_ca_system_score_codex":0.00023462191,"about_ca_system_score_gemma":0.00026589292,"threshold_uncertainty_score":0.99974436},"labels":[],"label_agreement":null},{"id":"W4380716205","doi":"10.1016/j.psyneuen.2023.106193","title":"Sex/gender, sexual orientation, and gender-affirming hormones are associated with white matter microstructure in a Thai sample","year":2023,"lang":"en","type":"article","venue":"Psychoneuroendocrinology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"","keywords":"Fractional anisotropy; Sexual orientation; White matter; Diffusion MRI; Transgender; Hormone; Testosterone (patch); Transgender women; Psychology; Physiology; Demography; Developmental psychology; Internal medicine; Medicine; Magnetic resonance imaging; Men who have sex with men; Social psychology; Psychoanalysis; Immunology","score_opus":0.07699350361168032,"score_gpt":0.35077397707625113,"score_spread":0.2737804734645708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380716205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99217105,0.00006704678,0.0015507492,0.004977141,0.000084017935,0.00047098464,0.00006482112,0.00042469212,0.00018947518],"genre_scores_gemma":[0.9949973,0.00012133165,0.0021559326,0.0019718145,0.000041242605,0.0001283578,0.00011938996,0.00005469887,0.00040988196],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99853957,0.000052420422,0.0002345661,0.0005977208,0.00012457874,0.00045116514],"domain_scores_gemma":[0.99927443,0.0001198521,0.0001189276,0.0003558242,0.000050413055,0.00008053822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029560462,0.00020201768,0.00029384549,0.00026365658,0.000105368825,0.000017222277,0.00009133141,0.00004611274,0.000029414181],"category_scores_gemma":[0.000062575804,0.00018254426,0.000022457743,0.00061670825,0.00012875523,0.000066519075,0.00006894639,0.00033509894,0.00001909877],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096501135,0.00007277717,0.9872635,0.000042713964,0.00002590022,0.00025658795,0.000642393,0.00001747542,0.0051661474,0.0001232867,0.00578526,0.0005074828],"study_design_scores_gemma":[0.0013140838,0.0001317674,0.9925489,0.000016133645,0.00003494953,0.0008177535,0.0006185659,0.00011450028,0.00041918707,0.0022357581,0.001574895,0.00017355087],"about_ca_topic_score_codex":0.000015607857,"about_ca_topic_score_gemma":0.000029624165,"teacher_disagreement_score":0.005285381,"about_ca_system_score_codex":0.000027310136,"about_ca_system_score_gemma":0.000017621902,"threshold_uncertainty_score":0.7443939},"labels":[],"label_agreement":null},{"id":"W4380793055","doi":"10.1016/j.neurobiolaging.2023.06.007","title":"Fiber-specific age-related differences in the white matter of healthy adults uncovered by fixel-based analysis","year":2023,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research","keywords":"White matter; White (mutation); Fiber; Psychology; Medicine; Biology; Materials science; Genetics; Composite material; Magnetic resonance imaging","score_opus":0.04124017950903353,"score_gpt":0.3142781312652037,"score_spread":0.2730379517561702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380793055","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98931634,0.00005445649,0.00023490706,0.0097458,0.00002153127,0.00026309965,0.0000411715,0.000070158574,0.00025250213],"genre_scores_gemma":[0.9980873,0.00007010927,0.00046154243,0.001059083,0.00000664857,0.000027239375,0.00015719667,0.000010399614,0.00012052308],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990172,0.0001057622,0.0003505635,0.00026801325,0.00007673009,0.00018176367],"domain_scores_gemma":[0.9991738,0.0002305451,0.0001689035,0.00037123053,0.000031720654,0.000023768876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012840884,0.00010386243,0.0003442825,0.0002823016,0.000037218157,0.0000028533814,0.00017048171,0.0000528507,0.000073762356],"category_scores_gemma":[0.000011879269,0.000074831376,0.00010400517,0.0012444947,0.0001845963,0.00001741489,0.000030364441,0.00020983139,0.000011905242],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002195817,0.00023687689,0.9768324,0.00013904116,0.00007567441,0.000020948108,0.0006161545,0.00039693632,0.010375358,0.00006806656,0.010242724,0.0007762448],"study_design_scores_gemma":[0.0008577691,0.00031326737,0.99466217,0.00008478012,0.00009928966,0.0000050359768,0.000096195094,0.0006357801,0.0019547304,0.00023268348,0.0009633006,0.000095023344],"about_ca_topic_score_codex":0.00002664154,"about_ca_topic_score_gemma":0.0000040721566,"teacher_disagreement_score":0.017829752,"about_ca_system_score_codex":0.0000091419315,"about_ca_system_score_gemma":0.000013594238,"threshold_uncertainty_score":0.30515352},"labels":[],"label_agreement":null},{"id":"W4380869621","doi":"10.1097/j.pain.0000000000002936","title":"Challenges of brain white matter imaging: proceed with caution","year":2023,"lang":"en","type":"letter","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; University Health Network; Mount Sinai Hospital","funders":"","keywords":"White (mutation); Mount; Brain research; White paper; White matter; Dental research; Research centre; Medicine; Library science; Psychology; Geography; Dentistry; Engineering; Neuroscience; Archaeology; Magnetic resonance imaging","score_opus":0.06958421053355707,"score_gpt":0.3300524511057817,"score_spread":0.2604682405722246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380869621","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000033761276,0.00015163892,0.014704871,0.9800932,0.000018351584,0.000593478,0.000019637382,0.00039486063,0.003990205],"genre_scores_gemma":[0.0063926266,0.00017235121,0.009151028,0.9688208,0.0011087256,0.00056238484,0.00044131614,0.0002530254,0.013097726],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99890256,0.00007823818,0.00020014598,0.0003807742,0.00021873537,0.00021955559],"domain_scores_gemma":[0.99908876,0.00018279061,0.00015909069,0.0004454463,0.00009272306,0.000031202577],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004312529,0.00019623783,0.00030532785,0.00015999062,0.000027647127,0.0000069805897,0.000106518324,0.00012662058,0.000031646367],"category_scores_gemma":[0.00007882846,0.00015913465,0.00006404893,0.00016619405,0.000087058215,0.000029604284,0.000033425244,0.0006456358,0.000049946004],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010095599,0.000020345695,0.0036713672,0.00075640756,0.000016503018,0.00008251978,0.00007066031,4.5209518e-7,0.00019410053,0.00005287281,0.9913118,0.0038128905],"study_design_scores_gemma":[0.00025710504,0.00009545974,0.008077625,0.00086132664,0.00007881033,0.00009859144,0.000043090608,0.00027587786,0.00024632172,0.0013769262,0.98834676,0.00024211328],"about_ca_topic_score_codex":0.000007669671,"about_ca_topic_score_gemma":0.00000161904,"teacher_disagreement_score":0.011272379,"about_ca_system_score_codex":0.00003501876,"about_ca_system_score_gemma":0.00003786444,"threshold_uncertainty_score":0.6489323},"labels":[],"label_agreement":null},{"id":"W4380884179","doi":"10.1002/alz.060795","title":"Assessing neuroinflammatory differences in FTLD‐Tau vs FTLD‐TDP using free water diffusion","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Parkinson's Clinic of Eastern Toronto & Movement Disorders Centre; University of Toronto; University Health Network; Ontario Brain Institute; Baycrest Hospital; Toronto Western Hospital; Occupational Cancer Research Centre","funders":"","keywords":"Frontotemporal lobar degeneration; Neuroinflammation; Primary progressive aphasia; Diffusion MRI; Psychology; Neuroscience; Frontotemporal dementia; Pathological; Aphasia; Pathology; Medicine; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.13562524144025834,"score_gpt":0.36610717679689636,"score_spread":0.23048193535663802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380884179","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99442875,0.0009778494,0.0013732789,0.001755155,0.00016069275,0.00046113125,0.000004015171,0.0005138266,0.00032527768],"genre_scores_gemma":[0.9924915,0.00010669052,0.0067321896,0.0003741419,0.000102248865,0.000057413312,0.00005340167,0.000055713343,0.00002674555],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983318,0.00005307416,0.00039819634,0.00046297023,0.00028771546,0.00046628303],"domain_scores_gemma":[0.9990774,0.00005218046,0.00008632045,0.0006352523,0.00004400923,0.00010485275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018535362,0.00021977095,0.00029116284,0.0002570471,0.00019659186,0.00007498532,0.00024050774,0.000072048286,0.000084613464],"category_scores_gemma":[0.000025793805,0.00017548325,0.00008507313,0.0003591646,0.000089123336,0.00028281088,0.0003524551,0.00026958907,0.00008180137],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056142904,0.0002750297,0.23376325,0.0000403785,0.00065185927,0.00030850057,0.0003409343,0.000027945207,0.73980945,0.0005373408,0.0030573127,0.021131877],"study_design_scores_gemma":[0.0026066713,0.00019620486,0.6876136,0.00039316897,0.005802705,0.00011965101,0.00026974117,0.01565671,0.26221246,0.0053669848,0.018783933,0.0009781708],"about_ca_topic_score_codex":0.00007232268,"about_ca_topic_score_gemma":0.000009596857,"teacher_disagreement_score":0.47759697,"about_ca_system_score_codex":0.000011035325,"about_ca_system_score_gemma":0.000034250625,"threshold_uncertainty_score":0.71559995},"labels":[],"label_agreement":null},{"id":"W4380990775","doi":"10.1016/j.neuroimage.2023.120231","title":"Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Health and Medical Research Council; National Institute of Mental Health; Horizon 2020 Framework Programme; Narodowa Agencja Wymiany Akademickiej; Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Natural Sciences and Engineering Research Council of Canada; Centre Hospitalier Universitaire Vaudois; Centre d'Imagerie BioMédicale; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Université de Lausanne; Hôpitaux Universitaires de Genève; Nvidia; Université de Genève; Academic Computer Centre Cyfronet, AGH University of Science and Technology; Polska Akademia Nauk; National Natural Science Foundation of China; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute on Drug Abuse; École Polytechnique Fédérale de Lausanne; Fundacja na rzecz Nauki Polskiej; European Commission; Consejo Nacional de Ciencia y Tecnología; National Institute of Allergy and Infectious Diseases; Agence Nationale de la Recherche; Ministerstwo Edukacji i Nauki; Infrastruktura PL-Grid; National Science Foundation","keywords":"Diffusion MRI; Computer science; Ground truth; Tractography; Diffusion; Monte Carlo method; Binary number; Task (project management); Scale (ratio); Functional connectivity; Artificial intelligence; Data mining; Algorithm; Pattern recognition (psychology); Magnetic resonance imaging; Mathematics; Statistics; Physics; Neuroscience; Psychology","score_opus":0.09610758939185464,"score_gpt":0.35369401888435575,"score_spread":0.2575864294925011,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4380990775","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90255845,0.00009286432,0.00048091417,0.09048721,0.00012464318,0.0011551119,0.0006063896,0.0013497435,0.003144693],"genre_scores_gemma":[0.9963432,0.00071634824,0.00019816386,0.0020346898,0.00020398098,0.000054681957,0.000107623135,0.00004827172,0.00029307127],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986278,0.00008614862,0.00025282768,0.0004934134,0.00026477524,0.00027506016],"domain_scores_gemma":[0.9951071,0.0034570678,0.00010846591,0.001190194,0.000061989864,0.00007518166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020260387,0.00018772234,0.00018734537,0.000056225654,0.00038897753,0.000046270838,0.00030714873,0.000051501866,0.00001865649],"category_scores_gemma":[0.0012740802,0.00010403451,0.00014309015,0.00075844134,0.00020390505,0.00006078668,0.00016097607,0.0005037982,0.00006322962],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011133624,0.003075412,0.08152731,0.000074292555,0.00017141637,0.0009993283,0.002954725,0.00035512427,0.5710973,0.0023336972,0.27566123,0.060636774],"study_design_scores_gemma":[0.0012769349,0.00021817743,0.88496155,0.000054221713,0.00008100788,0.000023650415,0.00012435621,0.0038340893,0.0028364738,0.0038826372,0.10252334,0.00018356618],"about_ca_topic_score_codex":0.00009807401,"about_ca_topic_score_gemma":0.00001802386,"teacher_disagreement_score":0.80343425,"about_ca_system_score_codex":0.000008604439,"about_ca_system_score_gemma":0.000027415337,"threshold_uncertainty_score":0.4242404},"labels":[],"label_agreement":null},{"id":"W4381108580","doi":"10.1016/j.psychres.2023.115319","title":"Polygenic risk for schizophrenia and the language network: Putative compensatory reorganization in unaffected siblings","year":2023,"lang":"en","type":"article","venue":"Psychiatry Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Western University","funders":"Xiangya Hospital, Central South University; Canada First Research Excellence Fund; Fonds de Recherche du Québec - Santé; Natural Science Foundation of Changzhou City; National Natural Science Foundation of China; McGill University","keywords":"Schizophrenia (object-oriented programming); Polygenic risk score; Cognition; Psychology; Developmental psychology; Neuroscience; Biology; Psychiatry; Genetics; Gene","score_opus":0.07738195335874927,"score_gpt":0.4386258022331791,"score_spread":0.36124384887442984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381108580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97399837,0.00097131147,0.0043481225,0.016498066,0.00006985331,0.0026724043,0.000020961126,0.0004125445,0.0010083854],"genre_scores_gemma":[0.9858715,0.00039191893,0.012064149,0.00016216846,0.00021006302,0.0002756253,0.000042514974,0.000055759505,0.0009262846],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990439,0.00015802683,0.0001321171,0.00023288738,0.00016264034,0.00027044228],"domain_scores_gemma":[0.9990775,0.00050691055,0.000041475498,0.00024015812,0.00008060928,0.000053326617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010377234,0.000069017486,0.00012949065,0.00022332954,0.00021689676,0.000019346606,0.000091519076,0.000039312887,0.000010733309],"category_scores_gemma":[0.00036042443,0.000050542865,0.000027809636,0.0017292631,0.00019243409,0.000026174044,0.00007451291,0.0003599399,0.000024678255],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0043963054,0.00029023617,0.7122348,0.0003628854,0.00012578929,0.00001538266,0.0024258909,0.00014631856,0.006179144,0.17376281,0.077119805,0.022940611],"study_design_scores_gemma":[0.0107909925,0.0003299533,0.80887944,0.00020412696,0.0000670509,0.00002568483,0.0015751257,0.0336699,0.00023685975,0.13983916,0.0041442453,0.00023745025],"about_ca_topic_score_codex":0.000049726903,"about_ca_topic_score_gemma":0.00004554861,"teacher_disagreement_score":0.096644625,"about_ca_system_score_codex":0.000019400764,"about_ca_system_score_gemma":0.000064105116,"threshold_uncertainty_score":0.20610783},"labels":[],"label_agreement":null},{"id":"W4381249848","doi":"10.3390/brainsci13060963","title":"Cortical Structure Differences in Relation to Age, Sexual Attractions, and Gender Dysphoria in Adolescents: An Examination of Mean Diffusivity and T1 Relaxation Time","year":2023,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; McGill University; Douglas Mental Health University Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research; Kids Brain Health Network; University of Toronto; Department of Psychiatry, University of Toronto; Fondation Brain Canada; Centre for Addiction and Mental Health Foundation; Government of Ontario; Centre for Addiction and Mental Health","keywords":"Relaxation (psychology); Psychology; Gender dysphoria; Diffusion MRI; Neuroscience; Gender identity; Medicine; Social psychology; Magnetic resonance imaging","score_opus":0.10824259226043619,"score_gpt":0.37907665755997794,"score_spread":0.27083406529954174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381249848","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.998163,0.000010374654,0.00065092597,0.0007709146,0.000015267284,0.0002934497,0.0000048390743,0.00004371098,0.000047522833],"genre_scores_gemma":[0.99805796,0.000012943558,0.0017711737,0.00007859427,0.000013572922,0.000011289161,0.000010192648,0.0000038247076,0.000040435843],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920434,0.000074674215,0.00016899488,0.0002665456,0.00018310717,0.00010233819],"domain_scores_gemma":[0.9996724,0.00010710147,0.000057106994,0.000089549525,0.00002236973,0.00005144165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004100263,0.000060772487,0.00011105054,0.0002449268,0.00007453888,0.000017313456,0.00004547323,0.00004193323,0.0000035535002],"category_scores_gemma":[0.0003244853,0.000052392086,0.0000048035017,0.0007051918,0.0001598045,0.00020130759,0.000031301694,0.00011007084,8.876897e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027352602,0.00012364538,0.80649054,0.000054205702,0.0000014899022,0.0000052828345,0.0025058798,0.00004363585,0.15984035,0.0021518604,0.000040367686,0.028715376],"study_design_scores_gemma":[0.00018584974,0.00012805223,0.98886687,0.000046818634,0.000003856938,0.000005971037,0.00036182726,0.0075451816,0.00024233831,0.002553532,0.000007772709,0.00005195644],"about_ca_topic_score_codex":0.00003271683,"about_ca_topic_score_gemma":0.00009961471,"teacher_disagreement_score":0.18237628,"about_ca_system_score_codex":0.000021407874,"about_ca_system_score_gemma":0.000018255132,"threshold_uncertainty_score":0.21364872},"labels":[],"label_agreement":null},{"id":"W4381715047","doi":"10.1002/hbm.26402","title":"Striatonigrostriatal connectivity‐based cross‐species parcellation of human and macaque substantia nigra","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health; Biotechnology and Biological Sciences Research Council; Fundo para o Desenvolvimento das Ciências e da Tecnologia; Universidade de Macau; Wellcome Trust; Fondation Brain Canada","keywords":"Substantia nigra; Connectome; Macaque; Neuroscience; Pars compacta; Biology; Voxel; Functional connectivity; Computer science; Artificial intelligence","score_opus":0.15920522327381417,"score_gpt":0.3919901970006795,"score_spread":0.23278497372686532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4381715047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99062407,0.00002111607,0.006178966,0.0011177037,0.000014901659,0.00044994478,0.00003030367,0.0004261636,0.001136802],"genre_scores_gemma":[0.99808824,0.000009456695,0.0008179011,0.00015604233,0.00006664341,0.000028090468,0.00015948202,0.00002629363,0.0006478344],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990017,0.00003466202,0.00030009376,0.0003005612,0.00016084065,0.00020213288],"domain_scores_gemma":[0.9992145,0.00019596948,0.00015106967,0.00030863812,0.00006718301,0.00006265863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023076829,0.00012914275,0.00024432215,0.0002748935,0.00032812334,0.0000346701,0.000072979514,0.00005975345,0.00004137103],"category_scores_gemma":[0.00009783038,0.00013740841,0.000067672874,0.00045742304,0.00019465962,0.00007178848,0.000053746677,0.00016405547,0.000003899571],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001476436,0.000035821722,0.07768067,0.00013306216,0.000012373113,0.000010534394,0.00023257916,0.000022030028,0.9043592,0.015698355,0.0015900822,0.00021052874],"study_design_scores_gemma":[0.0016637283,0.00015219694,0.94016033,0.0002276999,0.000025001671,0.000009888571,0.00024093408,0.0015166975,0.040630966,0.008387014,0.0067610084,0.00022453532],"about_ca_topic_score_codex":0.000025697014,"about_ca_topic_score_gemma":0.000008330933,"teacher_disagreement_score":0.8637282,"about_ca_system_score_codex":0.00002626828,"about_ca_system_score_gemma":0.000026356933,"threshold_uncertainty_score":0.5603352},"labels":[],"label_agreement":null},{"id":"W4382200459","doi":"10.1055/s-0043-1766831","title":"Asymmetrischer Hörverlust ist mit veränderter Mesostruktur der weißen und grauen Substanz der temporalen und okzipitalen Region assoziiert","year":2023,"lang":"de","type":"article","venue":"Laryngo-Rhino-Otologie","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Art","score_opus":0.13940977563941614,"score_gpt":0.3903717349628948,"score_spread":0.25096195932347864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382200459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.45207414,0.21500248,0.029815916,0.20272543,0.009345398,0.022334909,0.0020814391,0.01944841,0.047171883],"genre_scores_gemma":[0.93807614,0.015258925,0.0082177995,0.008057381,0.002107107,0.0010394208,0.0021032903,0.0007283179,0.024411628],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9927664,0.00039392713,0.001413123,0.002256615,0.0010907666,0.0020791942],"domain_scores_gemma":[0.99433345,0.00089336454,0.00068887,0.002948507,0.00039757855,0.00073824904],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007319715,0.0012645017,0.0015266119,0.00081214175,0.00069302233,0.00024622947,0.0014470116,0.001083503,0.000268226],"category_scores_gemma":[0.0007598122,0.0011810691,0.00067286915,0.0027780212,0.00072850706,0.00062575296,0.0009022421,0.0018891637,0.0033073246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005010212,0.00097029994,0.27312052,0.0006873627,0.0027497972,0.0032792755,0.0005780841,0.000030048053,0.0015678146,0.003794306,0.69741184,0.01530962],"study_design_scores_gemma":[0.003187626,0.00063756714,0.11570418,0.00061223534,0.0034406858,0.0001278288,0.00025702105,0.0012031037,0.0051550106,0.009035406,0.858756,0.0018833117],"about_ca_topic_score_codex":0.0006234947,"about_ca_topic_score_gemma":0.00011490573,"teacher_disagreement_score":0.486002,"about_ca_system_score_codex":0.0005995142,"about_ca_system_score_gemma":0.0003537319,"threshold_uncertainty_score":0.9990639},"labels":[],"label_agreement":null},{"id":"W4382894678","doi":"10.1101/2023.06.30.547294","title":"Variations in perfusion detectable in advance of microstructure in white matter aging","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"","keywords":"White matter; Microstructure; Perfusion; White (mutation); Psychology; Medicine; Internal medicine; Materials science; Biology; Composite material; Magnetic resonance imaging; Radiology; Genetics","score_opus":0.022167844420336084,"score_gpt":0.2790912591522365,"score_spread":0.2569234147319004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382894678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912337,0.0002752789,0.0054749637,0.0013319977,0.0001637737,0.0011742001,0.00011272766,0.00022270964,0.000010637597],"genre_scores_gemma":[0.9572076,0.0002647653,0.041841745,0.00020404902,0.000053153028,0.00031220858,9.0458644e-7,0.000102200975,0.000013345551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800193,0.000054600034,0.0006422541,0.00073876587,0.00018224718,0.00038021876],"domain_scores_gemma":[0.998519,0.000054549066,0.00026980843,0.0009465481,0.00013585757,0.0000742322],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002978886,0.00030202576,0.0005447523,0.00077599724,0.000034079672,0.000023265953,0.0002533268,0.0002702312,0.000028806619],"category_scores_gemma":[0.00011606469,0.00034434273,0.00006789186,0.0012293183,0.000057897094,0.00009651752,0.00035046597,0.0010207484,0.000014143172],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001838245,0.00008277887,0.5358611,0.0003110645,0.0000031982922,0.00004409389,0.000022525386,0.00047945417,0.4630418,0.00008808957,0.000044454147,0.0000030790093],"study_design_scores_gemma":[0.00057868246,0.000015078459,0.9284556,0.0015838196,0.000017729748,5.3505644e-8,0.0000040083,0.0013428023,0.06728336,0.0000490359,0.00038925,0.00028056983],"about_ca_topic_score_codex":0.00014964207,"about_ca_topic_score_gemma":0.00004394166,"teacher_disagreement_score":0.39575845,"about_ca_system_score_codex":0.00030221313,"about_ca_system_score_gemma":0.00021820153,"threshold_uncertainty_score":0.9999009},"labels":[],"label_agreement":null},{"id":"W4382933704","doi":"10.1101/2023.06.30.547270","title":"Delineation of the Trigeminal-Lateral Parabrachial-Central Amygdala Tract in Humans: An Ultra-High Field Diffusion MRI Study","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; NIH Blueprint for Neuroscience Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; University of Toronto","keywords":"Neuroscience; Psychology; Neuropsychology; Connectome; Trigeminal nerve; Diffusion MRI; Medicine; Audiology; Functional connectivity; Magnetic resonance imaging; Anesthesia; Cognition; Radiology","score_opus":0.04253121338777522,"score_gpt":0.31153391889512555,"score_spread":0.26900270550735034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382933704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9915698,0.00005705245,0.0043669934,0.00080747943,0.0003659268,0.0023701733,0.00008429577,0.00037572213,0.0000025215709],"genre_scores_gemma":[0.9962475,0.00019650115,0.0026164863,0.00019344424,0.0002582203,0.0003716081,0.0000019588738,0.000099577126,0.000014756311],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975013,0.00015019624,0.00075619685,0.00081936154,0.00039006714,0.00038287116],"domain_scores_gemma":[0.9975901,0.00009369725,0.00043264977,0.0015390313,0.00020769426,0.00013679238],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00039183022,0.00038003328,0.0005644563,0.00024030844,0.00012313531,0.000046025943,0.000455453,0.00027468553,0.000014788763],"category_scores_gemma":[0.00020376833,0.0003175578,0.00015192441,0.00054715405,0.00007096895,0.000107354215,0.00015457308,0.0010068532,0.000003931456],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016224089,0.0026832328,0.6026482,0.0003011382,0.000049072183,0.00006951383,0.00010028483,0.00028682567,0.3930526,0.00047413626,0.00014958759,0.00002316713],"study_design_scores_gemma":[0.000915111,0.00027036277,0.8750558,0.00049832975,0.0001528351,4.103901e-8,0.000012229611,0.00073358056,0.12177726,0.000017263264,0.00026995278,0.00029726993],"about_ca_topic_score_codex":0.00037064846,"about_ca_topic_score_gemma":0.000023615341,"teacher_disagreement_score":0.2724076,"about_ca_system_score_codex":0.00014917647,"about_ca_system_score_gemma":0.00021055985,"threshold_uncertainty_score":0.99992764},"labels":[],"label_agreement":null},{"id":"W4383199238","doi":"10.1162/netn_a_00327","title":"Epileptogenic networks in extra temporal lobe epilepsy","year":2023,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London; Engineering and Physical Sciences Research Council; National Institute for Health and Care Research; National Imaging Facility; UK Research and Innovation; Medical Research Charities Group; Wellcome Trust","keywords":"Temporal lobe; Epilepsy; Abnormality; Epilepsy surgery; Fractional anisotropy; Connection (principal bundle); Medicine; Neuroscience; Diffusion MRI; Surgery; Psychology; Magnetic resonance imaging; Radiology; Mathematics; Psychiatry; Geometry","score_opus":0.08547255297895016,"score_gpt":0.35815739773133254,"score_spread":0.27268484475238236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383199238","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8440729,0.0004924845,0.13114502,0.009412692,0.0018982091,0.0026558992,0.000012738157,0.003931206,0.0063788635],"genre_scores_gemma":[0.99248093,0.00048588827,0.0026366187,0.0030626992,0.00029734743,0.00010963276,0.000013160234,0.000033537315,0.0008801858],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981936,0.00003839838,0.00029472183,0.0005848527,0.0002430249,0.0006453586],"domain_scores_gemma":[0.99911946,0.00008808092,0.00007587851,0.00052819087,0.000026649133,0.00016176364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003105457,0.00015759535,0.00021950655,0.00012695367,0.00015728571,0.000027370439,0.0002831673,0.00006102713,0.000017748329],"category_scores_gemma":[0.000083351995,0.00015112541,0.0000749483,0.0028853032,0.00020244706,0.0001137128,0.0001479799,0.00039005594,0.000046961144],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006979808,0.00017948641,0.8596481,0.000023442086,0.0000016871306,0.00052191457,0.00003646736,0.054422587,0.0071617817,0.005692478,0.04977122,0.022471044],"study_design_scores_gemma":[0.00051733863,0.00020965104,0.66543466,0.0001025612,0.000011903578,0.00014841068,0.000008234993,0.23094237,0.00018848901,0.0040171137,0.0981334,0.0002858655],"about_ca_topic_score_codex":0.000007868085,"about_ca_topic_score_gemma":0.0000054222432,"teacher_disagreement_score":0.19421344,"about_ca_system_score_codex":0.000033335356,"about_ca_system_score_gemma":0.000050090406,"threshold_uncertainty_score":0.6162715},"labels":[],"label_agreement":null},{"id":"W4383217072","doi":"10.1093/braincomms/fcad195","title":"Longitudinal changes in hippocampal texture from healthy aging to Alzheimer’s disease","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital","funders":"Johnson and Johnson Pharmaceutical Research and Development; National Institute on Aging; Eisai Incorporated; Fonds de Recherche du Québec - Santé; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institutes of Health; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; DoD Alzheimer's Disease Neuroimaging Initiative; Pfizer; Biogen; BioClinica; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; Merck; Alzheimer's Drug Discovery Foundation; Janssen Alzheimer Immunotherapy Research And Development; AbbVie; Fujirebio Europe; Alzheimer's Association; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Hippocampal formation; Neuroimaging; Dementia; Neuroscience; Alzheimer's disease; Psychology; Neuropathology; Hippocampus; Cognitive decline; Atrophy; Cognition; Disease; Medicine; Pathology; Audiology","score_opus":0.2447787720848473,"score_gpt":0.451645994272378,"score_spread":0.2068672221875307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383217072","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08297447,0.0015814854,0.003014026,0.90888476,0.000047155732,0.0013786897,0.0002015832,0.0010603718,0.00085747615],"genre_scores_gemma":[0.96912956,0.0006263625,0.017545555,0.011197664,0.00008604303,0.0006598572,0.0005349297,0.00003575676,0.00018426348],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991035,0.000065122105,0.00018647249,0.00027821236,0.00012683145,0.0002398641],"domain_scores_gemma":[0.99735355,0.00042329825,0.000047356327,0.0018915707,0.000044254004,0.00023996276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015304102,0.00011438041,0.00016290828,0.00023059665,0.00020124503,0.000017821201,0.0004610028,0.00003389378,0.00002930076],"category_scores_gemma":[0.00016682116,0.00012016627,0.000042198368,0.0009329628,0.0000754935,0.000044808672,0.00039954603,0.00029240354,0.0001290034],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031372267,0.00156151,0.5110502,0.00010155924,0.00012426879,0.00014167956,0.0035296767,0.00029971602,0.008311553,0.031081408,0.24417333,0.19931133],"study_design_scores_gemma":[0.00050090963,0.00006465001,0.7515287,0.00021409953,0.00005650956,0.00000613512,0.00017857715,0.0037591998,0.00011822647,0.0077772406,0.2355746,0.00022119682],"about_ca_topic_score_codex":0.0001529878,"about_ca_topic_score_gemma":0.00041685606,"teacher_disagreement_score":0.8976871,"about_ca_system_score_codex":0.00005017017,"about_ca_system_score_gemma":0.00007126544,"threshold_uncertainty_score":0.49002382},"labels":[],"label_agreement":null},{"id":"W4383343678","doi":"10.3389/fnhum.2023.1196624","title":"Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks","year":2023,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Health Sciences Centre","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Atlas (anatomy); White matter; Medicine; Anatomy; Radiology; Magnetic resonance imaging","score_opus":0.033435169892414504,"score_gpt":0.29862613712141606,"score_spread":0.26519096722900154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383343678","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8430031,0.000009957481,0.1558044,0.00053502945,0.00014038781,0.000288537,0.0000066031594,0.00010953161,0.00010244477],"genre_scores_gemma":[0.9975278,0.000036692676,0.0012769017,0.00046303164,0.000057234007,0.00004271622,0.00005396403,0.000018729532,0.0005229341],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989051,0.00002490716,0.00027338808,0.00037779036,0.00019625694,0.00022254385],"domain_scores_gemma":[0.99955344,0.000011756581,0.00009405507,0.00023724664,0.00003924904,0.00006426932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009712855,0.00011110993,0.00019976309,0.00024394909,0.00017063726,0.00002315903,0.00012152028,0.000043300537,0.000012148856],"category_scores_gemma":[0.000024580318,0.00010958097,0.000037866437,0.0006471412,0.0002786615,0.000117247175,0.00009112098,0.00017269526,0.0000012514224],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008190356,0.00004323206,0.9184798,0.000023657432,0.0000011870005,0.000017276623,0.000023761577,0.00014414424,0.079394616,0.0005341818,0.0011589908,0.00017096283],"study_design_scores_gemma":[0.00023862997,0.000079340825,0.98974776,0.0000368596,0.000015731013,0.000014537272,0.00000938581,0.0076923138,0.00066743215,0.0005100062,0.0008972091,0.000090805544],"about_ca_topic_score_codex":0.0000017471565,"about_ca_topic_score_gemma":3.111492e-7,"teacher_disagreement_score":0.1545275,"about_ca_system_score_codex":0.000025407275,"about_ca_system_score_gemma":0.000011796364,"threshold_uncertainty_score":0.44685823},"labels":[],"label_agreement":null},{"id":"W4383497849","doi":"10.1016/j.neuroimage.2023.120248","title":"Randomized iterative spherical‐deconvolution informed tractogram filtering","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"National Institute of Mental Health","keywords":"Streamlines, streaklines, and pathlines; Deconvolution; Classifier (UML); Computer science; Tractography; Artificial intelligence; Scale-invariant feature transform; Pattern recognition (psychology); Diffusion MRI; Algorithm; Magnetic resonance imaging; Feature extraction; Physics","score_opus":0.09870090185074554,"score_gpt":0.3892425320522324,"score_spread":0.2905416302014869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383497849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7548425,0.00007878281,0.17184466,0.0119494805,0.00038821044,0.0047564693,0.000049937422,0.007037597,0.049052358],"genre_scores_gemma":[0.96634513,0.00034427553,0.027265146,0.0019957966,0.0001406703,0.00048738185,0.00012013807,0.00006288219,0.003238602],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989564,0.000044485758,0.00029666655,0.0002814714,0.00016074681,0.0002602663],"domain_scores_gemma":[0.99911356,0.00029648052,0.00008840276,0.00034050876,0.00005642491,0.00010463787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013967081,0.0001481807,0.00035359192,0.0001047575,0.00009812867,0.000035264195,0.000085469954,0.000041415715,0.00009322048],"category_scores_gemma":[0.0004366986,0.00012700388,0.00016558915,0.0005233072,0.00013471847,0.00016401026,0.00006076183,0.000241712,0.00020038114],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.03783431,0.0007744307,0.0030661316,0.0005660338,0.0001712882,0.000989211,0.0017980116,0.00026705716,0.7543383,0.008725134,0.07321563,0.11825442],"study_design_scores_gemma":[0.2893507,0.0008547199,0.06969966,0.00041141038,0.00041811235,0.00069890794,0.00022747995,0.082800485,0.084169894,0.012374336,0.4575875,0.0014068142],"about_ca_topic_score_codex":0.0000057480797,"about_ca_topic_score_gemma":5.5406997e-7,"teacher_disagreement_score":0.67016846,"about_ca_system_score_codex":0.000029310984,"about_ca_system_score_gemma":0.000034404417,"threshold_uncertainty_score":0.5179068},"labels":[],"label_agreement":null},{"id":"W4383987283","doi":"10.48550/arxiv.2307.03827","title":"Effect of Intensity Standardization on Deep Learning for WML Segmentation in Multi-Centre FLAIR MRI","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer Society Research Program; Alzheimer's Society; Government of Ontario","keywords":"Fluid-attenuated inversion recovery; Segmentation; Artificial intelligence; Normalization (sociology); Pattern recognition (psychology); Preprocessor; Computer science; Deep learning; Magnetic resonance imaging; Sørensen–Dice coefficient; Image segmentation; Medicine; Radiology","score_opus":0.1283769959695149,"score_gpt":0.2990233176373229,"score_spread":0.17064632166780802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383987283","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.382394,0.0000052233886,0.61610615,0.00009557392,0.00005735952,0.0010990193,0.00001850893,0.00018438678,0.000039784743],"genre_scores_gemma":[0.9959088,0.00017114008,0.0030491324,0.000026063435,0.000018863871,0.0000075605344,0.00026657697,0.0000329104,0.0005189295],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990626,0.00007194024,0.00016847078,0.00049337803,0.000058343005,0.0001452432],"domain_scores_gemma":[0.99910927,0.00018782717,0.00019968569,0.000299385,0.0001550438,0.000048780246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021649788,0.00016707114,0.00032947518,0.00024012996,0.00005766885,0.0000059123336,0.00010140811,0.00012716693,0.000004159835],"category_scores_gemma":[0.00016523489,0.00018242949,0.00013049837,0.00028666653,0.000048025173,0.000041592084,0.00014406719,0.000379384,0.0000055097785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017311849,0.00022289487,0.10786208,0.001037583,0.000072033276,0.00006872493,0.0002590225,0.8820347,0.0018813016,0.001581812,0.00016470124,0.0030839157],"study_design_scores_gemma":[0.0052150087,0.0009388414,0.01535683,0.0011720699,0.00041072367,0.0000026581477,0.00027677126,0.938283,0.034856156,0.0026947914,0.00038965404,0.00040344734],"about_ca_topic_score_codex":0.000037849008,"about_ca_topic_score_gemma":0.000025899453,"teacher_disagreement_score":0.61351484,"about_ca_system_score_codex":0.0002533089,"about_ca_system_score_gemma":0.0000309195,"threshold_uncertainty_score":0.74392587},"labels":[],"label_agreement":null},{"id":"W4384263540","doi":"10.48550/arxiv.2307.05786","title":"Merging multiple input descriptors and supervisors in a deep neural network for tractogram filtering","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Vetenskapsrådet; VINNOVA; Université de Sherbrooke","keywords":"Streamlines, streaklines, and pathlines; Tractography; Artificial intelligence; Computer science; Filter (signal processing); Task (project management); Artificial neural network; Pattern recognition (psychology); Diffusion MRI; Computer vision; Magnetic resonance imaging; Radiology; Physics; Engineering","score_opus":0.23522085090293102,"score_gpt":0.2702087456932591,"score_spread":0.03498789479032807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384263540","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80737895,0.00006561921,0.19076893,0.00025449702,0.00012835588,0.00093764934,0.00002103379,0.00040395962,0.000041033818],"genre_scores_gemma":[0.9863757,0.00031505132,0.01276573,0.00009921349,0.0000922423,0.000023920276,0.000073063435,0.000058621612,0.0001964953],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986872,0.00002634332,0.00019264987,0.0007048152,0.000038375823,0.0003506044],"domain_scores_gemma":[0.9991357,0.00017598795,0.00009561308,0.00042189035,0.000047163754,0.00012366885],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000113555354,0.00023386822,0.0003423479,0.00021444562,0.000106336935,0.000023646537,0.00018558734,0.00015301576,0.0000037989362],"category_scores_gemma":[0.000070837006,0.00027766783,0.00013388098,0.00038090214,0.00007547537,0.00008524136,0.00039834486,0.0005045485,0.0000017311129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042823603,0.00021177687,0.405464,0.00078009075,0.00010357851,0.00045976066,0.000561093,0.57973033,0.001320855,0.0045763394,0.00043718124,0.0059267334],"study_design_scores_gemma":[0.0010698675,0.000082264654,0.025231069,0.00029243372,0.00012906958,0.000011741379,0.00019103754,0.9597257,0.00013264902,0.011473611,0.0013078075,0.00035280135],"about_ca_topic_score_codex":0.00018392548,"about_ca_topic_score_gemma":0.00016025724,"teacher_disagreement_score":0.38023293,"about_ca_system_score_codex":0.000091845846,"about_ca_system_score_gemma":0.000025347274,"threshold_uncertainty_score":0.9999676},"labels":[],"label_agreement":null},{"id":"W4384662966","doi":"10.1161/strokeaha.123.043713","title":"White Matter Integrity and Chronic Poststroke Upper Limb Function: An ENIGMA Stroke Recovery Analysis","year":2023,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Genentech; Biogen; U.S. Department of Veterans Affairs","keywords":"Medicine; Corticospinal tract; Stroke (engine); Upper limb; Physical medicine and rehabilitation; White matter; Stroke recovery; Motor function; Chronic stroke; Rehabilitation; Physical therapy; Magnetic resonance imaging; Diffusion MRI; Radiology","score_opus":0.037850526328610704,"score_gpt":0.32934969164532285,"score_spread":0.29149916531671216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384662966","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96833545,0.00018991152,0.018468175,0.0067636278,0.00012460836,0.0004412881,0.00034421487,0.00078462047,0.004548119],"genre_scores_gemma":[0.968562,0.0002910063,0.0054493286,0.001053243,0.00030496577,0.000099544945,0.00029365704,0.00004335877,0.023902914],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986584,0.00003544455,0.0002486359,0.00051705755,0.00021066472,0.00032978677],"domain_scores_gemma":[0.9989581,0.000048337843,0.00007528512,0.00065687636,0.00008170637,0.00017965717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014106714,0.00019414876,0.0003249402,0.00044146925,0.00014627949,0.00004891494,0.000106604304,0.00010090711,0.0005457483],"category_scores_gemma":[0.000019118148,0.00017791503,0.00020772076,0.000645948,0.00009155516,0.00019035523,0.000095454474,0.00049175817,0.00016167351],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024928155,0.00013063452,0.96042687,0.00006485771,0.00045733165,0.000038210987,0.000069186164,0.00006420601,0.016971996,0.0005052173,0.010384198,0.010638002],"study_design_scores_gemma":[0.00056043454,0.00081968907,0.9630923,0.000027732716,0.00092060806,0.000057426852,0.00015555308,0.0021325515,0.0015457701,0.00061330356,0.029804766,0.00026983808],"about_ca_topic_score_codex":0.000028380919,"about_ca_topic_score_gemma":0.000037551417,"teacher_disagreement_score":0.019420566,"about_ca_system_score_codex":0.00008380134,"about_ca_system_score_gemma":0.0000573941,"threshold_uncertainty_score":0.72551644},"labels":[],"label_agreement":null},{"id":"W4384943329","doi":"10.1212/wnl.0000000000207543","title":"Microstructural Alterations in Tract Development in College Football and Volleyball Players","year":2023,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Football; Corpus callosum; Concussion; Superior longitudinal fasciculus; Medicine; Cingulum (brain); Psychology; Physical therapy; Physical medicine and rehabilitation; Poison control; Magnetic resonance imaging; Anatomy; Injury prevention; Radiology","score_opus":0.046859035886282846,"score_gpt":0.3331399991273095,"score_spread":0.2862809632410267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384943329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99291176,0.00001658181,0.00008301981,0.006245115,0.0000337374,0.0003256301,0.0000070176097,0.000097149925,0.00027996345],"genre_scores_gemma":[0.99558175,0.00003855648,0.0023153834,0.0018142695,0.000013030612,0.000085527325,0.000020400636,0.00001189208,0.00011919981],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993508,0.000018694014,0.00017810531,0.0002257746,0.000043913846,0.0001827512],"domain_scores_gemma":[0.9997492,0.00006531199,0.000023672797,0.00011067776,0.000011001253,0.00004014677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005278552,0.0000762062,0.0001340996,0.00020828511,0.000036628633,0.0000036330468,0.000043534885,0.000050560346,0.000008340974],"category_scores_gemma":[0.000022101181,0.00007541964,0.000011926294,0.00030013538,0.00004257155,0.000028123313,0.00003977454,0.00020826903,0.000008633158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009545716,0.00037918967,0.82823145,0.00009073071,0.00001569253,0.0021222192,0.001839758,0.00026075533,0.13502589,0.009459682,0.006770462,0.014849603],"study_design_scores_gemma":[0.0009841395,0.00017628481,0.97116894,0.000008659735,0.0000032820071,0.0002939875,0.0000132787,0.0015597037,0.0017832217,0.000969926,0.022956185,0.00008240799],"about_ca_topic_score_codex":0.000023675717,"about_ca_topic_score_gemma":0.00015803394,"teacher_disagreement_score":0.14293747,"about_ca_system_score_codex":0.00001737957,"about_ca_system_score_gemma":0.000040504605,"threshold_uncertainty_score":0.30755237},"labels":[],"label_agreement":null},{"id":"W4385191001","doi":"10.1016/j.neuroimage.2023.120288","title":"FIESTA: Autoencoders for accurate fiber segmentation in tractography","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institute on Aging; National Institutes of Health; Québec Consortium for Drug Discovery; Alliance de recherche numérique du Canada; Alzheimer's Disease Neuroimaging Initiative; Michael J. Fox Foundation for Parkinson's Research; McDonnell Center for Systems Neuroscience; U.S. Department of Defense","keywords":"Artificial intelligence; Bundle; Tractography; Computer science; Segmentation; Autoencoder; Human Connectome Project; Pattern recognition (psychology); Atlas (anatomy); Fiber bundle; Computer vision; Deep learning; Diffusion MRI; Geology; Magnetic resonance imaging","score_opus":0.12328774493107689,"score_gpt":0.41035526311576037,"score_spread":0.28706751818468346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385191001","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89681196,0.000041847845,0.065782875,0.021931676,0.0002164862,0.0046372064,0.00015404796,0.0028201796,0.007603704],"genre_scores_gemma":[0.92029536,0.00030543868,0.06901782,0.0035686826,0.00013021386,0.0013975638,0.0003557174,0.00012122409,0.0048079686],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992696,0.000012230482,0.00016722218,0.00025865782,0.00009214518,0.00020013083],"domain_scores_gemma":[0.9995466,0.0001145685,0.000044674052,0.00021771548,0.000030100633,0.000046361267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007546736,0.00009254585,0.00011882444,0.00020308988,0.000051347663,0.0000152077155,0.000059983857,0.0000292319,0.000027288208],"category_scores_gemma":[0.000063386935,0.00009159867,0.00007409552,0.00058036187,0.00003583423,0.0001110798,0.000019348181,0.00012746922,0.00004008257],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007149689,0.00091675395,0.0332271,0.00078079675,0.000046714573,0.0004985793,0.001129565,0.00207775,0.5964885,0.0026696199,0.20667776,0.15477192],"study_design_scores_gemma":[0.006006532,0.00074688473,0.60801536,0.00015870495,0.00011507532,0.00009175484,0.00030218688,0.033290263,0.045905236,0.011378165,0.29331094,0.00067890726],"about_ca_topic_score_codex":0.000004571925,"about_ca_topic_score_gemma":0.0000015764863,"teacher_disagreement_score":0.5747882,"about_ca_system_score_codex":0.000015076641,"about_ca_system_score_gemma":0.00001766376,"threshold_uncertainty_score":0.3735285},"labels":[],"label_agreement":null},{"id":"W4385230448","doi":"10.1111/ejn.16097","title":"Morphological alterations of contralesional hemisphere relate to functional outcomes after stroke","year":2023,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Health and Family Planning Commission of Sichuan Province; Shanghai Rising-Star Program; National Natural Science Foundation of China","keywords":"Gyrification; Precentral gyrus; Insula; Supplementary motor area; Psychology; Gyrus; Audiology; Functional magnetic resonance imaging; Physical medicine and rehabilitation; Neuroscience; Medicine; Magnetic resonance imaging; Cerebral cortex; Radiology","score_opus":0.09387910909969253,"score_gpt":0.3466624661524178,"score_spread":0.25278335705272525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385230448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96469337,0.000014225635,0.027780788,0.006451757,0.00018189514,0.00012245282,0.000022191072,0.000055880664,0.0006774639],"genre_scores_gemma":[0.98961276,0.000029229028,0.006610932,0.002168563,0.00005950809,0.0000030441813,0.0000010878362,0.0000128993815,0.0015019735],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989081,0.00006220403,0.0003803859,0.0001685143,0.0003347526,0.00014603166],"domain_scores_gemma":[0.9992773,0.000076862525,0.00015834595,0.0001766623,0.00014530214,0.00016551504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030623094,0.000083092586,0.00016672531,0.00011817339,0.000067365516,0.00001357548,0.00016455718,0.000009536841,0.000042057003],"category_scores_gemma":[0.0003658601,0.00006060864,0.00011196521,0.0003694897,0.00012368677,0.000096233554,0.00007852706,0.00021512092,0.000033281187],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001749164,0.0001529099,0.032322664,0.0000087598655,0.000005018874,0.0014083404,0.00005007451,0.0010977692,0.9569985,0.00037167128,0.006133711,0.0012756644],"study_design_scores_gemma":[0.00035339018,0.00032224358,0.9861964,0.000042620704,0.000015365398,0.00071327115,0.000009585212,0.00017637742,0.0020739362,0.00007922623,0.009959989,0.000057590387],"about_ca_topic_score_codex":1.1714904e-7,"about_ca_topic_score_gemma":4.053215e-8,"teacher_disagreement_score":0.9549246,"about_ca_system_score_codex":0.000011638941,"about_ca_system_score_gemma":0.00004023597,"threshold_uncertainty_score":0.24715485},"labels":[],"label_agreement":null},{"id":"W4385351255","doi":"10.1016/j.nicl.2023.103483","title":"Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Science and Technology Department of Zhejiang Province; National Institute of Mental Health; Agencia Estatal de Investigación; Engineering and Physical Sciences Research Council; National Institute on Aging; Narodowa Agencja Wymiany Akademickiej; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; Ministerio de Ciencia e Innovación; National Institute of Biomedical Imaging and Bioengineering; Ministerio de Ciencia, Innovación y Universidades; Ministry of Science and Technology of the People's Republic of China; Conselho Nacional de Desenvolvimento Científico e Tecnológico; National Natural Science Foundation of China; National Institutes of Health; Canada Research Chairs; University College London Hospitals NHS Foundation Trust; European Commission; National Institute of Dental and Craniofacial Research; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Deutsche Forschungsgemeinschaft","keywords":"False positive paradox; Chronic Migraine; Diffusion MRI; Artificial intelligence; Generalization; Migraine; White matter; Deep learning; Medicine; Psychology; Pattern recognition (psychology); Computer science; Statistics; Magnetic resonance imaging; Mathematics; Radiology; Internal medicine","score_opus":0.45927752470318695,"score_gpt":0.6082723008100177,"score_spread":0.14899477610683076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385351255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84754425,0.00005364366,0.14469011,0.003988392,0.00020404269,0.002816066,0.000022907083,0.00061084965,0.000069705005],"genre_scores_gemma":[0.8411814,0.0050997967,0.15019159,0.0009966075,0.00046031777,0.0012629253,0.00032702717,0.00008654726,0.0003938008],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997346,0.00024537637,0.0014896765,0.00054336345,0.00016953527,0.00020604112],"domain_scores_gemma":[0.99467903,0.004195779,0.0004291579,0.0003462863,0.0002839127,0.0000658556],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027457695,0.00013407493,0.00058313657,0.00014343363,0.000085653584,0.000008208259,0.000106404375,0.00012315664,0.000002922198],"category_scores_gemma":[0.007256121,0.00012537964,0.00030157308,0.0003218301,0.00019775874,0.00008864294,0.00009547489,0.00034461706,0.0000035019762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002185973,0.0017405079,0.6122999,0.0009855856,0.000071071816,0.000013692383,0.00027336655,0.000044623815,0.05075854,0.0017701637,0.0060661044,0.32379046],"study_design_scores_gemma":[0.008407136,0.0052605993,0.86237246,0.00039854523,0.0003052242,0.00001022898,0.0006178525,0.01466899,0.053760238,0.018444188,0.035245184,0.000509332],"about_ca_topic_score_codex":0.0000022423685,"about_ca_topic_score_gemma":0.0000016434063,"teacher_disagreement_score":0.32328114,"about_ca_system_score_codex":0.000026145282,"about_ca_system_score_gemma":0.000029223786,"threshold_uncertainty_score":0.86867785},"labels":[],"label_agreement":null},{"id":"W4385460989","doi":"10.3389/fninf.2023.1208073","title":"CACTUS: a computational framework for generating realistic white matter microstructure substrates","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre d'Imagerie BioMédicale; Université de Lausanne; Université de Genève; Hôpitaux Universitaires de Genève; École Polytechnique Fédérale de Lausanne; Centre Hospitalier Universitaire Vaudois; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Diffusion MRI; Computer science; Robustness (evolution); Bundle; Monte Carlo method; Microstructure; Biological system; Materials science; Magnetic resonance imaging; Mathematics; Composite material; Chemistry; Biology","score_opus":0.03961584959815493,"score_gpt":0.3331354017896845,"score_spread":0.29351955219152953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385460989","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07404726,0.000023756145,0.92112523,0.0028179975,0.00031948992,0.0008842066,0.00015118513,0.00030955573,0.00032130152],"genre_scores_gemma":[0.056131,0.000029019711,0.94034666,0.002536111,0.00008481305,0.00009802033,0.00044636562,0.00003976219,0.0002882453],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990503,0.000008394153,0.00038432115,0.00015739711,0.00013290721,0.00026665162],"domain_scores_gemma":[0.99940944,0.00010496827,0.00011806888,0.00024327244,0.000058920647,0.00006530568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007506459,0.000140924,0.00021588444,0.00019036222,0.00010796855,0.000042811975,0.00010479422,0.000073265175,0.000012539401],"category_scores_gemma":[0.000110862056,0.00013634254,0.00006045481,0.00040425413,0.000056996792,0.000105885374,0.000033965294,0.0002593998,0.000021909806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011887352,0.000066806606,0.22729449,0.0009279246,0.000035456014,0.00004307591,0.001817853,0.113274015,0.00036433284,0.005637372,0.6468748,0.0035450053],"study_design_scores_gemma":[0.00069098314,0.00008106692,0.053606343,0.00016976721,0.00003905241,0.00008338515,0.00044297185,0.853851,0.00022729834,0.08300207,0.0075429245,0.0002631452],"about_ca_topic_score_codex":8.465388e-7,"about_ca_topic_score_gemma":3.159218e-7,"teacher_disagreement_score":0.740577,"about_ca_system_score_codex":0.000037393645,"about_ca_system_score_gemma":0.00004100132,"threshold_uncertainty_score":0.5559887},"labels":[],"label_agreement":null},{"id":"W4385474130","doi":"10.48550/arxiv.2307.16421","title":"Wasserstein Mirror Gradient Flow as the limit of the Sinkhorn Algorithm","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Menzies School of Health Research; National Science Foundation","keywords":"Mathematics; Balanced flow; Wasserstein metric; Limit (mathematics); Flow (mathematics); Applied mathematics; Matrix norm; Mathematical analysis; Geometry; Eigenvalues and eigenvectors","score_opus":0.20654598876679478,"score_gpt":0.2640116044227801,"score_spread":0.05746561565598532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385474130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86410403,0.000108382956,0.11478001,0.011609897,0.0009550949,0.003643814,0.00027630944,0.0010843913,0.003438052],"genre_scores_gemma":[0.98578864,0.0004660848,0.004041411,0.00038180043,0.000055005217,0.000009263327,0.000033921242,0.00005250071,0.009171341],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885505,0.00006181181,0.00018895911,0.0005624502,0.000111312314,0.00022042955],"domain_scores_gemma":[0.9979117,0.00010748862,0.00022709696,0.0015303026,0.00013921995,0.00008421593],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013311012,0.0002190886,0.0002805378,0.00009896389,0.00017186413,0.000013225842,0.00070107786,0.00014380661,0.000017280225],"category_scores_gemma":[0.000057675603,0.000153256,0.0003436289,0.00056388933,0.00023140018,0.00003057271,0.00092480576,0.00071643747,0.000048795187],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018330811,0.0069008362,0.06420966,0.004275849,0.004531856,0.0047442853,0.009428906,0.18136573,0.016522333,0.5185957,0.07315162,0.114440165],"study_design_scores_gemma":[0.0025057697,0.0005354011,0.055852022,0.001798609,0.002976088,0.00014027898,0.002341361,0.56079143,0.0143310325,0.29162535,0.06563293,0.0014697416],"about_ca_topic_score_codex":0.00017964261,"about_ca_topic_score_gemma":0.00003503249,"teacher_disagreement_score":0.3794257,"about_ca_system_score_codex":0.00011909251,"about_ca_system_score_gemma":0.0001212657,"threshold_uncertainty_score":0.6249598},"labels":[],"label_agreement":null},{"id":"W4385497248","doi":"10.3389/fninf.2023.1197330","title":"Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Michael's Hospital; University of Toronto; Sunnybrook Health Science Centre; Health Sciences Centre; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer's Society; Government of Ontario","keywords":"Artificial intelligence; Pattern recognition (psychology); Fractional anisotropy; Fluid-attenuated inversion recovery; Diffusion MRI; Computer science; Similarity (geometry); Mean squared error; Neuroimaging; Mathematics; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Medicine; Statistics; Biology; Image (mathematics); Radiology; Neuroscience","score_opus":0.02870131174365778,"score_gpt":0.2852937493741453,"score_spread":0.25659243763048756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385497248","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3704064,0.00009354209,0.62619585,0.0005855414,0.0007271459,0.0008610768,0.00016214662,0.00038736404,0.0005809325],"genre_scores_gemma":[0.2906286,0.0015365741,0.70641536,0.00052587996,0.0002855656,0.000072481824,0.0002935544,0.00008764315,0.00015431902],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986392,0.000036341928,0.00058662985,0.00019869293,0.00025262253,0.00028647447],"domain_scores_gemma":[0.99900365,0.00014617396,0.00022922012,0.00046603274,0.000062238345,0.0000926754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010207184,0.00018732884,0.00044343382,0.00029723902,0.000097919044,0.00001543067,0.00018092743,0.000103505496,0.000008343476],"category_scores_gemma":[0.00014114895,0.00017814558,0.000106524305,0.0007468455,0.0001303428,0.00018335569,0.00013708584,0.00028281342,0.0000054258694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001569675,0.001067057,0.27401987,0.00080619205,0.0004978531,0.00040832703,0.0048869825,0.123344384,0.014062877,0.0015433787,0.4567053,0.1210881],"study_design_scores_gemma":[0.0006119878,0.000042701628,0.0030356129,0.00016197891,0.00008328599,0.000006440641,0.0003264464,0.9865924,0.004039385,0.0014743492,0.0034671002,0.00015830967],"about_ca_topic_score_codex":0.000021388332,"about_ca_topic_score_gemma":0.000001309908,"teacher_disagreement_score":0.863248,"about_ca_system_score_codex":0.000066678826,"about_ca_system_score_gemma":0.00005445241,"threshold_uncertainty_score":0.72645664},"labels":[],"label_agreement":null},{"id":"W4385502630","doi":"10.48550/arxiv.2108.03827","title":"Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Multiple sclerosis; Spinal cord; Diffusion MRI; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.22780760721992005,"score_gpt":0.2714940281932386,"score_spread":0.04368642097331854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385502630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9426354,0.00011276863,0.056129765,0.0001747798,0.00007592697,0.0005392344,0.00001574804,0.00009173303,0.00022460814],"genre_scores_gemma":[0.99830306,0.00025657468,0.0012149897,0.000054886685,0.0000406868,0.000008519434,0.000048411406,0.000022908154,0.000049955248],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99862605,0.00023920689,0.00024346655,0.00058097043,0.00013276102,0.00017751862],"domain_scores_gemma":[0.9984872,0.00034043935,0.00024018288,0.00064437214,0.000215725,0.00007213355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039416496,0.00021264191,0.00039937702,0.00012016538,0.00012197992,0.000023076247,0.00033474586,0.00014761525,0.0000049007817],"category_scores_gemma":[0.00021804938,0.00018886228,0.00018356495,0.00036314572,0.0002684452,0.00006753041,0.00062554417,0.00074973796,7.0618694e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0064704753,0.001310822,0.8517872,0.0037113526,0.00020852228,0.00062174746,0.00067449635,0.052082118,0.01314975,0.06842951,0.00007296875,0.0014810415],"study_design_scores_gemma":[0.0017236186,0.00028355827,0.9362915,0.006940656,0.00027274678,0.000042002044,0.00096269295,0.033560272,0.0065442715,0.012795833,0.00012212808,0.00046068028],"about_ca_topic_score_codex":0.00086100464,"about_ca_topic_score_gemma":0.00010708852,"teacher_disagreement_score":0.08450434,"about_ca_system_score_codex":0.00016490878,"about_ca_system_score_gemma":0.0001340627,"threshold_uncertainty_score":0.770158},"labels":[],"label_agreement":null},{"id":"W4385544898","doi":"10.58530/2022/3044","title":"The value of diffusion kurtosis imaging in detecting delayed brain development of premature infants","year":2023,"lang":"en","type":"article","venue":"Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Kurtosis; Internal capsule; Diffusion MRI; White matter; Brain development; Medicine; Neuroscience; Magnetic resonance imaging; Radiology; Psychology; Mathematics; Statistics","score_opus":0.02677539768738765,"score_gpt":0.3046242485238211,"score_spread":0.27784885083643346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385544898","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9782778,0.0032427437,0.000050100603,0.01458545,0.0008516243,0.0017573993,0.00006215017,0.00006854251,0.0011042149],"genre_scores_gemma":[0.9798537,0.001353649,0.015725102,0.000455581,0.0003061186,0.00063888036,0.00009513931,0.00005739808,0.0015144562],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99442345,0.000015325486,0.0019322315,0.0012107706,0.0017765873,0.0006416439],"domain_scores_gemma":[0.99586475,0.0012141092,0.0010935158,0.00023474902,0.0014700181,0.00012282957],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0074936217,0.0004102871,0.0006598126,0.00049336633,0.0008387486,0.00015383231,0.0007696127,0.00019387959,0.00000816728],"category_scores_gemma":[0.004259385,0.00030852703,0.00035863084,0.0018342803,0.0019430297,0.00028168102,0.00031835868,0.0005323833,3.9450745e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009244671,0.00039513607,0.047948133,0.0018188589,0.00005134327,0.0000014098928,0.026101312,0.0001180604,0.80016917,0.007326,0.05099624,0.06414987],"study_design_scores_gemma":[0.01869017,0.0017229988,0.37049928,0.0678278,0.0003398489,0.00012534074,0.069721736,0.24823382,0.057705477,0.040941015,0.122560866,0.0016316416],"about_ca_topic_score_codex":0.00014874792,"about_ca_topic_score_gemma":0.00005757067,"teacher_disagreement_score":0.7424637,"about_ca_system_score_codex":0.00033679596,"about_ca_system_score_gemma":0.00020887663,"threshold_uncertainty_score":0.9999367},"labels":[],"label_agreement":null},{"id":"W4385576122","doi":"10.1162/netn_a_00330","title":"The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts","year":2023,"lang":"en","type":"article","venue":"Network Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Canadian Institutes of Health Research; Hospital for Sick Children; Fondation Brain Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"White matter; Myelin; Neuroscience; Connectome; Diffusion MRI; Fractional anisotropy; Niche; Grey matter; Biology; Psychology; Central nervous system; Functional connectivity; Medicine; Magnetic resonance imaging","score_opus":0.0908628506769586,"score_gpt":0.35195213523566127,"score_spread":0.2610892845587027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385576122","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9849635,0.000053627773,0.0015186421,0.012499564,0.00017016203,0.0003832309,0.000025745114,0.00011155993,0.00027398905],"genre_scores_gemma":[0.99357706,0.000042065683,0.00010548384,0.0037285297,0.00011253059,0.000058593218,0.000010119995,0.000013473259,0.0023521306],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988319,0.000038516435,0.00025058066,0.00031784465,0.00027496062,0.00028618475],"domain_scores_gemma":[0.99911344,0.0003512308,0.00010816884,0.00028985267,0.00006288287,0.00007442994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033203728,0.000106064115,0.00011914052,0.000026518426,0.0008499063,0.000059468384,0.00019672416,0.000031121097,0.000017259903],"category_scores_gemma":[0.00007865338,0.00006299037,0.000045939196,0.0004794589,0.00076854305,0.000068231086,0.00013035303,0.00024618022,0.000004653681],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005663994,0.000066161636,0.75227576,0.000013167683,0.000004755025,0.000012341893,0.00006614331,0.00033845246,0.17579477,0.0031698954,0.06741206,0.0007898767],"study_design_scores_gemma":[0.00024055228,0.00009094912,0.97823346,0.000014360894,0.0000053468543,0.0001531345,0.000007910605,0.004280747,0.0007704127,0.001108573,0.015026249,0.00006829484],"about_ca_topic_score_codex":0.000003922641,"about_ca_topic_score_gemma":0.0000015189117,"teacher_disagreement_score":0.22595772,"about_ca_system_score_codex":0.000011392503,"about_ca_system_score_gemma":0.000020329928,"threshold_uncertainty_score":0.6536878},"labels":[],"label_agreement":null},{"id":"W4385728533","doi":"10.3389/fninf.2023.1191200","title":"versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Computer science; Fractional anisotropy; Artificial intelligence; Robustness (evolution); Image processing; Data mining; Computer vision; Magnetic resonance imaging; Medicine","score_opus":0.042022900369578196,"score_gpt":0.32039168386747907,"score_spread":0.2783687834979009,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385728533","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13499491,0.000027735516,0.8588588,0.0030094374,0.000069449736,0.0027914941,0.00004834399,0.00011212156,0.00008767408],"genre_scores_gemma":[0.9283881,0.00010842703,0.070640616,0.00043437883,0.00003337755,0.00026181745,0.000047049478,0.000021496946,0.000064726744],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991929,0.000030410534,0.00031218736,0.00014010498,0.0001609452,0.00016347936],"domain_scores_gemma":[0.99923086,0.00010880555,0.00013856444,0.00040486766,0.00007411742,0.000042794305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004976529,0.00008679568,0.0001418089,0.00008704263,0.00015932944,0.000009592593,0.00015418824,0.000030367326,2.6250066e-7],"category_scores_gemma":[0.00055039424,0.000059762653,0.000029346607,0.0005967639,0.000046334077,0.00010953452,0.00015474553,0.00015194164,6.1992745e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033988738,0.0016815544,0.12649488,0.0077162147,0.000088060115,0.0000066950033,0.043496504,0.04418774,0.17698266,0.0065731644,0.15537468,0.43399897],"study_design_scores_gemma":[0.00049449387,0.000042040163,0.00702273,0.00010675851,0.000037633225,0.0000033816386,0.0005139848,0.9813095,0.0022829368,0.0005477343,0.007579777,0.00005905367],"about_ca_topic_score_codex":0.0000030167153,"about_ca_topic_score_gemma":0.0000012907094,"teacher_disagreement_score":0.93712175,"about_ca_system_score_codex":0.00005901074,"about_ca_system_score_gemma":0.000058270663,"threshold_uncertainty_score":0.24370502},"labels":[],"label_agreement":null},{"id":"W4385760990","doi":"10.1162/imag_a_00011","title":"RELIEF: A structured multivariate approach for removal of latent inter-scanner effects","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; University of Toronto","funders":"National Institute of Mental Health; Centre for Addiction and Mental Health Foundation; Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada","keywords":"Scanner; Computer science; Generalizability theory; Harmonization; Univariate; Multivariate statistics; Artificial intelligence; Data mining; Machine learning; Context (archaeology); Data science; Statistics; Mathematics; Geography","score_opus":0.05939705709650033,"score_gpt":0.3652103886801835,"score_spread":0.3058133315836832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385760990","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1364333,0.000043006898,0.8566584,0.0029961632,0.0003916135,0.0018348449,0.000033855285,0.0009906258,0.0006181887],"genre_scores_gemma":[0.9041364,0.000011969755,0.09431556,0.00080570334,0.000037664173,0.00010612071,0.000011124126,0.000029043733,0.00054641144],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889356,0.000016916201,0.00019359741,0.00044925636,0.00017384095,0.00027282175],"domain_scores_gemma":[0.999272,0.00008210862,0.00009678,0.00039527623,0.00007440127,0.00007943812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013938993,0.00012037407,0.00018507868,0.00014767292,0.000095390365,0.000017361028,0.00020243405,0.000017941855,6.6584977e-7],"category_scores_gemma":[0.00037518857,0.00010162647,0.00008133419,0.0006165281,0.00018954968,0.0000878519,0.0001100608,0.00013114086,0.0000015242723],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038594735,0.000070852286,0.002524991,0.00014977549,0.0000016225205,0.00004842394,0.00007374743,0.00021842064,0.98257047,0.000980531,0.0011966323,0.012125954],"study_design_scores_gemma":[0.0019742274,0.00030513873,0.127691,0.00020902719,0.000078640776,0.0008224611,0.000020712463,0.6265545,0.2159643,0.004057451,0.021936253,0.00038630544],"about_ca_topic_score_codex":0.000009307189,"about_ca_topic_score_gemma":6.0893015e-8,"teacher_disagreement_score":0.7677031,"about_ca_system_score_codex":0.000018917854,"about_ca_system_score_gemma":0.000033489483,"threshold_uncertainty_score":0.41442072},"labels":[],"label_agreement":null},{"id":"W4385829186","doi":"10.1101/2023.08.13.553149","title":"The Spatial Patterns and Determinants of Cerebrospinal Fluid Circulation in the Human Brain","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Centre for Addiction and Mental Health","funders":"Center for High Performance Computing; National Institutes of Health","keywords":"Circulation (fluid dynamics); Cerebrospinal fluid; Human brain; Geography; Neuroscience; Psychology; Mechanics; Physics","score_opus":0.05410492567857453,"score_gpt":0.32076372476245885,"score_spread":0.26665879908388435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385829186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943474,0.000085714986,0.0027715089,0.0015123159,0.00009461573,0.00097526144,0.00006953716,0.00014186052,0.0000018015372],"genre_scores_gemma":[0.99860233,0.0001370861,0.00060764875,0.00017780482,0.00014737884,0.00026803944,4.803165e-7,0.000056620887,0.0000026084795],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99855703,0.00008208353,0.000426262,0.00044864247,0.00025012039,0.00023585508],"domain_scores_gemma":[0.99844754,0.00012939029,0.00027252818,0.0009740171,0.00012114165,0.00005541034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052944454,0.0002181751,0.0002904291,0.00011170989,0.000185016,0.00005700932,0.00029993313,0.0001447555,0.0000021634398],"category_scores_gemma":[0.00015256047,0.00015914375,0.00006825008,0.00020792046,0.00014154802,0.00003568165,0.00023708501,0.0004778787,0.000002300561],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017459914,0.00008465079,0.6868175,0.00035683005,0.000018534833,0.000035027788,0.000020749945,0.000009429757,0.31175122,0.00076007604,0.00009628695,0.000032195934],"study_design_scores_gemma":[0.0002564725,0.000046613495,0.9798181,0.00040582716,0.000041882737,8.500324e-8,0.00000362184,0.0008407073,0.018005455,0.00004062912,0.00039079622,0.00014983212],"about_ca_topic_score_codex":0.00026946052,"about_ca_topic_score_gemma":0.000034541652,"teacher_disagreement_score":0.29374576,"about_ca_system_score_codex":0.00005747894,"about_ca_system_score_gemma":0.000093158174,"threshold_uncertainty_score":0.64896935},"labels":[],"label_agreement":null},{"id":"W4385897358","doi":"10.1002/jmri.28964","title":"Probing Evidence of Cerebral White Matter Microstructural Disruptions in Ischemic Heart Disease Before and Following Cardiac Rehabilitation: A Diffusion Tensor <scp>MR</scp> Imaging Study","year":2023,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Lawson Health Research Institute; Western University","funders":"Canadian Institutes of Health Research; Heart and Stroke Foundation of Canada","keywords":"Fractional anisotropy; Medicine; White matter; Diffusion MRI; Cardiology; Internal medicine; Population; Disease; Magnetic resonance imaging; Radiology","score_opus":0.01711768691857494,"score_gpt":0.32055421633645953,"score_spread":0.30343652941788457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385897358","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9859641,0.0053108437,0.00011708348,0.00763522,0.00009024644,0.0007964336,0.000007214437,0.000059384052,0.000019462635],"genre_scores_gemma":[0.98818445,0.00008220643,0.011203501,0.00021254044,0.00008236,0.000052235777,0.00000192544,0.00004467387,0.00013608813],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99812084,0.00008717625,0.00073909515,0.000341448,0.0003820044,0.0003294107],"domain_scores_gemma":[0.9987299,0.00032981657,0.0002763497,0.0003421799,0.00016873934,0.00015302742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051207456,0.00019771955,0.00045939116,0.0003691805,0.00011771974,0.000052208426,0.00014252325,0.00001969369,0.0000055980217],"category_scores_gemma":[0.00050317356,0.00017219273,0.00018766201,0.00062505313,0.00015287964,0.00047473257,0.00014737225,0.00036564458,0.0000027384826],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041855983,0.000074805765,0.96769804,0.00014629374,0.0000035243056,0.00008736035,0.001587972,0.000012232426,0.024627259,0.0000027902634,0.0010586516,0.004659226],"study_design_scores_gemma":[0.00090082234,0.00019016497,0.9918274,0.0019698916,0.000106493404,0.00014723247,0.0022082275,0.0013906434,0.000097645934,0.00034951835,0.0007374787,0.00007445967],"about_ca_topic_score_codex":0.000017044367,"about_ca_topic_score_gemma":0.0000017960868,"teacher_disagreement_score":0.024529614,"about_ca_system_score_codex":0.00007982097,"about_ca_system_score_gemma":0.000075356584,"threshold_uncertainty_score":0.7021816},"labels":[],"label_agreement":null},{"id":"W4385970839","doi":"10.1093/braincomms/fcad225","title":"Neuroimaging, clinical and life course correlates of normal-appearing white matter integrity in 70-year-olds","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Avid Radiopharmaceuticals; Alzheimer’s Research UK; Wolfson Foundation; Dementias Platform UK; University College London; UK Dementia Research Institute; National Institute for Health and Care Research; California State University, Bakersfield; Brain Research UK; Alzheimer's Society; Weston Brain Institute; Eli Lilly and Company; Alzheimer's Association","keywords":"Fractional anisotropy; White matter; Brain size; Diffusion MRI; Cardiology; Medicine; Internal medicine; Psychology; Magnetic resonance imaging; Radiology","score_opus":0.12804861734077327,"score_gpt":0.4265769917215861,"score_spread":0.2985283743808128,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385970839","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8106352,0.00044061104,0.0016876851,0.1764822,0.000066082706,0.00086295774,0.000039577128,0.0005102589,0.009275438],"genre_scores_gemma":[0.9863693,0.0009404494,0.010135638,0.001839243,0.000019263338,0.000062643376,0.000050493993,0.000027304006,0.00055564736],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99891376,0.00011913461,0.0004813847,0.00022058113,0.00009460627,0.00017050133],"domain_scores_gemma":[0.99767774,0.0005864418,0.00012010451,0.0014373298,0.00007230913,0.00010607527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005252259,0.00010328609,0.0002481386,0.00014438349,0.00009669151,0.000014470241,0.00035577687,0.00006872644,0.000030152789],"category_scores_gemma":[0.00038476993,0.00010618391,0.00006323943,0.0005031384,0.0004599261,0.00008687564,0.00055367046,0.0007283053,0.00005706062],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010650967,0.00016057448,0.98471737,0.000025218473,0.000009103145,0.0000020100147,0.00014796697,0.000007153853,0.00013657377,0.002824125,0.010752462,0.0012068022],"study_design_scores_gemma":[0.0004847508,0.000033635133,0.9827985,0.00012252633,0.000029199418,0.000016614844,0.0001644069,0.00605328,0.000021840968,0.0014767312,0.00870794,0.0000905391],"about_ca_topic_score_codex":0.000043334596,"about_ca_topic_score_gemma":0.00002339562,"teacher_disagreement_score":0.17573413,"about_ca_system_score_codex":0.00000896576,"about_ca_system_score_gemma":0.00006423354,"threshold_uncertainty_score":0.43300542},"labels":[],"label_agreement":null},{"id":"W4386057060","doi":"10.1016/j.dib.2023.109513","title":"A population-averaged structural connectomic brain atlas dataset from 422 HCP-aging subjects","year":2023,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Concordia University","funders":"Alliance de recherche numérique du Canada","keywords":"Diffusion MRI; Human Connectome Project; Connectome; White matter; Connectomics; Population; Spatial normalization; Neuroscience; Deep brain stimulation; Neuroinformatics; Segmentation; Atlas (anatomy); Artificial intelligence; Brain atlas; Computer science; Brain mapping; Medicine; Voxel; Magnetic resonance imaging; Psychology; Pathology; Parkinson's disease; Functional connectivity; Anatomy","score_opus":0.10906075944420866,"score_gpt":0.4016066765765479,"score_spread":0.29254591713233924,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386057060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9655093,0.00003852463,0.0008539004,0.005546317,0.000079684876,0.000484817,0.026977455,0.00046437216,0.00004565922],"genre_scores_gemma":[0.7581501,0.000024530602,0.0039004204,0.0015044071,0.00011338884,0.000022945595,0.2362112,0.000027351229,0.00004564089],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9987556,0.000038625505,0.00025264247,0.000545073,0.00016707163,0.000241013],"domain_scores_gemma":[0.99804145,0.0002888192,0.00007093511,0.001511683,0.000012638737,0.000074453594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017178514,0.00013173617,0.00021986935,0.00012984443,0.00009112494,0.000034408895,0.00038556807,0.000043042313,0.000099775716],"category_scores_gemma":[0.00035604264,0.0001326142,0.00001898927,0.00042773833,0.000040435487,0.00027036172,0.00041255835,0.00025423517,0.00006534235],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013602461,0.00007479475,0.34383416,0.00009143139,0.00004832149,0.00044710442,0.00022558379,0.000105713334,0.023945542,0.0022489296,0.6166978,0.01214458],"study_design_scores_gemma":[0.0015994903,0.000028148248,0.83310294,0.00012870315,0.000036150497,0.000048354163,0.000042702784,0.024684321,0.0010602506,0.005881539,0.13309586,0.00029155152],"about_ca_topic_score_codex":0.0028357592,"about_ca_topic_score_gemma":0.00027247026,"teacher_disagreement_score":0.48926878,"about_ca_system_score_codex":0.00004347767,"about_ca_system_score_gemma":0.00002766816,"threshold_uncertainty_score":0.54078496},"labels":[],"label_agreement":null},{"id":"W4386070150","doi":"10.1101/2023.08.21.554083","title":"Multimodal Imaging Investigation of Rich Club Alterations in Alzheimer’s Disease and Mild Cognitive Impairment: Amyloid Deposition, Structural Atrophy, and Functional Activation Differences","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; BioClinica; F. Hoffmann-La Roche; University of Southern California; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Atrophy; Neuroscience; Disease; Neuroimaging; White matter; Psychology; Diffusion MRI; Grey matter; Pathology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.045014613908132474,"score_gpt":0.2864632776217589,"score_spread":0.24144866371362642,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386070150","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98977065,0.00039331536,0.0067924103,0.0012831378,0.00008271817,0.0011979414,0.00026814948,0.00021119506,5.0541513e-7],"genre_scores_gemma":[0.9904914,0.00020415022,0.008528873,0.00017333058,0.00012332448,0.00041281912,0.000014948775,0.000050433635,7.2991975e-7],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984498,0.00006549498,0.00040915798,0.0006442607,0.00023060448,0.00020069334],"domain_scores_gemma":[0.9988048,0.00011153839,0.00028385097,0.00028075042,0.0003256227,0.0001934305],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000110353234,0.00028830356,0.00031234327,0.00033353374,0.00016324855,0.000064877146,0.00006105379,0.000100710284,0.000004073111],"category_scores_gemma":[0.00008681049,0.00030186013,0.00004662413,0.00032902652,0.00023579135,0.00020720118,0.00017401829,0.00039162408,9.569868e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002481851,0.00008605464,0.7206235,0.00037643133,0.00011694446,0.000014854382,0.00005303379,0.00006192833,0.27781987,0.0005318256,0.00005152325,0.000015848329],"study_design_scores_gemma":[0.0007001926,0.00003765131,0.9400402,0.0007607633,0.00024770256,8.3981554e-8,0.000009064898,0.010297368,0.04752228,0.00014240705,0.0000015145762,0.00024079808],"about_ca_topic_score_codex":0.000107164255,"about_ca_topic_score_gemma":0.0000027817032,"teacher_disagreement_score":0.2302976,"about_ca_system_score_codex":0.00008197796,"about_ca_system_score_gemma":0.00020105967,"threshold_uncertainty_score":0.9999434},"labels":[],"label_agreement":null},{"id":"W4386116634","doi":"10.1002/hbm.26461","title":"Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion <scp>MRI</scp>","year":2023,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; McGill University; Montreal Neurological Institute and Hospital; Western University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Canadian Open Neuroscience Platform; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampus; Diffusion MRI; In vivo; Neuroscience; Microstructure; Diffusion; Nuclear magnetic resonance; Magnetic resonance imaging; Chemistry; Psychology; Biology; Medicine; Physics; Crystallography; Radiology","score_opus":0.058902106859095804,"score_gpt":0.32545130136221667,"score_spread":0.26654919450312087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386116634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9958134,0.00010773911,0.0007085423,0.0020925177,0.00005199011,0.0007389363,0.00001915183,0.00015331012,0.00031436057],"genre_scores_gemma":[0.9970546,0.000020987009,0.0010569913,0.001164257,0.00010541686,0.000022381815,0.000013971384,0.00004175742,0.00051968027],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987039,0.000068156056,0.00035025348,0.0003568103,0.00019732365,0.0003235519],"domain_scores_gemma":[0.99895567,0.00017167168,0.00020627455,0.00057414046,0.00004300763,0.00004925634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026167606,0.00019798886,0.00026319313,0.00019933922,0.00071582844,0.000036300073,0.00025889257,0.00010174604,0.000008647434],"category_scores_gemma":[0.0001250244,0.00013237218,0.00008800578,0.00081886596,0.0003071361,0.00005146057,0.0003530033,0.00048085564,6.608135e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010946723,0.000009300993,0.019596623,0.00012157401,0.000007883902,0.000007727136,0.0022282696,0.000048940477,0.9743395,0.0010333207,0.0023440872,0.00026166916],"study_design_scores_gemma":[0.00086959073,0.000027978096,0.90417033,0.00084974413,0.000023577773,0.00017248251,0.0025615278,0.0016581755,0.007031997,0.062367775,0.020136857,0.00012993137],"about_ca_topic_score_codex":0.0000415071,"about_ca_topic_score_gemma":0.000018978422,"teacher_disagreement_score":0.9673075,"about_ca_system_score_codex":0.000049592378,"about_ca_system_score_gemma":0.000021947748,"threshold_uncertainty_score":0.5505646},"labels":[],"label_agreement":null},{"id":"W4386133788","doi":"10.1016/j.bandl.2023.105300","title":"Treatment-induced neuroplasticity after anomia therapy in post-stroke aphasia: A systematic review of neuroimaging studies","year":2023,"lang":"en","type":"review","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Hôpital du Sacré-Cœur de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Heart and Stroke Foundation of Canada","keywords":"Aphasia; Neuroimaging; Supramarginal gyrus; Psychology; MEDLINE; CINAHL; PsycINFO; Stroke (engine); Neuroplasticity; Neurorehabilitation; Meta-analysis; Physical medicine and rehabilitation; Rehabilitation; Clinical psychology; Functional magnetic resonance imaging; Medicine; Psychiatry; Neuroscience; Psychological intervention; Internal medicine","score_opus":0.12666905364009645,"score_gpt":0.43671730503225054,"score_spread":0.3100482513921541,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386133788","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00069395825,0.9951612,0.000008194457,0.0003151123,0.00002503145,0.0034998918,0.00011325418,0.00013178811,0.000051567335],"genre_scores_gemma":[0.00017476713,0.99706954,0.00016132147,0.0009002095,0.000036431535,0.0010864408,0.000034146833,0.00007161375,0.00046555066],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99838424,0.00019026054,0.0006939536,0.0004076145,0.00012620066,0.0001977561],"domain_scores_gemma":[0.9984551,0.000633887,0.00029652537,0.0005055364,0.000046846017,0.00006210429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016303519,0.00035740982,0.0024199833,0.00024452756,0.00002587837,0.000009571136,0.000094889256,0.000062476865,0.000006115631],"category_scores_gemma":[0.00056865107,0.00023213164,0.00029737118,0.00032486764,0.000056821085,0.0000319368,0.000063402236,0.00022650302,0.0000069134912],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011687568,0.000081488964,0.0000064641354,0.8979345,0.0001540452,0.00082489534,0.00022707247,3.832922e-9,0.00013690126,0.000012650687,0.00003578233,0.100574516],"study_design_scores_gemma":[0.00082073134,0.0005607271,0.00004531515,0.97475445,0.0019535548,0.0010014733,0.00019735032,0.0000062327886,0.000026868953,0.0000068803265,0.020268124,0.00035830424],"about_ca_topic_score_codex":0.000016548114,"about_ca_topic_score_gemma":0.000004804843,"teacher_disagreement_score":0.10021621,"about_ca_system_score_codex":0.00005311084,"about_ca_system_score_gemma":0.000072375144,"threshold_uncertainty_score":0.9466054},"labels":[],"label_agreement":null},{"id":"W4386243593","doi":"10.1101/2023.08.28.555179","title":"Mapping caudolenticular gray matter bridges in the human brain striatum through diffusion magnetic resonance imaging and tractography","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Diffusion MRI; Putamen; White matter; Human brain; Caudate nucleus; Magnetic resonance imaging; Striatum; Nuclear magnetic resonance; Fractional anisotropy; Computer science; Physics; Artificial intelligence; Neuroscience; Psychology; Medicine; Radiology","score_opus":0.03394549049788514,"score_gpt":0.28610593598965606,"score_spread":0.2521604454917709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386243593","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9769584,0.0045067966,0.0050053555,0.010885115,0.00017895867,0.0017805032,0.00010303618,0.00057118176,0.0000106300895],"genre_scores_gemma":[0.9895973,0.00086589134,0.006485334,0.002200959,0.00020776698,0.00048378285,0.0000017507263,0.00014414743,0.0000130314775],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99743956,0.00013425069,0.00053020526,0.0010390097,0.000359081,0.00049787626],"domain_scores_gemma":[0.9980717,0.00012241042,0.00024262305,0.0013493156,0.00011520727,0.00009878901],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049342134,0.0004608564,0.00049523404,0.0003468023,0.00023870483,0.00017040544,0.00039612682,0.00018700703,0.000010838571],"category_scores_gemma":[0.000086612985,0.00040496886,0.00015100639,0.00074114697,0.00021952798,0.00011334303,0.00039484684,0.0011211325,0.000013194981],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014333645,0.00025239857,0.45352376,0.000595614,0.00001755396,0.0003020933,0.000104727624,0.000003318129,0.5402434,0.0007053938,0.004214011,0.000023407101],"study_design_scores_gemma":[0.0005700978,0.000026127309,0.97677404,0.0012741764,0.00006363323,3.3777545e-7,0.000025984875,0.0002128479,0.00546452,0.00010120357,0.015068378,0.00041862996],"about_ca_topic_score_codex":0.00017548523,"about_ca_topic_score_gemma":0.0000032930736,"teacher_disagreement_score":0.5347789,"about_ca_system_score_codex":0.00008049049,"about_ca_system_score_gemma":0.00006395311,"threshold_uncertainty_score":0.9998402},"labels":[],"label_agreement":null},{"id":"W4386252129","doi":"10.1111/ejn.16135","title":"Effect of number of diffusion encoding directions in neonatal diffusion tensor imaging using Tract‐Based Spatial Statistical analysis","year":2023,"lang":"en","type":"article","venue":"European Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistosäätiö; Turun Yliopistollinen Keskussairaala; Emil Aaltosen Säätiö; Signe ja Ane Gyllenbergin Säätiö; Jane ja Aatos Erkon Säätiö; Academy of Finland; Varsinais-Suomen Sairaanhoitopiiri; Alfred Kordelinin Säätiö","keywords":"Diffusion MRI; Diffusion; Encoding (memory); Statistical physics; Neuroscience; Computer science; Medicine; Physics; Biology; Radiology; Magnetic resonance imaging","score_opus":0.04305764631367952,"score_gpt":0.3744289100689669,"score_spread":0.33137126375528736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386252129","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8523853,0.0000088634615,0.14715432,0.00012127252,0.00008076153,0.000105672414,0.000014150223,0.00002684085,0.000102829414],"genre_scores_gemma":[0.9955538,0.000041040093,0.0042929943,0.00004560489,0.0000322933,7.2933744e-7,0.0000023576772,0.00001837449,0.000012817905],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983362,0.0003080268,0.0005712981,0.00021344761,0.00039497425,0.00017608424],"domain_scores_gemma":[0.99884224,0.000336197,0.00042251355,0.00019694275,0.00010081593,0.00010127649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080113945,0.000112396214,0.00034758108,0.00057957234,0.00008192569,0.000012149673,0.00017208312,0.000009734281,0.000011033783],"category_scores_gemma":[0.00072884746,0.00008955959,0.00015043878,0.0017055926,0.00019472308,0.000109486835,0.000073860014,0.00025851736,0.0000011212421],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108315435,0.000116330775,0.31617492,0.00003849974,0.0000034581133,0.00051896175,0.00006737765,0.0014628547,0.6685284,0.0000122998545,0.000007861881,0.0129607245],"study_design_scores_gemma":[0.0007450801,0.00034913854,0.840077,0.00018398283,0.00019379392,0.00029141107,0.000015804926,0.14416815,0.013711829,0.0000102649865,0.00017581761,0.000077750185],"about_ca_topic_score_codex":0.000018326684,"about_ca_topic_score_gemma":5.3377846e-7,"teacher_disagreement_score":0.65481657,"about_ca_system_score_codex":0.000030176243,"about_ca_system_score_gemma":0.000037694324,"threshold_uncertainty_score":0.3652134},"labels":[],"label_agreement":null},{"id":"W4386362772","doi":"10.1109/isbi53787.2023.10230661","title":"Explaining Anatomical Shape Variability: Supervised Disentangling with A Variational Graph Autoencoder","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Autoencoder; Artificial intelligence; Pattern recognition (psychology); Computer science; Diffusion MRI; Neuroimaging; Population; Graph; Scalar (mathematics); Laplace operator; Nonlinear dimensionality reduction; Tensor (intrinsic definition); Deep learning; Machine learning; Mathematics; Theoretical computer science; Dimensionality reduction; Magnetic resonance imaging","score_opus":0.062415642846957504,"score_gpt":0.33950134789361214,"score_spread":0.27708570504665464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386362772","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3945577,0.0000062816493,0.58336025,0.010988421,0.000045483263,0.000788324,0.000021766098,0.0029542828,0.0072774687],"genre_scores_gemma":[0.834446,0.00001101071,0.16404429,0.0009104002,0.00006901757,0.00014806261,0.000103152895,0.000030602358,0.00023746566],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99903226,0.000018978895,0.0001761981,0.00033962826,0.00021705758,0.00021586443],"domain_scores_gemma":[0.9993191,0.00017626196,0.000029574607,0.000293094,0.00006887515,0.00011309686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017126607,0.00011324284,0.00015978463,0.0001232596,0.00011460073,0.000017358027,0.00007335413,0.000038310012,0.00025789038],"category_scores_gemma":[0.000072091054,0.000087205306,0.00005222917,0.0006820606,0.000058980444,0.00008461374,0.000049987215,0.00015572156,0.000027460825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054914615,0.0008647695,0.5102572,0.00018159555,0.00021950818,0.00030278633,0.0009808706,0.0015898957,0.014171863,0.44461113,0.008282029,0.017989239],"study_design_scores_gemma":[0.0013760207,0.00013363875,0.065367475,0.0000726201,0.00008719621,0.00010096148,0.00023503473,0.9045396,0.00075676874,0.024369176,0.0026875178,0.00027399525],"about_ca_topic_score_codex":0.0000044612657,"about_ca_topic_score_gemma":8.646148e-7,"teacher_disagreement_score":0.9029497,"about_ca_system_score_codex":0.000033825134,"about_ca_system_score_gemma":0.00006252437,"threshold_uncertainty_score":0.35561293},"labels":[],"label_agreement":null},{"id":"W4386549227","doi":"10.1162/imag_a_00019","title":"Dual-encoded magnetization transfer and diffusion imaging and its application to tract-specific microstructure mapping","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; University of Calgary; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canada First Research Excellence Fund; Réseau en Bio-Imagerie du Quebec; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Magnetization transfer; White matter; Tractography; Diffusion MRI; Voxel; Partial volume; Fractional anisotropy; Nuclear magnetic resonance; Nuclear medicine; Biomedical engineering; Materials science; Computer science; Artificial intelligence; Magnetic resonance imaging; Physics; Medicine; Radiology","score_opus":0.032787579445728084,"score_gpt":0.3107966841154105,"score_spread":0.2780091046696824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386549227","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8394912,0.00024854895,0.14429905,0.014200216,0.00009748973,0.00091033836,0.000019294992,0.0006279026,0.00010599548],"genre_scores_gemma":[0.99479616,0.0005493421,0.001979698,0.0023520042,0.000057400262,0.00007446775,0.000013778354,0.000032183205,0.00014494153],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985742,0.000017801087,0.00020471198,0.0006973932,0.00020954823,0.00029633238],"domain_scores_gemma":[0.9994269,0.000039126422,0.000035166202,0.00026484375,0.00006650343,0.00016747565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012561111,0.0001658258,0.00014612477,0.00026641507,0.00031885106,0.00009561507,0.00009893994,0.000021067293,0.0000026449509],"category_scores_gemma":[0.000056443292,0.00016320316,0.000023053926,0.0009837651,0.00012511626,0.00025099778,0.00010005216,0.00017112856,0.000007876016],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000064700075,0.000016892422,0.010080388,0.00002711593,1.7027713e-7,0.000017639964,0.00021770163,0.0000196055,0.9638311,0.00036682028,0.0002526935,0.02516336],"study_design_scores_gemma":[0.0008799771,0.000056061686,0.7374213,0.00013708891,0.000021478068,0.0010671368,0.0001501558,0.12695011,0.057300493,0.0011030919,0.07446746,0.00044564685],"about_ca_topic_score_codex":0.0000039923634,"about_ca_topic_score_gemma":2.3234915e-7,"teacher_disagreement_score":0.9065307,"about_ca_system_score_codex":0.000020857311,"about_ca_system_score_gemma":0.000015237282,"threshold_uncertainty_score":0.6655232},"labels":[],"label_agreement":null},{"id":"W4386638349","doi":"10.1038/s41467-023-40999-z","title":"Non-invasive assessment of normal and impaired iron homeostasis in the brain","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Azrieli Foundation; Israel Science Foundation","keywords":"Iron homeostasis; Homeostasis; Ferritin; Transferrin; Ferrous; Human brain; In vivo; Magnetic resonance imaging; Biology; Ex vivo; Neuroscience; Cell biology; Pathology; Medicine; Chemistry; Biochemistry; Metabolism; Biotechnology","score_opus":0.05750786017996696,"score_gpt":0.4104235801183071,"score_spread":0.35291571993834014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386638349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7697837,0.0014606691,0.0005344743,0.21930003,0.00002720814,0.0015633296,0.00008355224,0.00023342368,0.007013622],"genre_scores_gemma":[0.98404914,0.0017768847,0.012644438,0.0012121543,0.000009320893,0.00014851718,0.00011185671,0.000009013075,0.00003866355],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994889,0.000047039943,0.00015446435,0.00010423203,0.0001095815,0.000095774936],"domain_scores_gemma":[0.9981467,0.0005526622,0.000061139006,0.0011612658,0.000053296655,0.000024894272],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025249,0.00006263802,0.00011241634,0.000118569966,0.00010803262,0.000007162529,0.0003422264,0.00007065162,0.0000021907174],"category_scores_gemma":[0.00012343956,0.00004741149,0.00003327978,0.0006484297,0.00012855309,0.000040770785,0.00019420448,0.0005635557,0.000001383314],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064298525,0.001869407,0.5608219,0.00043327117,0.000093199465,0.000043206706,0.0062005287,0.000074793454,0.09483515,0.18004653,0.11033171,0.045186058],"study_design_scores_gemma":[0.00039337212,0.00007320256,0.97875905,0.00006494514,0.000027570213,0.000028142078,0.0005148907,0.0015366137,0.00057124946,0.0009777969,0.016984502,0.00006869323],"about_ca_topic_score_codex":0.000018230783,"about_ca_topic_score_gemma":0.00008199681,"teacher_disagreement_score":0.41793716,"about_ca_system_score_codex":0.000021218073,"about_ca_system_score_gemma":0.00005328283,"threshold_uncertainty_score":0.24484003},"labels":[],"label_agreement":null},{"id":"W4386727224","doi":"10.1101/2023.09.14.557689","title":"A hierarchical atlas of the human cerebellum for functional precision mapping","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Atlas (anatomy); Computer science; Cerebellum; Cartography; Artificial intelligence; Geography; Neuroscience; Biology; Anatomy","score_opus":0.0871225521308664,"score_gpt":0.31077201962532197,"score_spread":0.22364946749445558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386727224","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82783574,0.00019106612,0.1607388,0.004352413,0.0009201206,0.0042681913,0.00052327255,0.0011478652,0.000022506802],"genre_scores_gemma":[0.9671171,0.00004356808,0.031097295,0.0001911905,0.00048568938,0.0008450009,0.0000015301496,0.00013777157,0.00008088674],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99803245,0.000044511766,0.0005206021,0.00072920526,0.00036600215,0.00030721436],"domain_scores_gemma":[0.99757016,0.00015588032,0.000368641,0.0013781857,0.00040176456,0.00012538098],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033498215,0.0002972675,0.00044210747,0.00019213474,0.000243932,0.000030492563,0.00037972143,0.00027427013,0.000012591639],"category_scores_gemma":[0.0003040961,0.00024838236,0.00031368408,0.00044201492,0.00018221977,0.000035561945,0.0006120831,0.00075854873,0.000008849281],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033658434,0.00017507972,0.012125429,0.00063740695,0.0000817313,0.000003887926,0.0000050274307,0.00004901871,0.97790504,0.005293422,0.0036847026,0.0000055951555],"study_design_scores_gemma":[0.0009965473,0.0001065067,0.6349437,0.0017924388,0.00024051078,7.915428e-8,0.0000022924105,0.0011855768,0.32786718,0.0005578332,0.03178984,0.0005174299],"about_ca_topic_score_codex":0.000010588544,"about_ca_topic_score_gemma":4.8688855e-7,"teacher_disagreement_score":0.6500378,"about_ca_system_score_codex":0.00013270407,"about_ca_system_score_gemma":0.00030494618,"threshold_uncertainty_score":0.99999684},"labels":[],"label_agreement":null},{"id":"W4386760135","doi":"10.1097/md.0000000000034979","title":"Combining ADC values in DWI with rCBF values in arterial spin labeling (ASL) for the diagnosis of mild cognitive impairment (MCI)","year":2023,"lang":"en","type":"article","venue":"Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Frontal lobe; Medicine; Montreal Cognitive Assessment; Occipital lobe; Cerebral blood flow; Temporal lobe; Cardiology; Lobe; Nuclear medicine; Audiology; Cognitive impairment; Internal medicine; Cognition; Radiology; Psychiatry; Pathology; Epilepsy","score_opus":0.10525494736136358,"score_gpt":0.4050164015564453,"score_spread":0.2997614541950817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386760135","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785948,0.00038671397,0.0027026806,0.015929047,0.00009813072,0.0019821564,0.000023326122,0.00014275374,0.00014042782],"genre_scores_gemma":[0.9953939,0.0006249738,0.0018598427,0.0007093621,0.00017157695,0.0010891084,0.00005065667,0.00003079475,0.00006980033],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988719,0.00003207898,0.0003685775,0.00025855514,0.00022261776,0.00024622146],"domain_scores_gemma":[0.99870247,0.0008259335,0.00011346322,0.00022218988,0.00008609612,0.00004984655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005055355,0.00014199178,0.00037332543,0.0002141805,0.00006125025,0.000003528607,0.0000992411,0.000036844995,0.000020144802],"category_scores_gemma":[0.00030283758,0.000088627705,0.000035611352,0.0006340641,0.00021449536,0.000036114074,0.00004373901,0.00017879743,0.0000019713837],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007108377,0.0029810483,0.7972485,0.0019181881,0.00041688807,0.00036955572,0.03128306,0.0009047505,0.036614604,0.0037674895,0.036850136,0.08053743],"study_design_scores_gemma":[0.047871694,0.0108583905,0.7840919,0.021885343,0.0009915066,0.00007107195,0.020081097,0.024584517,0.06520959,0.018174648,0.00533273,0.00084752927],"about_ca_topic_score_codex":0.00016104321,"about_ca_topic_score_gemma":0.000034463857,"teacher_disagreement_score":0.079689905,"about_ca_system_score_codex":0.00004043077,"about_ca_system_score_gemma":0.00003581733,"threshold_uncertainty_score":0.3614133},"labels":[],"label_agreement":null},{"id":"W4387036902","doi":"10.21203/rs.3.rs-3361804/v1","title":"Application of Diffusion Tensor Imaging of the Facial Nerve in Preoperative Planning for Large Vestibular Schwannoma","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Diffusion MRI; Schwannoma; Facial nerve; Cochrane Library; Vestibular system; Neuronavigation; Fractional anisotropy; Acoustic neuroma; Radiology; Magnetic resonance imaging; Meta-analysis; Surgery; Internal medicine","score_opus":0.1504520102117505,"score_gpt":0.4763909987498768,"score_spread":0.3259389885381263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387036902","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88918966,0.0004195778,0.09559132,0.004411488,0.000049477054,0.009106274,0.0009143878,0.00015138635,0.00016639533],"genre_scores_gemma":[0.99347687,0.00003642607,0.0043327445,0.000015412415,0.000076696575,0.0016524917,0.00021127929,0.000046606932,0.00015145041],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99819285,0.000118149226,0.0004039566,0.0004603032,0.0005026098,0.0003221611],"domain_scores_gemma":[0.99807996,0.00029801388,0.00018353072,0.00077225687,0.0006131551,0.000053097356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007695631,0.00014534901,0.0003445081,0.0003193115,0.00013948242,0.000013032229,0.000335516,0.00011521061,0.0000025273694],"category_scores_gemma":[0.0007582814,0.000111765774,0.00010769189,0.0005258375,0.00015279309,0.000033833698,0.00085863005,0.0008882896,0.0000014714761],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036740548,0.0006305957,0.8925423,0.0044672466,0.000032621483,0.000018365323,0.0019164928,0.0023455,0.08537763,0.0071758097,0.001153333,0.0039727096],"study_design_scores_gemma":[0.0015890112,0.00032526764,0.8230013,0.0054507805,0.000052063486,0.000008097711,0.0011196223,0.10968623,0.033721298,0.021037696,0.0037305998,0.0002780012],"about_ca_topic_score_codex":0.00014729398,"about_ca_topic_score_gemma":0.000008557119,"teacher_disagreement_score":0.10734073,"about_ca_system_score_codex":0.0001146714,"about_ca_system_score_gemma":0.00021711308,"threshold_uncertainty_score":0.45576757},"labels":[],"label_agreement":null},{"id":"W4387059333","doi":"10.1101/2023.09.25.559330","title":"White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"","keywords":"White matter; Tractography; Diffusion MRI; Neuroscience; Brain morphometry; Biology; Human brain; Psychology; Magnetic resonance imaging; Medicine","score_opus":0.028387914403368672,"score_gpt":0.2979703062748655,"score_spread":0.2695823918714968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387059333","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862016,0.00023431383,0.0016661563,0.007938512,0.0005457021,0.0013532271,0.0012779546,0.000776026,0.000006512833],"genre_scores_gemma":[0.9886262,0.00017779891,0.0047061243,0.005520261,0.00030243106,0.00032591453,0.000007634009,0.00027462738,0.000059031772],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99686366,0.00013619843,0.0006299792,0.0012364009,0.00031306688,0.0008207097],"domain_scores_gemma":[0.99721223,0.00013919716,0.00042599562,0.0016437898,0.00028960124,0.00028920846],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038645227,0.0006515246,0.0007676458,0.0001260389,0.0003976692,0.00023706294,0.00047568875,0.0006884659,0.00016079414],"category_scores_gemma":[0.00015776158,0.0005169059,0.00019259156,0.0004338682,0.0005786484,0.00007195375,0.00080598495,0.0022109866,0.00020845179],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003886325,0.00007658413,0.7648826,0.000171289,0.00010876636,0.00013468214,0.000018095923,0.0000053486374,0.22505029,0.000054104097,0.009458244,0.0000010838282],"study_design_scores_gemma":[0.00049499766,0.000033188753,0.98075,0.00018022694,0.00021299014,0.000002197053,0.000003502388,0.00006260319,0.014525912,0.000049732553,0.0031954856,0.00048913836],"about_ca_topic_score_codex":0.00003867026,"about_ca_topic_score_gemma":0.000002082443,"teacher_disagreement_score":0.21586739,"about_ca_system_score_codex":0.00014412672,"about_ca_system_score_gemma":0.00013143138,"threshold_uncertainty_score":0.99972826},"labels":[],"label_agreement":null},{"id":"W4387059515","doi":"10.1038/s41537-023-00392-7","title":"A systematic review of neuroimaging studies of clozapine-resistant schizophrenia","year":2023,"lang":"en","type":"review","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Clozapine; Neuroimaging; Schizophrenia (object-oriented programming); Dorsolateral prefrontal cortex; Magnetic resonance imaging; Antipsychotic; Diffusion MRI; Psychology; Medicine; Neuroscience; Prefrontal cortex; Psychiatry; Cognition; Radiology","score_opus":0.1824756410072629,"score_gpt":0.44717568970011473,"score_spread":0.2647000486928518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387059515","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000041117596,0.99375856,0.00007800507,0.00017939882,0.00012446335,0.0051257075,0.00021350676,0.0004213834,0.00009484285],"genre_scores_gemma":[0.0000036936797,0.9906657,0.007460496,0.00012261786,0.000108486296,0.0010024592,0.00010476789,0.00020732496,0.0003244838],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99481463,0.0002613348,0.0031657487,0.00075575843,0.0006357346,0.0003668182],"domain_scores_gemma":[0.99415445,0.0006716479,0.002514334,0.002026752,0.0004871652,0.00014565115],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00073511543,0.0007225218,0.00761831,0.0005875927,0.000081400336,0.000009913484,0.00059817726,0.00014929194,0.000013082436],"category_scores_gemma":[0.0021590157,0.00052976655,0.0014112649,0.0018092081,0.00031875243,0.000064948224,0.0003661383,0.0006794088,0.00006212905],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000523797,0.000059737886,1.4897151e-7,0.9785916,0.00059125555,0.000040707495,0.000009143098,5.228945e-8,0.000027338907,0.0015692614,0.0012253539,0.017833002],"study_design_scores_gemma":[0.00041577098,0.00012200541,0.0000010620209,0.9472237,0.009502251,0.0001659601,0.000010596981,0.000003643341,0.000020237292,0.0005491883,0.04165452,0.00033102577],"about_ca_topic_score_codex":0.00000511933,"about_ca_topic_score_gemma":9.504511e-7,"teacher_disagreement_score":0.040429167,"about_ca_system_score_codex":0.000099715784,"about_ca_system_score_gemma":0.00044787553,"threshold_uncertainty_score":0.9997154},"labels":[],"label_agreement":null},{"id":"W4387104808","doi":"10.31219/osf.io/qpmwk","title":"Diffusion MRI of the hippocampus","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Health Canada; Canada First Research Excellence Fund; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Hippocampus; Neuroscience; Diffusion MRI; Cognition; Computer science; Psychology; Medicine; Magnetic resonance imaging","score_opus":0.09679997249347998,"score_gpt":0.3746550518329754,"score_spread":0.27785507933949544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387104808","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6688816,0.00025173998,0.16829422,0.112955384,0.0013153495,0.0055284523,0.00011836943,0.0032923345,0.039362546],"genre_scores_gemma":[0.953649,0.00057606085,0.030570775,0.00089120737,0.00011431119,0.00016068165,0.0000347083,0.000055286007,0.013947987],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99939805,0.000009379765,0.0001662782,0.00021181999,0.00013728574,0.00007718501],"domain_scores_gemma":[0.99892485,0.000032777793,0.000102360944,0.0008634769,0.000048906943,0.000027614693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004655102,0.00008985779,0.0001679849,0.00003647215,0.00002988326,0.000003084148,0.00017977186,0.0000809116,0.00002994284],"category_scores_gemma":[0.00003800321,0.000053239102,0.00012819382,0.000104679835,0.000061539904,0.0000045533434,0.0008049341,0.00034981378,0.000012303373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015309539,0.0016297,0.14492746,0.004116308,0.00025140008,0.000047010923,0.00059974607,0.00082041323,0.16409078,0.07105135,0.4426464,0.16966632],"study_design_scores_gemma":[0.0005086802,0.00007105952,0.14981018,0.0014174592,0.00023693436,0.000034649147,0.000046028425,0.0037644273,0.034624226,0.7691922,0.039984386,0.0003097771],"about_ca_topic_score_codex":0.000037169862,"about_ca_topic_score_gemma":0.0000024004325,"teacher_disagreement_score":0.69814086,"about_ca_system_score_codex":0.000018932129,"about_ca_system_score_gemma":0.000045790588,"threshold_uncertainty_score":0.21710277},"labels":[],"label_agreement":null},{"id":"W4387139287","doi":"10.1101/2023.09.26.559530","title":"Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute; Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; Université de Sherbrooke","funders":"National Institutes of Health","keywords":"Distortion (music); Image quality; Preprocessor; Artificial intelligence; Diffusion MRI; Computer vision; Spinal cord; Computer science; Tractography; White matter; Image processing; Contrast (vision); Pattern recognition (psychology); Image (mathematics); Medicine; Magnetic resonance imaging; Radiology; Neuroscience; Psychology","score_opus":0.05972007701938037,"score_gpt":0.3414014745011572,"score_spread":0.28168139748177684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387139287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99499255,0.0002769541,0.003432099,0.00017451067,0.00014848576,0.0007114111,0.00008960103,0.00017065313,0.0000037511313],"genre_scores_gemma":[0.9975463,0.00065880356,0.001549031,0.000016085225,0.000050211453,0.0001293033,3.441497e-7,0.000042412077,0.0000075030453],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983729,0.0000769661,0.0006145037,0.00047565077,0.00031133642,0.00014860489],"domain_scores_gemma":[0.9975247,0.00012999018,0.0009564929,0.00086935615,0.0004566501,0.00006281444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006003803,0.0002112086,0.0005326166,0.0001468243,0.00007303678,0.000011363207,0.00015536405,0.00013694215,0.0000011725265],"category_scores_gemma":[0.0006784931,0.00017777615,0.00011103902,0.00034328166,0.00025788587,0.000053828207,0.00022104036,0.00038716153,6.171449e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025649148,0.0001168474,0.037645627,0.0012828169,0.00003063464,9.4850714e-7,0.000007457798,0.00008372,0.9602049,0.00026754467,0.00005030795,0.000052676118],"study_design_scores_gemma":[0.00010431765,0.00013527524,0.5358776,0.0012004613,0.00006224228,6.543548e-9,0.000003010101,0.00009015271,0.46235865,0.000010971811,0.00006278254,0.00009452953],"about_ca_topic_score_codex":0.00012629722,"about_ca_topic_score_gemma":2.9801944e-7,"teacher_disagreement_score":0.49823198,"about_ca_system_score_codex":0.000077768775,"about_ca_system_score_gemma":0.00013680151,"threshold_uncertainty_score":0.7249501},"labels":[],"label_agreement":null},{"id":"W4387152047","doi":"10.48550/arxiv.2309.15053","title":"Thalamic nuclei segmentation from T$_1$-weighted MRI: unifying and benchmarking state-of-the-art methods with young and old cohorts","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Pfizer; Novartis Pharmaceuticals Corporation; Eisai; U.S. Department of Defense; Meso Scale Diagnostics; Servier; BioClinica; Bristol-Myers Squibb; Eli Lilly and Company; Biogen","keywords":"Human Connectome Project; Neuroimaging; Thalamus; Neuroscience; Segmentation; Cognition; Alzheimer's disease; Disease; Connectome; Psychology; Medicine; Artificial intelligence; Computer science; Pathology; Functional connectivity","score_opus":0.10626338864023957,"score_gpt":0.28069112688633996,"score_spread":0.1744277382461004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387152047","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74237233,0.0000402883,0.2564341,0.00011724119,0.00006236342,0.0005812717,0.000031402364,0.00014480704,0.00021614268],"genre_scores_gemma":[0.93869233,0.00083337247,0.059581645,0.000052655345,0.00002143514,0.0000042590673,0.00008043471,0.000040469964,0.00069342315],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988857,0.00008056135,0.00016875064,0.00063778635,0.00007278263,0.0001544485],"domain_scores_gemma":[0.9989242,0.00014541447,0.00026047626,0.00051598315,0.00007639945,0.00007755359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011793494,0.0002060311,0.00031162205,0.00013475232,0.00012923131,0.000021816857,0.00013755969,0.00008840155,0.0000071443665],"category_scores_gemma":[0.000011525035,0.00018353286,0.00005478999,0.00031689726,0.00018970482,0.00008512586,0.00047662307,0.0003993438,8.774185e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035024434,0.00016172742,0.94591016,0.000478236,0.0006086978,0.00031263052,0.0010560809,0.0057594567,0.02020186,0.0065838513,0.0002971986,0.01827984],"study_design_scores_gemma":[0.0024451504,0.0002497963,0.7096588,0.0024521342,0.0019466314,0.0000661397,0.00042825128,0.16671304,0.016718447,0.0976933,0.0006579392,0.00097037025],"about_ca_topic_score_codex":0.00027042397,"about_ca_topic_score_gemma":0.000052147432,"teacher_disagreement_score":0.23625138,"about_ca_system_score_codex":0.00008004889,"about_ca_system_score_gemma":0.000046331203,"threshold_uncertainty_score":0.7484253},"labels":[],"label_agreement":null},{"id":"W4387187092","doi":"10.3390/brainsci13101386","title":"The Challenge of Diffusion Magnetic Resonance Imaging in Cerebral Palsy: A Proposed Method to Identify White Matter Pathways","year":2023,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université de Sherbrooke; Centre for Interdisciplinary Research in Rehabilitation","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Réseau en Bio-Imagerie du Quebec","keywords":"White matter; Magnetic resonance imaging; Diffusion MRI; Neuroimaging; Medicine; Cerebral palsy; Computer science; Medical physics; Nuclear medicine; Psychology; Radiology; Neuroscience; Physical medicine and rehabilitation","score_opus":0.07929878459541224,"score_gpt":0.40214479376355544,"score_spread":0.3228460091681432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387187092","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60795873,0.0013466538,0.013194028,0.3680067,0.00012841023,0.002170922,0.000019437264,0.00037813044,0.0067969654],"genre_scores_gemma":[0.95987624,0.000096315365,0.03682521,0.0019807045,0.000036594356,0.00012762894,0.0000017115708,0.000015734366,0.0010398669],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998809,0.00006986585,0.00023229436,0.00033952534,0.00028892438,0.00026038586],"domain_scores_gemma":[0.99932647,0.00023160523,0.000059727034,0.00029567388,0.00003610252,0.000050440667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001092824,0.00008210744,0.00013178092,0.00015897442,0.00017599112,0.000030165986,0.00028369232,0.000015737867,0.000024554029],"category_scores_gemma":[0.00015294708,0.0000532061,0.000036314254,0.0011214312,0.00021685919,0.00006934105,0.00016309356,0.000093024784,0.000029169241],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000587137,0.00016904334,0.3469551,0.00009483472,0.0000012914314,0.000043907658,0.0032926884,0.000030538362,0.18663822,0.011642044,0.017291386,0.43378225],"study_design_scores_gemma":[0.0002859503,0.00012800071,0.9533561,0.00020524318,0.0000038029823,0.0000127558815,0.00049018266,0.0034929586,0.002827608,0.02180651,0.017280068,0.000110836125],"about_ca_topic_score_codex":0.000020779004,"about_ca_topic_score_gemma":0.000013139076,"teacher_disagreement_score":0.606401,"about_ca_system_score_codex":0.0000147836345,"about_ca_system_score_gemma":0.000038664544,"threshold_uncertainty_score":0.21696818},"labels":[],"label_agreement":null},{"id":"W4387211202","doi":"10.1007/978-3-031-43999-5_42","title":"InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University","funders":"","keywords":"Computer science; Generative model; Real-time MRI; Diffusion MRI; Artificial intelligence; Superresolution; Resolution (logic); Image resolution; Generative grammar; Pattern recognition (psychology); Computer vision; Magnetic resonance imaging; Image (mathematics); Radiology","score_opus":0.09815763616661491,"score_gpt":0.33739609649054025,"score_spread":0.23923846032392534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387211202","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008387147,0.000043928307,0.9947836,0.0028150245,0.00020381004,0.00055181334,0.000011395866,0.00031956978,0.0004321553],"genre_scores_gemma":[0.058122147,0.00017575915,0.9338483,0.0051170588,0.0004085535,0.000022421753,0.00004114939,0.000116211515,0.0021483894],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979947,0.000008256403,0.0002917809,0.00084726536,0.00049779797,0.0003602059],"domain_scores_gemma":[0.99884254,0.00011854422,0.00011232223,0.0006860595,0.000119708464,0.00012083055],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022237269,0.00028874876,0.00032631852,0.00048424627,0.0001947302,0.00004749461,0.00035162337,0.0001907028,0.000008027235],"category_scores_gemma":[0.000059840895,0.000261358,0.000091922964,0.00035776143,0.00041419847,0.00010878572,0.00048735677,0.00061345095,0.000015430584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044452874,0.000106085936,0.00028521405,0.00017026436,0.000014625672,0.00019148947,0.00064435357,0.7981474,0.02423851,0.01152166,0.0004738726,0.16416211],"study_design_scores_gemma":[0.0001888538,0.00007044265,0.000044511355,0.00047806103,0.000018071192,0.000067746936,8.4821856e-8,0.9402157,0.0004659534,0.0574491,0.00077112473,0.00023033984],"about_ca_topic_score_codex":0.00002560459,"about_ca_topic_score_gemma":0.000014616689,"teacher_disagreement_score":0.16393177,"about_ca_system_score_codex":0.0003062672,"about_ca_system_score_gemma":0.0002459327,"threshold_uncertainty_score":0.99998385},"labels":[],"label_agreement":null},{"id":"W4387233484","doi":"10.1016/j.neuroimage.2023.120387","title":"High resolution 0.5mm isotropic T1-weighted and diffusion tensor templates of the brain of non-demented older adults in a common space for the MIITRA atlas","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Institute of Neurological Disorders and Stroke; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Template; Spatial normalization; Diffusion MRI; Neuroimaging; Computer science; Artificial intelligence; Psychology; Voxel; Neuroscience; Medicine; Magnetic resonance imaging","score_opus":0.025625918337278883,"score_gpt":0.3125989924006837,"score_spread":0.2869730740634048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387233484","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98185366,0.00004906232,0.0011319373,0.015231103,0.000035002602,0.001555508,0.00004323652,0.00006942926,0.000031047864],"genre_scores_gemma":[0.9976313,0.00014868281,0.0015101117,0.00031802445,0.00002153562,0.000112496746,0.00001836898,0.00002404593,0.00021544825],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99915403,0.000042124084,0.00026506797,0.00023284936,0.00014294383,0.00016295393],"domain_scores_gemma":[0.9988989,0.00044188809,0.00014536014,0.0004253111,0.000062067986,0.000026441114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010910792,0.00011076044,0.00021411791,0.000089209556,0.00009366001,0.0000050046056,0.00012788901,0.000040192877,0.0000036975289],"category_scores_gemma":[0.000116913325,0.00006744423,0.00006408621,0.00047049913,0.00014012666,0.00003429333,0.00010822047,0.00016956282,8.523794e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006231955,0.00039171008,0.07212101,0.00044480132,0.00002037414,0.000011320564,0.00056164555,0.000026899357,0.90734,0.0010067443,0.012053459,0.0053988793],"study_design_scores_gemma":[0.002039688,0.00022232624,0.94552064,0.0002933788,0.00004442814,0.000010515331,0.00007843045,0.016160445,0.033484474,0.00065741217,0.0014201859,0.00006806373],"about_ca_topic_score_codex":0.00014778534,"about_ca_topic_score_gemma":0.000028626211,"teacher_disagreement_score":0.8738555,"about_ca_system_score_codex":0.000012700901,"about_ca_system_score_gemma":0.000013283635,"threshold_uncertainty_score":0.27502957},"labels":[],"label_agreement":null},{"id":"W4387244433","doi":"10.1101/2023.09.29.560251","title":"Quantifying myelin density in the feline auditory cortex","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Auditory cortex; Neuroscience; Myelin; Cortex (anatomy); Cerebral cortex; Biology; Psychology; Central nervous system","score_opus":0.1024141935882349,"score_gpt":0.3348089771566043,"score_spread":0.2323947835683694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387244433","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97503686,0.0004522491,0.013345647,0.005875226,0.0011368371,0.0021864488,0.00012845945,0.0018273081,0.000010940119],"genre_scores_gemma":[0.9809177,0.00063643296,0.015626894,0.0011507041,0.0010396728,0.00046287762,0.000001384659,0.00015231171,0.000012058459],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9973827,0.00011650743,0.0005927409,0.0009824829,0.00044661466,0.0004789429],"domain_scores_gemma":[0.9970748,0.00018041664,0.0003213764,0.0019751994,0.00030211912,0.00014612648],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008840508,0.00043549822,0.0005710578,0.00029769982,0.00017333614,0.00008358603,0.0005633351,0.00034703413,0.000010397494],"category_scores_gemma":[0.00041207977,0.00038060904,0.00017665101,0.0007447201,0.00014591424,0.00006222125,0.0004480451,0.0016674738,0.000120975266],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009004372,0.0005757595,0.06890383,0.0009931257,0.00010687827,0.00093822187,0.000033741842,0.00008432407,0.91378677,0.0023532093,0.01211875,0.000015367397],"study_design_scores_gemma":[0.0005768443,0.00005533978,0.94972897,0.000946858,0.00018304992,1.998423e-7,0.000010289685,0.0017813577,0.026749989,0.000033144686,0.019297523,0.0006364663],"about_ca_topic_score_codex":0.00008162527,"about_ca_topic_score_gemma":0.000011055594,"teacher_disagreement_score":0.88703674,"about_ca_system_score_codex":0.00020911112,"about_ca_system_score_gemma":0.00036354063,"threshold_uncertainty_score":0.9998646},"labels":[],"label_agreement":null},{"id":"W4387336768","doi":"10.1186/s13195-023-01309-3","title":"In vivo cortical diffusion imaging relates to Alzheimer’s disease neuropathology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s Research & Therapy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; University of California, San Diego; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Neuropathology; Cerebral amyloid angiopathy; Diffusion MRI; Pathology; Neuroimaging; Neuroscience; White matter; Neurology; Neurodegeneration; Medicine; Lewy body; Alzheimer's disease; Psychology; Dementia; Disease; Magnetic resonance imaging; Radiology","score_opus":0.23715601182103507,"score_gpt":0.48136043609076024,"score_spread":0.24420442426972516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387336768","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.86913383,0.006170823,0.0006848872,0.118163764,0.0001705226,0.0034167252,0.000027326721,0.0010020755,0.0012300356],"genre_scores_gemma":[0.99026465,0.0032340758,0.0012208688,0.003980191,0.00015699601,0.00065547426,0.00001848519,0.00009639796,0.00037287062],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99746704,0.0002789297,0.00029803521,0.00065027183,0.0005255206,0.00078023056],"domain_scores_gemma":[0.9981337,0.00041219423,0.000027094073,0.0007821056,0.00015724507,0.00048764268],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007068523,0.00018097574,0.00024702272,0.00064732257,0.00022786896,0.000032875017,0.000288087,0.000048060174,0.00019946737],"category_scores_gemma":[0.00019384062,0.00015824352,0.000081797676,0.0016550124,0.00024722124,0.000119464836,0.00026740762,0.00077299465,0.00043636758],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027688635,0.0015134243,0.12526412,0.000020093657,0.00016841672,0.006017601,0.0012754626,0.000057357895,0.6057705,0.0086604655,0.12562598,0.12285771],"study_design_scores_gemma":[0.0032098265,0.0009600301,0.49452075,0.00018804421,0.00015868449,0.00017622334,0.00021384927,0.008475394,0.046768535,0.024119848,0.42047173,0.0007370807],"about_ca_topic_score_codex":0.0000491152,"about_ca_topic_score_gemma":0.000002225388,"teacher_disagreement_score":0.559002,"about_ca_system_score_codex":0.000027466142,"about_ca_system_score_gemma":0.00009397958,"threshold_uncertainty_score":0.64529836},"labels":[],"label_agreement":null},{"id":"W4387429097","doi":"10.1007/s00429-023-02714-y","title":"Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation","year":2023,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; McDonnell Center for Systems Neuroscience; European Commission","keywords":"White matter; Tractography; Diffusion MRI; Neuroscience; Grey matter; Cognition; Voxel; Artificial intelligence; Computer science; Pattern recognition (psychology); Connectomics; Psychology; Connectome; Functional connectivity; Magnetic resonance imaging; Medicine","score_opus":0.018166065083697964,"score_gpt":0.2952964809994426,"score_spread":0.27713041591574467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387429097","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8561907,0.00002806235,0.092624955,0.049103264,0.0001865849,0.0008920999,0.0002579877,0.00030974954,0.0004066236],"genre_scores_gemma":[0.99347514,0.000004537987,0.00040135215,0.002832414,0.00018325556,0.00007992854,0.00038984724,0.0000173072,0.0026162134],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993156,0.000022133165,0.00017568325,0.00021307851,0.00013192932,0.00014155376],"domain_scores_gemma":[0.99937856,0.00016858496,0.00009639962,0.00017253838,0.00013252163,0.00005137453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009206587,0.00010276175,0.00012754466,0.00008226875,0.00038270582,0.000015495372,0.000029470795,0.0000671085,0.00021281446],"category_scores_gemma":[0.00013979853,0.00007381398,0.00004430728,0.0005021658,0.000045473782,0.00008936518,0.00004320245,0.00015599793,0.000010640325],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021691663,0.000027767717,0.01789388,0.00004177684,0.000057853897,1.9802312e-7,0.00016503803,0.00010333682,0.74157053,0.0009411442,0.23101817,0.007963355],"study_design_scores_gemma":[0.0007674512,0.0002261836,0.85665387,0.000041389136,0.00010249876,0.000020238704,0.0002265494,0.0007571947,0.022635141,0.0041745845,0.1142269,0.00016801662],"about_ca_topic_score_codex":0.000009224522,"about_ca_topic_score_gemma":0.0000013266247,"teacher_disagreement_score":0.83875996,"about_ca_system_score_codex":0.000035459205,"about_ca_system_score_gemma":0.000018948875,"threshold_uncertainty_score":0.30100468},"labels":[],"label_agreement":null},{"id":"W4387453483","doi":"10.1101/2023.10.04.560912","title":"Automated Surface-Based Segmentation of Deep Gray Matter Regions Based on Diffusion Tensor Images Reveals Unique Age Trajectories Over the Healthy Lifespan","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Université de Sherbrooke","funders":"Canadian Institutes of Health Research","keywords":"Diffusion MRI; Globus pallidus; Human Connectome Project; Voxel; Segmentation; Fractional anisotropy; Artificial intelligence; Psychology; Neuroscience; Nuclear medicine; Magnetic resonance imaging; Computer science; Medicine; Basal ganglia; Radiology; Functional connectivity","score_opus":0.03724042871984424,"score_gpt":0.3073455149282868,"score_spread":0.2701050862084426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387453483","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9249445,0.00010947655,0.055884622,0.010653105,0.00036697602,0.0039607557,0.00065980444,0.0034119026,0.000008859099],"genre_scores_gemma":[0.96351135,0.000120262746,0.032609046,0.0028355815,0.00011876358,0.00056226435,0.000011032305,0.00021452007,0.000017199054],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99721473,0.00027192198,0.0007129726,0.0008723797,0.00049426337,0.00043373258],"domain_scores_gemma":[0.9964757,0.0003718687,0.000688146,0.0018582008,0.0004049312,0.00020117025],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047978148,0.00052649487,0.0006704238,0.00030927194,0.00025762533,0.00006990507,0.0003670668,0.00031998067,0.000031343094],"category_scores_gemma":[0.00020003873,0.00042655529,0.00022167574,0.00080069003,0.00025768107,0.000060022197,0.000142355,0.0008034451,0.000022062284],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028870764,0.00057263183,0.08271448,0.0013427152,0.00007234508,0.000075973636,0.000018867442,0.0019421148,0.9058938,0.00026910403,0.0068073478,0.0000019240008],"study_design_scores_gemma":[0.0011086115,0.00023445145,0.78014374,0.0013215761,0.00024047784,4.7108596e-8,0.000005906919,0.014180024,0.20153543,0.000020247051,0.00067873,0.0005307602],"about_ca_topic_score_codex":0.0001185268,"about_ca_topic_score_gemma":0.0000034776851,"teacher_disagreement_score":0.70435834,"about_ca_system_score_codex":0.00028523986,"about_ca_system_score_gemma":0.00035682114,"threshold_uncertainty_score":0.9998186},"labels":[],"label_agreement":null},{"id":"W4387455999","doi":"10.1101/2023.10.05.561088","title":"Data-driven characterization and correction of the orientation dependence of magnetization transfer measures using diffusion MRI","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Voxel; Diffusion MRI; Characterization (materials science); Orientation (vector space); Deconvolution; Magnetization transfer; Diffusion; Nuclear magnetic resonance; White matter; Fiber; Materials science; Computer science; Artificial intelligence; Physics; Mathematics; Optics; Magnetic resonance imaging; Algorithm; Medicine; Geometry; Radiology","score_opus":0.06997759832150899,"score_gpt":0.299893503790892,"score_spread":0.22991590546938304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387455999","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7140182,0.000037116613,0.284275,0.00012989805,0.00034206736,0.0007693745,0.0003011936,0.00012664429,4.997969e-7],"genre_scores_gemma":[0.99230874,0.00068095094,0.00679081,0.000029935994,0.00007607003,0.000042927604,0.000010051323,0.00005580487,0.0000047393637],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985848,0.00006483537,0.00041429323,0.00050445326,0.00031263666,0.00011899717],"domain_scores_gemma":[0.9982241,0.00003183646,0.00032056906,0.00097049575,0.000403332,0.00004967642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020623197,0.00018213305,0.0002785525,0.00014681024,0.00009197656,0.000020154095,0.0002227035,0.00016366996,0.0000032934797],"category_scores_gemma":[0.00014189813,0.00016339324,0.000045125573,0.0004624367,0.00010790052,0.00013345166,0.00027355072,0.00026362503,4.8821386e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002677784,0.000057610883,0.024812745,0.00028526096,0.000016570391,8.1459103e-7,0.000011992331,0.00031418857,0.97436094,0.00007263579,0.000009237693,0.000031252053],"study_design_scores_gemma":[0.00026922204,0.00003633744,0.46547684,0.00085321197,0.0002560266,7.099302e-8,0.0000032850548,0.075273365,0.4574086,0.000002558182,0.00025938166,0.00016110533],"about_ca_topic_score_codex":0.000044847522,"about_ca_topic_score_gemma":0.0000029468256,"teacher_disagreement_score":0.51695234,"about_ca_system_score_codex":0.000060484555,"about_ca_system_score_gemma":0.00016627526,"threshold_uncertainty_score":0.6662983},"labels":[],"label_agreement":null},{"id":"W4387483302","doi":"10.1088/1361-6560/ad0216","title":"Implications of fitting a two-compartment model in single-shell diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; Toronto Rehabilitation Institute; University of Toronto","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Compartment (ship); Diffusion MRI; Diffusion; Isotropy; Shell (structure); Sensitivity (control systems); Cellular compartment; White matter; Biological system; Physics; Chemistry; Magnetic resonance imaging; Materials science; Biology; Geology; Medicine; Optics","score_opus":0.4875591039183781,"score_gpt":0.49224013986117326,"score_spread":0.004681035942795175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387483302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95838016,0.000107930326,0.027114363,0.011844832,0.000017944101,0.0003748931,0.000008261806,0.000074851945,0.0020767727],"genre_scores_gemma":[0.99504673,0.00042196747,0.003822446,0.0005035465,0.000059249454,0.00005642831,0.00005891407,0.0000072279236,0.000023504632],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994045,0.000014260037,0.00022697613,0.00018694653,0.000033519416,0.00013382646],"domain_scores_gemma":[0.9995986,0.00011232415,0.000060555285,0.0001731678,0.000025172387,0.000030176143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011213319,0.00007089417,0.00023494176,0.00010843769,0.00002069093,6.262905e-7,0.000047348825,0.000026378311,0.000002117661],"category_scores_gemma":[0.00003264237,0.00005464184,0.000016668435,0.00038535235,0.00012847305,0.00001465216,0.000056279,0.00011855888,0.0000010008741],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003558509,0.00038785633,0.11761011,0.00008313692,0.0000070422475,0.0000031144493,0.0006374902,0.00092308875,0.7739023,0.06154123,0.0007392262,0.04412981],"study_design_scores_gemma":[0.004438333,0.00073062687,0.07059741,0.0006124894,0.00005828106,0.000019505896,0.0003989583,0.21586242,0.010966404,0.6934186,0.0026433228,0.00025360036],"about_ca_topic_score_codex":0.000034277917,"about_ca_topic_score_gemma":0.0000074601744,"teacher_disagreement_score":0.7629359,"about_ca_system_score_codex":0.000018722685,"about_ca_system_score_gemma":0.000012229114,"threshold_uncertainty_score":0.22282296},"labels":[],"label_agreement":null},{"id":"W4387519905","doi":"10.1016/j.nicl.2023.103529","title":"Impact of follow ups, time interval and study duration in diffusion &amp; myelin MRI clinical study in MS","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; CARE Canada; Q & T Research; Hôpital Fleurimont; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Centre Hospitalier Universitaire de Québec; Université de Sherbrooke","keywords":"Multiple sclerosis; Duration (music); Diffusion MRI; Medicine; White matter; Interval (graph theory); Confidence interval; Confounding; Affect (linguistics); Clinically isolated syndrome; Neurology; Internal medicine; Cardiology; Magnetic resonance imaging; Psychology; Radiology; Mathematics","score_opus":0.212553186826201,"score_gpt":0.5221445582839719,"score_spread":0.3095913714577709,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387519905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967152,0.000008463623,0.00017249995,0.0006193658,0.00009115245,0.0021147141,0.000013468521,0.00018846797,0.000076676224],"genre_scores_gemma":[0.99843526,0.00018457022,0.0007791904,0.00013112917,0.000112682916,0.000070550195,0.000030841216,0.000042608433,0.0002131568],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9961567,0.00059312134,0.0018904314,0.0008121283,0.0002794457,0.00026819887],"domain_scores_gemma":[0.9976216,0.0011051659,0.00027158693,0.00076472183,0.00008035528,0.00015657641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021124857,0.00021392053,0.0008263442,0.00029000858,0.000037780843,0.000018366809,0.00018078706,0.00011783064,0.000034355795],"category_scores_gemma":[0.0023142928,0.00018064059,0.00021857173,0.0008225541,0.00016283143,0.00010890208,0.0003301157,0.0008760562,0.000055333592],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005873337,0.006139343,0.98420423,0.000009892439,0.000017314782,0.0001950061,0.00016708035,0.00000718364,0.0008843666,0.000002016339,0.00086240383,0.0069238516],"study_design_scores_gemma":[0.0051297834,0.004567234,0.98659927,0.0000549239,0.000052408053,0.000013741097,0.000084098836,0.003058499,0.000004138227,0.000119268996,0.00019196705,0.00012464527],"about_ca_topic_score_codex":0.00010662917,"about_ca_topic_score_gemma":0.00013788113,"teacher_disagreement_score":0.006799206,"about_ca_system_score_codex":0.00003307611,"about_ca_system_score_gemma":0.00007804991,"threshold_uncertainty_score":0.736631},"labels":[],"label_agreement":null},{"id":"W4387662825","doi":"10.55458/neurolibre.00017","title":"A database of the healthy human spinal cord morphometryin the PAM50 template space","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada First Research Excellence Fund; Ministerstvo Zdravotnictví Ceské Republiky; European Commission; Natural Sciences and Engineering Research Council of Canada; Craig H. Neilsen Foundation","keywords":"Space (punctuation); Spinal cord; Computer science; Database; Medicine; Artificial intelligence; Operating system","score_opus":0.28777699163672305,"score_gpt":0.47059523930700226,"score_spread":0.1828182476702792,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387662825","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56463397,0.00083039864,0.12571037,0.28270158,0.0010430285,0.011591307,0.0011913829,0.0026004661,0.009697484],"genre_scores_gemma":[0.97057486,0.00047653238,0.019028606,0.002462489,0.00015388055,0.0003890368,0.0001327149,0.00008592853,0.006695977],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9986131,0.00004752151,0.00036788694,0.00044509495,0.0003087047,0.00021769907],"domain_scores_gemma":[0.99729085,0.00007876945,0.00030451754,0.002160964,0.0000893933,0.00007548962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002876226,0.00020462253,0.00032715785,0.000099163226,0.00019562757,0.0000146084585,0.0005523604,0.00008408631,0.00006395077],"category_scores_gemma":[0.00009296436,0.00011022194,0.00017174696,0.0004099885,0.00021797245,0.000016614456,0.0013505763,0.000995097,0.000019323643],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023848307,0.0017572792,0.039403796,0.007098384,0.0004916401,0.00015892445,0.00029410882,0.00018960753,0.09861968,0.19140947,0.6409524,0.017239861],"study_design_scores_gemma":[0.0037906652,0.003729341,0.46299973,0.008425919,0.0014914358,0.00063351117,0.0007743904,0.0024289356,0.08597452,0.14284927,0.28487715,0.0020251302],"about_ca_topic_score_codex":0.0007406377,"about_ca_topic_score_gemma":0.000037442165,"teacher_disagreement_score":0.42359594,"about_ca_system_score_codex":0.000049990387,"about_ca_system_score_gemma":0.00012773553,"threshold_uncertainty_score":0.449472},"labels":[],"label_agreement":null},{"id":"W4387703393","doi":"10.1101/2023.10.16.562599","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"UK Research and Innovation; Wellcome Trust","keywords":"Thalamus; Cerebellum; Neuroscience; Diffusion; Diffusion MRI; Biology; Anatomy; Psychology; Medicine; Physics; Magnetic resonance imaging","score_opus":0.04275811439867714,"score_gpt":0.27902090168843063,"score_spread":0.2362627872897535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387703393","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99677086,0.00028349765,0.0011827918,0.0005447874,0.00017886577,0.00083852507,0.0000445303,0.00015141912,0.000004724025],"genre_scores_gemma":[0.9912464,0.00030261508,0.008076983,0.000052865904,0.00005578432,0.00019755046,9.4476053e-7,0.00006002971,0.0000067983638],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983591,0.000061173036,0.0005367717,0.0005056087,0.00031006042,0.00022727376],"domain_scores_gemma":[0.99861634,0.00017474373,0.00031696656,0.00065452,0.00016624099,0.00007120084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032672237,0.00028445604,0.00047248942,0.00018185607,0.000068859124,0.000019339821,0.00027279768,0.00015040126,0.000004696528],"category_scores_gemma":[0.00015769257,0.00022771055,0.00007232467,0.00039488974,0.00021611515,0.000035985842,0.00026798347,0.0005115601,0.000001047372],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110978675,0.00052030914,0.30403215,0.0017373778,0.00005649397,0.000060684142,0.00019241119,0.000016298569,0.69164324,0.0013916144,0.00016784217,0.00007061278],"study_design_scores_gemma":[0.00034786158,0.000051847474,0.8202514,0.00046966493,0.00005584168,7.106079e-8,0.0000106281295,0.00010240921,0.17673105,0.000020180581,0.0017700096,0.00018902274],"about_ca_topic_score_codex":0.000040663897,"about_ca_topic_score_gemma":0.000005336396,"teacher_disagreement_score":0.51621926,"about_ca_system_score_codex":0.00004988263,"about_ca_system_score_gemma":0.00024043096,"threshold_uncertainty_score":0.92857665},"labels":[],"label_agreement":null},{"id":"W4387708434","doi":"10.21203/rs.3.rs-2476133/v2","title":"Unveiling the Axonal Connectivity Between the Precuneus and Temporal Pole: Structural Evidence from the Cingulum Pathways","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto; University Health Network","funders":"","keywords":"Cingulum (brain); Precuneus; Neuroscience; Functional connectivity; Anatomy; Psychology; Biology; Medicine; Magnetic resonance imaging; Diffusion MRI; Radiology; Cognition","score_opus":0.39882975641039914,"score_gpt":0.4940464859210959,"score_spread":0.09521672951069676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387708434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94559187,0.0026509496,0.0017626547,0.04565173,0.00011625375,0.0031283835,0.00061445107,0.00039333408,0.00009037342],"genre_scores_gemma":[0.9968977,0.00078007265,0.0005065519,0.00012910385,0.0008970377,0.00049530447,0.00011604222,0.00005521,0.0001229763],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9970678,0.0005716995,0.0002875908,0.0006604737,0.0009328899,0.0004795505],"domain_scores_gemma":[0.99174905,0.0061937664,0.00010603634,0.0015245281,0.00030067228,0.00012592206],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0018398958,0.00024891918,0.00031539175,0.000065839595,0.0009793593,0.00020728739,0.0008186045,0.00015785541,0.000021765982],"category_scores_gemma":[0.0016755015,0.00011969376,0.00012749241,0.00039550176,0.00080660486,0.00006328007,0.0019202704,0.003345851,0.000012326508],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019994284,0.00005474945,0.92056006,0.0009888498,0.00034074436,0.000095867406,0.003989503,0.0002708082,0.0034224628,0.0014917145,0.02200334,0.04658194],"study_design_scores_gemma":[0.00023025199,0.00014243742,0.93062574,0.0020213479,0.000092663926,0.000021803788,0.0010114774,0.0066227177,0.0019888931,0.05325507,0.0037361751,0.00025144033],"about_ca_topic_score_codex":0.0015205722,"about_ca_topic_score_gemma":0.00012607785,"teacher_disagreement_score":0.051763356,"about_ca_system_score_codex":0.000117270545,"about_ca_system_score_gemma":0.00031803807,"threshold_uncertainty_score":0.99895346},"labels":[],"label_agreement":null},{"id":"W4387731161","doi":"10.1101/2023.10.16.562488","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"HORIZON EUROPE Framework Programme; European Synchrotron Radiation Facility; Deutsches Elektronen-Synchrotron; European Commission; Lundbeckfonden; Scleroseforeningen","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Biology; Fractional anisotropy; Tractography; Anatomy; Neuroscience; Computer science; Magnetic resonance imaging; Medicine; Artificial intelligence","score_opus":0.051955037456250894,"score_gpt":0.28919226864616354,"score_spread":0.23723723118991263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387731161","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97636,0.00021031711,0.019011622,0.0027693443,0.00014215702,0.0007217755,0.0002968992,0.00048177535,0.0000060961984],"genre_scores_gemma":[0.98754907,0.00037078364,0.011236116,0.00032483155,0.00028249802,0.00010850147,0.0000010383562,0.000114208655,0.000012936118],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99810165,0.0000485508,0.0004735911,0.0006818906,0.00033503372,0.00035926537],"domain_scores_gemma":[0.9981665,0.00012534742,0.00030529525,0.001022578,0.0002420321,0.00013821872],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038866757,0.00031796837,0.00048983615,0.00021133687,0.0002581085,0.00006153968,0.0002761853,0.00023233381,0.000022081165],"category_scores_gemma":[0.00019847452,0.00026436654,0.000102386315,0.0006355656,0.00035189273,0.00006899223,0.0008960664,0.00072338665,0.000027361164],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040564413,0.00016909036,0.60128707,0.00065930834,0.00010320962,0.00003711565,0.00007391714,0.000022776963,0.39527687,0.0010368613,0.0012704944,0.000022722636],"study_design_scores_gemma":[0.00025594956,0.00002829778,0.92187643,0.00022495644,0.00008558839,1.749955e-7,0.000010007262,0.0010201634,0.07476889,0.000015216372,0.0014446595,0.00026963933],"about_ca_topic_score_codex":0.000012113418,"about_ca_topic_score_gemma":6.267337e-7,"teacher_disagreement_score":0.3205894,"about_ca_system_score_codex":0.00012033348,"about_ca_system_score_gemma":0.00010659535,"threshold_uncertainty_score":0.99998087},"labels":[],"label_agreement":null},{"id":"W4387772054","doi":"10.1093/braincomms/fcad279","title":"Assessment of white matter hyperintensity severity using multimodal magnetic resonance imaging","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Fonds de Recherche du Québec - Santé; Alzheimer Society; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Jean-Louis Lévesque","keywords":"Hyperintensity; White matter; Fluid-attenuated inversion recovery; Magnetic resonance imaging; Medicine; Leukoaraiosis; Dementia; Pathology; Cognitive decline; Psychology; Cardiology; Radiology; Disease","score_opus":0.09996895150362162,"score_gpt":0.4101687974468111,"score_spread":0.3101998459431895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387772054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8174003,0.00086259923,0.046239268,0.11722726,0.00007838885,0.0017372533,0.00018793647,0.0011581501,0.0151088685],"genre_scores_gemma":[0.803002,0.00009403255,0.19514073,0.0012023759,0.000011292258,0.00005256825,0.00004469806,0.000021010663,0.00043128635],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99921536,0.00005955564,0.00024927707,0.00019025036,0.00012354922,0.00016203042],"domain_scores_gemma":[0.99772924,0.00016842797,0.00008251883,0.0018139841,0.00015230826,0.00005353038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018449816,0.00009485298,0.00017702268,0.00010696016,0.0002865193,0.000008151944,0.00033434524,0.000025238234,0.0000476238],"category_scores_gemma":[0.000066370645,0.000101270954,0.00006677942,0.0004650473,0.0002271652,0.000064013024,0.00063079316,0.0002273552,0.000016154874],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000709022,0.0002031848,0.95407176,0.00004275493,0.0000049616233,0.00000475105,0.00018024755,0.000053380674,0.031729575,0.0016690465,0.004791333,0.007241891],"study_design_scores_gemma":[0.00020448885,0.000011634984,0.84978104,0.00006291699,0.000017991753,0.00004250487,0.00006523019,0.12845561,0.00015115307,0.00050154614,0.020624973,0.00008089657],"about_ca_topic_score_codex":0.000060964616,"about_ca_topic_score_gemma":0.0000053027243,"teacher_disagreement_score":0.14890146,"about_ca_system_score_codex":0.000051580293,"about_ca_system_score_gemma":0.000056613488,"threshold_uncertainty_score":0.41297096},"labels":[],"label_agreement":null},{"id":"W4387799082","doi":"10.1097/j.pain.0000000000003069","title":"Electrostimulation of the white matter of the posterior insula and medial operculum: perception of vibrations, heat, and pain","year":2023,"lang":"en","type":"review","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Université du Québec en Outaouais; Montreal Neurological Institute and Hospital; Université de Sherbrooke; Université de Montréal","funders":"","keywords":"White matter; Operculum (bryozoa); Insula; Sensation; Medicine; Thalamus; Stimulation; Nociception; Neuroscience; Psychology; Audiology; Anesthesia; Magnetic resonance imaging; Radiology; Biology; Internal medicine","score_opus":0.05762826270974261,"score_gpt":0.3627086908064472,"score_spread":0.30508042809670455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387799082","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02845124,0.9097152,0.033036616,0.014733232,0.00016846354,0.012853446,0.00054897164,0.00020016327,0.00029266963],"genre_scores_gemma":[0.028709395,0.9672151,0.002705388,0.0006398217,0.00009388788,0.00020036874,0.000112142894,0.00007356751,0.00025027886],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876577,0.00048766,0.00038860092,0.00015886164,0.00012634488,0.00007278163],"domain_scores_gemma":[0.9991354,0.00026822212,0.00019875796,0.00032925795,0.00004838612,0.000019972294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090228114,0.00011929079,0.00044425018,0.00006170208,0.000044803466,0.000004538677,0.000087704095,0.00007939443,0.000012412604],"category_scores_gemma":[0.00025825785,0.00006774903,0.0001069641,0.0002550716,0.0001293052,0.00002428664,0.00008158161,0.00015186172,5.6653164e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002905489,0.00013158954,0.024440333,0.027523166,0.00008600123,6.211208e-7,0.00076082145,0.000008069831,0.016351564,0.0002146467,0.0022175522,0.9282366],"study_design_scores_gemma":[0.002680196,0.0016218382,0.34281313,0.1287253,0.006557255,0.00045691727,0.0006961439,0.01950672,0.0013101582,0.0048489077,0.48896784,0.0018156099],"about_ca_topic_score_codex":0.000014430311,"about_ca_topic_score_gemma":0.0000035576202,"teacher_disagreement_score":0.926421,"about_ca_system_score_codex":0.000018886973,"about_ca_system_score_gemma":0.000051570696,"threshold_uncertainty_score":0.27627254},"labels":[],"label_agreement":null},{"id":"W4387826906","doi":"10.1016/j.neurobiolaging.2023.10.007","title":"Frontoparietal function and underlying structure reflect capacity for motor skill acquisition during healthy aging","year":2023,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Mitacs; Michael Smith Health Research BC","keywords":"Motor skill; Psychology; Dreyfus model of skill acquisition; Diffusion MRI; White matter; Neuroscience; Physical medicine and rehabilitation; Audiology; Medicine; Magnetic resonance imaging","score_opus":0.09228399696588749,"score_gpt":0.37213687519070904,"score_spread":0.2798528782248215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387826906","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9881175,0.000050037175,0.009074545,0.0018046815,0.00011855992,0.00045792366,0.000034623357,0.00032108184,0.000021040476],"genre_scores_gemma":[0.9913627,0.000053773234,0.0077835196,0.00055278576,0.000085205385,0.00003440684,0.000063231455,0.000023756622,0.000040635157],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991592,0.00002827387,0.00019954622,0.00033048747,0.00004820025,0.00023427953],"domain_scores_gemma":[0.9995082,0.00009782169,0.00011246199,0.00018118732,0.00004926463,0.000051079984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000830922,0.00011629057,0.0002157374,0.00014545332,0.00020841567,0.000006511108,0.000044411117,0.0000664786,0.000004325641],"category_scores_gemma":[0.000026553436,0.00011407702,0.000051560044,0.00015235778,0.00009136545,0.00007322378,0.00004453705,0.00018325483,7.1189623e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001461981,0.000020033858,0.016588263,0.00032524279,0.000019542807,0.0000020952566,0.00013268502,0.000049168717,0.98048854,0.0006058483,0.00009723918,0.001525135],"study_design_scores_gemma":[0.0023175513,0.0010505659,0.88584983,0.00018899603,0.00014212714,0.0001940755,0.00013601616,0.0013448683,0.095113896,0.012539338,0.0008379168,0.00028483916],"about_ca_topic_score_codex":0.000011378432,"about_ca_topic_score_gemma":0.000003380657,"teacher_disagreement_score":0.88537467,"about_ca_system_score_codex":0.000030495248,"about_ca_system_score_gemma":0.0000152379525,"threshold_uncertainty_score":0.4651926},"labels":[],"label_agreement":null},{"id":"W4387899515","doi":"10.3389/fnana.2023.1214629","title":"The anatomy of the four streams of the prefrontal cortex. Preliminary evidence from a population based high definition tractography study","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Uncinate fasciculus; Neuroscience; Prefrontal cortex; Tractography; Cingulum (brain); Connectome; Population; Psychology; Insula; Diffusion MRI; Functional connectivity; Fractional anisotropy; Cognition; Medicine; Magnetic resonance imaging","score_opus":0.04578174593541029,"score_gpt":0.3191902104755592,"score_spread":0.2734084645401489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387899515","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99527556,0.00013258081,0.00089871476,0.0016044988,0.00029099066,0.0016353211,0.000050293183,0.0000793038,0.00003272987],"genre_scores_gemma":[0.99782884,0.000081481434,0.0017302512,0.00010331382,0.000018979452,0.00017644008,0.000016704329,0.000024568502,0.000019409652],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985287,0.00018944313,0.00040474287,0.00029824857,0.00040785142,0.0001710085],"domain_scores_gemma":[0.99844056,0.0002924462,0.00030379265,0.0008664849,0.000064620195,0.000032072392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001752722,0.00014247932,0.00022918779,0.00013074759,0.000166066,0.000010401213,0.0004228333,0.000046848458,0.000002703742],"category_scores_gemma":[0.00018543327,0.00008175629,0.00015605826,0.0011258459,0.00015196897,0.0000944845,0.000114812974,0.00030008698,4.2010194e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001940915,0.00020629416,0.99317986,0.000023556935,0.000021805075,0.0000071159,0.00013680609,0.000080778904,0.0008864949,0.000085962754,0.0010109746,0.0041662334],"study_design_scores_gemma":[0.00060057914,0.00017793021,0.9894606,0.00020946303,0.00010363695,0.000002681602,0.000334841,0.004095617,0.0012790048,0.0035473723,0.00012036605,0.00006791283],"about_ca_topic_score_codex":0.0004701098,"about_ca_topic_score_gemma":0.000054400636,"teacher_disagreement_score":0.0040983204,"about_ca_system_score_codex":0.000040938212,"about_ca_system_score_gemma":0.00005386811,"threshold_uncertainty_score":0.33339247},"labels":[],"label_agreement":null},{"id":"W4388106547","doi":"10.1101/2023.10.29.23297734","title":"White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"National Health and Medical Research Council; Sociedade Beneficente Israelita Brasileira Albert Einstein; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; Michael Smith Health Research BC","keywords":"Corticospinal tract; Hyperintensity; Motor impairment; Stroke (engine); Physical medicine and rehabilitation; Lesion; Cardiology; White matter; Psychology; Internal medicine; Brain damage; Medicine; Magnetic resonance imaging; Psychiatry; Diffusion MRI; Radiology","score_opus":0.13948705139272027,"score_gpt":0.3540826914950334,"score_spread":0.21459564010231313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388106547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9778382,0.000059428174,0.007617486,0.012683062,0.000109151115,0.0007438591,0.00033909883,0.0004259525,0.000183741],"genre_scores_gemma":[0.9777795,0.00007245058,0.011324073,0.0005979195,0.0001570787,0.00042815512,0.00010952396,0.000098830445,0.009432476],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984802,0.000050156388,0.00040946627,0.00057482696,0.00023108048,0.00025424937],"domain_scores_gemma":[0.9986538,0.00012282789,0.00014939993,0.0008140183,0.00009856516,0.0001613337],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018113783,0.00030565812,0.0005152943,0.00019557831,0.000099200304,0.00005194831,0.00013745176,0.00020337764,0.000049556973],"category_scores_gemma":[0.00009871683,0.00027432753,0.00015470963,0.00007322188,0.00015426478,0.000049054168,0.00040524427,0.0011733626,0.00009050412],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025195679,0.000030544314,0.99901634,0.00014546615,0.000040287294,0.000053308755,0.000089427434,0.000007446735,0.00017145582,0.00002816308,0.00032200397,0.00007036568],"study_design_scores_gemma":[0.0001929813,0.000042659372,0.9964986,0.00017126279,0.00021579221,0.000025805353,0.000050604518,0.00021713335,0.000047808517,0.0012802841,0.0010294138,0.00022765595],"about_ca_topic_score_codex":0.000016861472,"about_ca_topic_score_gemma":0.0000025317518,"teacher_disagreement_score":0.012085143,"about_ca_system_score_codex":0.00003793178,"about_ca_system_score_gemma":0.00003417075,"threshold_uncertainty_score":0.9999709},"labels":[],"label_agreement":null},{"id":"W4388173883","doi":"10.1126/sciadv.adh9853","title":"The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity","year":2023,"lang":"en","type":"article","venue":"Science Advances","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); International Collaboration On Repair Discoveries; University of British Columbia","funders":"","keywords":"Myelin; Magnetic resonance imaging; Computer science; Context (archaeology); Spinal cord; Biomedical engineering; Artificial intelligence; Radiology; Medicine; Neuroscience; Biology; Central nervous system","score_opus":0.04572890420358438,"score_gpt":0.3791686319174054,"score_spread":0.333439727713821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388173883","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7023566,0.0002792492,0.2724381,0.022625951,0.00015511789,0.0013906028,0.000014742722,0.0006400945,0.00009958113],"genre_scores_gemma":[0.93678355,0.00015665796,0.06234461,0.00035628886,0.000054754757,0.00011918508,0.000005093686,0.000013282868,0.0001665719],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990098,0.00000991948,0.0001085897,0.0003638269,0.0001792617,0.00032858952],"domain_scores_gemma":[0.99914694,0.0003010425,0.00004039257,0.00027661552,0.0001610663,0.00007395328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052732613,0.00009056891,0.000101297366,0.00006078469,0.0007542728,0.0000852997,0.00008683489,0.000014581898,7.210252e-7],"category_scores_gemma":[0.00022671002,0.000044113895,0.000016829696,0.0005352207,0.00062908814,0.0003438765,0.000079559555,0.00011220903,0.0000034038433],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001324626,0.000016854015,0.0017061745,0.000020157906,0.0000025725199,0.000009484388,0.00013021365,0.000057317182,0.7944099,0.0018989821,0.00009817658,0.20151773],"study_design_scores_gemma":[0.00047506302,0.00021047899,0.007974968,0.00014292037,0.00002331628,0.00008274629,0.00034520138,0.02703654,0.8690709,0.052761413,0.041652042,0.00022443186],"about_ca_topic_score_codex":0.000004360732,"about_ca_topic_score_gemma":0.000004139129,"teacher_disagreement_score":0.23442699,"about_ca_system_score_codex":0.000019523655,"about_ca_system_score_gemma":0.000042370822,"threshold_uncertainty_score":0.58013326},"labels":[],"label_agreement":null},{"id":"W4388266230","doi":"10.1016/j.jcjd.2023.10.278","title":"CEREBRAL WHITE MATTER LESIONS AND ITS ASSOCIATIONS WITH BRAIN PULSATILITY: AN MRI, NIRS, AND TCD STUDY","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; White matter; Hyperintensity; Magnetic resonance imaging; Radiology","score_opus":0.044158514499392905,"score_gpt":0.31236585155468,"score_spread":0.2682073370552871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388266230","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97834617,0.000091288384,0.000021236823,0.021073839,0.000016192716,0.00024664158,0.000067213274,0.0000224796,0.00011496075],"genre_scores_gemma":[0.99788517,0.00000414514,0.0006488671,0.0010474747,0.00005013863,0.000010224752,0.000012576925,0.000018833214,0.00032255313],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935484,0.000035611884,0.0001728219,0.00013072904,0.00009531767,0.00021069648],"domain_scores_gemma":[0.99912065,0.00006676876,0.00009329456,0.00012933405,0.0001129313,0.0004769938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019526717,0.00008562783,0.00018504688,0.00022936532,0.00018069486,0.000044485838,0.000059625276,0.000027807659,0.00003788489],"category_scores_gemma":[0.00007627473,0.0000706022,0.000019751456,0.00024773297,0.000051267467,0.00015613272,0.000011869759,0.0001840825,0.0000043698924],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000010384808,0.000022476488,0.9929392,0.000008418559,0.000024416488,0.000013659693,0.0003678393,0.000003045523,0.00012502246,0.000056362664,0.0059034387,0.00053513254],"study_design_scores_gemma":[0.00040027167,0.00028145264,0.99680614,0.00004523955,0.000066198045,0.00001314455,0.00040267094,0.000130443,0.000047470952,0.00053903135,0.0011948969,0.00007306298],"about_ca_topic_score_codex":0.000059418195,"about_ca_topic_score_gemma":0.0020534212,"teacher_disagreement_score":0.020026365,"about_ca_system_score_codex":0.000038804097,"about_ca_system_score_gemma":0.00020765579,"threshold_uncertainty_score":0.28790742},"labels":[],"label_agreement":null},{"id":"W4388303642","doi":"10.1016/j.nicl.2023.103533","title":"Detecting conversion from mild cognitive impairment to Alzheimer’s disease using FLAIR MRI biomarkers","year":2023,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; Baycrest Hospital; Sunnybrook Health Science Centre; Toronto Metropolitan University; University of Toronto; Health Sciences Centre; St. Michael's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Alzheimer Society; Alzheimer's Society; Consortium canadien en neurodégénérescence associée au vieillissement; Government of Ontario","keywords":"Fluid-attenuated inversion recovery; White matter; Medicine; Brain size; Cerebrospinal fluid; Neuroimaging; Magnetic resonance imaging; Grey matter; Nuclear medicine; Internal medicine; Radiology","score_opus":0.2626896449891431,"score_gpt":0.4752544071267235,"score_spread":0.2125647621375804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388303642","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838916,0.000053502543,0.007875008,0.0053648343,0.00030740866,0.0012992539,0.00013425948,0.0009613697,0.00011273058],"genre_scores_gemma":[0.97959006,0.000118671116,0.013902042,0.0057468205,0.0003356191,0.00006601733,0.00010438581,0.00008144347,0.000054930555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99778205,0.00012318479,0.0005539887,0.00087753846,0.00028359995,0.00037965277],"domain_scores_gemma":[0.9976677,0.0008963442,0.00013340285,0.0005586023,0.00011248904,0.00063151185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031659502,0.00022024369,0.00034186442,0.00015574512,0.00019725216,0.000027635624,0.00015110231,0.0000758006,0.000059949558],"category_scores_gemma":[0.000711837,0.00021763789,0.00025658758,0.00059327326,0.00016264556,0.00008846213,0.00030372426,0.00040581622,0.00032835512],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008404875,0.0023786589,0.80175066,0.00016074293,0.00063385087,0.0050158645,0.0003495088,0.00015710221,0.05053623,0.00004146195,0.065527655,0.06504338],"study_design_scores_gemma":[0.0034016771,0.000794457,0.9413213,0.00048649593,0.0010094325,0.000029171582,0.00018587233,0.034999363,0.009351742,0.00040101542,0.0074857976,0.0005336776],"about_ca_topic_score_codex":0.00003287253,"about_ca_topic_score_gemma":8.4284017e-7,"teacher_disagreement_score":0.13957064,"about_ca_system_score_codex":0.000035542038,"about_ca_system_score_gemma":0.00009376066,"threshold_uncertainty_score":0.88750154},"labels":[],"label_agreement":null},{"id":"W4388598265","doi":"10.1111/psyp.14483","title":"Brains of endurance athletes differ in the association areas but not in the primary areas","year":2023,"lang":"en","type":"article","venue":"Psychophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Psychology; Brain size; Gray (unit); Athletes; Magnetic resonance imaging; Grey matter; Association (psychology); Neuroscience; Medicine; Physical therapy; Nuclear medicine","score_opus":0.053430097005919386,"score_gpt":0.3489260629725255,"score_spread":0.2954959659666061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388598265","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98147273,0.000026874233,0.00006657036,0.016528366,0.00003776158,0.00045118452,0.000020071288,0.00005466037,0.0013418001],"genre_scores_gemma":[0.9927794,0.00024233473,0.00015674325,0.006282698,0.00007969614,0.00024697618,0.00005590413,0.000009572226,0.000146675],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999186,0.000113889655,0.00019869456,0.00018869674,0.00013444632,0.00017828487],"domain_scores_gemma":[0.9989027,0.0005875294,0.000100942096,0.00037147198,0.000025754513,0.00001163278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023063911,0.00008130886,0.0001864755,0.00007744265,0.000031945376,0.0000030937397,0.00020350033,0.00005748932,0.0000042887877],"category_scores_gemma":[0.00013147284,0.000049033748,0.00005482332,0.00048785144,0.000057023182,0.000023740866,0.000022452694,0.00025206103,0.000015430514],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014983326,0.00038955372,0.05852553,0.000057728404,0.000013374198,0.00001457635,0.0011291069,0.000015998172,0.92422324,0.002051044,0.008757858,0.004672139],"study_design_scores_gemma":[0.0004131414,0.000057256806,0.9858705,0.00003527581,0.000006647151,0.000004957594,0.0000936578,0.00007345595,0.0015795737,0.009239466,0.002578892,0.00004720487],"about_ca_topic_score_codex":0.000023653047,"about_ca_topic_score_gemma":0.0000060742736,"teacher_disagreement_score":0.9273449,"about_ca_system_score_codex":0.000034051114,"about_ca_system_score_gemma":0.0000131015495,"threshold_uncertainty_score":0.19995382},"labels":[],"label_agreement":null},{"id":"W4388648711","doi":"10.1101/2023.11.13.23298482","title":"Connectome reorganization associated with temporal lobe pathology and its surgical resection","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Institute for Information and Communications Technology Promotion; National Science Foundation; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Institute for Basic Science; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Hospital for Sick Children; National Research Foundation of Korea; National Natural Science Foundation of China; Canada Research Chairs; China Postdoctoral Science Foundation; Inha University; National Research Foundation","keywords":"Connectome; Temporal lobe; Neuroscience; Psychology; Electrocorticography; Tractography; Diffusion MRI; Epilepsy; Medicine; Neuroimaging; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.09246074374099782,"score_gpt":0.3554091831884602,"score_spread":0.2629484394474624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388648711","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99145484,0.000104352664,0.0025362594,0.0038988667,0.00010035584,0.0006981916,0.000037247202,0.0009359859,0.00023388927],"genre_scores_gemma":[0.9967215,0.00033796547,0.00067582814,0.00009453079,0.000115301045,0.000117556534,0.0004771926,0.00007563217,0.0013845096],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987819,0.00007890875,0.00023481734,0.000540948,0.0001811818,0.0001822042],"domain_scores_gemma":[0.99906445,0.000113847505,0.00018078879,0.00033247372,0.0002182928,0.000090176465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002680608,0.00018324437,0.00033959068,0.00014653748,0.00008315839,0.000017767543,0.000077739634,0.00024471164,0.000019404739],"category_scores_gemma":[0.00040641232,0.00015603774,0.000034670797,0.00035316468,0.000072321614,0.000030315035,0.00020934759,0.00059165526,0.000012518718],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005015627,0.0004539412,0.9705946,0.00058419554,0.00019478757,0.0041036257,0.00029065803,0.00011620294,0.014174234,0.006350733,0.0020955207,0.0005399687],"study_design_scores_gemma":[0.0040831487,0.0014505584,0.93791753,0.0018404591,0.0005661825,0.0024602565,0.000060520688,0.0060816566,0.01896713,0.016092557,0.0093245935,0.0011553817],"about_ca_topic_score_codex":0.000008959545,"about_ca_topic_score_gemma":0.000014028657,"teacher_disagreement_score":0.032677013,"about_ca_system_score_codex":0.00006381348,"about_ca_system_score_gemma":0.00006147499,"threshold_uncertainty_score":0.6363034},"labels":[],"label_agreement":null},{"id":"W4388673090","doi":"10.1016/j.jadr.2023.100689","title":"A systematic review of abnormalities in intracortical myelin across psychiatric illnesses","year":2023,"lang":"en","type":"review","venue":"Journal of Affective Disorders Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"White matter; Neuroimaging; Neuroscience; Psychology; Schizophrenia (object-oriented programming); Major depressive disorder; Bipolar disorder; Temporal lobe; Psychiatry; Medicine; Cognition; Magnetic resonance imaging; Epilepsy","score_opus":0.05194091767584568,"score_gpt":0.44128540212396244,"score_spread":0.38934448444811676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388673090","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006943425,0.9957036,0.0007516529,0.00014217927,0.00022584682,0.0029482113,0.000012422673,0.00003927346,0.00010740053],"genre_scores_gemma":[0.00016923356,0.99882036,0.00045272504,0.00006723877,0.00007577281,0.00028508325,0.000012787441,0.000068964095,0.000047830486],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9953815,0.00023122603,0.0033693588,0.00028218498,0.0004805659,0.00025517857],"domain_scores_gemma":[0.9940697,0.0006026634,0.004337292,0.0005263718,0.00036421136,0.00009977304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015018876,0.00034192036,0.004171977,0.00044028106,0.000037920396,0.0000110204155,0.00015730876,0.0001497986,0.000007498718],"category_scores_gemma":[0.0033964815,0.00023551931,0.0010407588,0.0013990114,0.00011374297,0.00010083516,0.00006736151,0.00076388795,0.0000022507277],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000074784593,0.00021851413,0.000091169175,0.9688987,0.0002143691,0.0004786837,0.000044889046,6.5381386e-7,2.1386016e-7,0.000046863497,0.00041779678,0.029580666],"study_design_scores_gemma":[0.00016950075,0.0002616467,0.000100397745,0.9706854,0.003079141,0.0069940668,0.00012892582,0.0000011658313,0.0000016587553,0.0011155537,0.017243175,0.0002193715],"about_ca_topic_score_codex":0.000014441636,"about_ca_topic_score_gemma":0.000009293577,"teacher_disagreement_score":0.029361295,"about_ca_system_score_codex":0.00014910236,"about_ca_system_score_gemma":0.00045534884,"threshold_uncertainty_score":0.9604199},"labels":[],"label_agreement":null},{"id":"W4388749509","doi":"10.1101/2023.11.17.23297145","title":"The bidirectional effects between cognitive ability and brain morphology: A life course Mendelian randomization analysis","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; University of Toronto","funders":"ZonMw; Wellcome Trust","keywords":"Brain size; Brain morphometry; Cognition; Psychology; Cortex (anatomy); Cingulate cortex; White matter; Neuroscience; Developmental psychology; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.06258386717102385,"score_gpt":0.3827562947394861,"score_spread":0.3201724275684622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388749509","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7760872,0.0003220512,0.10726192,0.11321234,0.00013257388,0.0021067152,0.00015009896,0.000658334,0.000068768175],"genre_scores_gemma":[0.99456245,0.0002817468,0.0011520678,0.0023008676,0.00028005848,0.0007560003,0.00038682198,0.000039682785,0.00024033619],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983517,0.00025984796,0.00033645498,0.00061799475,0.0002290701,0.00020492522],"domain_scores_gemma":[0.9961295,0.0028554741,0.00021278208,0.00048453064,0.00018621601,0.00013145595],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084937096,0.00021534308,0.00057042885,0.00017844637,0.0002478801,0.000034802877,0.00011817732,0.00019217793,0.0000073146703],"category_scores_gemma":[0.0019889018,0.00015922086,0.00020931032,0.0005930813,0.00029793155,0.00002145617,0.00023120931,0.0007121363,0.0000084426665],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003001058,0.00010408032,0.9841806,0.00021354137,0.0026329209,0.000040873918,0.00010405743,0.000107542335,0.0008476579,0.00015057893,0.0055005564,0.0058174287],"study_design_scores_gemma":[0.001748126,0.000058796417,0.98065674,0.0000974971,0.004411692,0.000007992597,0.000025690531,0.0027462472,0.0007959974,0.0078266105,0.0014202807,0.00020432456],"about_ca_topic_score_codex":0.000041921354,"about_ca_topic_score_gemma":0.000009242337,"teacher_disagreement_score":0.21847521,"about_ca_system_score_codex":0.000033489236,"about_ca_system_score_gemma":0.00010599278,"threshold_uncertainty_score":0.6492838},"labels":[],"label_agreement":null},{"id":"W4388806341","doi":"10.1016/j.media.2023.103041","title":"WarpDrive: Improving spatial normalization using manual refinements","year":2023,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; Toronto Rehabilitation Institute; McGill University; Douglas Mental Health University Institute; Krembil Foundation; University of Toronto; University Health Network","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Eisai; Deutsche Forschungsgemeinschaft; Servier; EU Joint Programme – Neurodegenerative Disease Research; Northern California Institute for Research and Education; National Institute of Mental Health; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Spatial normalization; Normalization (sociology); Inference; Modalities; Pattern recognition (psychology); Neuroimaging; Process (computing); Computer vision; Machine learning; Neuroscience; Psychology","score_opus":0.05912185879799546,"score_gpt":0.42084703398665946,"score_spread":0.361725175188664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388806341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15981258,0.000011809039,0.8369536,0.0021413965,0.000029297069,0.00015743164,0.0000098978635,0.00044158867,0.00044239915],"genre_scores_gemma":[0.96511394,0.000102564954,0.031841356,0.0011910493,0.00026007445,0.0000409015,0.0005360024,0.000035272395,0.00087883533],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985041,0.000027893757,0.00030891405,0.00031677782,0.0005925278,0.00024980708],"domain_scores_gemma":[0.9992216,0.00003541832,0.000090960646,0.00034680232,0.000106528176,0.00019868127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025394466,0.00011414914,0.00026598052,0.0004154349,0.00013057467,0.000020358777,0.00011954332,0.00006718849,0.00068507995],"category_scores_gemma":[0.00034204795,0.00010130724,0.0001670641,0.0020567814,0.00008777613,0.00009295217,0.00012955358,0.00017779485,0.000066088985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016683285,0.0014853472,0.27938572,0.00047964827,0.002645926,0.002504259,0.00052271265,0.0010762938,0.21795227,0.0007254654,0.016604112,0.47645146],"study_design_scores_gemma":[0.0006417712,0.00006686795,0.034661055,0.000042792333,0.0021275508,0.000028167768,0.000052561638,0.95153576,0.0062180054,0.00016912654,0.004249609,0.00020671441],"about_ca_topic_score_codex":0.00032761533,"about_ca_topic_score_gemma":0.000024599878,"teacher_disagreement_score":0.9504595,"about_ca_system_score_codex":0.00004748712,"about_ca_system_score_gemma":0.00005275671,"threshold_uncertainty_score":0.7501145},"labels":[],"label_agreement":null},{"id":"W4388887794","doi":"10.1093/braincomms/fcad313","title":"Longitudinal evolution of diffusion metrics after left hemisphere ischaemic stroke","year":2023,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Toronto Rehabilitation Institute; Heart and Stroke Foundation; University of Toronto; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; University Health Network; Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Stroke (engine); Lesion; Medicine; Magnetic resonance imaging; Pathology; Radiology; Physics","score_opus":0.09061495565941778,"score_gpt":0.3774562144362619,"score_spread":0.28684125877684413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388887794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8223779,0.0030659996,0.10285019,0.05729755,0.00007534306,0.0015144772,0.00025729463,0.0015793414,0.010981901],"genre_scores_gemma":[0.9734707,0.0007002322,0.023082262,0.00017837888,0.000021371578,0.00010804424,0.00010170807,0.000023068187,0.0023142493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920505,0.00003861193,0.00025840013,0.00017602224,0.0001703493,0.0001515377],"domain_scores_gemma":[0.9976089,0.0003326824,0.00010104943,0.0017561624,0.00013566988,0.000065524546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016050492,0.00009465394,0.00016286847,0.00019974758,0.00014251746,0.0000066317843,0.0003565023,0.000057997975,0.000051903455],"category_scores_gemma":[0.00027323025,0.00009414214,0.00009126034,0.00081496657,0.00016739246,0.0000645588,0.0004016769,0.00023576523,0.000042903357],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016016951,0.0013247994,0.571139,0.00031337704,0.00011316424,0.000014406353,0.0007117692,0.00006801095,0.30410966,0.03962599,0.055533543,0.026886106],"study_design_scores_gemma":[0.0012962461,0.000206554,0.7481722,0.0003647107,0.00019234512,0.00012066511,0.000534881,0.01981823,0.0070701293,0.009101582,0.21271786,0.00040459645],"about_ca_topic_score_codex":0.00004062761,"about_ca_topic_score_gemma":0.00002367411,"teacher_disagreement_score":0.29703954,"about_ca_system_score_codex":0.000080580205,"about_ca_system_score_gemma":0.000055307475,"threshold_uncertainty_score":0.3839005},"labels":[],"label_agreement":null},{"id":"W4388921312","doi":"10.1016/j.celrep.2023.113487","title":"Development of white matter fiber covariance networks supports executive function in youth","year":2023,"lang":"en","type":"article","venue":"Cell Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Canadian Institutes of Health Research; National Institute of Biomedical Imaging and Bioengineering; University of Pennsylvania; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"White matter; Covariance; Function (biology); Fiber; White (mutation); Psychology; Covariance function; Neuroscience; Biology; Developmental psychology; Chemistry; Cell biology; Medicine; Mathematics; Genetics; Statistics; Gene; Magnetic resonance imaging","score_opus":0.040148557127289895,"score_gpt":0.29463122407197573,"score_spread":0.25448266694468585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388921312","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91677475,0.000051104333,0.055462398,0.00030994613,0.00021522412,0.00093345664,0.0000043080845,0.00034265962,0.025906175],"genre_scores_gemma":[0.9786919,0.000012828591,0.011936347,0.00018891324,0.000026786614,0.000059663234,0.00014431677,0.000022568018,0.008916676],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904907,0.000006779611,0.0003942099,0.0002620952,0.000119791504,0.00016804617],"domain_scores_gemma":[0.99940157,0.000011142117,0.00018331355,0.00030928504,0.000047178088,0.00004752426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015749628,0.0000890498,0.0001614533,0.000091714384,0.000045992223,0.0000029610173,0.00002441606,0.000047546815,0.00012437708],"category_scores_gemma":[0.000007791631,0.000085288564,0.000033042947,0.00035411224,0.0000251914,0.00003613813,0.000060026483,0.00011732878,0.000023803721],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022978835,0.0006454019,0.8947699,0.00036097603,0.000045567922,0.0027680986,0.0061892085,0.0044250493,0.01568714,0.000064903346,0.06262764,0.012186289],"study_design_scores_gemma":[0.0005156677,0.00006616969,0.8669104,0.00033559112,0.00007800468,0.00025797103,0.00037407075,0.0006735303,0.025898654,0.0007655478,0.103769824,0.0003545661],"about_ca_topic_score_codex":0.0000037744055,"about_ca_topic_score_gemma":0.0000011354405,"teacher_disagreement_score":0.061917175,"about_ca_system_score_codex":0.000034028606,"about_ca_system_score_gemma":0.000057934412,"threshold_uncertainty_score":0.34779668},"labels":[],"label_agreement":null},{"id":"W4389026709","doi":"10.1096/fasebj.30.1_supplement.1037.3","title":"Quantification of the 3D Orientation of Vascular Canals in Cortical Bone","year":2016,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orientation (vector space); Cortical bone; Perpendicular; Cortex (anatomy); Anatomy; Biomedical engineering; Materials science; Plane (geometry); Geometry; Geology; Biology; Mathematics; Medicine; Neuroscience","score_opus":0.06234886732221419,"score_gpt":0.3503181500232802,"score_spread":0.28796928270106603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389026709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9400776,0.000057656205,0.055589665,0.0040020896,0.000028978475,0.00015586868,0.000004047324,0.000006046918,0.00007803596],"genre_scores_gemma":[0.99837023,0.00012906709,0.0013311742,0.00007470687,0.00002402219,0.00000475375,5.346978e-7,0.0000047861527,0.000060715996],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994235,0.000054679476,0.00024502238,0.0000532774,0.00015871573,0.00006480877],"domain_scores_gemma":[0.99941653,0.00007381145,0.00016841142,0.00023469566,0.00008279146,0.00002373281],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031420312,0.000034402587,0.00008987632,0.000035460816,0.000042957032,0.0000020351472,0.00008208735,0.000014334083,0.000023232047],"category_scores_gemma":[0.00014395565,0.000014683314,0.000051263964,0.00014999192,0.00010470356,0.000031738004,0.000014165231,0.000112335365,0.000001082936],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002769663,0.000054668326,0.020602003,0.0000059813096,0.000007392211,0.0000011012328,0.00007091527,0.000016688056,0.97116745,0.0031844229,0.00010014961,0.0047615417],"study_design_scores_gemma":[0.0006580234,0.00006013262,0.28422806,0.0002057422,0.00006883812,0.00012533381,0.000078851364,0.00024154178,0.7102125,0.0035326842,0.0005509864,0.000037318598],"about_ca_topic_score_codex":0.000020275755,"about_ca_topic_score_gemma":0.0000048363486,"teacher_disagreement_score":0.26362604,"about_ca_system_score_codex":0.000026152222,"about_ca_system_score_gemma":0.000048821694,"threshold_uncertainty_score":0.059876814},"labels":[],"label_agreement":null},{"id":"W4389078794","doi":"10.1162/imag_a_00050","title":"White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"Vanderbilt University; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of Mental Health; National Institute on Aging; National Institutes of Health","keywords":"White matter; Gray (unit); Morphology (biology); Brain morphometry; Anatomy; Biology; Paleontology; Medicine; Magnetic resonance imaging","score_opus":0.03056917881249906,"score_gpt":0.35186490783382746,"score_spread":0.3212957290213284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389078794","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96637905,0.000029991927,0.0016075628,0.030628853,0.00027491714,0.00040144418,0.00009174888,0.0003973887,0.00018902015],"genre_scores_gemma":[0.97272193,0.000033036373,0.0004885478,0.02576898,0.00004657913,0.000035071953,0.00001965471,0.00004190212,0.00084432174],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99817324,0.00006372287,0.00027169686,0.0006324004,0.00023929785,0.0006196154],"domain_scores_gemma":[0.9990441,0.00012138436,0.00011272754,0.00052462646,0.000056725956,0.00014039855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023641773,0.00021023868,0.0002141634,0.00007365479,0.00055131986,0.00016049223,0.00030223315,0.0000472567,0.000062548796],"category_scores_gemma":[0.00017439203,0.00014766,0.0000626095,0.00071497,0.0010332665,0.00014534638,0.00025570934,0.0005582035,0.00010317417],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007996493,0.000018404908,0.8427455,0.0000106418065,0.0000010714945,0.000085549495,0.00008922555,0.00000829813,0.14698423,0.000025829457,0.009789791,0.00023349913],"study_design_scores_gemma":[0.0002559737,0.000020164458,0.9860666,0.000018805798,0.000016930413,0.0016824414,0.000025586693,0.0012291344,0.0017990011,0.00087637606,0.007864209,0.00014482143],"about_ca_topic_score_codex":0.000014162525,"about_ca_topic_score_gemma":7.2357153e-7,"teacher_disagreement_score":0.14518523,"about_ca_system_score_codex":0.000021999258,"about_ca_system_score_gemma":0.000022451746,"threshold_uncertainty_score":0.60214},"labels":[],"label_agreement":null},{"id":"W4389082732","doi":"10.1002/pbc.30787","title":"Higher order neurocognition in pediatric brain tumor survivors: What can we learn from white matter microstructure?","year":2023,"lang":"en","type":"article","venue":"Pediatric Blood & Cancer","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; Alberta Children's Hospital; University of Calgary","funders":"National Cancer Institute; St. Baldrick's Foundation","keywords":"Neurocognitive; Medicine; White matter; White (mutation); Pediatrics; Cognition; Psychiatry; Magnetic resonance imaging; Radiology; Genetics","score_opus":0.026041752452748448,"score_gpt":0.302363349720754,"score_spread":0.2763215972680056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389082732","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96319747,0.0026180593,0.00007424748,0.03187096,0.00053361105,0.0007933837,0.00020471652,0.0005343036,0.00017325308],"genre_scores_gemma":[0.9489224,0.026162662,0.0018399854,0.013066752,0.0046944623,0.0009433853,0.0004275647,0.00023656653,0.003706241],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99796206,0.000059107617,0.0004186684,0.0007268747,0.00030357932,0.0005297099],"domain_scores_gemma":[0.99893457,0.00015444015,0.00017632522,0.00044997942,0.00012089739,0.00016381891],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009498715,0.0003084651,0.00036277765,0.00044904108,0.00009236192,0.00007950698,0.00018803176,0.000110319525,0.000836473],"category_scores_gemma":[0.000037429014,0.00030005016,0.000093313734,0.0023070148,0.00004272436,0.00023618578,0.00011698878,0.00056252815,0.00019559714],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004385725,0.00011460934,0.96991414,0.00019962463,0.000013259703,0.0001081464,0.00021447129,0.000050681614,0.0010470488,0.000007864703,0.027147677,0.001138606],"study_design_scores_gemma":[0.0018275435,0.000064404354,0.98138285,0.00007181811,0.00048604392,0.000025586807,0.00006666427,0.00006166154,0.00041138657,0.0017102722,0.013439649,0.00045211584],"about_ca_topic_score_codex":0.00064393005,"about_ca_topic_score_gemma":0.0002879874,"teacher_disagreement_score":0.023544602,"about_ca_system_score_codex":0.0000501489,"about_ca_system_score_gemma":0.00013918149,"threshold_uncertainty_score":0.99994516},"labels":[],"label_agreement":null},{"id":"W4389091910","doi":"10.3389/fnana.2023.1240545","title":"Structural connectivity of cytoarchitectonically distinct human left temporal pole subregions: a diffusion MRI tractography study","year":2023,"lang":"en","type":"article","venue":"Frontiers in Neuroanatomy","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Japan Society for the Promotion of Science; National Institutes of Health; Tokyo Medical and Dental University; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Alliance for Research on Schizophrenia and Depression","keywords":"Cytoarchitecture; Tractography; Neuroscience; Diffusion MRI; Temporal lobe; Psychology; Magnetic resonance imaging; Medicine; Epilepsy","score_opus":0.03744864752543687,"score_gpt":0.3426132891846055,"score_spread":0.3051646416591686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389091910","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945255,0.000036953687,0.0024864879,0.0008775522,0.00011994515,0.0012611538,0.0000249334,0.00041087446,0.00025660652],"genre_scores_gemma":[0.99689996,0.000021834156,0.0027430363,0.00007713809,0.000029797779,0.00006741736,0.000041402498,0.000043412972,0.000075971264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983303,0.00010754553,0.0004279318,0.0005142142,0.0003000619,0.00031993582],"domain_scores_gemma":[0.9989839,0.00008361309,0.00015608862,0.00060475594,0.0000544063,0.00011723906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016387281,0.0002118027,0.0004674917,0.0005880037,0.00014261511,0.0000128911215,0.00023807817,0.00005662521,0.0000106672705],"category_scores_gemma":[0.000089787856,0.00019334031,0.00015712487,0.0010389779,0.000249023,0.00008124056,0.00013236879,0.00045553315,0.0000013974698],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008971185,0.0003776053,0.99381715,0.00003872478,0.000019216995,0.000117155556,0.00019727185,0.00000990265,0.002085143,0.0001656135,0.0013888689,0.0016936407],"study_design_scores_gemma":[0.0015005494,0.00045158324,0.99041885,0.000047104917,0.00004348224,0.000033325527,0.0003030253,0.0017405538,0.00039152216,0.0037488556,0.0011487933,0.00017234636],"about_ca_topic_score_codex":0.00012884318,"about_ca_topic_score_gemma":0.0000582598,"teacher_disagreement_score":0.003583242,"about_ca_system_score_codex":0.000037282083,"about_ca_system_score_gemma":0.000039377264,"threshold_uncertainty_score":0.78841895},"labels":[],"label_agreement":null},{"id":"W4389114783","doi":"","title":"Structural changes in white matter lesion patients and their correlation with cognitive impairment","year":2019,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cognitive impairment; White matter; Lesion; Cognition; Correlation; Medicine; Psychology; Neuroscience; Pathology; Magnetic resonance imaging; Radiology; Mathematics","score_opus":0.18009643986472218,"score_gpt":0.5104361970423364,"score_spread":0.33033975717761427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389114783","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968512,0.00041266202,0.0004144075,0.0004424117,0.000046598576,0.0011504297,0.00002751191,0.000021484962,0.0006332872],"genre_scores_gemma":[0.9981662,0.00068995217,0.00031212036,0.0005672476,0.000020897942,0.00004615616,0.000035356417,0.00002683762,0.00013525247],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99907947,0.000045806246,0.0002508378,0.00026749785,0.00019728171,0.0001591114],"domain_scores_gemma":[0.9992229,0.0000771908,0.00030557995,0.0001696172,0.00013906717,0.000085677144],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013609817,0.0001648822,0.0003309027,0.00029797314,0.00006183233,0.00010929208,0.00021254561,0.000040774914,0.0011649902],"category_scores_gemma":[0.000014703847,0.00011422856,0.000028411998,0.00029489756,0.00005653297,0.0005677487,0.00021395157,0.00022495692,0.0000051491315],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003082645,0.00008368292,0.9886406,0.000045718127,0.000016155493,0.000002891987,0.0001728764,0.000015533491,0.0043488736,0.0000055356563,0.0007421608,0.0056176907],"study_design_scores_gemma":[0.0010757982,0.000057645404,0.99187386,0.00065617915,0.000025218382,0.000015260135,0.000081539714,0.00023700921,0.005004445,0.000681301,0.00015426899,0.00013749299],"about_ca_topic_score_codex":0.00004916924,"about_ca_topic_score_gemma":0.000013056031,"teacher_disagreement_score":0.0054801977,"about_ca_system_score_codex":0.00004864498,"about_ca_system_score_gemma":0.000021300757,"threshold_uncertainty_score":0.99974805},"labels":[],"label_agreement":null},{"id":"W4389296200","doi":"10.1101/2023.12.02.569728","title":"Cortical Network Disruption is Minimal in Early Stages of Psychosis","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute; London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"National Institute of Mental Health; National Institutes of Health","keywords":"Psychosis; White matter; Voxel; Schizophrenia (object-oriented programming); Connectome; Neuroscience; Psychology; Diffusion MRI; Human Connectome Project; Magnetic resonance imaging; Medicine; Psychiatry; Functional connectivity; Radiology","score_opus":0.05740833260677875,"score_gpt":0.3263365423462528,"score_spread":0.26892820973947407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389296200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99116164,0.00022400163,0.005473355,0.0012050605,0.00025288996,0.00095572916,0.00017466987,0.0005465206,0.0000061542755],"genre_scores_gemma":[0.9687838,0.0005368914,0.02967099,0.0002331193,0.00026684208,0.00037537512,5.872595e-7,0.00012116433,0.000011235566],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978293,0.00005267593,0.0006260773,0.0007715599,0.0003078961,0.00041250058],"domain_scores_gemma":[0.99810135,0.000087671666,0.0003043632,0.0011234463,0.0002140227,0.00016915728],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030499382,0.00032048122,0.0005837133,0.00023030938,0.000055145,0.000036339836,0.00024848527,0.00031927045,0.000017843924],"category_scores_gemma":[0.00012568301,0.00034658558,0.0001522047,0.0007088797,0.00013958428,0.00005773813,0.00027569575,0.0008760394,0.000025422345],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013037656,0.00040559124,0.7613233,0.00065311015,0.000089272085,0.000074943004,0.000019329433,0.000053380198,0.23258622,0.001768881,0.0028859111,0.0000097030215],"study_design_scores_gemma":[0.00040856242,0.000112174646,0.9624056,0.00097043626,0.00011660624,1.7712724e-8,0.0000017869904,0.00037519998,0.033519495,0.000033442895,0.0017288895,0.00032776807],"about_ca_topic_score_codex":0.00005748172,"about_ca_topic_score_gemma":0.0000012216805,"teacher_disagreement_score":0.20108233,"about_ca_system_score_codex":0.00011673691,"about_ca_system_score_gemma":0.00013546342,"threshold_uncertainty_score":0.9998986},"labels":[],"label_agreement":null},{"id":"W4389327159","doi":"10.1162/imag_a_00055","title":"Robust frequency-dependent diffusional kurtosis computation using an efficient direction scheme, axisymmetric modelling, and spatial regularization","year":2023,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Congressionally Directed Medical Research Programs; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; U.S. Department of Defense","keywords":"Kurtosis; Computation; Rotational symmetry; Regularization (linguistics); Algorithm; Computer science; Scheme (mathematics); Mathematics; Applied mathematics; Statistical physics; Mathematical optimization; Physics; Mathematical analysis; Artificial intelligence; Statistics; Geometry","score_opus":0.1124566290593675,"score_gpt":0.34453630092826504,"score_spread":0.23207967186889755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389327159","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39101073,0.000016704644,0.6077925,0.00039479765,0.00012749982,0.00022301068,0.000005166275,0.00037444982,0.000055124347],"genre_scores_gemma":[0.9561099,0.000049495695,0.043367684,0.00027909846,0.000061027364,0.000017959466,0.000025416086,0.000027656237,0.00006176999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845,0.000036296336,0.00022158977,0.00061683246,0.00042162585,0.00025364774],"domain_scores_gemma":[0.99937254,0.000036942412,0.00011202859,0.0002289707,0.00011766552,0.00013188002],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020205039,0.0001409158,0.00013051667,0.0004403504,0.00042984585,0.000088851644,0.0000963166,0.000027539885,0.0000018946561],"category_scores_gemma":[0.00010290644,0.00014340633,0.000030528165,0.001362234,0.00015820502,0.00021791486,0.0000940181,0.00015946443,0.0000024309097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012532195,0.00022952586,0.02010969,0.000028885372,0.0000011702081,0.000025836056,0.00007666451,0.5569221,0.41170442,0.00048649285,0.000028488936,0.010374225],"study_design_scores_gemma":[0.00022941822,0.000040282634,0.032697264,0.000035523062,0.000016968537,0.000116311916,0.000011056437,0.96203685,0.003973777,0.0006712969,0.00004441736,0.00012682169],"about_ca_topic_score_codex":0.00014739737,"about_ca_topic_score_gemma":0.000001128734,"teacher_disagreement_score":0.5650992,"about_ca_system_score_codex":0.00006645239,"about_ca_system_score_gemma":0.00004896669,"threshold_uncertainty_score":0.58479404},"labels":[],"label_agreement":null},{"id":"W4389393863","doi":"10.1101/2023.12.05.23299222","title":"BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Pfizer; Novartis Pharmaceuticals Corporation; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; Alzheimer's Association","keywords":"Ethnic group; Voxel; Neuroimaging; Race (biology); Estimation; Field (mathematics); Stability (learning theory); Statistics; Psychology; Mathematics; Computer science; Artificial intelligence; Biology; Engineering; Machine learning; Neuroscience","score_opus":0.06594420547756673,"score_gpt":0.3812673033361469,"score_spread":0.31532309785858015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389393863","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97521704,0.00011338553,0.016549276,0.0066021946,0.000048473383,0.00057502417,0.000034493703,0.00037859206,0.00048153725],"genre_scores_gemma":[0.9615972,0.00050620997,0.036517773,0.00046514976,0.000044834935,0.000078281846,0.000018997198,0.000032530552,0.00073900295],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989139,0.000024552966,0.00032834406,0.0004087549,0.00018381371,0.0001406225],"domain_scores_gemma":[0.99834085,0.00054803654,0.0002050515,0.00071518845,0.00010842134,0.000082475155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017797836,0.00017368273,0.00037038018,0.00008116543,0.000045124725,0.000010571169,0.00016610847,0.00015518036,0.000015958947],"category_scores_gemma":[0.0013142809,0.00016623098,0.00006945509,0.00017885162,0.00011582932,0.000038335747,0.00044821374,0.0005939858,0.0000063837138],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053037005,0.0013817921,0.66815025,0.01502349,0.00050905504,0.0005532341,0.0025591836,0.014138961,0.11277622,0.022479035,0.023354368,0.13854405],"study_design_scores_gemma":[0.00073219364,0.00025959042,0.8747379,0.0015340643,0.00024622722,0.000054994885,0.00002922482,0.012759535,0.04791897,0.057116974,0.004089615,0.0005206758],"about_ca_topic_score_codex":0.000059243826,"about_ca_topic_score_gemma":0.000004369104,"teacher_disagreement_score":0.2065877,"about_ca_system_score_codex":0.0000170955,"about_ca_system_score_gemma":0.0000524327,"threshold_uncertainty_score":0.6778703},"labels":[],"label_agreement":null},{"id":"W4389438701","doi":"10.1212/wnl.90.15_supplement.p3.069","title":"Microstructural Changes in the Thalamus and Putamen, as Measured by Diffusion Tensor Imaging, Correlate with Gait Abnormalities in Parkinson’s Disease (P3.069)","year":2018,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Putamen; Diffusion MRI; Gait; Medicine; Thalamus; Parkinson's disease; Neuroscience; Physical medicine and rehabilitation; Disease; Psychology; Internal medicine; Radiology; Magnetic resonance imaging","score_opus":0.020025872185449416,"score_gpt":0.2813415149341007,"score_spread":0.26131564274865127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389438701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97409916,0.00028065566,0.00005562695,0.024760108,0.000039210936,0.00048599753,0.000015684562,0.00006927336,0.00019425541],"genre_scores_gemma":[0.9870896,0.00021159914,0.00018473204,0.012213941,0.0000573908,0.00010876686,0.000015707315,0.000021889047,0.000096415955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99904245,0.000088329485,0.00013647946,0.0003418974,0.00011888782,0.00027194992],"domain_scores_gemma":[0.99946904,0.00006880073,0.000063063715,0.00029118586,0.000036534395,0.00007135372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009035037,0.00015123609,0.0001768972,0.0000901916,0.00007870113,0.000016361866,0.00011402485,0.00004185954,0.000016167445],"category_scores_gemma":[0.00003760529,0.000098925615,0.000016083217,0.00013811373,0.00041536117,0.00004721787,0.00005597182,0.00030956801,0.0000033575595],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016060203,0.000098976794,0.9813529,0.000024396551,0.0000035324929,0.00034568232,0.00089325896,9.509688e-7,0.010231887,0.00021625285,0.001198441,0.0040276973],"study_design_scores_gemma":[0.0011889571,0.00081272563,0.93870056,0.000025562074,0.000027768994,0.0008714051,0.00005602357,0.00056570943,0.00042095638,0.0011345024,0.056069158,0.00012667033],"about_ca_topic_score_codex":0.00022228138,"about_ca_topic_score_gemma":0.00020243792,"teacher_disagreement_score":0.054870717,"about_ca_system_score_codex":0.0000109910925,"about_ca_system_score_gemma":0.000019502042,"threshold_uncertainty_score":0.40340695},"labels":[],"label_agreement":null},{"id":"W4389447579","doi":"10.1212/wnl.88.16_supplement.p1.156","title":"Assessment of radiation-induced white matter changes using myelin water imaging (P1.156)","year":2017,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"White matter; Medicine; White (mutation); Myelin; Radiation; Nuclear medicine; Internal medicine; Magnetic resonance imaging; Chemistry; Radiology; Optics; Physics; Central nervous system; Biochemistry","score_opus":0.07265836014425912,"score_gpt":0.39479148758252247,"score_spread":0.32213312743826333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389447579","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95661324,0.000010104505,0.0051631005,0.035952065,0.00013697085,0.00028404235,0.0000049302225,0.000063789266,0.0017717377],"genre_scores_gemma":[0.99079126,0.00001651142,0.0040226183,0.0049006543,0.0001380875,0.000028715229,0.000009422686,0.000026870062,0.00006587502],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924356,0.000027286034,0.00016517234,0.00026093886,0.00009155598,0.00021149254],"domain_scores_gemma":[0.9990669,0.00001963223,0.0001447155,0.000674182,0.000047010257,0.00004755884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008412325,0.00010364106,0.00020628114,0.00008710719,0.00013413325,0.000015843527,0.00015245505,0.000045970064,0.00012563827],"category_scores_gemma":[0.000013324291,0.00008389762,0.000041674713,0.000023216297,0.000085178865,0.00006723702,0.00011449672,0.00019969429,0.000011489941],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002779404,0.000052524436,0.59233147,0.00002547099,0.0000083795,0.000029202547,0.000046068963,0.000015303864,0.40238255,0.00016669852,0.0002591923,0.004655302],"study_design_scores_gemma":[0.0006224513,0.00019442663,0.92091495,0.000014533693,0.000060346523,0.00017478091,0.0000024888875,0.0059020403,0.06281457,0.00052819104,0.0086548645,0.000116372175],"about_ca_topic_score_codex":0.000041677966,"about_ca_topic_score_gemma":0.00000332969,"teacher_disagreement_score":0.339568,"about_ca_system_score_codex":0.0000115183375,"about_ca_system_score_gemma":0.000019214976,"threshold_uncertainty_score":0.34212458},"labels":[],"label_agreement":null},{"id":"W4389454614","doi":"10.1007/s10548-023-01020-4","title":"Correlation of Cognitive Reappraisal and the Microstructural Properties of the Forceps Minor: A Deductive Exploratory Diffusion Tensor Imaging Study","year":2023,"lang":"en","type":"article","venue":"Brain Topography","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Statistical parametric mapping; Psychology; White matter; Correlation; Population; Medicine; Mathematics; Magnetic resonance imaging; Radiology; Geometry","score_opus":0.03841103299032861,"score_gpt":0.31331938363475276,"score_spread":0.27490835064442415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389454614","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99582094,0.00019956229,0.0002736644,0.0021060097,0.000039512135,0.00140754,0.000013637617,0.000065854845,0.00007327693],"genre_scores_gemma":[0.9994593,0.000027778897,0.00012797143,0.0001730397,0.00002166225,0.00012614837,0.000005161777,0.000013166525,0.00004572232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99930745,0.00008626661,0.00019307616,0.00017257009,0.00014294733,0.000097693104],"domain_scores_gemma":[0.99926764,0.00021471668,0.000145256,0.00021432104,0.00013775883,0.000020299158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015661048,0.00009320946,0.00016917568,0.00011033581,0.00013283506,0.000006195988,0.000075523654,0.000017553153,0.0000013125422],"category_scores_gemma":[0.00026829034,0.000048774593,0.00008989744,0.0005294948,0.0007278997,0.000056690165,0.000098310935,0.00012010304,2.7291674e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008785021,0.00022773862,0.85286164,0.00009452375,0.0000946433,0.0000028310253,0.02257625,0.000005583254,0.111575864,0.0017010804,0.0007064779,0.009274848],"study_design_scores_gemma":[0.0026328266,0.00013931953,0.95594776,0.00027447683,0.00016742131,0.00002972549,0.024885407,0.00055487757,0.013263919,0.0018538324,0.00014899684,0.0001014646],"about_ca_topic_score_codex":0.000030491818,"about_ca_topic_score_gemma":0.0000029813732,"teacher_disagreement_score":0.10308607,"about_ca_system_score_codex":0.000002922284,"about_ca_system_score_gemma":0.000016015323,"threshold_uncertainty_score":0.2681977},"labels":[],"label_agreement":null},{"id":"W4389465228","doi":"10.1212/wnl.92.15_supplement.p5.1-025","title":"Diffusion Tensor Imaging in pre-dementia risk states: white matter atrophy findings in Mild Behavioral Impairment (P5.1-025)","year":2019,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Alberta Bible College; Centre for Addiction and Mental Health; Ontario Brain Institute","funders":"","keywords":"Diffusion MRI; Dementia; White matter; Atrophy; Medicine; Psychology; Psychiatry; Audiology; Neuroscience; Clinical psychology; Pathology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.015466424725711966,"score_gpt":0.3085858240965957,"score_spread":0.2931193993708837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389465228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99267685,0.000040592167,0.00031333542,0.005726274,0.000081675724,0.0009149529,0.000015526015,0.000105255735,0.0001255243],"genre_scores_gemma":[0.9936986,0.000101179015,0.0013386254,0.00449183,0.000023694065,0.0001271283,0.000030071411,0.00004299267,0.00014587243],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854726,0.000066091474,0.00034457812,0.0005124031,0.00012547165,0.00040417194],"domain_scores_gemma":[0.9993535,0.00003672679,0.00009398082,0.00042669356,0.000023594417,0.00006550121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009833482,0.00017983034,0.00026999277,0.00026619167,0.000035669258,0.000010529876,0.00013056485,0.000067353794,0.0003377316],"category_scores_gemma":[0.000004818633,0.00016970867,0.000063074345,0.000167891,0.00005841181,0.00007718007,0.00014260427,0.00053407945,0.00014969941],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003019738,0.00032158164,0.99366456,0.000017038064,0.0000021518144,0.00006379341,0.00019665869,0.00008087731,0.00412718,0.000009917383,0.0008210123,0.0003932294],"study_design_scores_gemma":[0.0018951609,0.0006439348,0.9912199,0.000022956187,0.000033494518,0.000050547427,0.000009465143,0.001940979,0.00018499352,0.00034637508,0.003524851,0.00012738352],"about_ca_topic_score_codex":0.00032213065,"about_ca_topic_score_gemma":0.000033865523,"teacher_disagreement_score":0.003942187,"about_ca_system_score_codex":0.000039293605,"about_ca_system_score_gemma":0.000014506544,"threshold_uncertainty_score":0.6920519},"labels":[],"label_agreement":null},{"id":"W4389504585","doi":"10.1007/s00429-023-02729-5","title":"Ventral and dorsal aspects of the inferior frontal-occipital fasciculus support verbal semantic access and visually-guided behavioural control","year":2023,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"HORIZON EUROPE European Research Council","keywords":"Fasciculus; Psychology; Neuroscience; Lateralization of brain function; Cognitive psychology; Dorsum; White matter; Anatomy; Biology; Medicine; Magnetic resonance imaging","score_opus":0.034605007669759276,"score_gpt":0.32854251223875613,"score_spread":0.29393750456899687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389504585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99682933,0.00004562116,0.00072197453,0.0016626987,0.0001218487,0.00040856694,0.000049699807,0.0000836391,0.00007661697],"genre_scores_gemma":[0.99929607,0.00001791735,0.000046863966,0.00045164654,0.00006192806,0.000011562517,0.000029840061,0.000012315012,0.00007187308],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99938977,0.00001618224,0.00014515611,0.00020196033,0.00011392415,0.00013298451],"domain_scores_gemma":[0.9996791,0.0000337055,0.000069108864,0.00013465495,0.000030711584,0.000052732717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000049670227,0.00010614882,0.00016504174,0.000047654044,0.000107282634,0.00002808534,0.000041209038,0.00005809412,0.00001750117],"category_scores_gemma":[0.000031827258,0.00007446062,0.000032667394,0.00013346759,0.00012104129,0.00010698793,0.00007018437,0.00012605112,2.8686466e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037678826,0.00004933528,0.83411896,0.00019197165,0.000085495645,0.000035662724,0.0004954876,0.000010660051,0.13207929,0.0041627483,0.0040560905,0.024337515],"study_design_scores_gemma":[0.0011521371,0.00019027224,0.99180865,0.000024114908,0.00012547296,0.00020074639,0.00004308129,0.000368841,0.0023070408,0.0031774568,0.0005243019,0.00007788941],"about_ca_topic_score_codex":0.00002990926,"about_ca_topic_score_gemma":0.000013132976,"teacher_disagreement_score":0.15768969,"about_ca_system_score_codex":0.000010958963,"about_ca_system_score_gemma":0.000024751296,"threshold_uncertainty_score":0.30364162},"labels":[],"label_agreement":null},{"id":"W4389685319","doi":"10.1038/s41380-023-02321-7","title":"Cortical microstructural associations with CSF amyloid and pTau","year":2023,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Eli Lilly and Company; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Bristol-Myers Squibb; National Institute on Aging; Alzheimer's Association; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Amyloid (mycology); Neuroscience; Amyloid β; Psychology; Medicine; Pathology; Disease","score_opus":0.021956056100683442,"score_gpt":0.3251232938679941,"score_spread":0.30316723776731064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389685319","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9777318,0.00011199602,0.006525,0.013902217,0.00006426478,0.0002835134,0.000021352873,0.0004391252,0.0009207014],"genre_scores_gemma":[0.95448923,0.000026485308,0.04303052,0.002047323,0.000047515452,0.000035445624,0.000069344445,0.000030340369,0.00022381263],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937373,0.00001218523,0.00010874791,0.00021695813,0.00011690907,0.00017147414],"domain_scores_gemma":[0.99959487,0.000014049564,0.000035816207,0.00023155707,0.000037090977,0.00008659801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000036760826,0.00009141847,0.000116781324,0.00005823762,0.00011170227,0.00001740397,0.00004304552,0.000033787175,0.000008121312],"category_scores_gemma":[0.0000214809,0.000076763885,0.00003635922,0.00030740176,0.00006837527,0.000026946438,0.000030887393,0.00018257163,0.000018304328],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011918997,0.00021358623,0.53656083,0.0001218916,0.00015992874,0.00019387505,0.00014572949,0.000023620205,0.37402245,0.062898025,0.021586424,0.003954453],"study_design_scores_gemma":[0.0013783635,0.0002779356,0.9668111,0.00007319579,0.00017583721,0.0004446379,0.000093528775,0.00049833255,0.007752894,0.014128501,0.008059377,0.0003063055],"about_ca_topic_score_codex":0.0000039813035,"about_ca_topic_score_gemma":0.0000022101442,"teacher_disagreement_score":0.43025026,"about_ca_system_score_codex":0.0000143365605,"about_ca_system_score_gemma":0.000041586914,"threshold_uncertainty_score":0.31303403},"labels":[],"label_agreement":null},{"id":"W4389720650","doi":"10.1016/j.brainresbull.2023.110847","title":"Association between altered white matter networks and post operative ventricle volume in shunt-treated pediatric hydrocephalus","year":2023,"lang":"en","type":"article","venue":"Brain Research Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"White matter; Tractography; Hydrocephalus; Fractional anisotropy; Diffusion MRI; Ventriculomegaly; Frontal lobe; Medicine; Psychology; Neuroscience; Radiology; Magnetic resonance imaging; Biology; Fetus","score_opus":0.059906250697530014,"score_gpt":0.39088964651261265,"score_spread":0.3309833958150826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389720650","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8636414,0.0001060355,0.00031571605,0.13398488,0.000013655306,0.00096642785,0.000034185337,0.00019440218,0.000743333],"genre_scores_gemma":[0.98003316,0.0002756024,0.00042298887,0.0009289697,0.00034327575,0.00021766227,0.0001757787,0.00004338558,0.01755919],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9981831,0.00024058795,0.00024688215,0.00039840865,0.00038374134,0.0005472943],"domain_scores_gemma":[0.9987882,0.0005723318,0.00005569195,0.00023674902,0.00019991137,0.00014711863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011606769,0.00011748723,0.00021487215,0.00042510923,0.00016287269,0.00005645736,0.00011729611,0.00010448235,0.00035665213],"category_scores_gemma":[0.0005802409,0.00011517623,0.000034369554,0.0013416973,0.000052931773,0.00004166673,0.00018663498,0.0006089731,0.0006028157],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029604114,0.000039510633,0.7636165,0.000022426992,0.000009893786,0.00003370201,0.00008080278,0.000041955613,0.00024212128,0.000009809099,0.23527707,0.00059661694],"study_design_scores_gemma":[0.00077073707,0.00013980546,0.96828943,0.000035266854,0.000014955271,0.0000057536495,0.0000552038,0.0023266128,0.00007642418,0.00010996608,0.02806844,0.0001074173],"about_ca_topic_score_codex":0.00012533397,"about_ca_topic_score_gemma":0.0000058973337,"teacher_disagreement_score":0.20720863,"about_ca_system_score_codex":0.00017925851,"about_ca_system_score_gemma":0.000036386744,"threshold_uncertainty_score":0.77481776},"labels":[],"label_agreement":null},{"id":"W4389912612","doi":"10.3390/diagnostics13243679","title":"Whole Brain and Corpus Callosum Fractional Anisotropy Differences in Patients with Cognitive Impairment","year":2023,"lang":"en","type":"article","venue":"Diagnostics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Corpus callosum; Diffusion MRI; Cognitive impairment; Percentile rank; Normative; Psychology; Percentile; Montreal Cognitive Assessment; Cognition; Population; Medicine; Audiology; Magnetic resonance imaging; Internal medicine; Psychiatry; Radiology; Neuroscience","score_opus":0.03263545401581467,"score_gpt":0.3120306757375723,"score_spread":0.2793952217217576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389912612","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9946584,0.00001809498,0.0020629182,0.0025786257,0.000018158164,0.0004151159,0.0000968531,0.000103050756,0.000048766047],"genre_scores_gemma":[0.9977766,0.00011259265,0.00105826,0.0006405797,0.00002151709,0.00009298989,0.00017917223,0.000012404812,0.000105835694],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994801,0.000009419306,0.00009064562,0.00016214376,0.00013219025,0.00012544633],"domain_scores_gemma":[0.9993223,0.00045368783,0.000034138895,0.000074707685,0.000057291483,0.000057906764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000025718045,0.00007637464,0.000108933935,0.00006583585,0.000044601857,0.000008720596,0.000023466744,0.000024540619,0.000007146299],"category_scores_gemma":[0.00020094367,0.00006167305,0.000010262317,0.00018307644,0.00006760711,0.000032879845,0.00003056351,0.00010972447,0.000013587947],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005196118,0.00021532478,0.9959211,0.000010269372,0.000006007258,0.000023756329,0.000045931058,0.0000014366094,0.00002225071,0.00033339625,0.002144675,0.0012239341],"study_design_scores_gemma":[0.0011517253,0.0004367948,0.9958895,0.000106614454,0.000017255074,0.0000028363636,0.00004553834,0.00019607674,0.00007202891,0.00085556845,0.001155374,0.00007069419],"about_ca_topic_score_codex":0.00001049019,"about_ca_topic_score_gemma":0.0000045911825,"teacher_disagreement_score":0.003118231,"about_ca_system_score_codex":0.000020649462,"about_ca_system_score_gemma":0.00001998771,"threshold_uncertainty_score":0.2514954},"labels":[],"label_agreement":null},{"id":"W4389990655","doi":"10.1016/j.compbiomed.2023.107873","title":"Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN","year":2023,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"National Key Research and Development Program of China; Science and Technology Department of Gansu Province; National Natural Science Foundation of China","keywords":"Deep learning; Computer science; Artificial intelligence; Convolutional neural network; Context (archaeology); Feature engineering; Feature (linguistics); Feature extraction; Machine learning; Neuroimaging; Pattern recognition (psychology); Salient; Neuroscience; Psychology","score_opus":0.026409830575013792,"score_gpt":0.3527112814833023,"score_spread":0.3263014509082885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389990655","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7438208,0.00021000372,0.22130617,0.03251074,0.000261234,0.0006363778,0.000007771347,0.00060139113,0.0006455037],"genre_scores_gemma":[0.97901607,0.0002927322,0.01769548,0.002212145,0.000240569,0.000049328097,0.00023086013,0.000014427319,0.0002484003],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993003,0.00002448321,0.00013868057,0.0003074563,0.000051602146,0.0001774688],"domain_scores_gemma":[0.9995731,0.00011415576,0.000046612036,0.0001703281,0.000024643334,0.00007112411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014061996,0.00010517743,0.0002222395,0.00017279027,0.000063815205,0.0000026186924,0.00005306167,0.00009439052,0.0000033318506],"category_scores_gemma":[0.00005241047,0.000073576935,0.000014910128,0.0003404989,0.00029437183,0.00003024483,0.000046041157,0.00026380678,0.0000020370328],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060362683,0.00017317303,0.14353767,0.00026480036,0.000086736916,0.00041875363,0.00065068895,0.000027620365,0.5293014,0.013116693,0.042206533,0.26961228],"study_design_scores_gemma":[0.008721,0.0027383952,0.92252856,0.0012147469,0.00011868972,0.00050163345,0.00028855551,0.02553548,0.0013611496,0.008576862,0.028023204,0.000391728],"about_ca_topic_score_codex":0.000010011209,"about_ca_topic_score_gemma":0.0000033556707,"teacher_disagreement_score":0.77899086,"about_ca_system_score_codex":0.000023697276,"about_ca_system_score_gemma":0.000014320178,"threshold_uncertainty_score":0.30003804},"labels":[],"label_agreement":null},{"id":"W4390081233","doi":"10.1093/geroni/igad104.2230","title":"AGE EFFECTS ON WHITE MATTER TOPOLOGY IN OLDER ADULTS AT HIGH RISK OF ALZHEIMER’S DISEASE","year":2023,"lang":"en","type":"article","venue":"Innovation in Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"White matter; Betweenness centrality; Medicine; Stroop effect; Cognition; Cohort; Psychology; Gerontology; Internal medicine; Centrality; Neuroscience; Magnetic resonance imaging","score_opus":0.032175810138589195,"score_gpt":0.34731557564005056,"score_spread":0.3151397655014614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390081233","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9924767,0.000014532509,0.00065670407,0.005911688,0.000056556357,0.00045793588,0.0000064515125,0.000109311644,0.0003101247],"genre_scores_gemma":[0.9971287,0.000016524451,0.00086075295,0.0015250524,0.000032037227,0.0001417727,0.000087919136,0.000017905575,0.00018929427],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992182,0.000028416955,0.00030548402,0.00021134905,0.00009533558,0.00014115938],"domain_scores_gemma":[0.9994986,0.00007955163,0.00011806361,0.0002418267,0.000041492578,0.000020479081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013650431,0.00008007107,0.0001440651,0.0005581025,0.000024778476,0.0000026637524,0.000045189827,0.000030309098,0.000029151324],"category_scores_gemma":[0.00007676799,0.00007857161,0.000017521097,0.0013508382,0.000033101853,0.000035953046,0.00004783938,0.00016386701,0.00003352045],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000074964926,0.00006992951,0.9871422,0.00009685917,0.0000052424125,0.00008203359,0.00026579195,0.00011512638,0.0015464544,0.0026942915,0.0018451704,0.006061957],"study_design_scores_gemma":[0.0008402394,0.000019530133,0.98936665,0.00036527443,0.000011714516,0.0000015814679,0.000015781661,0.0004570098,0.005882696,0.00269824,0.00027597166,0.00006528534],"about_ca_topic_score_codex":0.000038660008,"about_ca_topic_score_gemma":0.0000054111933,"teacher_disagreement_score":0.005996672,"about_ca_system_score_codex":0.00004205692,"about_ca_system_score_gemma":0.000009947399,"threshold_uncertainty_score":0.32040572},"labels":[],"label_agreement":null},{"id":"W4390084724","doi":"10.1017/s135561772301130x","title":"48 Sex Differences and Longitudinal Changes in White Matter Microstructure in Healthy Older Adults","year":2023,"lang":"en","type":"article","venue":"Journal of the International Neuropsychological Society","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Institute of Aging; University of Victoria","funders":"","keywords":"Longitudinal study; White matter; Diffusion MRI; Cohort; Aging brain; Medicine; Population; Superior longitudinal fasciculus; Gerontology; Cohort study; Psychology; Disease; Magnetic resonance imaging; Fractional anisotropy; Pathology","score_opus":0.051027585576921296,"score_gpt":0.3635444276507216,"score_spread":0.3125168420738003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390084724","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91105247,0.000031959884,0.00005466701,0.08843558,0.00019339657,0.00012599745,0.000005742005,0.0000138565865,0.0000863487],"genre_scores_gemma":[0.9904542,0.00045436705,0.000784559,0.007947869,0.00011610832,0.000006535193,0.000001082608,0.0000073446395,0.00022795926],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992169,0.000029801071,0.0002501074,0.00016783742,0.00020856161,0.00012679976],"domain_scores_gemma":[0.99959713,0.00005694769,0.0001541519,0.00009890708,0.00004879162,0.00004405088],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014765857,0.00008410134,0.0001563224,0.000055496923,0.000032820073,0.00001729873,0.00021835335,0.00005207896,0.000059613976],"category_scores_gemma":[0.000038469385,0.000048801525,0.00009297625,0.00023544162,0.00008146676,0.00003890267,0.00009913103,0.0005052985,0.0000030810786],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001902732,0.000084520696,0.9895358,0.000010711194,0.000006700965,0.000035022073,0.000194006,0.0000051840807,0.0013303948,0.000014383277,0.007856707,0.0007362717],"study_design_scores_gemma":[0.0007964108,0.000089303205,0.99674153,0.000105017134,0.000003892925,0.00038721482,0.00008644195,0.00017872317,0.00003666944,0.0006054981,0.00092659466,0.00004269787],"about_ca_topic_score_codex":0.0000033567583,"about_ca_topic_score_gemma":0.0000046191903,"teacher_disagreement_score":0.08048772,"about_ca_system_score_codex":0.000034401663,"about_ca_system_score_gemma":0.000009686779,"threshold_uncertainty_score":0.21952987},"labels":[],"label_agreement":null},{"id":"W4390097831","doi":"10.1109/mercon60487.2023.10355503","title":"Exploring Asymmetrical White Matter Abnormalities in Alzheimer’s using Deep Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"White matter; Deep learning; Artificial intelligence; Computer science; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.3979311201407268,"score_gpt":0.39915428140046544,"score_spread":0.0012231612597386476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390097831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.942034,0.000120956196,0.033142418,0.0032898765,0.00006206472,0.00037114022,9.874368e-7,0.0012476536,0.019730883],"genre_scores_gemma":[0.97701246,0.00011467387,0.021316014,0.00049383973,0.000057445584,0.00007657757,0.0000088913375,0.000030911157,0.00088917214],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992577,0.000016945767,0.00017787114,0.00018973695,0.0001183522,0.00023943298],"domain_scores_gemma":[0.99967897,0.000058261907,0.000026705013,0.00015758102,0.000022800838,0.000055683482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010860704,0.00008562678,0.00013896027,0.00036100837,0.00006250108,0.000013815224,0.000050567305,0.000023622593,0.00013228873],"category_scores_gemma":[0.000031584295,0.000079709076,0.000039162987,0.0009165194,0.000025591686,0.00016525635,0.00007318394,0.00023234484,0.00015490322],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026785929,0.000068873895,0.971326,0.000043818032,0.000025862326,0.00012598594,0.0006042142,0.0023177422,0.0022287774,0.0023621446,0.0010358355,0.01983399],"study_design_scores_gemma":[0.0010180523,0.00012575483,0.85809463,0.00020039799,0.00011689633,0.00024182396,0.0024488692,0.09305298,0.009707203,0.0014155833,0.03300966,0.0005681322],"about_ca_topic_score_codex":0.00004106097,"about_ca_topic_score_gemma":0.0000016793074,"teacher_disagreement_score":0.11323132,"about_ca_system_score_codex":0.000029911122,"about_ca_system_score_gemma":0.000008372002,"threshold_uncertainty_score":0.32504418},"labels":[],"label_agreement":null},{"id":"W4390192459","doi":"10.1002/alz.071668","title":"The effect of computerized cognitive training and exercise on white matter integrity: a secondary analysis of a randomized controlled trial","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Randomized controlled trial; Fractional anisotropy; Medicine; Diffusion MRI; White matter; Cognition; Aerobic exercise; Physical therapy; Brain Structure and Function; Cognitive training; Cognitive decline; Physical medicine and rehabilitation; Psychology; Dementia; Internal medicine; Psychiatry; Magnetic resonance imaging","score_opus":0.03995827972316692,"score_gpt":0.3412856810052768,"score_spread":0.3013274012821099,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390192459","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9801572,0.004469474,0.003626697,0.0014975086,0.000110704,0.009069238,0.00005382581,0.00014243844,0.0008729387],"genre_scores_gemma":[0.99792135,0.00017910199,0.00070524233,0.00014060788,0.000017272878,0.0009456261,0.00005842648,0.0000148438,0.000017552202],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.99870557,0.00023744357,0.00054078735,0.00020944481,0.00016770305,0.00013905733],"domain_scores_gemma":[0.99739945,0.0019712946,0.00030689375,0.00021118602,0.000069365204,0.00004182701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010626127,0.00014101577,0.0015823861,0.00024654213,0.00007255727,0.00001328225,0.0000695766,0.00003704174,0.000053801858],"category_scores_gemma":[0.00010665082,0.00008258227,0.00048243307,0.0004611314,0.0002124809,0.000026081061,0.000051778963,0.0001621622,0.0000040838395],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.9147229,0.00007219159,0.0010143295,0.000015711226,0.04745552,0.0000049423966,0.00043464353,0.0000031912475,0.0007187266,0.00008163325,0.0005121342,0.03496407],"study_design_scores_gemma":[0.83892125,0.0005453199,0.0016062042,0.00012818292,0.1501264,0.0000015321601,0.000071719325,0.0040687784,0.0042186435,0.00012464344,0.000093979455,0.00009335708],"about_ca_topic_score_codex":0.0000071749314,"about_ca_topic_score_gemma":7.8483106e-7,"teacher_disagreement_score":0.102670886,"about_ca_system_score_codex":0.000001217106,"about_ca_system_score_gemma":0.000018667271,"threshold_uncertainty_score":0.33676073},"labels":[],"label_agreement":null},{"id":"W4390194192","doi":"10.1002/alz.072638","title":"Longitudinal free‐water changes in dementia with Lewy bodies","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Dementia with Lewy bodies; White matter; Fractional anisotropy; Grey matter; Diffusion MRI; Medicine; Dementia; Putamen; Psychology; Internal medicine; Magnetic resonance imaging; Radiology; Disease","score_opus":0.09174883435333978,"score_gpt":0.3391665871301575,"score_spread":0.24741775277681774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87725866,0.032730613,0.0051905517,0.068087496,0.00037134252,0.0038767299,0.00008521142,0.0035184284,0.008880939],"genre_scores_gemma":[0.99092245,0.00025482982,0.007793388,0.00045466007,0.00006571279,0.0002789444,0.00010557169,0.000040941195,0.00008348913],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988756,0.000013803121,0.00017380192,0.0003520381,0.00019667188,0.0003880773],"domain_scores_gemma":[0.9993478,0.000016641836,0.00004055638,0.00048217303,0.00004401617,0.00006882389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011235529,0.00016426976,0.000189574,0.00018582326,0.00009518238,0.000019851617,0.00015280885,0.00003643185,0.00017989514],"category_scores_gemma":[0.0000057876678,0.00012012664,0.000036393852,0.00023824837,0.00008288837,0.00008408493,0.00017305645,0.00014068797,0.00016686061],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032437666,0.0006266907,0.7832524,0.00007615383,0.011560943,0.0007473994,0.00092222705,0.00005061448,0.07616694,0.0026579644,0.0813588,0.042255506],"study_design_scores_gemma":[0.0031770633,0.00069433235,0.31164247,0.00019535478,0.015596569,0.0001223536,0.00018501405,0.0003395643,0.4345457,0.0033438867,0.22935662,0.0008010814],"about_ca_topic_score_codex":0.000054947133,"about_ca_topic_score_gemma":0.00025060453,"teacher_disagreement_score":0.47160992,"about_ca_system_score_codex":0.000004427955,"about_ca_system_score_gemma":0.000014091969,"threshold_uncertainty_score":0.48986223},"labels":[],"label_agreement":null},{"id":"W4390194261","doi":"10.1002/alz.080004","title":"Multivariate white matter differences links to cognition in individuals with family history of Alzheimer’s disease and APOE4 genetic risk","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Concordia University; McGill Genome Centre; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Multivariate statistics; Mahalanobis distance; Splenium; Univariate; Psychology; Neuropsychology; Corpus callosum; Multivariate analysis; Voxel; Cognition; White matter; Medicine; Clinical psychology; Artificial intelligence; Magnetic resonance imaging; Statistics; Internal medicine; Psychiatry; Neuroscience; Computer science; Mathematics; Radiology","score_opus":0.06582336743214791,"score_gpt":0.31374557819658794,"score_spread":0.24792221076444004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803223,0.014049284,0.0021701364,0.0013779955,0.000059556824,0.0013478694,0.00012245405,0.00017723342,0.00037318032],"genre_scores_gemma":[0.9835364,0.00027214971,0.015003439,0.0007706059,0.000021699148,0.00027236118,0.000065298686,0.000031148065,0.000026900147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989445,0.00004115887,0.0002768672,0.0003506658,0.00018227984,0.00020451409],"domain_scores_gemma":[0.9993657,0.000036205005,0.00012712549,0.00027564194,0.00004739027,0.00014795974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000089836794,0.00015398297,0.00021934643,0.00022080044,0.000036063237,0.000008084065,0.00007715532,0.000049321166,0.000052699546],"category_scores_gemma":[0.000009515233,0.00013393215,0.00003161299,0.00021956512,0.00009619737,0.0000601352,0.00008545652,0.00017745787,0.000049654423],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006641843,0.0001361471,0.978974,0.000014823891,0.0011656939,0.00001604883,0.0004013403,0.000017127715,0.0026657158,0.000021439391,0.0052689337,0.011252341],"study_design_scores_gemma":[0.0006039439,0.000102764294,0.9889284,0.00008836332,0.0067858063,0.0000022996987,0.000031840817,0.0002444797,0.00048712108,0.00031223622,0.0022621746,0.00015061353],"about_ca_topic_score_codex":0.00007938497,"about_ca_topic_score_gemma":0.000006857906,"teacher_disagreement_score":0.013777134,"about_ca_system_score_codex":0.0000065667496,"about_ca_system_score_gemma":0.000047217323,"threshold_uncertainty_score":0.54615945},"labels":[],"label_agreement":null},{"id":"W4390194382","doi":"10.1002/alz.080407","title":"Visualizing Braak stages with deformation‐based morphometry in super‐sampled MRI","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Alzheimer's Disease Neuroimaging Initiative; Neuroimaging; Entorhinal cortex; Voxel; Magnetic resonance imaging; Neocortex; Neurodegeneration; Neuroscience; Nuclear medicine; Hippocampus; Medicine; Pathology; Psychology; Alzheimer's disease; Radiology; Disease","score_opus":0.08663960118001099,"score_gpt":0.36831609014210415,"score_spread":0.2816764889620932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194382","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9008091,0.005258624,0.07897625,0.008375093,0.00011465923,0.002353274,0.00007453927,0.0024087895,0.0016296722],"genre_scores_gemma":[0.9678289,0.000067520275,0.030824112,0.0007785923,0.000025192565,0.00016432273,0.00025587642,0.000038585833,0.000016859365],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989644,0.000020814648,0.0002495343,0.00025679977,0.00022337437,0.000285043],"domain_scores_gemma":[0.99939615,0.00005830965,0.00006411819,0.00035218068,0.000052667245,0.00007657499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015038245,0.00014107281,0.00017421089,0.0003442193,0.00009057715,0.000023511648,0.00010612641,0.000036786776,0.00011224332],"category_scores_gemma":[0.000015962112,0.00012240298,0.000042800613,0.0010226953,0.000049389626,0.0001606683,0.000051343857,0.00013727197,0.00010128015],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000351948,0.0009107148,0.83206147,0.00012640223,0.0031856375,0.00026899186,0.00067365204,0.0012066187,0.076515704,0.005434795,0.02920563,0.05005845],"study_design_scores_gemma":[0.007840582,0.00086517096,0.47122663,0.00045320898,0.008983314,0.00009738445,0.0007210315,0.024043912,0.35119745,0.0012729221,0.13188869,0.0014097042],"about_ca_topic_score_codex":0.000051965053,"about_ca_topic_score_gemma":0.000015135101,"teacher_disagreement_score":0.3608348,"about_ca_system_score_codex":0.000009242999,"about_ca_system_score_gemma":0.00004627495,"threshold_uncertainty_score":0.49914488},"labels":[],"label_agreement":null},{"id":"W4390194419","doi":"10.1002/alz.078896","title":"Amyloid and tau pathology are associated with white matter properties in cognitively unimpaired older adults at risk of AD dementia","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; Montreal Neurological Institute and Hospital; Université de Sherbrooke; Douglas College; McGill University; Douglas Mental Health University Institute","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Psychology; Pathology; Neuropathology; Posterior cingulate; Medicine; Neuroscience; Magnetic resonance imaging; Cortex (anatomy); Disease","score_opus":0.03918809377620077,"score_gpt":0.27711028372746543,"score_spread":0.23792218995126466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194419","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938778,0.0039350158,0.00010109196,0.000965028,0.000015608248,0.00077748764,0.00006771401,0.00015515155,0.00010507285],"genre_scores_gemma":[0.9979719,0.00024555574,0.0010248853,0.00033741514,0.000008097626,0.00020027318,0.00011275976,0.000039639177,0.000059463993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988815,0.00006864705,0.0002790608,0.00035295295,0.00014710167,0.0002707323],"domain_scores_gemma":[0.99933475,0.0000340533,0.00023155696,0.00022229578,0.00011753848,0.000059784223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001318768,0.00016769789,0.00027392159,0.00013749063,0.0000826113,0.000007181919,0.00006816929,0.00006155836,0.00006485164],"category_scores_gemma":[0.000022502638,0.0001361657,0.00003649798,0.00033140133,0.0001666535,0.00007075647,0.00012599888,0.00014217886,0.000024261724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017133619,0.00019352148,0.9898803,0.000022163546,0.0015563642,0.000052454998,0.00047199088,0.0000027723895,0.0025869296,0.0000031974835,0.001894624,0.0031643142],"study_design_scores_gemma":[0.0016782373,0.00014872625,0.98289603,0.00030796754,0.0040494697,0.000018838986,0.00024691297,0.00014855419,0.010082825,0.00003698069,0.00023383816,0.00015164285],"about_ca_topic_score_codex":0.000022030248,"about_ca_topic_score_gemma":0.0001046315,"teacher_disagreement_score":0.007495896,"about_ca_system_score_codex":0.0000069162734,"about_ca_system_score_gemma":0.000017253473,"threshold_uncertainty_score":0.55526763},"labels":[],"label_agreement":null},{"id":"W4390194500","doi":"10.1002/alz.080381","title":"Subcortical deformation is uniquely related to cortical thickness among FTLD mutation carriers","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Putamen; Mutation; Grey matter; Frontotemporal lobar degeneration; Temporal lobe; Medicine; White matter; Magnetic resonance imaging; Anatomy; Pathology; Psychology; Neuroscience; Internal medicine; Biology; Frontotemporal dementia; Genetics; Dementia; Radiology; Epilepsy; Disease","score_opus":0.053309445814585944,"score_gpt":0.35127794575157967,"score_spread":0.2979684999369937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194500","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9725646,0.00038777568,0.014169937,0.008684496,0.00014763702,0.0012252309,0.000019520252,0.0013142704,0.0014865792],"genre_scores_gemma":[0.9921354,0.00003096008,0.006134807,0.0012155923,0.000015914029,0.00017648569,0.00019854045,0.000037156555,0.000055129152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986891,0.000034897992,0.00038139915,0.00030955405,0.00027906656,0.0003059586],"domain_scores_gemma":[0.9991841,0.000040614308,0.00007085868,0.00035398031,0.00012706105,0.00022341289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001781247,0.00014414811,0.00017089867,0.00015716521,0.00017198063,0.000025340494,0.00009992842,0.000094423856,0.00011217537],"category_scores_gemma":[0.00006714215,0.00013972334,0.000074028554,0.0007620507,0.00009021396,0.0001749483,0.00007317768,0.00025462665,0.00043126586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085728586,0.0009945013,0.25818086,0.00015129964,0.014534096,0.0008025586,0.010174495,0.00071051106,0.15310474,0.10635879,0.2123237,0.24180716],"study_design_scores_gemma":[0.002388664,0.00075875816,0.6961434,0.0001896859,0.019033674,0.00028738714,0.0008323163,0.031262875,0.20237485,0.015397844,0.030159643,0.0011709023],"about_ca_topic_score_codex":0.00002690035,"about_ca_topic_score_gemma":0.0000034532898,"teacher_disagreement_score":0.43796256,"about_ca_system_score_codex":0.000013275593,"about_ca_system_score_gemma":0.00004207974,"threshold_uncertainty_score":0.5697752},"labels":[],"label_agreement":null},{"id":"W4390194755","doi":"10.1002/alz.080772","title":"Antagonistic Amyloid‐β and tau interactions with T1‐weighted/T2‐weighted magnetic resonance ratio in Alzheimer’s disesase continuum","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nexen (Canada)","funders":"","keywords":"Neurodegeneration; Psychology; Magnetic resonance imaging; Amyloid (mycology); Entorhinal cortex; Pittsburgh compound B; Alzheimer's disease; Neuroscience; Chemistry; Nuclear magnetic resonance; Internal medicine; Medicine; Pathology; Disease; Physics; Hippocampus","score_opus":0.047383722405745635,"score_gpt":0.3274654809087871,"score_spread":0.28008175850304146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194755","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7401006,0.20898467,0.009809746,0.022015864,0.0007038741,0.00787941,0.00041380475,0.003488148,0.0066038263],"genre_scores_gemma":[0.9868221,0.0008689006,0.01078313,0.00054534624,0.000080599035,0.00044054963,0.00022456389,0.000068676476,0.00016611534],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983359,0.000044540488,0.00040495163,0.00058096787,0.00021794713,0.00041571958],"domain_scores_gemma":[0.99899495,0.000112106754,0.00011491761,0.0005211757,0.00009075139,0.0001660995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010448823,0.00027115093,0.00031753743,0.00024884974,0.0001918894,0.00005261348,0.0001333244,0.000052872776,0.00014610944],"category_scores_gemma":[0.000017335942,0.00024091046,0.000050409286,0.0007893263,0.0002099282,0.00019509728,0.00010590775,0.00030449888,0.000096747826],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017130254,0.0023061128,0.1983035,0.000098655386,0.0066929213,0.002105477,0.0015037869,0.000015378835,0.08179444,0.01323742,0.10623974,0.58598953],"study_design_scores_gemma":[0.0071794805,0.0014370406,0.3193099,0.00064359297,0.025171844,0.00059232046,0.0003354054,0.011984447,0.06267582,0.004238597,0.5647265,0.0017050877],"about_ca_topic_score_codex":0.000087071916,"about_ca_topic_score_gemma":0.00016035012,"teacher_disagreement_score":0.5842844,"about_ca_system_score_codex":0.000009869189,"about_ca_system_score_gemma":0.000060924882,"threshold_uncertainty_score":0.98240435},"labels":[],"label_agreement":null},{"id":"W4390194807","doi":"10.1002/alz.077371","title":"Voxel‐by‐Voxel regression analysis identifies association between postmortem TDP‐43 and antemortem fractional anisotropy within white matter fibers connected to the hippocampus","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Parahippocampal gyrus; Entorhinal cortex; Hippocampus; Fractional anisotropy; Voxel; Fornix; Pathology; Medicine; Grey matter; Neuroscience; Psychology; Magnetic resonance imaging; Temporal lobe; Radiology","score_opus":0.03679855996780896,"score_gpt":0.32985917308936996,"score_spread":0.293060613121561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95894444,0.0018224092,0.006938271,0.030216936,0.0001882687,0.0009680972,0.00022181982,0.00052440533,0.00017534116],"genre_scores_gemma":[0.9940462,0.00008618861,0.0028285359,0.0015805735,0.00011465822,0.000113429276,0.0007368416,0.000038889597,0.00045468408],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826723,0.000080235935,0.00041787562,0.00049782026,0.0004376492,0.00029921008],"domain_scores_gemma":[0.9987933,0.00015095616,0.0003081239,0.0004554556,0.00015547452,0.00013671505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034451467,0.00021150758,0.0003230546,0.00023574657,0.0003546029,0.000086064,0.00015123743,0.00009228787,0.00015806204],"category_scores_gemma":[0.000044551074,0.00016408585,0.00012426483,0.0011558475,0.00004655583,0.00017006665,0.00013127283,0.00024175034,0.00022002097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034545883,0.000041157018,0.7983617,0.0000068640506,0.008347358,0.000008200181,0.00023552029,0.000032662832,0.0072523886,0.000034752225,0.18368512,0.001959724],"study_design_scores_gemma":[0.00048537666,0.000078808895,0.9519288,0.000049185153,0.026334427,0.000011061149,0.0002060651,0.00076876744,0.0077941185,0.0007350726,0.011317524,0.00029081583],"about_ca_topic_score_codex":0.00006250109,"about_ca_topic_score_gemma":0.000023219036,"teacher_disagreement_score":0.1723676,"about_ca_system_score_codex":0.00002636388,"about_ca_system_score_gemma":0.000025380756,"threshold_uncertainty_score":0.66912264},"labels":[],"label_agreement":null},{"id":"W4390194918","doi":"10.1002/alz.080038","title":"White Matter Correlates of Speech in Cerebrovascular Disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Baycrest Hospital; Robarts Clinical Trials; Western University","funders":"","keywords":"Fractional anisotropy; White matter; Uncinate fasciculus; Hyperintensity; Diffusion MRI; Fasciculus; Psychology; Audiology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.04595456001111764,"score_gpt":0.3227140425372381,"score_spread":0.2767594825261205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390194918","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9709049,0.011084224,0.0015070236,0.009665178,0.00016850232,0.0015576446,0.000045626213,0.00062364724,0.004443261],"genre_scores_gemma":[0.99524915,0.000113866416,0.004072322,0.00027949244,0.000022289147,0.000059674087,0.000071911825,0.000025107069,0.00010615744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928385,0.000011906218,0.00020389554,0.00020329982,0.00013214514,0.00016490454],"domain_scores_gemma":[0.9994627,0.000015483141,0.00004751078,0.0003735527,0.000030382467,0.00007031862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071912626,0.00008756918,0.00014030741,0.00012400899,0.000022069653,0.0000045307042,0.00008107863,0.000023647854,0.0004367405],"category_scores_gemma":[0.000007188178,0.00008391347,0.00007490474,0.00037028608,0.00004391068,0.000047621637,0.00006909931,0.00009162326,0.0004810869],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000144909345,0.000060849456,0.9859953,0.00001097955,0.00035730575,0.00002448246,0.000025567764,0.000012838,0.0004956734,0.00015171738,0.009722998,0.0031277805],"study_design_scores_gemma":[0.0003934453,0.00002196817,0.98134667,0.000051268293,0.0025899208,0.0000066911944,0.0000139215945,0.0003603494,0.004404354,0.0012225828,0.00948369,0.00010515962],"about_ca_topic_score_codex":0.000012181107,"about_ca_topic_score_gemma":0.0000014778853,"teacher_disagreement_score":0.024344286,"about_ca_system_score_codex":0.000002234567,"about_ca_system_score_gemma":0.000016606511,"threshold_uncertainty_score":0.61835593},"labels":[],"label_agreement":null},{"id":"W4390196993","doi":"10.1002/alz.081758","title":"Voxel‐by‐Voxel regression analysis identifies association between postmortem TDP‐43 and antemortem fractional anisotropy within white matter fibers connected to the hippocampus","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; Parahippocampal gyrus; Entorhinal cortex; Hippocampus; Voxel; Fractional anisotropy; Fornix; Pathology; Medicine; Neuroscience; Grey matter; Psychology; Magnetic resonance imaging; Temporal lobe; Radiology","score_opus":0.03679855996780896,"score_gpt":0.32985917308936996,"score_spread":0.293060613121561,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390196993","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95894444,0.0018224092,0.006938271,0.030216936,0.0001882687,0.0009680972,0.00022181982,0.00052440533,0.00017534116],"genre_scores_gemma":[0.9940462,0.00008618861,0.0028285359,0.0015805735,0.00011465822,0.000113429276,0.0007368416,0.000038889597,0.00045468408],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99826723,0.000080235935,0.00041787562,0.00049782026,0.0004376492,0.00029921008],"domain_scores_gemma":[0.9987933,0.00015095616,0.0003081239,0.0004554556,0.00015547452,0.00013671505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034451467,0.00021150758,0.0003230546,0.00023574657,0.0003546029,0.000086064,0.00015123743,0.00009228787,0.00015806204],"category_scores_gemma":[0.000044551074,0.00016408585,0.00012426483,0.0011558475,0.00004655583,0.00017006665,0.00013127283,0.00024175034,0.00022002097],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034545883,0.000041157018,0.7983617,0.0000068640506,0.008347358,0.000008200181,0.00023552029,0.000032662832,0.0072523886,0.000034752225,0.18368512,0.001959724],"study_design_scores_gemma":[0.00048537666,0.000078808895,0.9519288,0.000049185153,0.026334427,0.000011061149,0.0002060651,0.00076876744,0.0077941185,0.0007350726,0.011317524,0.00029081583],"about_ca_topic_score_codex":0.00006250109,"about_ca_topic_score_gemma":0.000023219036,"teacher_disagreement_score":0.1723676,"about_ca_system_score_codex":0.00002636388,"about_ca_system_score_gemma":0.000025380756,"threshold_uncertainty_score":0.66912264},"labels":[],"label_agreement":null},{"id":"W4390197002","doi":"10.1002/alz.081960","title":"White Matter Correlates of Speech in Cerebrovascular Disease","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto; Nova Scotia Health Authority; Western University; Robarts Clinical Trials","funders":"","keywords":"Fractional anisotropy; White matter; Uncinate fasciculus; Hyperintensity; Diffusion MRI; Fasciculus; Psychology; Audiology; Medicine; Magnetic resonance imaging; Neuroscience; Radiology","score_opus":0.04595456001111764,"score_gpt":0.3227140425372381,"score_spread":0.2767594825261205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197002","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9709049,0.011084224,0.0015070236,0.009665178,0.00016850232,0.0015576446,0.000045626213,0.00062364724,0.004443261],"genre_scores_gemma":[0.99524915,0.000113866416,0.004072322,0.00027949244,0.000022289147,0.000059674087,0.000071911825,0.000025107069,0.00010615744],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99928385,0.000011906218,0.00020389554,0.00020329982,0.00013214514,0.00016490454],"domain_scores_gemma":[0.9994627,0.000015483141,0.00004751078,0.0003735527,0.000030382467,0.00007031862],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000071912626,0.00008756918,0.00014030741,0.00012400899,0.000022069653,0.0000045307042,0.00008107863,0.000023647854,0.0004367405],"category_scores_gemma":[0.000007188178,0.00008391347,0.00007490474,0.00037028608,0.00004391068,0.000047621637,0.00006909931,0.00009162326,0.0004810869],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000144909345,0.000060849456,0.9859953,0.00001097955,0.00035730575,0.00002448246,0.000025567764,0.000012838,0.0004956734,0.00015171738,0.009722998,0.0031277805],"study_design_scores_gemma":[0.0003934453,0.00002196817,0.98134667,0.000051268293,0.0025899208,0.0000066911944,0.0000139215945,0.0003603494,0.004404354,0.0012225828,0.00948369,0.00010515962],"about_ca_topic_score_codex":0.000012181107,"about_ca_topic_score_gemma":0.0000014778853,"teacher_disagreement_score":0.024344286,"about_ca_system_score_codex":0.000002234567,"about_ca_system_score_gemma":0.000016606511,"threshold_uncertainty_score":0.61835593},"labels":[],"label_agreement":null},{"id":"W4390197039","doi":"10.1002/alz.081879","title":"In vivo data‐driven patterns of Tau accumulation associated with AD progression using 18F‐MK‐6240 PET","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Standardized uptake value; Temporal lobe; Dementia; Positron emission tomography; Neuroscience; Cognitive impairment; Partial volume; Pathology; Alzheimer's disease; Psychology; Nuclear medicine; Medicine; Cognition; Disease","score_opus":0.19230463758943447,"score_gpt":0.431125597920623,"score_spread":0.23882096033118852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9931718,0.00062066206,0.0039904513,0.0007737243,0.000047144727,0.00090786826,0.00014647686,0.0002753789,0.000066500616],"genre_scores_gemma":[0.98792636,0.000049238966,0.0113129625,0.00008723675,0.000019119272,0.000036443293,0.0005259993,0.00003187519,0.000010759345],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989933,0.000029491252,0.00025375426,0.00030358738,0.00022402093,0.00019584298],"domain_scores_gemma":[0.9991761,0.000037674006,0.00017985243,0.00049980823,0.00006291966,0.00004365223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013636543,0.0001139463,0.00018067332,0.00012924768,0.000053375927,0.000009219102,0.00015267421,0.00002707662,0.000057691544],"category_scores_gemma":[0.000024768558,0.000099880315,0.000023952864,0.00043364632,0.0000338969,0.00020314557,0.00016199226,0.00011322383,0.0000056830618],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020795615,0.0010682198,0.7691765,0.000070612026,0.0038793471,0.00035018328,0.0003823753,0.0010107618,0.19359817,0.00021724234,0.0070388447,0.022999797],"study_design_scores_gemma":[0.0057483953,0.0007127598,0.53109765,0.002198173,0.018247586,0.000110410896,0.00023695611,0.23421134,0.19240378,0.00064602785,0.0133559685,0.0010309299],"about_ca_topic_score_codex":0.00005338388,"about_ca_topic_score_gemma":0.0000387329,"teacher_disagreement_score":0.23807882,"about_ca_system_score_codex":0.000008988753,"about_ca_system_score_gemma":0.00003640673,"threshold_uncertainty_score":0.4073001},"labels":[],"label_agreement":null},{"id":"W4390197060","doi":"10.1002/alz.081853","title":"Amyloid and tau pathology are associated with white matter properties in cognitively unimpaired older adults at risk of AD dementia","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; Université de Sherbrooke; McGill University","funders":"","keywords":"White matter; Fractional anisotropy; Dementia; Psychology; Pathology; Fascicle; Posterior cingulate; Medicine; Neuroscience; Magnetic resonance imaging; Cortex (anatomy); Disease; Anatomy","score_opus":0.03918809377620077,"score_gpt":0.27711028372746543,"score_spread":0.23792218995126466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390197060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938778,0.0039350158,0.00010109196,0.000965028,0.000015608248,0.00077748764,0.00006771401,0.00015515155,0.00010507285],"genre_scores_gemma":[0.9979719,0.00024555574,0.0010248853,0.00033741514,0.000008097626,0.00020027318,0.00011275976,0.000039639177,0.000059463993],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988815,0.00006864705,0.0002790608,0.00035295295,0.00014710167,0.0002707323],"domain_scores_gemma":[0.99933475,0.0000340533,0.00023155696,0.00022229578,0.00011753848,0.000059784223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001318768,0.00016769789,0.00027392159,0.00013749063,0.0000826113,0.000007181919,0.00006816929,0.00006155836,0.00006485164],"category_scores_gemma":[0.000022502638,0.0001361657,0.00003649798,0.00033140133,0.0001666535,0.00007075647,0.00012599888,0.00014217886,0.000024261724],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017133619,0.00019352148,0.9898803,0.000022163546,0.0015563642,0.000052454998,0.00047199088,0.0000027723895,0.0025869296,0.0000031974835,0.001894624,0.0031643142],"study_design_scores_gemma":[0.0016782373,0.00014872625,0.98289603,0.00030796754,0.0040494697,0.000018838986,0.00024691297,0.00014855419,0.010082825,0.00003698069,0.00023383816,0.00015164285],"about_ca_topic_score_codex":0.000022030248,"about_ca_topic_score_gemma":0.0001046315,"teacher_disagreement_score":0.007495896,"about_ca_system_score_codex":0.0000069162734,"about_ca_system_score_gemma":0.000017253473,"threshold_uncertainty_score":0.55526763},"labels":[],"label_agreement":null},{"id":"W4390198288","doi":"10.1002/alz.081611","title":"Predicting cognitive decline in a low‐dimensional representation of brain morphology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Cognitive decline; Cognition; Representation (politics); Embedding; Neurodegeneration; Psychology; Nonlinear dimensionality reduction; Projection (relational algebra); Artificial intelligence; Pattern recognition (psychology); Cognitive psychology; Computer science; Dimensionality reduction; Neuroscience; Medicine; Dementia; Disease; Algorithm; Pathology","score_opus":0.0828630327894677,"score_gpt":0.3936465999757778,"score_spread":0.31078356718631006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99335,0.00077468896,0.0012109558,0.0036898248,0.00004125297,0.00047116843,0.000021114882,0.00016471518,0.00027622827],"genre_scores_gemma":[0.99452853,0.00002949788,0.0042913933,0.00078606256,0.000029609437,0.00008769943,0.0002160577,0.000017115575,0.000014054117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991384,0.00003131446,0.000289145,0.00024076989,0.00014319879,0.00015716806],"domain_scores_gemma":[0.9994163,0.0002042856,0.00010093759,0.00016442683,0.00007515378,0.00003892924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014534549,0.00007689977,0.00016055287,0.00015675918,0.00003172194,0.000002530952,0.000051383355,0.000037700047,0.000060830593],"category_scores_gemma":[0.00013676821,0.0000789432,0.00004444404,0.000527723,0.00006868501,0.000051442083,0.00010602134,0.000111208115,0.000034460016],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029596357,0.00047547228,0.772328,0.000024085566,0.0016643739,0.00017636878,0.00025688641,0.00021959787,0.18733814,0.0007171029,0.0056386935,0.030865278],"study_design_scores_gemma":[0.0028574446,0.0002731358,0.70667064,0.00024538607,0.003025976,0.000088407854,0.00017198606,0.010800316,0.2716245,0.0032372056,0.00079055,0.00021443343],"about_ca_topic_score_codex":0.00006877323,"about_ca_topic_score_gemma":0.000009879907,"teacher_disagreement_score":0.08428637,"about_ca_system_score_codex":0.0000024979245,"about_ca_system_score_gemma":0.000026294692,"threshold_uncertainty_score":0.32192102},"labels":[],"label_agreement":null},{"id":"W4390198417","doi":"10.1002/alz.081613","title":"Synthetic FDG‐PET hypometabolism sensitivity validation in AD","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Precuneus; Nuclear medicine; Positron emission tomography; Standardized uptake value; Posterior cingulate; Medicine; Pet imaging; Fluorodeoxyglucose; Radiology; Functional magnetic resonance imaging","score_opus":0.0779369262783936,"score_gpt":0.3501547217909986,"score_spread":0.272217795512605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198417","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96602166,0.007810018,0.0069993297,0.011928883,0.00032398762,0.0017271097,0.00005459266,0.0018298251,0.003304618],"genre_scores_gemma":[0.9922444,0.00026893252,0.0068943435,0.00030872668,0.000034582044,0.000090082955,0.00009428048,0.000027877837,0.000036760957],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907076,0.000042239884,0.00019851599,0.00029677968,0.0001576813,0.00023401954],"domain_scores_gemma":[0.9994114,0.00006020981,0.000053678712,0.0003733633,0.00003841553,0.00006289895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024334485,0.00011319414,0.00016839155,0.00018545233,0.000057262634,0.000012877238,0.000052689382,0.000027289894,0.00005272289],"category_scores_gemma":[0.000042561467,0.000114418894,0.000053777134,0.00057164987,0.000042028347,0.0000884314,0.00006801711,0.00013429858,0.0003156713],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012099369,0.00094257377,0.029634595,0.000044072935,0.0030511061,0.00098017,0.0003766774,0.00022592564,0.49500445,0.007002327,0.025167905,0.43744922],"study_design_scores_gemma":[0.0020112142,0.000135678,0.29730338,0.00015345655,0.01073285,0.00036479626,0.00010225523,0.007354332,0.44176057,0.008016295,0.23124978,0.0008153701],"about_ca_topic_score_codex":0.0000230739,"about_ca_topic_score_gemma":0.0000046685013,"teacher_disagreement_score":0.43663383,"about_ca_system_score_codex":0.0000046173163,"about_ca_system_score_gemma":0.000020635001,"threshold_uncertainty_score":0.4665867},"labels":[],"label_agreement":null},{"id":"W4390198436","doi":"10.1002/alz.081953","title":"Multivariate white matter differences links to cognition in individuals with family history of Alzheimer’s disease and APOE4 genetic risk","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; McGill Genome Centre; Montreal Neurological Institute and Hospital; Concordia University","funders":"","keywords":"Multivariate statistics; Mahalanobis distance; Univariate; Splenium; Psychology; Neuropsychology; Corpus callosum; Multivariate analysis; Voxel; Cognition; White matter; Medicine; Artificial intelligence; Statistics; Magnetic resonance imaging; Internal medicine; Computer science; Psychiatry; Mathematics; Neuroscience","score_opus":0.06582336743214791,"score_gpt":0.31374557819658794,"score_spread":0.24792221076444004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198436","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803223,0.014049284,0.0021701364,0.0013779955,0.000059556824,0.0013478694,0.00012245405,0.00017723342,0.00037318032],"genre_scores_gemma":[0.9835364,0.00027214971,0.015003439,0.0007706059,0.000021699148,0.00027236118,0.000065298686,0.000031148065,0.000026900147],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989445,0.00004115887,0.0002768672,0.0003506658,0.00018227984,0.00020451409],"domain_scores_gemma":[0.9993657,0.000036205005,0.00012712549,0.00027564194,0.00004739027,0.00014795974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000089836794,0.00015398297,0.00021934643,0.00022080044,0.000036063237,0.000008084065,0.00007715532,0.000049321166,0.000052699546],"category_scores_gemma":[0.000009515233,0.00013393215,0.00003161299,0.00021956512,0.00009619737,0.0000601352,0.00008545652,0.00017745787,0.000049654423],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006641843,0.0001361471,0.978974,0.000014823891,0.0011656939,0.00001604883,0.0004013403,0.000017127715,0.0026657158,0.000021439391,0.0052689337,0.011252341],"study_design_scores_gemma":[0.0006039439,0.000102764294,0.9889284,0.00008836332,0.0067858063,0.0000022996987,0.000031840817,0.0002444797,0.00048712108,0.00031223622,0.0022621746,0.00015061353],"about_ca_topic_score_codex":0.00007938497,"about_ca_topic_score_gemma":0.000006857906,"teacher_disagreement_score":0.013777134,"about_ca_system_score_codex":0.0000065667496,"about_ca_system_score_gemma":0.000047217323,"threshold_uncertainty_score":0.54615945},"labels":[],"label_agreement":null},{"id":"W4390198688","doi":"10.1002/alz.082001","title":"Subcortical deformation is uniquely related to cortical thickness among FTLD mutation carriers","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Putamen; Mutation; Grey matter; Frontotemporal lobar degeneration; Temporal lobe; Medicine; White matter; Magnetic resonance imaging; Pathology; Anatomy; Internal medicine; Psychology; Neuroscience; Frontotemporal dementia; Biology; Dementia; Genetics; Radiology; Epilepsy; Gene","score_opus":0.053309445814585944,"score_gpt":0.35127794575157967,"score_spread":0.2979684999369937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390198688","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9725646,0.00038777568,0.014169937,0.008684496,0.00014763702,0.0012252309,0.000019520252,0.0013142704,0.0014865792],"genre_scores_gemma":[0.9921354,0.00003096008,0.006134807,0.0012155923,0.000015914029,0.00017648569,0.00019854045,0.000037156555,0.000055129152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986891,0.000034897992,0.00038139915,0.00030955405,0.00027906656,0.0003059586],"domain_scores_gemma":[0.9991841,0.000040614308,0.00007085868,0.00035398031,0.00012706105,0.00022341289],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001781247,0.00014414811,0.00017089867,0.00015716521,0.00017198063,0.000025340494,0.00009992842,0.000094423856,0.00011217537],"category_scores_gemma":[0.00006714215,0.00013972334,0.000074028554,0.0007620507,0.00009021396,0.0001749483,0.00007317768,0.00025462665,0.00043126586],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00085728586,0.0009945013,0.25818086,0.00015129964,0.014534096,0.0008025586,0.010174495,0.00071051106,0.15310474,0.10635879,0.2123237,0.24180716],"study_design_scores_gemma":[0.002388664,0.00075875816,0.6961434,0.0001896859,0.019033674,0.00028738714,0.0008323163,0.031262875,0.20237485,0.015397844,0.030159643,0.0011709023],"about_ca_topic_score_codex":0.00002690035,"about_ca_topic_score_gemma":0.0000034532898,"teacher_disagreement_score":0.43796256,"about_ca_system_score_codex":0.000013275593,"about_ca_system_score_gemma":0.00004207974,"threshold_uncertainty_score":0.5697752},"labels":[],"label_agreement":null},{"id":"W4390199074","doi":"10.1002/alz.074136","title":"Impact of White Matter Hyperintensity Changes on Cognition One Year After Mild Ischemic Stroke","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Diffusion MRI; Fractional anisotropy; Montreal Cognitive Assessment; Medicine; White matter; Cardiology; Stroke (engine); Cognitive decline; Internal medicine; Cognition; Dementia; Brain size; Physical therapy; Magnetic resonance imaging; Disease; Psychiatry; Radiology","score_opus":0.07915447804355537,"score_gpt":0.3430500800400003,"score_spread":0.26389560199644496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199074","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9949376,0.00044534795,0.00017838975,0.001827704,0.00003069453,0.00036925025,0.00011603206,0.00017680122,0.0019181912],"genre_scores_gemma":[0.9967411,0.00008239442,0.0021903904,0.00061411294,0.0000516113,0.00008661467,0.000109687586,0.000027725062,0.00009633422],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993581,0.00000834766,0.0001240638,0.0002046433,0.00013287488,0.00017195304],"domain_scores_gemma":[0.99950904,0.000012492807,0.000057314755,0.00029276777,0.00007315317,0.00005522895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042285734,0.000107326225,0.0001532787,0.00010029475,0.000039199214,0.000004523281,0.00005159681,0.00003682584,0.00044386584],"category_scores_gemma":[0.0000044358685,0.00009778921,0.00008840161,0.000150909,0.000044898152,0.000028056962,0.00007195967,0.00010918419,0.00036160037],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060172845,0.000515542,0.53071874,0.000031771517,0.0056750155,0.000014254731,0.00020223478,0.000004190268,0.38414776,0.000030415884,0.06959742,0.008460914],"study_design_scores_gemma":[0.00046904807,0.00026501826,0.8484549,0.00006707697,0.0039677154,0.0000042724823,0.000015382138,0.000031796586,0.14281031,0.000049479317,0.0037282407,0.00013675584],"about_ca_topic_score_codex":0.000011734192,"about_ca_topic_score_gemma":0.0000021058308,"teacher_disagreement_score":0.31773615,"about_ca_system_score_codex":0.000004189189,"about_ca_system_score_gemma":0.000009321469,"threshold_uncertainty_score":0.48600197},"labels":[],"label_agreement":null},{"id":"W4390199449","doi":"10.1002/alz.073422","title":"Synthetic FDG‐PET hypometabolism sensitivity validation in AD","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Precuneus; Nuclear medicine; Positron emission tomography; Standardized uptake value; Posterior cingulate; Medicine; Pet imaging; Fluorodeoxyglucose; Radiology; Functional magnetic resonance imaging","score_opus":0.0779369262783936,"score_gpt":0.3501547217909986,"score_spread":0.272217795512605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96602166,0.007810018,0.0069993297,0.011928883,0.00032398762,0.0017271097,0.00005459266,0.0018298251,0.003304618],"genre_scores_gemma":[0.9922444,0.00026893252,0.0068943435,0.00030872668,0.000034582044,0.000090082955,0.00009428048,0.000027877837,0.000036760957],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99907076,0.000042239884,0.00019851599,0.00029677968,0.0001576813,0.00023401954],"domain_scores_gemma":[0.9994114,0.00006020981,0.000053678712,0.0003733633,0.00003841553,0.00006289895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024334485,0.00011319414,0.00016839155,0.00018545233,0.000057262634,0.000012877238,0.000052689382,0.000027289894,0.00005272289],"category_scores_gemma":[0.000042561467,0.000114418894,0.000053777134,0.00057164987,0.000042028347,0.0000884314,0.00006801711,0.00013429858,0.0003156713],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012099369,0.00094257377,0.029634595,0.000044072935,0.0030511061,0.00098017,0.0003766774,0.00022592564,0.49500445,0.007002327,0.025167905,0.43744922],"study_design_scores_gemma":[0.0020112142,0.000135678,0.29730338,0.00015345655,0.01073285,0.00036479626,0.00010225523,0.007354332,0.44176057,0.008016295,0.23124978,0.0008153701],"about_ca_topic_score_codex":0.0000230739,"about_ca_topic_score_gemma":0.0000046685013,"teacher_disagreement_score":0.43663383,"about_ca_system_score_codex":0.0000046173163,"about_ca_system_score_gemma":0.000020635001,"threshold_uncertainty_score":0.4665867},"labels":[],"label_agreement":null},{"id":"W4390199460","doi":"10.1002/alz.076693","title":"Blood‐based markers of neurodegeneration linked with brain atrophy and cognition in aging","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Atrophy; Neurodegeneration; Neuropsychology; Psychology; Montreal Cognitive Assessment; Glial fibrillary acidic protein; Cognitive decline; Brain size; Magnetic resonance imaging; Audiology; Cognition; Neuropsychological assessment; Pathology; Medicine; Neuroscience; Internal medicine; Cognitive impairment; Dementia; Immunohistochemistry; Disease; Radiology","score_opus":0.049504536565580834,"score_gpt":0.3160257329354967,"score_spread":0.26652119636991584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199460","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889128,0.0011263045,0.004431014,0.0044488977,0.000018241542,0.00061779126,0.000010511735,0.00019898849,0.00023543391],"genre_scores_gemma":[0.9869541,0.00004932749,0.012264215,0.0005230206,0.0000164867,0.000060490598,0.00010912682,0.00001835978,0.000004898836],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994267,0.000021164864,0.00015122509,0.0001902692,0.000099629164,0.000110985246],"domain_scores_gemma":[0.99968696,0.00004151845,0.000059552276,0.00014365277,0.00003462513,0.000033669683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000083732186,0.0000767011,0.00010412269,0.00013430993,0.000035823454,0.0000068992226,0.000028604676,0.000021223632,0.000009562966],"category_scores_gemma":[0.00001043574,0.000072052804,0.000018718842,0.00030242096,0.00004784633,0.000050776358,0.000019660825,0.00007603797,0.0000027048354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038935672,0.0003397791,0.07796092,0.00008416476,0.0015475608,0.000104258565,0.00012053122,0.0003529645,0.8630317,0.000819999,0.0025589808,0.05268978],"study_design_scores_gemma":[0.0069907675,0.0014190101,0.3464498,0.00037886685,0.014597482,0.00005489755,0.00008581742,0.023135863,0.60081947,0.0009754086,0.0045539057,0.00053870276],"about_ca_topic_score_codex":0.000015369766,"about_ca_topic_score_gemma":0.000007691065,"teacher_disagreement_score":0.26848888,"about_ca_system_score_codex":0.0000011102707,"about_ca_system_score_gemma":0.000018308212,"threshold_uncertainty_score":0.29382282},"labels":[],"label_agreement":null},{"id":"W4390199920","doi":"10.1002/alz.079169","title":"In vivo data‐driven patterns of Tau accumulation associated with AD progression using <sup>18</sup>F‐MK‐6240 PET","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Standardized uptake value; Temporal lobe; Dementia; Positron emission tomography; Cognitive impairment; Partial volume; Neuroscience; Pathology; Nuclear medicine; Alzheimer's disease; Psychology; Medicine; Cognition; Disease","score_opus":0.1895984076868383,"score_gpt":0.42421744955521273,"score_spread":0.23461904186837443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918466,0.0006556623,0.004794798,0.00081113796,0.000033385066,0.0012114919,0.00020684558,0.0003438099,0.00009626023],"genre_scores_gemma":[0.9867673,0.000055313936,0.0122464085,0.000106016916,0.000027036553,0.000054435794,0.0006863567,0.00004222372,0.000014945799],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874145,0.000041412914,0.00031544332,0.00037695962,0.00027696602,0.0002477525],"domain_scores_gemma":[0.9990119,0.00005166029,0.00019974106,0.00060172315,0.00007804623,0.00005694737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001697841,0.00014731065,0.00022596252,0.00016063523,0.00006873676,0.000012461183,0.00019288824,0.000043422297,0.00011519556],"category_scores_gemma":[0.000034449677,0.00013009943,0.000031891625,0.00051383174,0.00004275062,0.00025784393,0.00020199243,0.00014730029,0.000007871231],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031717043,0.0015093946,0.8351256,0.00011187774,0.0053776014,0.0003978236,0.0008194959,0.00681691,0.10235974,0.00022527447,0.015007399,0.031931665],"study_design_scores_gemma":[0.0054236325,0.0006513616,0.23906834,0.002050107,0.015354036,0.00008909706,0.0003433472,0.6374842,0.08388527,0.00052664266,0.014120939,0.0010030526],"about_ca_topic_score_codex":0.000064346226,"about_ca_topic_score_gemma":0.000023236658,"teacher_disagreement_score":0.63066727,"about_ca_system_score_codex":0.000012476271,"about_ca_system_score_gemma":0.000044998535,"threshold_uncertainty_score":0.5305301},"labels":[],"label_agreement":null},{"id":"W4390199949","doi":"10.1002/alz.073341","title":"Predicting cognitive decline in a low‐dimensional representation of brain morphology","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Biotechnology and Biological Sciences Research Council","keywords":"Cognitive decline; Representation (politics); Embedding; Cognition; Neurodegeneration; Psychology; Projection (relational algebra); Nonlinear dimensionality reduction; Artificial intelligence; Pattern recognition (psychology); Cognitive psychology; Computer science; Dimensionality reduction; Neuroscience; Medicine; Dementia; Disease; Algorithm; Pathology","score_opus":0.0828630327894677,"score_gpt":0.3936465999757778,"score_spread":0.31078356718631006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390199949","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99335,0.00077468896,0.0012109558,0.0036898248,0.00004125297,0.00047116843,0.000021114882,0.00016471518,0.00027622827],"genre_scores_gemma":[0.99452853,0.00002949788,0.0042913933,0.00078606256,0.000029609437,0.00008769943,0.0002160577,0.000017115575,0.000014054117],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991384,0.00003131446,0.000289145,0.00024076989,0.00014319879,0.00015716806],"domain_scores_gemma":[0.9994163,0.0002042856,0.00010093759,0.00016442683,0.00007515378,0.00003892924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014534549,0.00007689977,0.00016055287,0.00015675918,0.00003172194,0.000002530952,0.000051383355,0.000037700047,0.000060830593],"category_scores_gemma":[0.00013676821,0.0000789432,0.00004444404,0.000527723,0.00006868501,0.000051442083,0.00010602134,0.000111208115,0.000034460016],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029596357,0.00047547228,0.772328,0.000024085566,0.0016643739,0.00017636878,0.00025688641,0.00021959787,0.18733814,0.0007171029,0.0056386935,0.030865278],"study_design_scores_gemma":[0.0028574446,0.0002731358,0.70667064,0.00024538607,0.003025976,0.000088407854,0.00017198606,0.010800316,0.2716245,0.0032372056,0.00079055,0.00021443343],"about_ca_topic_score_codex":0.00006877323,"about_ca_topic_score_gemma":0.000009879907,"teacher_disagreement_score":0.08428637,"about_ca_system_score_codex":0.0000024979245,"about_ca_system_score_gemma":0.000026294692,"threshold_uncertainty_score":0.32192102},"labels":[],"label_agreement":null},{"id":"W4390201829","doi":"10.1002/alz.082484","title":"DTI changes of thalamic subregions in genetic frontotemporal dementia: findings from the GENFI cohort","year":2023,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Western University; Sunnybrook Health Science Centre; Toronto Western Hospital; Université Laval","funders":"","keywords":"C9orf72; Fractional anisotropy; Frontotemporal dementia; Diffusion MRI; Thalamus; Neuroscience; Psychology; Internal medicine; Medicine; Dementia; Magnetic resonance imaging; Disease; Radiology","score_opus":0.08735111776774905,"score_gpt":0.3351516772999296,"score_spread":0.24780055953218055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390201829","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9711321,0.01973405,0.001146416,0.0061617056,0.000108423264,0.0010992745,0.00006518822,0.00024106388,0.00031175237],"genre_scores_gemma":[0.9928465,0.00089676643,0.005275251,0.00047582408,0.00006182842,0.00022142411,0.00016750324,0.000034651872,0.000020269998],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99885166,0.0000336441,0.00029114942,0.00032857768,0.00021961251,0.00027536094],"domain_scores_gemma":[0.99919385,0.00007582702,0.00009960681,0.0005394939,0.000039201474,0.0000520246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014432355,0.00015135822,0.00022798048,0.00010099598,0.00008895528,0.000011154807,0.00023309642,0.00005538867,0.000109839944],"category_scores_gemma":[0.000013646159,0.00012303644,0.00007499689,0.0004144528,0.00010950554,0.00004380146,0.00013749987,0.0001604233,0.00005726163],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012950006,0.00007120936,0.9733769,0.000003866753,0.0017905935,0.000018876755,0.0001650118,0.0000050050107,0.008602942,0.00021186932,0.011173894,0.004566856],"study_design_scores_gemma":[0.0004149857,0.000048972077,0.97413194,0.000039815393,0.004582964,0.0000061536866,0.00006280643,0.00032112855,0.008455293,0.00103344,0.010777344,0.0001251513],"about_ca_topic_score_codex":0.00061734853,"about_ca_topic_score_gemma":0.00022699872,"teacher_disagreement_score":0.021714354,"about_ca_system_score_codex":0.0000061505048,"about_ca_system_score_gemma":0.000032148866,"threshold_uncertainty_score":0.50172806},"labels":[],"label_agreement":null},{"id":"W4390263399","doi":"10.1523/eneuro.0363-23.2023","title":"Dissection of the Temporofrontal Extreme Capsule Fasciculus Using Diffusion MRI Tractography and Association with Lexical Retrieval","year":2023,"lang":"en","type":"article","venue":"eNeuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université de Montréal; Institut Universitaire de Gériatrie de Montréal; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Alzheimer's Society; Alzheimer Society Research Program; Courtois Foundation; Government of Canada","keywords":"Arcuate fasciculus; Tractography; Diffusion MRI; Neuroscience; Uncinate fasciculus; White matter; Fasciculus; Anatomy; Psychology; Magnetic resonance imaging; Medicine; Fractional anisotropy; Radiology","score_opus":0.06248257841336648,"score_gpt":0.3156608470315914,"score_spread":0.25317826861822496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390263399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9965062,0.000013027444,0.0017404938,0.0011985501,0.00004837045,0.00022936742,0.0000066887537,0.00011787823,0.00013941832],"genre_scores_gemma":[0.9990061,0.00004170186,0.0006213453,0.000069171234,0.00003975667,0.0000043096597,0.000006837189,0.000013794617,0.00019699882],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99941075,0.000022584923,0.000110500354,0.00015590715,0.00020215366,0.000098081575],"domain_scores_gemma":[0.99965316,0.00003389975,0.000092207876,0.00015322906,0.000033799857,0.00003370194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007599169,0.00006524164,0.00009760744,0.00005363082,0.00010318672,0.000006626682,0.00003468678,0.00003747286,0.0000030618378],"category_scores_gemma":[0.000052652085,0.000043095006,0.000042105254,0.00043049935,0.00004216517,0.000043971362,0.000032193057,0.00013875857,4.5825627e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055063254,0.00006943345,0.21408296,0.000018276198,0.000008073465,0.0000065875065,0.00008442581,0.000019884936,0.78481233,0.00010072469,0.0003149108,0.00042732985],"study_design_scores_gemma":[0.00047788612,0.0001456755,0.8814584,0.00005916872,0.00006539324,0.000070827475,0.00006219884,0.0033830598,0.112676434,0.00029083324,0.0012288027,0.000081316866],"about_ca_topic_score_codex":0.000020180278,"about_ca_topic_score_gemma":0.000003234165,"teacher_disagreement_score":0.6721359,"about_ca_system_score_codex":0.000029073266,"about_ca_system_score_gemma":0.000014385096,"threshold_uncertainty_score":0.17573634},"labels":[],"label_agreement":null},{"id":"W4390404629","doi":"10.1002/mrm.29975","title":"Tensor‐valued diffusion <scp>MRI</scp> of human acute stroke","year":2023,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"China Scholarship Council; Canada Research Chairs; Medical College of Wisconsin; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Anisotropy; Diffusion; Isotropy; Monte Carlo method; Nuclear magnetic resonance; Chemistry; Physics; Medicine; Magnetic resonance imaging; Mathematics; Radiology; Statistics; Optics; Quantum mechanics","score_opus":0.05297050507675024,"score_gpt":0.36571458095207504,"score_spread":0.3127440758753248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390404629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9851687,0.002026779,0.0004635264,0.00410236,0.00007771336,0.0008612357,0.000026004027,0.00034705055,0.0069266316],"genre_scores_gemma":[0.94173455,0.006472882,0.009656511,0.0014732042,0.00037721463,0.00035958723,0.0001476695,0.00011125001,0.039667152],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981496,0.000036707374,0.00054968765,0.0004169679,0.0004739217,0.00037312825],"domain_scores_gemma":[0.998792,0.00019658083,0.0001308156,0.0006653378,0.000096617696,0.00011864588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002974574,0.00019588246,0.00053155894,0.00035938245,0.00006659156,0.0000034252944,0.00022156884,0.00008595652,0.000073407224],"category_scores_gemma":[0.00036422955,0.00015755784,0.000062952284,0.0009954919,0.00035952538,0.00003366419,0.00010722458,0.00033335952,0.000025874033],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056205234,0.00032729292,0.10256007,0.00023686094,0.000013102783,0.00044630087,0.0011456147,0.0000087457465,0.7614214,0.003257694,0.06757629,0.06295042],"study_design_scores_gemma":[0.0045201145,0.0023773273,0.7964218,0.0012262162,0.00014456912,0.00008748611,0.0005944902,0.0034412828,0.009839279,0.004728993,0.17648734,0.00013107837],"about_ca_topic_score_codex":0.00007063039,"about_ca_topic_score_gemma":0.0000056728895,"teacher_disagreement_score":0.75158215,"about_ca_system_score_codex":0.000036721733,"about_ca_system_score_gemma":0.000025859117,"threshold_uncertainty_score":0.6425022},"labels":[],"label_agreement":null},{"id":"W4390426154","doi":"10.21037/qims-23-847","title":"U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities","year":2023,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Nanjing University; Nanjing University of Science and Technology; National Natural Science Foundation of China","keywords":"Neuroimaging; Hyperintensity; White matter; Diffusion MRI; Fiber; Medicine; Internal medicine; Psychology; Pathology; Neuroscience; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.13741435567307747,"score_gpt":0.40989301879934814,"score_spread":0.27247866312627067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390426154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.953389,0.00066921214,0.018014206,0.026435176,0.00005073526,0.000570613,0.000026623722,0.0004099537,0.00043447196],"genre_scores_gemma":[0.9861475,0.0003314762,0.011814207,0.0010581247,0.000019248515,0.00010797617,0.0001309311,0.000024571384,0.00036596783],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998993,0.000035662266,0.00039425783,0.00029001484,0.00011389677,0.00017319145],"domain_scores_gemma":[0.99859446,0.000874213,0.00012654775,0.0001827081,0.00017147209,0.00005062588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00054625206,0.00012189934,0.0005103301,0.0008958862,0.000048959424,0.000008290985,0.000027551843,0.00002445363,0.000019156101],"category_scores_gemma":[0.00028762573,0.00010211982,0.00006764003,0.000962378,0.00032717964,0.000092256276,0.000015960048,0.000076451244,0.0000035710884],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014514492,0.00004006288,0.9538794,0.00037740733,0.00011900725,0.000020181013,0.0015611574,0.000055996814,0.00834572,0.0010847367,0.03208705,0.0022841413],"study_design_scores_gemma":[0.00046635076,0.000058624373,0.91765815,0.00042170382,0.00036138683,0.000027987908,0.0037105414,0.07321014,0.00034948287,0.00076109846,0.0028175055,0.00015703884],"about_ca_topic_score_codex":0.000056754434,"about_ca_topic_score_gemma":0.0000030837286,"teacher_disagreement_score":0.073154144,"about_ca_system_score_codex":0.000010885662,"about_ca_system_score_gemma":0.000020250473,"threshold_uncertainty_score":0.41643253},"labels":[],"label_agreement":null},{"id":"W4390489205","doi":"10.1109/sipaim56729.2023.10373434","title":"White Matter Bundles Linked to Cognitive Impairment in Alzheimer’s Patients and Intermediate Stages","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Cognitive impairment; Cognition; Psychology; Computer science; Medicine; Neuroscience; Magnetic resonance imaging; Radiology","score_opus":0.06008979235118269,"score_gpt":0.36432095769088163,"score_spread":0.30423116533969896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390489205","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9928088,0.0000103997245,0.00051068,0.004844987,0.000018568995,0.0007689365,0.000024401981,0.00019446328,0.00081874593],"genre_scores_gemma":[0.9939076,0.000043474294,0.0016248386,0.0034957624,0.0000147956125,0.00017813902,0.000049359118,0.000016982396,0.00066910713],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99941134,0.0000090236945,0.00013685066,0.00020804172,0.000078565296,0.00015616356],"domain_scores_gemma":[0.9997158,0.00003779014,0.00002150742,0.00009978521,0.00003892579,0.00008618316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004385668,0.00008336625,0.00011542431,0.00014913414,0.000022295397,0.000009932465,0.000032868065,0.000021264083,0.00006961158],"category_scores_gemma":[0.000015144924,0.000069346795,0.000016617616,0.00020911475,0.000031012547,0.000040221592,0.000102537684,0.00008128672,0.00017041308],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043776967,0.000109011475,0.9852985,0.00001319644,0.000011167971,0.000008694243,0.0003346043,6.668832e-7,0.00013670752,0.000023530076,0.008091844,0.0059283134],"study_design_scores_gemma":[0.00058113213,0.00019005525,0.9975488,0.00007686379,0.000019843406,0.000001615612,0.00013053331,0.00007548845,0.00041611007,0.00022983433,0.00065267365,0.00007700511],"about_ca_topic_score_codex":0.0000113523365,"about_ca_topic_score_gemma":0.000006975279,"teacher_disagreement_score":0.012250358,"about_ca_system_score_codex":0.00001368748,"about_ca_system_score_gemma":0.0000067773412,"threshold_uncertainty_score":0.28278804},"labels":[],"label_agreement":null},{"id":"W4390508574","doi":"10.3390/neurosci5010003","title":"Moving towards an Understanding of the Role of the Inferior Fronto-Occipital Fasciculus in Language Processing","year":2024,"lang":"en","type":"article","venue":"NeuroSci","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fasciculus; Fractional anisotropy; Dorsum; Diffusion MRI; Psychology; White matter; Superior longitudinal fasciculus; Anatomy; Biology; Medicine","score_opus":0.04862853014544044,"score_gpt":0.3477391946118507,"score_spread":0.29911066446641027,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390508574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99401546,0.00032658558,0.0021206813,0.00089160167,0.00009246749,0.00032206124,0.000013486115,0.00009092053,0.0021267626],"genre_scores_gemma":[0.99936455,0.000007508997,0.00035685705,0.00012756682,0.000027600085,0.000011612169,7.1598606e-7,0.000016689764,0.0000868697],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994258,0.000022508835,0.00014899702,0.0001553189,0.00014752016,0.00009981234],"domain_scores_gemma":[0.99962753,0.000017756884,0.00004918323,0.0002717142,0.000012749285,0.000021069816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057765574,0.00006645573,0.00010390341,0.000043783388,0.00004771469,0.000015559126,0.00014534155,0.000024133893,0.0000045513725],"category_scores_gemma":[0.00005742852,0.0000392879,0.000053482676,0.00031458883,0.00008843736,0.00008462308,0.00009141175,0.0001870353,2.189424e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012790744,0.000099849174,0.017731769,0.00016104901,0.000002410619,0.000010162768,0.002186638,0.00004208725,0.95868695,0.0036520653,0.000028237328,0.01738597],"study_design_scores_gemma":[0.0008309782,0.000339095,0.23804705,0.0021614856,0.00014175363,0.00018694052,0.007315787,0.07668514,0.65271324,0.01674966,0.004478887,0.000349966],"about_ca_topic_score_codex":0.000052244184,"about_ca_topic_score_gemma":0.000017167762,"teacher_disagreement_score":0.3059737,"about_ca_system_score_codex":0.000049677103,"about_ca_system_score_gemma":0.00007303018,"threshold_uncertainty_score":0.16021141},"labels":[],"label_agreement":null},{"id":"W4390512644","doi":"10.1038/s41598-023-50768-z","title":"White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"White matter; Diffusion MRI; Fiber tract; Medicine; Cognition; Type 2 Diabetes Mellitus; Internal medicine; Diabetes mellitus; Psychology; Cardiology; Pathology; Psychiatry; Magnetic resonance imaging; Endocrinology; Radiology","score_opus":0.017234161584411295,"score_gpt":0.27283407408042254,"score_spread":0.2555999124960112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390512644","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99637604,0.0017581026,0.00038153556,0.00065540534,0.00023754885,0.00039470635,0.000008016179,0.00005803435,0.00013063497],"genre_scores_gemma":[0.9976748,0.000042589967,0.000697624,0.00009838164,0.00002083894,0.000032042666,0.00011550447,0.000011950235,0.0013062484],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99926317,0.000007032896,0.00013741266,0.0003968201,0.00008218994,0.000113359965],"domain_scores_gemma":[0.9996465,0.000015709915,0.000038295522,0.00014674893,0.00007494848,0.00007779531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008947952,0.000079668,0.00008012366,0.00008415395,0.00010855941,0.00012730586,0.000013587079,0.000020058025,0.000022618196],"category_scores_gemma":[0.00001623585,0.00006183477,0.000009364356,0.00027885762,0.00011005633,0.00015213234,0.000022335485,0.00011147925,0.000004112457],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032992397,0.00002601906,0.9922039,0.00030051282,0.000009589587,0.00013921713,0.00042877783,0.000035054116,0.0038906508,0.00007676629,0.0009952439,0.0018613122],"study_design_scores_gemma":[0.0001768287,0.00005838737,0.97346723,0.0009473916,0.000100266836,0.0003642718,0.000036706548,0.01558975,0.0042254417,0.0021331292,0.0027297605,0.00017084047],"about_ca_topic_score_codex":7.2793114e-7,"about_ca_topic_score_gemma":0.0000017826682,"teacher_disagreement_score":0.018736638,"about_ca_system_score_codex":0.000010922872,"about_ca_system_score_gemma":0.000051986117,"threshold_uncertainty_score":0.2521549},"labels":[],"label_agreement":null},{"id":"W4390537154","doi":"10.2139/ssrn.4668765","title":"Diffusion Tensor Imaging for Evaluation of Cortical Spinal Tract and Cerebral Infarction Lesion in Arterial Ischemic Stroke Pediatric Patients","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Diffusion MRI; Medicine; Stroke (engine); Infarction; Lesion; Cerebral infarction; Magnetic resonance imaging; Brain infarction; Radiology; Cardiology; Internal medicine; Ischemia; Pathology; Myocardial infarction","score_opus":0.03890195195586875,"score_gpt":0.3642319694553152,"score_spread":0.32533001749944646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390537154","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889668,0.0012327373,0.0075908606,0.00077267137,0.0002067171,0.0011308708,0.000025843437,0.000036887326,0.000036609537],"genre_scores_gemma":[0.9970159,0.0014871145,0.0007701071,0.000022974562,0.0004768859,0.000096760974,0.00006841775,0.000038515525,0.000023350116],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99791706,0.00007284517,0.0005435393,0.00037596803,0.00042939963,0.0006612022],"domain_scores_gemma":[0.99912995,0.0000347571,0.00030829658,0.00017138751,0.00028955526,0.00006605246],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0012992263,0.0002014712,0.0003090602,0.0003476403,0.00007188035,0.000028593693,0.00008422557,0.00012863771,0.0000042206316],"category_scores_gemma":[0.00020891846,0.00018155703,0.0001365394,0.00010629829,0.000033097673,0.00006543741,0.00013596682,0.0025610423,7.1361893e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031861076,0.0019621465,0.59970665,0.0013236084,0.00013949169,0.0000054591533,0.00023950031,0.0001384864,0.04678262,0.0041598086,0.00039370084,0.3419624],"study_design_scores_gemma":[0.012976986,0.002023489,0.6028296,0.0011716674,0.0029524555,0.000644111,0.00038899673,0.061502974,0.0013445991,0.3132233,0.00025371322,0.00068815134],"about_ca_topic_score_codex":0.000013484897,"about_ca_topic_score_gemma":0.000007860975,"teacher_disagreement_score":0.34127426,"about_ca_system_score_codex":0.00082877453,"about_ca_system_score_gemma":0.001199056,"threshold_uncertainty_score":0.99974006},"labels":[],"label_agreement":null},{"id":"W4390584905","doi":"10.3389/fnins.2023.1228952","title":"Evaluation of tractography-based myelin-weighted connectivity across the lifespan","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Myelin; Tractography; Connectome; Diffusion MRI; White matter; Neuroscience; Magnetic resonance imaging; Neuroplasticity; Computer science; Biology; Functional connectivity; Medicine; Central nervous system; Radiology","score_opus":0.08478501845121374,"score_gpt":0.40210080993244784,"score_spread":0.3173157914812341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390584905","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6504863,0.00062950555,0.34232974,0.0042626876,0.0007907239,0.0009589204,0.00002970553,0.0001953991,0.00031699598],"genre_scores_gemma":[0.99392885,0.00004375306,0.0053600706,0.00052091456,0.00002444686,0.00008917219,0.0000018974436,0.000010923297,0.000019952424],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867445,0.00009515841,0.00017629753,0.00034350064,0.00053324446,0.00017733446],"domain_scores_gemma":[0.9993579,0.00009047662,0.000049346465,0.00035423235,0.00010738506,0.000040695755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001166139,0.00008531541,0.00012725325,0.00012666883,0.000086256456,0.000026441106,0.00018022973,0.000029708612,0.0000028396903],"category_scores_gemma":[0.00033137843,0.00006057832,0.00006799455,0.0012236314,0.0003822822,0.00010132335,0.000025096382,0.00022956706,5.499859e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017404612,0.0010326866,0.24378452,0.00028428924,0.000018674618,0.0000606481,0.0012865623,0.0030247841,0.25796032,0.0032836506,0.01199861,0.47709122],"study_design_scores_gemma":[0.00046088724,0.00014379543,0.18829186,0.00012991647,0.00007874268,0.000017080378,0.0000836791,0.76513463,0.024296548,0.006064328,0.0151790455,0.00011950382],"about_ca_topic_score_codex":0.000008697325,"about_ca_topic_score_gemma":0.0000020288635,"teacher_disagreement_score":0.7621098,"about_ca_system_score_codex":0.000044993216,"about_ca_system_score_gemma":0.00016667055,"threshold_uncertainty_score":0.24703121},"labels":[],"label_agreement":null},{"id":"W4390607650","doi":"10.1117/1.jmi.11.1.014005","title":"Robust fiber orientation distribution function estimation using deep constrained spherical deconvolution for diffusion-weighted magnetic resonance imaging","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Center for Research Resources; National Institute of General Medical Sciences; National Institutes of Health; National Science Foundation","keywords":"Human Connectome Project; Deconvolution; Diffusion MRI; Magnetic resonance imaging; Artificial intelligence; Regularization (linguistics); Tractography; Orientation (vector space); Deep learning; Computer science; Real-time MRI; Pattern recognition (psychology); Algorithm; Medicine; Mathematics","score_opus":0.03570822091407746,"score_gpt":0.3462099798567345,"score_spread":0.3105017589426571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390607650","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016658552,0.0044069295,0.9701797,0.0077650277,0.00044215593,0.0003577133,0.000013295883,0.00013663906,0.000040031842],"genre_scores_gemma":[0.7636485,0.00029933924,0.2337512,0.00088062964,0.0010373272,0.000040634524,0.0001930604,0.00006585166,0.00008342785],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980551,0.000043570923,0.0006884073,0.00027046527,0.000690623,0.0002518107],"domain_scores_gemma":[0.9988333,0.0002399243,0.00022286523,0.00013909445,0.0003397429,0.00022509885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060003845,0.00016188178,0.00025909857,0.0001353999,0.00016367793,0.000084078274,0.00010049707,0.00007014494,0.00022049814],"category_scores_gemma":[0.0005478573,0.000138673,0.00016379774,0.00039225174,0.00016769754,0.00042531342,0.00003298842,0.0004335677,0.000005020958],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022987966,0.00014057352,0.0013978817,0.000148892,0.000013948284,0.00012209505,0.000057979138,0.00030353453,0.005819253,0.0011909227,0.0034906764,0.9870844],"study_design_scores_gemma":[0.0012574033,0.00007500433,0.0020957817,0.0009221905,0.00025823025,0.00184159,0.000084062245,0.969075,0.00034712715,0.002810496,0.021105364,0.00012770513],"about_ca_topic_score_codex":0.0000074804475,"about_ca_topic_score_gemma":4.184454e-7,"teacher_disagreement_score":0.98695666,"about_ca_system_score_codex":0.00031274534,"about_ca_system_score_gemma":0.00024766274,"threshold_uncertainty_score":0.5654921},"labels":[],"label_agreement":null},{"id":"W4390616343","doi":"10.1038/s41467-023-44591-3","title":"Radiomic tractometry reveals tract-specific imaging biomarkers in white matter","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Deutsches Krebsforschungszentrum; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"White matter; Computational biology; Medicine; Magnetic resonance imaging; Biology; Radiology","score_opus":0.046331377153241295,"score_gpt":0.3832871021868001,"score_spread":0.3369557250335588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390616343","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14451978,0.25100604,0.014862208,0.47274208,0.0007724758,0.0038166023,0.00026983864,0.0032137744,0.10879722],"genre_scores_gemma":[0.955944,0.0026060313,0.039023206,0.0016947695,0.000051783485,0.00013060594,0.00012839958,0.00004929014,0.00037190627],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989623,0.00005564287,0.00031759508,0.00032132043,0.00013367747,0.00020947287],"domain_scores_gemma":[0.99774,0.00025865136,0.00004836901,0.0018243273,0.000052077037,0.000076610275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023377268,0.00015039042,0.00019251084,0.0005451461,0.00010560069,0.0000645845,0.00050955906,0.00013717232,0.00010939695],"category_scores_gemma":[0.000034205586,0.00014385968,0.0001077576,0.0012096295,0.00013619338,0.00018739505,0.000121133155,0.0015434584,0.00012269778],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003642787,0.0007221212,0.6190817,0.00016157315,0.00007848477,0.00009830973,0.00044816415,0.0000034595487,0.048843816,0.018093806,0.2779375,0.03449467],"study_design_scores_gemma":[0.0002705459,0.000010813097,0.45665672,0.00033721322,0.000044497174,0.00037001976,0.00006866963,0.0011550382,0.0003358575,0.0016181786,0.53892624,0.00020616964],"about_ca_topic_score_codex":0.0000034481727,"about_ca_topic_score_gemma":0.0000032997032,"teacher_disagreement_score":0.81142426,"about_ca_system_score_codex":0.000157114,"about_ca_system_score_gemma":0.000040668507,"threshold_uncertainty_score":0.6705645},"labels":[],"label_agreement":null},{"id":"W4390666148","doi":"10.3389/fneur.2023.1322815","title":"Preoperative validation of edema-corrected tractography in neurosurgical practice: translating surgeon insights into novel software implementation","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Synaptive (Canada)","funders":"","keywords":"Medicine; Radiology; Medical physics; Tractography; Magnetic resonance imaging; Diffusion MRI","score_opus":0.030109449360110303,"score_gpt":0.3629948687341775,"score_spread":0.33288541937406724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390666148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81627786,0.00049519876,0.17748068,0.0041387533,0.0004153824,0.0009017077,0.000009374344,0.00017499272,0.00010606846],"genre_scores_gemma":[0.9583048,0.0002181854,0.040705405,0.00048460427,0.000033773304,0.00013627078,0.00008258528,0.000029299557,0.000005055085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985603,0.0001509782,0.0005125158,0.00043535497,0.00014782141,0.00019303629],"domain_scores_gemma":[0.999303,0.0002795549,0.00013163175,0.00017773065,0.000065391854,0.00004271446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000174461,0.00014614328,0.00029849715,0.0005984263,0.00003372672,0.000013203751,0.00007319294,0.000107696134,0.000011342324],"category_scores_gemma":[0.00018550025,0.00014372283,0.000070613285,0.0010585693,0.00008791725,0.00026611713,0.000020755682,0.0005038239,5.422371e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017836841,0.0013990883,0.8106804,0.0005122519,0.00008871762,0.0005494352,0.010452268,0.001474477,0.06390766,0.0023765191,0.0025450906,0.10423045],"study_design_scores_gemma":[0.009823292,0.0042775073,0.73999774,0.0005900406,0.00048963627,0.0008082668,0.0019527867,0.06983885,0.081847645,0.020252232,0.06891628,0.001205733],"about_ca_topic_score_codex":0.000068457615,"about_ca_topic_score_gemma":0.000029395227,"teacher_disagreement_score":0.14202699,"about_ca_system_score_codex":0.000028524159,"about_ca_system_score_gemma":0.00007087123,"threshold_uncertainty_score":0.5860847},"labels":[],"label_agreement":null},{"id":"W4390692324","doi":"10.1162/imag_a_00075","title":"A database of the healthy human spinal cord morphometry in the PAM50 template space","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"HORIZON EUROPE Framework Programme; Natural Sciences and Engineering Research Council of Canada; European Commission; Institut de Valorisation des Données; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Ministerstvo Zdravotnictví Ceské Republiky","keywords":"Spinal cord; Space (punctuation); Computer science; Database; Medicine; Artificial intelligence; Neuroscience; Biology; Operating system","score_opus":0.1230567045196196,"score_gpt":0.4452457757036849,"score_spread":0.3221890711840653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390692324","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9034759,0.00074252975,0.018708015,0.07391711,0.00044863392,0.0010920193,0.00004701959,0.00030049076,0.001268272],"genre_scores_gemma":[0.9937523,0.000047271216,0.0011550948,0.004871692,0.000031248055,0.000029136581,0.0000011453965,0.00001276206,0.000099350225],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989214,0.000042842625,0.00018443345,0.00034841942,0.00029068525,0.00021219949],"domain_scores_gemma":[0.99917495,0.00006329526,0.0000537111,0.0006462899,0.000020926358,0.00004084282],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031053254,0.00009299042,0.00010161799,0.00012446051,0.00016054673,0.00004629596,0.00042915638,0.000008622504,0.00000331656],"category_scores_gemma":[0.00012265095,0.00005479436,0.00004819269,0.0013420434,0.00038805132,0.00013156928,0.0001348405,0.00036950884,0.0000024998346],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000747344,0.00024119172,0.05753911,0.00030801923,0.0000010324705,0.0002954775,0.00016239804,0.00001235663,0.9112943,0.014654337,0.0070834444,0.008333637],"study_design_scores_gemma":[0.0006900344,0.00082505774,0.7934153,0.0016713182,0.00006465116,0.002942355,0.00020065698,0.01360783,0.04155545,0.0051308125,0.13949847,0.00039803845],"about_ca_topic_score_codex":0.00006649833,"about_ca_topic_score_gemma":0.0000020530676,"teacher_disagreement_score":0.8697388,"about_ca_system_score_codex":0.000023300137,"about_ca_system_score_gemma":0.00007227138,"threshold_uncertainty_score":0.22344491},"labels":[],"label_agreement":null},{"id":"W4390747482","doi":"10.1016/j.media.2024.103085","title":"What matters in reinforcement learning for tractography","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Compute Canada","keywords":"Reinforcement learning; Tractography; Computer science; Codebase; Artificial intelligence; Function (biology); Machine learning; White matter; Software","score_opus":0.033939239268384484,"score_gpt":0.3895429358701114,"score_spread":0.3556036966017269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390747482","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007500368,0.00054508983,0.94225794,0.048745994,0.000047698264,0.00031315951,0.0000010520341,0.00026535094,0.00032335293],"genre_scores_gemma":[0.9789048,0.0016736048,0.0116818305,0.005794777,0.000099797915,0.00029311437,0.00017192171,0.000028567152,0.0013515917],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990103,0.000013795969,0.00025254872,0.0002688455,0.0002746544,0.00017980696],"domain_scores_gemma":[0.99950635,0.00013438542,0.000024607705,0.00017827225,0.000030086334,0.00012630876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002632383,0.00008843773,0.0002331478,0.00051884144,0.00003457226,0.000070238195,0.00007466255,0.000046497644,0.00044842958],"category_scores_gemma":[0.000105335734,0.00007280447,0.00025114653,0.0013286204,0.00006729,0.00018248516,0.000023268269,0.0002797573,0.0000134443635],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000290261,0.0010519616,0.030690018,0.002036776,0.005137765,0.0023621977,0.0022810518,0.0038376334,0.037820973,0.004540199,0.07739695,0.8325542],"study_design_scores_gemma":[0.0008879011,0.00023582061,0.004288794,0.000732485,0.0029507854,0.000038233837,0.00050169555,0.64537424,0.003016005,0.0014841188,0.3401463,0.00034362427],"about_ca_topic_score_codex":0.000020379943,"about_ca_topic_score_gemma":0.0000069349394,"teacher_disagreement_score":0.97140443,"about_ca_system_score_codex":0.000032624237,"about_ca_system_score_gemma":0.000029591336,"threshold_uncertainty_score":0.49099895},"labels":[],"label_agreement":null},{"id":"W4390840316","doi":"10.1101/2024.01.11.575169","title":"Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"White matter; In utero; Fractional anisotropy; Diffusion MRI; Tractography; Macaque; Neuroscience; Cohort; Biology; Psychology; Medicine; Pregnancy; Internal medicine; Fetus; Magnetic resonance imaging; Genetics","score_opus":0.027320700792127606,"score_gpt":0.2577149400748102,"score_spread":0.2303942392826826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390840316","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9918408,0.00008705384,0.0013476331,0.004345967,0.000082665494,0.0017843173,0.00010825465,0.0003934119,0.000009941936],"genre_scores_gemma":[0.9921832,0.000048386548,0.00656116,0.0003282789,0.000046436933,0.0006746941,0.000005168925,0.000104660874,0.00004800557],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9984596,0.000050406103,0.00046428427,0.00066278945,0.0001282421,0.00023467674],"domain_scores_gemma":[0.99907434,0.000017611843,0.0000930031,0.0004564271,0.00021305158,0.00014557081],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000094418465,0.00031408056,0.00033429038,0.0005669508,0.000057177513,0.00013558722,0.00009095958,0.00015641526,0.000030454863],"category_scores_gemma":[0.00008906533,0.00029593694,0.000026461972,0.00089030777,0.000029220411,0.00007433608,0.00023564497,0.00033007257,0.00007955582],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042054282,0.00014140263,0.48320192,0.00022771956,0.000022763401,0.00006483478,0.00013401819,0.00019221462,0.5156826,0.00020589435,0.00007850992,0.00000613154],"study_design_scores_gemma":[0.00042939375,0.00007593438,0.7956861,0.001123394,0.00005521682,2.2661494e-7,0.00000413658,0.00084404566,0.20128457,0.00001535144,0.00019152103,0.00029007456],"about_ca_topic_score_codex":0.00006169739,"about_ca_topic_score_gemma":0.000012907429,"teacher_disagreement_score":0.314398,"about_ca_system_score_codex":0.00047032477,"about_ca_system_score_gemma":0.00016852775,"threshold_uncertainty_score":0.9999493},"labels":[],"label_agreement":null},{"id":"W4390856523","doi":"","title":"A Riemannian framework for incorporating white matter bundle priors in ODF-based tractography algorithms.","year":2025,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Prior probability; Tractography; Bundle; Algorithm; Mathematics; White matter; Artificial intelligence; Computer science; Bayesian probability; Materials science; Medicine","score_opus":0.03347959620418627,"score_gpt":0.3156327220764811,"score_spread":0.2821531258722948,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390856523","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013278444,0.00024155078,0.9380671,0.038211413,0.00008711792,0.0019627267,0.00019561389,0.0003847234,0.00757132],"genre_scores_gemma":[0.22575012,0.00006365378,0.76947904,0.0010126453,0.000024999044,0.0009007107,0.0006408039,0.000055726476,0.0020722868],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970471,0.0007613019,0.00066424673,0.0009124288,0.0002632087,0.00035170803],"domain_scores_gemma":[0.9949225,0.001247388,0.00053391466,0.0020728523,0.0010736795,0.00014963654],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0018218126,0.00036126177,0.0005230918,0.0004901431,0.00022342055,0.00015227878,0.0006500062,0.0003636945,0.00004704672],"category_scores_gemma":[0.0007750137,0.0003975442,0.0003167637,0.0007461245,0.00020218895,0.000071801725,0.00046562526,0.0011390087,0.000006468682],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031871232,0.010073873,0.5713397,0.006151721,0.0003170441,0.000037035712,0.011899524,0.0012245682,0.002515738,0.27306405,0.008677148,0.11438087],"study_design_scores_gemma":[0.006091197,0.000012588944,0.1849073,0.05187485,0.0007097253,0.00004138508,0.00048148018,0.2067232,0.07112518,0.39208418,0.08256278,0.0033861299],"about_ca_topic_score_codex":0.00020536213,"about_ca_topic_score_gemma":0.00018008467,"teacher_disagreement_score":0.3864324,"about_ca_system_score_codex":0.00012498513,"about_ca_system_score_gemma":0.00036466494,"threshold_uncertainty_score":0.99984765},"labels":[],"label_agreement":null},{"id":"W4390987871","doi":"10.1016/j.neuroimage.2024.120516","title":"A unified filtering method for estimating asymmetric orientation distribution functions","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"NIH Blueprint for Neuroscience Research; National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; McDonnell Center for Systems Neuroscience; Université de Bordeaux; National Institutes of Health","keywords":"Computer science; Human Connectome Project; Orientation (vector space); Artificial intelligence; Robustness (evolution); Algorithm; Mathematics","score_opus":0.08145382950075854,"score_gpt":0.41301489582213924,"score_spread":0.3315610663213807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390987871","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023175625,0.0000461943,0.9930277,0.001729886,0.00029457957,0.0006436594,0.00014785382,0.0008733204,0.0009192717],"genre_scores_gemma":[0.18131842,0.000010633197,0.8159693,0.0002713013,0.0002837302,0.00037981776,0.0006029033,0.000051543993,0.0011123812],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991337,0.000018667788,0.00019598371,0.00036841584,0.00011072331,0.00017248343],"domain_scores_gemma":[0.99932575,0.00025320888,0.000038994945,0.00024253386,0.000075475255,0.00006404961],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014364423,0.00011106456,0.00012415138,0.00013261494,0.0001475551,0.00006693791,0.000049017202,0.000032325937,0.000012925077],"category_scores_gemma":[0.00030713461,0.000107458436,0.00009334382,0.000699347,0.00002125211,0.00014281007,0.000028774906,0.0001773997,0.000019614334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112173126,0.00020233421,0.00020550517,0.000853706,0.00004382332,0.00007987133,0.00012139908,0.000634005,0.2801454,0.028063668,0.036243852,0.65329427],"study_design_scores_gemma":[0.00053568964,0.0003172524,0.0023394334,0.00015585124,0.00022553379,0.00028319506,0.00003361762,0.7912348,0.020045843,0.0040818094,0.1805303,0.00021670583],"about_ca_topic_score_codex":0.0000058890505,"about_ca_topic_score_gemma":2.2188578e-7,"teacher_disagreement_score":0.7906008,"about_ca_system_score_codex":0.000060581548,"about_ca_system_score_gemma":0.00003374167,"threshold_uncertainty_score":0.43820277},"labels":[],"label_agreement":null},{"id":"W4391014509","doi":"10.1088/1361-6560/ad209c","title":"High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling","year":2024,"lang":"en","type":"article","venue":"Physics in Medicine and Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"National Institute of Biomedical Imaging and Bioengineering; National Cancer Institute; National Institutes of Health","keywords":"Bicubic interpolation; Computer science; Artificial intelligence; Probabilistic logic; Noise reduction; Interpolation (computer graphics); Noise (video); Pattern recognition (psychology); Computer vision; Resolution (logic); Image (mathematics); Linear interpolation","score_opus":0.37939140524178533,"score_gpt":0.45162854348542714,"score_spread":0.07223713824364181,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391014509","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30333102,0.00051828247,0.693662,0.0021265585,0.00003600796,0.00020529586,0.000008324597,0.00008849077,0.000024034474],"genre_scores_gemma":[0.91114885,0.00048627963,0.08769148,0.00021302614,0.00036215855,0.000022610886,0.000055736673,0.000017669803,0.0000021666],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991761,0.00002732778,0.0001739729,0.00040042694,0.00006410634,0.0001581054],"domain_scores_gemma":[0.9993693,0.00019913701,0.000032218322,0.00033335848,0.000023658262,0.00004231208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012712422,0.00011667535,0.0002584462,0.000077127595,0.000062702245,0.000007268108,0.000083492436,0.00006139165,0.0000031177178],"category_scores_gemma":[0.000120549725,0.00007595719,0.000011555428,0.00026682782,0.00017989123,0.00005908415,0.00009706465,0.0002797242,6.707115e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007117862,0.0008305363,0.01425247,0.0022735586,0.00026822678,0.00027234005,0.0020659424,0.052523013,0.20738012,0.3405119,0.000492454,0.37841767],"study_design_scores_gemma":[0.00018237626,0.00013118835,0.000067652414,0.0017701519,0.00014522784,0.00005421322,0.000059099093,0.9262514,0.00010296649,0.07082519,0.00031816855,0.00009234489],"about_ca_topic_score_codex":0.00014592361,"about_ca_topic_score_gemma":0.0000047373896,"teacher_disagreement_score":0.8737284,"about_ca_system_score_codex":0.000038635902,"about_ca_system_score_gemma":0.000034759043,"threshold_uncertainty_score":0.30974445},"labels":[],"label_agreement":null},{"id":"W4391023660","doi":"10.1016/j.neuropsychologia.2024.108801","title":"Examining the consistency in bilingualism and white matter research: A meta-analysis","year":2024,"lang":"en","type":"article","venue":"Neuropsychologia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Neuroscience of multilingualism; White matter; Psychology; Fractional anisotropy; Operationalization; Cognition; Developmental psychology; Meta-analysis; Neuroscience; Magnetic resonance imaging; Medicine","score_opus":0.5498971572156616,"score_gpt":0.5024093913961325,"score_spread":0.04748776581952907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391023660","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89025956,0.004082799,0.0015901241,0.06582182,0.00007751858,0.0010478793,0.00001701651,0.00045715438,0.03664613],"genre_scores_gemma":[0.99194497,0.00011156268,0.0019290581,0.0039499523,0.000026639029,0.00012320485,0.0000030428018,0.00002029903,0.0018912948],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987412,0.00017739441,0.00021754668,0.0004961785,0.0001698843,0.0001977849],"domain_scores_gemma":[0.99887276,0.00039507123,0.00002192125,0.00061946205,0.000046642886,0.000044120647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000696799,0.000100745994,0.00028844055,0.00036250873,0.00007481598,0.000059894966,0.000115057665,0.00003834968,0.00021856368],"category_scores_gemma":[0.000103491686,0.000058154244,0.00014169206,0.0015150235,0.00024227852,0.00003648706,0.000077793935,0.00059464836,0.000045608725],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026883013,0.0010212337,0.7134244,0.00052312366,0.030905712,0.0068750097,0.007478207,0.0001048121,0.04621185,0.028192393,0.13826925,0.026725225],"study_design_scores_gemma":[0.00028721342,0.00026706347,0.92242354,0.000027081875,0.023526926,0.00061635615,0.00029664137,0.0008666417,0.00018423726,0.00718434,0.044071842,0.00024809767],"about_ca_topic_score_codex":0.00000910071,"about_ca_topic_score_gemma":0.0000032478465,"teacher_disagreement_score":0.2089992,"about_ca_system_score_codex":0.000009238878,"about_ca_system_score_gemma":0.000014017716,"threshold_uncertainty_score":0.25834844},"labels":[],"label_agreement":null},{"id":"W4391055807","doi":"10.1093/nop/npae003","title":"Multimodal imaging with magnetization transfer and diffusion tensor imaging reveals evidence of myelin damage in children and youth treated for a brain tumor","year":2024,"lang":"en","type":"article","venue":"Neuro-Oncology Practice","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Canadian Institutes of Health Research","keywords":"Magnetization transfer; Diffusion MRI; Neuroimaging; Myelin; Nuclear magnetic resonance; Neuroscience; Psychology; Medicine; Magnetic resonance imaging; Materials science; Physics; Radiology","score_opus":0.030584150671444557,"score_gpt":0.35576698830464343,"score_spread":0.3251828376331989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391055807","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9566798,0.0009393352,0.01839491,0.021950012,0.000018158662,0.0017291442,0.000043792847,0.0001562517,0.00008855935],"genre_scores_gemma":[0.97844845,0.0004401681,0.018511025,0.002369588,0.000038572227,0.00009757934,0.00002603194,0.000041942283,0.000026670976],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988037,0.00013627009,0.0002834269,0.000490725,0.00010213375,0.00018375319],"domain_scores_gemma":[0.9979798,0.001575332,0.000079025114,0.00018989688,0.00010855854,0.000067384346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003460428,0.00015641825,0.00026313352,0.00018777608,0.00006399598,0.00002745482,0.000054529988,0.000036124286,0.0000037020145],"category_scores_gemma":[0.0010394003,0.0001321939,0.000025137835,0.00027401975,0.00016419368,0.00042759257,0.00003810052,0.00028886535,4.0916404e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001775701,0.00027990324,0.27160162,0.00025590736,0.0000201096,0.00017647726,0.0012675015,0.000014379395,0.6902849,0.00041306554,0.00021746055,0.03369297],"study_design_scores_gemma":[0.010641788,0.003703468,0.85958034,0.0026001288,0.0019260814,0.008405249,0.0014776639,0.08884631,0.015603047,0.0005458673,0.0058803526,0.00078972446],"about_ca_topic_score_codex":0.00009459142,"about_ca_topic_score_gemma":0.0000062797176,"teacher_disagreement_score":0.67468184,"about_ca_system_score_codex":0.000035816127,"about_ca_system_score_gemma":0.00006116812,"threshold_uncertainty_score":0.5390711},"labels":[],"label_agreement":null},{"id":"W4391055873","doi":"10.1093/brain/awae021","title":"Multimodal study of multilevel pulvino-temporal connections: a new piece in the puzzle of lexical retrieval networks","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Centre d'Imagerie BioMédicale; National Institute of Dental and Craniofacial Research; Institut National de la Santé et de la Recherche Médicale; University of Minnesota; University of Southern California; Massachusetts General Hospital","keywords":"Temporal lobe; Neuroscience; Temporal cortex; Inferior temporal gyrus; Superior temporal gyrus; Tractography; Middle temporal gyrus; Psychology; White matter; Superior temporal sulcus; Electrocorticography; Angular gyrus; Anatomy; Biology; Electroencephalography; Functional magnetic resonance imaging; Magnetic resonance imaging; Medicine","score_opus":0.09833140360147559,"score_gpt":0.3979470373016012,"score_spread":0.2996156337001256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391055873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92398024,0.00040611788,0.06476686,0.008610715,0.0000863705,0.0016392545,0.000014180834,0.00016532009,0.00033092257],"genre_scores_gemma":[0.99631417,0.000011701852,0.0029584644,0.00022370082,0.000093619405,0.000031069678,0.000008983678,0.00001549653,0.00034281408],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991458,0.000060285416,0.00030201432,0.00021109357,0.00016078829,0.000119989796],"domain_scores_gemma":[0.9991769,0.00039374156,0.000050744635,0.0003075911,0.00003144332,0.000039561935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027377522,0.000087627486,0.00019059198,0.000091905196,0.000030602892,0.0000084283,0.00012047927,0.000046967758,0.000018432833],"category_scores_gemma":[0.0002345533,0.00006366993,0.000059666974,0.0004493122,0.000060012295,0.000041830346,0.000039047736,0.00028454364,0.0000016216441],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0049582855,0.030078892,0.22496182,0.0015404772,0.0006939187,0.0011401549,0.040175952,0.008458249,0.10825976,0.087223254,0.22043693,0.27207232],"study_design_scores_gemma":[0.011797109,0.0053739063,0.38788378,0.0015359494,0.00037819965,0.00050142815,0.0066787116,0.49043062,0.007965,0.011701152,0.074943505,0.0008106071],"about_ca_topic_score_codex":0.0003200355,"about_ca_topic_score_gemma":0.000059225462,"teacher_disagreement_score":0.4819724,"about_ca_system_score_codex":0.000019905377,"about_ca_system_score_gemma":0.00005385818,"threshold_uncertainty_score":0.25963846},"labels":[],"label_agreement":null},{"id":"W4391065342","doi":"10.1101/2024.01.18.576325","title":"The FinnBrain Multimodal Neonatal Template and Atlas Collection: T1, T2, and DTI brain templates, and accompanying cortical and subcortical atlases","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Hospital for Sick Children; Montreal Neurological Institute and Hospital","funders":"","keywords":"Spatial normalization; Diffusion MRI; Computer science; White matter; Artificial intelligence; Anterior commissure; Neuroimaging; Segmentation; Pattern recognition (psychology); Template; Neuroscience; Brain morphometry; Brain atlas; Computer vision; Psychology; Medicine; Magnetic resonance imaging; Voxel; Radiology","score_opus":0.030965555731908654,"score_gpt":0.2925237791060957,"score_spread":0.26155822337418705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391065342","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9848821,0.0062419474,0.0008451481,0.006186449,0.00015112004,0.0010817471,0.00013083806,0.0004755933,0.0000050637495],"genre_scores_gemma":[0.9875439,0.0024111585,0.009200559,0.0002903962,0.00020088362,0.00023101356,9.3041933e-7,0.00010056445,0.00002061101],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9976763,0.00007963805,0.0004733739,0.0010771444,0.00025301098,0.00044052262],"domain_scores_gemma":[0.9980443,0.00069119723,0.00013706689,0.00056774524,0.00014954036,0.0004101515],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00040287004,0.00046829382,0.00052678835,0.00016963312,0.00060844864,0.00042022625,0.00012682377,0.00030799943,0.0000042986258],"category_scores_gemma":[0.00047475472,0.00038724628,0.00005792554,0.00032526685,0.0007066344,0.00008651046,0.000996172,0.001269923,0.0000034914058],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013242789,0.0005748022,0.18785748,0.005316214,0.0011093428,0.001732312,0.00023052476,0.000010092481,0.7658998,0.021508843,0.012501917,0.0019344258],"study_design_scores_gemma":[0.002853053,0.0003429601,0.89796,0.0018214255,0.00082310353,0.00003365851,0.000037511338,0.019885968,0.02986464,0.00038761544,0.044419013,0.0015710508],"about_ca_topic_score_codex":0.000061398256,"about_ca_topic_score_gemma":0.0000083875975,"teacher_disagreement_score":0.7360351,"about_ca_system_score_codex":0.00008321672,"about_ca_system_score_gemma":0.00019911348,"threshold_uncertainty_score":0.99985796},"labels":[],"label_agreement":null},{"id":"W4391099314","doi":"10.3390/info15010066","title":"Baseline Structural Connectomics Data of Healthy Brain Development Assessed with Multi-Modal Magnetic Resonance Imaging","year":2024,"lang":"en","type":"article","venue":"Information","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University; Memorial University of Newfoundland","funders":"National Institutes of Health; Canada Foundation for Innovation; Nova Scotia Research Innovation Trust","keywords":"Connectomics; Diffusion MRI; Magnetic resonance imaging; Baseline (sea); Tractography; Neuroimaging; Medicine; Functional magnetic resonance imaging; Neuroscience; Connectome; Psychology; Biology; Radiology; Functional connectivity","score_opus":0.07220338928432064,"score_gpt":0.3798657373353466,"score_spread":0.307662348051026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391099314","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13010448,0.0011113848,0.85784477,0.008740366,0.000110495355,0.001019795,0.00022203705,0.00052639964,0.00032026478],"genre_scores_gemma":[0.74147594,0.000027857552,0.25633863,0.0012168746,0.000030332098,0.00002469277,0.00084503286,0.000011456591,0.000029196826],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930024,0.00000883036,0.00030988417,0.00012497987,0.00014472804,0.00011135306],"domain_scores_gemma":[0.999385,0.00006751858,0.00007052253,0.00034498985,0.00009116898,0.000040820538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018029523,0.00008319824,0.00010780285,0.00009582468,0.000046320736,0.000027240565,0.000110438225,0.000017835278,0.000013098728],"category_scores_gemma":[0.000072464776,0.000066808585,0.000010324841,0.00019599752,0.000037636408,0.0006497394,0.000057320085,0.000118113654,0.000007272147],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002481579,0.00004892521,0.00573061,0.0007955767,0.0000104145165,0.000008426272,0.0009776831,0.00011000415,0.0025346763,0.0032039431,0.0052823857,0.9810492],"study_design_scores_gemma":[0.001063643,0.00010113761,0.032021653,0.00034799118,0.000021780115,0.00014488971,0.00011294205,0.71564376,0.002841053,0.00010052839,0.24744608,0.0001545716],"about_ca_topic_score_codex":0.00001585428,"about_ca_topic_score_gemma":0.0000050316567,"teacher_disagreement_score":0.9808946,"about_ca_system_score_codex":0.000049098504,"about_ca_system_score_gemma":0.00020834315,"threshold_uncertainty_score":0.2724375},"labels":[],"label_agreement":null},{"id":"W4391116136","doi":"10.1101/2024.01.20.576373","title":"Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fibre calibre, and vascularization","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Canada Research Chairs; Washington University in St. Louis","keywords":"Caliber; White matter; Order (exchange); White (mutation); Neuroscience; Biology; Medicine; Engineering; Genetics; Magnetic resonance imaging; Business; Gene; Mechanical engineering","score_opus":0.0583193677192866,"score_gpt":0.2912724294215054,"score_spread":0.2329530617022188,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391116136","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9523738,0.00052104087,0.03955368,0.0042013586,0.00011610595,0.0021068119,0.00038529254,0.0007308692,0.00001104433],"genre_scores_gemma":[0.71233726,0.000077258635,0.28549445,0.0010431019,0.00016680102,0.000764641,0.000004808773,0.00009847296,0.00001322934],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99824476,0.000025597572,0.00035641144,0.0009249784,0.00015883382,0.00028940194],"domain_scores_gemma":[0.9988622,0.000077209836,0.00012249341,0.0003956817,0.00031159708,0.00023083994],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016162106,0.00035279756,0.00039056255,0.00021146012,0.00018373704,0.00013507943,0.000119303775,0.00033894143,0.00000915338],"category_scores_gemma":[0.00021663151,0.00034720037,0.000064025946,0.00047269772,0.00006630985,0.00006413834,0.00043060695,0.00054763077,0.000008448224],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037312246,0.00023415443,0.09824545,0.0018807605,0.0001685417,0.00004649732,0.00004546414,0.00006434921,0.89495426,0.0006863834,0.0035164936,0.00012032557],"study_design_scores_gemma":[0.0008012416,0.00017287495,0.900443,0.0017271122,0.0005765383,0.0000016556434,0.000011638666,0.003656213,0.07840658,0.00010065603,0.012913378,0.0011890958],"about_ca_topic_score_codex":0.0000074971144,"about_ca_topic_score_gemma":2.582941e-7,"teacher_disagreement_score":0.8165477,"about_ca_system_score_codex":0.000106644795,"about_ca_system_score_gemma":0.0001948705,"threshold_uncertainty_score":0.999898},"labels":[],"label_agreement":null},{"id":"W4391264577","doi":"10.1016/j.media.2024.103093","title":"Neural deformation fields for template-based reconstruction of cortical surfaces from MRI","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Segmentation; Polygon mesh; Computer vision; Surface (topology); Flow (mathematics); Surface reconstruction; Pattern recognition (psychology); Mathematics; Geometry; Computer graphics (images)","score_opus":0.03829917376689692,"score_gpt":0.3651151343577,"score_spread":0.3268159605908031,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391264577","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23969628,0.000096090465,0.75391567,0.0058008144,0.00006211022,0.00015737493,0.00004470537,0.00014102412,0.00008590827],"genre_scores_gemma":[0.95280397,0.00004123355,0.04638382,0.0003358134,0.000107146334,0.00003895123,0.00024346658,0.000009134903,0.000036445468],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908936,0.000022071881,0.00033086375,0.00020293797,0.000246812,0.00010794353],"domain_scores_gemma":[0.9992487,0.00030898288,0.00005118637,0.00020057007,0.00008758706,0.000102987986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016657427,0.00007789914,0.00025430633,0.00016385259,0.000042986005,0.000018404766,0.000064758366,0.000082758044,0.00045426155],"category_scores_gemma":[0.0002449645,0.000060903698,0.00023676685,0.00053211657,0.00011746602,0.000096163334,0.000013914209,0.0001868927,0.000005135959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010861058,0.0013759433,0.10614023,0.0022133484,0.0057183546,0.000280377,0.0006913676,0.003426623,0.13809432,0.0026207713,0.049071,0.6892815],"study_design_scores_gemma":[0.00026097134,0.000074299285,0.003726832,0.00007557591,0.0014533425,0.000010166362,0.000028777386,0.97835624,0.013677565,0.0008422136,0.0014215632,0.00007243157],"about_ca_topic_score_codex":0.000077231474,"about_ca_topic_score_gemma":0.000015763788,"teacher_disagreement_score":0.97492963,"about_ca_system_score_codex":0.000019693074,"about_ca_system_score_gemma":0.000052045536,"threshold_uncertainty_score":0.49738455},"labels":[],"label_agreement":null},{"id":"W4391289272","doi":"10.1016/j.bas.2024.102759","title":"Parcellating the vertical associative fiber network of the temporoparietal area: Evidence from focused anatomic fiber dissections","year":2024,"lang":"en","type":"article","venue":"Brain and Spine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University Health Network","funders":"","keywords":"Anatomy; Intraparietal sulcus; Neuroscience; Superior parietal lobule; Arcuate fasciculus; Sulcus; Inferior parietal lobule; Psychology; Posterior parietal cortex; Biology; Medicine; Cognition; White matter; Fractional anisotropy","score_opus":0.060246112724505016,"score_gpt":0.3435291800678275,"score_spread":0.2832830673433225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391289272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.855291,0.057147216,0.010294364,0.072022125,0.00018149083,0.0017435661,0.00004757876,0.0004467384,0.0028259275],"genre_scores_gemma":[0.99510837,0.00095470395,0.002349286,0.00029670587,0.00013792202,0.000037785874,0.000004521314,0.000016197744,0.0010944904],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99942315,0.0000393984,0.00016105524,0.00017220431,0.00009574128,0.00010843157],"domain_scores_gemma":[0.9991698,0.00053397834,0.000031151085,0.00020906632,0.0000224508,0.000033548768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011659361,0.000079503356,0.00014499105,0.000009578724,0.00014203109,0.000019808516,0.00006516195,0.000032362925,0.00006821075],"category_scores_gemma":[0.00024140492,0.000041901618,0.00007981869,0.0002424177,0.00012780791,0.000036215737,0.00006970849,0.0002064766,0.0000045633387],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019634322,0.00047770198,0.07922228,0.0007738328,0.0010379935,0.00008094915,0.004654459,0.00030982672,0.039249767,0.036536958,0.11906618,0.7183937],"study_design_scores_gemma":[0.0009838013,0.00035015776,0.5646784,0.0070627253,0.001004218,0.00011820801,0.00022098668,0.055279616,0.0056605735,0.032032706,0.33202946,0.00057916064],"about_ca_topic_score_codex":0.000032130476,"about_ca_topic_score_gemma":0.0000069996713,"teacher_disagreement_score":0.71781456,"about_ca_system_score_codex":0.00002008786,"about_ca_system_score_gemma":0.00003600951,"threshold_uncertainty_score":0.17086984},"labels":[],"label_agreement":null},{"id":"W4391292901","doi":"10.1016/j.jad.2024.01.238","title":"White matter alterations in affective and non-affective early psychosis: A diffusion MRI study","year":2024,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministero dell'Istruzione e del Merito","keywords":"White matter; Psychosis; Diffusion MRI; Psychology; Affect (linguistics); Psychiatry; Neuroscience; Medicine; Magnetic resonance imaging; Radiology; Communication","score_opus":0.012224279075635993,"score_gpt":0.3390501681491027,"score_spread":0.3268258890734667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391292901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96612513,0.0003405848,0.028203666,0.0025873438,0.00013246274,0.0015339082,0.000006548744,0.000044975215,0.0010254006],"genre_scores_gemma":[0.998347,0.00019206862,0.0009067476,0.00019877788,0.000081011494,0.00015508292,0.0000015091613,0.0000393986,0.00007844837],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988679,0.000113287875,0.0002896916,0.00032920248,0.00021157836,0.00018831337],"domain_scores_gemma":[0.9992542,0.00023410839,0.000120778146,0.0001781033,0.000113975046,0.000098812765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002538315,0.00020335929,0.000345515,0.0005183738,0.0000890581,0.00006548606,0.00007453081,0.000054791533,0.000019931002],"category_scores_gemma":[0.000048774607,0.0001630754,0.00012735053,0.00058709853,0.00007947805,0.00032518897,0.000044310913,0.00058434857,0.000009079829],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027299515,0.0013201946,0.9761248,0.00007127582,0.00015625208,0.00007325947,0.00612692,0.000045907516,0.0021226513,0.000075794545,0.0016973977,0.011912554],"study_design_scores_gemma":[0.0017081008,0.0022452981,0.9904883,0.0004615965,0.00015393003,0.00010094233,0.0014151343,0.00060966314,0.00017611704,0.0022825429,0.00020366404,0.00015471902],"about_ca_topic_score_codex":0.00009885809,"about_ca_topic_score_gemma":0.00019577051,"teacher_disagreement_score":0.032221846,"about_ca_system_score_codex":0.00012988415,"about_ca_system_score_gemma":0.000040224146,"threshold_uncertainty_score":0.66500217},"labels":[],"label_agreement":null},{"id":"W4391467208","doi":"10.1101/2024.02.01.578366","title":"A Multimodal Characterization of Low-Dimensional Thalamocortical Structural Connectivity Patterns","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Max-Planck-Gesellschaft; Bundesministerium für Bildung und Forschung; Canada Research Chairs; McGill University","keywords":"Neuroscience; Thalamus; Human Connectome Project; Connectome; Diffusion MRI; Tractography; Default mode network; Functional connectivity; Psychology; Computer science; Magnetic resonance imaging; Medicine","score_opus":0.023777826702546957,"score_gpt":0.28422209264990594,"score_spread":0.260444265947359,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391467208","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919927,0.000056981913,0.0046442025,0.0005741047,0.00037181994,0.0010342925,0.0007460848,0.00057673815,0.000003069632],"genre_scores_gemma":[0.9919708,0.000025164163,0.007213005,0.00016060284,0.00029611468,0.00021421825,0.0000044267576,0.00011190086,0.000003770854],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980012,0.00004484108,0.0004954734,0.000822055,0.0003333341,0.00030307626],"domain_scores_gemma":[0.9982035,0.000049268674,0.00027640755,0.00091246725,0.00036718897,0.00019113303],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013374817,0.0003875348,0.00056601135,0.00019722768,0.000063345695,0.000041632524,0.0001816176,0.00030237992,0.00004515177],"category_scores_gemma":[0.00009997866,0.00037475856,0.00018942094,0.0002591838,0.00012998561,0.000057531826,0.0005506306,0.00091793056,0.00001563253],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004566209,0.00012625608,0.018253148,0.00097307604,0.00007159161,0.000054236883,0.0000039026027,0.0000076649685,0.9791436,0.0013021977,0.000012312087,0.0000063121684],"study_design_scores_gemma":[0.00032676882,0.000056974026,0.45735633,0.0009150477,0.00017297379,1.9370167e-7,3.6526762e-7,0.008281976,0.53245634,0.000039312716,0.000060179143,0.00033353394],"about_ca_topic_score_codex":0.000015996566,"about_ca_topic_score_gemma":2.4056357e-7,"teacher_disagreement_score":0.44668728,"about_ca_system_score_codex":0.00013143219,"about_ca_system_score_gemma":0.00036109402,"threshold_uncertainty_score":0.9998704},"labels":[],"label_agreement":null},{"id":"W4391484784","doi":"10.1016/j.mri.2024.01.008","title":"Influence of preprocessing, distortion correction and cardiac triggering on the quality of diffusion MR images of spinal cord","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute; Centre Hospitalier Universitaire Sainte-Justine; Université de Montréal; Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Distortion (music); Image quality; Preprocessor; Artificial intelligence; Diffusion MRI; Spinal cord; Computer vision; Computer science; Tractography; Image processing; White matter; Pattern recognition (psychology); Medicine; Image (mathematics); Magnetic resonance imaging; Radiology","score_opus":0.03561056874983854,"score_gpt":0.3677234859921943,"score_spread":0.33211291724235575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391484784","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9870091,0.009126052,0.0027132477,0.0004473618,0.000048629227,0.00028608425,0.00000909062,0.000056231125,0.0003042098],"genre_scores_gemma":[0.99815106,0.00065467536,0.0008745065,0.000024333805,0.000019798355,0.000032643275,0.0000014825198,0.000011878418,0.0002296323],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.999101,0.000033723616,0.00034137332,0.00023073476,0.00019567153,0.00009754284],"domain_scores_gemma":[0.9993261,0.00012913228,0.00015052364,0.00027510553,0.0000960256,0.000023090992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027567666,0.0000885333,0.00020731377,0.00006741188,0.0000448819,0.000009733594,0.00006007797,0.000016303666,0.0000037386749],"category_scores_gemma":[0.00021166084,0.00006587475,0.000053520518,0.00022857699,0.00025117135,0.00007256368,0.000043041106,0.0001321516,2.9787358e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025536015,0.00005781097,0.06211265,0.00059512275,0.0000024864298,0.0000017079327,0.00011892599,0.00002228439,0.3922442,0.00072624924,0.00016021151,0.543703],"study_design_scores_gemma":[0.00015160504,0.00032503268,0.8738842,0.0018666878,0.000039578692,0.00000887185,0.000068071124,0.00247335,0.11795286,0.00058102794,0.002569114,0.00007961282],"about_ca_topic_score_codex":0.000108114626,"about_ca_topic_score_gemma":2.7656418e-7,"teacher_disagreement_score":0.8117715,"about_ca_system_score_codex":0.000023957024,"about_ca_system_score_gemma":0.000028429788,"threshold_uncertainty_score":0.26862946},"labels":[],"label_agreement":null},{"id":"W4391576525","doi":"10.1089/neu.2023.0208","title":"Advanced Magnetic Resonance Imaging Biomarkers of the Injured Spinal Cord: A Comparative Study of Imaging and Histology in Human Traumatic Spinal Cord Injury","year":2024,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver General Hospital; International Collaboration On Repair Discoveries; Vancouver Spine Surgery Institute; University of British Columbia; University of British Columbia Hospital","funders":"","keywords":"Myelin; Spinal cord; Medicine; Magnetic resonance imaging; Pathology; Fractional anisotropy; Diffusion MRI; Luxol fast blue stain; White matter; Spinal cord injury; Central nervous system; Radiology; Internal medicine","score_opus":0.10837825317078192,"score_gpt":0.43644165587663486,"score_spread":0.32806340270585294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391576525","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99290615,0.00474954,0.00025294858,0.0011113646,0.00012595199,0.0007150008,0.000006190015,0.00002282754,0.000110049434],"genre_scores_gemma":[0.9980912,0.000078266676,0.0016381769,0.0001050134,0.00002866534,0.000019521181,3.2747292e-7,0.000023506935,0.000015320038],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99819654,0.00013990427,0.0009305188,0.000259419,0.00028472499,0.00018889709],"domain_scores_gemma":[0.9989382,0.00007936357,0.00047544538,0.00029995237,0.00014013312,0.000066906956],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002501391,0.00018464189,0.00055927876,0.0003951416,0.00006474945,0.000013871259,0.00023179212,0.000022063807,0.0000070741335],"category_scores_gemma":[0.000059167978,0.00014162756,0.000110461646,0.0005508199,0.00040693596,0.00014413882,0.000074984724,0.00053121697,2.0563735e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010662723,0.0016886602,0.05452372,0.00066096155,0.000056152276,0.00067188154,0.0015793932,0.0000116666415,0.38093784,0.0007497501,0.00068782485,0.5477694],"study_design_scores_gemma":[0.0029107304,0.016219597,0.9627418,0.002625814,0.00024939634,0.0021540488,0.0020642055,0.0011031928,0.006380015,0.0017060684,0.0016296415,0.00021550704],"about_ca_topic_score_codex":0.00002171205,"about_ca_topic_score_gemma":0.000007726583,"teacher_disagreement_score":0.9082181,"about_ca_system_score_codex":0.00006583314,"about_ca_system_score_gemma":0.000069830145,"threshold_uncertainty_score":0.57754046},"labels":[],"label_agreement":null},{"id":"W4391585419","doi":"10.1007/978-3-031-47292-3","title":"Computational Diffusion MRI","year":2023,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Diffusion; Thermodynamics; Physics","score_opus":0.03998252665559456,"score_gpt":0.34057089504401056,"score_spread":0.300588368388416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585419","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00012822164,0.000046996996,0.99501,0.0024251125,0.00027755616,0.0004362571,0.000008928491,0.00039286655,0.0012740596],"genre_scores_gemma":[0.020607052,0.00010223201,0.96252537,0.005014525,0.0009807937,0.00005509902,0.00018090023,0.00010349796,0.010430517],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982423,0.000008549331,0.0002403529,0.00071186206,0.0005180408,0.0002788549],"domain_scores_gemma":[0.9988932,0.0002852828,0.00009760153,0.00049851736,0.00012828714,0.00009710085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017172557,0.00021029293,0.0002811961,0.00042948133,0.0001364909,0.000046959947,0.0003859773,0.0001221906,0.000011624271],"category_scores_gemma":[0.000057879268,0.00018658263,0.00006807891,0.0006939757,0.00042326038,0.000058706384,0.00034803126,0.00055676285,0.000058235742],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034318542,0.00019012827,0.0012009194,0.00029702886,0.000017001104,0.00043894871,0.00050156243,0.20712534,0.0008020266,0.0052516763,0.009649871,0.7744912],"study_design_scores_gemma":[0.00033921184,0.00014613067,0.0018368857,0.00066369487,0.000017261744,0.00017061236,8.705102e-8,0.55624783,0.0003080763,0.42994118,0.009989394,0.00033961757],"about_ca_topic_score_codex":0.0000028184054,"about_ca_topic_score_gemma":0.000002577666,"teacher_disagreement_score":0.77415156,"about_ca_system_score_codex":0.0002508798,"about_ca_system_score_gemma":0.00053092884,"threshold_uncertainty_score":0.7608619},"labels":[],"label_agreement":null},{"id":"W4391585483","doi":"10.1007/978-3-031-47292-3_4","title":"Improving Multi-Tensor Fitting with Global Information from Track Orientation Density Imaging","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Orientation (vector space); Track (disk drive); Tensor (intrinsic definition); Computer vision; Artificial intelligence; Geometry; Mathematics","score_opus":0.032347199288199166,"score_gpt":0.3066180835841583,"score_spread":0.27427088429595914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585483","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023804854,0.000018339351,0.9957733,0.00051664433,0.0001864074,0.0005166515,0.000026238376,0.000385215,0.00019667477],"genre_scores_gemma":[0.15162317,0.0000107008145,0.8465664,0.0014139024,0.00019718189,0.000015193858,0.00009547156,0.000027935701,0.00005008836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984384,0.0000057878974,0.00031232586,0.0005617459,0.0004150042,0.00026671804],"domain_scores_gemma":[0.9988238,0.00011910187,0.00026260965,0.0004553376,0.00025438698,0.00008476864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016412142,0.00024544811,0.00025523707,0.0001916814,0.00017718211,0.0001222362,0.00024270646,0.00008587854,0.0000034959949],"category_scores_gemma":[0.000108376735,0.00021252639,0.000046686706,0.0003359272,0.00025992797,0.00044800952,0.00017959366,0.0004245974,0.000019393143],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027655618,0.0000133176,0.005825892,0.00004976317,0.0000060943157,0.00005244452,0.00032790803,0.0022488297,0.00050405954,0.0005490158,0.000008574596,0.9903864],"study_design_scores_gemma":[0.000971527,0.00011919868,0.018464986,0.0009468509,0.00006989836,0.00016608834,0.0000036762442,0.9504084,0.003237654,0.024691263,0.00035303988,0.0005673956],"about_ca_topic_score_codex":0.00012793874,"about_ca_topic_score_gemma":0.000046061894,"teacher_disagreement_score":0.98981905,"about_ca_system_score_codex":0.0002700793,"about_ca_system_score_gemma":0.00017727588,"threshold_uncertainty_score":0.86665744},"labels":[],"label_agreement":null},{"id":"W4391585496","doi":"10.1007/978-3-031-47292-3_5","title":"BundleSeg: A Versatile, Reliable and Reproducible Approach to White Matter Bundle Segmentation","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec en Outaouais","funders":"","keywords":"Computer science; Segmentation; Bundle; Artificial intelligence; Computer vision; Materials science","score_opus":0.05548664248652436,"score_gpt":0.3148966712500903,"score_spread":0.25941002876356595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391585496","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00036972124,0.000049262588,0.98498964,0.0030133568,0.00015457842,0.0009838261,0.000007178963,0.00021800201,0.01021441],"genre_scores_gemma":[0.022933442,0.00006645451,0.9600336,0.0045195566,0.0002963668,0.000100275356,0.000041351792,0.00008661564,0.011922325],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978203,0.0000044244057,0.0002524432,0.0012697233,0.00036059256,0.00029247443],"domain_scores_gemma":[0.9986926,0.00005319846,0.00009331916,0.00092926144,0.00010478258,0.00012684241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002920026,0.00024280512,0.00029695354,0.00044958605,0.00013054656,0.00009003128,0.00026354165,0.00010518654,0.000016556507],"category_scores_gemma":[0.000032324722,0.00022431208,0.000038457914,0.00046264313,0.00023765532,0.00011321864,0.0003655969,0.00038881757,0.00006985483],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004955302,0.0012634944,0.06463517,0.0034731175,0.00016856726,0.00025841477,0.013263193,0.15081893,0.0181876,0.034330845,0.03354943,0.6795557],"study_design_scores_gemma":[0.0034876151,0.00317222,0.03216255,0.0055621946,0.00037970545,0.0016406988,0.000016305872,0.3455529,0.02896972,0.53091127,0.043129124,0.0050157136],"about_ca_topic_score_codex":0.000016206146,"about_ca_topic_score_gemma":0.0000030077272,"teacher_disagreement_score":0.67454,"about_ca_system_score_codex":0.00012787459,"about_ca_system_score_gemma":0.00009140742,"threshold_uncertainty_score":0.9147181},"labels":[],"label_agreement":null},{"id":"W4391668587","doi":"10.1016/j.cobeha.2024.101353","title":"Cerebellar imaging with diffusion magnetic resonance imaging: approaches, challenges, and potential","year":2024,"lang":"en","type":"article","venue":"Current Opinion in Behavioral Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"H2020 European Research Council; European Research Council; Horizon 2020; Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; European Commission; Canada Foundation for Innovation; Horizon 2020 Framework Programme; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; White matter; Magnetic resonance imaging; Cerebellum; Neuroscience; Computer science; Tractography; Diffusion imaging; Medicine; Psychology; Radiology","score_opus":0.22106940932986416,"score_gpt":0.4033958399592782,"score_spread":0.18232643062941403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391668587","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25732097,0.7196172,0.0031121194,0.01528009,0.0015784567,0.00150588,0.00002357071,0.00070454285,0.0008571589],"genre_scores_gemma":[0.980999,0.014702362,0.003993226,0.000015862037,0.0001400074,0.000088912275,0.0000146135635,0.0000176025,0.00002841677],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986927,0.000020937836,0.0001715487,0.00058309175,0.00027926144,0.00025245416],"domain_scores_gemma":[0.99967456,0.000017950737,0.000029346684,0.00017086534,0.000019688943,0.000087603075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016774736,0.00014550303,0.00013408525,0.00016902745,0.00012126027,0.00007639673,0.00012216369,0.000018473893,0.000010888814],"category_scores_gemma":[0.0000050677836,0.00010862286,0.000026857495,0.0003490814,0.0004393381,0.00020737047,0.00009384395,0.00022609896,0.0000025588024],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011462066,0.0001818943,0.040080678,0.000104028346,2.2050227e-7,0.000011720823,0.0001912147,0.0000018570968,0.00044713813,0.003556932,0.00024388851,0.95516896],"study_design_scores_gemma":[0.0016358631,0.00082772545,0.5981831,0.006780087,0.00009431601,0.0011944978,0.0011347021,0.050136525,0.00030621508,0.0060524098,0.33265835,0.0009962056],"about_ca_topic_score_codex":0.000015597514,"about_ca_topic_score_gemma":0.0000012376324,"teacher_disagreement_score":0.9541728,"about_ca_system_score_codex":0.000037913254,"about_ca_system_score_gemma":0.000054327058,"threshold_uncertainty_score":0.44295114},"labels":[],"label_agreement":null},{"id":"W4391671707","doi":"10.1016/j.media.2024.103101","title":"Blurred streamlines: A novel representation to reduce redundancy in tractography","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Streamlines, streaklines, and pathlines; Redundancy (engineering); Artificial intelligence; False positive paradox; Computer science; Tractography; Representation (politics); Pattern recognition (psychology); Algorithm; Mathematics; Computer vision; Diffusion MRI","score_opus":0.070228611807333,"score_gpt":0.4499603158126226,"score_spread":0.37973170400528955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391671707","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19355728,0.0003697577,0.76240057,0.04052943,0.000060858074,0.00053517637,0.000032316097,0.0005779828,0.001936657],"genre_scores_gemma":[0.95332265,0.00018053634,0.044476803,0.0010407923,0.0001545608,0.00016525063,0.00014301421,0.000026166343,0.0004902061],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983719,0.000021957861,0.00039982735,0.0005271797,0.00046994077,0.0002091692],"domain_scores_gemma":[0.99905014,0.00012158592,0.000032681153,0.00044711126,0.000072109455,0.0002763472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022361043,0.00012775224,0.00032894756,0.0009824805,0.00003169226,0.000045289875,0.00013150215,0.00006918364,0.0003359828],"category_scores_gemma":[0.00055646885,0.00010966732,0.00027897512,0.0055526565,0.00007955678,0.000115757415,0.00004407874,0.0003213747,0.000031705775],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029042774,0.003297006,0.045835648,0.0004285366,0.002162549,0.0027973896,0.0018251301,0.00021371472,0.31488904,0.0022403125,0.033906057,0.5921142],"study_design_scores_gemma":[0.0050516794,0.0007516445,0.347748,0.0030028103,0.012292724,0.0005965411,0.0015762413,0.3835024,0.07628771,0.007333722,0.15975738,0.002099153],"about_ca_topic_score_codex":0.00018010559,"about_ca_topic_score_gemma":0.00004594389,"teacher_disagreement_score":0.7597654,"about_ca_system_score_codex":0.000045654422,"about_ca_system_score_gemma":0.0000817579,"threshold_uncertainty_score":0.44721037},"labels":[],"label_agreement":null},{"id":"W4391814809","doi":"10.1080/09297049.2024.2307662","title":"Assessing the impact of infantile hydrocephalus on visuomotor integration through behavioural and neuroimaging studies","year":2024,"lang":"en","type":"article","venue":"Child Neuropsychology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Academic Medical Organization of Southwestern Ontario","keywords":"Psychology; Hydrocephalus; Precuneus; Neuroimaging; Functional neuroimaging; Neuroscience; Corticospinal tract; Audiology; Diffusion MRI; Functional magnetic resonance imaging; Medicine; Magnetic resonance imaging; Psychiatry","score_opus":0.13953132264676033,"score_gpt":0.4962925954373502,"score_spread":0.3567612727905899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391814809","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867338,0.0008612084,0.0014192001,0.007998328,0.00017283334,0.0003473404,0.0000067896117,0.00020838027,0.002252131],"genre_scores_gemma":[0.99709165,0.0005671648,0.0004907022,0.0016631046,0.0000895258,0.000025241241,0.0000063397833,0.000033719,0.000032556993],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991291,0.00005681939,0.00022026549,0.000354169,0.0000863046,0.00015334324],"domain_scores_gemma":[0.9993428,0.00017229475,0.000067629066,0.00032864208,0.000056930003,0.000031732758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007735961,0.00015564122,0.0002150674,0.00009162717,0.000118355616,0.000040174145,0.000082916355,0.00003155934,0.000007929897],"category_scores_gemma":[0.0001193579,0.000093347306,0.00009832182,0.00025282483,0.00027199704,0.00016342515,0.000049661558,0.00043287157,0.0000038924395],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004191959,0.0014241162,0.081031494,0.0004038981,0.00040845075,0.0008963242,0.006430809,0.00011671646,0.64561594,0.020192025,0.022921665,0.2201394],"study_design_scores_gemma":[0.00063734624,0.0014550386,0.9738042,0.00058190146,0.00018808444,0.0035751883,0.00019876918,0.0029057902,0.010963459,0.0037901166,0.0016653956,0.00023475653],"about_ca_topic_score_codex":0.000011341925,"about_ca_topic_score_gemma":1.9477635e-7,"teacher_disagreement_score":0.8927727,"about_ca_system_score_codex":0.00002001438,"about_ca_system_score_gemma":0.000015067674,"threshold_uncertainty_score":0.38065925},"labels":[],"label_agreement":null},{"id":"W4391838314","doi":"10.3389/fnagi.2024.1301826","title":"Diffusion kurtosis imaging of brain white matter alteration in patients with coronary artery disease based on the TBSS method","year":2024,"lang":"en","type":"article","venue":"Frontiers in Aging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corona radiata (embryology); Internal capsule; Fractional anisotropy; Superior longitudinal fasciculus; Corpus callosum; Diffusion MRI; Medicine; White matter; Optic radiation; Cardiology; Kurtosis; Anatomy; Internal medicine; Radiology; Magnetic resonance imaging","score_opus":0.01713418937310324,"score_gpt":0.2976968954639986,"score_spread":0.28056270609089534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391838314","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3897898,0.000029046008,0.5880761,0.020964101,0.00024168087,0.0006966506,0.00001752657,0.00008359047,0.00010152971],"genre_scores_gemma":[0.9749366,0.0000042532242,0.018169327,0.0067104385,0.000010305454,0.00006166608,0.000009118145,0.000020230389,0.00007806889],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988464,0.00008118139,0.0001907847,0.00042472716,0.000272921,0.00018395303],"domain_scores_gemma":[0.9994255,0.00010064195,0.000048800244,0.00034949664,0.000020829813,0.000054733584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020697145,0.00012066441,0.00013110241,0.0002958781,0.00006272864,0.000038359736,0.00014719852,0.000011258854,0.0000063298057],"category_scores_gemma":[0.000058310543,0.00008282252,0.000032445547,0.0006343912,0.00013043392,0.00016084875,0.00004029158,0.00021775832,8.575805e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000073340445,0.00012376408,0.99270546,0.000040838888,4.5392466e-7,0.0000311877,0.00007705031,0.0010241834,0.0012982208,0.000041692667,0.001904277,0.002679547],"study_design_scores_gemma":[0.00024062359,0.000043809636,0.7178352,0.00036549562,0.000007326297,0.0000020750153,0.000010917799,0.28075173,0.00022094352,0.00021896539,0.00023710876,0.00006581624],"about_ca_topic_score_codex":0.000002947793,"about_ca_topic_score_gemma":2.7425503e-7,"teacher_disagreement_score":0.5851468,"about_ca_system_score_codex":0.000060362167,"about_ca_system_score_gemma":0.00004214469,"threshold_uncertainty_score":0.33774042},"labels":[],"label_agreement":null},{"id":"W4392011062","doi":"10.1016/s2589-7500(23)00250-9","title":"Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation","year":2024,"lang":"en","type":"review","venue":"The Lancet Digital Health","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":108,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"FP7 Euratom; HORIZON EUROPE Excellent Science; H2020 Excellent Science; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Research Resources; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Knut och Alice Wallenbergs Stiftelse; National Cancer Institute; European Research Council; Seventh Framework Programme; Radboud Universiteit; Instituto de Salud Carlos III; Helse Sør-Øst RHF; National Center for Advancing Translational Sciences; Medical Research Council Canada; Medical Research Council; National Institutes of Health; Horizon 2020 Framework Programme; National Institute of Mental Health; Vetenskapsrådet; Norges Forskningsråd; Instituto de Investigación Marqués de Valdecilla; University of British Columbia; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Health and Medical Research Council; Russian Foundation for Basic Research; Bundesministerium für Bildung und Forschung; National Institute on Drug Abuse; Icahn School of Medicine at Mount Sinai","keywords":"Covariate; Normative; Benchmarking; Multivariate statistics; Neuroimaging; Robustness (evolution); Algorithm; Computer science; Artificial intelligence; Machine learning; Statistics; Mathematics; Econometrics; Psychology; Biology","score_opus":0.19398824350393468,"score_gpt":0.43477473142110357,"score_spread":0.2407864879171689,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392011062","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000031641976,0.69313174,0.29957762,0.0044424133,0.000023290888,0.0015229083,0.0008163493,0.00012984425,0.00032418492],"genre_scores_gemma":[0.00074802415,0.97265697,0.024773272,0.00096744235,0.0002375699,0.00012955256,0.00024548953,0.00006606271,0.00017561152],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985751,0.000043320382,0.0004663749,0.00032711038,0.00024325226,0.00034484972],"domain_scores_gemma":[0.99860066,0.0003020767,0.0003975653,0.00056080736,0.00005219957,0.00008671709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004364185,0.00028066323,0.0010569732,0.000066133034,0.00018870672,0.00009496535,0.00021959619,0.00006479644,7.0548964e-7],"category_scores_gemma":[0.00001947968,0.00013428427,0.00012511214,0.00044759514,0.00021254428,0.00013128144,0.00015232488,0.0006523633,0.0000022029449],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010822661,0.000028539154,0.0000024898827,0.008314305,0.000060446644,0.0000022562065,0.0006661797,0.00080682663,3.025153e-8,0.0007727233,0.0014855338,0.98784983],"study_design_scores_gemma":[0.00041020688,0.0003119184,0.0000049541686,0.026240934,0.00040414423,0.0005149963,0.00028257578,0.52555585,0.0000013258259,0.0053929635,0.44048336,0.00039677173],"about_ca_topic_score_codex":0.000014948935,"about_ca_topic_score_gemma":0.0000010768623,"teacher_disagreement_score":0.9874531,"about_ca_system_score_codex":0.00007682278,"about_ca_system_score_gemma":0.00024617676,"threshold_uncertainty_score":0.5475954},"labels":[],"label_agreement":null},{"id":"W4392033560","doi":"10.32920/25266748","title":"Flair MRI Biomarkers of the Normal Appearing Brain Matter are Related to Cognition","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fluid-attenuated inversion recovery; Montreal Cognitive Assessment; Biomarker; Cognition; Diffusion MRI; Correlation; White matter; Medicine; Psychology; Magnetic resonance imaging; Internal medicine; Nuclear medicine; Neuroscience; Audiology; Oncology; Cognitive impairment; Radiology; Chemistry; Mathematics","score_opus":0.034776849628172235,"score_gpt":0.33867864063516634,"score_spread":0.3039017910069941,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392033560","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36620086,0.0002455027,0.035871882,0.39520678,0.0007424052,0.006331404,0.00025404562,0.0018063824,0.19334073],"genre_scores_gemma":[0.9768119,0.000013599276,0.011163567,0.0040233224,0.000041007588,0.00017981413,0.000052661286,0.000056370976,0.0076578013],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990493,0.000018876424,0.00028500252,0.0003587613,0.00015474857,0.00013329499],"domain_scores_gemma":[0.99913996,0.000031367308,0.00010953545,0.00059364556,0.000069140304,0.000056350935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000102237624,0.00015291461,0.00020318723,0.00011685137,0.00003844721,0.0000146416405,0.0001569937,0.00012323685,0.00015828348],"category_scores_gemma":[0.000030600022,0.000108127686,0.00015310915,0.0002458636,0.000058282596,0.000012982805,0.00094071694,0.0005750665,0.00014021741],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000258855,0.00045114482,0.03868118,0.005773199,0.0008889134,0.00008409835,0.00087658194,0.00066726474,0.15969226,0.0076456447,0.7705496,0.014431271],"study_design_scores_gemma":[0.002031042,0.0002695316,0.31168842,0.025532456,0.0021161507,0.0006765675,0.00084752525,0.009138752,0.33580878,0.22236873,0.087429434,0.002092597],"about_ca_topic_score_codex":0.000025663629,"about_ca_topic_score_gemma":0.0000030268525,"teacher_disagreement_score":0.68312013,"about_ca_system_score_codex":0.000040647457,"about_ca_system_score_gemma":0.0000382136,"threshold_uncertainty_score":0.4409319},"labels":[],"label_agreement":null},{"id":"W4392082539","doi":"10.32920/25266655.v1","title":"DTI Metrics Correlation to FLAIR Biomarkers, Cognition, and Neurodegenerative Diseases","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Fluid-attenuated inversion recovery; Diffusion MRI; Correlation; Cognition; Fractional anisotropy; Dementia; Cognitive impairment; Internal medicine; Neuroscience; Medicine; Psychology; Biomarker; Cardiology; Audiology; Radiology; Magnetic resonance imaging; Biology; Disease; Mathematics","score_opus":0.07290672667454942,"score_gpt":0.3706102512596073,"score_spread":0.2977035245850579,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392082539","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0836425,0.0053749844,0.8291988,0.04648873,0.000999139,0.007114498,0.0015102484,0.0037639209,0.021907208],"genre_scores_gemma":[0.9220938,0.0007483409,0.06916831,0.0030953859,0.00026662555,0.00057654444,0.000857678,0.000086316315,0.0031070034],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99884933,0.00002053359,0.00022431141,0.00061112765,0.0001687992,0.00012590109],"domain_scores_gemma":[0.9991443,0.000088004716,0.000057422018,0.0003485314,0.00016661646,0.0001950925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047319514,0.00021035012,0.00023832913,0.00034705817,0.000067304485,0.000059107773,0.000060932183,0.00009626943,0.0000366627],"category_scores_gemma":[0.00017712303,0.00018443035,0.00007361445,0.00044189408,0.000053220705,0.000025071446,0.00054511084,0.0003647418,0.000041012358],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000579552,0.0011130027,0.015238537,0.0034657184,0.00093344785,0.00036496675,0.0006196502,0.00085438037,0.022799712,0.08307411,0.6992557,0.17170122],"study_design_scores_gemma":[0.002576154,0.0013779708,0.08107015,0.0036890982,0.008144649,0.0005101973,0.00031500994,0.13073733,0.050181307,0.5380013,0.17993885,0.003457987],"about_ca_topic_score_codex":0.000011368246,"about_ca_topic_score_gemma":0.0000016765491,"teacher_disagreement_score":0.8384513,"about_ca_system_score_codex":0.00004532941,"about_ca_system_score_gemma":0.00007751694,"threshold_uncertainty_score":0.7520851},"labels":[],"label_agreement":null},{"id":"W4392163870","doi":"10.1007/s00406-024-01760-9","title":"Interactions between overweight/obesity and alcohol dependence impact human brain white matter microstructure: evidence from DTI","year":2024,"lang":"en","type":"article","venue":"European Archives of Psychiatry and Clinical Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Overweight; Fractional anisotropy; White matter; Obesity; Medicine; Diffusion MRI; Internal medicine; Psychology; Endocrinology; Magnetic resonance imaging","score_opus":0.08839282318214507,"score_gpt":0.43811346111972244,"score_spread":0.34972063793757735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392163870","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9802088,0.00036394602,0.010479246,0.007162495,0.00026153587,0.00023815742,0.00010949429,0.00011559209,0.0010607225],"genre_scores_gemma":[0.9867756,0.00035969302,0.010867886,0.0013795069,0.00025872554,0.0000020127209,0.000007306996,0.000025113786,0.00032419836],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998196,0.00020120452,0.0004908413,0.00077060715,0.00014508644,0.00019626357],"domain_scores_gemma":[0.9984661,0.00071412313,0.0001245237,0.00044409008,0.000012924765,0.00023823918],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023677837,0.00018141977,0.00025898797,0.00008919333,0.00019274367,0.00008856339,0.0002657006,0.000023595621,0.000038847367],"category_scores_gemma":[0.00014843977,0.00014331756,0.00015422606,0.00018488534,0.0008391265,0.00025314713,0.00028063657,0.00060200767,0.000010679161],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030108658,0.00007532326,0.95678127,0.00005204463,0.000009508506,0.000016290409,0.00006944251,8.7419346e-7,0.03866299,0.00019646417,0.0009934652,0.0031122428],"study_design_scores_gemma":[0.00017577926,0.00032355112,0.9927351,0.0005816572,0.00006831194,0.000082523366,0.0000078102885,0.0002650696,0.00016259697,0.0041918987,0.0012752119,0.00013050722],"about_ca_topic_score_codex":0.000015751779,"about_ca_topic_score_gemma":0.0000045169054,"teacher_disagreement_score":0.038500395,"about_ca_system_score_codex":0.0000040209966,"about_ca_system_score_gemma":0.00004256383,"threshold_uncertainty_score":0.58443207},"labels":[],"label_agreement":null},{"id":"W4392189336","doi":"10.1101/2024.02.15.580574","title":"A Neural Network Approach to Identify Left-Right Orientation of Anatomical Brain MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Commonwealth Scientific and Industrial Research Organisation; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Orientation (vector space); Artificial intelligence; Temporal lobe; Corpus callosum; Convolutional neural network; Psychology; Planum temporale; Computer science; Lateralization of brain function; Neuroscience; Medicine","score_opus":0.031315591073945714,"score_gpt":0.3199626815194136,"score_spread":0.2886470904454679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392189336","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.90792173,0.00086649094,0.08071821,0.0046034735,0.0009315288,0.0030990182,0.0002528079,0.0014978567,0.00010889378],"genre_scores_gemma":[0.9051844,0.000052103664,0.09288417,0.0008235211,0.00057321065,0.00031090024,0.0000023033651,0.00015114652,0.000018241128],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99729663,0.00006861307,0.00064520753,0.001141303,0.00040177445,0.00044644615],"domain_scores_gemma":[0.9976863,0.00006396385,0.0002612749,0.0013393508,0.000333691,0.0003153926],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037195382,0.0004315754,0.0006414925,0.00031273888,0.00008585689,0.00008807135,0.00037586974,0.00031480467,0.000018488641],"category_scores_gemma":[0.00012409512,0.0004342586,0.00021847534,0.0008282994,0.00011956143,0.00006201725,0.0007055296,0.0010347174,0.000034828427],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019668098,0.0007666586,0.008515853,0.002960301,0.00033355103,0.00014078531,0.00005651994,0.0021975436,0.91398084,0.030577647,0.0402531,0.000020518453],"study_design_scores_gemma":[0.0022579418,0.0004944991,0.28410333,0.0043152915,0.001838312,0.0000018084307,0.0000148184645,0.04980646,0.58175683,0.0010736311,0.07099885,0.0033382226],"about_ca_topic_score_codex":0.000014477991,"about_ca_topic_score_gemma":3.2976718e-7,"teacher_disagreement_score":0.332224,"about_ca_system_score_codex":0.00019768257,"about_ca_system_score_gemma":0.00027695892,"threshold_uncertainty_score":0.99981093},"labels":[],"label_agreement":null},{"id":"W4392291576","doi":"10.1101/2024.02.27.582303","title":"The Douglas Bell Canada Brain Bank Post-mortem Brain Imaging Protocol","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Ex vivo; Magnetic resonance imaging; Fixation (population genetics); Pathology; In vivo; Medicine; Brain tissue; Biomedical engineering; Biology; Radiology","score_opus":0.0194784093903341,"score_gpt":0.2902365284055896,"score_spread":0.2707581190152555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392291576","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14847144,0.0037120094,0.0077905613,0.44878554,0.0058917645,0.3715287,0.0026382967,0.01035096,0.00083067163],"genre_scores_gemma":[0.69261783,0.00009099781,0.02099374,0.0203317,0.0030558363,0.2612804,0.0000039689244,0.0010097367,0.0006158367],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9964513,0.00010308594,0.00074525614,0.0013042768,0.00061539887,0.0007806805],"domain_scores_gemma":[0.99595565,0.0002612265,0.000377562,0.0024258737,0.0005958559,0.0003838387],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006197887,0.0006942555,0.0005676727,0.0001747884,0.00045448425,0.00030303458,0.00074540626,0.00021745038,0.000027489781],"category_scores_gemma":[0.00048825567,0.00057224237,0.00021455769,0.00059353624,0.0002183142,0.00006804367,0.0011440929,0.0019973172,0.000040436924],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019894411,0.00029418987,0.0042403843,0.0031422526,0.00037217347,0.0013928384,0.000017798877,0.000028686363,0.63316387,0.012878693,0.34411994,0.00015024484],"study_design_scores_gemma":[0.00061617524,0.000055967303,0.011285105,0.0011622268,0.0001579712,6.7059403e-7,0.0000050894664,0.0012608673,0.07318957,0.000067936744,0.9113649,0.00083350146],"about_ca_topic_score_codex":0.013513226,"about_ca_topic_score_gemma":0.0020166626,"teacher_disagreement_score":0.567245,"about_ca_system_score_codex":0.00078766124,"about_ca_system_score_gemma":0.0037964429,"threshold_uncertainty_score":0.9996729},"labels":[],"label_agreement":null},{"id":"W4392344604","doi":"10.1101/2024.02.27.582381","title":"MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"Canadian Institutes of Health Research","keywords":"Univariate; Multivariate statistics; Computer science; Toolbox; Artificial intelligence; Python (programming language); Voxel; Mahalanobis distance; Data mining; Pattern recognition (psychology); Machine learning","score_opus":0.041497693143805185,"score_gpt":0.3402944671751039,"score_spread":0.29879677403129873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392344604","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5882978,0.0019365655,0.3844865,0.007933533,0.0015508005,0.0074458965,0.0053242864,0.0029436487,0.00008097027],"genre_scores_gemma":[0.85822946,0.00006526588,0.14031093,0.0005700849,0.00021669689,0.0004915915,0.000007741829,0.000101076854,0.0000071822988],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99772197,0.000035565256,0.00084297534,0.00057757,0.0003568645,0.00046504603],"domain_scores_gemma":[0.99696606,0.00029325602,0.000707372,0.0011630463,0.0007185464,0.00015169017],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00063020276,0.00045435884,0.0008076045,0.00041014882,0.00018365878,0.00020113825,0.00041429006,0.0004123188,0.000003790928],"category_scores_gemma":[0.0005434116,0.00046126425,0.0002724665,0.00086269766,0.00012146506,0.00020417914,0.0006315093,0.0011281706,0.000013480548],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049216556,0.0010017051,0.018831179,0.015664771,0.0009506439,0.000044583874,0.0002603438,0.0010457543,0.86703706,0.033943273,0.0604215,0.00030704238],"study_design_scores_gemma":[0.0025875315,0.0002695887,0.16887921,0.0035046395,0.0009451078,4.2616264e-7,0.00004776525,0.032198835,0.5884061,0.00017840428,0.201208,0.0017743928],"about_ca_topic_score_codex":0.00008589876,"about_ca_topic_score_gemma":0.0000018869986,"teacher_disagreement_score":0.27863094,"about_ca_system_score_codex":0.00021330385,"about_ca_system_score_gemma":0.0002787085,"threshold_uncertainty_score":0.99978393},"labels":[],"label_agreement":null},{"id":"W4392344620","doi":"10.1101/2024.02.22.581646","title":"Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Canadian Institutes of Health Research; Directorate for Biological Sciences; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; National Institute of Mental Health; Pfizer; Novartis Pharmaceuticals Corporation; Medical Research Council; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Eisai; Alzheimer's Association","keywords":"White matter; Diffusion MRI; Diffusion; Medicine; Magnetic resonance imaging; Physics; Radiology; Thermodynamics","score_opus":0.10397147367815911,"score_gpt":0.31931693750610285,"score_spread":0.21534546382794373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392344620","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51274234,0.01677791,0.36234683,0.08794994,0.0014983424,0.007989255,0.00620644,0.004450647,0.000038264076],"genre_scores_gemma":[0.57131916,0.0034163273,0.40861598,0.013112018,0.00097178377,0.0018162758,0.000034202407,0.00047815952,0.00023608742],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99681085,0.00006118452,0.00063811225,0.0015620032,0.0004194832,0.0005083508],"domain_scores_gemma":[0.9969355,0.00022607227,0.00038658027,0.0016189163,0.0005125044,0.00032042112],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00033976306,0.0006166788,0.0007193195,0.00045295255,0.00017595613,0.00015668185,0.00044790035,0.00043811367,0.00005648282],"category_scores_gemma":[0.00026026688,0.00061619835,0.00026585304,0.000681263,0.000115692535,0.000090401845,0.00088530226,0.0013797202,0.00013733964],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012173359,0.00051028334,0.063411914,0.004046094,0.00024416985,0.000092251365,0.000026797214,0.000012065903,0.82286614,0.0006295888,0.1080238,0.000015182713],"study_design_scores_gemma":[0.0026877015,0.00021170745,0.4738439,0.017609527,0.0017464097,4.1226824e-7,0.000006833194,0.015183275,0.12036331,0.0001887108,0.36511168,0.0030465403],"about_ca_topic_score_codex":0.000060761053,"about_ca_topic_score_gemma":0.0000020324276,"teacher_disagreement_score":0.70250285,"about_ca_system_score_codex":0.0002531526,"about_ca_system_score_gemma":0.00031600575,"threshold_uncertainty_score":0.99962896},"labels":[],"label_agreement":null},{"id":"W4392377681","doi":"10.1038/s41467-024-46023-2","title":"Genetic architecture of the structural connectome","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; Krembil Foundation; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation","keywords":"Neuroscience; Connectome; Connectomics; Biology; Genome-wide association study; Diffusion MRI; Genetic architecture; Evolutionary biology; Phenotype; Genetics; Functional connectivity; Magnetic resonance imaging; Gene; Single-nucleotide polymorphism; Medicine","score_opus":0.04277835830423975,"score_gpt":0.38646626693332614,"score_spread":0.3436879086290864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392377681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.59831476,0.09164998,0.012210051,0.2679453,0.0007952635,0.0032110978,0.0003028652,0.001796462,0.023774227],"genre_scores_gemma":[0.9615713,0.00020821704,0.037365247,0.00058107707,0.00003403299,0.000033287797,0.000012082318,0.000014413148,0.00018036553],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995627,0.000027726568,0.00012655111,0.00011178586,0.000097853874,0.0000733997],"domain_scores_gemma":[0.99809444,0.00014479512,0.00003150461,0.001641799,0.000060866318,0.000026600357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003139203,0.00006646872,0.00008769368,0.000050906347,0.000106088606,0.000009947589,0.00051146286,0.000078775236,0.000014358394],"category_scores_gemma":[0.00006807447,0.000041566105,0.00008842569,0.00040373916,0.00018986558,0.000017538763,0.0002041926,0.0008784046,0.0000030554934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028370421,0.00016160478,0.036941413,0.00034603765,0.00018060613,0.000007635002,0.00080131803,0.00010993632,0.12838034,0.7381017,0.020829078,0.07411192],"study_design_scores_gemma":[0.00024153103,0.000052721898,0.28256917,0.00029349592,0.00016808877,0.00044471832,0.000032686847,0.004558921,0.0077312626,0.039388712,0.66433895,0.00017973437],"about_ca_topic_score_codex":0.0000034372347,"about_ca_topic_score_gemma":0.000011391417,"teacher_disagreement_score":0.698713,"about_ca_system_score_codex":0.000020696327,"about_ca_system_score_gemma":0.00005169251,"threshold_uncertainty_score":0.38162798},"labels":[],"label_agreement":null},{"id":"W4392455053","doi":"10.1016/j.media.2024.103134","title":"Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada); Université de Sherbrooke","funders":"Engineering and Physical Sciences Research Council; European Commission; Agencia Estatal de Investigación; Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Diffusion MRI; Protocol (science); Computer science; Artificial intelligence; Relaxation (psychology); Machine learning; Diffusion; Algorithm; Magnetic resonance imaging; Physics; Medicine","score_opus":0.04037254488641366,"score_gpt":0.40363153447511524,"score_spread":0.36325898958870156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392455053","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020844184,0.000046009423,0.969558,0.0064511094,0.000005530361,0.0022251462,0.000012483188,0.00027008384,0.0005874721],"genre_scores_gemma":[0.8543247,0.00012119757,0.14035091,0.00060224213,0.00010219321,0.0027016338,0.00096976064,0.00004501998,0.0007823676],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986051,0.000050071874,0.00033847892,0.00028103808,0.00058979896,0.00013556224],"domain_scores_gemma":[0.99905884,0.000276442,0.00015244911,0.0002280697,0.00017136807,0.000112853304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026201704,0.00012927366,0.00032325048,0.00025106076,0.00007651958,0.000030297155,0.00007720192,0.000059386522,0.0003981941],"category_scores_gemma":[0.0003114541,0.000092837065,0.00016496493,0.0015211819,0.0001583594,0.00020902956,0.00003408288,0.00030118693,0.000013836912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002297287,0.0038434737,0.09944618,0.005070638,0.008277735,0.00077923585,0.008490799,0.009423039,0.34874046,0.041627884,0.011014885,0.46098837],"study_design_scores_gemma":[0.0010149493,0.0007326915,0.008752499,0.00088330527,0.001685109,0.000025472156,0.00018025494,0.9654976,0.015057399,0.0011970657,0.0047352877,0.0002383712],"about_ca_topic_score_codex":0.000045349814,"about_ca_topic_score_gemma":0.000008185161,"teacher_disagreement_score":0.95607454,"about_ca_system_score_codex":0.00005967873,"about_ca_system_score_gemma":0.000116332645,"threshold_uncertainty_score":0.43599463},"labels":[],"label_agreement":null},{"id":"W4392455528","doi":"10.21203/rs.3.rs-3855042/v1","title":"A hierarchical atlas of the human cerebellum for functional precision mapping","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada First Research Excellence Fund","keywords":"Atlas (anatomy); Cerebellum; Computer science; Neuroscience; Cartography; Geography; Biology; Anatomy","score_opus":0.2571819720625176,"score_gpt":0.485651847083358,"score_spread":0.22846987502084043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392455528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7446128,0.0034931186,0.11582634,0.08244637,0.0009941523,0.027068127,0.001609525,0.0011420015,0.022807552],"genre_scores_gemma":[0.9851124,0.000073700445,0.006773086,0.00005066763,0.0005463636,0.0014263956,0.00016924583,0.00006569852,0.00578244],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978995,0.00009963725,0.0003217435,0.0005529084,0.00081909925,0.0003071683],"domain_scores_gemma":[0.99797493,0.00042400628,0.00007098668,0.00093742023,0.00049669365,0.000095965144],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006942077,0.00014798621,0.00026295718,0.00028374742,0.00026042387,0.000034301134,0.00031918156,0.00018286063,0.000052092975],"category_scores_gemma":[0.0003891959,0.0001013477,0.00033489792,0.00039305363,0.00028382058,0.000012245535,0.0019168854,0.0021435313,0.000011199714],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062061223,0.0018593089,0.01440662,0.033868674,0.00045346192,0.000042969295,0.0012755927,0.0004929822,0.26803353,0.2870228,0.33679178,0.055131678],"study_design_scores_gemma":[0.00069655734,0.0004006031,0.041660283,0.008071554,0.00008625184,0.00003757089,0.00012865476,0.0039614337,0.016975867,0.7622785,0.16543235,0.00027035625],"about_ca_topic_score_codex":0.000021910697,"about_ca_topic_score_gemma":0.000002831374,"teacher_disagreement_score":0.47525573,"about_ca_system_score_codex":0.00015435311,"about_ca_system_score_gemma":0.0003579893,"threshold_uncertainty_score":0.93126965},"labels":[],"label_agreement":null},{"id":"W4392462618","doi":"10.1016/j.neuroimage.2024.120555","title":"Associations of quantitative susceptibility mapping with cortical atrophy and brain connectome in Alzheimer's disease: A multi-parametric study","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Connectome; Neuroscience; Superior parietal lobule; Precuneus; Statistical parametric mapping; Inferior parietal lobule; Atrophy; Parahippocampal gyrus; Tractography; Resting state fMRI; Psychology; Diffusion MRI; Medicine; Pathology; Temporal lobe; Functional connectivity; Magnetic resonance imaging; Cognition","score_opus":0.14852974669698024,"score_gpt":0.4140012270818498,"score_spread":0.26547148038486956,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392462618","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98916477,0.00043071547,0.007361571,0.0014802392,0.000016976617,0.0012206433,0.000087431115,0.00018081823,0.000056806723],"genre_scores_gemma":[0.9886639,0.00001852753,0.011039728,0.0001442804,0.000009619301,0.000067202614,0.000013684895,0.00002641548,0.000016612485],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988055,0.00010652739,0.0002873989,0.00045044927,0.00018524108,0.00016488355],"domain_scores_gemma":[0.99874413,0.00072540407,0.00005934504,0.00029414397,0.0000715068,0.0001054485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019842344,0.00013003725,0.000282136,0.0002763088,0.000050260624,0.000025093414,0.00005776206,0.000022596345,0.00000781909],"category_scores_gemma":[0.00062788115,0.00011061691,0.00004530807,0.0010393065,0.00016098276,0.00009754505,0.00005334245,0.0003227456,0.0000031332943],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020274479,0.0020947168,0.9673576,0.00014221543,0.00011419552,0.00060223945,0.0008140706,0.000031524713,0.023339642,0.0033407812,0.00015747795,0.0018028114],"study_design_scores_gemma":[0.0007783898,0.0005837394,0.9886896,0.00007034449,0.00014148053,0.000010871169,0.000187234,0.008975166,0.00013520155,0.00023580687,0.00009043786,0.00010173519],"about_ca_topic_score_codex":0.000045119796,"about_ca_topic_score_gemma":0.00002367005,"teacher_disagreement_score":0.02320444,"about_ca_system_score_codex":0.000032752043,"about_ca_system_score_gemma":0.000064173415,"threshold_uncertainty_score":0.45108265},"labels":[],"label_agreement":null},{"id":"W4392592471","doi":"10.21037/qims-23-1397","title":"Knowledge atlas of white matter microstructure: a bibliometric analysis","year":2024,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Tongji University; National Natural Science Foundation of China","keywords":"White matter; Atlas (anatomy); White paper; Computer science; Data science; Medicine; Geography; Magnetic resonance imaging; Archaeology; Radiology","score_opus":0.09699502246704417,"score_gpt":0.42028256994744,"score_spread":0.32328754748039584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392592471","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8884862,0.04069642,0.051935054,0.015918454,0.000163145,0.00033241618,0.000023096882,0.00016477102,0.0022804379],"genre_scores_gemma":[0.9910951,0.0012950475,0.0066538043,0.00060462055,0.00004316931,0.00001985771,0.000035787274,0.000022815866,0.00022974925],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988351,0.000046677018,0.00043496134,0.0003462365,0.00015010886,0.00018691424],"domain_scores_gemma":[0.9985114,0.0010103049,0.00007132676,0.00021163744,0.00012274215,0.00007260142],"candidate_categories":["bibliometrics"],"consensus_categories":["bibliometrics"],"category_scores_codex":[0.00047495504,0.00014869562,0.0005722065,0.03974151,0.000043690867,0.000013012703,0.00004771384,0.000028135699,0.00013210262],"category_scores_gemma":[0.00021348493,0.00011262626,0.00012739404,0.05968265,0.00032570816,0.00011103095,0.000043938562,0.00020348218,0.0000079341135],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023206925,0.00003786267,0.9675794,0.00034814284,0.000091591486,0.00007540799,0.000923398,0.0000022605448,0.004322909,0.0008481043,0.019759856,0.005987822],"study_design_scores_gemma":[0.00020270313,0.00004110419,0.97784007,0.00080735254,0.00046508943,0.00008231032,0.00030661726,0.004179616,0.000404569,0.0015665788,0.013958978,0.00014498853],"about_ca_topic_score_codex":0.00005978431,"about_ca_topic_score_gemma":0.0000036982715,"teacher_disagreement_score":0.10260894,"about_ca_system_score_codex":0.000022444241,"about_ca_system_score_gemma":0.000047829843,"threshold_uncertainty_score":0.9711422},"labels":[],"label_agreement":null},{"id":"W4392637325","doi":"10.1038/s41598-024-56453-z","title":"Investigating female versus male differences in white matter neuroplasticity associated with complex visuo-motor learning","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia Hospital; University of British Columbia; Simon Fraser University","funders":"CIHR Skin Research Training Centre; University of British Columbia Graduate School; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Simon Fraser University; Michael Smith Health Research BC; University of British Columbia; Government of Canada","keywords":"Neuroplasticity; White matter; Corpus callosum; Brain Structure and Function; Psychology; Fractional anisotropy; Corticospinal tract; Motor learning; Myelin; Medicine; Physiology; Magnetic resonance imaging; Neuroscience; Neuroimaging; Diffusion MRI; Central nervous system","score_opus":0.09555926935103116,"score_gpt":0.33556858165550957,"score_spread":0.24000931230447842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392637325","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9945814,0.000019788016,0.0011703129,0.0005018949,0.00055791077,0.00031952557,0.000002533477,0.0003185916,0.0025280395],"genre_scores_gemma":[0.99144554,0.0000010892684,0.0023628636,0.000064152184,0.000030874555,0.000045099325,0.00005122397,0.000024955865,0.0059742057],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984375,0.000038199578,0.00030554846,0.00064514636,0.00031995613,0.0002536387],"domain_scores_gemma":[0.9992916,0.000116437055,0.00011806519,0.00030482325,0.000070356225,0.00009874485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031824212,0.00013130347,0.00019344474,0.00017314647,0.0001932847,0.00020505209,0.00005902344,0.00003326309,0.00021274509],"category_scores_gemma":[0.0002721573,0.00010481954,0.000040767383,0.00072546664,0.00026715465,0.000114304756,0.00005961506,0.00033379457,0.000025394304],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010569487,0.000050244304,0.9774451,0.000053076943,0.000009401787,0.00070888497,0.00015570727,0.000056757504,0.019378817,0.000031369214,0.0019067692,0.00019326742],"study_design_scores_gemma":[0.00030391596,0.00019317563,0.97569364,0.0007733609,0.000058786914,0.00055442605,0.00010460211,0.01386326,0.0015011559,0.000522164,0.006182665,0.0002488404],"about_ca_topic_score_codex":0.000008724312,"about_ca_topic_score_gemma":0.000012501569,"teacher_disagreement_score":0.01787766,"about_ca_system_score_codex":0.00005969075,"about_ca_system_score_gemma":0.00008465824,"threshold_uncertainty_score":0.4274417},"labels":[],"label_agreement":null},{"id":"W4392697010","doi":"10.1371/journal.pone.0300139","title":"White matter microstructure in transmasculine and cisgender adolescents: A multiparametric and multivariate study","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Douglas Mental Health University Institute; Centre for Addiction and Mental Health; University of Toronto","funders":"University of Toronto; Canadian Institutes of Health Research; Department of Psychiatry, University of Toronto; Centre for Addiction and Mental Health Foundation","keywords":"Fractional anisotropy; Diffusion MRI; Transgender; White matter; Psychology; Multivariate analysis; Multivariate statistics; Medicine; Internal medicine; Magnetic resonance imaging","score_opus":0.07905843093316198,"score_gpt":0.3259788032646483,"score_spread":0.2469203723314863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392697010","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99521065,0.00081225514,0.0013366664,0.0014258522,0.000008192067,0.0010343293,0.000015576885,0.00012415196,0.000032334916],"genre_scores_gemma":[0.98443645,0.00015129508,0.014723021,0.00038407216,0.00002922067,0.000069099115,0.0000056600247,0.000027144604,0.00017406077],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999252,0.000016850057,0.0001562597,0.00033600058,0.00010952852,0.00012932972],"domain_scores_gemma":[0.99970436,0.000023010947,0.0000147378505,0.00017461822,0.000022022345,0.00006123759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005521831,0.00011488576,0.00020615318,0.00018971499,0.000025559044,0.000027336291,0.000032657026,0.00003889764,0.00002084927],"category_scores_gemma":[0.000015438702,0.00009577648,0.000017558958,0.0003299904,0.000035357512,0.000054106073,0.000033780765,0.00025956533,0.0000063107173],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061268736,0.0019081624,0.9678455,0.0005160056,0.00006627998,0.00005523763,0.0009906181,0.000001371496,0.026911454,0.000011373847,0.000046669295,0.0015860805],"study_design_scores_gemma":[0.0013163537,0.00012963978,0.9937998,0.0004270777,0.00012427033,0.000026519783,0.00010420662,0.0029365811,0.0007498955,0.00018351885,0.00008236036,0.000119742705],"about_ca_topic_score_codex":0.000013455578,"about_ca_topic_score_gemma":0.0000047400335,"teacher_disagreement_score":0.026161557,"about_ca_system_score_codex":0.000017046792,"about_ca_system_score_gemma":0.0000073647843,"threshold_uncertainty_score":0.39056516},"labels":[],"label_agreement":null},{"id":"W4392765341","doi":"10.1016/j.neurobiolaging.2024.02.014","title":"Brain age of rhesus macaques over the lifespan","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institute on Aging; Mitacs; Canadian Institutes of Health Research; National Institutes of Health; Liverpool University Hospitals NHS Foundation Trust; Brain and Behavior Research Foundation","keywords":"Macaque; Neuroimaging; Human brain; Neuroscience; Rhesus macaque; Cortex (anatomy); Brain morphometry; Primate; Psychology; Magnetic resonance imaging; Biology; Medicine","score_opus":0.05033033103707092,"score_gpt":0.36869562510107934,"score_spread":0.31836529406400843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392765341","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9757775,0.00046146062,0.0021048957,0.019018998,0.00011717571,0.00027003288,0.000015203178,0.00024209658,0.001992639],"genre_scores_gemma":[0.996592,0.00010760156,0.0013069562,0.001620119,0.000057097623,0.00001050593,0.000010413091,0.000015300333,0.00028000926],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994832,0.000031895615,0.00016840687,0.00016883462,0.00004123691,0.00010640617],"domain_scores_gemma":[0.9993897,0.00027192544,0.000045275276,0.0002551343,0.000018861101,0.00001910433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008377681,0.00007115358,0.0001524504,0.00006720845,0.000026562318,0.0000033929389,0.00009973849,0.000031753036,0.00002087623],"category_scores_gemma":[0.000038838458,0.000047346653,0.00006951981,0.00014450512,0.00022203634,0.000020656018,0.00005545778,0.00019176454,0.0000025958743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029908228,0.000079875324,0.015059327,0.00033908998,0.000061424544,0.00006993191,0.00043916854,0.000014859377,0.9334687,0.026896464,0.014505337,0.009035887],"study_design_scores_gemma":[0.0006986079,0.0007619186,0.25214484,0.0008000271,0.00022986156,0.00043651217,0.000085322645,0.00082779,0.42665616,0.013867498,0.30319336,0.00029809095],"about_ca_topic_score_codex":0.000012335199,"about_ca_topic_score_gemma":8.623882e-7,"teacher_disagreement_score":0.5068126,"about_ca_system_score_codex":0.00000571322,"about_ca_system_score_gemma":0.000019489962,"threshold_uncertainty_score":0.19307405},"labels":[],"label_agreement":null},{"id":"W4392774425","doi":"10.1177/08830738241231343","title":"Structural Alterations of the Corpus Callosum in Children With Infantile Hydrocephalus","year":2024,"lang":"en","type":"article","venue":"Journal of Child Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Academic Medical Organization of Southwestern Ontario","keywords":"Corpus callosum; Diffusion MRI; Hydrocephalus; Magnetic resonance imaging; Psychology; Medicine; Neuroscience; Radiology; Psychiatry","score_opus":0.014382791236022189,"score_gpt":0.2956051249925846,"score_spread":0.2812223337565624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392774425","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9557331,0.0002246671,0.00024203307,0.043242235,0.00008338895,0.00018564363,0.000006082406,0.000017046808,0.00026580083],"genre_scores_gemma":[0.9960466,0.00006548114,0.00021060595,0.0035299808,0.000110025605,0.0000027736587,0.0000013095174,0.000013212659,0.000020013242],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993676,0.000029326937,0.00028277215,0.00010229175,0.000121155135,0.00009686434],"domain_scores_gemma":[0.999581,0.000040172497,0.0001355516,0.00016496769,0.000044361997,0.00003395508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005073482,0.000074247335,0.00018075111,0.00012787158,0.000033430722,0.000006814157,0.00012110862,0.000033758417,0.000013395935],"category_scores_gemma":[0.00002735557,0.000042326963,0.000070509996,0.00024068003,0.00010262779,0.00006285929,0.000029389836,0.00053892797,4.7247872e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045180533,0.0001840453,0.96963364,0.00005433641,0.00012669647,0.00022170485,0.00020133829,0.0021934537,0.009669525,0.007528187,0.0033509836,0.006384309],"study_design_scores_gemma":[0.00085173,0.0008938422,0.95544994,0.00012398891,0.000105445826,0.023747725,0.0000011699179,0.0014160429,0.0064686104,0.0020265193,0.008843508,0.00007148383],"about_ca_topic_score_codex":0.000004700015,"about_ca_topic_score_gemma":0.0000050185504,"teacher_disagreement_score":0.040313493,"about_ca_system_score_codex":0.000008040463,"about_ca_system_score_gemma":0.00006298308,"threshold_uncertainty_score":0.2341404},"labels":[],"label_agreement":null},{"id":"W4392922065","doi":"10.1002/nbm.5142","title":"ComBating inter‐site differences in field strength: harmonizing preclinical traumatic brain injury MRI data","year":2024,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vancouver Island University","funders":"National Institute of Neurological Disorders and Stroke; National Health and Medical Research Council","keywords":"Traumatic brain injury; Medicine; Corpus callosum; Magnetic resonance imaging; Nuclear medicine; Neuroimaging; Effective diffusion coefficient; Diffusion MRI; Radiology; Pathology","score_opus":0.3168383269899163,"score_gpt":0.4728099251554381,"score_spread":0.1559715981655218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392922065","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75266993,0.0018663008,0.027963938,0.21441196,0.0003510223,0.0011560016,0.00011456671,0.00062855944,0.00083769194],"genre_scores_gemma":[0.9844963,0.00034139352,0.011968834,0.0024754757,0.00019458705,0.00005047188,0.00018617196,0.000024927325,0.00026183712],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983409,0.000050256895,0.0006286898,0.000534324,0.00019674952,0.00024906275],"domain_scores_gemma":[0.9980748,0.0010734069,0.000060669852,0.00066794734,0.000016677763,0.00010645394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005713756,0.00016311448,0.00038112377,0.00037935423,0.00002717577,0.000025654372,0.0003091329,0.00009315959,0.00010266608],"category_scores_gemma":[0.0008649203,0.00012810306,0.000033949786,0.0007545973,0.00008552485,0.00012801857,0.00022349795,0.00067508337,0.000015245256],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019840656,0.0008964424,0.16738403,0.0015618565,0.00006108613,0.0004904714,0.002517055,9.0136433e-7,0.019918036,0.0010260284,0.065743595,0.74020207],"study_design_scores_gemma":[0.008942679,0.005552176,0.17436136,0.049724124,0.00043854426,0.0004890164,0.002568958,0.4994067,0.008659157,0.015316937,0.23256956,0.0019707966],"about_ca_topic_score_codex":0.00016103189,"about_ca_topic_score_gemma":0.000082002436,"teacher_disagreement_score":0.7382313,"about_ca_system_score_codex":0.00008763076,"about_ca_system_score_gemma":0.00005848541,"threshold_uncertainty_score":0.5223891},"labels":[],"label_agreement":null},{"id":"W4393097549","doi":"10.1101/2024.03.20.24304650","title":"Dissociation of white matter bundles in different recovery measures in post-stroke aphasia","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Canadian Institutes of Health Research; Eisai; Heart and Stroke Foundation of Canada","keywords":"Aphasia; White matter; Psychology; Dissociation (chemistry); Stroke (engine); Physical medicine and rehabilitation; Cognitive psychology; Medicine; Physics; Chemistry; Radiology","score_opus":0.042691644698238385,"score_gpt":0.328216887312799,"score_spread":0.28552524261456064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393097549","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9901978,0.00041462827,0.00078560965,0.0064822617,0.00013492565,0.0006647201,0.00014274812,0.00009289836,0.0010844478],"genre_scores_gemma":[0.9968767,0.00027751824,0.0011887569,0.0002065698,0.00007172899,0.00023472268,0.00008679885,0.000043901226,0.0010133144],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986457,0.00004945586,0.0004743777,0.00042195985,0.00023200647,0.00017645877],"domain_scores_gemma":[0.9992269,0.00005555153,0.00015985299,0.00045338846,0.00006241403,0.00004188149],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017359974,0.00021238717,0.00046248527,0.0003966535,0.000016011001,0.000012755945,0.000140783,0.00016099252,0.000038427883],"category_scores_gemma":[0.00007567459,0.00018013103,0.00015420467,0.00014813324,0.000040290546,0.000023141964,0.000386977,0.0007656187,0.000012610318],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005950446,0.00025451274,0.974209,0.0005234072,0.000028899787,0.000031950487,0.00035253493,0.000041723335,0.02201653,0.000090314286,0.000254776,0.0021368235],"study_design_scores_gemma":[0.00024600705,0.000049188275,0.9796763,0.0010495675,0.000068184374,0.0000094168245,0.00003133803,0.00016777046,0.0058004335,0.012368972,0.00036617197,0.00016665166],"about_ca_topic_score_codex":0.00006544393,"about_ca_topic_score_gemma":0.00009532785,"teacher_disagreement_score":0.016216097,"about_ca_system_score_codex":0.00015869264,"about_ca_system_score_gemma":0.000054655415,"threshold_uncertainty_score":0.734553},"labels":[],"label_agreement":null},{"id":"W4393111973","doi":"10.1002/hbm.26665","title":"Structural brain networks correlating with poststroke cognition","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Health and Medical Research Council; Medical Research Council; Commonwealth Scientific and Industrial Research Organisation; Orionin Tutkimussäätiö; Signe ja Ane Gyllenbergin Säätiö; University of Queensland; Suomen Kulttuurirahasto","keywords":"Cognition; Connectome; Psychology; Montreal Cognitive Assessment; Diffusion MRI; Stroke (engine); White matter; Cognitive decline; Tractography; Neuroimaging; Neuroscience; Magnetic resonance imaging; Physical medicine and rehabilitation; Medicine; Dementia; Pathology; Disease; Radiology; Cognitive impairment; Functional connectivity","score_opus":0.06775704452473501,"score_gpt":0.34491150193225734,"score_spread":0.2771544574075223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393111973","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44680563,0.0004906698,0.5185683,0.019116329,0.00013033515,0.0011507603,0.000013872044,0.0024717443,0.011252409],"genre_scores_gemma":[0.9881698,0.000002899641,0.0077293706,0.002417449,0.00030287993,0.0000441877,0.0001296714,0.000045697278,0.0011580636],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912274,0.000020224958,0.00018337765,0.00031786,0.00012912789,0.00022666261],"domain_scores_gemma":[0.99947554,0.00016329902,0.000047428322,0.0002022968,0.000041974676,0.000069488255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011243249,0.00014093795,0.00014533498,0.00011228887,0.0002657877,0.00007079371,0.00005851786,0.00004872318,0.00007160371],"category_scores_gemma":[0.00004030766,0.00012122147,0.00005282359,0.00025853756,0.000079059886,0.00010951612,0.000034983135,0.00039617193,0.000010555814],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001310292,0.00009677595,0.018442819,0.0010599701,0.0003238941,0.0009993938,0.0024976558,0.0022468104,0.6406133,0.17126277,0.08477871,0.07754687],"study_design_scores_gemma":[0.0035690316,0.0012614295,0.2613217,0.009314868,0.00040177317,0.0039963624,0.0012777416,0.5233129,0.0011034872,0.038976997,0.15356654,0.0018971579],"about_ca_topic_score_codex":0.0000045000656,"about_ca_topic_score_gemma":0.0000026195203,"teacher_disagreement_score":0.6395098,"about_ca_system_score_codex":0.00004255145,"about_ca_system_score_gemma":0.000020735122,"threshold_uncertainty_score":0.4943268},"labels":[],"label_agreement":null},{"id":"W4393119485","doi":"10.1002/hbm.26654","title":"White adipose tissue distribution and amount are associated with increased white matter connectivity","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft","keywords":"White matter; Adipose tissue; Connectome; Orbitofrontal cortex; White adipose tissue; Prefrontal cortex; Anterior cingulate cortex; Insula; Psychology; Neuroscience; Nucleus accumbens; Medicine; Endocrinology; Magnetic resonance imaging; Cognition; Central nervous system; Functional connectivity; Radiology","score_opus":0.03683830063534014,"score_gpt":0.3110238852919262,"score_spread":0.27418558465658605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393119485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92576647,0.00012857124,0.059875198,0.011631667,0.000018338762,0.0006157812,0.00011495442,0.0007256326,0.0011233719],"genre_scores_gemma":[0.9968641,0.0000030554547,0.0005279063,0.0011802758,0.00006393408,0.00007145698,0.0003093,0.00003136738,0.00094862096],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991664,0.00004083434,0.0001419839,0.00034596564,0.00011709569,0.00018766483],"domain_scores_gemma":[0.9994881,0.00009248713,0.000064528,0.00021980137,0.000053419517,0.00008164594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017420451,0.00014150873,0.0001911487,0.00007189167,0.00020227158,0.000073403535,0.0000424755,0.000052322965,0.00008332957],"category_scores_gemma":[0.00005998983,0.00012506127,0.000026729631,0.00023437933,0.00009071627,0.00010378898,0.000041406587,0.00023830369,0.000014519902],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004192343,0.00021377868,0.84352887,0.0005584863,0.00015062313,0.00029784127,0.000722603,0.000008709187,0.074206695,0.0057834364,0.07333515,0.0011519036],"study_design_scores_gemma":[0.00034611995,0.00006999364,0.9759371,0.000852544,0.00005567632,0.00007243862,0.000053205073,0.00053237757,0.00020284251,0.001348071,0.02036552,0.00016406606],"about_ca_topic_score_codex":0.000016060083,"about_ca_topic_score_gemma":0.000021555627,"teacher_disagreement_score":0.13240829,"about_ca_system_score_codex":0.000106695006,"about_ca_system_score_gemma":0.000017150152,"threshold_uncertainty_score":0.509985},"labels":[],"label_agreement":null},{"id":"W4393255309","doi":"10.1016/j.xcrp.2024.101892","title":"Quantifying synergy and redundancy between networks","year":2024,"lang":"en","type":"article","venue":"Cell Reports Physical Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Max-Planck-Institut für Mathematik in den Naturwissenschaften; Gates Cambridge Trust; Max-Planck-Gesellschaft; Universiteit van Amsterdam; German-Israeli Foundation for Scientific Research and Development; Tel Aviv University; University of Kent; McGill University; Bill and Melinda Gates Foundation","keywords":"Computer science; Range (aeronautics); Redundancy (engineering); Complex network; Key (lock); Network topology; Distributed computing; Data science; Theoretical computer science; Topology (electrical circuits); Computer network; Mathematics; Engineering; Computer security","score_opus":0.0735377796238917,"score_gpt":0.3862345241926942,"score_spread":0.31269674456880253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393255309","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9380439,0.00038731875,0.048079345,0.0005600313,0.000114640134,0.00022377982,6.847127e-7,0.00046480075,0.012125527],"genre_scores_gemma":[0.997355,0.000040210878,0.0019418908,0.000055741377,0.00022049458,0.000013253161,0.0000021707672,0.0000114469685,0.00035983504],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989811,0.0000035996156,0.00013584622,0.00046822912,0.00020393608,0.00020725014],"domain_scores_gemma":[0.99942946,0.000055290082,0.000037807073,0.0002894822,0.000033225395,0.00015472293],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015003492,0.00007980566,0.00012712943,0.00004768992,0.00015092538,0.00007352913,0.000060145005,0.00001710929,0.000002638702],"category_scores_gemma":[0.000033681845,0.00006207806,0.00003627427,0.00057377125,0.00039632356,0.00014247501,0.00009038769,0.00017177782,0.0000028134866],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000070013834,0.00021291657,0.026059058,0.00029679842,0.000013210294,0.0016703845,0.00040322,0.00020131578,0.67665344,0.05911495,0.0018400482,0.23352763],"study_design_scores_gemma":[0.0002681929,0.00056542363,0.10432694,0.0011850918,0.00034619085,0.0020906893,0.00008874171,0.18714435,0.38850677,0.06620047,0.24812767,0.0011494611],"about_ca_topic_score_codex":0.000010615289,"about_ca_topic_score_gemma":9.666712e-8,"teacher_disagreement_score":0.28814667,"about_ca_system_score_codex":0.000027286158,"about_ca_system_score_gemma":0.00007020626,"threshold_uncertainty_score":0.253147},"labels":[],"label_agreement":null},{"id":"W4393270801","doi":"10.1002/hbm.26635","title":"The superior frontal sulcus in the human brain: Morphology and probability maps","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research","keywords":"Sulcus; Central sulcus; Precentral gyrus; Brain morphometry; Neuroimaging; Inferior frontal gyrus; Human brain; Middle frontal gyrus; Frontal lobe; Neuroscience; Anatomy; Brain mapping; Superior temporal sulcus; Magnetic resonance imaging; Psychology; Biology; Medicine; Functional magnetic resonance imaging; Radiology","score_opus":0.08155849015715583,"score_gpt":0.35504833923048357,"score_spread":0.27348984907332774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393270801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91683006,0.0005687086,0.0012474798,0.07711483,0.00003545581,0.0010851162,0.000008813373,0.000274718,0.0028348016],"genre_scores_gemma":[0.9950383,0.0000141133105,0.0007857262,0.002962694,0.000136039,0.00022904827,0.000024254157,0.000023080951,0.00078674796],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989133,0.0001022485,0.00024657088,0.00036722075,0.00011794765,0.0002527502],"domain_scores_gemma":[0.99906474,0.0003905958,0.000028374992,0.00045961034,0.000017939445,0.000038714803],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006909474,0.00013165793,0.00015781929,0.00006890977,0.00050669047,0.000091350725,0.00018514908,0.000050284663,0.000023105491],"category_scores_gemma":[0.0001115882,0.000082381535,0.000055321256,0.00018168881,0.00034695028,0.000058624548,0.0000955559,0.0004359553,0.000007038742],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017849958,0.00014869301,0.015028879,0.0003190108,0.00003242411,0.00028427623,0.0050852466,0.0000021436754,0.49993014,0.40365443,0.06891182,0.006585093],"study_design_scores_gemma":[0.00058902067,0.00016227657,0.34548053,0.00024027516,0.000022675118,0.0005412741,0.0010716565,0.0002217669,0.00017212308,0.22745754,0.4238003,0.00024058536],"about_ca_topic_score_codex":0.000039576702,"about_ca_topic_score_gemma":0.000055248962,"teacher_disagreement_score":0.499758,"about_ca_system_score_codex":0.0000535918,"about_ca_system_score_gemma":0.000022067217,"threshold_uncertainty_score":0.38971046},"labels":[],"label_agreement":null},{"id":"W4393276331","doi":"10.3389/fnimg.2024.1359589","title":"Down-sampling in diffusion MRI: a bundle-specific DTI and NODDI study","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Nuclear medicine; Magnetic resonance imaging; Sampling (signal processing); Medicine; Nuclear magnetic resonance; Physics; Radiology; Optics","score_opus":0.06528717279994371,"score_gpt":0.3495831204202306,"score_spread":0.28429594762028687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393276331","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8602237,0.004370225,0.12779,0.0038555572,0.0006050471,0.0014656767,0.0000066941343,0.00054023723,0.0011428155],"genre_scores_gemma":[0.9647851,0.0010443267,0.033448108,0.00032184416,0.00007067871,0.000097445874,0.0000068432932,0.00006142912,0.00016424654],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984294,0.00004177825,0.00033609453,0.0006947514,0.00017963933,0.00031831994],"domain_scores_gemma":[0.9994163,0.00007441061,0.00003300412,0.00037747715,0.000017561102,0.00008128076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020126153,0.00019862459,0.0003022589,0.0005870928,0.000072768446,0.000098906494,0.000111515736,0.00003487534,0.0000061594646],"category_scores_gemma":[0.000034342593,0.00019492596,0.000043870892,0.000702014,0.000080837744,0.00019226002,0.0001414495,0.00059615023,0.0000036738575],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121971374,0.00093630265,0.8756901,0.00022810005,0.000015825379,0.0012147917,0.0020550424,0.00013959946,0.013384644,0.00064427976,0.0065613594,0.099007994],"study_design_scores_gemma":[0.003734146,0.00046403724,0.671652,0.001585709,0.00009486744,0.00053027744,0.0025191638,0.1455208,0.00047735847,0.010622447,0.16189826,0.00090088364],"about_ca_topic_score_codex":0.000029037898,"about_ca_topic_score_gemma":0.0000038706307,"teacher_disagreement_score":0.20403805,"about_ca_system_score_codex":0.00010028897,"about_ca_system_score_gemma":0.000023972445,"threshold_uncertainty_score":0.794885},"labels":[],"label_agreement":null},{"id":"W4393388452","doi":"10.1007/s11682-024-00876-9","title":"Sleep disturbances, altered brain microstructure and chronic headache in youth","year":2024,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Alberta Bone and Joint Health Institute; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Fractional anisotropy; Actigraphy; Medicine; Cingulum (brain); White matter; Diffusion MRI; Chronic pain; Pittsburgh Sleep Quality Index; Physical therapy; Psychology; Audiology; Internal medicine; Insomnia; Psychiatry; Magnetic resonance imaging; Radiology; Sleep quality","score_opus":0.03210649844894815,"score_gpt":0.33879631179786107,"score_spread":0.30668981334891293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393388452","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95669174,0.013816456,0.0017638535,0.026471602,0.00010471072,0.0005763195,0.00010257423,0.00036495767,0.00010778949],"genre_scores_gemma":[0.9956949,0.00012069114,0.0023856687,0.0010702865,0.00014427843,0.00006414324,0.000067302484,0.000032643744,0.0004201269],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99911416,0.000016132995,0.00016374991,0.00041578984,0.00007749382,0.00021270664],"domain_scores_gemma":[0.9996353,0.000045871417,0.000022167515,0.00020083743,0.0000124922635,0.00008334137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000089626505,0.0001505267,0.00016931936,0.000105314764,0.00006570714,0.00007722165,0.000049047787,0.000035981513,0.0000071688614],"category_scores_gemma":[0.00002225502,0.00012966029,0.00003354653,0.00017466949,0.00012935072,0.00009168472,0.000053512238,0.00030063762,0.0000012969205],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003477268,0.00016229003,0.10839315,0.00043652262,0.000012779158,0.00033519935,0.001517614,0.0000011813668,0.31757513,0.0007578186,0.0112029165,0.5595706],"study_design_scores_gemma":[0.003943777,0.00034751548,0.84303206,0.0022221936,0.0005888482,0.0037241485,0.0010095364,0.006682767,0.016769107,0.0027639098,0.1176364,0.0012797415],"about_ca_topic_score_codex":0.00005752805,"about_ca_topic_score_gemma":0.000013096618,"teacher_disagreement_score":0.7346389,"about_ca_system_score_codex":0.00005367566,"about_ca_system_score_gemma":0.000028649836,"threshold_uncertainty_score":0.52873933},"labels":[],"label_agreement":null},{"id":"W4393507590","doi":"10.5281/zenodo.7608831","title":"Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – The Vogt-Vogt legacy in the 21st century","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Neuroimaging; Neuroscience; Psychology","score_opus":0.17712244695351662,"score_gpt":0.3626593921002978,"score_spread":0.18553694514678118,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393507590","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00014823583,0.00032966078,0.0020600038,0.019203514,0.00018197902,0.0046627815,0.96762955,0.001064237,0.004720033],"genre_scores_gemma":[0.0061595635,0.0010975624,0.0002008331,0.0011498567,0.00034989993,0.000001748864,0.98996985,0.00097202533,0.00009865579],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99730843,0.00048708363,0.00047260657,0.00079084,0.0005050707,0.00043597588],"domain_scores_gemma":[0.9966149,0.00035194436,0.00021349765,0.0024794436,0.00023137714,0.000108879045],"candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0013610228,0.00025305818,0.00027719483,0.00026171783,0.0017034726,0.0006293583,0.0025755332,0.00009131251,0.00024116231],"category_scores_gemma":[0.0017489167,0.00018614114,0.000083562605,0.0008203368,0.0003432833,0.00020567479,0.0020157245,0.00123587,0.0014315096],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008232934,0.00012803182,0.000001240982,0.00014793093,0.000020475814,0.000029496596,0.000089474794,0.000006717579,0.00015588108,0.00057897257,0.98674846,0.012010989],"study_design_scores_gemma":[0.0005250232,0.00015867787,0.0004533173,0.000107194646,0.00006557432,0.00019236306,0.00036489885,0.0008299863,0.000007478322,0.00018642581,0.9969351,0.00017390755],"about_ca_topic_score_codex":0.00006967461,"about_ca_topic_score_gemma":0.0000018028193,"teacher_disagreement_score":0.0223403,"about_ca_system_score_codex":0.00009153313,"about_ca_system_score_gemma":0.000025478726,"threshold_uncertainty_score":0.9995962},"labels":[],"label_agreement":null},{"id":"W4393598281","doi":"10.5281/zenodo.10458910","title":"White matter multi-scale dataset: Diffusion weighted MRI and synchrotron x-ray scans of vervet monkey-, healthy mouse-, and cuprizone mouse brains","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Synchrotron; Diffusion MRI; Diffusion; Nuclear magnetic resonance; Nuclear medicine; Anatomy; Biology; Magnetic resonance imaging; Physics; Medicine; Optics; Radiology","score_opus":0.04484241246136825,"score_gpt":0.316662184498596,"score_spread":0.27181977203722774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393598281","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036787705,0.00024323704,0.0023928504,0.0026292403,0.000030575004,0.0012223789,0.98917246,0.00045445742,0.00017604524],"genre_scores_gemma":[0.0009035595,0.0028359338,0.0029947706,0.00059942156,0.00008913128,6.2326535e-7,0.99079907,0.0011155442,0.00066192896],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794924,0.00014701819,0.0004273509,0.000785012,0.00034777704,0.0003436288],"domain_scores_gemma":[0.9982577,0.000024417835,0.00019389763,0.0010301153,0.00020523141,0.00028865735],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024361776,0.00029947137,0.00040802566,0.00039843237,0.00067736045,0.0002303888,0.00047933613,0.00015233281,0.0019675547],"category_scores_gemma":[0.00006980887,0.00028756628,0.000048590362,0.0003752447,0.00034023696,0.0001460399,0.0016688211,0.00067493675,0.0016846101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012638555,0.00029060815,0.000021617689,0.0010077152,0.0000357572,0.000016451228,0.000094322044,0.000001953157,0.0040509007,0.000016624199,0.9930126,0.0013250787],"study_design_scores_gemma":[0.0008464941,0.00041025414,0.00047906954,0.0002104028,0.00010987303,0.0001510798,0.00004786364,0.0005956082,0.00021855216,0.00001548202,0.9966813,0.0002340216],"about_ca_topic_score_codex":0.000068705376,"about_ca_topic_score_gemma":0.0000027084088,"teacher_disagreement_score":0.0038323484,"about_ca_system_score_codex":0.00010160846,"about_ca_system_score_gemma":0.000008805773,"threshold_uncertainty_score":0.9999576},"labels":[],"label_agreement":null},{"id":"W4393610770","doi":"10.5281/zenodo.10458911","title":"White matter multi-scale dataset: Diffusion weighted MRI and synchrotron x-ray scans of vervet monkey-, healthy mouse-, and cuprizone mouse brains","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Synchrotron; Diffusion MRI; Anatomy; Biology; Nuclear medicine; Magnetic resonance imaging; Physics; Medicine; Optics; Radiology","score_opus":0.04484241246136825,"score_gpt":0.316662184498596,"score_spread":0.27181977203722774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393610770","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036787705,0.00024323704,0.0023928504,0.0026292403,0.000030575004,0.0012223789,0.98917246,0.00045445742,0.00017604524],"genre_scores_gemma":[0.0009035595,0.0028359338,0.0029947706,0.00059942156,0.00008913128,6.2326535e-7,0.99079907,0.0011155442,0.00066192896],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794924,0.00014701819,0.0004273509,0.000785012,0.00034777704,0.0003436288],"domain_scores_gemma":[0.9982577,0.000024417835,0.00019389763,0.0010301153,0.00020523141,0.00028865735],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00024361776,0.00029947137,0.00040802566,0.00039843237,0.00067736045,0.0002303888,0.00047933613,0.00015233281,0.0019675547],"category_scores_gemma":[0.00006980887,0.00028756628,0.000048590362,0.0003752447,0.00034023696,0.0001460399,0.0016688211,0.00067493675,0.0016846101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012638555,0.00029060815,0.000021617689,0.0010077152,0.0000357572,0.000016451228,0.000094322044,0.000001953157,0.0040509007,0.000016624199,0.9930126,0.0013250787],"study_design_scores_gemma":[0.0008464941,0.00041025414,0.00047906954,0.0002104028,0.00010987303,0.0001510798,0.00004786364,0.0005956082,0.00021855216,0.00001548202,0.9966813,0.0002340216],"about_ca_topic_score_codex":0.000068705376,"about_ca_topic_score_gemma":0.0000027084088,"teacher_disagreement_score":0.0038323484,"about_ca_system_score_codex":0.00010160846,"about_ca_system_score_gemma":0.000008805773,"threshold_uncertainty_score":0.9999576},"labels":[],"label_agreement":null},{"id":"W4393711011","doi":"10.5281/zenodo.8339143","title":"Painting a more complete picture of white matter microstructure with myelin water and tensor valued diffusion","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Anisotropy; Myelin; Microstructure; Fractional anisotropy; Painting; Materials science; Mineralogy; Chemistry; Physics; Psychology; White matter; Composite material; Art; Optics; Neuroscience; Art history; Medicine; Central nervous system","score_opus":0.04305434030819109,"score_gpt":0.28672485766181505,"score_spread":0.24367051735362397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393711011","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012019387,0.000032555534,0.0023484195,0.004317382,0.000042456417,0.0017209849,0.97818756,0.00091266254,0.00041859905],"genre_scores_gemma":[0.0022991605,0.00009330438,0.0017274914,0.0006501418,0.00010955732,2.0398912e-7,0.9933743,0.0011625472,0.0005832764],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985698,0.00008968894,0.00026947362,0.00049073284,0.00029096717,0.00028936815],"domain_scores_gemma":[0.99868834,0.000014338797,0.00014697757,0.0006550457,0.00037793227,0.000117376265],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00017780342,0.00022625116,0.0003139364,0.00023720403,0.00096324965,0.00011996066,0.00038653534,0.00011723615,0.0016877431],"category_scores_gemma":[0.00008715529,0.00016107701,0.000046820067,0.00026713326,0.00025170174,0.000050282924,0.0013151537,0.0005437907,0.0009893425],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009813306,0.000043385986,0.000022877957,0.00050526456,0.00003316279,0.000034484176,0.00025129452,0.0000052163527,0.0105741015,0.000007478867,0.987589,0.0008355863],"study_design_scores_gemma":[0.0005087029,0.00018643492,0.0019949945,0.00026479558,0.00008621683,0.00046500095,0.000102913546,0.000071880146,0.00030357364,0.00003753297,0.9957989,0.00017908205],"about_ca_topic_score_codex":0.0000143109,"about_ca_topic_score_gemma":2.002304e-7,"teacher_disagreement_score":0.015186764,"about_ca_system_score_codex":0.000039843057,"about_ca_system_score_gemma":0.0000025631089,"threshold_uncertainty_score":0.9997885},"labels":[],"label_agreement":null},{"id":"W4393905672","doi":"10.59275/j.melba.2024-267f","title":"Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Mesh Variational Autoencoder with Contrastive Learning","year":2024,"lang":"en","type":"preprint","venue":"The Journal of Machine Learning for Biomedical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Canadian Institutes of Health Research; Women and Children's Health Research Institute; Canada Research Chairs; Children's Health Research Institute","keywords":"Autoencoder; Hippocampal formation; Neuroscience; Psychology; Graph; Artificial intelligence; Pattern recognition (psychology); Medicine; Computer science; Deep learning; Theoretical computer science","score_opus":0.03634657959718149,"score_gpt":0.3565907821513885,"score_spread":0.32024420255420705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393905672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29964045,0.00073712977,0.6908331,0.0069732955,0.00025680897,0.0013403934,0.00002688823,0.00015380498,0.00003811158],"genre_scores_gemma":[0.9544595,0.00009595575,0.044718154,0.00015062146,0.0003845046,0.000036671074,0.0000493931,0.000082346945,0.000022856446],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971056,0.00038249049,0.0009996537,0.00038648746,0.00080042356,0.00032532646],"domain_scores_gemma":[0.9967642,0.0011692977,0.0012697615,0.00023716058,0.0003945318,0.00016506978],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0015113096,0.00035704943,0.00075010676,0.00040438276,0.00033044338,0.000058794332,0.00035651255,0.000106025545,0.00003248669],"category_scores_gemma":[0.0010828619,0.00022121058,0.00025815258,0.00040149284,0.00032033536,0.00007217776,0.00047986954,0.0035897198,5.617638e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007967994,0.0065814494,0.3193867,0.0018935715,0.0038132155,0.00043751847,0.011802328,0.55255973,0.0038363927,0.0022347374,0.00030233606,0.089184046],"study_design_scores_gemma":[0.001969551,0.0017679501,0.0044382634,0.00068369514,0.0019197667,0.000526752,0.000569636,0.98062545,0.000007673991,0.0068234485,0.00046384239,0.00020394799],"about_ca_topic_score_codex":0.000039409897,"about_ca_topic_score_gemma":0.0000019451907,"teacher_disagreement_score":0.6548191,"about_ca_system_score_codex":0.00009609218,"about_ca_system_score_gemma":0.00033031567,"threshold_uncertainty_score":0.998709},"labels":[],"label_agreement":null},{"id":"W4393991482","doi":"10.1093/schbul/sbae037","title":"Distinct Volume Alterations of Thalamic Nuclei Across the Schizophrenia Spectrum","year":2024,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McGill University","keywords":"Schizophrenia (object-oriented programming); Psychosis; Thalamus; Cognition; Neuroscience; Psychology; Schizophrenia spectrum; Brain size; Effects of sleep deprivation on cognitive performance; Magnetic resonance imaging; Medicine; Psychiatry; Radiology","score_opus":0.02594945853949701,"score_gpt":0.31769348464525154,"score_spread":0.29174402610575456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393991482","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8349895,0.002165534,0.023138382,0.13057163,0.0005384541,0.0016599157,0.00042692013,0.0016793401,0.0048303367],"genre_scores_gemma":[0.9830178,0.00009283953,0.012898722,0.000311722,0.00041934542,0.00012385772,0.000057077104,0.00007222893,0.003006385],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983794,0.000043037297,0.00046749398,0.00047889553,0.00027418943,0.00035696043],"domain_scores_gemma":[0.99877167,0.00013182842,0.00010000319,0.00083288125,0.00006259303,0.00010100096],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024644588,0.00023912173,0.00029134628,0.00008062333,0.0002943583,0.000100894766,0.00029435827,0.00007289181,0.00067356444],"category_scores_gemma":[0.000097033844,0.00017004967,0.00021677386,0.00046657844,0.00032739868,0.000049223643,0.0001529978,0.0005523753,0.00058951136],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003063009,0.0013195206,0.008811089,0.0013076403,0.00061820704,0.00050221727,0.0018877928,0.00013519358,0.08321379,0.38563344,0.38342324,0.13008487],"study_design_scores_gemma":[0.0016363886,0.00034594728,0.049039133,0.0006349014,0.00025959956,0.00064859836,0.00010075409,0.004388475,0.010978854,0.019907648,0.91152406,0.0005356536],"about_ca_topic_score_codex":0.000040914198,"about_ca_topic_score_gemma":0.000013896113,"teacher_disagreement_score":0.5281008,"about_ca_system_score_codex":0.00004764873,"about_ca_system_score_gemma":0.0000945068,"threshold_uncertainty_score":0.75771725},"labels":[],"label_agreement":null},{"id":"W4394120694","doi":"10.6084/m9.figshare.7603271","title":"White Matter Tractography Guides","year":2019,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tractography; White matter; White (mutation); Psychology; Geology; Medicine; Biology; Radiology; Magnetic resonance imaging","score_opus":0.1394907963545433,"score_gpt":0.3862822743998692,"score_spread":0.24679147804532586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394120694","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[2.6025074e-7,0.000112698894,0.0000027324793,0.00055456546,0.00002679308,0.00057358685,0.99721557,0.00011481118,0.0013989718],"genre_scores_gemma":[0.0000035737025,0.000025067011,0.0006671276,0.003913134,0.00017682694,0.00042737703,0.9935239,0.00003868643,0.001224301],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990796,0.000007660101,0.00019253325,0.00036463904,0.00016393326,0.00019163777],"domain_scores_gemma":[0.99865615,0.00003877494,0.00013971321,0.0010050858,0.00007967417,0.00008059842],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000011157117,0.00022120585,0.00028261443,0.00014769261,0.000034845798,0.000026831303,0.00023802451,0.00018535793,0.36204565],"category_scores_gemma":[0.000069416994,0.00019688308,0.00017284746,0.0001674446,0.0000066912403,0.000043775428,0.00010492082,0.0004628717,0.022396771],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038707008,0.000038344082,0.00011603786,0.0005106939,0.000011079967,0.0000188961,8.472198e-7,2.6717566e-7,0.000002171738,1.31628e-7,0.9992231,0.00007456823],"study_design_scores_gemma":[0.00010715687,0.000029356663,0.0044958876,0.0019128994,0.00004720427,0.000060105154,8.3481547e-7,0.0000015581724,0.000021524535,0.000015384203,0.9931206,0.00018745966],"about_ca_topic_score_codex":0.0000022756574,"about_ca_topic_score_gemma":4.7111655e-7,"teacher_disagreement_score":0.33964887,"about_ca_system_score_codex":0.000017505514,"about_ca_system_score_gemma":0.00003949372,"threshold_uncertainty_score":0.9783644},"labels":[],"label_agreement":null},{"id":"W4394264727","doi":"10.6084/m9.figshare.12649388","title":"Multimodal adolescent white matter imaging dataset","year":2020,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Psychology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.08870218789884723,"score_gpt":0.3644682305331559,"score_spread":0.2757660426343087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394264727","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[3.2973276e-8,0.00006846918,0.000012111273,0.002751369,0.000026500584,0.0006828905,0.99620974,0.00017714994,0.00007175387],"genre_scores_gemma":[0.0000047364065,0.00001664322,0.0009552008,0.017538879,0.0003896396,0.0004019297,0.9805754,0.000055270575,0.00006231989],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986035,0.000015506464,0.0002608343,0.0006111954,0.00023268764,0.00027622882],"domain_scores_gemma":[0.9984711,0.000025123456,0.00016681821,0.0010619431,0.000061009836,0.00021402523],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0000122742185,0.00032198554,0.00034459095,0.00008436691,0.000070038564,0.000047866164,0.0003694105,0.00010608342,0.14337958],"category_scores_gemma":[0.00014613516,0.00031007145,0.000106562315,0.00014223598,0.000011883425,0.000069487076,0.00043502328,0.0008038053,0.03268851],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011840081,0.00006720819,0.000059091257,0.00083103136,0.000008648033,0.00019532518,0.000001444203,5.6254447e-7,0.0000057914176,5.3534535e-8,0.9985763,0.00024270483],"study_design_scores_gemma":[0.0002378533,0.00001573727,0.0011055238,0.0024118384,0.00006682657,0.00011365372,0.0000017036664,0.000074470925,0.0000326475,0.000003310031,0.9956586,0.00027785663],"about_ca_topic_score_codex":0.0000054420148,"about_ca_topic_score_gemma":8.918256e-7,"teacher_disagreement_score":0.11069108,"about_ca_system_score_codex":0.000054521726,"about_ca_system_score_gemma":0.000070154994,"threshold_uncertainty_score":0.99993515},"labels":[],"label_agreement":null},{"id":"W4394550046","doi":"10.6084/m9.figshare.1216667","title":"CST Mask in ICBM152 space","year":2014,"lang":"en","type":"dataset","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Space (punctuation); Computer science; Computer graphics (images); Operating system","score_opus":0.1273186298284547,"score_gpt":0.39074171810531044,"score_spread":0.26342308827685573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394550046","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[4.230349e-7,0.00008895285,0.000004455098,0.0007820105,0.000016484515,0.00045341186,0.9979752,0.000120792996,0.0005583124],"genre_scores_gemma":[0.000013239412,0.000037695107,0.0004964242,0.0011290492,0.0002104656,0.0005171614,0.9970722,0.000029691171,0.0004940726],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991291,0.000013242779,0.0001721959,0.0003452248,0.00014285819,0.00019736655],"domain_scores_gemma":[0.99890685,0.000057414327,0.00010789925,0.0008077772,0.000036330275,0.00008371021],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000021339587,0.00018926995,0.0002879874,0.00012852893,0.000025848374,0.000014155627,0.0002110589,0.00018079646,0.04704191],"category_scores_gemma":[0.00048330272,0.00018152934,0.00006786751,0.00017687218,0.0000053237095,0.000025109794,0.00013631921,0.0005679679,0.0041337847],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000041046137,0.00003639592,0.0000027846786,0.00034121994,0.0000024495723,0.000052217314,0.0000011157762,6.9004795e-7,0.000005489107,0.0000025002698,0.9992488,0.00030220166],"study_design_scores_gemma":[0.00017098343,0.00003489322,0.0001557058,0.0027296403,0.000014085917,0.00003633666,0.0000013232959,0.000014546512,0.00006269116,0.00005186222,0.9965678,0.00016013885],"about_ca_topic_score_codex":0.000016601436,"about_ca_topic_score_gemma":0.000015659378,"teacher_disagreement_score":0.04290813,"about_ca_system_score_codex":0.00005072532,"about_ca_system_score_gemma":0.000055448876,"threshold_uncertainty_score":0.99664164},"labels":[],"label_agreement":null},{"id":"W4394683503","doi":"10.7554/elife.94917","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"National Institute of Mental Health; HORIZON EUROPE Framework Programme; McDonnell Center for Systems Neuroscience; Lundbeckfonden; National Institutes of Health; European Synchrotron Radiation Facility; Deutsches Elektronen-Synchrotron; European Commission; Scleroseforeningen","keywords":"White matter; Corpus callosum; Diffusion MRI; Biology; Voxel; Anatomy; Fractional anisotropy; Tractography; Neuroscience; Evolutionary biology; Magnetic resonance imaging; Medicine; Computer science; Artificial intelligence","score_opus":0.052240007719115585,"score_gpt":0.33678857049714667,"score_spread":0.2845485627780311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394683503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96362466,0.00038530477,0.027929213,0.007308341,0.000031403644,0.00015794362,0.000026945174,0.00013626229,0.00039995756],"genre_scores_gemma":[0.99580556,0.00014391614,0.0030373111,0.0006571654,0.00013608158,0.000009315617,0.0000075512394,0.000015526695,0.0001875771],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99944305,0.000009395381,0.00013888572,0.00015722025,0.00014379874,0.000107674874],"domain_scores_gemma":[0.9996688,0.00007587269,0.000023672595,0.00016938642,0.000025607249,0.000036677244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010601751,0.00006452881,0.00010641214,0.00005115251,0.00009488811,0.000018453475,0.00004868564,0.00002663979,0.000042880347],"category_scores_gemma":[0.000039579314,0.00004298006,0.000029834111,0.0002449248,0.0001284439,0.000045754245,0.00008814561,0.00014441244,0.00001823243],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005638204,0.00019364632,0.7955094,0.00042486817,0.000070687754,0.000048468053,0.0037567255,0.000014463743,0.098373964,0.013661282,0.033701204,0.054188922],"study_design_scores_gemma":[0.00023557663,0.00006022916,0.90611386,0.0001142602,0.00004484513,0.00016221582,0.00023487587,0.0060791015,0.037297852,0.0005921824,0.0489285,0.00013650878],"about_ca_topic_score_codex":0.0000023175346,"about_ca_topic_score_gemma":4.5851235e-7,"teacher_disagreement_score":0.110604465,"about_ca_system_score_codex":0.000019633088,"about_ca_system_score_gemma":0.000012452403,"threshold_uncertainty_score":0.1752676},"labels":[],"label_agreement":null},{"id":"W4394691933","doi":"10.7554/elife.94917.1","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bridging (networking); White matter; Geography; Geology; Evolutionary biology; Biology; Computer science; Medicine","score_opus":0.06363895321397584,"score_gpt":0.34557660972726695,"score_spread":0.2819376565132911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394691933","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97496086,0.0006751979,0.013188216,0.009660463,0.000096172116,0.0004620486,0.00015725532,0.00019359945,0.00060619717],"genre_scores_gemma":[0.9924813,0.00038193417,0.0057196557,0.0007386738,0.00030459883,0.00003858241,0.000042957807,0.000039664883,0.00025263493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998885,0.000019842795,0.00029486176,0.00037018364,0.00026345908,0.0001666891],"domain_scores_gemma":[0.9992241,0.00007956504,0.00010863779,0.00046231406,0.00006464509,0.000060697508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017846361,0.00016536022,0.00029063414,0.0001009887,0.000111398054,0.00003237038,0.00013109483,0.00011286057,0.000040636525],"category_scores_gemma":[0.00007159838,0.000116670504,0.000080416175,0.0002057368,0.00022079062,0.000018979297,0.0011528889,0.00069310126,0.00002410403],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001684445,0.0005804308,0.8232928,0.0037006733,0.00036142327,0.00010845745,0.008097711,0.00016500858,0.037789945,0.01137324,0.06659934,0.04776252],"study_design_scores_gemma":[0.00047175994,0.00008245328,0.9276981,0.0007312925,0.0002686017,0.00021630658,0.00037378122,0.0078121475,0.030513527,0.007690477,0.02363685,0.00050472765],"about_ca_topic_score_codex":0.0000074230034,"about_ca_topic_score_gemma":0.0000010608339,"teacher_disagreement_score":0.10440527,"about_ca_system_score_codex":0.000050868348,"about_ca_system_score_gemma":0.000040201227,"threshold_uncertainty_score":0.4757685},"labels":[],"label_agreement":null},{"id":"W4394750715","doi":"10.1002/alz.13776","title":"Structural white matter properties and cognitive resilience to tau pathology","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research; Alzheimer's Society; Fondation Brain Canada; McGill University; National Institutes of Health; Alzheimer's Association","keywords":"White matter; Hyperintensity; Cognition; Psychology; Diffusion MRI; Default mode network; Psychological resilience; Effects of sleep deprivation on cognitive performance; Neuroscience; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.06274017266133386,"score_gpt":0.33435124625811335,"score_spread":0.2716110735967795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394750715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9268247,0.048544444,0.006445692,0.014841401,0.00015438824,0.0011338636,0.000032939293,0.0004148758,0.0016076842],"genre_scores_gemma":[0.9906382,0.000029751329,0.0071239616,0.0019197952,0.000042666437,0.00010395054,0.00001004263,0.000019303494,0.00011232603],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993362,0.000012430817,0.0001168874,0.00030389667,0.0000742659,0.00015633329],"domain_scores_gemma":[0.99972516,0.000013461434,0.000014237163,0.00014173752,0.00003756615,0.00006783362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000036162568,0.000097576936,0.000099988385,0.000059733717,0.00006424591,0.00003194738,0.00004651627,0.000024221412,0.00012914062],"category_scores_gemma":[0.000007398361,0.000075999844,0.000021760901,0.000112356814,0.00009586929,0.00008007876,0.000084286774,0.00010416031,0.00013948062],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000363185,0.00013148258,0.2763681,0.00019605955,0.005084419,0.00073972344,0.00426151,0.000010174313,0.22694394,0.0041272524,0.07457454,0.4071996],"study_design_scores_gemma":[0.00090280565,0.0008489574,0.7170186,0.00079939014,0.021059427,0.0019557946,0.0004949075,0.0013522902,0.19817458,0.003253308,0.053128213,0.0010116965],"about_ca_topic_score_codex":0.000005383869,"about_ca_topic_score_gemma":0.0000015567988,"teacher_disagreement_score":0.4406505,"about_ca_system_score_codex":0.0000017814854,"about_ca_system_score_gemma":0.000014936423,"threshold_uncertainty_score":0.30991837},"labels":[],"label_agreement":null},{"id":"W4395025790","doi":"10.1162/imag_a_00166","title":"Thalamic nuclei segmentation from T1-weighted MRI: Unifying and benchmarking state-of-the-art methods","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Universität Zürich; Eisai; Eidgenössische Technische Hochschule Zürich; Northern California Institute for Research and Education; F. Hoffmann-La Roche; University of Southern California; Pfizer; BioClinica; Biogen; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; National Institute on Aging; Alzheimer's Association","keywords":"Thalamus; Neuroscience; Neuroimaging; Segmentation; Cognition; Human Connectome Project; Brain morphometry; Artificial intelligence; Psychology; Medicine; Magnetic resonance imaging; Computer science; Radiology; Functional connectivity","score_opus":0.04700027216139852,"score_gpt":0.39394381173466353,"score_spread":0.346943539573265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395025790","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3328929,0.0005161094,0.66043687,0.0043024994,0.0005179289,0.00044994347,0.000017455583,0.00036396508,0.00050232303],"genre_scores_gemma":[0.831817,0.0001587765,0.16688022,0.0009104768,0.000031336087,0.00001740771,0.0000037789318,0.000023633682,0.00015743202],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9989651,0.00005520497,0.00019075307,0.00043137558,0.00018761952,0.00016996119],"domain_scores_gemma":[0.9993902,0.00016320994,0.00006649514,0.0002970622,0.000030707866,0.000052369778],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018446973,0.000110118985,0.000119762386,0.00009549667,0.00014951035,0.00008072188,0.00014731182,0.000010738804,0.000005876192],"category_scores_gemma":[0.00005703459,0.00008585428,0.00004346957,0.00055520347,0.0002650432,0.00023027991,0.00013258356,0.000204976,0.0000015761377],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000031349578,0.000015427322,0.011851913,0.000028457043,0.0000015176308,0.000013097876,0.0001463308,0.000015884747,0.8787856,0.00027325464,0.00023907053,0.108626306],"study_design_scores_gemma":[0.0002909117,0.00005901602,0.12024679,0.0006058101,0.00009695086,0.00024397775,0.00003798704,0.36751688,0.46864352,0.015144812,0.026841775,0.00027158775],"about_ca_topic_score_codex":0.000021415894,"about_ca_topic_score_gemma":6.084789e-7,"teacher_disagreement_score":0.49892405,"about_ca_system_score_codex":0.00003072388,"about_ca_system_score_gemma":0.000044698707,"threshold_uncertainty_score":0.3501036},"labels":[],"label_agreement":null},{"id":"W4395479506","doi":"10.21203/rs.3.rs-4260180/v1","title":"White Matter Microstructural Lateralization and Links to Language Function in Perinatal Stroke","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; University of Oxford","keywords":"Arcuate fasciculus; Lateralization of brain function; White matter; Uncinate fasciculus; Psychology; Diffusion MRI; Verbal fluency test; Inferior longitudinal fasciculus; Fasciculus; Fluency; Fractional anisotropy; Stroke (engine); Neuroscience; Audiology; Medicine; Magnetic resonance imaging; Neuropsychology; Cognition; Radiology; Physics","score_opus":0.05516237733175905,"score_gpt":0.4333716100701113,"score_spread":0.3782092327383523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395479506","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98824584,0.00047199216,0.0006756887,0.0082631055,0.00006954508,0.0012711947,0.00018014571,0.00013906519,0.0006834405],"genre_scores_gemma":[0.99231535,0.00007017273,0.002485942,0.00028389154,0.00014832047,0.00026088068,0.00024385126,0.000044886692,0.004146686],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99876684,0.000048865717,0.00016784924,0.00048797517,0.000268706,0.0002597414],"domain_scores_gemma":[0.9993637,0.000024030607,0.000019323697,0.00037077453,0.00011690831,0.00010523179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018325074,0.0001374958,0.00017311717,0.00047226032,0.000051088235,0.000106775304,0.00008302457,0.00020439853,0.00011973603],"category_scores_gemma":[0.000030337822,0.00012412347,0.00004154198,0.0002576924,0.00005200347,0.000030923493,0.00083650445,0.0017625939,0.00007504243],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000791686,0.000153362,0.83895063,0.012461321,0.00007169693,0.0006295585,0.0071284445,0.0002908606,0.08526253,0.0017980275,0.022412766,0.030049128],"study_design_scores_gemma":[0.000459286,0.00029930074,0.9749732,0.0023529483,0.000029217772,0.00010363773,0.00043370473,0.0016619693,0.003344606,0.0050764633,0.010946268,0.00031941463],"about_ca_topic_score_codex":0.00010488941,"about_ca_topic_score_gemma":0.00002318707,"teacher_disagreement_score":0.13602257,"about_ca_system_score_codex":0.00013512163,"about_ca_system_score_gemma":0.00005102386,"threshold_uncertainty_score":0.7657691},"labels":[],"label_agreement":null},{"id":"W4396589421","doi":"10.1101/2024.04.29.591421","title":"Body size interacts with the structure of the central nervous system: A multi-center in vivo neuroimaging study","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Mila - Quebec Artificial Intelligence Institute; CARE Canada; Montreal Neurological Institute and Hospital; International Collaboration On Repair Discoveries; University of British Columbia; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Université de Montréal; Polytechnique Montréal","funders":"Instituto de Salud Carlos III; Agència de Gestió d'Ajuts Universitaris i de Recerca; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; European Commission; Ministerstvo Zdravotnictví Ceské Republiky; Center for Neurobehavioral Development; Courtois Foundation; National Natural Science Foundation of China; Agentura Pro Zdravotnický Výzkum České Republiky; University College London Hospitals NHS Foundation Trust; National Imaging Facility; Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona; National Institute for Health and Care Research; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; University of Queensland; American Heart Association; SpinalCure Australia; University of Pennsylvania; Craig H. Neilsen Foundation; Deutsche Forschungsgemeinschaft; International Collaboration on Repair Discoveries; Bristol-Myers Squibb; Max-Planck-Gesellschaft; University of Minnesota","keywords":"Precentral gyrus; White matter; Fractional anisotropy; Diffusion MRI; Brain size; Anatomy; Neuroimaging; Magnetic resonance imaging; Grey matter; Neuroscience; Psychology; Nuclear medicine; Nuclear magnetic resonance; Medicine; Physics; Radiology","score_opus":0.019208700150429265,"score_gpt":0.27132429731497737,"score_spread":0.2521155971645481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396589421","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938219,0.00016690262,0.00037986677,0.0014820965,0.00044057268,0.0031186824,0.00021414283,0.00036935258,0.000006446561],"genre_scores_gemma":[0.9968761,0.000013496961,0.002332519,0.0003144388,0.00015668945,0.00015343913,1.03083785e-7,0.00014474787,0.000008418488],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99767077,0.0001472933,0.00050737703,0.00085055083,0.00038803366,0.00043599197],"domain_scores_gemma":[0.99737436,0.00008676632,0.00037004284,0.0018260926,0.00022714493,0.000115614144],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016459695,0.00047765792,0.0005569723,0.00013637295,0.0001036874,0.00010445586,0.0006461312,0.00012648858,0.0000067130445],"category_scores_gemma":[0.000101644386,0.0002812784,0.00014196453,0.0006570251,0.00015818063,0.00005217267,0.00093135086,0.0016606487,0.0000019660824],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000122066405,0.0009750459,0.08967201,0.0016820687,0.00019602715,0.0003247253,0.00016549835,0.00013304644,0.9059744,0.00031342608,0.00043888175,0.0000028396578],"study_design_scores_gemma":[0.0023231204,0.00017562,0.7607202,0.004561727,0.0006923904,0.0000018228767,0.00011615822,0.0029560153,0.22634953,0.0000034630193,0.00144384,0.0006560948],"about_ca_topic_score_codex":0.000111252724,"about_ca_topic_score_gemma":0.000013572839,"teacher_disagreement_score":0.67962486,"about_ca_system_score_codex":0.00025618193,"about_ca_system_score_gemma":0.00031380018,"threshold_uncertainty_score":0.99996394},"labels":[],"label_agreement":null},{"id":"W4396605090","doi":"10.1093/brain/awae141","title":"Connectome reorganization associated with temporal lobe pathology and its surgical resection","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; Institute for Basic Science; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; Hospital for Sick Children; National Research Foundation of Korea; National Natural Science Foundation of China; Canada Research Chairs; Institute for Information and Communications Technology Promotion; Canadian Open Neuroscience Platform; China Postdoctoral Science Foundation; Inha University; National Research Foundation; Canadian Institutes of Health Research; National Science Foundation","keywords":"Connectome; Temporal lobe; Neuroscience; Tractography; Psychology; Diffusion MRI; Electrocorticography; Neuroimaging; Epilepsy surgery; Medicine; Epilepsy; Magnetic resonance imaging; Radiology; Functional connectivity","score_opus":0.04241734601448008,"score_gpt":0.3426464226229718,"score_spread":0.30022907660849174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396605090","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97545105,0.00031868895,0.005382073,0.016665261,0.000034136854,0.00034028248,0.000013014827,0.00068078307,0.0011147114],"genre_scores_gemma":[0.99734765,0.0000342941,0.0004337417,0.0002864733,0.000054995653,0.000018443245,0.000077050885,0.000020305022,0.0017270292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995504,0.000027755927,0.00008048103,0.00019045196,0.00006585751,0.00008504335],"domain_scores_gemma":[0.9997153,0.000102356404,0.00001938041,0.00007845527,0.0000455698,0.000038904906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011268373,0.00005729981,0.000088440946,0.000058987036,0.000042259002,0.000013732344,0.00001705303,0.00004863667,0.000026205482],"category_scores_gemma":[0.00015837149,0.000045508146,0.00001086066,0.00030352047,0.00003133652,0.000047454887,0.00001527923,0.000121038094,0.000006567225],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010999603,0.00092725566,0.08407302,0.0007610358,0.00026623716,0.013402317,0.0014507821,0.000028968821,0.3634127,0.4320732,0.07825499,0.024249496],"study_design_scores_gemma":[0.009559332,0.006297992,0.20868824,0.0024592832,0.00046330443,0.026235832,0.0002424612,0.03418878,0.08618312,0.03312319,0.5909601,0.001598373],"about_ca_topic_score_codex":0.0000019499666,"about_ca_topic_score_gemma":0.0000036620581,"teacher_disagreement_score":0.5127051,"about_ca_system_score_codex":0.0000272698,"about_ca_system_score_gemma":0.000023485332,"threshold_uncertainty_score":0.18557684},"labels":[],"label_agreement":null},{"id":"W4396729524","doi":"10.1007/s11682-024-00889-4","title":"Structural network disruption of corticothalamic pathways in cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"Brain Imaging and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Beijing Municipal Administration of Hospitals; National Natural Science Foundation of China","keywords":"Neuropsychology; Cognition; Disease; Neuroradiology; Cognitive impairment; Neurology; Effects of sleep deprivation on cognitive performance; Hippocampal formation; Neuroscience; Medicine; Internal medicine; Psychology","score_opus":0.050815154299471116,"score_gpt":0.33461832293080485,"score_spread":0.2838031686313337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396729524","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99563986,0.00083356915,0.0012264034,0.0016827404,0.00008207694,0.00029899811,0.00002466567,0.00017307299,0.000038594873],"genre_scores_gemma":[0.99661785,0.00003837382,0.0028773036,0.00016157316,0.000077582234,0.000064912056,0.00004080186,0.000021953441,0.000099675795],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999316,0.000013833701,0.0001865656,0.00024644623,0.00007228989,0.00016488759],"domain_scores_gemma":[0.9996574,0.000042283897,0.000029584617,0.00017234607,0.00001756253,0.000080827456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058975635,0.000099777746,0.0001324217,0.000059901227,0.000035787478,0.000024267127,0.00003976375,0.000015533014,0.0000081515755],"category_scores_gemma":[0.000020520523,0.00008843532,0.000044476394,0.00017032256,0.00008846584,0.000066887194,0.000035582976,0.0001488475,0.0000010475937],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003613859,0.00010590954,0.80447674,0.00025947765,0.000004144805,0.00025872962,0.00013806544,0.000017552038,0.041810248,0.0031292906,0.00050535315,0.14925838],"study_design_scores_gemma":[0.00027011815,0.00002379043,0.98810613,0.00037943956,0.000099666766,0.00009877395,0.000024398976,0.007839078,0.0005157853,0.0021523135,0.0003832833,0.00010723173],"about_ca_topic_score_codex":0.000022003947,"about_ca_topic_score_gemma":0.000002203748,"teacher_disagreement_score":0.18362941,"about_ca_system_score_codex":0.00002252231,"about_ca_system_score_gemma":0.00003278993,"threshold_uncertainty_score":0.36062878},"labels":[],"label_agreement":null},{"id":"W4396809662","doi":"10.1101/2024.05.08.593260","title":"Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Anisotropy; White matter; Magnetic resonance elastography; Isotropy; Fractional anisotropy; Diffusion MRI; Materials science; Elastography; Nuclear magnetic resonance; Composite material; Magnetic resonance imaging; Physics; Medicine; Optics; Ultrasound","score_opus":0.031360464034686994,"score_gpt":0.272409400664368,"score_spread":0.24104893662968097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396809662","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98582155,0.0009177666,0.009454746,0.001718318,0.0002619264,0.0011767474,0.000048948456,0.0005824969,0.000017530068],"genre_scores_gemma":[0.971437,0.00016008409,0.027344108,0.0003638431,0.00014655032,0.00038443762,3.1129963e-7,0.0001565001,0.000007162808],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99760884,0.0000605347,0.0006756402,0.00091348775,0.00032773893,0.00041375146],"domain_scores_gemma":[0.99815965,0.000023636894,0.0002710964,0.0011427671,0.00024035954,0.0001624841],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022756208,0.00044734174,0.0007079381,0.0005788931,0.00006689181,0.00005328619,0.00031247202,0.0003224957,0.000030205389],"category_scores_gemma":[0.000042361986,0.00042696405,0.00021597907,0.0007578475,0.00012221913,0.00007977621,0.0006506035,0.0012975007,0.000030724077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029870042,0.0002757106,0.02468822,0.0016910419,0.00006214484,0.00006760264,0.000012499731,0.000016071635,0.97255975,0.00047484267,0.00011985242,0.0000023654156],"study_design_scores_gemma":[0.00052538497,0.00008642854,0.15830879,0.0037747668,0.00027276672,2.4264855e-7,0.000003763398,0.0009274568,0.83390945,0.00008060879,0.0015034718,0.00060689513],"about_ca_topic_score_codex":0.000026357166,"about_ca_topic_score_gemma":0.0000013842115,"teacher_disagreement_score":0.13865034,"about_ca_system_score_codex":0.00014235961,"about_ca_system_score_gemma":0.0002691606,"threshold_uncertainty_score":0.9998182},"labels":[],"label_agreement":null},{"id":"W4397045463","doi":"10.1681/asn.20233411s1656a","title":"White Matter Alternation at Corpus Callosum and Stria Terminalis Contributes to the Cognitive Impairment in ESRD via Dysregulating Homeostasis of Calcium","year":2023,"lang":"en","type":"article","venue":"Journal of the American Society of Nephrology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Internal medicine; Homeostasis; Endocrinology; Medicine; Stria terminalis; White matter; Psychology; Anatomy; Magnetic resonance imaging; Central nervous system; Radiology","score_opus":0.037516566927443186,"score_gpt":0.34884572460238994,"score_spread":0.31132915767494673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4397045463","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9350726,0.00005259439,0.0055495603,0.0589796,0.000020151332,0.0002841894,0.000029025583,0.000006643636,0.0000056254335],"genre_scores_gemma":[0.9886884,0.00010348137,0.0031493371,0.007938451,0.000045385204,0.000011029553,0.0000023720802,0.000010100738,0.000051422467],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991568,0.000074777185,0.00037511994,0.000099007615,0.00015263946,0.00014165857],"domain_scores_gemma":[0.998715,0.0002386036,0.0007172339,0.0001415615,0.00015104395,0.000036589026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030414131,0.0000795581,0.00033983443,0.0000642704,0.000053124564,0.0000032486744,0.00012644402,0.000024179271,0.000006268203],"category_scores_gemma":[0.00003338566,0.00004946356,0.00014507273,0.00034715162,0.00038451963,0.000026312891,0.00015409793,0.00016696683,7.6072035e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084295054,0.00014490388,0.7796364,0.0000584505,0.00025923608,0.000008596148,0.0023606827,0.0001855223,0.15728638,0.000024031313,0.0461201,0.013072767],"study_design_scores_gemma":[0.000768294,0.00044551012,0.99028707,0.000087379136,0.00010726228,0.00013954027,0.00063867576,0.0006796523,0.0047264607,0.00064918457,0.0014278679,0.000043123644],"about_ca_topic_score_codex":0.000096747965,"about_ca_topic_score_gemma":0.0000092402115,"teacher_disagreement_score":0.21065067,"about_ca_system_score_codex":0.000071121394,"about_ca_system_score_gemma":0.000026156638,"threshold_uncertainty_score":0.20170654},"labels":[],"label_agreement":null},{"id":"W4398147234","doi":"10.1162/imag_x_00158","title":"Correction to: White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan","year":2024,"lang":"en","type":"erratum","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; Université de Sherbrooke; Baycrest Hospital; University of Calgary","funders":"","keywords":"Gray (unit); White matter; Morphology (biology); Evolutionary biology; Brain morphometry; Biology; Zoology; Medicine; Magnetic resonance imaging","score_opus":0.02008746994466979,"score_gpt":0.3418442102674843,"score_spread":0.3217567403228145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398147234","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22181727,0.0037685987,0.035644304,0.36807373,0.32658374,0.011616918,0.0045066266,0.0052593094,0.022729503],"genre_scores_gemma":[0.7101332,0.00024150418,0.0009632748,0.09933826,0.0011247332,0.00021147665,0.00027065544,0.00032341116,0.1873935],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99678105,0.0000967085,0.00049247395,0.0013927943,0.00042590717,0.00081104576],"domain_scores_gemma":[0.9984084,0.00013449874,0.00022311349,0.0008549949,0.00012414447,0.0002548553],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.000253022,0.0005214629,0.00049456174,0.00016516823,0.000581356,0.0005025797,0.00050239457,0.00018112051,0.00010174998],"category_scores_gemma":[0.00038674753,0.00037659687,0.00014806894,0.00077556394,0.0009830943,0.00013879946,0.00047402305,0.0030192889,0.0001574305],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013892233,0.000029570114,0.096529834,0.000061016723,0.0000037796492,0.00013914998,0.000111135945,0.0000048743163,0.023393976,0.0000057188595,0.879341,0.00036602296],"study_design_scores_gemma":[0.00012684145,0.000049157443,0.6605743,0.00025603554,0.00008895511,0.0043716603,0.000016212922,0.0010308962,0.00034027928,0.00033366366,0.33249426,0.00031770964],"about_ca_topic_score_codex":0.00005490602,"about_ca_topic_score_gemma":0.000006276243,"teacher_disagreement_score":0.56404454,"about_ca_system_score_codex":0.00010569814,"about_ca_system_score_gemma":0.00010821958,"threshold_uncertainty_score":0.9998686},"labels":[],"label_agreement":null},{"id":"W4398768708","doi":"10.1016/j.appet.2024.107527","title":"Obesity and diffusion-weighted imaging of subcortical grey matter in young and older adults","year":2024,"lang":"en","type":"article","venue":"Appetite","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada","keywords":"Grey matter; Diffusion MRI; Obesity; Psychology; Medicine; Magnetic resonance imaging; Internal medicine; Radiology; White matter","score_opus":0.009810157193559783,"score_gpt":0.2867510256005421,"score_spread":0.27694086840698234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398768708","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9940772,0.0007208039,0.0021319587,0.002258293,0.000017069275,0.00020283583,0.0000044071817,0.0000679334,0.0005194963],"genre_scores_gemma":[0.9966328,0.0003465853,0.0026382727,0.00021447838,0.000019621468,0.000015174444,0.0000054794978,0.000012818974,0.00011477966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949384,0.0000065351246,0.00012888273,0.00020815924,0.00006335522,0.00009924911],"domain_scores_gemma":[0.99975985,0.000034857112,0.000013988592,0.000127348,0.000017395974,0.000046535366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000037833917,0.00006827465,0.00011301189,0.00007331793,0.000018217897,0.0000114812765,0.000022520977,0.000020323621,0.000029894194],"category_scores_gemma":[0.000007919195,0.0000570701,0.000016516866,0.00011683648,0.000079299985,0.0000524352,0.000056449833,0.00011599959,0.0000059437075],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002449566,0.00006210864,0.9835367,0.0003105811,0.000003207017,0.000042221207,0.00018629132,1.4796955e-8,0.008939252,0.0016070517,0.00027755843,0.005010482],"study_design_scores_gemma":[0.00037395838,0.000015097864,0.99120116,0.0016760314,0.000015999729,0.00015437377,0.000028543143,0.003327375,0.0014886194,0.0011176604,0.0005303375,0.00007081721],"about_ca_topic_score_codex":0.00005217944,"about_ca_topic_score_gemma":0.0000059258946,"teacher_disagreement_score":0.00766445,"about_ca_system_score_codex":0.000008298049,"about_ca_system_score_gemma":0.0000063605103,"threshold_uncertainty_score":0.23272511},"labels":[],"label_agreement":null},{"id":"W4399139593","doi":"10.1038/s41380-024-02604-7","title":"Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McGill University; McGill Genome Centre","funders":"Université de Bordeaux; Agence Nationale de la Recherche; McGill University","keywords":"Diffusion MRI; White matter; Genome-wide association study; Dementia; Hyperintensity; Locus (genetics); Neuroimaging; Biobank; Disease; Medicine; Neuroscience; Pathology; Magnetic resonance imaging; Biology; Genetics; Single-nucleotide polymorphism; Genotype; Gene","score_opus":0.017618381692906505,"score_gpt":0.2844274265415538,"score_spread":0.26680904484864726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399139593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35903326,0.0016835271,0.63173157,0.0062557016,0.00021619682,0.00045630225,0.00001636942,0.00028599697,0.0003210535],"genre_scores_gemma":[0.8178425,0.0000319317,0.18078704,0.0010451348,0.00006781499,0.00005717298,0.000029098983,0.000066279084,0.000073071446],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99898165,0.000011944037,0.0002539831,0.00041220261,0.000158236,0.00018195502],"domain_scores_gemma":[0.99923474,0.000011537767,0.000058678583,0.0004910667,0.00004785182,0.00015610976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052495074,0.00017376553,0.00017499547,0.000116974814,0.00006185137,0.00003460882,0.00014228087,0.00003343804,0.00000838407],"category_scores_gemma":[0.000015819669,0.00016103132,0.00015196268,0.00024402913,0.000061390354,0.00006350195,0.00010347847,0.0002108189,0.000007826497],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006890718,0.0003644513,0.0060869,0.0006490317,0.000035184763,0.00007388161,0.00016997996,0.000013576373,0.8340391,0.15432614,0.00024484404,0.0039280183],"study_design_scores_gemma":[0.0028980526,0.00053020363,0.047267713,0.0027941663,0.0010989279,0.00029816787,0.00016483472,0.03667852,0.22513755,0.64478934,0.03696635,0.0013761799],"about_ca_topic_score_codex":0.000028261455,"about_ca_topic_score_gemma":0.0000014615998,"teacher_disagreement_score":0.60890156,"about_ca_system_score_codex":0.000042440282,"about_ca_system_score_gemma":0.00017630083,"threshold_uncertainty_score":0.6566667},"labels":[],"label_agreement":null},{"id":"W4399346227","doi":"10.52294/001c.118427","title":"MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across measures","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Toolbox; Multivariate statistics; Computer science; Multivariate analysis; Artificial intelligence; Statistics; Econometrics; Accounting; Mathematics; Machine learning; Business; Programming language","score_opus":0.054598876583771785,"score_gpt":0.3866768930689983,"score_spread":0.3320780164852265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399346227","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02668125,0.0011484155,0.758242,0.20327494,0.00065736356,0.0037520798,0.0007477241,0.002160264,0.003335937],"genre_scores_gemma":[0.955043,0.000033472574,0.02262165,0.021598117,0.00014463591,0.00014560117,0.00019398965,0.00004169728,0.0001777913],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990707,0.00001754828,0.00030741398,0.00020745369,0.00018113464,0.00021573917],"domain_scores_gemma":[0.99689066,0.002535323,0.000094017174,0.00031599158,0.00011122777,0.000052793755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014106005,0.00015620638,0.00025964328,0.00007403431,0.00012613295,0.00007106633,0.00013703929,0.00008021036,0.0000042426705],"category_scores_gemma":[0.0012123516,0.00012760091,0.00012846924,0.00022899898,0.000059979924,0.0002899564,0.00004800242,0.00031872504,0.000006401364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003241964,0.00019626284,0.0024313123,0.0010609303,0.000095468386,0.000013899413,0.0016596274,0.00021923587,0.14644659,0.020575387,0.7527188,0.07425829],"study_design_scores_gemma":[0.00042808522,0.00010130168,0.009901106,0.0001631332,0.000044025855,0.00006459625,0.00006717338,0.012504271,0.007952387,0.00046245183,0.96818453,0.00012690737],"about_ca_topic_score_codex":0.000032675856,"about_ca_topic_score_gemma":0.0000073590854,"teacher_disagreement_score":0.9283618,"about_ca_system_score_codex":0.000020948739,"about_ca_system_score_gemma":0.000031249707,"threshold_uncertainty_score":0.5203414},"labels":[],"label_agreement":null},{"id":"W4399363497","doi":"10.1101/2024.06.04.597406","title":"Age-trajectories of higher-order diffusion properties of major brain metabolites in cerebral and cerebellar grey matter using in vivo diffusion-weighted MR spectroscopy at 3T","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Diffusion; In vivo; Diffusion MRI; In vivo magnetic resonance spectroscopy; Grey matter; Nuclear magnetic resonance; Order (exchange); Nuclear magnetic resonance spectroscopy; Cerebellum; Chemistry; Neuroscience; Physics; Magnetic resonance imaging; Medicine; Biology; White matter; Radiology; Thermodynamics","score_opus":0.023919185767010236,"score_gpt":0.2713127150410414,"score_spread":0.24739352927403113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399363497","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936477,0.0033980873,0.00021602526,0.0009204059,0.000197749,0.0012853687,0.00015722663,0.00016671023,0.000010725223],"genre_scores_gemma":[0.973892,0.0003430593,0.02515511,0.00016492298,0.00011234859,0.00013688295,7.4062064e-7,0.00014493009,0.000050038434],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9973982,0.00009299436,0.00084180554,0.0009157372,0.00033216467,0.00041910863],"domain_scores_gemma":[0.99833566,0.00005097683,0.0003633297,0.0008951956,0.00022824797,0.0001266164],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00021499152,0.00052214577,0.0010273729,0.00061834994,0.00006277521,0.000045811306,0.00022840091,0.00032861668,0.00007593815],"category_scores_gemma":[0.000075725395,0.00046357454,0.00011488833,0.00085172046,0.00033345178,0.000083599465,0.0009649859,0.0007244653,0.000002924293],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011151888,0.0002177477,0.112969816,0.001889267,0.000040522824,0.000039212948,0.00004697143,0.000003048764,0.88402575,0.00056356716,0.00009201843,5.354102e-7],"study_design_scores_gemma":[0.0007511299,0.000041895713,0.13655947,0.0023940809,0.00014964723,1.7121168e-7,0.000005280977,0.00048121548,0.85851985,0.00010125548,0.00060953514,0.00038644485],"about_ca_topic_score_codex":0.0004130741,"about_ca_topic_score_gemma":0.000019841458,"teacher_disagreement_score":0.025505906,"about_ca_system_score_codex":0.00021271934,"about_ca_system_score_gemma":0.00020735271,"threshold_uncertainty_score":0.9997816},"labels":[],"label_agreement":null},{"id":"W4399401389","doi":"10.1523/jneurosci.1705-23.2024","title":"Diffusion MRI of the Hippocampus","year":2024,"lang":"en","type":"review","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canadian Open Neuroscience Platform; Health Canada; Canada Research Chairs; Canada First Research Excellence Fund; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Hippocampus; Diffusion MRI; Neuroscience; Medicine; Magnetic resonance imaging; Psychology; Radiology","score_opus":0.12263189980638309,"score_gpt":0.43046578682198583,"score_spread":0.30783388701560277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399401389","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009177681,0.99728733,0.00062019395,0.00082947774,0.00067718356,0.00031427195,0.0000074574255,0.000017522107,0.0001547885],"genre_scores_gemma":[0.0002366455,0.9983121,0.00075430196,0.00022563917,0.00010473825,0.0000037864418,1.5595789e-7,0.00001934665,0.00034326897],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876845,0.000037321322,0.00055014796,0.00016762225,0.00037199247,0.000104494655],"domain_scores_gemma":[0.99870193,0.00005535517,0.00072037743,0.00037882413,0.000076522585,0.0000669887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016199323,0.0001356636,0.00061788753,0.00014661418,0.00004750527,0.0000145877475,0.00049078825,0.0000482858,0.0000018273932],"category_scores_gemma":[0.00018772593,0.000063663814,0.0005076053,0.0007004026,0.00018835995,0.000045296012,0.00016811315,0.0006693324,0.0000021334088],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000037419313,0.00012643696,0.00001641693,0.0054485197,0.000005910709,0.00010117576,0.000014142888,0.0000010613438,0.0022900922,0.00033891402,0.00490713,0.98674643],"study_design_scores_gemma":[0.000038495735,0.000114236565,0.00006914394,0.010818661,0.00048620178,0.003002867,9.932401e-7,0.000018780658,0.00002334478,0.0010342461,0.9843444,0.000048592294],"about_ca_topic_score_codex":2.465819e-7,"about_ca_topic_score_gemma":2.7104765e-8,"teacher_disagreement_score":0.98669785,"about_ca_system_score_codex":0.000036170364,"about_ca_system_score_gemma":0.00028668757,"threshold_uncertainty_score":0.29079536},"labels":[],"label_agreement":null},{"id":"W4399433832","doi":"10.7554/elife.96625.1","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"","keywords":"Cerebellum; Thalamus; Neuroscience; Biology; Taurine; Diffusion MRI; Anatomy; Magnetic resonance imaging; Medicine; Biochemistry; Amino acid","score_opus":0.04930940267079468,"score_gpt":0.3312707699946626,"score_spread":0.2819613673238679,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399433832","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9959954,0.0009054347,0.00050041307,0.0014217146,0.00012923623,0.0005500357,0.00001824721,0.000051488216,0.0004280106],"genre_scores_gemma":[0.9952838,0.00032705118,0.003963155,0.00009103753,0.000048046382,0.00008832999,0.000039211795,0.000020246613,0.00013914017],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989889,0.000027643542,0.00035259797,0.00027661683,0.00025000513,0.00010422089],"domain_scores_gemma":[0.9993968,0.00012113379,0.00012011452,0.00028743007,0.00004383861,0.000030666964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014636881,0.00015601557,0.0002902389,0.00008108868,0.000027409658,0.000008528793,0.0001358128,0.0000708004,0.000007478773],"category_scores_gemma":[0.000055954482,0.00010524393,0.00005656154,0.00011492755,0.00013158351,0.000009281691,0.00030255064,0.0004802195,5.765334e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094066525,0.0035046495,0.51995033,0.017910331,0.0003090578,0.00032308957,0.03885581,0.00019629777,0.1265815,0.022020124,0.010229737,0.2591784],"study_design_scores_gemma":[0.0008078266,0.00020478046,0.84799534,0.0019499646,0.00019676841,0.00008161988,0.00044825466,0.0006325907,0.10150633,0.010727523,0.035043854,0.0004051566],"about_ca_topic_score_codex":0.000032371576,"about_ca_topic_score_gemma":0.000014396659,"teacher_disagreement_score":0.328045,"about_ca_system_score_codex":0.00001921305,"about_ca_system_score_gemma":0.00011122505,"threshold_uncertainty_score":0.4291723},"labels":[],"label_agreement":null},{"id":"W4399433921","doi":"10.7554/elife.96625","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"UK Research and Innovation; Wellcome Trust","keywords":"Cerebellum; Thalamus; Neuroscience; Taurine; Biology; Diffusion MRI; Anatomy; Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Medicine; Biochemistry; Amino acid","score_opus":0.04017943180066636,"score_gpt":0.32255769961411135,"score_spread":0.282378267813445,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399433921","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9967623,0.00053573656,0.0010169131,0.0011181047,0.000044015982,0.00019632516,0.0000033556362,0.000036911973,0.00028633577],"genre_scores_gemma":[0.9975252,0.00012415067,0.002106276,0.000081936894,0.000021825845,0.00002182781,0.000007139521,0.000008079328,0.00010355116],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99949586,0.000013173806,0.0001675672,0.0001185053,0.00013733086,0.00006753656],"domain_scores_gemma":[0.99971616,0.00011379925,0.000027037162,0.00010681773,0.000017591883,0.000018592174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008654765,0.000061740575,0.00010805786,0.00004105225,0.00002324374,0.0000048618504,0.000051063027,0.000017159757,0.00000770492],"category_scores_gemma":[0.00003102541,0.000039348735,0.000021228934,0.00013467432,0.00007685782,0.00002146706,0.000024629164,0.00010327474,4.324346e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027503647,0.0010277145,0.43493482,0.0018431928,0.000053095715,0.00012468983,0.015746245,0.000015411902,0.2750252,0.021868188,0.004591067,0.24449536],"study_design_scores_gemma":[0.0003981742,0.00014677511,0.8109802,0.0003065613,0.00003333797,0.00005805692,0.00027639492,0.0004808425,0.11929991,0.0008617222,0.06704924,0.00010876133],"about_ca_topic_score_codex":0.0000103397,"about_ca_topic_score_gemma":0.000006421228,"teacher_disagreement_score":0.3760454,"about_ca_system_score_codex":0.0000074929535,"about_ca_system_score_gemma":0.000035135658,"threshold_uncertainty_score":0.16045949},"labels":[],"label_agreement":null},{"id":"W4399446846","doi":"10.1016/j.neuroimage.2024.120672","title":"Divergent functional connectivity changes associated with white matter hyperintensities","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Hjärnfonden; Alzheimerfonden; Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse; University Hospital Foundation; Vetenskapsrådet; Marcus och Amalia Wallenbergs minnesfond; Knut och Alice Wallenbergs Stiftelse","keywords":"Hyperintensity; White matter; Cognition; Diffusion MRI; Neuroscience; Voxel; Default mode network; Resting state fMRI; Psychology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.07126254151730615,"score_gpt":0.3015506494475971,"score_spread":0.23028810793029092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399446846","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9387737,0.00013466597,0.016105825,0.031277917,0.00028088852,0.0005336413,0.00009515964,0.0014664333,0.011331753],"genre_scores_gemma":[0.98888355,0.000023404531,0.0005322093,0.0035261528,0.000101585705,0.00006969077,0.000040294086,0.00004246378,0.0067806323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992384,0.000018128629,0.00007958342,0.00032882427,0.00016540533,0.00016969073],"domain_scores_gemma":[0.99954575,0.00006652398,0.000023230235,0.00022264336,0.00007964136,0.000062205494],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000047562684,0.0001293422,0.00014431153,0.00007770367,0.0000781792,0.000039195525,0.000038618582,0.000028146082,0.00040530108],"category_scores_gemma":[0.000028759658,0.00010121121,0.00004734895,0.0001874308,0.00008970296,0.000075999014,0.00004688848,0.00022856343,0.00010809418],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050526165,0.00081602286,0.47989005,0.0004706128,0.0003197947,0.0023782658,0.00051665545,0.00007283112,0.1757174,0.004755566,0.327551,0.0070065223],"study_design_scores_gemma":[0.00031849172,0.00027740156,0.9411406,0.00016746095,0.00011245215,0.0004457235,0.000032331536,0.0011183326,0.0044335304,0.00033398374,0.05141897,0.00020073885],"about_ca_topic_score_codex":0.000004130813,"about_ca_topic_score_gemma":0.0000048868146,"teacher_disagreement_score":0.4612505,"about_ca_system_score_codex":0.000040363284,"about_ca_system_score_gemma":0.000024157162,"threshold_uncertainty_score":0.44377625},"labels":[],"label_agreement":null},{"id":"W4399457528","doi":"10.1016/j.neurobiolaging.2024.05.017","title":"Menopause status- and sex-related differences in age associations with spatial context memory and white matter microstructure at midlife","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; Douglas College; McGill University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Context (archaeology); Psychology; White matter; Corpus callosum; Menopause; Developmental psychology; Medicine; Neuroscience; Internal medicine; Biology; Magnetic resonance imaging","score_opus":0.018587480869495496,"score_gpt":0.2794575233510993,"score_spread":0.2608700424816038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399457528","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9964899,0.0003041801,0.00006501083,0.0026305239,0.000030291578,0.00022574166,0.00004432855,0.00006765803,0.00014235592],"genre_scores_gemma":[0.9981641,0.00012568448,0.00050446845,0.00067965605,0.000011062494,0.000010983473,0.000034294422,0.000015267015,0.00045448152],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999349,0.00003474201,0.00016437176,0.00026757008,0.000035455036,0.00014888178],"domain_scores_gemma":[0.9996861,0.00009911894,0.00005412523,0.00010802702,0.00001373692,0.000038890288],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038624272,0.00010569696,0.00022302456,0.00009666424,0.000048164522,0.0000106890875,0.000030063387,0.000054616088,0.000024000874],"category_scores_gemma":[0.00000702727,0.000080866645,0.000012230537,0.00009096239,0.00021858868,0.00003478562,0.000056938195,0.00022060832,0.0000010215888],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016054995,0.000015227095,0.9529651,0.00006389672,0.00002393232,0.00003176823,0.0009465332,0.0000016300598,0.045126006,0.000053281525,0.00023200156,0.0005245948],"study_design_scores_gemma":[0.00048218743,0.00013519081,0.9946636,0.000115224575,0.000049681446,0.00010338365,0.0000738324,0.0000625997,0.003639761,0.00028511768,0.00030241997,0.00008699638],"about_ca_topic_score_codex":0.00004963357,"about_ca_topic_score_gemma":0.000057993846,"teacher_disagreement_score":0.041698534,"about_ca_system_score_codex":0.000019952222,"about_ca_system_score_gemma":0.000015516287,"threshold_uncertainty_score":0.3297646},"labels":[],"label_agreement":null},{"id":"W4399466581","doi":"10.1101/2024.06.05.597645","title":"White Matter Microstructural Correlates of Cognitive and Motor Functioning Revealed via Multimodal Multivariate Analysis","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Psychology; Cognition; Multivariate statistics; Neuroimaging; Mahalanobis distance; Cognitive psychology; White matter; Multivariate analysis; Metric (unit); Neuroscience; Artificial intelligence; Computer science; Magnetic resonance imaging; Medicine; Machine learning","score_opus":0.01632460991388035,"score_gpt":0.2722177133181243,"score_spread":0.2558931034042439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399466581","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9760734,0.00065120915,0.020694204,0.0002937497,0.00021999291,0.00105972,0.000620312,0.0003798332,0.000007585581],"genre_scores_gemma":[0.9650482,0.000067024324,0.034254543,0.00015668123,0.00012962641,0.00020171571,0.0000036605616,0.00010564833,0.000032918655],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99792063,0.00005157442,0.0005596564,0.0009611722,0.00020298816,0.00030398744],"domain_scores_gemma":[0.9981839,0.00010485334,0.000395777,0.0006657212,0.00047296297,0.00017680672],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016687381,0.00044579685,0.0007826827,0.00052306807,0.000104276376,0.00007379988,0.0001327745,0.00030504641,0.000073816176],"category_scores_gemma":[0.00009485931,0.0004337056,0.0002637235,0.00072452496,0.00020603988,0.00006256041,0.0005016531,0.00091130816,0.00002520697],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013498247,0.00007637979,0.4722917,0.00066305423,0.0010552434,0.000036350157,0.00002919949,0.000031603802,0.5255683,0.000046136105,0.00006123411,0.000005786305],"study_design_scores_gemma":[0.0005294611,0.000054034088,0.9594934,0.0009302616,0.0032077332,1.8599388e-7,0.000004309251,0.0078189485,0.027506847,0.000017643886,0.00003538738,0.00040177256],"about_ca_topic_score_codex":0.00006229036,"about_ca_topic_score_gemma":6.638419e-7,"teacher_disagreement_score":0.49806148,"about_ca_system_score_codex":0.00009562697,"about_ca_system_score_gemma":0.000105831605,"threshold_uncertainty_score":0.9998115},"labels":[],"label_agreement":null},{"id":"W4399511621","doi":"10.1186/s12880-024-01324-2","title":"Alterations in structural integrity of superior longitudinal fasciculus III associated with cognitive performance in cerebral small vessel disease","year":2024,"lang":"en","type":"article","venue":"BMC Medical Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Anhui University; Anhui University of Science and Technology; National Natural Science Foundation of China","keywords":"Cognition; Structural integrity; Neuroscience; Disease; Computer science; Medicine; Pathology; Psychology","score_opus":0.052871482746483706,"score_gpt":0.34992412560570135,"score_spread":0.2970526428592176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399511621","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9752018,0.00027652763,0.02262869,0.0011813671,0.000041725467,0.00037190478,0.000022749224,0.00011895437,0.00015629368],"genre_scores_gemma":[0.9976585,0.000036102785,0.0018589699,0.00016892212,0.00004748082,0.00008667898,0.00008479818,0.000019087991,0.000039440994],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987691,0.000045425222,0.000322843,0.00032473452,0.00029696958,0.00024089377],"domain_scores_gemma":[0.99929655,0.00026191983,0.000040728853,0.00013665992,0.0000803062,0.00018381033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021188054,0.00013782119,0.0002447276,0.00014333044,0.00004357189,0.000023123626,0.00009230172,0.000036122037,0.00006275527],"category_scores_gemma":[0.0005877525,0.000106773005,0.000046338577,0.0004913229,0.00025000772,0.0001705478,0.000056550172,0.00060996175,0.000001722762],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014203378,0.00011839487,0.9907269,0.00026078848,0.0000107748965,0.00023725699,0.00023567541,0.000013485942,0.00016318128,0.00066927425,0.000017871245,0.0074043814],"study_design_scores_gemma":[0.0010926746,0.000036007903,0.79803425,0.0041008005,0.00004760646,0.000055508528,0.00013985812,0.1957465,0.000402709,0.0002148975,0.00001194865,0.0001172208],"about_ca_topic_score_codex":0.00008456426,"about_ca_topic_score_gemma":0.00021729703,"teacher_disagreement_score":0.19573301,"about_ca_system_score_codex":0.000096946125,"about_ca_system_score_gemma":0.00047646058,"threshold_uncertainty_score":0.43540767},"labels":[],"label_agreement":null},{"id":"W4399561968","doi":"10.1101/2024.06.10.598357","title":"Sex, racial, and <i>APOE</i> -ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer’s disease","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; Genentech; National Institutes of Health; H. Lundbeck A/S; Eisai; Siemens Medical Solutions USA; Vanderbilt University Medical Center; Novo Nordisk; Northern California Institute for Research and Education; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; University of Pennsylvania; Vanderbilt University; University of Southern California; Bristol-Myers Squibb; Eli Lilly and Company; Vanderbilt Memory and Alzheimer's Center; Biogen; National Institute on Aging; Alzheimer's Association","keywords":"Allele; Apolipoprotein E; Longitudinal study; Disease; White (mutation); White matter; Gerontology; Medicine; Genetics; Biology; Internal medicine; Pathology; Gene","score_opus":0.03411138672146659,"score_gpt":0.2787128996092358,"score_spread":0.2446015128877692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399561968","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9906955,0.0067131384,0.00018028004,0.0010456069,0.00007846058,0.0009270918,0.00023353532,0.00012324896,0.000003169124],"genre_scores_gemma":[0.9932218,0.00085688755,0.0053640814,0.00022308396,0.00007659273,0.00018043912,0.0000013150845,0.000071871174,0.0000039154697],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99816483,0.00004137025,0.00044569926,0.0008829143,0.00016952101,0.00029565394],"domain_scores_gemma":[0.9989379,0.00004907591,0.00017331817,0.0005737169,0.00007487413,0.00019113517],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00015852728,0.00037206005,0.0006383491,0.0002987365,0.00004736315,0.00006842524,0.00013502844,0.00017818066,0.0000121941075],"category_scores_gemma":[0.000038523976,0.000365516,0.00005656116,0.00028429952,0.00021643593,0.000059508027,0.0005476247,0.00076071284,0.00000185536],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036204918,0.000072307535,0.95498943,0.0007475265,0.00003591768,0.0001272752,0.000029284824,0.0000047271674,0.043773092,0.000050224615,0.00012823453,0.0000057630673],"study_design_scores_gemma":[0.0004290365,0.000017375833,0.9841641,0.0011159325,0.00017451527,1.8690437e-7,0.0000037774712,0.00048378436,0.012952979,0.000045777022,0.00028698635,0.00032553053],"about_ca_topic_score_codex":0.000061989806,"about_ca_topic_score_gemma":0.00001144596,"teacher_disagreement_score":0.030820115,"about_ca_system_score_codex":0.00005065005,"about_ca_system_score_gemma":0.00013973795,"threshold_uncertainty_score":0.99987966},"labels":[],"label_agreement":null},{"id":"W4399593070","doi":"10.3389/fnins.2024.1389680","title":"Tractometry of the Human Connectome Project: resources and insights","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Office of Science; National Science Foundation; National Institutes of Health; Amazon Web Services; Advanced Scientific Computing Research; University of Washington; U.S. Department of Energy","keywords":"Human Connectome Project; Computer science; Connectome; Diffusion MRI; White matter; Connectomics; Visualization; Artificial intelligence; Tractography; Voxel; Pattern recognition (psychology); Machine learning; Functional connectivity; Neuroscience; Biology; Magnetic resonance imaging","score_opus":0.05272257028497808,"score_gpt":0.35716659443240106,"score_spread":0.304444024147423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399593070","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9950617,0.0006677065,0.0019731023,0.00072469504,0.00022146835,0.00031709595,0.0000037149014,0.00007884574,0.0009516923],"genre_scores_gemma":[0.997299,0.000100462516,0.0019763748,0.00028638047,0.000011381751,0.00001613469,2.1275841e-7,0.000007810078,0.00030219884],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99938065,0.000016338461,0.00011963407,0.00024981407,0.00013655038,0.00009698864],"domain_scores_gemma":[0.9997027,0.00002395611,0.000027585786,0.0002114637,0.000010438776,0.000023844339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006567058,0.000058738948,0.00010094536,0.00019920626,0.00006438473,0.000018924224,0.00014123043,0.000020172236,5.3191894e-7],"category_scores_gemma":[0.00007507481,0.000038389575,0.00002463638,0.0009639255,0.00036521518,0.0000749815,0.00006160604,0.00017527607,9.797794e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002271709,0.00023859106,0.30932552,0.00045050276,0.000004224381,0.00009141983,0.0030605032,0.000012149855,0.64910465,0.014613013,0.0120849125,0.010991809],"study_design_scores_gemma":[0.00041233626,0.0002717212,0.75150406,0.00053751544,0.00003407682,0.0001715696,0.00034920906,0.008523795,0.03657117,0.013104144,0.18829809,0.00022231703],"about_ca_topic_score_codex":0.000005941001,"about_ca_topic_score_gemma":5.4067436e-7,"teacher_disagreement_score":0.6125335,"about_ca_system_score_codex":0.000013726472,"about_ca_system_score_gemma":0.000025763928,"threshold_uncertainty_score":0.15654814},"labels":[],"label_agreement":null},{"id":"W4399663873","doi":"10.1093/brain/awae192","title":"Explaining slow seizure propagation with white matter tractography","year":2024,"lang":"en","type":"article","venue":"Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; McGill University","keywords":"Stereoelectroencephalography; Tractography; White matter; Epilepsy; Epileptic seizure; Neuroscience; Electroencephalography; Connectome; Psychology; Medicine; Epilepsy surgery; Functional connectivity; Magnetic resonance imaging; Radiology","score_opus":0.032086412828542986,"score_gpt":0.32095522872762056,"score_spread":0.2888688158990776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399663873","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15022829,0.0003045798,0.68561834,0.1283867,0.00008212293,0.0013882254,0.000023923652,0.0021243887,0.03184342],"genre_scores_gemma":[0.9606847,0.000005935565,0.032876465,0.0029672203,0.00009671442,0.00013164079,0.000036094887,0.000035809302,0.003165413],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995054,0.000007912817,0.00008384552,0.00020154404,0.00009421287,0.0001070713],"domain_scores_gemma":[0.99972,0.000029637567,0.000017192637,0.00017154646,0.000019768777,0.00004187465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053115895,0.00007777441,0.00007639285,0.000093666014,0.00004013662,0.000029441855,0.00003252581,0.000025698135,0.00007669188],"category_scores_gemma":[0.000006163282,0.000057164372,0.000034573255,0.00028432984,0.00003103923,0.00008726647,0.000008550876,0.00015357047,0.00004816721],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025718202,0.00035108507,0.18457308,0.0010884064,0.0001474775,0.00076309807,0.0029852332,0.000069088805,0.088058166,0.02267914,0.58245283,0.116575226],"study_design_scores_gemma":[0.0010268152,0.000509269,0.21768269,0.0016110496,0.00015846865,0.0015827379,0.00034128092,0.005306622,0.011388092,0.004259159,0.7555426,0.0005912426],"about_ca_topic_score_codex":0.000001207838,"about_ca_topic_score_gemma":4.3020853e-7,"teacher_disagreement_score":0.8104564,"about_ca_system_score_codex":0.000010959997,"about_ca_system_score_gemma":0.000019984656,"threshold_uncertainty_score":0.23310955},"labels":[],"label_agreement":null},{"id":"W4399707580","doi":"10.1002/alz.13808","title":"In vivo effect of LATE‐NC on integrity of white matter connections to the hippocampus","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Science Foundation; National Institutes of Health; Rush University; National Institute on Aging","keywords":"Hippocampus; White matter; Neuroscience; In vivo; Psychology; Biology; Medicine; Genetics; Magnetic resonance imaging","score_opus":0.03451498303370768,"score_gpt":0.34629155188784105,"score_spread":0.31177656885413335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399707580","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9576898,0.0049814377,0.0025316016,0.028942062,0.00032706707,0.0015142246,0.000055591947,0.0001405444,0.0038176596],"genre_scores_gemma":[0.99772745,0.000021031245,0.0011788317,0.00085908687,0.000029076104,0.000112757036,0.000003977465,0.000016191743,0.00005157779],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99937594,0.000036346213,0.00020091984,0.00018058164,0.00009940659,0.00010680468],"domain_scores_gemma":[0.9994766,0.0001151969,0.000033427223,0.0003172997,0.00002640459,0.00003106147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016340712,0.00009044002,0.00015733119,0.000107758235,0.00003453182,0.000004913427,0.000088922985,0.000029820349,0.0002996123],"category_scores_gemma":[0.000014100252,0.000059945414,0.000067551264,0.00029923435,0.00004251328,0.00003568644,0.000059474813,0.00020188402,0.00006758027],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006975627,0.0009830588,0.20880888,0.0004245349,0.0077158147,0.00007507831,0.0024918432,0.00033918145,0.21939345,0.013982102,0.45948675,0.085601754],"study_design_scores_gemma":[0.0007143375,0.0012284773,0.030867368,0.0006164793,0.007126674,0.00003882266,0.000033615743,0.0006648606,0.8068947,0.0044039357,0.14715676,0.0002539208],"about_ca_topic_score_codex":0.000051549196,"about_ca_topic_score_gemma":0.000012555514,"teacher_disagreement_score":0.5875013,"about_ca_system_score_codex":0.000004653217,"about_ca_system_score_gemma":0.000013557833,"threshold_uncertainty_score":0.32805446},"labels":[],"label_agreement":null},{"id":"W4399749900","doi":"10.20944/preprints202301.0571.v3","title":"Spin Helicity","year":2024,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Helicity; Physics; Spin (aerodynamics); Condensed matter physics; Particle physics","score_opus":0.28031779554085823,"score_gpt":0.46344382454692906,"score_spread":0.18312602900607083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399749900","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.936188,0.00038726875,0.0021360167,0.009629087,0.00039075792,0.0014938285,0.00005314404,0.0021535154,0.04756839],"genre_scores_gemma":[0.9869888,0.00039429672,0.0043550637,0.00088935404,0.00036818252,0.00051888754,0.00006580669,0.00009003757,0.006329568],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99793494,0.00002607348,0.0003993612,0.001097707,0.00026142763,0.00028047155],"domain_scores_gemma":[0.99771434,0.000027426588,0.00012805476,0.0018487753,0.000108527114,0.00017284967],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021975455,0.00031846695,0.0004325818,0.0001564105,0.000057606183,0.000015909143,0.00034227048,0.0002507337,0.0004982496],"category_scores_gemma":[0.0001345203,0.00031066017,0.00028055257,0.00017873358,0.00010036296,0.000020592968,0.0031961433,0.0018628555,0.0034380318],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022085731,0.0013993267,0.67107064,0.0058999215,0.0005947959,0.0006202725,0.0008205987,0.000260721,0.2575369,0.035115555,0.010311908,0.016148498],"study_design_scores_gemma":[0.00044105735,0.00005342354,0.29797468,0.0019447792,0.0005317437,0.0002094385,0.000025028017,0.001009811,0.305904,0.18775646,0.20326452,0.00088504696],"about_ca_topic_score_codex":0.000069905014,"about_ca_topic_score_gemma":0.0000015648149,"teacher_disagreement_score":0.37309596,"about_ca_system_score_codex":0.00015112554,"about_ca_system_score_gemma":0.00016623519,"threshold_uncertainty_score":0.99993455},"labels":[],"label_agreement":null},{"id":"W4399796974","doi":"10.1016/b978-0-12-820480-1.00170-4","title":"MRI of brain plasticity","year":2024,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Neuroscience; Plasticity; Neuroplasticity; Psychology; Physics","score_opus":0.04383439821937826,"score_gpt":0.32673139408632296,"score_spread":0.2828969958669447,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399796974","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000013036821,0.00032492614,0.00036661557,0.0010082615,0.00006263455,0.00056509406,0.00008343888,0.00024039754,0.9973356],"genre_scores_gemma":[0.00072979176,0.00009097184,0.0039233775,0.00059238623,0.00018577598,0.00003719364,0.000021158625,0.00009699558,0.99432236],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989916,0.000002805801,0.0003288662,0.00034892588,0.00019460997,0.00013318787],"domain_scores_gemma":[0.99922454,0.00007860957,0.00012772094,0.00041443974,0.0000693729,0.000085333915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005088309,0.00023385457,0.00043705673,0.0001276794,0.000025776157,0.000006442985,0.00010956986,0.00015522123,0.00012813906],"category_scores_gemma":[0.000017495571,0.00020648378,0.00020961523,0.000013240107,0.00015908059,0.000008865387,0.000102729595,0.0005028954,0.0001160191],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023267712,0.000015459716,0.0000033988235,0.00058304524,0.00008468521,0.000077185025,0.00004020379,3.2797487e-7,0.0014491568,0.25792214,0.0041671866,0.7356339],"study_design_scores_gemma":[0.0001026668,0.00008255643,0.0000072793905,0.0009665726,0.00019471982,0.000059850176,8.153548e-7,0.0000179016,0.000928894,0.093819894,0.9036772,0.00014163295],"about_ca_topic_score_codex":1.4630989e-7,"about_ca_topic_score_gemma":8.410274e-7,"teacher_disagreement_score":0.89951,"about_ca_system_score_codex":0.000041082832,"about_ca_system_score_gemma":0.00006981678,"threshold_uncertainty_score":0.8420164},"labels":[],"label_agreement":null},{"id":"W4399835591","doi":"10.14740/jmc4206","title":"Prompt Identification and Intervention for Ischemic Monomelic Neuropathy in Preventing Major Patient Disability","year":2024,"lang":"en","type":"article","venue":"Journal of Medical Cases","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Medicine; Intervention (counseling); Identification (biology); Psychiatry","score_opus":0.058917780985413115,"score_gpt":0.3970325341333588,"score_spread":0.3381147531479457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399835591","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776465,0.0014008854,0.013963174,0.006521394,0.00009204865,0.00033761366,0.000004893172,0.000024741947,0.000008718058],"genre_scores_gemma":[0.99783456,0.00017362477,0.0017229915,0.000077537064,0.00011502147,0.00004189963,0.000004442608,0.00000977075,0.000020167252],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99902296,0.000027530305,0.00049534085,0.00013225971,0.00024245634,0.00007945445],"domain_scores_gemma":[0.99945,0.00019908947,0.0001248704,0.00008794932,0.000048934613,0.00008912615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005824791,0.000056959765,0.00013969201,0.00006704075,0.00002100305,0.00002229273,0.00005249973,0.000035568937,0.000017686258],"category_scores_gemma":[0.0010464633,0.000044045715,0.00008689274,0.000104083236,0.000059963735,0.00010585929,0.000031340453,0.0002276329,4.9839355e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002664287,0.0011330894,0.019589638,0.0020595822,0.00003346098,0.00046720527,0.00033164723,0.000002609764,0.021378776,0.00054166705,0.0033568975,0.950839],"study_design_scores_gemma":[0.013007754,0.010756329,0.36521772,0.029816974,0.0016516245,0.04379558,0.002670061,0.08848413,0.14962341,0.030811463,0.26287195,0.0012929873],"about_ca_topic_score_codex":0.00000509072,"about_ca_topic_score_gemma":0.0000016323196,"teacher_disagreement_score":0.94954604,"about_ca_system_score_codex":0.000046312478,"about_ca_system_score_gemma":0.000034084438,"threshold_uncertainty_score":0.17961322},"labels":[],"label_agreement":null},{"id":"W4399835759","doi":"10.1093/cercor/bhae220","title":"Structural connectivity changes in unilateral hearing loss","year":2024,"lang":"en","type":"article","venue":"Cerebral Cortex","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University Health Network; University of Toronto; University of New Brunswick; Canada Research Chairs; Toronto Western Hospital; Krembil Foundation","funders":"Canadian Institutes of Health Research","keywords":"Hearing loss; Connectome; Connectomics; Audiology; Diffusion MRI; Node (physics); Unilateral hearing loss; Psychology; Medicine; Neuroscience; Magnetic resonance imaging; Functional connectivity; Physics","score_opus":0.07232046924430291,"score_gpt":0.35845888716737523,"score_spread":0.2861384179230723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399835759","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99371666,0.00011910883,0.0004048711,0.0040729814,0.00010499773,0.00023574558,0.0000068066097,0.00037984486,0.00095900096],"genre_scores_gemma":[0.9981441,0.000018827659,0.0007885761,0.00037940283,0.00010996575,0.00002415189,0.00001514904,0.000020327856,0.0004995175],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993875,0.000009665507,0.00009487713,0.0002563743,0.00007380276,0.00017776855],"domain_scores_gemma":[0.99971056,0.00002643178,0.000013125516,0.00017966381,0.000015012556,0.000055198616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004090562,0.000094316114,0.00013620715,0.000087568245,0.000034853467,0.000024978244,0.00004984511,0.000036501573,0.000080417274],"category_scores_gemma":[0.000011656872,0.0000813173,0.00003485711,0.00021819385,0.000047265683,0.00007667058,0.0000464001,0.00024377146,0.000014844933],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015730126,0.00010764093,0.67590755,0.0007057946,0.00005483506,0.0012505028,0.00077712396,0.000032293847,0.11463452,0.09551401,0.00200473,0.10885371],"study_design_scores_gemma":[0.00047637487,0.00015827375,0.9489156,0.00030607733,0.000027803577,0.0005135131,0.00003369697,0.014482591,0.009999396,0.01618561,0.008650341,0.00025069978],"about_ca_topic_score_codex":0.00003933587,"about_ca_topic_score_gemma":0.00005510784,"teacher_disagreement_score":0.27300808,"about_ca_system_score_codex":0.00006248605,"about_ca_system_score_gemma":0.000024079092,"threshold_uncertainty_score":0.33160233},"labels":[],"label_agreement":null},{"id":"W4399914534","doi":"10.1038/s42003-024-06420-1","title":"Associative white matter tracts selectively predict sensorimotor learning","year":2024,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Minority Health and Health Disparities; SBE Office of Multidisciplinary Activities; Division of Behavioral and Cognitive Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Directorate for Social, Behavioral and Economic Sciences; Government of Canada; U.S. Department of Health and Human Services; National Institutes of Health; National Science Foundation","keywords":"White matter; Fractional anisotropy; Psychology; Tractography; Associative learning; Lateralization of brain function; Cognitive psychology; Diffusion MRI; Artificial intelligence; Neuroscience; Computer science; Medicine; Magnetic resonance imaging","score_opus":0.08983519086896198,"score_gpt":0.40879287206141246,"score_spread":0.3189576811924505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399914534","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21224089,0.010317551,0.19072874,0.24880892,0.00045934285,0.0044389134,0.0003756168,0.0077444944,0.32488552],"genre_scores_gemma":[0.95888245,0.0006355761,0.03605906,0.0008426292,0.00006351524,0.00020619277,0.0001863898,0.000029164188,0.0030950245],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992491,0.00013292693,0.00017700376,0.00023047277,0.000041766274,0.00016870009],"domain_scores_gemma":[0.9988151,0.00031094177,0.000053847252,0.0006665892,0.00010168667,0.000051829036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012188777,0.000102490005,0.00015939293,0.000111760266,0.00018909859,0.00001890893,0.00023107466,0.000090503076,0.000081202146],"category_scores_gemma":[0.000108818545,0.00009226448,0.00006696635,0.00031365725,0.00017458068,0.00005746188,0.0001477346,0.0006161928,0.00022840819],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044989618,0.0004644494,0.8457734,0.000096327116,0.00030599246,0.000010899339,0.001374896,0.00000906933,0.03646188,0.050435726,0.03314341,0.031878967],"study_design_scores_gemma":[0.0002474328,0.00023365434,0.2495104,0.0001110865,0.00011962451,0.00012241285,0.00010033507,0.0065344484,0.001047324,0.0071746754,0.7345927,0.00020590372],"about_ca_topic_score_codex":0.000006159432,"about_ca_topic_score_gemma":0.0000015267732,"teacher_disagreement_score":0.7466416,"about_ca_system_score_codex":0.00009882327,"about_ca_system_score_gemma":0.000060522612,"threshold_uncertainty_score":0.37624365},"labels":[],"label_agreement":null},{"id":"W4399918218","doi":"10.1002/hbm.26758","title":"Can gray matter loss in early adolescence be explained by white matter growth?","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; Alberta Children's Hospital; Baycrest Hospital; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Gray (unit); White matter; Psychology; Developmental psychology; Medicine; Magnetic resonance imaging; Nuclear medicine; Radiology","score_opus":0.0398145550865226,"score_gpt":0.31325661813882133,"score_spread":0.27344206305229873,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399918218","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7742954,0.000176302,0.0232757,0.19495973,0.00008229837,0.0009844973,0.000049316375,0.00078311155,0.0053936765],"genre_scores_gemma":[0.97553176,0.000006731943,0.0016862552,0.017290879,0.00009785151,0.00013217189,0.00005284293,0.000058424954,0.0051430943],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99873024,0.00002959898,0.0002777009,0.0004643478,0.00016904902,0.00032906723],"domain_scores_gemma":[0.99944955,0.000044954137,0.000038817874,0.00034993343,0.000027924822,0.000088793575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014297306,0.00018413404,0.00020192396,0.00022087496,0.000107243635,0.00007581372,0.00016433724,0.000058205766,0.000286366],"category_scores_gemma":[0.000011463536,0.00018137756,0.00006439253,0.00033746974,0.00009639265,0.000115900235,0.000075828386,0.00039219766,0.00014806517],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000007704298,0.00006405954,0.54053307,0.00040251587,0.000010970872,0.00016656645,0.0014072877,8.6575994e-7,0.12214688,0.0025981811,0.33256024,0.0001016635],"study_design_scores_gemma":[0.00055214163,0.00005412126,0.9431263,0.0016687788,0.000019653711,0.00012375123,0.00016882841,0.00013991598,0.001153061,0.009595814,0.04294473,0.00045289722],"about_ca_topic_score_codex":0.0000553467,"about_ca_topic_score_gemma":0.000009576031,"teacher_disagreement_score":0.40259326,"about_ca_system_score_codex":0.00007980737,"about_ca_system_score_gemma":0.00001663572,"threshold_uncertainty_score":0.73963624},"labels":[],"label_agreement":null},{"id":"W4399980465","doi":"10.1002/mrm.30195","title":"Characterization of the orientation dependence of magnetization transfer measures in single and crossing‐fiber white matter","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Voxel; Diffusion MRI; Homogeneity (statistics); Characterization (materials science); Orientation (vector space); Magnetization transfer; White matter; Nuclear magnetic resonance; Materials science; Physics; Mathematics; Optics; Magnetic resonance imaging; Computer science; Geometry; Artificial intelligence; Statistics; Medicine","score_opus":0.032957997790857535,"score_gpt":0.3076968442036872,"score_spread":0.27473884641282964,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399980465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98848546,0.0024415583,0.004201228,0.0037710431,0.000049720627,0.0004986885,0.000006111763,0.000019445557,0.00052672933],"genre_scores_gemma":[0.99776894,0.00032789208,0.0008408911,0.00019703033,0.000025888416,0.000039222603,0.000009373502,0.000014113112,0.0007766785],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990707,0.000032923755,0.000373942,0.00020718308,0.00021889132,0.000096335476],"domain_scores_gemma":[0.9996609,0.000039412083,0.000037377948,0.00018565646,0.00005729316,0.000019352265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016929308,0.00008500034,0.00018170442,0.00013600013,0.000018845176,0.000008369447,0.000054585664,0.000041727235,0.00013638081],"category_scores_gemma":[0.00004878797,0.000060043953,0.000016937913,0.00058504305,0.00029941264,0.00007156493,0.000014978928,0.00012385563,0.0000010128128],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006750902,0.000074882744,0.29369715,0.00036675786,0.000001035699,0.0000064852475,0.0016757572,0.000009093305,0.6055066,0.00030358217,0.00006038097,0.0982308],"study_design_scores_gemma":[0.0005076385,0.00017583901,0.97237843,0.001632989,0.00002177642,0.000024123345,0.00003883378,0.00082804234,0.019356837,0.0004691775,0.0045120995,0.00005420912],"about_ca_topic_score_codex":0.000040184033,"about_ca_topic_score_gemma":0.000021977607,"teacher_disagreement_score":0.6786813,"about_ca_system_score_codex":0.000024028152,"about_ca_system_score_gemma":0.000029512868,"threshold_uncertainty_score":0.24485214},"labels":[],"label_agreement":null},{"id":"W4399985193","doi":"10.1371/journal.pone.0305818","title":"A comparison of white matter microstructure and correlates with neuropsychological measures in younger and older adults","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Francis Xavier University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Corpus callosum; Neuropsychology; White matter; Diffusion MRI; Young adult; Psychology; Population; Cognition; Medicine; Audiology; Gerontology; Magnetic resonance imaging; Psychiatry; Neuroscience","score_opus":0.05820287161750912,"score_gpt":0.32567462806126357,"score_spread":0.2674717564437544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399985193","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.996206,0.0010661032,0.00020835447,0.0020103706,0.0000045933507,0.00028410094,0.0000065487116,0.00005615649,0.00015779414],"genre_scores_gemma":[0.9940778,0.000088802604,0.0053783623,0.00032761,0.0000111491045,0.000020047333,0.000004166912,0.0000131831075,0.000078894016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99953073,0.000008474476,0.00010963083,0.00019824765,0.00007965467,0.00007325334],"domain_scores_gemma":[0.99979424,0.000022683565,0.000020358328,0.00010762347,0.000023953911,0.000031156193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001976154,0.00007124334,0.00017305234,0.000047625796,0.000017592749,0.000008255428,0.000021625172,0.000034211233,0.000018934783],"category_scores_gemma":[0.0000065518198,0.00004901056,0.0000080862965,0.000096473996,0.000087007975,0.000032000302,0.00002544743,0.0001966699,0.0000014465843],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018214193,0.0003154614,0.9443444,0.00026730614,0.000019535559,0.000018308128,0.0005500294,4.1657958e-7,0.053398617,0.000052891064,0.00022803032,0.00062287995],"study_design_scores_gemma":[0.0004073584,0.0001733469,0.993067,0.0010485044,0.00007318809,0.00006914186,0.00003581061,0.00045611506,0.0043566073,0.00017310414,0.000075902964,0.000063891115],"about_ca_topic_score_codex":0.0000024524209,"about_ca_topic_score_gemma":0.0000011154301,"teacher_disagreement_score":0.04904201,"about_ca_system_score_codex":0.000003655061,"about_ca_system_score_gemma":0.0000034820955,"threshold_uncertainty_score":0.19985926},"labels":[],"label_agreement":null},{"id":"W4399995661","doi":"10.1162/imag_a_00221","title":"Imaging of the superficial white matter in health and disease","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; White (mutation); Medicine; Magnetic resonance imaging; Radiology; Chemistry","score_opus":0.03323279792111178,"score_gpt":0.3574973428935282,"score_spread":0.3242645449724164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399995661","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6048298,0.00246908,0.01731148,0.37266082,0.0005495562,0.0009669507,0.000035487006,0.00033763846,0.0008392222],"genre_scores_gemma":[0.98771924,0.000047732272,0.00058781565,0.011439929,0.000019482486,0.000011532968,4.500092e-7,0.000012352675,0.00016148388],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920946,0.00002111744,0.00016098005,0.0003017331,0.00013776486,0.00016896505],"domain_scores_gemma":[0.99956465,0.000023060496,0.000027054895,0.0002530206,0.000012850934,0.000119377546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000106144165,0.000070864924,0.0000861795,0.00009060671,0.00007039771,0.000037604237,0.0001132106,0.0000034625791,0.0000040114433],"category_scores_gemma":[0.00008376238,0.000051478186,0.000028686629,0.00042509782,0.00028000018,0.00013029632,0.00010034968,0.00015214086,0.0000015546366],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000047618782,0.000023647384,0.98597544,0.00011704299,1.1187224e-7,0.000025558182,0.000110296576,0.000009523301,0.008885311,0.0007672301,0.0013251541,0.0027559313],"study_design_scores_gemma":[0.00010979579,0.00001050839,0.95068663,0.00046006846,0.000005763438,0.00015930929,0.000025757263,0.034735564,0.00046665338,0.0022424231,0.011015592,0.00008194983],"about_ca_topic_score_codex":0.000015809088,"about_ca_topic_score_gemma":3.978668e-7,"teacher_disagreement_score":0.38288945,"about_ca_system_score_codex":0.000020842315,"about_ca_system_score_gemma":0.00014908674,"threshold_uncertainty_score":0.20992194},"labels":[],"label_agreement":null},{"id":"W4400051699","doi":"10.1002/hbm.26771","title":"Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"NIH Blueprint for Neuroscience Research; National Institute of Neurological Disorders and Stroke","keywords":"Cingulum (brain); Precuneus; Tractography; Neuroscience; Psychology; Posterior cingulate; Population; Human brain; Resting state fMRI; Neuroimaging; Fractional anisotropy; Anatomy; Diffusion MRI; Cognition; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.1650740918079777,"score_gpt":0.37170056318072503,"score_spread":0.20662647137274734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400051699","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9512714,0.0020618893,0.010510137,0.034859397,0.000068957015,0.0006370721,0.000032453383,0.0003604025,0.00019825636],"genre_scores_gemma":[0.99731624,0.000022812965,0.0005733044,0.0012937696,0.0006205128,0.000052295025,0.000015652551,0.000022998292,0.00008241625],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99902934,0.000096620475,0.00019218611,0.000311129,0.00017666258,0.00019408356],"domain_scores_gemma":[0.9975749,0.0018582451,0.0000496662,0.000446696,0.000027158578,0.00004328926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045035506,0.00014666936,0.0001478614,0.000025608624,0.000780353,0.00014884265,0.00023393858,0.000037670437,0.000023066375],"category_scores_gemma":[0.00019210976,0.000073353185,0.000064017004,0.0001856757,0.00028991897,0.000104194856,0.00014690509,0.00053689914,0.0000033926942],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041519863,0.000035429137,0.37045047,0.0005038063,0.00046353863,0.00010441424,0.020654546,0.00007737245,0.4343847,0.037383605,0.049599268,0.08630133],"study_design_scores_gemma":[0.00020108347,0.00006088887,0.9052147,0.0010703196,0.000101941354,0.00007791052,0.0008467033,0.008067077,0.001144627,0.05120863,0.031764828,0.00024127883],"about_ca_topic_score_codex":0.00011072555,"about_ca_topic_score_gemma":0.00002172039,"teacher_disagreement_score":0.53476423,"about_ca_system_score_codex":0.000033540004,"about_ca_system_score_gemma":0.00003681645,"threshold_uncertainty_score":0.6001923},"labels":[],"label_agreement":null},{"id":"W4400051904","doi":"10.1002/hbm.26693","title":"Surface‐based morphometry of the corpus callosum in young children of ages 1–5","year":2024,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Dental and Craniofacial Research; Wellcome Trust; Saban Research Institute; National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; Bill and Melinda Gates Foundation","keywords":"Corpus callosum; Sexual dimorphism; White matter; Psychology; Cognition; Brain morphometry; Neuroscience; Anatomy; Developmental psychology; Biology; Medicine; Magnetic resonance imaging; Zoology","score_opus":0.0702995056777756,"score_gpt":0.35040828119709005,"score_spread":0.28010877551931446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400051904","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99227715,0.0002775553,0.0039794915,0.00204959,0.000029387964,0.00038292946,0.000016189742,0.00010195714,0.00088573765],"genre_scores_gemma":[0.99678624,0.0000079765705,0.0026101186,0.0002048165,0.000022826012,0.000009896789,0.000013443947,0.000018846578,0.00032584846],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99930644,0.000025193123,0.0002427144,0.00017577872,0.00013599779,0.00011389659],"domain_scores_gemma":[0.9994677,0.00008958963,0.00006671992,0.0003300969,0.000024740426,0.00002119704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016357085,0.000081438426,0.00017275814,0.00013456552,0.000041910534,0.000006521171,0.00012748528,0.00003362139,0.000022234775],"category_scores_gemma":[0.000054630986,0.00006366094,0.00008103611,0.00049991795,0.0001129081,0.000025911844,0.000052841988,0.00019749878,0.0000010910062],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003740904,0.00006271822,0.2595803,0.0002171812,0.000014556913,0.0000058062433,0.00014577436,0.00010266067,0.73388666,0.0042194277,0.0014459083,0.0003152241],"study_design_scores_gemma":[0.0002932363,0.00003082793,0.9787662,0.0008466662,0.000017277987,0.000018490262,0.00002599709,0.0011081315,0.016157253,0.0017472507,0.0009091486,0.0000795402],"about_ca_topic_score_codex":0.000108859116,"about_ca_topic_score_gemma":0.0000120533805,"teacher_disagreement_score":0.7191859,"about_ca_system_score_codex":0.000031025913,"about_ca_system_score_gemma":0.000028202221,"threshold_uncertainty_score":0.25960177},"labels":[],"label_agreement":null},{"id":"W4400135600","doi":"10.3389/fradi.2024.1416672","title":"Feasibility study to unveil the potential: considerations of constrained spherical deconvolution tractography with unsedated neonatal diffusion brain MRI data","year":2024,"lang":"en","type":"article","venue":"Frontiers in Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"European Commission; Wellcome Trust","keywords":"Deconvolution; Tractography; Diffusion MRI; Diffusion; Medicine; Medical physics; Computer science; Radiology; Physics; Magnetic resonance imaging; Algorithm; Thermodynamics","score_opus":0.04914655114847281,"score_gpt":0.3503692760602306,"score_spread":0.3012227249117578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400135600","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4440247,0.00032545792,0.5431165,0.010627961,0.00016287065,0.0014737459,0.000108203174,0.00012902106,0.00003148151],"genre_scores_gemma":[0.9200466,0.000036781712,0.07921738,0.00042734493,0.0000324193,0.00005372864,0.00015118779,0.00001547577,0.000019068035],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987349,0.00016259655,0.00031718932,0.00049839565,0.000109482105,0.00017744381],"domain_scores_gemma":[0.99888366,0.00018498991,0.00005137631,0.0007634951,0.000048601345,0.00006784817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032262632,0.00012692921,0.00029921695,0.00014027444,0.00007378403,0.000012408347,0.00017955509,0.000053534033,0.000024161218],"category_scores_gemma":[0.00014882363,0.00008628969,0.000039847142,0.0005154795,0.0004285647,0.00007372614,0.00008128311,0.00029112882,9.073429e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022362487,0.0036464178,0.69074756,0.00017468091,0.0006061845,0.00087758974,0.0033875434,0.0014915426,0.032798707,0.004777988,0.23492444,0.024331119],"study_design_scores_gemma":[0.008567446,0.005776554,0.7518606,0.00032491572,0.00087298243,0.0034554515,0.010692742,0.16512403,0.0009708123,0.022507448,0.02889781,0.00094919995],"about_ca_topic_score_codex":0.000051936982,"about_ca_topic_score_gemma":0.000060369122,"teacher_disagreement_score":0.4760219,"about_ca_system_score_codex":0.000046955083,"about_ca_system_score_gemma":0.00013074114,"threshold_uncertainty_score":0.35187915},"labels":[],"label_agreement":null},{"id":"W4400336623","doi":"10.1038/s41537-024-00478-w","title":"A systematic review of structural and functional magnetic resonance imaging studies on the neurobiology of depressive symptoms in schizophrenia spectrum disorders","year":2024,"lang":"en","type":"review","venue":"Schizophrenia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mental Health Research Canada; University of Toronto","funders":"","keywords":"PsycINFO; Neuroimaging; Functional magnetic resonance imaging; Major depressive disorder; Depression (economics); Cochrane Library; MEDLINE; Schizophrenia (object-oriented programming); Brain Structure and Function; Psychology; Systematic review; Magnetic resonance imaging; Diffusion MRI; Psychiatry; Depressive symptoms; Meta-analysis; Clinical psychology; Medicine; Neuroscience; Cognition; Internal medicine; Radiology","score_opus":0.03790875485051529,"score_gpt":0.3469683465234314,"score_spread":0.3090595916729161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400336623","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000262217,0.9956267,0.0000068367212,0.0008101995,0.00013424306,0.002976961,0.00009060769,0.000058167097,0.000034054214],"genre_scores_gemma":[0.0013258967,0.9974127,0.00026178177,0.00015703971,0.00005190327,0.00065871316,0.000027547943,0.000057584948,0.00004686828],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.99741787,0.00024037527,0.0013309035,0.00057883334,0.00021486131,0.0002171419],"domain_scores_gemma":[0.99786603,0.0005994664,0.0006927183,0.0007441483,0.00005424411,0.00004336186],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00026881104,0.00045048224,0.0023918648,0.00028214417,0.000055952103,0.0000089120995,0.00022598832,0.000076490905,0.000011258394],"category_scores_gemma":[0.00046761776,0.00025270163,0.0003402166,0.000626116,0.0004237355,0.000031838863,0.00020589333,0.0006992386,0.000005630545],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079961945,0.000027863283,0.000024899718,0.9506507,0.00013129067,0.000010881892,0.000022583472,4.0369758e-7,0.0000046936384,0.015895393,0.0002121598,0.032939184],"study_design_scores_gemma":[0.00044380972,0.0001836764,0.00021634971,0.985002,0.0034386353,0.0002437176,0.000011736477,0.000038173494,0.000008923812,0.0072154915,0.0029257315,0.0002717457],"about_ca_topic_score_codex":0.0000041115436,"about_ca_topic_score_gemma":0.0000052941787,"teacher_disagreement_score":0.034351327,"about_ca_system_score_codex":0.000054459662,"about_ca_system_score_gemma":0.00013727168,"threshold_uncertainty_score":0.99999255},"labels":[],"label_agreement":null},{"id":"W4400395422","doi":"10.1101/2024.07.05.602300","title":"Motor training improves impaired cortico-cerebellar connectivity in cerebellar ataxia","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Cerebellar Degeneration; Cerebellum; Neuroscience; Degeneration (medical); Motor learning; Cerebellar diseases; Medicine; Physical medicine and rehabilitation; Psychology; Pathology","score_opus":0.044341167842959245,"score_gpt":0.2893026463364276,"score_spread":0.24496147849346836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400395422","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9892288,0.001758086,0.0024067631,0.0013799102,0.00058363366,0.0024161488,0.00035319073,0.0018351646,0.000038343092],"genre_scores_gemma":[0.9778388,0.0003866188,0.019944716,0.00041373086,0.0004417205,0.0006645597,0.0000012389888,0.00028294706,0.000025665642],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.996283,0.00008839054,0.0008031193,0.0016493276,0.00040431964,0.00077182666],"domain_scores_gemma":[0.99699366,0.00012584504,0.00036136655,0.0018659997,0.00026610252,0.00038703688],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000507223,0.00073382905,0.0010303367,0.00048622725,0.00012983629,0.00014769296,0.00041983378,0.00057113287,0.000028593693],"category_scores_gemma":[0.00037018966,0.00078040524,0.00029388964,0.0007631861,0.00019985872,0.00009499825,0.00083175785,0.0020301268,0.000059358004],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000075011696,0.00027922014,0.0057860524,0.0011668125,0.00012514164,0.00033298478,0.00003232526,0.000012789045,0.99054646,0.0011441038,0.00045557195,0.00004349823],"study_design_scores_gemma":[0.0030265127,0.00064173987,0.31426942,0.005323885,0.0011798415,0.0000015360222,0.000036024092,0.014767514,0.6219541,0.0005750532,0.034760084,0.0034643174],"about_ca_topic_score_codex":0.00009279814,"about_ca_topic_score_gemma":0.0000048620564,"teacher_disagreement_score":0.3685924,"about_ca_system_score_codex":0.0005607816,"about_ca_system_score_gemma":0.00093372964,"threshold_uncertainty_score":0.9994647},"labels":[],"label_agreement":null},{"id":"W4400491270","doi":"10.1016/j.compbiomed.2024.108811","title":"Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors","year":2024,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; Genentech; National Institutes of Health; IXICO; H. Lundbeck A/S; Servier; Eisai; Institució Catalana de Recerca i Estudis Avançats; Northern California Institute for Research and Education; Ministerio de Ciencia, Innovación y Universidades; Ministerio de Ciencia e Innovación; Pfizer; Biogen; BioClinica; Nvidia; F. Hoffmann-La Roche; Alzheimer's Society; University of Southern California; GlaxoSmithKline; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Artificial intelligence; Computer science; Segmentation; Pipeline (software); Pattern recognition (psychology); Neuroimaging; Magnetic resonance imaging; Similarity (geometry); Brain atlas; Brain tissue; Prior probability; Medicine; Radiology; Bayesian probability; Biomedical engineering; Image (mathematics)","score_opus":0.0551296310800513,"score_gpt":0.396634208431548,"score_spread":0.3415045773514967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400491270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43049827,0.0016007139,0.5624568,0.0044873906,0.00011569074,0.00026187793,0.0000018907214,0.0005490462,0.000028301747],"genre_scores_gemma":[0.92208785,0.00014521752,0.07686391,0.0006343291,0.00013573737,0.000010346551,0.00009184892,0.000015824518,0.00001494391],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992039,0.000049794882,0.00018744297,0.0003640237,0.000047012676,0.00014782623],"domain_scores_gemma":[0.99946797,0.00024131779,0.00005107686,0.00015355754,0.000028053597,0.00005799586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015111231,0.00011753382,0.00023224035,0.00014009101,0.00007819852,0.000007956266,0.000052809457,0.00008532918,0.000006496766],"category_scores_gemma":[0.00006805512,0.000086028784,0.000011245763,0.00024734595,0.00024533793,0.00004200253,0.000040057894,0.00031852073,0.0000010736364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020460648,0.00008481753,0.04468097,0.00030635588,0.0000800329,0.00023441622,0.0012985718,0.0004170465,0.6697771,0.0073205936,0.00047565214,0.27511984],"study_design_scores_gemma":[0.0013384129,0.00088650954,0.026468176,0.0012101716,0.00012330622,0.00021980572,0.00012445505,0.9539288,0.0035453383,0.0028313792,0.00908408,0.00023956114],"about_ca_topic_score_codex":0.00015090316,"about_ca_topic_score_gemma":0.000006733067,"teacher_disagreement_score":0.9535118,"about_ca_system_score_codex":0.0000381878,"about_ca_system_score_gemma":0.00002446398,"threshold_uncertainty_score":0.3508152},"labels":[],"label_agreement":null},{"id":"W4400524585","doi":"10.3174/ajnr.a8297","title":"Fractional Anisotropy is a More Sensitive Diagnostic Biomarker Than Mean Kurtosis for Patients with Parkinson Disease with Cognitive Dysfunction: A Diffusional Kurtosis Map Tract-Based Spatial Statistics Study","year":2024,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Kurtosis; Medicine; Fractional anisotropy; Biomarker; Parkinson's disease; Disease; Statistics; Diffusion MRI; Internal medicine; Radiology; Magnetic resonance imaging; Mathematics","score_opus":0.02171088772215245,"score_gpt":0.3148241680250375,"score_spread":0.293113280302885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400524585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6564207,0.000020220617,0.33897814,0.0028481213,0.00010015782,0.00079460075,0.0007902729,0.000045213405,0.0000025310214],"genre_scores_gemma":[0.98580045,0.000026410597,0.011979952,0.0016283866,0.00018842937,0.0001424404,0.0001562347,0.00006671568,0.000010967966],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99834365,0.00014367356,0.0003863024,0.00045775613,0.00040874592,0.00025988708],"domain_scores_gemma":[0.9963914,0.0020901235,0.00042004877,0.00017781463,0.0006281634,0.00029245106],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008067034,0.00027992163,0.0005141678,0.00026372753,0.00014369642,0.000027225376,0.0000794739,0.00002849971,0.000029568666],"category_scores_gemma":[0.00022254493,0.00019694258,0.000122024845,0.00032602772,0.0005021189,0.00010047641,0.000018572646,0.00036625296,0.0000023958698],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.021452555,0.005156564,0.9382613,0.00009809144,0.00081751164,0.00204001,0.0005848027,0.00011329606,0.0002999929,0.000081909595,0.0023044404,0.028789554],"study_design_scores_gemma":[0.0037294836,0.020323355,0.967666,0.00026658643,0.0014660631,0.0004113879,0.00045019874,0.0031358856,0.00005976411,0.000101067446,0.0021419479,0.0002482802],"about_ca_topic_score_codex":0.000029203171,"about_ca_topic_score_gemma":0.0000047771955,"teacher_disagreement_score":0.32937974,"about_ca_system_score_codex":0.00008618549,"about_ca_system_score_gemma":0.00030911583,"threshold_uncertainty_score":0.8031086},"labels":[],"label_agreement":null},{"id":"W4400642964","doi":"10.1162/imag_a_00247","title":"Uncovering patterns of white matter degeneration in normal aging: Links between morphometry and microstructure","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Degeneration (medical); Psychology; Biology; Pathology; Medicine; Magnetic resonance imaging","score_opus":0.026552404324141014,"score_gpt":0.3235926997866115,"score_spread":0.29704029546247046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400642964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96162975,0.00013955358,0.03493833,0.002865625,0.00009648961,0.00014439924,0.000026335849,0.00008865052,0.000070854774],"genre_scores_gemma":[0.99532855,0.0000370178,0.0033659148,0.0010706187,0.00005254779,0.000007565799,0.000005696339,0.000017878298,0.0001142043],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991375,0.000010931524,0.00019150169,0.00035555614,0.00013225524,0.00017222381],"domain_scores_gemma":[0.9996702,0.000028601637,0.000037016063,0.00019150857,0.000020737863,0.000051935207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008497992,0.00010163661,0.0001274353,0.00022990044,0.00006578743,0.0000537202,0.0000905369,0.000027497801,0.0000068427053],"category_scores_gemma":[0.000020080073,0.00009526483,0.00002545214,0.00041483497,0.000094098876,0.00023525911,0.00012246046,0.00032077354,0.0000012210949],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001131325,0.0000049589034,0.7438418,0.00007438498,2.7197717e-7,0.000020337162,0.000073287745,0.00005027949,0.25442958,0.000019581974,0.000053058175,0.0014313237],"study_design_scores_gemma":[0.00011393538,0.000017543123,0.92918944,0.00019316676,0.000012068066,0.00017364637,0.000009151383,0.002950124,0.06508406,0.00019531409,0.001964593,0.00009697095],"about_ca_topic_score_codex":0.00001727455,"about_ca_topic_score_gemma":9.218065e-7,"teacher_disagreement_score":0.18934551,"about_ca_system_score_codex":0.000021632819,"about_ca_system_score_gemma":0.00002545513,"threshold_uncertainty_score":0.38847873},"labels":[],"label_agreement":null},{"id":"W4400822590","doi":"10.3389/fnins.2024.1391407","title":"White matter microstructure, traumatic brain injury, and disruptive behavior disorders in girls and boys","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut national de psychiatrie légale Philippe-Pinel; Université de Montréal; Université de Sherbrooke; McGill University","funders":"National Institute on Drug Abuse; National Institute of Mental Health; Université de Sherbrooke; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health","keywords":"White matter; Psychology; Clinical psychology; Medicine; Developmental psychology; Magnetic resonance imaging","score_opus":0.022922172466045075,"score_gpt":0.33934897885010357,"score_spread":0.3164268063840585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400822590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9785534,0.00034179067,0.013737679,0.0060142353,0.00026504367,0.0007504943,0.000028978382,0.00008100873,0.00022734496],"genre_scores_gemma":[0.9880675,0.00020155095,0.0099732755,0.0013096584,0.000008682117,0.000098732984,0.0000018580623,0.000018252813,0.0003204695],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990611,0.000019842508,0.00016166108,0.0004595183,0.00009527503,0.00020258437],"domain_scores_gemma":[0.9997201,0.000021466036,0.000021883518,0.00016648517,0.0000048336724,0.00006525724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000079647936,0.00011846611,0.00015426817,0.00023256229,0.00004568896,0.00005622404,0.00008569491,0.00003356658,0.0000034788725],"category_scores_gemma":[0.000029688135,0.00010630301,0.000018042494,0.00045669198,0.00034816389,0.00016976777,0.00006387649,0.00024428812,6.9735404e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013595367,0.00004003877,0.9759611,0.00007797386,4.5500383e-7,0.00003036349,0.0004996704,0.0000019587362,0.007535388,0.000113487826,0.0035450973,0.012180907],"study_design_scores_gemma":[0.00017971631,0.00007091851,0.9915669,0.00009285657,0.000009467867,0.00007246143,0.0000932517,0.002376307,0.00015557816,0.0022361623,0.003033152,0.00011322016],"about_ca_topic_score_codex":0.000009487821,"about_ca_topic_score_gemma":0.0000073883584,"teacher_disagreement_score":0.015605844,"about_ca_system_score_codex":0.000028403872,"about_ca_system_score_gemma":0.000017403827,"threshold_uncertainty_score":0.43349108},"labels":[],"label_agreement":null},{"id":"W4400903047","doi":"10.1186/s13041-024-01115-4","title":"The myelin water imaging transcriptome: myelin water fraction regionally varies with oligodendrocyte-specific gene expression","year":2024,"lang":"en","type":"article","venue":"Molecular Brain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Michael Smith Health Research BC; BC Children's Hospital; International Foundation for Research in Paraplegia; Craig H. Neilsen Foundation; National Science Foundation","keywords":"Myelin; Brain atlas; Neuroimaging; Gene expression; Biology; Transcriptome; Human brain; Neuroscience; Gene; Computational biology; Genetics; Central nervous system","score_opus":0.021237354560969424,"score_gpt":0.28844119972183135,"score_spread":0.26720384516086193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400903047","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14690086,0.002020599,0.7784946,0.07068437,0.00011321383,0.000618823,0.000007463994,0.00066697085,0.0004930753],"genre_scores_gemma":[0.9782977,0.00027391617,0.01686329,0.0025206108,0.00018885093,0.00023096194,0.00015104066,0.000108977016,0.0013646648],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985329,0.000053646057,0.00024059745,0.0004818424,0.00032364027,0.0003674118],"domain_scores_gemma":[0.9992337,0.000052897147,0.000021722086,0.0005286554,0.000075951466,0.00008706336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021119317,0.00021425135,0.00016543342,0.000098993914,0.00028643495,0.00014724053,0.00014669728,0.00005358435,0.00005052699],"category_scores_gemma":[0.000008936272,0.000107218504,0.0001083698,0.00012612814,0.00014096202,0.00013504212,0.000047649133,0.00036739072,0.00006764047],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000994904,0.00002835527,0.00002071611,0.000030463456,0.00001981252,0.0003334851,0.00025237596,0.000045850327,0.9877688,0.0009465545,0.0064963363,0.0039577093],"study_design_scores_gemma":[0.00022592809,0.0000326125,0.000046838308,0.00010755021,0.000027437145,0.00028248053,0.00003353163,0.00049286993,0.6982664,0.002161136,0.29819643,0.00012681283],"about_ca_topic_score_codex":0.000006468236,"about_ca_topic_score_gemma":9.24571e-7,"teacher_disagreement_score":0.8313968,"about_ca_system_score_codex":0.00007288105,"about_ca_system_score_gemma":0.00002754308,"threshold_uncertainty_score":0.43722436},"labels":[],"label_agreement":null},{"id":"W4400909329","doi":"10.1073/pnas.2403212121","title":"Sex and mental health are related to subcortical brain microstructure","year":2024,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation","funders":"National Institute of Mental Health; University of California, San Diego","keywords":"Amygdala; Psychology; Anxiety; Neuroscience; Thalamus; Mental health; Brain Structure and Function; Autism; Depression (economics); Diffusion MRI; Neuroimaging; Clinical psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.0518229110192636,"score_gpt":0.39850460994258463,"score_spread":0.346681698923321,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400909329","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73974377,0.00031547647,0.0000061352594,0.25891834,0.000008319328,0.00029891857,0.000025885072,0.000042830896,0.0006403271],"genre_scores_gemma":[0.9919626,0.00004125717,0.0052509145,0.002445243,0.000017404973,0.0000057288244,1.8400317e-7,0.0000034928323,0.00027318834],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992271,0.0000016315505,0.00016426522,0.0001821293,0.00034304144,0.000081825645],"domain_scores_gemma":[0.99979216,0.00003817087,0.00007264161,0.0000050390913,0.000045858247,0.00004612332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032294868,0.00004830457,0.00009540009,0.00008573113,0.00010387954,0.00001263629,0.00012903921,0.000029036039,0.0000038988105],"category_scores_gemma":[0.00013362619,0.00003078101,0.000026428983,0.00050184765,0.00033469775,0.00008748009,0.00007298327,0.00014089078,4.309558e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013493442,0.000027508295,0.013113399,0.00021835984,0.000010508826,2.1197403e-8,0.00042098627,0.0000033693839,0.7990663,0.1555935,0.029055644,0.0024769213],"study_design_scores_gemma":[0.00035874321,0.00029232993,0.3683808,0.0010987463,0.000019303894,0.0004360564,0.00047166456,0.0030592468,0.33639672,0.26632112,0.022979852,0.00018539983],"about_ca_topic_score_codex":9.145597e-7,"about_ca_topic_score_gemma":7.816475e-9,"teacher_disagreement_score":0.46266958,"about_ca_system_score_codex":0.00002488329,"about_ca_system_score_gemma":0.000023040535,"threshold_uncertainty_score":0.12552132},"labels":[],"label_agreement":null},{"id":"W4400932948","doi":"10.1162/imag_a_00259","title":"Tractography from T1-weighted MRI: Empirically exploring the clinical viability of streamline propagation without diffusion MRI","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Alzheimer's Association; National Institute on Aging; National Institute of Diabetes and Digestive and Kidney Diseases; Vanderbilt Memory and Alzheimer's Center; Vanderbilt University Medical Center; Vanderbilt University; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; National Institute of Mental Health; National Institutes of Health; National Science Foundation","keywords":"Tractography; Diffusion MRI; Computer science; Population; Neuroimaging; Limiting; White matter; Artificial intelligence; Magnetic resonance imaging; Medicine; Psychology; Neuroscience; Radiology","score_opus":0.12484921621911774,"score_gpt":0.41529681972330534,"score_spread":0.29044760350418763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400932948","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7861855,0.0000935277,0.20090996,0.011115821,0.00039240674,0.0006441772,0.000029508617,0.00048387356,0.00014525116],"genre_scores_gemma":[0.98809016,0.00021771336,0.010591883,0.0008342079,0.00012549087,0.000076581746,0.000010086196,0.000024607725,0.00002925023],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99809784,0.000090266396,0.00050127023,0.0007039223,0.00038797586,0.00021874122],"domain_scores_gemma":[0.9986147,0.00038748368,0.00011533784,0.0006735769,0.00010256105,0.00010629449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040851164,0.00015747386,0.00022836938,0.00011252067,0.00015561585,0.00006724371,0.0002860894,0.000023211926,0.000008021831],"category_scores_gemma":[0.00029414272,0.00010244299,0.00015191441,0.00088930613,0.0006740659,0.00030547485,0.00011592891,0.0004591717,0.0000032185262],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068814705,0.0005729436,0.49248198,0.00007450394,0.000005597994,0.00003780214,0.00022450463,0.000018389272,0.40974844,0.0005275278,0.00055419,0.095685296],"study_design_scores_gemma":[0.0004315214,0.00023999093,0.76771134,0.0003550053,0.00012427152,0.00006276012,0.000046469082,0.16118993,0.040261302,0.005128475,0.024190325,0.0002586063],"about_ca_topic_score_codex":0.00003470221,"about_ca_topic_score_gemma":0.0000015479918,"teacher_disagreement_score":0.36948714,"about_ca_system_score_codex":0.000021607888,"about_ca_system_score_gemma":0.00008707113,"threshold_uncertainty_score":0.41775036},"labels":[],"label_agreement":null},{"id":"W4401314990","doi":"10.1016/j.neuroimage.2024.120775","title":"Evaluation of cervical spinal cord atrophy using a modified SIENA approach","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institutes of Health; National Institute for Nanotechnology; Dodd-Walls Centre; Central European Initiative; U.S. Department of Defense","keywords":"Atrophy; Spinal cord; Medicine; Magnetic resonance imaging; Multiple sclerosis; Sample size determination; Nuclear medicine; Radiology; Physical medicine and rehabilitation; Pathology; Mathematics; Statistics","score_opus":0.2849929251162904,"score_gpt":0.44899335193755213,"score_spread":0.16400042682126176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401314990","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.75305927,0.00052674534,0.22849749,0.0006670904,0.00011726859,0.0010779352,0.000020827156,0.00047246722,0.01556091],"genre_scores_gemma":[0.9687515,0.000016883736,0.030837357,0.00015271778,0.000105619794,0.000040657906,0.000011793484,0.000035049117,0.00004840617],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986496,0.000060000904,0.00022574844,0.00036688813,0.0005442577,0.0001535293],"domain_scores_gemma":[0.99929154,0.00002383049,0.0000469489,0.00038188827,0.00018982864,0.000065977714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029533036,0.000117654476,0.00017649564,0.00012479452,0.00004236188,0.000020415651,0.000086075626,0.000039726543,0.00003076155],"category_scores_gemma":[0.00007795213,0.000106518375,0.0001016498,0.00038244523,0.00008673924,0.000085362415,0.00005192772,0.00023526499,0.0000076101055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049807806,0.00059900305,0.00031854914,0.0007787706,0.00005567206,0.00009674019,0.00006929722,0.001174234,0.80439746,0.012626582,0.0009773427,0.17840825],"study_design_scores_gemma":[0.00066141784,0.00069964316,0.0067854407,0.0001394224,0.00057321595,0.0003909582,0.000016417827,0.9733082,0.0101957405,0.0051319213,0.0019248422,0.00017274465],"about_ca_topic_score_codex":0.000008490089,"about_ca_topic_score_gemma":7.57714e-8,"teacher_disagreement_score":0.972134,"about_ca_system_score_codex":0.00004926919,"about_ca_system_score_gemma":0.00011659877,"threshold_uncertainty_score":0.43436933},"labels":[],"label_agreement":null},{"id":"W4401367286","doi":"10.4103/nrr.nrr-d-23-01392","title":"A radiomics approach for predicting gait freezing in Parkinson’s disease based on resting-state functional magnetic resonance imaging indices: A cross-sectional study","year":2024,"lang":"en","type":"article","venue":"Neural Regeneration Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Science Foundation of Liaoning Province","keywords":"Magnetic resonance imaging; Parkinson's disease; Gait; Medicine; Disease; Functional magnetic resonance imaging; Physical medicine and rehabilitation; Gait analysis; Pathology; Radiology","score_opus":0.1611351498607611,"score_gpt":0.4212158446894742,"score_spread":0.2600806948287131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401367286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94725394,0.001284625,0.045185436,0.0017897248,0.00014610332,0.0035742975,0.00010413702,0.00039666545,0.0002650828],"genre_scores_gemma":[0.988993,0.000022895829,0.006923015,0.00021342255,0.00043248662,0.00239629,0.00019865637,0.000060687566,0.00075958093],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99714917,0.00017822834,0.0004420896,0.0009001774,0.0008828698,0.0004474593],"domain_scores_gemma":[0.9985274,0.00058028684,0.00004761329,0.0003871421,0.00027906982,0.00017847358],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013521085,0.00017893636,0.00016124213,0.00065504207,0.00046891207,0.00031833962,0.00014448176,0.000043032232,0.000015483864],"category_scores_gemma":[0.0007298048,0.00016963472,0.00007393068,0.00091729016,0.0001339223,0.00019325863,0.000059699913,0.0007621132,0.0000034453592],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012999091,0.0007116408,0.9226672,0.00023431364,0.0000050923377,0.00012660232,0.00011942123,0.049369205,0.008432706,0.00046981036,0.0010838622,0.015480216],"study_design_scores_gemma":[0.00084954896,0.0003459348,0.2779293,0.00008890911,0.0000073568103,0.000014352956,0.000021911497,0.71752363,0.0004184127,0.00029428725,0.0024067934,0.00009954435],"about_ca_topic_score_codex":0.00004650536,"about_ca_topic_score_gemma":0.000013677176,"teacher_disagreement_score":0.6681544,"about_ca_system_score_codex":0.000331664,"about_ca_system_score_gemma":0.00032783113,"threshold_uncertainty_score":0.6917503},"labels":[],"label_agreement":null},{"id":"W4401385585","doi":"10.3389/fnins.2024.1440653","title":"Exploring white matter microstructural alterations in mild cognitive impairment: a multimodal diffusion MRI investigation utilizing diffusion kurtosis and free-water imaging","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Barrow Neurological Foundation; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Kurtosis; Diffusion MRI; White matter; Diffusion imaging; Cognitive impairment; Diffusion; Magnetic resonance imaging; Cognition; Psychology; Nuclear magnetic resonance; Neuroscience; Medicine; Physics; Radiology; Mathematics; Statistics","score_opus":0.05171655342244838,"score_gpt":0.2997681900204657,"score_spread":0.2480516365980173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401385585","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9741153,0.00013598254,0.020385804,0.0041319644,0.00042893345,0.0006044265,0.000018514707,0.00012675567,0.000052292733],"genre_scores_gemma":[0.98341787,0.00021802356,0.014916951,0.00113272,0.000034746605,0.00016470227,0.000017619182,0.000025789843,0.00007158636],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99854654,0.00003938658,0.00027306107,0.00063685013,0.00017611617,0.0003280738],"domain_scores_gemma":[0.9996115,0.000027990984,0.00003179761,0.00020901498,0.000023398718,0.00009629243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011410856,0.00017516577,0.00016913186,0.00046845787,0.00017127191,0.00012546529,0.00011656651,0.000027150454,0.000005142848],"category_scores_gemma":[0.000036229536,0.00014609842,0.00003547349,0.0004890448,0.00025340088,0.0007278078,0.0002041427,0.00031140246,0.0000018792193],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003508987,0.00003836221,0.7680692,0.000073098585,8.092743e-7,0.00004849905,0.0022924338,0.000021241849,0.22711153,0.000023296907,0.00036489134,0.0019215571],"study_design_scores_gemma":[0.00077930215,0.000048753453,0.8177681,0.00083260797,0.000018738965,0.00008970681,0.0004947371,0.15264726,0.025792768,0.0010809813,0.00022690611,0.00022014735],"about_ca_topic_score_codex":0.00004615759,"about_ca_topic_score_gemma":0.0000050106473,"teacher_disagreement_score":0.20131876,"about_ca_system_score_codex":0.00008723838,"about_ca_system_score_gemma":0.000020045967,"threshold_uncertainty_score":0.5957721},"labels":[],"label_agreement":null},{"id":"W4401507606","doi":"10.1101/2024.08.12.607581","title":"Longitudinal deformation based morphometry pipeline to study neuroanatomical differences in structural MRI based on SyN unbiased templates","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Hospital for Sick Children; Ontario Brain Institute","funders":"","keywords":"dBm; Pipeline (software); Segmentation; Magnetic resonance imaging; Brain size; Neuroimaging; Longitudinal study; Volume (thermodynamics); Computer science; Statistical power; Psychology; Artificial intelligence; Neuroscience; Pattern recognition (psychology); Medicine; Mathematics; Statistics; Pathology; Physics; Radiology; Telecommunications","score_opus":0.04383876866835115,"score_gpt":0.3062636692934381,"score_spread":0.26242490062508694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401507606","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98103034,0.00007068979,0.012660794,0.0022638123,0.0003097841,0.0025842532,0.00024179161,0.0008344541,0.0000040733303],"genre_scores_gemma":[0.98132426,0.0000080135,0.016753156,0.0009869528,0.00016350273,0.00062976114,0.0000030229683,0.00012964653,0.0000016682269],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9967268,0.000120741504,0.00077130576,0.0013068597,0.0005900231,0.00048423113],"domain_scores_gemma":[0.9976527,0.0001744803,0.00023301101,0.0013533428,0.00025650192,0.00032997382],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037439485,0.0006466557,0.00079241936,0.0011599363,0.00011788144,0.00016115386,0.0004236408,0.000257657,0.00003821026],"category_scores_gemma":[0.00028719616,0.00058691803,0.00015864958,0.001402789,0.00007576605,0.00006526432,0.0003429989,0.0014801373,0.000041386033],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00130922,0.0032632987,0.8470616,0.0022012957,0.00019140873,0.0014697044,0.000036864094,0.0069536814,0.13564229,0.0006641889,0.0011477399,0.000058720016],"study_design_scores_gemma":[0.0013278765,0.00046108727,0.73711145,0.00094020093,0.00023288354,1.221415e-7,0.0000051471243,0.20587866,0.05315716,0.000017209117,0.0001294321,0.00073877006],"about_ca_topic_score_codex":0.000056163044,"about_ca_topic_score_gemma":0.0000033669178,"teacher_disagreement_score":0.19892499,"about_ca_system_score_codex":0.00038560995,"about_ca_system_score_gemma":0.00035107104,"threshold_uncertainty_score":0.9996582},"labels":[],"label_agreement":null},{"id":"W4401522547","doi":"10.1097/wad.0000000000000642","title":"DXA-Measured Abdominal Adipose Depots and Structural Brain Integrity in Postmenopausal Women","year":2024,"lang":"en","type":"article","venue":"Alzheimer Disease & Associated Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Adipose tissue; Medicine; Abdominal fat; Atrophy; Postmenopausal women; Intra-Abdominal Fat; Brain tissue; Subcutaneous fat; Lesion; Subcutaneous adipose tissue; Magnetic resonance imaging; Internal medicine; Endocrinology; Radiology; Pathology; Obesity; Visceral fat; Insulin resistance","score_opus":0.035195802899079476,"score_gpt":0.3394532787900382,"score_spread":0.30425747589095875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401522547","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.974932,0.005467251,0.00012804502,0.013101292,0.00010348583,0.0045808256,0.000160305,0.00074088963,0.00078588456],"genre_scores_gemma":[0.9967747,0.000080608224,0.0003488043,0.0010042271,0.00003358504,0.0015553538,0.00010436315,0.000046466143,0.00005193312],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984188,0.00008081504,0.00028577572,0.0005186604,0.0002512835,0.00044466113],"domain_scores_gemma":[0.9991296,0.00014401838,0.000058369533,0.00025764664,0.000044671993,0.00036569475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001871897,0.00025309913,0.0002719773,0.0001709881,0.000097548735,0.000059851576,0.0000999113,0.00009111696,0.00005904586],"category_scores_gemma":[0.00024469037,0.00023353125,0.000074406365,0.00045395826,0.00014122244,0.00017858605,0.00006544974,0.0005098027,0.000011788798],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003326918,0.0019205473,0.67311937,0.00036552173,0.0022404734,0.0008942857,0.0027240743,0.000038625974,0.0046102777,0.008175456,0.013676418,0.28890803],"study_design_scores_gemma":[0.0026358396,0.00030870488,0.9413369,0.00029138484,0.00081116636,0.000021747106,0.00028402847,0.0060455496,0.00008747773,0.04120621,0.00637913,0.00059180276],"about_ca_topic_score_codex":0.000119925186,"about_ca_topic_score_gemma":0.00006640086,"teacher_disagreement_score":0.28831622,"about_ca_system_score_codex":0.00014763021,"about_ca_system_score_gemma":0.00018355917,"threshold_uncertainty_score":0.9523128},"labels":[],"label_agreement":null},{"id":"W4401525937","doi":"10.1016/j.mri.2025.110424","title":"Harmonized connectome resampling for variance in voxel sizes","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vanderbilt Kennedy Center, Vanderbilt University Medical Center; Georgia Clinical and Translational Science Alliance; McMaster University; National Institute on Aging; Vanderbilt Institute for Clinical and Translational Research; National Cancer Institute; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University","keywords":"Resampling; Connectome; Variance (accounting); Voxel; Computer science; Statistics; Artificial intelligence; Pattern recognition (psychology); Mathematics; Psychology; Neuroscience; Functional connectivity","score_opus":0.046902943086093454,"score_gpt":0.3656866638133341,"score_spread":0.31878372072724065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401525937","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.095938705,0.055161264,0.75466174,0.06923629,0.0004162551,0.0059772567,0.00006816387,0.0012655009,0.01727483],"genre_scores_gemma":[0.7163443,0.0005667631,0.2700029,0.0047695255,0.0000941741,0.0011854235,0.000016858166,0.000055578075,0.006964498],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987394,0.000016877817,0.00033325976,0.0004573987,0.00010239255,0.00035065506],"domain_scores_gemma":[0.99906844,0.00029561482,0.00005512032,0.00043774574,0.00009640751,0.000046676305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019451726,0.00015473622,0.00028751954,0.00017728796,0.00010017234,0.000035542904,0.00015682644,0.000031463496,0.00002220734],"category_scores_gemma":[0.0003942482,0.00015920585,0.000068802314,0.00049407163,0.00009525537,0.00007580883,0.000062839485,0.00019479622,0.000004080508],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005900827,0.0002728639,0.09098979,0.00034206535,0.0000061195788,0.000071319155,0.00013370151,0.000040666902,0.074570455,0.043580804,0.006214081,0.78318805],"study_design_scores_gemma":[0.005802241,0.00010208534,0.17959581,0.0011963312,0.000060634706,0.00004548653,0.00008100763,0.04765082,0.009218867,0.050889093,0.7049682,0.00038942558],"about_ca_topic_score_codex":0.000037765887,"about_ca_topic_score_gemma":0.000003428303,"teacher_disagreement_score":0.78279865,"about_ca_system_score_codex":0.00007379022,"about_ca_system_score_gemma":0.00007991592,"threshold_uncertainty_score":0.6492227},"labels":[],"label_agreement":null},{"id":"W4401540984","doi":"10.3390/app14167001","title":"MRI Diffusion Connectomics-Based Characterization of Progression in Alzheimer’s Disease","year":2024,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nova Scotia Health Authority; St. Francis Xavier University; Memorial University of Newfoundland","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; St. Francis Xavier University; Canada Foundation for Innovation; National Institute of Biomedical Imaging and Bioengineering; Nova Scotia Research Innovation Trust; Foundation for the National Institutes of Health","keywords":"Connectomics; Diffusion MRI; Disease; Medicine; Biomarker; Neuroscience; Pathology; Psychology; Magnetic resonance imaging; Radiology; Connectome; Functional connectivity; Biology","score_opus":0.06855626450805484,"score_gpt":0.38315750755329625,"score_spread":0.3146012430452414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401540984","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9791107,0.00019007565,0.01551882,0.003319527,0.00004399609,0.00069296686,0.000010621117,0.00019663638,0.00091661816],"genre_scores_gemma":[0.9950956,0.000043218093,0.004502101,0.00019606091,0.000020545052,0.00009821385,0.000029532619,0.000007323856,0.0000074172162],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993222,0.0000064105307,0.00014856673,0.00025388677,0.00016567984,0.00010326797],"domain_scores_gemma":[0.99972534,0.000039041737,0.00004005759,0.00012949898,0.000013907939,0.00005212741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013019964,0.00006488485,0.000096680495,0.00014233818,0.000050957406,0.000017436958,0.000080358324,0.000019437257,0.000015444177],"category_scores_gemma":[0.000008957448,0.000048926962,0.000023667195,0.0005167226,0.00018346266,0.000054181783,0.00002514678,0.00006558179,0.000004385583],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006151604,0.00016252953,0.007910244,0.000070469665,0.000002238147,0.000008492345,0.00006993501,0.00003075475,0.9290196,0.025194533,0.000039872386,0.037429843],"study_design_scores_gemma":[0.0009922948,0.0002946865,0.1685123,0.0013791143,0.00013245497,0.000007164726,0.00006457545,0.19045949,0.61269176,0.01237795,0.012685122,0.00040309047],"about_ca_topic_score_codex":0.0000017008695,"about_ca_topic_score_gemma":3.2704722e-7,"teacher_disagreement_score":0.3163278,"about_ca_system_score_codex":0.000011832174,"about_ca_system_score_gemma":0.00008492457,"threshold_uncertainty_score":0.19951837},"labels":[],"label_agreement":null},{"id":"W4401557770","doi":"10.1002/nbm.5227","title":"Automatic deep learning segmentation of the hippocampus on high‐resolution diffusion magnetic resonance imaging and its application to the healthy lifespan","year":2024,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"MacEwan University; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Canada Foundation for Innovation; University Hospital Foundation; Ministry of Advanced Education, Government of Alberta; Women and Children's Health Research Institute; Children's Health Research Institute","keywords":"Fractional anisotropy; Diffusion MRI; Magnetic resonance imaging; Segmentation; Artificial intelligence; Hippocampus; Computer science; Sørensen–Dice coefficient; Voxel; Population; Pattern recognition (psychology); Image segmentation; Neuroscience; Medicine; Psychology; Radiology","score_opus":0.017071568410379562,"score_gpt":0.3269405340313867,"score_spread":0.30986896562100713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401557770","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9039051,0.009804395,0.010332095,0.073445275,0.00013813106,0.0020443178,0.00000634097,0.00022244272,0.00010193494],"genre_scores_gemma":[0.99595916,0.00054499495,0.0013000509,0.0017792415,0.00010457803,0.0002121373,0.000016720427,0.000019279423,0.000063840096],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898535,0.000058470374,0.00028039704,0.0002753114,0.00024872486,0.0001517232],"domain_scores_gemma":[0.99943686,0.00013237009,0.00006957569,0.00025928102,0.000037237118,0.00006466302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028281752,0.00010678877,0.00014127707,0.00017901017,0.00011356868,0.000008661584,0.000095134485,0.000030391073,0.000012863597],"category_scores_gemma":[0.00012068606,0.000063903135,0.00002187889,0.0007901811,0.00007729886,0.0000358469,0.000058151483,0.00024594076,0.0000075162156],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052989348,0.000068483474,0.004045574,0.0002291142,0.0000018781318,0.0000030496692,0.00060927577,0.00008332045,0.06838703,0.0012260239,0.000439636,0.9248536],"study_design_scores_gemma":[0.0013970726,0.0009847891,0.42815563,0.0023666928,0.000089616806,0.00009893193,0.00046372812,0.53069305,0.003903763,0.0034303549,0.028221935,0.00019443357],"about_ca_topic_score_codex":0.00004941219,"about_ca_topic_score_gemma":0.0000097307175,"teacher_disagreement_score":0.9246592,"about_ca_system_score_codex":0.00009452407,"about_ca_system_score_gemma":0.000028978686,"threshold_uncertainty_score":0.26058945},"labels":[],"label_agreement":null},{"id":"W4401589671","doi":"10.1038/s41390-024-03463-2","title":"Methodological considerations on diffusion MRI tractography in infants aged 0–2 years: a scoping review","year":2024,"lang":"en","type":"review","venue":"Pediatric Research","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tractography; Diffusion MRI; White matter; Neuroimaging; Psychology; Neuroscience; Computer science; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.7491203727056088,"score_gpt":0.6474514212079429,"score_spread":0.10166895149766597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401589671","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000015840084,0.9922531,0.00015598969,0.0007882654,0.00006031708,0.0057546585,0.000029517649,0.00019079122,0.0007515167],"genre_scores_gemma":[0.000011753356,0.9895477,0.007482266,0.00021761988,0.0004268567,0.0020471334,0.000076617645,0.000069522896,0.00012049842],"study_design_codex":"design_other","study_design_gemma":"systematic_review","domain_scores_codex":[0.99565625,0.0012617402,0.00092746335,0.00088921917,0.0007602121,0.0005051374],"domain_scores_gemma":[0.9944398,0.0043044672,0.00014927641,0.0008119959,0.00010743072,0.00018702012],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003359612,0.00031570785,0.0016840304,0.0017425045,0.000113290014,0.00006169241,0.00022601195,0.0002800811,0.00014707002],"category_scores_gemma":[0.0034834307,0.0002293237,0.00048460698,0.0033592908,0.000110727626,0.00004556735,0.00024637624,0.003159401,0.00020532143],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018693057,0.00058225763,0.00012109682,0.35245544,0.000042448635,0.001393143,0.000047217316,2.7998937e-7,0.0000027068354,0.0011527085,0.05019021,0.59399384],"study_design_scores_gemma":[0.00032714292,0.00033533925,0.00022687597,0.51709944,0.0011907065,0.00033272692,0.00000452985,0.000006847789,7.676375e-7,0.0035423972,0.47646636,0.00046686584],"about_ca_topic_score_codex":0.0000109435,"about_ca_topic_score_gemma":0.000003105847,"teacher_disagreement_score":0.59352696,"about_ca_system_score_codex":0.00012642001,"about_ca_system_score_gemma":0.00064880546,"threshold_uncertainty_score":0.9991403},"labels":[],"label_agreement":null},{"id":"W4401693937","doi":"10.1038/s41386-024-01934-y","title":"Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry","year":2024,"lang":"en","type":"review","venue":"Neuropsychopharmacology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute of Mental Health; U.S. Department of Health and Human Services","keywords":"Neuromelanin; Catecholaminergic; Neuroscience; Locus coeruleus; Substantia nigra; Dopaminergic; Biomarker; Psychology; Dopamine; Biology; Central nervous system; Biochemistry","score_opus":0.30786089324811633,"score_gpt":0.5419774707818467,"score_spread":0.23411657753373033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401693937","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0001266256,0.9896432,0.0008118671,0.0017783035,0.0014317036,0.0052629644,0.00006894983,0.00024578918,0.0006305804],"genre_scores_gemma":[0.00006473723,0.9874293,0.008428851,0.0006707727,0.0002198572,0.0021755958,0.00007014257,0.00017752087,0.000763178],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99735856,0.00018743711,0.0006271773,0.0011202473,0.00018191893,0.0005246659],"domain_scores_gemma":[0.9987882,0.0004649768,0.00011341927,0.0003402545,0.00012223686,0.00017091386],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00038255067,0.00040431737,0.0010579856,0.0009481046,0.00011703909,0.000026367554,0.00018242946,0.00023306691,0.000017274884],"category_scores_gemma":[0.00005279596,0.00034325564,0.0001446589,0.0009135537,0.00016879167,0.000022556904,0.00018790712,0.0013063097,0.00008520698],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027284227,0.0005611973,0.000005671697,0.025020484,0.000180213,0.0007233758,0.000046287132,8.261552e-8,0.0009135905,0.005817829,0.054378077,0.91208035],"study_design_scores_gemma":[0.00059329596,0.0003187287,0.00004121969,0.0024958572,0.00046936536,0.00075270346,0.0000036151328,0.000043925585,0.000010813721,0.0015226345,0.99352074,0.00022710908],"about_ca_topic_score_codex":0.0000011316682,"about_ca_topic_score_gemma":0.0000018235352,"teacher_disagreement_score":0.93914264,"about_ca_system_score_codex":0.00011230266,"about_ca_system_score_gemma":0.00043036285,"threshold_uncertainty_score":0.99990195},"labels":[],"label_agreement":null},{"id":"W4401737335","doi":"10.1016/j.mri.2024.110221","title":"Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Diffusion MRI; White matter; Diffusion; Microstructure; Nuclear magnetic resonance; Magnetic resonance imaging; Materials science; Physics; Medicine; Radiology; Thermodynamics; Composite material","score_opus":0.02711337820230662,"score_gpt":0.3125536775083727,"score_spread":0.28544029930606607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401737335","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34586668,0.024397865,0.6258897,0.0026128073,0.000035985224,0.0003205638,0.000033098877,0.00027538923,0.0005678761],"genre_scores_gemma":[0.7616113,0.00079814554,0.23403075,0.0009739836,0.0000790285,0.000028014183,0.00002082901,0.000060405015,0.0023975507],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872136,0.000012118683,0.0002452819,0.0005747923,0.00016902674,0.0002774337],"domain_scores_gemma":[0.99941576,0.00002583447,0.000040302686,0.00038176012,0.000046985217,0.00008938026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000068525114,0.0002025853,0.00025975573,0.00027300545,0.00013902495,0.00014841132,0.00008873652,0.000038796097,0.00007395423],"category_scores_gemma":[0.0000039195315,0.00017895669,0.000104437015,0.00059586327,0.00011120878,0.00016534513,0.00009899635,0.00025702213,0.0000056100735],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000091140086,0.000102690115,0.5548318,0.0006682681,0.000070693255,0.00024115543,0.0010743894,0.23097153,0.08524649,0.0008978602,0.002227495,0.12357649],"study_design_scores_gemma":[0.00015221031,0.000008950218,0.017447155,0.00018966009,0.00039135886,0.000114057875,0.000014780752,0.9712195,0.00015340693,0.0016433027,0.008491277,0.0001743722],"about_ca_topic_score_codex":0.000042129846,"about_ca_topic_score_gemma":9.894073e-7,"teacher_disagreement_score":0.74024796,"about_ca_system_score_codex":0.000040159364,"about_ca_system_score_gemma":0.000025160603,"threshold_uncertainty_score":0.7297642},"labels":[],"label_agreement":null},{"id":"W4401827704","doi":"10.1101/2024.08.21.608995","title":"Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer’s disease","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Concordia University","funders":"","keywords":"Apolipoprotein E; Family history; Disease; White matter; Affect (linguistics); Glycated hemoglobin; Psychology; Cognition; Risk factor; Blood pressure; Medicine; Internal medicine; Gerontology; Endocrinology; Neuroscience; Type 2 diabetes; Diabetes mellitus; Magnetic resonance imaging","score_opus":0.04311881122111306,"score_gpt":0.27275612125670345,"score_spread":0.2296373100355904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401827704","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.983851,0.011946965,0.0011030345,0.00039399977,0.00010179226,0.0012276878,0.0011234626,0.00023185188,0.000020194806],"genre_scores_gemma":[0.9889086,0.001569061,0.008788959,0.00012742246,0.00014995881,0.00031147746,0.0000033636945,0.00012827672,0.000012890044],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979161,0.00008374184,0.00050507876,0.00093405193,0.00027508163,0.0002859689],"domain_scores_gemma":[0.9982368,0.00006260786,0.0002902935,0.0009565625,0.00013548863,0.0003182797],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00024875873,0.0004573767,0.00082402304,0.00065940304,0.000054253942,0.000059522405,0.0001414608,0.0002731617,0.000008171161],"category_scores_gemma":[0.00002445505,0.0004109971,0.000091373215,0.00038026078,0.00028159592,0.000078240635,0.00038377228,0.001293534,0.0000044622116],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013466041,0.00006854212,0.9908633,0.00035668685,0.00021511193,0.000021675294,0.00007571909,0.000011213079,0.0075093405,0.00010637717,0.0007464827,0.000012056094],"study_design_scores_gemma":[0.00036053514,0.000036220143,0.98567307,0.0005267566,0.00090668065,4.2097735e-8,0.000005663892,0.000059430222,0.0024610444,0.000018398889,0.009563492,0.0003886429],"about_ca_topic_score_codex":0.000062144325,"about_ca_topic_score_gemma":5.728357e-7,"teacher_disagreement_score":0.010377904,"about_ca_system_score_codex":0.00016307991,"about_ca_system_score_gemma":0.00038002292,"threshold_uncertainty_score":0.9998342},"labels":[],"label_agreement":null},{"id":"W4401828721","doi":"10.1097/j.pain.0000000000003345","title":"What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review","year":2024,"lang":"en","type":"review","venue":"Pain","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arthritis Society","keywords":"Magnetic resonance imaging; Narrative review; Narrative; Chronic pain; Medicine; Functional magnetic resonance imaging; Diffusion MRI; Psychology; Neuroscience; Radiology; Philosophy; Intensive care medicine; Linguistics","score_opus":0.059806742251609805,"score_gpt":0.3814469241030221,"score_spread":0.3216401818514123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401828721","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.6196536e-8,0.97438484,0.0050114756,0.015559537,0.00016890565,0.0038957556,0.000037465124,0.0005690171,0.00037290595],"genre_scores_gemma":[2.9953677e-7,0.973532,0.0026959006,0.014198764,0.0004680497,0.0021027732,0.00049090374,0.00019664697,0.006314636],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99567956,0.0013074441,0.00095146126,0.001142713,0.00039168954,0.0005271534],"domain_scores_gemma":[0.99716216,0.0009625097,0.0003490981,0.0012468422,0.000090685055,0.00018871891],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0033579404,0.00073567155,0.0020440896,0.00020628347,0.00020847151,0.00015587606,0.00038343135,0.0001609901,0.00015414094],"category_scores_gemma":[0.0009144382,0.00056315603,0.0006848727,0.000906373,0.00024389708,0.00016700405,0.00026369694,0.0011976868,0.00014002727],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017732613,0.000041727923,0.0000014952466,0.078732684,0.000010054804,0.00012343915,0.00005123049,1.4458925e-8,0.000005711242,0.00006569088,0.15038936,0.77057683],"study_design_scores_gemma":[0.00009389443,0.00008295409,0.0000032163618,0.30669394,0.0005870975,0.00017343822,0.0000097559705,0.00016566155,3.2397182e-7,0.00023359877,0.69161814,0.00033800656],"about_ca_topic_score_codex":0.000007147394,"about_ca_topic_score_gemma":0.0000036059994,"teacher_disagreement_score":0.7702388,"about_ca_system_score_codex":0.00068435894,"about_ca_system_score_gemma":0.0006703706,"threshold_uncertainty_score":0.999682},"labels":[],"label_agreement":null},{"id":"W4401852142","doi":"10.1016/j.media.2024.103309","title":"Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling","year":2024,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Inference; Computer science; Generative model; Artificial intelligence; Machine learning; Statistical inference; Bayesian inference; Bayesian probability; Pattern recognition (psychology); Generative grammar; Mathematics; Statistics","score_opus":0.07956383460373577,"score_gpt":0.39229125966041684,"score_spread":0.31272742505668105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401852142","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23479314,0.0003483201,0.749459,0.014245587,0.000052660835,0.0001599534,0.000016918279,0.00049294514,0.00043146082],"genre_scores_gemma":[0.9629775,0.000027554048,0.03549442,0.00083499285,0.0002512774,0.000030476987,0.00013364069,0.000041330502,0.00020876828],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979028,0.00009810426,0.0004334686,0.00068148685,0.0005442822,0.00033983865],"domain_scores_gemma":[0.99847174,0.0005047375,0.000062684725,0.00043848468,0.00012982827,0.00039250893],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000702527,0.00023269583,0.0005152656,0.00042767075,0.0001719892,0.00016713965,0.00020476377,0.00014469605,0.00023985698],"category_scores_gemma":[0.00094995304,0.00019024657,0.00035884595,0.0020223032,0.00018051763,0.00034274283,0.00020960683,0.0008379512,0.000021338452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034374578,0.0020659894,0.06374292,0.0022269331,0.010980958,0.0055729016,0.002815608,0.015603726,0.128633,0.25922778,0.024680356,0.48410606],"study_design_scores_gemma":[0.0002560033,0.000025018999,0.0018786389,0.00012540573,0.0008801253,0.000066213695,0.000076296645,0.98766714,0.00042222327,0.008015208,0.000386807,0.0002008875],"about_ca_topic_score_codex":0.00022340156,"about_ca_topic_score_gemma":0.000112835565,"teacher_disagreement_score":0.9720634,"about_ca_system_score_codex":0.00017193877,"about_ca_system_score_gemma":0.000148519,"threshold_uncertainty_score":0.775803},"labels":[],"label_agreement":null},{"id":"W4401856347","doi":"10.1101/2024.08.19.608590","title":"The developing hippocampus: Microstructural evolution through childhood and adolescence","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Engineering and Physical Sciences Research Council; UK Research and Innovation; National Institutes of Health; Children's Hospital Foundation; Canada First Research Excellence Fund; Canada Research Chairs; Wellcome Trust; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; Diffusion MRI; Subiculum; Hippocampus; Neuroscience; Psychology; Soma; Neurite; White matter; Medicine; Chemistry; Magnetic resonance imaging; Dentate gyrus","score_opus":0.021995759269147163,"score_gpt":0.2766549236822922,"score_spread":0.25465916441314507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401856347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9595424,0.012521034,0.016851645,0.007103004,0.00077027775,0.0016956687,0.00010684098,0.0013950919,0.000014024861],"genre_scores_gemma":[0.93767244,0.001654642,0.059539825,0.0004960636,0.00033936894,0.00019136546,2.7177606e-7,0.00010073606,0.0000052968303],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99810785,0.000037344078,0.00037819913,0.0008528033,0.00022212154,0.0004016968],"domain_scores_gemma":[0.99844027,0.000052570358,0.00019351633,0.00096701,0.00022985338,0.00011677444],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018838646,0.00040116973,0.00033528073,0.000078428806,0.0003703722,0.00019998549,0.00028157,0.00024167978,0.0000016724006],"category_scores_gemma":[0.00012905464,0.00031973346,0.00009815376,0.00035495716,0.00027807028,0.00007256511,0.0007707799,0.0011772057,0.00001844659],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006793751,0.00010942728,0.0126918955,0.0021871957,0.00026995962,0.00010578993,0.00006016418,0.000007701879,0.91743845,0.0646019,0.002259469,0.00020012062],"study_design_scores_gemma":[0.00069899997,0.00008644791,0.795901,0.00538465,0.0004944934,0.0000022208978,0.000013397723,0.00054795295,0.16949077,0.006282507,0.019708771,0.0013887798],"about_ca_topic_score_codex":0.000017062219,"about_ca_topic_score_gemma":7.251772e-7,"teacher_disagreement_score":0.7832091,"about_ca_system_score_codex":0.00029948415,"about_ca_system_score_gemma":0.0005253377,"threshold_uncertainty_score":0.9999255},"labels":[],"label_agreement":null},{"id":"W4401894643","doi":"10.1002/hbm.26811","title":"Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega‐analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes","year":2024,"lang":"en","type":"review","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; University of British Columbia Hospital; Alberta Children's Hospital; University of Calgary; University of British Columbia; Queen's University","funders":"RWTH Aachen University","keywords":"Voxel; Concussion; White matter; Diffusion MRI; Grey matter; Psychology; Poison control; Medicine; Magnetic resonance imaging; Injury prevention; Radiology","score_opus":0.06095162663689272,"score_gpt":0.37330124197634734,"score_spread":0.3123496153394546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401894643","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08023288,0.9143688,0.00011703307,0.0009515026,0.0000700875,0.0038919798,0.00010247247,0.00015262736,0.00011258524],"genre_scores_gemma":[0.14533333,0.8502114,0.0012080097,0.0007425074,0.00050757424,0.0007792153,0.00059457356,0.00023302916,0.00039038158],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977515,0.00017265508,0.0006302515,0.0007718596,0.00028326802,0.00039046234],"domain_scores_gemma":[0.99799675,0.0007753849,0.00055510894,0.00051272067,0.000055108383,0.00010494253],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000496934,0.00055495475,0.0017052568,0.0003938095,0.00016760796,0.00008054696,0.00020263896,0.00018380118,0.0000065862328],"category_scores_gemma":[0.00025125773,0.00036109073,0.00039282537,0.0005703015,0.00015900406,0.000090524365,0.00023332228,0.0008191356,7.4221776e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013741667,0.00025605396,0.0032476764,0.19983882,0.001795881,0.0015569916,0.0072926786,0.000003102415,0.11364212,0.004270205,0.0019503714,0.6660087],"study_design_scores_gemma":[0.0032425702,0.0015350636,0.100079015,0.4373195,0.0047586528,0.003750397,0.0008268417,0.00032465818,0.00071488396,0.0032515752,0.44131896,0.002877897],"about_ca_topic_score_codex":0.000036627887,"about_ca_topic_score_gemma":0.000009150746,"teacher_disagreement_score":0.6631308,"about_ca_system_score_codex":0.00027128466,"about_ca_system_score_gemma":0.00014185751,"threshold_uncertainty_score":0.9998841},"labels":[],"label_agreement":null},{"id":"W4401928009","doi":"10.3389/fnhum.2024.1432830","title":"Sex differences in patterns of white matter neuroplasticity after balance training in young adults","year":2024,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Neuroplasticity; Psychology; Balance (ability); Motor skill; White matter; Motor learning; Developmental psychology; Young adult; Physical medicine and rehabilitation; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.03339143975419038,"score_gpt":0.30101934352845217,"score_spread":0.26762790377426177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401928009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9664545,0.000045388664,0.032331668,0.00026054823,0.0003054896,0.00028989126,0.000016750762,0.000055866945,0.00023986393],"genre_scores_gemma":[0.9979554,0.000042177402,0.0013090188,0.0003106996,0.000021048774,0.000089491594,0.0000014693844,0.000017572838,0.00025314974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986143,0.000038225957,0.00033299995,0.0005346488,0.00019249301,0.00028729925],"domain_scores_gemma":[0.9996316,0.000028371653,0.000042624903,0.00023856461,0.000010521133,0.000048323673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010672872,0.00013649985,0.000265907,0.00039266227,0.000034077235,0.000022508806,0.00020156366,0.00003351933,0.0000131361],"category_scores_gemma":[0.00003600525,0.00012798872,0.000033945504,0.00055229454,0.00016673924,0.00015926057,0.00008912802,0.00036451017,4.3734337e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020636735,0.00004957793,0.99587977,0.00010507647,2.8027904e-7,0.00014321096,0.0014167076,0.00004459773,0.0018714726,0.00004093632,0.000060138478,0.0003676113],"study_design_scores_gemma":[0.00022035057,0.00006967999,0.97734654,0.00060282066,0.0000030219655,0.000022975131,0.000118564145,0.02070388,0.0003424213,0.00040413145,0.000060190814,0.000105445906],"about_ca_topic_score_codex":0.000032221404,"about_ca_topic_score_gemma":0.00004864385,"teacher_disagreement_score":0.031500842,"about_ca_system_score_codex":0.000041435047,"about_ca_system_score_gemma":0.00002855617,"threshold_uncertainty_score":0.5219228},"labels":[],"label_agreement":null},{"id":"W4401977490","doi":"10.21203/rs.3.rs-4883534/v1","title":"MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression","year":2024,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Ottawa Mental Health Centre","funders":"Engineering and Physical Sciences Research Council","keywords":"Oligodendrocyte; Neuroscience; Cell type; Human brain; Cell; Pathology; Biology; Medicine; Myelin; Central nervous system; Genetics","score_opus":0.08121285262941325,"score_gpt":0.44149022490200146,"score_spread":0.3602773722725882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401977490","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921439,0.0019305896,0.0007271971,0.00053090753,0.000039022692,0.0022961905,0.000036596768,0.0001995595,0.0020960236],"genre_scores_gemma":[0.98018515,0.00022531285,0.018425344,0.00002778544,0.000068176865,0.00021689654,0.00017850974,0.000068298206,0.0006045404],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975975,0.0001064858,0.00038195122,0.0006940261,0.000801551,0.00041846716],"domain_scores_gemma":[0.9985577,0.00010303792,0.00007683403,0.0007246844,0.00038343554,0.00015434304],"candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0003278821,0.000245448,0.0004109906,0.00047572545,0.00010885128,0.000034487646,0.00029284446,0.0003078475,0.00005398147],"category_scores_gemma":[0.000048086218,0.00018388453,0.00006396491,0.00048763357,0.00021548188,0.000017420196,0.0011146908,0.0031868739,0.000008416307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054153055,0.00042325442,0.004192195,0.007516057,0.000038415445,0.0005351869,0.0011465057,0.00048515966,0.9736998,0.0011971215,0.009617091,0.0006076989],"study_design_scores_gemma":[0.0005737748,0.00041701153,0.010585783,0.006585624,0.000026233465,0.000026658769,0.00016441691,0.00015039291,0.9722867,0.00396098,0.00496341,0.00025900087],"about_ca_topic_score_codex":0.000034667646,"about_ca_topic_score_gemma":0.000011775449,"teacher_disagreement_score":0.017698146,"about_ca_system_score_codex":0.00020816238,"about_ca_system_score_gemma":0.00060262054,"threshold_uncertainty_score":0.9991128},"labels":[],"label_agreement":null},{"id":"W4402029496","doi":"10.1101/2024.08.29.610312","title":"Stable White Matter Structure in the First Three Years after Psychosis Onset","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; London Health Sciences Centre; Western University","funders":"","keywords":"Psychosis; White matter; White (mutation); Psychology; Psychiatry; Medicine; Chemistry; Magnetic resonance imaging","score_opus":0.020669453105410872,"score_gpt":0.27041650564796876,"score_spread":0.24974705254255788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402029496","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98457813,0.0011178937,0.00070185156,0.010421363,0.0003774912,0.0015942487,0.00073101424,0.00044037792,0.000037601963],"genre_scores_gemma":[0.9847685,0.00011796696,0.010074266,0.0037356138,0.00025813133,0.00088719046,8.3534457e-7,0.00014349117,0.000013980396],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99800813,0.00003144716,0.00037348396,0.00086767564,0.00031329927,0.0004059541],"domain_scores_gemma":[0.9978317,0.000032990418,0.00012559113,0.0018092474,0.00009996329,0.000100522324],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001987023,0.000402847,0.00039305835,0.00025062324,0.000063092324,0.0001677717,0.00045538435,0.00030285897,0.00019841299],"category_scores_gemma":[0.000019674555,0.00033137965,0.000138578,0.0006048057,0.00010159822,0.00005240447,0.0004167204,0.0015351254,0.00014552388],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001443894,0.00034385835,0.9269889,0.0018314301,0.0001578252,0.0006547669,0.000087165135,0.000039802682,0.0147289615,0.00064396916,0.054370623,0.000008319473],"study_design_scores_gemma":[0.00022820478,0.000025280571,0.94628507,0.0008352756,0.00015470869,2.3340613e-7,0.0000018426589,0.000106447056,0.0021746089,0.00017159228,0.049622234,0.0003944764],"about_ca_topic_score_codex":0.00003629931,"about_ca_topic_score_gemma":0.000024590747,"teacher_disagreement_score":0.019296205,"about_ca_system_score_codex":0.00015231105,"about_ca_system_score_gemma":0.00012802846,"threshold_uncertainty_score":0.9999138},"labels":[],"label_agreement":null},{"id":"W4402148258","doi":"","title":"Can We Encode Intra-and Inter-Variability with Log Jacobian Maps Derived from Brain Morphological Deformations Using Pediatric MRI Scans?","year":2024,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canada First Research Excellence Fund; Polytechnique Montréal","keywords":"ENCODE; Jacobian matrix and determinant; Computer science; Artificial intelligence; Pattern recognition (psychology); Computer vision; Mathematics; Biology; Gene; Applied mathematics; Genetics","score_opus":0.030640994637806,"score_gpt":0.2803198884322599,"score_spread":0.2496788937944539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402148258","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36923623,0.00024172767,0.5826336,0.045350358,0.000027532313,0.00036943972,0.00011000894,0.0003561048,0.0016749899],"genre_scores_gemma":[0.8201985,0.00028934292,0.17868614,0.00026187,0.000023509065,0.00004602888,0.00019330163,0.00002426691,0.00027704952],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980422,0.00074331014,0.00031282948,0.0005059507,0.00016980771,0.00022588512],"domain_scores_gemma":[0.99753666,0.0009877954,0.00010461379,0.0008298874,0.00036475912,0.00017628622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010466296,0.0001807532,0.00021838918,0.00013127594,0.00023882682,0.0001447368,0.00023630908,0.00008920243,0.00008010734],"category_scores_gemma":[0.00045340744,0.00015228441,0.00006596751,0.00050046295,0.00025310845,0.00014526448,0.00018923172,0.00038007722,0.000007607388],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022950058,0.0032235489,0.27704966,0.0013449241,0.0004268022,0.00030951897,0.035759177,0.00037834008,0.2975297,0.19138576,0.0074217976,0.18494126],"study_design_scores_gemma":[0.004922482,0.000029459918,0.089294,0.006918747,0.0016482663,0.0021676912,0.0017848526,0.41536132,0.25662452,0.1584757,0.059767608,0.0030053689],"about_ca_topic_score_codex":0.0004418741,"about_ca_topic_score_gemma":0.0003496413,"teacher_disagreement_score":0.45096225,"about_ca_system_score_codex":0.00011340196,"about_ca_system_score_gemma":0.00016081356,"threshold_uncertainty_score":0.6209978},"labels":[],"label_agreement":null},{"id":"W4402232009","doi":"10.7554/elife.83838","title":"White matter structural bases for phase accuracy during tapping synchronization","year":2024,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Laboratory for Brain, Music and Sound Research","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Consejo Nacional de Ciencia y Tecnología","keywords":"Tapping; Synchronization (alternating current); White matter; Phase (matter); Computer science; Neuroscience; Biology; Physics; Medicine; Acoustics; Telecommunications; Magnetic resonance imaging","score_opus":0.05085489224150328,"score_gpt":0.40634679874448176,"score_spread":0.35549190650297846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402232009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53132486,0.0004316338,0.45636284,0.009343987,0.00016589327,0.000979319,0.00006991995,0.0008838321,0.0004377149],"genre_scores_gemma":[0.9809912,0.000029912186,0.016637873,0.0010325481,0.00032812223,0.00011146663,0.00008292438,0.000031309155,0.00075468206],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994668,0.0000038137227,0.0001291909,0.00019606309,0.000079388345,0.00012477027],"domain_scores_gemma":[0.9996866,0.00004421529,0.000024595063,0.0001627744,0.000038118058,0.00004371286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000027010788,0.000078351695,0.000086678156,0.00005911112,0.00008687135,0.000035560613,0.000039286802,0.000020448824,0.00014238518],"category_scores_gemma":[0.000044452365,0.00006873905,0.00004600116,0.00012269443,0.00001771888,0.00012446126,0.000021261336,0.00007833103,0.00002706831],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006640736,0.0004689123,0.1106561,0.00778936,0.0003058165,0.00028663102,0.0019114233,0.0011228949,0.41686743,0.012803794,0.2959872,0.15113637],"study_design_scores_gemma":[0.005154629,0.0004049413,0.06172655,0.0020505257,0.0004183822,0.00081848376,0.00015454534,0.27567545,0.22397682,0.0029227766,0.42569068,0.0010061923],"about_ca_topic_score_codex":0.0000010943035,"about_ca_topic_score_gemma":1.353805e-7,"teacher_disagreement_score":0.4496663,"about_ca_system_score_codex":0.00003863296,"about_ca_system_score_gemma":0.000023579641,"threshold_uncertainty_score":0.2803097},"labels":[],"label_agreement":null},{"id":"W4402311891","doi":"10.1121/10.0028500","title":"Investigating muscle coordination patterns with Granger causality analysis in protrusive motion from tagged and diffusion MRI","year":2024,"lang":"en","type":"article","venue":"JASA Express Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute on Deafness and Other Communication Disorders; National Cancer Institute; National Institutes of Health","keywords":"Motion (physics); Tongue; Granger causality; Motion analysis; Muscle fibre; Dynamics (music); Biology; Diffusion; Anatomy; Computer science; Computer vision; Artificial intelligence; Biological system; Physics; Acoustics; Machine learning; Medicine","score_opus":0.030075468857216594,"score_gpt":0.30597365991621495,"score_spread":0.2758981910589984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402311891","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8373708,0.000037124606,0.15304892,0.008845816,0.000013035962,0.00048254663,0.000033223907,0.00015584614,0.000012706627],"genre_scores_gemma":[0.9895846,0.000018304941,0.00876034,0.0011860005,0.000053160064,0.00022504244,0.00013729752,0.000019517447,0.000015738971],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99910957,0.00004369703,0.0001724367,0.00039078135,0.00015844096,0.0001250545],"domain_scores_gemma":[0.99955475,0.00007963892,0.000056300214,0.00022656615,0.000024856276,0.000057887035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007988877,0.00011747757,0.00018082275,0.00019588601,0.000053206295,0.00004409351,0.000042075386,0.000037518614,0.000013211952],"category_scores_gemma":[0.000026617952,0.00009685431,0.000038079517,0.00043780223,0.000060644266,0.00014900393,0.000037081627,0.00020399272,9.5129144e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012848493,0.000050277253,0.43892318,0.000102342594,0.000057260026,0.00004111764,0.0007985874,0.00012862877,0.55406845,0.00006152803,0.00030854042,0.0054472256],"study_design_scores_gemma":[0.00044159067,0.00003258347,0.96420825,0.0005037456,0.00029184218,0.0000039808083,0.00009045899,0.023628987,0.009643791,0.00032464263,0.0006589683,0.00017117891],"about_ca_topic_score_codex":0.0006574493,"about_ca_topic_score_gemma":0.000049200746,"teacher_disagreement_score":0.54442465,"about_ca_system_score_codex":0.000055318033,"about_ca_system_score_gemma":0.0000070804517,"threshold_uncertainty_score":0.3949604},"labels":[],"label_agreement":null},{"id":"W4402354789","doi":"10.1002/mrm.30279","title":"Particle‐based MR modeling with diffusion, microstructure, and enzymatic reactions","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; University of Toronto; Innovation, Science and Economic Development Canada","keywords":"Biological system; SIGNAL (programming language); Diffusion; Imaging phantom; Nuclear magnetic resonance; In silico; Brownian dynamics; Diffusion MRI; Biomedical engineering; Magnetic resonance imaging; Brownian motion; Chemistry; Computer science; Materials science; Physics; Thermodynamics; Medicine; Optics","score_opus":0.04344542131942288,"score_gpt":0.3333778175657322,"score_spread":0.28993239624630934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402354789","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8773591,0.03898405,0.05582925,0.025300767,0.00007567819,0.0009890716,0.000006332464,0.00043001905,0.0010257578],"genre_scores_gemma":[0.9818136,0.001101989,0.01539565,0.0009231495,0.00008215855,0.00012487611,0.00000796262,0.000031610536,0.00051898445],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99896145,0.000016945618,0.00028480537,0.0003447973,0.00019019927,0.00020178227],"domain_scores_gemma":[0.9994273,0.00010661804,0.000023382538,0.00030738863,0.00004004469,0.00009522884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012647298,0.0001429622,0.00023040856,0.000115304436,0.000055477096,0.000014874762,0.00005438844,0.00004055195,0.00007512544],"category_scores_gemma":[0.00007917683,0.000096810516,0.000016635087,0.00046579936,0.00020154388,0.00004483216,0.00001925234,0.00028011863,0.000003357008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009419324,0.0005776982,0.058970485,0.0035345703,0.00002788358,0.0018043055,0.002600545,0.0017506984,0.30520335,0.037119113,0.005529355,0.58194005],"study_design_scores_gemma":[0.001988688,0.00082156056,0.023695134,0.004107278,0.0001088425,0.0005243287,0.00015255349,0.8899516,0.0011643762,0.0064601353,0.0707875,0.00023804484],"about_ca_topic_score_codex":0.00006606616,"about_ca_topic_score_gemma":0.000012361113,"teacher_disagreement_score":0.8882009,"about_ca_system_score_codex":0.000033693173,"about_ca_system_score_gemma":0.00004195887,"threshold_uncertainty_score":0.39478183},"labels":[],"label_agreement":null},{"id":"W4402354923","doi":"10.1002/mrm.30247","title":"Rational approximation of golden angles: Accelerated reconstructions for radial MRI","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Institute of Biomedical Imaging and Bioengineering; Deutsche Forschungsgemeinschaft; National Institute on Aging; National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Deutsches Zentrum für Herz-Kreislaufforschung","keywords":"Golden ratio; Sampling (signal processing); Precomputation; Equidistant; Computer science; Algorithm; Imaging phantom; Mathematics; Golden hamster; Artificial intelligence; Computer vision; Computation; Optics; Geometry; Physics","score_opus":0.08137913570329844,"score_gpt":0.3705281476296144,"score_spread":0.2891490119263159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402354923","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32775316,0.06427218,0.46751562,0.105496965,0.0017441453,0.011584349,0.00032469735,0.0013608964,0.019947996],"genre_scores_gemma":[0.7840072,0.0028669408,0.20581761,0.00073582196,0.0010691474,0.0015261557,0.00033665312,0.000077169,0.0035633228],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99897903,0.00001618278,0.00041888776,0.0002761812,0.00016585279,0.00014388855],"domain_scores_gemma":[0.99939746,0.00018548733,0.000050915995,0.0002144355,0.00010497051,0.000046727328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019451107,0.00010643143,0.00024947044,0.00022288754,0.00003345558,0.000007387674,0.00007425901,0.000055722845,0.00018463036],"category_scores_gemma":[0.00017637572,0.00008945314,0.000043167787,0.0005566291,0.00021577059,0.00007001975,0.000012158884,0.00015227239,0.0000030996189],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032252746,0.00021666089,0.0057560056,0.00089726323,0.00001577691,0.000030286594,0.00077214814,0.000068802314,0.05883884,0.05920981,0.050015073,0.82385683],"study_design_scores_gemma":[0.0056881383,0.0022761505,0.06902221,0.0038419126,0.00021457745,0.000490468,0.00041226431,0.1345991,0.009816006,0.057511184,0.71568924,0.00043873806],"about_ca_topic_score_codex":0.000019007255,"about_ca_topic_score_gemma":0.00000501953,"teacher_disagreement_score":0.8234181,"about_ca_system_score_codex":0.00005111264,"about_ca_system_score_gemma":0.00008858289,"threshold_uncertainty_score":0.36477932},"labels":[],"label_agreement":null},{"id":"W4402389629","doi":"10.1101/2024.09.05.610266","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"","keywords":"Zona incerta; Zona; Diffusion MRI; Diffusion; Cartography; Geology; Geography; Neuroscience; Psychology; Magnetic resonance imaging; Biology; Medicine; Physics; Radiology; Virology; Human immunodeficiency virus (HIV)","score_opus":0.043735647785188084,"score_gpt":0.2841951467688496,"score_spread":0.24045949898366153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402389629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9879753,0.0004666254,0.0074540316,0.0020753052,0.00034339033,0.0012052875,0.000047844125,0.00041945322,0.00001274428],"genre_scores_gemma":[0.9937084,0.00018764831,0.005359261,0.0002971059,0.00025342664,0.00006407219,4.5120964e-7,0.000121021076,0.000008671098],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9983529,0.00006374617,0.00044763778,0.00057615386,0.00032577274,0.0002338215],"domain_scores_gemma":[0.9975363,0.00003661168,0.0003673755,0.0015929292,0.0003949512,0.00007185061],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023902833,0.00030668493,0.0003370282,0.00021024724,0.00034112707,0.00006839804,0.00050176063,0.00021896668,0.000016367103],"category_scores_gemma":[0.00010135744,0.00020723298,0.0001583153,0.00153166,0.00022059676,0.000034150115,0.0011815968,0.0009388305,0.0000040214945],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000001820293,0.00007119039,0.027491169,0.00043403724,0.000048254336,0.0000047318094,0.000020815723,0.000034059314,0.96811485,0.003618733,0.00015797255,0.0000023522966],"study_design_scores_gemma":[0.00044093907,0.00003710645,0.39817202,0.0042341426,0.0006361577,3.4094077e-7,0.000018081624,0.0040183216,0.5844153,0.00031963235,0.0069852984,0.0007226087],"about_ca_topic_score_codex":0.00006259185,"about_ca_topic_score_gemma":7.9749674e-7,"teacher_disagreement_score":0.38369954,"about_ca_system_score_codex":0.00014469428,"about_ca_system_score_gemma":0.00025787324,"threshold_uncertainty_score":0.84507155},"labels":[],"label_agreement":null},{"id":"W4402418555","doi":"10.1016/j.neuroimage.2024.120850","title":"Ultra-high-resolution mapping of myelin and g-ratio in a panel of Mbp enhancer-edited mouse strains using microstructural MRI","year":2024,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto General Hospital; Lunenfeld-Tanenbaum Research Institute; University Health Network; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada","keywords":"Myelin; High resolution; Resolution (logic); Enhancer; Chemistry; Materials science; Molecular biology; Biology; Computer science; Neuroscience; Biochemistry; Geography; Artificial intelligence; Remote sensing; Gene","score_opus":0.07542896647390292,"score_gpt":0.3381736405925891,"score_spread":0.2627446741186862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402418555","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9704006,0.00019789624,0.028233547,0.00044730867,0.000053411906,0.00038610192,0.00010122057,0.000105301115,0.000074651995],"genre_scores_gemma":[0.9787364,0.0001649037,0.020841215,0.00007795599,0.000055796445,0.000009592439,0.000028094775,0.00002611394,0.000059953945],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990399,0.000026123944,0.00035095925,0.00029969227,0.00012346446,0.00015986145],"domain_scores_gemma":[0.9995355,0.000052597043,0.000085995365,0.00023013611,0.000052612664,0.000043161606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007722718,0.0001247761,0.00024042335,0.0002072697,0.000028935738,0.000014193482,0.00006004606,0.0000481168,0.000010121549],"category_scores_gemma":[0.000052265765,0.000120748664,0.000045670036,0.00037043786,0.00014733856,0.000116250805,0.000029800716,0.00023236574,6.159297e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000188754,0.000029151819,0.00043103908,0.00024762252,0.00000554008,0.000021838498,0.00021324438,0.00008675161,0.9969399,0.00041993786,0.00006189032,0.0015242193],"study_design_scores_gemma":[0.0006698623,0.00014904392,0.03545017,0.00043734553,0.00005348616,0.00015622904,0.00010116262,0.030254079,0.93131524,0.00069554895,0.00054874516,0.00016910507],"about_ca_topic_score_codex":0.000105644416,"about_ca_topic_score_gemma":0.0000057180673,"teacher_disagreement_score":0.06562467,"about_ca_system_score_codex":0.000031394153,"about_ca_system_score_gemma":0.000045682205,"threshold_uncertainty_score":0.49239877},"labels":[],"label_agreement":null},{"id":"W4402476141","doi":"10.1371/journal.pone.0310312","title":"White matter disconnection impacts proprioception post-stroke","year":2024,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions; Heart and Stroke Foundation of Canada","keywords":"Proprioception; Disconnection; Superior longitudinal fasciculus; Fasciculus; White matter; Psychology; Physical medicine and rehabilitation; Arcuate fasciculus; Neuroimaging; Neuroscience; Corticospinal tract; Stroke (engine); Corpus callosum; Corona radiata (embryology); Inferior longitudinal fasciculus; Grey matter; Medicine; Magnetic resonance imaging; Tractography; Diffusion MRI; Physics; Internal medicine","score_opus":0.06886686923058691,"score_gpt":0.3159629885609188,"score_spread":0.2470961193303319,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402476141","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96939105,0.00014254343,0.0052098283,0.020268355,0.00002831974,0.00058161066,0.00003774683,0.00073684397,0.0036037096],"genre_scores_gemma":[0.980472,0.00007041701,0.010197098,0.0008774469,0.0001816298,0.00009539863,0.00004676456,0.000030827152,0.008028391],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994278,0.0000064045116,0.00010574259,0.00019899986,0.00013888668,0.00012217685],"domain_scores_gemma":[0.9996549,0.000012001913,0.000018700952,0.00020380733,0.00005115454,0.000059441903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035549914,0.000077369055,0.00010147183,0.00008566567,0.000039992465,0.00003212705,0.000030012323,0.000032461216,0.00030034978],"category_scores_gemma":[0.000016422851,0.00006410546,0.000042526062,0.00011187965,0.000022935554,0.00012179431,0.00001966436,0.00016888224,0.000490908],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003407538,0.00059397105,0.042945195,0.00041178928,0.00006390202,0.000016914131,0.00013068411,5.533419e-7,0.95169616,0.00037430497,0.0018448258,0.0018876151],"study_design_scores_gemma":[0.0007523281,0.0010717962,0.3852511,0.002838794,0.001013765,0.00029282115,0.000105224215,0.004250183,0.59407675,0.0034193387,0.0063600917,0.0005678076],"about_ca_topic_score_codex":0.000004890779,"about_ca_topic_score_gemma":0.0000010605604,"teacher_disagreement_score":0.35761943,"about_ca_system_score_codex":0.00004844931,"about_ca_system_score_gemma":0.000019951163,"threshold_uncertainty_score":0.6309793},"labels":[],"label_agreement":null},{"id":"W4402544130","doi":"10.1016/j.cccb.2024.100369","title":"The effects of a six-month exercise intervention on white matter microstructure in older adults at risk for diabetes","year":2024,"lang":"en","type":"article","venue":"Cerebral Circulation - Cognition and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canada First Research Excellence Fund; Western University; Canada Research Chairs","keywords":"Diabetes mellitus; Medicine; Intervention (counseling); Physical therapy; Gerontology; Endocrinology; Psychiatry","score_opus":0.01327237237505767,"score_gpt":0.3007230457551044,"score_spread":0.2874506733800467,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402544130","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969591,0.0002802814,0.0005745776,0.00030418005,0.00008917645,0.0016511921,0.000055729517,0.000060350314,0.000025438772],"genre_scores_gemma":[0.9985212,0.000045058063,0.00025867095,0.00010738425,0.000025996882,0.0006529331,0.00019827747,0.000019116618,0.00017137792],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99939215,0.000018721352,0.00019470321,0.00021560579,0.0000757382,0.00010310403],"domain_scores_gemma":[0.99964094,0.00008821896,0.00006886714,0.00011446971,0.00005526465,0.000032240507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000057008598,0.00009520901,0.000115101655,0.00008229795,0.000089783614,0.000025932484,0.00002437675,0.000054580974,0.000039383533],"category_scores_gemma":[0.000023448625,0.000070844675,0.00008508818,0.00010468832,0.000049330054,0.0000638496,0.000015722808,0.00010719401,0.0000042929205],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033619785,0.00043508512,0.7910962,0.0019668231,0.000017866994,0.000005022863,0.000425702,0.000002572543,0.024177853,0.00015605832,0.00079168886,0.18058893],"study_design_scores_gemma":[0.0014389422,0.00011901717,0.98399436,0.0014348238,0.0002530202,0.0000060331286,0.000022426082,0.0006361419,0.011244842,0.00062233495,0.00014768964,0.00008037647],"about_ca_topic_score_codex":0.0000023063747,"about_ca_topic_score_gemma":0.0000057970205,"teacher_disagreement_score":0.19289815,"about_ca_system_score_codex":0.000029795001,"about_ca_system_score_gemma":0.0000045288834,"threshold_uncertainty_score":0.2888962},"labels":[],"label_agreement":null},{"id":"W4402555343","doi":"10.1002/alz.14161","title":"Morphometry of medial temporal lobe subregions using high‐resolution T2‐weighted MRI in ADNI3: Why, how, and what's next?","year":2024,"lang":"en","type":"review","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; H. Lundbeck A/S; Servier; Universidad de Castilla-La Mancha; Fred A. And Barbara M. Erb Family Foundation; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; Biogen; BioClinica; Meso Scale Diagnostics; Novartis Pharmaceuticals Corporation; Eli Lilly and Company; Bristol-Myers Squibb; F. Hoffmann-La Roche; University of Pennsylvania; Merck; Alzheimer's Drug Discovery Foundation; National Institute of Neurological Disorders and Stroke; Takeda Pharmaceutical Company; AbbVie; Fujirebio Europe; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Temporal lobe; Lobe; High resolution; Anatomy; T2 weighted; Magnetic resonance imaging; Cartography; Psychology; Geology; Neuroscience; Medicine; Geography; Radiology; Epilepsy; Remote sensing","score_opus":0.14616736262954372,"score_gpt":0.3854787341895066,"score_spread":0.2393113715599629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402555343","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00013255618,0.9949225,0.0022237943,0.00087137864,0.00030344512,0.0013449873,0.000045456636,0.00013990454,0.000015957175],"genre_scores_gemma":[0.003980262,0.97346175,0.02147298,0.000102494065,0.00021616933,0.00015365794,0.0005008927,0.00010629366,0.0000054882694],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978478,0.000087998196,0.00071866077,0.0006854478,0.00030681692,0.00035327504],"domain_scores_gemma":[0.9987072,0.000075473574,0.0003888177,0.0006038823,0.00007914803,0.00014547573],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019249159,0.0004621141,0.0012745039,0.00068563124,0.000070215974,0.0001580288,0.00020538177,0.0002733564,0.000036921156],"category_scores_gemma":[0.000014903035,0.00039935645,0.00027961604,0.0010809893,0.00021905598,0.0006588045,0.00024984378,0.0005874413,0.000010365336],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023205797,0.00032224433,0.00010002076,0.0036887892,0.005204187,0.00013476885,0.00005842914,7.182927e-7,0.00021425432,0.0015093354,0.011850016,0.976894],"study_design_scores_gemma":[0.00035307702,0.00009373348,0.000025954609,0.009382125,0.052143697,0.00016472007,0.00004588487,0.00024710153,0.00011578831,0.00043223728,0.93658507,0.00041058852],"about_ca_topic_score_codex":0.00015092133,"about_ca_topic_score_gemma":0.000018347017,"teacher_disagreement_score":0.97648346,"about_ca_system_score_codex":0.000033117187,"about_ca_system_score_gemma":0.00019490733,"threshold_uncertainty_score":0.9998458},"labels":[],"label_agreement":null},{"id":"W4402699223","doi":"10.48550/arxiv.2408.12921","title":"Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR$^2$-CSD) of Diffusion MRI Data","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Deconvolution; Diffusion; Diffusion MRI; Physics; Algorithm; Computer science; Statistical physics; Magnetic resonance imaging; Radiology; Medicine; Thermodynamics","score_opus":0.16298231659628606,"score_gpt":0.27464767176666266,"score_spread":0.1116653551703766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402699223","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25827003,0.00015171942,0.73625535,0.0011788579,0.00021482544,0.0011447753,0.0003886414,0.0005951749,0.0018006574],"genre_scores_gemma":[0.9663321,0.00065486424,0.030409725,0.000098817116,0.00011720048,0.0000029125038,0.000838782,0.000051354185,0.0014942464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979702,0.00006440057,0.0003635768,0.0012190781,0.0001236584,0.00025905253],"domain_scores_gemma":[0.9971492,0.00009256185,0.0002245326,0.0021854627,0.00017215656,0.00017606415],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016824125,0.00031432492,0.0005688235,0.00016314327,0.00007594849,0.000019026256,0.00069379644,0.0003077625,0.00014113526],"category_scores_gemma":[0.00009069961,0.00033247095,0.00021215879,0.00040631034,0.000386709,0.000075934964,0.002612426,0.00081381004,0.000026657433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006181739,0.006144418,0.030749496,0.008259941,0.0024625813,0.0068722726,0.00072104664,0.023750622,0.40739718,0.43707937,0.038270164,0.032111153],"study_design_scores_gemma":[0.0035115038,0.00035685115,0.002905143,0.0015928262,0.0021991145,0.00009777483,0.00012756228,0.84904176,0.0040234104,0.11766731,0.01744743,0.001029312],"about_ca_topic_score_codex":0.00015325073,"about_ca_topic_score_gemma":0.000030048177,"teacher_disagreement_score":0.82529116,"about_ca_system_score_codex":0.00015000325,"about_ca_system_score_gemma":0.00035316465,"threshold_uncertainty_score":0.99991274},"labels":[],"label_agreement":null},{"id":"W4402894228","doi":"10.1002/mrm.30298","title":"Investigating microstructural changes between in vivo and perfused ex vivo marmoset brains using oscillating gradient and b‐tensor encoded diffusion <scp>MRI</scp> at 9.<scp>4 T</scp>","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Center for Research Computing, University of Pittsburgh; Canada Research Chairs; University of Pittsburgh; Canada First Research Excellence Fund; National Science Foundation","keywords":"Ex vivo; Diffusion MRI; Fractional anisotropy; In vivo; Kurtosis; Nuclear magnetic resonance; Perfusion; Fixation (population genetics); Materials science; Biomedical engineering; Chemistry; Magnetic resonance imaging; Biology; Physics; Medicine; Internal medicine; Mathematics; Radiology; Genetics","score_opus":0.054555015936560536,"score_gpt":0.32491782410609354,"score_spread":0.270362808169533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402894228","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98043823,0.014832475,0.00014573286,0.0029157314,0.000094096555,0.0009906911,0.000051846586,0.00016808738,0.00036311583],"genre_scores_gemma":[0.9708917,0.0036596311,0.021983983,0.0011919792,0.00048937235,0.00008678774,0.000037961745,0.00010658378,0.0015519591],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9974382,0.00008968417,0.0006124822,0.0008687168,0.00038627695,0.0006046398],"domain_scores_gemma":[0.9980123,0.0011725666,0.0001404528,0.00036606588,0.000053088726,0.0002555171],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004574309,0.00039025082,0.0006683162,0.0004140682,0.0001749131,0.00004263159,0.00013654318,0.0001466096,0.000017066923],"category_scores_gemma":[0.0012505265,0.00032647682,0.000035553832,0.0007931582,0.00065298245,0.00008720452,0.0002655192,0.0005689677,0.0000010789212],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005100336,0.00002054363,0.32644516,0.0005158267,0.000004942855,0.00014820848,0.0060001197,0.0000070141928,0.6423284,0.00008901294,0.0017050594,0.02273062],"study_design_scores_gemma":[0.0052945944,0.0014722642,0.74462104,0.010336891,0.00022983554,0.0011099278,0.003625122,0.083681,0.029426485,0.0036667313,0.11619672,0.0003393631],"about_ca_topic_score_codex":0.00027507317,"about_ca_topic_score_gemma":0.00012725788,"teacher_disagreement_score":0.6129019,"about_ca_system_score_codex":0.0001764345,"about_ca_system_score_gemma":0.000041399962,"threshold_uncertainty_score":0.9999187},"labels":[],"label_agreement":null},{"id":"W4402906635","doi":"10.1101/2024.09.25.614579","title":"Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Modal; Aggregate (composite); White matter; Materials science; Magnetic resonance imaging; Medicine; Composite material; Radiology","score_opus":0.06456217936251007,"score_gpt":0.30309320108048665,"score_spread":0.23853102171797658,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402906635","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89987946,0.0014903421,0.09100071,0.004186114,0.0005407167,0.0019489907,0.00023057152,0.00069451646,0.000028581479],"genre_scores_gemma":[0.8995418,0.00014885174,0.09901373,0.00061426,0.0002984987,0.00018597605,4.4306657e-7,0.00016521143,0.00003125277],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9977574,0.000058626152,0.0006391734,0.0008275299,0.00031935913,0.00039796234],"domain_scores_gemma":[0.99742645,0.00004618928,0.00046288513,0.0015698795,0.00034170732,0.00015288299],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00032368934,0.00045867724,0.0005639837,0.000285057,0.00020453313,0.0000871399,0.0003893944,0.00028357675,0.00003680941],"category_scores_gemma":[0.000057582973,0.00037959105,0.00023394251,0.00058050454,0.0002011451,0.00007255332,0.00083970994,0.0012555133,0.000047692665],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021472586,0.00018228276,0.016575046,0.0013595999,0.00015819608,0.00007840039,0.00006476668,0.000212252,0.9802796,0.00052459,0.00054022705,0.0000035561836],"study_design_scores_gemma":[0.0010440696,0.0000720967,0.29849178,0.0064130155,0.0008897595,0.0000011714525,0.000020277852,0.04041952,0.63661313,0.0000778958,0.014512376,0.0014449],"about_ca_topic_score_codex":0.000023827113,"about_ca_topic_score_gemma":4.1129658e-7,"teacher_disagreement_score":0.34366646,"about_ca_system_score_codex":0.00017411218,"about_ca_system_score_gemma":0.00038391573,"threshold_uncertainty_score":0.9998656},"labels":[],"label_agreement":null},{"id":"W4402943543","doi":"10.1016/j.neurobiolaging.2024.09.013","title":"Midlife dynamics of white matter architecture in lexical production","year":2024,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut Universitaire de Gériatrie de Montréal","funders":"Biotechnology and Biological Sciences Research Council; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Language production; Speech production; White matter; Psychology; Production (economics); Cognitive psychology; Linguistics; Cognition; Neuroscience; Medicine","score_opus":0.02816459705956561,"score_gpt":0.33052041618497535,"score_spread":0.30235581912540976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402943543","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9701754,0.0000681548,0.004629631,0.024280116,0.00009889191,0.00018814197,0.0000072932785,0.00008127957,0.00047113068],"genre_scores_gemma":[0.9943255,0.000024096456,0.0049934927,0.00035702166,0.000039706007,0.000009684014,0.000017074275,0.000013245117,0.00022013766],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994484,0.00002074555,0.00018619887,0.0002132196,0.000033489196,0.00009792516],"domain_scores_gemma":[0.99972236,0.00003255664,0.000035486104,0.00017484066,0.00001885603,0.00001590469],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000055205073,0.000065630076,0.00015523714,0.00015386705,0.000014338697,0.0000012079281,0.000048413054,0.000038813563,0.000016625216],"category_scores_gemma":[0.000014214871,0.000056046963,0.000041343643,0.00018971371,0.00012234236,0.000019397054,0.00004320126,0.00024461048,0.0000025621484],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000089093475,0.00023172579,0.7953621,0.0011811247,0.000027936348,0.000035448073,0.0006070454,0.0008766648,0.18824589,0.0039929366,0.0022631797,0.0070868204],"study_design_scores_gemma":[0.0005962405,0.00052808557,0.83529663,0.0014240016,0.000117734075,0.0009902369,0.00007064347,0.0036262437,0.1359002,0.014138035,0.0069738817,0.00033809713],"about_ca_topic_score_codex":0.000004080603,"about_ca_topic_score_gemma":0.0000037982581,"teacher_disagreement_score":0.052345693,"about_ca_system_score_codex":0.000013825837,"about_ca_system_score_gemma":0.000016192529,"threshold_uncertainty_score":0.22855288},"labels":[],"label_agreement":null},{"id":"W4402946633","doi":"10.1167/jov.24.10.1129","title":"High-resolution diffusion MRI of the cortico-cortical connections between lower visual areas reveals divergence of connections and enhanced connectivity of the central visual field representation","year":2024,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; McGill University","funders":"","keywords":"Representation (politics); Diffusion MRI; Visual field; Neuroscience; Divergence (linguistics); Geology; Diffusion; Computer science; Psychology; Physics; Magnetic resonance imaging; Medicine; Philosophy; Radiology; Political science","score_opus":0.02878254338115882,"score_gpt":0.3757099250149787,"score_spread":0.34692738163381986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402946633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9304936,0.000099621044,0.06630516,0.002352414,0.0003672695,0.0003249251,0.000016890464,0.000016095062,0.000024043225],"genre_scores_gemma":[0.9989738,0.00022780879,0.0006006811,0.00003862906,0.000114123926,0.000003945514,0.0000019223137,0.000009913338,0.000029185532],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99858457,0.00012438517,0.00065021997,0.00016561586,0.0003560103,0.000119171964],"domain_scores_gemma":[0.9982396,0.000692251,0.0005010728,0.00021798722,0.00028142938,0.00006770863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023421581,0.00009856338,0.00031060606,0.000095741816,0.00014093015,0.00000936063,0.00009826347,0.000074974756,0.000030533574],"category_scores_gemma":[0.0007631761,0.000059983027,0.00020067862,0.00042217702,0.00019395692,0.0001340912,0.00010889677,0.00034265436,2.3783184e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025209165,0.00040709323,0.071620405,0.00010363064,0.00006091715,0.0000024241947,0.00018373122,0.00013424887,0.9216641,0.001942684,0.00046652858,0.003162141],"study_design_scores_gemma":[0.00041408485,0.00087223586,0.72809535,0.00077939045,0.00026676888,0.000053494317,0.00009391374,0.0021731968,0.26519564,0.0019359131,0.00006565769,0.000054378514],"about_ca_topic_score_codex":0.000066603345,"about_ca_topic_score_gemma":0.0000063701464,"teacher_disagreement_score":0.65647495,"about_ca_system_score_codex":0.000048486305,"about_ca_system_score_gemma":0.000072220224,"threshold_uncertainty_score":0.24460368},"labels":[],"label_agreement":null},{"id":"W4403021640","doi":"10.52294/001c.123347","title":"The Douglas-Bell Canada Brain Bank Post-mortem Brain Imaging Protocol","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Trois-Rivières; Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Protocol (science); Neuroscience; Medicine; Psychology; Pathology","score_opus":0.01905484560485165,"score_gpt":0.3331046117301227,"score_spread":0.314049766125271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403021640","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00044806118,0.00024543624,0.0018427368,0.9576644,0.00032919063,0.032321155,0.000039008097,0.00087057287,0.006239466],"genre_scores_gemma":[0.06279324,0.000036514983,0.002412328,0.830743,0.0014105242,0.0803467,0.00008063548,0.00030985812,0.021867152],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99865085,0.00004153175,0.00024153657,0.00044772748,0.00027798433,0.0003403926],"domain_scores_gemma":[0.99535936,0.0037603406,0.000042805663,0.0006327316,0.00007302894,0.00013174416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011530394,0.00020917674,0.00015431354,0.000042885684,0.00025862682,0.0000966863,0.00023664933,0.000034314246,0.0000386319],"category_scores_gemma":[0.0015385828,0.00013537775,0.000085361935,0.00030072912,0.000081584796,0.00008081628,0.00008685084,0.0005528965,0.000019665857],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033891665,0.000022190392,0.00016393019,0.0000810619,0.000010817185,0.0004070472,0.000027229824,0.0000011888083,0.018772198,0.003962016,0.95683473,0.01968367],"study_design_scores_gemma":[0.00022856242,0.00005484437,0.00069280347,0.0000815442,0.000015807636,0.00046467347,0.000014771389,0.0024824336,0.0012659107,0.00042020198,0.99414366,0.00013477643],"about_ca_topic_score_codex":0.0060846214,"about_ca_topic_score_gemma":0.0064166365,"teacher_disagreement_score":0.12692134,"about_ca_system_score_codex":0.000086683365,"about_ca_system_score_gemma":0.0004229096,"threshold_uncertainty_score":0.9198168},"labels":[],"label_agreement":null},{"id":"W4403090217","doi":"10.1007/978-3-031-72069-7_45","title":"TractOracle: Towards an Anatomically-Informed Reward Function for RL-Based Tractography","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Tractography; Function (biology); Artificial intelligence; Diffusion MRI; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.05447009360161693,"score_gpt":0.35388631582252805,"score_spread":0.29941622222091113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403090217","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00046901562,0.00014837502,0.9938624,0.0019883106,0.0004640755,0.0011205644,0.000041972307,0.0004928698,0.0014124357],"genre_scores_gemma":[0.5090386,0.000043218795,0.48447433,0.0048595304,0.00077869016,0.0001427984,0.00016858314,0.000124436,0.00036978468],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997826,0.0000044359713,0.0003915377,0.0009690798,0.00044343612,0.0003655386],"domain_scores_gemma":[0.9984917,0.00020338819,0.00014247045,0.00075968157,0.00021288007,0.00018990274],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002468217,0.00036373522,0.00040827144,0.00075979624,0.0001508739,0.00016647656,0.0004150441,0.00027026254,0.000022583517],"category_scores_gemma":[0.000057969683,0.0003106955,0.00022100116,0.00043806757,0.00052408,0.00019775618,0.0000714529,0.0007364332,0.0000060115635],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002078636,0.0001082962,0.00007473548,0.0003689346,0.000023247647,0.000036784822,0.00015658779,0.0015400419,0.0018087864,0.011457298,0.00018648584,0.98403096],"study_design_scores_gemma":[0.0012777193,0.0025098077,0.001284729,0.001523262,0.00028543678,0.00013146651,7.093655e-7,0.25433928,0.0100438995,0.55005705,0.17729123,0.0012553907],"about_ca_topic_score_codex":0.000006538002,"about_ca_topic_score_gemma":0.00001661751,"teacher_disagreement_score":0.98277557,"about_ca_system_score_codex":0.0002001635,"about_ca_system_score_gemma":0.00067308976,"threshold_uncertainty_score":0.9999345},"labels":[],"label_agreement":null},{"id":"W4403299410","doi":"10.52294/001c.123922","title":"Bilateral differences in structural connectivity of the afferent visual pathways of children with perinatal stroke","year":2024,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Tractography; Stroke (engine); Fractional anisotropy; Diffusion MRI; Visual cortex; Medicine; Psychology; Population; Neuroscience; Cardiology; Audiology; Magnetic resonance imaging; Radiology","score_opus":0.025756258519602258,"score_gpt":0.2943239145301624,"score_spread":0.2685676560105601,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403299410","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99727374,0.000085602536,0.00019349136,0.0018832989,0.000039347917,0.00032735436,0.00006388829,0.000057966663,0.0000753024],"genre_scores_gemma":[0.9993467,0.000013886595,0.00019478054,0.00035737848,0.000023950464,0.000015266118,0.0000053042577,0.0000141625105,0.000028623364],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993851,0.000022931541,0.00013126362,0.00020874591,0.00014759577,0.00010434227],"domain_scores_gemma":[0.99933964,0.00037256227,0.000041063766,0.00020039346,0.000020586876,0.000025752737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000019239103,0.00011003776,0.00018939393,0.000049021488,0.000024601884,0.0000073305296,0.000100205296,0.00003097327,0.000011523494],"category_scores_gemma":[0.00010138185,0.000056976944,0.000059611004,0.00017046882,0.00011952895,0.00004232696,0.000057953366,0.00025228155,2.3121484e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013003995,0.00011524018,0.8423541,0.00014309905,0.00003956482,0.000022257815,0.0003281595,0.000004756977,0.14587326,0.0048737293,0.00008763995,0.006028115],"study_design_scores_gemma":[0.00027156493,0.00033942563,0.965731,0.00012856197,0.000025485835,0.00013144969,0.00001324816,0.0016119996,0.031259187,0.00022543491,0.00019456363,0.000068046604],"about_ca_topic_score_codex":0.000027535656,"about_ca_topic_score_gemma":0.000009874202,"teacher_disagreement_score":0.123376906,"about_ca_system_score_codex":0.000011340937,"about_ca_system_score_gemma":0.000034060544,"threshold_uncertainty_score":0.23234522},"labels":[],"label_agreement":null},{"id":"W4403348570","doi":"10.1016/j.mri.2024.110255","title":"Comparisons of MR and EM inferred tissue microstructure properties using a human autopsy corpus callosum sample","year":2024,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Corpus callosum; Autopsy; Sample (material); Tissue sample; Anatomy; Pathology; Medicine; Chemistry","score_opus":0.06286301817996268,"score_gpt":0.3530613754392496,"score_spread":0.2901983572592869,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403348570","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9365272,0.042905286,0.017777443,0.0013243448,0.00008034054,0.0007113494,0.00006610491,0.00038589345,0.00022205328],"genre_scores_gemma":[0.9503043,0.00011349082,0.048885956,0.00016474056,0.000056157827,0.00002951152,0.000011326074,0.000040802064,0.00039366775],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989588,0.000017271352,0.00029348675,0.00035422033,0.0001440317,0.00023217194],"domain_scores_gemma":[0.9994557,0.000039560808,0.00005385988,0.00031752538,0.00006577452,0.00006761426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060221137,0.0001698138,0.00027788657,0.00010782831,0.00012014062,0.00007021457,0.0000917159,0.00003345387,0.000037042453],"category_scores_gemma":[0.00004279428,0.00014848456,0.000040463674,0.00023274,0.00026567376,0.000083308434,0.00009803446,0.00023082102,0.0000011618317],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020529655,0.00003936886,0.034262173,0.00037753506,0.0000049258056,0.0000501008,0.00049266964,0.000009241374,0.8667568,0.0012806305,0.00081797777,0.09588806],"study_design_scores_gemma":[0.0014288471,0.00039157574,0.22803243,0.0033640298,0.00031877836,0.0017678804,0.00040206726,0.11205413,0.14561555,0.0058842166,0.49992386,0.000816654],"about_ca_topic_score_codex":0.00029498612,"about_ca_topic_score_gemma":0.000010664713,"teacher_disagreement_score":0.7211412,"about_ca_system_score_codex":0.00003688198,"about_ca_system_score_gemma":0.000051963496,"threshold_uncertainty_score":0.6055025},"labels":[],"label_agreement":null},{"id":"W4403371687","doi":"10.7759/cureus.71389","title":"A Comparative Study of Frontal and Cerebellar Lobe Volumes Between Patients With First-Episode Schizophrenia and Healthy Controls and Its Association With Psychopathology and Neurological Soft Signs in Patients","year":2024,"lang":"en","type":"article","venue":"Cureus","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Krishna Institute Of Medical Sciences Deemed To Be University","keywords":"Medicine; Frontal lobe; Positive and Negative Syndrome Scale; Bayesian multivariate linear regression; Psychopathology; Cross-sectional study; Schizophrenia (object-oriented programming); Montreal Cognitive Assessment; Cerebellum; Internal medicine; Logistic regression; Audiology; Cognition; Psychiatry; Linear regression; Psychosis; Cognitive impairment; Pathology","score_opus":0.03062352256791595,"score_gpt":0.31694728032416525,"score_spread":0.2863237577562493,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403371687","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9975757,0.0005114607,0.00024232912,0.00033073645,0.000008717117,0.0012243749,0.000040290062,0.00004450436,0.000021870848],"genre_scores_gemma":[0.99909526,0.00006138684,0.0006697708,0.000067248395,0.0000124549715,0.00005398935,0.000012297193,0.000015660686,0.000011928872],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999215,0.00004875382,0.00016676214,0.0003309537,0.0001121208,0.00012640624],"domain_scores_gemma":[0.9995536,0.0001460043,0.00009072829,0.00008588175,0.000050508228,0.00007328309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058445494,0.00012445511,0.00033586027,0.0000556985,0.00005249774,0.000013402384,0.000024628673,0.000053718828,0.0000017617734],"category_scores_gemma":[0.000031260453,0.0000900332,0.000006191874,0.00008903516,0.00006753568,0.00006646834,0.0000395157,0.00016634616,2.6171543e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054694444,0.00032385072,0.9979413,0.000037937487,0.000027631404,0.000003543631,0.00044629586,8.343116e-7,0.000016346821,0.000031851778,0.00005582452,0.0005676437],"study_design_scores_gemma":[0.0047584884,0.008175155,0.9861895,0.00005545318,0.00008777144,0.000003230665,0.00004918484,0.00036951783,0.0000070212077,0.000095930736,0.00012456093,0.00008422134],"about_ca_topic_score_codex":0.000024063324,"about_ca_topic_score_gemma":0.00017556643,"teacher_disagreement_score":0.0117518315,"about_ca_system_score_codex":0.000016298423,"about_ca_system_score_gemma":0.000008704721,"threshold_uncertainty_score":0.36714476},"labels":[],"label_agreement":null},{"id":"W4403553634","doi":"10.1007/978-981-97-8043-3_68","title":"Identifying Neuronal Damage and Plasticity by Analyzing Changes in Diffusion Tensor Imaging","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Diffusion MRI; Plasticity; Neuroscience; Diffusion; Psychology; Medicine; Materials science; Physics; Radiology; Magnetic resonance imaging","score_opus":0.018343899781031996,"score_gpt":0.27741319465665204,"score_spread":0.25906929487562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403553634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024202319,0.019167071,0.9422766,0.007154241,0.0002651874,0.0019335258,0.00008024261,0.0015843787,0.0033364212],"genre_scores_gemma":[0.98139596,0.002331642,0.011951033,0.0008549,0.00042425908,0.00008920419,0.00009996332,0.00036460953,0.0024884206],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985434,0.0000047950393,0.00028833878,0.0006003744,0.00019034096,0.0003727564],"domain_scores_gemma":[0.9993355,0.0003201827,0.00005455003,0.000171863,0.000020873775,0.0000969919],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006161279,0.00036977718,0.00046049152,0.0006649599,0.00003342531,0.000041715768,0.000094444425,0.00018689065,0.000013591709],"category_scores_gemma":[0.00018373979,0.00036123197,0.00006484322,0.00026918988,0.00003424519,0.00004020339,0.000110257475,0.0017054082,0.000002410249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021278446,0.00024546916,0.011452289,0.002995729,0.00015304225,0.0025559638,0.00038310068,0.011033226,0.72722346,0.025834037,0.00042141028,0.21748948],"study_design_scores_gemma":[0.0013862981,0.0003269658,0.007189718,0.005272427,0.00041375397,0.0005185072,0.0000015313351,0.90320635,0.013980233,0.0332843,0.032530207,0.0018896968],"about_ca_topic_score_codex":0.000012942376,"about_ca_topic_score_gemma":0.000013824257,"teacher_disagreement_score":0.9571937,"about_ca_system_score_codex":0.00018871178,"about_ca_system_score_gemma":0.0000171815,"threshold_uncertainty_score":0.99988395},"labels":[],"label_agreement":null},{"id":"W4403588636","doi":"10.1162/imag_a_00356","title":"Hippocampal microscopic fractional anisotropy is reduced in temporal lobe epilepsy","year":2024,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Fractional anisotropy; Diffusion MRI; Temporal lobe; Subiculum; White matter; Magnetic resonance imaging; Axon; Hippocampal formation; Epilepsy surgery; Epilepsy; Neuroscience; Medicine; Dentate gyrus; Pathology; Psychology; Radiology","score_opus":0.05245541796340334,"score_gpt":0.38512766917043356,"score_spread":0.3326722512070302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403588636","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83790165,0.0008514455,0.10305641,0.05150133,0.0015310087,0.0009523431,0.000056849527,0.0015522935,0.0025966766],"genre_scores_gemma":[0.98342365,0.00005990015,0.01030693,0.005465767,0.0000942828,0.000041114767,0.0000051940997,0.000027538747,0.0005756175],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985574,0.000017757107,0.00022597567,0.0006408975,0.00024808347,0.0003098727],"domain_scores_gemma":[0.99945,0.000044904882,0.00003696565,0.00033127744,0.000032747466,0.00010408625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010819861,0.00014459524,0.00014396996,0.00021206269,0.00010725438,0.00010954662,0.00017906897,0.000022799728,0.00004074103],"category_scores_gemma":[0.00007446455,0.00013865127,0.000060200735,0.00077370333,0.00024102071,0.00030656194,0.000070399605,0.00037631197,0.000044483444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014473645,0.00011190619,0.084506065,0.000045934936,8.095149e-7,0.00031567353,0.000083541076,0.00001189622,0.9001831,0.0016761234,0.0079591125,0.0050913934],"study_design_scores_gemma":[0.0010021069,0.0002401089,0.37375444,0.00077948475,0.00004465641,0.0026964685,0.000062299514,0.08379973,0.14889385,0.022225404,0.3657414,0.0007600541],"about_ca_topic_score_codex":0.000031103395,"about_ca_topic_score_gemma":5.160865e-7,"teacher_disagreement_score":0.75128925,"about_ca_system_score_codex":0.0000843496,"about_ca_system_score_gemma":0.00016146798,"threshold_uncertainty_score":0.5654035},"labels":[],"label_agreement":null},{"id":"W4403706251","doi":"10.1016/j.mri.2024.110265","title":"Corrigendum to “Modelling white matter microstructure using diffusion OGSE MRI: Model and analysis choices” [Magnetic Resonance Imaging 113 (2024) 110221]","year":2024,"lang":"en","type":"erratum","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Magnetic resonance imaging; Diffusion MRI; Diffusion-Weighted Magnetic Resonance Imaging; Nuclear magnetic resonance; White matter; Materials science; Medicine; Physics; Radiology","score_opus":0.026316507779777686,"score_gpt":0.30002112444735946,"score_spread":0.2737046166675818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403706251","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0063880007,0.65293396,0.29137033,0.015191859,0.011440263,0.005560684,0.0018407855,0.0016744867,0.013599645],"genre_scores_gemma":[0.007049647,0.011276056,0.25978583,0.011313606,0.0022160418,0.00059576484,0.00079710985,0.0011058459,0.7058601],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9931267,0.000083680075,0.0012991889,0.0030330895,0.00096546597,0.0014918952],"domain_scores_gemma":[0.9964585,0.000054566663,0.00038579424,0.002150901,0.00037828786,0.00057199993],"candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.0002979248,0.0013891782,0.0016585022,0.0015590109,0.0005540274,0.00061313034,0.00071422214,0.00033612901,0.0004767663],"category_scores_gemma":[0.00004719214,0.0013871049,0.00052042963,0.0025423695,0.00041616702,0.00030003328,0.00095831364,0.002657989,0.00007326902],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001709169,0.00014434295,0.05623606,0.0011594762,0.000054761116,0.0006891569,0.0008350419,0.0050729564,0.004359285,0.0000792945,0.8385601,0.09263862],"study_design_scores_gemma":[0.00034876488,0.000039693536,0.010826116,0.0015278533,0.0013285031,0.00026894768,0.000040303483,0.5629669,0.00002062086,0.00067542575,0.42111197,0.0008448942],"about_ca_topic_score_codex":0.0003242073,"about_ca_topic_score_gemma":0.000028964414,"teacher_disagreement_score":0.69226044,"about_ca_system_score_codex":0.0004131805,"about_ca_system_score_gemma":0.0003087339,"threshold_uncertainty_score":0.99988586},"labels":[],"label_agreement":null},{"id":"W4404061408","doi":"10.1038/s41380-024-02784-2","title":"White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Ontario Brain Institute; Centre for Addiction and Mental Health; Dalhousie University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; Norges Forskningsråd; National Health and Medical Research Council; Stiftelsen för Strategisk Forskning; Hjärnfonden; U.S. Department of Health and Human Services; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche; National Institute of Mental Health; Vetenskapsrådet; Government of Canada; Deutsche Forschungsgemeinschaft","keywords":"Bipolar disorder; Psychology; White matter; Psychiatry; Obesity; Medicine; Cognition; Internal medicine; Magnetic resonance imaging","score_opus":0.012956464741473692,"score_gpt":0.30532487556777693,"score_spread":0.2923684108263032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404061408","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9731934,0.018401824,0.0039290795,0.0030595146,0.00013350708,0.001055022,0.000013792933,0.00016542885,0.000048432277],"genre_scores_gemma":[0.98610675,0.0002819814,0.012252724,0.0010698739,0.000051011786,0.00009981693,0.00003908021,0.00007310366,0.000025665133],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99843866,0.00009400607,0.00031168605,0.0006719898,0.00017674976,0.0003069001],"domain_scores_gemma":[0.99934125,0.000015148699,0.00004126275,0.0005018162,0.000009270511,0.00009125546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018633417,0.00025015257,0.00026813935,0.00038459437,0.000069446935,0.00008396601,0.00015224246,0.000098247496,0.000028873292],"category_scores_gemma":[0.000006282422,0.000239724,0.000060316914,0.0007101184,0.000061287144,0.00012653718,0.00011024153,0.000605736,0.0000071618247],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000131076295,0.0005483554,0.9917389,0.00009190625,0.00001772385,0.000041841737,0.00053076836,0.000007790402,0.0013157122,0.00042686332,0.00009589552,0.0051711206],"study_design_scores_gemma":[0.000740452,0.00017325731,0.97782254,0.00023426647,0.000052419102,0.000051264666,0.0003498794,0.00014619646,0.000034419645,0.0065888325,0.0135471225,0.00025937214],"about_ca_topic_score_codex":0.00010234692,"about_ca_topic_score_gemma":0.00065847614,"teacher_disagreement_score":0.018119844,"about_ca_system_score_codex":0.00003269509,"about_ca_system_score_gemma":0.00003240071,"threshold_uncertainty_score":0.9775661},"labels":[],"label_agreement":null},{"id":"W4404089810","doi":"10.1152/jn.00408.2024","title":"Magnetic resonance diffusion tensor imaging for detecting the cerebral microstructure changes in patients with CSVD-induced mild cognitive impairment","year":2024,"lang":"en","type":"article","venue":"Journal of Neurophysiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Entorhinal cortex; Hippocampus; Fractional anisotropy; Diffusion MRI; Receiver operating characteristic; Atrophy; Internal medicine; Montreal Cognitive Assessment; Dementia; Medicine; Cardiology; Psychology; Magnetic resonance imaging; Disease; Radiology","score_opus":0.022220803669820835,"score_gpt":0.29912103811219903,"score_spread":0.2769002344423782,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404089810","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99611163,0.00021588377,0.00021419433,0.0027115082,0.000117202515,0.00058683904,0.000012822005,0.000025300658,0.0000045981146],"genre_scores_gemma":[0.9973522,0.000047966612,0.0011857483,0.0011686889,0.00016936233,0.000027024096,0.0000027690478,0.0000295331,0.000016749169],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992653,0.00003805518,0.00021201945,0.00019607751,0.00009918457,0.00018934465],"domain_scores_gemma":[0.9993954,0.00018228292,0.00011942454,0.000116967574,0.0001471244,0.000038853887],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003271891,0.00012276984,0.00020749785,0.00011451803,0.00007514785,0.0000143039315,0.00008894158,0.000026849271,0.000004248594],"category_scores_gemma":[0.000060820716,0.000069076654,0.000061968865,0.00017583522,0.000062113184,0.000043220614,0.000039658873,0.00039547269,5.77242e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003648796,0.0003192248,0.05047333,0.00020161437,0.000024427902,0.00020688122,0.00048265315,0.000019100635,0.84195846,0.00004512488,0.00021096092,0.102409415],"study_design_scores_gemma":[0.0018825266,0.0031645936,0.9879201,0.00047218375,0.00007084512,0.00022446108,0.000057132744,0.0010427984,0.00375029,0.0003622052,0.00095859054,0.000094238894],"about_ca_topic_score_codex":0.000002098332,"about_ca_topic_score_gemma":0.0000010614414,"teacher_disagreement_score":0.93744683,"about_ca_system_score_codex":0.000033619686,"about_ca_system_score_gemma":0.00003107919,"threshold_uncertainty_score":0.28168643},"labels":[],"label_agreement":null},{"id":"W4404130284","doi":"10.1101/2024.11.07.24316876","title":"Transdiagnostic alterations in white matter microstructure associated with suicidal thoughts and behaviours in the ENIGMA Suicidal Thoughts and Behaviours consortium","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Dalhousie University","funders":"Instituto de Salud Carlos III; National Institutes of Health; Canadian Institutes of Health Research; Junta de Andalucía; National Institute of Mental Health; Ministero della Salute; Japan Society for the Promotion of Science; National Health and Medical Research Council; Dalhousie University; Universiteit Leiden; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Agence Nationale de la Recherche; Wellcome Trust; Instituto de Investigación Marqués de Valdecilla; European Commission; Japan Agency for Medical Research and Development; Bundesministerium für Bildung und Forschung; National Alliance for Research on Schizophrenia and Depression; University of Minnesota; Deutsche Forschungsgemeinschaft; Nova Scotia Health Research Foundation; Medical Research Council; American Foundation for Suicide Prevention","keywords":"Fractional anisotropy; Corpus callosum; Suicidal ideation; Psychology; White matter; Diffusion MRI; Psychiatry; Medicine; Clinical psychology; Poison control; Injury prevention; Neuroscience; Magnetic resonance imaging","score_opus":0.030427590266131534,"score_gpt":0.317941579987709,"score_spread":0.2875139897215775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404130284","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98721176,0.0011252085,0.0004620058,0.0085963,0.000095590585,0.0018512437,0.00042806132,0.00013165726,0.00009817574],"genre_scores_gemma":[0.99629235,0.000178701,0.0014629776,0.0008606888,0.00012164146,0.00046136865,0.00034732634,0.000082984974,0.00019193493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978441,0.00016826636,0.00047993462,0.00082947506,0.0002807368,0.0003974658],"domain_scores_gemma":[0.99883604,0.0002630214,0.00014346406,0.0005762866,0.00006832828,0.00011288798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031531803,0.0004509682,0.00054342573,0.00028300952,0.00011622417,0.00014940699,0.00021499759,0.00030303796,0.000014942327],"category_scores_gemma":[0.00005466003,0.00031811235,0.000077658675,0.00035974995,0.00033925148,0.000059339127,0.00016750857,0.0018712225,0.0000018138765],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000509788,0.00018222204,0.9951422,0.00012789441,0.000023058608,0.00086560065,0.0020885041,0.000031052798,0.000765961,0.00017976413,0.00042397942,0.00011874824],"study_design_scores_gemma":[0.0007018777,0.000093303235,0.993582,0.0005457865,0.00043748989,0.00051241374,0.00009273239,0.00021491098,0.0012411625,0.0021567498,0.000074480035,0.00034710928],"about_ca_topic_score_codex":0.00019282932,"about_ca_topic_score_gemma":0.0041714236,"teacher_disagreement_score":0.00908062,"about_ca_system_score_codex":0.00007440912,"about_ca_system_score_gemma":0.000105634506,"threshold_uncertainty_score":0.9999271},"labels":[],"label_agreement":null},{"id":"W4404289864","doi":"10.2196/64825","title":"Multiparametric MRI Assessment of Morpho-Functional Muscle Changes Following a 6-Month FES-Cycling Training Program: Pilot Study in People With a Complete Spinal Cord Injury","year":2024,"lang":"en","type":"article","venue":"JMIR Rehabilitation and Assistive Technologies","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Istituto Nazionale per l'Assicurazione Contro Gli Infortuni sul Lavoro; Ministero della Salute","keywords":"Spinal cord injury; Cycling; Functional electrical stimulation; Physical medicine and rehabilitation; Back muscles; Medicine; Preprint; Training (meteorology); Physical therapy; Spinal cord; Psychology; Neuroscience; Computer science; Internal medicine; Stimulation; Physics","score_opus":0.11753916975689538,"score_gpt":0.4294734938374198,"score_spread":0.3119343240805244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404289864","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9836457,0.0001519668,0.009031739,0.0026806998,0.00002941025,0.00316887,0.000016389331,0.0011905782,0.000084654224],"genre_scores_gemma":[0.8860678,0.000016143204,0.11088257,0.000014399232,0.000008083134,0.002968566,0.000010817454,0.000019764871,0.000011815906],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987521,0.000037402522,0.0002912962,0.00048696325,0.00024479,0.00018742765],"domain_scores_gemma":[0.999212,0.0003717449,0.00010074945,0.00020449118,0.000082119455,0.000028885901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002583774,0.0001776696,0.00035979837,0.0006798769,0.0000903387,0.00003475817,0.000071536066,0.000043806984,0.000002294773],"category_scores_gemma":[0.0002423519,0.000141895,0.00004949059,0.0013837689,0.00021730774,0.000103376566,0.000070748436,0.00033602692,3.6790055e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008280697,0.0025755446,0.36233935,0.00044978413,0.000092207236,0.000038939976,0.0005634721,0.000017570153,0.0144169405,0.0020395294,0.000059952778,0.61657864],"study_design_scores_gemma":[0.00078815065,0.024942288,0.9599959,0.0005948549,0.000052402265,0.000011725205,0.009731787,0.0027393717,0.00007796596,0.0004959909,0.00041786217,0.0001516706],"about_ca_topic_score_codex":0.000036625504,"about_ca_topic_score_gemma":0.000061030765,"teacher_disagreement_score":0.61642694,"about_ca_system_score_codex":0.00012769451,"about_ca_system_score_gemma":0.00006900825,"threshold_uncertainty_score":0.57863104},"labels":[],"label_agreement":null},{"id":"W4404339721","doi":"10.3389/fphys.2024.1487953","title":"A diffusion tensor imaging-based multidimensional study of brain structural changes after long-term high-altitude exposure and their relationships with cognitive function","year":2024,"lang":"en","type":"article","venue":"Frontiers in Physiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; White matter; Corpus callosum; Cognition; Effects of high altitude on humans; Montreal Cognitive Assessment; Psychology; Magnetic resonance imaging; Medicine; Internal medicine; Audiology; Cognitive impairment; Neuroscience","score_opus":0.021523040737430884,"score_gpt":0.28622009124766096,"score_spread":0.26469705051023007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404339721","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98151076,0.0007298228,0.01604417,0.0007744997,0.00010794977,0.0007193925,0.000027474454,0.00008353768,0.0000024097787],"genre_scores_gemma":[0.99589795,0.000011507337,0.0034792759,0.00024261016,0.000046131936,0.00019691086,0.000082100756,0.000021869644,0.00002161603],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992275,0.000080173806,0.00013997694,0.00035082712,0.00007237884,0.00012913371],"domain_scores_gemma":[0.9995675,0.00013374315,0.000050875486,0.00015246849,0.000059091948,0.000036332247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000053445798,0.00014256641,0.00023877957,0.00018579,0.000055864697,0.00000462863,0.000029302091,0.00004482304,0.000007390688],"category_scores_gemma":[0.000024604897,0.00009739239,0.00002174332,0.00016902147,0.00016270283,0.00005052724,0.00003371977,0.0002598165,3.9078003e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016016116,0.0002577111,0.96978074,0.00011644521,0.00006375026,0.000034078923,0.0006507256,0.0000284546,0.020516625,0.00004328841,0.00015473775,0.0067518153],"study_design_scores_gemma":[0.0014924296,0.0007898887,0.99154013,0.00023426088,0.000077188655,0.000015880345,0.00047731982,0.0041852053,0.00044932534,0.000619814,0.000019960415,0.00009859226],"about_ca_topic_score_codex":0.000012539058,"about_ca_topic_score_gemma":0.000037004746,"teacher_disagreement_score":0.021759378,"about_ca_system_score_codex":0.000023863255,"about_ca_system_score_gemma":0.000022482964,"threshold_uncertainty_score":0.39715463},"labels":[],"label_agreement":null},{"id":"W4404340498","doi":"10.1093/braincomms/fcae353","title":"Compensatory mechanisms amidst demyelinating disorders: insights into cognitive preservation","year":2024,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Queen's University; McGill University; Montreal Neurological Institute and Hospital; Hospital for Sick Children","funders":"Canadian Institutes of Health Research; Health Canada; Government of Canada; Ontario Institute for Regenerative Medicine; Hospital for Sick Children; Canadian Bee Research Fund; Fondation Brain Canada","keywords":"Neuroscience; Cognition; Multiple sclerosis; Saccade; Psychology; Magnetoencephalography; Diffusion MRI; Neuroimaging; Tractography; White matter; Myelin; Eye movement; Magnetic resonance imaging; Medicine; Electroencephalography; Central nervous system; Psychiatry","score_opus":0.09096486323302172,"score_gpt":0.40057447805293295,"score_spread":0.3096096148199112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404340498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01156695,0.0047219503,0.8548735,0.102555186,0.00008662635,0.0017155563,0.000022769871,0.0025316044,0.021925895],"genre_scores_gemma":[0.9120066,0.00070922065,0.084121354,0.0018107479,0.00004057218,0.00043210428,0.00028562694,0.00004297436,0.00055077346],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99907994,0.00008630772,0.0002664664,0.0002761312,0.00015366594,0.00013750874],"domain_scores_gemma":[0.9977865,0.00092917104,0.00005810204,0.0010234806,0.000128209,0.000074501746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015840764,0.00013141801,0.0001482789,0.0001584796,0.00039575293,0.00005410017,0.00035224148,0.00006168582,0.000023179073],"category_scores_gemma":[0.00030752248,0.00013018919,0.00007567168,0.0005019215,0.00019197894,0.00026437442,0.00032187125,0.0003954989,0.000060683353],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012942846,0.00033577764,0.00028928075,0.000167353,0.00007075758,0.0000040988357,0.002132142,0.000008922888,0.02281517,0.88343567,0.004540724,0.08618717],"study_design_scores_gemma":[0.00055596785,0.00016330775,0.005103553,0.0010808515,0.00014886456,0.000028360666,0.0009681573,0.10218029,0.0028123013,0.51426727,0.37231502,0.00037604006],"about_ca_topic_score_codex":0.00004359673,"about_ca_topic_score_gemma":0.00008226522,"teacher_disagreement_score":0.9004397,"about_ca_system_score_codex":0.00008443075,"about_ca_system_score_gemma":0.00008377805,"threshold_uncertainty_score":0.53089607},"labels":[],"label_agreement":null},{"id":"W4404349164","doi":"10.1038/s41583-024-00878-y","title":"Reply to ‘Issues of parcellation in the calculation of structure–function coupling’","year":2024,"lang":"en","type":"review","venue":"Nature reviews. Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Coupling (piping); Function (biology); Psychology; Statistical physics; Computer science; Mathematics; Physics; Materials science","score_opus":0.12526227443637436,"score_gpt":0.4734032259864475,"score_spread":0.3481409515500732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404349164","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000020457144,0.99510175,0.0013185008,0.00051319046,0.00020369655,0.0027121531,0.000023465594,0.000037671238,0.00006913151],"genre_scores_gemma":[0.0014133,0.9958698,0.0014983242,0.0009081445,0.00008435138,0.00009451246,0.000032799202,0.000025220159,0.00007355005],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99794275,0.00008657512,0.0008647433,0.00055416115,0.00040807264,0.00014368145],"domain_scores_gemma":[0.99849707,0.00009514899,0.0005010691,0.000778504,0.000087382075,0.000040809533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057448813,0.00024809726,0.001057573,0.00030201534,0.000036118385,0.00001536611,0.00033367236,0.0001748832,0.0000027142582],"category_scores_gemma":[0.00062679563,0.00014080894,0.00026563456,0.00236335,0.000089015695,0.000053524487,0.00006623488,0.0009238643,0.000003589573],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011161377,0.00008106749,0.000051743093,0.03345248,0.0000048105544,0.000008186712,0.00008672886,0.000035279274,0.0011756957,0.0036982838,0.005761833,0.95563275],"study_design_scores_gemma":[0.000026423702,0.00009912467,0.00019908794,0.0107453,0.00036824017,0.00004587331,0.0000011881605,0.00011365402,0.000043920834,0.00027394082,0.9879871,0.00009612133],"about_ca_topic_score_codex":0.000006682673,"about_ca_topic_score_gemma":0.0000010647648,"teacher_disagreement_score":0.9822253,"about_ca_system_score_codex":0.00004210798,"about_ca_system_score_gemma":0.000096497744,"threshold_uncertainty_score":0.5742022},"labels":[],"label_agreement":null},{"id":"W4404395863","doi":"10.52202/079017-0425","title":"On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Computer science; Metadata; Artificial intelligence; Machine learning; Training (meteorology); Generative model; Generative grammar; Transfer of learning; Field (mathematics); Training set; Data mining; Mathematics","score_opus":0.08187471162418929,"score_gpt":0.37248853495099205,"score_spread":0.29061382332680274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404395863","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024929313,0.000038745547,0.96960044,0.0010494292,0.000024660068,0.00050220947,0.000012413048,0.00053591526,0.0033068464],"genre_scores_gemma":[0.88109255,0.00002108468,0.11741805,0.0004706907,0.000025383351,0.00018345051,0.0000221747,0.000017552378,0.00074907596],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995741,0.000002319132,0.00008310823,0.00019870991,0.000045603345,0.00009612887],"domain_scores_gemma":[0.99975324,0.0000819504,0.000012213389,0.00009567913,0.000018916362,0.000037993726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000041825104,0.000069746995,0.000082727856,0.00004536114,0.000076224635,0.000050937135,0.000020172842,0.000027265634,0.0000132299065],"category_scores_gemma":[0.000008316833,0.000054271815,0.0000268584,0.000044626322,0.000020419699,0.000110563116,0.000014868377,0.000076310054,6.749971e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015219728,0.000012125481,2.603296e-7,0.000051650528,0.000004636229,0.0000013721028,0.00015569561,0.000051764295,0.13573048,0.8575882,0.0002205066,0.0061681317],"study_design_scores_gemma":[0.00016531638,0.00019752774,0.000011159957,0.00010203743,0.000018408731,0.000016723558,0.00023762503,0.3395526,0.004829424,0.65437317,0.00044477955,0.000051231145],"about_ca_topic_score_codex":0.000003631154,"about_ca_topic_score_gemma":6.518391e-7,"teacher_disagreement_score":0.8561632,"about_ca_system_score_codex":0.000012642074,"about_ca_system_score_gemma":0.000030085128,"threshold_uncertainty_score":0.22131404},"labels":[],"label_agreement":null},{"id":"W4404579697","doi":"10.1016/j.compbiomed.2024.109410","title":"Deep learning-based denoising for unbiased analysis of morphology and stiffness in amyloid fibrils","year":2024,"lang":"en","type":"article","venue":"Computers in Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Ministry of Science and ICT, South Korea; Korea Health Industry Development Institute; Information Technology Research Centre; Ministry of Health and Welfare","keywords":"Morphology (biology); Amyloid fibril; Stiffness; Noise reduction; Amyloid (mycology); Artificial intelligence; Computer science; Biological system; Pattern recognition (psychology); Materials science; Amyloid β; Chemistry; Biology; Composite material; Medicine; Internal medicine; Disease","score_opus":0.048127487474445,"score_gpt":0.397424460641367,"score_spread":0.349296973166922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404579697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6717438,0.0025253817,0.3229465,0.0024199248,0.00005039671,0.00022416294,0.0000025792845,0.00007852889,0.000008759221],"genre_scores_gemma":[0.99172926,0.00027099162,0.0073911543,0.00048629165,0.00003250766,0.00002259133,0.000052294898,0.000010545401,0.0000043472123],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993346,0.00003470925,0.00021936318,0.00026517292,0.000024329956,0.00012182367],"domain_scores_gemma":[0.9992932,0.00050713494,0.00003906567,0.000098752505,0.00002261676,0.000039209037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019433796,0.00008319183,0.00038869798,0.00056446856,0.000021323067,0.0000017056964,0.00003487866,0.000071234426,0.000002000728],"category_scores_gemma":[0.00009322387,0.000066276836,0.000027521759,0.00050259655,0.00031695236,0.000012480842,0.000021872991,0.00014093937,6.878999e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007944408,0.00019736709,0.4970234,0.0011553633,0.00043682757,0.00017365412,0.0012723339,0.0037780388,0.09990226,0.0142306965,0.0002579021,0.38077772],"study_design_scores_gemma":[0.0032808997,0.0010829523,0.44661346,0.0009875263,0.0006863708,0.00006637381,0.00011145222,0.53679657,0.0011635537,0.005947585,0.003076353,0.00018690721],"about_ca_topic_score_codex":0.000030086481,"about_ca_topic_score_gemma":0.00001362757,"teacher_disagreement_score":0.5330185,"about_ca_system_score_codex":0.00001644365,"about_ca_system_score_gemma":0.000014808532,"threshold_uncertainty_score":0.2702691},"labels":[],"label_agreement":null},{"id":"W4404903795","doi":"10.3390/life14121580","title":"Enhancing Amyloid PET Quantification: MRI-Guided Super-Resolution Using Latent Diffusion Models","year":2024,"lang":"en","type":"article","venue":"Life","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Strong; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Arizona State University; Biogen; Eli Lilly and Company; BioClinica; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Positron emission tomography; Neuroimaging; Partial volume; Leverage (statistics); Statistical power; Pet imaging; Magnetic resonance imaging; Amyloid (mycology); Computer science; Artificial intelligence; Biomedical engineering; Nuclear medicine; Medicine; Pathology; Neuroscience; Radiology; Mathematics; Biology","score_opus":0.16426662318476207,"score_gpt":0.3816011422324775,"score_spread":0.21733451904771542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404903795","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.348892,0.000480926,0.6452296,0.003990451,0.00013421141,0.00033906146,0.000008752015,0.00060669205,0.00031828845],"genre_scores_gemma":[0.94704145,0.0002481142,0.051395476,0.0005002473,0.00022564355,0.00004412441,0.00005037748,0.00003691327,0.00045763384],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998987,0.000017305807,0.0002765474,0.00034823557,0.00018822744,0.00018266025],"domain_scores_gemma":[0.9993899,0.000034495417,0.000036533267,0.00036635814,0.00005889619,0.00011380805],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011271144,0.00012017026,0.00015031642,0.000103416285,0.00013243937,0.000041562103,0.0000685941,0.00003373725,0.000038481176],"category_scores_gemma":[0.000033381744,0.000108357955,0.00007643349,0.000267827,0.000037176065,0.00015258553,0.00005046762,0.00017181374,0.000040596093],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015979542,0.00008479811,0.00023781783,0.00014728052,0.000013358269,0.000031607855,0.0001421404,0.002874759,0.97469443,0.018648852,0.0025136678,0.0005953031],"study_design_scores_gemma":[0.0002239564,0.000035093242,0.0007135062,0.0004157963,0.00009411644,0.00024701766,0.000032781092,0.94456375,0.03883514,0.003317539,0.01132735,0.00019395124],"about_ca_topic_score_codex":0.000045603083,"about_ca_topic_score_gemma":0.0000018390917,"teacher_disagreement_score":0.941689,"about_ca_system_score_codex":0.00008415441,"about_ca_system_score_gemma":0.00006593634,"threshold_uncertainty_score":0.44187093},"labels":[],"label_agreement":null},{"id":"W4404933030","doi":"10.1038/s41380-024-02821-0","title":"Deciphering white matter microstructural alterations in catatonia according to ICD-11: replication and machine learning analysis","year":2024,"lang":"en","type":"article","venue":"Molecular Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft; Physicians' Services Incorporated Foundation","keywords":"Catatonia; Psychomotor learning; Cohort; White matter; Fractional anisotropy; Corpus callosum; Psychology; Magnetic resonance imaging; Replication (statistics); Psychomotor retardation; Psychiatry; Medicine; Internal medicine; Neuroscience; Cognition; Pathology; Radiology; Schizophrenia (object-oriented programming); Virology","score_opus":0.0168071735524025,"score_gpt":0.3306560348096529,"score_spread":0.31384886125725037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404933030","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8086581,0.0006583192,0.17791863,0.012122357,0.000049724855,0.0002776471,0.000008612852,0.00015342026,0.00015316292],"genre_scores_gemma":[0.91402984,0.000016857946,0.08407183,0.001498514,0.00003129424,0.000072056435,0.00008546776,0.00003083697,0.0001633134],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990257,0.000020059771,0.00021823599,0.0004926089,0.000083893734,0.00015948579],"domain_scores_gemma":[0.99945176,0.00001162671,0.000029814126,0.00041694543,0.000021732953,0.000068149006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085155734,0.00012365733,0.00016330523,0.0003137457,0.00007963171,0.00008218487,0.00006333166,0.0000305697,0.000025526917],"category_scores_gemma":[0.000015290554,0.00012339946,0.00007307523,0.00087924977,0.000017267252,0.000070417474,0.000057020272,0.00021401011,0.000013972886],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012657445,0.000017684844,0.93106574,0.00006274522,0.000053895754,0.000018137222,0.00014427598,0.0011033533,0.06455677,0.0008891006,0.0002206385,0.001855],"study_design_scores_gemma":[0.0005983462,0.00010582194,0.91556835,0.0004371157,0.0008332827,0.00045262076,0.00022138354,0.05332119,0.012523731,0.0023055244,0.012986464,0.0006461692],"about_ca_topic_score_codex":0.000057806985,"about_ca_topic_score_gemma":0.000055655186,"teacher_disagreement_score":0.1053717,"about_ca_system_score_codex":0.000039903593,"about_ca_system_score_gemma":0.00002239544,"threshold_uncertainty_score":0.50320834},"labels":[],"label_agreement":null},{"id":"W4405030241","doi":"10.48550/arxiv.2411.19339","title":"Towards a Mechanistic Explanation of Diffusion Model Generalization","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Alliance de recherche numérique du Canada; Compute Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs; Canadian Institute for Advanced Research","keywords":"Generalization; Diffusion; Computer science; Statistical physics; Mathematical economics; Epistemology; Economics; Philosophy; Physics; Thermodynamics","score_opus":0.17553938457602006,"score_gpt":0.2696021957492422,"score_spread":0.09406281117322216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405030241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20391975,0.000032596305,0.79290044,0.0001873728,0.00006341243,0.0003797246,0.00005744486,0.00023226577,0.0022269587],"genre_scores_gemma":[0.98984474,0.00045208345,0.007708895,0.00006961272,0.000036586538,0.0000039849524,0.00017580502,0.000029695104,0.0016785923],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999168,0.000015848547,0.00016248469,0.00047590173,0.00007215024,0.000105622436],"domain_scores_gemma":[0.9991906,0.000010877807,0.00013386236,0.0004597239,0.00014032926,0.00006460378],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005472001,0.00015716928,0.000225325,0.00022429788,0.00003844827,0.000008695106,0.00014074838,0.00014712349,0.000017252894],"category_scores_gemma":[0.000020149473,0.0001691926,0.00012141605,0.0002722659,0.00004045177,0.000029974663,0.00043908326,0.00029159937,0.0000078312905],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007357712,0.00017350214,0.00018289022,0.0007142916,0.00004995301,0.00007328252,0.00010227228,0.23704773,0.012816604,0.7470331,0.0008634845,0.0008692791],"study_design_scores_gemma":[0.0001434018,0.000026421852,0.000059562615,0.00017780789,0.00020426884,0.0000037954044,0.000010494602,0.7043096,0.0020847102,0.2927806,0.000099429664,0.00009995068],"about_ca_topic_score_codex":0.000041575815,"about_ca_topic_score_gemma":0.0000031450656,"teacher_disagreement_score":0.785925,"about_ca_system_score_codex":0.00013509026,"about_ca_system_score_gemma":0.00012891783,"threshold_uncertainty_score":0.6899474},"labels":[],"label_agreement":null},{"id":"W4405303900","doi":"10.1109/tci.2024.3516574","title":"FgC2F-UDiff: Frequency-Guided and Coarse-to-Fine Unified Diffusion Model for Multi-Modality Missing MRI Synthesis","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Computational Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modality (human–computer interaction); Computer science; Artificial intelligence; Computer vision","score_opus":0.1243962032311734,"score_gpt":0.3944708048256058,"score_spread":0.2700746015944324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405303900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067491448,0.000065623535,0.97258013,0.018953703,0.00011365795,0.0007543111,0.00018676666,0.0005319603,0.00006472068],"genre_scores_gemma":[0.5829616,0.000012492898,0.41602075,0.0005924842,0.000027448375,0.00017865299,0.000016812957,0.000038126334,0.000151634],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987022,0.000022064278,0.00032284769,0.00052847393,0.00020268571,0.00022171038],"domain_scores_gemma":[0.99902016,0.00041276845,0.000041306383,0.00020913621,0.00015162614,0.00016498589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014074851,0.00020887017,0.00022700006,0.00028121742,0.00034442445,0.00008329424,0.00007417818,0.000040233488,0.000011608733],"category_scores_gemma":[0.000023112576,0.00020811439,0.0001173878,0.0002687889,0.000084759595,0.00015631747,0.0000033574574,0.00022544888,0.0000073215747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016942226,0.0007576033,0.0000910439,0.0005513873,0.0001177409,0.00003891674,0.00064992026,0.6887256,0.08626601,0.0053486535,0.0015557294,0.215728],"study_design_scores_gemma":[0.00044215826,0.000025117937,0.00020757773,0.00031390428,0.00012337569,0.00009542437,0.000016086777,0.980013,0.005893932,0.0124644535,0.00021195426,0.00019298166],"about_ca_topic_score_codex":0.000023615006,"about_ca_topic_score_gemma":0.0000042416505,"teacher_disagreement_score":0.57621247,"about_ca_system_score_codex":0.000120780256,"about_ca_system_score_gemma":0.00010592141,"threshold_uncertainty_score":0.84866583},"labels":[],"label_agreement":null},{"id":"W4405372902","doi":"10.3390/brainsci14121252","title":"Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation","year":2024,"lang":"en","type":"article","venue":"Brain Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Hebei University","keywords":"Neuroimaging; Diffusion MRI; Artificial intelligence; Deep learning; Computer science; Magnetoencephalography; Tensor (intrinsic definition); Rank (graph theory); Sensor fusion; Pattern recognition (psychology); Machine learning; Magnetic resonance imaging; Psychology; Neuroscience; Mathematics; Medicine; Electroencephalography","score_opus":0.051272985969632784,"score_gpt":0.3926637304508105,"score_spread":0.3413907444811777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405372902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.086045876,0.00008862328,0.8879224,0.023856621,0.00008435308,0.00078502327,0.0000062032436,0.000627069,0.00058381533],"genre_scores_gemma":[0.8566458,0.000006488906,0.14030525,0.0017118772,0.00007816599,0.0001917212,0.000031839554,0.00001705182,0.0010117872],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988865,0.000025235675,0.00017947661,0.00044348644,0.00023678316,0.00022849103],"domain_scores_gemma":[0.99895865,0.00071450556,0.000048048434,0.0001565967,0.000050890176,0.00007133903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004423525,0.00011517202,0.00013692783,0.00015576229,0.0003030283,0.00008381769,0.00013585955,0.00004478873,0.00003452983],"category_scores_gemma":[0.00089306984,0.00009154272,0.00008260359,0.00050821283,0.00026487972,0.00013320976,0.000024081104,0.00013771464,0.000021052389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068024216,0.00014791181,0.00013899412,0.00030925457,0.000007083882,0.000023495806,0.00044509963,0.014955118,0.6569318,0.00412142,0.0048868605,0.31796488],"study_design_scores_gemma":[0.0004295532,0.0004148357,0.0011338975,0.0002472013,0.00001611112,0.00001136518,0.00005758425,0.89221394,0.077616036,0.0037658196,0.023935223,0.00015844431],"about_ca_topic_score_codex":0.000006567474,"about_ca_topic_score_gemma":0.0000037173836,"teacher_disagreement_score":0.87725884,"about_ca_system_score_codex":0.000032570162,"about_ca_system_score_gemma":0.00008231461,"threshold_uncertainty_score":0.37330037},"labels":[],"label_agreement":null},{"id":"W4405385553","doi":"10.1523/jneurosci.2139-23.2024","title":"Individual Variability in the Structural Connectivity Architecture of the Human Brain","year":2024,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fundamental Research Funds for the Central Universities; State Key Laboratory of Cognitive Neuroscience and Learning; National Natural Science Foundation of China","keywords":"Cognition; Tractography; Neuroscience; Connectome; Human brain; Connectomics; Laminar organization; Psychology; Functional connectivity; Diffusion MRI; Biology; Medicine","score_opus":0.0669868368762148,"score_gpt":0.3873426448932615,"score_spread":0.32035580801704666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405385553","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97976184,0.000020042124,0.0034626496,0.016352681,0.00012128776,0.00016134347,0.000006562043,0.000009952563,0.00010364488],"genre_scores_gemma":[0.998205,0.000002199858,0.0004578579,0.0012674114,0.000048839076,0.0000017465893,8.311994e-8,0.0000036068054,0.000013221988],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99911976,0.00014751767,0.00021256052,0.000116705,0.00031503337,0.00008841018],"domain_scores_gemma":[0.9992346,0.00036697712,0.00010952841,0.00023167061,0.000032860255,0.000024353916],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000911558,0.000054633943,0.00010632189,0.000061344326,0.000073495445,0.000024806632,0.00038343863,0.000015933774,0.0000022203535],"category_scores_gemma":[0.0007352302,0.000025372443,0.00007805512,0.0005059237,0.00026686763,0.00007390386,0.0000587711,0.000543545,5.3269446e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015941567,0.00011385014,0.038896307,0.00006866049,0.0000029812804,0.000064261105,0.0010804278,0.00019947864,0.9384073,0.012766452,0.00067195186,0.0077123665],"study_design_scores_gemma":[0.000114845476,0.0001577061,0.96117955,0.00007790358,0.000017111483,0.0011999262,0.000022952016,0.00042440312,0.0047627822,0.029366218,0.0026426716,0.0000339155],"about_ca_topic_score_codex":0.0000029476507,"about_ca_topic_score_gemma":0.0000013493025,"teacher_disagreement_score":0.93364453,"about_ca_system_score_codex":0.000015895781,"about_ca_system_score_gemma":0.00007660454,"threshold_uncertainty_score":0.23614627},"labels":[],"label_agreement":null},{"id":"W4405459036","doi":"10.1007/s00429-024-02884-3","title":"Involvement of the left uncinate fasciculus in the amyotrophic lateral sclerosis: an exploratory longitudinal multi-modal neuroimaging and neuropsychological study","year":2024,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Women and Children’s Health Research Institute; University of Alberta","funders":"","keywords":"Diffusion MRI; Amyotrophic lateral sclerosis; Fractional anisotropy; Inferior longitudinal fasciculus; Uncinate fasciculus; Medicine; Fasciculus; Superior longitudinal fasciculus; Cardiology; Resting state fMRI; Neuropsychology; Neuroimaging; Neuroscience; Psychology; Audiology; Internal medicine; Magnetic resonance imaging; Radiology; Cognition","score_opus":0.0910966967118141,"score_gpt":0.33427803069617246,"score_spread":0.24318133398435837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405459036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9954339,0.00023985973,0.0009598615,0.0025831044,0.00012421327,0.0005802758,0.000006309589,0.00006362215,0.000008803036],"genre_scores_gemma":[0.9984226,0.000030046413,0.00016043667,0.0012667712,0.000066706576,0.000022650567,0.000004571847,0.000012544623,0.000013622223],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99911404,0.00011805473,0.00016604023,0.00034112047,0.00014686286,0.00011385575],"domain_scores_gemma":[0.9996082,0.000036217905,0.00003611599,0.00026176558,0.000025095014,0.000032558746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016446448,0.00012130632,0.00012203749,0.00006385621,0.00010934174,0.000045512235,0.00007503325,0.00003146656,0.0000049769883],"category_scores_gemma":[0.000018764682,0.00006496482,0.000028292965,0.00020169449,0.000113535454,0.00011942189,0.0000601473,0.00032462523,2.125215e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038201746,0.00058084197,0.76175106,0.00018959813,0.00004692678,0.00010278996,0.0058111143,0.00011173491,0.19660217,0.0013154576,0.0005402467,0.03256606],"study_design_scores_gemma":[0.00049953366,0.00045841082,0.9952057,0.000047296904,0.00005074531,0.000088534114,0.00045947696,0.0014997704,0.0001445233,0.001120154,0.0003622424,0.00006362908],"about_ca_topic_score_codex":0.000014149126,"about_ca_topic_score_gemma":0.000029523018,"teacher_disagreement_score":0.23345464,"about_ca_system_score_codex":0.000011064889,"about_ca_system_score_gemma":0.000011716618,"threshold_uncertainty_score":0.26491883},"labels":[],"label_agreement":null},{"id":"W4405483262","doi":"10.1007/s00701-024-06374-7","title":"Mini-strokes within Broca-caudate connections during left insular glioma awake surgery cause transient severe naming deficits","year":2024,"lang":"en","type":"article","venue":"Acta Neurochirurgica","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Medicine; Neuroradiology; Neurology; Perseveration; Stroke (engine); Exact test; Diffusion MRI; Magnetic resonance imaging; Effective diffusion coefficient; Neurosurgery; Glioma; Radiology; Surgery; Audiology; Cognition","score_opus":0.04718354036768995,"score_gpt":0.30554855444189927,"score_spread":0.2583650140742093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405483262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99025357,0.0003938494,0.0013658436,0.004637495,0.00035072808,0.0005428036,0.00007654954,0.001524116,0.00085505995],"genre_scores_gemma":[0.996744,0.00039974623,0.0010546404,0.0004462964,0.00017924432,0.0000844307,0.000061473096,0.000120528144,0.00090963795],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99780756,0.000054152973,0.00054598553,0.00079469173,0.0003232764,0.00047433696],"domain_scores_gemma":[0.99860775,0.0003164921,0.00010156903,0.00065550284,0.00007413025,0.000244562],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000113946364,0.00035535195,0.00042505696,0.00041347594,0.00036975284,0.00011195492,0.00016485443,0.00010563446,0.00007118394],"category_scores_gemma":[0.00013238176,0.00033675632,0.00026366964,0.0006487132,0.00010458038,0.00026295902,0.00008017121,0.0006085494,0.000044980072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001716993,0.0003905482,0.0027415855,0.0007015846,0.00018636677,0.0037892293,0.0007920817,0.0001304551,0.98562825,0.0013636781,0.0031587319,0.00094580377],"study_design_scores_gemma":[0.0028843428,0.00054108916,0.07329519,0.0033705656,0.0015969776,0.05803472,0.0005782474,0.0068160896,0.47858682,0.0015115301,0.3699813,0.0028031298],"about_ca_topic_score_codex":0.000013359318,"about_ca_topic_score_gemma":0.0000061670103,"teacher_disagreement_score":0.5070414,"about_ca_system_score_codex":0.0000649907,"about_ca_system_score_gemma":0.00012055318,"threshold_uncertainty_score":0.99990845},"labels":[],"label_agreement":null},{"id":"W4405515272","doi":"10.1001/jamanetworkopen.2024.51678","title":"Frontal White Matter Changes and Craving Recovery in Inpatients With Heroin Use Disorder","year":2024,"lang":"en","type":"article","venue":"JAMA Network Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Complementary and Integrative Health; National Institute on Drug Abuse; National Institute of Mental Health; Canadian Institutes of Health Research","keywords":"Craving; Heroin; Medicine; Opioid use disorder; Psychological intervention; Psychiatry; Mood; Psychology; Clinical psychology; Internal medicine; Opioid; Addiction; Drug","score_opus":0.0419218034781447,"score_gpt":0.3201518424256862,"score_spread":0.2782300389475415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405515272","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9776179,0.00052665616,0.00418417,0.013841004,0.00005778491,0.0011592502,0.000014011607,0.00010390499,0.0024953184],"genre_scores_gemma":[0.95861936,0.0003547448,0.032158695,0.003915969,0.00016870898,0.0002702742,0.000052780342,0.000058705493,0.0044007823],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99936104,0.000020394467,0.000106366664,0.00027398596,0.00006947991,0.00016874552],"domain_scores_gemma":[0.9996678,0.000048144568,0.000026310889,0.00019933865,0.000012821751,0.000045580742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009016145,0.000098864526,0.0001475809,0.000045151508,0.00004179094,0.0001962327,0.00008492986,0.00003685823,0.000070076094],"category_scores_gemma":[0.0000064173128,0.00007732132,0.000011728758,0.00020454386,0.000027825597,0.0003225904,0.00018882315,0.00019205807,0.000013239684],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016219332,0.000039777493,0.9504664,0.000042516956,0.000012823028,0.00005023909,0.0001579485,0.00008727163,0.000024852568,0.00009430777,0.020525523,0.028336177],"study_design_scores_gemma":[0.0006953017,0.00021136415,0.9070238,0.0016289594,0.00002841944,0.00007447935,0.000050412393,0.0024001307,0.000016790975,0.0008924195,0.08679898,0.00017895817],"about_ca_topic_score_codex":0.00012629745,"about_ca_topic_score_gemma":0.0003143181,"teacher_disagreement_score":0.06627346,"about_ca_system_score_codex":0.000029559294,"about_ca_system_score_gemma":0.000014216535,"threshold_uncertainty_score":0.31530717},"labels":[],"label_agreement":null},{"id":"W4405635575","doi":"10.7554/elife.94917.2.sa0","title":"Author response: Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Biology; Tractography; Anatomy; Bridging (networking); Fractional anisotropy; Neuroscience; Evolutionary biology; Computer science; Medicine; Magnetic resonance imaging; Artificial intelligence","score_opus":0.0990567845682077,"score_gpt":0.3961257767576528,"score_spread":0.2970689921894451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405635575","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030781254,0.016446074,0.018166026,0.9286782,0.00036855091,0.0019735505,0.0012342031,0.0005222248,0.0018299305],"genre_scores_gemma":[0.1760917,0.0071976855,0.025044069,0.021389673,0.0011720234,0.00032548423,0.0007859826,0.0003216333,0.76767176],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982093,0.000077223434,0.0005242713,0.0005187177,0.00041464248,0.0002558664],"domain_scores_gemma":[0.99854594,0.00038254252,0.00016828564,0.00065921043,0.00015247465,0.000091519934],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006775379,0.000275782,0.0006082852,0.00018579945,0.00016677697,0.00003398553,0.00019304043,0.00016311576,0.00043780432],"category_scores_gemma":[0.0003399175,0.00017359998,0.0001435687,0.00062474457,0.00031965223,0.000042145104,0.00043161117,0.00071850384,0.000054089203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052476993,0.000042769138,0.0012230431,0.0017499075,0.000031406867,0.000013302003,0.00012373802,2.0599218e-7,0.00074769027,0.00038763828,0.99096817,0.0046596318],"study_design_scores_gemma":[0.00012579183,0.00006263691,0.025353968,0.0015175516,0.00022850599,0.00021492201,0.00005066686,0.00017365534,0.0006873755,0.00031339616,0.9710769,0.0001946438],"about_ca_topic_score_codex":0.000009070488,"about_ca_topic_score_gemma":0.000003051646,"teacher_disagreement_score":0.9072885,"about_ca_system_score_codex":0.00008595711,"about_ca_system_score_gemma":0.000081734855,"threshold_uncertainty_score":0.7079202},"labels":[],"label_agreement":null},{"id":"W4405635920","doi":"10.7554/elife.94917.2","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2024,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"White matter; Corpus callosum; Diffusion MRI; Voxel; Anatomy; Biology; Tractography; Fractional anisotropy; Neuroscience; Magnetic resonance imaging; Computer science; Medicine; Artificial intelligence","score_opus":0.06363895321397584,"score_gpt":0.34557660972726695,"score_spread":0.2819376565132911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405635920","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97496086,0.0006751979,0.013188216,0.009660463,0.000096172116,0.0004620486,0.00015725532,0.00019359945,0.00060619717],"genre_scores_gemma":[0.9924813,0.00038193417,0.0057196557,0.0007386738,0.00030459883,0.00003858241,0.000042957807,0.000039664883,0.00025263493],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998885,0.000019842795,0.00029486176,0.00037018364,0.00026345908,0.0001666891],"domain_scores_gemma":[0.9992241,0.00007956504,0.00010863779,0.00046231406,0.00006464509,0.000060697508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017846361,0.00016536022,0.00029063414,0.0001009887,0.000111398054,0.00003237038,0.00013109483,0.00011286057,0.000040636525],"category_scores_gemma":[0.00007159838,0.000116670504,0.000080416175,0.0002057368,0.00022079062,0.000018979297,0.0011528889,0.00069310126,0.00002410403],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001684445,0.0005804308,0.8232928,0.0037006733,0.00036142327,0.00010845745,0.008097711,0.00016500858,0.037789945,0.01137324,0.06659934,0.04776252],"study_design_scores_gemma":[0.00047175994,0.00008245328,0.9276981,0.0007312925,0.0002686017,0.00021630658,0.00037378122,0.0078121475,0.030513527,0.007690477,0.02363685,0.00050472765],"about_ca_topic_score_codex":0.0000074230034,"about_ca_topic_score_gemma":0.0000010608339,"teacher_disagreement_score":0.10440527,"about_ca_system_score_codex":0.000050868348,"about_ca_system_score_gemma":0.000040201227,"threshold_uncertainty_score":0.4757685},"labels":[],"label_agreement":null},{"id":"W4405656544","doi":"10.3389/fnins.2024.1467786","title":"Multi-tensor fixel-based metrics in tractometry: application to multiple sclerosis","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; Consejo Nacional de Ciencia y Tecnología; Université de Sherbrooke","keywords":"Diffusion MRI; Tractography; Tensor (intrinsic definition); Artificial intelligence; Computer science; White matter; Pattern recognition (psychology); Pipeline (software); Fractional anisotropy; Mathematics; Medicine; Radiology; Magnetic resonance imaging; Geometry","score_opus":0.11011443424357255,"score_gpt":0.358482281332626,"score_spread":0.24836784708905346,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405656544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10933424,0.00021618546,0.8865991,0.0022201273,0.00034386807,0.0009395797,0.000020173597,0.0002800986,0.00004662872],"genre_scores_gemma":[0.7990158,0.00006549866,0.1991012,0.0014292164,0.000016680531,0.00026591978,0.0000040169657,0.000022168071,0.000079491925],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985121,0.00002144448,0.00025113797,0.000675826,0.00024435457,0.00029514765],"domain_scores_gemma":[0.9993253,0.00008607083,0.0000317535,0.00039441694,0.000030373556,0.0001321267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021755479,0.00013273353,0.00019198815,0.0012154115,0.000049492945,0.00004562668,0.00025121338,0.000050135444,0.0000013796007],"category_scores_gemma":[0.00058830954,0.00013044392,0.000047819918,0.005317951,0.00008308488,0.00013585632,0.000046273304,0.0002952957,0.000008461025],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007097786,0.0009321907,0.5050762,0.00014454055,0.0000013829092,0.00008074056,0.00012497876,0.003704465,0.39712065,0.00012980559,0.004306844,0.08830721],"study_design_scores_gemma":[0.0004467564,0.00011316802,0.32872513,0.00012959604,0.000007653583,0.000006377469,0.000020188241,0.62476975,0.011689397,0.00007664904,0.033850063,0.00016529261],"about_ca_topic_score_codex":0.000022654902,"about_ca_topic_score_gemma":0.000005801885,"teacher_disagreement_score":0.6896816,"about_ca_system_score_codex":0.00016434529,"about_ca_system_score_gemma":0.00006284437,"threshold_uncertainty_score":0.53193486},"labels":[],"label_agreement":null},{"id":"W4405721377","doi":"10.3390/s24248173","title":"Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation","year":2024,"lang":"en","type":"article","venue":"Sensors","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Breast cancer; Medicine; Receiver operating characteristic; Cancer; Prostate cancer; Diffusion MRI; Mammography; Magnetic resonance imaging; Gold standard (test); Modality (human–computer interaction); Medical imaging; Radiology; Medical physics; Computer science; Internal medicine; Artificial intelligence","score_opus":0.024322844281075114,"score_gpt":0.3334430636174504,"score_spread":0.3091202193363753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405721377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47279027,0.00078710925,0.5069423,0.014918867,0.00042223957,0.001801647,0.00017951721,0.0018864764,0.0002715884],"genre_scores_gemma":[0.9650016,0.00007879511,0.032774907,0.0004178533,0.00018260207,0.00020780959,0.000045558078,0.00006683517,0.0012240863],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923396,0.000009081424,0.00018516446,0.00030505867,0.00009094279,0.00017579838],"domain_scores_gemma":[0.9995327,0.00007614334,0.000042306554,0.0001901718,0.000096358504,0.00006230447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006958521,0.000116767995,0.0001414791,0.00009474237,0.0000921872,0.000029493356,0.00004070106,0.000024674824,0.00003943241],"category_scores_gemma":[0.000046146946,0.00009840564,0.00008403913,0.00017047832,0.00003492871,0.000051666666,0.000021886926,0.00014007771,0.000009409763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006206281,0.00020876802,0.0017206769,0.0008741432,0.000059114467,0.0001358362,0.00031804395,0.006229319,0.40674782,0.0018060779,0.003613664,0.5776659],"study_design_scores_gemma":[0.0005320014,0.000019407951,0.0005586326,0.00031743268,0.00015437168,0.0003460927,0.00004277555,0.98635334,0.005556713,0.00020367399,0.0057859235,0.00012966206],"about_ca_topic_score_codex":0.000054796823,"about_ca_topic_score_gemma":5.9685027e-7,"teacher_disagreement_score":0.980124,"about_ca_system_score_codex":0.00008351348,"about_ca_system_score_gemma":0.000043780547,"threshold_uncertainty_score":0.40128654},"labels":[],"label_agreement":null},{"id":"W4405737824","doi":"10.3390/curroncol31120595","title":"A Longitudinal Multimodal Imaging Study in Patients with Temporo-Insular Diffuse Low-Grade Tumors: How the Inferior Fronto-Occipital Fasciculus Provides Information on Cognitive Outcomes","year":2024,"lang":"en","type":"article","venue":"Current Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Ministero della Salute","keywords":"Inferior longitudinal fasciculus; Boston Naming Test; Fasciculus; Medicine; Fractional anisotropy; Tractography; White matter; Grey matter; Audiology; Neuropsychology; Magnetic resonance imaging; Radiology; Cognition; Psychiatry","score_opus":0.0677534620503598,"score_gpt":0.3906204305209329,"score_spread":0.3228669684705731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405737824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9912121,0.00008990137,0.0025655439,0.0025508695,0.00018698085,0.0030571558,0.000054274187,0.00022902635,0.000054094293],"genre_scores_gemma":[0.9985808,0.000009743441,0.00026456677,0.000158613,0.000056139546,0.0007755425,0.00012277704,0.000021800555,0.0000099760255],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99874765,0.00007164604,0.00030303354,0.0003298239,0.00027947396,0.00026838836],"domain_scores_gemma":[0.99923104,0.00020000884,0.00011938234,0.00024800323,0.00012815642,0.000073419695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013039929,0.00023372468,0.00032583097,0.0002148664,0.00010294458,0.00007743929,0.00012300735,0.000034562192,0.0000045890465],"category_scores_gemma":[0.00017138247,0.0001400587,0.00006359201,0.00025444737,0.00014503037,0.00041730725,0.00009454093,0.0005174273,0.000014222832],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019362237,0.0028188196,0.9553069,0.00007934019,0.000030372155,0.00004875917,0.0014520079,0.0000040998025,0.0000052707032,0.00007688533,0.00013642746,0.0398475],"study_design_scores_gemma":[0.0044594803,0.0014446452,0.98736274,0.00043722556,0.00009951122,0.000014512274,0.0011819154,0.0026764022,0.000022775157,0.000058461985,0.0020695822,0.00017274696],"about_ca_topic_score_codex":0.000028832706,"about_ca_topic_score_gemma":0.000025694868,"teacher_disagreement_score":0.039674755,"about_ca_system_score_codex":0.0002735313,"about_ca_system_score_gemma":0.00012670801,"threshold_uncertainty_score":0.5711428},"labels":[],"label_agreement":null},{"id":"W4405975791","doi":"10.1101/2024.12.24.630267","title":"Anatomy-to-Tract Mapping Infers White Matter Pathways Without Diffusion Streamline Propagation","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health","keywords":"Tractography; Diffusion MRI; Computer science; Artificial intelligence; Human Connectome Project; Distortion (music); Bundle; Segmentation; Streamlines, streaklines, and pathlines; Process (computing); White matter; Computer vision; Pattern recognition (psychology); Magnetic resonance imaging; Biology; Physics; Neuroscience","score_opus":0.030981754218409038,"score_gpt":0.28654245570942743,"score_spread":0.2555607014910184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405975791","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95454675,0.00024607286,0.033987857,0.0056694923,0.0004420086,0.0027622487,0.0002822254,0.0019851546,0.000078202116],"genre_scores_gemma":[0.94844544,0.00011285046,0.048438143,0.0015271154,0.0004630676,0.0007198743,0.0000034836098,0.0002516102,0.000038406506],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.997009,0.000048687565,0.00065218756,0.0013260576,0.0004469539,0.0005171054],"domain_scores_gemma":[0.9972768,0.00002772815,0.00030686636,0.0015767041,0.00041413007,0.00039777328],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028754573,0.0006261531,0.0006386129,0.0006058291,0.00014541573,0.00018173827,0.0003185955,0.0003753723,0.00006479847],"category_scores_gemma":[0.000091021066,0.00060845964,0.00018779552,0.0007792,0.00008165278,0.00009616149,0.0008040126,0.0013847748,0.0003459995],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004290333,0.00039071284,0.15451539,0.0016283272,0.00008459942,0.00015638722,0.00003427022,0.000052383366,0.83975947,0.0006617376,0.002640966,0.000032862295],"study_design_scores_gemma":[0.0009353459,0.0002047818,0.77383804,0.006158964,0.0005422267,5.4648115e-7,0.000010906581,0.005542637,0.18610676,0.00014098563,0.024645472,0.001873336],"about_ca_topic_score_codex":0.000017855078,"about_ca_topic_score_gemma":5.0812565e-7,"teacher_disagreement_score":0.6536527,"about_ca_system_score_codex":0.00037962772,"about_ca_system_score_gemma":0.00038606755,"threshold_uncertainty_score":0.99963665},"labels":[],"label_agreement":null},{"id":"W4406197134","doi":"10.1002/alz.094891","title":"A harmonized, histology‐based protocol for selection of medial temporal lobe cortical subregion ranges on magnetic resonance imaging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Magnetic resonance imaging; Temporal lobe; Selection (genetic algorithm); Protocol (science); Functional magnetic resonance imaging; Artificial intelligence; Computer science; Psychology; Neuroscience; Medicine; Pathology; Radiology; Epilepsy","score_opus":0.08603957029224812,"score_gpt":0.3817699912048395,"score_spread":0.2957304209125914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406197134","genre_codex":"protocol","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010062662,0.05632772,0.3664075,0.05020942,0.0011817797,0.50906926,0.00015874577,0.004094216,0.0024887107],"genre_scores_gemma":[0.801707,0.000008943212,0.05123792,0.000659876,0.0001633363,0.14607188,0.000048540656,0.000063852276,0.000038658534],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989307,0.00003129395,0.00029419904,0.0003639757,0.00016741188,0.00021243231],"domain_scores_gemma":[0.99946684,0.00010430359,0.000067407964,0.00020882602,0.00009064994,0.00006198569],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012449823,0.00014696486,0.00019797617,0.00011777226,0.00007538044,0.0000133990425,0.00007726819,0.000047009384,0.00008321037],"category_scores_gemma":[0.000030912208,0.00013272249,0.00010218639,0.00019873885,0.00013129284,0.000053727214,0.000018331752,0.0001756891,0.000009350977],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005981036,0.0015969198,0.02661295,0.0005388136,0.0008610706,0.00011684477,0.0001696599,0.0000077795285,0.2613281,0.010503127,0.12470122,0.5675825],"study_design_scores_gemma":[0.0037223233,0.0012820142,0.0038820156,0.00036525764,0.004253812,0.000068377754,0.0000064499804,0.02097048,0.2408465,0.0010334832,0.7232827,0.00028657037],"about_ca_topic_score_codex":0.000012167651,"about_ca_topic_score_gemma":0.0000030984272,"teacher_disagreement_score":0.79164433,"about_ca_system_score_codex":0.00001489647,"about_ca_system_score_gemma":0.000094322546,"threshold_uncertainty_score":0.5412266},"labels":[],"label_agreement":null},{"id":"W4406200478","doi":"10.1002/alz.088849","title":"Postmortem MRI signature of Hippocampal Sclerosis of Aging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Hippocampal sclerosis; Hippocampal formation; Signature (topology); Medicine; Neuroscience; Pathology; Multiple sclerosis; Psychology; Temporal lobe; Epilepsy; Psychiatry; Mathematics","score_opus":0.0671703147120653,"score_gpt":0.3370752229886436,"score_spread":0.2699049082765783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406200478","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33115867,0.5963991,0.0476419,0.012337281,0.00070955046,0.0023582343,0.0002295874,0.0014930298,0.0076726032],"genre_scores_gemma":[0.9757873,0.0003507798,0.023553634,0.00017275775,0.000048488597,0.00002020903,0.000026785932,0.000026909915,0.000013153085],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992089,0.0000105916115,0.00025927846,0.00021995614,0.00016571645,0.00013550208],"domain_scores_gemma":[0.99947375,0.00003519272,0.00006728077,0.00030767635,0.00006653122,0.000049554284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008101525,0.0001040247,0.00018194715,0.00009318822,0.000026361588,0.000007300084,0.00009678198,0.000043796164,0.00010935637],"category_scores_gemma":[0.0000054476573,0.00009378005,0.000107537046,0.0002762838,0.000071275295,0.0000658522,0.000055418972,0.00015536248,0.000011027877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034923694,0.00028435866,0.0054536937,0.00019592728,0.0063331407,0.000030113648,0.00036299622,0.000017345885,0.80855894,0.010464406,0.021673795,0.14659038],"study_design_scores_gemma":[0.00029736047,0.00017512742,0.0069539947,0.000535829,0.011332744,0.00002459869,0.0000473433,0.0005633295,0.9504773,0.0016293756,0.027782146,0.00018083035],"about_ca_topic_score_codex":0.000012942308,"about_ca_topic_score_gemma":4.908604e-7,"teacher_disagreement_score":0.64462864,"about_ca_system_score_codex":0.0000026430614,"about_ca_system_score_gemma":0.00003654792,"threshold_uncertainty_score":0.38242397},"labels":[],"label_agreement":null},{"id":"W4406200945","doi":"10.1002/alz.093247","title":"White Matter Integrity of Age‐Related Hearing Loss and Cognitive Impairment","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Audiology; Montreal Cognitive Assessment; White matter; Psychology; Fractional anisotropy; Diffusion MRI; Cognitive decline; Superior longitudinal fasciculus; Cognition; Effects of sleep deprivation on cognitive performance; Population; Dementia; Hearing loss; Medicine; Gerontology; Magnetic resonance imaging; Psychiatry; Cognitive impairment; Disease; Internal medicine","score_opus":0.053606880687252355,"score_gpt":0.34933400448983526,"score_spread":0.2957271238025829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406200945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9078002,0.062300343,0.011273574,0.009340227,0.00020410132,0.0016554215,0.00006840396,0.00061920163,0.00673855],"genre_scores_gemma":[0.99448156,0.000094360104,0.0049633076,0.0002986736,0.00001700038,0.000039720166,0.000029515566,0.000021026071,0.00005486137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993387,0.000012826421,0.00019581954,0.00023290399,0.00009068821,0.00012910363],"domain_scores_gemma":[0.9997075,0.000027924074,0.000032585558,0.00013985642,0.000036921945,0.00005521684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000077840814,0.00009968841,0.00014045654,0.00006750074,0.00003427997,0.00001711952,0.000036079146,0.000036645404,0.00022332482],"category_scores_gemma":[0.0000030612414,0.0000873275,0.000049587445,0.00013332769,0.000110453715,0.000065569475,0.000076416545,0.0002142258,0.000049594375],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019310074,0.00081079564,0.83183455,0.0003679254,0.019406421,0.0005869183,0.0021394095,0.0000024306905,0.016413262,0.0065869973,0.019595409,0.102062784],"study_design_scores_gemma":[0.0016849788,0.00059740845,0.85170835,0.0015262715,0.035971038,0.0006099565,0.0002393452,0.0012202546,0.0826438,0.008962323,0.0142270755,0.0006092198],"about_ca_topic_score_codex":0.000018357525,"about_ca_topic_score_gemma":9.0706584e-7,"teacher_disagreement_score":0.101453565,"about_ca_system_score_codex":0.000002905982,"about_ca_system_score_gemma":0.000015778882,"threshold_uncertainty_score":0.3561112},"labels":[],"label_agreement":null},{"id":"W4406201315","doi":"10.1002/alz.092362","title":"Post‐mortem MR imaging of tau pathology – a pilot study","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Brain Institute; University of Toronto; University Health Network; Toronto Western Hospital; Parkinson's Clinic of Eastern Toronto & Movement Disorders Centre; Hospital for Sick Children; Occupational Cancer Research Centre","funders":"","keywords":"Tau pathology; Pathology; Medicine; Alzheimer's disease; Disease","score_opus":0.07115574344779192,"score_gpt":0.3641402115747239,"score_spread":0.292984468126932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201315","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81464016,0.14705518,0.01785097,0.00924188,0.00064681383,0.003609206,0.00009546757,0.0019422928,0.00491804],"genre_scores_gemma":[0.9920447,0.000049613824,0.0072470442,0.00040740392,0.000056359368,0.00010790376,0.000023385477,0.000037731395,0.000025865691],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99901855,0.000026196582,0.00028178605,0.00034290328,0.00014314943,0.000187427],"domain_scores_gemma":[0.999358,0.000034562203,0.000052755528,0.0004204544,0.00007635482,0.000057882575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013171311,0.00012929171,0.00019423784,0.00012235148,0.000048351176,0.000014624348,0.00011069628,0.000013066263,0.00010878526],"category_scores_gemma":[0.000010987348,0.00011670526,0.000056508383,0.00020879638,0.000071225484,0.000076656084,0.0000981979,0.00015397834,0.0000541751],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020424598,0.0042110146,0.08197989,0.000091863,0.010491074,0.0017113164,0.00095834624,0.0000037439938,0.6894372,0.008925709,0.016791541,0.18519403],"study_design_scores_gemma":[0.005760904,0.015937945,0.29420456,0.000656844,0.15858188,0.0028405015,0.0019904033,0.0030997267,0.36636123,0.007921315,0.14061233,0.0020323684],"about_ca_topic_score_codex":0.000044050812,"about_ca_topic_score_gemma":0.0000038554676,"teacher_disagreement_score":0.32307598,"about_ca_system_score_codex":0.0000032744338,"about_ca_system_score_gemma":0.0000414251,"threshold_uncertainty_score":0.47591025},"labels":[],"label_agreement":null},{"id":"W4406201399","doi":"10.1002/alz.090781","title":"Links between cognition and multivariate brain white matter differences in individuals with family history of Alzheimer's disease","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; Alzheimer Society of Canada; Concordia University; Montreal Neurological Institute and Hospital; Montreal Heart Institute","funders":"","keywords":"Multivariate statistics; White matter; Cognition; Family history; Disease; Brain size; Psychology; Multivariate analysis; White (mutation); Neuroscience; Medicine; Biology; Genetics; Internal medicine; Magnetic resonance imaging; Gene; Computer science","score_opus":0.06833019083614691,"score_gpt":0.3193577257615229,"score_spread":0.251027534925376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201399","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77869374,0.1938004,0.008869043,0.012795584,0.00017520458,0.002475335,0.00036569423,0.0004824653,0.0023425596],"genre_scores_gemma":[0.9925909,0.00008463011,0.0062207943,0.00076607976,0.000039548686,0.00011703095,0.00011715891,0.00003144452,0.00003242209],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990203,0.00003551208,0.00026974056,0.0003437382,0.00016601964,0.00016468352],"domain_scores_gemma":[0.9995097,0.00007144062,0.00007464432,0.00020548547,0.00003328699,0.00010547839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010400368,0.0001563082,0.00023466365,0.00017234149,0.000023426413,0.000015456015,0.000063899184,0.0000610682,0.00007259776],"category_scores_gemma":[0.0000054612956,0.00012971928,0.000037866535,0.00013596479,0.00014755523,0.0001278633,0.000058286467,0.00024410195,0.0000150513],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040589857,0.00014386227,0.9656337,0.000054591725,0.0027002958,0.000031457483,0.00049436255,6.830516e-7,0.0030940443,0.00024356513,0.007935558,0.019627297],"study_design_scores_gemma":[0.0004987,0.000089938956,0.97903043,0.00030398305,0.0100910235,0.000004063806,0.000022415245,0.00013173501,0.0008703409,0.00064050226,0.008145409,0.00017143188],"about_ca_topic_score_codex":0.000038729282,"about_ca_topic_score_gemma":0.0000018616166,"teacher_disagreement_score":0.21389718,"about_ca_system_score_codex":0.0000076249526,"about_ca_system_score_gemma":0.00007167268,"threshold_uncertainty_score":0.52897984},"labels":[],"label_agreement":null},{"id":"W4406201579","doi":"10.1002/alz.085994","title":"Can neuroimaging methods help us to disentangle WMH etiology in AD?","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Diffusion MRI; Neuroimaging; Fractional anisotropy; Neuropathology; White matter; Pathology; Magnetic resonance imaging; Neuroscience; Amyloid (mycology); Ex vivo; Medicine; In vivo; Psychology; Disease; Biology; Radiology","score_opus":0.08564462893579457,"score_gpt":0.423573589266043,"score_spread":0.33792896033024844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406201579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22077847,0.19349806,0.3068992,0.25201154,0.0027982898,0.006617951,0.00017422435,0.0045666345,0.012655658],"genre_scores_gemma":[0.84329486,0.00014198617,0.15280044,0.0033533962,0.0000694682,0.00020114784,0.00003701952,0.000050457365,0.000051243802],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987882,0.00006530509,0.00025853398,0.00047840743,0.00009941909,0.00031014654],"domain_scores_gemma":[0.99935573,0.00007564427,0.000025819367,0.00038615603,0.000026294812,0.00013037487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017369688,0.00015531495,0.0002023436,0.0002053277,0.000050704675,0.000028790026,0.00012516118,0.00003645576,0.000104872095],"category_scores_gemma":[0.000027489847,0.00014992812,0.00007087633,0.00046721683,0.000049024973,0.000060400598,0.00012733573,0.00024111947,0.000072177194],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006845213,0.00029090987,0.023720862,0.000045904875,0.0017419243,0.0005433368,0.00060171605,0.000042424188,0.26422122,0.0052778,0.025867108,0.67757833],"study_design_scores_gemma":[0.0006001561,0.00028064763,0.048630062,0.00019086062,0.0063014356,0.0002954305,0.0000806373,0.003274508,0.09455361,0.0058209742,0.8393975,0.0005742147],"about_ca_topic_score_codex":0.00008878021,"about_ca_topic_score_gemma":0.000032118012,"teacher_disagreement_score":0.8135303,"about_ca_system_score_codex":0.000013606636,"about_ca_system_score_gemma":0.000042030726,"threshold_uncertainty_score":0.61138916},"labels":[],"label_agreement":null},{"id":"W4406209725","doi":"10.1002/alz.091117","title":"Exploring heterogeneity in Motoric Cognitive Risk Syndrome using Volumetric MRI‐guided Clustering","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University","funders":"","keywords":"Cluster analysis; Cognition; Magnetic resonance imaging; Medicine; Physical medicine and rehabilitation; Psychology; Computer science; Neuroscience; Artificial intelligence; Radiology","score_opus":0.2779196360340695,"score_gpt":0.39007970819867677,"score_spread":0.11216007216460727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406209725","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.89528924,0.026240058,0.0768258,0.00009555779,0.00025740932,0.00070627243,0.0000218379,0.00042198985,0.00014184107],"genre_scores_gemma":[0.9773929,0.0007777109,0.021411214,0.00007186155,0.00006811967,0.00019773415,0.000018292278,0.00005782059,0.000004353419],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986181,0.000038478116,0.00034437454,0.0004875045,0.00019063812,0.00032089266],"domain_scores_gemma":[0.9994451,0.00007205263,0.000065011736,0.00027293782,0.000047419067,0.00009747707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018563803,0.00018945654,0.00023471635,0.0004483634,0.00010118139,0.000046488545,0.00009401676,0.000041480966,0.00003124284],"category_scores_gemma":[0.00003446026,0.00019765044,0.00010261288,0.0010597606,0.000039304905,0.00031146876,0.00014059314,0.00030321648,0.000052058793],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021043263,0.0012334986,0.3567536,0.00044854617,0.021302313,0.0041122246,0.0012094921,0.0019001793,0.053975765,0.00044063307,0.0010344508,0.5573789],"study_design_scores_gemma":[0.004408062,0.0009789983,0.35126135,0.0033782641,0.068392016,0.0040374123,0.00039883217,0.37670347,0.16638559,0.0012823185,0.020024369,0.0027493273],"about_ca_topic_score_codex":0.00018569709,"about_ca_topic_score_gemma":0.000009773874,"teacher_disagreement_score":0.55462956,"about_ca_system_score_codex":0.000032684056,"about_ca_system_score_gemma":0.000034941677,"threshold_uncertainty_score":0.8059951},"labels":[],"label_agreement":null},{"id":"W4406209861","doi":"10.1002/alz.083704","title":"Harmonization of diffusion MRI measures is crucial for white matter tract normative assessment in ADNI","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Normative; Diffusion MRI; Harmonization; White matter; Diffusion; Psychology; Medicine; Magnetic resonance imaging; Political science; Radiology; Physics; Law","score_opus":0.06404005221395062,"score_gpt":0.3724719858851196,"score_spread":0.30843193367116895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406209861","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055781055,0.013354042,0.9028685,0.020757336,0.00030642672,0.0033163636,0.00018970971,0.00029504733,0.0031315219],"genre_scores_gemma":[0.94851923,0.00012759372,0.050409056,0.0005731552,0.00004573218,0.00019678088,0.000075640564,0.000025609026,0.000027174903],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919015,0.000016058322,0.00028859347,0.00022020563,0.00015597271,0.00012902702],"domain_scores_gemma":[0.99962234,0.00002998662,0.00006666763,0.00017313032,0.00007492345,0.000032970223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000107793836,0.000105263236,0.00015618063,0.00012108952,0.000039340946,0.000018773346,0.00006355949,0.000038154612,0.00017816333],"category_scores_gemma":[0.0000041303274,0.000094147406,0.000071302566,0.00018625519,0.000028377845,0.00013033052,0.00003181314,0.00011676755,0.000013920717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003914655,0.0023340636,0.3128379,0.0004972302,0.005144701,0.00003498583,0.0050969496,0.000085558706,0.20037137,0.004984261,0.17855322,0.2896683],"study_design_scores_gemma":[0.002268398,0.0005102687,0.45945978,0.0007380421,0.012337337,0.0000343418,0.00022699156,0.020747531,0.36725357,0.0053968583,0.13042355,0.0006033433],"about_ca_topic_score_codex":0.000013038199,"about_ca_topic_score_gemma":0.0000025315699,"teacher_disagreement_score":0.8927382,"about_ca_system_score_codex":0.000010043085,"about_ca_system_score_gemma":0.000041824725,"threshold_uncertainty_score":0.38392198},"labels":[],"label_agreement":null},{"id":"W4406222660","doi":"10.1002/alz.093795","title":"Postmortem MRI signature of Hippocampal Sclerosis of Aging","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"","keywords":"Hippocampal sclerosis; Hippocampal formation; Signature (topology); Neuroscience; Multiple sclerosis; Medicine; Pathology; Psychology; Psychiatry; Temporal lobe; Mathematics","score_opus":0.0671703147120653,"score_gpt":0.3370752229886436,"score_spread":0.2699049082765783,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406222660","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33115867,0.5963991,0.0476419,0.012337281,0.00070955046,0.0023582343,0.0002295874,0.0014930298,0.0076726032],"genre_scores_gemma":[0.9757873,0.0003507798,0.023553634,0.00017275775,0.000048488597,0.00002020903,0.000026785932,0.000026909915,0.000013153085],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992089,0.0000105916115,0.00025927846,0.00021995614,0.00016571645,0.00013550208],"domain_scores_gemma":[0.99947375,0.00003519272,0.00006728077,0.00030767635,0.00006653122,0.000049554284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008101525,0.0001040247,0.00018194715,0.00009318822,0.000026361588,0.000007300084,0.00009678198,0.000043796164,0.00010935637],"category_scores_gemma":[0.0000054476573,0.00009378005,0.000107537046,0.0002762838,0.000071275295,0.0000658522,0.000055418972,0.00015536248,0.000011027877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034923694,0.00028435866,0.0054536937,0.00019592728,0.0063331407,0.000030113648,0.00036299622,0.000017345885,0.80855894,0.010464406,0.021673795,0.14659038],"study_design_scores_gemma":[0.00029736047,0.00017512742,0.0069539947,0.000535829,0.011332744,0.00002459869,0.0000473433,0.0005633295,0.9504773,0.0016293756,0.027782146,0.00018083035],"about_ca_topic_score_codex":0.000012942308,"about_ca_topic_score_gemma":4.908604e-7,"teacher_disagreement_score":0.64462864,"about_ca_system_score_codex":0.0000026430614,"about_ca_system_score_gemma":0.00003654792,"threshold_uncertainty_score":0.38242397},"labels":[],"label_agreement":null},{"id":"W4406222901","doi":"10.1002/alz.094084","title":"Exploring the effects of using multiple different cerebellar reference regions to improve tau‐PET harmonization ‐ The HEAD Study","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Standardized uptake value; Cerebellum; Nuclear medicine; Harmonization; Reference values; Context (archaeology); Psychology; Positron emission tomography; Medicine; Neuroscience; Biology; Physics; Internal medicine","score_opus":0.19257388931497577,"score_gpt":0.3687361545296678,"score_spread":0.17616226521469203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406222901","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.949662,0.0064683366,0.03851426,0.0019514526,0.00032378276,0.0028061946,0.00000994413,0.00022256655,0.000041436113],"genre_scores_gemma":[0.99682844,0.00015653818,0.0022651667,0.00017319914,0.000069517686,0.00045202623,0.000009242692,0.00003449599,0.000011356124],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990307,0.00005423397,0.00023288239,0.0003065991,0.00019849661,0.00017705874],"domain_scores_gemma":[0.99902016,0.00020715728,0.000056097466,0.0005971677,0.0000652513,0.00005416629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010061631,0.0001456793,0.00015192416,0.000061053106,0.00020153579,0.000036105797,0.00017741676,0.000012575605,0.000005188194],"category_scores_gemma":[0.000050784653,0.00008449939,0.000056939258,0.00032823492,0.00004667807,0.00008831239,0.00015519811,0.00018576988,0.0000080443915],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011861621,0.0014410303,0.019696545,0.0002211162,0.008345235,0.000078176956,0.004871298,0.00013023718,0.7614709,0.005282269,0.0032692254,0.19507535],"study_design_scores_gemma":[0.0017076038,0.001647512,0.077654615,0.0010308177,0.043230295,0.00007660937,0.0015692221,0.017588569,0.8244413,0.0011123981,0.029198723,0.0007423526],"about_ca_topic_score_codex":0.00010832619,"about_ca_topic_score_gemma":0.00001895891,"teacher_disagreement_score":0.194333,"about_ca_system_score_codex":0.000009249987,"about_ca_system_score_gemma":0.000021825206,"threshold_uncertainty_score":0.34457853},"labels":[],"label_agreement":null},{"id":"W4406223146","doi":"10.1002/alz.094116","title":"Inflammation in the white matter relates to core Alzheimer's disease pathophysiological processes","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill Genome Centre; McGill University; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Translocator protein; White matter; Microglia; Astrogliosis; Neuroinflammation; Dementia; Cognitive decline; Psychology; Pathology; Medicine; Diffusion MRI; Internal medicine; Neuroscience; Magnetic resonance imaging; Inflammation; Disease; Central nervous system","score_opus":0.06938848726882091,"score_gpt":0.34645497272340453,"score_spread":0.2770664854545836,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223146","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6664314,0.14716572,0.006877424,0.16605943,0.00036705943,0.0068941377,0.000112595066,0.001672907,0.0044193002],"genre_scores_gemma":[0.99260575,0.00009992468,0.0039241053,0.0026060622,0.000113130016,0.00051891216,0.00009052374,0.00002398137,0.00001763016],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990713,0.000023891476,0.00022409641,0.00033041547,0.00016008997,0.00019021875],"domain_scores_gemma":[0.9994575,0.00005500248,0.000030394043,0.00032998095,0.00004494608,0.00008218838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010004818,0.00013952368,0.00011745459,0.00008100003,0.00006768658,0.00005103336,0.00014921953,0.000035154088,0.00013020834],"category_scores_gemma":[0.000023747736,0.00009134903,0.000050852,0.00044046994,0.00004457536,0.00012085049,0.000064486514,0.00018542977,0.00038078625],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089761394,0.0015244831,0.38419983,0.0005708528,0.0071145752,0.0015856323,0.0063467226,0.000555509,0.057816576,0.021747958,0.25768065,0.25995958],"study_design_scores_gemma":[0.0006669335,0.00042929663,0.65477616,0.00078375044,0.022097081,0.0000970518,0.00025070837,0.0018427416,0.013130526,0.02697192,0.278029,0.00092484255],"about_ca_topic_score_codex":0.0000033047745,"about_ca_topic_score_gemma":0.000001764788,"teacher_disagreement_score":0.3261743,"about_ca_system_score_codex":0.0000034084123,"about_ca_system_score_gemma":0.000040230752,"threshold_uncertainty_score":0.4894364},"labels":[],"label_agreement":null},{"id":"W4406223252","doi":"10.1002/alz.094000","title":"In vivo data‐driven patterns of Amyloid‐ and Tau accumulation associated with AD progression using 18F‐MK6240 and 18F‐NAV4694 PET","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Voxel; Positron emission tomography; Cognitive impairment; Standardized uptake value; Nuclear medicine; In vivo; Spatial normalization; Neuroimaging; Amyloid (mycology); Pittsburgh compound B; Grey matter; Pathology; Medicine; Neuroscience; Magnetic resonance imaging; Psychology; White matter; Radiology; Biology; Disease","score_opus":0.12560127233161428,"score_gpt":0.40887756190496066,"score_spread":0.2832762895733464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223252","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9862324,0.00880258,0.003424238,0.00061256374,0.000027620377,0.00064263935,0.000109472974,0.00011363276,0.000034883207],"genre_scores_gemma":[0.98684615,0.00020506054,0.012682291,0.000072153205,0.00001766195,0.000020765669,0.00012276588,0.00002671617,0.0000064293035],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99913937,0.000024070829,0.00020650766,0.00034425096,0.0001459901,0.0001398123],"domain_scores_gemma":[0.9995386,0.00004274573,0.00008672378,0.00024806723,0.000035624624,0.00004826044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011335807,0.00011756209,0.00016691224,0.00009781281,0.000046658595,0.000027171449,0.00006945807,0.000023684493,0.000026315878],"category_scores_gemma":[0.000012384881,0.00009844587,0.000013396394,0.00017614815,0.000056637833,0.00025542302,0.00013933938,0.00012359227,5.757377e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026052556,0.00089029246,0.61377674,0.00034246533,0.006008322,0.0006105374,0.0009132314,0.00009809533,0.2891098,0.0008177971,0.002741771,0.08443044],"study_design_scores_gemma":[0.00628187,0.0013389247,0.40777302,0.007502901,0.038654447,0.00085787807,0.00035011352,0.3741862,0.13566534,0.0016245372,0.02418383,0.0015809323],"about_ca_topic_score_codex":0.000052805186,"about_ca_topic_score_gemma":0.00003865479,"teacher_disagreement_score":0.3740881,"about_ca_system_score_codex":0.000006720639,"about_ca_system_score_gemma":0.000029217741,"threshold_uncertainty_score":0.4014506},"labels":[],"label_agreement":null},{"id":"W4406223305","doi":"10.1002/alz.093909","title":"Links between cognition and multivariate brain white matter differences in individuals with family history of Alzheimer's disease","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Heart Institute; Montreal Neurological Institute and Hospital; Concordia University","funders":"","keywords":"White matter; Cognition; Family history; Multivariate statistics; Disease; Psychology; Brain size; Multivariate analysis; Alzheimer's disease; Developmental psychology; Neuroscience; Medicine; Internal medicine; Magnetic resonance imaging; Computer science","score_opus":0.06833019083614691,"score_gpt":0.3193577257615229,"score_spread":0.251027534925376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406223305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77869374,0.1938004,0.008869043,0.012795584,0.00017520458,0.002475335,0.00036569423,0.0004824653,0.0023425596],"genre_scores_gemma":[0.9925909,0.00008463011,0.0062207943,0.00076607976,0.000039548686,0.00011703095,0.00011715891,0.00003144452,0.00003242209],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990203,0.00003551208,0.00026974056,0.0003437382,0.00016601964,0.00016468352],"domain_scores_gemma":[0.9995097,0.00007144062,0.00007464432,0.00020548547,0.00003328699,0.00010547839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010400368,0.0001563082,0.00023466365,0.00017234149,0.000023426413,0.000015456015,0.000063899184,0.0000610682,0.00007259776],"category_scores_gemma":[0.0000054612956,0.00012971928,0.000037866535,0.00013596479,0.00014755523,0.0001278633,0.000058286467,0.00024410195,0.0000150513],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040589857,0.00014386227,0.9656337,0.000054591725,0.0027002958,0.000031457483,0.00049436255,6.830516e-7,0.0030940443,0.00024356513,0.007935558,0.019627297],"study_design_scores_gemma":[0.0004987,0.000089938956,0.97903043,0.00030398305,0.0100910235,0.000004063806,0.000022415245,0.00013173501,0.0008703409,0.00064050226,0.008145409,0.00017143188],"about_ca_topic_score_codex":0.000038729282,"about_ca_topic_score_gemma":0.0000018616166,"teacher_disagreement_score":0.21389718,"about_ca_system_score_codex":0.0000076249526,"about_ca_system_score_gemma":0.00007167268,"threshold_uncertainty_score":0.52897984},"labels":[],"label_agreement":null},{"id":"W4406239147","doi":"10.1101/2025.01.07.631402","title":"EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital; Institut Universitaire de Gériatrie de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Institut de Valorisation des Données; Polytechnique Montréal; Craig H. Neilsen Foundation; Canada First Research Excellence Fund; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation","keywords":"Segmentation; Computer science; Artificial intelligence; Ghosting; Spinal cord; Computer vision; Functional magnetic resonance imaging; Ground truth; Preprocessor; Pattern recognition (psychology); Medicine; Neuroscience; Psychology; Radiology","score_opus":0.19308266940326882,"score_gpt":0.4375408830752436,"score_spread":0.24445821367197476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406239147","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8402146,0.0005875072,0.13241518,0.0032478976,0.0016650899,0.010288573,0.00883093,0.0026877443,0.00006250343],"genre_scores_gemma":[0.8743431,0.00017760567,0.12434005,0.0007872307,0.00009330194,0.00016915369,0.000007379469,0.000073276424,0.000008926622],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99784654,0.00009368773,0.00053132686,0.00096878706,0.0002883593,0.0002713028],"domain_scores_gemma":[0.99592644,0.000030633822,0.00060509413,0.0030307767,0.00030579316,0.00010124817],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027336468,0.00036933998,0.0004969257,0.00019794093,0.00017517994,0.00020362492,0.0023701345,0.0001801644,0.0000075445605],"category_scores_gemma":[0.00015255388,0.00031671324,0.00008262372,0.00054153695,0.00012110059,0.00029246448,0.0032343452,0.00060965074,0.0000032048863],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050258334,0.0014453451,0.0209053,0.0013535528,0.00021216144,0.00003709268,0.0000037148707,0.00011667663,0.97190887,0.00038883908,0.0030795976,0.000046266756],"study_design_scores_gemma":[0.0025942998,0.00016985784,0.16251197,0.0062816855,0.0004991531,1.8322842e-7,0.0000031957718,0.023112888,0.8009933,0.000009157248,0.0031449026,0.0006793634],"about_ca_topic_score_codex":0.00012346059,"about_ca_topic_score_gemma":0.000001490004,"teacher_disagreement_score":0.17091553,"about_ca_system_score_codex":0.00021862137,"about_ca_system_score_gemma":0.00056069053,"threshold_uncertainty_score":0.9999285},"labels":[],"label_agreement":null},{"id":"W4406249842","doi":"10.1016/b978-0-12-818894-1.00035-5","title":"From diffusion models to fiber orientations","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion; Fiber; Materials science; Physics; Composite material; Thermodynamics","score_opus":0.057286745752930045,"score_gpt":0.3337178140014015,"score_spread":0.27643106824847147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249842","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000038979917,0.00013578632,0.0037678017,0.0010624994,0.000088511355,0.0012177465,0.00023952458,0.00029907146,0.99315006],"genre_scores_gemma":[0.00013559594,0.000066541324,0.033512417,0.0024341664,0.00024971276,0.00020280892,0.00022841842,0.0000690698,0.96310127],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99875003,0.0000055834003,0.0003209455,0.00053560035,0.00021966391,0.0001681708],"domain_scores_gemma":[0.9987256,0.000059302176,0.000095958225,0.0008337675,0.00012083669,0.00016455817],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000029135705,0.00028537816,0.00039572013,0.00017070698,0.00010522071,0.000017415794,0.00015217514,0.00016780307,0.00036025717],"category_scores_gemma":[0.000009486091,0.0002719083,0.00017012359,0.000024991416,0.000049669197,0.000024356508,0.00017964107,0.0003787623,0.00021918424],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019424102,0.000016274202,0.0000010551187,0.00002695253,0.00003197759,0.0000146441,0.00013257751,0.0000035084352,0.00021291812,0.020138156,0.00584441,0.9735581],"study_design_scores_gemma":[0.00018395377,0.00003450201,0.0000063563216,0.00062958605,0.00019106534,0.000004546356,0.000003942243,0.00006842445,0.0001425417,0.12769891,0.8708406,0.00019558154],"about_ca_topic_score_codex":0.0000027628016,"about_ca_topic_score_gemma":0.0000033563153,"teacher_disagreement_score":0.9733625,"about_ca_system_score_codex":0.00009198827,"about_ca_system_score_gemma":0.0000960296,"threshold_uncertainty_score":0.9999733},"labels":[],"label_agreement":null},{"id":"W4406249847","doi":"10.1016/b978-0-12-818894-1.00032-x","title":"Machine learning in tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University Health Network; Université de Sherbrooke","funders":"","keywords":"Tractography; Neuroscience; Psychology; Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.03499768014462313,"score_gpt":0.31553050630763796,"score_spread":0.28053282616301484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249847","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000008659066,0.0013362294,0.000104508305,0.0004812276,0.00003483566,0.0006633199,0.000016809485,0.00030040994,0.997054],"genre_scores_gemma":[0.0010878516,0.0007285242,0.003531485,0.0008404831,0.00006764884,0.000075894604,0.00006783157,0.00006221937,0.9935381],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989471,0.0000090053445,0.00032420174,0.0003928299,0.00014696518,0.00017989815],"domain_scores_gemma":[0.9992956,0.000051516272,0.000120090124,0.00042094672,0.000042221858,0.00006962113],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008253015,0.00026705183,0.0004465253,0.0003940087,0.000051966592,0.000009707187,0.00011310039,0.00018309541,0.00008121551],"category_scores_gemma":[0.000018255749,0.00025848378,0.00020903022,0.000034075376,0.00007510305,0.000013623168,0.00006713596,0.0011833131,0.000018697481],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016400507,0.000013870919,0.00025161897,0.00009389878,0.000019916819,0.00005568912,0.000017097746,4.5232056e-7,0.00006406141,0.012794871,0.000119436285,0.9865527],"study_design_scores_gemma":[0.00027531447,0.000053604923,0.00013294349,0.0008056076,0.00008372157,0.000025782863,9.127321e-7,0.00003304318,0.00005338775,0.016251124,0.9820987,0.00018588317],"about_ca_topic_score_codex":7.2929697e-7,"about_ca_topic_score_gemma":0.000005912539,"teacher_disagreement_score":0.9863668,"about_ca_system_score_codex":0.000048055346,"about_ca_system_score_gemma":0.00007035231,"threshold_uncertainty_score":0.99998677},"labels":[],"label_agreement":null},{"id":"W4406249850","doi":"10.1016/b978-0-12-818894-1.00037-9","title":"Current challenges and opportunities for tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Université de Sherbrooke","funders":"","keywords":"Tractography; Current (fluid); Psychology; Geology; Medicine; Diffusion MRI; Oceanography; Radiology; Magnetic resonance imaging","score_opus":0.18447455694137602,"score_gpt":0.3614914835877903,"score_spread":0.1770169266464143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249850","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000002418584,0.044056155,0.00019962093,0.0021642928,0.00007399729,0.0011852523,0.00009361881,0.00018355748,0.9520411],"genre_scores_gemma":[0.00008962713,0.08209853,0.0030149953,0.00059340114,0.00017474973,0.00038893052,0.00005827955,0.00005724042,0.91352427],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991726,0.000003939378,0.00022817201,0.00035407694,0.00009983674,0.0001413427],"domain_scores_gemma":[0.99925673,0.000075388765,0.000109053966,0.00037248584,0.000091460104,0.000094903815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000657401,0.00025209924,0.00039551553,0.0001932898,0.000065207954,0.000009549921,0.0000730279,0.000118861935,0.0000073532415],"category_scores_gemma":[0.0000076334945,0.00023310543,0.00018232303,0.0000037355974,0.00013569371,0.000015036518,0.000051791427,0.00029038228,8.4214906e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000121673465,0.000009454043,4.0516903e-7,0.0005076434,0.000030072491,0.000004084354,0.000026889355,1.7992979e-9,0.0000054241527,0.13753669,0.0005574756,0.8613097],"study_design_scores_gemma":[0.00020411788,0.000082112296,0.000015235169,0.0010258094,0.000236842,0.00001687728,0.00000755078,0.0000022798365,0.000022323306,0.07272844,0.9254886,0.0001698008],"about_ca_topic_score_codex":1.6374905e-8,"about_ca_topic_score_gemma":5.3675984e-7,"teacher_disagreement_score":0.9249311,"about_ca_system_score_codex":0.000015178108,"about_ca_system_score_gemma":0.00006575231,"threshold_uncertainty_score":0.95057636},"labels":[],"label_agreement":null},{"id":"W4406249897","doi":"10.1016/b978-0-12-818894-1.00026-4","title":"Diffusion MRI acquisition for tractography: Beyond the in vivo adult human brain","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Human brain; Neuroscience; Psychology; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Physics; Radiology","score_opus":0.023900918092789932,"score_gpt":0.32082866794688786,"score_spread":0.2969277498540979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249897","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000194185,0.0002410716,0.0008784008,0.0056412662,0.00007154784,0.0032471586,0.00015091368,0.00018823164,0.9893872],"genre_scores_gemma":[0.0018570952,0.00016238682,0.0029044955,0.008398437,0.00025565267,0.0007344428,0.0001642876,0.00008433479,0.9854389],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998705,0.000013519451,0.0004100823,0.0004678726,0.00018465285,0.00021886108],"domain_scores_gemma":[0.9987921,0.00015767236,0.00018476447,0.0006852783,0.000120340446,0.000059827657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013209548,0.0003088321,0.0004106173,0.0002532722,0.00019393083,0.0000199841,0.00019766718,0.00022502195,0.00005919114],"category_scores_gemma":[0.000013809138,0.00023735863,0.00031249822,0.00003361006,0.00014419053,0.000022314407,0.00007363721,0.00051554805,0.000002979033],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007503611,0.00006090283,0.000048252077,0.000274843,0.00004348883,0.000014461476,0.00012631092,2.6538407e-7,0.0067078862,0.16084799,0.009961088,0.82183945],"study_design_scores_gemma":[0.0006000179,0.0001145463,0.00016527863,0.00076508964,0.00013161509,0.000011060932,0.0000059530003,0.0000211371,0.0004671974,0.13913332,0.858383,0.00020177482],"about_ca_topic_score_codex":0.0000011231726,"about_ca_topic_score_gemma":0.00002307309,"teacher_disagreement_score":0.84842193,"about_ca_system_score_codex":0.00006435283,"about_ca_system_score_gemma":0.000046607845,"threshold_uncertainty_score":0.9679204},"labels":[],"label_agreement":null},{"id":"W4406249912","doi":"10.1016/b978-0-12-818894-1.00010-0","title":"Single-shell diffusion models: From DTI to HARDI","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; Diffusion imaging; Diffusion; Shell (structure); Neuroscience; Psychology; Materials science; Physics; Medicine; Magnetic resonance imaging","score_opus":0.08899307441662753,"score_gpt":0.3175447907616004,"score_spread":0.2285517163449729,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249912","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00019550031,0.0032580385,0.022192014,0.0024806934,0.0008376832,0.0023839695,0.000551147,0.00050975714,0.9675912],"genre_scores_gemma":[0.0031164265,0.0010102199,0.054951712,0.005809014,0.0012059244,0.00026074427,0.0002072204,0.000207473,0.93323123],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99653286,0.000046086978,0.0008852323,0.0013775001,0.00048923196,0.0006691074],"domain_scores_gemma":[0.99680936,0.0002753697,0.0002754987,0.0018828784,0.00023091247,0.0005259538],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014372944,0.00085994374,0.001116133,0.00030550797,0.0002860604,0.00006161381,0.0005639519,0.00050813216,0.00044477903],"category_scores_gemma":[0.00006757952,0.00088037434,0.00047761586,0.00006258956,0.00027644233,0.00007158218,0.0006940708,0.0010724147,0.0006042191],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006108757,0.00009106038,0.000013948416,0.0001557969,0.000087020664,0.00007574573,0.00012018491,0.000020790561,0.007544554,0.05235447,0.0009027638,0.9385726],"study_design_scores_gemma":[0.00047025355,0.00017824855,0.000023850727,0.0052682953,0.0005840213,0.000015349358,0.000010661083,0.0011107393,0.0019106437,0.08425148,0.90552753,0.00064892037],"about_ca_topic_score_codex":0.000015999329,"about_ca_topic_score_gemma":0.000018479443,"teacher_disagreement_score":0.93792367,"about_ca_system_score_codex":0.00040792604,"about_ca_system_score_gemma":0.00016506875,"threshold_uncertainty_score":0.9993647},"labels":[],"label_agreement":null},{"id":"W4406249945","doi":"10.1016/b978-0-12-818894-1.00001-x","title":"Diffusion MRI acquisition for tractography: Diffusion encoding","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Diffusion; Encoding (memory); Computer science; Neuroscience; Psychology; Medicine; Physics; Magnetic resonance imaging; Radiology","score_opus":0.04062800354253887,"score_gpt":0.3271607197921676,"score_spread":0.2865327162496287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249945","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00055776007,0.0027041896,0.037618384,0.002082362,0.0011408767,0.005264846,0.00041002812,0.00055554684,0.949666],"genre_scores_gemma":[0.018471261,0.00516418,0.03986245,0.0024550802,0.0017944964,0.0010269845,0.0006270322,0.00024124343,0.9303573],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99690026,0.000039287064,0.0008975881,0.0011120139,0.00038527136,0.00066557014],"domain_scores_gemma":[0.9974429,0.0004597083,0.00048200588,0.00105761,0.00027435212,0.00028343787],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027382176,0.00078003906,0.0009359468,0.00049832393,0.0006401469,0.00005391866,0.00034863933,0.0005986523,0.00024241596],"category_scores_gemma":[0.000045394285,0.0007767438,0.00083468616,0.000071693255,0.00035401832,0.000079785306,0.0002419502,0.00085288024,0.000042106913],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010572036,0.00010146529,0.00016745037,0.0007214696,0.00006701669,0.000021014457,0.000066529596,0.0000013511027,0.012410238,0.10012601,0.00027374708,0.885938],"study_design_scores_gemma":[0.001116057,0.00032030896,0.00046981676,0.0059422567,0.0008711509,0.00004077905,0.000017647932,0.00078001583,0.0014885542,0.032789726,0.9555225,0.0006412187],"about_ca_topic_score_codex":0.0000015556585,"about_ca_topic_score_gemma":0.0000034115149,"teacher_disagreement_score":0.9552487,"about_ca_system_score_codex":0.00023819794,"about_ca_system_score_gemma":0.00012445537,"threshold_uncertainty_score":0.9994683},"labels":[],"label_agreement":null},{"id":"W4406249946","doi":"10.1016/b978-0-12-818894-1.00029-x","title":"Deterministic fiber tractography","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Fiber; Computer science; Materials science; Medicine; Diffusion MRI; Radiology; Composite material; Magnetic resonance imaging","score_opus":0.043032978637481095,"score_gpt":0.3283351373224557,"score_spread":0.28530215868497455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249946","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000004391774,0.00037278023,0.00010249415,0.0002725964,0.000062112085,0.0008229008,0.00005481369,0.00033739785,0.9979705],"genre_scores_gemma":[0.00027174837,0.0001379382,0.0069500506,0.0013944479,0.00015585826,0.00011432748,0.000051364073,0.00007675661,0.9908475],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99882364,0.0000051202164,0.00033773482,0.00045780666,0.00017914118,0.00019655495],"domain_scores_gemma":[0.9987934,0.00006794731,0.00014296127,0.00079763995,0.000081411796,0.000116595904],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000448443,0.00032910984,0.00047570255,0.00022984967,0.00007958346,0.000015971533,0.0001492801,0.00021987349,0.00031613462],"category_scores_gemma":[0.00001451018,0.00030931787,0.00034013172,0.000020220274,0.00014551138,0.000012276008,0.00007326782,0.00058109686,0.00012792733],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012912682,0.0000117040845,0.0000039860543,0.000130275,0.000040956184,0.00006124896,0.0000072077705,2.5160901e-8,0.000037526996,0.007858155,0.0016980862,0.99013793],"study_design_scores_gemma":[0.00018258863,0.00006690363,0.00003285231,0.00072456495,0.0003490178,0.000071245726,4.2112478e-7,0.000003942963,0.00008143611,0.024005508,0.97424674,0.00023480345],"about_ca_topic_score_codex":7.914707e-8,"about_ca_topic_score_gemma":4.7286758e-7,"teacher_disagreement_score":0.9899031,"about_ca_system_score_codex":0.00003771101,"about_ca_system_score_gemma":0.00010504186,"threshold_uncertainty_score":0.99993587},"labels":[],"label_agreement":null},{"id":"W4406249967","doi":"10.1016/b978-0-12-818894-1.00020-3","title":"Tractography validation Part 2: The use of anatomical model systems and measures for validation","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Model validation; Computer science; Data science; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.1431679597984093,"score_gpt":0.3398599600333243,"score_spread":0.196692000234915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249967","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014717827,0.0035488699,0.17427382,0.0028954044,0.00046248583,0.020197956,0.0017281728,0.0007415581,0.79467994],"genre_scores_gemma":[0.021791548,0.0012422013,0.018463107,0.0005112815,0.00023783033,0.0010146006,0.00039004124,0.00013019098,0.9562192],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989872,0.000016391508,0.00039909664,0.00029879896,0.0001912452,0.00010729236],"domain_scores_gemma":[0.99881035,0.00018701257,0.000257494,0.0004757916,0.00022218909,0.000047169302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016265092,0.00019859428,0.00036947467,0.00013980626,0.00008546512,0.000030617364,0.00008232112,0.00015833632,0.0000014562181],"category_scores_gemma":[0.000048370166,0.00014800181,0.000168185,0.000018834771,0.00012909053,0.00003944427,0.000032727465,0.00021788597,3.179347e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010440721,0.000030120988,0.000037778012,0.0006156144,0.00016352911,9.2695916e-7,0.000062253566,0.00015039067,0.000983711,0.112494074,0.0027046103,0.8826526],"study_design_scores_gemma":[0.00026548415,0.00004879151,0.000009176198,0.00069597684,0.00055084535,0.000009753604,0.0000025225024,0.004464361,0.0013731665,0.015321943,0.9771096,0.0001483725],"about_ca_topic_score_codex":5.728681e-7,"about_ca_topic_score_gemma":4.1972493e-7,"teacher_disagreement_score":0.974405,"about_ca_system_score_codex":0.000023543736,"about_ca_system_score_gemma":0.00006688461,"threshold_uncertainty_score":0.60353386},"labels":[],"label_agreement":null},{"id":"W4406249969","doi":"10.1016/b978-0-12-818894-1.00027-6","title":"Linking behavior with white matter networks","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"White (mutation); White matter; Biology; Medicine","score_opus":0.028053720992555067,"score_gpt":0.29923250529536083,"score_spread":0.2711787843028058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249969","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011662151,0.000299447,0.002612878,0.00046546102,0.00006453247,0.0012580204,0.000017235612,0.00029317627,0.9949776],"genre_scores_gemma":[0.000567042,0.00008267229,0.01269461,0.0033029185,0.0002673435,0.00030265865,0.0000923122,0.00012395349,0.9825665],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987325,0.000005584022,0.0003091277,0.00051215495,0.00019286214,0.0002477623],"domain_scores_gemma":[0.9987479,0.000024491042,0.00017085427,0.00084749656,0.00010673104,0.00010256239],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000049736722,0.0003736726,0.00048464167,0.00013792378,0.000101256606,0.000026905192,0.0001588917,0.00024267171,0.0002187073],"category_scores_gemma":[0.000001347189,0.0003110601,0.00015581562,0.000020244455,0.00012385083,0.00001907263,0.000114491006,0.0008692419,0.00005659165],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031650146,0.000017651077,0.0025527764,0.00012632673,0.00004543077,0.00013581182,0.000016372278,0.0000021988908,0.000008732775,0.0028507602,0.001826807,0.9923855],"study_design_scores_gemma":[0.0002550516,0.00007360783,0.00063297886,0.0020370767,0.0006044038,0.00014183909,8.592797e-7,0.000022305472,0.000017704577,0.0013869404,0.99451405,0.00031318876],"about_ca_topic_score_codex":1.0661651e-7,"about_ca_topic_score_gemma":0.0000017446562,"teacher_disagreement_score":0.9926872,"about_ca_system_score_codex":0.00006537081,"about_ca_system_score_gemma":0.00007836924,"threshold_uncertainty_score":0.99993414},"labels":[],"label_agreement":null},{"id":"W4406249987","doi":"10.1016/b978-0-12-818894-1.00023-9","title":"Methods and statistics for diffusion MRI tractometry","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Diffusion; Diffusion MRI; Statistics; Statistical physics; Computer science; Mathematics; Physics; Medicine; Magnetic resonance imaging; Radiology; Thermodynamics","score_opus":0.05563087874895355,"score_gpt":0.41417792358470623,"score_spread":0.35854704483575267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406249987","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000017882452,0.00052382075,0.27342936,0.00024530006,0.000059037397,0.0011368187,0.0002718068,0.000120981436,0.7242111],"genre_scores_gemma":[0.000008039422,0.00038966286,0.4545426,0.00038943338,0.00006313688,0.000081139966,0.00004901824,0.000037473023,0.5444395],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99901557,0.0000097969005,0.0002929217,0.00039683038,0.000134629,0.00015027222],"domain_scores_gemma":[0.9988394,0.00033787134,0.0001405081,0.00043050796,0.00015370309,0.00009802952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018031603,0.00024890475,0.0004615999,0.00017650737,0.00009140679,0.000014831057,0.0000791846,0.00018698016,0.000029344332],"category_scores_gemma":[0.000087817345,0.0002260937,0.00010187766,0.000013423161,0.00010214296,0.00001055609,0.000087882996,0.0003566461,0.0000021583762],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021215466,0.000009483239,0.000005922259,0.00030648324,0.00002767118,0.0000037229458,0.000011504138,1.2967344e-8,0.00056264736,0.03880458,0.00134176,0.958905],"study_design_scores_gemma":[0.0002901163,0.00009255555,0.000045133278,0.00037336713,0.00031544568,0.000021894215,0.0000013304269,0.00009446189,0.00035925605,0.088473246,0.9097643,0.00016890393],"about_ca_topic_score_codex":1.3815092e-7,"about_ca_topic_score_gemma":5.326604e-7,"teacher_disagreement_score":0.9587361,"about_ca_system_score_codex":0.000053206724,"about_ca_system_score_gemma":0.00009265408,"threshold_uncertainty_score":0.92198336},"labels":[],"label_agreement":null},{"id":"W4406250042","doi":"10.1016/b978-0-12-818894-1.00030-6","title":"Probabilistic tractography","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Probabilistic logic; Psychology; Computer science; Artificial intelligence; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.05037777134875867,"score_gpt":0.32734000110396644,"score_spread":0.2769622297552078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250042","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000026306085,0.0030830163,0.00082576927,0.0012872459,0.00054605777,0.0024645387,0.00015729773,0.00044385562,0.99116594],"genre_scores_gemma":[0.0036555827,0.0010154615,0.012853103,0.0016516108,0.0006586155,0.00038760048,0.00007815805,0.00013223964,0.97956765],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973965,0.00003427963,0.0007556537,0.00092659006,0.00032251782,0.00056440313],"domain_scores_gemma":[0.99757385,0.00028243684,0.00029442547,0.0013543006,0.00020817193,0.00028683752],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00018666821,0.00068220496,0.00085192645,0.0003360707,0.00023415523,0.000035027777,0.0003730702,0.00042334438,0.00044900907],"category_scores_gemma":[0.00009617243,0.00068242993,0.0005864723,0.000069401765,0.00077170104,0.000036217403,0.00017216422,0.0012440077,0.00023555983],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016697248,0.000048236347,0.000043579403,0.0005289861,0.00008169724,0.000055360862,0.000019760164,9.209578e-7,0.00012219038,0.28586707,0.00023819105,0.7129773],"study_design_scores_gemma":[0.00031853063,0.00014160329,0.00018054548,0.0032416058,0.0007936138,0.000070584174,0.000003733243,0.000058266254,0.00014309649,0.08440182,0.91017795,0.000468668],"about_ca_topic_score_codex":8.991218e-7,"about_ca_topic_score_gemma":0.00000393727,"teacher_disagreement_score":0.90993977,"about_ca_system_score_codex":0.00016146699,"about_ca_system_score_gemma":0.00025558975,"threshold_uncertainty_score":0.9995627},"labels":[],"label_agreement":null},{"id":"W4406250051","doi":"10.1016/b978-0-12-818894-1.00019-7","title":"Diffusion MRI acquisition for tractography: Diffusion sequences","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hotchkiss Brain Institute; Robarts Clinical Trials; University of Alberta; Western University; Polytechnique Montréal; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Tractography; Diffusion MRI; Diffusion; Diffusion imaging; Computer science; Medicine; Radiology; Physics; Magnetic resonance imaging","score_opus":0.040346980600094215,"score_gpt":0.33013603123248936,"score_spread":0.28978905063239513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250051","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087100785,0.004365188,0.025489641,0.0036575785,0.0012486508,0.006267574,0.00067835674,0.0006318799,0.95679015],"genre_scores_gemma":[0.015057951,0.0063337632,0.041381165,0.0028113795,0.0015676119,0.0011641968,0.00071077445,0.00019942824,0.93077374],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969023,0.000044466775,0.00087781885,0.0011260759,0.00041202965,0.0006373399],"domain_scores_gemma":[0.9974913,0.00041897676,0.000493696,0.0010269836,0.00029227269,0.0002767993],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025929077,0.00077949354,0.00093089126,0.0004363173,0.0005951251,0.00005610661,0.0003870199,0.0005985384,0.0002620504],"category_scores_gemma":[0.00003630217,0.0007377152,0.000784939,0.00007397211,0.0005580088,0.000085621985,0.00020054347,0.0007765131,0.000045146113],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000103121594,0.00009641895,0.00018058521,0.0006913016,0.00007247345,0.000023543873,0.000057400288,0.0000015850226,0.007862629,0.09310053,0.0002929135,0.8975175],"study_design_scores_gemma":[0.00089153217,0.00039873028,0.00052680745,0.0049606613,0.00082052615,0.000045312103,0.000018908353,0.00055425346,0.0012078335,0.059982825,0.92997485,0.0006177734],"about_ca_topic_score_codex":0.0000030590052,"about_ca_topic_score_gemma":0.0000064193437,"teacher_disagreement_score":0.9296819,"about_ca_system_score_codex":0.00020587913,"about_ca_system_score_gemma":0.00016902377,"threshold_uncertainty_score":0.99950737},"labels":[],"label_agreement":null},{"id":"W4406250086","doi":"10.1016/b978-0-12-818894-1.00036-7","title":"Tractography in pathological anatomy: Some general considerations","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Pathological anatomy; Pathological; Anatomy; Medicine; Pathology; Radiology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.051792435581865574,"score_gpt":0.3435095831315025,"score_spread":0.2917171475496369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250086","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024049943,0.0008313735,0.00007060832,0.001819026,0.00006601077,0.0010721106,0.000056563083,0.00027210117,0.99557173],"genre_scores_gemma":[0.0038059382,0.0004880704,0.020097585,0.005598619,0.0001969507,0.00025403456,0.000088585315,0.0000574165,0.9694128],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986361,0.00001657018,0.00044977135,0.00051559403,0.0001595241,0.00022241636],"domain_scores_gemma":[0.9990532,0.00008605122,0.00011915148,0.00057163363,0.00007081386,0.000099195895],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000864913,0.00030917782,0.0005491776,0.00038947395,0.00008169204,0.000020065594,0.000091770286,0.00029767555,0.00011888965],"category_scores_gemma":[0.00003151314,0.00028476867,0.00025309995,0.000030133006,0.00018790149,0.000029084345,0.00007293885,0.000836284,0.00001588815],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012468606,0.00004566241,0.000115910836,0.000057452657,0.000028278526,0.00040625,0.000023298711,4.1605804e-7,0.00022542571,0.4724709,0.0012481607,0.52536577],"study_design_scores_gemma":[0.00029216244,0.000049334525,0.000384708,0.00026728527,0.00008572158,0.000083444356,0.0000010390556,0.000011716697,0.000094003066,0.28782594,0.71069837,0.00020627708],"about_ca_topic_score_codex":3.6321197e-7,"about_ca_topic_score_gemma":0.000004593728,"teacher_disagreement_score":0.70945024,"about_ca_system_score_codex":0.000062074876,"about_ca_system_score_gemma":0.00015377215,"threshold_uncertainty_score":0.9999604},"labels":[],"label_agreement":null},{"id":"W4406250100","doi":"10.1016/b978-0-12-818894-1.00004-5","title":"Tractography validation part 3: Lessons learned through validation studies","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Psychology; Computer science; Neuroscience; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.20737022110032607,"score_gpt":0.4248103367021694,"score_spread":0.21744011560184331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250100","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00002989248,0.0016079107,0.00078616565,0.0047055515,0.00020952885,0.0013662738,0.00007911285,0.00054137374,0.9906742],"genre_scores_gemma":[0.0006781845,0.005981072,0.007212774,0.0010839,0.0003142659,0.00030543192,0.00035425412,0.00009368246,0.9839764],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99816114,0.000026869766,0.00055362086,0.0006901575,0.00032597405,0.00024225099],"domain_scores_gemma":[0.99827135,0.00013467486,0.00035879962,0.0008692726,0.00029459537,0.000071292845],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016329283,0.00043468532,0.0006902857,0.00022496429,0.00021136685,0.000031567422,0.00015850029,0.0002600546,0.00006390148],"category_scores_gemma":[0.000068145266,0.0004098216,0.00036058718,0.00005670761,0.00020853673,0.000076796816,0.00010482997,0.00063875125,0.000043140724],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026132057,0.00003149902,0.00001206461,0.0002624966,0.0002432322,0.000013219991,0.00013815577,0.0000011214801,0.00023826303,0.062318668,0.004304263,0.9324109],"study_design_scores_gemma":[0.00027203612,0.00006947463,0.000010293531,0.0010855288,0.00059958576,0.000013888826,0.00001643079,0.000001893286,0.0029005911,0.1276135,0.86714077,0.00027603217],"about_ca_topic_score_codex":3.3149746e-7,"about_ca_topic_score_gemma":0.0000010343291,"teacher_disagreement_score":0.93213487,"about_ca_system_score_codex":0.00009895089,"about_ca_system_score_gemma":0.00011296063,"threshold_uncertainty_score":0.9998354},"labels":[],"label_agreement":null},{"id":"W4406250106","doi":"10.1016/b978-0-12-818894-1.00017-3","title":"Tractography validation Part 1: Foundations, numerical simulations, and phantom models","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Imaging phantom; Tractography; Computer science; Nuclear medicine; Medicine; Radiology; Diffusion MRI; Magnetic resonance imaging","score_opus":0.06992056873028775,"score_gpt":0.3455646180430042,"score_spread":0.27564404931271647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250106","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00004235189,0.0007006596,0.016876526,0.0007754002,0.00007857,0.0013602586,0.00014523914,0.00036062975,0.9796604],"genre_scores_gemma":[0.015911784,0.00083941355,0.014390393,0.0010328044,0.00022771931,0.00014734115,0.0006384421,0.0000892011,0.9667229],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986154,0.000018666942,0.00044399977,0.00051772495,0.00023141644,0.00017278489],"domain_scores_gemma":[0.9988359,0.00014327336,0.000196036,0.0005559788,0.00014889539,0.00011991917],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008925976,0.00031252456,0.00043013264,0.00028350277,0.00021385818,0.000044407134,0.00009057486,0.0002022088,0.00007758641],"category_scores_gemma":[0.000025023175,0.0003132522,0.0001675715,0.000043442604,0.00011900945,0.00008456158,0.00006552543,0.00050483964,0.000009137303],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019668083,0.000030376355,0.00003203031,0.00009848656,0.00007047262,0.0000055625474,0.00003547583,0.000019101439,0.000052249583,0.058566764,0.0006122112,0.9404576],"study_design_scores_gemma":[0.00027178813,0.000042824024,0.000019366063,0.0003867666,0.00033938017,0.000021090076,0.0000018227163,0.0014905364,0.00008577594,0.11412252,0.8829807,0.0002373967],"about_ca_topic_score_codex":4.1255294e-7,"about_ca_topic_score_gemma":6.412846e-7,"teacher_disagreement_score":0.9402202,"about_ca_system_score_codex":0.00004872849,"about_ca_system_score_gemma":0.00010129598,"threshold_uncertainty_score":0.99993193},"labels":[],"label_agreement":null},{"id":"W4406250126","doi":"10.1016/b978-0-12-818894-1.09994-8","title":"Spherical harmonics","year":2025,"lang":"fr","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Zonal spherical harmonics; Spin-weighted spherical harmonics; Spherical harmonics; Harmonics; Physics; Vector spherical harmonics","score_opus":0.06095962306599624,"score_gpt":0.3380871245711569,"score_spread":0.2771275015051607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250126","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009064107,0.0044383714,0.0047267536,0.0024432605,0.00062457967,0.0012973999,0.00008898869,0.00039330986,0.98597825],"genre_scores_gemma":[0.0005183967,0.001958118,0.054909095,0.003298257,0.0007536208,0.00015021634,0.000047860034,0.00012672732,0.9382377],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975526,0.000029965777,0.0006872322,0.0008370811,0.0003276999,0.0005654643],"domain_scores_gemma":[0.9978112,0.0001974959,0.0002446298,0.0012703307,0.00016664888,0.00030968685],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00014795094,0.0006216788,0.0008368924,0.000107188745,0.0002206135,0.00003185491,0.0003885524,0.0004472421,0.0008112691],"category_scores_gemma":[0.000071897535,0.00063512713,0.00043837767,0.000043558357,0.0005659298,0.000030240379,0.00033096975,0.0013696516,0.0006173275],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018305644,0.000033162407,0.000032953983,0.00022720937,0.000073135954,0.000107432825,0.000015789741,8.333317e-7,0.0002674233,0.19372803,0.0009565733,0.80453914],"study_design_scores_gemma":[0.0003447392,0.00011913983,0.00004940421,0.0020047294,0.0005570488,0.00008622755,0.000004859365,0.00016761996,0.0005586979,0.027488641,0.96815896,0.00045990612],"about_ca_topic_score_codex":8.177507e-7,"about_ca_topic_score_gemma":0.0000017365192,"teacher_disagreement_score":0.9672024,"about_ca_system_score_codex":0.0002752184,"about_ca_system_score_gemma":0.00032344615,"threshold_uncertainty_score":0.99961},"labels":[],"label_agreement":null},{"id":"W4406250132","doi":"10.1016/b978-0-12-818894-1.00002-1","title":"Tractography visualization","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Tractography; Visualization; Neuroscience; Psychology; Computer science; Medicine; Artificial intelligence; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.042214420144186665,"score_gpt":0.34683259649290554,"score_spread":0.3046181763487189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250132","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000028157747,0.00041795714,0.0014735789,0.00026044933,0.00006430761,0.0008127968,0.000027800099,0.00040714824,0.99653316],"genre_scores_gemma":[0.00027074077,0.00034507865,0.0036052954,0.001540693,0.00013806272,0.000077528246,0.00012224598,0.000066496985,0.99383384],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990209,0.000005020702,0.0002900733,0.0003704629,0.00017502582,0.00013851545],"domain_scores_gemma":[0.99909586,0.000029756155,0.0001387635,0.0005497883,0.000107288695,0.0000785479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004688614,0.00025236607,0.00035508798,0.00025774856,0.000070727074,0.000013753017,0.00010000137,0.00019886198,0.000101251375],"category_scores_gemma":[0.000011081804,0.00024392614,0.00023698078,0.00002742619,0.000084334875,0.0000162009,0.00004834022,0.00035258365,0.000030132256],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009963408,0.0000125876995,0.000012708705,0.00010694462,0.0000347808,0.0000122400725,0.000010642669,3.9698303e-8,0.000102463346,0.09655485,0.0016927626,0.90145004],"study_design_scores_gemma":[0.00016057196,0.00004754659,0.0000330505,0.0005893555,0.00021538597,0.000020728407,6.8155606e-7,0.000009271706,0.00023346556,0.030401304,0.9681103,0.00017833551],"about_ca_topic_score_codex":8.467039e-8,"about_ca_topic_score_gemma":5.2967005e-7,"teacher_disagreement_score":0.96641755,"about_ca_system_score_codex":0.000038208967,"about_ca_system_score_gemma":0.000079267775,"threshold_uncertainty_score":0.9947019},"labels":[],"label_agreement":null},{"id":"W4406250231","doi":"10.1016/b978-0-12-818894-1.00021-5","title":"Improving tractography using anatomical priors and multimodal integration","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; Université du Québec en Outaouais","funders":"","keywords":"Prior probability; Tractography; Computer science; Artificial intelligence; Diffusion MRI; Medicine; Radiology; Bayesian probability; Magnetic resonance imaging","score_opus":0.033405986212041945,"score_gpt":0.32430407573151215,"score_spread":0.2908980895194702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250231","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0024732836,0.0007605868,0.010442449,0.0002521333,0.000082988256,0.0018837986,0.000051312403,0.00040841292,0.983645],"genre_scores_gemma":[0.024875682,0.0002534095,0.13765572,0.0009788547,0.00026519832,0.00007677404,0.000080228456,0.00014422604,0.8356699],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99891263,0.000007940541,0.00032178283,0.00045659984,0.00014039128,0.00016067932],"domain_scores_gemma":[0.9992298,0.00004360092,0.00016618184,0.0003756805,0.00008361414,0.00010115715],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000072327544,0.00028815342,0.00039746315,0.00027375272,0.00010112247,0.000026507307,0.00007540307,0.00023667386,0.000011853402],"category_scores_gemma":[0.000023044344,0.0002665419,0.00016431953,0.00002241658,0.00015463747,0.0000347261,0.00007897933,0.0006310954,0.0000014933299],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019738169,0.000009332917,0.00002776638,0.00009119024,0.000024492889,0.0000109697085,0.000028932942,1.2876505e-7,0.0039695445,0.0057109864,0.00002305721,0.9900839],"study_design_scores_gemma":[0.001101729,0.00017458716,0.00027043262,0.002626198,0.0010611671,0.00022320205,0.0000212434,0.007763167,0.003332912,0.018921897,0.96362716,0.0008762948],"about_ca_topic_score_codex":0.0000019502672,"about_ca_topic_score_gemma":0.0000026343712,"teacher_disagreement_score":0.98920757,"about_ca_system_score_codex":0.00006884569,"about_ca_system_score_gemma":0.00009661869,"threshold_uncertainty_score":0.99997866},"labels":[],"label_agreement":null},{"id":"W4406250261","doi":"10.1016/b978-0-12-818894-1.00013-6","title":"Dissecting white matter pathways: Automatic and semiautomatic approaches","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Microsoft (Canada)","funders":"","keywords":"White matter; Computer science; Neuroscience; Psychology; Medicine","score_opus":0.06733804487472023,"score_gpt":0.2921523119491402,"score_spread":0.22481426707441998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250261","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032201756,0.00049489486,0.0002527571,0.0005578626,0.00005699081,0.001268353,0.000023123437,0.00056220836,0.9964618],"genre_scores_gemma":[0.0034799294,0.00004334625,0.016534783,0.0009397272,0.00012809609,0.0002160231,0.0000400692,0.00010585603,0.97851217],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985409,0.000010082273,0.0004659766,0.0005512983,0.00019225787,0.00023947898],"domain_scores_gemma":[0.9987766,0.00008587737,0.00022760767,0.0007316444,0.000060348393,0.000117925854],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000108593806,0.00041567246,0.00063284015,0.0001868592,0.00013386905,0.000042423304,0.00013025259,0.00021437593,0.000105970365],"category_scores_gemma":[0.000023912155,0.0003711399,0.00015399014,0.000022074006,0.00013882376,0.000031075193,0.0001773046,0.00057641615,0.0000482076],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004739183,0.000015910453,0.0004309382,0.0017328234,0.000078390825,0.00002892624,0.00018858581,2.1394932e-7,0.000045592038,0.008507929,0.0006937377,0.9882722],"study_design_scores_gemma":[0.00089094334,0.00016408676,0.0023501033,0.0120254,0.0015159515,0.0006610426,0.00007836772,0.0032396277,0.00026066974,0.1303536,0.8470233,0.0014369121],"about_ca_topic_score_codex":1.0640435e-7,"about_ca_topic_score_gemma":5.857064e-7,"teacher_disagreement_score":0.9868353,"about_ca_system_score_codex":0.00006912776,"about_ca_system_score_gemma":0.00006352325,"threshold_uncertainty_score":0.99987406},"labels":[],"label_agreement":null},{"id":"W4406250263","doi":"10.1016/b978-0-12-818894-1.00009-4","title":"Tractography: Applications to neurodevelopment, aging, and plasticity","year":2025,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"","keywords":"Neuroscience; Plasticity; Neuroplasticity; Tractography; Psychology; Medicine; Materials science; Diffusion MRI; Magnetic resonance imaging","score_opus":0.040147636839029714,"score_gpt":0.323033680408383,"score_spread":0.28288604356935326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406250263","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000021641232,0.00022473796,0.005845858,0.0009817726,0.000029520379,0.0019839585,0.00007014285,0.00034248037,0.9904999],"genre_scores_gemma":[0.0006753694,0.00023691551,0.025014617,0.0033977649,0.00010774098,0.00061524916,0.000038359074,0.000069425376,0.9698446],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99868315,0.0000048963307,0.00032189442,0.0006177067,0.0001670742,0.00020529641],"domain_scores_gemma":[0.99904096,0.00007022734,0.000109957706,0.00046527502,0.00009697937,0.0002165906],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000045202458,0.00032569154,0.00040707542,0.0003090685,0.00014090959,0.000024452336,0.00014065822,0.00013147367,0.000028927241],"category_scores_gemma":[0.000014530578,0.0003273015,0.00011031011,0.000043108863,0.000106125546,0.000015950936,0.00015431886,0.0004862887,0.000025382878],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000097384645,0.000014711442,0.00005417869,0.00014158219,0.000035728528,0.000008716689,0.000024930288,1.5466894e-7,0.00023946469,0.019402867,0.0009722668,0.97909564],"study_design_scores_gemma":[0.00014563958,0.000041727933,0.0005588965,0.00038914915,0.0001704587,0.000034100252,0.0000011051288,0.000003123581,0.00018588694,0.010010516,0.98821163,0.00024775538],"about_ca_topic_score_codex":2.7736607e-7,"about_ca_topic_score_gemma":0.0000024241942,"teacher_disagreement_score":0.98723936,"about_ca_system_score_codex":0.00003897772,"about_ca_system_score_gemma":0.00010487513,"threshold_uncertainty_score":0.9999179},"labels":[],"label_agreement":null},{"id":"W4406256038","doi":"10.1088/2057-1976/ada8b0","title":"Nyquist ghost elimination for diffusion MRI by dual-polarity readout at low b-values","year":2025,"lang":"en","type":"article","venue":"Biomedical Physics & Engineering Express","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada","funders":"Stiftelsen Assar Gabrielssons Fond; Cancerfonden","keywords":"Ghosting; Polarity (international relations); Diffusion MRI; SIGNAL (programming language); Physics; Diffusion; Isotropy; Kurtosis; Nuclear magnetic resonance; Polarity reversal; Nyquist frequency; Algorithm; Optics; Mathematics; Computer science; Chemistry; Computer vision; Statistics; Magnetic resonance imaging; Medicine","score_opus":0.017690822592697705,"score_gpt":0.3179522657743437,"score_spread":0.300261443181646,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406256038","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029072609,0.00013319582,0.96725637,0.0020874527,0.00018698731,0.000593471,0.00013781732,0.0004744194,0.000057680732],"genre_scores_gemma":[0.7417347,0.0002200867,0.24979462,0.00094811665,0.0008626943,0.00075858197,0.0018093617,0.00012214041,0.0037497303],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989359,0.0000071478553,0.00022698249,0.00034553278,0.00023110663,0.0002533292],"domain_scores_gemma":[0.9992309,0.0001345883,0.0000524435,0.00037323937,0.00007899646,0.0001298077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008063317,0.00017745343,0.00023654029,0.000067195615,0.00011638631,0.000017556185,0.00011672447,0.00010381071,0.000005233033],"category_scores_gemma":[0.000114270864,0.00017080885,0.00009494608,0.00023283111,0.00009390594,0.000060972267,0.0001246074,0.00017834043,0.000004038525],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034481818,0.0003028863,0.000057897763,0.00032278872,0.000017448194,0.000002065657,0.00003371654,0.000022587648,0.9586717,0.0040781223,0.03368715,0.0027691708],"study_design_scores_gemma":[0.0015403065,0.00015384963,0.0014921323,0.00055567606,0.0001292986,0.000006538452,0.000012874654,0.04171237,0.1099047,0.0034295297,0.8406982,0.00036457073],"about_ca_topic_score_codex":0.000007841489,"about_ca_topic_score_gemma":2.4354572e-8,"teacher_disagreement_score":0.848767,"about_ca_system_score_codex":0.00012975748,"about_ca_system_score_gemma":0.000024919256,"threshold_uncertainty_score":0.69653827},"labels":[],"label_agreement":null},{"id":"W4406270907","doi":"10.1007/s10334-026-01355-6","title":"Associations between iron and mean kurtosis in iron-rich grey matter nuclei in aging","year":2025,"lang":"en","type":"preprint","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Kurtosis; Grey matter; Mathematics; Statistics; Medicine; Magnetic resonance imaging; White matter","score_opus":0.039184659137859484,"score_gpt":0.35416199296336454,"score_spread":0.3149773338255051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406270907","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9868993,0.0034610725,0.00012337317,0.0072111934,0.00015280812,0.00095062505,0.0002458816,0.000043775774,0.00091195223],"genre_scores_gemma":[0.9902907,0.005469668,0.0019940257,0.0010484945,0.0003299165,0.00024344526,0.00036936722,0.000024336081,0.00023003596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99810237,0.00015079686,0.00066791533,0.0006689371,0.00008655914,0.00032340147],"domain_scores_gemma":[0.999123,0.00021451442,0.00018798783,0.0003862696,0.000035584988,0.000052654228],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004322473,0.00029195068,0.0009842465,0.0002449744,0.00004454527,0.000011599435,0.00013902472,0.00029420745,0.00004141474],"category_scores_gemma":[0.00008977786,0.0002634936,0.000020787722,0.00024336198,0.00032370916,0.000030121659,0.00038339422,0.0005455729,0.0000019388963],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005411048,0.00011623538,0.9371262,0.00054099323,0.000006899974,0.000016095039,0.00096542673,0.0000040695622,0.015516807,0.002082597,0.00030265647,0.043267883],"study_design_scores_gemma":[0.0014334795,0.00013265648,0.9518795,0.0017923169,0.00007255515,0.0000033110316,0.000039366998,0.000032040334,0.001670315,0.041621946,0.0010926925,0.00022982182],"about_ca_topic_score_codex":0.0007654973,"about_ca_topic_score_gemma":0.00006291379,"teacher_disagreement_score":0.04303806,"about_ca_system_score_codex":0.00008927388,"about_ca_system_score_gemma":0.00004296425,"threshold_uncertainty_score":0.9999817},"labels":[],"label_agreement":null},{"id":"W4406501509","doi":"10.1016/s0084-3970(09)79181-9","title":"10.1016/s0084-3970(09)79181-9","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Functional magnetic resonance imaging; Nuclear magnetic resonance; Medicine; Neuroimaging; Neuroscience; Psychology; Radiology; Physics","score_opus":0.024946955395429734,"score_gpt":0.2681998120168722,"score_spread":0.24325285662144247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406501509","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00024611186,0.000029433422,0.00007051961,0.0026060878,3.4410368e-7,0.00035283275,0.000010637217,0.00049909553,0.99618495],"genre_scores_gemma":[0.000037849946,0.0000010901512,0.004782002,0.000066026245,0.00010659061,0.000070248774,0.000020934704,0.000031572403,0.99488366],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.999315,0.0000084849235,0.00013623056,0.0002304307,0.00011767905,0.000192161],"domain_scores_gemma":[0.999349,0.00002223499,0.000019392191,0.00042438466,0.00003575508,0.00014921465],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000043862678,0.00010735053,0.00014803592,0.000051040468,0.000061490005,0.000010385004,0.00010731264,0.00003526433,0.9877893],"category_scores_gemma":[0.000019998137,0.00009993752,0.00005230305,0.00019589171,0.000033148062,0.000040608502,0.000027567245,0.00012622222,0.98085475],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039156253,0.00005871983,2.7805783e-7,0.000004539631,0.000004147232,0.0000069494963,0.0000037151058,0.0000069076787,0.00056845916,0.000005160681,0.14039822,0.85890377],"study_design_scores_gemma":[0.00020256231,0.00013920669,0.000056844267,0.000024635132,0.000022725475,0.000049635957,2.7965302e-7,0.00013246035,0.0010371942,0.00006885307,0.9981597,0.0001058911],"about_ca_topic_score_codex":0.000005161742,"about_ca_topic_score_gemma":1.6165382e-8,"teacher_disagreement_score":0.85879785,"about_ca_system_score_codex":0.000026883186,"about_ca_system_score_gemma":0.000017983826,"threshold_uncertainty_score":0.40753335},"labels":[],"label_agreement":null},{"id":"W4406522036","doi":"10.1016/j.yneu.2013.04.009","title":"10.1016/j.yneu.2013.04.009","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Arcuate fasciculus; Tractography; Medicine; Diffusion MRI; Fasciculus; Radiology; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.02426337712801217,"score_gpt":0.2676022629608561,"score_spread":0.24333888583284394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406522036","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003876706,0.00003513302,0.00004883862,0.004141557,3.8384658e-7,0.00034682007,0.0000095143305,0.0005137461,0.9945163],"genre_scores_gemma":[0.00024218805,0.000001680789,0.0040095714,0.00033664494,0.00009412902,0.000034967215,0.000017442653,0.000029204608,0.9952342],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993647,0.000007815,0.0001256294,0.00021581819,0.00010722324,0.00017882681],"domain_scores_gemma":[0.99937725,0.00002135528,0.000018598052,0.0004116984,0.000033112574,0.00013798414],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000038690207,0.000100145044,0.00013757194,0.000047973594,0.000053971235,0.000009825054,0.00010273769,0.000032707558,0.9809895],"category_scores_gemma":[0.000015691683,0.00009328759,0.00004699029,0.0001748059,0.000029974402,0.000040576408,0.00002525977,0.0001166664,0.9727277],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037651465,0.000060682294,2.3556603e-7,0.0000043078617,0.0000037827808,0.0000063857888,0.0000032123849,0.000011721455,0.0005516437,0.000005407916,0.4637987,0.53551626],"study_design_scores_gemma":[0.0001784386,0.0001373739,0.000058051057,0.000021784068,0.000019703464,0.000042318938,2.1541432e-7,0.00018354412,0.00074124616,0.00007118816,0.99844843,0.00009770645],"about_ca_topic_score_codex":0.000007976782,"about_ca_topic_score_gemma":1.8969077e-8,"teacher_disagreement_score":0.53541857,"about_ca_system_score_codex":0.000021654958,"about_ca_system_score_gemma":0.000014764558,"threshold_uncertainty_score":0.38041577},"labels":[],"label_agreement":null},{"id":"W4406807036","doi":"10.1016/j.neuroimage.2025.121031","title":"Decoding cortical folding patterns in marmosets using machine learning and large language model","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Hebei United University","keywords":"Folding (DSP implementation); Computer science; Decoding methods; Artificial intelligence; Natural language processing; Cognitive science; Psychology; Algorithm; Engineering","score_opus":0.05371819581743156,"score_gpt":0.39664179365520125,"score_spread":0.3429235978377697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406807036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84305,0.0001649216,0.15501466,0.00045883842,0.000021513202,0.00023650214,0.000015312848,0.00016787404,0.00087038236],"genre_scores_gemma":[0.9803101,0.00012689843,0.01827471,0.0009515235,0.000017097253,0.000012911143,0.0000134623715,0.000025622703,0.00026767844],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991149,0.00003468396,0.00019446031,0.0003186856,0.0000860883,0.00025120084],"domain_scores_gemma":[0.9996265,0.000079333295,0.000037640137,0.00017962577,0.000016633507,0.00006023962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012282483,0.000122054575,0.0001905303,0.00015337173,0.00011417404,0.000023770534,0.00005467174,0.000038685004,0.000015748486],"category_scores_gemma":[0.00014918034,0.00012483244,0.000035049045,0.00018010887,0.000027075519,0.00007122946,0.0001463648,0.0004814523,0.0000011612894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054560627,0.00016035629,0.60017806,0.00016898046,0.0000076537835,0.00032517337,0.00017591448,0.00016957703,0.39005983,0.0021129379,0.000056669407,0.006530285],"study_design_scores_gemma":[0.0009606019,0.000033922995,0.02532487,0.00019271579,0.000043341955,0.00007527102,0.000065234046,0.96708494,0.004718587,0.00034585263,0.0010189688,0.00013569735],"about_ca_topic_score_codex":0.000023886387,"about_ca_topic_score_gemma":0.000008157936,"teacher_disagreement_score":0.96691537,"about_ca_system_score_codex":0.00003661684,"about_ca_system_score_gemma":0.00002089939,"threshold_uncertainty_score":0.5090519},"labels":[],"label_agreement":null},{"id":"W4406936014","doi":"10.3389/fneur.2025.1507475","title":"Electroacupuncture combined with cognitive rehabilitation outperforms cognitive rehabilitation alone in treating post-stroke cognitive impairment: a randomized controlled trial","year":2025,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Shanghai Municipal Health Commission","keywords":"Montreal Cognitive Assessment; Cognitive rehabilitation therapy; Electroacupuncture; Supramarginal gyrus; Medicine; Cognition; Stroke (engine); Rehabilitation; Verbal learning; Randomized controlled trial; Effects of sleep deprivation on cognitive performance; Fusiform gyrus; Physical therapy; Physical medicine and rehabilitation; Psychology; Internal medicine; Acupuncture; Neuroscience; Psychiatry; Cognitive impairment; Pathology","score_opus":0.006289308848466026,"score_gpt":0.2858935654695705,"score_spread":0.2796042566211045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406936014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94680685,0.00018381076,0.023187466,0.006806772,0.00021551336,0.021581227,0.000051842813,0.00016134253,0.0010051705],"genre_scores_gemma":[0.98086214,0.000058631493,0.007340023,0.0021137353,0.000042023552,0.009064468,0.00023462233,0.000042821113,0.00024152998],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9964671,0.0009671807,0.0009994035,0.00082226656,0.00024357218,0.0005004389],"domain_scores_gemma":[0.9917183,0.007111025,0.00038793872,0.00021317601,0.00048969645,0.00007989261],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009482721,0.0004260439,0.0021800299,0.0010627842,0.000114411065,0.000019162937,0.00009339453,0.00024370187,0.000011703034],"category_scores_gemma":[0.0072609736,0.00030938123,0.0003213218,0.0007569864,0.00067833764,0.00016451362,0.000042843916,0.00089638954,0.0000018441033],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.96017724,0.0011254291,0.03421505,0.00006919383,0.00021322817,0.000041519237,0.001040375,0.0000147623205,0.00021957666,0.00022263643,0.000105126965,0.0025558749],"study_design_scores_gemma":[0.9610468,0.015539288,0.012738633,0.00046550372,0.00074069516,0.000021189135,0.0015221571,0.0035050584,0.00033161923,0.003825991,0.000017892547,0.00024518097],"about_ca_topic_score_codex":0.000043455886,"about_ca_topic_score_gemma":0.000052056697,"teacher_disagreement_score":0.03405529,"about_ca_system_score_codex":0.00013132353,"about_ca_system_score_gemma":0.00023312154,"threshold_uncertainty_score":0.9999358},"labels":[],"label_agreement":null},{"id":"W4406962873","doi":"10.1161/str.56.suppl_1.24","title":"Abstract 24: Iron deposition changes of ipsilateral ventral posterolateral nuclei correlate with central post-stroke pain after thalamic infarction","year":2025,"lang":"en","type":"article","venue":"Stroke","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Medicine; Stroke (engine); Infarction; Ischemic stroke; Cardiology; Ischemia; Myocardial infarction","score_opus":0.01156478996736028,"score_gpt":0.26550098420324086,"score_spread":0.2539361942358806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406962873","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99301803,0.00007574311,0.0029856348,0.002439469,0.00015880163,0.00054573355,0.000156631,0.00016025608,0.00045968045],"genre_scores_gemma":[0.99510324,0.000037012986,0.0028098125,0.0009521898,0.000070264454,0.00007080049,0.000110457266,0.000026355676,0.00081986235],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989484,0.000030252118,0.00024183182,0.0002823914,0.0001626727,0.00033446852],"domain_scores_gemma":[0.99941105,0.000027360595,0.00011767648,0.00028806602,0.00007976077,0.000076061784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007603346,0.00018751994,0.00022791952,0.00015487401,0.000063771746,0.00002093165,0.00007720291,0.00009065395,0.00004414012],"category_scores_gemma":[0.000009535617,0.00016173517,0.000089349785,0.00010078558,0.00008533771,0.000119879,0.00003407655,0.00029047718,0.000003837048],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002585003,0.0003379823,0.28545892,0.0003329859,0.00010882799,0.00007758774,0.00030783663,0.000053280397,0.6898935,0.00017925238,0.00020748365,0.020457393],"study_design_scores_gemma":[0.0011909078,0.0007568295,0.9582649,0.0003914862,0.00015244773,0.0000756263,0.000052813437,0.00071591896,0.037395045,0.00008411726,0.00074589555,0.00017400755],"about_ca_topic_score_codex":0.00007234767,"about_ca_topic_score_gemma":0.00003371382,"teacher_disagreement_score":0.672806,"about_ca_system_score_codex":0.00008238424,"about_ca_system_score_gemma":0.00003191805,"threshold_uncertainty_score":0.6595369},"labels":[],"label_agreement":null},{"id":"W4406972261","doi":"10.1016/j.jocmr.2024.101258","title":"Towards electrocardiogram-free diffusion tensor cardiac magnetic resonance using a machine learning approach","year":2025,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Diffusion MRI; Angiology; Medicine; Cardiac magnetic resonance; Nuclear magnetic resonance; Magnetic resonance imaging; Tensor (intrinsic definition); Artificial intelligence; Cardiology; Radiology; Computer science; Physics; Mathematics","score_opus":0.022894659073126714,"score_gpt":0.2823678662109494,"score_spread":0.2594732071378227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406972261","genre_codex":"review","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043610286,0.88002616,0.06969918,0.0005701193,0.00021586464,0.00097563164,0.000014890049,0.00014825778,0.0047396286],"genre_scores_gemma":[0.20049661,0.24667093,0.54531384,0.0009211537,0.001323844,0.00019874194,0.000020130594,0.00028269697,0.0047720657],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99662685,0.00028823144,0.0008531649,0.0005705573,0.001103323,0.000557844],"domain_scores_gemma":[0.9975067,0.00007211834,0.00023871164,0.0014030649,0.000582859,0.00019655353],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0010038796,0.00039669996,0.001384332,0.00043325362,0.0002399803,0.000064257685,0.0005563642,0.00016833947,0.000012271538],"category_scores_gemma":[0.00052038976,0.00034528843,0.0019110634,0.0012541728,0.00020105414,0.0001299694,0.00024548869,0.0011227344,0.0000020387001],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041088753,0.0002425795,0.010138729,0.00022485609,0.00031979688,0.00023860806,0.000060885468,0.00061858376,0.0042204843,0.00052565994,0.001222332,0.9817766],"study_design_scores_gemma":[0.0025294693,0.00067665457,0.039872542,0.00047822756,0.0015321699,0.0010950485,0.000033154887,0.007438183,0.0011287346,0.00083193684,0.9440699,0.00031395827],"about_ca_topic_score_codex":0.00006433933,"about_ca_topic_score_gemma":3.2981538e-7,"teacher_disagreement_score":0.98146266,"about_ca_system_score_codex":0.00020616381,"about_ca_system_score_gemma":0.00027610944,"threshold_uncertainty_score":0.9998999},"labels":[],"label_agreement":null},{"id":"W4406981800","doi":"10.1016/j.jocmr.2024.101384","title":"Inline automated post-processing and on-scanner diffusion tensor maps visualization for cardiac diffusion tensor imaging using FIRE","year":2025,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Siemens (Canada)","funders":"","keywords":"Diffusion MRI; Medicine; Visualization; Scanner; Angiology; Diffusion; Cardiac imaging; Tensor (intrinsic definition); Artificial intelligence; Computer vision; Radiology; Computer science; Cardiology; Magnetic resonance imaging; Geometry; Physics; Mathematics","score_opus":0.020559667874763734,"score_gpt":0.3215332973577026,"score_spread":0.3009736294829389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406981800","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7268211,0.20210922,0.06586705,0.0028290483,0.00031121995,0.001546454,0.000054038836,0.00029008707,0.00017173994],"genre_scores_gemma":[0.8655207,0.028911738,0.101043805,0.0026038357,0.0008301245,0.00009490648,0.00005606417,0.00018331093,0.000755495],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983328,0.00007222273,0.00055041106,0.000341433,0.0004350112,0.0002681343],"domain_scores_gemma":[0.9983773,0.00008188874,0.00022372954,0.00039030754,0.0008188489,0.00010789723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042791598,0.00022729111,0.00066655705,0.00020719419,0.00023588788,0.000055433742,0.00011403137,0.00007888539,0.000002008463],"category_scores_gemma":[0.0003228823,0.0001849319,0.0005040277,0.00040022447,0.00009850658,0.0001301044,0.00006842243,0.00022387042,3.4060176e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005035185,0.00021417707,0.008698366,0.0004912441,0.0001451502,0.000081351674,0.0000911865,0.00055324874,0.018165197,0.00023303008,0.0018896778,0.9689339],"study_design_scores_gemma":[0.004334801,0.00055500696,0.14303166,0.003073559,0.0016675404,0.0005678831,0.00015909811,0.337281,0.001825635,0.00045608808,0.5066507,0.00039703873],"about_ca_topic_score_codex":0.00001077603,"about_ca_topic_score_gemma":1.1572711e-7,"teacher_disagreement_score":0.9685368,"about_ca_system_score_codex":0.00010766393,"about_ca_system_score_gemma":0.00012293171,"threshold_uncertainty_score":0.75413036},"labels":[],"label_agreement":null},{"id":"W4407029036","doi":"10.7554/elife.101950.2","title":"From histology to macroscale function in the human amygdala","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Hospital for Sick Children; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Savoy Foundation","keywords":"Amygdala; Neuroscience; Neuroimaging; Human brain; Spatial normalization; Voxel; Psychology; Computer science; Artificial intelligence","score_opus":0.08474947672382899,"score_gpt":0.4147889573534217,"score_spread":0.3300394806295927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407029036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71573526,0.00071015104,0.16711903,0.07744781,0.001107855,0.003950195,0.0003385789,0.0009001549,0.032690987],"genre_scores_gemma":[0.9583611,0.00006990482,0.013983697,0.020965466,0.0006227961,0.001010568,0.00044430065,0.000025284719,0.0045169103],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991479,0.00003597517,0.00020228012,0.0003651275,0.0001253374,0.00012341024],"domain_scores_gemma":[0.9990965,0.000053660064,0.00005644036,0.0007249342,0.000032043296,0.000036424495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000093398696,0.00012140599,0.00021803325,0.00009635662,0.00005701269,0.000010213977,0.00021129393,0.00011951725,0.000036713573],"category_scores_gemma":[0.000042746913,0.000098013865,0.00006212251,0.00012248923,0.00003510541,0.000007942444,0.0002481044,0.00060351216,0.000022964678],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002613615,0.001129059,0.061333977,0.00034158467,0.00009527462,0.00012912601,0.0032449951,0.00035484324,0.036331523,0.027017912,0.8370375,0.03272282],"study_design_scores_gemma":[0.00038428494,0.00008453784,0.1225159,0.0002712931,0.00010737118,0.0000069331913,0.00008307391,0.00010158015,0.002037069,0.024946079,0.84926283,0.00019902542],"about_ca_topic_score_codex":0.00036705987,"about_ca_topic_score_gemma":0.000049516224,"teacher_disagreement_score":0.24262583,"about_ca_system_score_codex":0.00008080454,"about_ca_system_score_gemma":0.000043892924,"threshold_uncertainty_score":0.39968893},"labels":[],"label_agreement":null},{"id":"W4407030709","doi":"10.1016/j.pscychresns.2025.111958","title":"Correlation study between the microstructural abnormalities of medial prefrontal cortex and white matter hyperintensities with mild cognitive impairment patients: A diffusion kurtosis imaging study","year":2025,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Kurtosis; White matter; Prefrontal cortex; Psychology; Diffusion MRI; Cognitive impairment; Correlation; Audiology; Neuroscience; Cognition; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.036444473273477544,"score_gpt":0.3656877081897759,"score_spread":0.32924323491629837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407030709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9916306,0.00009141218,0.00040233016,0.0036960777,0.00012269325,0.003589513,0.000045703055,0.00007461435,0.00034706912],"genre_scores_gemma":[0.9987139,0.000014117385,0.00041330137,0.00037528522,0.00007124695,0.00021445104,0.000028822216,0.00003560771,0.00013325074],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99772954,0.0002899578,0.00043321197,0.00054852,0.00060468575,0.00039406237],"domain_scores_gemma":[0.998551,0.00028109096,0.00013376508,0.00042674295,0.00052167877,0.000085726926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039153238,0.00023825113,0.00033927555,0.00034851077,0.00053792924,0.00009011268,0.00018024555,0.000021391326,0.000014532096],"category_scores_gemma":[0.000050383467,0.00016350768,0.000053094514,0.0004733548,0.00054634205,0.00019832201,0.0003743862,0.0006729616,0.0000018523061],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005858728,0.0006592728,0.9948986,0.000082814,0.000062475345,0.000005291031,0.0025301229,9.906898e-7,0.00019171218,0.000010695054,0.0003480656,0.00062407955],"study_design_scores_gemma":[0.0029229114,0.0009825887,0.9731724,0.00027661657,0.00020989927,0.000020700965,0.021775724,0.0002802763,0.00004654416,0.00016752855,0.000017258062,0.00012750403],"about_ca_topic_score_codex":0.00018262587,"about_ca_topic_score_gemma":0.00002690715,"teacher_disagreement_score":0.02172616,"about_ca_system_score_codex":0.000054267908,"about_ca_system_score_gemma":0.00009097717,"threshold_uncertainty_score":0.666765},"labels":[],"label_agreement":null},{"id":"W4407103892","doi":"10.7554/elife.103530.1.sa1","title":"Reviewer #1 (Public review): Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Cartography; Diffusion; Zona; Geography; Biology; Neuroscience; Physics; Virology","score_opus":0.13312969900421867,"score_gpt":0.3878983160392467,"score_spread":0.254768617035028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103892","genre_codex":"commentary","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00011158531,0.4176452,0.029455524,0.53303987,0.0010336742,0.0101899775,0.00008937897,0.00037305552,0.008061718],"genre_scores_gemma":[0.00024016951,0.8533195,0.0035451495,0.06114447,0.00033358988,0.00019098661,0.0007089639,0.000081715465,0.08043542],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977049,0.00016681185,0.0009352457,0.000477642,0.0005011877,0.00021419804],"domain_scores_gemma":[0.99516165,0.00009296496,0.0007722365,0.0019862766,0.001934667,0.000052182255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056274957,0.00033733412,0.00091509346,0.00014691446,0.00038098288,0.000016109436,0.0007213699,0.00013247613,0.00046970832],"category_scores_gemma":[0.0015722688,0.00017488777,0.00036694176,0.0027531697,0.00017072102,0.000047545713,0.00055843545,0.0007094155,0.0000026427613],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[2.338112e-7,0.00006612041,0.0005155773,0.02331041,0.00003136357,4.0858885e-7,0.0000065568865,1.6651393e-7,0.00047691548,0.0014920263,0.9671133,0.00698689],"study_design_scores_gemma":[0.000079126476,0.000009460349,0.00047108057,0.091480605,0.00063289347,0.000016379749,0.000003071467,0.000028835831,0.00006180435,0.00019250397,0.9068773,0.00014694654],"about_ca_topic_score_codex":0.00008860882,"about_ca_topic_score_gemma":0.000010965343,"teacher_disagreement_score":0.47189543,"about_ca_system_score_codex":0.00008723823,"about_ca_system_score_gemma":0.00022873233,"threshold_uncertainty_score":0.7131716},"labels":[],"label_agreement":null},{"id":"W4407103926","doi":"10.7554/elife.103530.1","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Zona; Diffusion; Diffusion MRI; Cartography; Geography; Geology; Biology; Neuroscience; Physics; Magnetic resonance imaging; Medicine; Radiology; Virology","score_opus":0.08933693897071142,"score_gpt":0.3609058517935722,"score_spread":0.2715689128228608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103926","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9123643,0.0002304813,0.0770516,0.007241352,0.00022970093,0.001459936,0.000028478182,0.00021464602,0.001179498],"genre_scores_gemma":[0.99311554,0.0002831452,0.0048979498,0.0010561298,0.00013747947,0.000027073507,0.00004380794,0.000022449254,0.0004164357],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991357,0.00003859729,0.00026680576,0.0002434052,0.00021849306,0.00009701101],"domain_scores_gemma":[0.99866015,0.000036946112,0.00023486545,0.00087888475,0.0001674153,0.000021743583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010387838,0.00012997475,0.00019297439,0.00009332612,0.00026715617,0.000012674398,0.00032283054,0.000098287914,0.000014758532],"category_scores_gemma":[0.00008190238,0.00007937455,0.00009604743,0.00057432154,0.000105362094,0.000013022936,0.0008323353,0.0004655659,4.5197956e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014094473,0.00056134944,0.59124756,0.0016102609,0.00019764464,0.000004387304,0.0026107177,0.002142543,0.35998538,0.028594282,0.007795369,0.005236433],"study_design_scores_gemma":[0.0013275461,0.000061151455,0.7305974,0.008840602,0.00086001126,0.000056340574,0.0006177451,0.017779227,0.14499392,0.02218954,0.07173288,0.00094362855],"about_ca_topic_score_codex":0.0001072271,"about_ca_topic_score_gemma":0.000003547094,"teacher_disagreement_score":0.21499145,"about_ca_system_score_codex":0.000044763616,"about_ca_system_score_gemma":0.00009994431,"threshold_uncertainty_score":0.32368},"labels":[],"label_agreement":null},{"id":"W4407103944","doi":"10.7554/elife.103530","title":"Mapping the topographic organization of the human zona incerta using diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University; Robarts Clinical Trials","funders":"McDonnell Center for Systems Neuroscience; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Zona incerta; Zona; Diffusion; Diffusion MRI; Cartography; Geography; Psychology; Neuroscience; Medicine; Magnetic resonance imaging; Physics; Radiology; Virology","score_opus":0.08933693897071142,"score_gpt":0.3609058517935722,"score_spread":0.2715689128228608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407103944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9123643,0.0002304813,0.0770516,0.007241352,0.00022970093,0.001459936,0.000028478182,0.00021464602,0.001179498],"genre_scores_gemma":[0.99311554,0.0002831452,0.0048979498,0.0010561298,0.00013747947,0.000027073507,0.00004380794,0.000022449254,0.0004164357],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991357,0.00003859729,0.00026680576,0.0002434052,0.00021849306,0.00009701101],"domain_scores_gemma":[0.99866015,0.000036946112,0.00023486545,0.00087888475,0.0001674153,0.000021743583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010387838,0.00012997475,0.00019297439,0.00009332612,0.00026715617,0.000012674398,0.00032283054,0.000098287914,0.000014758532],"category_scores_gemma":[0.00008190238,0.00007937455,0.00009604743,0.00057432154,0.000105362094,0.000013022936,0.0008323353,0.0004655659,4.5197956e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014094473,0.00056134944,0.59124756,0.0016102609,0.00019764464,0.000004387304,0.0026107177,0.002142543,0.35998538,0.028594282,0.007795369,0.005236433],"study_design_scores_gemma":[0.0013275461,0.000061151455,0.7305974,0.008840602,0.00086001126,0.000056340574,0.0006177451,0.017779227,0.14499392,0.02218954,0.07173288,0.00094362855],"about_ca_topic_score_codex":0.0001072271,"about_ca_topic_score_gemma":0.000003547094,"teacher_disagreement_score":0.21499145,"about_ca_system_score_codex":0.000044763616,"about_ca_system_score_gemma":0.00009994431,"threshold_uncertainty_score":0.32368},"labels":[],"label_agreement":null},{"id":"W4407161502","doi":"10.1038/s42003-025-07528-8","title":"A multimodal characterization of low-dimensional thalamocortical structural connectivity patterns","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Hospital for Sick Children; Max-Planck-Gesellschaft; Canadian Institutes of Health Research; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Bundesministerium für Bildung und Forschung; Canada Research Chairs; McGill University","keywords":"Thalamus; Neuroscience; Connectome; Human Connectome Project; Diffusion MRI; Functional connectivity; Default mode network; Stimulus modality; Psychology; Sensory system; Medicine; Magnetic resonance imaging","score_opus":0.05494794832803931,"score_gpt":0.3950609596979854,"score_spread":0.3401130113699461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407161502","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96108973,0.000039759656,0.032889176,0.0049183005,0.000033551954,0.00036659875,0.000068823785,0.00009482384,0.00049920834],"genre_scores_gemma":[0.98917013,0.00004997723,0.009767926,0.00040241826,0.0000101477135,0.00008369146,0.00044979574,0.000005983585,0.000059900518],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994274,0.00006606126,0.00022624785,0.00015231449,0.00003058257,0.000097421485],"domain_scores_gemma":[0.9986087,0.00015829658,0.0000818581,0.0009914571,0.00013080581,0.000028874802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000052505926,0.00007489412,0.00017843304,0.000089168556,0.000098209675,0.0000026262123,0.00022694067,0.00006781542,0.000023793085],"category_scores_gemma":[0.00009092128,0.000066911685,0.0000504289,0.00017239782,0.0002626534,0.000030176758,0.00024877267,0.00016956466,0.0000023730338],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044762666,0.00022878313,0.31031254,0.000039959432,0.000031519718,3.6152522e-7,0.000029008166,0.0000015143731,0.59172183,0.085312285,0.000020789346,0.01225664],"study_design_scores_gemma":[0.0005982816,0.000080753896,0.94052136,0.00008850401,0.00004667247,0.000019282694,0.000011443443,0.01693607,0.033833753,0.0062848744,0.0014828219,0.000096201235],"about_ca_topic_score_codex":0.000013306383,"about_ca_topic_score_gemma":0.000003359522,"teacher_disagreement_score":0.6302088,"about_ca_system_score_codex":0.000023246106,"about_ca_system_score_gemma":0.0000608588,"threshold_uncertainty_score":0.27285793},"labels":[],"label_agreement":null},{"id":"W4407295955","doi":"10.1111/jon.70019","title":"Magnetization Transfer Ratio in the Typically Developing Pediatric Spinal Cord: Normative Data and Age Correlation","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"National Institute of Neurological Disorders and Stroke; National Institutes of Health","keywords":"Medicine; White matter; Magnetization transfer; Magnetic resonance imaging; Spinal cord; Nuclear medicine; Correlation; Fasciculus; Dorsum; Anatomy; Radiology","score_opus":0.09257360947177605,"score_gpt":0.3904115014308506,"score_spread":0.29783789195907456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407295955","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23610607,0.00031867137,0.74766034,0.014934084,0.000081561804,0.00030372897,0.0000028142128,0.00001987585,0.0005728744],"genre_scores_gemma":[0.98286676,0.0005554949,0.014326109,0.002127023,0.00007832852,0.0000031315287,0.000008924529,0.0000075028306,0.000026714335],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991951,0.00006045274,0.00037460966,0.00012988198,0.00014893009,0.00009100182],"domain_scores_gemma":[0.99946344,0.00011129882,0.000098437966,0.00020042765,0.00010355415,0.000022819906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030193548,0.00007754989,0.0001434141,0.00022184379,0.000073107025,0.000044206314,0.00018461184,0.000019228708,0.0000019609013],"category_scores_gemma":[0.00018546007,0.000057838308,0.000021166043,0.0004470649,0.00003554481,0.00030633077,0.000045283115,0.00035635504,5.084597e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028543214,0.0007232694,0.57694757,0.0009671321,0.00006711342,0.0013659325,0.0027447043,0.0006372033,0.027479667,0.039369505,0.01031337,0.3365302],"study_design_scores_gemma":[0.0013943284,0.00038544208,0.9673294,0.00029617065,0.00020410681,0.000893037,0.00023520923,0.015982509,0.000163653,0.0038850948,0.009094629,0.00013644909],"about_ca_topic_score_codex":0.0000017997173,"about_ca_topic_score_gemma":0.0000013287918,"teacher_disagreement_score":0.7467607,"about_ca_system_score_codex":0.000024115101,"about_ca_system_score_gemma":0.00008980305,"threshold_uncertainty_score":0.23585777},"labels":[],"label_agreement":null},{"id":"W4407419860","doi":"10.1002/hbm.70143","title":"Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross‐Sectional Datasets Across the Lifespan","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; H. Lundbeck A/S; Servier; Eisai; Georgia Clinical and Translational Science Alliance; Pfizer; Biogen; BioClinica; National Center for Research Resources; F. Hoffmann-La Roche; Vanderbilt University; Vanderbilt Memory and Alzheimer's Center; Novartis Pharmaceuticals Corporation; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Association; Foundation for the National Institutes of Health","keywords":"Magnetic resonance imaging; Motion (physics); Diffusion MRI; Functional magnetic resonance imaging; Neuroimaging; Psychology; Computer vision; Artificial intelligence; Computer science; Neuroscience; Medicine; Radiology","score_opus":0.0494239448141113,"score_gpt":0.40001855553710297,"score_spread":0.3505946107229917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407419860","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9765155,0.00052679895,0.00988116,0.0119776465,0.000046611345,0.00066403014,0.00018910288,0.00009618565,0.000102969876],"genre_scores_gemma":[0.99633515,0.000019300855,0.0008966816,0.0014205606,0.00004416462,0.000108471264,0.0007174643,0.000011423856,0.00044676155],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987616,0.00007632215,0.00040261896,0.0003760527,0.0001445742,0.00023883992],"domain_scores_gemma":[0.99928236,0.00016470773,0.00010253188,0.00034278753,0.0000763805,0.000031210602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004955236,0.00011602159,0.00013653708,0.00015749563,0.0006363338,0.00011784983,0.00011927029,0.000049740185,0.000009890993],"category_scores_gemma":[0.0003340283,0.000108087166,0.000028007269,0.0005195172,0.00014295086,0.00020163144,0.00009459514,0.00029577955,0.0000013808079],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062368895,0.000046034016,0.96972936,0.000022610013,0.0000012773814,0.0000019796607,0.00033687585,0.000016220249,0.0143864555,0.013364436,0.0007852543,0.0013032546],"study_design_scores_gemma":[0.0007987116,0.0000071017826,0.9740517,0.000112949325,0.0000031268307,0.000008575605,0.00012962305,0.005694493,0.000043140943,0.011067349,0.007997128,0.00008605998],"about_ca_topic_score_codex":0.00010528678,"about_ca_topic_score_gemma":0.00039688245,"teacher_disagreement_score":0.019819677,"about_ca_system_score_codex":0.00012377687,"about_ca_system_score_gemma":0.000029654397,"threshold_uncertainty_score":0.48942292},"labels":[],"label_agreement":null},{"id":"W4407591286","doi":"10.7554/elife.101950.3","title":"From histology to macroscale function in the human amygdala","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Sickkids Research Institute; Savoy Foundation; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Amygdala; Neuroscience; Neuroimaging; Human brain; Spatial normalization; Cytoarchitecture; Voxel; Anatomy; Biology; Computer science; Artificial intelligence","score_opus":0.05220968834402858,"score_gpt":0.400782774699086,"score_spread":0.34857308635505746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407591286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8862662,0.000116502764,0.05829014,0.039933342,0.00012346142,0.0005363054,0.000007814906,0.00018272629,0.014543525],"genre_scores_gemma":[0.98086053,0.000005768882,0.0024527549,0.014932586,0.00007554511,0.00010571297,0.000017346443,0.0000048207635,0.001544938],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99963146,0.000014064278,0.00009161958,0.00013265507,0.000054974502,0.000075212825],"domain_scores_gemma":[0.9996669,0.000032936612,0.000013427325,0.00025592354,0.000013176632,0.000017632634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000050153427,0.00004155203,0.00007478383,0.00004846249,0.000050789815,0.0000041143976,0.00007119531,0.000023505361,0.000023797305],"category_scores_gemma":[0.000026128517,0.00003152933,0.00001891387,0.00016765857,0.000022587865,0.000010556543,0.00002476584,0.00011347591,0.000022819693],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011924341,0.00046661583,0.12565625,0.000024962354,0.000018189312,0.00003346621,0.000877323,0.000015949745,0.23304628,0.06581895,0.54831773,0.025605043],"study_design_scores_gemma":[0.0002787155,0.00005275671,0.2750304,0.000026209182,0.00001862136,0.000002855269,0.00007320842,0.000027843415,0.004437262,0.007996974,0.71201193,0.000043194545],"about_ca_topic_score_codex":0.00009790819,"about_ca_topic_score_gemma":0.000025690351,"teacher_disagreement_score":0.22860903,"about_ca_system_score_codex":0.000028512017,"about_ca_system_score_gemma":0.000010223724,"threshold_uncertainty_score":0.12857288},"labels":[],"label_agreement":null},{"id":"W4407710349","doi":"10.1002/mrm.30465","title":"Interpretation of inhomogeneous magnetization transfer in myelin water using a four‐pool model with dipolar reservoirs","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; McGill University; University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; International Collaboration on Repair Discoveries","keywords":"Myelin; Magnetization transfer; White matter; Nuclear magnetic resonance; Chemistry; Magnetic resonance imaging; Dipole; Drop (telecommunication); Biophysics; Physics; Neuroscience; Biology; Medicine; Radiology; Central nervous system","score_opus":0.04129908535081966,"score_gpt":0.32660694325929646,"score_spread":0.2853078579084768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407710349","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.773356,0.0027761708,0.21827373,0.003792704,0.00002122269,0.0009682465,0.0000039653023,0.00004384368,0.00076410075],"genre_scores_gemma":[0.9813619,0.0006222653,0.016841011,0.00053118414,0.000018960982,0.00010712701,0.000016632763,0.000023519846,0.00047736213],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985847,0.000046909852,0.0005475443,0.00033966103,0.00024348452,0.00023770014],"domain_scores_gemma":[0.9993904,0.000053854157,0.000034623907,0.00036632823,0.000114315095,0.000040477462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002542878,0.0001620169,0.00038938606,0.0004287914,0.000025268333,0.000003690567,0.00012297003,0.0000747362,0.000036386326],"category_scores_gemma":[0.00008873662,0.00011500897,0.000026392558,0.00066086213,0.00020752932,0.00005952631,0.000029041545,0.00024619454,5.911396e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004602701,0.00075574877,0.10439526,0.001468996,0.000018702229,0.0003109557,0.0059220144,0.09166044,0.47885165,0.002432677,0.00033516908,0.30924568],"study_design_scores_gemma":[0.0038724446,0.00084120495,0.022900704,0.00382862,0.00008985773,0.000048345202,0.00015435787,0.9458114,0.017205015,0.0036663872,0.0013952771,0.00018642572],"about_ca_topic_score_codex":0.0001938437,"about_ca_topic_score_gemma":0.00013289125,"teacher_disagreement_score":0.85415095,"about_ca_system_score_codex":0.00008378038,"about_ca_system_score_gemma":0.00006769193,"threshold_uncertainty_score":0.46899298},"labels":[],"label_agreement":null},{"id":"W4407777100","doi":"10.1016/j.pnpbp.2025.111294","title":"White matter integrity and verbal memory following a first episode of psychosis: A longitudinal study","year":2025,"lang":"en","type":"article","venue":"Progress in Neuro-Psychopharmacology and Biological Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre; McGill University; Douglas Mental Health University Institute","funders":"Canadian Institutes of Health Research","keywords":"Psychosis; Psychology; White matter; Verbal memory; Psychiatry; Developmental psychology; Clinical psychology; Medicine; Cognition","score_opus":0.054293657111784244,"score_gpt":0.4096242642019829,"score_spread":0.35533060709019865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407777100","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98085225,0.0029173638,0.0001753965,0.013849368,0.0005453843,0.0011769972,0.0000069712883,0.000092372815,0.00038392036],"genre_scores_gemma":[0.99282706,0.00037619998,0.003210387,0.0030555367,0.000053996762,0.00043658665,0.000002963395,0.000011005839,0.00002625019],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983882,0.00011570442,0.0004469479,0.000692044,0.000082397615,0.00027473754],"domain_scores_gemma":[0.9993884,0.00013830606,0.000109220906,0.00024558385,0.000030740088,0.00008776427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022690801,0.00023386373,0.00046495275,0.00018749665,0.00011936918,0.00001143063,0.00016142962,0.000166005,0.000037947615],"category_scores_gemma":[0.000021780543,0.0001783392,0.00009319334,0.00039913628,0.00040261477,0.00005031566,0.00014700278,0.00077678566,0.0000017014926],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001231626,0.0017333681,0.99208635,0.00011139865,0.00006243886,0.00002715804,0.000047037618,2.0006503e-7,0.0000204918,0.00019593937,0.0018747349,0.0026092748],"study_design_scores_gemma":[0.0033566717,0.0008272164,0.9923302,0.00012558597,0.00011959639,0.000042117957,0.000075410586,0.000048285565,0.0000075865005,0.0024753045,0.00045591715,0.00013610779],"about_ca_topic_score_codex":0.000006423066,"about_ca_topic_score_gemma":0.000013254777,"teacher_disagreement_score":0.011974848,"about_ca_system_score_codex":0.000011413471,"about_ca_system_score_gemma":0.000017063538,"threshold_uncertainty_score":0.7272462},"labels":[],"label_agreement":null},{"id":"W4407788542","doi":"10.1016/j.bpsgos.2025.100472","title":"Stable White Matter Structure in the First Three Years After Psychosis Onset","year":2025,"lang":"en","type":"article","venue":"Biological Psychiatry Global Open Science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute; London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"Janssen Canada; National Institute of Mental Health; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Sunovion; Canadian Institutes of Health Research; Canada Research Chairs; Canada First Research Excellence Fund; National Institutes of Health; Western University; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Brain and Behavior Research Foundation; McGill University; Mitsubishi Tanabe Pharma Corporation","keywords":"Psychosis; White matter; Psychology; Psychiatry; Medicine; Magnetic resonance imaging","score_opus":0.04428910245027392,"score_gpt":0.3820150096875228,"score_spread":0.3377259072372489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407788542","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91789424,0.00017855248,0.0013460666,0.06116967,0.00026891084,0.0011823142,0.00009732401,0.00005116563,0.017811777],"genre_scores_gemma":[0.9534356,0.000013897637,0.01588918,0.030460306,0.000022989481,0.000101924285,0.000004014198,0.0000024353208,0.00006965612],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998803,0.000019620482,0.00019092928,0.0005234457,0.00017194792,0.0002910485],"domain_scores_gemma":[0.99921507,0.000019407633,0.00004361048,0.0006322587,0.000034884997,0.00005477339],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026825015,0.00011688631,0.00015678225,0.000043303346,0.00015482098,0.00013312572,0.0014279461,0.00006261772,0.00017843382],"category_scores_gemma":[0.00002962543,0.00006702062,0.000040798637,0.0014929355,0.0004481527,0.00012429133,0.0004066209,0.00018584548,0.000032898115],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007322058,0.00007765666,0.97511417,0.0000042470406,0.0000014916582,0.000002669333,0.000008207573,0.0000019501063,0.000021957943,0.005392454,0.01889394,0.0004080584],"study_design_scores_gemma":[0.00022044608,0.000060631646,0.926003,0.000047680634,0.0000058865335,0.000019346446,0.00003227157,0.000015964759,0.0000041187363,0.042920936,0.030592907,0.000076833494],"about_ca_topic_score_codex":0.000054570417,"about_ca_topic_score_gemma":0.00019818377,"teacher_disagreement_score":0.049111173,"about_ca_system_score_codex":0.000062255596,"about_ca_system_score_gemma":0.00009826078,"threshold_uncertainty_score":0.27330217},"labels":[],"label_agreement":null},{"id":"W4407793608","doi":"10.1101/2025.02.19.638284","title":"White-matter controllability at birth predicts social engagement and language outcomes in toddlerhood","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Columbia College","funders":"","keywords":"Controllability; White (mutation); Psychology; White matter; Developmental psychology; Medicine; Mathematics; Chemistry","score_opus":0.028304870949952165,"score_gpt":0.2964071252606344,"score_spread":0.26810225431068224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407793608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9910661,0.00038213586,0.00096779055,0.0042610876,0.00016053447,0.001978388,0.0005747282,0.00050705264,0.00010217022],"genre_scores_gemma":[0.9918092,0.00008923449,0.0057806447,0.0013867302,0.000119386226,0.0006472356,0.000001048963,0.000054599164,0.000111924965],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978224,0.00011860144,0.0005045096,0.0009141355,0.00025127086,0.0003891002],"domain_scores_gemma":[0.9984413,0.00009470072,0.00021444129,0.00095419725,0.00014972604,0.00014564952],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00041313362,0.00041905974,0.00076398073,0.00024357846,0.0001471395,0.00005247095,0.00021789553,0.00028453767,0.00007258983],"category_scores_gemma":[0.00015838494,0.00041244182,0.0001238329,0.0002700586,0.00012877767,0.000055151413,0.00082403375,0.0008253202,0.00001328294],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007027246,0.00029919646,0.9730525,0.0007660687,0.00008254986,0.00004070908,0.00006200819,0.000004642578,0.024296857,0.00023770501,0.0010834666,0.0000040319123],"study_design_scores_gemma":[0.0013193669,0.000031893607,0.9866009,0.00023573969,0.00011964043,2.0929747e-8,0.0000071179666,0.00013065117,0.008370864,0.000008151657,0.002840689,0.00033496082],"about_ca_topic_score_codex":0.000026109457,"about_ca_topic_score_gemma":0.000005385963,"teacher_disagreement_score":0.015925992,"about_ca_system_score_codex":0.000375566,"about_ca_system_score_gemma":0.00020747307,"threshold_uncertainty_score":0.99983275},"labels":[],"label_agreement":null},{"id":"W4407819042","doi":"10.1002/hbm.70165","title":"The <i>Psy</i>chosis <scp>MRI</scp><i>Share</i>d <i>D</i>ata Resource (Psy‐<scp>ShareD</scp>)","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Medical Research Council","keywords":"Neuroimaging; Schizophrenia (object-oriented programming); General partnership; Data sharing; Psychology; Psychosis; Resource (disambiguation); Medicine; Psychiatry; Computer science; Business; Pathology; Finance","score_opus":0.055153388133853155,"score_gpt":0.3326830771960151,"score_spread":0.2775296890621619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407819042","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12583624,0.009242993,0.14057909,0.123620085,0.0008212356,0.0096642645,0.00053821097,0.009738804,0.5799591],"genre_scores_gemma":[0.441807,0.0017985696,0.04296373,0.14000829,0.003141534,0.0045055067,0.0018305564,0.00090862333,0.3630362],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99673456,0.0001354432,0.0007443895,0.0009923021,0.00047339752,0.0009198952],"domain_scores_gemma":[0.99520993,0.0021950384,0.00031656274,0.0018691526,0.00016106438,0.0002482317],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00069929665,0.00047387395,0.00052252697,0.00027913557,0.0018751024,0.0002721603,0.00095272047,0.00017774802,0.000020786178],"category_scores_gemma":[0.0016162039,0.00041359008,0.00029342587,0.0010755467,0.00032207245,0.00018633633,0.00056311494,0.0009450415,0.00009605984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000035252733,0.00012022253,0.0025203445,0.00018499908,0.00008194407,0.000027197859,0.0006301497,0.000013733728,0.04856455,0.022862215,0.92323554,0.0017555675],"study_design_scores_gemma":[0.00072856486,0.00005866811,0.014545426,0.00067514967,0.00007667885,0.000038540915,0.0007426601,0.00026225328,0.002361391,0.011192599,0.9692238,0.000094262476],"about_ca_topic_score_codex":0.000026517471,"about_ca_topic_score_gemma":0.000012983136,"teacher_disagreement_score":0.31597075,"about_ca_system_score_codex":0.00015611167,"about_ca_system_score_gemma":0.00010473599,"threshold_uncertainty_score":0.9998316},"labels":[],"label_agreement":null},{"id":"W4407987573","doi":"10.1002/mrm.30424","title":"Considerations and recommendations from the <scp>ISMRM</scp> Diffusion Study Group for preclinical diffusion <scp>MRI</scp> : Part 3—Ex vivo imaging: Data processing, comparisons with microscopy, and tractography","year":2025,"lang":"en","type":"review","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"H2020 European Research Council; National Cancer Institute; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; National Institute on Drug Abuse; Institut de Valorisation des Données; National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Vlaamse regering; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; Canada First Research Excellence Fund; Universiteit Antwerpen; Canada Foundation for Innovation; Fonds Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; National Science Foundation; National Institute of Neurological Disorders and Stroke; Generalitat de Catalunya; Wellcome Trust","keywords":"Ex vivo; Diffusion MRI; Tractography; Diffusion imaging; Microscopy; Magnetic resonance imaging; In vivo; Nuclear magnetic resonance; Neuroscience; Medicine; Pathology; Biology; Physics; Radiology","score_opus":0.12290899044640002,"score_gpt":0.4309845932417162,"score_spread":0.30807560279531615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407987573","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007744545,0.97853726,0.005402201,0.0055095255,0.00013981647,0.008324857,0.0009084682,0.00016718346,0.00023620324],"genre_scores_gemma":[0.00025540293,0.9682746,0.02580668,0.0011127469,0.00030900748,0.0019098262,0.0016266075,0.00009287219,0.00061227585],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99563193,0.0003249388,0.0014721958,0.0016614379,0.00041204516,0.000497432],"domain_scores_gemma":[0.9877874,0.009443435,0.00063730986,0.0017434143,0.0001645494,0.00022384788],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00086087675,0.0007055292,0.0020611035,0.0003214682,0.00060117483,0.00012253886,0.000546039,0.00020454128,0.000016914288],"category_scores_gemma":[0.0023756975,0.00044770943,0.00010217071,0.00083147583,0.0009679293,0.00014637105,0.00051907846,0.0011778369,8.498643e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018982946,0.001631983,0.027758738,0.003046378,0.000054091237,0.00003384406,0.0009847797,1.378714e-7,0.00003328831,0.00013285466,0.2181788,0.74812615],"study_design_scores_gemma":[0.0026511494,0.0007770414,0.010177305,0.021840185,0.0018739464,0.000081557075,0.0012002243,0.00065936975,9.3548056e-7,0.0004886332,0.9601383,0.00011134336],"about_ca_topic_score_codex":0.00018463592,"about_ca_topic_score_gemma":0.0003492914,"teacher_disagreement_score":0.7480148,"about_ca_system_score_codex":0.000041514533,"about_ca_system_score_gemma":0.00025571705,"threshold_uncertainty_score":0.99979746},"labels":[],"label_agreement":null},{"id":"W4407987811","doi":"10.1002/mrm.30429","title":"Considerations and recommendations from the <scp>ISMRM</scp> diffusion study group for preclinical diffusion <scp>MRI</scp> : Part 1: In vivo small‐animal imaging","year":2025,"lang":"en","type":"review","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"National Cancer Institute; National Institute of Mental Health; National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; HORIZON EUROPE Framework Programme; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; Universiteit Antwerpen; Canada First Research Excellence Fund; Norges Forskningsråd; Fonds Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; National Science Foundation; National Institute of Neurological Disorders and Stroke; Generalitat de Catalunya; National Institute on Drug Abuse; Institut de Valorisation des Données; National Institute of Biomedical Imaging and Bioengineering; Vlaamse regering; European Commission","keywords":"In vivo; Diffusion; Diffusion imaging; Chemistry; Diffusion MRI; Nuclear magnetic resonance; Medicine; Magnetic resonance imaging; Physics; Biology; Radiology","score_opus":0.10475546549551583,"score_gpt":0.40542778403316126,"score_spread":0.3006723185376454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407987811","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002274216,0.97834206,0.0011914804,0.0069029774,0.00031416316,0.009788093,0.00029531887,0.00017030747,0.00072141463],"genre_scores_gemma":[0.00028558588,0.98327476,0.007644739,0.0015529364,0.0005473433,0.004612157,0.0003826974,0.000093826,0.0016059746],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.995104,0.00051608303,0.002003232,0.0013870441,0.0003938721,0.000595748],"domain_scores_gemma":[0.98008466,0.017920958,0.00050146616,0.0011727966,0.00013505023,0.00018509451],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0012346109,0.0006865326,0.0021698615,0.00042180964,0.00035171836,0.00005971602,0.0004095592,0.0002591096,0.000053187778],"category_scores_gemma":[0.0075024543,0.0004842301,0.00020954401,0.0008881321,0.00044827114,0.00007687231,0.00042408655,0.0013620162,0.000003169415],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016509019,0.0014826432,0.016707921,0.0021444582,0.000030837327,0.000099979785,0.001211693,5.189657e-7,0.00005999979,0.0009946652,0.069553964,0.9076968],"study_design_scores_gemma":[0.0028627894,0.0007200405,0.011431103,0.021763938,0.0007824613,0.0000480104,0.0009834478,0.0005325997,0.0000014380892,0.0025076964,0.95826495,0.00010151279],"about_ca_topic_score_codex":0.00029463903,"about_ca_topic_score_gemma":0.00054077245,"teacher_disagreement_score":0.9075953,"about_ca_system_score_codex":0.00014364839,"about_ca_system_score_gemma":0.00022904247,"threshold_uncertainty_score":0.9997609},"labels":[],"label_agreement":null},{"id":"W4408061855","doi":"10.7554/elife.94917.3","title":"Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Scleroseforeningen","keywords":"White matter; Bridging (networking); Evolutionary biology; Biology; Anatomy; Neuroscience; Computer science; Medicine; Magnetic resonance imaging","score_opus":0.041203847167856904,"score_gpt":0.33508642851343073,"score_spread":0.2938825813455738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408061855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9518129,0.00012406698,0.038737744,0.008181513,0.000020098003,0.00017836076,0.0000149866755,0.000066173976,0.00086413184],"genre_scores_gemma":[0.9942228,0.00008907847,0.0037287425,0.0015882569,0.00005118935,0.000009972897,0.00000575267,0.000007787888,0.00029642132],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994842,0.000011143145,0.00014917871,0.0001385489,0.000112672744,0.00010427018],"domain_scores_gemma":[0.9996158,0.00007159198,0.000040274008,0.00020504628,0.000040122377,0.00002718031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009622579,0.000061346305,0.00012241543,0.00005573783,0.0001316118,0.000008896396,0.00005953925,0.000028043545,0.000022159456],"category_scores_gemma":[0.00006964907,0.00004308062,0.000025587855,0.00027055704,0.00013990278,0.000030507108,0.00011507433,0.00012014638,0.0000051559873],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028416938,0.000087253,0.9558568,0.00006442501,0.000017682441,0.0000027706458,0.00044079282,0.0000044436597,0.020483227,0.004496934,0.008284125,0.010233156],"study_design_scores_gemma":[0.0002415032,0.000019084906,0.96000975,0.000036796446,0.000019656965,0.000014758608,0.00012394281,0.0008136451,0.026242167,0.00034449968,0.012081732,0.000052431726],"about_ca_topic_score_codex":0.000003037057,"about_ca_topic_score_gemma":7.327122e-7,"teacher_disagreement_score":0.042409874,"about_ca_system_score_codex":0.000019635385,"about_ca_system_score_gemma":0.000014234131,"threshold_uncertainty_score":0.17567767},"labels":[],"label_agreement":null},{"id":"W4408061889","doi":"10.7554/elife.94917.3.sa3","title":"Author response: Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Bridging (networking); White matter; Evolutionary biology; Geography; Biology; Computer science; Medicine","score_opus":0.09015636814630748,"score_gpt":0.395265702107038,"score_spread":0.3051093339607305,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408061889","genre_codex":"commentary","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025756437,0.010020413,0.053459343,0.9022572,0.0002895782,0.002650316,0.0012477625,0.0004357197,0.0038831972],"genre_scores_gemma":[0.11332447,0.0092432285,0.036136303,0.029933073,0.00068010605,0.00033330242,0.0008339047,0.00017469429,0.8093409],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99827504,0.000099258184,0.0005364613,0.0004715932,0.00036723827,0.00025042842],"domain_scores_gemma":[0.9982342,0.000535654,0.00021986807,0.00072478136,0.00020773873,0.0000777653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063843635,0.00026305718,0.00065725774,0.00019363235,0.00022099816,0.000021982274,0.00022136724,0.00016777116,0.00033123096],"category_scores_gemma":[0.00057581754,0.00017374716,0.00013021835,0.00064866216,0.00030206458,0.000041449257,0.00042637583,0.0005944506,0.00001253983],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000082547514,0.00006669922,0.0040976615,0.0015499761,0.00003191854,0.000006107483,0.00008340573,3.1783654e-7,0.00058796274,0.00045958167,0.98518753,0.007846288],"study_design_scores_gemma":[0.00021252791,0.000053806074,0.063100964,0.0014797607,0.00018493528,0.00008107344,0.00004636131,0.00011929928,0.0008785526,0.00018262914,0.93347305,0.00018701347],"about_ca_topic_score_codex":0.000010582287,"about_ca_topic_score_gemma":0.0000029620362,"teacher_disagreement_score":0.87232417,"about_ca_system_score_codex":0.00008399705,"about_ca_system_score_gemma":0.000113285634,"threshold_uncertainty_score":0.70852035},"labels":[],"label_agreement":null},{"id":"W4408076912","doi":"10.1016/j.dcn.2025.101540","title":"White matter microstructure in school-age children with down syndrome","year":2025,"lang":"en","type":"article","venue":"Developmental Cognitive Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development","keywords":"Psychology; White matter; White (mutation); Developmental psychology; Magnetic resonance imaging; Medicine; Chemistry","score_opus":0.018783958102442145,"score_gpt":0.3019772539410905,"score_spread":0.28319329583864833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408076912","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9905478,0.000011270003,0.0027708078,0.00090670807,0.000033411638,0.00071721827,0.000026646898,0.00009215453,0.004894009],"genre_scores_gemma":[0.9805114,0.000009657916,0.006387769,0.011425858,0.0000039987203,0.00008227665,0.000024468254,0.000013498111,0.0015410349],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887985,0.000015075057,0.00016479986,0.0005197815,0.00016070464,0.00025980402],"domain_scores_gemma":[0.99969095,0.000017522952,0.000039503233,0.00012484613,0.00004355607,0.000083642284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004386038,0.00016083174,0.000163396,0.00020968683,0.00012774889,0.00004174796,0.00014823987,0.00003198507,0.000049364175],"category_scores_gemma":[0.000042750347,0.00013380562,0.000021267006,0.0009271944,0.00027914555,0.00013658246,0.00012410143,0.00029078845,0.000033404045],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000343979,0.00005189005,0.9891586,0.000009330783,0.0000022426882,0.0001363266,0.000028887016,6.1434093e-7,0.009940491,0.000022503353,0.00025280833,0.00036194292],"study_design_scores_gemma":[0.00062462327,0.000055868444,0.9923457,0.0002059839,0.000011013088,0.0010906153,0.000035151366,0.0000045276183,0.0050131655,0.00012455245,0.0003501031,0.00013873323],"about_ca_topic_score_codex":0.0000071572877,"about_ca_topic_score_gemma":0.000005470675,"teacher_disagreement_score":0.010519151,"about_ca_system_score_codex":0.000070563816,"about_ca_system_score_gemma":0.00014611418,"threshold_uncertainty_score":0.54564345},"labels":[],"label_agreement":null},{"id":"W4408099246","doi":"10.1073/pnas.2412160122","title":"Curve-fitting alone cannot validate neutral theory","year":2025,"lang":"en","type":"letter","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Curve fitting; Mathematics; Statistics","score_opus":0.11205389369712819,"score_gpt":0.38933975755917816,"score_spread":0.27728586386204995,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408099246","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0108874,0.00013250548,0.000024221952,0.960968,0.00003344322,0.000641379,0.00009936238,0.00008803159,0.027125657],"genre_scores_gemma":[0.36924434,0.00017805335,0.017358832,0.6008675,0.0015276994,0.00012534637,0.0000067343003,0.000033296543,0.010658216],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99800396,0.000009626768,0.0004390049,0.00040856283,0.00091601285,0.00022282246],"domain_scores_gemma":[0.9986533,0.00026224888,0.0006573816,0.000020993075,0.00038062694,0.00002545348],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010303071,0.00017339147,0.00032676882,0.00027940958,0.0002076488,0.000020391657,0.0009104468,0.00023680266,0.000009596673],"category_scores_gemma":[0.000564628,0.00011817752,0.0001646982,0.00087492575,0.00096517854,0.00016928714,0.00022812822,0.0011346427,8.7647857e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022165143,0.000054767046,0.0013168039,0.00074041716,0.000049288094,1.337366e-7,0.000055249344,0.000013782988,0.045367487,0.08924807,0.86240405,0.00072781957],"study_design_scores_gemma":[0.00032186537,0.00007515309,0.0061977427,0.0015027336,0.00019307317,0.00007613931,0.000037358564,0.00024523592,0.29889494,0.4372957,0.25487652,0.00028353892],"about_ca_topic_score_codex":0.0000054665893,"about_ca_topic_score_gemma":7.708731e-9,"teacher_disagreement_score":0.6075275,"about_ca_system_score_codex":0.000050354738,"about_ca_system_score_gemma":0.00009741063,"threshold_uncertainty_score":0.49295214},"labels":[],"label_agreement":null},{"id":"W4408105333","doi":"10.1016/j.jad.2025.03.005","title":"Modulation of cerebellar homotopic connectivity by modified electroconvulsive therapy at rest: Study of first-episode, drug-naive adolescent major depressive disorder","year":2025,"lang":"en","type":"article","venue":"Journal of Affective Disorders","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Key Research and Development Program of China; Health and Family Planning Commission of Hubei Province; Department of Science and Technology, Hubei Provincial People's Government; Institute of Clinical and Translational Sciences; Health Commission of Hubei Province; McGill University","keywords":"Electroconvulsive therapy; Drug-naïve; Major depressive disorder; Psychology; Neuroscience; Drug; Cerebellum; Medicine; Psychiatry; Cognition","score_opus":0.01462537213739195,"score_gpt":0.31399185662286694,"score_spread":0.299366484485475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408105333","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96727467,0.0013455986,0.028153585,0.0009676601,0.000049939947,0.0019971791,0.000012994494,0.000022482247,0.00017590294],"genre_scores_gemma":[0.9984128,0.0010994337,0.00019822929,0.00008532487,0.000018297293,0.0000795224,0.0000058244786,0.00002469194,0.000075877266],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985308,0.00016057395,0.0005232063,0.0002865844,0.00030708805,0.00019175693],"domain_scores_gemma":[0.9979556,0.0003092013,0.0008013953,0.00033976015,0.0005318656,0.00006216654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016607183,0.00021898434,0.00059819146,0.0002668801,0.00013890448,0.000005925501,0.00017017954,0.00006868467,0.000008311563],"category_scores_gemma":[0.00018901077,0.0001866323,0.00019569513,0.00048700505,0.00012632126,0.00011505661,0.00006441021,0.00034465457,2.451247e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002168701,0.0066665756,0.92268604,0.00023269079,0.0006350292,0.000005882983,0.001442016,0.0016382397,0.045564853,0.00028680416,0.0014159043,0.01725726],"study_design_scores_gemma":[0.013730124,0.0029706617,0.86767536,0.00043837717,0.0003786876,0.000012737778,0.0013345269,0.0013864134,0.107155845,0.0037650368,0.0008753383,0.00027688936],"about_ca_topic_score_codex":0.0003097681,"about_ca_topic_score_gemma":0.0004644873,"teacher_disagreement_score":0.061590992,"about_ca_system_score_codex":0.0001659712,"about_ca_system_score_gemma":0.00005125217,"threshold_uncertainty_score":0.76106447},"labels":[],"label_agreement":null},{"id":"W4408111203","doi":"10.1101/2025.02.27.25322897","title":"Leveraging multimodal neuroimaging and GWAS for identifying modality-level causal pathways to Alzheimer’s disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health; Public Health Ontario; University of Toronto","funders":"National Heart, Lung, and Blood Institute; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Hjartavernd; Connaught Fund; Simon Fraser University; Krembil Foundation; University of Toronto; Erasmus Medisch Centrum; Bundesministerium für Bildung und Forschung; Institut National de la Santé et de la Recherche Médicale; Université de Lille; Canadian Institutes of Health Research; Centre hospitalier régional universitaire de Lille; Centre for Addiction and Mental Health Foundation; Wellcome Trust; Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer's disease; National Institute on Aging; Alzheimer's Association","keywords":"Imaging genetics; Biobank; Neuroimaging; Genome-wide association study; Modality (human–computer interaction); Mendelian randomization; Causality (physics); Genetic association; Genomics; Psychology; Computer science; Data science; Computational biology; Neuroscience; Biology; Genetic variants; Bioinformatics; Artificial intelligence; Genetics; Genome; Gene; Single-nucleotide polymorphism","score_opus":0.2798626862278928,"score_gpt":0.4197805164507116,"score_spread":0.13991783022281884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408111203","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38580942,0.00089167786,0.5896269,0.017086744,0.0004970965,0.004156292,0.0008395065,0.0008536888,0.0002386779],"genre_scores_gemma":[0.884771,0.000111369714,0.11037608,0.0026866093,0.00025586615,0.001256271,0.0001817383,0.000087328626,0.0002737481],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973964,0.000049855687,0.00050858577,0.0012820144,0.0002853273,0.00047779465],"domain_scores_gemma":[0.9978657,0.00019795136,0.00016570135,0.0010891763,0.00020332061,0.00047819188],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030218577,0.00045992987,0.0005815678,0.00032165504,0.00027447086,0.00010853315,0.00031951125,0.00011004851,0.000005984547],"category_scores_gemma":[0.0003401067,0.0004890235,0.0002166474,0.00019312366,0.00008731529,0.000080447,0.0011341934,0.0006998584,0.000003846674],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021891457,0.0020665913,0.66611034,0.014322859,0.001315761,0.0011825006,0.0059016496,0.008800583,0.08468699,0.025710031,0.009929886,0.17778365],"study_design_scores_gemma":[0.0033645008,0.0001569339,0.7311034,0.0045038206,0.0031642874,0.00008900353,0.00017028503,0.13767433,0.014644216,0.08014077,0.02253602,0.002452398],"about_ca_topic_score_codex":0.0000636325,"about_ca_topic_score_gemma":0.0000021751189,"teacher_disagreement_score":0.49896157,"about_ca_system_score_codex":0.000074380114,"about_ca_system_score_gemma":0.00024790858,"threshold_uncertainty_score":0.99975616},"labels":[],"label_agreement":null},{"id":"W4408120172","doi":"10.21037/qims-24-1516","title":"White matter microstructural alterations are associated with cognitive decline in benzodiazepine use disorders: a multi-shell diffusion magnetic resonance imaging study","year":2025,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Magnetic resonance imaging; Diffusion MRI; Shell (structure); Benzodiazepine; Cognition; Diffusion-Weighted Magnetic Resonance Imaging; Diffusion; Medicine; Nuclear magnetic resonance; Neuroscience; Psychology; Psychiatry; Materials science; Physics; Internal medicine; Radiology","score_opus":0.061787237893749826,"score_gpt":0.3723903835233813,"score_spread":0.3106031456296314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408120172","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97219056,0.003434273,0.005723971,0.017320428,0.000050972474,0.0011101738,0.0000301617,0.00008042457,0.000059053255],"genre_scores_gemma":[0.99036855,0.00042197134,0.0037276407,0.004961772,0.000015238331,0.00016004354,0.00010857934,0.00003275821,0.00020342291],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99813044,0.00018325468,0.00057962385,0.0005747824,0.00019157883,0.00034029517],"domain_scores_gemma":[0.9978589,0.0014683224,0.00016905904,0.00022530378,0.00020955467,0.00006889645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004026106,0.0002822855,0.000617524,0.000747567,0.00013381995,0.000042212414,0.0000646183,0.000028747383,0.000025413457],"category_scores_gemma":[0.0010400488,0.00022727417,0.000041828553,0.0009921477,0.00039417407,0.00027775488,0.00007921945,0.00038312667,0.0000015690312],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019684692,0.00046404888,0.9933238,0.000035750734,0.0000076151728,0.00014700108,0.0011683011,0.000003093391,0.00043059402,0.000022706034,0.0007086866,0.0034915514],"study_design_scores_gemma":[0.0033755244,0.000100950194,0.9832286,0.0032324453,0.00007274963,0.000016787122,0.0038470987,0.0053627025,0.000018829931,0.00024861287,0.00028846398,0.00020722715],"about_ca_topic_score_codex":0.0004253418,"about_ca_topic_score_gemma":0.0011704052,"teacher_disagreement_score":0.01817803,"about_ca_system_score_codex":0.00006553818,"about_ca_system_score_gemma":0.000055267024,"threshold_uncertainty_score":0.92679715},"labels":[],"label_agreement":null},{"id":"W4408126894","doi":"10.1002/mrm.30436","title":"<scp>3D MERMAID</scp> : <scp>3D</scp> Multi‐shot enhanced recovery motion artifact insensitive diffusion for submillimeter, multi‐shell, and <scp>SNR</scp> ‐efficient diffusion imaging","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; McGill University Health Centre; Montreal Neurological Institute and Hospital","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Imaging phantom; Flip angle; Physics; Pulse sequence; Artifact (error); Scanner; Optics; Single shot; Diffusion; Nuclear magnetic resonance; Materials science; Computer science; Computer vision; Magnetic resonance imaging","score_opus":0.03692552816653036,"score_gpt":0.3238531735608782,"score_spread":0.2869276453943479,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408126894","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8231164,0.010264659,0.15901586,0.0010126629,0.00050764624,0.0039414936,0.000073484596,0.00041769582,0.0016500512],"genre_scores_gemma":[0.8711813,0.013035211,0.084413126,0.0052500633,0.00054047914,0.0017097963,0.000428942,0.00028730056,0.023153778],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99471545,0.0002116471,0.0013849984,0.0017306904,0.0007314814,0.0012257502],"domain_scores_gemma":[0.99429435,0.0032669567,0.0004891269,0.0011174697,0.00044536186,0.0003867632],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008883649,0.0008381248,0.00128814,0.00081867323,0.0004940652,0.000070487666,0.00035690743,0.00030219764,0.00001373061],"category_scores_gemma":[0.006083969,0.0007416874,0.00019544657,0.0012972534,0.00071456237,0.00019031005,0.0003519511,0.0009315583,0.000013713151],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013695235,0.0019262085,0.016453765,0.00084991474,0.000039630293,0.00018872695,0.0040912987,0.00024747686,0.63489395,0.00014473105,0.0118693095,0.32915804],"study_design_scores_gemma":[0.019036165,0.0017725077,0.44119892,0.0058583654,0.00059425127,0.0001799184,0.0033139633,0.29848602,0.076901995,0.0012830609,0.15106136,0.00031349482],"about_ca_topic_score_codex":0.00030000816,"about_ca_topic_score_gemma":0.000050610197,"teacher_disagreement_score":0.5579919,"about_ca_system_score_codex":0.0003236406,"about_ca_system_score_gemma":0.00011197276,"threshold_uncertainty_score":0.99950343},"labels":[],"label_agreement":null},{"id":"W4408161681","doi":"10.1002/mrm.30435","title":"Considerations and recommendations from the <scp>ISMRM</scp> diffusion study group for preclinical diffusion <scp>MRI</scp> : Part 2—Ex vivo imaging: Added value and acquisition","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Hotchkiss Brain Institute; Mila - Quebec Artificial Intelligence Institute; Alberta Children's Hospital; Université de Sherbrooke; University of Calgary","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Drug Abuse; National Institute on Aging; National Cancer Institute; Generalitat de Catalunya; National Institutes of Health; Vlaamse regering; Fonds Wetenschappelijk Onderzoek; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Ex vivo; Diffusion; In vivo; Diffusion MRI; Diffusion imaging; Chemistry; Nuclear magnetic resonance; Magnetic resonance imaging; Nuclear medicine; Medicine; In vitro; Physics; Biochemistry; Biology; Radiology; Thermodynamics","score_opus":0.04485616966101895,"score_gpt":0.3638918068535761,"score_spread":0.3190356371925571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408161681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87650144,0.017490571,0.015854187,0.08031926,0.0004398018,0.0072267023,0.00018561588,0.00030713103,0.0016752734],"genre_scores_gemma":[0.9308655,0.013028706,0.031326223,0.016731545,0.0008344613,0.0027054877,0.0004414049,0.00009750293,0.0039691664],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99758613,0.0002141371,0.0007938651,0.0007848008,0.0002819314,0.00033910625],"domain_scores_gemma":[0.992336,0.0065386407,0.00017707584,0.0006701615,0.00013898627,0.00013915179],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007207632,0.00029220388,0.0005325562,0.00016703166,0.00043536653,0.00004993168,0.00014979832,0.00009970846,0.000040273804],"category_scores_gemma":[0.0030101205,0.00021602529,0.000053068456,0.00040092506,0.00047135164,0.00009932633,0.00020417402,0.00044209475,0.000001585042],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000925112,0.0024388176,0.4464248,0.0001616413,0.00004620751,0.00005176725,0.0055131814,0.0000058484884,0.018415784,0.012165769,0.39053982,0.12414383],"study_design_scores_gemma":[0.0067508076,0.0010195477,0.56576264,0.0011416901,0.0003360637,0.00003269859,0.0037211527,0.009279972,0.00017301842,0.03505765,0.3766515,0.00007327504],"about_ca_topic_score_codex":0.0001892232,"about_ca_topic_score_gemma":0.00010042965,"teacher_disagreement_score":0.124070555,"about_ca_system_score_codex":0.00004887572,"about_ca_system_score_gemma":0.000052147843,"threshold_uncertainty_score":0.8809256},"labels":[],"label_agreement":null},{"id":"W4408229559","doi":"10.1101/2025.03.06.641646","title":"The relationship of white matter tract orientation to vascular geometry in the human brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Wellcome Trust","keywords":"White matter; Orientation (vector space); Geometry; Human brain; White (mutation); Geology; Psychology; Mathematics; Neuroscience; Medicine; Biology","score_opus":0.03911334127865196,"score_gpt":0.32078400047885086,"score_spread":0.2816706592001989,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408229559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9738534,0.00020017846,0.012560287,0.011038776,0.00012738476,0.0019363153,0.0000775722,0.00014066277,0.00006540016],"genre_scores_gemma":[0.9907542,0.00003348574,0.0068743415,0.0016032654,0.0000870452,0.0005748604,9.987411e-7,0.00003569812,0.0000361333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983416,0.00013800229,0.00049570465,0.00048249363,0.00030605812,0.00023609833],"domain_scores_gemma":[0.997599,0.00035369874,0.00023769987,0.0015313135,0.00021335497,0.000064929845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008714522,0.00022895537,0.0002862552,0.00030591642,0.0002904697,0.000050818795,0.00044528287,0.00016666789,0.000010974542],"category_scores_gemma":[0.00040572498,0.00017076466,0.00012682987,0.0010295376,0.00008434195,0.00005206777,0.00023137937,0.0007721546,0.000011233752],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022613116,0.00038454554,0.92105335,0.00046117094,0.00005146382,0.0000126033565,0.000109532084,0.0001117482,0.059280075,0.014599532,0.0039071133,0.0000062769855],"study_design_scores_gemma":[0.0002621714,0.00002714398,0.9839022,0.00038459353,0.000074546195,2.114605e-8,0.000009375027,0.000029884855,0.00530464,0.000069196176,0.009777018,0.00015921415],"about_ca_topic_score_codex":0.000024325067,"about_ca_topic_score_gemma":0.0000018677221,"teacher_disagreement_score":0.062848866,"about_ca_system_score_codex":0.00012188736,"about_ca_system_score_gemma":0.00014982325,"threshold_uncertainty_score":0.6963581},"labels":[],"label_agreement":null},{"id":"W4408250548","doi":"10.1016/j.neurobiolaging.2025.03.003","title":"Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer's disease","year":2025,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Montreal Neurological Institute and Hospital; Université de Montréal; Concordia University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Réseau en Bio-Imagerie du Quebec; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Disease; Family history; Medicine; White (mutation); White matter; Gerontology; Psychology; Internal medicine; Genetics; Biology; Gene; Magnetic resonance imaging","score_opus":0.03910536625496768,"score_gpt":0.2980154925984705,"score_spread":0.2589101263435028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408250548","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99619794,0.0015098136,0.0008817975,0.0007135187,0.000021714035,0.00030597075,0.00006718475,0.00003017879,0.00027189372],"genre_scores_gemma":[0.99749494,0.00037570053,0.0016940458,0.0002983594,0.000013037807,0.000021524322,0.00002672702,0.000011475891,0.0000642195],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99927825,0.00006351005,0.00023161355,0.00026941142,0.000041309915,0.00011593517],"domain_scores_gemma":[0.99946743,0.00010602678,0.0001138159,0.00023442674,0.000028605835,0.000049705886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075385826,0.000115565046,0.00036163407,0.00032248395,0.000030190375,0.0000028520053,0.00004901277,0.000052180647,0.0000027070857],"category_scores_gemma":[0.000008459656,0.00009586461,0.00002955197,0.0001571012,0.00028506856,0.00003994467,0.00005930825,0.00026494396,1.9635358e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000072719545,0.000021669632,0.9974989,0.00002675298,0.000037476137,0.0000010090932,0.00020744198,0.0000107391015,0.0012546924,0.000046588597,0.00031596108,0.00057146116],"study_design_scores_gemma":[0.00037431368,0.00004437648,0.99522716,0.00006488592,0.00019279035,0.000002112887,0.000033005752,0.000011374529,0.0010173107,0.00013053582,0.0028385432,0.00006357358],"about_ca_topic_score_codex":0.000030998435,"about_ca_topic_score_gemma":8.638229e-7,"teacher_disagreement_score":0.002522582,"about_ca_system_score_codex":0.000014169293,"about_ca_system_score_gemma":0.000042892792,"threshold_uncertainty_score":0.39092454},"labels":[],"label_agreement":null},{"id":"W4408252633","doi":"10.1101/2025.02.27.640654","title":"<i>Ex vivo</i> human brain volumetry: validation of magnetic resonance imaging measurements","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University; Douglas Mental Health University Institute; Université du Québec à Trois-Rivières","funders":"","keywords":"Magnetic resonance imaging; Gold standard (test); Ex vivo; Nuclear medicine; Automated method; Biomedical engineering; Segmentation; In vivo; White matter; Atrophy; Medicine; Artificial intelligence; Pathology; Computer science; Radiology; Biology","score_opus":0.04392171318554433,"score_gpt":0.3041903960060731,"score_spread":0.2602686828205288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408252633","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8954056,0.017113945,0.06279471,0.0074354364,0.001451922,0.0088746315,0.0018608936,0.003953386,0.0011095149],"genre_scores_gemma":[0.9595906,0.00014423199,0.038690392,0.0008771726,0.00018303834,0.00029554512,0.000001528697,0.00010541868,0.0001120393],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99731004,0.000092949056,0.00070938456,0.00097014935,0.0005204622,0.0003970077],"domain_scores_gemma":[0.9968162,0.000066212364,0.00046646717,0.0017617048,0.00072853104,0.00016089331],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00051077217,0.00044696778,0.0006382011,0.00039013533,0.00014230316,0.000055620727,0.0004540514,0.0002102652,0.000050006514],"category_scores_gemma":[0.000383708,0.00052338315,0.00017774735,0.0007223766,0.00016298877,0.000095029136,0.0004332782,0.00065386895,0.000008730456],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022677068,0.00021648346,0.050484583,0.00056798203,0.000025497546,0.000011469736,0.0000037967293,0.00000865508,0.94390804,0.0005273514,0.0041930685,0.000030380164],"study_design_scores_gemma":[0.0007254622,0.000074095595,0.10003461,0.0022866947,0.00027880693,4.3995364e-8,0.0000011794633,0.00035756273,0.86114377,0.000028898077,0.03452501,0.00054387853],"about_ca_topic_score_codex":0.00005569212,"about_ca_topic_score_gemma":5.051881e-7,"teacher_disagreement_score":0.0827643,"about_ca_system_score_codex":0.0002545263,"about_ca_system_score_gemma":0.0003706627,"threshold_uncertainty_score":0.99972177},"labels":[],"label_agreement":null},{"id":"W4408293277","doi":"10.52294/001c.130075","title":"Understanding variability in brain MRI templates: Optimal sample sizes for representative population averages","year":2025,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Canada First Research Excellence Fund; McGill University","keywords":"Template; Sample (material); Sample size determination; Population; Computer science; Statistics; Artificial intelligence; Mathematics; Medicine; Chromatography; Chemistry","score_opus":0.13109705640806182,"score_gpt":0.40271285709053734,"score_spread":0.2716158006824755,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408293277","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008332602,0.00001528325,0.91546553,0.073835425,0.00005882293,0.0012506112,0.00004330417,0.00020463103,0.0007937949],"genre_scores_gemma":[0.9348989,0.000024353887,0.04970259,0.014795933,0.00003740081,0.00019227005,0.00010672195,0.000020456355,0.00022135022],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99909616,0.00005700994,0.00021496775,0.00039036848,0.00007918143,0.0001623177],"domain_scores_gemma":[0.9855135,0.014059122,0.00005139154,0.00030698002,0.000033580945,0.000035444482],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00018084794,0.00011598086,0.00019594954,0.00009874391,0.00009915135,0.000016731257,0.000071468574,0.000059979786,0.000014346945],"category_scores_gemma":[0.008362513,0.00010613368,0.00006205864,0.0002913207,0.000040392668,0.0000828958,0.00004010775,0.00018592442,4.7656872e-7],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00175897,0.0010294091,0.348323,0.000782346,0.00011568083,0.000055167446,0.0011381124,0.0028066635,0.049335405,0.3362579,0.25079098,0.0076063704],"study_design_scores_gemma":[0.0050743343,0.0005295191,0.24656387,0.00047120193,0.00015830585,0.000049479208,0.0005232101,0.09555277,0.006454793,0.4363227,0.2076238,0.00067603466],"about_ca_topic_score_codex":0.00006742641,"about_ca_topic_score_gemma":0.000011953009,"teacher_disagreement_score":0.9265663,"about_ca_system_score_codex":0.00011820911,"about_ca_system_score_gemma":0.000025852862,"threshold_uncertainty_score":0.99999046},"labels":[],"label_agreement":null},{"id":"W4408528886","doi":"10.1002/hbm.70188","title":"White Matter Microstructure Among Straight and Gay Cisgender Men, <i>Sao Praphet Song</i>, and Straight Cisgender Women in Thailand","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; Centre for Addiction and Mental Health; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fractional anisotropy; Corpus callosum; White matter; Cingulum (brain); Psychology; Diffusion MRI; Corona radiata (embryology); Population; Generalizability theory; Superior longitudinal fasciculus; Developmental psychology; Demography; Neuroscience; Medicine; Internal medicine; Sociology; Magnetic resonance imaging; Hormone","score_opus":0.03375090106925206,"score_gpt":0.31570396658989275,"score_spread":0.2819530655206407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408528886","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9352536,0.00037389633,0.004600569,0.010496407,0.00003823359,0.0011735968,0.000030285122,0.00021678036,0.04781662],"genre_scores_gemma":[0.9846264,0.00005007876,0.002442937,0.0031698232,0.000055582244,0.000111884845,0.000033319902,0.000036073146,0.009473901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984685,0.00004048588,0.0003249182,0.00057779334,0.00012407967,0.000464222],"domain_scores_gemma":[0.9993106,0.000061359846,0.000090686226,0.0003685327,0.00003326742,0.00013554636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021230835,0.00025675606,0.00034752488,0.00029007136,0.00021897937,0.00008368356,0.00010547089,0.000119453856,0.0002835054],"category_scores_gemma":[0.00001597057,0.00023847996,0.000039209655,0.00025873334,0.0002386118,0.00013702434,0.000126225,0.0003960866,0.0000019103354],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038395963,0.00006809443,0.8444512,0.0003980893,0.00006711341,0.00004928378,0.0026373025,0.000004951942,0.09605312,0.0033974845,0.051960107,0.0008748818],"study_design_scores_gemma":[0.0011216565,0.000028141556,0.96432877,0.00015846864,0.000012547531,0.000051252522,0.00062686164,0.000055613848,0.00017195643,0.009607399,0.023602001,0.00023531567],"about_ca_topic_score_codex":0.000005051701,"about_ca_topic_score_gemma":0.00002118807,"teacher_disagreement_score":0.11987761,"about_ca_system_score_codex":0.00006744239,"about_ca_system_score_gemma":0.000030593914,"threshold_uncertainty_score":0.97249305},"labels":[],"label_agreement":null},{"id":"W4408548800","doi":"10.1080/10255842.2025.2472015","title":"Is a 3D representation of muscle architecture needed to model craniomaxillofacial skeletal mechanics?","year":2025,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Sunnybrook Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Representation (politics); Architecture; Computer science; Skeletal muscle; Medicine; Geography; Anatomy; Political science","score_opus":0.05397550222691014,"score_gpt":0.4128762470811565,"score_spread":0.3589007448542464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408548800","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0050326255,0.00004766855,0.9912427,0.0024710922,0.00030545046,0.0005956726,0.00002524038,0.00024985668,0.000029667875],"genre_scores_gemma":[0.026800798,0.00002571747,0.97151494,0.0014291458,0.000066481705,0.000083953695,0.000019394605,0.000033607335,0.000025934129],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982846,0.00004027499,0.00056147383,0.00052303093,0.00026393853,0.00032667705],"domain_scores_gemma":[0.99899894,0.00012570461,0.000073140654,0.00053642923,0.000083574596,0.00018218506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003977211,0.00023006322,0.0004888706,0.00101976,0.000034301902,0.000013468162,0.00027829755,0.0001844529,0.00000996943],"category_scores_gemma":[0.000177736,0.00023043147,0.00014855884,0.0022253778,0.000029738587,0.000041769334,0.0003207508,0.0003114989,0.0000012074203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020940308,0.00012557511,0.0000010772484,0.00014178744,0.000024703584,0.000007688123,0.00016955029,0.0027199665,0.6803644,0.0047339764,0.00023183334,0.3114585],"study_design_scores_gemma":[0.0005584818,0.00011730803,0.000021925727,0.0002335757,0.000032714943,0.000013688754,0.000012175546,0.90145254,0.078791,0.010529884,0.008071788,0.00016491639],"about_ca_topic_score_codex":0.000014521086,"about_ca_topic_score_gemma":2.9170826e-7,"teacher_disagreement_score":0.89873254,"about_ca_system_score_codex":0.00009047401,"about_ca_system_score_gemma":0.00006682194,"threshold_uncertainty_score":0.9396723},"labels":[],"label_agreement":null},{"id":"W4408560758","doi":"10.1162/imag_a_00526","title":"Microstructure-informed brain tissue classification using clustering of quantitative MRI measures","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); International Collaboration On Repair Discoveries; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada; Canadian Institutes of Health Research; Biogen; Sanofi","keywords":"White matter; Magnetic resonance imaging; Voxel; Brain tissue; Fractional anisotropy; Cluster analysis; Multiple sclerosis; Pathology; Segmentation; Medicine; Diffusion MRI; Pathological; Artificial intelligence; Computer science; Pattern recognition (psychology); Radiology; Biomedical engineering","score_opus":0.11966148007359705,"score_gpt":0.45276459835472965,"score_spread":0.3331031182811326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408560758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04587569,0.000092770846,0.94534767,0.0065627713,0.00019465492,0.00045461033,0.0000107859305,0.00017187317,0.0012891992],"genre_scores_gemma":[0.91385305,0.000027560307,0.08366948,0.002190923,0.000010549727,0.0000122758,0.000002417971,0.000012082799,0.00022168111],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900603,0.00002104998,0.00026790684,0.00033320184,0.00018043084,0.00019138896],"domain_scores_gemma":[0.99922025,0.00009672965,0.00013973597,0.00036360772,0.0001330663,0.000046615674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012283302,0.00011266214,0.0001666106,0.00020360298,0.00015232949,0.000032303302,0.00019382627,0.000019322955,0.0000017024106],"category_scores_gemma":[0.0005148268,0.00010762711,0.000037741273,0.00067015603,0.0003613661,0.0001891095,0.00008574384,0.00013938479,7.5367126e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001656827,0.000020002099,0.005170281,0.00005114807,9.3185577e-7,0.0000030791182,0.000068915164,0.00025318598,0.98665226,0.0024498964,0.00034501974,0.004968725],"study_design_scores_gemma":[0.00065185496,0.00009169767,0.13885958,0.0004623278,0.00005545124,0.00019394851,0.00018769757,0.32132587,0.49645036,0.0023850154,0.039064936,0.00027125122],"about_ca_topic_score_codex":0.000023442519,"about_ca_topic_score_gemma":0.0000018613027,"teacher_disagreement_score":0.8679773,"about_ca_system_score_codex":0.000058702997,"about_ca_system_score_gemma":0.00016080396,"threshold_uncertainty_score":0.4388906},"labels":[],"label_agreement":null},{"id":"W4408646494","doi":"10.1186/s41747-025-00570-5","title":"Connectivity related to major brain functions in Alzheimer disease progression: microstructural properties of the cingulum bundle and its subdivision using diffusion-weighted MRI","year":2025,"lang":"en","type":"article","venue":"European Radiology Experimental","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; University of Southern California; BioClinica; Bristol-Myers Squibb; Eli Lilly and Company; Biogen","keywords":"Cingulum (brain); Diffusion MRI; Neuroscience; Fractional anisotropy; Tractography; White matter; Psychology; Uncinate fasciculus; Alzheimer's disease; Dementia; Medicine; Magnetic resonance imaging; Pathology; Radiology; Disease","score_opus":0.03494078093468672,"score_gpt":0.33986643232350067,"score_spread":0.30492565138881395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408646494","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9937863,0.0027593835,0.00010610691,0.0019928012,0.00012641733,0.00092952757,0.000009763205,0.00007121863,0.0002185219],"genre_scores_gemma":[0.99859756,0.00000620334,0.0006535191,0.0004938705,0.000017820472,0.000027963208,0.000007974963,0.000019534795,0.00017553048],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900556,0.00020538099,0.00024153895,0.00032542035,0.00006595002,0.0001561641],"domain_scores_gemma":[0.999529,0.000030858082,0.00006928399,0.0002638232,0.000031701948,0.000075329604],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009713858,0.00013524941,0.00018986869,0.000099538825,0.0001924772,0.0000073621045,0.00010043313,0.000030778196,0.000013014522],"category_scores_gemma":[0.000064140884,0.000091364556,0.000047969104,0.00025340848,0.00019728992,0.0000460256,0.00026539524,0.00017271742,0.00000192497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000259898,0.00019864105,0.03305371,0.000011677827,0.00002028261,0.000011035154,0.00031495778,0.0000063726575,0.96511817,0.0004360366,0.00029697627,0.0002722526],"study_design_scores_gemma":[0.002401147,0.00030675565,0.3157353,0.00067245436,0.00010797251,0.00023208941,0.000371552,0.0033013998,0.67536336,0.00014540862,0.0011114487,0.00025109854],"about_ca_topic_score_codex":0.000007524656,"about_ca_topic_score_gemma":5.7330027e-7,"teacher_disagreement_score":0.2897548,"about_ca_system_score_codex":0.00004535454,"about_ca_system_score_gemma":0.00003440313,"threshold_uncertainty_score":0.37257385},"labels":[],"label_agreement":null},{"id":"W4408658106","doi":"10.1038/s41598-025-93033-1","title":"Gauge equivariant convolutional neural networks for diffusion MRI","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"National Institute of Mental Health; Canadian Open Neuroscience Platform; Canada Research Chairs","keywords":"Diffusion MRI; Convolutional neural network; Equivariant map; Computer science; Tensor (intrinsic definition); Angular resolution (graph drawing); Artificial intelligence; Fractional anisotropy; SIGNAL (programming language); Pattern recognition (psychology); Physics; Algorithm; Mathematics; Geometry; Magnetic resonance imaging; Pure mathematics; Combinatorics","score_opus":0.04298510535479371,"score_gpt":0.3545560619039544,"score_spread":0.31157095654916067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408658106","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049080383,0.00026916765,0.9344368,0.00646817,0.0044016554,0.0015929724,0.000009116244,0.000381372,0.0033603944],"genre_scores_gemma":[0.9700697,0.000006988932,0.014555742,0.0005549469,0.000113796275,0.00019938551,0.00023290579,0.000012551762,0.014254],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988022,0.0000075697844,0.0002996803,0.00051074714,0.00016169049,0.00021812531],"domain_scores_gemma":[0.9990034,0.000043704742,0.00011046078,0.0006054977,0.00016526581,0.00007165842],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032935906,0.000087956214,0.00013845348,0.00010365993,0.00033933765,0.00005448453,0.00006265143,0.00004285542,0.000031933683],"category_scores_gemma":[0.00010100739,0.00007572452,0.000097568416,0.0003460343,0.00016902827,0.000051696094,0.00007507384,0.000100836696,0.0000012838395],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014119814,0.0005972297,0.01895268,0.00015507625,0.00004005215,0.000304911,0.000042317795,0.0011943503,0.11239528,0.10130084,0.747122,0.017754095],"study_design_scores_gemma":[0.00052024407,0.00006111727,0.0073337737,0.00012731356,0.000091964466,0.00047832675,0.000014102031,0.18989635,0.0053754165,0.12390211,0.6720123,0.00018693731],"about_ca_topic_score_codex":0.000004396641,"about_ca_topic_score_gemma":0.0000010621582,"teacher_disagreement_score":0.9209893,"about_ca_system_score_codex":0.00004362575,"about_ca_system_score_gemma":0.000088214794,"threshold_uncertainty_score":0.30879563},"labels":[],"label_agreement":null},{"id":"W4408743981","doi":"10.1007/s10334-025-01244-4","title":"Assessing measurement consistency of a diffusion tensor imaging (DTI) quality control (QC) anisotropy phantom","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Materials in Physics Biology and Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University Medical Centre; Systems, Applications & Products in Data Processing (Canada); McMaster University; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Imaging phantom; Diffusion MRI; Fractional anisotropy; Anisotropy; Consistency (knowledge bases); Nuclear magnetic resonance; Tractography; Tensor (intrinsic definition); Physics; Medicine; Magnetic resonance imaging; Computer science; Optics; Mathematics; Radiology; Artificial intelligence","score_opus":0.07346922782753491,"score_gpt":0.4073890482619861,"score_spread":0.3339198204344512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408743981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9463599,0.01361855,0.029855674,0.0067537976,0.00031123782,0.0011454242,0.000037985297,0.00009440788,0.001823027],"genre_scores_gemma":[0.9948558,0.000987909,0.0028350332,0.0010715924,0.00010395986,0.000078058074,0.000014019923,0.000009640529,0.000043993496],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985919,0.00014602017,0.00057296257,0.0003472107,0.00012785962,0.00021405205],"domain_scores_gemma":[0.99915534,0.00015122369,0.00017502559,0.0003119936,0.00016527301,0.000041160147],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006073144,0.0001661746,0.0006500518,0.00008222885,0.00007245214,0.000007098328,0.000080822,0.00006010321,0.000027315438],"category_scores_gemma":[0.0003070171,0.00012580672,0.000028330634,0.00018512119,0.00061081036,0.000039954826,0.00005432209,0.00011303858,4.437448e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019303845,0.00013033858,0.06672384,0.00017854734,0.000005686946,0.0000050608583,0.000043248103,1.337508e-7,0.8263199,0.020307831,0.00007818296,0.08601424],"study_design_scores_gemma":[0.008217186,0.00051014655,0.8150444,0.0024294262,0.00018715918,0.000024284893,0.00020951615,0.00025433942,0.08830064,0.07860404,0.0059700133,0.00024886458],"about_ca_topic_score_codex":0.0001580578,"about_ca_topic_score_gemma":0.0000027361302,"teacher_disagreement_score":0.7483205,"about_ca_system_score_codex":0.00003680976,"about_ca_system_score_gemma":0.000064289015,"threshold_uncertainty_score":0.5130249},"labels":[],"label_agreement":null},{"id":"W4408819125","doi":"10.1371/journal.pone.0304449","title":"A Riemannian framework for incorporating white matter bundle prior in orientation distribution function based tractography algorithms","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Computer science; Diffusion MRI; Bundle; Prior probability; Artificial intelligence; Connectome; Algorithm; Orientation (vector space); Fiber bundle; Context (archaeology); Parallelizable manifold; Voxel; Computer vision; Magnetic resonance imaging; Mathematics; Bayesian probability; Functional connectivity; Geometry; Biology; Neuroscience","score_opus":0.059503971055531006,"score_gpt":0.3293319319535799,"score_spread":0.2698279608980489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408819125","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13787128,0.000016436501,0.85570484,0.0049335565,0.00002330701,0.0011241896,0.00004897736,0.00014364129,0.00013379438],"genre_scores_gemma":[0.68868136,0.0000029263942,0.30894846,0.0010609321,0.00004735041,0.00069866015,0.00044929053,0.0000138669,0.000097179596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992369,0.000014954026,0.00023419852,0.00025589237,0.000121541205,0.00013651059],"domain_scores_gemma":[0.9994477,0.000085997446,0.0000988195,0.0002207903,0.00011110621,0.000035607623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000990276,0.00009581407,0.0001648216,0.00013679854,0.00009474391,0.000019459394,0.000040972976,0.000074342126,0.00001697917],"category_scores_gemma":[0.00008843028,0.00009992606,0.00005105532,0.0005970176,0.000031331376,0.000086827284,0.000011452559,0.00019336847,0.000004163915],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006553455,0.0062085134,0.9518569,0.0009131213,0.00009045917,0.00000261964,0.00010957388,0.000055290762,0.016947953,0.014033866,0.0010316726,0.008094672],"study_design_scores_gemma":[0.0028336695,0.00074346614,0.83066684,0.0024340006,0.000565449,0.0000015646191,0.00012778897,0.031584665,0.037796833,0.09145765,0.0014229538,0.000365134],"about_ca_topic_score_codex":0.0000058168594,"about_ca_topic_score_gemma":0.0000028646482,"teacher_disagreement_score":0.55081004,"about_ca_system_score_codex":0.00007015607,"about_ca_system_score_gemma":0.000034008517,"threshold_uncertainty_score":0.40748665},"labels":[],"label_agreement":null},{"id":"W4409028149","doi":"10.1101/2025.03.26.645559","title":"Standardization of postmortem human brainstem along the rostrocaudal axis to accommodate for heterogeneity in samples","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"","keywords":"Brainstem; Standardization; Biology; Pathology; Neuroscience; Medicine; Computer science","score_opus":0.06053224548258985,"score_gpt":0.33899775684001415,"score_spread":0.2784655113574243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409028149","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80477214,0.00015878178,0.18828382,0.0016681155,0.00011580904,0.0031739636,0.0015647314,0.0002569107,0.0000057374377],"genre_scores_gemma":[0.9590936,0.000040109968,0.039404444,0.0004898205,0.00010413918,0.0008033418,0.0000035438547,0.000057477006,0.0000035819105],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9980588,0.00006297641,0.0006445984,0.00068349415,0.0002380194,0.0003120966],"domain_scores_gemma":[0.9976036,0.000106538806,0.00031947423,0.0013821867,0.00047579603,0.00011238854],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00049075333,0.00032152323,0.0005720027,0.00025519903,0.00014898035,0.00004507743,0.00042160065,0.00019622303,0.0000029640578],"category_scores_gemma":[0.00022605364,0.00029236518,0.00016361939,0.00049718295,0.00008068194,0.000042649972,0.00042485612,0.0004005332,7.7785484e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021277269,0.0003193486,0.071312904,0.0015718555,0.00015276694,0.000009640605,0.000027514716,0.0014419908,0.9175207,0.006679757,0.000702059,0.000048657366],"study_design_scores_gemma":[0.00080169225,0.00014275576,0.29925978,0.0012276528,0.0001548727,3.3740644e-8,0.0000044374074,0.000426485,0.6852463,0.000030849642,0.01231255,0.00039258986],"about_ca_topic_score_codex":0.00007671798,"about_ca_topic_score_gemma":0.00003557736,"teacher_disagreement_score":0.23227444,"about_ca_system_score_codex":0.00022227982,"about_ca_system_score_gemma":0.00033902033,"threshold_uncertainty_score":0.99995285},"labels":[],"label_agreement":null},{"id":"W4409210508","doi":"10.1016/j.ejrad.2025.112098","title":"Diffusion MRI tractography with along-tract profiling reveals subtle neurodevelopmental differences between moderate and late preterm infants","year":2025,"lang":"en","type":"article","venue":"European Journal of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"Calgary Health Foundation; Alberta Children's Hospital Research Institute; Alberta Children's Hospital Foundation; Koninklijke Nederlandse Akademie van Wetenschappen; Wellcome Trust","keywords":"Medicine; Diffusion MRI; Tractography; Profiling (computer programming); Magnetic resonance imaging; Radiology","score_opus":0.0346405438625101,"score_gpt":0.30299424609960107,"score_spread":0.268353702237091,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409210508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98001313,0.0002133913,0.01778368,0.0008663382,0.000041940923,0.00020832113,0.0000055377586,0.000037579874,0.0008300568],"genre_scores_gemma":[0.97896534,0.00053794903,0.020055797,0.00029065978,0.000060809303,0.000002060318,0.0000056748204,0.000018556086,0.000063179585],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989675,0.00017768641,0.00040369478,0.00019869053,0.00008789508,0.00016449305],"domain_scores_gemma":[0.9993144,0.00010819029,0.0002723002,0.00014127133,0.00006879816,0.000094992654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028209976,0.00013919792,0.0003519842,0.00019687312,0.00009494814,0.000018281062,0.00012147457,0.000024590887,0.0000029766848],"category_scores_gemma":[0.000036870868,0.000095614436,0.000049418923,0.00014691408,0.00011463094,0.00008493194,0.00004439156,0.00037916697,6.2087605e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030301537,0.00005461694,0.9736195,0.00003345551,0.00005563395,0.00023925805,0.00011240142,0.000006704906,0.01873358,0.00007571636,0.000112361835,0.0066537187],"study_design_scores_gemma":[0.0009006633,0.000575813,0.99445057,0.00022314063,0.00008199989,0.0011726944,0.000014366217,0.000070399874,0.0017174798,0.00034747864,0.00035440072,0.000091023656],"about_ca_topic_score_codex":6.1415784e-7,"about_ca_topic_score_gemma":1.3461904e-7,"teacher_disagreement_score":0.020831004,"about_ca_system_score_codex":0.000011346316,"about_ca_system_score_gemma":0.000037030222,"threshold_uncertainty_score":0.38990435},"labels":[],"label_agreement":null},{"id":"W4409238054","doi":"10.1002/oby.24277","title":"Sex‐specific white matter alterations in children exposed to high pregestational <scp>BMI</scp>","year":2025,"lang":"en","type":"article","venue":"Obesity","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Calgary","funders":"Alberta Children's Hospital Research Institute; Jacobs Foundation","keywords":"Splenium; Fractional anisotropy; Corpus callosum; Medicine; Overweight; White matter; Offspring; Body mass index; Pregnancy; Pediatrics; Endocrinology; Magnetic resonance imaging; Pathology; Biology","score_opus":0.02134412088106482,"score_gpt":0.2974359276915425,"score_spread":0.2760918068104777,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409238054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93964595,0.000024789148,0.049466714,0.0044285115,0.000030991298,0.0007799579,0.000043653556,0.00014134905,0.0054380754],"genre_scores_gemma":[0.9556274,0.000015902078,0.03055393,0.0028086472,0.000058532787,0.00017938955,0.00014486474,0.000014331578,0.010597022],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99920964,0.000021803231,0.00018630268,0.00030561778,0.00011146589,0.0001651914],"domain_scores_gemma":[0.9994298,0.00006360141,0.00003065678,0.00035604334,0.00005276936,0.000067109475],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000061013332,0.000105811385,0.00014879678,0.00015887128,0.000094445684,0.000024199813,0.000099739664,0.000040154173,0.00006463112],"category_scores_gemma":[0.000027450662,0.000108888955,0.00003432334,0.0003567495,0.000028208538,0.000067585854,0.000058863596,0.00016205118,0.00011811056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000046782575,0.00021870046,0.94258446,0.000010287535,0.000007525711,0.0000027198078,0.00009730985,0.0000841031,0.0034714453,0.0060618026,0.04697255,0.0004844174],"study_design_scores_gemma":[0.000342313,0.00002282436,0.97811764,0.00004717364,0.000010246499,0.00000943555,0.000014201993,0.00004406234,0.008769667,0.003176224,0.0094065005,0.000039684095],"about_ca_topic_score_codex":0.0000138335035,"about_ca_topic_score_gemma":0.000005992915,"teacher_disagreement_score":0.037566047,"about_ca_system_score_codex":0.00006780349,"about_ca_system_score_gemma":0.00003749799,"threshold_uncertainty_score":0.44403628},"labels":[],"label_agreement":null},{"id":"W4409248602","doi":"10.1101/2025.04.07.25325401","title":"Diffusion MRI-based measures of neurite microstructure associate with future risk of Alzheimer’s Disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Alzheimer's disease; Diffusion MRI; Disease; Diffusion; Neurite; Medicine; Neuroscience; Psychology; Magnetic resonance imaging; Internal medicine; Chemistry; Radiology; Physics","score_opus":0.04320602276908402,"score_gpt":0.31993010434402014,"score_spread":0.2767240815749361,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409248602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9666538,0.0040135593,0.018450981,0.0053255293,0.00025441145,0.002166451,0.002523226,0.00033571204,0.00027632093],"genre_scores_gemma":[0.9807854,0.0010519779,0.017156446,0.0003390276,0.00014377134,0.000112496564,0.00023444717,0.0000495116,0.00012689977],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983128,0.000095240306,0.0004352882,0.0005412932,0.00040509482,0.00021031109],"domain_scores_gemma":[0.9975578,0.00006505828,0.00072020903,0.001159486,0.00035311753,0.00014429046],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016503327,0.00032642393,0.0006803376,0.00018110684,0.0000724687,0.0000075804664,0.00026832335,0.00019711885,0.000012945412],"category_scores_gemma":[0.000099259436,0.00024708666,0.00027653706,0.0002515104,0.00016591483,0.000017058526,0.00024667897,0.0008407915,3.9527e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010479449,0.0005718193,0.96352464,0.0016840571,0.00042958368,0.00004762253,0.00013187827,0.0012091991,0.022608513,0.0002631826,0.0016870536,0.0067945304],"study_design_scores_gemma":[0.0014923244,0.00014917832,0.91892743,0.0019623935,0.0033220432,0.0000039325264,0.000016621747,0.0012363949,0.06066321,0.0026365805,0.0091923,0.00039757483],"about_ca_topic_score_codex":0.000044503708,"about_ca_topic_score_gemma":0.0000073178526,"teacher_disagreement_score":0.044597168,"about_ca_system_score_codex":0.000028343336,"about_ca_system_score_gemma":0.0003009744,"threshold_uncertainty_score":0.99999815},"labels":[],"label_agreement":null},{"id":"W4409255900","doi":"10.1162/imag_a_00552","title":"Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Institutes of Health; Genentech; National Institute of Neurological Disorders and Stroke; IXICO; Servier; Georgia Clinical and Translational Science Alliance; Eisai; H. Lundbeck A/S; National Institute of Mental Health and Neurosciences; Pfizer; Biogen; BioClinica; Vanderbilt University; University of Southern California; National Institute of Dental and Craniofacial Research; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Alzheimer's Association","keywords":"Diffusion MRI; Magnetic resonance imaging; Neuroimaging; Brain aging; Disease; Psychology; Neuroscience; Cognition; Medicine; Pathology; Radiology","score_opus":0.03237756794422935,"score_gpt":0.3517147861451662,"score_spread":0.31933721820093686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409255900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16002892,0.0000999798,0.7817076,0.054821655,0.00050210964,0.0007567396,0.00009035234,0.0007378315,0.0012548099],"genre_scores_gemma":[0.978085,0.000058792644,0.0037894147,0.015652793,0.000060574897,0.000087414686,0.000041143223,0.000019174238,0.002205723],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99835026,0.000050737504,0.0002746812,0.0007857758,0.00029006923,0.00024845952],"domain_scores_gemma":[0.9987735,0.00014492527,0.00008324936,0.0007168555,0.00008645457,0.00019498222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009720432,0.00016075799,0.00015283827,0.00014072488,0.00028936623,0.00012004243,0.00029735194,0.000017513443,0.000006609678],"category_scores_gemma":[0.0010312286,0.00015170149,0.00005974427,0.0005737524,0.00038386052,0.0001920514,0.00017794032,0.00021213398,0.000008946223],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041829542,0.00021426054,0.019099226,0.000021455875,0.0000012570779,0.00018897341,0.00003026429,0.00011796756,0.95905703,0.006878268,0.009264544,0.0050849225],"study_design_scores_gemma":[0.00050688896,0.000030379213,0.7964644,0.00016507927,0.00007606469,0.0000129763175,0.000008396921,0.12401601,0.025028633,0.011423545,0.042044807,0.00022282854],"about_ca_topic_score_codex":0.000016944081,"about_ca_topic_score_gemma":7.7798893e-7,"teacher_disagreement_score":0.9340284,"about_ca_system_score_codex":0.00004173977,"about_ca_system_score_gemma":0.000106614396,"threshold_uncertainty_score":0.61862075},"labels":[],"label_agreement":null},{"id":"W4409353465","doi":"10.21037/qims-24-1440","title":"Brain white matter microstructural alterations in patients with diabetic retinopathy: an automated fiber-tract quantification study","year":2025,"lang":"en","type":"article","venue":"Quantitative Imaging in Medicine and Surgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Diabetic retinopathy; White matter; Medicine; Pathology; Fiber tract; Computer science; Diabetes mellitus; Magnetic resonance imaging; Radiology; Endocrinology","score_opus":0.04005825587990369,"score_gpt":0.3780055563282895,"score_spread":0.33794730044838583,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409353465","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9867636,0.00008771866,0.0010117838,0.010891484,0.000046769102,0.0008804785,0.0000073512047,0.00014855401,0.00016225767],"genre_scores_gemma":[0.99457055,0.0000075003327,0.0030733952,0.0019213749,0.000011734479,0.00009709889,0.00018148164,0.000021940898,0.00011494192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984853,0.00017138621,0.00050148676,0.00045072174,0.00016392978,0.00022712257],"domain_scores_gemma":[0.9988262,0.00051398185,0.00012429118,0.000317033,0.00015942536,0.00005903319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046483384,0.00018915476,0.0004166501,0.0006755958,0.000092518014,0.000029139524,0.000059060156,0.000026861471,0.000029582838],"category_scores_gemma":[0.0002546892,0.00014960054,0.000021021067,0.00072306563,0.00020793329,0.00025281758,0.000020314237,0.00023271913,0.0000036920287],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012619371,0.00037424223,0.99443966,0.000045178058,0.000006375948,0.000020711434,0.0010070502,0.000011182522,0.0005204521,0.000098167744,0.0021380635,0.0012127194],"study_design_scores_gemma":[0.0012364519,0.0001733807,0.99392956,0.00054063404,0.00003294601,0.0000057078405,0.00096457487,0.0025758373,0.000056235167,0.00019008968,0.00015673107,0.00013784187],"about_ca_topic_score_codex":0.00011584583,"about_ca_topic_score_gemma":0.00002201644,"teacher_disagreement_score":0.008970109,"about_ca_system_score_codex":0.00004927489,"about_ca_system_score_gemma":0.000054121545,"threshold_uncertainty_score":0.6100533},"labels":[],"label_agreement":null},{"id":"W4409428638","doi":"10.52294/001c.133510","title":"Longitudinal deformation-based morphometry pipeline to study neuroanatomical differences in structural MRI based on SyN unbiased templates","year":2025,"lang":"en","type":"article","venue":"Aperture Neuro","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Krembil Foundation; Douglas Mental Health University Institute; University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Alliance de recherche numérique du Canada; University of Toronto; Innovation, Science and Economic Development Canada","keywords":"Template; Pipeline (software); Deformation (meteorology); Anatomy; Computer science; Geology; Artificial intelligence; Biology","score_opus":0.039477860949327315,"score_gpt":0.3423003763430829,"score_spread":0.3028225153937556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409428638","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9257267,0.00001633149,0.026691644,0.045387432,0.0001052734,0.0015134251,0.000028773113,0.00030828232,0.00022213109],"genre_scores_gemma":[0.9444836,0.0000019891909,0.0028131118,0.052424666,0.000029968653,0.00014217121,0.00003885104,0.00002386791,0.00004177703],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984359,0.00007269727,0.00038502133,0.000545738,0.0002885335,0.00027210586],"domain_scores_gemma":[0.9966236,0.0025374882,0.00006584548,0.00057076145,0.00007469955,0.00012761627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008208186,0.00026875196,0.0003731981,0.00052684714,0.00011939149,0.000036010988,0.00023583791,0.0000657956,0.00003945259],"category_scores_gemma":[0.0016401666,0.00020965794,0.000079766265,0.001125189,0.000047645135,0.000054612574,0.000050212977,0.0004782637,0.000010070836],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011525494,0.0015542645,0.97562087,0.00010379305,0.000021248168,0.00028958247,0.00006106794,0.0024606942,0.003904025,0.0005129291,0.009999245,0.0043197325],"study_design_scores_gemma":[0.0024094745,0.0007328351,0.7416513,0.00011934916,0.000064166525,0.000014856421,0.000032595002,0.24808636,0.0029637087,0.00020004944,0.0034659633,0.00025935232],"about_ca_topic_score_codex":0.000030939023,"about_ca_topic_score_gemma":0.000012264592,"teacher_disagreement_score":0.24562567,"about_ca_system_score_codex":0.00006118966,"about_ca_system_score_gemma":0.00007006191,"threshold_uncertainty_score":0.8549603},"labels":[],"label_agreement":null},{"id":"W4409451448","doi":"10.1162/imag_a_00559","title":"Body size and intracranial volume interact with the structure of the central nervous system: A multi-center in vivo neuroimaging study","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); McGill University; Mila - Quebec Artificial Intelligence Institute; CARE Canada; Montreal Neurological Institute and Hospital; International Collaboration On Repair Discoveries; University of British Columbia; Centre Hospitalier Universitaire Sainte-Justine; Université de Sherbrooke; Université de Montréal; Polytechnique Montréal","funders":"Institut TransMedTech; H2020 European Research Council; National Institute of Neurological Disorders and Stroke; Instituto de Salud Carlos III; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; HORIZON EUROPE Framework Programme; Agència de Gestió d'Ajuts Universitaris i de Recerca; Institut de Valorisation des Données; Agentura Pro Zdravotnický Výzkum České Republiky; University College London Hospitals NHS Foundation Trust; Center for Neurobehavioral Development; European Commission; Ministerstvo Zdravotnictví Ceské Republiky; National Natural Science Foundation of China; National Institutes of Health; International Collaboration on Repair Discoveries; Rosetrees Trust; Ministerstvo Školství, Mládeže a Tělovýchovy; Craig H. Neilsen Foundation; Ataxia UK; National Imaging Facility; Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona; National Institute for Health and Care Research; H2020 Marie Skłodowska-Curie Actions; Courtois Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research; Canada Foundation for Innovation; SpinalCure Australia; University of Pennsylvania; Wings for Life; Canada First Research Excellence Fund; Max-Planck-Gesellschaft; Bristol-Myers Squibb; “la Caixa” Foundation; Deutsche Forschungsgemeinschaft; University of Queensland; American Heart Association; Réseau en Bio-Imagerie du Quebec; University of Minnesota","keywords":"Neuroimaging; Central nervous system; Brain size; Neuroscience; Center (category theory); In vivo; Medicine; Psychology; Biology; Magnetic resonance imaging; Chemistry; Radiology","score_opus":0.013895481833627606,"score_gpt":0.3068382174446539,"score_spread":0.2929427356110263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409451448","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98788095,0.000021123797,0.004474951,0.006184528,0.00019678837,0.001074755,0.0000150442675,0.000086882326,0.00006500271],"genre_scores_gemma":[0.9974342,0.00000325353,0.0006842246,0.0017185842,0.000017402996,0.000014621829,1.5252122e-7,0.000015171116,0.00011236801],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987254,0.00008550204,0.00023524876,0.0004511458,0.00021851115,0.00028416462],"domain_scores_gemma":[0.999157,0.0000890252,0.00011657215,0.00053640746,0.000055582714,0.000045412184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009211383,0.00016262992,0.00019680726,0.000075977914,0.00019381674,0.00007214749,0.00038741675,0.000011286052,0.000001411078],"category_scores_gemma":[0.00015625318,0.0000909295,0.00003489362,0.00065343006,0.00042547626,0.00014842635,0.00023967458,0.00038087837,9.6155375e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005076315,0.00026009599,0.7529145,0.000052780422,0.0000020499429,0.00006137861,0.0003243428,0.00004509531,0.24523957,0.000067932466,0.00012435888,0.00085716136],"study_design_scores_gemma":[0.0011919355,0.00006041413,0.96844405,0.00020082387,0.000038360886,0.00037383958,0.00035460756,0.025759129,0.0028122196,0.000015769685,0.0006613908,0.000087442546],"about_ca_topic_score_codex":0.00010827647,"about_ca_topic_score_gemma":0.000018169007,"teacher_disagreement_score":0.24242735,"about_ca_system_score_codex":0.00004159469,"about_ca_system_score_gemma":0.00006561748,"threshold_uncertainty_score":0.37079972},"labels":[],"label_agreement":null},{"id":"W4409487638","doi":"10.1162/imag_a_00567","title":"Delineation of the trigeminal-lateral parabrachial-central amygdala tract in humans","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Sinai Hospital; Krembil Foundation; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; University of Toronto; Canada Research Chairs","keywords":"Parabrachial Nucleus; Neuroscience; Amygdala; Lateral parabrachial nucleus; Medicine; Anatomy; Biology; Central nervous system","score_opus":0.039538107805077556,"score_gpt":0.37162943088871747,"score_spread":0.3320913230836399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409487638","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9484726,0.000047317582,0.04080743,0.008915416,0.00022545867,0.00045396472,0.000005362908,0.00008740969,0.0009850445],"genre_scores_gemma":[0.9963603,0.000022631526,0.0010243077,0.0020161688,0.000014872846,0.000018251032,0.0000010598939,0.000006110185,0.00053630385],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991327,0.000026242164,0.00023717959,0.00026177365,0.00014658025,0.00019553374],"domain_scores_gemma":[0.9994873,0.000035753914,0.000076266144,0.00033570785,0.000036423666,0.000028553242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010468102,0.00008135413,0.00011703699,0.00010819446,0.0000902632,0.000016766453,0.00021391467,0.000013054819,0.0000021832873],"category_scores_gemma":[0.00017143403,0.00006104325,0.000054124506,0.00064726226,0.00021187162,0.00011166071,0.00005574896,0.0001917701,4.2947062e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016626549,0.00020655186,0.7959876,0.00002516246,3.512304e-7,0.000009181843,0.00007153079,0.00019649579,0.19278908,0.0023288506,0.00028848712,0.008080089],"study_design_scores_gemma":[0.0003122264,0.000016170463,0.95482486,0.000108911554,0.000012491898,0.00002176981,0.0000077160985,0.015504629,0.02254249,0.00086784683,0.005725259,0.00005561884],"about_ca_topic_score_codex":0.000029961635,"about_ca_topic_score_gemma":0.0000021057601,"teacher_disagreement_score":0.1702466,"about_ca_system_score_codex":0.000034401266,"about_ca_system_score_gemma":0.000079458165,"threshold_uncertainty_score":0.24892715},"labels":[],"label_agreement":null},{"id":"W4409489633","doi":"10.1142/s0219887825502007","title":"Heisenberg spin chain models and Bäcklund transformations of isotropic curves in ℂ3","year":2025,"lang":"en","type":"article","venue":"International Journal of Geometric Methods in Modern Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Research Foundation of Korea","keywords":"Isotropy; Spin (aerodynamics); Physics; Chain (unit); Mathematical physics; Heisenberg model; Quantum mechanics; Ferromagnetism; Thermodynamics","score_opus":0.1111423339458594,"score_gpt":0.4857761111357464,"score_spread":0.374633777189887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409489633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046846524,0.0021438622,0.9481848,0.0016847735,0.00007247526,0.0001781957,0.000009088481,0.00000788737,0.0008724242],"genre_scores_gemma":[0.59499186,0.00461995,0.39994586,0.00032551467,0.000036865422,0.000009945276,0.000003319166,0.000008061166,0.00005863122],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987622,0.000076706114,0.00066518434,0.00011856648,0.0002756867,0.00010163702],"domain_scores_gemma":[0.99891734,0.0003331362,0.00026378577,0.00013237984,0.00031610316,0.000037225705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005555123,0.00009606151,0.0003386882,0.0011518174,0.000013373466,0.000008773475,0.00020294586,0.000039533195,0.0000031741667],"category_scores_gemma":[0.00026251172,0.000090031404,0.00009043158,0.0011035394,0.00005732281,0.00023337906,0.000045060366,0.00031554225,8.6461725e-8],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017023868,0.00088353,0.00948587,0.00035636936,0.00016231423,0.000024969397,0.0004565753,0.020310735,0.013248807,0.034041338,0.00017125235,0.920688],"study_design_scores_gemma":[0.002686941,0.00014228598,0.023317972,0.0019234793,0.00009357163,0.00009067173,0.000114724426,0.23422542,0.016510798,0.72009313,0.0006324775,0.00016849331],"about_ca_topic_score_codex":0.000018149432,"about_ca_topic_score_gemma":0.0000013091961,"teacher_disagreement_score":0.92051953,"about_ca_system_score_codex":0.00009542802,"about_ca_system_score_gemma":0.00009698929,"threshold_uncertainty_score":0.3671374},"labels":[],"label_agreement":null},{"id":"W4409665004","doi":"10.7554/elife.96625.2","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Thalamus; Cerebellum; Neuroscience; Diffusion; Biology; Physics","score_opus":0.04797523747320988,"score_gpt":0.3343625564876865,"score_spread":0.2863873190144766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409665004","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948393,0.00045032098,0.0020221046,0.001181847,0.00010112987,0.00066190545,0.000024545636,0.000039319428,0.0006795281],"genre_scores_gemma":[0.99266094,0.00036953232,0.006422481,0.00014335138,0.000028387884,0.000090742404,0.00004829655,0.000009616499,0.00022668137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990331,0.00003512629,0.0003576471,0.00025215853,0.00022088684,0.00010105972],"domain_scores_gemma":[0.999278,0.00016626233,0.00015460611,0.000316188,0.000058843532,0.00002610515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013741858,0.00014816753,0.00031097003,0.000082314495,0.000035828616,0.000005288517,0.00015918817,0.00007251552,0.000006045927],"category_scores_gemma":[0.000083325125,0.000104849176,0.00005114933,0.00011644232,0.0001237344,0.000011662301,0.0002265246,0.00036034477,1.3237229e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062249374,0.0022401204,0.7997535,0.0060643214,0.00012817871,0.00005495211,0.013120048,0.00015221564,0.027977355,0.008268173,0.003626079,0.13799259],"study_design_scores_gemma":[0.0006759743,0.00008949261,0.9171463,0.0009347276,0.000082856386,0.000015705118,0.00020862822,0.00025140267,0.05610111,0.0017080653,0.022586577,0.00019915387],"about_ca_topic_score_codex":0.00004164533,"about_ca_topic_score_gemma":0.000017500106,"teacher_disagreement_score":0.13779344,"about_ca_system_score_codex":0.000018507808,"about_ca_system_score_gemma":0.00013962336,"threshold_uncertainty_score":0.42756253},"labels":[],"label_agreement":null},{"id":"W4409709964","doi":"10.21203/rs.3.rs-6480729/v1","title":"Brain Dissection Photogrammetry for Studying Human White Matter Connections: a Unique Resource for Integrating Ex-vivo and In-vivo Multimodal Datasets","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Centre National de la Recherche Scientifique; Université de Sherbrooke","keywords":"Ex vivo; Photogrammetry; White matter; Computer science; Resource (disambiguation); Dissection (medical); In vivo; Artificial intelligence; Computer vision; Neuroscience; Biology; Medicine; Anatomy; Magnetic resonance imaging; Radiology","score_opus":0.13324129880321525,"score_gpt":0.4874112130988974,"score_spread":0.3541699142956821,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409709964","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27985933,0.00059027993,0.6352975,0.023210706,0.00017614536,0.04393393,0.013226133,0.0009535947,0.0027523995],"genre_scores_gemma":[0.9105469,0.00010530329,0.06313676,0.00076005625,0.00034007564,0.018067399,0.003700851,0.0001446221,0.0031980376],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99752635,0.00020364726,0.00046903212,0.0009848303,0.00028958748,0.0005265586],"domain_scores_gemma":[0.9971442,0.001420508,0.0001243238,0.0008283104,0.0003466243,0.00013599763],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0013936136,0.00028243667,0.000451657,0.00088720885,0.0005255069,0.00013580905,0.00024064042,0.00025533646,0.000027496088],"category_scores_gemma":[0.0009941427,0.00027899846,0.00013475749,0.00050567434,0.00014846592,0.000073042924,0.00064834824,0.0014769137,6.207516e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0041586873,0.004245963,0.3569315,0.047678184,0.00055193645,0.00010276594,0.005687026,0.0006503752,0.0977221,0.008860952,0.43015534,0.043255176],"study_design_scores_gemma":[0.017206505,0.0043388666,0.062068142,0.043176312,0.00054410537,0.000245825,0.026284073,0.107231244,0.060624763,0.064852886,0.6098893,0.003537973],"about_ca_topic_score_codex":0.00054254854,"about_ca_topic_score_gemma":0.00056727463,"teacher_disagreement_score":0.6306876,"about_ca_system_score_codex":0.00028672768,"about_ca_system_score_gemma":0.00013902261,"threshold_uncertainty_score":0.9999662},"labels":[],"label_agreement":null},{"id":"W4409727375","doi":"10.1101/2025.04.14.648733","title":"White matter geometry confounds Diffusion Tensor Imaging Along Perivascular Space (DTI-ALPS) measures","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Wellcome Trust","keywords":"Diffusion MRI; White matter; Perivascular space; Geometry; Space (punctuation); Physics; Geology; Magnetic resonance imaging; Mathematics; Medicine; Computer science; Anatomy; Radiology","score_opus":0.023398528204105946,"score_gpt":0.2737017571994477,"score_spread":0.2503032289953418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409727375","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85241765,0.003969255,0.12257583,0.011735781,0.0012191503,0.00394051,0.00048389987,0.003282415,0.00037549582],"genre_scores_gemma":[0.9546808,0.00064191944,0.04089269,0.0024101604,0.0004486821,0.000502,0.0000023940202,0.00020927987,0.00021206029],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996194,0.000100922596,0.00070918427,0.0015987412,0.0006538099,0.0007433082],"domain_scores_gemma":[0.995566,0.00007136341,0.00040928178,0.0027876028,0.0007967239,0.0003689899],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000449082,0.00082376215,0.0009876234,0.00068058545,0.0003160786,0.00022845161,0.0006147296,0.0004068002,0.00013518767],"category_scores_gemma":[0.0002140932,0.00084531045,0.00041389378,0.0008078158,0.00024424936,0.00014869384,0.0009707902,0.0014943223,0.00009903943],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054200344,0.00030585934,0.7983032,0.00106053,0.00019839201,0.00017331849,0.0000125560355,0.000040386567,0.19452015,0.0006516368,0.004664031,0.000015742065],"study_design_scores_gemma":[0.0010324735,0.000033945507,0.8770542,0.0019268874,0.00065261946,5.878796e-7,0.000007483582,0.0011323425,0.05393029,0.000014456515,0.06303254,0.0011821878],"about_ca_topic_score_codex":0.00007018864,"about_ca_topic_score_gemma":7.6829406e-7,"teacher_disagreement_score":0.14058985,"about_ca_system_score_codex":0.00039004884,"about_ca_system_score_gemma":0.0004674598,"threshold_uncertainty_score":0.9993998},"labels":[],"label_agreement":null},{"id":"W4409890982","doi":"10.1007/s00429-025-02922-8","title":"Small brains but big challenges: white matter tractography in early life samples","year":2025,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; University of Alberta","funders":"CHIST-ERA; Agence Nationale de la Recherche; Royal Children's Hospital Foundation","keywords":"White matter; Tractography; White (mutation); Psychology; Biology; Medicine; Magnetic resonance imaging; Radiology","score_opus":0.06383955807671973,"score_gpt":0.28865875241622196,"score_spread":0.22481919433950223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409890982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93007576,0.0010404594,0.038438994,0.026582489,0.00014202014,0.00050837744,0.000028216422,0.00018186076,0.0030018059],"genre_scores_gemma":[0.9889328,0.0002187592,0.0025019378,0.007687168,0.00012403271,0.000034470577,0.00002906073,0.000015118818,0.00045664216],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993104,0.000019985537,0.00016472876,0.0002984711,0.000061459694,0.0001449528],"domain_scores_gemma":[0.9995802,0.00006418173,0.000041548898,0.00022602321,0.000028902348,0.000059133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004891823,0.00012667132,0.00016905175,0.00024806432,0.000059722664,0.000018504958,0.00004062658,0.00009911884,0.00002536667],"category_scores_gemma":[0.00003371898,0.00011044601,0.000045934,0.00026061057,0.00005171568,0.000045918245,0.000022599763,0.00022796333,0.0000016344069],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038195756,0.00011052933,0.7681663,0.00033655818,0.000069722926,0.000008863961,0.00061541813,0.000010772787,0.018215582,0.011127323,0.006572591,0.1943844],"study_design_scores_gemma":[0.00052219606,0.00006881671,0.949515,0.00006240161,0.000030307914,0.000012131474,0.00010304878,0.000016112697,0.00018863326,0.011335155,0.038056087,0.000090119094],"about_ca_topic_score_codex":0.000032079533,"about_ca_topic_score_gemma":0.00004767392,"teacher_disagreement_score":0.19429427,"about_ca_system_score_codex":0.000011171436,"about_ca_system_score_gemma":0.00002270973,"threshold_uncertainty_score":0.45038578},"labels":[],"label_agreement":null},{"id":"W4409905333","doi":"10.1007/s00429-025-02924-6","title":"Due to difference in anatomical definitions, population variability and tractography methods, it will not be possible to standardize brain tractography for users, or will it?","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Institutes of Health; Wellcome Leap; Canada Research Chairs; Hope for Depression Research Foundation","keywords":"Tractography; Population; Psychology; Diffusion MRI; Medicine; Radiology; Magnetic resonance imaging","score_opus":0.09689947693585951,"score_gpt":0.4222279968961041,"score_spread":0.3253285199602446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409905333","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026193704,0.10377311,0.84744775,0.027802259,0.00040199963,0.012397918,0.0050656525,0.0003893383,0.00010259793],"genre_scores_gemma":[0.0062459907,0.5531978,0.41356763,0.020784354,0.00038248507,0.0022528667,0.0031897458,0.0001674182,0.00021169333],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99749595,0.00027079842,0.00072089926,0.0009981119,0.00020114802,0.00031308096],"domain_scores_gemma":[0.99681437,0.0021415192,0.00020222415,0.00049345504,0.0001109096,0.0002375174],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00059261743,0.00047759086,0.0013466148,0.00085545087,0.00018995977,0.000074337106,0.00010863092,0.000430613,0.000022445653],"category_scores_gemma":[0.001272964,0.00037651425,0.00026573092,0.0014166604,0.00006927587,0.00016226248,0.000065153,0.0005369173,9.7817896e-8],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005534173,0.00007242234,0.00042959463,0.004661611,0.000071202194,0.000003325694,0.000077334706,0.000001766456,0.00015735521,0.0046131844,0.0039103166,0.9854485],"study_design_scores_gemma":[0.000784572,0.00047195525,0.016172985,0.0032258285,0.00072630716,0.00009335881,0.00003608745,0.000021204833,0.000020319787,0.016734477,0.9612263,0.00048660932],"about_ca_topic_score_codex":0.00003619668,"about_ca_topic_score_gemma":0.00007330695,"teacher_disagreement_score":0.98496187,"about_ca_system_score_codex":0.00008889407,"about_ca_system_score_gemma":0.00013994877,"threshold_uncertainty_score":0.9998687},"labels":[],"label_agreement":null},{"id":"W4409905343","doi":"10.1007/s00429-025-02921-9","title":"The scientific value of tractography: accuracy vs usefulness","year":2025,"lang":"en","type":"article","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Institutes of Health; Université de Bordeaux; Agence Nationale de la Recherche; European Commission; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Hope for Depression Research Foundation","keywords":"Tractography; Value (mathematics); Psychology; Computer science; Medical physics; Medicine; Diffusion MRI; Radiology; Machine learning; Magnetic resonance imaging","score_opus":0.025902433290218938,"score_gpt":0.31960660354039766,"score_spread":0.2937041702501787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409905343","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95067376,0.0003498917,0.039891403,0.007619162,0.00033450863,0.00041417894,0.000014170554,0.000092646886,0.0006102815],"genre_scores_gemma":[0.9980973,0.00002395255,0.00074978103,0.00059534464,0.000033064873,0.000012874402,0.000014603873,0.000004573591,0.00046852598],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995649,0.00001294619,0.0001123554,0.00015594023,0.00007783144,0.00007605983],"domain_scores_gemma":[0.99946815,0.00016077902,0.000051263618,0.0002393911,0.000059497328,0.00002091055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008086665,0.000058991354,0.00008274018,0.00007278668,0.00026300526,0.000028451555,0.000044397624,0.000034787707,0.000006008336],"category_scores_gemma":[0.0000973761,0.000037922135,0.00003610691,0.00034722395,0.00016666931,0.000047809,0.000018865569,0.00010880012,1.7201332e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005862067,0.00006876936,0.03181204,0.0002018839,0.000084372914,0.0000014927916,0.00016591151,0.000025091504,0.19745909,0.26135612,0.033900954,0.47433808],"study_design_scores_gemma":[0.00047490082,0.00009767184,0.4542892,0.000059659338,0.00009562089,0.000017637372,0.000071548704,0.00027069554,0.02874176,0.08648054,0.42932722,0.00007353167],"about_ca_topic_score_codex":0.000005499656,"about_ca_topic_score_gemma":0.0000024383173,"teacher_disagreement_score":0.47426456,"about_ca_system_score_codex":0.0000051415195,"about_ca_system_score_gemma":0.000027489577,"threshold_uncertainty_score":0.20228504},"labels":[],"label_agreement":null},{"id":"W4409947176","doi":"10.1101/2025.04.25.650626","title":"Multivariate white matter microstructure alterations in older adults with coronary artery disease","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Ontario Brain Institute; Sunnybrook Health Science Centre; Université de Montréal; Concordia University; Institut Universitaire de Gériatrie de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Fondation Brain Canada","keywords":"Multivariate statistics; Coronary artery disease; Cardiology; White (mutation); White matter; Internal medicine; Medicine; Disease; Multivariate analysis; Microstructure; Materials science; Magnetic resonance imaging; Mathematics; Radiology; Chemistry; Metallurgy","score_opus":0.012997203915251393,"score_gpt":0.26018792049747963,"score_spread":0.24719071658222824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409947176","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9730367,0.0003812381,0.017110057,0.0038512726,0.00025598716,0.0034811602,0.001215663,0.00064177735,0.000026157782],"genre_scores_gemma":[0.9600943,0.00006455678,0.036602307,0.0019668506,0.00013785463,0.0009683803,0.0000069538496,0.00009338636,0.000065410495],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978155,0.000052050047,0.0004441649,0.00108047,0.00020852913,0.0003992816],"domain_scores_gemma":[0.99771124,0.000032744414,0.00021087915,0.0014953741,0.00028196882,0.00026780897],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007778211,0.0005040128,0.00048500154,0.0003202643,0.00011310122,0.00008041479,0.0002633427,0.00023418349,0.00007694197],"category_scores_gemma":[0.000029188739,0.00047385885,0.00010258985,0.0004253218,0.00011155224,0.00011207107,0.0002859757,0.00096111436,0.000021851638],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012036944,0.0010128596,0.9198918,0.0024120572,0.00017681062,0.0009634441,0.00009182325,0.00034122728,0.07065052,0.00037691317,0.0028702768,0.00000857819],"study_design_scores_gemma":[0.0013435811,0.000027267899,0.9887535,0.002882703,0.00013089436,2.0067056e-7,0.0000028686047,0.0007622201,0.004763626,0.0000064623036,0.0008448439,0.0004818242],"about_ca_topic_score_codex":0.000018724764,"about_ca_topic_score_gemma":0.0000025655531,"teacher_disagreement_score":0.06886171,"about_ca_system_score_codex":0.00018478972,"about_ca_system_score_gemma":0.00048295336,"threshold_uncertainty_score":0.9997713},"labels":[],"label_agreement":null},{"id":"W4410044611","doi":"10.1063/5.0258081","title":"Measuring the velocity autocorrelation function using diffusion NMR","year":2025,"lang":"en","type":"article","venue":"The Journal of Chemical Physics","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Engineering Link (Canada)","funders":"National Institute of Child Health and Human Development; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Vetenskapsrådet","keywords":"Autocorrelation; Scaling; Diffusion; Nuclear magnetic resonance; Permeability (electromagnetism); Function (biology); Chemistry; Self-diffusion; Statistical physics; Exponent; Magnet; Molecular dynamics; Anomalous diffusion; Physics; Materials science; Molecular physics; Membrane; Mathematics; Computer science; Thermodynamics; Computational chemistry; Statistics; Geometry","score_opus":0.08160887345774435,"score_gpt":0.33556937164731543,"score_spread":0.25396049818957106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410044611","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5404896,0.00008935375,0.4569665,0.00185183,0.000049130733,0.00014499205,2.8886674e-7,0.000022536075,0.0003857252],"genre_scores_gemma":[0.9976273,0.00002443939,0.0016428042,0.00044820912,0.00021542117,0.0000015981002,6.4053717e-7,0.0000061726982,0.00003341121],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99953514,0.000022074344,0.00017688598,0.00004504244,0.00015481781,0.00006601358],"domain_scores_gemma":[0.999436,0.00010550644,0.0001567086,0.00016070418,0.00012079177,0.000020295825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017349281,0.00005561435,0.000099216595,0.000014434364,0.000097143056,0.000006714484,0.000096211625,0.000023906585,0.0000019787458],"category_scores_gemma":[0.000056297693,0.000029404973,0.00006882652,0.00018682332,0.00005837892,0.000056175493,0.000040304272,0.00035564057,7.4585773e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016543985,0.00008650264,0.00032135387,0.000017084285,0.000027556303,4.3063918e-7,0.00006413189,0.0005908515,0.97670376,0.002360196,0.0008453404,0.018817378],"study_design_scores_gemma":[0.0012784873,0.000104172235,0.008423269,0.0005954216,0.0012196674,0.00013922989,0.00007854701,0.07751513,0.64549536,0.2584245,0.0065711453,0.00015506928],"about_ca_topic_score_codex":0.0000020393206,"about_ca_topic_score_gemma":1.8499458e-8,"teacher_disagreement_score":0.45713767,"about_ca_system_score_codex":0.000058068144,"about_ca_system_score_gemma":0.00003950428,"threshold_uncertainty_score":0.15451011},"labels":[],"label_agreement":null},{"id":"W4410075648","doi":"10.1101/2025.04.29.651339","title":"A combined neuroanatomy, ex vivo imaging and immunohistochemistry defined MRI mask for the human paraventricular nucleus of the thalamus","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Neuroscience; Thalamus; Neuroanatomy; Magnetic resonance imaging; Human brain; Ex vivo; Anatomy; Biology; Voxel; Computer science; In vivo; Artificial intelligence; Medicine; Radiology","score_opus":0.018051623961105705,"score_gpt":0.2792097397888182,"score_spread":0.2611581158277125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410075648","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96228886,0.0039621927,0.016868647,0.008365205,0.0006085948,0.0063605076,0.0007283185,0.0007123741,0.00010530725],"genre_scores_gemma":[0.9909947,0.00036219848,0.0073727164,0.00045125006,0.000086105225,0.0006133242,5.549078e-7,0.000072876326,0.000046303914],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9982156,0.000043295644,0.0004866124,0.0006909229,0.00024180593,0.0003217736],"domain_scores_gemma":[0.99699765,0.00016573205,0.00046077554,0.0019388266,0.0003457916,0.000091245725],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025264928,0.00039170537,0.00049504655,0.0000937782,0.00034366077,0.00005471319,0.00061291555,0.00016130239,0.0000062792683],"category_scores_gemma":[0.00022894083,0.00029052305,0.0002627779,0.00035800732,0.00032417642,0.000033164288,0.0007086992,0.00066274905,4.7855514e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046879533,0.00017003484,0.012584401,0.0009223039,0.00013329806,0.000015642105,0.000008143686,0.000020710771,0.9804049,0.0044871494,0.0011999523,0.000006571537],"study_design_scores_gemma":[0.0017169514,0.000051989293,0.09560274,0.0014694401,0.0011648899,4.679416e-7,0.00001008968,0.0028239293,0.879469,0.00016622458,0.016884323,0.00063997606],"about_ca_topic_score_codex":0.000029225244,"about_ca_topic_score_gemma":1.4993878e-7,"teacher_disagreement_score":0.100935936,"about_ca_system_score_codex":0.000115258255,"about_ca_system_score_gemma":0.0002572936,"threshold_uncertainty_score":0.9999547},"labels":[],"label_agreement":null},{"id":"W4410142627","doi":"10.1523/jneurosci.0096-25.2025","title":"Beyond Motor Control: Diffusion MRI Reveals Associations between the Cerebello-VTA Pathway and Socio-affective Behaviors in Humans","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Diffusion MRI; Psychology; Neuroscience; Control (management); Diffusion; Cognitive psychology; Medicine; Physics; Computer science; Magnetic resonance imaging; Artificial intelligence","score_opus":0.031976109158424186,"score_gpt":0.351825254258974,"score_spread":0.3198491451005498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410142627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9802464,0.000066680965,0.008038363,0.01088523,0.00009420134,0.00042445102,0.000030350764,0.000019216332,0.00019505442],"genre_scores_gemma":[0.99750787,0.00012660587,0.00046391806,0.001577631,0.000049237064,0.000010866385,5.4575344e-7,0.0000067471888,0.00025657972],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99902314,0.00008116858,0.00033593527,0.00017628046,0.00023065702,0.00015280907],"domain_scores_gemma":[0.9990995,0.0003109656,0.00024855198,0.00017276366,0.00010534117,0.00006290855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004485202,0.00008771347,0.0002406566,0.0001525643,0.00024769828,0.00003135382,0.00018743596,0.00003910204,0.0000010177703],"category_scores_gemma":[0.00037736833,0.000059710153,0.0000711773,0.00036819675,0.00018926014,0.00012963264,0.000060404585,0.0004184464,2.489907e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001583767,0.000150206,0.6343269,0.0000072298817,0.0000033642148,0.000019313418,0.00015851705,0.000010100222,0.3621292,0.0010952441,0.00040219066,0.0016819299],"study_design_scores_gemma":[0.0005745468,0.00020597698,0.9930359,0.000060860282,0.000052551066,0.000015879019,0.000034549,0.00009788287,0.0008913226,0.004219819,0.000763637,0.000047089663],"about_ca_topic_score_codex":0.000008554387,"about_ca_topic_score_gemma":0.0000026736413,"teacher_disagreement_score":0.36123788,"about_ca_system_score_codex":0.00008182694,"about_ca_system_score_gemma":0.00007598586,"threshold_uncertainty_score":0.24349093},"labels":[],"label_agreement":null},{"id":"W4410250211","doi":"10.1101/2025.05.09.653169","title":"A Unified Imaging-Histology Framework for Superficial White Matter Architecture Studies in the Human Brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Hospital for Sick Children; Savoy Foundation; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"White matter; Architecture; Human brain; Neuroimaging; Histology; Computer science; Artificial intelligence; Neuroscience; Psychology; Medicine; Pathology; Geography; Magnetic resonance imaging; Radiology; Archaeology","score_opus":0.05607601025933815,"score_gpt":0.3541923202867194,"score_spread":0.2981163100273812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410250211","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5206197,0.0043343673,0.30774856,0.15196528,0.0015763141,0.010992419,0.0009933934,0.0016270842,0.00014286555],"genre_scores_gemma":[0.89037377,0.00008415602,0.09418587,0.0122531485,0.000572245,0.002385123,0.0000020304835,0.00010193454,0.000041722375],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9976842,0.00013940735,0.0005308951,0.0009522944,0.00020115264,0.00049204985],"domain_scores_gemma":[0.9974057,0.00041746793,0.00023069407,0.001565833,0.00030418433,0.00007613814],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004757221,0.00048103638,0.00072397146,0.00038414283,0.00024292823,0.000055344335,0.00060164917,0.00032525792,0.000014361819],"category_scores_gemma":[0.00043734765,0.00040578455,0.00019704128,0.00050073024,0.00034172906,0.000033783253,0.0003677299,0.0015733148,0.0000060933717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005933589,0.0020085883,0.34601003,0.009769641,0.00086922693,0.00061350607,0.0013553541,0.0002483001,0.32634038,0.21833336,0.09381009,0.000048159738],"study_design_scores_gemma":[0.005378667,0.00051555975,0.63918906,0.0110754315,0.0020174389,0.0000022354207,0.00026266224,0.0006479115,0.044682294,0.021388128,0.27034584,0.004494778],"about_ca_topic_score_codex":0.000014889985,"about_ca_topic_score_gemma":0.000004095475,"teacher_disagreement_score":0.36975405,"about_ca_system_score_codex":0.0002069833,"about_ca_system_score_gemma":0.00024920623,"threshold_uncertainty_score":0.9998394},"labels":[],"label_agreement":null},{"id":"W4410308882","doi":"10.1038/s41598-025-00886-7","title":"Multiscale gradients of corticopontine structural connectivity","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Neuroscience; Tractography; Context (archaeology); Cerebellum; Cognition; Brainstem; Diffusion MRI; Biology; Anatomy; Magnetic resonance imaging; Medicine","score_opus":0.03328700621610978,"score_gpt":0.3593777805707021,"score_spread":0.3260907743545923,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410308882","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99001515,0.000057509053,0.0055152304,0.00035694864,0.0011345524,0.00039493715,0.0000026166447,0.0001109401,0.002412139],"genre_scores_gemma":[0.9896581,0.0000017090221,0.006492064,0.000040073337,0.000010384224,0.000017851666,0.000019407467,0.0000053605772,0.0037550079],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990008,0.0000090447165,0.00030924604,0.00038043203,0.00016805924,0.00013241744],"domain_scores_gemma":[0.99892426,0.000022500275,0.0001614822,0.00067835365,0.00016302126,0.000050412076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019411826,0.00007056386,0.00017499636,0.00011657215,0.00011927192,0.000016812997,0.000049797458,0.0000244985,0.000026613656],"category_scores_gemma":[0.00019676538,0.000060060127,0.00006633458,0.00044013176,0.0002569609,0.000050757815,0.000056837824,0.000081314654,0.0000012026991],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003791555,0.00024139333,0.46141893,0.00013750966,0.000029344988,0.00017232286,0.00008298245,0.0000177776,0.5031055,0.0033657611,0.017031813,0.014358767],"study_design_scores_gemma":[0.00048337906,0.000055827968,0.34133092,0.00018624355,0.00009524273,0.00043619372,0.000025532789,0.00154736,0.5530999,0.060381465,0.042207573,0.00015038457],"about_ca_topic_score_codex":0.000017101147,"about_ca_topic_score_gemma":0.0000038265357,"teacher_disagreement_score":0.12008801,"about_ca_system_score_codex":0.000024162631,"about_ca_system_score_gemma":0.00006275192,"threshold_uncertainty_score":0.2449181},"labels":[],"label_agreement":null},{"id":"W4410519647","doi":"10.1101/2025.05.14.654080","title":"Repeated Subconcussive Head Impacts Compromise White Matter Integrity and Bimanual Coordination in Collegiate Football Players","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Head (geology); Compromise; Football; Football players; College football; Aeronautics; Engineering; History; Political science","score_opus":0.03406424164529666,"score_gpt":0.30789568555939295,"score_spread":0.2738314439140963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410519647","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98587304,0.00037487617,0.0043571093,0.005878829,0.00020597177,0.0023694653,0.00034738955,0.00053495885,0.000058380636],"genre_scores_gemma":[0.98214656,0.00019906317,0.016102904,0.0009156841,0.000074910175,0.0004080263,0.000003133868,0.000068795634,0.00008089095],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99758726,0.00010420147,0.0006083008,0.0010541327,0.00020512073,0.00044099442],"domain_scores_gemma":[0.99792135,0.000078294885,0.00036341342,0.0009838187,0.00039911232,0.00025402766],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00035343273,0.0005020202,0.00073913764,0.000534463,0.00011166377,0.000096605414,0.00024173898,0.00043961906,0.00002110429],"category_scores_gemma":[0.00017060169,0.00051459175,0.00010300968,0.0006340166,0.00016215199,0.00012429491,0.00043021797,0.0015796577,0.000011449893],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006153212,0.00067636685,0.72880054,0.0020438407,0.00020888128,0.00025558347,0.000065498076,0.000054213906,0.2594845,0.001293922,0.006482947,0.000018392633],"study_design_scores_gemma":[0.0022967784,0.00012100008,0.94283324,0.002264374,0.00019637257,2.9660507e-7,0.0000073782967,0.003677655,0.04417747,0.00002518011,0.003663352,0.00073686935],"about_ca_topic_score_codex":0.00015539849,"about_ca_topic_score_gemma":0.000009178582,"teacher_disagreement_score":0.21530704,"about_ca_system_score_codex":0.0004853639,"about_ca_system_score_gemma":0.00047720489,"threshold_uncertainty_score":0.9997306},"labels":[],"label_agreement":null},{"id":"W4410594449","doi":"10.1093/braincomms/fcaf193","title":"Sensitivity of diffusion tensor imaging to regional mixed cerebrovascular pathology","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of British Columbia; The Scarborough Hospital; University of Toronto; Sunnybrook Health Science Centre; Simon Fraser University","funders":"Health Research; Heart and Stroke Foundation of Canada","keywords":"Diffusion MRI; Sensitivity (control systems); Medicine; Diffusion; Pathology; Magnetic resonance imaging; Radiology; Physics; Engineering","score_opus":0.06520047307115506,"score_gpt":0.3761593914150825,"score_spread":0.3109589183439274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410594449","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16044714,0.00044308274,0.40463647,0.4260741,0.00004796553,0.0012853906,0.000038470625,0.00042341513,0.00660397],"genre_scores_gemma":[0.87782055,0.00013770271,0.11457495,0.0067137796,0.000011610076,0.00010346231,0.00006054246,0.000013582439,0.0005638246],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992068,0.00015842743,0.00022661456,0.00019857149,0.00008694138,0.00012265223],"domain_scores_gemma":[0.997095,0.00056965713,0.00006417847,0.0020354271,0.00018135196,0.000054422035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029015177,0.00008710841,0.00019538919,0.00016878756,0.00016867602,0.0000050883405,0.00024251724,0.00003378352,0.0000055775176],"category_scores_gemma":[0.00045000747,0.00008773788,0.00009455342,0.00041864836,0.00019608022,0.000028881175,0.00041325763,0.00018112098,0.0000068623563],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000625305,0.0013565761,0.10752942,0.00011557151,0.00007598186,0.000013503182,0.00038933026,0.000041586554,0.54674315,0.17871052,0.07572483,0.08923699],"study_design_scores_gemma":[0.0008659814,0.000046168647,0.5551337,0.0003375842,0.00011029138,0.0001924141,0.00021087856,0.006319807,0.006561687,0.008321287,0.42169583,0.00020438386],"about_ca_topic_score_codex":0.000054715714,"about_ca_topic_score_gemma":0.00002542231,"teacher_disagreement_score":0.71737343,"about_ca_system_score_codex":0.00003662402,"about_ca_system_score_gemma":0.00005745322,"threshold_uncertainty_score":0.3577847},"labels":[],"label_agreement":null},{"id":"W4410708406","doi":"10.1093/bjro/tzaf014","title":"Myelin mapping in patients with rheumatoid arthritis-related fatigue: a TBSS-MTR study of integrity","year":2024,"lang":"en","type":"article","venue":"BJR|Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Infection and Immunity","funders":"University of Aberdeen; Pfizer","keywords":"Rheumatoid arthritis; Structural integrity; Medicine; Myelin; White matter; Internal medicine; Structural engineering; Radiology; Engineering; Central nervous system; Magnetic resonance imaging","score_opus":0.09358581657652058,"score_gpt":0.37787659341259255,"score_spread":0.28429077683607196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410708406","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993008,0.00015444176,0.0010769366,0.00052340946,0.00003175599,0.0030299546,0.000019837928,0.00014297335,0.0020126482],"genre_scores_gemma":[0.99393,0.00007869565,0.005416716,0.00007322543,0.0000056548693,0.00025736872,0.000043488573,0.00003022188,0.00016463899],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988996,0.00003533058,0.00038537264,0.00035961985,0.00017018348,0.00014989449],"domain_scores_gemma":[0.99933404,0.000046571087,0.000080341735,0.00040466027,0.00007978708,0.000054589036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020326446,0.00012807146,0.00032258805,0.00013409361,0.00004276649,0.00006007484,0.00032130643,0.00004325473,0.00006433026],"category_scores_gemma":[0.000050665723,0.000102574915,0.00002418569,0.0005915723,0.000039851937,0.00019779774,0.0003146051,0.00038681948,0.000012428447],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029744476,0.0038836643,0.87930334,0.00015358457,0.000119824326,0.00010317389,0.0027199176,0.000023486227,0.00043791338,0.0044752187,0.0029946014,0.10548781],"study_design_scores_gemma":[0.009663322,0.0018060512,0.96212864,0.006055626,0.000035805584,0.000027770444,0.0013905169,0.0011261167,0.0004932016,0.0045876196,0.012249379,0.0004359374],"about_ca_topic_score_codex":0.0004489206,"about_ca_topic_score_gemma":0.00007624442,"teacher_disagreement_score":0.105051875,"about_ca_system_score_codex":0.00004896228,"about_ca_system_score_gemma":0.000071861105,"threshold_uncertainty_score":0.41828838},"labels":[],"label_agreement":null},{"id":"W4410741941","doi":"10.1038/s41598-025-99724-z","title":"The relationship of white matter tract orientation to vascular geometry in the human brain","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; National Institute of Biomedical Imaging and Bioengineering; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"White matter; Diffusion MRI; Fiber tract; Orientation (vector space); Anatomy; Fractional anisotropy; Human brain; Neuroscience; Voxel; Biology; Medicine; Pathology; Magnetic resonance imaging; Geometry; Mathematics; Radiology","score_opus":0.04575417525798251,"score_gpt":0.3772887596440092,"score_spread":0.3315345843860267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410741941","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743493,0.000037342757,0.00641797,0.0149171185,0.00028964365,0.00072480674,7.685699e-7,0.000028778823,0.0032342798],"genre_scores_gemma":[0.9932429,6.97059e-7,0.0009913562,0.0005969785,0.000010805078,0.00008628954,0.000019362466,0.0000048139564,0.0050467555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990087,0.000039112772,0.00033642017,0.00026713917,0.00024027693,0.000108314096],"domain_scores_gemma":[0.99876946,0.00015212338,0.000109378685,0.0008719008,0.00007603109,0.000021122392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014762501,0.000052193733,0.00007905894,0.0001872384,0.00043822342,0.000045966608,0.00010123464,0.000021003254,0.000014298202],"category_scores_gemma":[0.00033646537,0.000031996602,0.000052589232,0.0012430474,0.00011139855,0.00004882723,0.000037695714,0.00012225023,0.000004611708],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000027511028,0.00011555667,0.9362467,0.000023162436,0.000003640283,0.000017929904,0.0005863599,0.000034853234,0.008148998,0.0052570566,0.048900757,0.0006622312],"study_design_scores_gemma":[0.00007259827,0.000010281831,0.8975043,0.000053207194,0.000014011345,0.000028954064,0.00015127074,0.0000101828455,0.0013656674,0.030480122,0.07027636,0.000033034623],"about_ca_topic_score_codex":0.0000088530705,"about_ca_topic_score_gemma":0.0000065100935,"teacher_disagreement_score":0.038742397,"about_ca_system_score_codex":0.000025744983,"about_ca_system_score_gemma":0.000037827725,"threshold_uncertainty_score":0.33705047},"labels":[],"label_agreement":null},{"id":"W4410756831","doi":"10.1017/s0954579425000367","title":"Testing the ecophenotype hypothesis: Differences in white matter microstructure in youth with conduct disorder with versus without a history of childhood abuse","year":2025,"lang":"en","type":"article","venue":"Development and Psychopathology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Public Health","funders":"HORIZON EUROPE Framework Programme; Economic and Social Research Council; Bundesministerium für Bildung und Forschung; Universität Zürich; European Commission; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; UK Research and Innovation; National Science Foundation","keywords":"Fractional anisotropy; Corpus callosum; Psychology; White matter; Sexual abuse; Child abuse; Diffusion MRI; Physical abuse; Superior longitudinal fasciculus; Fasciculus; Clinical psychology; Poison control; Injury prevention; Medicine; Neuroscience; Magnetic resonance imaging","score_opus":0.0646917933197815,"score_gpt":0.284459099789703,"score_spread":0.21976730646992151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410756831","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9968636,0.0003328823,0.00017899097,0.00062563695,0.000042462274,0.00031731025,0.0000019702227,0.000019664012,0.0016174943],"genre_scores_gemma":[0.9750729,0.000024294379,0.024043996,0.0005110991,0.0000052242417,0.000057774352,0.000004707126,0.000010306371,0.0002697026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993987,0.000024057565,0.00016884634,0.00023135428,0.00004805063,0.00012895552],"domain_scores_gemma":[0.9996662,0.000058413687,0.000068999994,0.00016439294,0.000025657095,0.000016310945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006109206,0.00011818382,0.00020945881,0.00012258587,0.000027433884,0.0000033450053,0.000069728514,0.00003904519,0.000007310231],"category_scores_gemma":[0.000010281577,0.00006903243,0.000007182625,0.00020753089,0.00016051033,0.000021204289,0.000014783927,0.0001716469,5.8953015e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036874085,0.000062985106,0.985673,0.000022858763,0.0000089036175,0.0000061711253,0.009605546,9.297775e-7,0.0002999568,0.00003662619,0.000039439743,0.0038748123],"study_design_scores_gemma":[0.0017625195,0.00009375858,0.99587107,0.00019726044,0.00002131726,0.00002502043,0.00063162926,0.0000024628036,0.00006382939,0.000092472335,0.0011534488,0.000085202286],"about_ca_topic_score_codex":0.000013667736,"about_ca_topic_score_gemma":0.00012852484,"teacher_disagreement_score":0.023865005,"about_ca_system_score_codex":0.00003507944,"about_ca_system_score_gemma":0.000107559375,"threshold_uncertainty_score":0.28150606},"labels":[],"label_agreement":null},{"id":"W4410946066","doi":"10.1016/j.mri.2025.110443","title":"Rapid 1 mm isotropic diffusion tensor imaging with denoising and improved parameter estimation for detecting focal hippocampal lesions in temporal lobe epilepsy","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Consejo Nacional de Ciencia y Tecnología; Canada Research Chairs","keywords":"Diffusion MRI; Hippocampal formation; Temporal lobe; Epilepsy; Isotropy; Tensor (intrinsic definition); Physics; Nuclear magnetic resonance; Noise reduction; Medicine; Biomedical engineering; Neuroscience; Materials science; Optics; Radiology; Magnetic resonance imaging; Mathematics; Psychology; Acoustics; Geometry","score_opus":0.021814285447326644,"score_gpt":0.3052864779706673,"score_spread":0.28347219252334066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410946066","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.588087,0.004712986,0.40070236,0.004469723,0.000050395636,0.0016104338,0.0000067888277,0.00023300781,0.00012730322],"genre_scores_gemma":[0.7640687,0.0000891447,0.23466305,0.0006793296,0.000031979067,0.00028732937,0.00001105068,0.00003718663,0.00013218778],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833703,0.000037585003,0.00042133045,0.0006194506,0.00013850552,0.00044608765],"domain_scores_gemma":[0.9990267,0.00030175998,0.00011891223,0.00038894778,0.00008067606,0.0000829999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018644554,0.00025626592,0.000340724,0.00028133905,0.00026939777,0.00008590131,0.000107281645,0.000041424046,0.0000059401827],"category_scores_gemma":[0.000320399,0.00022743193,0.000059530335,0.00040685068,0.00018680475,0.00018517923,0.00009219733,0.00030924837,7.2533743e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015007802,0.00005475911,0.24296854,0.00007810945,0.0000016198744,0.000016203025,0.000060854883,0.0000091570055,0.009571178,0.00010573596,0.000056558893,0.7469272],"study_design_scores_gemma":[0.0036542641,0.00025451728,0.41417783,0.0012814612,0.000101363505,0.00016928399,0.00025570107,0.566104,0.002585093,0.0038604105,0.0071882755,0.00036777934],"about_ca_topic_score_codex":0.00009895175,"about_ca_topic_score_gemma":0.000018764174,"teacher_disagreement_score":0.74655944,"about_ca_system_score_codex":0.0001056115,"about_ca_system_score_gemma":0.00007180177,"threshold_uncertainty_score":0.92744046},"labels":[],"label_agreement":null},{"id":"W4410948111","doi":"10.1162/imag.a.49","title":"Mapping the aggregate g-ratio of white matter tracts using multi-modal MRI","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; University of Calgary; McGill University; Montreal Neurological Institute and Hospital","funders":"Fonds de Recherche du Québec - Santé; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Modal; White matter; Aggregate (composite); Magnetic resonance imaging; Materials science; Medicine; Radiology; Composite material","score_opus":0.0864788581969707,"score_gpt":0.37344812854845294,"score_spread":0.28696927035148223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410948111","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24497436,0.00009092719,0.7349738,0.018173072,0.00020132643,0.00047698736,0.0000060672373,0.00013830722,0.0009651875],"genre_scores_gemma":[0.96576375,0.000016908873,0.026225625,0.0071747703,0.000017605744,0.00001570606,6.554649e-7,0.000012396185,0.0007726007],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990208,0.00002486413,0.0002331558,0.0003354458,0.0001632198,0.00022249979],"domain_scores_gemma":[0.9992411,0.00004473792,0.0001208199,0.00047724944,0.00007448432,0.00004159919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013445361,0.000111498244,0.00013881135,0.00013858813,0.00033239776,0.000035219455,0.00025951344,0.000013551794,0.000005084329],"category_scores_gemma":[0.000086942455,0.00008432665,0.000055913475,0.0006964215,0.000369713,0.00017062025,0.00015769892,0.00019736185,0.0000025810418],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000068847953,0.000086181186,0.24780796,0.00004654721,0.0000014073182,0.000014861367,0.00021520608,0.00035201485,0.7492112,0.00037845693,0.00047625715,0.0014030049],"study_design_scores_gemma":[0.000458129,0.000016176573,0.6740368,0.00033883628,0.000034360513,0.00020780393,0.00008021417,0.2441957,0.067694284,0.00057569577,0.012190305,0.00017166388],"about_ca_topic_score_codex":0.0000127565945,"about_ca_topic_score_gemma":2.8216323e-7,"teacher_disagreement_score":0.7207894,"about_ca_system_score_codex":0.000024883182,"about_ca_system_score_gemma":0.00007469644,"threshold_uncertainty_score":0.34387413},"labels":[],"label_agreement":null},{"id":"W4410966131","doi":"10.1007/978-1-0716-4438-6_30","title":"Functional MRI of the Spinal Cord","year":2025,"lang":"en","type":"book-chapter","venue":"Neuromethods","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Spinal cord; Medicine; Neuroscience; Psychology","score_opus":0.1685469080467526,"score_gpt":0.42495596588025186,"score_spread":0.25640905783349927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410966131","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000033315944,0.00031344578,0.10593051,0.0056122784,0.0005656199,0.00077593897,0.000058410238,0.00018454417,0.8865259],"genre_scores_gemma":[0.0006128161,0.00029554655,0.11025235,0.0025186192,0.00021450524,0.000034244178,0.000013086318,0.000054932836,0.8860039],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990745,0.00002289778,0.00026187,0.000313218,0.0002280952,0.00009938378],"domain_scores_gemma":[0.99881977,0.00009704746,0.00018319595,0.00074935006,0.000109870445,0.00004078446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000996542,0.00017654794,0.0003100469,0.000118039374,0.000059224127,0.0000038847247,0.00016885446,0.000120703415,0.00017807753],"category_scores_gemma":[0.00008575492,0.00013127922,0.00024469936,0.000092154194,0.00016083616,0.000012308391,0.0001555952,0.00059281,0.0000065028653],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048758564,0.00008019818,0.00014020494,0.00043284308,0.00007091418,0.000020635634,0.0000028295826,0.0000036922975,0.00866417,0.6574509,0.09095451,0.24169151],"study_design_scores_gemma":[0.0001676638,0.00030317032,0.0040485533,0.00039304685,0.00018015174,0.000092574635,3.504218e-7,0.000016340015,0.0024603063,0.043734774,0.94849956,0.00010353175],"about_ca_topic_score_codex":0.0000011903295,"about_ca_topic_score_gemma":1.2308114e-7,"teacher_disagreement_score":0.857545,"about_ca_system_score_codex":0.00002624988,"about_ca_system_score_gemma":0.0001113203,"threshold_uncertainty_score":0.5353411},"labels":[],"label_agreement":null},{"id":"W4411009153","doi":"10.1002/hbm.70245","title":"Mapping Caudolenticular Gray Matter Bridges in the Human Brain Striatum Through Diffusion Magnetic Resonance Imaging and Tractography","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université de Sherbrooke","funders":"National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Université de Sherbrooke","keywords":"Tractography; Human Connectome Project; Diffusion MRI; Putamen; White matter; Magnetic resonance imaging; Human brain; Connectome; Striatum; Nuclear magnetic resonance; Caudate nucleus; Artificial intelligence; Physics; Neuroscience; Computer science; Psychology; Radiology; Medicine","score_opus":0.03518705620220358,"score_gpt":0.32583069353233846,"score_spread":0.2906436373301349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411009153","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9049761,0.003663215,0.024952298,0.060956284,0.000052442418,0.0014655531,0.00000852276,0.0002578112,0.003667739],"genre_scores_gemma":[0.9794884,0.00007468358,0.002347582,0.016969256,0.00008778741,0.00015079469,0.00003500868,0.000034362438,0.0008121622],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99822503,0.00013343945,0.00044568628,0.00057861535,0.00021559461,0.0004016046],"domain_scores_gemma":[0.99896824,0.00021843733,0.00011035435,0.0006212738,0.000038808765,0.000042858555],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043327766,0.00025763855,0.0003133549,0.0003636671,0.00058052514,0.00011088977,0.00025073838,0.00006127886,0.000031715434],"category_scores_gemma":[0.00006285114,0.0002205958,0.000113067974,0.0006668497,0.00022958836,0.00014328475,0.00013941692,0.00050875853,0.0000035105697],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012796736,0.00029176008,0.42498067,0.00041158512,0.000013900385,0.000119678014,0.0038367126,0.0000024252754,0.49535987,0.018026922,0.0498036,0.0071400763],"study_design_scores_gemma":[0.0009161139,0.000024457226,0.8715876,0.00096517673,0.000018516354,0.000041774292,0.0011063991,0.0001617072,0.00015330623,0.01630706,0.108515985,0.0002019189],"about_ca_topic_score_codex":0.00012805249,"about_ca_topic_score_gemma":0.000018379973,"teacher_disagreement_score":0.49520656,"about_ca_system_score_codex":0.00004422938,"about_ca_system_score_gemma":0.00001507526,"threshold_uncertainty_score":0.8995636},"labels":[],"label_agreement":null},{"id":"W4411010217","doi":"10.1016/j.mri.2025.110445","title":"Comparing single-shot EPI and 2D-navigated, multi-shot EPI diffusion tensor imaging acquisitions in the lumbar spinal cord at 3T","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Institute of Neurological Disorders and Stroke; Natural Sciences and Engineering Research Council of Canada; National Institute of Biomedical Imaging and Bioengineering; Vanderbilt University; Society for Anthropological Sciences; National Institutes of Health; National Multiple Sclerosis Society","keywords":"Single shot; Shot (pellet); Diffusion MRI; Spinal cord; Lumbar; Medicine; Anatomy; Materials science; Radiology; Physics; Magnetic resonance imaging; Optics","score_opus":0.08584864028324021,"score_gpt":0.36745536553047603,"score_spread":0.28160672524723585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411010217","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9425617,0.02172874,0.010859596,0.017703075,0.00012121507,0.001633855,0.000021109085,0.00038014015,0.0049905847],"genre_scores_gemma":[0.9807627,0.0005649453,0.013880415,0.0036949166,0.000060232574,0.00021001173,0.00002589266,0.000041161074,0.00075968757],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978486,0.000087338594,0.00051720196,0.0007180261,0.00026783993,0.00056103384],"domain_scores_gemma":[0.99882376,0.00012200782,0.00011811856,0.0007310132,0.00010371169,0.000101398786],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027530527,0.00031828324,0.00040372674,0.00023468949,0.00047275156,0.00011113984,0.00030415494,0.000041665153,0.000034543795],"category_scores_gemma":[0.00012251768,0.0002746263,0.0000876002,0.000663201,0.00042908528,0.00015165553,0.00032567713,0.00050032884,0.000010182278],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027113024,0.0005182125,0.66221946,0.00015534845,0.0000044969247,0.0003291197,0.00032787074,0.000010856287,0.107025675,0.0012038944,0.0014880232,0.22644591],"study_design_scores_gemma":[0.002082866,0.00013606795,0.92622614,0.0012495528,0.00008836739,0.0005306355,0.00039897405,0.031187551,0.0008651771,0.00092250976,0.035985716,0.0003264133],"about_ca_topic_score_codex":0.00014553255,"about_ca_topic_score_gemma":0.000028842203,"teacher_disagreement_score":0.2640067,"about_ca_system_score_codex":0.00016826669,"about_ca_system_score_gemma":0.000035156492,"threshold_uncertainty_score":0.9999706},"labels":[],"label_agreement":null},{"id":"W4411010286","doi":"10.1101/2025.05.30.25328630","title":"Gray matter microstructure from in-vivo diffusion MRI reflects post-mortem neuropathology severity and clinical progression of Alzheimer’s disease","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; McGill University; Douglas Mental Health University Institute","funders":"National Institutes of Health; Cleveland Clinic; Northern California Institute for Research and Education; National Institute on Aging; Emory University; University of Southern California","keywords":"Neuropathology; Diffusion MRI; Gray (unit); Disease; Neuroscience; In vivo; Pathology; Medicine; Magnetic resonance imaging; Psychology; Biology; Radiology","score_opus":0.04840301331926834,"score_gpt":0.40796145377888315,"score_spread":0.3595584404596148,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411010286","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99145085,0.00087472546,0.00053365977,0.005036498,0.0002589113,0.0011646318,0.0004390629,0.00011478135,0.00012685783],"genre_scores_gemma":[0.982917,0.0010926753,0.013369204,0.0020732442,0.000112778216,0.0000953506,0.0002026727,0.00003886988,0.00009819507],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99785656,0.00019073367,0.0006674672,0.00091007655,0.00016703963,0.00020814993],"domain_scores_gemma":[0.99826455,0.00011163161,0.0003322086,0.0009972575,0.00011221536,0.00018211028],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016115684,0.00029759365,0.0006830087,0.00015186456,0.000045635086,0.000010930978,0.00017752718,0.00029092556,0.0000424898],"category_scores_gemma":[0.00013310491,0.00024611727,0.00015841506,0.00012774998,0.00025971132,0.000026727892,0.0009413215,0.001061741,0.000002105878],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003213637,0.0002778779,0.96685356,0.0002453924,0.000021649343,0.00025415295,0.00004499871,0.0000012954139,0.028429752,0.000018699033,0.00061433174,0.0029169042],"study_design_scores_gemma":[0.00052098866,0.00007668367,0.98996556,0.0008328883,0.0003179956,0.00002541139,0.000003446644,0.00020056179,0.0038944017,0.0024668027,0.0015178997,0.00017734879],"about_ca_topic_score_codex":0.000042346164,"about_ca_topic_score_gemma":0.000008473437,"teacher_disagreement_score":0.02453535,"about_ca_system_score_codex":0.000017931872,"about_ca_system_score_gemma":0.00012081873,"threshold_uncertainty_score":0.9999991},"labels":[],"label_agreement":null},{"id":"W4411063250","doi":"10.1007/s00429-025-02932-6","title":"MRI and non-MRI quantifiable neuroanatomical and functional parameters are useful for tractography","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Wellcome Trust","keywords":"Tractography; Neuroscience; Diffusion MRI; Psychology; Magnetic resonance imaging; Computer science; Medicine; Radiology","score_opus":0.0597558029076259,"score_gpt":0.34575043608806444,"score_spread":0.28599463318043855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411063250","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00084724394,0.9272924,0.06675571,0.0013156205,0.00035827266,0.0027581898,0.0004303363,0.0001744205,0.00006776682],"genre_scores_gemma":[0.00067614275,0.990153,0.0068715084,0.0010667499,0.00015461554,0.0002452021,0.00048439408,0.00004856377,0.00029978756],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99874043,0.000027237895,0.00029526287,0.00065769145,0.00009842455,0.00018095173],"domain_scores_gemma":[0.99896926,0.00043101696,0.0001817462,0.00025466376,0.000052573258,0.00011071583],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00007140934,0.00032360264,0.0007831145,0.00026073202,0.00018104978,0.000054241224,0.000035425604,0.00026960325,0.0000066030143],"category_scores_gemma":[0.00007046422,0.00025890267,0.00016571344,0.00026326862,0.00012586357,0.00007319566,0.000040469444,0.00038755007,2.1970074e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002161703,0.000045171117,0.0007704467,0.017754853,0.0002095894,0.0000053731333,0.000012247712,0.0000024428728,0.000057492372,0.0016923557,0.03190002,0.9473338],"study_design_scores_gemma":[0.00048710825,0.00015591587,0.0035960812,0.0016957028,0.0010616728,0.00018871862,0.000010939641,0.00010724643,0.0000058644273,0.0031531923,0.98930764,0.00022990257],"about_ca_topic_score_codex":0.0000031576928,"about_ca_topic_score_gemma":0.000001846113,"teacher_disagreement_score":0.95740765,"about_ca_system_score_codex":0.000014623233,"about_ca_system_score_gemma":0.000054836106,"threshold_uncertainty_score":0.9999863},"labels":[],"label_agreement":null},{"id":"W4411138398","doi":"10.1002/hbm.70255","title":"Microstructural Characterization of Short Association Fibers Related to Long‐Range White Matter Tracts in Normative Development","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; National Institute of Biomedical Imaging and Bioengineering; National Institute of General Medical Sciences; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute on Drug Abuse; National Institute on Aging; National Institutes of Health; National Science Foundation","keywords":"White matter; Normative; Association (psychology); Characterization (materials science); Psychology; Neuroscience; Medicine; Materials science; Magnetic resonance imaging; Nanotechnology; Philosophy; Radiology; Epistemology","score_opus":0.02964620367892138,"score_gpt":0.3201241704359451,"score_spread":0.2904779667570237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411138398","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838163,0.0000030257606,0.007572528,0.0067141466,0.000024523673,0.0005878107,0.0000049080863,0.00006096825,0.0012157754],"genre_scores_gemma":[0.99067885,0.0000012102508,0.004441249,0.002144456,0.000007761644,0.000055228313,0.00014842648,0.000010861378,0.0025119537],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99919087,0.000024558865,0.000366553,0.0001746231,0.00010006251,0.00014334229],"domain_scores_gemma":[0.99964696,0.000029540724,0.000104016515,0.00013245613,0.00005875237,0.000028256121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015409947,0.000092185706,0.00017501127,0.00025678345,0.0000811407,0.000011384291,0.000059091642,0.000056010165,0.00003691759],"category_scores_gemma":[0.000030825104,0.00009914373,0.000027701286,0.00037784543,0.000013552121,0.000087655266,0.00003571501,0.00014489092,0.000008399636],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000066921693,0.000023692366,0.5904299,0.00006902108,0.0000130512135,0.0000018040947,0.0020549572,0.0000049938894,0.40604502,0.00014741991,0.00058575085,0.00061771565],"study_design_scores_gemma":[0.00023551268,0.000008569356,0.9903159,0.00032785418,0.0000068531845,0.0000022602878,0.000040016814,0.000028986902,0.006562949,0.00023920987,0.0021519926,0.000079901285],"about_ca_topic_score_codex":0.0000028261634,"about_ca_topic_score_gemma":0.0000052260043,"teacher_disagreement_score":0.399886,"about_ca_system_score_codex":0.0002501204,"about_ca_system_score_gemma":0.000025545445,"threshold_uncertainty_score":0.4042964},"labels":[],"label_agreement":null},{"id":"W4411165765","doi":"10.1016/j.bpsc.2025.06.001","title":"Neurite Density and Kurtosis in the Gray Matter of People With Early Schizophrenia","year":2025,"lang":"en","type":"article","venue":"Biological Psychiatry Cognitive Neuroscience and Neuroimaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; Western University","funders":"Janssen Canada; Fonds de Recherche du Québec - Santé; Sunovion; Canadian Institutes of Health Research; Canadian Psychiatric Association; Canada First Research Excellence Fund; Canada Research Chairs; Canada Foundation for Innovation; Physicians' Services Incorporated Foundation; Western University; Academic Medical Organization of Southwestern Ontario; McGill University; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Gray (unit); Kurtosis; Neurite; Neuroscience; Psychiatry; Psychology; Medicine; Biology; Radiology; Mathematics; Statistics","score_opus":0.0389110924635004,"score_gpt":0.3264922113081556,"score_spread":0.2875811188446552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411165765","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9908822,0.00011832252,0.0015784673,0.0063938587,0.00004902562,0.00044917033,0.000005912181,0.00003732319,0.00048568082],"genre_scores_gemma":[0.9887378,0.00018884178,0.0007449327,0.01026479,0.000014060757,0.000029818804,0.0000012531492,0.0000057965553,0.000012664323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998926,0.000079225596,0.00017788753,0.00050989224,0.000108113796,0.00019891793],"domain_scores_gemma":[0.99947906,0.00018865145,0.000066244655,0.00017209919,0.000046762216,0.00004719874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011982977,0.00014558982,0.00020867628,0.000124192,0.00015926977,0.000035844183,0.0001168179,0.00002431688,0.0000015180882],"category_scores_gemma":[0.00009072431,0.0000850918,0.00003118952,0.0006346827,0.00057528,0.00009031958,0.0000941658,0.00028863718,6.2829406e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015676857,0.0001082775,0.9827215,0.000022724596,0.0000010786285,0.000008449408,0.0000410344,1.0977439e-7,0.014830906,0.0008662403,0.00002778508,0.0012151342],"study_design_scores_gemma":[0.0005486267,0.0003292552,0.99610597,0.00011088237,0.000026914913,0.0001229364,0.000081862105,0.000058367517,0.00066919345,0.0017926792,0.00007089063,0.00008243177],"about_ca_topic_score_codex":0.0000144863225,"about_ca_topic_score_gemma":0.0000036472304,"teacher_disagreement_score":0.0141617125,"about_ca_system_score_codex":0.0000024794435,"about_ca_system_score_gemma":0.000025405077,"threshold_uncertainty_score":0.34699428},"labels":[],"label_agreement":null},{"id":"W4411203935","doi":"10.1371/journal.pone.0324802","title":"Math skills and microstructure of the middle longitudinal fasciculus: A developmental investigation","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Fasciculus; Inferior longitudinal fasciculus; Superior longitudinal fasciculus; Microstructure; Psychology; Medicine; Diffusion MRI; Chemistry; Magnetic resonance imaging; Fractional anisotropy","score_opus":0.07168577405719179,"score_gpt":0.2811281177496088,"score_spread":0.209442343692417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411203935","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9969734,0.000060514394,0.0002348614,0.0020517928,0.0000056456106,0.00034391787,0.000007820189,0.000034949004,0.0002870796],"genre_scores_gemma":[0.95821166,0.000028036004,0.040572193,0.0005020344,0.000009331598,0.00003419965,0.000005067257,0.000004688347,0.00063281204],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99965006,0.0000053018593,0.00009716569,0.00010842856,0.000078671736,0.000060370825],"domain_scores_gemma":[0.99976933,0.000014444511,0.000037843554,0.00011892172,0.00003800935,0.000021464868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000024383768,0.000049348182,0.00009312185,0.000027110005,0.000052622203,0.00000454904,0.000045312103,0.000022451964,0.0000028953846],"category_scores_gemma":[0.000042817115,0.000034683893,0.0000149130665,0.00015239343,0.00009965411,0.000021271502,0.000059054208,0.000078060955,5.709062e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009168714,0.00034420073,0.42387265,0.0002731816,0.00005911797,8.730596e-7,0.00021225901,2.5852643e-7,0.56984293,0.004273164,0.00027131065,0.00084087555],"study_design_scores_gemma":[0.0002043131,0.000012698492,0.6084693,0.00042524634,0.00007987439,0.000009832119,0.00002218827,0.00004078454,0.3868136,0.0037496255,0.00013647007,0.000036083373],"about_ca_topic_score_codex":0.0000034287061,"about_ca_topic_score_gemma":0.0000015296965,"teacher_disagreement_score":0.18459664,"about_ca_system_score_codex":0.000021796126,"about_ca_system_score_gemma":0.000035315854,"threshold_uncertainty_score":0.1414368},"labels":[],"label_agreement":null},{"id":"W4411236123","doi":"10.1093/mnrasl/slaf062","title":"SHAM-OT: rapid subhalo abundance matching with optimal transport","year":2025,"lang":"en","type":"article","venue":"Monthly Notices of the Royal Astronomical Society Letters","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institute of Particle Physics","funders":"Spine Education and Research Institute; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Physics; Astrophysics; Abundance (ecology); Astronomy; Biology; Ecology","score_opus":0.01253571060582177,"score_gpt":0.2506089550133551,"score_spread":0.23807324440753336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411236123","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95538574,0.000049778948,0.020331532,0.02336393,0.000040943465,0.00039371944,0.000021156044,0.00009072002,0.00032250275],"genre_scores_gemma":[0.91595113,4.1130306e-7,0.08176359,0.0019841031,0.000049770104,0.000034530094,0.000009480553,0.000019170904,0.00018780853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9990177,0.000015828995,0.00025926594,0.0003033127,0.00014849636,0.00025537505],"domain_scores_gemma":[0.9993132,0.00006363801,0.00012602664,0.00041368091,0.000024909034,0.000058576574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008942076,0.00016999291,0.0002788293,0.0000151366185,0.00013823407,0.0000123691125,0.0003110763,0.000047308997,0.000015191058],"category_scores_gemma":[0.000004526273,0.00011889371,0.00031099346,0.00012371362,0.00030996645,0.000057306017,0.00006876495,0.00034935068,0.0000015030323],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044077626,0.00035862625,0.10704408,0.00022953427,0.00033205314,0.0000021266792,0.00052073953,0.876279,0.0065191975,0.0003855775,0.005375816,0.0025124538],"study_design_scores_gemma":[0.0028045706,0.00021882105,0.8478025,0.00071008864,0.0007144072,5.729851e-7,0.00040788396,0.117981985,0.017431252,0.000063864776,0.011352749,0.0005113018],"about_ca_topic_score_codex":0.00008075324,"about_ca_topic_score_gemma":0.000003225877,"teacher_disagreement_score":0.758297,"about_ca_system_score_codex":0.0000844878,"about_ca_system_score_gemma":0.000039882554,"threshold_uncertainty_score":0.48483446},"labels":[],"label_agreement":null},{"id":"W4411266029","doi":"10.55458/neurolibre.00039","title":"Parkinson’s disease in the spinal cord: an exploratorystudy to establish T2*w, MTR and diffusion-weighted imaging metricvalues","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Courtois Foundation; Canada First Research Excellence Fund; Polytechnique Montréal","keywords":"Metric (unit); Parkinson's disease; Diffusion MRI; Spinal cord; Medicine; Disease; Psychology; Magnetic resonance imaging; Neuroscience; Pathology; Radiology; Economics; Operations management","score_opus":0.08573376771606607,"score_gpt":0.40164159119129,"score_spread":0.31590782347522395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411266029","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9210049,0.0024548722,0.045145053,0.02153063,0.00022873397,0.005879311,0.000136002,0.00092356786,0.0026969546],"genre_scores_gemma":[0.9688521,0.0006684224,0.02192936,0.0066424133,0.0001410062,0.0013645024,0.00009959381,0.00003507873,0.00026749272],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9979499,0.00010185771,0.000395857,0.0009120921,0.00035538577,0.0002849006],"domain_scores_gemma":[0.99805135,0.00009034701,0.00010273556,0.0012528776,0.00013638687,0.0003663329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030286997,0.00033438465,0.0004231643,0.0005979402,0.00014684677,0.00013775179,0.00043829274,0.000060830724,0.000015595435],"category_scores_gemma":[0.0002433138,0.00023923459,0.000076561475,0.0007885809,0.00007652048,0.000119094766,0.0008356998,0.00065491104,0.0000024132266],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004010487,0.00495397,0.6945818,0.0015720829,0.0000884474,0.0008290062,0.0027634287,0.000039292067,0.00087225455,0.015147413,0.028028414,0.2471134],"study_design_scores_gemma":[0.0027673454,0.0011683769,0.63441575,0.003272125,0.0007834187,0.00004592411,0.0045825536,0.01650082,0.00033710277,0.04289417,0.29154202,0.0016904097],"about_ca_topic_score_codex":0.00021718202,"about_ca_topic_score_gemma":0.000015663387,"teacher_disagreement_score":0.26351362,"about_ca_system_score_codex":0.00008857136,"about_ca_system_score_gemma":0.00019548039,"threshold_uncertainty_score":0.9755704},"labels":[],"label_agreement":null},{"id":"W4411349417","doi":"10.1007/s00429-025-02964-y","title":"The tractographer’s dilemma: understanding sources of variability in tractography","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Hanarth Fonds; European Research Council; Alzheimer Nederland; Galen and Hilary Weston Foundation","keywords":"Dilemma; Tractography; Psychology; Computer science; Philosophy; Medicine; Diffusion MRI; Epistemology; Radiology; Magnetic resonance imaging","score_opus":0.08098850839584715,"score_gpt":0.3625468262216743,"score_spread":0.28155831782582713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411349417","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00006733028,0.9792657,0.018356334,0.0002911761,0.00011402194,0.001151821,0.00005717558,0.00006712331,0.00062934804],"genre_scores_gemma":[0.0061125387,0.9932313,0.00037609303,0.00005947822,0.000053743508,0.000056050892,0.00005106836,0.00001603077,0.000043681368],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893874,0.00013208952,0.00039040702,0.00030271523,0.00010366968,0.00013235449],"domain_scores_gemma":[0.99814796,0.0013012144,0.00021221947,0.00027911988,0.000025733741,0.000033759843],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033993993,0.0001986988,0.0006128496,0.00021606722,0.00011639494,0.000018964956,0.00006633211,0.00019363067,0.000008293184],"category_scores_gemma":[0.00018797061,0.00012289628,0.00021767616,0.0007128385,0.0001545988,0.000035233552,0.000025201092,0.00044478202,4.5930907e-8],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026934817,0.000022043705,0.000653755,0.004682053,0.000048366786,0.0000010100582,0.000014588666,1.8012567e-7,0.0000054124134,0.011792922,0.00027985466,0.9824729],"study_design_scores_gemma":[0.00016388421,0.000055240675,0.00089181215,0.0025841442,0.00045020448,0.00002991518,0.000037977814,0.000003619712,0.000002401698,0.03154544,0.96412474,0.000110638524],"about_ca_topic_score_codex":0.00000880818,"about_ca_topic_score_gemma":0.000010535671,"teacher_disagreement_score":0.9823622,"about_ca_system_score_codex":0.00003701766,"about_ca_system_score_gemma":0.00007005795,"threshold_uncertainty_score":0.5011565},"labels":[],"label_agreement":null},{"id":"W4411349534","doi":"10.1007/s00429-025-02938-0","title":"Think deep in the tractography game: deep learning for tractography computing and analysis","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health","keywords":"Tractography; Deep learning; Computer science; Artificial intelligence; Data science; Psychology; Medicine; Diffusion MRI; Radiology; Magnetic resonance imaging","score_opus":0.033750727196719565,"score_gpt":0.36135284852739324,"score_spread":0.3276021213306737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411349534","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020496844,0.8240647,0.17395188,0.00023603193,0.000040918767,0.0013044641,0.0000176469,0.0000901279,0.00008930545],"genre_scores_gemma":[0.0093896855,0.98447835,0.004546357,0.0007146422,0.00014815429,0.00007907467,0.0005899786,0.000027548174,0.000026213886],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881935,0.00009950718,0.00034202702,0.0004565395,0.00010759452,0.00017497517],"domain_scores_gemma":[0.998638,0.0008234186,0.00021932533,0.00024084386,0.00003758137,0.00004087885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002161302,0.00026965103,0.0008191808,0.00071686925,0.00018184887,0.000055473447,0.000076881806,0.00021808164,0.0000041863573],"category_scores_gemma":[0.00009296731,0.00017866745,0.00039839937,0.001621139,0.00006722534,0.000045883306,0.000022741124,0.00068297354,5.1052567e-8],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015028966,0.000013734285,0.0005011354,0.0025519924,0.00020603757,0.0000014351829,0.00018101618,0.000012470805,0.0000023409732,0.000461588,0.00005496304,0.99599826],"study_design_scores_gemma":[0.00042794397,0.00017443442,0.015376409,0.0013502656,0.007357187,0.00008392344,0.0001985459,0.0012168513,4.4839996e-7,0.0033268481,0.9702034,0.0002837703],"about_ca_topic_score_codex":0.000005232427,"about_ca_topic_score_gemma":0.000011681067,"teacher_disagreement_score":0.9957145,"about_ca_system_score_codex":0.000010679616,"about_ca_system_score_gemma":0.000018170196,"threshold_uncertainty_score":0.7285847},"labels":[],"label_agreement":null},{"id":"W4411626609","doi":"10.1016/j.neuroimage.2025.121324","title":"Diffusion Bubble Model: A novel MRI approach for detection and subtyping of neonatal punctate white matter lesions","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Centre de recherche du CHU Sainte-Justine; Canada First Research Excellence Fund; China Scholarship Council; Polytechnique Montréal; Réseau en Bio-Imagerie du Quebec","keywords":"Diffusion MRI; Voxel; White matter; Nuclear magnetic resonance; Isotropy; Diffusion; Magnetic resonance imaging; Anisotropy; Chemistry; Nuclear medicine; Physics; Optics; Radiology; Medicine","score_opus":0.04398671906828196,"score_gpt":0.31851831759380167,"score_spread":0.2745315985255197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411626609","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.079429,0.000032146563,0.9169925,0.0012032643,0.000020610622,0.0007217614,0.000034132572,0.00011107882,0.0014554979],"genre_scores_gemma":[0.821381,0.000044476536,0.17600141,0.0008306252,0.000017484708,0.00015382054,0.000025839756,0.000028780827,0.0015165656],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999247,0.000007342555,0.00019341132,0.00032671276,0.00007748365,0.00014806277],"domain_scores_gemma":[0.9994856,0.000040207484,0.000066210145,0.00029289565,0.00007045626,0.000044624107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000058014877,0.00011709578,0.00018296801,0.00012732534,0.00011411338,0.000012482933,0.00006277477,0.000042743864,0.0000034879959],"category_scores_gemma":[0.000028740304,0.000106978856,0.000063220854,0.00018017455,0.00006824657,0.00007765707,0.00008814953,0.00015120389,6.13296e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024322311,0.000255028,0.0048446003,0.00046508826,0.000011135434,0.0000017079345,0.000084912084,0.000649237,0.9800057,0.00094828627,0.0013178043,0.011173312],"study_design_scores_gemma":[0.0021503153,0.00016309126,0.034576595,0.0001310828,0.00016669492,0.00007532347,0.000057150708,0.8885784,0.066324,0.002402816,0.005156317,0.00021820991],"about_ca_topic_score_codex":0.0000063774246,"about_ca_topic_score_gemma":7.943368e-7,"teacher_disagreement_score":0.9136817,"about_ca_system_score_codex":0.0000122144465,"about_ca_system_score_gemma":0.000020860933,"threshold_uncertainty_score":0.4362471},"labels":[],"label_agreement":null},{"id":"W4411661858","doi":"10.1007/s00415-025-13201-1","title":"Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration","year":2025,"lang":"en","type":"article","venue":"Journal of Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; NOSM University; Women and Children’s Health Research Institute; University of Alberta; Centre for Addiction and Mental Health; Toronto Public Health; Sunnybrook Health Science Centre; Western University; Bruyère; Ottawa Hospital; Health Sciences Centre; University Health Network; Wilfrid Laurier University; Montreal Neurological Institute and Hospital; Baycrest Hospital; McGill University; University of Ottawa; Ontario Brain Institute; Toronto Western Hospital; Canada Research Chairs","funders":"","keywords":"Neuroinflammation; Neurodegeneration; Neurology; Neuroradiology; Neuroscience; Diffusion MRI; Medicine; Psychology; Magnetic resonance imaging; Pathology; Internal medicine; Inflammation; Disease","score_opus":0.030498215015040117,"score_gpt":0.3328593692701872,"score_spread":0.3023611542551471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411661858","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78556025,0.000017630533,0.0062748767,0.20752339,0.00017821243,0.00021169648,0.0000018926421,0.000043306267,0.00018873288],"genre_scores_gemma":[0.98237085,0.000060071092,0.0025452205,0.0140793165,0.000121703626,0.000009647058,0.00000946029,0.000022270708,0.0007814837],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988768,0.000059161885,0.000488152,0.00021273427,0.00019248846,0.00017064833],"domain_scores_gemma":[0.9991127,0.0000453761,0.00017051546,0.0003613467,0.0002174825,0.00009256606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010925554,0.00012087425,0.00022959552,0.0003308424,0.000084123334,0.000013341985,0.00017673933,0.00008317867,0.000024876901],"category_scores_gemma":[0.000093224924,0.00009119212,0.00010788903,0.0002109976,0.00004449696,0.00009961161,0.000090686495,0.00043703587,0.000006519757],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093864696,0.0002238657,0.01244522,0.000027514863,0.000030688323,0.00020387779,0.00023325319,0.001111351,0.9340273,0.0037102697,0.043891218,0.0031567917],"study_design_scores_gemma":[0.00529937,0.0046380507,0.43774423,0.00012726556,0.00035348657,0.0048180344,0.000029420316,0.010828596,0.15527558,0.019446418,0.36105648,0.00038306665],"about_ca_topic_score_codex":0.0000021527137,"about_ca_topic_score_gemma":0.0000010088453,"teacher_disagreement_score":0.77875173,"about_ca_system_score_codex":0.000019120856,"about_ca_system_score_gemma":0.00004466805,"threshold_uncertainty_score":0.37187067},"labels":[],"label_agreement":null},{"id":"W4411729192","doi":"10.1016/j.neuroimage.2025.121347","title":"Comparison of post-stroke white matter assessment using disconnectome-symptom mapping versus quantitative diffusion MRI","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Center for Medical Rehabilitation Research; National Institute of General Medical Sciences; National Institutes of Health; Deutsche Forschungsgemeinschaft; National Institute of Child Health and Human Development; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs","keywords":"White matter; Diffusion MRI; Stroke (engine); Diffusion; Medicine; Psychology; Physical medicine and rehabilitation; Radiology; Magnetic resonance imaging; Physics","score_opus":0.10560227963598093,"score_gpt":0.44323627140923383,"score_spread":0.33763399177325293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411729192","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8129487,0.000051134197,0.17443584,0.003218542,0.0001791516,0.00057497923,0.000059615173,0.00014011329,0.008391919],"genre_scores_gemma":[0.90532464,0.000017808232,0.093214594,0.0006716694,0.000020294,0.000024754752,0.000030320669,0.000028061135,0.000667863],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99871296,0.00005322287,0.00040115835,0.00039568995,0.00020932734,0.00022763567],"domain_scores_gemma":[0.9989397,0.0001681794,0.0001876466,0.0005043373,0.00014001192,0.00006013406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007286855,0.00018408161,0.00039948986,0.0002576632,0.00012589843,0.000024038543,0.0001424543,0.000045934194,0.00007194501],"category_scores_gemma":[0.000052908315,0.00017354629,0.00012244454,0.00033722745,0.00012167936,0.000112306356,0.00017172385,0.00031563855,0.000009954262],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018853768,0.00032931662,0.30183887,0.00013052014,0.000028278713,0.0000109136,0.0001616679,0.00006643169,0.6944956,0.0015472417,0.0007285427,0.0004740325],"study_design_scores_gemma":[0.0031385424,0.0006098629,0.91814923,0.0004678218,0.0002590626,0.00001545371,0.0009666234,0.037340153,0.032750662,0.0002523411,0.005716309,0.00033391797],"about_ca_topic_score_codex":0.000018844286,"about_ca_topic_score_gemma":0.0000018249971,"teacher_disagreement_score":0.661745,"about_ca_system_score_codex":0.00006979466,"about_ca_system_score_gemma":0.00006507619,"threshold_uncertainty_score":0.7077012},"labels":[],"label_agreement":null},{"id":"W4411894088","doi":"10.1002/mrm.30620","title":"Myelin water and tensor‐valued diffusion imaging: (How) are they related?","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Collaboration On Repair Discoveries; Philips (Canada); University of British Columbia","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Multiple Sclerosis Society of Canada; Michael Smith Health Research BC","keywords":"Diffusion MRI; Fractional anisotropy; White matter; Myelin; Pathological; Tractography; Pathology; Abnormality; Correlation; Multiple sclerosis; Medicine; Neuroscience; Biology; Magnetic resonance imaging; Central nervous system; Radiology; Mathematics","score_opus":0.024904762421955735,"score_gpt":0.3171838362803847,"score_spread":0.292279073858429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411894088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7043558,0.02854681,0.0011386105,0.25210288,0.00019656986,0.0015334827,0.000004880262,0.0003790894,0.0117418915],"genre_scores_gemma":[0.9753588,0.0035516354,0.0033859585,0.003915884,0.00008218865,0.00013074077,0.00001902793,0.00003169097,0.013524068],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986003,0.000043097978,0.0003522523,0.00047636314,0.00021425865,0.0003136958],"domain_scores_gemma":[0.99918973,0.00007826659,0.00005439329,0.00051700434,0.000076110286,0.00008450023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002621602,0.00019871019,0.0004018404,0.0002319643,0.00008124245,0.000011070771,0.0001270571,0.00007069314,0.00008247803],"category_scores_gemma":[0.00024965958,0.00012849837,0.000032122218,0.000261663,0.0003044739,0.000042851185,0.000110524685,0.0003883816,0.000005735464],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029042756,0.00030622724,0.4369528,0.00034586428,0.000008572115,0.00048593376,0.0012031957,0.0000032303417,0.088868074,0.0050163963,0.024931613,0.4415877],"study_design_scores_gemma":[0.0043614777,0.00027797773,0.598391,0.0022798094,0.00009231266,0.00016507185,0.00047626457,0.005102205,0.0017147253,0.022551034,0.3643369,0.00025119432],"about_ca_topic_score_codex":0.00006382974,"about_ca_topic_score_gemma":0.000007737456,"teacher_disagreement_score":0.44133648,"about_ca_system_score_codex":0.000046586218,"about_ca_system_score_gemma":0.000017349472,"threshold_uncertainty_score":0.5240012},"labels":[],"label_agreement":null},{"id":"W4412166637","doi":"10.1017/cjn.2025.10174","title":"E.2 Isolated restricted diffusion at admission predicts survival in patients of glioblastoma (IRD-GB) – a prospective pilot study","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Glioblastoma; Prospective cohort study; Internal medicine; Oncology; Medicine; Diffusion; Cancer research; Physics; Thermodynamics","score_opus":0.04163984647954227,"score_gpt":0.31332197764372854,"score_spread":0.27168213116418627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412166637","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99621236,0.00013667565,0.00005867225,0.0016424021,0.0003158092,0.00067638233,0.000009846216,0.000029456301,0.00091839535],"genre_scores_gemma":[0.9985308,0.00010540303,0.0006323114,0.0006302758,0.00004232237,0.0000074909285,3.8076521e-7,0.000009912591,0.000041068597],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9962292,0.00060805085,0.0010617889,0.00056105753,0.00073418266,0.0008057575],"domain_scores_gemma":[0.99705344,0.0003581119,0.0007404002,0.00020623193,0.0006600124,0.000981787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014738033,0.0002801878,0.00061010645,0.0015577617,0.0011948833,0.000111187925,0.0010416256,0.000103234896,0.000042402913],"category_scores_gemma":[0.002505867,0.00019090198,0.00011952936,0.0029788488,0.0024507127,0.00039466465,0.00014717306,0.0010469086,5.8692115e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009877991,0.00046451745,0.99569374,0.00000842062,0.000009072353,0.000964449,0.00013140787,0.00022080242,0.00027498134,0.00014437661,0.00019107257,0.00090937555],"study_design_scores_gemma":[0.0010927002,0.1644326,0.82942164,0.00010113553,0.00003695093,0.0007939777,0.00007633832,0.00074304536,0.00014820563,0.00287233,0.00016396161,0.00011709113],"about_ca_topic_score_codex":0.0008830106,"about_ca_topic_score_gemma":0.02012769,"teacher_disagreement_score":0.16627206,"about_ca_system_score_codex":0.00041811808,"about_ca_system_score_gemma":0.002014146,"threshold_uncertainty_score":0.9977524},"labels":[],"label_agreement":null},{"id":"W4412166743","doi":"10.1017/cjn.2025.10310","title":"P.165 Comparison of preoperative diffusion tensor imaging tractography platforms for intrinsic brain lesions","year":2025,"lang":"en","type":"article","venue":"Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Alberta Hospital Edmonton; Workers Compensation Board of Alberta","funders":"","keywords":"Diffusion MRI; Tractography; Medicine; Neuroscience; Nuclear magnetic resonance; Radiology; Psychology; Magnetic resonance imaging; Physics","score_opus":0.073518601362403,"score_gpt":0.3690019808808544,"score_spread":0.2954833795184514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412166743","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9804995,0.0008360512,0.002945546,0.013986068,0.00028205034,0.00044610168,0.000019858653,0.000026059193,0.00095873594],"genre_scores_gemma":[0.9835791,0.00016063907,0.012120522,0.0040027965,0.000084466796,0.000010148916,7.4019994e-7,0.000009096718,0.000032484222],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99722874,0.00016029908,0.0009766353,0.0004384948,0.0004124626,0.00078334584],"domain_scores_gemma":[0.99663484,0.0009910945,0.00071464747,0.00016750333,0.000657708,0.0008342113],"candidate_categories":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.0016432251,0.00026198488,0.0006285563,0.0013090795,0.001973512,0.00018982592,0.0010122071,0.00011141625,0.000027165192],"category_scores_gemma":[0.0024456556,0.0001653689,0.00032667632,0.001577469,0.004626173,0.0005143215,0.000057777615,0.0009234033,2.8128247e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013338275,0.00008740403,0.9794962,0.000019493798,0.00001230055,0.00021650431,0.00021884117,0.0004569199,0.00045700042,0.0045619574,0.001860843,0.012479199],"study_design_scores_gemma":[0.0011500822,0.051234107,0.84335256,0.00031883226,0.0001633662,0.007025244,0.0009175157,0.0072438247,0.0020810168,0.075522535,0.010570546,0.00042035623],"about_ca_topic_score_codex":0.00026649423,"about_ca_topic_score_gemma":0.004252645,"teacher_disagreement_score":0.13614358,"about_ca_system_score_codex":0.00011684216,"about_ca_system_score_gemma":0.0019926452,"threshold_uncertainty_score":0.9993258},"labels":[],"label_agreement":null},{"id":"W4412392585","doi":"10.1038/s41597-025-05350-9","title":"In vivo submillimeter diffusion MRI dataset of 9 macaque brains curated for tractography","year":2025,"lang":"en","type":"article","venue":"Scientific Data","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"HORIZON EUROPE Framework Programme; Université de Bordeaux; Alliance de recherche numérique du Canada; Conseil Régional Aquitaine; European Commission","keywords":"Macaque; Tractography; Diffusion MRI; Neuroscience; Computer science; Biology; Nuclear magnetic resonance; Magnetic resonance imaging; Medicine; Physics; Radiology","score_opus":0.11451306423913672,"score_gpt":0.4241875787324237,"score_spread":0.309674514493287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412392585","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12930393,0.00029307778,0.37439775,0.018027492,0.0013250671,0.0057388265,0.46851596,0.0003274571,0.002070419],"genre_scores_gemma":[0.54517883,0.0002492461,0.18943024,0.00374334,0.00009423334,0.00033963638,0.25344628,0.000064224645,0.007453929],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989466,0.0000118669095,0.00025899473,0.0005169056,0.0001139572,0.0001516979],"domain_scores_gemma":[0.9980247,0.000072579,0.00006780041,0.0017403008,0.000056620585,0.00003799158],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002897019,0.0000764698,0.00014971643,0.00031777442,0.00007354404,0.000026906657,0.00049092947,0.000032430475,0.000049221057],"category_scores_gemma":[0.00011200889,0.00006603564,0.000030212967,0.00094385043,0.00018083966,0.00019409758,0.0002692876,0.00008853611,0.000002153737],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037768255,0.00024278669,0.0012148903,0.00008223394,0.0000067616775,0.0000021116482,0.000014624788,5.272583e-7,0.20786153,0.001094669,0.7876167,0.0018253857],"study_design_scores_gemma":[0.0005706169,0.000023987535,0.0015034316,0.00009797268,0.00003690633,0.0000026883229,0.000021790653,0.0029135349,0.06616281,0.0023674439,0.9262298,0.00006903692],"about_ca_topic_score_codex":0.000023614746,"about_ca_topic_score_gemma":0.00002832444,"teacher_disagreement_score":0.41587493,"about_ca_system_score_codex":0.000010026727,"about_ca_system_score_gemma":0.000052872107,"threshold_uncertainty_score":0.26928553},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"dataset","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"agree"},{"id":"W4412413781","doi":"10.1007/s11357-025-01773-9","title":"Testing retrogenesis and physiological explanations for tract-wise white matter aging: links to developmental order, fiber calibre, and vascularization","year":2025,"lang":"en","type":"article","venue":"GeroScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Caliber; Fiber; Biology; Anatomy; White (mutation); Order (exchange); Neuroscience; Medicine; Genetics; Engineering; Magnetic resonance imaging; Mechanical engineering; Chemistry","score_opus":0.09633646232879,"score_gpt":0.3509578979395293,"score_spread":0.2546214356107393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412413781","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7080325,0.000034811408,0.2847276,0.005973651,0.00002198165,0.0006719516,0.00001702144,0.00011680861,0.0004036433],"genre_scores_gemma":[0.627012,0.000010841292,0.36785963,0.0039301114,0.000015031485,0.00017639369,0.0000129130885,0.000007635518,0.0009754275],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993894,0.0000065788745,0.00011110681,0.00029729513,0.00006694812,0.0001286867],"domain_scores_gemma":[0.9996926,0.000059745595,0.000025503987,0.00009650889,0.00006597117,0.00005963331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007373604,0.00007188994,0.00009268049,0.000066482615,0.00020422887,0.000030572086,0.00005139528,0.000039447918,0.0000065960103],"category_scores_gemma":[0.00016296204,0.00006241238,0.000012422812,0.00041713967,0.00006844737,0.000071712,0.000063728134,0.00006633917,0.0000018173412],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025814597,0.00022994677,0.45061108,0.00014990628,0.000011157435,0.0000041248445,0.00033166967,0.00010184014,0.4874282,0.001285366,0.00709065,0.052730244],"study_design_scores_gemma":[0.00033649208,0.00007638626,0.9742126,0.00010034048,0.000029180628,0.00003506544,0.00004248972,0.0026295886,0.010303171,0.0007070203,0.011372578,0.00015512863],"about_ca_topic_score_codex":0.0000033464783,"about_ca_topic_score_gemma":3.4037453e-7,"teacher_disagreement_score":0.5236015,"about_ca_system_score_codex":0.000019184252,"about_ca_system_score_gemma":0.000035846217,"threshold_uncertainty_score":0.2545103},"labels":[],"label_agreement":null},{"id":"W4412530434","doi":"10.1371/journal.pbio.3003241","title":"Personalised regional modelling predicts tau progression in the human brain","year":2025,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Institut Universitaire de Gériatrie de Montréal","funders":"Engineering and Physical Sciences Research Council; Greta och Johan Kocks stiftelser; Fonds de Recherche du Québec - Santé; Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse; National Institute of Mental Health; Cure Alzheimer's Fund; Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse; F. Hoffmann-La Roche; Hjärnfonden; National Institute on Aging; Alzheimer's Association; Wellcome Trust; GHR Foundation","keywords":"Biology; Neuroscience; Human brain; Computational biology","score_opus":0.1507732709786695,"score_gpt":0.4172186440886334,"score_spread":0.2664453731099639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412530434","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8655515,0.0003553467,0.039883073,0.088246234,0.000021933618,0.0010632699,0.000008742591,0.00022417236,0.0046457755],"genre_scores_gemma":[0.98687375,0.00003109346,0.007413125,0.0050202296,0.000054366552,0.00020304523,0.00008402321,0.000006088933,0.00031429398],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.999478,0.000046263234,0.0001165113,0.00018649545,0.0000506763,0.00012207523],"domain_scores_gemma":[0.99962175,0.00009766397,0.000030356863,0.00020889041,0.000024752711,0.000016612565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009899899,0.00006283984,0.000103253486,0.00006905036,0.00007621793,0.0000035401708,0.0001103564,0.00005570462,0.000008481882],"category_scores_gemma":[0.000034049484,0.000040417566,0.00002883734,0.00015440636,0.00009586418,0.000013390213,0.000027719221,0.00018869784,0.0000022966813],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021456298,0.0016847362,0.10374852,0.00021287518,0.000064281005,0.00003130344,0.0014336167,0.00013032659,0.4589981,0.37557948,0.04818425,0.00971792],"study_design_scores_gemma":[0.0048494088,0.00085011096,0.053717077,0.0016207725,0.00018248815,0.00013802743,0.00037933857,0.050262738,0.0096098455,0.31465018,0.5631813,0.0005587218],"about_ca_topic_score_codex":0.000008216202,"about_ca_topic_score_gemma":0.0000022549295,"teacher_disagreement_score":0.514997,"about_ca_system_score_codex":0.000018209023,"about_ca_system_score_gemma":0.000024673613,"threshold_uncertainty_score":0.16481805},"labels":[],"label_agreement":null},{"id":"W4412573094","doi":"10.1007/s11357-025-01787-3","title":"Variations in perfusion detectable in advance of microstructure in white matter aging","year":2025,"lang":"en","type":"article","venue":"GeroScience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Baycrest Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Microstructure; White (mutation); Medicine; Materials science; Chemistry; Magnetic resonance imaging; Metallurgy; Radiology","score_opus":0.01655770807556216,"score_gpt":0.32980770114065394,"score_spread":0.31324999306509177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412573094","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96073717,0.000070554604,0.03524351,0.0023593314,0.000038259826,0.00030977494,0.0000039777096,0.000022126156,0.0012152654],"genre_scores_gemma":[0.9746915,0.000026572146,0.024208672,0.00061979477,0.0000027332849,0.00002937832,0.0000010357232,0.0000036868962,0.00041661237],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99936634,0.000011248837,0.00018593708,0.00022005998,0.00006685838,0.00014954936],"domain_scores_gemma":[0.9996917,0.000025544956,0.000038524602,0.00021008171,0.000019272818,0.0000148772115],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000109629415,0.000055571232,0.00011534572,0.00025993286,0.000026029082,0.00000567138,0.00010400136,0.00002538322,0.000015623817],"category_scores_gemma":[0.000047136844,0.00005407996,0.000012548354,0.0011681902,0.00006024501,0.00009103431,0.000060199225,0.00014801028,0.0000013930706],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000005923038,0.000033173772,0.6725152,0.000019539877,6.105624e-8,0.000002165905,0.00013981828,0.00023398621,0.32535264,0.00032621933,0.000026447527,0.0013448136],"study_design_scores_gemma":[0.0002970486,0.000011233032,0.9687508,0.00025074367,0.0000012968745,0.0000047309068,0.00003607984,0.002563776,0.025113683,0.002466294,0.00045518894,0.00004917441],"about_ca_topic_score_codex":0.000053610693,"about_ca_topic_score_gemma":0.000072159586,"teacher_disagreement_score":0.30023897,"about_ca_system_score_codex":0.000059309536,"about_ca_system_score_gemma":0.000047240334,"threshold_uncertainty_score":0.22053167},"labels":[],"label_agreement":null},{"id":"W4412589709","doi":"10.1038/s44400-025-00024-0","title":"Smoking predicts brain atrophy in 10,134 healthy individuals and is potentially influenced by body mass index","year":2025,"lang":"en","type":"article","venue":"npj Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada); AXYS Technologies (Canada)","funders":"National Institute on Aging; National Institutes of Health","keywords":"Precuneus; White matter; Atrophy; Brain size; Temporal lobe; Body mass index; Medicine; Neuroimaging; Neurodegeneration; Imaging biomarker; Internal medicine; Posterior cingulate; Dementia; Cardiology; Psychology; Magnetic resonance imaging; Neuroscience; Cortex (anatomy); Radiology; Cognition; Epilepsy","score_opus":0.0178539470451032,"score_gpt":0.3365159294493598,"score_spread":0.31866198240425664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412589709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92682886,0.0013306558,0.038340986,0.02772635,0.00009033001,0.0015427298,0.00010750536,0.00035195763,0.0036806318],"genre_scores_gemma":[0.98366284,0.00017622502,0.0061933557,0.008879336,0.000024523477,0.00011507779,0.000059694572,0.000020504105,0.00086845004],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987045,0.000034162218,0.0003533755,0.00040306657,0.00021437157,0.00029050914],"domain_scores_gemma":[0.99938875,0.000046678226,0.00010121502,0.00032105198,0.000048124326,0.00009416877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019009612,0.00015325403,0.0002267771,0.00021253855,0.00010785276,0.00003513428,0.00012728354,0.000093935276,0.00007674814],"category_scores_gemma":[0.000056304227,0.00015967264,0.000038552946,0.00039504044,0.00007308567,0.00010133514,0.00011514884,0.0002647205,0.000004742198],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001089909,0.00020607021,0.8166707,0.00018387231,0.00014145412,0.000017455592,0.000099509074,0.0000087270555,0.072993875,0.0012426716,0.09549197,0.012834659],"study_design_scores_gemma":[0.005764251,0.00047129494,0.62965035,0.0005268175,0.00033312777,0.000015385262,0.00007348154,0.0007824524,0.016953439,0.012662036,0.3323215,0.0004458665],"about_ca_topic_score_codex":0.000048156257,"about_ca_topic_score_gemma":0.0000029947723,"teacher_disagreement_score":0.2368295,"about_ca_system_score_codex":0.00004759586,"about_ca_system_score_gemma":0.000078813246,"threshold_uncertainty_score":0.6511261},"labels":[],"label_agreement":null},{"id":"W4412602088","doi":"10.1001/jamanetworkopen.2025.22211","title":"Distinct Patterns of Weight Gain, Age, and Subcortical Microstructure in Early Adolescence","year":2025,"lang":"en","type":"article","venue":"JAMA Network Open","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"National Institute of Diabetes and Digestive and Kidney Diseases","keywords":"Weight gain; Medicine; Body mass index; Cohort; Overweight; Demography; Percentile; Cohort study; Longitudinal study; Obesity; Synaptic pruning; Weight change; Gerontology; Internal medicine; Psychology; Weight loss; Body weight; Pathology","score_opus":0.027604382389156076,"score_gpt":0.33935597113193594,"score_spread":0.31175158874277986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412602088","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9834433,0.00021116476,0.010399554,0.003203162,0.00003374218,0.00076554704,0.000013122822,0.000034668632,0.0018956899],"genre_scores_gemma":[0.99181235,0.0001388799,0.006594528,0.0009628406,0.0000556287,0.000035343975,0.0000131721845,0.000009571313,0.00037771207],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993135,0.0000256685,0.00021430441,0.0002285045,0.000058050333,0.00015998287],"domain_scores_gemma":[0.9995283,0.00005813495,0.000051977117,0.0002833918,0.000030380103,0.000047850644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009797327,0.000086834385,0.00022180386,0.000032176755,0.000035695462,0.000031984197,0.00018769162,0.00005634504,0.000011335508],"category_scores_gemma":[0.00003767398,0.00007444362,0.000022422451,0.00022841615,0.00006758021,0.00005808501,0.00027619037,0.00023528637,6.885363e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012160401,0.000040771367,0.98433477,0.000056427663,0.00000577063,0.000060622362,0.00003112863,0.0000038346193,0.00071879214,0.0045062923,0.00224862,0.00787137],"study_design_scores_gemma":[0.00059301115,0.00003732797,0.9899566,0.00067603076,0.000018824901,0.000012814659,0.000006680678,0.0001695546,0.00046108765,0.0041492134,0.003855878,0.00006295784],"about_ca_topic_score_codex":0.00009064317,"about_ca_topic_score_gemma":0.000032610464,"teacher_disagreement_score":0.008368974,"about_ca_system_score_codex":0.000016147153,"about_ca_system_score_gemma":0.000025539124,"threshold_uncertainty_score":0.30357227},"labels":[],"label_agreement":null},{"id":"W4412627997","doi":"10.1371/journal.pone.0327828","title":"Assessing quantitative MRI techniques using multimodal comparisons","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Concordia University; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Heart And Stroke Foundation Of Quebec; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Bundesministerium für Bildung und Forschung; Horizon 2020 Framework Programme; Deutsche Forschungsgemeinschaft; Natural Sciences and Engineering Research Council of Canada; European Commission; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Heart and Stroke Foundation of Canada","keywords":"White matter; Fractional anisotropy; Neuroscience; Magnetization transfer; Context (archaeology); Neuroimaging; Grey matter; Diffusion MRI; Brain tissue; Contrast (vision); Cognitive neuroscience; Brain mapping; Computer science; Nuclear magnetic resonance; Magnetic resonance imaging; Artificial intelligence; Cognition; Biology; Physics; Medicine","score_opus":0.31408587125337306,"score_gpt":0.4598301876674588,"score_spread":0.14574431641408575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412627997","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28079772,0.00013826799,0.70471734,0.003818789,0.000012154266,0.0007904917,0.0000078045105,0.0008898171,0.008827607],"genre_scores_gemma":[0.40780517,0.000025339827,0.5915503,0.00037797613,0.000017666072,0.000043219192,0.000007517462,0.000012179049,0.00016061988],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99925816,0.000021061,0.00019125504,0.00023616053,0.00013773346,0.00015560641],"domain_scores_gemma":[0.99936914,0.00008891643,0.0000675982,0.00029631838,0.00013325358,0.000044796554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000072520976,0.00010533988,0.0002606705,0.00013676968,0.00014076199,0.00003336627,0.00007776306,0.000047238373,0.000011946334],"category_scores_gemma":[0.000088209796,0.00010478687,0.000043136555,0.00030601895,0.00008816213,0.00012969207,0.00006139106,0.00023566124,0.0000049218092],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003705671,0.0022806968,0.021566696,0.00019799998,0.00013295791,0.000009692728,0.000050357667,0.00000854095,0.95942146,0.013333457,0.0009196217,0.0020414395],"study_design_scores_gemma":[0.00043973504,0.00011582636,0.008838924,0.0018760575,0.00047825286,0.0000070811006,0.00019875837,0.06447205,0.91831994,0.0029635304,0.0020631994,0.00022664412],"about_ca_topic_score_codex":0.000024527855,"about_ca_topic_score_gemma":0.0000010249429,"teacher_disagreement_score":0.12700745,"about_ca_system_score_codex":0.00007222784,"about_ca_system_score_gemma":0.00006510088,"threshold_uncertainty_score":0.42730847},"labels":[],"label_agreement":null},{"id":"W4412831590","doi":"10.1162/imag.a.115","title":"High resolution diffusion tensor imaging of the human cortex reveals non-linear trajectories over the healthy lifespan","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Diffusion MRI; Diffusion; Cortex (anatomy); High resolution; Tensor (intrinsic definition); Resolution (logic); Neuroscience; Psychology; Physics; Medicine; Mathematics; Computer science; Artificial intelligence; Geology; Magnetic resonance imaging; Geometry; Radiology","score_opus":0.03466408011579197,"score_gpt":0.36411149534523335,"score_spread":0.3294474152294414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412831590","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9472163,0.00011089828,0.019739643,0.030825758,0.0005558061,0.0009345288,0.000016803273,0.00021177097,0.00038851038],"genre_scores_gemma":[0.9893891,0.000045764235,0.001184532,0.008584491,0.00006877495,0.000037771028,0.0000017339174,0.000017359796,0.0006704556],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99846107,0.00006949283,0.00037800852,0.00045245857,0.0003348372,0.0003041262],"domain_scores_gemma":[0.9986032,0.00011628964,0.00022300586,0.000883713,0.00011715786,0.00005662534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028513008,0.00015469998,0.00020042933,0.000103261,0.00077999383,0.000034590787,0.0004744382,0.000017889226,0.0000034374425],"category_scores_gemma":[0.00035675053,0.00009547483,0.000092111695,0.00090621115,0.0007783188,0.00012947911,0.00023947882,0.00034458353,8.28931e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022833457,0.00011053777,0.36049402,0.000064870204,0.0000011143675,0.0000046867226,0.000078530116,0.0000512066,0.63118064,0.004460011,0.0026348953,0.00089667994],"study_design_scores_gemma":[0.00034775413,0.00003102822,0.97268856,0.00021489628,0.000029397772,0.000034178905,0.000030294417,0.010734317,0.0071342755,0.001695528,0.006969844,0.000089938636],"about_ca_topic_score_codex":0.00016295,"about_ca_topic_score_gemma":0.0000018075,"teacher_disagreement_score":0.6240463,"about_ca_system_score_codex":0.000055152817,"about_ca_system_score_gemma":0.00009828114,"threshold_uncertainty_score":0.5999161},"labels":[],"label_agreement":null},{"id":"W4412839143","doi":"10.1002/hbm.70265","title":"Enhanced Detection of Age‐Related and Cognitive Declines Using Automated Hippocampal‐To‐Ventricle Ratio in Alzheimer's Patients","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Université Laval; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; National Institutes of Health; Health Canada; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Fondation Brain Canada; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Atrophy; Segmentation; Fornix; Neuroimaging; Psychology; Biomarker; Alzheimer's disease; Neuroscience; Internal medicine; Audiology; Medicine; Hippocampus; Disease; Artificial intelligence; Computer science; Chemistry","score_opus":0.06619587824073389,"score_gpt":0.3785401440390851,"score_spread":0.3123442657983512,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412839143","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9410772,0.00007167277,0.05745574,0.00020558918,0.000021058775,0.000760179,0.0000027512492,0.00021964549,0.00018616793],"genre_scores_gemma":[0.9973726,0.000003422342,0.0021123765,0.00040743765,0.000008187351,0.000039901563,0.00001886886,0.0000123534655,0.00002484383],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99918646,0.0000390895,0.00032724725,0.00023531032,0.000076262746,0.00013561257],"domain_scores_gemma":[0.9995305,0.0001026775,0.00010410123,0.000118349664,0.00010577302,0.00003862145],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000105629515,0.00009966228,0.00019870106,0.00034246832,0.000113357964,0.000009774793,0.000037607224,0.00004922938,0.000004538386],"category_scores_gemma":[0.0002068127,0.00010877652,0.000027479435,0.0006483349,0.00005803904,0.000055830827,0.00004865231,0.00011271902,9.612687e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003715714,0.00013659167,0.010506221,0.000056590456,0.00005018542,0.000005179047,0.00052160234,0.00007543011,0.9767823,0.00029831598,0.00003663278,0.011493757],"study_design_scores_gemma":[0.0031148659,0.00017847487,0.8499932,0.0015425063,0.00015030388,0.0000050521226,0.00028945232,0.023268703,0.11684922,0.0042032115,0.00016603956,0.00023895557],"about_ca_topic_score_codex":0.000028180826,"about_ca_topic_score_gemma":0.000010518981,"teacher_disagreement_score":0.85993314,"about_ca_system_score_codex":0.00003349235,"about_ca_system_score_gemma":0.000017776385,"threshold_uncertainty_score":0.44357777},"labels":[],"label_agreement":null},{"id":"W4412852879","doi":"10.1111/jnc.70167","title":"In Vivo Cortical Microstructure: Relationships With Tauopathy and Cognitive Impairment in the Elderly","year":2025,"lang":"en","type":"article","venue":"Journal of Neurochemistry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Carleton University; Centre for Addiction and Mental Health","funders":"","keywords":"Psychology; Tauopathy; Diffusion MRI; Neuroscience; Dementia; Positron emission tomography; Cognitive decline; Fractional anisotropy; Cognitive impairment; Cognition; Audiology; Medicine; Internal medicine; Magnetic resonance imaging; Radiology; Disease; Neurodegeneration","score_opus":0.023576526742192027,"score_gpt":0.32302054769049326,"score_spread":0.29944402094830125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412852879","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99315774,0.00011563518,0.0008861211,0.005296481,0.000008935097,0.00013433748,0.0000022340596,0.000004641478,0.0003938454],"genre_scores_gemma":[0.99808556,0.000042994558,0.0009245862,0.00086507195,0.000021737707,0.0000068200775,5.180673e-7,0.0000042838615,0.000048409438],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9995047,0.000027423444,0.00020861746,0.00009041477,0.000091841415,0.000077004566],"domain_scores_gemma":[0.99956244,0.00018213563,0.00008373753,0.000086122396,0.000055141965,0.000030446847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011253238,0.000063376196,0.000115804265,0.000052829517,0.000034484707,0.000010524205,0.000057323352,0.000026446756,0.000003211622],"category_scores_gemma":[0.00014254764,0.000040874293,0.000021179301,0.00019844435,0.000068815076,0.00003762412,0.00001353266,0.00064843526,7.488566e-8],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012460767,0.00065310707,0.30706444,0.00020468267,0.00002964314,0.0019514444,0.00058483327,0.000011808983,0.68359536,0.00047573482,0.0032094363,0.00097344397],"study_design_scores_gemma":[0.0028187714,0.00061854854,0.933408,0.00071271777,0.0001305468,0.0068981615,0.0009686664,0.000059197577,0.04973412,0.003148033,0.0013971573,0.00010605833],"about_ca_topic_score_codex":7.269487e-7,"about_ca_topic_score_gemma":0.0000010374678,"teacher_disagreement_score":0.6338612,"about_ca_system_score_codex":0.000018199265,"about_ca_system_score_gemma":0.000059210397,"threshold_uncertainty_score":0.28171647},"labels":[],"label_agreement":null},{"id":"W4412921945","doi":"10.1101/2025.07.24.666667","title":"The role of white matter myelin in structural-functional network coupling","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McGill University; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Canadian Institutes of Health Research; Killam Trusts; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"White matter; Coupling (piping); Myelin; Functional connectivity; Neuroscience; Psychology; Computer science; Materials science; Medicine; Composite material; Central nervous system; Magnetic resonance imaging","score_opus":0.017952489269755324,"score_gpt":0.2643323456352827,"score_spread":0.24637985636552737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412921945","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97633487,0.0042713936,0.011943987,0.0033008154,0.0009084665,0.0023188689,0.00022214682,0.0005410411,0.00015843919],"genre_scores_gemma":[0.9828026,0.00028731732,0.015887955,0.0003407064,0.00033259654,0.00026816296,7.373241e-7,0.000048895497,0.00003097522],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983295,0.000027498776,0.0005309039,0.000541743,0.00023047655,0.00033984182],"domain_scores_gemma":[0.9981698,0.000108640306,0.00029704074,0.001053606,0.00029097853,0.00007994687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028964115,0.00028556387,0.00040322045,0.00012875447,0.0002175966,0.000033390734,0.00028596542,0.00021441744,0.000033063425],"category_scores_gemma":[0.0000621752,0.00024419764,0.00011838933,0.0004528099,0.000121306875,0.000040268304,0.0004918487,0.0008485472,0.000007543104],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017110935,0.000096521675,0.8807732,0.00046328583,0.00013124086,0.000014203434,0.000009582755,0.009091373,0.09721124,0.010289693,0.0017330821,0.000015482443],"study_design_scores_gemma":[0.00047133045,0.000024980645,0.92361647,0.0011805511,0.00013230422,4.817891e-8,0.0000037077953,0.016878815,0.03672684,0.00034683693,0.020196564,0.0004215305],"about_ca_topic_score_codex":0.000018219052,"about_ca_topic_score_gemma":0.0000016507071,"teacher_disagreement_score":0.0604844,"about_ca_system_score_codex":0.00013628369,"about_ca_system_score_gemma":0.0003134692,"threshold_uncertainty_score":0.99580914},"labels":[],"label_agreement":null},{"id":"W4413099917","doi":"10.1007/s00429-025-02998-2","title":"A thousand ways to tailor your tractography-based connectome","year":2025,"lang":"en","type":"letter","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Hôpitaux Universitaires de Genève; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Connectome; Tractography; Human Connectome Project; Computer science; Weighting; Connectomics; Diffusion MRI; Artificial intelligence; Data science; Functional connectivity; Psychology; Neuroscience; Magnetic resonance imaging; Physics; Medicine","score_opus":0.04690433661336975,"score_gpt":0.31654436477652365,"score_spread":0.2696400281631539,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413099917","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001869572,0.00016509213,0.2012848,0.7932317,0.00031447233,0.0012876294,0.00033576443,0.0004777962,0.0010331251],"genre_scores_gemma":[0.016310213,0.000017602177,0.009328965,0.9704133,0.0017171542,0.0001259992,0.0009420656,0.00005450158,0.0010901921],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988015,0.000017360391,0.00020746878,0.00055281055,0.0001833515,0.00023749059],"domain_scores_gemma":[0.9991783,0.0001321773,0.00009101468,0.0004336222,0.00008383112,0.00008104427],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000043085765,0.00029277493,0.00036281088,0.00036944554,0.00012757626,0.000039355855,0.00007384082,0.00043763843,0.000081421786],"category_scores_gemma":[0.00006196093,0.0002466206,0.00012116139,0.0003882334,0.000052770283,0.000035481873,0.00002618677,0.0010037958,0.0000027720503],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120308956,0.000010683552,0.00018008548,0.00022596172,0.000034792756,0.000031917276,0.000014767673,0.0000037660475,0.0033323658,0.00023924226,0.98125273,0.014553391],"study_design_scores_gemma":[0.0005392831,0.0002650231,0.002685415,0.0001438412,0.0002031736,0.00004710703,0.0000049023465,0.000025937145,0.000804176,0.004604427,0.9904516,0.00022511951],"about_ca_topic_score_codex":0.00001041016,"about_ca_topic_score_gemma":0.0000018146561,"teacher_disagreement_score":0.19195583,"about_ca_system_score_codex":0.000026810807,"about_ca_system_score_gemma":0.00006629183,"threshold_uncertainty_score":0.9999986},"labels":[],"label_agreement":null},{"id":"W4413159892","doi":"10.1016/j.media.2025.103743","title":"Exploring the robustness of TractOracle methods in RL-based tractography","year":2025,"lang":"en","type":"article","venue":"Medical Image Analysis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Robustness (evolution); Artificial intelligence; Computer science; Tractography; Computer vision; Diffusion MRI; Biology; Magnetic resonance imaging; Radiology; Medicine","score_opus":0.16667939381837615,"score_gpt":0.47539322498763364,"score_spread":0.3087138311692575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413159892","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10927947,0.000101672114,0.8809969,0.008753973,0.000022306363,0.00016428606,0.0000024102626,0.00006731368,0.0006116736],"genre_scores_gemma":[0.85109514,0.00011719543,0.14780708,0.00072472927,0.000023886392,0.00015657139,0.000013540723,0.000009831605,0.00005201148],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99880177,0.00012193253,0.0003938253,0.00023493086,0.000290578,0.00015697017],"domain_scores_gemma":[0.9987039,0.0005489022,0.00007830845,0.0005061504,0.00008259917,0.000080162274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073083676,0.00009963363,0.00040011905,0.00061182975,0.000044525004,0.000008818836,0.00021037574,0.00004259838,0.00015584494],"category_scores_gemma":[0.000593519,0.000067143585,0.00032681818,0.0041462462,0.00021294206,0.00007664188,0.000034372057,0.00035422636,4.8860255e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022548325,0.0029629795,0.13072555,0.00043037726,0.0016205319,0.00015460972,0.00029851086,0.00329453,0.0456391,0.0012827924,0.0013528271,0.81201273],"study_design_scores_gemma":[0.0018135064,0.000089746114,0.5667722,0.00039922944,0.0048485766,0.0000066085117,0.00044862434,0.30822706,0.10483779,0.0007847378,0.011446375,0.0003255254],"about_ca_topic_score_codex":0.00007768951,"about_ca_topic_score_gemma":0.000021691105,"teacher_disagreement_score":0.8116872,"about_ca_system_score_codex":0.000021317603,"about_ca_system_score_gemma":0.000077759534,"threshold_uncertainty_score":0.2738036},"labels":[],"label_agreement":null},{"id":"W4413183765","doi":"10.1101/2025.08.06.668521","title":"A Scalable Toolkit for Modeling 3D Surface-based Brain Geometry","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; University of British Columbia","funders":"National Institute on Aging; National Institutes of Health; National Health and Medical Research Council; Norges Forskningsråd; Medical University of South Carolina; National Imaging Facility; Bundesministerium für Bildung und Forschung; Australian Rotary Health; Swinburne University of Technology; University of New South Wales; Deutsche Forschungsgemeinschaft; John S. Dunn Foundation; European Commission; National Institute of Mental Health; Ministerio de Ciencia, Tecnología e Innovación; University of Texas Health Science Center at Houston","keywords":"Geometry; Surface (topology); Scalability; Computer science; Computer graphics (images); Mathematics; Database","score_opus":0.048447476899320184,"score_gpt":0.305939608424462,"score_spread":0.25749213152514183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413183765","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15715048,0.00072725525,0.8310091,0.0050894427,0.0003365189,0.0030633262,0.00087377575,0.0017123627,0.00003773999],"genre_scores_gemma":[0.5733905,0.00010072343,0.42258012,0.002540774,0.00031284723,0.00085302995,0.0000031467175,0.00014418765,0.00007466133],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997149,0.000051682313,0.0006003717,0.0012471925,0.0003112789,0.0006404813],"domain_scores_gemma":[0.9965703,0.00024806175,0.0002589408,0.0019389802,0.0007237234,0.00026001042],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006648038,0.00055237074,0.0008312237,0.00036023316,0.00022142798,0.0001168291,0.00047137457,0.0004804366,0.000021760161],"category_scores_gemma":[0.0006285564,0.0006132634,0.00029000093,0.0007312141,0.00008354097,0.00008226918,0.00035501126,0.00092011056,0.000012014013],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005342908,0.0013235642,0.009078532,0.008041701,0.00045590187,0.000068014655,0.0000066314337,0.056121763,0.90157396,0.0067741345,0.015963726,0.00005779924],"study_design_scores_gemma":[0.0022485992,0.00013607719,0.0013056819,0.002490358,0.00053983455,3.474285e-8,0.0000013824358,0.7205876,0.20895007,0.00006474581,0.062414125,0.0012614968],"about_ca_topic_score_codex":0.000030470233,"about_ca_topic_score_gemma":4.1658436e-7,"teacher_disagreement_score":0.69262385,"about_ca_system_score_codex":0.0003446628,"about_ca_system_score_gemma":0.0011259605,"threshold_uncertainty_score":0.9996319},"labels":[],"label_agreement":null},{"id":"W4413223952","doi":"10.21203/rs.3.rs-7247101/v1","title":"Pontine Functional Connectivity Gradients","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Pons; Neuroscience; Pontine nuclei; Cerebellum; Cerebral cortex; Biology; Functional connectivity; Psychology; Anatomy","score_opus":0.24161425691648258,"score_gpt":0.4992522449537585,"score_spread":0.2576379880372759,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413223952","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57120997,0.0028529153,0.14845139,0.07171248,0.0013206677,0.015712684,0.002094277,0.0036222974,0.18302333],"genre_scores_gemma":[0.9743918,0.0004448246,0.0054242965,0.00025373683,0.00040079575,0.001117947,0.0005740121,0.000035288478,0.017357254],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9979006,0.0001213147,0.00020522636,0.0006739312,0.00069846126,0.00040044333],"domain_scores_gemma":[0.99777555,0.0002915338,0.000052486575,0.0009589485,0.0007565079,0.00016496985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056539587,0.00017647176,0.00030697734,0.00042834342,0.00022232627,0.00003634677,0.00019867739,0.00018541241,0.00015583537],"category_scores_gemma":[0.00059834815,0.00016668216,0.00016680348,0.00046175093,0.00016161891,0.000030376752,0.0010227715,0.0020331785,0.000043568147],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017160205,0.0052760607,0.2305792,0.011495257,0.00053159276,0.00045777156,0.00029653448,0.00041625425,0.00754987,0.14253838,0.5122952,0.086847864],"study_design_scores_gemma":[0.0017176162,0.00046948576,0.47480416,0.003914964,0.00011348245,0.00007524571,0.000087705615,0.0031668798,0.006054263,0.10763391,0.40138394,0.00057836174],"about_ca_topic_score_codex":0.000086705644,"about_ca_topic_score_gemma":0.000006790976,"teacher_disagreement_score":0.40318188,"about_ca_system_score_codex":0.00025815645,"about_ca_system_score_gemma":0.00044569938,"threshold_uncertainty_score":0.88332623},"labels":[],"label_agreement":null},{"id":"W4413323186","doi":"10.1523/jneurosci.0790-25.2025","title":"Multivariate White Matter Microstructure Alterations in Older Adults with Coronary Artery Disease","year":2025,"lang":"en","type":"article","venue":"Journal of Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital; Ontario Brain Institute; Sunnybrook Health Science Centre; Université de Montréal; Concordia University; Institut Universitaire de Gériatrie de Montréal; Montreal Heart Institute","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada; Heart and Stroke Foundation of Canada","keywords":"Cardiology; White matter; Medicine; Internal medicine; Coronary artery disease; Cognitive decline; Magnetic resonance imaging; Cognition; Dementia; Radiology; Disease; Psychiatry","score_opus":0.01714424457512084,"score_gpt":0.3164412437319306,"score_spread":0.2992969991568098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413323186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9661981,0.00004763798,0.022547081,0.010651331,0.00012614133,0.00029917067,0.0000085571255,0.000016639366,0.000105376734],"genre_scores_gemma":[0.9903618,0.000015763811,0.0041523664,0.0049393126,0.00001718534,0.000008027723,0.0000010745699,0.000006609988,0.00049787835],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993571,0.000016113501,0.00022253074,0.00016756497,0.00011684322,0.00011981896],"domain_scores_gemma":[0.99952394,0.000020729518,0.000112300884,0.00018516564,0.000083169725,0.00007466742],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042439016,0.00007969133,0.000120508514,0.00016270026,0.000060949147,0.000024741317,0.00012200416,0.000014093614,0.000009324521],"category_scores_gemma":[0.000032958487,0.000056519766,0.000034364166,0.00034575976,0.00009191687,0.00018032856,0.000028669852,0.00023633114,0.0000012073435],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081300875,0.0004504576,0.85742897,0.000071661874,0.0000034333304,0.00077294785,0.0002867498,0.0004815643,0.13562666,0.00010144427,0.0027933829,0.0011697162],"study_design_scores_gemma":[0.0008382275,0.00007536538,0.9961336,0.00037313573,0.000013620043,0.0005452575,0.000018957206,0.00059934496,0.0005360171,0.0001482632,0.000669536,0.000048621612],"about_ca_topic_score_codex":8.214663e-7,"about_ca_topic_score_gemma":5.8153705e-7,"teacher_disagreement_score":0.13870469,"about_ca_system_score_codex":0.00002390557,"about_ca_system_score_gemma":0.00010375393,"threshold_uncertainty_score":0.23048091},"labels":[],"label_agreement":null},{"id":"W4413326697","doi":"10.1101/2025.08.15.25331829","title":"Cognitive Reserve Disrupts Cognitive Decline from White Matter Hyperintensities","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas College; York University; Carleton University","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; Japan Atomic Energy Agency; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; Natural Sciences and Engineering Research Council of Canada; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Hyperintensity; Cognition; Cognitive reserve; Cognitive decline; Effects of sleep deprivation on cognitive performance; Disconnection; Psychology; Lesion; Neuroscience; White matter; Magnetic resonance imaging; Cognitive impairment; Medicine; Dementia; Internal medicine; Disease; Psychiatry; Radiology","score_opus":0.0849119792704019,"score_gpt":0.38673091300934026,"score_spread":0.30181893373893837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413326697","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93303037,0.00050035166,0.028538872,0.016784461,0.00026973075,0.0015177132,0.0024541656,0.00054528256,0.016359061],"genre_scores_gemma":[0.9735653,0.0002923057,0.0058454303,0.008359958,0.0003094295,0.00062126975,0.0012681995,0.00006725154,0.009670901],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.997933,0.00007495214,0.00046312224,0.0009329033,0.00028356194,0.00031248856],"domain_scores_gemma":[0.9978917,0.00040964916,0.00021116632,0.00071305776,0.0006259932,0.00014841603],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00011967729,0.0004236384,0.00069462863,0.00017991212,0.00010552293,0.000046339843,0.00025434094,0.00023873802,0.0005068234],"category_scores_gemma":[0.00037812986,0.00039420824,0.0002475409,0.0001693256,0.00026910703,0.000048799364,0.0014011435,0.0011611336,0.00017688304],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004327493,0.00021448011,0.9923499,0.00026074532,0.0002195649,0.00018171109,0.0004098005,0.000003320635,0.0003037323,0.000055849545,0.0038761282,0.0016920101],"study_design_scores_gemma":[0.0012005229,0.0000884496,0.96850324,0.004626143,0.00090202887,0.000040458614,0.0004455961,0.00047109483,0.0071948622,0.007999882,0.007934212,0.00059352204],"about_ca_topic_score_codex":0.0008310747,"about_ca_topic_score_gemma":0.00011212042,"teacher_disagreement_score":0.04053489,"about_ca_system_score_codex":0.000067506146,"about_ca_system_score_gemma":0.00020352934,"threshold_uncertainty_score":0.999851},"labels":[],"label_agreement":null},{"id":"W4413335507","doi":"10.1093/braincomms/fcaf305","title":"Superficial and deep white matter abnormalities in temporal lobe epilepsy","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Medical Research Council; Epilepsy Society; University College London; University of Western Australia; National Institute for Health and Care Research; National Imaging Facility; Medical Research Centre; Wellcome Trust","keywords":"Temporal lobe; White matter; Epilepsy; Grey matter; Neuroimaging; Fractional anisotropy; Abnormality; Psychology; Magnetic resonance imaging; Medicine; Diffusion MRI; Cohort; Hippocampus; Hippocampal sclerosis; Temporal cortex; Nuclear medicine; Neuroscience; Audiology; Pathology; Radiology; Psychiatry","score_opus":0.051417317376212704,"score_gpt":0.3642687004136942,"score_spread":0.3128513830374815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413335507","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22307444,0.0028017398,0.030234622,0.6061712,0.000065681474,0.0018463352,0.000057713245,0.00055058004,0.13519773],"genre_scores_gemma":[0.95580417,0.0002941631,0.033612266,0.0072415196,0.000014231876,0.0001876027,0.00006732353,0.00001236728,0.002766379],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9994014,0.000055171684,0.00022134751,0.00014603787,0.000049397437,0.00012668342],"domain_scores_gemma":[0.9986258,0.0001965747,0.000031344982,0.0010706286,0.000039950304,0.00003566559],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012679468,0.000082923296,0.0001408131,0.00014756063,0.00014478531,0.000019983465,0.00024407927,0.0000429241,0.0000442573],"category_scores_gemma":[0.000057002897,0.00008559999,0.000028878116,0.00028441244,0.00020433086,0.00007222206,0.00026168788,0.00023343952,0.000012276717],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017304514,0.00018758187,0.9257346,0.0000445459,0.000009208549,0.0000020187165,0.00046693318,0.000002924826,0.00037513615,0.05699288,0.012271916,0.0038949624],"study_design_scores_gemma":[0.00061794603,0.000028301645,0.7433348,0.00015174728,0.000025296695,0.000033010994,0.0004725553,0.0017228269,0.00012034738,0.015764225,0.23757876,0.0001502141],"about_ca_topic_score_codex":0.00009124471,"about_ca_topic_score_gemma":0.0002011955,"teacher_disagreement_score":0.73272973,"about_ca_system_score_codex":0.000031841926,"about_ca_system_score_gemma":0.000041149193,"threshold_uncertainty_score":0.34906662},"labels":[],"label_agreement":null},{"id":"W4413340964","doi":"10.1101/2025.08.13.25333630","title":"Axonal Degeneration Across the Alzheimer’s Disease Spectrum: A Longitudinal MRI and Fluid Biomarker Study","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Dementia; Biomarker; Cognitive decline; Degeneration (medical); Cognition; Neuropathology; Effects of sleep deprivation on cognitive performance; Disease; Medicine; Neuroscience; Cohort; Psychology; Oncology; Internal medicine; Pathology; Biology","score_opus":0.13278439267153413,"score_gpt":0.4122324645585679,"score_spread":0.27944807188703374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413340964","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9601291,0.0022554959,0.0178501,0.016069878,0.00020565181,0.0027757182,0.00017364339,0.00028781942,0.00025258985],"genre_scores_gemma":[0.9958821,0.00035339716,0.0018798793,0.0004380662,0.00020629306,0.00073475327,0.000085649044,0.00002596742,0.0003938961],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983737,0.00007482603,0.0003110835,0.0007271374,0.00027048477,0.00024280178],"domain_scores_gemma":[0.998566,0.00007453627,0.0001134078,0.0010185875,0.00007826372,0.00014923238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030571554,0.00028245972,0.0002990856,0.000069095644,0.00029405934,0.000077794226,0.00023459253,0.000073678224,0.000022482584],"category_scores_gemma":[0.000058863796,0.0002019432,0.00011167934,0.00018373535,0.00016788149,0.000034993274,0.00072550273,0.0004712531,0.0000052788355],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028912188,0.00075068075,0.9878401,0.00013124054,0.00029102774,0.00013679854,0.0003071288,0.00008567919,0.0008268689,0.0012205617,0.0032573577,0.0048633954],"study_design_scores_gemma":[0.00052957213,0.0000739958,0.98443437,0.0001374561,0.0007844983,0.00002816831,0.000050501854,0.0037321204,0.0009487308,0.0027647528,0.00626881,0.00024704597],"about_ca_topic_score_codex":0.00003703875,"about_ca_topic_score_gemma":0.000030484684,"teacher_disagreement_score":0.035752997,"about_ca_system_score_codex":0.00003548732,"about_ca_system_score_gemma":0.00013290583,"threshold_uncertainty_score":0.82350045},"labels":[],"label_agreement":null},{"id":"W4413352538","doi":"10.3389/fneur.2025.1612598","title":"Improved injury detection through harmonizing multi-site neuroimaging data after experimental TBI: a Translational Outcomes Project in Neurotrauma consortium study","year":2025,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, Los Angeles; National Institute of Neurological Disorders and Stroke; Vivian L. Smith Foundation; Johns Hopkins University; Georgetown University; Uniformed Services University of the Health Sciences; University of Waterloo; Henry M. Jackson Foundation","keywords":"Statistical power; Neuroimaging; Outlier; Univariate; Voxel; Harmonization; Statistical parametric mapping; Population; Sample size determination; Medicine; Traumatic brain injury; Psychology; Multivariate statistics; Statistics; Neuroscience; Psychiatry; Mathematics; Magnetic resonance imaging; Radiology","score_opus":0.13125389996010506,"score_gpt":0.4102484699397621,"score_spread":0.27899456997965705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413352538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92936206,0.00023271571,0.06387361,0.0030200828,0.0005744806,0.0026153023,0.000040821124,0.00021412142,0.0000668335],"genre_scores_gemma":[0.97566044,0.000026523912,0.019365385,0.004178963,0.000026442945,0.00062714936,0.000030349607,0.000040081355,0.000044661985],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977844,0.00018881015,0.00055079133,0.0009729653,0.00012906047,0.00037402046],"domain_scores_gemma":[0.9989572,0.00006889361,0.00009848377,0.0008121046,0.000028981282,0.000034296852],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00016436848,0.00026105225,0.0004468897,0.0004991955,0.00007958372,0.000023446619,0.00028822816,0.00008940412,0.000004012053],"category_scores_gemma":[0.000096614865,0.0002698627,0.000060473492,0.00059409626,0.0001431618,0.00030387676,0.00022982334,0.00074866484,9.1585207e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011335723,0.001068281,0.9771553,0.000024886827,0.000020397178,0.00016553828,0.00051171734,0.000015152238,0.015667234,0.000007617931,0.00026480714,0.0039654425],"study_design_scores_gemma":[0.005071314,0.000582955,0.92563546,0.000028215054,0.00007107412,0.00005178851,0.00023884364,0.060230166,0.004006549,0.00015233796,0.003652879,0.00027841216],"about_ca_topic_score_codex":0.000152473,"about_ca_topic_score_gemma":0.000095812415,"teacher_disagreement_score":0.060215015,"about_ca_system_score_codex":0.000042235777,"about_ca_system_score_gemma":0.0000757229,"threshold_uncertainty_score":0.9999754},"labels":[],"label_agreement":null},{"id":"W4413395701","doi":"10.1101/2025.08.15.670595","title":"Characterizing neuronal cell bodies in human postmortem cerebral white matter tracts","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"White matter; Neuroscience; Cell bodies; Biology; Human brain; Pathology; Anatomy; Medicine; Central nervous system; Magnetic resonance imaging","score_opus":0.02955704536588889,"score_gpt":0.28089769204802334,"score_spread":0.25134064668213446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413395701","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.993075,0.00016690794,0.0007795065,0.0030270182,0.00031318417,0.0013191344,0.00027970268,0.0006810601,0.00035846274],"genre_scores_gemma":[0.98502207,0.00008283291,0.011228004,0.0027633558,0.00028146137,0.00037666995,0.0000027622268,0.00011875937,0.00012409975],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99725646,0.000065510714,0.00067932927,0.0011380573,0.00028285588,0.00057781127],"domain_scores_gemma":[0.99783164,0.000036192567,0.00035896196,0.0013630799,0.00020133743,0.00020878173],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019439685,0.0005719957,0.0007138648,0.00046499318,0.00014402541,0.00010976352,0.000408854,0.00034651338,0.00006901489],"category_scores_gemma":[0.000031541917,0.000641279,0.00018466353,0.0003139485,0.00010242872,0.00014246171,0.00052962016,0.00150407,0.000040429815],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003613275,0.0003882214,0.31180558,0.0009781,0.000029117804,0.00011791651,0.000014872019,0.0000096224685,0.68530357,0.00027837584,0.0010368809,0.0000016088466],"study_design_scores_gemma":[0.0005135655,0.000042578376,0.8346215,0.0007395044,0.00008656545,7.5179486e-8,0.0000015112048,0.00009074443,0.15798016,0.0000070993797,0.005415025,0.00050165894],"about_ca_topic_score_codex":0.000022340322,"about_ca_topic_score_gemma":0.0000016098791,"teacher_disagreement_score":0.52732337,"about_ca_system_score_codex":0.00022273463,"about_ca_system_score_gemma":0.00026019485,"threshold_uncertainty_score":0.99960387},"labels":[],"label_agreement":null},{"id":"W4413440516","doi":"10.21203/rs.3.rs-7361397/v1","title":"Longitudinal Visualization Tools for Advanced Characterization of Multiple Sclerosis Lesions Using Diffusion MRI and Magnetization Transfer Imaging Metrics","year":2025,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Mitacs; Université de Sherbrooke","keywords":"Diffusion MRI; Lesion; Magnetization transfer; Multiple sclerosis; White matter; Computer science; Visualization; Radiology; Magnetic resonance imaging; Artificial intelligence; Pathology; Medicine","score_opus":0.27826180301709097,"score_gpt":0.4659820557567396,"score_spread":0.18772025273964865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413440516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3457485,0.0002292457,0.6501089,0.00039029587,0.00003964002,0.0028865018,0.00047987513,0.000092276736,0.00002475409],"genre_scores_gemma":[0.9632921,0.0037778516,0.02992117,0.00003312285,0.00007250159,0.00053725234,0.0022136187,0.000051008537,0.000101344565],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99798584,0.00011072214,0.00046908797,0.00063414103,0.0004971995,0.00030298726],"domain_scores_gemma":[0.9975131,0.00047287927,0.00011954117,0.00046259517,0.0013284889,0.00010336083],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044439128,0.00021440367,0.00039613916,0.0009260702,0.00031376048,0.00008815963,0.00013453516,0.00016538984,0.000009947058],"category_scores_gemma":[0.00086527877,0.00022132433,0.00011514653,0.0010121327,0.00012685146,0.00021850372,0.00031220648,0.00040097762,2.2336077e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035191266,0.0004174222,0.03555028,0.0046306574,0.000025773268,0.0000017511126,0.00020517422,0.00053062954,0.8720724,0.0023522256,0.000031471835,0.08383031],"study_design_scores_gemma":[0.0032878343,0.0004340357,0.21434283,0.009995255,0.00034709246,0.000008315762,0.00025060982,0.5850689,0.18170947,0.001779167,0.0021804709,0.0005960644],"about_ca_topic_score_codex":0.00003058943,"about_ca_topic_score_gemma":0.000003106789,"teacher_disagreement_score":0.69036293,"about_ca_system_score_codex":0.00017241262,"about_ca_system_score_gemma":0.00019897749,"threshold_uncertainty_score":0.90253437},"labels":[],"label_agreement":null},{"id":"W4413445538","doi":"10.18060/29082","title":"Effect of Cigarette Smoking and Alcohol Use on White Matter Tract Integrity","year":2025,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Cigarette smoking; Alcohol; White (mutation); White matter; Medicine; Environmental health; Chemistry; Internal medicine; Magnetic resonance imaging; Organic chemistry","score_opus":0.0374371625871624,"score_gpt":0.3570489508855109,"score_spread":0.3196117882983485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413445538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9941663,0.000024845971,0.00011584954,0.0017126703,0.000014410734,0.0003736577,0.000005921295,0.00005946566,0.0035268904],"genre_scores_gemma":[0.997777,0.000027999313,0.0013606824,0.0005335851,0.00001125433,0.000032699412,0.0000013856474,0.000011815796,0.00024358716],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99940354,0.0000025009015,0.00018563669,0.00019035005,0.000104392624,0.00011357114],"domain_scores_gemma":[0.99957144,0.00009280574,0.00010741659,0.00008774528,0.000103544015,0.0000370489],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001818978,0.000103327344,0.00023685677,0.00012829059,0.000026049518,0.0000114767145,0.00006241266,0.00005499687,0.000006799567],"category_scores_gemma":[0.00015573432,0.00008212674,0.000050811243,0.00016781707,0.000076733995,0.00010055076,0.000043054093,0.00026741254,3.5011053e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015932447,0.00006904272,0.9115444,0.00061649224,0.00002563582,6.4635054e-7,0.000057080193,1.3592047e-7,0.0746284,0.0010406924,0.0028236401,0.009034497],"study_design_scores_gemma":[0.0007192077,0.0004980657,0.4607576,0.0007817097,0.00016905965,0.000017536475,0.000020363655,0.00006853238,0.5355051,0.0005288817,0.0008508908,0.00008304508],"about_ca_topic_score_codex":0.000007936314,"about_ca_topic_score_gemma":4.0722597e-8,"teacher_disagreement_score":0.4608767,"about_ca_system_score_codex":0.000018978462,"about_ca_system_score_gemma":0.000008140463,"threshold_uncertainty_score":0.33490312},"labels":[],"label_agreement":null},{"id":"W4413445665","doi":"10.18060/29106","title":"Relationship between Perivascular Space Burden, White Matter Hyperintensities, and Cognitive Function","year":2025,"lang":"en","type":"article","venue":"Proceedings of IMPRS","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hyperintensity; Perivascular space; Cognition; White matter; Space (punctuation); Psychology; Cognitive psychology; Medicine; Neuroscience; Magnetic resonance imaging; Pathology; Philosophy; Radiology; Linguistics","score_opus":0.03968803237689291,"score_gpt":0.31254009013241457,"score_spread":0.2728520577555217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413445665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9786903,0.0001769764,0.005435292,0.005701948,0.000015054913,0.00036902196,0.0000067812985,0.00011157541,0.009493027],"genre_scores_gemma":[0.9936925,0.000018470222,0.0039277147,0.0003728326,0.00004700432,0.000041561943,0.000007663558,0.000013752884,0.0018784691],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99943936,0.0000015716657,0.00015278537,0.00020409636,0.00008499022,0.00011717263],"domain_scores_gemma":[0.999492,0.000051178144,0.0000672672,0.00006015677,0.0002819889,0.00004743049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000075763,0.00009255038,0.00017092611,0.00012580462,0.00007116235,0.000015355383,0.00003333227,0.000050574574,0.000010932886],"category_scores_gemma":[0.00013504703,0.00008942873,0.00004128415,0.00020900178,0.00010789236,0.0001029944,0.000050993727,0.00015859496,0.000004160013],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004227559,0.000010944283,0.9887049,0.00019650933,0.000025375391,2.391457e-7,0.00011811586,8.214394e-8,0.0049782256,0.0036064829,0.0013213222,0.0009955231],"study_design_scores_gemma":[0.00039389185,0.00008163146,0.9865504,0.00022456811,0.00032391274,0.000016622605,0.00072447653,0.000024718878,0.0049817497,0.0042270366,0.0023705452,0.00008047857],"about_ca_topic_score_codex":0.000008593455,"about_ca_topic_score_gemma":7.6201715e-8,"teacher_disagreement_score":0.015002207,"about_ca_system_score_codex":0.00001643888,"about_ca_system_score_gemma":0.000016235144,"threshold_uncertainty_score":0.36467978},"labels":[],"label_agreement":null},{"id":"W4413509559","doi":"10.1016/j.jrras.2025.101876","title":"Deep learning-based magnetic resonance imaging image reconstruction in the assessment of brain microstructural changes in Parkinson's disease patients","year":2025,"lang":"en","type":"article","venue":"Journal of Radiation Research and Applied Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Parkinson's disease; Disease; Nuclear magnetic resonance; Neuroimaging; Medicine; Neuroscience; Materials science; Psychology; Pathology; Radiology; Physics","score_opus":0.03243055240761956,"score_gpt":0.388594276016298,"score_spread":0.35616372360867843,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413509559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9846796,0.00075848104,0.00096349063,0.012862263,0.000020435742,0.0003903115,0.0000019675003,0.0000042341426,0.0003192456],"genre_scores_gemma":[0.9944253,0.00024726687,0.0050404537,0.00023648783,0.000016217165,0.000022550017,0.0000015919557,0.0000021879844,0.000007944758],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990238,0.00010928168,0.00022363961,0.00013551873,0.00035786157,0.00014991302],"domain_scores_gemma":[0.9993313,0.00031322247,0.00012692569,0.00007299256,0.00011229972,0.000043277727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013194571,0.000049703525,0.000113548325,0.0004875405,0.0001317055,0.00004310023,0.00013272154,0.000014163051,0.0000045564097],"category_scores_gemma":[0.00022840289,0.000035447676,0.000017088421,0.0008197672,0.00041374483,0.00008411338,0.000020076588,0.00033858494,6.484574e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008407718,0.00008114167,0.7468891,0.000032984524,5.9845195e-7,0.0000036693293,0.000078636855,0.0001617447,0.006500527,0.00062202406,0.000115296374,0.24543022],"study_design_scores_gemma":[0.0008179353,0.00018656476,0.9815165,0.00010740381,0.0000030849847,0.0000046140963,0.0003488573,0.011661292,0.0014001532,0.0024457986,0.0014757134,0.000032093307],"about_ca_topic_score_codex":0.0000058190803,"about_ca_topic_score_gemma":0.000008179201,"teacher_disagreement_score":0.24539812,"about_ca_system_score_codex":0.00005649564,"about_ca_system_score_gemma":0.00016403654,"threshold_uncertainty_score":0.152446},"labels":[],"label_agreement":null},{"id":"W4413878449","doi":"10.1038/s42003-025-08774-6","title":"Anatomical insights into the superior longitudinal system from integrative in- vivo and ex-vivo mapping","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Provincia Autonoma di Trento","keywords":"Ex vivo; In vivo; Biology; Genetics","score_opus":0.0664635604551278,"score_gpt":0.3751419750123706,"score_spread":0.3086784145572428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413878449","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91818154,0.008343004,0.038151402,0.026415342,0.00006462374,0.0009279582,0.000021549673,0.00023604224,0.0076585496],"genre_scores_gemma":[0.9791346,0.0013233114,0.018760394,0.00044595526,0.000014185431,0.0002025112,0.00002865327,0.000006628066,0.000083713014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99925756,0.00013993561,0.0002451634,0.00022696127,0.000025437643,0.00010491311],"domain_scores_gemma":[0.9981494,0.00048474292,0.000049239545,0.0012197511,0.00006621246,0.00003065471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008131423,0.000104727034,0.00022234082,0.00013786089,0.00022137741,0.000012191778,0.00042882885,0.00007955478,0.000007142945],"category_scores_gemma":[0.000087736014,0.00007008717,0.00003357944,0.00035159852,0.00055806455,0.000033622382,0.00045379117,0.0003435109,0.0000033077422],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057697984,0.0002217041,0.20930329,0.0000484028,0.00009877673,0.000004797979,0.004579254,9.4769064e-7,0.08235933,0.6864631,0.00096818444,0.015894504],"study_design_scores_gemma":[0.002230968,0.00019897669,0.16231337,0.0014786413,0.00021190113,0.0000733125,0.016218,0.024104133,0.018468272,0.095739104,0.6784143,0.00054905954],"about_ca_topic_score_codex":0.00038299794,"about_ca_topic_score_gemma":0.00032603255,"teacher_disagreement_score":0.67744607,"about_ca_system_score_codex":0.0000957934,"about_ca_system_score_gemma":0.000051913223,"threshold_uncertainty_score":0.28580716},"labels":[],"label_agreement":null},{"id":"W4413981681","doi":"10.1139/jpn.090177","title":"White-matter abnormalities in adolescents with long-term inhalant and cannabis use: a diffusion magnetic resonance imaging study","year":2010,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Magnetic resonance imaging; Intoxicative inhalant; Term (time); White matter; Medicine; Diffusion MRI; Diffusion imaging; Diffusion-Weighted Magnetic Resonance Imaging; Nuclear magnetic resonance; Pediatrics; Radiology; Physics; Astronomy","score_opus":0.017109069483508214,"score_gpt":0.30101840219703285,"score_spread":0.28390933271352464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413981681","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99619067,0.00033820598,0.00019830024,0.0028740787,0.00016005129,0.0002163141,0.0000015577725,0.000009635667,0.000011193426],"genre_scores_gemma":[0.99754447,0.000117612195,0.001128863,0.001068217,0.00004489657,0.0000048039615,6.6485235e-8,0.000009102173,0.000081967264],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992029,0.000022322052,0.00023524111,0.00020374298,0.00018470378,0.000151086],"domain_scores_gemma":[0.99955016,0.000006611893,0.00013081158,0.00015904948,0.00004548155,0.00010789854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013016275,0.000102030994,0.00015031872,0.00013296887,0.00009344807,0.000055824847,0.000092555754,0.00001527787,0.000002662665],"category_scores_gemma":[0.000018978828,0.00007198727,0.000016108548,0.000186004,0.00018192886,0.00028960517,0.000048950635,0.00039718623,1.3964964e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000094498646,0.00030124284,0.9955918,0.000033382643,1.8590897e-7,0.00009298623,0.000108443324,4.513752e-7,0.0030146015,0.000013147678,0.000047042366,0.00070219743],"study_design_scores_gemma":[0.0008288158,0.00049894134,0.99532527,0.00035525378,0.000015478257,0.002588031,0.000063932064,0.00006361249,0.00004409082,0.000046746714,0.000096002004,0.000073857234],"about_ca_topic_score_codex":0.000011785953,"about_ca_topic_score_gemma":0.00006930929,"teacher_disagreement_score":0.0029705106,"about_ca_system_score_codex":0.0000052202095,"about_ca_system_score_gemma":0.000044415177,"threshold_uncertainty_score":0.29355556},"labels":[],"label_agreement":null},{"id":"W4414080826","doi":"10.1371/journal.pcbi.1013459","title":"Blood flow in the human cerebral cortex: Large-scale pial vascularization and 1D simulation","year":2025,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Health Research Council of New Zealand; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Pulsatile flow; Blood flow; Cerebral blood flow; Hemodynamics; Blood pressure; Cerebral autoregulation; Intracranial pressure","score_opus":0.0369265125769312,"score_gpt":0.35566203552426284,"score_spread":0.31873552294733165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414080826","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6765278,0.000049070037,0.3198612,0.0024743008,0.000020463269,0.00048299637,0.000019001822,0.000079514975,0.0004856445],"genre_scores_gemma":[0.98258626,0.000004570477,0.015428359,0.0014101138,0.000043725704,0.00004253372,0.00045222318,0.00000523542,0.000026949492],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994253,0.000052304025,0.00016351805,0.00019750465,0.00006309945,0.00009830175],"domain_scores_gemma":[0.999611,0.00016569695,0.000037155918,0.0001093822,0.000061021114,0.000015695317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008124479,0.0000689319,0.00011340393,0.00009249024,0.00011554027,0.000009195575,0.0000543472,0.000052250678,0.0000099855815],"category_scores_gemma":[0.00003763819,0.00005471746,0.000025778625,0.00019264361,0.000059145874,0.00002838637,0.000032192565,0.00012025788,0.0000017705128],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008259109,0.0018786956,0.5999565,0.00012806777,0.0001454035,0.000011149108,0.0007920021,0.062078424,0.01840621,0.31028318,0.00031576105,0.0059219906],"study_design_scores_gemma":[0.001330959,0.00009637367,0.4149264,0.000029947805,0.000075841825,0.0000109013645,0.000026364884,0.49145132,0.000144874,0.090783805,0.0010461491,0.000077045275],"about_ca_topic_score_codex":0.0000037590996,"about_ca_topic_score_gemma":0.0000047238136,"teacher_disagreement_score":0.4293729,"about_ca_system_score_codex":0.00001207253,"about_ca_system_score_gemma":0.00002335485,"threshold_uncertainty_score":0.22313133},"labels":[],"label_agreement":null},{"id":"W4414083439","doi":"10.1109/tbme.2025.3607105","title":"Spherical Harmonics Representation Learning for High-Fidelity and Generalizable Super-Resolution in Diffusion MRI","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Youth Innovation Promotion Association of the Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Representation (politics); Harmonics; Signal processing; Diffusion MRI; Spherical harmonics; Diffusion; Data acquisition; Pattern recognition (psychology)","score_opus":0.030566198256701434,"score_gpt":0.32079380328000306,"score_spread":0.29022760502330164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414083439","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06925762,0.000053298587,0.92774516,0.0022126266,0.000120402525,0.0003823208,0.0000057052503,0.00020774352,0.000015133911],"genre_scores_gemma":[0.91183823,0.00039391813,0.08710564,0.00016023895,0.000030588013,0.00021049115,0.00002295996,0.00001753912,0.0002203896],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99917287,0.000012602895,0.0002384009,0.00027735592,0.000117901596,0.00018088291],"domain_scores_gemma":[0.99961287,0.000109840425,0.000019919464,0.00014316228,0.00003121175,0.000082986015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009936997,0.000107516265,0.00017409476,0.00017474258,0.00009308506,0.000011447161,0.000040086903,0.000095709016,0.000009904277],"category_scores_gemma":[0.00003541947,0.00010776751,0.00004615638,0.00042420547,0.00004474708,0.000055054796,0.000002561509,0.00030143224,7.818715e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039376612,0.0010315637,0.00059723377,0.00046297748,0.000064034444,0.000017576915,0.00014135965,0.3296805,0.56559485,0.0023844652,0.0010303765,0.098601274],"study_design_scores_gemma":[0.0014417312,0.00016886674,0.00223883,0.00018606173,0.00004922487,0.000011562779,0.000029859666,0.9600288,0.026839517,0.00038077336,0.0084894765,0.00013529632],"about_ca_topic_score_codex":0.00006951289,"about_ca_topic_score_gemma":0.0000031037177,"teacher_disagreement_score":0.8425806,"about_ca_system_score_codex":0.000084174964,"about_ca_system_score_gemma":0.00002594553,"threshold_uncertainty_score":0.43946317},"labels":[],"label_agreement":null},{"id":"W4414155731","doi":"10.7554/elife.96625.3","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"preprint","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cerebellum; Thalamus; Taurine; Attenuation; Central nervous system; Neurite","score_opus":0.04797523747320988,"score_gpt":0.3343625564876865,"score_spread":0.2863873190144766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414155731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9948393,0.00045032098,0.0020221046,0.001181847,0.00010112987,0.00066190545,0.000024545636,0.000039319428,0.0006795281],"genre_scores_gemma":[0.99266094,0.00036953232,0.006422481,0.00014335138,0.000028387884,0.000090742404,0.00004829655,0.000009616499,0.00022668137],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990331,0.00003512629,0.0003576471,0.00025215853,0.00022088684,0.00010105972],"domain_scores_gemma":[0.999278,0.00016626233,0.00015460611,0.000316188,0.000058843532,0.00002610515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013741858,0.00014816753,0.00031097003,0.000082314495,0.000035828616,0.000005288517,0.00015918817,0.00007251552,0.000006045927],"category_scores_gemma":[0.000083325125,0.000104849176,0.00005114933,0.00011644232,0.0001237344,0.000011662301,0.0002265246,0.00036034477,1.3237229e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062249374,0.0022401204,0.7997535,0.0060643214,0.00012817871,0.00005495211,0.013120048,0.00015221564,0.027977355,0.008268173,0.003626079,0.13799259],"study_design_scores_gemma":[0.0006759743,0.00008949261,0.9171463,0.0009347276,0.000082856386,0.000015705118,0.00020862822,0.00025140267,0.05610111,0.0017080653,0.022586577,0.00019915387],"about_ca_topic_score_codex":0.00004164533,"about_ca_topic_score_gemma":0.000017500106,"teacher_disagreement_score":0.13779344,"about_ca_system_score_codex":0.000018507808,"about_ca_system_score_gemma":0.00013962336,"threshold_uncertainty_score":0.42756253},"labels":[],"label_agreement":null},{"id":"W4414168204","doi":"10.1016/j.mri.2025.110522","title":"Correction of orientation dependence in magnetization transfer measures in the context of tractometry: Challenges, pitfalls and solutions","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Philips (Canada); CARE Canada; Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Université de Sherbrooke","keywords":"Orientation (vector space); Context (archaeology); Magnetization; Variance (accounting); Diffusion; Work (physics); Polynomial; Measure (data warehouse)","score_opus":0.04497411306941035,"score_gpt":0.3230898056104971,"score_spread":0.27811569254108676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414168204","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8135433,0.1086938,0.0570331,0.011121893,0.0001956599,0.0023208254,0.00001700117,0.00008363186,0.0069907927],"genre_scores_gemma":[0.9934435,0.005396912,0.00084591884,0.00015689904,0.0000057724046,0.000075395954,0.0000038728504,0.0000061376063,0.00006562783],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991545,0.00006118353,0.00030927118,0.00019755715,0.00015521668,0.00012225792],"domain_scores_gemma":[0.9995152,0.00015921182,0.00004238405,0.00018983691,0.000080427846,0.000012983197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030860645,0.00007904159,0.00016207177,0.0002613203,0.000030461939,0.0000063224843,0.00007508718,0.00002718911,0.0000045620754],"category_scores_gemma":[0.00015480221,0.00006937427,0.000022909244,0.00061734585,0.000119630924,0.00008508476,0.000013128753,0.00015203837,1.5234872e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007562558,0.00019414813,0.07740949,0.00008975284,0.0000011128236,0.000003778629,0.0013114123,0.000020598916,0.016450848,0.0139146475,0.000082850194,0.8904457],"study_design_scores_gemma":[0.00096787256,0.00010451391,0.97779524,0.00049848476,0.000027328813,0.000019245315,0.0016307203,0.00627315,0.0052861157,0.0014968544,0.005824538,0.00007593358],"about_ca_topic_score_codex":0.0002028366,"about_ca_topic_score_gemma":0.00018687847,"teacher_disagreement_score":0.90038574,"about_ca_system_score_codex":0.000028880082,"about_ca_system_score_gemma":0.00003783364,"threshold_uncertainty_score":0.28290007},"labels":[],"label_agreement":null},{"id":"W4414370731","doi":"10.1101/2025.09.16.25335779","title":"Revisiting the Role of Structural Connectivity-Based Parcellation in Thalamic Nuclei Segmentation: comparison with recent state-of-the-art methods","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Segmentation; Thalamus; Workflow; Pattern recognition (psychology); Diffusion MRI","score_opus":0.05460757683439453,"score_gpt":0.39934570138231706,"score_spread":0.3447381245479225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414370731","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92329776,0.00034613165,0.07155582,0.0026589015,0.000055726163,0.0014273331,0.000025839692,0.00005747582,0.0005749987],"genre_scores_gemma":[0.8982637,0.000051832783,0.10144993,0.00006565814,0.00002031065,0.00007958963,0.000028553297,0.000014296882,0.000026151694],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986481,0.00029885594,0.00045032697,0.0002841456,0.00020298721,0.0001155509],"domain_scores_gemma":[0.9983405,0.00034294085,0.00053782243,0.00061368116,0.00014487021,0.00002017631],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046034477,0.00015623546,0.00039334208,0.000078933976,0.000057323192,0.00000823406,0.00019210253,0.00004902095,0.000011595193],"category_scores_gemma":[0.000096348864,0.00009773401,0.00007546692,0.00033277916,0.00011535145,0.000018808636,0.0001428839,0.0005064958,2.1147319e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010263072,0.000036405905,0.85640025,0.00039273652,0.000029609204,6.32013e-7,0.0003338989,0.009321511,0.026351117,0.0003737311,0.00000803535,0.10664944],"study_design_scores_gemma":[0.0005625804,0.000051928124,0.45451406,0.0015421145,0.0001537742,0.000003890845,0.00015505658,0.042503495,0.49144256,0.006972053,0.0019435646,0.00015494043],"about_ca_topic_score_codex":0.000027111884,"about_ca_topic_score_gemma":0.0000070116416,"teacher_disagreement_score":0.46509144,"about_ca_system_score_codex":0.00007517768,"about_ca_system_score_gemma":0.00013148706,"threshold_uncertainty_score":0.3985477},"labels":[],"label_agreement":null},{"id":"W4414371298","doi":"10.1002/nbm.70148","title":"Evaluating a Cellular Microstructure Model Within Apoptotic Cell Death via Diffusion Magnetic Resonance and Long Diffusion Times","year":2025,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Apoptosis; Intracellular; Diffusion; Programmed cell death; Myeloid leukemia; Cancer; Immune system","score_opus":0.03292858301950447,"score_gpt":0.34859327333847784,"score_spread":0.3156646903189734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414371298","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9526248,0.005490497,0.0380537,0.0022014177,0.000054159962,0.0009043991,0.0000075879625,0.00013865094,0.00052480394],"genre_scores_gemma":[0.9434355,0.00041889166,0.051967558,0.0012444733,0.00005076964,0.000054831286,0.000045000095,0.000029069526,0.0027539297],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985269,0.000030985208,0.00040921275,0.0005137498,0.0002539593,0.00026519675],"domain_scores_gemma":[0.99920964,0.000067411005,0.00009503732,0.00044207825,0.00006690812,0.000118918484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002226526,0.00022551628,0.00034440905,0.00030170957,0.00011784009,0.000011429957,0.000102734986,0.00011966197,0.000030138155],"category_scores_gemma":[0.000084518506,0.00018080542,0.000034970602,0.0005442318,0.00016787427,0.000040168547,0.0001510157,0.00035116516,0.0000021025646],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104366634,0.000145858,0.013233755,0.0002694395,0.0000021415324,0.00003574087,0.00022400223,0.00006501839,0.96240544,0.00021742687,0.00025083937,0.023045957],"study_design_scores_gemma":[0.005810468,0.0007557367,0.07465901,0.0020789076,0.000209913,0.000114615395,0.00008744449,0.83773994,0.06290482,0.014151476,0.0010953355,0.0003923418],"about_ca_topic_score_codex":0.000039958442,"about_ca_topic_score_gemma":0.0000039534734,"teacher_disagreement_score":0.8995006,"about_ca_system_score_codex":0.00008536297,"about_ca_system_score_gemma":0.00007309507,"threshold_uncertainty_score":0.73730314},"labels":[],"label_agreement":null},{"id":"W4414394996","doi":"10.1002/brb3.70919","title":"Microstructural Hippocampal Alterations in Alzheimer's Disease: A Systematic Review and Meta‐Analysis of Diffusion Kurtosis Imaging","year":2025,"lang":"en","type":"review","venue":"Brain and Behavior","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hippocampal formation; Kurtosis; Diffusion; Hippocampus; Diffusion MRI","score_opus":0.08828730761518705,"score_gpt":0.4191704529746279,"score_spread":0.33088314535944086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414394996","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000022973383,0.9952253,0.000072163115,0.0006702937,0.0000069745333,0.00357758,0.00038216927,0.000035743335,0.0000068002887],"genre_scores_gemma":[0.00014415508,0.99609244,0.00093529787,0.0005350206,0.00000491772,0.0018076039,0.00034233692,0.00001855722,0.00011964778],"study_design_codex":"systematic_review","study_design_gemma":"meta_analysis","domain_scores_codex":[0.9984929,0.00012335708,0.00073489756,0.0004079319,0.00010993695,0.00013099771],"domain_scores_gemma":[0.998868,0.00021420787,0.00029581675,0.0004721839,0.000046747515,0.00010305904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014048356,0.00029012686,0.0034216535,0.00045512282,0.000058096917,0.000021697406,0.00009139626,0.000050543138,0.000026718924],"category_scores_gemma":[0.00008026729,0.00020110441,0.00067900843,0.000777281,0.00008078041,0.00004216727,0.00010001531,0.00017856574,2.8321864e-7],"study_design_candidate":"systematic_review","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000025232644,0.00015378508,0.00012809025,0.962841,0.007885141,0.000025677322,0.000022724982,3.2009304e-8,0.000013107567,0.00014622143,0.00012768836,0.028654018],"study_design_scores_gemma":[0.00007813684,0.000007630559,0.00030669835,0.06404104,0.93345463,0.000036643713,0.000004231423,0.000010518865,9.46009e-7,0.000011854722,0.0018877112,0.0001599366],"about_ca_topic_score_codex":0.000014381768,"about_ca_topic_score_gemma":0.00000423296,"teacher_disagreement_score":0.92556953,"about_ca_system_score_codex":0.00001865611,"about_ca_system_score_gemma":0.00006192178,"threshold_uncertainty_score":0.82008},"labels":[],"label_agreement":null},{"id":"W4414403629","doi":"10.1101/2025.09.22.675000","title":"Evaluating the quality of brainstem ROI registration using structural and diffusion MRI","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Toronto Western Hospital; University Health Network; University of Toronto; Ontario Brain Institute; Centre for Addiction and Mental Health","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto","keywords":"Region of interest; Brainstem; Diffusion MRI; Fractional anisotropy; Pattern recognition (psychology); Robustness (evolution); Metric (unit); Image registration; Image quality","score_opus":0.12822983302517535,"score_gpt":0.40723773259713847,"score_spread":0.27900789957196315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414403629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9767168,0.00042171995,0.020396931,0.0008536868,0.00013764173,0.0011594857,0.000100011894,0.00020125617,0.000012425789],"genre_scores_gemma":[0.9321425,0.00011597814,0.06734161,0.0001785669,0.00012069334,0.000062866384,5.138484e-7,0.000029211915,0.00000804616],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9980979,0.00014869815,0.00061714364,0.0005938987,0.00034503412,0.00019734833],"domain_scores_gemma":[0.9975326,0.00013933756,0.0006783731,0.001159128,0.00041189708,0.000078670535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000751822,0.00027236584,0.00044615834,0.000107017484,0.00021455788,0.000050010596,0.00020756015,0.00019545858,0.0000037975813],"category_scores_gemma":[0.0003992216,0.00022332458,0.00009871296,0.0002870386,0.00017437949,0.00006325799,0.00038011998,0.00054894696,2.6752184e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004700747,0.000031665448,0.0100352205,0.00074576266,0.00003534405,0.0000018536093,0.000012163587,0.00010350158,0.9850197,0.003920433,0.000019673917,0.000027710894],"study_design_scores_gemma":[0.0014938399,0.00019722505,0.59331894,0.0029326999,0.00061575935,2.405373e-7,0.000019005398,0.09644361,0.30329663,0.00020631083,0.0006325389,0.000843177],"about_ca_topic_score_codex":0.00009302497,"about_ca_topic_score_gemma":0.0000011556424,"teacher_disagreement_score":0.68172306,"about_ca_system_score_codex":0.00012875623,"about_ca_system_score_gemma":0.0003714228,"threshold_uncertainty_score":0.9106912},"labels":[],"label_agreement":null},{"id":"W4414492054","doi":"10.1101/2025.09.22.677842","title":"Distinct cellular processes drive motor skill learning in the human brain","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Fondo para la Investigación Científica y Tecnológica; National Institute of Dental and Craniofacial Research; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health","keywords":"Human brain; Precuneus; Neuroplasticity; Motor learning; Diffusion MRI; Soma; Motor skill; Hippocampus","score_opus":0.027500140735174424,"score_gpt":0.2959379614449278,"score_spread":0.26843782070975336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414492054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9734224,0.00092514366,0.015163907,0.0053156,0.00017211317,0.003205165,0.0001718686,0.0014183894,0.00020539419],"genre_scores_gemma":[0.9912222,0.0001165986,0.006350575,0.00089661364,0.00026361214,0.0009708709,0.0000021443745,0.000076446566,0.000100952835],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9977261,0.00013375666,0.00048205486,0.0009137479,0.00032512232,0.00041923442],"domain_scores_gemma":[0.99775666,0.00022620516,0.000306395,0.0012563758,0.00034310794,0.00011125635],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047115117,0.000445092,0.0005109305,0.0002779607,0.0002657314,0.00010399879,0.00061618356,0.0002714551,0.000015172325],"category_scores_gemma":[0.00082763575,0.00038431823,0.00012709238,0.0008072285,0.0001503802,0.00006590124,0.0003981532,0.0016732267,0.000010787313],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041674317,0.00086864654,0.07931024,0.0035618898,0.00010504329,0.00032988674,0.00011898873,0.000059899132,0.9083827,0.005161664,0.0020467127,0.000012630509],"study_design_scores_gemma":[0.0018100381,0.00034229129,0.54543805,0.005429084,0.0005377356,1.9568387e-7,0.000044895838,0.0008722846,0.28929868,0.00018085868,0.15410605,0.0019398358],"about_ca_topic_score_codex":0.00003963372,"about_ca_topic_score_gemma":0.0000029807934,"teacher_disagreement_score":0.61908406,"about_ca_system_score_codex":0.00017920356,"about_ca_system_score_gemma":0.0005274458,"threshold_uncertainty_score":0.9998609},"labels":[],"label_agreement":null},{"id":"W4414509608","doi":"10.1002/hbm.70366","title":"A Combined Neuroanatomy, Ex Vivo Imaging, and Immunohistochemistry Defined <scp>MRI</scp> Mask for the Human Paraventricular Nucleus of the Thalamus","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of General Medical Sciences; National Institute of Mental Health","keywords":"Thalamus; Ex vivo; Human brain; Nucleus; Translation (biology); In vivo; Voxel; Magnetic resonance imaging","score_opus":0.026351798345765877,"score_gpt":0.316765132927157,"score_spread":0.2904133345813911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414509608","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9385464,0.0013238043,0.028944535,0.017835373,0.0001170418,0.0032319478,0.000033698983,0.0003702225,0.009596988],"genre_scores_gemma":[0.99238,0.000029759914,0.0014303157,0.0019648494,0.00004225899,0.000213269,0.000012578005,0.000033534936,0.0038933894],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99888104,0.000032924807,0.00033878072,0.0003451512,0.00014793806,0.00025417435],"domain_scores_gemma":[0.9984402,0.00042606887,0.00020566722,0.0007947941,0.00009113854,0.0000421542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002186601,0.0001891889,0.00025917927,0.000078763485,0.00066109665,0.000033291595,0.0003432626,0.00004705497,0.0000061631727],"category_scores_gemma":[0.00032239893,0.00013573401,0.00016781104,0.00028315277,0.00031744715,0.00003289611,0.00021875094,0.00026315814,4.369686e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000006436121,0.00010855006,0.010377688,0.00030538545,0.000063577085,0.000007715331,0.00027796635,0.000008212744,0.91723025,0.039262887,0.031999666,0.0003516694],"study_design_scores_gemma":[0.00598575,0.00015449601,0.39930272,0.0016101118,0.000661615,0.00016874945,0.00174273,0.0043838024,0.09228075,0.09392459,0.399386,0.00039868808],"about_ca_topic_score_codex":0.000018436465,"about_ca_topic_score_gemma":7.290748e-7,"teacher_disagreement_score":0.8249495,"about_ca_system_score_codex":0.000043667413,"about_ca_system_score_gemma":0.000035449484,"threshold_uncertainty_score":0.5535072},"labels":[],"label_agreement":null},{"id":"W4414516295","doi":"10.3390/neurolint17100154","title":"Fractional Anisotropy Alterations in Key White Matter Pathways Associated with Cognitive Performance Assessed by MoCA","year":2025,"lang":"en","type":"article","venue":"Neurology International","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Fractional anisotropy; Diffusion MRI; Montreal Cognitive Assessment; White matter; Fasciculus; Inferior longitudinal fasciculus; Cognition; Biomarker","score_opus":0.023099932438510218,"score_gpt":0.3166568386578504,"score_spread":0.29355690621934016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414516295","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9194969,0.0000081321805,0.038849667,0.022463487,0.00014432076,0.00033649773,0.00011680641,0.000121493955,0.01846273],"genre_scores_gemma":[0.98197097,0.000021821377,0.00076476816,0.014997595,0.00003240262,0.00019756686,0.0004663485,0.000014256178,0.0015342552],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99914956,0.000033124867,0.00020225463,0.00029626978,0.00016686495,0.00015193108],"domain_scores_gemma":[0.9994344,0.0001444185,0.000085212036,0.000114830844,0.00019010676,0.000031044052],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054141434,0.00011624022,0.00013728226,0.00017909503,0.00007788727,0.000018315019,0.0001001594,0.00008060527,0.00029285077],"category_scores_gemma":[0.000065667664,0.00011062319,0.000028700191,0.00020491618,0.00008951986,0.00014352781,0.00003543616,0.00042763498,0.000028317178],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044694607,0.0005015503,0.9809597,0.0000063624143,0.000056067023,0.000028272072,0.000032608983,0.00012823672,0.0027713631,0.0022817769,0.01256374,0.00022334492],"study_design_scores_gemma":[0.0017482982,0.00024995458,0.9806925,0.00007268786,0.000031453656,0.000069112866,0.0000090365065,0.009479306,0.001283945,0.0007407257,0.0055147223,0.00010826603],"about_ca_topic_score_codex":0.0000055372666,"about_ca_topic_score_gemma":0.0000102042,"teacher_disagreement_score":0.06247412,"about_ca_system_score_codex":0.000051953608,"about_ca_system_score_gemma":0.00007639096,"threshold_uncertainty_score":0.45110828},"labels":[],"label_agreement":null},{"id":"W4414562304","doi":"10.1101/2025.09.26.678469","title":"Subthreshold violations of trajectory predictions are sensitive to TMS of Cerebellum CRUS I/II","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Nautical Research Society","funders":"Fondation de France; Agence Nationale de la Recherche; Institut National de la Santé et de la Recherche Médicale; Deutsche Forschungsgemeinschaft","keywords":"Trajectory; Transcranial magnetic stimulation; Illusion; Electroencephalography; Modulation (music); Task (project management)","score_opus":0.035553404289907095,"score_gpt":0.289438461151674,"score_spread":0.2538850568617669,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414562304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9134118,0.00031063563,0.07603549,0.0015902773,0.0004973019,0.0031419683,0.003927413,0.00090220966,0.00018288502],"genre_scores_gemma":[0.9646558,0.0001586348,0.034333963,0.00025055982,0.00015388595,0.0003313529,0.0000016320804,0.00006767764,0.000046453653],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99778837,0.000052308562,0.00073475495,0.000786978,0.00032114965,0.00031642264],"domain_scores_gemma":[0.9964406,0.00009440835,0.0005597976,0.0015866923,0.0010824181,0.00023606948],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00019421517,0.00039338422,0.0007964978,0.00057751604,0.00016720522,0.000013083626,0.0002846081,0.00033070546,0.000018408795],"category_scores_gemma":[0.00024523723,0.00044403432,0.00025035048,0.00093151175,0.0001821702,0.000058872836,0.0004777185,0.0007180892,0.0000039651836],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009080308,0.00071015203,0.014313447,0.00092600664,0.0002394194,0.000017998213,0.000041209878,0.00066787895,0.97882044,0.0022836083,0.0018836843,0.000005364236],"study_design_scores_gemma":[0.0004931326,0.00018020728,0.35701144,0.0024681487,0.00051925256,6.966391e-8,0.000013670298,0.0008505356,0.63334036,0.000011509933,0.0046654907,0.00044619784],"about_ca_topic_score_codex":0.00005739391,"about_ca_topic_score_gemma":0.000003926741,"teacher_disagreement_score":0.34548008,"about_ca_system_score_codex":0.00019943948,"about_ca_system_score_gemma":0.0006178806,"threshold_uncertainty_score":0.99980116},"labels":[],"label_agreement":null},{"id":"W4414613967","doi":"10.53555/qxw7sp51","title":"Quantum Mechanical Simulations In Diffusion MRI","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"University of Southampton","keywords":"Bloch equations; Spin diffusion; Quantum; Magnetic field; Diffusion; Formalism (music); Flow (mathematics); Spin echo; Diffusion equation; Spin (aerodynamics)","score_opus":0.36489803478972227,"score_gpt":0.4027617854837921,"score_spread":0.03786375069406983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414613967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99254155,0.00001921942,0.0015374095,0.005540572,0.00009722222,0.00009399956,0.0000053349377,0.000025270647,0.00013939213],"genre_scores_gemma":[0.99693125,0.00019186808,0.0026736555,0.0001162503,0.000024470655,0.0000022088002,0.0000025576664,0.0000046826985,0.0000530773],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9990424,0.00007432903,0.00036174047,0.00011451652,0.00026112338,0.0001459103],"domain_scores_gemma":[0.9992644,0.00039946884,0.00012331952,0.00009111635,0.00007376288,0.00004794044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012897284,0.000055704513,0.00017635098,0.00030839068,0.000065272245,0.000020954156,0.00014963832,0.000030094627,0.000025471965],"category_scores_gemma":[0.00063996774,0.0000423016,0.000033258388,0.0015664718,0.00014790388,0.00019791131,0.00004566302,0.00019422751,0.0000022688744],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033008608,0.00007643111,0.99338543,0.0000050828826,0.0000010204494,0.000031475793,0.00008274267,0.00047331306,0.003677826,0.000502853,0.0011141264,0.00061668304],"study_design_scores_gemma":[0.00028572557,0.00020570167,0.9820962,0.000076929,0.0000023586915,0.000032633336,0.00011482684,0.00619702,0.0003349257,0.009159196,0.0014418494,0.00005263631],"about_ca_topic_score_codex":0.00009002743,"about_ca_topic_score_gemma":0.00024437904,"teacher_disagreement_score":0.01128924,"about_ca_system_score_codex":0.000033262655,"about_ca_system_score_gemma":0.00008446454,"threshold_uncertainty_score":0.17250091},"labels":[],"label_agreement":null},{"id":"W4414656468","doi":"10.3390/axioms14100743","title":"First and Second Moments of Spherical Distributions That Are Relevant for Biological Applications","year":2025,"lang":"en","type":"article","venue":"Axioms","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anisotropy; Moment (physics); Distribution (mathematics); Bessel function; Divergence (linguistics); Method of moments (probability theory); Trigonometric functions; Second moment of area; Upper and lower bounds","score_opus":0.07442368640475619,"score_gpt":0.3633774067911345,"score_spread":0.28895372038637834,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414656468","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05474317,0.00023890189,0.93768454,0.0055110347,0.000013627213,0.0009960955,0.00025165066,0.0000931159,0.00046789576],"genre_scores_gemma":[0.9839872,0.000139579,0.014357544,0.0002405052,0.0000149268835,0.0007130385,0.00006840328,0.0000052725018,0.0004735438],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99955547,0.0000038703947,0.00012766643,0.00017988797,0.00003639466,0.00009669971],"domain_scores_gemma":[0.99954426,0.00010523217,0.00005443202,0.00021062896,0.000044271153,0.00004116188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031811203,0.00006307046,0.00014404123,0.000024020526,0.00009378894,0.0000041053113,0.00005388532,0.000041995565,0.000017774413],"category_scores_gemma":[0.00003942868,0.000051078554,0.000042613905,0.000150985,0.00012361714,0.000016876727,0.000045575787,0.00006156256,0.000001228526],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026084218,0.0018029754,0.098404214,0.0009625249,0.00017946557,0.0000054155,0.00008968536,0.00000528308,0.04565945,0.80217195,0.021131895,0.029326279],"study_design_scores_gemma":[0.0013213821,0.0002489373,0.2347729,0.00017117313,0.00011729558,0.000024054856,0.00015013636,0.0008631099,0.026512528,0.059556857,0.6760696,0.00019200293],"about_ca_topic_score_codex":0.0000021968103,"about_ca_topic_score_gemma":0.0000016864186,"teacher_disagreement_score":0.92924404,"about_ca_system_score_codex":0.000020126334,"about_ca_system_score_gemma":0.000012556349,"threshold_uncertainty_score":0.2082923},"labels":[],"label_agreement":null},{"id":"W4414672190","doi":"10.1101/2025.09.29.678806","title":"Lifespan Trajectories of Asymmetry in White Matter Tracts","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Euroimmun Medizinische Labordiagnostika; Common Fund; National Institute of General Medical Sciences; National Institute on Deafness and Other Communication Disorders; National Institute of Mental Health; National Institute on Aging; Biotechnology and Biological Sciences Research Council; Avid Radiopharmaceuticals; University of Cambridge; University of Calgary; IXICO; Servier; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Canadian Institutes of Health Research; University of Queensland; Northern California Institute for Research and Education; Vanderbilt Institute for Clinical and Translational Research; National Institute on Drug Abuse; University of Pennsylvania; Vanderbilt University; Pfizer; BioClinica; Biogen; Illinois Department of Public Health; National Center for Advancing Translational Sciences; Cure Alzheimer's Fund; Alzheimer's Association; National Institutes of Health; U.S. Department of Health and Human Services; National Health and Medical Research Council; Foundation for the National Institutes of Health","keywords":"White matter; Asymmetry; Lateralization of brain function; Brain asymmetry; Neuroimaging; Scope (computer science); Association (psychology)","score_opus":0.027781070003884654,"score_gpt":0.29095870653653794,"score_spread":0.2631776365326533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414672190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98449314,0.00082805095,0.008290262,0.0027429995,0.00047813723,0.001809676,0.00043164621,0.00061502354,0.00031107332],"genre_scores_gemma":[0.9633443,0.00018809352,0.03533534,0.00062027015,0.00013995988,0.00025755994,5.6440115e-7,0.0000680856,0.000045855184],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9980061,0.000051166586,0.0006211748,0.0007274593,0.00024811496,0.00034599332],"domain_scores_gemma":[0.9978862,0.00006827826,0.00031892036,0.0013158796,0.0002705436,0.0001401843],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022357432,0.0003837411,0.0007198683,0.00051029597,0.00004088081,0.000028975279,0.0003187997,0.00035848565,0.000037605583],"category_scores_gemma":[0.0001306003,0.00041224205,0.00015462736,0.0007475131,0.00011760515,0.0000733789,0.00026788923,0.00094370765,0.000012569218],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000086586224,0.00056923967,0.8069529,0.0020580436,0.00008678927,0.00006071778,0.000017812663,0.000036025034,0.1867643,0.001466841,0.0018945348,0.0000062145355],"study_design_scores_gemma":[0.00043949223,0.000037432706,0.79577166,0.0012880601,0.000118359945,3.0166284e-8,0.000002202902,0.000076565324,0.19706953,0.000014087979,0.004833329,0.00034925446],"about_ca_topic_score_codex":0.000033359967,"about_ca_topic_score_gemma":0.0000014085683,"teacher_disagreement_score":0.027045079,"about_ca_system_score_codex":0.00016135658,"about_ca_system_score_gemma":0.00045044618,"threshold_uncertainty_score":0.9998329},"labels":[],"label_agreement":null},{"id":"W4414712871","doi":"10.1016/j.neuroimage.2025.121489","title":"Early White Matter Microstructure Alterations in Infants with Down Syndrome","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital; University of Alberta","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Child Health and Human Development; National Institute of Mental Health; National Institutes of Health","keywords":"Fractional anisotropy; Uncinate fasciculus; White matter; Diffusion MRI; Trisomy; Inferior longitudinal fasciculus","score_opus":0.014862701400506802,"score_gpt":0.3019618203962363,"score_spread":0.2870991189957295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414712871","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97777796,0.000020113353,0.0041651996,0.007507271,0.000038196416,0.0005743792,0.000020716127,0.00015556478,0.009740623],"genre_scores_gemma":[0.983046,0.000007304247,0.008237209,0.0052230586,0.000013272799,0.00007450352,0.000018044317,0.00002309838,0.003357528],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9991895,0.000016476712,0.00017947046,0.00033040292,0.00009051872,0.00019362717],"domain_scores_gemma":[0.999373,0.000022498905,0.000037816833,0.00047772075,0.00004134971,0.00004757097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000025668684,0.00013535412,0.0001782529,0.00018361014,0.00006613148,0.000048203496,0.0001001857,0.000039762872,0.000090408495],"category_scores_gemma":[0.000011662621,0.00011334104,0.00003184965,0.00045586805,0.000072821014,0.00014302069,0.000048533802,0.00032189814,0.000038819282],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016304918,0.00015648971,0.93245494,0.00009204077,0.000013581245,0.00056493696,0.0001669418,0.0000323827,0.0561126,0.000608474,0.008839493,0.00079505664],"study_design_scores_gemma":[0.00062032207,0.000076882985,0.99202555,0.00010916691,0.000016762237,0.000350999,0.000007467449,0.000052286672,0.001525653,0.0005031073,0.0046151155,0.00009666517],"about_ca_topic_score_codex":0.00001810338,"about_ca_topic_score_gemma":0.0000069499606,"teacher_disagreement_score":0.059570618,"about_ca_system_score_codex":0.000023068173,"about_ca_system_score_gemma":0.000037521757,"threshold_uncertainty_score":0.46219134},"labels":[],"label_agreement":null},{"id":"W4414867530","doi":"10.1016/j.mri.2025.110539","title":"Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling","year":2025,"lang":"en","type":"article","venue":"Magnetic Resonance Imaging","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"National Center for Advancing Translational Sciences; Vanderbilt Kennedy Center, Vanderbilt University Medical Center; Vanderbilt Institute for Clinical and Translational Research; National Institute on Aging; National Cancer Institute; National Institutes of Health; Vanderbilt University","keywords":"Anisotropy; Voxel; Diffusion MRI; Sensitivity (control systems); Fractional anisotropy; Tractography; Thermal diffusivity","score_opus":0.021869585696872734,"score_gpt":0.33425271619481484,"score_spread":0.3123831304979421,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414867530","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6443228,0.0030128683,0.34781796,0.0038870955,0.000043472533,0.00052949664,0.000026417138,0.00008417715,0.00027568018],"genre_scores_gemma":[0.86508507,0.00019753662,0.13395344,0.0006298588,0.000015820231,0.000017310702,0.0000045496595,0.000012378928,0.000084060004],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99917173,0.00002883787,0.00020401567,0.0003223486,0.00010243986,0.00017062936],"domain_scores_gemma":[0.9994177,0.00012227411,0.000054338125,0.0002585785,0.00009191765,0.000055180397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008467479,0.00012720692,0.00023192202,0.0001613198,0.00008776778,0.000016737256,0.000046771147,0.000025376588,0.0000072320977],"category_scores_gemma":[0.00009610816,0.00012061957,0.00004731669,0.0003424095,0.0001417004,0.000039756655,0.00008148603,0.00014960313,6.0939624e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009409285,0.000046802223,0.16894838,0.00007311332,0.0000023355435,0.000011790322,0.0001630091,0.0000056921813,0.52739465,0.0019413752,0.00018724412,0.30113152],"study_design_scores_gemma":[0.00051094353,0.00010364203,0.9574007,0.00034308396,0.000038163216,0.000036344834,0.00008468592,0.0027124782,0.013980904,0.0020552918,0.022615448,0.00011833185],"about_ca_topic_score_codex":0.0001907799,"about_ca_topic_score_gemma":0.00001517367,"teacher_disagreement_score":0.7884523,"about_ca_system_score_codex":0.00001564696,"about_ca_system_score_gemma":0.000023748667,"threshold_uncertainty_score":0.4918723},"labels":[],"label_agreement":null},{"id":"W4414905029","doi":"10.1101/2025.10.03.25337290","title":"Towards repeatable and converging methods in diffusion MRI: Evidence from a longitudinal chronic pain cohort","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Repeatability; Fractional anisotropy; Diffusion MRI; Cohort; White matter; Chronic pain; Diffusion imaging","score_opus":0.10245665909581683,"score_gpt":0.4348610783171668,"score_spread":0.33240441922135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414905029","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33985975,0.007300781,0.6464269,0.0039988984,0.00016224683,0.0013759126,0.000036150446,0.00031429858,0.0005250326],"genre_scores_gemma":[0.4315871,0.016616417,0.5488397,0.0005622518,0.0002412116,0.0009070951,0.00011841816,0.000053883774,0.0010739404],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9977811,0.0002820743,0.0004472929,0.0010117599,0.00020785941,0.00026993637],"domain_scores_gemma":[0.99803627,0.0005660652,0.00016647698,0.0010496097,0.00007453375,0.000107064385],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0015034059,0.00028735708,0.000633417,0.000198831,0.00007037487,0.000032600085,0.00024355543,0.00018788193,0.000050223138],"category_scores_gemma":[0.0008056904,0.00027107293,0.000093027586,0.00025353502,0.00010895461,0.00006164003,0.0009950516,0.0009465912,0.0000016250729],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046791618,0.00006846505,0.94642067,0.00062138203,0.000040650517,0.00008102854,0.00010914943,0.000053071773,0.014554032,0.0001369873,0.00030286334,0.03756493],"study_design_scores_gemma":[0.00060082483,0.00010126623,0.91574806,0.00939913,0.00031672907,0.000023737812,0.000022323533,0.040777944,0.013759268,0.010117095,0.008669455,0.00046415153],"about_ca_topic_score_codex":0.0012049207,"about_ca_topic_score_gemma":0.00003697308,"teacher_disagreement_score":0.09758725,"about_ca_system_score_codex":0.00028414122,"about_ca_system_score_gemma":0.000288843,"threshold_uncertainty_score":0.99997413},"labels":[],"label_agreement":null},{"id":"W4415010674","doi":"10.7554/elife.96625.4","title":"Diffusion MRS tracks distinct trajectories of neuronal development in the cerebellum and thalamus of rat neonates","year":2025,"lang":"en","type":"article","venue":"eLife","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Hospital for Sick Children; University of Toronto","funders":"","keywords":"Cerebellum; Thalamus; Neurite; Attenuation; Taurine; Diffusion MRI; Diffusion","score_opus":0.03124378646310415,"score_gpt":0.3209232413370653,"score_spread":0.28967945487396113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415010674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9961968,0.00018364239,0.0014551297,0.0012744498,0.000029213,0.00022601018,0.000001954069,0.000018853696,0.0006139239],"genre_scores_gemma":[0.9969521,0.000078503515,0.0025755502,0.00019173205,0.000008503858,0.00002328567,0.0000055144224,0.0000041447415,0.00016064702],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999526,0.000015559865,0.00017950685,0.00010488674,0.00010857138,0.000065477194],"domain_scores_gemma":[0.99967736,0.00010803696,0.00004512477,0.00012841617,0.000027144217,0.000013933041],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078836114,0.000058789097,0.00012371247,0.00004458851,0.000031902662,0.0000024051571,0.000062019404,0.000018032828,0.000004079236],"category_scores_gemma":[0.00005359779,0.000039437928,0.00001830869,0.00014813188,0.000083346466,0.000014557518,0.000031783602,0.00008638601,1.2727953e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019285071,0.00064674567,0.83485544,0.00040597175,0.00001892103,0.000010706976,0.0027075363,0.0000067120905,0.0821579,0.010174799,0.0016036613,0.06721874],"study_design_scores_gemma":[0.00039841403,0.00004732082,0.8997667,0.000100519224,0.000014659666,0.0000056001604,0.0001450535,0.00006760227,0.081906065,0.00049622427,0.017009655,0.000042219024],"about_ca_topic_score_codex":0.000013469289,"about_ca_topic_score_gemma":0.000010103371,"teacher_disagreement_score":0.06717652,"about_ca_system_score_codex":0.0000074900486,"about_ca_system_score_gemma":0.000040103125,"threshold_uncertainty_score":0.1608232},"labels":[],"label_agreement":null},{"id":"W4415057797","doi":"10.31083/jin36357","title":"Reappraising the Anatomy of the Ansa Lenticularis in the Human Brain: A Cadaveric, Focused Fiber Micro-Dissection Study Perspective","year":2025,"lang":"en","type":"article","venue":"Journal of Integrative Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University Health Network","funders":"","keywords":"Perspective (graphical); Microdissection; Tractography; Fiber tract; Fiber; Cadaveric spasm","score_opus":0.04431137675831527,"score_gpt":0.41872808108439374,"score_spread":0.3744167043260785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415057797","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97061414,0.00006468418,0.004524565,0.022712212,0.000104993356,0.0007713071,0.0000020089935,0.000008805029,0.0011972958],"genre_scores_gemma":[0.99774575,0.000010437608,0.00031592153,0.0016220359,0.000019675852,0.000014018532,6.4028455e-8,0.000004912941,0.00026719447],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9988101,0.00024860946,0.00033482182,0.00017607519,0.0003187745,0.000111601985],"domain_scores_gemma":[0.9987396,0.00025579165,0.0003336274,0.00032533106,0.00032405363,0.000021566488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055793585,0.000107759144,0.00018996472,0.00013792513,0.00028248323,0.00003788343,0.00047543857,0.000019404548,0.0000029995185],"category_scores_gemma":[0.00097153435,0.000043320775,0.00013106516,0.0012913824,0.00038238766,0.0001202748,0.000057376903,0.00066340656,1.1096881e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011421126,0.001494986,0.03861932,0.000016722513,0.000029400171,0.00006638729,0.014859037,0.000076012315,0.9284027,0.011037673,0.003778807,0.0015047387],"study_design_scores_gemma":[0.0011699458,0.0012061181,0.87056744,0.00045990807,0.00015115582,0.00047789395,0.031741463,0.00028694727,0.08188106,0.005276247,0.006657585,0.00012422126],"about_ca_topic_score_codex":0.00009478357,"about_ca_topic_score_gemma":0.00004113062,"teacher_disagreement_score":0.8465216,"about_ca_system_score_codex":0.000089943715,"about_ca_system_score_gemma":0.00012682933,"threshold_uncertainty_score":0.28822082},"labels":[],"label_agreement":null},{"id":"W4415116021","doi":"10.1101/2025.10.12.681536","title":"A Comprehensive Characterization of the Phospholipid and Cholesterol Composition of the Uncinate Fasciculus in the Human Brain: Evidence of Age‐Related Alterations","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; McGill University","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Uncinate fasciculus; Myelin; Phospholipid; White matter; Cholesterol; Cortex (anatomy); Depression (economics); Triglyceride; Prefrontal cortex","score_opus":0.04040338551975504,"score_gpt":0.3021549334276938,"score_spread":0.26175154790793875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415116021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9936623,0.00015833376,0.000893711,0.0032964372,0.00009195873,0.0017322025,0.00012356568,0.000036832982,0.0000046688865],"genre_scores_gemma":[0.9987297,0.00012933998,0.00042194157,0.0005354575,0.000020445743,0.00014087706,0.0000010921012,0.000016516122,0.000004626068],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9985737,0.00019482101,0.00055001886,0.00032047508,0.00024083663,0.000120116834],"domain_scores_gemma":[0.9977608,0.00011286162,0.0006437559,0.001063637,0.00039352517,0.000025427533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023084265,0.00019252843,0.00036159743,0.00010269282,0.00012170148,0.000020306717,0.0003931032,0.0001273901,0.0000020600492],"category_scores_gemma":[0.00007725876,0.00012561707,0.00010215084,0.0006305692,0.00032049097,0.000066418936,0.0003204572,0.00048768477,1.7371721e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000117444415,0.000111032976,0.008909741,0.00058443676,0.000023682733,0.0000010030597,0.00007805471,0.00004101532,0.9887568,0.0014645286,0.00001529104,0.0000027160588],"study_design_scores_gemma":[0.0002514079,0.000027968073,0.6105897,0.0024374977,0.00008975944,7.0795046e-8,0.0000031971585,0.00029112044,0.3861093,0.000016400223,0.00010994425,0.00007366918],"about_ca_topic_score_codex":0.00004194705,"about_ca_topic_score_gemma":0.0000015616047,"teacher_disagreement_score":0.6026475,"about_ca_system_score_codex":0.00005700247,"about_ca_system_score_gemma":0.00014086156,"threshold_uncertainty_score":0.5122515},"labels":[],"label_agreement":null},{"id":"W4415225287","doi":"10.1227/neu.0000000000003792","title":"Resectability of White Matter Tracts in Patients With Language-Critical Gliomas","year":2025,"lang":"en","type":"article","venue":"Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Temporal lobe; Magnetic resonance imaging; Central nervous system disease; Operculum (bryozoa); Hyperintensity","score_opus":0.020009986665413794,"score_gpt":0.3330147159183774,"score_spread":0.3130047292529636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415225287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99528223,0.000011839174,0.00038289442,0.0023031414,0.000036001093,0.00024925778,0.000010708544,0.000051289146,0.0016726166],"genre_scores_gemma":[0.99752283,0.0000013034912,0.0011919354,0.0010813283,0.000007727355,0.000028092596,0.0000070968345,0.000011340548,0.00014834745],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992926,0.000027289085,0.00020942916,0.00021326047,0.00011959569,0.00013778865],"domain_scores_gemma":[0.9993307,0.00018747732,0.000031115982,0.00034998334,0.00006349888,0.00003724405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000065844404,0.00007442159,0.0001840852,0.00014945799,0.000025304746,0.000003611931,0.00004504182,0.000029542422,0.0000398579],"category_scores_gemma":[0.00020494909,0.00006141102,0.000035663328,0.00038869135,0.000092816364,0.000048442587,0.000039453134,0.00015874911,0.0000026185128],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023248428,0.00036499993,0.99648297,0.000091311565,0.0000015222654,0.000016024727,0.000023722532,0.0000016032883,0.0014926399,0.00010345149,0.0008830495,0.00030622727],"study_design_scores_gemma":[0.00036289447,0.00006429318,0.99503106,0.000096287135,0.000010568386,0.000002648272,0.0000044360113,0.000012829407,0.00377331,0.00013109764,0.00046649954,0.000044050455],"about_ca_topic_score_codex":0.000005832001,"about_ca_topic_score_gemma":0.0000012878119,"teacher_disagreement_score":0.00228067,"about_ca_system_score_codex":0.000015449117,"about_ca_system_score_gemma":0.000029767125,"threshold_uncertainty_score":0.25042686},"labels":[],"label_agreement":null},{"id":"W4415248294","doi":"10.1038/s41598-025-20016-7","title":"Standardization of postmortem human brainstem along the rostrocaudal axis to accommodate for inter-specimen structural heterogeneity","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Hospital","funders":"National Institute on Aging; National Institutes of Health","keywords":"Brainstem; Standardization; Postmortem studies; Central nervous system; Brain development","score_opus":0.05055876487264321,"score_gpt":0.39105012773952097,"score_spread":0.34049136286687776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415248294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8190989,0.000021986189,0.17679147,0.0016817325,0.00059239473,0.0013436949,0.000029554507,0.00009129794,0.00034896584],"genre_scores_gemma":[0.99336785,5.0942964e-7,0.0053054006,0.00017910486,0.00003120176,0.00008305134,0.000107442356,0.000011043043,0.00091440167],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987264,0.000016058677,0.00045238555,0.00043764382,0.00020449316,0.00016302054],"domain_scores_gemma":[0.9985054,0.000026858937,0.00019718731,0.00093064405,0.00028492606,0.00005498681],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047426074,0.00009922327,0.00018563925,0.0001116967,0.00034813074,0.00006948363,0.00013360046,0.000027618948,0.000008985919],"category_scores_gemma":[0.00009577515,0.00007178756,0.00010023387,0.00039087652,0.00014146158,0.00007032084,0.00012095466,0.00007293608,4.1949428e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015846969,0.00012647152,0.06128589,0.0002651471,0.000111327616,0.000032534783,0.00048930186,0.0005274719,0.8529022,0.0076874527,0.046290893,0.030122874],"study_design_scores_gemma":[0.00034737636,0.00013700887,0.042984426,0.00020055438,0.00008420722,0.00011103582,0.000091165246,0.00036528532,0.8017007,0.0133996485,0.14042297,0.000155602],"about_ca_topic_score_codex":0.00001246157,"about_ca_topic_score_gemma":0.000037869766,"teacher_disagreement_score":0.17426895,"about_ca_system_score_codex":0.00006205943,"about_ca_system_score_gemma":0.00007611455,"threshold_uncertainty_score":0.29274115},"labels":[],"label_agreement":null},{"id":"W4415249470","doi":"10.46298/mbj.16170","title":"Cumulative Directional Strain and Fractional Anisotropy Changes in the Corpus Callosum After a Football Season","year":2025,"lang":"en","type":"article","venue":"Multidisciplinary Biomechanics Journal","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada; Université de Montréal","keywords":"Corpus callosum; Anisotropy; Strain (injury); Football","score_opus":0.04771591689516888,"score_gpt":0.3671117044093601,"score_spread":0.3193957875141912,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415249470","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.707748,0.0014696544,0.21740736,0.07038864,0.0005124212,0.0014312153,0.00021872931,0.00016708446,0.0006568948],"genre_scores_gemma":[0.9788138,0.0005616948,0.019031283,0.0008229211,0.00018057204,0.00013968673,0.000025606507,0.000018268982,0.00040613057],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99895495,0.00007207375,0.00022710871,0.00026599024,0.0002528254,0.00022707367],"domain_scores_gemma":[0.99941546,0.00012597041,0.000101693506,0.0001759932,0.000098357625,0.000082511026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033352867,0.00016146737,0.00017972838,0.00027182492,0.0003023509,0.00004915402,0.00011217632,0.00008176139,0.000030930732],"category_scores_gemma":[0.00003896707,0.00011671851,0.000068423666,0.00042052576,0.00007499206,0.000097385244,0.0001075689,0.0005652304,0.000001978537],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006294959,0.0060099447,0.13293593,0.00046172805,0.00059721415,0.0028986393,0.005388455,0.00016628594,0.5457663,0.07728042,0.0055294614,0.21667069],"study_design_scores_gemma":[0.006232981,0.0016513612,0.6176139,0.00097554806,0.0003245342,0.0070042503,0.0023125242,0.074163154,0.0063698776,0.24251346,0.040036347,0.0008020261],"about_ca_topic_score_codex":0.0000069485864,"about_ca_topic_score_gemma":0.00002290909,"teacher_disagreement_score":0.5393964,"about_ca_system_score_codex":0.0001337722,"about_ca_system_score_gemma":0.00008647195,"threshold_uncertainty_score":0.47596428},"labels":[],"label_agreement":null},{"id":"W4415298994","doi":"10.1093/schbul/sbaf172","title":"Altered Cortical Gyrification Is Associated with Cortical and White Matter Microstructure in Individuals with Early Psychosis: A Multimodal Neuroimaging Study","year":2025,"lang":"en","type":"article","venue":"Schizophrenia Bulletin","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"National Institute of Mental Health; Japan Agency for Medical Research and Development","keywords":"Cytoarchitecture; Gyrification; White matter; Neuroimaging; Grey matter; Cerebral cortex; Insula","score_opus":0.01631633499069506,"score_gpt":0.29830287972734215,"score_spread":0.2819865447366471,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415298994","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9810832,0.00003259591,0.001425736,0.01571258,0.000020676533,0.0013818156,0.00002853372,0.00015289304,0.0001619673],"genre_scores_gemma":[0.9826686,0.0000061838036,0.014230053,0.0025653741,0.000022654329,0.00023414181,0.000024283745,0.000040815743,0.00020790887],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99829245,0.00011117681,0.00036404285,0.0006787293,0.00023717158,0.00031643626],"domain_scores_gemma":[0.9991125,0.0000991235,0.000112591886,0.00046707637,0.00009815185,0.00011058615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001534371,0.0002595344,0.00037458466,0.0002016153,0.00015006303,0.000081492624,0.00012591228,0.000080224374,0.0000825024],"category_scores_gemma":[0.0000659408,0.00020402498,0.000030260533,0.00048536656,0.0001901592,0.00004590508,0.00006462873,0.0007760844,0.000015246003],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078069343,0.00045076164,0.9944869,0.000019008523,0.000055200086,0.000025373507,0.0003805134,0.0000024707685,0.0014054861,0.000058895836,0.0019246929,0.0004099641],"study_design_scores_gemma":[0.005017112,0.0003583424,0.99274236,0.00027176208,0.00016726587,0.000051608957,0.00013288329,0.00015886826,0.00021432599,0.00013409769,0.000552967,0.00019837735],"about_ca_topic_score_codex":0.000035873112,"about_ca_topic_score_gemma":0.000017879336,"teacher_disagreement_score":0.013147207,"about_ca_system_score_codex":0.00004084084,"about_ca_system_score_gemma":0.000045319124,"threshold_uncertainty_score":0.83198977},"labels":[],"label_agreement":null},{"id":"W4415375973","doi":"10.1038/s41598-025-20328-8","title":"Advancing image-based meta-analysis through systematic use of crowdsourced NeuroVault data","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"National Institute of Mental Health; National Institutes of Health; Florida International University","keywords":"Spurious relationship; Human Connectome Project; Set (abstract data type); Heuristic; Neuroimaging; Selection (genetic algorithm); Estimator; Connectome","score_opus":0.22183971592356214,"score_gpt":0.416917559587585,"score_spread":0.19507784366402284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415375973","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021528069,0.00075430213,0.96932596,0.003548829,0.00062440505,0.0027327435,0.00006844981,0.000492974,0.0009242961],"genre_scores_gemma":[0.75964856,0.0000051828524,0.23280875,0.00071744825,0.000011017913,0.0001579795,0.0004222866,0.000028315282,0.0062004607],"study_design_codex":"bench_or_experimental","study_design_gemma":"meta_analysis","domain_scores_codex":[0.99724257,0.000073431176,0.0009918975,0.0010046781,0.00046929021,0.00021813107],"domain_scores_gemma":[0.9934234,0.00022842147,0.00063348643,0.005247485,0.00040247513,0.00006472922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010775144,0.00016554889,0.0010334554,0.00038504542,0.00017590723,0.0001266621,0.0002720441,0.000035652654,0.00005579284],"category_scores_gemma":[0.0014165549,0.00012534838,0.0005510654,0.002496091,0.00024258638,0.00032912436,0.000210566,0.0001288926,0.000002483579],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000107685126,0.0021572446,0.010190901,0.03526003,0.069683835,0.002225075,0.00034107198,0.012106719,0.6924213,0.0023495567,0.17287463,0.00028192176],"study_design_scores_gemma":[0.00052018074,0.000074804266,0.0009301107,0.0011825226,0.5710118,0.0003107384,0.00011689603,0.059682254,0.28613845,0.008763164,0.07060422,0.00066488894],"about_ca_topic_score_codex":0.000044075023,"about_ca_topic_score_gemma":0.0000075576477,"teacher_disagreement_score":0.7381205,"about_ca_system_score_codex":0.000027665074,"about_ca_system_score_gemma":0.00016232727,"threshold_uncertainty_score":0.5111559},"labels":[],"label_agreement":null},{"id":"W4415408384","doi":"10.1002/hbm.70386","title":"Mapping Human Proprioceptive Projections of Upper Limb Muscles Through Spinal Cord <scp>fMRI</scp>","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"Agence Nationale de la Recherche; Agence de l'innovation de Défense; Centre National de la Recherche Scientifique; Aix-Marseille Université","keywords":"Proprioception; Spinal cord; Myotome; Functional magnetic resonance imaging; Wrist; Somatosensory system; Electromyography; Upper limb; Magnetic resonance imaging","score_opus":0.11460665955832795,"score_gpt":0.3976209959361577,"score_spread":0.28301433637782974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415408384","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7684572,0.00028940354,0.14942755,0.0047958395,0.00010262058,0.002694016,0.00001508131,0.0010235874,0.073194735],"genre_scores_gemma":[0.96072817,0.000027615384,0.028087115,0.0016983175,0.00018436117,0.00034143566,0.000045304598,0.000049166785,0.008838522],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9982604,0.000051035266,0.00053802365,0.00055185624,0.00022035328,0.0003783575],"domain_scores_gemma":[0.99875224,0.000128869,0.00024519378,0.0005990955,0.0002129575,0.00006166608],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002054738,0.00025630952,0.0004134828,0.0004358892,0.00070118875,0.00003357932,0.00022708687,0.00010626047,0.000029814713],"category_scores_gemma":[0.00024222434,0.0002595145,0.00019801265,0.0007946424,0.00031137664,0.00014459154,0.0001784959,0.00046336997,0.000011264977],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022652699,0.00047354755,0.010098667,0.0007918482,0.00013098637,0.000016691707,0.002114273,0.0000057603306,0.8256706,0.13314268,0.023531655,0.004000658],"study_design_scores_gemma":[0.0016883253,0.0012886855,0.501127,0.0036399902,0.00012843948,0.00006456862,0.0078853965,0.00013946614,0.017240234,0.075531036,0.3909365,0.0003303615],"about_ca_topic_score_codex":0.00006069608,"about_ca_topic_score_gemma":0.0000059132694,"teacher_disagreement_score":0.8084304,"about_ca_system_score_codex":0.00011507561,"about_ca_system_score_gemma":0.000091644026,"threshold_uncertainty_score":0.9999857},"labels":[],"label_agreement":null},{"id":"W4415456288","doi":"10.1007/s00429-025-03025-0","title":"Rethinking tractography and neuroanatomy: does image resolution hold the key?","year":2025,"lang":"en","type":"review","venue":"Brain Structure and Function","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Université de Sherbrooke","funders":"European Research Council; Canada Research Chairs","keywords":"Tractography; Resolution (logic); Image resolution; Projection (relational algebra); Diffusion MRI; Connectome; Image (mathematics); Diffusion imaging","score_opus":0.038656618432298694,"score_gpt":0.33801836096818777,"score_spread":0.2993617425358891,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415456288","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000080651494,0.99194735,0.0035685138,0.0023552973,0.00018339683,0.0011231529,0.00006590887,0.00020130345,0.0004744471],"genre_scores_gemma":[0.0003188905,0.9960746,0.0016013836,0.0012475753,0.00023015868,0.000064628875,0.00013537669,0.000028737335,0.00029860935],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989684,0.00007450268,0.00025286622,0.0004418722,0.00011807426,0.00014425574],"domain_scores_gemma":[0.9990968,0.00026088348,0.0001677005,0.00038248466,0.000042339805,0.00004979744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011695121,0.0002595625,0.0005027138,0.00018407534,0.000270092,0.00005946742,0.000068691195,0.00021042072,0.000007935174],"category_scores_gemma":[0.00010154086,0.00013867952,0.00014428268,0.00039112064,0.00014665506,0.00007884273,0.00006236663,0.00070117164,2.7740978e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016448204,0.0000065070194,0.000018530636,0.0039027396,0.000038267935,0.000004396794,0.00004688134,5.1504582e-8,0.000048032554,0.0027838924,0.003159648,0.9899746],"study_design_scores_gemma":[0.00012487808,0.000049416652,0.0005195922,0.0020108747,0.00077424076,0.00014951675,0.000008039485,0.000012580204,0.000004391431,0.015064497,0.9811507,0.00013128869],"about_ca_topic_score_codex":0.000006471538,"about_ca_topic_score_gemma":0.0000030438914,"teacher_disagreement_score":0.9898433,"about_ca_system_score_codex":0.000016406166,"about_ca_system_score_gemma":0.00004872734,"threshold_uncertainty_score":0.5655187},"labels":[],"label_agreement":null},{"id":"W4415464241","doi":"10.1101/2025.10.22.683760","title":"Bridging Histology and Tractography: First In-Vivo Visualization of Short-Range Prefrontal Connections Informed by Primate Tract-Tracing","year":2025,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Human Connectome Project; Prefrontal cortex; Bridging (networking); Primate; Connectome; Visualization; Cognition; Nonhuman primate","score_opus":0.025505865460210924,"score_gpt":0.3032880370588792,"score_spread":0.27778217159866825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415464241","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9522791,0.0012159402,0.043119717,0.00046965783,0.00020436822,0.0016703169,0.00046294354,0.0005030872,0.000074855125],"genre_scores_gemma":[0.9910605,0.0012882883,0.0070526353,0.00013725711,0.000047327223,0.00035141755,0.0000027847827,0.00005329457,0.00000651557],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981222,0.000035730307,0.00068460376,0.0006499821,0.00018215648,0.0003253303],"domain_scores_gemma":[0.998614,0.000105960804,0.00032885856,0.00060883694,0.00021186868,0.00013048513],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001835585,0.00035786995,0.00064601965,0.00057330146,0.00012623305,0.00003233025,0.00015998803,0.00033900817,0.000011286766],"category_scores_gemma":[0.0001573684,0.00041625154,0.00011167935,0.0005276028,0.00017282904,0.00015817114,0.00015349108,0.0005646789,4.5655284e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013881865,0.001017531,0.3444616,0.00410153,0.0001598227,0.00004009968,0.000110043715,0.000126593,0.6466195,0.0020865137,0.0010845872,0.00005339165],"study_design_scores_gemma":[0.0018024568,0.00023411094,0.5628533,0.0037915495,0.00061891606,0.0000010075822,0.00001605984,0.0061638663,0.40636247,0.000014831928,0.016948463,0.0011930019],"about_ca_topic_score_codex":0.00012338758,"about_ca_topic_score_gemma":0.000021272182,"teacher_disagreement_score":0.240257,"about_ca_system_score_codex":0.00024002099,"about_ca_system_score_gemma":0.0002892542,"threshold_uncertainty_score":0.99982893},"labels":[],"label_agreement":null},{"id":"W4415522803","doi":"10.1038/s41398-025-03602-1","title":"Transdiagnostic alterations in white matter microstructure associated with suicidal thoughts and behaviours in the ENIGMA Suicidal Thoughts and Behaviours consortium","year":2025,"lang":"en","type":"article","venue":"Translational Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Dalhousie University","funders":"National Institute on Drug Abuse; Weill Institute for Neurosciences, University of California, San Francisco; National Institute of Mental Health; National Center for Complementary and Integrative Health; National Institute on Aging; Instituto de Salud Carlos III; National Health and Medical Research Council; Engineering and Physical Sciences Research Council; National Center for Advancing Translational Sciences; Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; Instituto de Investigación Marqués de Valdecilla; Junta de Andalucía; University of California, San Francisco; Ministero della Salute; Bundesministerium für Bildung und Forschung; Universiteit Leiden; Japan Agency for Medical Research and Development; Deutsche Forschungsgemeinschaft; South African Medical Research Council; Japan Society for the Promotion of Science; Conselho Nacional de Desenvolvimento Científico e Tecnológico; University of Texas Health Science Center at Houston; Dalhousie University; Nova Scotia Health Research Foundation; Scottish Funding Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; National Center for Research Resources; Agence Nationale de la Recherche; Wellcome Trust; Bill and Melinda Gates Foundation; National Alliance for Research on Schizophrenia and Depression; University of Minnesota; Ministerio de Ciencia e Innovación; American Foundation for Suicide Prevention; European Commission; Brain and Behavior Research Foundation; John S. Dunn Foundation; Universidad de Sevilla; Chief Scientist Office, Scottish Government Health and Social Care Directorate; Scottish Government; U.S. Department of Health and Human Services","keywords":"Corpus callosum; Fractional anisotropy; Suicidal ideation; White matter; Diffusion MRI; Poison control; Young adult","score_opus":0.01910613751411181,"score_gpt":0.3157839278725122,"score_spread":0.29667779035840036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415522803","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96157277,0.00084688084,0.0045783874,0.03136573,0.00006415975,0.0010105883,0.00020467004,0.000053095133,0.00030370787],"genre_scores_gemma":[0.9913765,0.000035910176,0.005957413,0.002103016,0.00005909796,0.00010325055,0.00024587466,0.00002138299,0.000097553464],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988274,0.000076131655,0.00032487352,0.0003640245,0.00018080996,0.00022674775],"domain_scores_gemma":[0.99945587,0.00018626993,0.000058880618,0.0002039391,0.000043290947,0.00005173895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013666751,0.00020507736,0.00022908006,0.00018690103,0.00015272798,0.000043444925,0.0000909436,0.00011483238,0.000016277325],"category_scores_gemma":[0.000008692219,0.00015653294,0.000043535863,0.00041777774,0.00019529871,0.0001126379,0.0000067299184,0.00045570318,4.94322e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010692355,0.00022003394,0.99504626,0.00002722101,0.000012039024,0.000017537363,0.0005442187,0.000049199407,0.00017002654,0.0032817433,0.0004061111,0.00011868133],"study_design_scores_gemma":[0.0016910171,0.000059864502,0.99222153,0.00013732357,0.00015490204,0.00011255703,0.00007644021,0.00018966,0.00009505357,0.0050448924,0.00006371276,0.00015302704],"about_ca_topic_score_codex":0.00005655141,"about_ca_topic_score_gemma":0.0046628853,"teacher_disagreement_score":0.029803721,"about_ca_system_score_codex":0.000019222321,"about_ca_system_score_gemma":0.00011149158,"threshold_uncertainty_score":0.63832283},"labels":[],"label_agreement":null},{"id":"W4415523828","doi":"10.1093/braincomms/fcaf420","title":"Thalamus involvement in genetic frontotemporal dementia assessed using structural and diffusion MRI: a GENFI study","year":2025,"lang":"en","type":"article","venue":"Brain Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; Health Sciences Centre; Occupational Cancer Research Centre; Montreal Neurological Institute and Hospital; University of Toronto; Western University; Douglas Mental Health University Institute; Université Laval","funders":"National Institute of Mental Health; NIHR Cambridge Biomedical Research Centre; Instituto de Salud Carlos III; Canadian Institutes of Health Research; National Institutes of Health; Alzheimer Nederland; Medical Research Council; Department of Health and Social Care; Medical Research Council Canada; Alzheimer’s Research UK; Weston Brain Institute; ZonMw; Wellcome Trust; University College London; Stichting Dioraphte; National Institute of Neurological Disorders and Stroke; University of Cambridge; Bundesministerium für Bildung und Forschung; National Institute on Aging; National Institute for Health and Care Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Ministero della Salute; Alzheimer's Society; Deutsche Forschungsgemeinschaft; Brain Research UK; Nvidia; Ontario Brain Institute; UK Dementia Research Institute; Vetenskapsrådet; Alzheimer's Association","keywords":"Frontotemporal dementia; Thalamus; Mutation; Diffusion MRI; Dementia; Pons; Effective diffusion coefficient","score_opus":0.11341533745719364,"score_gpt":0.42152545146379233,"score_spread":0.3081101140065987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415523828","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9760497,0.0010658836,0.01429025,0.0066825617,0.000018613247,0.0013658089,0.0000055193677,0.00009326625,0.00042835216],"genre_scores_gemma":[0.9043832,0.00015067325,0.09460731,0.0005920779,0.000007662897,0.00015050326,0.000024674298,0.000011903357,0.00007203234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999129,0.00010835273,0.00029683378,0.00023279057,0.00009621535,0.00013680651],"domain_scores_gemma":[0.99843866,0.000120626384,0.00007325952,0.0012740451,0.000048835707,0.00004460462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013292243,0.000113782764,0.00017430325,0.00015889603,0.00024618086,0.000028489096,0.0002822179,0.00003418143,0.0000081977305],"category_scores_gemma":[0.000042683303,0.00011225519,0.000028374914,0.0003147455,0.00009852629,0.000056590536,0.000499977,0.00020024188,5.014727e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012175299,0.00048242422,0.98436713,0.000024681913,0.000037333488,0.000003485783,0.0004458964,0.000024504277,0.008517394,0.0017679617,0.0002132935,0.0041037067],"study_design_scores_gemma":[0.0011394914,0.000060597817,0.9595561,0.000082503706,0.00008975863,0.000007383243,0.0006363436,0.03256664,0.00006443974,0.002995578,0.0026981675,0.00010299551],"about_ca_topic_score_codex":0.00049361115,"about_ca_topic_score_gemma":0.0005317787,"teacher_disagreement_score":0.08031706,"about_ca_system_score_codex":0.00007663942,"about_ca_system_score_gemma":0.00007204112,"threshold_uncertainty_score":0.45776337},"labels":[],"label_agreement":null},{"id":"W4415531709","doi":"10.1016/j.drugalcdep.2025.112948","title":"Abnormal white matter microstructure in tobacco use disorder: A machine learning study based on whole-brain skeletonized DTI data","year":2025,"lang":"en","type":"article","venue":"Drug and Alcohol Dependence","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; Canadian Anesthesiologists' Society","keywords":"Discriminative model; Nicotine; Multivariate statistics; White matter; Diffusion MRI; Pattern recognition (psychology)","score_opus":0.040477120492502315,"score_gpt":0.34411179275469095,"score_spread":0.30363467226218865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415531709","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9770548,0.00013702454,0.004721417,0.016436305,0.000034708806,0.001050824,0.00011012979,0.00015566326,0.0002991567],"genre_scores_gemma":[0.98948324,0.000020024187,0.0034534612,0.003884829,0.000018198298,0.00005771752,0.0001948645,0.000022561138,0.0028651333],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99857056,0.00012468819,0.00025139312,0.0006370555,0.00017330886,0.00024302275],"domain_scores_gemma":[0.9987839,0.00022531094,0.0000669309,0.00082836463,0.000031107964,0.00006437568],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003134238,0.00020438513,0.00026626373,0.00018116839,0.00019677116,0.000078398676,0.00028007908,0.00004839433,0.000036942238],"category_scores_gemma":[0.00014323709,0.00017668198,0.00002989894,0.00034425524,0.000057318754,0.00020457037,0.0002699478,0.0008203615,0.000009657609],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014427972,0.00022325161,0.99153817,0.000028728991,0.00000823607,0.00005880364,0.0001402512,0.00020377357,0.0012496318,0.000022314787,0.0018465538,0.004536026],"study_design_scores_gemma":[0.0037654673,0.000107812964,0.950076,0.0002518168,0.00005441654,0.000029584411,0.0003104193,0.021689048,0.0002553284,0.00010787464,0.023090372,0.00026189696],"about_ca_topic_score_codex":0.00026608692,"about_ca_topic_score_gemma":0.00020101498,"teacher_disagreement_score":0.041462187,"about_ca_system_score_codex":0.000024855333,"about_ca_system_score_gemma":0.000041077703,"threshold_uncertainty_score":0.7204882},"labels":[],"label_agreement":null},{"id":"W4415595897","doi":"10.1073/pnas.2502674122","title":"Quantitative MRI of the hippocampus reveals microstructural trajectories of aging and Alzheimer’s disease pathology","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; Douglas Mental Health University Institute; McGill University; McGill Genome Centre; Montreal Neurological Institute and Hospital","funders":"National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Hospital for Sick Children; Canada Research Chairs; McGill University; National Institutes of Health; Alzheimer's Association","keywords":"Hippocampal formation; Hippocampus; Pathological; Disease; Ageing; Brain aging; Degeneration (medical); Dementia","score_opus":0.07504404563849823,"score_gpt":0.3938925772449612,"score_spread":0.318848531606463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415595897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98777795,0.0007672572,0.0000086915725,0.010803311,0.000011157064,0.00024540277,0.000028986073,0.0000069572134,0.00035031777],"genre_scores_gemma":[0.9915848,0.000073321506,0.008030781,0.000264928,0.000007985578,0.000007703072,9.7409696e-8,0.0000018863043,0.000028529032],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99925786,0.000006013572,0.00024288047,0.00014527809,0.00028039672,0.00006759382],"domain_scores_gemma":[0.9992473,0.00013263241,0.00035096865,0.000013611777,0.00023912893,0.000016373295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003147661,0.000056726778,0.00014774335,0.0000837391,0.00010031353,0.0000031331251,0.0002752863,0.000025682599,0.0000010504091],"category_scores_gemma":[0.00043701462,0.00003239009,0.00005141176,0.00051004346,0.0016739023,0.00009705551,0.000116243194,0.00010016703,1.5823508e-8],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029924688,0.0000231323,0.08520123,0.00015022128,0.0000146752955,6.079224e-9,0.00019977312,0.000007672439,0.7331494,0.1804523,0.00022998216,0.0005416723],"study_design_scores_gemma":[0.00008981598,0.00002346949,0.39684746,0.00020137435,0.000047365338,0.000004793314,0.000118691096,0.00009473581,0.32294983,0.27957505,0.00002409755,0.000023317485],"about_ca_topic_score_codex":0.0000023953169,"about_ca_topic_score_gemma":2.0530921e-8,"teacher_disagreement_score":0.41019958,"about_ca_system_score_codex":0.000007552325,"about_ca_system_score_gemma":0.0000390845,"threshold_uncertainty_score":0.61675626},"labels":[],"label_agreement":null},{"id":"W4415958339","doi":"10.1038/s41467-025-64788-y","title":"Brain dissection photogrammetry: a tool for studying human white matter connections integrating ex vivo and in vivo multimodal datasets","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"Provincia Autonoma di Trento; Centre National de la Recherche Scientifique; Université de Sherbrooke","keywords":"White matter; Tractography; Neuroimaging; Ex vivo; Human brain; Dissection (medical)","score_opus":0.043548607285335134,"score_gpt":0.40693170972642173,"score_spread":0.3633831024410866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415958339","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53571856,0.002152902,0.2688218,0.15947992,0.00036078674,0.013692975,0.0025304728,0.0015290971,0.015713494],"genre_scores_gemma":[0.94181246,0.000050989933,0.05442306,0.0021615215,0.000020001526,0.0007738458,0.00041424055,0.000020308436,0.0003235992],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991233,0.000058653724,0.00029051214,0.00029487367,0.00006724081,0.00016542614],"domain_scores_gemma":[0.9981044,0.00047971745,0.00008238838,0.001198794,0.0000960403,0.000038666065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020843942,0.0001408616,0.00019883367,0.00028810254,0.00050467654,0.000049176244,0.00027797846,0.00014219312,0.000015655774],"category_scores_gemma":[0.00027674928,0.00013987655,0.000053709842,0.0005919279,0.000106765816,0.000111897076,0.00023216326,0.00083005277,8.623192e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014795884,0.0016937834,0.6570573,0.00026686714,0.00012984946,0.0000028961124,0.0007980857,0.000017427212,0.17234325,0.04646992,0.112220466,0.0088522155],"study_design_scores_gemma":[0.0055345297,0.000268244,0.41151327,0.001319789,0.00041028563,0.00012023361,0.002328386,0.024241427,0.01245155,0.009734081,0.53115094,0.00092723424],"about_ca_topic_score_codex":0.00008157718,"about_ca_topic_score_gemma":0.0013456055,"teacher_disagreement_score":0.4189305,"about_ca_system_score_codex":0.00008338704,"about_ca_system_score_gemma":0.000028515431,"threshold_uncertainty_score":0.5704},"labels":[],"label_agreement":null},{"id":"W4416002342","doi":"10.22541/au.176253018.86072169/v1","title":"Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Medical Research Council; Canadian Institutes of Health Research; National Health and Medical Research Council; National Natural Science Foundation of China","keywords":"Undersampling; Acceleration; Sampling (signal processing); Diffusion; Iterative reconstruction; Pattern recognition (psychology); Signal reconstruction","score_opus":0.10011544123521207,"score_gpt":0.350063010551624,"score_spread":0.2499475693164119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416002342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08360405,0.00034943642,0.9027383,0.004548666,0.00033584939,0.0010669332,0.000021170621,0.00027585652,0.0070597837],"genre_scores_gemma":[0.8029786,0.0004752595,0.19436003,0.00059617753,0.000060502487,0.000040084917,0.000020268853,0.000033138866,0.001435986],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99784774,0.000045367222,0.00089867425,0.00063989765,0.0002096128,0.00035872794],"domain_scores_gemma":[0.99826944,0.000208112,0.0003242499,0.0008031327,0.00027804155,0.00011703828],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013897281,0.00030210897,0.00056665856,0.00037332342,0.00021086521,0.000029496277,0.00019397555,0.00017970132,0.0001481118],"category_scores_gemma":[0.000055492103,0.00029705596,0.00019267004,0.00071488327,0.00025436297,0.00022427799,0.00021676786,0.0003011493,0.0000056921976],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002941283,0.0006803805,0.00065668457,0.00041976085,0.00008103141,0.0000019956926,0.00014558161,0.00040244265,0.77941734,0.036811147,0.00019861056,0.1808909],"study_design_scores_gemma":[0.00418493,0.001051302,0.0013090087,0.0041089007,0.0010080691,0.00022698421,0.0009867224,0.21728148,0.2927404,0.47200507,0.0042565013,0.00084065064],"about_ca_topic_score_codex":0.00015818622,"about_ca_topic_score_gemma":0.0000122611855,"teacher_disagreement_score":0.7193745,"about_ca_system_score_codex":0.00020552624,"about_ca_system_score_gemma":0.00013431648,"threshold_uncertainty_score":0.99994814},"labels":[],"label_agreement":null},{"id":"W4416079897","doi":"10.1227/ons.0000000000001848","title":"Revisiting the Telovelar Approach for Lesions of the Mesial Part of the Cerebellar Peduncles by Using the Cerebellar Functional Networks to Guide Surgical Practice","year":2025,"lang":"en","type":"article","venue":"Operative Neurosurgery","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"White matter; Dissection (medical); Cerebellum; Brain anatomy; Clinical neurology; Microsurgery","score_opus":0.07352704740947871,"score_gpt":0.3731775910478172,"score_spread":0.29965054363833854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416079897","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2049896,0.002292438,0.53014183,0.23676917,0.0012986461,0.011151002,0.00037489957,0.00017184486,0.012810563],"genre_scores_gemma":[0.9779361,0.00032653648,0.0073129255,0.00961396,0.00073606864,0.00035519,0.00002453993,0.00006690179,0.0036278162],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99811983,0.00043925107,0.00053594005,0.00035500125,0.00031684167,0.00023316064],"domain_scores_gemma":[0.9962171,0.0022959881,0.00029193977,0.0007798534,0.0003732139,0.000041960924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008340553,0.00018656658,0.0003064518,0.000025625568,0.00090501126,0.000035383928,0.00032807488,0.0000643059,0.000009942596],"category_scores_gemma":[0.0013588945,0.000084627565,0.0002689753,0.000693244,0.0003277099,0.00006985598,0.0002913805,0.00042378495,2.2016154e-7],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015854402,0.0012619905,0.022468345,0.0003763051,0.0005265079,0.000009611224,0.0008902095,0.104236536,0.2576788,0.05103435,0.54267824,0.017253669],"study_design_scores_gemma":[0.0005854732,0.0000669501,0.0027610268,0.00037566246,0.000496462,0.00014615744,0.0008230867,0.028583506,0.04984767,0.00012869727,0.9159637,0.00022158319],"about_ca_topic_score_codex":0.000018625216,"about_ca_topic_score_gemma":5.7359483e-7,"teacher_disagreement_score":0.7729465,"about_ca_system_score_codex":0.00004073402,"about_ca_system_score_gemma":0.00022430847,"threshold_uncertainty_score":0.6960707},"labels":[],"label_agreement":null},{"id":"W4416140053","doi":"10.1093/neuonc/noaf201.1317","title":"NCOG-50. Correlation of tract-based diffusion metrics with visuospatial function following glioma surgery","year":2025,"lang":"en","type":"article","venue":"Neuro-Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Diffusion MRI; White matter; Arcuate fasciculus; Fractional anisotropy; Superior longitudinal fasciculus; Tractography; Fasciculus; Inferior longitudinal fasciculus; Human Connectome Project; Glioma","score_opus":0.03657880437120672,"score_gpt":0.3415430757264585,"score_spread":0.3049642713552518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416140053","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.61258644,0.00005595636,0.38262618,0.0020852282,0.00041376674,0.0005373651,0.0000039433253,0.00021773041,0.0014734099],"genre_scores_gemma":[0.99326956,0.000022490374,0.005431717,0.001041069,0.00005201975,0.00007702176,0.00005044304,0.000023676892,0.00003198861],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99887025,0.00007963668,0.00036349395,0.00031283623,0.00019930961,0.00017446141],"domain_scores_gemma":[0.99814403,0.0011460627,0.00023110604,0.0003014442,0.00011658337,0.00006075957],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016957287,0.00013919424,0.00039579888,0.0005195222,0.00009538305,0.0000057164634,0.000061945226,0.00013789111,0.00001576856],"category_scores_gemma":[0.00034663524,0.00012199803,0.00013826803,0.0010636584,0.000065837114,0.00006714529,0.000029348925,0.00027848865,0.0000032585688],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012696984,0.0011137973,0.11468654,0.00009269567,0.0000326942,0.0001334848,0.000024538373,0.0002629058,0.80288804,0.0008238239,0.002670778,0.07600098],"study_design_scores_gemma":[0.009570355,0.0072864317,0.24212752,0.00053048565,0.0019206147,0.00029091886,0.00014977682,0.041660186,0.313305,0.0014280671,0.38105524,0.00067544007],"about_ca_topic_score_codex":0.00003038228,"about_ca_topic_score_gemma":0.00000549356,"teacher_disagreement_score":0.48958308,"about_ca_system_score_codex":0.00011888698,"about_ca_system_score_gemma":0.00028606437,"threshold_uncertainty_score":0.49749354},"labels":[],"label_agreement":null},{"id":"W4416183376","doi":"10.1109/mipr67560.2025.00037","title":"Structural Mri Synthesis for Alzheimer's Disease Via Conditional Diffusion on Anatomical Masks","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Becton Dickinson (Canada)","funders":"","keywords":"Segmentation; Synthetic data; Generative model; Pattern recognition (psychology); Diffusion MRI; Process (computing); Fidelity; Neuroimaging","score_opus":0.05282526902645439,"score_gpt":0.37558248393275095,"score_spread":0.32275721490629655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416183376","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034502383,0.0011460033,0.87972707,0.07185381,0.0005952387,0.0053731077,0.001595325,0.00071574224,0.004491348],"genre_scores_gemma":[0.977843,0.00013193206,0.01462613,0.0049176426,0.00024514273,0.0008023655,0.0002829624,0.000044692795,0.0011061459],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979403,0.000042204403,0.00049449335,0.00081035733,0.00027623455,0.00043641802],"domain_scores_gemma":[0.99778485,0.00087647676,0.00012117095,0.0006989242,0.00014741255,0.0003711479],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000082117665,0.00037090862,0.0004178156,0.00022071108,0.00045834028,0.000038850325,0.00025133233,0.00013142827,0.0009313143],"category_scores_gemma":[0.00020987616,0.00032329906,0.00030870974,0.00026330343,0.0002911331,0.00008590494,0.00013174697,0.00030755968,0.000032877088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035169022,0.0012729546,0.006466022,0.00035183405,0.0005972603,0.000043358676,0.000023905523,0.0003049164,0.005681381,0.8321615,0.064524904,0.08505506],"study_design_scores_gemma":[0.0035862774,0.00042938135,0.09025497,0.0009628388,0.004443782,0.00001848636,0.000058842663,0.44640142,0.038657136,0.34827822,0.06583347,0.0010751754],"about_ca_topic_score_codex":0.000009018069,"about_ca_topic_score_gemma":8.746701e-7,"teacher_disagreement_score":0.9433406,"about_ca_system_score_codex":0.00011899716,"about_ca_system_score_gemma":0.00017302138,"threshold_uncertainty_score":0.999982},"labels":[],"label_agreement":null},{"id":"W4416234271","doi":"10.3389/fonc.2025.1605190","title":"Wallerian degeneration of the corticospinal tract following multimodal high-grade glioma treatment: a case series and recommendations for radiotherapy planning","year":2025,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Corticospinal tract; Radiation therapy; Wallerian degeneration; Pyramidal tracts; Complication; Glioma; Etiology; Astrocytoma","score_opus":0.04877081833163789,"score_gpt":0.3965515109962655,"score_spread":0.34778069266462763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416234271","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7551331,0.00085246214,0.22324517,0.019070001,0.00045636698,0.001117673,0.000025814783,0.000039708957,0.000059679907],"genre_scores_gemma":[0.7095903,0.00010106506,0.28965646,0.00019843974,0.000025072632,0.00026344974,0.000015934702,0.000007840118,0.00014141265],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994931,0.000034510445,0.00019482369,0.00015093708,0.000024653898,0.00010194936],"domain_scores_gemma":[0.9996977,0.00005749678,0.00007278046,0.00013481418,0.000016574017,0.000020669542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005628728,0.000076254146,0.00021555492,0.00010270952,0.00012385259,0.000004935793,0.000036422683,0.00005940857,0.0000014692923],"category_scores_gemma":[0.000033545974,0.00006006158,0.0000531204,0.00014668681,0.00006151433,0.000046902554,0.000010299901,0.000064381326,1.3027387e-8],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022998932,0.0026414609,0.19034937,0.00019316163,0.0006506246,0.0007178027,0.0041103447,0.00073425024,0.12152877,0.014618837,0.011978436,0.65017706],"study_design_scores_gemma":[0.03156525,0.008789619,0.061678614,0.00059050455,0.0014131322,0.0060148654,0.004370677,0.083357334,0.07026715,0.019436687,0.71182424,0.000691927],"about_ca_topic_score_codex":0.00004830147,"about_ca_topic_score_gemma":0.00002247285,"teacher_disagreement_score":0.6998458,"about_ca_system_score_codex":0.0001564996,"about_ca_system_score_gemma":0.000079672915,"threshold_uncertainty_score":0.24492401},"labels":[],"label_agreement":null},{"id":"W4416257142","doi":"10.1002/hbm.70408","title":"Utility of Harmonisation for Fixel‐Based Metrics in Travelling Subjects and Alzheimer's Disease Data","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Japan Agency for Medical Research and Development; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Diffusion MRI; Metric (unit); Comparability; Scanner; White matter; Subject matter","score_opus":0.3215893071424486,"score_gpt":0.4295181423094712,"score_spread":0.10792883516702262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416257142","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15707041,0.0007862011,0.8347646,0.0051790397,0.000019646382,0.0015047687,0.000091187445,0.00011261681,0.00047151552],"genre_scores_gemma":[0.9772405,0.000012190494,0.021851486,0.00060795626,0.00001338143,0.000039811628,0.0001916634,0.000008343152,0.000034676334],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993149,0.000019777632,0.00021676216,0.00027715453,0.00006721068,0.00010417485],"domain_scores_gemma":[0.99912757,0.0002851182,0.000065974884,0.00044056898,0.000040168004,0.00004062518],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029769397,0.000071573064,0.0001478163,0.00023339469,0.00008606857,0.000009378233,0.000103154336,0.000024537116,0.0000033561364],"category_scores_gemma":[0.00031241702,0.00007751025,0.00002432666,0.00031608046,0.00005582108,0.00005443223,0.000053342214,0.000065246124,7.847505e-8],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007760247,0.0019878272,0.4264637,0.005449234,0.00022097897,0.00003046829,0.0008818723,0.00015711258,0.24422638,0.103596374,0.015562112,0.2006479],"study_design_scores_gemma":[0.0016150931,0.00003256115,0.7943083,0.00045762345,0.00012980886,5.1450354e-7,0.00006701278,0.16198595,0.0036703118,0.01838871,0.019205365,0.00013874937],"about_ca_topic_score_codex":0.000011653879,"about_ca_topic_score_gemma":0.0000050429894,"teacher_disagreement_score":0.8201701,"about_ca_system_score_codex":0.000009658902,"about_ca_system_score_gemma":0.000053650067,"threshold_uncertainty_score":0.31607765},"labels":[],"label_agreement":null},{"id":"W4416291370","doi":"10.1038/s42003-025-08954-4","title":"Early but discontinued exposure to a language exerts lasting effects on white matter architecture in the brain","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University; Centre for Research on Brain Language and Music; Montreal Neurological Institute and Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Centre for Research on Brain, Language and Music","keywords":"Mandarin Chinese; Arcuate fasciculus; White matter; Cognition; Neuroscience of multilingualism; Lateralization of brain function; Expressive Suppression; Neuroimaging","score_opus":0.028771641143775076,"score_gpt":0.36678769723325383,"score_spread":0.33801605608947877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416291370","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7622308,0.00029953857,0.011195346,0.21372393,0.000026738237,0.0011525459,0.000015645619,0.00012356482,0.011231859],"genre_scores_gemma":[0.9707292,0.000011019007,0.0113229,0.016452717,0.000022151477,0.00050533994,0.000040220966,0.000009451435,0.00090703234],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992907,0.00019971168,0.00015181147,0.00017842685,0.000031186926,0.0001481487],"domain_scores_gemma":[0.9974774,0.00087276753,0.00003633796,0.0015693425,0.000019921245,0.000024198573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013665746,0.00009334435,0.00014560318,0.00014913768,0.000113009926,0.000012500674,0.0005353667,0.000052087456,0.000005721991],"category_scores_gemma":[0.0002390338,0.0000643052,0.00003767342,0.00035336684,0.000082122264,0.000012144458,0.00020956408,0.00036159813,0.000023671093],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002015135,0.00073156616,0.63942623,0.00014316097,0.000053007403,0.00002141001,0.009837551,0.000037101083,0.14413843,0.037809737,0.021798907,0.14580137],"study_design_scores_gemma":[0.0008076948,0.00041601397,0.92109025,0.00062971987,0.00003822621,0.000030745552,0.00034411094,0.000054741507,0.0026832144,0.005609307,0.06808931,0.00020665699],"about_ca_topic_score_codex":0.000024927327,"about_ca_topic_score_gemma":0.00005446613,"teacher_disagreement_score":0.281664,"about_ca_system_score_codex":0.000019556546,"about_ca_system_score_gemma":0.000014360405,"threshold_uncertainty_score":0.262229},"labels":[],"label_agreement":null},{"id":"W4416388641","doi":"10.1038/s42003-025-08981-1","title":"Microstructural maturation of the adult mouse brain","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Government of Canada","keywords":"Kurtosis; Fractional anisotropy; Diffusion MRI; Oligodendrocyte; White matter; Myelin; Diffusion","score_opus":0.05152972534530199,"score_gpt":0.3994223674831016,"score_spread":0.34789264213779963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416388641","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5706637,0.0011076912,0.021028467,0.3871519,0.00014904032,0.0015907206,0.000103731465,0.00032932058,0.017875414],"genre_scores_gemma":[0.972266,0.00014548363,0.023330634,0.003167074,0.0000058109954,0.00004754968,0.00006255742,0.0000039163565,0.000970935],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99963826,0.000051572188,0.0001545363,0.00008047596,0.000016801567,0.000058353362],"domain_scores_gemma":[0.9982614,0.0001054925,0.000067782654,0.0014362161,0.00011921829,0.000009884941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035001027,0.000045559213,0.00008709945,0.00004087443,0.000119594,0.0000025378295,0.000399371,0.0000437007,0.0000044382186],"category_scores_gemma":[0.0001570861,0.000031166583,0.00004387547,0.00022199564,0.0003223274,0.000014649756,0.00024074347,0.00014392154,0.0000017325765],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015786874,0.000046529745,0.012882537,0.000013354266,0.000012007384,1.8099211e-8,0.00003567989,6.3729044e-7,0.5901469,0.38631627,0.004116741,0.006413553],"study_design_scores_gemma":[0.001085672,0.000097330034,0.15277806,0.0001476168,0.00009003313,0.000044647823,0.00014397496,0.0017635691,0.4258097,0.09614597,0.32170784,0.000185564],"about_ca_topic_score_codex":0.000014819597,"about_ca_topic_score_gemma":0.000010249223,"teacher_disagreement_score":0.40160233,"about_ca_system_score_codex":0.00001825499,"about_ca_system_score_gemma":0.000036115587,"threshold_uncertainty_score":0.12709364},"labels":[],"label_agreement":null},{"id":"W4416431621","doi":"10.1615/critrevbiomedeng.2025059839","title":"Diffusion Tensor Imaging for Brain Injury Assessment: Methodological Foundations and Clinical Insights","year":2025,"lang":"en","type":"article","venue":"Critical Reviews in Biomedical Engineering","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University; McMaster University Medical Centre; St. Joseph’s Healthcare Hamilton","funders":"","keywords":"Diffusion MRI; Neuroimaging; Interpretability; Traumatic brain injury; White matter; Functional neuroimaging","score_opus":0.20445534852867076,"score_gpt":0.5546723545852813,"score_spread":0.35021700605661055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416431621","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034434085,0.002210176,0.96741253,0.025373632,0.0001915436,0.0009653827,0.000006923298,0.00015752009,0.00023889537],"genre_scores_gemma":[0.12144726,0.0053975713,0.8658002,0.0061844285,0.00024147185,0.0007429076,0.000050876268,0.000033125605,0.0001021683],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982904,0.00010571866,0.0007705067,0.0004409074,0.00011996621,0.00027249067],"domain_scores_gemma":[0.9958171,0.003584475,0.00003576088,0.000282634,0.000058079633,0.00022193405],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0011744248,0.00016520667,0.000585931,0.00021043894,0.00007834137,0.000022820881,0.00010672536,0.0001182553,0.000014683752],"category_scores_gemma":[0.016649563,0.00012882684,0.00013967256,0.0004294222,0.00030139837,0.00006583134,0.00012677789,0.00049849314,0.0000018410528],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049264072,0.0007786534,0.008238125,0.0016216412,0.0000217015,0.00002962434,0.000016877386,0.00000107183,0.013395084,0.35438284,0.0058114985,0.61565363],"study_design_scores_gemma":[0.00090259034,0.00016314798,0.030370584,0.0017200992,0.000109777015,0.000026342379,0.000010898569,0.07818616,0.000054102587,0.018095324,0.8701416,0.00021932679],"about_ca_topic_score_codex":0.000001150161,"about_ca_topic_score_gemma":1.8262163e-7,"teacher_disagreement_score":0.8643302,"about_ca_system_score_codex":0.00006340238,"about_ca_system_score_gemma":0.000049277933,"threshold_uncertainty_score":0.9916336},"labels":[],"label_agreement":null},{"id":"W4416510209","doi":"10.1162/imag.a.1035","title":"Advanced diffusion imaging in grey matter reflects individual differences in cognitive ability in older adults","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; DoD Alzheimer's Disease Neuroimaging Initiative; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Biogen; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; National Institute on Aging; Alzheimer's Association","keywords":"Working memory; Cognition; Diffusion MRI; Elementary cognitive task; Task (project management); Lateralization of brain function; Diffusion","score_opus":0.03717804297074438,"score_gpt":0.3725359190231563,"score_spread":0.3353578760524119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416510209","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99057823,0.00011266725,0.0023446234,0.004856799,0.00011892169,0.00089944387,0.000008801118,0.00010894973,0.0009715338],"genre_scores_gemma":[0.9935944,0.00004519367,0.00081238756,0.005278122,0.000008010675,0.0001795152,0.000004849301,0.000014337345,0.00006316983],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99785477,0.00007684855,0.00041687273,0.0009161947,0.00025908352,0.00047626017],"domain_scores_gemma":[0.999245,0.0001943251,0.000087404536,0.00034500175,0.000060532253,0.0000677331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002463113,0.00021016214,0.00028651443,0.0006144921,0.00008129515,0.000054620727,0.000287426,0.000027193613,0.000009885621],"category_scores_gemma":[0.00050083315,0.00020101079,0.000037856928,0.0015229443,0.00033825354,0.00038749687,0.00024008196,0.0005072929,0.0000031813229],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000062531304,0.00031470513,0.9564578,0.000038398208,1.6550858e-7,0.000078266195,0.00029632216,0.0000039793777,0.02042027,0.000039090068,0.00002544406,0.022263015],"study_design_scores_gemma":[0.0015704435,0.00001817756,0.9885281,0.001269146,0.0000051575153,0.00002249394,0.00018095733,0.0046194354,0.0025394873,0.0010406558,0.00004638894,0.00015955862],"about_ca_topic_score_codex":0.00012876815,"about_ca_topic_score_gemma":0.000046618352,"teacher_disagreement_score":0.032070283,"about_ca_system_score_codex":0.000105022664,"about_ca_system_score_gemma":0.00008639291,"threshold_uncertainty_score":0.8196982},"labels":[],"label_agreement":null},{"id":"W4416595726","doi":"10.1038/s41598-025-25400-x","title":"Challenges and best practices when using ComBAT to harmonize diffusion MRI data","year":2025,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; Q & T Research; Université de Sherbrooke","funders":"National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Mitacs; Eisai; Québec Consortium for Drug Discovery; University of Southern California; Université de Sherbrooke; Northern California Institute for Research and Education; BioClinica; Natural Sciences and Engineering Research Council of Canada; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Alzheimer's Association","keywords":"Best practice; Consistency (knowledge bases); Normative; Multiplicative function; Set (abstract data type); Population","score_opus":0.3568150277456852,"score_gpt":0.4593066519482567,"score_spread":0.10249162420257152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416595726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84901017,0.010357223,0.041039564,0.07167347,0.0034420623,0.002945807,0.00001735573,0.00061783404,0.020896513],"genre_scores_gemma":[0.7562703,0.0015590608,0.22273129,0.0008799756,0.00013016858,0.00006342154,0.00015132509,0.00003914323,0.01817534],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985914,0.000014736922,0.00022964393,0.0008201853,0.0001993597,0.00014467286],"domain_scores_gemma":[0.99785465,0.00004308108,0.00021766617,0.0016890418,0.000099294295,0.00009628153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053529016,0.00008729216,0.0001440624,0.0001358231,0.0002418754,0.000102502134,0.00013180732,0.000029775994,0.000008936606],"category_scores_gemma":[0.0004181538,0.0000755785,0.000015543286,0.00020154343,0.000112934176,0.00020014732,0.00051779434,0.00010017267,0.0000031635],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000056965044,0.0010158196,0.010362887,0.0004227744,0.000048360933,0.0007834701,0.0009638321,0.000010056662,0.57526046,0.0020379082,0.10963357,0.29940388],"study_design_scores_gemma":[0.00014308996,0.000039541526,0.0024956039,0.00038142593,0.000117111085,0.00058555213,0.00021628368,0.001792846,0.009667136,0.013196852,0.9712312,0.00013333916],"about_ca_topic_score_codex":0.000035910485,"about_ca_topic_score_gemma":0.000015156193,"teacher_disagreement_score":0.86159766,"about_ca_system_score_codex":0.000021913582,"about_ca_system_score_gemma":0.00007614868,"threshold_uncertainty_score":0.30820018},"labels":[],"label_agreement":null},{"id":"W4416610599","doi":"10.1002/hbm.70417","title":"In Vivo Quantification of White Matter Pathways in the Human Hippocampus","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Hippocampal formation; White matter; Hippocampus; In vivo; Cognition; Human brain","score_opus":0.08480388152076788,"score_gpt":0.3596885992740911,"score_spread":0.2748847177533232,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416610599","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9534191,0.00003692025,0.011729481,0.01998435,0.000019447409,0.000698928,0.0000034241066,0.00005946632,0.01404892],"genre_scores_gemma":[0.99374515,0.0000028524287,0.0010076012,0.00429406,0.000020199868,0.00010583437,0.000010572678,0.000009162208,0.00080456765],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99921167,0.000052775555,0.0003139342,0.0002038992,0.00008770869,0.00013000646],"domain_scores_gemma":[0.9993789,0.00007233932,0.00008129513,0.00043071122,0.000025148287,0.000011573892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033666586,0.00008087537,0.00015153944,0.00026366973,0.00012698518,0.000009153028,0.00015508369,0.000037271275,0.000060529637],"category_scores_gemma":[0.00002699302,0.00006953154,0.000037670925,0.00040618764,0.00006501381,0.00004873744,0.000046624245,0.0001924106,0.000004101491],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000004277449,0.00015915961,0.12735993,0.00016892907,0.0000037681648,0.000008322063,0.0018271615,0.000013756279,0.7714119,0.08195933,0.01684447,0.00023901452],"study_design_scores_gemma":[0.0005212624,0.000022419516,0.8842143,0.00047016682,0.0000077918485,0.0000066245766,0.00052584056,0.00013495024,0.0026969998,0.094309,0.01699223,0.00009841572],"about_ca_topic_score_codex":0.000026272031,"about_ca_topic_score_gemma":0.000022753899,"teacher_disagreement_score":0.7687149,"about_ca_system_score_codex":0.000034776916,"about_ca_system_score_gemma":0.0000134322145,"threshold_uncertainty_score":0.28354138},"labels":[],"label_agreement":null},{"id":"W4416697937","doi":"10.1111/epi.70038","title":"Mapping white matter tracts with <scp>SEEG</scp> electrodes","year":2025,"lang":"en","type":"article","venue":"Epilepsia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Epilepsy Research UK","keywords":"Stereoelectroencephalography; White matter; Tractography; Electrode; Deep brain stimulation; Stimulation; Radiomics","score_opus":0.024930474713962335,"score_gpt":0.3077977485338836,"score_spread":0.28286727381992127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416697937","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47162724,0.00023794112,0.34574732,0.018657008,0.000047746737,0.0008899828,0.0000073267925,0.00075025,0.16203517],"genre_scores_gemma":[0.927825,0.000050719,0.041307993,0.006490413,0.00007235856,0.000138312,0.000021607559,0.00003335054,0.02406026],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99917114,0.000012542064,0.00016019092,0.00028897705,0.00010526245,0.00026190985],"domain_scores_gemma":[0.999367,0.00006843566,0.00005470356,0.0003939606,0.000051796695,0.00006410937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000054737862,0.00013483889,0.00019173427,0.000129804,0.00008875052,0.000021066257,0.00009678046,0.000044563312,0.000037931022],"category_scores_gemma":[0.000030367097,0.000110682144,0.00004553105,0.00038834068,0.00005324248,0.00006715254,0.000028619492,0.00025128975,0.00008168427],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029241939,0.00023759258,0.62836075,0.00017471402,0.00006736797,0.000059909093,0.00026234373,0.000022742557,0.041979272,0.0076918257,0.3174164,0.0036978186],"study_design_scores_gemma":[0.0005121639,0.00008723721,0.6031119,0.00022924702,0.000048181893,0.000094259434,0.00008020455,0.00018923302,0.018590137,0.0022208288,0.37476903,0.000067555244],"about_ca_topic_score_codex":0.0000031351624,"about_ca_topic_score_gemma":8.184039e-7,"teacher_disagreement_score":0.45619774,"about_ca_system_score_codex":0.00003644098,"about_ca_system_score_gemma":0.000047164463,"threshold_uncertainty_score":0.4513487},"labels":[],"label_agreement":null},{"id":"W4416842357","doi":"10.1186/s40478-025-02183-w","title":"MRI investigation of orientation-dependent changes in microstructure and function in a mouse model of mild traumatic brain injury","year":2025,"lang":"en","type":"article","venue":"Acta Neuropathologica Communications","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Peer Reviewed Alzheimer’s Research Program; Canadian Institutes of Health Research; Canada Research Chairs","keywords":"White matter; Traumatic brain injury; Diffusion MRI; Kurtosis; Neuroimaging; Magnetic resonance imaging; Thermal diffusivity; Rotation (mathematics)","score_opus":0.09943251725005171,"score_gpt":0.359532328680109,"score_spread":0.2600998114300573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416842357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9863795,0.00009808884,0.0020260352,0.01062643,0.000008464424,0.000607753,0.000041483767,0.000044236196,0.00016802488],"genre_scores_gemma":[0.9816852,0.0008636117,0.01627234,0.00091483106,0.0000017505068,0.0001340396,0.00004310088,0.000009134428,0.00007597948],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999157,0.000116290415,0.00036433502,0.0001986034,0.00007367422,0.000090114976],"domain_scores_gemma":[0.998731,0.00016717422,0.00017198439,0.00083253,0.00007267365,0.000024612349],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018558252,0.00009741556,0.0002178016,0.0003197627,0.000052507643,0.0000050178182,0.00021191307,0.0000634178,0.000001723715],"category_scores_gemma":[0.00015640368,0.00009360075,0.000022840763,0.00048139776,0.00023118363,0.00006721345,0.00017022713,0.00026519215,1.3486705e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005918155,0.00014802253,0.054298982,0.00009241817,0.0000031634422,4.6998244e-7,0.0006684106,0.00009720899,0.93762785,0.0058365706,0.00004780883,0.0011198994],"study_design_scores_gemma":[0.0016892687,0.00042796496,0.7747983,0.00042660383,0.00008940008,0.000017309958,0.0006908499,0.021699997,0.16360563,0.036100175,0.00021685468,0.000237653],"about_ca_topic_score_codex":0.000020768195,"about_ca_topic_score_gemma":0.00007830246,"teacher_disagreement_score":0.7740222,"about_ca_system_score_codex":0.00002640646,"about_ca_system_score_gemma":0.000040799572,"threshold_uncertainty_score":0.38169277},"labels":[],"label_agreement":null},{"id":"W4417146313","doi":"10.3389/fpsyt.2025.1650055","title":"Cortical microstructural changes in schizophrenia spectrum disorders using quantitative T1 mapping","year":2025,"lang":"en","type":"article","venue":"Frontiers in Psychiatry","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"Canadian Institutes of Health Research","keywords":"Schizophrenia (object-oriented programming); Reliability (semiconductor); Schizophrenia spectrum; Neuroimaging; Brain mapping; Selection (genetic algorithm); Functional connectivity","score_opus":0.029352305162599533,"score_gpt":0.34511024494519527,"score_spread":0.31575793978259575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417146313","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78122115,0.0018550497,0.19279219,0.019813491,0.0028197006,0.0007135886,0.000011462513,0.00011217216,0.0006612186],"genre_scores_gemma":[0.49016944,0.00017860497,0.50873685,0.00074887194,0.000048707865,0.000028649307,0.000009632938,0.000018270808,0.000060965438],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.999008,0.000030581847,0.00026905994,0.0003338752,0.00007967317,0.00027879074],"domain_scores_gemma":[0.99962044,0.00001964911,0.000060971724,0.00024782107,0.000009241023,0.00004186346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000078130586,0.00014644967,0.0002674739,0.0004716513,0.00007363127,0.000012019796,0.00011013971,0.00007286931,0.0000066983193],"category_scores_gemma":[0.00003403737,0.00014972076,0.00005066973,0.00078492967,0.00013212176,0.00005194266,0.000046770365,0.00042979655,9.871651e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003735295,0.00015441816,0.9634452,0.00013835361,0.00002857143,0.000006976049,0.00018887692,0.000043469125,0.0039875815,0.021564757,0.006429726,0.0036385262],"study_design_scores_gemma":[0.003737279,0.00014012081,0.7437969,0.0010996272,0.00006327095,0.000025153537,0.0020210792,0.01749996,0.0010313925,0.22522153,0.004925535,0.00043818553],"about_ca_topic_score_codex":0.000041541945,"about_ca_topic_score_gemma":0.00019018444,"teacher_disagreement_score":0.31594467,"about_ca_system_score_codex":0.00011819118,"about_ca_system_score_gemma":0.00009802047,"threshold_uncertainty_score":0.61054355},"labels":[],"label_agreement":null},{"id":"W4417189574","doi":"10.1002/hbm.70414","title":"Psychotic‐Like Experiences and White Matter Microstructure: A Fixel‐Based Analysis Approach With Robust Replication Across Two Cohorts","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Centre Hospitalier Universitaire Sainte-Justine","funders":"Medical Research Council; H. Lundbeck A/S; Fédération pour la Recherche sur le Cerveau; Fondation pour la Recherche Médicale; Fondation de France; National Imaging Facility; Bundesministerium für Bildung und Forschung; National Natural Science Foundation of China; Centre of Excellence for Integrative Brain Function, Australian Research Council; Lundbeckfonden; Institut National de la Santé et de la Recherche Médicale; HORIZON EUROPE Framework Programme; Agence Nationale de la Recherche; Mission Interministérielle de Lutte Contre les Drogues et les Conduites Addictives; UK Research and Innovation; Science Foundation Ireland; European Commission; Australian Government; Deutsche Forschungsgemeinschaft; National Institutes of Health; Fondation de l'Avenir pour la Recherche Médicale Appliquée","keywords":"White matter; Diffusion MRI; Neuroimaging; Replication (statistics); Tractography; Schizotypy; Diffusion imaging","score_opus":0.05083138182168458,"score_gpt":0.36338135314713954,"score_spread":0.312549971325455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417189574","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5361399,0.000050639916,0.4581972,0.0034440488,0.000010456728,0.0005784695,0.0000060234347,0.00017384993,0.0013993876],"genre_scores_gemma":[0.93070126,0.0000022797788,0.062170696,0.0055213566,0.000025770349,0.00035559037,0.00010924383,0.000017628485,0.0010962085],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986769,0.000027048467,0.0002444196,0.0006988478,0.00012468049,0.0002281081],"domain_scores_gemma":[0.9988608,0.00003505775,0.00011907712,0.0008538255,0.00006815627,0.000063085165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001648701,0.00017094827,0.00028909516,0.00019893664,0.00039670567,0.00008440939,0.0001197686,0.0000457493,0.000040054027],"category_scores_gemma":[0.000011923693,0.00014609042,0.00006435564,0.00089018646,0.0002200956,0.000068124806,0.000045137775,0.00016842512,0.0000010451621],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008971152,0.00017838605,0.92903256,0.00029837003,0.0002857002,0.000009344735,0.0050574536,0.0010680008,0.04930588,0.0008625714,0.012736064,0.0010759752],"study_design_scores_gemma":[0.0010431116,0.000040806153,0.9826546,0.00014693844,0.00023298248,0.00003698241,0.0016475362,0.006675154,0.00044410155,0.00055564946,0.0062528714,0.00026930464],"about_ca_topic_score_codex":0.000016075952,"about_ca_topic_score_gemma":0.000012894975,"teacher_disagreement_score":0.39602652,"about_ca_system_score_codex":0.000031945914,"about_ca_system_score_gemma":0.000018019633,"threshold_uncertainty_score":0.5957394},"labels":[],"label_agreement":null},{"id":"W4417399411","doi":"10.1016/j.neuroimage.2025.121656","title":"Spatially regularized super-resolved constrained spherical deconvolution (SR2-CSD) of diffusion MRI data","year":2025,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agencia Estatal de Investigación; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; European Social Fund; Ministerio de Ciencia, Innovación y Universidades","keywords":"Deconvolution; Spatial coherence; Prior probability; Tractography; Image resolution; Spherical harmonics; Diffusion MRI; Orientation (vector space); Coherence (philosophical gambling strategy)","score_opus":0.0675359183058252,"score_gpt":0.3609758912461194,"score_spread":0.2934399729402942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417399411","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13364214,0.00011597278,0.84497535,0.011742902,0.00016456476,0.0013429177,0.00015483885,0.00055343896,0.007307879],"genre_scores_gemma":[0.7909437,0.0002119648,0.2046883,0.0018651674,0.00007689905,0.000039132763,0.0004110109,0.00004496375,0.0017188839],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985003,0.00005884679,0.00042577248,0.00057694205,0.00021186932,0.00022629206],"domain_scores_gemma":[0.99800044,0.0001341738,0.000113496964,0.0015411286,0.00012143183,0.00008934194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013986055,0.00017476072,0.00036352177,0.000092159666,0.00008953811,0.000015399202,0.00037554337,0.00007998722,0.000100349236],"category_scores_gemma":[0.00034578168,0.0001654235,0.00008391522,0.0003719698,0.00029006504,0.00011139569,0.00037776108,0.00027186092,0.000007867851],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002533799,0.00039949422,0.0037948515,0.00010244246,0.00001772794,0.00004850607,0.00001514279,0.0000046634927,0.969414,0.0026577709,0.007938801,0.015353234],"study_design_scores_gemma":[0.014284938,0.0011819026,0.20529656,0.00088042044,0.0009684697,0.0003730668,0.00009417771,0.122797996,0.20572878,0.0106511675,0.43668023,0.0010622896],"about_ca_topic_score_codex":0.000042835636,"about_ca_topic_score_gemma":0.0000066373077,"teacher_disagreement_score":0.7636852,"about_ca_system_score_codex":0.000028416207,"about_ca_system_score_gemma":0.00014414609,"threshold_uncertainty_score":0.6745774},"labels":[],"label_agreement":null},{"id":"W53841409","doi":"10.1007/978-3-642-33415-3_86","title":"Tractometer: Online Evaluation System for Tractography","year":2012,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Deconvolution; Wavelet; Artificial intelligence; Noise reduction; Pattern recognition (psychology); Data mining; Algorithm; Diffusion MRI","score_opus":0.10058233065189592,"score_gpt":0.4048299809011763,"score_spread":0.30424765024928035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W53841409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21047644,0.000104845705,0.7879072,0.0005912646,0.0001867983,0.0006123892,0.000004764461,0.00010835803,0.000007957294],"genre_scores_gemma":[0.64092684,0.0000019225924,0.35849237,0.00033033412,0.00018324735,0.000051534193,0.000007598695,0.0000060292673,1.3038661e-7],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989905,0.0000148298805,0.00016143861,0.00026708827,0.00028587165,0.00028027617],"domain_scores_gemma":[0.9992426,0.00016166888,0.000058739966,0.00030772036,0.00013910182,0.00009017749],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005870876,0.00009197962,0.00013185338,0.00025545075,0.000108424,0.000030371977,0.00015673906,0.000036489062,0.0000020299995],"category_scores_gemma":[0.00009742753,0.00007499722,0.000051136674,0.00088215666,0.00013530235,0.00019314986,0.000030736777,0.00012817617,0.0000010986417],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019852308,0.0002644068,0.014143015,0.0000716393,0.0000035099602,8.908922e-7,0.0003766598,0.001651504,0.033296153,0.00023097164,0.000011195641,0.9499302],"study_design_scores_gemma":[0.001388492,0.00039019328,0.13069883,0.0002621786,0.00006548059,0.00023834752,0.0000049274445,0.7230835,0.13764673,0.003932645,0.0019401768,0.00034847684],"about_ca_topic_score_codex":0.000003425725,"about_ca_topic_score_gemma":0.000001390259,"teacher_disagreement_score":0.94958174,"about_ca_system_score_codex":0.000097263015,"about_ca_system_score_gemma":0.00006858481,"threshold_uncertainty_score":0.30582976},"labels":[],"label_agreement":null},{"id":"W560408112","doi":"10.71781/18789","title":"Étude de la réorganisation fonctionnelle des aires cérébrales de réception des afférences auditives chez les personnes ayant une atteinte structurelle","year":2007,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Monaural; Psychology; Lesion; Corpus callosum; Neuroscience; Anatomy; Audiology; Medicine","score_opus":0.014503197538364574,"score_gpt":0.2521426594933745,"score_spread":0.23763946195500993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W560408112","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91639787,0.013567275,0.06379101,0.0003254401,0.00028964697,0.00050225767,0.00006814637,0.00035678258,0.0047015995],"genre_scores_gemma":[0.9543095,0.006215957,0.029030515,0.00007345469,0.00057819474,0.000058829744,0.00041493718,0.00006935109,0.009249215],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99738765,0.0002515228,0.00046035,0.000731844,0.00050035765,0.0006682545],"domain_scores_gemma":[0.99808735,0.00035200786,0.00049136404,0.0003319014,0.0003767494,0.00036060854],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00035843617,0.00055372063,0.00044517542,0.00048059958,0.00976131,0.00011034167,0.00033042041,0.0005793425,0.00013984261],"category_scores_gemma":[0.00019718343,0.00063416816,0.000321786,0.00059970585,0.0022109442,0.0004581849,0.000102008,0.000693367,0.00002475904],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010740262,0.0006576037,0.11357284,0.0008897421,0.0004519172,0.0008147377,0.19991928,0.008403768,0.5999618,0.03449829,0.00037706865,0.039378908],"study_design_scores_gemma":[0.0011282903,0.00028518133,0.6573464,0.001528793,0.0008383311,0.002134078,0.17463322,0.0031945438,0.14378382,0.008760113,0.0056182547,0.0007489436],"about_ca_topic_score_codex":0.09269569,"about_ca_topic_score_gemma":0.02687474,"teacher_disagreement_score":0.5437736,"about_ca_system_score_codex":0.0067813876,"about_ca_system_score_gemma":0.0012427557,"threshold_uncertainty_score":0.99961096},"labels":[],"label_agreement":null},{"id":"W575675008","doi":"10.1212/wnl.84.14_supplement.s15.007","title":"Longitudinal Voxel-Based Analysis of Brain Atrophy over 6 and 12 Months in CBD and PSP from Two Multicenter Studies (S15.007)","year":2015,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Western Hospital; University of Toronto","funders":"","keywords":"Voxel-based morphometry; Atrophy; Voxel; Neuroscience; Medicine; Multicenter study; Physical medicine and rehabilitation; Pathology; Psychology; Radiology; Magnetic resonance imaging; White matter; Randomized controlled trial","score_opus":0.09675726929919488,"score_gpt":0.39920910675740184,"score_spread":0.302451837458207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W575675008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99302167,0.00061608694,0.0010797224,0.004968676,0.000023824101,0.00019531391,0.000020490215,0.00003482322,0.000039398914],"genre_scores_gemma":[0.994758,0.00008722623,0.0025813414,0.002489291,0.000029380748,0.000020201893,0.000012851293,0.000011350548,0.000010332047],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992079,0.000053133415,0.0002007648,0.00032310115,0.000082290186,0.00013281418],"domain_scores_gemma":[0.9992884,0.000261619,0.00007860248,0.0002471199,0.00005140493,0.00007286104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000742723,0.00010697336,0.00038490433,0.00021301823,0.000018412971,0.0000031699037,0.00004556103,0.000041624422,0.0000070232268],"category_scores_gemma":[0.00012966637,0.00009407731,0.000042883777,0.00020926246,0.00020810535,0.00003255765,0.0000722677,0.00015390031,5.8343545e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005513628,0.00008400678,0.9942205,0.000011303059,0.00012173053,0.000057252248,0.00015275317,0.00019125296,0.0032427558,0.00008331029,0.0002599541,0.0010238207],"study_design_scores_gemma":[0.0023852126,0.0005089872,0.977239,0.000008865975,0.00044002282,0.000005663209,0.00001349631,0.016888013,0.0003065116,0.00065156823,0.001477636,0.00007501444],"about_ca_topic_score_codex":0.0003793288,"about_ca_topic_score_gemma":0.00038818226,"teacher_disagreement_score":0.01698149,"about_ca_system_score_codex":0.000009637736,"about_ca_system_score_gemma":0.000012392213,"threshold_uncertainty_score":0.38363612},"labels":[],"label_agreement":null},{"id":"W577586447","doi":"10.1016/j.dib.2015.05.019","title":"Quantitative analysis of the myelin g -ratio from electron microscopy images of the macaque corpus callosum","year":2015,"lang":"en","type":"article","venue":"Data in Brief","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Université Laval; Montreal Neurological Institute and Hospital; McGill University; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Myelin; Corpus callosum; Axon; Macaque; Magnetic resonance imaging; Electron microscope; Stereology; Anatomy; Myelin sheath; Aspect ratio (aeronautics); Biology; Pathology; Chemistry; Nuclear magnetic resonance; Materials science; Medicine; Physics; Neuroscience; Central nervous system; Optics; Radiology","score_opus":0.11724128166656239,"score_gpt":0.41942288485755297,"score_spread":0.3021816031909906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W577586447","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96742857,0.00040961156,0.021397052,0.0050344565,0.00005073646,0.0006137169,0.004669275,0.00003249493,0.00036407946],"genre_scores_gemma":[0.98175424,0.00008219032,0.016846057,0.00047962676,0.000015689795,0.000015141134,0.0007035938,0.000011073864,0.00009240003],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992599,0.00005382134,0.0002376842,0.00020617063,0.00015418847,0.000088241526],"domain_scores_gemma":[0.99834526,0.000098946075,0.00017305187,0.0012859404,0.0000731994,0.000023598284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001217414,0.000068670444,0.0002154682,0.000051322004,0.000024010966,0.000004957622,0.00047818694,0.00002752217,0.000008263185],"category_scores_gemma":[0.00028700207,0.00004228504,0.000049164508,0.0006854056,0.00017927596,0.00006173663,0.00023019037,0.0001539741,7.8626834e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015240302,0.00025577383,0.18524854,0.000019207437,0.00022124291,0.000002236719,0.00034225726,0.000111345405,0.7883645,0.004422731,0.02033188,0.0005278848],"study_design_scores_gemma":[0.0007513985,0.00011525292,0.3152292,0.00010967123,0.0009660412,0.0000033129018,0.00013514803,0.008888289,0.6531928,0.0035323638,0.016944803,0.00013168497],"about_ca_topic_score_codex":0.0019844007,"about_ca_topic_score_gemma":0.00034532012,"teacher_disagreement_score":0.13517167,"about_ca_system_score_codex":0.000027137812,"about_ca_system_score_gemma":0.00008309633,"threshold_uncertainty_score":0.29998335},"labels":[],"label_agreement":null},{"id":"W620785370","doi":"","title":"Phantomas: a flexible software library to simulate diffusion MR phantoms","year":2014,"lang":"en","type":"preprint","venue":"Infoscience (Ecole Polytechnique Fédérale de Lausanne)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Tractography; Computer science; Preprocessor; Imaging phantom; Pipeline (software); Software; Diffusion MRI; Diffusion; Field (mathematics); Artificial intelligence; Magnetic resonance imaging; Physics; Nuclear medicine; Radiology; Mathematics; Medicine; Programming language","score_opus":0.04425934752557032,"score_gpt":0.34723979454588894,"score_spread":0.3029804470203186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W620785370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17157108,0.00026852923,0.8017683,0.0066488376,0.00040862162,0.0054592863,0.00029345887,0.008886456,0.0046954607],"genre_scores_gemma":[0.52927095,0.00055707095,0.4450609,0.014545326,0.0005762958,0.002425233,0.00021438504,0.00026395076,0.007085858],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9953957,0.00009580796,0.00090550166,0.0016371447,0.0007218881,0.0012439307],"domain_scores_gemma":[0.9958264,0.00020429795,0.00048354082,0.002375211,0.00018466871,0.0009258798],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004818096,0.0007905978,0.00095672224,0.0008734949,0.00037256163,0.00027921365,0.0015898818,0.00067353377,0.00018530207],"category_scores_gemma":[0.0004197048,0.00079309347,0.00038380362,0.0011842923,0.0003724502,0.00045504636,0.0026348978,0.0015248698,0.00012570988],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014209048,0.003877423,0.08468397,0.0042853667,0.00018193833,0.00093230756,0.002050065,0.0155613795,0.48393095,0.011380653,0.15818729,0.23350775],"study_design_scores_gemma":[0.0014596019,0.0015643935,0.010606516,0.006089325,0.00026471596,0.0004699029,0.00005031609,0.048964214,0.61377,0.037957117,0.27576986,0.0030340112],"about_ca_topic_score_codex":0.00010461936,"about_ca_topic_score_gemma":0.0000056786166,"teacher_disagreement_score":0.3576999,"about_ca_system_score_codex":0.0002577412,"about_ca_system_score_gemma":0.0006483248,"threshold_uncertainty_score":0.999452},"labels":[],"label_agreement":null},{"id":"W657417801","doi":"10.1016/j.neuroimage.2015.06.033","title":"Multivariate combination of magnetization transfer, T 2 * and B0 orientation to study the myelo-architecture of the in vivo human cortex","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; National Center for Research Resources; Natural Sciences and Engineering Research Council of Canada; National Multiple Sclerosis Society Lone Star","keywords":"Magnetization transfer; Myelin; Multivariate statistics; Cortex (anatomy); Contrast (vision); Orientation (vector space); Nuclear magnetic resonance; Content (measure theory); Chemistry; Nuclear medicine; Biology; Neuroscience; Mathematics; Medicine; Magnetic resonance imaging; Physics; Central nervous system; Artificial intelligence; Computer science; Statistics; Radiology","score_opus":0.05875683033107572,"score_gpt":0.3591327970337346,"score_spread":0.30037596670265887,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W657417801","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9889677,0.000008181766,0.007792697,0.0014468114,0.000025339643,0.0014532539,0.0000092236905,0.000025191875,0.00027158033],"genre_scores_gemma":[0.9990419,0.0000035413063,0.0006286413,0.0001980095,0.000008465618,0.000044609034,0.0000033057217,0.000012389111,0.000059093985],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99928236,0.00008824626,0.00021343524,0.00016530437,0.0001821509,0.00006850633],"domain_scores_gemma":[0.9994882,0.000039834522,0.000055763736,0.00028636673,0.000097601616,0.00003223691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014706347,0.00007307062,0.00011839986,0.00006642999,0.000046576268,0.0000054707375,0.00009462933,0.000017838396,0.0000044846515],"category_scores_gemma":[0.000084374566,0.00004718612,0.000020074282,0.00036389136,0.000066364155,0.00003580992,0.00003970238,0.00012070908,2.1117913e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013392519,0.0008300997,0.052859187,0.00003758451,0.000006921397,0.0000036566346,0.0060550263,0.00015654688,0.9307217,0.0026197007,0.000109367065,0.006466301],"study_design_scores_gemma":[0.0019268707,0.00075274665,0.94627905,0.00002654181,0.00004669729,0.0000090643125,0.00033963806,0.000429581,0.047917947,0.0018948725,0.00031864308,0.00005835053],"about_ca_topic_score_codex":0.000075447104,"about_ca_topic_score_gemma":0.000025621554,"teacher_disagreement_score":0.89341986,"about_ca_system_score_codex":0.000011396021,"about_ca_system_score_gemma":0.0000150948945,"threshold_uncertainty_score":0.19241941},"labels":[],"label_agreement":null},{"id":"W6885906044","doi":"10.1371/journal.pone.0279823.s001","title":"General context effect: Full pictures with the context vs. firstly presented images (pictures without the context) at p&lt; .05, family-wise error (FWE) corrected for multiple comparison.","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Pattern recognition (psychology); Visualization; Feature (linguistics); Statistical analysis","score_opus":0.05834125457593781,"score_gpt":0.3325987668574668,"score_spread":0.274257512281529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6885906044","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49353912,0.011134068,0.0027364597,0.038305473,0.0006411407,0.038185544,0.41083747,0.0035057217,0.0011149753],"genre_scores_gemma":[0.95792776,0.0000053618915,0.00037192059,0.007445686,0.00020893716,0.008923715,0.021813054,0.00011953232,0.0031840382],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977402,0.00020488842,0.00038850744,0.0006487123,0.0004892398,0.0005284567],"domain_scores_gemma":[0.9967646,0.0013878974,0.0003758232,0.0009977771,0.00032277036,0.00015113338],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010956029,0.00046778185,0.00063042244,0.00006815583,0.0013653715,0.000083934094,0.0006670349,0.00008270367,0.0032299648],"category_scores_gemma":[0.0007176283,0.00026073895,0.00024847972,0.00028964962,0.00014424472,0.000077879406,0.0004590145,0.0007262522,0.000043203287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00222939,0.00013529693,0.0024701646,0.00011752286,0.00010233827,0.000016484446,0.00073303486,0.00023835515,0.005511029,0.000023036895,0.98521936,0.003204009],"study_design_scores_gemma":[0.004338809,0.0013610955,0.016285617,0.00032916354,0.00018452216,0.00016682626,0.0012452358,0.01201682,0.013303828,0.000017373424,0.950356,0.00039469913],"about_ca_topic_score_codex":0.00009389963,"about_ca_topic_score_gemma":0.00041583154,"teacher_disagreement_score":0.4643886,"about_ca_system_score_codex":0.0001483814,"about_ca_system_score_gemma":0.00008801264,"threshold_uncertainty_score":0.9999845},"labels":[],"label_agreement":null},{"id":"W6889808992","doi":"10.26044/ecr2020/c-13687","title":"\"Correlation of Resting State fMRI and Diffusion Tensor Imaging in Mild Traumatic Brain Injury\"","year":2020,"lang":"en","type":"article","venue":"European Society of Radiology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre de Santé et de Services Sociaux Cavendish","funders":"","keywords":"Resting state fMRI; Diffusion MRI; Diffusion; Neuroimaging; Tractography; Brain mapping","score_opus":0.06330271749414192,"score_gpt":0.33137730551624706,"score_spread":0.26807458802210515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6889808992","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9579645,0.00021326865,0.030668648,0.010374331,0.00000957296,0.00025519155,0.000009021914,0.00006918898,0.0004363111],"genre_scores_gemma":[0.96400094,0.00023833587,0.034008656,0.001659255,0.000028059774,0.0000024077347,0.000012508823,0.000020134306,0.000029730454],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992654,0.00009319219,0.0002997232,0.00018462261,0.000053423017,0.000103637394],"domain_scores_gemma":[0.9995327,0.0001199089,0.00015482293,0.000119407516,0.000027720527,0.00004542698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020925917,0.000075374825,0.00021112082,0.000025407193,0.000027327485,0.0000015874296,0.00005408625,0.000016311646,0.0000034753793],"category_scores_gemma":[0.0001385307,0.00007138716,0.00005283452,0.0001369401,0.00016098087,0.000032355554,0.00005208485,0.00016750803,0.0000010220054],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015452603,0.00011948517,0.48378718,0.00049090455,0.000021529744,0.000016644006,0.012567481,0.00024365366,0.43046895,0.00033909164,0.02208813,0.049702432],"study_design_scores_gemma":[0.00227904,0.00051348994,0.9045585,0.00039213657,0.000044630156,0.00012880635,0.0010650327,0.08306015,0.002127767,0.0007920205,0.00481614,0.00022232744],"about_ca_topic_score_codex":0.0000069999655,"about_ca_topic_score_gemma":1.4611298e-7,"teacher_disagreement_score":0.42834118,"about_ca_system_score_codex":0.000011448986,"about_ca_system_score_gemma":0.000009560692,"threshold_uncertainty_score":0.2911084},"labels":[],"label_agreement":null},{"id":"W6901437950","doi":"10.60692/dhm26-4b264","title":"Tractography at 3T MRI of Corpus Callosum Tracts Crossing White Matter Hyperintensities","year":2016,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kingston General Hospital; University of Toronto; Queen's University","funders":"","keywords":"Hyperintensity; White matter; Corpus callosum; Diffusion MRI; Tractography; Fractional anisotropy","score_opus":0.056304909901160896,"score_gpt":0.26474150177468153,"score_spread":0.20843659187352065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901437950","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8892221,0.000003172231,0.10599224,0.00065165036,0.000085281434,0.0003748448,0.00011738742,0.00026647432,0.0032868707],"genre_scores_gemma":[0.9963875,5.462167e-7,0.002432007,0.00041303443,0.000031910997,0.000048191512,0.000009163328,0.000015096771,0.0006625899],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989706,0.0000133558915,0.0005160104,0.00012611161,0.00019217069,0.0001817322],"domain_scores_gemma":[0.9990044,0.000009277122,0.0003045409,0.00038692396,0.00021410322,0.00008074812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008494676,0.0001406812,0.0002502905,0.00020058018,0.00011096198,0.00004227377,0.00007201111,0.00006589241,0.00004033897],"category_scores_gemma":[0.0000070424717,0.00009093238,0.000108873275,0.00013316772,0.00012593668,0.0003755298,0.00003726249,0.000060802267,0.0002188375],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013661457,0.0000048913444,0.9895101,0.00039186023,0.00002300447,0.000004421035,0.0075331423,0.00000482671,0.0010602021,0.00017964731,0.00063383044,0.00051743735],"study_design_scores_gemma":[0.0014357896,0.00007849772,0.9590659,0.0008767888,0.00006559331,0.00064266624,0.0014917615,0.00013613,0.02863922,0.0000084745925,0.0073159467,0.00024323071],"about_ca_topic_score_codex":0.0000026071193,"about_ca_topic_score_gemma":6.5211275e-8,"teacher_disagreement_score":0.10716538,"about_ca_system_score_codex":0.000072489,"about_ca_system_score_gemma":0.00001872096,"threshold_uncertainty_score":0.37081146},"labels":[],"label_agreement":null},{"id":"W6901772981","doi":"10.60692/85pph-h2r25","title":"Altered coupling of resting-state cerebral blood flow and functional connectivity in Meige syndrome","year":2023,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Cerebral blood flow; Neurovascular bundle; Precentral gyrus; Middle frontal gyrus; Perfusion; Blood flow; Perfusion scanning; Voxel; Blood-oxygen-level dependent","score_opus":0.08301841575121341,"score_gpt":0.27563846348308496,"score_spread":0.19262004773187155,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901772981","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.98491496,0.0000014522492,0.014004955,0.00008227769,0.000051526084,0.00039159073,0.00007027745,0.00031270462,0.00017022908],"genre_scores_gemma":[0.9987866,3.8706182e-7,0.0010092944,0.000034604534,0.000015723226,0.000069657086,0.000033255463,0.000008637988,0.000041810712],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99918115,0.000008560598,0.00039488063,0.00012198702,0.00015349912,0.00013990072],"domain_scores_gemma":[0.9994946,0.000019732854,0.00016074453,0.0001935048,0.00008052126,0.000050885687],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023408169,0.000092946524,0.00020485147,0.00027418695,0.000055008535,0.000017354903,0.000032543965,0.000037418635,0.0000036299189],"category_scores_gemma":[0.000035843634,0.000084026346,0.00002939367,0.00035182622,0.00003076054,0.00021991628,0.00004425205,0.000097909,0.000026548752],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009922952,0.000007886023,0.98954767,0.0009374154,0.000029695639,0.000020304185,0.005662636,0.0029360466,0.00017031947,0.00029863752,0.00005119956,0.00023897411],"study_design_scores_gemma":[0.0014581457,0.00006716903,0.8963611,0.00037051114,0.000027108501,0.00039265153,0.0008699723,0.09876922,0.0015336724,0.000025205494,0.000021035183,0.00010419965],"about_ca_topic_score_codex":0.0000073428714,"about_ca_topic_score_gemma":1.9538139e-7,"teacher_disagreement_score":0.095833175,"about_ca_system_score_codex":0.000029329773,"about_ca_system_score_gemma":0.00002225622,"threshold_uncertainty_score":0.3426495},"labels":[],"label_agreement":null},{"id":"W6901965036","doi":"10.60692/xa8tc-g9b05","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Cognition; Executive functions; Dementia; Cognitive impairment; Executive dysfunction","score_opus":0.06329485058994336,"score_gpt":0.2947313742875131,"score_spread":0.23143652369756976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6901965036","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850633,0.00000395273,0.010656843,0.00067909213,0.000015375168,0.003197469,0.000098170385,0.00021693672,0.000068849455],"genre_scores_gemma":[0.9978233,9.305867e-7,0.00014183027,0.0014875811,0.000018173676,0.00042593453,0.00007954244,0.000019949632,0.0000027400047],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985357,0.000066195345,0.00058556756,0.0002954138,0.0002556461,0.0002615015],"domain_scores_gemma":[0.9992443,0.00003219814,0.00028536227,0.00014088559,0.00016039556,0.00013687904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017202931,0.00022862953,0.00037058754,0.00028134533,0.00010086256,0.000058259015,0.000056772875,0.00004349499,0.0000037215302],"category_scores_gemma":[0.000044133765,0.00017998125,0.000027197624,0.0004182482,0.000034667057,0.00037496595,0.00006338202,0.00035296718,0.000011731362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090240967,0.000084344116,0.9351418,0.0003756987,0.000012699654,0.000015621285,0.063178904,0.0000010967256,0.0000017148602,0.0000013000007,0.0000050258122,0.00027939412],"study_design_scores_gemma":[0.010899605,0.0007771716,0.9302577,0.0030899735,0.000064508014,0.000026120477,0.036864597,0.0178005,0.000046267523,0.0000015102543,4.2656393e-7,0.00017165352],"about_ca_topic_score_codex":0.000043189553,"about_ca_topic_score_gemma":0.000003931028,"teacher_disagreement_score":0.026314303,"about_ca_system_score_codex":0.00014274662,"about_ca_system_score_gemma":0.00003208127,"threshold_uncertainty_score":0.7339422},"labels":[],"label_agreement":null},{"id":"W6906675206","doi":"10.17605/osf.io/nwv8g","title":"Hubner (2023). Keeping Ahead of Chronic Wasting Disease: An Assessment of Trans-Boundary Cervid Movement in British Columbia - UBCO M.Sc. Thesis Repository","year":2023,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Chronic wasting disease; Wasting; Movement (music); Population","score_opus":0.030474493541289116,"score_gpt":0.34014136558412933,"score_spread":0.3096668720428402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906675206","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95504147,0.000024442168,0.005648966,0.0003525923,0.00009274465,0.0018227173,0.000059356335,0.00033367996,0.036624048],"genre_scores_gemma":[0.97860014,0.00052828284,0.005284849,0.00010414982,0.00005936471,0.00059257535,0.000059050937,0.000060399936,0.014711176],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99677074,0.00022813499,0.0008663808,0.001299598,0.0004589848,0.00037617655],"domain_scores_gemma":[0.9968538,0.0002165658,0.0003213933,0.002257611,0.00014101873,0.0002095942],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0016241564,0.00017000377,0.00048988685,0.00014282922,0.00015513565,0.000064888416,0.00047371478,0.000092183254,0.015522],"category_scores_gemma":[0.00031030644,0.00026935482,0.00017954413,0.00046783718,0.00020746652,0.00018333025,0.00045846307,0.00037271017,0.0011332704],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006245624,0.0015413299,0.76585144,0.0019243743,0.00011969419,0.0001906944,0.00037752066,0.0032466804,0.15529262,0.00019383086,0.002208316,0.06899108],"study_design_scores_gemma":[0.000819912,0.000009894407,0.9703032,0.0015474266,0.00011570341,0.000022550264,0.00012637867,0.009903475,0.010175866,0.0021800902,0.004532332,0.00026316533],"about_ca_topic_score_codex":0.0019587562,"about_ca_topic_score_gemma":0.0010790959,"teacher_disagreement_score":0.2044518,"about_ca_system_score_codex":0.0003600224,"about_ca_system_score_gemma":0.00038685673,"threshold_uncertainty_score":0.99997586},"labels":[],"label_agreement":null},{"id":"W6911390267","doi":"10.5281/zenodo.11726703","title":"les taches d un agent commercial dans une banque pdf","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Limiting; State owned; Commercial banking; Security market","score_opus":0.0974405021559019,"score_gpt":0.33059531715986906,"score_spread":0.23315481500396718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6911390267","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00031638372,0.0011420909,0.03957276,0.006139298,0.0003088157,0.0012131381,0.0005866139,0.0019163106,0.9488046],"genre_scores_gemma":[0.06201761,0.00228003,0.004808096,0.0008422623,0.0024267193,6.2098695e-7,0.00569865,0.016853843,0.90507215],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973453,0.00031126544,0.0004485266,0.0008753579,0.00042039377,0.00059915765],"domain_scores_gemma":[0.9981992,0.00003611139,0.0001842199,0.00094395294,0.0002936502,0.00034281658],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00037977257,0.0004126597,0.00039399185,0.00035344806,0.0015096145,0.00046522426,0.0010627822,0.00023945255,0.17892309],"category_scores_gemma":[0.00032110506,0.00043431015,0.00016389416,0.00088703784,0.0005913536,0.000084133324,0.0013918155,0.0010576956,0.14496236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000344021,0.00032708145,0.0000072055377,0.000489518,0.00013738107,0.00013943974,0.0009853725,0.00001694237,0.003551054,0.046068203,0.66602916,0.28221425],"study_design_scores_gemma":[0.0003822351,0.0002728987,0.0005721877,0.0005914848,0.00020427081,0.0003347694,0.0002717197,0.00025747053,0.00076785847,0.001390582,0.9945846,0.00036990404],"about_ca_topic_score_codex":0.000115556846,"about_ca_topic_score_gemma":0.0000021204412,"teacher_disagreement_score":0.32855546,"about_ca_system_score_codex":0.00050427904,"about_ca_system_score_gemma":0.0000090905905,"threshold_uncertainty_score":0.9998109},"labels":[],"label_agreement":null},{"id":"W6920687054","doi":"10.6084/m9.figshare.28630036.v1","title":"Additional file 1 of Connectivity related to major brain functions in Alzheimer disease progression: microstructural properties of the cingulum bundle and its subdivision using diffusion-weighted MRI","year":2025,"lang":"en","type":"article","venue":"Open MIND","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Region of interest; Subdivision; Cingulum (brain); Voxel; Retrosplenial cortex; Distortion (music); Pattern recognition (psychology)","score_opus":0.04905254241155561,"score_gpt":0.34899369539510944,"score_spread":0.29994115298355384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920687054","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9790633,0.00011225087,0.000029098544,0.0018530582,0.00002226643,0.0013655208,0.017284313,0.0000044786493,0.00026575514],"genre_scores_gemma":[0.99076885,0.000001216523,0.006920531,0.00009627861,0.000006702936,0.00017055435,0.00091795844,0.000008943037,0.0011089407],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9993559,0.000036734145,0.00020540439,0.00021935736,0.000094215124,0.00008838014],"domain_scores_gemma":[0.9994017,0.000153584,0.00009454776,0.00020676041,0.0000936311,0.00004975921],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00004583467,0.0000818808,0.00015545075,0.000072521136,0.00012041417,0.000012189069,0.00010448052,0.000032693613,0.017753648],"category_scores_gemma":[0.00030894805,0.000054761193,0.000032091593,0.00037087177,0.00009090501,0.00007564155,0.00028876564,0.0001065672,0.0000024181238],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015572716,0.0016208454,0.014079255,0.00016708988,0.00012878067,0.000011268743,0.00061766815,0.000036822177,0.66381305,0.0002713463,0.27072135,0.04697523],"study_design_scores_gemma":[0.0036479088,0.00038507127,0.41594946,0.013984996,0.00044720122,0.00007758351,0.00044096282,0.018466655,0.37129632,0.0020863179,0.17264456,0.0005729763],"about_ca_topic_score_codex":0.000014955843,"about_ca_topic_score_gemma":0.000008469212,"teacher_disagreement_score":0.4018702,"about_ca_system_score_codex":0.00001951524,"about_ca_system_score_gemma":0.00012826496,"threshold_uncertainty_score":0.9831443},"labels":[],"label_agreement":null},{"id":"W6920687338","doi":"10.60692/z0kkx-dby80","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Diffusion MRI; Core (optical fiber); Neuroimaging","score_opus":0.08639512390122667,"score_gpt":0.29637261351750305,"score_spread":0.20997748961627638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6920687338","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934027,0.000008498902,0.002542257,0.001342275,0.00027004874,0.00079311914,0.0007254553,0.0002403183,0.0006753364],"genre_scores_gemma":[0.9937411,9.428698e-7,0.005182889,0.0004857118,0.00020670665,0.00013647926,0.00013984085,0.000021839149,0.000084490974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99797696,0.000062296866,0.0008905749,0.00034112562,0.00033746517,0.00039157402],"domain_scores_gemma":[0.9975517,0.000049106166,0.00080952124,0.0014113629,0.000081250895,0.00009706677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035840966,0.00029633063,0.00039784698,0.000108067485,0.00077467354,0.00080158166,0.00065479503,0.00014183517,0.000013656493],"category_scores_gemma":[0.000084142914,0.00019647421,0.00010111637,0.00014792087,0.00017637822,0.00076336775,0.00030862843,0.00039809992,0.00022983542],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045962885,0.0000025308143,0.9798114,0.000038822956,0.000022280465,0.0000043159203,0.017435867,0.0000024638064,0.000029384295,0.000066474786,0.00023369516,0.0018931538],"study_design_scores_gemma":[0.0031692723,0.00002003738,0.99209255,0.0008045331,0.000029114297,0.00005803329,0.0024728435,0.00028543512,0.0004075283,0.000034025325,0.0004106343,0.00021597685],"about_ca_topic_score_codex":0.00009776056,"about_ca_topic_score_gemma":0.000006986193,"teacher_disagreement_score":0.014963024,"about_ca_system_score_codex":0.000085906126,"about_ca_system_score_gemma":0.000025019004,"threshold_uncertainty_score":0.8011986},"labels":[],"label_agreement":null},{"id":"W6928789993","doi":"10.3897/zookeys.179.2601.map8","title":"Map 8 from: Webster R, Sweeney J, DeMerchant I, Silk P, Mayo P (2012) New Coleoptera records from New Brunswick, Canada: Cerambycidae. ZooKeys 179: 309-311. https://doi.org/10.3897/zookeys.179.2601","year":2012,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"SILK; Historical record; Line drawings","score_opus":0.07088916089450704,"score_gpt":0.28627580877802894,"score_spread":0.2153866478835219,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6928789993","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00065775827,0.0023016892,0.016534625,0.0067694597,0.0006364643,0.0023268273,0.00042495553,0.0030070154,0.9673412],"genre_scores_gemma":[0.0021239228,0.0010775416,0.0087761,0.0018322051,0.0033973926,6.726438e-7,0.007752787,0.0074761435,0.9675632],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9955485,0.00028462146,0.0007611356,0.0013701625,0.00095513475,0.0010804567],"domain_scores_gemma":[0.9957522,0.00008031362,0.0005419463,0.0019235411,0.0003882817,0.0013137121],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00025775205,0.0007726379,0.0008499327,0.000437272,0.00081656856,0.00034632802,0.0015013255,0.00043196292,0.535876],"category_scores_gemma":[0.00024967818,0.0008064197,0.00019916125,0.0004983475,0.00020993772,0.00026582627,0.0014063562,0.0014529291,0.09232542],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013236539,0.0001546001,0.0001669601,0.00008775782,0.00019878327,0.00005800047,0.00016416967,0.0000021868207,0.0004662406,0.0005262527,0.96830714,0.029735574],"study_design_scores_gemma":[0.0013310721,0.0001834934,0.0033188788,0.00043457892,0.00026087023,0.000011836972,0.000047465815,0.00006923431,0.00051121385,0.0002764902,0.9928185,0.000736404],"about_ca_topic_score_codex":0.32515338,"about_ca_topic_score_gemma":0.0048216274,"teacher_disagreement_score":0.44355056,"about_ca_system_score_codex":0.0006953663,"about_ca_system_score_gemma":0.00040348663,"threshold_uncertainty_score":0.99943864},"labels":[],"label_agreement":null},{"id":"W6928886133","doi":"10.3897/zookeys.788.26048.figures1-12","title":"Figures 1-12 from: Schmidt CB, Sullivan BJ (2018) Three species in one: a revision of Clemensia albata Packard (Erebidae, Arctiinae, Lithosiini). In: Schmidt BC, Lafontaine JD (Eds) Contributions to the systematics of New World macro-moths VII. ZooKeys 788: 39-55. https://doi.org/10.3897/zookeys.788.26048","year":2018,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Systematics; State (computer science)","score_opus":0.08606102278607895,"score_gpt":0.3274063947683063,"score_spread":0.24134537198222733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6928886133","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038898091,0.0024005426,0.017756453,0.010002115,0.0002070087,0.009452932,0.0010287868,0.0014576742,0.9538047],"genre_scores_gemma":[0.058965206,0.0029294125,0.010557009,0.0005673443,0.0013571373,0.000004385528,0.0038551863,0.004757835,0.9170065],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960052,0.00042092244,0.0012026484,0.0008619521,0.00085832365,0.00065097463],"domain_scores_gemma":[0.99595016,0.00015687899,0.0007872372,0.0020057652,0.0007790905,0.00032089],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009348527,0.0004910581,0.0010353335,0.0009933694,0.00042586238,0.00016183702,0.0014077049,0.00022625794,0.08246185],"category_scores_gemma":[0.0017090185,0.0004315037,0.00016995962,0.0015869229,0.0004345753,0.00013043573,0.001429288,0.0008852036,0.015407874],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026995086,0.00042277182,0.00047985426,0.0009825515,0.00013237099,0.000020056566,0.00033729867,0.000008894323,0.0021693306,0.0067867204,0.9847588,0.0036313764],"study_design_scores_gemma":[0.0013355123,0.0004116979,0.0045774085,0.0047819708,0.0001407865,0.0000036509766,0.00014812048,0.0001103781,0.0016131485,0.0004133688,0.9861046,0.00035936746],"about_ca_topic_score_codex":0.0008553443,"about_ca_topic_score_gemma":0.00007231769,"teacher_disagreement_score":0.06705397,"about_ca_system_score_codex":0.00036465382,"about_ca_system_score_gemma":0.000053465406,"threshold_uncertainty_score":0.9998137},"labels":[],"label_agreement":null},{"id":"W6929460105","doi":"10.5066/p97r96is","title":"Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Lake Ontario, U.S.: Degree Flowlines","year":2021,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Wetland; Impervious surface; Hydrology (agriculture); Habitat; Restoration ecology; Nature Conservation; Wetland conservation; Recreational use","score_opus":0.06389841341094381,"score_gpt":0.3153651365480106,"score_spread":0.2514667231370668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6929460105","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074423454,0.00029504127,0.006643686,0.009821461,0.0016183566,0.003986332,0.9693579,0.00043046105,0.00040442115],"genre_scores_gemma":[0.00017258919,0.001707499,0.016119609,0.00030911947,0.0013100032,0.00061958894,0.9693269,0.00006105947,0.010373619],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9971434,0.00007173158,0.0005856828,0.001181322,0.0006930483,0.00032485262],"domain_scores_gemma":[0.99780005,0.00002458251,0.00033338438,0.0016454081,0.00006634419,0.00013019933],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00022124764,0.00049111585,0.0005339222,0.00015280001,0.00025729818,0.00006298281,0.00016448983,0.0002483281,0.0018826198],"category_scores_gemma":[0.00006281765,0.00046960835,0.00016955883,0.00013990032,0.00015783196,0.00017316626,0.0001921066,0.0007841101,0.00010468219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047803824,0.0004946125,0.0013359755,0.00012949243,0.00006622893,0.00005908924,0.000015433157,0.00020935273,0.001618,0.0000055568953,0.9933597,0.0026587697],"study_design_scores_gemma":[0.00042200714,0.00019204342,0.01018343,0.00014651785,0.0003724782,0.00023104697,0.000014855367,0.00001664756,0.00085430534,0.000055917335,0.987097,0.00041374998],"about_ca_topic_score_codex":0.00037836126,"about_ca_topic_score_gemma":0.014006268,"teacher_disagreement_score":0.013627907,"about_ca_system_score_codex":0.0005569795,"about_ca_system_score_gemma":0.00024839878,"threshold_uncertainty_score":0.9997756},"labels":[],"label_agreement":null},{"id":"W6930154912","doi":"10.5281/zenodo.12340696","title":"mcgraw-hill ryerson chemistry 11 2011 pdf","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Download; Process (computing); Subject (documents); Bridge (graph theory); Resource (disambiguation); The Internet; Chemistry education; Virtual lab","score_opus":0.06049457925126113,"score_gpt":0.3090227688378551,"score_spread":0.248528189586594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930154912","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000019544474,0.00042817666,0.0030165892,0.0018745137,0.00006213763,0.0006245929,0.00035592448,0.0036401767,0.9899784],"genre_scores_gemma":[0.00096653687,0.0005122324,0.0014322144,0.00028799422,0.0005299735,2.314065e-7,0.0027755278,0.010838615,0.98265666],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985116,0.000054421766,0.00021043282,0.00062575506,0.00029318058,0.0003045848],"domain_scores_gemma":[0.9987258,0.000007264121,0.000119300326,0.00078365783,0.0001538063,0.00021021103],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00019575792,0.00023274584,0.00024276698,0.00021094088,0.00034968648,0.00019723446,0.0005283993,0.00016699244,0.16439356],"category_scores_gemma":[0.00014034346,0.00023735066,0.00010069853,0.00030000065,0.00016430281,0.000038665952,0.0006485058,0.0005519092,0.098710336],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010618423,0.000076599135,5.251073e-7,0.00039571102,0.000035113,0.00004183204,0.00003796773,2.3595746e-7,0.003852025,0.00066480006,0.9845048,0.010379724],"study_design_scores_gemma":[0.00022934345,0.00006008111,0.000010125039,0.00026807166,0.000067636145,0.00029786225,0.00003126377,0.00004438888,0.0007201828,0.000252851,0.99780977,0.00020842296],"about_ca_topic_score_codex":0.00001905314,"about_ca_topic_score_gemma":1.307334e-7,"teacher_disagreement_score":0.065683216,"about_ca_system_score_codex":0.00011733111,"about_ca_system_score_gemma":0.000004914979,"threshold_uncertainty_score":0.96788794},"labels":[],"label_agreement":null},{"id":"W6930397088","doi":"10.5281/zenodo.14135892","title":"PM_134927_B_Maarke","year":2021,"lang":"nl","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Period (music); Exposition (narrative); Government (linguistics); Quarter (Canadian coin); Subject (documents)","score_opus":0.09596298050184221,"score_gpt":0.32909117195004345,"score_spread":0.23312819144820124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930397088","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009731672,0.0013134528,0.015738761,0.0023823397,0.00022835484,0.001214305,0.00051759824,0.0020427683,0.9764651],"genre_scores_gemma":[0.006806179,0.004053908,0.00555564,0.0011851096,0.0014255875,3.1379847e-7,0.013785809,0.018572608,0.94861484],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99680567,0.00035287841,0.00047596043,0.001124575,0.00056870043,0.00067221094],"domain_scores_gemma":[0.9969474,0.000035291534,0.00030260716,0.0015710612,0.0007311352,0.0004125058],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00043787374,0.0004251923,0.00049805274,0.00041111518,0.0020013768,0.0006205155,0.0012787945,0.00025916073,0.4218156],"category_scores_gemma":[0.00079455704,0.00047417067,0.00018549856,0.00096087385,0.0003719241,0.000084484614,0.0019581928,0.0009858946,0.08601036],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003644042,0.00032643412,0.0000026792286,0.00033792644,0.00010130449,0.00010322458,0.0000893551,0.0000030741894,0.004227851,0.00609119,0.9317489,0.056931604],"study_design_scores_gemma":[0.00062573666,0.00022907658,0.00023288713,0.00058502547,0.00010636719,0.000477849,0.00014080793,0.00013936295,0.0004289357,0.00027324073,0.996346,0.0004147242],"about_ca_topic_score_codex":0.000016152688,"about_ca_topic_score_gemma":7.658968e-8,"teacher_disagreement_score":0.33580527,"about_ca_system_score_codex":0.00027710607,"about_ca_system_score_gemma":0.000014157953,"threshold_uncertainty_score":0.999771},"labels":[],"label_agreement":null},{"id":"W6930425449","doi":"10.5281/zenodo.10402001","title":"Research protocol. Worldwide trends in sodium and potassium intakes in children and adolescents: a systematic review and meta-analysis","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Blood pressure; Sodium; Potassium; High sodium; Kidney disease; Dietary Sodium","score_opus":0.11834855531793197,"score_gpt":0.38380085748942167,"score_spread":0.2654523021714897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930425449","genre_codex":"protocol","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.110538006,0.027079796,0.0032147593,0.17498273,0.000040896743,0.61881924,0.0020222971,0.01081314,0.052489143],"genre_scores_gemma":[0.9903092,0.0026483622,0.0008403998,0.0010673878,0.000035410387,0.0003877926,0.0009578698,0.0010416227,0.002711958],"study_design_codex":"systematic_review","study_design_gemma":"observational","domain_scores_codex":[0.9981898,0.00044717066,0.00035642966,0.00045803242,0.00027545384,0.00027308846],"domain_scores_gemma":[0.9991722,0.000031005115,0.00007848297,0.0004125632,0.00017818142,0.00012753467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001548486,0.00012367811,0.00057107327,0.0012251914,0.0003584392,0.00016985348,0.00021654987,0.00003428449,0.0003694771],"category_scores_gemma":[0.0004074387,0.000103458246,0.000058437945,0.0033193529,0.00016542581,0.000112187874,0.00062837487,0.00036438854,0.00007615023],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012571337,0.004796074,0.01898013,0.48701316,0.031260572,0.0006808399,0.0076130116,0.00007514826,0.006223093,0.021630134,0.33395866,0.08651205],"study_design_scores_gemma":[0.008952022,0.0018475553,0.7360406,0.015871385,0.08137794,0.0018459084,0.0014414826,0.003020812,0.00043745624,0.0026745473,0.14439565,0.0020946872],"about_ca_topic_score_codex":0.000027319064,"about_ca_topic_score_gemma":0.0000022170232,"teacher_disagreement_score":0.8797712,"about_ca_system_score_codex":0.000055634457,"about_ca_system_score_gemma":0.0000022622826,"threshold_uncertainty_score":0.4218905},"labels":[],"label_agreement":null},{"id":"W6930527726","doi":"10.5281/zenodo.11841300","title":"Kb psychiatrie pdf gratuit","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paraphernalia; Nucleofection; Limiting; Context (archaeology)","score_opus":0.06464322918848939,"score_gpt":0.32373092840694484,"score_spread":0.2590876992184554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930527726","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000034033408,0.0029711996,0.01937468,0.0068465252,0.0007306132,0.0013046229,0.00054807955,0.002862954,0.96532726],"genre_scores_gemma":[0.0032947392,0.0025491347,0.004420632,0.00084649486,0.002586639,3.5685346e-7,0.0029065302,0.01551163,0.9678838],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9972117,0.00020261122,0.0004445739,0.0010176895,0.00045098746,0.00067242066],"domain_scores_gemma":[0.99788415,0.00002479754,0.00018541164,0.001139276,0.00036810245,0.00039826497],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00039838353,0.00040588167,0.00037749633,0.00049701286,0.0011649714,0.00067470013,0.001098992,0.00024515478,0.2782386],"category_scores_gemma":[0.00038422784,0.00042887282,0.00018064995,0.0010195398,0.0004071038,0.000106927386,0.0012524863,0.0011215663,0.3727191],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027660875,0.00019906838,0.0000012851743,0.00050708046,0.00008528332,0.000062959385,0.00016358815,0.000003785149,0.0012855929,0.054563962,0.8279116,0.11518813],"study_design_scores_gemma":[0.0003973549,0.00032782095,0.000054321652,0.00067541184,0.00019144185,0.00044875662,0.00008280961,0.00018564572,0.0001641364,0.0042028013,0.9928975,0.00037200688],"about_ca_topic_score_codex":0.0000125721035,"about_ca_topic_score_gemma":2.999023e-7,"teacher_disagreement_score":0.1649859,"about_ca_system_score_codex":0.00032982833,"about_ca_system_score_gemma":0.000012306785,"threshold_uncertainty_score":0.9998163},"labels":[],"label_agreement":null},{"id":"W6930560715","doi":"10.5281/zenodo.14366804","title":"globalbioticinteractions/globalbioticinteractions: v0.27.2","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Interoperability; Context (archaeology); Key (lock); Process (computing)","score_opus":0.07944087637282128,"score_gpt":0.3564202520129595,"score_spread":0.27697937564013825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930560715","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000009964916,0.0006338713,0.00879757,0.0034667174,0.00039578535,0.000930643,0.0006424566,0.0054557216,0.97966725],"genre_scores_gemma":[0.0041509042,0.0010878512,0.0048726886,0.0007446194,0.00091005524,2.316263e-7,0.0034284547,0.014137497,0.9706677],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982318,0.00008208681,0.0003026545,0.00071339955,0.00032233485,0.00034768725],"domain_scores_gemma":[0.9984559,0.000014770962,0.00015835791,0.0008769103,0.00027678322,0.00021731657],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00014662366,0.00028457717,0.00029817462,0.00051743764,0.0004943128,0.00043400118,0.0005105287,0.0001603753,0.033486627],"category_scores_gemma":[0.00028722137,0.00028671106,0.00014742112,0.0006394032,0.00017142475,0.000086512475,0.00065639074,0.00070132967,0.05327685],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024580228,0.00016253957,7.4324015e-7,0.00022041857,0.00009957784,0.000043105618,0.00003541522,0.0000013034052,0.0005462234,0.0046340316,0.97762585,0.016606228],"study_design_scores_gemma":[0.00024603755,0.00016899264,0.000021663172,0.0006063469,0.00015797323,0.0010895762,0.00007813072,0.00008562364,0.0001149295,0.00045412872,0.99674517,0.0002314281],"about_ca_topic_score_codex":0.00004646736,"about_ca_topic_score_gemma":6.2909385e-7,"teacher_disagreement_score":0.019790227,"about_ca_system_score_codex":0.00035188656,"about_ca_system_score_gemma":0.000008009994,"threshold_uncertainty_score":0.9999585},"labels":[],"label_agreement":null},{"id":"W6930978024","doi":"10.5281/zenodo.4489215","title":"Osmia (Centrosmia) nigriventris","year":2011,"lang":"de","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Bay; North sea","score_opus":0.13662739112436095,"score_gpt":0.3109746497342994,"score_spread":0.17434725860993844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930978024","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013503334,0.0075049642,0.16783544,0.007506648,0.0012341742,0.0056382604,0.0018476588,0.010256223,0.7846733],"genre_scores_gemma":[0.9565778,0.008434215,0.0124738095,0.0018872258,0.0018083479,4.4853363e-7,0.0051389067,0.00802977,0.0056494744],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99746186,0.00025333292,0.00044001432,0.00073138135,0.0004356755,0.0006777699],"domain_scores_gemma":[0.99761146,0.000023543955,0.00021834241,0.0010655898,0.00063780055,0.00044326117],"candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00044148794,0.00027467488,0.00029039054,0.0002980047,0.0021868774,0.0003053015,0.0011118173,0.000121601006,0.02124512],"category_scores_gemma":[0.00047340977,0.00030030598,0.00013332277,0.00078906654,0.00037190568,0.00021556541,0.0012929481,0.0006522422,0.030970283],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035157433,0.0012189668,0.000094800846,0.0002429516,0.00024230724,0.0001727164,0.002595855,0.0000057780812,0.005370059,0.026314395,0.6874037,0.27598694],"study_design_scores_gemma":[0.00080944743,0.00047870685,0.0018236089,0.00012151618,0.00017242195,0.00010300646,0.00016413962,0.00028462338,0.0027903756,0.0011100431,0.99186003,0.00028210628],"about_ca_topic_score_codex":0.00002005596,"about_ca_topic_score_gemma":5.4485227e-8,"teacher_disagreement_score":0.94307446,"about_ca_system_score_codex":0.00022967372,"about_ca_system_score_gemma":0.000007832021,"threshold_uncertainty_score":0.9999449},"labels":[],"label_agreement":null},{"id":"W6931103072","doi":"10.5281/zenodo.4339840","title":"Anthomyza equiseti Roháćek & Barber 2016, sp. nov.","year":2016,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Carex; Bay; Pollen; Hay; Peat","score_opus":0.09087258302477849,"score_gpt":0.32847050741635386,"score_spread":0.23759792439157537,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931103072","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04848888,0.00031579725,0.30394068,0.042230066,0.00021132376,0.0027341477,0.0007303423,0.008435614,0.59291315],"genre_scores_gemma":[0.9780758,0.00055515347,0.0070272046,0.0011202748,0.00034824043,2.9355198e-7,0.00054253056,0.00223813,0.010092382],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986962,0.000075482116,0.00021332783,0.00041443022,0.00026075658,0.0003398042],"domain_scores_gemma":[0.9986705,0.00002747812,0.00007404004,0.0006367681,0.00037164454,0.00021952257],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000250332,0.00013232845,0.00014931466,0.00014854246,0.0008282726,0.000121629884,0.00043249773,0.000048119415,0.009744353],"category_scores_gemma":[0.00038280876,0.000102301005,0.000058375546,0.00033722402,0.00020171457,0.00016863571,0.00058030983,0.00017365042,0.008372843],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000109593726,0.00022217979,0.000039022176,0.000043970518,0.000026677864,0.00003633984,0.0001163955,0.0000014311145,0.16291972,0.01028099,0.55995095,0.26625276],"study_design_scores_gemma":[0.00062286714,0.00017550393,0.0011585114,0.000080725775,0.000018154604,0.0002398871,0.000020776579,0.00003335459,0.0065053795,0.00071200106,0.9902973,0.00013554441],"about_ca_topic_score_codex":0.0000032190571,"about_ca_topic_score_gemma":3.372041e-8,"teacher_disagreement_score":0.9295869,"about_ca_system_score_codex":0.000101767226,"about_ca_system_score_gemma":0.0000053156127,"threshold_uncertainty_score":0.9923993},"labels":[],"label_agreement":null},{"id":"W6931227347","doi":"10.5281/zenodo.2575124","title":"An open science approach to standardizing T1 mapping","year":2019,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Transparency (behavior); Software; Field (mathematics); Open science; Open source; Open data","score_opus":0.21364604167460896,"score_gpt":0.42669402829967085,"score_spread":0.21304798662506189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931227347","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046492506,0.00011391258,0.015372121,0.0030341097,0.00009805133,0.013453123,0.10211662,0.0021825617,0.817137],"genre_scores_gemma":[0.8648841,6.313475e-7,0.123815775,0.0023273807,0.00006775233,0.00048490302,0.007726542,0.00003293714,0.000660007],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991793,0.0000047078665,0.000084033825,0.0003645608,0.000186043,0.00018132187],"domain_scores_gemma":[0.9991066,0.000011254646,0.00003020594,0.0005871772,0.00011409832,0.00015070131],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007937094,0.00006824967,0.00011178105,0.00007865726,0.00011051295,0.00010496637,0.0006248669,0.000017342969,0.004690388],"category_scores_gemma":[0.00015076587,0.00006230088,0.000014968461,0.00045921493,0.000007863988,0.00026604213,0.00039407605,0.00009960174,0.0004976819],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008089118,0.0006141821,0.0023702409,0.0006661995,0.000015917627,0.000018999277,0.0011899145,0.00040751888,0.39751625,0.005000561,0.5279304,0.06418893],"study_design_scores_gemma":[0.00037269504,0.00019796126,0.012295673,0.0012334422,0.0000044263334,0.000045622874,0.00016345749,0.0027938,0.018997217,0.00022754172,0.9634228,0.0002453871],"about_ca_topic_score_codex":0.0000023703365,"about_ca_topic_score_gemma":7.587596e-8,"teacher_disagreement_score":0.81839156,"about_ca_system_score_codex":0.00005807621,"about_ca_system_score_gemma":0.00011357621,"threshold_uncertainty_score":0.99621946},"labels":[],"label_agreement":null},{"id":"W6931267091","doi":"10.5281/zenodo.4589366","title":"dockstore/dockstore-ui2: 2.7.4","year":2021,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Interface (matter); Process (computing); Identification (biology); User interface; Set (abstract data type)","score_opus":0.09066590561079756,"score_gpt":0.3327679811899743,"score_spread":0.24210207557917673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931267091","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000023972923,0.00060585083,0.009270036,0.0012933008,0.000089674766,0.00073171774,0.00025658406,0.0031264808,0.9846024],"genre_scores_gemma":[0.0042248257,0.0018201265,0.011072808,0.0011554414,0.001273686,4.7088085e-7,0.013876764,0.02424456,0.9423313],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99831796,0.00010587854,0.00023001195,0.00064218696,0.00036126623,0.0003427046],"domain_scores_gemma":[0.99828196,0.00001193389,0.00015970726,0.0010212808,0.00029378186,0.00023133782],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001521831,0.00024208601,0.00031036284,0.00033777038,0.00068920193,0.00020247595,0.0005882955,0.00015724383,0.0693989],"category_scores_gemma":[0.00027026588,0.00025577034,0.00011070583,0.0005096219,0.0001727471,0.000039413684,0.00082937576,0.0005218481,0.0036464266],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014199547,0.00013185847,0.0000018639885,0.0001499186,0.000044076343,0.000057942358,0.000048685062,7.639739e-7,0.0015110779,0.004474608,0.965626,0.027939],"study_design_scores_gemma":[0.00036490694,0.00011690591,0.000061008006,0.00025939738,0.000047306225,0.00040854368,0.000029814588,0.00002465443,0.00026543392,0.00016851633,0.998027,0.00022648966],"about_ca_topic_score_codex":0.00002018406,"about_ca_topic_score_gemma":1.8165944e-7,"teacher_disagreement_score":0.06575248,"about_ca_system_score_codex":0.00015596885,"about_ca_system_score_gemma":0.000008540964,"threshold_uncertainty_score":0.99998945},"labels":[],"label_agreement":null},{"id":"W6931783036","doi":"10.5281/zenodo.7264584","title":"IMPACT OF COVID-19 ON INFLOW OF FOREIGN DIRECT INVESTMENT.","year":2022,"lang":"en","type":"book-chapter","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Foreign direct investment; Inflow; Multinational corporation; Recession; World economy; Quarter (Canadian coin); Investment (military); Constructive","score_opus":0.1162170048877067,"score_gpt":0.34941457100669526,"score_spread":0.23319756611898856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931783036","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0003683851,0.00007890527,0.00070937164,0.00032261285,0.000012931179,0.00093271915,0.0012824646,0.0005187265,0.9957739],"genre_scores_gemma":[0.5296622,0.0060734195,0.007491904,0.005040743,0.00070288137,0.0000025011273,0.040913116,0.02120352,0.38890973],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99856967,0.000066051296,0.00035601854,0.0003912148,0.00043336893,0.0001836709],"domain_scores_gemma":[0.99828887,0.000047240814,0.00033988926,0.0007843898,0.00030397275,0.00023560967],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00026229,0.0002007397,0.00035635952,0.0004093273,0.0004915464,0.000029561052,0.000489079,0.0000771481,0.025760865],"category_scores_gemma":[0.0004538631,0.00019597665,0.00019708548,0.00018219945,0.00024109929,0.00005346069,0.0006804242,0.00042804528,0.0002592145],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006286409,0.0004565224,0.000014676785,0.0005799293,0.0003259895,0.000058890502,0.00040388427,0.0003092255,0.004748904,0.56664705,0.40171131,0.024114978],"study_design_scores_gemma":[0.00045753145,0.0014995753,0.00008373503,0.00007957615,0.000060075112,0.000088645764,0.000013943584,0.0000314635,0.00026828944,0.0054427655,0.9918329,0.00014151282],"about_ca_topic_score_codex":0.000018453513,"about_ca_topic_score_gemma":3.7223472e-8,"teacher_disagreement_score":0.60686415,"about_ca_system_score_codex":0.00041495688,"about_ca_system_score_gemma":0.00002883662,"threshold_uncertainty_score":0.9751297},"labels":[],"label_agreement":null},{"id":"W6939670003","doi":"10.6084/m9.figshare.19565791.v1","title":"Additional file 1 of Towns and trails drive carnivore movement behaviour, resource selection, and connectivity","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Environment and Protected Areas; University of British Columbia","funders":"","keywords":"Carnivore; Resource (disambiguation); Movement (music); Habitat; Selection (genetic algorithm); Function (biology)","score_opus":0.045407687948656815,"score_gpt":0.2920948518311393,"score_spread":0.2466871638824825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939670003","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015358198,0.00002002411,0.0000037119987,0.0002122103,0.0000011436255,0.0002445132,0.9971078,0.000058618305,0.00081615866],"genre_scores_gemma":[0.056395292,0.0000011445068,0.0017750997,0.0005567052,0.000033487802,0.0030566608,0.9371298,0.00001628355,0.001035541],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995652,0.000013623549,0.00007768053,0.000166343,0.000104425286,0.00007272656],"domain_scores_gemma":[0.9995295,0.00023052268,0.00006180223,0.000085764965,0.000046348257,0.000046063473],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000010591564,0.000057235255,0.00008974123,0.000035535995,0.00013739475,0.0000040140008,0.000028192548,0.000015536207,0.90215945],"category_scores_gemma":[0.00023517956,0.00006114839,0.00002150612,0.00009965545,0.000010398241,0.000024937817,0.00008316257,0.0001374774,0.0000035015244],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000062526824,0.0000472466,0.00011832268,0.000020193362,0.000004154915,0.0000027173658,0.000035729325,0.0000032038472,0.000113085196,0.000018134946,0.998375,0.0012559653],"study_design_scores_gemma":[0.00014853854,0.0001658683,0.03179578,0.00016248778,0.000009776499,0.000066454646,0.00008506167,0.0001863271,0.00037487652,0.00015137627,0.96679145,0.00006197361],"about_ca_topic_score_codex":0.0000042450556,"about_ca_topic_score_gemma":0.0000035159253,"teacher_disagreement_score":0.90215594,"about_ca_system_score_codex":0.000027761254,"about_ca_system_score_gemma":0.000031776795,"threshold_uncertainty_score":0.24935591},"labels":[],"label_agreement":null},{"id":"W6950452120","doi":"10.5281/zenodo.7853589","title":"What matters in reinforcement learning for tractography - Trained models","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université de Sherbrooke","funders":"","keywords":"Reinforcement learning; Hyperparameter; Reinforcement; Training (meteorology); Artificial neural network","score_opus":0.12044598153088538,"score_gpt":0.33502085466450593,"score_spread":0.21457487313362056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6950452120","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09029253,0.00018018665,0.7682569,0.06959812,0.00027280246,0.00868265,0.00012364652,0.01298933,0.049603857],"genre_scores_gemma":[0.9910577,0.0006596429,0.0018206022,0.0010712647,0.000068405534,0.0000014370011,0.0024638693,0.0011580072,0.0016990528],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989696,0.00004705775,0.0002102799,0.0002961929,0.00018273332,0.00029409418],"domain_scores_gemma":[0.99940336,0.000028584593,0.000058788242,0.00025594266,0.00015480994,0.0000985315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003463783,0.000097827884,0.00012788778,0.00038627334,0.00061414856,0.00021715602,0.00024146997,0.00003520594,0.00047468935],"category_scores_gemma":[0.00011605312,0.000104372695,0.000054658925,0.00078804576,0.0000639948,0.00032298308,0.00019243677,0.00021675004,0.00034671562],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007558529,0.0005074021,0.000031286603,0.00066683645,0.00010903128,0.00007217284,0.0064573414,0.050043926,0.08366365,0.030709065,0.41279393,0.4141895],"study_design_scores_gemma":[0.0009871909,0.00033452717,0.0004058193,0.00010756175,0.000014480453,0.000039787126,0.0006729574,0.04122462,0.00068175036,0.0021411364,0.9532468,0.00014337573],"about_ca_topic_score_codex":0.0000031827801,"about_ca_topic_score_gemma":6.233599e-8,"teacher_disagreement_score":0.9007652,"about_ca_system_score_codex":0.00006444173,"about_ca_system_score_gemma":0.0000022127947,"threshold_uncertainty_score":0.51975155},"labels":[],"label_agreement":null},{"id":"W6950617641","doi":"10.5683/sp3/aiahgw","title":"Scénario 69_3","year":2025,"lang":"fr","type":"dataset","venue":"Borealis","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"3d simulation; 3d model; Frame (networking)","score_opus":0.0538308744748698,"score_gpt":0.3728492578674505,"score_spread":0.3190183833925807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6950617641","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[8.097691e-7,0.0028973003,0.0035847714,0.007194845,0.00029465999,0.0007702015,0.97397035,0.00023794755,0.011049087],"genre_scores_gemma":[0.0000049015907,0.0061100037,0.0058396133,0.003961015,0.0009135663,0.00023322871,0.97415787,0.000027354761,0.008752448],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99804574,0.000051220384,0.00046024335,0.0006632537,0.00026730652,0.0005122371],"domain_scores_gemma":[0.9973072,0.00019082855,0.00018133661,0.0019520043,0.00014037559,0.00022824924],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00013513735,0.00040788978,0.0006091172,0.0001973701,0.00018468479,0.00003986783,0.0005206283,0.00034749327,0.00022424568],"category_scores_gemma":[0.0002935371,0.00041403912,0.00021084271,0.00035826745,0.00024366837,0.000055777884,0.00028558713,0.00081476977,0.000057732293],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013739365,0.00022267722,0.000057756566,0.00028782687,0.000053482505,0.00011639726,0.000009388318,0.0000037396424,0.00002156757,0.0121698985,0.97406,0.012983524],"study_design_scores_gemma":[0.00031430725,0.000096520744,0.00030891068,0.0013102471,0.0005085723,0.00006869702,0.000010588629,0.0000713161,0.00016295741,0.0011355728,0.99570614,0.00030615611],"about_ca_topic_score_codex":0.012918311,"about_ca_topic_score_gemma":0.00065884436,"teacher_disagreement_score":0.021646151,"about_ca_system_score_codex":0.00021289782,"about_ca_system_score_gemma":0.0003361382,"threshold_uncertainty_score":0.99983114},"labels":[],"label_agreement":null},{"id":"W6957721200","doi":"10.60692/0rczc-zbf06","title":"Fornix Integrity Is Differently Associated With Cognition in Healthy Aging and Non-amnestic Mild Cognitive Impairment: A Pilot Diffusion Tensor Imaging Study in Thai Older Adults","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"","keywords":"Fornix; Diffusion MRI; Fractional anisotropy; Cognition; Executive functions; Dementia; Cognitive impairment; Executive dysfunction","score_opus":0.06329485058994336,"score_gpt":0.2947313742875131,"score_spread":0.23143652369756976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957721200","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9850633,0.00000395273,0.010656843,0.00067909213,0.000015375168,0.003197469,0.000098170385,0.00021693672,0.000068849455],"genre_scores_gemma":[0.9978233,9.305867e-7,0.00014183027,0.0014875811,0.000018173676,0.00042593453,0.00007954244,0.000019949632,0.0000027400047],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9985357,0.000066195345,0.00058556756,0.0002954138,0.0002556461,0.0002615015],"domain_scores_gemma":[0.9992443,0.00003219814,0.00028536227,0.00014088559,0.00016039556,0.00013687904],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017202931,0.00022862953,0.00037058754,0.00028134533,0.00010086256,0.000058259015,0.000056772875,0.00004349499,0.0000037215302],"category_scores_gemma":[0.000044133765,0.00017998125,0.000027197624,0.0004182482,0.000034667057,0.00037496595,0.00006338202,0.00035296718,0.000011731362],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090240967,0.000084344116,0.9351418,0.0003756987,0.000012699654,0.000015621285,0.063178904,0.0000010967256,0.0000017148602,0.0000013000007,0.0000050258122,0.00027939412],"study_design_scores_gemma":[0.010899605,0.0007771716,0.9302577,0.0030899735,0.000064508014,0.000026120477,0.036864597,0.0178005,0.000046267523,0.0000015102543,4.2656393e-7,0.00017165352],"about_ca_topic_score_codex":0.000043189553,"about_ca_topic_score_gemma":0.000003931028,"teacher_disagreement_score":0.026314303,"about_ca_system_score_codex":0.00014274662,"about_ca_system_score_gemma":0.00003208127,"threshold_uncertainty_score":0.7339422},"labels":[],"label_agreement":null},{"id":"W6957900148","doi":"10.60692/0qd81-van75","title":"Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Corpus callosum; Schizophrenia (object-oriented programming); White matter; Fractional anisotropy; Diffusion MRI; Core (optical fiber); Neuroimaging","score_opus":0.08639512390122667,"score_gpt":0.29637261351750305,"score_spread":0.20997748961627638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957900148","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9934027,0.000008498902,0.002542257,0.001342275,0.00027004874,0.00079311914,0.0007254553,0.0002403183,0.0006753364],"genre_scores_gemma":[0.9937411,9.428698e-7,0.005182889,0.0004857118,0.00020670665,0.00013647926,0.00013984085,0.000021839149,0.000084490974],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99797696,0.000062296866,0.0008905749,0.00034112562,0.00033746517,0.00039157402],"domain_scores_gemma":[0.9975517,0.000049106166,0.00080952124,0.0014113629,0.000081250895,0.00009706677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035840966,0.00029633063,0.00039784698,0.000108067485,0.00077467354,0.00080158166,0.00065479503,0.00014183517,0.000013656493],"category_scores_gemma":[0.000084142914,0.00019647421,0.00010111637,0.00014792087,0.00017637822,0.00076336775,0.00030862843,0.00039809992,0.00022983542],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045962885,0.0000025308143,0.9798114,0.000038822956,0.000022280465,0.0000043159203,0.017435867,0.0000024638064,0.000029384295,0.000066474786,0.00023369516,0.0018931538],"study_design_scores_gemma":[0.0031692723,0.00002003738,0.99209255,0.0008045331,0.000029114297,0.00005803329,0.0024728435,0.00028543512,0.0004075283,0.000034025325,0.0004106343,0.00021597685],"about_ca_topic_score_codex":0.00009776056,"about_ca_topic_score_gemma":0.000006986193,"teacher_disagreement_score":0.014963024,"about_ca_system_score_codex":0.000085906126,"about_ca_system_score_gemma":0.000025019004,"threshold_uncertainty_score":0.8011986},"labels":[],"label_agreement":null},{"id":"W6957936600","doi":"10.60692/gnma5-j5308","title":"Subject–Motion Correction in HARDI Acquisitions: Choices and Consequences","year":2014,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary; Montreal Neurological Institute and Hospital","funders":"","keywords":"Motion (physics); Orientation (vector space); Noise (video); Match moving; Set (abstract data type); Interpolation (computer graphics); Software; Transformation (genetics)","score_opus":0.054041223314886554,"score_gpt":0.2810328532407359,"score_spread":0.22699162992584934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6957936600","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.85123116,0.000005884022,0.1402335,0.00043580472,0.00021497198,0.00066408765,0.000016312259,0.00049807754,0.00670021],"genre_scores_gemma":[0.998,9.618608e-7,0.0014192495,0.00033734925,0.0000458352,0.000113012225,0.000015927493,0.000005328459,0.00006229584],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993269,0.0000330374,0.00030321252,0.00011745274,0.00011130945,0.00010807674],"domain_scores_gemma":[0.99954796,0.000013548311,0.0001357468,0.00017715947,0.000077312645,0.000048298036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020182876,0.000089089255,0.00014604603,0.00021417599,0.00008614775,0.0000530412,0.000028550105,0.00005072537,0.0000082180995],"category_scores_gemma":[0.00004089759,0.0000767053,0.0000239807,0.00015967357,0.000050169652,0.00040471507,0.000015737984,0.00008204796,0.000057161466],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007881701,0.0000084745925,0.9770457,0.0005350411,0.00001436314,0.0000034410373,0.008945977,0.00010632437,0.00013970949,0.0046243337,0.00031312156,0.008184665],"study_design_scores_gemma":[0.0014351576,0.00011737084,0.9715407,0.00058500434,0.00004031555,0.0006359664,0.002717744,0.016161742,0.0038395808,0.00011973437,0.0025767672,0.00022990516],"about_ca_topic_score_codex":0.000015735084,"about_ca_topic_score_gemma":3.402738e-7,"teacher_disagreement_score":0.14676888,"about_ca_system_score_codex":0.000057824836,"about_ca_system_score_gemma":0.000011030029,"threshold_uncertainty_score":0.3127951},"labels":[],"label_agreement":null},{"id":"W6958044850","doi":"10.60692/06rtj-2m915","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Segmentation; White matter; Bundle; Diffusion MRI; Fiber bundle","score_opus":0.07414940868802887,"score_gpt":0.27084432861359076,"score_spread":0.19669491992556187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958044850","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64942485,0.000006966786,0.29617858,0.04190661,0.00038926993,0.0038037319,0.0019071392,0.0014636009,0.004919266],"genre_scores_gemma":[0.9912316,0.0000010376434,0.00067488564,0.0070817643,0.00011857791,0.00022741755,0.00061243615,0.000021129466,0.000031148316],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998626,0.00007445522,0.00052590366,0.00026502914,0.00029429822,0.00021431953],"domain_scores_gemma":[0.99878204,0.00003424209,0.00024362418,0.0007119082,0.000087656175,0.00014050645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025773008,0.00022185768,0.00025191187,0.000115068746,0.0002114766,0.00031217624,0.00018728501,0.000078213634,0.00012433069],"category_scores_gemma":[0.000032304575,0.00014478447,0.000112884045,0.00029155353,0.000057529774,0.0010588425,0.000059797658,0.00026772355,0.00063128787],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084824517,0.00006437857,0.8502144,0.0019539814,0.00020364231,0.000014479055,0.09988046,0.00011214908,0.00013173025,0.0060135024,0.038531363,0.0020316746],"study_design_scores_gemma":[0.0034613274,0.0009162892,0.8392869,0.002231337,0.00063319085,0.000679018,0.058403887,0.010653502,0.0039649354,0.0003628846,0.07779729,0.0016093852],"about_ca_topic_score_codex":0.0000029810644,"about_ca_topic_score_gemma":1.2511053e-7,"teacher_disagreement_score":0.34180677,"about_ca_system_score_codex":0.000052822852,"about_ca_system_score_gemma":0.00001295305,"threshold_uncertainty_score":0.8114139},"labels":[],"label_agreement":null},{"id":"W6958395042","doi":"10.6084/m9.figshare.27274189.v1","title":"Additional file 1 of High-cost users after sepsis: a population-based observational cohort study","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Sunnybrook Health Science Centre; University of Ottawa; Trillium Health Centre; University of British Columbia; Western University; Institute for Clinical Evaluative Sciences; McMaster University; University of Toronto; University Health Network","funders":"","keywords":"Observational study; Cohort study; Cohort; Data collection; Research design","score_opus":0.09433529156298764,"score_gpt":0.35077160987754114,"score_spread":0.2564363183145535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958395042","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00087323657,0.000008582394,0.0000129074015,0.00035256078,0.000008652909,0.0007832533,0.99751574,0.00022149841,0.00022358424],"genre_scores_gemma":[0.13901247,9.998547e-8,0.0044055954,0.0004805826,0.00007065057,0.009590398,0.84593123,0.00002100587,0.00048799097],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9992657,0.000009489267,0.00017196049,0.00023401061,0.00023100917,0.000087848726],"domain_scores_gemma":[0.9989946,0.00057724485,0.00004573263,0.000216816,0.00011929113,0.00004631848],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000011448061,0.000090290414,0.00012363058,0.000076888915,0.00003304191,0.00001493879,0.000056148096,0.000032562904,0.9798945],"category_scores_gemma":[0.00053791056,0.00008498344,0.00006682075,0.0002614694,0.000004981813,0.000073409356,0.000023719225,0.00011279597,0.0005229178],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009840948,0.00009678773,0.003913827,0.000074026946,0.000017693645,0.000015569383,0.000004273116,0.000019502746,0.0000017708408,0.000011388516,0.9954907,0.0003446607],"study_design_scores_gemma":[0.00006832341,0.000032260086,0.6153174,0.0012158896,0.000016974747,0.0000025966017,0.0000027015274,0.0009369499,0.000012371193,0.00010164074,0.3822362,0.0000566608],"about_ca_topic_score_codex":0.000007095142,"about_ca_topic_score_gemma":0.00000409652,"teacher_disagreement_score":0.9793716,"about_ca_system_score_codex":0.00004823665,"about_ca_system_score_gemma":0.00011919449,"threshold_uncertainty_score":0.6721225},"labels":[],"label_agreement":null},{"id":"W6976445412","doi":"10.60692/wn0sf-1h128","title":"High resolution diffusion imaging in the unfixed post-mortem infant brain at 7T","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Context (archaeology); Diffusion MRI; Tractography; Diffusion imaging; High resolution; Brain tissue; Human brain","score_opus":0.039260283882608014,"score_gpt":0.2790321893806808,"score_spread":0.23977190549807278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976445412","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9462045,0.000025425814,0.04196708,0.007552811,0.0002055271,0.0011584063,0.0000871785,0.00084504805,0.0019540694],"genre_scores_gemma":[0.99718726,7.7890144e-7,0.0006782945,0.0015630483,0.00008150718,0.0001829699,0.00010601811,0.000014430364,0.00018566904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879444,0.000050312337,0.00049351086,0.00017627556,0.00028165462,0.000203792],"domain_scores_gemma":[0.999302,0.000025172714,0.0001052341,0.0004411735,0.0000782223,0.00004814362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038452784,0.00014642437,0.0001600681,0.00029731935,0.000141246,0.00011223723,0.00011948152,0.00005000306,0.000011356452],"category_scores_gemma":[0.000028547958,0.00009528513,0.00006968787,0.00039139678,0.000032836444,0.00039539847,0.0000739669,0.00017822682,0.0002491664],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010331629,0.00006566693,0.55095303,0.0061122198,0.00010661105,0.0005598286,0.3202008,0.0006142582,0.00554122,0.053906396,0.032421578,0.02848522],"study_design_scores_gemma":[0.0028911042,0.00017473215,0.82717943,0.0029927257,0.00014621331,0.0028111727,0.016926182,0.09197856,0.0026011032,0.00008111365,0.051529028,0.0006886142],"about_ca_topic_score_codex":0.000034930883,"about_ca_topic_score_gemma":6.286344e-7,"teacher_disagreement_score":0.30327463,"about_ca_system_score_codex":0.00024008505,"about_ca_system_score_gemma":0.00002930446,"threshold_uncertainty_score":0.3885615},"labels":[],"label_agreement":null},{"id":"W6976483059","doi":"10.60692/sdwb0-b6g13","title":"High resolution diffusion imaging in the unfixed post-mortem infant brain at 7T","year":2024,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"St. Thomas Hospital","funders":"","keywords":"Context (archaeology); Diffusion MRI; Tractography; Diffusion imaging; High resolution; Brain tissue; Human brain","score_opus":0.039260283882608014,"score_gpt":0.2790321893806808,"score_spread":0.23977190549807278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976483059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9462045,0.000025425814,0.04196708,0.007552811,0.0002055271,0.0011584063,0.0000871785,0.00084504805,0.0019540694],"genre_scores_gemma":[0.99718726,7.7890144e-7,0.0006782945,0.0015630483,0.00008150718,0.0001829699,0.00010601811,0.000014430364,0.00018566904],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99879444,0.000050312337,0.00049351086,0.00017627556,0.00028165462,0.000203792],"domain_scores_gemma":[0.999302,0.000025172714,0.0001052341,0.0004411735,0.0000782223,0.00004814362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038452784,0.00014642437,0.0001600681,0.00029731935,0.000141246,0.00011223723,0.00011948152,0.00005000306,0.000011356452],"category_scores_gemma":[0.000028547958,0.00009528513,0.00006968787,0.00039139678,0.000032836444,0.00039539847,0.0000739669,0.00017822682,0.0002491664],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010331629,0.00006566693,0.55095303,0.0061122198,0.00010661105,0.0005598286,0.3202008,0.0006142582,0.00554122,0.053906396,0.032421578,0.02848522],"study_design_scores_gemma":[0.0028911042,0.00017473215,0.82717943,0.0029927257,0.00014621331,0.0028111727,0.016926182,0.09197856,0.0026011032,0.00008111365,0.051529028,0.0006886142],"about_ca_topic_score_codex":0.000034930883,"about_ca_topic_score_gemma":6.286344e-7,"teacher_disagreement_score":0.30327463,"about_ca_system_score_codex":0.00024008505,"about_ca_system_score_gemma":0.00002930446,"threshold_uncertainty_score":0.3885615},"labels":[],"label_agreement":null},{"id":"W6976546751","doi":"10.60692/9bvr8-p7s07","title":"Identification and Classification of Alzheimer's Disease Patients Using Novel Fractional Motion Model","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Hurst exponent; Receiver operating characteristic; Correlation; Pattern recognition (psychology); Diffusion MRI; Fractional Brownian motion; Detrended fluctuation analysis; Exponent","score_opus":0.17790635687034637,"score_gpt":0.31222454646661385,"score_spread":0.13431818959626748,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976546751","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38559794,0.0000014563882,0.6135129,0.00021064728,0.000017270037,0.0003803551,0.000116342344,0.00009357401,0.00006955738],"genre_scores_gemma":[0.9942135,2.2708736e-7,0.005435634,0.00017200787,0.000025386298,0.000039886603,0.00010146974,0.000008771377,0.0000030954016],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991145,0.00000871795,0.00045419217,0.00013552837,0.00021526571,0.00007177219],"domain_scores_gemma":[0.99905175,0.000002424634,0.00037833268,0.00017956272,0.0002704948,0.000117406926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000059712766,0.000088925306,0.00012521696,0.0000981875,0.00007369251,0.000024567085,0.000037878315,0.000038728045,0.000002142627],"category_scores_gemma":[0.000026679985,0.00008456497,0.000037348775,0.00014489656,0.000029248053,0.00051265303,0.000023119945,0.000060374496,0.000013887867],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000536408,0.00007755984,0.9488211,0.0016243627,0.00010539606,4.6843564e-7,0.013931104,0.014574918,0.009226155,0.008588723,0.0001552995,0.002358476],"study_design_scores_gemma":[0.0004718825,0.000012093346,0.3435879,0.00004657903,0.00009232807,0.0000028501029,0.00023202538,0.65458643,0.0008781754,0.0000066357475,0.000020555803,0.00006251696],"about_ca_topic_score_codex":6.116993e-7,"about_ca_topic_score_gemma":1.9832973e-9,"teacher_disagreement_score":0.64001155,"about_ca_system_score_codex":0.00003964952,"about_ca_system_score_gemma":0.000027470174,"threshold_uncertainty_score":0.34484592},"labels":[],"label_agreement":null},{"id":"W6976597944","doi":"10.60692/nqdvd-9np21","title":"Tractography dissection variability: what happens when 42 groups dissect 14 white matter bundles on the same dataset?","year":2020,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Tractography; Segmentation; White matter; Bundle; Diffusion MRI; Fiber bundle","score_opus":0.07414940868802887,"score_gpt":0.27084432861359076,"score_spread":0.19669491992556187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976597944","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.64942485,0.000006966786,0.29617858,0.04190661,0.00038926993,0.0038037319,0.0019071392,0.0014636009,0.004919266],"genre_scores_gemma":[0.9912316,0.0000010376434,0.00067488564,0.0070817643,0.00011857791,0.00022741755,0.00061243615,0.000021129466,0.000031148316],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.998626,0.00007445522,0.00052590366,0.00026502914,0.00029429822,0.00021431953],"domain_scores_gemma":[0.99878204,0.00003424209,0.00024362418,0.0007119082,0.000087656175,0.00014050645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025773008,0.00022185768,0.00025191187,0.000115068746,0.0002114766,0.00031217624,0.00018728501,0.000078213634,0.00012433069],"category_scores_gemma":[0.000032304575,0.00014478447,0.000112884045,0.00029155353,0.000057529774,0.0010588425,0.000059797658,0.00026772355,0.00063128787],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084824517,0.00006437857,0.8502144,0.0019539814,0.00020364231,0.000014479055,0.09988046,0.00011214908,0.00013173025,0.0060135024,0.038531363,0.0020316746],"study_design_scores_gemma":[0.0034613274,0.0009162892,0.8392869,0.002231337,0.00063319085,0.000679018,0.058403887,0.010653502,0.0039649354,0.0003628846,0.07779729,0.0016093852],"about_ca_topic_score_codex":0.0000029810644,"about_ca_topic_score_gemma":1.2511053e-7,"teacher_disagreement_score":0.34180677,"about_ca_system_score_codex":0.000052822852,"about_ca_system_score_gemma":0.00001295305,"threshold_uncertainty_score":0.8114139},"labels":[],"label_agreement":null},{"id":"W6977136271","doi":"10.6084/m9.figshare.13357659.v1","title":"Additional file 4 of The effect of a pharmacist consultation on pregnant women’s quality of life with a special focus on nausea and vomiting: an intervention study","year":2020,"lang":"en","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Intervention (counseling); Quality of life (healthcare); Pharmacist; Focus group; Nausea; Baseline (sea); Focus (optics)","score_opus":0.10438433448930275,"score_gpt":0.37825961261674257,"score_spread":0.27387527812743984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6977136271","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17469402,0.000002328114,0.0000022432043,0.00006707379,0.0000020599882,0.0007968906,0.82419026,0.000020432544,0.0002247002],"genre_scores_gemma":[0.94522864,1.819812e-7,0.000076449374,0.000058813624,0.00005784483,0.0008853035,0.05367024,0.000008089282,0.000014466691],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9993723,0.00007829212,0.00019077597,0.00013886689,0.00016973207,0.00005003779],"domain_scores_gemma":[0.99884063,0.0006418379,0.0002691244,0.00011965051,0.00008042266,0.000048359594],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000031729385,0.00006750437,0.00016898976,0.000020553985,0.000024763267,0.0000027642357,0.000052241307,0.0000140218945,0.19138731],"category_scores_gemma":[0.0021658237,0.00004398072,0.000035133056,0.00010759087,0.000020003105,0.00002789703,0.000026920226,0.00008904808,0.000004925648],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0054326775,0.0014900316,0.0013446256,0.0016346391,0.00009560337,0.0000045215857,0.0015259006,0.00001522608,0.001034361,0.000036322148,0.9741782,0.013207884],"study_design_scores_gemma":[0.030890914,0.07103054,0.6597343,0.035794456,0.00020745127,0.000018441931,0.0017762516,0.0019966303,0.13696094,0.00020917365,0.060714994,0.0006658859],"about_ca_topic_score_codex":0.0000012857403,"about_ca_topic_score_gemma":0.0000015965683,"teacher_disagreement_score":0.91346323,"about_ca_system_score_codex":0.000015242701,"about_ca_system_score_gemma":0.000025775898,"threshold_uncertainty_score":0.80935186},"labels":[],"label_agreement":null},{"id":"W6980568879","doi":"","title":"Clifton wind farm owners enter partnership with Canadian energy firm [Bangor Daily News, Maine]","year":2016,"lang":"en","type":"other","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"General partnership; Energy (signal processing); Wind power; Renewable energy; Government (linguistics); Work (physics)","score_opus":0.03869472779378222,"score_gpt":0.3163243483050506,"score_spread":0.2776296205112684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6980568879","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000011162742,0.00012336728,0.0051929723,0.008149604,0.000039561517,0.0004843801,0.00007749417,0.0005770046,0.98534447],"genre_scores_gemma":[0.0015314672,0.000323197,0.006375043,0.008274467,0.00050699,0.00010088327,0.00019318494,0.0005221582,0.9821726],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985716,0.000015831514,0.00018347899,0.000545447,0.00020083097,0.0004828395],"domain_scores_gemma":[0.9985096,0.00002213343,0.00012396455,0.0008051411,0.00003778697,0.0005014074],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000032292217,0.00035785406,0.00037018204,0.0003350779,0.00005162574,0.000018194534,0.00019231363,0.0002169557,0.00517845],"category_scores_gemma":[0.000008251857,0.00021584069,0.000079800884,0.00013661952,0.00013248477,0.00002135365,0.000028387885,0.00019991299,0.00016084405],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025135303,0.000037669597,0.0014257582,0.000028813312,0.000058004716,0.00006934891,0.000008317611,7.980056e-8,0.00006421042,0.0059424117,0.98495513,0.007385147],"study_design_scores_gemma":[0.0005723341,0.00009976585,0.00010302004,0.00034213014,0.000085057225,0.000048914113,0.000017059288,0.000003276191,0.00022902858,0.00014190307,0.9980506,0.0003069242],"about_ca_topic_score_codex":0.05693896,"about_ca_topic_score_gemma":0.17635742,"teacher_disagreement_score":0.11941845,"about_ca_system_score_codex":0.0001493922,"about_ca_system_score_gemma":0.00027457663,"threshold_uncertainty_score":0.99573094},"labels":[],"label_agreement":null},{"id":"W6982192183","doi":"","title":"Haydn et l'opera buffa, analyse dramaturgique et stylistique de \"La fedelta premiata\" (French text, Joseph Haydn, Austria)","year":2000,"lang":"fr","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Subject (documents); Context (archaeology); Feature (linguistics); Identity (music)","score_opus":0.007788213969374981,"score_gpt":0.2318637448835944,"score_spread":0.22407553091421942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6982192183","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030546556,0.0023478223,0.0031597256,0.01941689,0.00015485077,0.0009695144,0.0020124004,0.00009156951,0.96879256],"genre_scores_gemma":[0.5100585,0.0101798335,0.028131915,0.012304652,0.00039962423,0.00015418787,0.00029518883,0.00038549464,0.43809056],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9958856,0.0004775237,0.000691484,0.0008050404,0.0014036366,0.00073669746],"domain_scores_gemma":[0.99695057,0.0009859672,0.0004528873,0.00081951986,0.0000018924427,0.0007891956],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000060781593,0.0006942984,0.0008657328,0.00010023534,0.00020555579,0.00009428068,0.00054776156,0.00025670585,0.0012086319],"category_scores_gemma":[0.000029222423,0.0007023327,0.000120683755,0.00023343354,0.0003837325,0.00030023084,0.0002561468,0.0013037059,4.8317087e-8],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":true,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011051281,0.00068076997,0.029490894,0.002098784,0.00084681006,0.0019005649,0.0005602571,0.0013053337,0.04646633,0.6882695,0.17364456,0.05363105],"study_design_scores_gemma":[0.0007560326,0.00013857323,0.023633935,0.0015577159,0.00023430302,0.00012422513,0.00028375725,0.0016936802,0.014735322,0.0020430856,0.9541098,0.00068957306],"about_ca_topic_score_codex":0.018403813,"about_ca_topic_score_gemma":0.035476808,"teacher_disagreement_score":0.78046525,"about_ca_system_score_codex":0.00007032289,"about_ca_system_score_gemma":0.007211393,"threshold_uncertainty_score":0.9997044},"labels":[],"label_agreement":null},{"id":"W6983403260","doi":"","title":"Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware [accepted manuscript]","year":2018,"lang":"en","type":"article","venue":"Research Bank (Australian Catholic University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust","keywords":"Tractography; Siemens; Variance (accounting); Data acquisition; Protocol (science); Diffusion MRI; Optic radiation; Loop (graph theory); Epilepsy surgery","score_opus":0.26923883609895466,"score_gpt":0.4482483460042289,"score_spread":0.17900950990527426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6983403260","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6671692,0.000029001809,0.0118510565,0.049796466,0.00020652359,0.19890137,0.000696941,0.0025706715,0.06877877],"genre_scores_gemma":[0.89949054,0.00010960564,0.036756426,0.0009108851,0.000869629,0.010394738,0.00020888663,0.0002420005,0.05101732],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978799,0.00012777702,0.00021741966,0.0006661805,0.0004023861,0.00070634065],"domain_scores_gemma":[0.9980365,0.00022637342,0.00008270172,0.00061359984,0.0006723484,0.0003684519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057865895,0.00022360058,0.00030288773,0.0013729376,0.00054506946,0.00008740269,0.00026239606,0.00009348807,0.0001325164],"category_scores_gemma":[0.00018132325,0.00022943901,0.00017173332,0.001223812,0.0007529866,0.00030496108,0.00012105204,0.0005134022,0.000024380752],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004593367,0.0023699026,0.03858775,0.0022954582,0.00030811442,0.0031212908,0.0018032157,0.0000019760623,0.26691884,0.011942925,0.4879198,0.18013738],"study_design_scores_gemma":[0.0014993551,0.0003615667,0.013728094,0.0002187266,0.000051610023,0.00014971316,0.00022796621,0.00007470229,0.054577287,0.00030315478,0.9285191,0.000288684],"about_ca_topic_score_codex":0.00009321196,"about_ca_topic_score_gemma":0.0000061737387,"teacher_disagreement_score":0.44059935,"about_ca_system_score_codex":0.00014600818,"about_ca_system_score_gemma":0.00015683327,"threshold_uncertainty_score":0.9356252},"labels":[],"label_agreement":null},{"id":"W6990497220","doi":"","title":"Diffusion imaging of white matter fibre tracts","year":2004,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Diffusion MRI; Imaging phantom; White matter; Tractography; Magnetic resonance imaging; Tracking (education); Partial volume; Diffusion; Fiber tract; Point spread function","score_opus":0.02391838742505104,"score_gpt":0.2983301245031977,"score_spread":0.27441173707814664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6990497220","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91532266,0.0002244924,0.0000077690165,0.00025232814,0.000295159,0.0012209599,0.0006296312,0.00047131738,0.0815757],"genre_scores_gemma":[0.97912145,0.00023905809,0.007368736,0.0008470824,0.000050019167,0.0001636425,0.0015185892,0.00028269828,0.010408731],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99689215,0.00006034377,0.00091111416,0.0009723376,0.0006321541,0.0005318908],"domain_scores_gemma":[0.9974922,0.00007471231,0.00070116966,0.0010601722,0.00038433346,0.0002873929],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001964728,0.0006425278,0.0008415698,0.00043106987,0.00064085383,0.000022310809,0.0003789574,0.00038543422,0.0003963965],"category_scores_gemma":[0.0001425647,0.0006508056,0.00042006702,0.0004901549,0.0000762428,0.00037170548,0.0001411301,0.0014198349,0.00015056464],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088588113,0.0017847816,0.0073592463,0.003962793,0.000208247,0.0003839102,0.00005263153,0.000043453514,0.8112635,0.03419582,0.00015368438,0.13970608],"study_design_scores_gemma":[0.00421515,0.00042278567,0.14015612,0.0076764463,0.0013191476,0.000645185,0.00034372386,0.0000489706,0.64265484,0.07330815,0.12675038,0.0024591286],"about_ca_topic_score_codex":0.0000735727,"about_ca_topic_score_gemma":0.000031238123,"teacher_disagreement_score":0.16860867,"about_ca_system_score_codex":0.00040287417,"about_ca_system_score_gemma":0.00007029819,"threshold_uncertainty_score":0.99959433},"labels":[],"label_agreement":null},{"id":"W6991361011","doi":"","title":"Guerre et paix : La valse à deux temps de l'atome au Canada","year":2021,"lang":"fr","type":"other","venue":"R-libre (Université Téluq)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"First world war; Context (archaeology); Portrait; Object (grammar)","score_opus":0.022795062552245574,"score_gpt":0.277538736026601,"score_spread":0.25474367347435545,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6991361011","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05500456,0.005071831,0.017000755,0.024127621,0.0008588273,0.0013499021,0.0005892501,0.00075212214,0.89524513],"genre_scores_gemma":[0.14426614,0.0028959897,0.009941931,0.003600838,0.0009970791,0.000034761648,0.0005453028,0.0005433746,0.8371746],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9976215,0.00020545798,0.00024565565,0.00078211795,0.00037392986,0.00077134714],"domain_scores_gemma":[0.9977933,0.00031114547,0.0002502543,0.0010111057,0.00010674858,0.00052744255],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015930846,0.0005256348,0.00064609695,0.00012243979,0.0002573304,0.000033138593,0.0005491419,0.00041728598,0.005196471],"category_scores_gemma":[0.000073112096,0.00062879623,0.00022714736,0.0006877127,0.00019495848,0.000110736306,0.0003688776,0.0009219847,0.000059345],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000087096996,0.0005184623,0.016918205,0.0014752108,0.00064928463,0.010107878,0.0011218695,0.00014806802,0.0055903946,0.08631916,0.2574709,0.61959344],"study_design_scores_gemma":[0.00070062006,0.0000515188,0.05442597,0.0013190854,0.00032234797,0.00047572787,0.00041129222,0.00025414155,0.0002846173,0.00035842942,0.9408693,0.00052696257],"about_ca_topic_score_codex":0.21817145,"about_ca_topic_score_gemma":0.3260011,"teacher_disagreement_score":0.68339837,"about_ca_system_score_codex":0.0015029548,"about_ca_system_score_gemma":0.0046358416,"threshold_uncertainty_score":0.9996163},"labels":[],"label_agreement":null},{"id":"W6996142048","doi":"","title":"Reduced field of view diffusion imaging at 7T using the “blOCh” pulse design package","year":2016,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"iNano Medical (Canada)","funders":"","keywords":"Field (mathematics); Pulse (music); Diffusion; Electromagnetic field; Reliability (semiconductor)","score_opus":0.09656309656697007,"score_gpt":0.3796296811499766,"score_spread":0.2830665845830065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6996142048","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1542591,0.0001537554,0.8268969,0.015969645,0.000028696491,0.0005507697,0.0000023680961,0.00014582239,0.0019929241],"genre_scores_gemma":[0.959985,0.00022343872,0.037126925,0.0012819647,0.000039303948,0.000020023708,8.8012456e-7,0.000018009281,0.0013044352],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993744,0.000027033644,0.00017858937,0.00017259395,0.00010927674,0.00013811914],"domain_scores_gemma":[0.9991499,0.00020626011,0.0000740635,0.0004738,0.000050578637,0.00004538133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010848916,0.00008688494,0.00013546509,0.000032468655,0.00009215362,0.00000405142,0.00009739812,0.000021415191,0.00024122579],"category_scores_gemma":[0.00008926649,0.00004156917,0.000056525976,0.00011157586,0.00006569866,0.000045411227,0.000096333206,0.0000616027,0.000006835037],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002534355,0.000031421107,0.00087542686,0.000011607837,0.0000030664355,0.0000033028277,0.000021745123,4.3433127e-7,0.9640273,0.0005534485,0.0016866743,0.032760248],"study_design_scores_gemma":[0.00036563084,0.000051326515,0.00093531463,0.00024040727,0.000045868936,0.00008913935,0.000020385654,0.00082724495,0.99089074,0.0017993456,0.0046490026,0.00008556469],"about_ca_topic_score_codex":0.000018529645,"about_ca_topic_score_gemma":5.027988e-7,"teacher_disagreement_score":0.80572593,"about_ca_system_score_codex":0.00003612082,"about_ca_system_score_gemma":0.000018648936,"threshold_uncertainty_score":0.26412532},"labels":[],"label_agreement":null},{"id":"W7006586430","doi":"","title":"Upper and extra-motoneuron involvement in early motoneuron disease: a diffusion tensor imaging study","year":2011,"lang":"en","type":"article","venue":"EUR Research Repository (Erasmus University Rotterdam)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Pediatric Oncology Group","funders":"","keywords":"Diffusion MRI; Diffusion; Tensor (intrinsic definition); Intensity (physics); Noise (video)","score_opus":0.1186860102379764,"score_gpt":0.3415962067385941,"score_spread":0.2229101965006177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7006586430","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99403346,0.00007312874,0.00020919178,0.0006176089,0.000040797226,0.002131684,0.000005609034,0.0001771536,0.002711395],"genre_scores_gemma":[0.9964819,0.0000952836,0.0007171471,0.00011831314,0.000045454108,0.000031315085,0.0000043408495,0.00003895739,0.0024672865],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9975188,0.00039084404,0.00023475537,0.0007890957,0.00057165197,0.00049489265],"domain_scores_gemma":[0.9985696,0.00007750469,0.00006488473,0.00072814577,0.00016076249,0.00039912146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033249726,0.00020845608,0.00023726377,0.0005939168,0.00047550566,0.000046905163,0.00028161265,0.000037437636,0.000014743582],"category_scores_gemma":[0.0000429695,0.00021475033,0.00006698114,0.00045107986,0.00026627624,0.00027558568,0.0006489718,0.0007058213,0.000009846698],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007999802,0.0013382045,0.97486144,0.000054218533,0.000012063119,0.0041504498,0.0014688487,6.5629615e-7,0.016040038,0.00016857355,0.00024599413,0.0008595241],"study_design_scores_gemma":[0.0020564175,0.0005496989,0.9917328,0.00011903647,0.00003763713,0.000054713088,0.0008930684,0.0005284409,0.0009964149,0.00013719959,0.0027054807,0.00018914536],"about_ca_topic_score_codex":0.00083528896,"about_ca_topic_score_gemma":0.000011821575,"teacher_disagreement_score":0.016871298,"about_ca_system_score_codex":0.00020092723,"about_ca_system_score_gemma":0.00008065862,"threshold_uncertainty_score":0.8757264},"labels":[],"label_agreement":null},{"id":"W7014465020","doi":"","title":"Probing tissue microstructure using oscillating spin echo gradients","year":2018,"lang":"en","type":"dissertation","venue":"Mspace (University of Manitoba)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Manitoba; University of Winnipeg","keywords":"Axon; Spin echo; Diffusion; Monte Carlo method; Gradient echo; Cylinder; Planar; Range (aeronautics); Measure (data warehouse)","score_opus":0.039345015143173095,"score_gpt":0.30488886098625095,"score_spread":0.2655438458430779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7014465020","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9921082,0.00007539911,0.0037180244,0.00018513203,0.00017040293,0.0006733292,0.00003179823,0.00016542226,0.0028722445],"genre_scores_gemma":[0.7449188,0.00014276106,0.2486855,0.00007582742,0.0003014163,0.000001180742,0.00075814134,0.00012528404,0.0049910517],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99906033,0.000015252084,0.00011706392,0.0003939791,0.00020083082,0.00021252924],"domain_scores_gemma":[0.9989792,0.00001078399,0.00034941258,0.00037300604,0.0002080208,0.000079571895],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00004985978,0.0002085153,0.0003436289,0.0002050316,0.00030240184,0.000011730229,0.00019292392,0.00020832059,0.000014917031],"category_scores_gemma":[0.000019219457,0.00026578747,0.00010073717,0.0002592432,0.00009167815,0.0000948923,0.00006556283,0.0003153155,0.000010207428],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004351924,0.00019669719,0.029237414,0.0023322112,0.00019643271,0.00018836987,0.0025762536,0.000044446246,0.9428107,0.0005117344,0.007268957,0.014201578],"study_design_scores_gemma":[0.005291902,0.0015766047,0.43160507,0.0112059135,0.0032749423,0.0005583796,0.063596115,0.0067472425,0.25320697,0.003905822,0.2157057,0.0033253257],"about_ca_topic_score_codex":0.000512503,"about_ca_topic_score_gemma":0.008070059,"teacher_disagreement_score":0.68960375,"about_ca_system_score_codex":0.00015539459,"about_ca_system_score_gemma":0.00007450687,"threshold_uncertainty_score":0.99997944},"labels":[],"label_agreement":null},{"id":"W7027949612","doi":"","title":"Diffusion of personal health information : self-determining and empowering practices for Manitoba Inuit","year":2012,"lang":"en","type":"other","venue":"VIUSpace (Vancouver Island University Library)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Relevance (law); Health information; Health care; Set (abstract data type); Space (punctuation); HRHIS; Information system; Personally identifiable information","score_opus":0.022553993890534942,"score_gpt":0.274778308119597,"score_spread":0.2522243142290621,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7027949612","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008217385,0.00077771815,0.021782244,0.004021415,0.00047464878,0.0038740481,0.0010248068,0.0018654419,0.9579623],"genre_scores_gemma":[0.03193675,0.0047290693,0.16459821,0.0008633543,0.000492546,0.000014099344,0.00021880177,0.00038685204,0.7967603],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999398,0.000016978285,0.00012151147,0.0001714817,0.00011631551,0.00017571008],"domain_scores_gemma":[0.99896836,0.000051746425,0.0006790242,0.00017249191,0.000019200741,0.00010915504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000031991487,0.00016682512,0.0002877867,0.00027862296,0.0000876828,0.000013793718,0.00008405258,0.00011891914,0.00008753716],"category_scores_gemma":[0.000011651156,0.00016474717,0.000058599035,0.00012451381,0.000041113366,0.00068576727,0.00011959876,0.00015758094,0.0000017736237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008110966,0.00006313251,0.0012780264,0.0007891362,0.000037748545,0.0000024769602,0.0019349847,1.3364779e-7,0.000021973423,0.00014903545,0.98979414,0.0058481027],"study_design_scores_gemma":[0.0007590732,0.00016240931,0.0004168471,0.00037348224,0.00008551774,0.000006517491,0.0015836223,0.00016692825,0.000037564598,0.00001612457,0.99624026,0.0001516311],"about_ca_topic_score_codex":0.00019467773,"about_ca_topic_score_gemma":0.005509643,"teacher_disagreement_score":0.16120197,"about_ca_system_score_codex":0.00004754341,"about_ca_system_score_gemma":0.00013907785,"threshold_uncertainty_score":0.67181945},"labels":[],"label_agreement":null},{"id":"W7029452335","doi":"","title":"Investigating VTA, SNc and dopamine projections in the brain using MRI","year":2018,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Dopamine; Dopaminergic; Neurotransmitter; Neuron; Neuroimaging; Central nervous system; Brain mapping","score_opus":0.2442081936304015,"score_gpt":0.4090928660723926,"score_spread":0.1648846724419911,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7029452335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99102587,0.00002341149,0.004946105,0.002990632,0.000030504556,0.0005337724,0.0000069466532,0.00014368666,0.00029908726],"genre_scores_gemma":[0.99505115,0.000018046981,0.0024694677,0.0015581083,0.00012232253,0.000003342261,0.000007867446,0.00002546327,0.00074425805],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887496,0.00012399499,0.00017104331,0.00038728176,0.00017736058,0.00026537446],"domain_scores_gemma":[0.99916416,0.0001073977,0.00010016222,0.0004276577,0.00009076831,0.00010983127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029018175,0.00016675319,0.00017741256,0.00031724357,0.00032806487,0.00008355533,0.00024074026,0.00007841349,0.000004356258],"category_scores_gemma":[0.00008378175,0.00014988486,0.0000419991,0.0007376929,0.00033055182,0.00049941416,0.00016448989,0.00047660354,0.000010195908],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015178,0.000058787384,0.9899115,0.00002659346,0.000008183498,0.000053879907,0.00037390218,0.0000028355812,0.0088599045,0.0002798228,0.0000019359625,0.00040747758],"study_design_scores_gemma":[0.0008762815,0.00022399866,0.98775685,0.00027753698,0.00007250496,0.00044966352,0.00055326446,0.000023391172,0.0031323265,0.00052914716,0.00587939,0.00022563568],"about_ca_topic_score_codex":0.000012074252,"about_ca_topic_score_gemma":0.00037181075,"teacher_disagreement_score":0.0058774543,"about_ca_system_score_codex":0.00009275993,"about_ca_system_score_gemma":0.00006644009,"threshold_uncertainty_score":0.61121273},"labels":[],"label_agreement":null},{"id":"W7074072862","doi":"","title":"Diffusion-tensor imaging at 3 T - Detection of white matter alterations in neurological patients on the basis of normal values","year":2007,"lang":"en","type":"article","venue":"UCL Discovery (University College London)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"White matter; Fractional anisotropy; Diffusion MRI; Confidence interval; Diffusion imaging; Anisotropy; Spatial normalization; Isotropy; Magnetic resonance imaging","score_opus":0.01474593932125867,"score_gpt":0.2366414716413514,"score_spread":0.22189553232009274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7074072862","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9904219,0.000003794295,0.0058310847,0.001846343,0.000031714644,0.00042005343,0.00013485935,0.000025688478,0.0012845543],"genre_scores_gemma":[0.9974216,0.00001039615,0.00046952526,0.00057397864,0.000011652204,0.0000017490239,0.000015482156,0.000009147778,0.0014864169],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924725,0.000044282202,0.00017255645,0.00020572757,0.00017751285,0.00015269255],"domain_scores_gemma":[0.9993329,0.00016207031,0.00012255397,0.00026981955,0.00007374404,0.000038915296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009413846,0.0000987434,0.00016571792,0.00020664476,0.00022431437,0.0000030728283,0.00011448828,0.000035268476,0.00006762834],"category_scores_gemma":[0.0000305143,0.00008139378,0.00009190343,0.0003959549,0.00012964981,0.00020373167,0.00016751605,0.00015298487,0.000005921059],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00089479296,0.00042530012,0.9901873,0.00001818815,0.00000730122,0.000030027497,0.00016623658,0.0000437872,0.0061772983,0.0012553788,0.0005094121,0.0002850047],"study_design_scores_gemma":[0.00078952906,0.0001612275,0.99125856,0.000034849127,0.000031816715,0.000008894665,0.00017966035,0.0013191927,0.0056159846,0.00012052619,0.00040568452,0.00007405128],"about_ca_topic_score_codex":0.000039545255,"about_ca_topic_score_gemma":0.000045863108,"teacher_disagreement_score":0.006999744,"about_ca_system_score_codex":0.00005998173,"about_ca_system_score_gemma":0.00001248023,"threshold_uncertainty_score":0.33191422},"labels":[],"label_agreement":null},{"id":"W7086785543","doi":"10.5281/zenodo.17307263","title":"Digital book & tutorial","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Centre for Addiction and Mental Health","funders":"","keywords":"Workflow; Preprocessor; Work (physics)","score_opus":0.04687585758568818,"score_gpt":0.30917007210102704,"score_spread":0.26229421451533885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7086785543","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0000012099966,0.00023037751,0.011160647,0.00097553706,0.000103345694,0.00066965196,0.0006008833,0.0032567778,0.9830016],"genre_scores_gemma":[0.00029222172,0.00040621767,0.0010271458,0.00048243313,0.00072258856,1.05044826e-7,0.0033363297,0.0060450016,0.98768795],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99893135,0.0000335598,0.0001638375,0.00041696825,0.00023242552,0.00022186818],"domain_scores_gemma":[0.99898356,0.000009942383,0.00009299023,0.0006052341,0.00018538801,0.00012286457],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000073223135,0.00016449286,0.000200027,0.00028427987,0.00045980638,0.00029181023,0.00044939926,0.00011121196,0.024645023],"category_scores_gemma":[0.00026908028,0.00017106926,0.00007168346,0.00028887406,0.00012569698,0.000069992275,0.0006453063,0.0003317135,0.005514138],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002141406,0.000075549564,3.1044073e-7,0.000069459995,0.000026930718,0.000011952909,0.000011652982,2.1227527e-7,0.00015795464,0.003933619,0.9225331,0.073157854],"study_design_scores_gemma":[0.0003479661,0.0000973969,0.000010246811,0.00015204813,0.000032138152,0.000066510736,0.0000076005485,0.000011398255,0.00006860314,0.00017060841,0.9988993,0.00013620172],"about_ca_topic_score_codex":0.00000448764,"about_ca_topic_score_gemma":1.7309016e-8,"teacher_disagreement_score":0.07636619,"about_ca_system_score_codex":0.000092863294,"about_ca_system_score_gemma":0.000007836095,"threshold_uncertainty_score":0.9952602},"labels":[],"label_agreement":null},{"id":"W7096269665","doi":"","title":"© Science and Education Publishing DOI:10.12691/env-3-3-3 Flood Vulnerability Assessment of Niger Delta States","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Niger delta; Vulnerability (computing); Flooding (psychology); Flood myth; Vulnerability assessment; Quarter (Canadian coin); Delta; Risk assessment","score_opus":0.09850929873630512,"score_gpt":0.4285512833466199,"score_spread":0.33004198461031475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096269665","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9098669,0.000080130696,0.034299713,0.01469902,0.00007080303,0.000653109,0.000010035917,0.000201505,0.040118743],"genre_scores_gemma":[0.90104187,0.000018043072,0.09709266,0.0007225904,0.000035415094,0.00004219409,0.0000204587,0.000008137229,0.0010186442],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9989534,0.000018022556,0.00020831646,0.00029599492,0.0003785398,0.0001457424],"domain_scores_gemma":[0.99833256,0.000053972242,0.0000791901,0.000408331,0.00092903024,0.00019693529],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008729457,0.00007939584,0.00013839938,0.00014260093,0.00008275829,0.00008691169,0.00013032499,0.000025493788,0.000040270126],"category_scores_gemma":[0.00064658985,0.00006336911,0.000016027334,0.0005254583,0.00028585162,0.0006597723,0.0001118714,0.00014076683,0.0000014039316],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009191615,0.0036707649,0.3307161,0.0003606883,0.000034812812,0.0000032490793,0.0009748987,0.000121719895,0.07691425,0.14699481,0.15558101,0.28453577],"study_design_scores_gemma":[0.0033190395,0.0016937495,0.42459044,0.00030795333,0.00020467986,0.0001629822,0.0033991921,0.050891977,0.095651515,0.12312738,0.29572996,0.00092112675],"about_ca_topic_score_codex":0.000104520266,"about_ca_topic_score_gemma":0.0000040215214,"teacher_disagreement_score":0.28361464,"about_ca_system_score_codex":0.00011946663,"about_ca_system_score_gemma":0.0011448233,"threshold_uncertainty_score":0.25841174},"labels":[],"label_agreement":null},{"id":"W7096400195","doi":"","title":"maturation and correlation with postmortem findings in infancyBrain","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Correlation; Sample (material); Human brain; Postmortem studies; Sample size determination","score_opus":0.016657812774074854,"score_gpt":0.2924128781095858,"score_spread":0.275755065335511,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096400195","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9376821,0.000018659488,0.049667038,0.0027720605,0.000004229417,0.00029863243,8.119827e-7,0.000121852245,0.00943463],"genre_scores_gemma":[0.9744404,0.0000055909395,0.024428783,0.00026248724,0.000013078091,0.000017959635,0.000024015706,0.0000061197416,0.0008015866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9997226,0.0000026608998,0.000077640136,0.00009768784,0.00004566152,0.000053735585],"domain_scores_gemma":[0.999873,0.000013500631,0.00001627969,0.00006879772,0.000014920074,0.000013547116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002499003,0.00004080503,0.0000526601,0.000048218953,0.000019385996,0.000006409294,0.000009167524,0.000018690833,0.0000079317215],"category_scores_gemma":[0.0000049056275,0.000031226835,0.000004772207,0.000113746435,0.000017744122,0.000068796406,0.000005220146,0.000060968643,0.0000018009616],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001785614,0.0001226209,0.87578535,0.000033116077,0.0000028032941,0.000024150258,0.00008875636,0.00010458065,0.028611312,0.08643386,0.00279528,0.0058196154],"study_design_scores_gemma":[0.00046899027,0.00006770353,0.98864514,0.000035186178,0.0000062496874,0.000089088346,0.000013310967,0.0035086866,0.0023444619,0.0027600147,0.0020041845,0.00005701454],"about_ca_topic_score_codex":0.000049087004,"about_ca_topic_score_gemma":0.000028193848,"teacher_disagreement_score":0.11285977,"about_ca_system_score_codex":0.000012597202,"about_ca_system_score_gemma":0.000006900118,"threshold_uncertainty_score":0.12733933},"labels":[],"label_agreement":null},{"id":"W7097165581","doi":"","title":"TITLE: ANALYSIS OF FUNCTIONAL MRI FOR PRESURGICAL MAPPING: REPRODUCIBILITY, AUTOMATED THRESHOLDS,","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Permission; Acknowledgement; Honor; Signature (topology); Feature (linguistics)","score_opus":0.11149755240205592,"score_gpt":0.3930460201479506,"score_spread":0.2815484677458947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097165581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17545351,0.00005033415,0.56674373,0.012134223,0.00030775557,0.0019129433,0.00012517691,0.0031216755,0.24015066],"genre_scores_gemma":[0.9432373,0.0000042309593,0.050652932,0.00014230011,0.00005956207,0.0000424838,0.00008716759,0.0000075571065,0.0057664826],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995216,0.0000022683016,0.00011580128,0.000245422,0.00006363231,0.000051277606],"domain_scores_gemma":[0.9992868,0.000035420293,0.00002956781,0.0005434279,0.000078507976,0.000026299056],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001468699,0.000035116253,0.00011021832,0.00007248355,0.000016894477,0.0000020729026,0.000032156608,0.000028882934,0.0010648967],"category_scores_gemma":[0.00008845594,0.000027320526,0.00008111437,0.00025397923,0.000036239846,0.000011557195,0.00001685213,0.00006187424,0.000007659642],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012944496,0.00083873,0.08237881,0.000110348905,0.00067535485,0.0000026940088,0.000033846125,0.00015951435,0.19417217,0.10017608,0.6139912,0.007331818],"study_design_scores_gemma":[0.00044492385,0.000064032836,0.21148849,0.000007891981,0.00061616243,0.000018890021,0.0000063859475,0.17977017,0.015011473,0.004267774,0.58817416,0.00012966283],"about_ca_topic_score_codex":0.000002426817,"about_ca_topic_score_gemma":9.901148e-7,"teacher_disagreement_score":0.76778376,"about_ca_system_score_codex":0.0000035774308,"about_ca_system_score_gemma":0.000016117956,"threshold_uncertainty_score":0.99984825},"labels":[],"label_agreement":null},{"id":"W7097199262","doi":"","title":"Probabilistic Topography of Human Corpus Callosum Using Cytoarchitectural Parcellation and High Angular Resolution Diffusion","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Corpus callosum; Diffusion MRI; Probabilistic logic; Pattern recognition (psychology); Tractography; Somatosensory system; Voxel; Landmark; Fiber tract","score_opus":0.10750804987505869,"score_gpt":0.35558865931998,"score_spread":0.24808060944492133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097199262","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96510327,0.0000708227,0.03370005,0.0002608141,0.0000138890055,0.00037775564,0.0000028478617,0.0001029892,0.00036757175],"genre_scores_gemma":[0.967884,0.000008781373,0.031932574,0.000044520573,0.00003057169,0.0000075011544,0.000022533131,0.000010007832,0.00005950746],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99943215,0.000018697092,0.00016361928,0.00016468563,0.00012624191,0.00009463618],"domain_scores_gemma":[0.9995632,0.000015458902,0.000067659756,0.00018895189,0.0000857683,0.00007896285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006977992,0.00007410796,0.00012969521,0.00008723983,0.00005611052,0.000004928287,0.00002831727,0.000033021613,0.00000454743],"category_scores_gemma":[0.000027207998,0.00006049723,0.00002778869,0.00014737363,0.00012579531,0.00002994773,0.00003912224,0.000071403796,2.3425306e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013836531,0.00022394472,0.04917327,0.00014099464,0.0000128072215,0.000007283033,0.0002753388,0.00033978562,0.9175926,0.023761643,0.00015497356,0.008179014],"study_design_scores_gemma":[0.007359707,0.0037189645,0.34035584,0.00067747675,0.00064066594,0.00059633644,0.00036196187,0.21103388,0.14229149,0.28673738,0.0051342174,0.0010920783],"about_ca_topic_score_codex":0.0002670579,"about_ca_topic_score_gemma":0.000007295753,"teacher_disagreement_score":0.7753011,"about_ca_system_score_codex":0.000024671592,"about_ca_system_score_gemma":0.000013943737,"threshold_uncertainty_score":0.24670054},"labels":[],"label_agreement":null},{"id":"W7097756428","doi":"","title":"2Sherbrooke, QC,CA,Université de Sherbrooke,Sherbrooke Connectivity Imaging Lab,","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Feature (linguistics); Set (abstract data type); Noise (video); Identification (biology)","score_opus":0.026535601364685836,"score_gpt":0.28613577529779854,"score_spread":0.2596001739331127,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097756428","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4982305,0.00036725833,0.11736339,0.012617839,0.00007458864,0.0015713783,0.000009204585,0.0018497912,0.36791608],"genre_scores_gemma":[0.9068818,0.00015060163,0.053123634,0.004781375,0.0001093533,0.00014232768,0.000019868718,0.00006598854,0.034725033],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.99864554,0.000027387274,0.00021008762,0.00046146373,0.00018908149,0.00046641447],"domain_scores_gemma":[0.99880123,0.000092580725,0.00006270473,0.0006313005,0.0001230843,0.0002890737],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00010260716,0.00022964654,0.00027056673,0.00010340291,0.00022745991,0.000037566886,0.00018330607,0.00006825875,0.002260705],"category_scores_gemma":[0.000050749448,0.00021350522,0.00012827489,0.00022779034,0.00012269698,0.00025169388,0.00020101832,0.0002800453,0.0006235371],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008988928,0.00050030736,0.19609578,0.00020728073,0.000067964436,0.000118709104,0.00023016693,0.000046818015,0.4771802,0.01928413,0.27271855,0.03346021],"study_design_scores_gemma":[0.0028223675,0.00022114508,0.22234678,0.00025222288,0.00018668518,0.00083144865,0.00026914422,0.018948397,0.17060207,0.017213617,0.565354,0.0009521515],"about_ca_topic_score_codex":0.00056715874,"about_ca_topic_score_gemma":0.000049559505,"teacher_disagreement_score":0.40865132,"about_ca_system_score_codex":0.00046836317,"about_ca_system_score_gemma":0.000051183408,"threshold_uncertainty_score":0.9986514},"labels":[],"label_agreement":null},{"id":"W7106206700","doi":"","title":"Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography.","year":2025,"lang":"en","type":"article","venue":"PubMed","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Université du Québec à Montréal; University of Alberta; Université de Sherbrooke","funders":"","keywords":"Tractography; Grand Challenges; Relevance (law); Neuroinformatics; 2019-20 coronavirus outbreak; Translational research","score_opus":0.07447673012838404,"score_gpt":0.3108779646974531,"score_spread":0.23640123456906906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106206700","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36510846,0.09136572,0.043200273,0.4258864,0.0014074943,0.035367392,0.0006258224,0.0017201644,0.035318296],"genre_scores_gemma":[0.9829138,0.0044101984,0.0034153806,0.0015948225,0.00016489901,0.0073745255,0.000010460925,0.000020736632,0.000095170646],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991478,0.000013365968,0.00021085971,0.000263228,0.0001104383,0.00025432158],"domain_scores_gemma":[0.99917924,0.00013944884,0.000064867534,0.0004335906,0.000096184434,0.000086683445],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017593146,0.0001271363,0.0002270566,0.0001887806,0.00008717648,0.000007997395,0.00018019974,0.000063049294,0.0000026991484],"category_scores_gemma":[0.000035864174,0.000086501925,0.00021569991,0.0004285852,0.0000684198,0.00003236698,0.00002629244,0.00014811619,2.7556294e-7],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002645562,0.00023980887,0.0006867478,0.00017439623,0.00005977168,9.99304e-7,0.00017068659,8.666067e-7,0.001181685,0.017188236,0.007755798,0.97227645],"study_design_scores_gemma":[0.00069915096,0.00007742464,0.3963739,0.00003492389,0.000118708886,0.0000046577875,0.00024345149,0.000014139026,0.0057816524,0.007435713,0.58910936,0.00010694097],"about_ca_topic_score_codex":0.000002174993,"about_ca_topic_score_gemma":0.000006967652,"teacher_disagreement_score":0.9721695,"about_ca_system_score_codex":0.000008431046,"about_ca_system_score_gemma":0.000015230345,"threshold_uncertainty_score":0.3527446},"labels":[],"label_agreement":null},{"id":"W7106238655","doi":"10.48550/arxiv.2511.16471","title":"FastSurfer-CC: A robust, accurate, and comprehensive framework for corpus callosum morphometry","year":2025,"lang":"en","type":"preprint","venue":"DZNE Pub","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; McDonnell Center for Systems Neuroscience; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Society; University of Southern California; Biogen; Deutsches Zentrum für Neurodegenerative Erkrankungen; GlaxoSmithKline; Eli Lilly and Company; Bristol-Myers Squibb; BioClinica; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Alzheimer's Association","keywords":"Corpus callosum; Commissure; Focus (optics); Remyelination","score_opus":0.15559769935946707,"score_gpt":0.40757803451743435,"score_spread":0.25198033515796725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106238655","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021556,0.0020556636,0.9616269,0.008199418,0.00041612773,0.0033080615,0.00094882277,0.00066478096,0.0012242505],"genre_scores_gemma":[0.11923867,0.0022291827,0.86514014,0.005507334,0.000500362,0.0024189989,0.0008605249,0.000117857424,0.003986935],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983598,0.000022041084,0.0003602818,0.000766603,0.00016179898,0.00032947463],"domain_scores_gemma":[0.9979867,0.00044870374,0.00021142846,0.00087982893,0.0003117964,0.00016158244],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000070374605,0.00035607317,0.00065826153,0.00021664711,0.000119725,0.00005651394,0.00023060816,0.000379418,0.000012101158],"category_scores_gemma":[0.00025536612,0.0003472376,0.00017641397,0.00025839292,0.0001338823,0.000036802743,0.000664076,0.0010496054,0.0000035296537],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0026440495,0.00819745,0.029218098,0.025625791,0.0026261709,0.00043759934,0.0010753198,0.0034915844,0.008422521,0.37633577,0.31339255,0.22853312],"study_design_scores_gemma":[0.006544638,0.00055652903,0.019177908,0.0050209486,0.001389426,0.00027753343,0.00021842896,0.017275995,0.006167433,0.31661788,0.62475497,0.0019983172],"about_ca_topic_score_codex":0.000030819774,"about_ca_topic_score_gemma":0.0000014813724,"teacher_disagreement_score":0.31136242,"about_ca_system_score_codex":0.000079659025,"about_ca_system_score_gemma":0.00014197611,"threshold_uncertainty_score":0.99989796},"labels":[],"label_agreement":null},{"id":"W7110949963","doi":"10.1162/imag.a.1080","title":"Revisiting the interpretation of axon diameter mapping using higher-order signal representations","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Engineering and Physical Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Wolfson Foundation; Center for Advanced Imaging Innovation and Research; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Wellcome Trust","keywords":"Axon; Scaling; Estimator; Robustness (evolution); SIGNAL (programming language); Perpendicular; Monte Carlo method","score_opus":0.07640376401577224,"score_gpt":0.4004362656322108,"score_spread":0.32403250161643854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7110949963","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041738108,0.00009653752,0.9445951,0.01079632,0.00014749228,0.0003501424,0.000003245646,0.00012386178,0.0021491982],"genre_scores_gemma":[0.9682227,0.000012750973,0.028848393,0.00260817,0.000038622573,0.0000203114,0.0000015245097,0.00000891244,0.00023863264],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991008,0.00004106338,0.00025172543,0.00029551116,0.00015984877,0.00015105715],"domain_scores_gemma":[0.999198,0.00016135698,0.00012918744,0.00035746727,0.00012794023,0.000026038453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016389102,0.000082811086,0.00011390891,0.00013740588,0.00020945152,0.000040564264,0.00017621617,0.000010216884,0.00000537867],"category_scores_gemma":[0.00026676423,0.00006537273,0.00005154529,0.0009200196,0.00028492147,0.0001699184,0.00010373147,0.00015563768,8.040239e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010627054,0.000028946757,0.04817071,0.000061611754,0.0000027105755,0.000006581963,0.00013891817,0.0010317812,0.91198575,0.002691911,0.00017157341,0.035698853],"study_design_scores_gemma":[0.00039711245,0.000023629029,0.22425774,0.0008948637,0.000101955025,0.000094865776,0.00019892002,0.71985704,0.041598476,0.0043987012,0.007970605,0.00020611509],"about_ca_topic_score_codex":0.00001617519,"about_ca_topic_score_gemma":6.7816465e-8,"teacher_disagreement_score":0.9264846,"about_ca_system_score_codex":0.000026493097,"about_ca_system_score_gemma":0.00005508621,"threshold_uncertainty_score":0.26658228},"labels":[],"label_agreement":null},{"id":"W7112282630","doi":"","title":"Sleep Health and White Matter Integrity in the UK Biobank","year":2025,"lang":"en","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"LMC Diabetes & Endocrinology (Canada)","funders":"","keywords":"White matter; Insomnia; Fractional anisotropy; Sleep (system call); Biobank; Actigraphy","score_opus":0.17357306589573054,"score_gpt":0.4050871247249946,"score_spread":0.23151405882926404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7112282630","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.794156,0.00027069505,0.005754872,0.19757988,0.000012481536,0.0008841446,0.000004461959,0.000032334065,0.0013050868],"genre_scores_gemma":[0.99611706,0.00045099162,0.0016403096,0.0016268988,0.000010152696,0.0000041053368,0.0000045779325,0.0000043704836,0.00014156644],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99916345,0.0001732865,0.00009078793,0.00018442834,0.00019225237,0.00019576863],"domain_scores_gemma":[0.99924034,0.0001755978,0.00002861857,0.00043575026,0.00007094797,0.000048748996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067225413,0.000059847796,0.00012934447,0.00016569135,0.00019077345,0.00001016501,0.00028150508,0.000030240775,0.000032522745],"category_scores_gemma":[0.000032679905,0.00004091862,0.000033565608,0.0004225838,0.0003946016,0.000050376864,0.00020636043,0.0005549555,0.000014882576],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003649345,0.00036056378,0.836778,0.0005184365,0.000036013284,0.00004204841,0.048214447,0.0000031891286,0.0004523267,0.007854659,0.08816978,0.017205609],"study_design_scores_gemma":[0.0008481569,0.00020194947,0.8799487,0.00035117194,0.000015703934,0.000018723325,0.03784155,0.00027381667,0.00020447123,0.00688721,0.073323004,0.00008556944],"about_ca_topic_score_codex":0.000032875167,"about_ca_topic_score_gemma":0.0000066547723,"teacher_disagreement_score":0.20196098,"about_ca_system_score_codex":0.000068870875,"about_ca_system_score_gemma":0.000061521314,"threshold_uncertainty_score":0.24110365},"labels":[],"label_agreement":null},{"id":"W7113260559","doi":"","title":"Étude du rôle pronostique des déconnexions cérébrales chez les patients présentant une occlusion de l'artère basilaire","year":2025,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Modified Rankin Scale; Stroke (engine); Logistic regression; Magnetic resonance imaging; Occlusion; Infarction; Cerebral infarction","score_opus":0.02042952591352124,"score_gpt":0.28468242435375035,"score_spread":0.2642528984402291,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7113260559","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.80703473,0.0021510394,0.14609529,0.021118328,0.0003712096,0.0025961895,0.00030326005,0.0007731275,0.019556845],"genre_scores_gemma":[0.9049258,0.00442866,0.06694595,0.00025862208,0.00008772658,0.00044404232,0.004955843,0.00013446042,0.017818877],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9940559,0.0025384445,0.0009789538,0.0011521234,0.00047965275,0.0007948918],"domain_scores_gemma":[0.9924018,0.0016440823,0.00072532124,0.001761039,0.003054622,0.0004131671],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0019121208,0.0006920368,0.00066841766,0.0003476366,0.0017524064,0.00018828394,0.0010331422,0.0005086694,0.00018544208],"category_scores_gemma":[0.003010233,0.0007486648,0.0003627891,0.0011231003,0.0006163674,0.00027249043,0.0005044764,0.0009928648,0.000042293595],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022319767,0.00698306,0.42637664,0.0029020093,0.00027878874,0.00005867975,0.040825106,0.00011844327,0.055732526,0.27695486,0.0047046775,0.184842],"study_design_scores_gemma":[0.0028657753,0.0000128036,0.44889516,0.027411811,0.00080306054,0.00007146412,0.003333152,0.017318426,0.45537877,0.01271808,0.029566884,0.0016246273],"about_ca_topic_score_codex":0.0038831676,"about_ca_topic_score_gemma":0.01042421,"teacher_disagreement_score":0.39964625,"about_ca_system_score_codex":0.00058797194,"about_ca_system_score_gemma":0.0008029279,"threshold_uncertainty_score":0.9995472},"labels":[],"label_agreement":null},{"id":"W7114381595","doi":"","title":"Sex-specific white matter alterations in children exposed to high pregestational BMI","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Splenium; Corpus callosum; Fractional anisotropy; White matter; Overweight; Offspring; Pregnancy; Wechsler Adult Intelligence Scale","score_opus":0.05236405623082192,"score_gpt":0.32837319482187005,"score_spread":0.27600913859104814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7114381595","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026667412,0.0015972721,0.008746538,0.06088917,0.00030801637,0.013591609,0.8631637,0.00085489784,0.024181398],"genre_scores_gemma":[0.73922265,0.000043078926,0.01180887,0.010445846,0.00042254638,0.004726137,0.21228251,0.00009646097,0.020951912],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.9980304,0.00005146595,0.00054261065,0.00074029004,0.00023004346,0.00040517998],"domain_scores_gemma":[0.99866575,0.00013847864,0.00010213114,0.00076605333,0.00017227369,0.00015528765],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000041370204,0.00029713297,0.0003132559,0.0004099646,0.00018730784,0.00010769229,0.00031576198,0.000117502095,0.1293523],"category_scores_gemma":[0.00013313239,0.00033557377,0.0000835068,0.0009392916,0.000015564387,0.00017214403,0.00021389702,0.00043069216,0.0036539566],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003325762,0.00027170824,0.024407243,0.00010777207,0.000023725774,0.0000090853255,0.00019237524,0.00045801725,0.00046906478,0.000827784,0.9696561,0.003543845],"study_design_scores_gemma":[0.0011197992,0.00008863826,0.78386223,0.0051973867,0.000027309261,0.000021884642,0.000039284612,0.00038459926,0.0050027333,0.0011363466,0.2026845,0.00043527439],"about_ca_topic_score_codex":0.0000054276497,"about_ca_topic_score_gemma":0.0000046011637,"teacher_disagreement_score":0.76697165,"about_ca_system_score_codex":0.00017213242,"about_ca_system_score_gemma":0.00016681787,"threshold_uncertainty_score":0.99990964},"labels":[],"label_agreement":null},{"id":"W7115036435","doi":"","title":"Modelling the microstructural effects of white matter hyperintensities","year":2025,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Biomedical Research Council; Medical Research Council; Wellcome Trust","keywords":"Hyperintensity; White matter; White noise; Welding","score_opus":0.025649400140560167,"score_gpt":0.2807553727119799,"score_spread":0.25510597257141976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115036435","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9748867,0.00034917565,0.000022399608,0.00016008114,0.000489551,0.0012733133,0.00032179945,0.00023594334,0.022261031],"genre_scores_gemma":[0.97050244,0.0002591622,0.0057877987,0.0009871734,0.000034568846,0.00021444964,0.00045157477,0.000120694494,0.02164213],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99801046,0.00007460301,0.0005863423,0.0006236495,0.00033608289,0.00036887627],"domain_scores_gemma":[0.9979673,0.00021465617,0.00035887925,0.00092636433,0.0004361909,0.00009659887],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00012918955,0.0004844517,0.00067514606,0.00022356518,0.0007274689,0.000022077438,0.00037044188,0.00030352466,0.000048282614],"category_scores_gemma":[0.00011205644,0.00038319503,0.00034929792,0.0003374823,0.00008751971,0.00014302378,0.00014480727,0.0012171242,0.00002591049],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016334178,0.0005052478,0.00072805374,0.0144455675,0.0009963955,0.00020670758,0.00015596437,0.0027303982,0.79872745,0.1107016,0.000313767,0.06885544],"study_design_scores_gemma":[0.0013124559,0.00022266817,0.0034528656,0.004192068,0.0013538158,0.00021709199,0.00037855186,0.0012418113,0.8916119,0.04125007,0.053654645,0.0011121046],"about_ca_topic_score_codex":0.00011203621,"about_ca_topic_score_gemma":0.000014132686,"teacher_disagreement_score":0.092884414,"about_ca_system_score_codex":0.000151902,"about_ca_system_score_gemma":0.00003747,"threshold_uncertainty_score":0.999862},"labels":[],"label_agreement":null},{"id":"W7115824167","doi":"","title":"Keeping It Consistent: Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Higher Order Diffusion Tensor MRI Sequences","year":2025,"lang":"en","type":"dissertation","venue":"MacSphere (McMaster University)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Kurtosis; Diffusion MRI; Repeatability; Fractional anisotropy; Imaging phantom; Anisotropy; Intraclass correlation; Tensor (intrinsic definition)","score_opus":0.10161508667914616,"score_gpt":0.32881324207797247,"score_spread":0.22719815539882632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7115824167","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037312213,0.000779731,0.36812988,0.00384903,0.0009783788,0.0073846257,0.0004219074,0.0008046386,0.5803396],"genre_scores_gemma":[0.15521032,0.00034416074,0.16949072,0.00072637317,0.00016656383,0.00006646052,0.0009196184,0.00012753604,0.67294824],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982901,0.000038115762,0.00038720065,0.00067138014,0.00035822543,0.0002549552],"domain_scores_gemma":[0.99806154,0.00008578359,0.00041079664,0.00048120233,0.00087748445,0.00008317508],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00011568395,0.00030592785,0.00058166607,0.00019365651,0.00020038782,0.000029955085,0.0002288694,0.00017564597,0.001483287],"category_scores_gemma":[0.00007957391,0.00031436142,0.00022349662,0.00053173455,0.00008563986,0.00014343721,0.00007378154,0.00025923838,8.828162e-7],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037680045,0.0053986874,0.03453828,0.02414003,0.0017759028,0.00017173716,0.0015651908,0.00029766923,0.3423722,0.02328181,0.003577351,0.55911314],"study_design_scores_gemma":[0.007406947,0.00044304633,0.02074172,0.007923777,0.002873717,0.000016067184,0.004986447,0.002072127,0.01797704,0.00066988834,0.9337814,0.0011078212],"about_ca_topic_score_codex":0.00011237671,"about_ca_topic_score_gemma":0.00013917666,"teacher_disagreement_score":0.93020403,"about_ca_system_score_codex":0.00033468343,"about_ca_system_score_gemma":0.00034923072,"threshold_uncertainty_score":0.99993086},"labels":[],"label_agreement":null},{"id":"W7116829184","doi":"10.1002/alz70862_110231","title":"Sex differences in white matter hyperintensity pathophysiology","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Pathophysiology; Hyperintensity; White matter; Animal studies","score_opus":0.047670494239238415,"score_gpt":0.32121785807004744,"score_spread":0.273547363830809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116829184","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96537757,0.0051923804,0.005836576,0.012544413,0.00015661433,0.0006677547,0.000008865776,0.00021945623,0.009996388],"genre_scores_gemma":[0.9892618,0.000060755032,0.0059861317,0.0044243443,0.000016156413,0.00006861518,0.000011930321,0.000007911332,0.00016235531],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937344,0.000018370632,0.00015946152,0.00024369887,0.000048144753,0.00015686883],"domain_scores_gemma":[0.9996108,0.000017594472,0.000029750932,0.00028460872,0.00002901805,0.000028227318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035560508,0.00009396905,0.0001865803,0.00007764642,0.00003888636,0.0000064522023,0.00008242583,0.00003667385,0.00014457534],"category_scores_gemma":[0.000004741024,0.00008280209,0.000039805203,0.0001466913,0.000059244052,0.000029936005,0.00008519583,0.0001293549,0.00006173623],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020771513,0.00010760224,0.9717104,0.000005339627,0.00034287613,0.000010444514,0.000028167988,4.417473e-7,0.011901418,0.00047297802,0.0069381795,0.008461403],"study_design_scores_gemma":[0.000266291,0.00003238976,0.9806398,0.000024248857,0.0010297634,0.0000052083633,0.000022881071,0.00010615285,0.008584476,0.0033334338,0.0058626416,0.00009268936],"about_ca_topic_score_codex":0.000020030939,"about_ca_topic_score_gemma":0.000003810558,"teacher_disagreement_score":0.023884248,"about_ca_system_score_codex":0.0000029697903,"about_ca_system_score_gemma":0.000015262698,"threshold_uncertainty_score":0.33765712},"labels":[],"label_agreement":null},{"id":"W7116853221","doi":"10.1371/journal.pdig.0001155","title":"Autism spectrum disorder detection using diffusion tensor imaging and machine learning","year":2025,"lang":"en","type":"article","venue":"PLOS Digital Health","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Agence Universitaire de la Francophonie; University of Edinburgh; Mrs Gladys Row Fogo Charitable Trust","keywords":"Diffusion MRI; Fractional anisotropy; Autism spectrum disorder; Support vector machine; Neuroimaging; Pattern recognition (psychology); White matter; Generalization; Random forest; Anisotropy","score_opus":0.03973981842652238,"score_gpt":0.3362264295065378,"score_spread":0.2964866110800154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116853221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.84119177,0.0011090786,0.13867912,0.016470123,0.000040081777,0.0006418695,0.000014676584,0.0005840201,0.001269256],"genre_scores_gemma":[0.99674094,0.00022892117,0.0018289178,0.00068764354,0.000020989319,0.000011799737,0.000017591963,0.000021047683,0.00044213302],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992543,0.0000119971655,0.00018092168,0.00025390796,0.000088956775,0.00020994474],"domain_scores_gemma":[0.9996525,0.000034362864,0.00006676452,0.00014562505,0.000012611789,0.00008815581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000038479244,0.00010747205,0.00017111804,0.00012464478,0.00026772227,0.0000432073,0.000030188114,0.000020217327,0.0000034281022],"category_scores_gemma":[0.000042039188,0.00009896448,0.000028973005,0.00021042828,0.000045639154,0.00013740112,0.00006991378,0.00023406443,0.0000020416644],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000088804416,0.00048419755,0.63986033,0.00052369345,0.000020931491,0.000012862913,0.00011314857,0.000027695412,0.0058313645,0.0026551546,0.000035238678,0.35034657],"study_design_scores_gemma":[0.0031393357,0.000705654,0.37915036,0.001828821,0.00012465821,0.00052725204,0.00029066674,0.5300413,0.0038790565,0.030659648,0.048981942,0.00067134015],"about_ca_topic_score_codex":0.00009699821,"about_ca_topic_score_gemma":0.000007029179,"teacher_disagreement_score":0.53001356,"about_ca_system_score_codex":0.000098867094,"about_ca_system_score_gemma":0.000043373944,"threshold_uncertainty_score":0.40356544},"labels":[],"label_agreement":null},{"id":"W7116873550","doi":"10.1002/alz70862_109829","title":"Advanced MRI biomarkers for efficient clinical trial designs in Progressive Supranuclear Palsy (PSP)","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Clinical trial; Progressive supranuclear palsy; Magnetic resonance imaging; Sample size determination; Biomarker","score_opus":0.13863381392749036,"score_gpt":0.4472783274104305,"score_spread":0.30864451348294014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116873550","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4859928,0.07868582,0.35146856,0.030565513,0.0028030965,0.04326712,0.00014745898,0.001859379,0.005210266],"genre_scores_gemma":[0.87177825,0.00015128175,0.12557793,0.0010086717,0.00008324054,0.0012813228,0.00005669846,0.00003827527,0.000024330808],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983047,0.00006462321,0.00063999154,0.0005246899,0.00013673068,0.00032921214],"domain_scores_gemma":[0.9989813,0.00023646757,0.00015191697,0.00046183393,0.00009354311,0.00007494355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042528549,0.00017475878,0.00034491502,0.00014661172,0.00010268352,0.000018455345,0.00016970473,0.00009195148,0.00003653619],"category_scores_gemma":[0.00013460965,0.00016208613,0.00019381335,0.00035525826,0.00013737546,0.0000433619,0.000079883335,0.00018459625,0.000013488135],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.06176197,0.0055924696,0.007980271,0.00009168771,0.010411254,0.00007534283,0.00013170255,0.0001463369,0.009837167,0.013542143,0.04463967,0.84578997],"study_design_scores_gemma":[0.21471043,0.0052698874,0.017210346,0.00084757217,0.032206442,0.000024509194,0.00023011795,0.012388501,0.07680622,0.0064618257,0.6324489,0.0013952133],"about_ca_topic_score_codex":0.0000040123377,"about_ca_topic_score_gemma":0.0000020560205,"teacher_disagreement_score":0.84439474,"about_ca_system_score_codex":0.000011202814,"about_ca_system_score_gemma":0.0001044806,"threshold_uncertainty_score":0.66096807},"labels":[],"label_agreement":null},{"id":"W7116965308","doi":"10.64898/2025.12.20.695692","title":"Anatomical White Matter Tracts Span the Cortical Hierarchy to Support Cognitive Diversity","year":2025,"lang":"en","type":"article","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Pennsylvania","keywords":"Hierarchy; Cognition; White matter; Association (psychology); Projection (relational algebra); Bridge (graph theory)","score_opus":0.028940693073203665,"score_gpt":0.29302832824420044,"score_spread":0.26408763517099676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116965308","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96122444,0.000018931774,0.026046077,0.011146205,0.00009270338,0.00088017015,0.000061353094,0.00032115084,0.00020897292],"genre_scores_gemma":[0.98474485,0.000011117834,0.0042408127,0.010762454,0.000067592635,0.000086407104,2.0109375e-7,0.000027121558,0.000059448645],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99877095,0.000044076096,0.00021192363,0.000441757,0.00019631675,0.0003349817],"domain_scores_gemma":[0.99887323,0.00010518938,0.000050300434,0.0005235032,0.00021666574,0.00023109437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017948265,0.00017950928,0.0002289515,0.00013140308,0.00034323332,0.0000388234,0.00021824373,0.00008093133,0.000113151684],"category_scores_gemma":[0.00015501796,0.00014869301,0.000075079945,0.0006338463,0.00016768361,0.00007976988,0.00031301248,0.0004110488,0.00017427531],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002230979,0.0003917617,0.84729487,0.00006703887,0.00008456176,0.00011587071,0.000024610039,0.0000011308621,0.13216923,0.004117791,0.015486709,0.0000232958],"study_design_scores_gemma":[0.00043906103,0.000074415184,0.9276552,0.00008252983,0.0001293446,9.204642e-8,0.0000054398806,0.000048637303,0.058836047,0.0000074857358,0.012562838,0.00015890953],"about_ca_topic_score_codex":0.000007915868,"about_ca_topic_score_gemma":6.8202974e-7,"teacher_disagreement_score":0.0803603,"about_ca_system_score_codex":0.000093386974,"about_ca_system_score_gemma":0.00013278061,"threshold_uncertainty_score":0.6063525},"labels":[],"label_agreement":null},{"id":"W7116988651","doi":"10.1002/alz70861_108716","title":"Valiltramiprosate Effects on Microstructural Integrity of Grey and White Matter in APOE4/4 Homozygotes with Early AD and their Correlations to Clinical Outcomes: MRI Mean Diffusivity Results from the 78‐Week APOLLOE4 Phase 3 Trial","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Public Health","funders":"","keywords":"White matter; Thermal diffusivity; Hippocampal formation; Grey matter; Phase (matter); Diffusion MRI; Neurodegeneration; Neuroimaging","score_opus":0.05821910477358937,"score_gpt":0.37004393269767943,"score_spread":0.31182482792409005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7116988651","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9842688,0.00052269705,0.00175505,0.011297087,0.00011679891,0.0017316403,0.00021937289,0.00004398072,0.000044571803],"genre_scores_gemma":[0.9930914,0.000029528856,0.004575345,0.0020949051,0.000028666307,0.0000813643,0.000063795516,0.000016556387,0.000018436473],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99863666,0.00013187823,0.00048731433,0.00045630225,0.00010851126,0.00017934994],"domain_scores_gemma":[0.998098,0.0011074864,0.00015139143,0.0005153358,0.000055960703,0.00007179965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002637759,0.00020906793,0.0004083011,0.000078073324,0.00010412708,0.00003639572,0.00012474396,0.000072706054,0.000004752938],"category_scores_gemma":[0.00013808937,0.00012447349,0.00007267323,0.00021442163,0.00020562981,0.00007188042,0.0001068588,0.0004234292,0.0000027230453],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.017953161,0.0009659008,0.9202449,0.00001812607,0.0023651794,0.0000101522455,0.0017679334,0.000002217786,0.0039124493,0.00014902686,0.0026896305,0.049921334],"study_design_scores_gemma":[0.02522717,0.00094923406,0.9641656,0.00018346842,0.0019673326,0.0000034669188,0.00006573263,0.000067452216,0.005589505,0.00082289457,0.0008031737,0.00015493599],"about_ca_topic_score_codex":0.00027702065,"about_ca_topic_score_gemma":0.00014239983,"teacher_disagreement_score":0.0497664,"about_ca_system_score_codex":0.000005014271,"about_ca_system_score_gemma":0.000029347664,"threshold_uncertainty_score":0.50758815},"labels":[],"label_agreement":null},{"id":"W7117062403","doi":"10.1002/alz70862_110131","title":"Microstructural differences in white matter tracts in Alzheimer’s disease, cerebrovascular disease, and Parkinson's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; Disease; Diffusion MRI; Magnetic resonance imaging; White (mutation)","score_opus":0.03351699596125572,"score_gpt":0.3047288863599643,"score_spread":0.2712118903987086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117062403","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8883953,0.09772153,0.00031081127,0.011417282,0.00011543072,0.0015331728,0.00009352741,0.00014042301,0.00027253534],"genre_scores_gemma":[0.995109,0.00054098637,0.0018185249,0.0020420991,0.000031925254,0.00027729574,0.00011714972,0.000029847799,0.000033143617],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983556,0.000054511318,0.00036768144,0.000646082,0.00019080585,0.00038527226],"domain_scores_gemma":[0.99894184,0.000037243914,0.0000733998,0.0005539789,0.0000338523,0.00035969898],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006995264,0.00028161381,0.00031586655,0.00024807785,0.00008688254,0.000055519587,0.00017393306,0.000042187276,0.000116197334],"category_scores_gemma":[0.000018354649,0.00026080295,0.000105406376,0.00035369868,0.00016039409,0.00018165591,0.00014671218,0.00022880636,0.000015346906],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001640691,0.00016142671,0.9925158,0.000025235822,0.00051204686,0.00005612928,0.000025533735,0.0000034369843,0.00013168085,0.00029404153,0.0016644375,0.0044461377],"study_design_scores_gemma":[0.000841104,0.000011832083,0.98099357,0.00017313917,0.005978265,0.000002146266,0.000012984238,0.00023517231,0.00022206722,0.0020935764,0.009197397,0.00023874921],"about_ca_topic_score_codex":0.000037582122,"about_ca_topic_score_gemma":0.000021757276,"teacher_disagreement_score":0.10671374,"about_ca_system_score_codex":0.000010165499,"about_ca_system_score_gemma":0.00009448799,"threshold_uncertainty_score":0.99998444},"labels":[],"label_agreement":null},{"id":"W7117234009","doi":"10.1002/alz70856_100338","title":"Sex differences in white matter hyperintensity pathophysiology","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Douglas Mental Health University Institute","funders":"","keywords":"Pathophysiology; Hyperintensity; White matter; Animal studies","score_opus":0.047670494239238415,"score_gpt":0.32121785807004744,"score_spread":0.273547363830809,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117234009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96537757,0.0051923804,0.005836576,0.012544413,0.00015661433,0.0006677547,0.000008865776,0.00021945623,0.009996388],"genre_scores_gemma":[0.9892618,0.000060755032,0.0059861317,0.0044243443,0.000016156413,0.00006861518,0.000011930321,0.000007911332,0.00016235531],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99937344,0.000018370632,0.00015946152,0.00024369887,0.000048144753,0.00015686883],"domain_scores_gemma":[0.9996108,0.000017594472,0.000029750932,0.00028460872,0.00002901805,0.000028227318],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000035560508,0.00009396905,0.0001865803,0.00007764642,0.00003888636,0.0000064522023,0.00008242583,0.00003667385,0.00014457534],"category_scores_gemma":[0.000004741024,0.00008280209,0.000039805203,0.0001466913,0.000059244052,0.000029936005,0.00008519583,0.0001293549,0.00006173623],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020771513,0.00010760224,0.9717104,0.000005339627,0.00034287613,0.000010444514,0.000028167988,4.417473e-7,0.011901418,0.00047297802,0.0069381795,0.008461403],"study_design_scores_gemma":[0.000266291,0.00003238976,0.9806398,0.000024248857,0.0010297634,0.0000052083633,0.000022881071,0.00010615285,0.008584476,0.0033334338,0.0058626416,0.00009268936],"about_ca_topic_score_codex":0.000020030939,"about_ca_topic_score_gemma":0.000003810558,"teacher_disagreement_score":0.023884248,"about_ca_system_score_codex":0.0000029697903,"about_ca_system_score_gemma":0.000015262698,"threshold_uncertainty_score":0.33765712},"labels":[],"label_agreement":null},{"id":"W7117259059","doi":"10.1002/alz70856_098641","title":"Genetic architecture of the limbic white matter microstructure in aging and Alzheimer's Disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Disease; Inflammation; White matter; Genetic architecture; Vascular disease; Senescence; Cellular architecture","score_opus":0.018011445062366592,"score_gpt":0.2950078279124745,"score_spread":0.2769963828501079,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117259059","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81285876,0.14990535,0.0030762828,0.030744812,0.00018365245,0.001961419,0.000054594922,0.00011693348,0.0010982138],"genre_scores_gemma":[0.98959994,0.000072958,0.007821815,0.0023977368,0.000018176937,0.000042432068,0.0000065203108,0.000016557293,0.000023885323],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9992545,0.000025745201,0.00021041972,0.00025787842,0.00008797315,0.00016348514],"domain_scores_gemma":[0.99938637,0.000017976863,0.00006519595,0.00045260752,0.000025543024,0.000052300307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000033554745,0.0001288844,0.00014998109,0.00008980799,0.00006258875,0.00001181612,0.00013629135,0.000032499072,0.000043778407],"category_scores_gemma":[0.000005170782,0.000096479605,0.000058896017,0.00024610528,0.00012726277,0.000023857452,0.00015741348,0.00018640404,0.0000024027158],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034507426,0.000058700003,0.9708006,0.000025289934,0.0006606017,0.0000070614437,0.00010556503,0.00004136133,0.0081398655,0.0001994128,0.0022435545,0.017683495],"study_design_scores_gemma":[0.00033780374,0.000010087474,0.97759074,0.00011098059,0.0045561134,0.000012250522,0.000011064995,0.00005792957,0.008300854,0.0024231086,0.0064990753,0.000090002286],"about_ca_topic_score_codex":0.00001591695,"about_ca_topic_score_gemma":0.000008110764,"teacher_disagreement_score":0.17674118,"about_ca_system_score_codex":0.0000023660584,"about_ca_system_score_gemma":0.000036280297,"threshold_uncertainty_score":0.3934324},"labels":[],"label_agreement":null},{"id":"W7117293742","doi":"10.1002/alz70856_104478","title":"Microstructural differences in white matter tracts in Alzheimer's disease, cerebrovascular disease, and Parkinson's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Toronto Western Hospital; Sunnybrook Hospital; University of Toronto; Robarts Clinical Trials; Western University","funders":"","keywords":"White matter; Disease; Diffusion MRI; Magnetic resonance imaging; White (mutation)","score_opus":0.02952110442464411,"score_gpt":0.299392257337648,"score_spread":0.2698711529130039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117293742","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88872355,0.09815656,0.00030089516,0.0107233245,0.00011365283,0.0014927507,0.00009259417,0.0001386923,0.0002580061],"genre_scores_gemma":[0.99524677,0.0005169536,0.0017894169,0.0019665328,0.000032545555,0.0002737925,0.00011576572,0.000029951036,0.000028252209],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9983563,0.0000549223,0.00036574827,0.0006466122,0.00019095435,0.00038549266],"domain_scores_gemma":[0.99893755,0.000037548238,0.00007359775,0.0005543135,0.00003400151,0.00036300145],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006991377,0.000282451,0.00031625692,0.00024772258,0.00008786936,0.000056462453,0.00017480575,0.000042371204,0.00011365744],"category_scores_gemma":[0.000017702741,0.00026170918,0.00010562898,0.00035774364,0.00016247548,0.00018358536,0.00014741179,0.00022890308,0.000014907236],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016227491,0.00016031686,0.99274576,0.000024086134,0.00055880006,0.000057417037,0.000024730305,0.000003751613,0.00011966363,0.00028509996,0.0014631746,0.004394954],"study_design_scores_gemma":[0.0008405585,0.0000119790875,0.981462,0.00017467125,0.006119718,0.000002160958,0.000013002607,0.00024286659,0.00022497645,0.0021401343,0.008528202,0.00023970802],"about_ca_topic_score_codex":0.000037615675,"about_ca_topic_score_gemma":0.000020956299,"teacher_disagreement_score":0.10652327,"about_ca_system_score_codex":0.000009988139,"about_ca_system_score_gemma":0.00009306383,"threshold_uncertainty_score":0.9999835},"labels":[],"label_agreement":null},{"id":"W7117303328","doi":"10.1212/wnl.0000000000214582","title":"Integrating Intracranial EEG and Tractography","year":2025,"lang":"en","type":"article","venue":"Neurology","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"","score_opus":0.0234489022100841,"score_gpt":0.34005754197472293,"score_spread":0.3166086397646388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117303328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9418031,0.000087233835,0.025488766,0.023314863,0.00006981018,0.00022705077,0.0000019004742,0.00023134562,0.008775954],"genre_scores_gemma":[0.98245764,0.000068238805,0.00788218,0.009483413,0.000024194394,0.000025993699,0.0000022117365,0.000006532925,0.000049571594],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995922,0.000013336644,0.00009605732,0.00017527104,0.000026211694,0.00009694581],"domain_scores_gemma":[0.99972504,0.00006842422,0.000020301628,0.00013881394,0.000019173252,0.000028254415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000029089108,0.000058563408,0.00010620245,0.00009078788,0.000046528825,0.0000050112026,0.000036261426,0.00004669236,0.0000091228085],"category_scores_gemma":[0.000041939707,0.000051622243,0.000025154366,0.00014981239,0.0000835837,0.000018496348,0.000027156864,0.00025250076,0.0000014089705],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007568711,0.00034243293,0.2280483,0.000097853925,0.00004421804,0.00021050617,0.000108488915,0.0000021536298,0.17564477,0.17035124,0.0046551647,0.41973802],"study_design_scores_gemma":[0.00142074,0.00124387,0.68150765,0.000034352237,0.000109788605,0.00074860285,0.000011085574,0.0020146847,0.0028290506,0.044776097,0.26513565,0.00016844431],"about_ca_topic_score_codex":0.000009848141,"about_ca_topic_score_gemma":0.0000035399198,"teacher_disagreement_score":0.45345935,"about_ca_system_score_codex":0.0000017656403,"about_ca_system_score_gemma":0.00001147283,"threshold_uncertainty_score":0.2105094},"labels":[],"label_agreement":null},{"id":"W7117569236","doi":"10.1055/s-0045-1814098","title":"Diffusion Tensor Imaging to Analyze White Matter Tract Abnormalities in Major Psychiatric Disorders","year":2025,"lang":"en","type":"article","venue":"Avicenna Journal of Medicine","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"White matter; Diffusion MRI; Pathophysiology; Major depressive disorder; Tractography; Diffusion imaging","score_opus":0.01335015821961329,"score_gpt":0.3359721219370203,"score_spread":0.32262196371740703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117569236","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4569458,0.0043921615,0.03779415,0.48891175,0.0004366261,0.0007033622,0.0000044531953,0.00006689117,0.010744801],"genre_scores_gemma":[0.9738618,0.0009022154,0.007919505,0.015446375,0.00025286886,0.0000129463115,0.0000028971883,0.000023252915,0.0015781202],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99849105,0.00003617756,0.00070132304,0.00018798356,0.00033921216,0.00024427313],"domain_scores_gemma":[0.9990647,0.00008637847,0.00022668889,0.00027620414,0.00019545158,0.000150621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042732988,0.00016371766,0.00043247518,0.00077576056,0.00005955385,0.0000067550686,0.00018258473,0.000035643738,0.00019276045],"category_scores_gemma":[0.00011908785,0.00011853725,0.000096525175,0.00085982,0.00008481846,0.0001175443,0.000039412804,0.00043324882,0.000009326072],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021089401,0.0002373253,0.9528857,0.000097707016,0.000016445287,0.00005815733,0.0003791803,0.000013997565,0.0013699981,0.00014518555,0.034339707,0.010245742],"study_design_scores_gemma":[0.0032699045,0.00022821163,0.94107085,0.0009710293,0.00020192224,0.00032637277,0.00069765944,0.00018813876,0.00005033326,0.0023749163,0.05049897,0.00012169508],"about_ca_topic_score_codex":0.00006654813,"about_ca_topic_score_gemma":0.00001831607,"teacher_disagreement_score":0.51691604,"about_ca_system_score_codex":0.00012017809,"about_ca_system_score_gemma":0.00008901549,"threshold_uncertainty_score":0.48338088},"labels":[],"label_agreement":null},{"id":"W7119504168","doi":"10.1002/alz70856_106960","title":"In vivo mean diffusivity is associated with neuropathology markers of Alzheimer's disease","year":2025,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Douglas Mental Health University Institute; McGill University; Douglas College","funders":"","keywords":"Neuropathology; Senile plaques; Cerebral amyloid angiopathy; Biomarker; White matter; Neurodegeneration; Neurofibrillary tangle; Disease","score_opus":0.03173778335946836,"score_gpt":0.31938305870818523,"score_spread":0.28764527534871687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7119504168","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9401467,0.02386442,0.005158386,0.017793637,0.0002581494,0.0030324014,0.00023363184,0.0005188652,0.008993804],"genre_scores_gemma":[0.9955015,0.00008151752,0.001677312,0.0025559524,0.000009656125,0.00008502448,0.00001884066,0.000024167639,0.0000460307],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9988893,0.000063109575,0.00029395966,0.00036475057,0.00015240359,0.00023644498],"domain_scores_gemma":[0.9991569,0.00005507946,0.00013471555,0.00048166967,0.00008051271,0.000091147194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011853321,0.00016315238,0.0002937219,0.00016065405,0.000050943738,0.000005985806,0.0001242495,0.000043987067,0.00012514119],"category_scores_gemma":[0.000036517293,0.00014859204,0.00007286918,0.00044380935,0.00015897237,0.00007305175,0.00009360446,0.00016773999,0.000003668056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002482797,0.005564487,0.7462944,0.00007521448,0.017284572,0.0012017807,0.00042802945,0.00003804401,0.10141435,0.0098944,0.07871192,0.03661005],"study_design_scores_gemma":[0.0044534663,0.00056286104,0.76121014,0.00040001998,0.04682613,0.000026406477,0.000050858216,0.0011378862,0.15780063,0.0034557965,0.023446608,0.0006291771],"about_ca_topic_score_codex":0.000039296345,"about_ca_topic_score_gemma":0.000016238013,"teacher_disagreement_score":0.05638628,"about_ca_system_score_codex":0.0000063607476,"about_ca_system_score_gemma":0.00007524943,"threshold_uncertainty_score":0.60594076},"labels":[],"label_agreement":null},{"id":"W7126232837","doi":"10.1162/nol.e.241","title":"The White Matter Connectome Supporting Speech and Language in the Human","year":2025,"lang":"en","type":"article","venue":"Neurobiology of Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"White matter; Connectome; Connectomics; Lateralization of brain function; Diffusion MRI; Reading (process); Functional connectivity; Human brain","score_opus":0.021267148409192912,"score_gpt":0.3656625327855713,"score_spread":0.3443953843763784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7126232837","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9838874,0.00015086908,0.000042874908,0.009973322,0.000016734282,0.00028117085,0.0000055416076,0.000032968033,0.00560912],"genre_scores_gemma":[0.9948941,0.000012356081,0.0002874575,0.0038756733,0.000016132006,0.000023015229,0.000010523728,0.0000062002237,0.00087455986],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99945784,0.000058070804,0.00017307786,0.000144707,0.00003056506,0.00013572752],"domain_scores_gemma":[0.99943525,0.00017258708,0.00006189612,0.0003075993,0.000012018328,0.000010669609],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019018115,0.000066282235,0.00012614192,0.000050960894,0.00007463733,0.00000641083,0.0001305987,0.00003303298,0.000024318593],"category_scores_gemma":[0.000050271,0.000037514135,0.000026716829,0.00012380313,0.00016960088,0.000012224628,0.00005710743,0.00019897264,0.0000026924392],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000038114624,0.0001054923,0.54855436,0.00010145384,0.000017149025,0.00012618258,0.0036269987,6.6544175e-7,0.43057403,0.0060813576,0.005968022,0.004806194],"study_design_scores_gemma":[0.00095255085,0.00016601999,0.9486544,0.00008226401,0.00005411288,0.0002639192,0.0045302683,0.000020579439,0.03772385,0.0013207407,0.0061030434,0.00012821336],"about_ca_topic_score_codex":0.000024380639,"about_ca_topic_score_gemma":0.000022520297,"teacher_disagreement_score":0.4001001,"about_ca_system_score_codex":0.0000042277716,"about_ca_system_score_gemma":0.000007701549,"threshold_uncertainty_score":0.15297821},"labels":[],"label_agreement":null},{"id":"W7132412335","doi":"","title":"Associations between white matter structural properties and global cognition as measured by MoCA scores in older adults","year":2024,"lang":"en","type":"article","venue":"Lithuanian University of Health Sciences","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Montreal Cognitive Assessment; Cognition; White matter; Tractography; Cognitive decline; Cognitive Assessment System; Diffusion MRI; Voxel","score_opus":0.05440461188945767,"score_gpt":0.31985591380875,"score_spread":0.26545130191929234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132412335","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9796809,0.0005878874,0.00054122525,0.018062415,0.000017475213,0.00034181276,0.00015553407,0.000065251734,0.00054749567],"genre_scores_gemma":[0.997592,0.000051533996,0.0019119772,0.00030269354,0.000007883147,4.7109427e-7,0.00001960095,0.0000023436567,0.00011150618],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99934673,0.000030547784,0.00011583121,0.00021121699,0.00016056692,0.00013508616],"domain_scores_gemma":[0.99977565,0.000016870883,0.00005508231,0.00005688204,0.000037695616,0.000057805853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000155199,0.000056007837,0.00013573974,0.00006809353,0.0002010965,0.000019138362,0.00006806913,0.000025710846,0.000016954193],"category_scores_gemma":[0.000010951621,0.00005078865,0.000017551107,0.0003343202,0.00026404663,0.00016951021,0.000027955424,0.00007575036,0.000004028056],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017818906,0.000021455235,0.9895,0.00017146491,0.0000061215196,0.0000028832803,0.0016026456,0.0000012110957,0.000059825306,0.00042371458,0.0018671873,0.006325672],"study_design_scores_gemma":[0.000229479,0.00011402409,0.99663955,0.00044201463,0.000013429459,0.000007189833,0.0007147079,0.0002665836,0.000053138043,0.0011516061,0.00031096637,0.00005731301],"about_ca_topic_score_codex":0.00092856714,"about_ca_topic_score_gemma":0.000103925086,"teacher_disagreement_score":0.017911088,"about_ca_system_score_codex":0.00006822769,"about_ca_system_score_gemma":0.00013209866,"threshold_uncertainty_score":0.2071101},"labels":[],"label_agreement":null},{"id":"W7132962706","doi":"","title":"Modeling Isotropic and Anisotropic Diffusion in Aging Brain White Matter with MRI","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Anisotropy; Isotropy; White matter; Diffusion MRI; Fractional anisotropy; Diffusion","score_opus":0.02629674239357279,"score_gpt":0.3581952664341419,"score_spread":0.33189852404056913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132962706","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92161596,0.001222051,0.06028712,0.012970734,0.0001063002,0.0015610338,0.000009770579,0.00017375179,0.0020532703],"genre_scores_gemma":[0.96422684,0.002175282,0.0122960685,0.0014262125,0.00011599135,0.00043747903,0.00042469098,0.00019831076,0.018699128],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99739707,0.00009449378,0.00048719536,0.0010661646,0.00040758552,0.00054751657],"domain_scores_gemma":[0.9987364,0.0000916309,0.00023917061,0.0006975429,0.00007337139,0.0001619117],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000116655654,0.0005431422,0.0006383486,0.00045030314,0.0004467254,0.00006267582,0.00021544083,0.0001544452,0.00088209007],"category_scores_gemma":[0.000025425481,0.0005365959,0.00007190613,0.0005736014,0.00007018276,0.00013430766,0.00017636099,0.0012164974,0.000017444734],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002202711,0.0016369772,0.7930212,0.005975462,0.00020603777,0.0008618307,0.08491497,0.046126373,0.047704782,0.0037749833,0.003429902,0.010144773],"study_design_scores_gemma":[0.011108417,0.0021126783,0.20422956,0.0083429385,0.0010190415,0.0005162449,0.07832656,0.6671753,0.0011995527,0.0022017101,0.019877316,0.0038907027],"about_ca_topic_score_codex":0.0005341939,"about_ca_topic_score_gemma":0.0002772126,"teacher_disagreement_score":0.62104887,"about_ca_system_score_codex":0.00021914578,"about_ca_system_score_gemma":0.00011570307,"threshold_uncertainty_score":0.99970853},"labels":[],"label_agreement":null},{"id":"W7132963379","doi":"","title":"From Structure to Function: Social and Cognitive Networks in Children Born Very Low Birth Weight","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Fractional anisotropy; White matter; Low birth weight; Diffusion MRI; Cognition; Affect (linguistics)","score_opus":0.016770201925742252,"score_gpt":0.34649680589754234,"score_spread":0.3297266039718001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132963379","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9820961,0.002551546,0.009722485,0.0014497562,0.00053138734,0.0023727291,0.0005937806,0.00018763104,0.00049458933],"genre_scores_gemma":[0.9867332,0.0005772763,0.0006112432,0.0012967022,0.0017382446,0.00034838577,0.0064081163,0.00012853235,0.002158306],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976238,0.000100638965,0.00040055037,0.0010750992,0.0003507788,0.00044911276],"domain_scores_gemma":[0.99892527,0.00014919274,0.00029343544,0.000320953,0.00011409376,0.00019702844],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000075490294,0.00052405737,0.0006415732,0.00026553107,0.0004858036,0.000051896077,0.00017627346,0.00034046866,0.0019182211],"category_scores_gemma":[0.000054014236,0.0005938212,0.00010441279,0.0008305577,0.00008884888,0.00008621187,0.00015079485,0.0016165617,0.000008750895],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.020052368,0.0021808932,0.36210024,0.0008272057,0.0025118848,0.00031545016,0.09238434,0.0015657739,0.012363987,0.0032896718,0.04090022,0.46150795],"study_design_scores_gemma":[0.0030520863,0.00057876454,0.96688396,0.0007279002,0.0010063726,0.000027506985,0.010805364,0.00095087785,0.000823647,0.0021709935,0.011819792,0.0011527577],"about_ca_topic_score_codex":0.0006115983,"about_ca_topic_score_gemma":0.00013803643,"teacher_disagreement_score":0.60478365,"about_ca_system_score_codex":0.00014074879,"about_ca_system_score_gemma":0.00014319552,"threshold_uncertainty_score":0.9996513},"labels":[],"label_agreement":null},{"id":"W7133002250","doi":"","title":"Multiparametric and Multivariate Analysis of White Matter Microstructure and its Relationship with Psychosexuality","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Hospital for Sick Children","keywords":"Fractional anisotropy; White matter; Diffusion MRI; Transgender; Multivariate statistics; Multivariate analysis; Neuroimaging; Sexual orientation","score_opus":0.07908626917155533,"score_gpt":0.43635865806241747,"score_spread":0.35727238889086216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133002250","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99268115,0.000963198,0.0035450065,0.00096318836,0.000056760156,0.0012777932,0.00016523317,0.00011726188,0.00023042764],"genre_scores_gemma":[0.9771577,0.0004716615,0.010954842,0.00011485784,0.000029621608,0.00010022958,0.0007232988,0.00009273312,0.010355048],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99771637,0.000098105076,0.0005947644,0.00097396626,0.0003050479,0.00031177633],"domain_scores_gemma":[0.99756134,0.00056522334,0.0007745502,0.0005755989,0.00033161987,0.00019164624],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022652854,0.00047029104,0.0009728033,0.0013082606,0.00032202902,0.00003437385,0.00012757693,0.00033645116,0.000085893276],"category_scores_gemma":[0.00024997815,0.00041608544,0.000110893634,0.0042202785,0.00015294318,0.00008811577,0.00008191841,0.0006902913,0.000009827318],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006006492,0.00014357138,0.9634524,0.001282623,0.0013205233,0.000011482858,0.018553259,0.00028570284,0.013124613,0.00039027238,0.00015316726,0.00068172894],"study_design_scores_gemma":[0.000859759,0.00011867926,0.984691,0.00031291842,0.005022788,0.000015109175,0.0024286667,0.0052027283,0.0006912243,0.00018723373,0.00010060679,0.0003692576],"about_ca_topic_score_codex":0.00023829877,"about_ca_topic_score_gemma":0.00006704357,"teacher_disagreement_score":0.021238621,"about_ca_system_score_codex":0.000036794674,"about_ca_system_score_gemma":0.000048930855,"threshold_uncertainty_score":0.9998291},"labels":[],"label_agreement":null},{"id":"W7133020232","doi":"","title":"Characterizing Topological and Topographical Resilience in Structural Networks Supporting Language in Childhood","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"University of Toronto; Strong","keywords":"Tractography; Resilience (materials science); Representation (politics); Deconvolution; Psychological resilience; Topology (electrical circuits); Language model","score_opus":0.02189960200563452,"score_gpt":0.4001682106898068,"score_spread":0.3782686086841723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133020232","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99482393,0.0014188644,0.00018897121,0.0017245762,0.00013632688,0.0010324089,0.000006842557,0.000103308375,0.0005647536],"genre_scores_gemma":[0.9962887,0.0010517602,0.0011293058,0.00044620427,0.00012705596,0.00020281048,0.00039016365,0.000046063793,0.0003178999],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9973046,0.00014049423,0.00069995504,0.000915503,0.00027030776,0.000669095],"domain_scores_gemma":[0.99884015,0.00020031819,0.0003724021,0.0004110592,0.00002352945,0.00015254045],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00037261387,0.00038695146,0.0006388956,0.0003752563,0.00021559534,0.000039862476,0.00024979853,0.00027117023,0.0004945094],"category_scores_gemma":[0.00026366426,0.00039731336,0.00009089803,0.0009145567,0.0001532868,0.00009963443,0.00019182108,0.0022675772,8.072656e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010876295,0.00082897453,0.7327842,0.000652407,0.000047748785,0.0026395775,0.11116082,0.00063499674,0.04760826,0.010997796,0.000040680356,0.09151689],"study_design_scores_gemma":[0.0008059099,0.00025684747,0.9518664,0.00040979494,0.000040081624,0.00013185422,0.037336532,0.00751277,0.00051273877,0.00050095085,0.0001581671,0.00046799248],"about_ca_topic_score_codex":0.0004009801,"about_ca_topic_score_gemma":0.00017958073,"teacher_disagreement_score":0.21908215,"about_ca_system_score_codex":0.00010659649,"about_ca_system_score_gemma":0.00007239922,"threshold_uncertainty_score":0.9998479},"labels":[],"label_agreement":null},{"id":"W7161938113","doi":"10.82308/46062","title":"Combined application of voxel-based morphometry and magnetization transfer ratio for group analysis of magnetic resonance images","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Magnetization transfer; White matter; Voxel; Population; Magnetic resonance imaging; Voxel-based morphometry; Context (archaeology)","score_opus":0.015147482049937638,"score_gpt":0.3078146013710807,"score_spread":0.29266711932114303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7161938113","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09975307,0.0014481624,0.89484864,0.00017130242,0.000017703951,0.002476521,0.00037524413,0.00011165365,0.0007977062],"genre_scores_gemma":[0.9269314,0.00026529434,0.055195034,0.00008387474,0.000020147907,0.00081052165,0.0142142,0.000057962385,0.0024215744],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9986728,0.000015337386,0.00058898947,0.00040368643,0.00020062913,0.00011857801],"domain_scores_gemma":[0.9988599,0.00012398727,0.00020237415,0.0004036762,0.00037008215,0.000039980114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000925342,0.00020685075,0.0006194553,0.0006542075,0.000041875363,0.000007295025,0.000085568965,0.00015537102,0.00002986514],"category_scores_gemma":[0.000029816705,0.00020403443,0.00019019292,0.0011524096,0.00007787886,0.000039803992,0.0000044023186,0.00009542469,1.8871569e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018390054,0.0014249729,0.027065769,0.0039060244,0.00025326628,0.000001077477,0.00009247496,0.00037599014,0.83148736,0.020465838,0.0013785993,0.1117096],"study_design_scores_gemma":[0.0030836044,0.0013443563,0.60115516,0.00021897035,0.007159066,9.934919e-7,0.00007697231,0.080373056,0.30215168,0.0013499516,0.0026014533,0.00048475302],"about_ca_topic_score_codex":0.00009863986,"about_ca_topic_score_gemma":0.00006521208,"teacher_disagreement_score":0.8396536,"about_ca_system_score_codex":0.000020396255,"about_ca_system_score_gemma":0.00003788494,"threshold_uncertainty_score":0.83202827},"labels":[],"label_agreement":null},{"id":"W804767602","doi":"10.1016/j.nicl.2015.06.007","title":"Altered whole-brain white matter networks in preclinical Alzheimer's disease","year":2015,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":102,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; Johnson and Johnson Pharmaceutical Research and Development; Janssen Research and Development; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, San Diego; National Institutes of Health; Servier; Innogenetics; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; Synarc; University of Southern California; Novartis Pharmaceuticals Corporation; IXICO; Takeda Pharmaceutical Company; Medpace; Genentech; Biogen Idec; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Drug Discovery Foundation; Merck; Alzheimer's Association; Foundation for the National Institutes of Health; GE Healthcare; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics","keywords":"Neurodegeneration; White matter; Diffusion MRI; Fractional anisotropy; Neuroscience; Neuroimaging; Connectome; Medicine; Alzheimer's disease; Alzheimer's Disease Neuroimaging Initiative; Psychology; Disease; Pathology; Functional connectivity; Magnetic resonance imaging","score_opus":0.2835831370933138,"score_gpt":0.47840786024234194,"score_spread":0.19482472314902816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W804767602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49235764,0.001186962,0.046015408,0.44245544,0.00203749,0.0046571395,0.00010440233,0.0017003663,0.009485177],"genre_scores_gemma":[0.9434824,0.000055408753,0.010633788,0.042628914,0.0012246976,0.00016186207,0.00010517232,0.000119184646,0.0015885734],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9968661,0.00030826678,0.0011228976,0.0009531147,0.00029098187,0.0004586571],"domain_scores_gemma":[0.9968873,0.00062393886,0.00018393311,0.0012476557,0.00011043942,0.000946726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008511691,0.00026396042,0.00056586426,0.000096681295,0.000042666827,0.00003972382,0.0002947105,0.00015700868,0.000092352835],"category_scores_gemma":[0.0012155995,0.00024442788,0.00026532722,0.0003091933,0.00033708516,0.00015577947,0.0002504153,0.0012078559,0.00037420014],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005920968,0.0007721877,0.78729,0.000008545027,0.000011930989,0.00032523187,0.000012788331,0.00012448544,0.000018091849,0.000060420967,0.20652075,0.0042634713],"study_design_scores_gemma":[0.002649836,0.00036701866,0.86713636,0.00007320449,0.00011986073,0.000057442325,0.0000065279655,0.011799891,0.000006114761,0.0011153657,0.11641997,0.00024840163],"about_ca_topic_score_codex":0.0000035096402,"about_ca_topic_score_gemma":0.0000021698686,"teacher_disagreement_score":0.45112476,"about_ca_system_score_codex":0.000025633646,"about_ca_system_score_gemma":0.00014603423,"threshold_uncertainty_score":0.996748},"labels":[],"label_agreement":null},{"id":"W838115849","doi":"10.1016/j.neuroimage.2015.06.038","title":"In vivo mapping of human spinal cord microstructure at 300 mT/m","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":75,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Mental Health; National Institutes of Health; Multiple Sclerosis Society of Canada; National Multiple Sclerosis Society","keywords":"Spinal cord; White matter; Axon; Anatomy; Diffusion MRI; Neuroscience; Biology; Magnetic resonance imaging; Medicine; Radiology","score_opus":0.11007648811325242,"score_gpt":0.38734587001366616,"score_spread":0.2772693819004137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W838115849","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9919109,0.000062080006,0.00067212345,0.0015062065,0.000058618098,0.00035885148,0.000019483381,0.000110991525,0.00530078],"genre_scores_gemma":[0.9901021,0.00001217951,0.007153018,0.001167416,0.000071614944,0.000016389748,0.0000073828037,0.000030600986,0.0014393143],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99912137,0.000018523728,0.0002468843,0.0002774868,0.00015223057,0.00018348618],"domain_scores_gemma":[0.9993101,0.000011772625,0.00009766633,0.00041372448,0.000064770684,0.00010198692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006525531,0.00012172614,0.00022319643,0.00011625276,0.000038965387,0.0000061032906,0.00012097917,0.000042728607,0.000059921866],"category_scores_gemma":[0.000045932662,0.00011838423,0.000051372095,0.0002401755,0.000107749554,0.00006890356,0.00011283261,0.0002189659,0.000009787612],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012411077,0.000054084998,0.0071930415,0.000042834214,0.0000017169255,0.00010246476,0.000055154145,0.0000010379749,0.98127145,0.0003274963,0.0104302205,0.00039637994],"study_design_scores_gemma":[0.0033707353,0.0020439536,0.13850705,0.00025066794,0.000045615037,0.00097113353,0.00010829291,0.00017494199,0.5893241,0.00659793,0.25817204,0.00043353363],"about_ca_topic_score_codex":0.000024738565,"about_ca_topic_score_gemma":0.000004067648,"teacher_disagreement_score":0.39194736,"about_ca_system_score_codex":0.000056724883,"about_ca_system_score_gemma":0.00002700085,"threshold_uncertainty_score":0.48275688},"labels":[],"label_agreement":null},{"id":"W90999908","doi":"10.1007/978-3-642-31298-4_34","title":"Function-Valued Mappings, Total Variation and Compressed Sensing for diffusion MRI","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Diffusion MRI; Hilbert space; Minification; Compressed sensing; Formalism (music); Algorithm; Unit sphere; Diffusion; Magnetic resonance imaging; Artificial intelligence; Mathematics; Pure mathematics; Physics","score_opus":0.03782224024557197,"score_gpt":0.29631795854297743,"score_spread":0.2584957182974055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W90999908","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00043608173,0.00020973281,0.9970233,0.00084122166,0.00031742538,0.0007975996,0.0000069216117,0.00013158261,0.00023613984],"genre_scores_gemma":[0.18500124,0.00005790726,0.8125087,0.0012995879,0.00070432853,0.000013880847,0.00003685194,0.00004365998,0.00033382836],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987507,0.000005875936,0.00021697325,0.00054957287,0.00023679085,0.00024007802],"domain_scores_gemma":[0.999087,0.00017570343,0.00014118891,0.0003667872,0.00013838863,0.00009095017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018727656,0.0002118195,0.00026726074,0.0002325512,0.0002171187,0.000049820024,0.00010258895,0.00013549952,0.0000062541794],"category_scores_gemma":[0.000036611316,0.00019150465,0.000049242666,0.000116937976,0.00031671734,0.00010641546,0.00015742869,0.00029604195,0.0000017301801],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012988599,0.00007354739,0.00017980779,0.00029128886,0.000024075716,0.000009357499,0.001057412,0.002513706,0.050410047,0.015848,0.0001293674,0.9293335],"study_design_scores_gemma":[0.0009970277,0.00032951368,0.0038437417,0.00078608823,0.00012348236,0.00024085036,4.6233407e-7,0.83023274,0.0027756118,0.14993533,0.010160938,0.000574227],"about_ca_topic_score_codex":0.000006995812,"about_ca_topic_score_gemma":0.000001252451,"teacher_disagreement_score":0.9287593,"about_ca_system_score_codex":0.00008402865,"about_ca_system_score_gemma":0.00006180833,"threshold_uncertainty_score":0.7809333},"labels":[],"label_agreement":null},{"id":"W910086267","doi":"10.1016/j.bandl.2015.06.006","title":"Fiber tracking of the frontal aslant tract and subcomponents of the arcuate fasciculus in 5–8-year-olds: Relation to speech and language function","year":2015,"lang":"en","type":"article","venue":"Brain and Language","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval; Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Arcuate fasciculus; Psychology; Fractional anisotropy; Fasciculus; Fiber tract; Diffusion MRI; Neuroscience; Audiology; Cognitive psychology; Magnetic resonance imaging; Medicine","score_opus":0.036315339610534035,"score_gpt":0.31350800807523166,"score_spread":0.27719266846469764,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W910086267","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.997549,0.00021979211,0.0001232492,0.0010836865,0.00001479255,0.00031002358,0.000009931739,0.000013338371,0.0006762097],"genre_scores_gemma":[0.9987254,0.0000072662306,0.0006095728,0.00022072239,0.000017516093,0.0000051407897,0.0000041933463,0.000006910733,0.00040323584],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99960417,0.000030037922,0.00011048742,0.000108063694,0.00008411189,0.00006316244],"domain_scores_gemma":[0.9997205,0.000035994733,0.000052418545,0.00014329085,0.000012822797,0.00003497821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001467036,0.000053931573,0.00009710991,0.000032705524,0.000022070886,0.000004917923,0.00003322097,0.000027618946,0.0000067693823],"category_scores_gemma":[0.00007513645,0.000032656884,0.00001765266,0.0000907019,0.000043659747,0.000035653673,0.000041923067,0.00009277819,4.2496487e-7],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053672993,0.00029535225,0.29965898,0.00019787073,0.000025579599,0.00003155977,0.025155505,0.000015932517,0.5659921,0.0010772535,0.0012810886,0.105731994],"study_design_scores_gemma":[0.00084705395,0.00010181428,0.9833988,0.00013489391,0.000024038973,0.00006549485,0.0017612791,0.00019409783,0.012346221,0.000251046,0.000814602,0.000060648727],"about_ca_topic_score_codex":0.00020504477,"about_ca_topic_score_gemma":0.000052456548,"teacher_disagreement_score":0.68373984,"about_ca_system_score_codex":0.000010447603,"about_ca_system_score_gemma":0.000008235203,"threshold_uncertainty_score":0.1331709},"labels":[],"label_agreement":null}]}